2014-08-07T15:28:19Z

AndrewBangham: Created page with " function quickCompareSieves(X, scale, types ) %quickCompareSieves(X, scale ) % <span sty..."

function quickCompareSieves(X, scale, types )
%quickCompareSieves(X, scale )
% 
%X, data
%scale, scale at which different sieves will be compared
%types, 'o' etc.

if nargin<1
X=[1 1 1 1 10 1 1 1 1 2 2 1 1 1 1 1 5 5 5 5 5 1 1 1 5 5 5 5 1 1 1 1 1];
end
if nargin<2
scale=5;
end
if nargin<3
types={'o','c','m','n','v'};
end
X=X+randn(size(X))*0.1*max(X(:));
subplot(2,1,1);cla
plot(X)
title('X')
colours='rmbck';
for i=1:length(types)
type=types{i};
subplot(2,1,2)
y=siv1_alt(X,scale,type);
if i==1
cla
plot(X,'ok')
hold on
end
plot(y,'-','color',colours(i));
end
title(sprintf('scale=%d ''o''''c''(red,magenta)''m''''n''(blue, cyan),''v'' (black)',scale));

end

Types of 1D sieve

2014-08-07T15:28:02Z

Mean and median filters bad

2014-08-06T16:06:52Z

AndrewBangham:

MSER and Sieve Details

2014-08-06T15:59:54Z

AndrewBangham: /* Gaussian filters preserve scale space */

[[Software#MSERs.2C_extrema.2C_connected-set_filters_and_sieves|Back to Software]]
==What is the connection between MSER's and sieves'?==
The papers by George Matas((Matas, et. al. 2002<ref>Matas, J., M. Urban, O. Chum and T. Pajdla (2002). ''Robust Wide baseline Stereo from Maximally Stable Extremal Regions.'' BMVC, Cardiff</ref>))((Matas et al., 2004)<ref>Matas, Jiri, et al. ''Robust wide-baseline stereo from maximally stable extremal regions''. Image and vision computing 22.10 (2004): 761-767.</ref>))
(Mishkin et al., 2013)<ref>Dmytro Mishkin, Michal Perdoch,Jiri Matas (2013) ''Two-view Matching with View Synthesis Revisited'' arXiv preprint arXiv:1306.3855 </ref> put together an effective way of finding distinguished regions (DR’s) namely maximally stable extremal regions ('''''MSER’s''''' ) with a powerful way of ''describing'' the regions at multiple scales and ''robustly matching'' such measurements with others in a second image. Since then many authors have confirmed the algorithms as a powerful tool for finding objects in images (review Mikolajczyk et al 2006: <ref>Krystian Mikolajczyk, Tinne Tuytelaars, Cordelia Schmid, Andrew Zisserman, Jiri Matas, Frederik Schaffalitzky, Timor Kadir, L Van Gool, (2006) ''A Comparison of Affine Region Detectors.''International Journal of Computer Vision. DOI: 10.1007/s11263-005-3848-x</ref>, Kimmel 2011 <ref>Kimmel, R., Zhang, C., Bronstein, A.M., Bronstein, M. (2011) ''Are MSER features really interesting?'' IEEE Trans. Pattern Analysis and Machine Intelligence 33:2316–2320</ref>
 


The algorithm '''underlying''' that for finding Maximally stable extremal regions (MSER's) '''is an 'o' sieve'''. Such algorithms relate closely to mathematical morphology (dilations-erosion (Jackway et al 1996<ref>P. T. Jackway and M. Deriche. ''Scale-space properties of multiscale morphological dilation-erosion.'' IEEE Trans. Pattern Analysis and Machine Intelligence
, 18(1):38–51</ref>) openings, closings and in particular watersheds (Vincent et al 1991 <ref>Vincent, Luc, and Pierre Soille. "Watersheds in digital spaces: an efficient algorithm based on immersion simulations." IEEE transactions on pattern analysis and machine intelligence 13.6 (1991): 583-598.</ref>) and reconstruction filters (Salembier, P. et. al. 1995<ref>Salembier P, Serra J (1995). ''Flat zones filtering, connected operators, and filters by reconstruction.'' IEEE Trans Image Process 4:1153</ref>). In mathematical morphology the 'filtering' element of the MSER algorithm might be called a 'connected-set opening' ('o' sieve) . It is one of a family of closely related algorithms which for which I coined the term '''sieves'''. Why?
 
===='''Why call the family of feature finding algorithms ''sieves'' and not ''filters''?''' ====
I thought it may be helpful to distinguish between '''two very different signal simplifying algorithms''' both of which preserve scale-space: '''linear 'filters'''' and '''non-linear 'sieves''''. In a linear-filter-bank such as a bank of Gaussian filters the input signal is separated, prism like, into frequency related scale bands (large and small blobs). Like all linear filters they spread outliers such as impulses and sharp edges over many scales. Sieves do not - hence the distinction. Now Gaussian filters have a very attractive property, that it turns out, is shared with sieves ... 

===='''Gaussian filters preserve scale space''' ====
In the 1980's-1990's there were many publications on the properties of Gaussian (diffusion) filters. Key is that they ''preserve'' [http://en.wikipedia.org/wiki/Scale_space scale-space] (Babaud et. al. 1986 "The uniqueness of the Gaussian kernel ...")<ref>Babaud, Jean; Witkin, Andrew P.; Baudin, Michel; Duda, Richard O., "Uniqueness of the Gaussian Kernel for Scale-Space Filtering," Pattern Analysis and Machine Intelligence, IEEE Transactions on , vol.PAMI-8, no.1, pp.26,33, Jan. 1986 doi: 10.1109/TPAMI.1986.4767749</ref> To understand what is meant: imagine a photo projected onto a wall using a data projector. Leave it on for an hour. Then turn of the projector. Regions that were illuminated (white) will be warmer than those that were black. Now turn the projector off and turn on an infrared image viewer. Once again the image will be visible (warm and cold regions showing up). However, as we wait heat will diffuse from the warm to cooler regions - the image will become blurred. Heat will never flow to form new extrema. If the thermal conductivity of the surface is uniform and isotropic then there is one simple filter that will produce the same result. A Gaussian blur filter. 
Here, we have three panels illustrating one dimensional signals represented in scale space. I have used 'heat maps' to represent the signal intensity at each scale.
 
=====Both Gaussian filters and Sieves preserve scale-space=====
{| border="0" cellpadding="5" cellspacing="5" 3D extrema thumb.gif
|- valign="top"
|width="20%"| 
|'''Consider a signal''', <math>X</math> 
X=getData('PULSES3WIDE')
>blue X=0 5 5 0 0 1 1 4 3 3 2 2 1 2 2 2 1 0 0 0 1 1 0 3 2 0 0 0 6 0 0
|}
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="50%"| The data has minima and maxima of different scales (lengths).
|[[Image:IllustrateSIV_1_02.png|400px]]
|}

{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="60%"| [[Image:Siv4 test 5.png|400px|'m' non-linear filter (sieve) compared to Gaussian filter]]
|[[Image:UpsideDownWitkin.jpg|300px|AAMToolbox]]
|}
'''Left Panel.''' Here, a '''A low-pass''' siv4.m gradually removes extrema (from the signal shown above) as scale increases from scale 1 to scale 64. The resulting traces are shown as a 'heat map' where the signal goes from left to right, bright colours like red are large amplitude, small scale extrema. At each increasing scale (down the map) extrema have been removed. The 'm'-sieve preserves scale-space so no new extrema (light regions) are formed as we move to increasing scales. Moreover, the features do not wander about in scale-space. We could say that in one dimension we measure pulse length using a sieve just as we might use a ruler or measuring tape in the physical world. 
Superficially it is clear that, by 'knocking off' outliers at increasingly large scales, sieves cannot introduce new extrema but to clarify the issue we formally proved that they do not introduce new extrema, i.e. preserve '''''scale-space''''' (Bangham et al 1996<ref>Bangham, JA, Harvey, RW, Ling, PD and Aldridge, RV (1996) ''Morphological scale-space preserving transforms in many dimensions.'' The Journal of Electronic Imaging (JEI), 5 (3). pp. 283-299.</ref>Bangham et al 1996b<ref>Bangham, JA, Chardaire, P, Pye, CJ and Ling, PD (1996) ''Multiscale nonlinear decomposition: The sieve decomposition theorem.'' IEEE Transactions on Pattern Analysis and Machine Intelligence, 18 (5). pp. 529-539. ISSN 0162-8828</ref>, c.f. the properties of multiscale dilation and erosion, Jackway et al 1996<ref>Jackway, P.T. and Deriche, M. (1996) ''Scale-space properties of the multiscale morphological dilation-erosion'' IEEE Transactions on Pattern Analysis and Machine Intelligence, vol.18, no.1, pp.38,51</ref>). Preserving scale-space is one of the '''important reasons why MSER's''' are so useful for finding interest points worthy of further characterisation as feature points. 
'''Middle Panel'''. A ''Gaussian'' filter bank also preserves scale-space as shown by Witkin 1986. No new features (local extrema) are formed. However, the features wander about in scale-space. 
(Babaud et. al. 1986 "The uniqueness of the Gaussian kernel for Scale-Space Filtering")<ref>Babaud, Jean; Witkin, Andrew P.; Baudin, Michel; Duda, Richard O., "Uniqueness of the Gaussian Kernel for Scale-Space Filtering," Pattern Analysis and Machine Intelligence, IEEE Transactions on , vol.PAMI-8, no.1, pp.26,33, Jan. 1986 doi: 10.1109/TPAMI.1986.4767749</ref>
 
'''Right Panel,''' Babaud's original Figure showing heat-map 'isotherms'. (Actually, to be consistent with the other Panels I have flipped the image vertically.) The features wander about in scale-space and sharp edged features do not sharply disappear - they are smudged over scale-space.
 

*Small, hot areas (outliers) are smoothed out as are sharp edges.
*Sieves are the opposite, impulses and regions with sharp edges do not spread over many scales (c.f. mechanical sieves in which particles (granules) either go through holes or they do not [http://en.wikipedia.org/wiki/Mesh_%28scale%29 Particle filters and sieves].) They do however, spread smooth waveforms over many scales. 
One could consider '''Gaussian filter banks and filter banks based on sieves as complementary to each other'''.

===='''Implementation'''====
One dimensional sieves are easily implemented by run-length coding the signal, each extremum has a list of just two neighbours. Indeed, in collaboration with [http://www.cambridgeconsultants.com/ CCL] we implemented the algorithm on a PC board to characterise the output, in real time, from line-scan cameras (often used industrially when, in the early 1990's, 2D digital camera's were not easily available). Implementations for images in higher dimensions are similar but keeping track of lists of neighbours is a little more complex, but see Nister and Stewenius, <ref>D. Nister and H. Stewenius ''Linear time maximally stable extremal regions'' ECCV 2008 part II LNCS 5303 pp 183-196. </ref> for a cool implementation of the MSER algorithm.
[[Image:Scan 10.jpeg|350px|right|first hardware implementation of sieve]] 
'''Dug up from the past.''' First hardware implementation of a sieve. Just a few stages. Later implementations used an application-specific integrated circuit (ASIC). We wanted a full decomposition at speed for the line-scan cameras. 

===='''Applications''' ====
In addition to their role finding in objects in 2D images we have used sieves to analyse 1, 2 and 3D signals. We started in 1D (digital images were not available at the time). For example analysing protein hydrophobicity plots(Bangham, 1988<ref>Bangham, J.A. (1988) ''Data-sieving hydrophobicity plots. Anal. Biochem''. 174, 142–145</ref>) for which it was found by Fasman (1990) <ref>Fasman and Gilbert "The prediction of transmembrane protein sequences and their conformation: an evaluation" in Trends in Biochemistry 15 pp 89:91</ref> to "correctly predict the hydrophobic transmembrane regions ..." [[Details on hydrophobicity plots | (see more details)]]. , de-noising single channel current data (Bangham et al, 1984<ref>Bangham, J.A., and T.J.C. Jacob (1984). ''Channel Recognition Using an Online Hardware Filter'' in The Journal of Physiology, (London: Physiological Society), pp. 3–5</ref>). Much later we used them for texture analysis (Southam et al, 2009<ref>Southam, P., and Harvey, R. (2009). ''Texture classification via morphological scale-space: Tex-Mex features''. J. Electron. Imaging 18, 043007–043007</ref>) and lipreading (Matthews et al., 2002<ref>Matthews, I., Cootes, T.F., Bangham, J.A., Cox, S., and Harvey, R. (2002). ''Extraction of visual features for lipreading''. Pattern Anal. Mach. Intell. Ieee Trans. 24, 198–213</ref>). In 2D for segmenting images through extremal trees (c.f. MSER's) (Bangham et al., 1998<ref>Bangham, J.A., Hidalgo, J.R., Harvey, R., and Cawley, G. (1998). ''The segmentation of images via scale-space trees''. In Proceedings of British Machine Vision Conference, pp. 33–43</ref>), maximally stable contours(Lan et al., 2010<ref> Lan, Y., Harvey, R., and Perez Torres, J.R. (2010). ''Finding stable salient contours.'' Image Vis. Comput. 28, 1244–1254</ref>), creating painterly pictures from photos (Bangham et al., 2003<ref>Bangham, J.A., Gibson, S.E., and Harvey, R. (2003). ''The art of scale-space''. In Proc. British Machine Vision Conference, pp. 569–578</ref>)(Fo2Pix sold about 65,000 licences for our software package: ArtMaster); and in 3D for segmenting volumes in CAT scans.

====Could non-linear filter banks (sieves) have evolved in biological systems?====
Biological systems are too complex too huge to comprehend without some initial insights. In vision the particular theoretical 'torches' that light the experimental findings are the Fourier transform, Gaussian or Gabor filter banks. ''We look where those lights are shining and what we find seems to fit that intuition'' e.g. [http://en.wikipedia.org/wiki/Scale_space#Why_a_Gaussian_filter.3F Gaussian]/[http://en.wikipedia.org/wiki/Gabor_filter Gabor]. ''Or perhaps has to fit for want of other ''torches''''. 

So care is needed. Science should be creative, we should create a number of torches pointing in different directions (based on different theoretical frameworks where possible) then use experimental evidence to reject those that do not fit leaving us with the best hypothesis, theoretical framework, so far.

We now know that sieves (MSER's) not only exist but offer significant practical advantages over other methods in computer vision. They are an alternative 'torch' that might need rejecting. Perhaps we should re-evaluate the biological evidence. Could the brain be understood in terms of sieves? Were this to be the case then it could change what we look for in brain structures. Hardware implementations of sieves are all about connectivity and relative thresholds as are brains, so perhaps it is possible.
*our hardware implementation of the 1D filter bank was very different to a linear filter bank.
*Likewise the linear time implementation of the 2D MSER algorithm (Nister and Stewenius, <ref>D. Nister and H. Stewenius ''Linear time maximally stable extremal regions'' ECCV 2008 part II LNCS 5303 pp 183-196. </ref>) in which dynamic connectivity is everything. 
Exploring this problem would be '''just the 'wild' opportunity that I have enjoyed exploring in my research life'''. It would be a wild ride whatever the outcome - unfortunately cancer now (June 2014) leaves me out of the game..

====Summary of basic properties of sieves, linear and non-linear filters?====
 
{| style="width: 80%; height: 60px" border="1"
|- valign="top"
!
! Sieve 1D
! Sieve 2D
! Sieve 3D
! Gaussian 1D
! Gaussian 2D
! Median 1D
! Median 2D
|-
|- valign="top"
| Preserve Scale space
! Yes || Yes || Yes
|| Yes || Yes || No || No
|-
|- valign="top"
| Separate signals by
! Length|| Area || Volume
||Pulse Frequency|| Blob Frequency 2D || Roughly Pulse length || Roughly Blob Area
|}

==References==
<references />

==Limitations?==

Mean and median filters bad

2014-08-06T15:30:10Z

AndrewBangham: Created page with "{| border="0" cellpadding="5" cellspacing="3" |- valign="top" |<wikiflv width="800" height="900" logo="false" loop="true" background="white">Siv1-meanmedian_2.flv|Siv1-meanme..."

Comparison of Matlab MSER's and 'o' sieve

2014-08-06T15:28:12Z

AndrewBangham: Created page with "I just have to mend some code - I was using earlier this year but somehow I must have missed saving the latest versions on the svn."

I just have to mend some code - I was using earlier this year but somehow I must have missed saving the latest versions on the svn.

Tutorial on different ways of specifying the growth of shapes

2014-08-06T15:23:37Z

AndrewBangham: /* Illustrating independent ways to form shapes and the use of submodels. */

[[GFtbox Tutorial pages#Output and Results|Back to GFtbox Tutorial pages]] 
We illustrate the practical advantage of having submodels within a project and an important consequence of understanding biological growth within the GPT-framework. 
Conclusion: using a '''combination''' of polarity patterns to set local axes for anisotropic growth and patterns of differential specified growth to regulate the growth of shape would be powerful.
==Illustrating independent ways to form shapes and the use of submodels. ==
The full interaction function is shown at the bottom. The line of code that selects the submodel and the start of each submodel is shown in red. 
{| border="0" cellpadding="15" cellspacing="3"
|- valign="top"
|width="400pt"|'''Uniform specified polariser''' (no polariser gradient). Creating a shape using a specified pattern of isotropic growth. 
'''Result''': simple patterns tend to produce blobby shapes. 
'''Conclusion''': Whilst it may be possible to produce complex shapes such as the outgrowth shown in the GFtbox icon, we don't know how.
|width="180pt"|[[image:GPT TwoWayHeart 20110531-0001 Last.png‎|thumb|180px|Pattern of isotropic specified growth (no polariser)]]
|width="180pt"|[[image:GPT_TwoWayHeart_20110531-0001.png‎|thumb|180px|Pattern of isotropic specified growth after growing to 3 times the original area.]]
|- valign="top"
|width="400pt"|'''Uniform specified growth'''. Creating a shape using a specified pattern of diffusable polariser. 
'''Result''': simple patterns can readily produce sharp shapes. 
'''Conclusion''': It is not so easy to produce blobby shapes using patterns of polariser alone. But it is easy to produce outgrowths.
|width="180pt"|[[image:GPT_TwoWayHeart_20110531-0002_Last.png‎|thumb|180px|Pattern of specified polariser levels (green-cyan). Polariser can diffuse and the gradient is arrowed. Uniform specified growth (red).]]
|width="180pt"|[[image:GPT_TwoWayHeart_20110531-0002.png‎|thumb|180px|Patterns and shape after growing to 3 times the original area.]]
|- valign="top"
|}
% Section 1
function m = gpt_twowayheart_20110531( m )
%m = gpt_twowayheart_20110531( m )
% Morphogen interaction function.
% Written at 2011-05-31 19:51:32.
% GFtbox revision 3548, 2011-05-31 14:37:10.747930.

% The user may edit any part of this function between delimiters
% of the form "USER CODE..." and "END OF USER CODE...". The
% delimiters themselves must not be moved, edited, deleted, or added.

if isempty(m), return; end

fprintf( 1, '%s found in %s\n', mfilename(), which(mfilename()) );

try
m = local_setproperties( m );
catch
end

realtime = m.globalDynamicProps.currenttime;

% Section 2
%%% USER CODE: INITIALISATION

% In this section you may modify the mesh in any way whatsoever.
if (Steps(m)==0) && m.globalDynamicProps.doinit % First iteration
% Set up names for variant models. Useful for running multiple models on a cluster.
m.userdata.ranges.modelname.range = { 'PolariserBased', 'DifferentialGrowthBased' }; % CLUSTER
 m.userdata.ranges.modelname.index = 1; % CLUSTER
end
modelname = m.userdata.ranges.modelname.range{m.userdata.ranges.modelname.index}; % CLUSTER
disp(sprintf('\nRunning %s model %s\n',mfilename, modelname));

% Set priorities for simultaneous plotting of multiple morphogens, if desired.
m = leaf_mgen_plotpriority( m, {'ID_PLUSORG', 'ID_MINUSORG'}, [1,2], [0.4,0.4] );

% Set colour of polariser gradient arrows.
m = leaf_plotoptions(m,'highgradcolor',[0,0,0],'lowgradcolor',[1,0,0]);
m = leaf_plotoptions(m,'decorscale',1.5);

% setup a multiplot of the following morphogens
m = leaf_plotoptions( m, 'morphogen', {'V_KAREAL','ID_PLUSORG','ID_MINUSORG'});
%%% END OF USER CODE: INITIALISATION

% Section 3
%%% SECTION 1: ACCESSING MORPHOGENS AND TIME.
%%% AUTOMATICALLY GENERATED CODE: DO NOT EDIT.

if isempty(m), return; end

setGlobals();
global gNEW_KA_PAR gNEW_KA_PER gNEW_KB_PAR gNEW_KB_PER
global gNEW_K_NOR gNEW_POLARISER gNEW_STRAINRET gNEW_ARREST
dt = m.globalProps.timestep;
polariser_i = gNEW_POLARISER;
P = m.morphogens(:,polariser_i);
[kapar_i,kapar_p,kapar_a,kapar_l] = getMgenLevels( m, 'KAPAR' );
[kaper_i,kaper_p,kaper_a,kaper_l] = getMgenLevels( m, 'KAPER' );
[kbpar_i,kbpar_p,kbpar_a,kbpar_l] = getMgenLevels( m, 'KBPAR' );
[kbper_i,kbper_p,kbper_a,kbper_l] = getMgenLevels( m, 'KBPER' );
[knor_i,knor_p,knor_a,knor_l] = getMgenLevels( m, 'KNOR' );
[strainret_i,strainret_p,strainret_a,strainret_l] = getMgenLevels( m, 'STRAINRET' );
[arrest_i,arrest_p,arrest_a,arrest_l] = getMgenLevels( m, 'ARREST' );
[id_plusorg_i,id_plusorg_p,id_plusorg_a,id_plusorg_l] = getMgenLevels( m, 'ID_PLUSORG' );
[id_minusorg_i,id_minusorg_p,id_minusorg_a,id_minusorg_l] = getMgenLevels( m, 'ID_MINUSORG' );
[v_kareal_i,v_kareal_p,v_kareal_a,v_kareal_l] = getMgenLevels( m, 'V_KAREAL' );
[id_tip_i,id_tip_p,id_tip_a,id_tip_l] = getMgenLevels( m, 'ID_TIP' );
[id_top_i,id_top_p,id_top_a,id_top_l] = getMgenLevels( m, 'ID_TOP' );
[s_growth_i,s_growth_p,s_growth_a,s_growth_l] = getMgenLevels( m, 'S_GROWTH' );
[id_mid_i,id_mid_p,id_mid_a,id_mid_l] = getMgenLevels( m, 'ID_MID' );

% Mesh type: circle
% centre: 0
% circumpts: 24
% coneangle: 0
% dealign: 0
% height: 0
% innerpts: 0
% randomness: 0.1
% rings: 4
% version: 1
% xwidth: 2
% ywidth: 2

% Morphogen Diffusion Decay Dilution Mutant
% -------------------------------------------------
% KAPAR ---- ---- ---- ----
% KAPER ---- ---- ---- ----
% KBPAR ---- ---- ---- ----
% KBPER ---- ---- ---- ----
% KNOR ---- ---- ---- ----
% POLARISER 0.1 ---- ---- ----
% STRAINRET ---- ---- ---- ----
% ARREST ---- ---- ---- ----
% ID_PLUSORG ---- ---- ---- ----
% ID_MINUSORG ---- ---- ---- ----
% V_KAREAL ---- ---- ---- ----
% ID_TIP ---- ---- ---- ----
% ID_TOP ---- ---- ---- ----
% S_GROWTH 0.01 ---- ---- ----
% ID_MID ---- ---- ---- ----

%%% USER CODE: MORPHOGEN INTERACTIONS

% In this section you may modify the mesh in any way that does not
% Section 4
% alter the set of nodes.

% Use the same pattern for both submodels
RangeTip=(m.nodes(:,1)<-0.8)&...
(abs(m.nodes(:,2))<0.2);
RangeMid=(m.nodes(:,1)<=0.5)&...
(m.nodes(:,1)>-0.5)&...
(abs(m.nodes(:,2))<0.3);
RangeTops=(m.nodes(:,1)<=max(m.nodes(:,1))&...
(m.nodes(:,1)>0.5)&...
(abs(m.nodes(:,2))>0.3));
if (Steps(m)==0) && m.globalDynamicProps.doinit % Initialisation code.
switch modelname
 case 'PolariserBased' % 
% One way to set up a morphogen gradient is by ...
% Setting up a gradient by clamping the ends (execute only once)
P(RangeTip)=0;
P(RangeMid)=0.5;
P(RangeTops)=1;
id_plusorg_p=P;
id_minusorg_p(RangeTip)=1;
m.morphogenclamp( RangeTops|RangeTip|RangeMid, polariser_i ) = 1;
m = leaf_mgen_conductivity( m, 'POLARISER', 0.1 ); %specifies the diffusion rate of polariser
m = leaf_mgen_absorption( m, 'POLARISER', 0.0 ); % specifies degradation rate of polariser
 case 'DifferentialGrowthBased' % 
P(:)=0;
% One way to set up a morphogen gradient is by ...
% Setting up a gradient by clamping the ends (execute only once)
s_growth_p(RangeTip)=1;
s_growth_p(RangeMid)=0.05;
s_growth_p(RangeTops)=0.8;
m.morphogenclamp( RangeTops|RangeTip|RangeMid, s_growth_i ) = 1;
m = leaf_mgen_conductivity( m, 's_growth', 0.001 ); %specifies the diffusion rate of polariser
m = leaf_mgen_absorption( m, 's_growth', 0.0 ); % specifies degradation rate of polariser
end
end
BasicGrowth=0.01;
switch modelname
 case 'PolariserBased' %
% Every equation to be formatted should end with an at-at Eqn N comment.
kapar_p(:) = BasicGrowth; % when isotropic this will be 0.005
kaper_p(:) = 0.0; % when isotropic this will be 0.005
kbpar_p(:) = BasicGrowth; % when isotropic this will be 0.005
kbper_p(:) = 0.0; % when isotropic this will be 0.005
knor_p(:) = 0; % thickness
 case 'DifferentialGrowthBased' % 
% Every equation to be formatted should end with an at-at Eqn N comment.
kapar_p(:) = BasicGrowth*s_growth_p; %0.01; % when isotropic this will be 0.005
kaper_p(:) = BasicGrowth*s_growth_p; %0.0; % when isotropic this will be 0.005
kbpar_p(:) = BasicGrowth*s_growth_p; %0.01; % when isotropic this will be 0.005
kbper_p(:) = BasicGrowth*s_growth_p; %0.0; % when isotropic this will be 0.005
knor_p(:) = 0; % thickness
end
v_kareal_p=kapar_p+kaper_p; % total specified areal growth
% Section 5
%%% END OF USER CODE: MORPHOGEN INTERACTIONS

%%% SECTION 3: INSTALLING MODIFIED VALUES BACK INTO MESH STRUCTURE
%%% AUTOMATICALLY GENERATED CODE: DO NOT EDIT.
m.morphogens(:,polariser_i) = P;
m.morphogens(:,kapar_i) = kapar_p;
m.morphogens(:,kaper_i) = kaper_p;
m.morphogens(:,kbpar_i) = kbpar_p;
m.morphogens(:,kbper_i) = kbper_p;
m.morphogens(:,knor_i) = knor_p;
m.morphogens(:,strainret_i) = strainret_p;
m.morphogens(:,arrest_i) = arrest_p;
m.morphogens(:,id_plusorg_i) = id_plusorg_p;
m.morphogens(:,id_minusorg_i) = id_minusorg_p;
m.morphogens(:,v_kareal_i) = v_kareal_p;
m.morphogens(:,id_tip_i) = id_tip_p;
m.morphogens(:,id_top_i) = id_top_p;
m.morphogens(:,s_growth_i) = s_growth_p;
m.morphogens(:,id_mid_i) = id_mid_p;

%%% USER CODE: FINALISATION

%%% END OF USER CODE: FINALISATION

end

%%% USER CODE: SUBFUNCTIONS

% Section 6
function m = local_setproperties( m )
end

Gaussian and sieve filters

2014-08-06T15:09:11Z

Software

2014-08-06T15:08:44Z

AndrewBangham: /* 1 A */

__TOC__


'''Current activity: a collaboration''' with the [http://rico-coen.jic.ac.uk/index.php/Main_Page CoenLab] with the aim of understanding how patterns of gene activity in biological organs influence the developing shape. The BanghamLab is focussed on the conceptual underpinning: concepts captured in computational growth models, experimental data visualisation and analysis.

===Notes on documenting our software===

[[Tricks for documenting software|Notes for Lab members on how to contribute to this Wiki and where to put downloads. ]]
 Matlab tip: searching a large data structure for a particular field. Clear the command window. Evaluate the structure to list all the fields, then use the usual control-f search tool on the command window.

='''Computational biology'''=
==Quantitative understanding of growing shapes: '''GFtbox'''==
====We developed ''GFtbox'' to allow us to model the growth of complex shapes with the ultimate goal: to understand the relationships between genes, growth and form.====
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="400"| [[Image:Journal.pbio.1000537.g009.png|350px|Growth of a flower]] Example of a growing snapdragon flower and some mutants ( [http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1000537 Green et al 2011]). Growth is specified by factors (genes) according to the Growing Polarised Tissue Framework. Colours represent putative gene activity, arrows the polariser gradient and spots clones.
|<wikiflv width="300" height="313" logo="false" loop="true" background="white" position="right" autoplay='true'>GPT_Snapdragon_2010_Green_et_al-0002_1.flv|GPT_Snapdragon_2010_Green_et_al-0002.png</wikiflv>

|}

{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>GPT_thumbnail2.png|120px|GFtbox</imgicon>
|width="40%"|
For modelling the growth of shapes. 

[[Ready Reference Manual|'''''Ready Reference''''' Manual]] 
(PC, Mac, Linux, uses Matlab no Mathworks toolboxes needed [http://www.mathworks.com/products/matlab/tryit.html Matlab 30 day free trial] and [http://www.mathworks.com/academia/student_version/?s_cid=global_nav student edition]) 

[[Ready Reference Manual ancillary functions|'''''Ready Reference'for ancillary functions: in '''interaction function''' and external functions'''' Manual]] 

[[GFtbox|'''What? How? Where?''']] Background 
[[GFtbox Tutorial pages|'''''Tutorials''''': from the beginning]] Start here 
[[GFtbox Example pages|'''''Examples''''': from publications]] 

[https://sourceforge.net/p/gftbox/ '''''Download GFTbox''''' from SourceForge] 
'''''Download GFTbox project files:''''' 

[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSourceDownload_PLoS_SauretGueto_2013/GPT_Petal_PLoS_20130502.zip '''''Petals''''' Sauret-Güeto et al 2013] 

[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSourceDownload_Science_Paper_2012/GPT_ArabidopsisLeafModel_20120207.zip '''''Leaves''''' Kuchen et al 2012] 

[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSourceDownload_PLoS_Kennaway_2011/Kennaway-etal-2011.zip '''''Principles and concepts''''' Kennaway et al 2011] 

[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSourceDownload_PLoS_Green_2011/Green-etal-2010.zip '''''Snapdragon''''' Green et al 2011, Cui et al 2010] 

|width="50%"| ''GFtbox'' is an implementation of the Growing Polarised Tissue Framework (GPT-framework) for understanding and modelling the relationship between gene activity and the growth of shapes such leaves, flowers and animal embryos ([http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002071 Kennaway et al 2011]). 

The GPT-framework was used to capture an understanding of (to model) the growing petal ([http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001550 Sauret-Güeto et al 2013]), leaf ([http://www.sciencemag.org/content/335/6072/1092.abstract Kuchen et al 2012]) and Snapdragon flower [http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1000537 Green et al 2011]. The Snapdragon model was validated by comparing the results with other mutant and transgenic flowers [http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1000538 Cui et al 2010.] 

The key point is how '''outgrowths can be specified by genes'''. The icon shows an asymmetrical outgrowth. Conceptually, it is specifed by two independent patterns under genetic control: a pattern of growth and a pattern of organisers. The outgrowth arises from a region of extra overall growth. Growth is aligned along axes set by two interacting systems. Organisers at the ends of the mesh create a lengthwise gradient. This gradient interacts with the second due to putative organisers that generate polariser sinks in the region that becomes the tips of the palette outgrowth. ([http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002071 Kennaway et al 2011]). These hypotheses need to be tested in biological systems.
|}

==Viewing and measuring volume images: '''VolViewer'''==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>VolViewer-logo.png|120px|VolViewer</imgicon>
|width="40%"|For viewing and measuring '''volume images''' on both normal and '''stereo''' screens. Typical images from: confocal microscope and Optical Projection Tomography (OPT) images 
[[VolViewer#Description|'''What? How? Where?''']] 
[[VolViewer#User Documentation|'''''Tutorials''''': from the beginning]] 
[[VolViewer#Download| '''''Download''''']] 
(Windows, Mac, Linux) 
Output from VolViewer has appeared in: 

[http://www.cell.com/cell_picture_show-plantbio Cell: Online Gallery] | [http://www.amazon.co.uk/Handbook-Plant-Science-Keith-Roberts/dp/0470057238/ref=sr_1_19?s=books&ie=UTF8&qid=1289321357&sr=1-19 Front cover: Handbook of Plant Science] | [http://www.plantcell.org/content/18/9.toc Front cover: The Plant Cell] | [http://www.americanscientist.org/issues/pub/2013/1/3d-carnivorous-plants American Scientist] | [http://www.rms.org.uk/Resources/Royal%20Microscopical%20Society/infocus/Edgar%20article.pdf Royal Microscopical Society: Infocus Magazine] | [http://www.bioptonics.com/Home.htm Bundled with the Bioptonic 3001 scanner: Bioptonics Viewer] | [http://www.dailymail.co.uk/sciencetech/article-2215052/The-complexity-intricacy-Mother-Nature-revealed-incredible-pictures-plants--seen-inside.html The Daily Mail] | [http://www.guardian.co.uk/science/gallery/2007/sep/04/fruitflybrain#/?picture=330675671&index=1 The Guardian newspaper: 3D Fruit fly] | [http://qt.nokia.com/qt-in-use/ambassadors/project?id=a0F20000006LZ2pEAG Qt Ambassador program] | [http://www.triffidnurseries.co.uk/special3.php Triffid Nurseries website]

 
|width="50%"| VolViewer is used as a '''stand-alone''' app. or as a '''viewport for other systems''', e.g. Matlab programs. VolViewer uses [http://www.opengl.org/ OpenGL] and [http://qt.nokia.com/products/ Qt] to provide a user friendly application to interactively explore and quantify multi-dimensional biological images. It has been successfully used in our lab to explore and quantify confocal microscopy and optical projection tomography images. Written by Jerome Avondo it is open-source and is also compatible with the Open Microscopy Environment ([http://openmicroscopy.org/site OME]) (Chris Allen and Avondo, et. al. ''OMERO: flexible, model-driven data management for experimental biology'' Nature Methods 9, 245–253 (2012)) [[image:Silique.PNG|360px]]).
|}

==Analysing shapes in 2D and 3D: '''AAMToolbox'''==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>AAMToolbox_logo.jpg|120px|AAMToolbox</imgicon>
|width="40%"|For analysing populations of shapes and colours within the shapes using principal component analysis. 
[[AAMToolbox Details|'''What? How? Where?''']] 
[[Tutorials on the Shape modelling toolbox|'''''Tutorials''''': from the beginning]] 

[[AAMToolbox Download|'''''Download revised Nov2012''''' ]] 

(PC, Mac, Linux, uses Matlab no Mathworks toolboxes needed [http://www.mathworks.com/products/matlab/tryit.html Matlab 30 day free trial] and [http://www.mathworks.com/academia/student_version/?s_cid=global_nav student edition]) 
|width="50%"| The AAMToolbox enables the user analyse the shape and colour of collections of similar objects. Originally developed to analyse face shapes for lipreading ([http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=982900 Matthews ''et al''. 2002][http://www2.cmp.uea.ac.uk/~sjc/matthews-pami-01.pdf version of pdf]), we have used it extensively for analysing the shapes of leaves ([http://www.pnas.org/content/102/29/10221.short Langlade ''et al'' 2005.],[http://www.tandfonline.com/doi/abs/10.2976/1.2836738 Bensmihen ''et al.'' 2010]) and petals ([http://www.sciencemag.org/content/313/5789/963.short Whibley ''et al'' 2006],[http://www.mssaleshops.info/content/21/10/2999.short Feng ''et al''. 2010]). The analysis can be applied to art, for example, finding systematic differences between portraits by Rembrandt and Modigliani.
|}
==Analysing the shapes of clones: '''SectorAnalysisToolbox'''==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>Sector analysis icon.jpg|120px|SectorAnalysisToolbox</imgicon>
|width="40%"|For analysing the shapes of marked cell clones. 
[[SectorAnalysisToolbox Details|'''What? How? Where?''']] 
[[SectorAnalysisToolbox Documentation|'''''Tutorials''''': from the beginning]] 
[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSourceDownload_Science_Paper_2012/SectorAnalysisToolbox.zip '''''Download''''' ] 
(PC, Mac, Linux, uses Matlab no Mathworks toolboxes needed [http://www.mathworks.com/products/matlab/tryit.html Matlab 30 day free trial] and [http://www.mathworks.com/academia/student_version/?s_cid=global_nav student edition]) 
|width="50%"| The SectorAnalysisToolbox enables the user analyse the shapes of marked clones in a sheet of tissue.
|}

='''Algorithms'''=
==MSERs, extrema, connected-set filters and sieves==
====The algorithm finding MSER's starts with a connected-set opening or 'o' sieve====
[[Comparison of Matlab MSER's and 'o' sieve|Comparison of Matlab MSER's and 'o' sieve]] Essentially, no difference.
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="50%"| [[Image:Cameraman_iso_topview.jpg|300px|link=AAMToolbox Details|MSERs]] Cameraman image. Superimposed red spots are maximal extrema and blue spots are minima. Irregular cyan, blue and yellow regions illustrate regions associated with maxima and the magenta region is a minimum.
|[[Image:cameraman_iso_tree.jpg|300px|link=AAMToolbox Details|MSERs over scale-space]] Isometric view of the cameraman image with superimposed maxima (red) and minima (blue). The trees trace the maxima through increasing scale-space. Large spots have been identified as stable extrema.
|}

===Finding interest points, features and segmenting images. ===
#[[MSER and Sieve Details|'''Technical briefing''']] MSER's incorporate 'o' sieves.
#[[MSER's and Connected sets|'''The twist''': from restricted median filters to sieves and MSER's]]
#One dimensional sieves (measure length)
##[[Types of 1D sieve|Types of 1D sieve]]
##[[First applied to hydrophobicity plots|First applied to hydrophobicity plots]] but lets exploit their idempotency.
#Two dimensional sieves (measure areas)
##Properties
##Relation to MSER's
#Three dimensional sieves (measure volumes)
##[[Segment by volume|Segment by volume]] instant gratification.




===Art, extrema of light and shade: '''''PhotoArtMaster'''''===

Art created using ArtMaster, and ArtMaster itself was featured in an exhibit at the London Victoria and Albert (V&A) Museum exhibition 'Cheating? How to make Perfect Work of Art' (2003). The exhibition centered on the idea of [http://en.wikipedia.org/wiki/Hockney%E2%80%93Falco_thesis Hockney's] that advances in realism and accuracy in the history of Western art since the Renaissance were primarily the result of optical aids such as the camera obscura, camera lucida, and curved mirrors. My exhibit used a touch screen (rare in those days) and ArtMaster to help visitors create 'paintings' from photographs. [http://www.sciencemuseum.org.uk/visitmuseum/galleries/turing.aspx finding its name]. (It is entirely different in principle from the software more recently used by Hockney to paint with an iPad.) 

{| border="0" width=100% style="background-color:#ffffff;"
|-
|align="center"|[[Image:DegasLightAndShade.jpg|400px]][[Image:Emma_face_Art_C.jpg|300px]]
 
Illustration of PhotoArtMaster used to find and 'paint' with regions of light and shade crisply segmented from a photograph. Likewise, on the right, edges.
|}
=====PhotoArtMaster=====
Saturday 07/06/2014: Inspired Photographer of the Year 2013 Tony Bennett when asked whether his photograph [http://www.bbc.co.uk/programmes/galleries/p020hd8s Mists and Reflections] had been Photoshopped replied something like 
"A digital camera delivers an unemotional ''raw'' image of pixels that you have to manipulate to ''create your photograph''" Photographers manipulate as little as possible. 
However there is '''another path one that creates pictures'''. For this you need another piece of software: PhotoArtMaster (ArtMaster). Professional Photographer said ''"'''Forget any comparison whatsoever with the art filters in Photoshop - this software reaches out and enters different stratospheres'''"'' [[Professional Photographer]]. 
Early versions of PhotoArtMaster are still '''available from Amazon''' at low prices (I'm not sure where they come from.)
[http://www.amazon.co.uk/s/ref=nb_sb_noss?url=search-alias%3Daps&field-keywords=photoartmaster] . Some help for both the early versions and the latest version can be found in [http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/SieveWebPages/a4a_2_screensize.pdf ''''this document''''' ]).
=====Links to third party PhotoArtMastered pictures=====
*[https://picasaweb.google.com/113257474829608374943/InTheStyleOf Oliver Bangham] Colouful rounded shapes from, yes, my brother.
*[http://en.wikipedia.org/wiki/Wimbledon_%28film%29 The entry sequence of the comedy film 'Wimbledon']

====The final version of the Windows ArtMaster2.0 [http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSource_ArtMaster/ArtMaster2.0Release.zip '''''is downloadable here'''''] with no support.====
Unzip into (for example) the "Program Files" directory then set your system environment to include: ''C:\Program Files\Pam2.0 Release\jre\bin;C:\Program Files\Pam2.0 Release\bin;'' (You may need help for this. I right clicked 'computer' from the 'Start' menu, then selected 'Advanced system settings', then 'Environment Variables' and finally slid through the System variables until I found and selected 'Path'. This allowed me to edit the path by adding ';C:\Program Files\Pam2.0 Release\jre\bin;C:\Program Files\Pam2.0 Release\bin' to the end). Rather detailed help using the software is available in [http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/SieveWebPages/a4a_2_screensize.pdf ''''this essay''''' ]. 
[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/SieveWebPages/Art_For_All_a4a_3_web2.pdf '''''The sieve algorithms underpinning PhotoArtMaster software''''' ] are described in an extract of the
[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/SieveWebPages/a4a_2_screensize.pdf ''''essay''''' ]. These documents were written to support our Fo2Pix company. PhotoArtMaster originally sold >65,000 licences but ill health forced the closure of Fo2Pix.

{| border="0" width=100% style="background-color:#ffffff;"
|-
|align="center"|[[Image:Trees_1.jpg|600px]]
 
Illustration of PhotoArtMaster used to find and 'paint' with regions of colour crisply segmented from a photograph.
|}



==Reaction-diffusion and morphogenesis==
{| border="0" width=100% style="background-color:#000000;"
|-
|align="center"|
[[Image:tentacles_morphogenesis.png|600px]]
|}
Illustration of morphogenesis inspired by Turing's paper. 
[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/GPT_ReactionDiffusionTentacles_20121211.zip Example using growth toolbox GPT_ReactionDiffusionTentacles_20121211.zip]
 
===1 A===

=Open source systems to which we have contributed=
==OMERO==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>OMERO_DIAGRAM.jpg|100px|OMERO</imgicon>
|width="40%"|For working with the OME image database. See [http://www.openmicroscopy.org/site/products/omero ''Details''], [http://www.openmicroscopy.org/site/support/omero4/downloads ''Download''] [http://dmbi.nbi.bbsrc.ac.uk/index.php/OMEROWorkshop OMERO Workshop] 
(Windows, Mac, Linux)
|width="50%"| [http://openmicroscopy.org/site/support/omero4 Open Microscopy Environment Remote Objects (OMERO).] for visualising, managing, and annotating scientific image data. See also our [http://dmbi.nbi.bbsrc.ac.uk/index.php/OMEROWorkshop OMERO Workshop] training course we ran in April 2011.
|}

=Tools and Utilities=
==BioformatsConverter==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>BioformatsConverterZip.png|100px|BioformatsConverter</imgicon>
|width="40%"|For converting microscope manufacturer proprietary file formats. See [[BioformatsConverter|''Details'']] 
(Windows, Mac, Linux)
|width="50%"| This tool allows for the batch conversion of microscope manufacturer proprietary file formats, to the open source OME-TIFF standard. Uses the [http://www.loci.wisc.edu/software/bio-formats Bioformats] library.
|}
==Dependency Checking Tool==

Tool for recursively finding what further functions a function depends on. See [[myDepFun|''Details'']]

=In development=
==MTtbox==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>MTtboxA.jpg|100px|BioformatsConverter</imgicon>
|width="40%"|For modelling the behaviour of microtubules within a cell. 
See [[MTtbox documentation|''Details'']] 
(Windows, Mac, Linux)
|width="50%"| In development. The idea is to be able to model the behaviour of growing microtubules and factors as they react chemically and diffuse within the different cell compartments. 
The icon shows a spherical cell sliced open to show concentric components: cell wall (magenta), plasma-membrane (yellow), cytoplasm (green) and vacuole (yellow). Microtubules (blue) grow in 3D within the cytoplasm.
|}
=Historical=
==Robot arm: still in production after 30 years (serving local industry)==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="50%"|[[Image:2014-06-10 14.22.20 small robot.jpg|400px|]]
|width="40%"|For teaching '''production control''' and '''interrupt programming'''. 
1983 and we are in a world of '''Apple II and BBC B computers''' - the ''6502'' processor reigns. Particularly good for real-time control it responded very fast to hardware interrupts from, for example, the timer. To illustrate timer interrupts what better than digital servo-motors? Set up the on-board timers to produce a stream of 'heartbeat' of pulses, one every 20 ms out of the parallel port and control up to eight motors. Pulse widths, from 1 to 2 ms, control the position of each motor arm. Derek Fulton and I made some loose lab. money by writing a series of articles showing exactly how to build and, in particular, control this robot arm.[[Publications#.28G.29_Computer_control.2C_measurement_and_commercial_software |Bangham et al.]].
Our copyright, I took it to a local company LJ-Electronics ([http://www.ljcreate.com/products/product.asp?id=314&program=195&curr=2 now LJ-Creative]) who incorporated it detail for detail into their product line. Originally, they called it the Emu. Still in production: '''Lovely outcome.'''
|}

=Historical=

Software

2014-08-06T15:07:30Z

AndrewBangham: /* 1 A */

__TOC__


'''Current activity: a collaboration''' with the [http://rico-coen.jic.ac.uk/index.php/Main_Page CoenLab] with the aim of understanding how patterns of gene activity in biological organs influence the developing shape. The BanghamLab is focussed on the conceptual underpinning: concepts captured in computational growth models, experimental data visualisation and analysis.

===Notes on documenting our software===

[[Tricks for documenting software|Notes for Lab members on how to contribute to this Wiki and where to put downloads. ]]
 Matlab tip: searching a large data structure for a particular field. Clear the command window. Evaluate the structure to list all the fields, then use the usual control-f search tool on the command window.

='''Computational biology'''=
==Quantitative understanding of growing shapes: '''GFtbox'''==
====We developed ''GFtbox'' to allow us to model the growth of complex shapes with the ultimate goal: to understand the relationships between genes, growth and form.====
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="400"| [[Image:Journal.pbio.1000537.g009.png|350px|Growth of a flower]] Example of a growing snapdragon flower and some mutants ( [http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1000537 Green et al 2011]). Growth is specified by factors (genes) according to the Growing Polarised Tissue Framework. Colours represent putative gene activity, arrows the polariser gradient and spots clones.
|<wikiflv width="300" height="313" logo="false" loop="true" background="white" position="right" autoplay='true'>GPT_Snapdragon_2010_Green_et_al-0002_1.flv|GPT_Snapdragon_2010_Green_et_al-0002.png</wikiflv>

|}

{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>GPT_thumbnail2.png|120px|GFtbox</imgicon>
|width="40%"|
For modelling the growth of shapes. 

[[Ready Reference Manual|'''''Ready Reference''''' Manual]] 
(PC, Mac, Linux, uses Matlab no Mathworks toolboxes needed [http://www.mathworks.com/products/matlab/tryit.html Matlab 30 day free trial] and [http://www.mathworks.com/academia/student_version/?s_cid=global_nav student edition]) 

[[Ready Reference Manual ancillary functions|'''''Ready Reference'for ancillary functions: in '''interaction function''' and external functions'''' Manual]] 

[[GFtbox|'''What? How? Where?''']] Background 
[[GFtbox Tutorial pages|'''''Tutorials''''': from the beginning]] Start here 
[[GFtbox Example pages|'''''Examples''''': from publications]] 

[https://sourceforge.net/p/gftbox/ '''''Download GFTbox''''' from SourceForge] 
'''''Download GFTbox project files:''''' 

[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSourceDownload_PLoS_SauretGueto_2013/GPT_Petal_PLoS_20130502.zip '''''Petals''''' Sauret-Güeto et al 2013] 

[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSourceDownload_Science_Paper_2012/GPT_ArabidopsisLeafModel_20120207.zip '''''Leaves''''' Kuchen et al 2012] 

[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSourceDownload_PLoS_Kennaway_2011/Kennaway-etal-2011.zip '''''Principles and concepts''''' Kennaway et al 2011] 

[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSourceDownload_PLoS_Green_2011/Green-etal-2010.zip '''''Snapdragon''''' Green et al 2011, Cui et al 2010] 

|width="50%"| ''GFtbox'' is an implementation of the Growing Polarised Tissue Framework (GPT-framework) for understanding and modelling the relationship between gene activity and the growth of shapes such leaves, flowers and animal embryos ([http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002071 Kennaway et al 2011]). 

The GPT-framework was used to capture an understanding of (to model) the growing petal ([http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001550 Sauret-Güeto et al 2013]), leaf ([http://www.sciencemag.org/content/335/6072/1092.abstract Kuchen et al 2012]) and Snapdragon flower [http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1000537 Green et al 2011]. The Snapdragon model was validated by comparing the results with other mutant and transgenic flowers [http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1000538 Cui et al 2010.] 

The key point is how '''outgrowths can be specified by genes'''. The icon shows an asymmetrical outgrowth. Conceptually, it is specifed by two independent patterns under genetic control: a pattern of growth and a pattern of organisers. The outgrowth arises from a region of extra overall growth. Growth is aligned along axes set by two interacting systems. Organisers at the ends of the mesh create a lengthwise gradient. This gradient interacts with the second due to putative organisers that generate polariser sinks in the region that becomes the tips of the palette outgrowth. ([http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002071 Kennaway et al 2011]). These hypotheses need to be tested in biological systems.
|}

==Viewing and measuring volume images: '''VolViewer'''==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>VolViewer-logo.png|120px|VolViewer</imgicon>
|width="40%"|For viewing and measuring '''volume images''' on both normal and '''stereo''' screens. Typical images from: confocal microscope and Optical Projection Tomography (OPT) images 
[[VolViewer#Description|'''What? How? Where?''']] 
[[VolViewer#User Documentation|'''''Tutorials''''': from the beginning]] 
[[VolViewer#Download| '''''Download''''']] 
(Windows, Mac, Linux) 
Output from VolViewer has appeared in: 

[http://www.cell.com/cell_picture_show-plantbio Cell: Online Gallery] | [http://www.amazon.co.uk/Handbook-Plant-Science-Keith-Roberts/dp/0470057238/ref=sr_1_19?s=books&ie=UTF8&qid=1289321357&sr=1-19 Front cover: Handbook of Plant Science] | [http://www.plantcell.org/content/18/9.toc Front cover: The Plant Cell] | [http://www.americanscientist.org/issues/pub/2013/1/3d-carnivorous-plants American Scientist] | [http://www.rms.org.uk/Resources/Royal%20Microscopical%20Society/infocus/Edgar%20article.pdf Royal Microscopical Society: Infocus Magazine] | [http://www.bioptonics.com/Home.htm Bundled with the Bioptonic 3001 scanner: Bioptonics Viewer] | [http://www.dailymail.co.uk/sciencetech/article-2215052/The-complexity-intricacy-Mother-Nature-revealed-incredible-pictures-plants--seen-inside.html The Daily Mail] | [http://www.guardian.co.uk/science/gallery/2007/sep/04/fruitflybrain#/?picture=330675671&index=1 The Guardian newspaper: 3D Fruit fly] | [http://qt.nokia.com/qt-in-use/ambassadors/project?id=a0F20000006LZ2pEAG Qt Ambassador program] | [http://www.triffidnurseries.co.uk/special3.php Triffid Nurseries website]

 
|width="50%"| VolViewer is used as a '''stand-alone''' app. or as a '''viewport for other systems''', e.g. Matlab programs. VolViewer uses [http://www.opengl.org/ OpenGL] and [http://qt.nokia.com/products/ Qt] to provide a user friendly application to interactively explore and quantify multi-dimensional biological images. It has been successfully used in our lab to explore and quantify confocal microscopy and optical projection tomography images. Written by Jerome Avondo it is open-source and is also compatible with the Open Microscopy Environment ([http://openmicroscopy.org/site OME]) (Chris Allen and Avondo, et. al. ''OMERO: flexible, model-driven data management for experimental biology'' Nature Methods 9, 245–253 (2012)) [[image:Silique.PNG|360px]]).
|}

==Analysing shapes in 2D and 3D: '''AAMToolbox'''==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>AAMToolbox_logo.jpg|120px|AAMToolbox</imgicon>
|width="40%"|For analysing populations of shapes and colours within the shapes using principal component analysis. 
[[AAMToolbox Details|'''What? How? Where?''']] 
[[Tutorials on the Shape modelling toolbox|'''''Tutorials''''': from the beginning]] 

[[AAMToolbox Download|'''''Download revised Nov2012''''' ]] 

(PC, Mac, Linux, uses Matlab no Mathworks toolboxes needed [http://www.mathworks.com/products/matlab/tryit.html Matlab 30 day free trial] and [http://www.mathworks.com/academia/student_version/?s_cid=global_nav student edition]) 
|width="50%"| The AAMToolbox enables the user analyse the shape and colour of collections of similar objects. Originally developed to analyse face shapes for lipreading ([http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=982900 Matthews ''et al''. 2002][http://www2.cmp.uea.ac.uk/~sjc/matthews-pami-01.pdf version of pdf]), we have used it extensively for analysing the shapes of leaves ([http://www.pnas.org/content/102/29/10221.short Langlade ''et al'' 2005.],[http://www.tandfonline.com/doi/abs/10.2976/1.2836738 Bensmihen ''et al.'' 2010]) and petals ([http://www.sciencemag.org/content/313/5789/963.short Whibley ''et al'' 2006],[http://www.mssaleshops.info/content/21/10/2999.short Feng ''et al''. 2010]). The analysis can be applied to art, for example, finding systematic differences between portraits by Rembrandt and Modigliani.
|}
==Analysing the shapes of clones: '''SectorAnalysisToolbox'''==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>Sector analysis icon.jpg|120px|SectorAnalysisToolbox</imgicon>
|width="40%"|For analysing the shapes of marked cell clones. 
[[SectorAnalysisToolbox Details|'''What? How? Where?''']] 
[[SectorAnalysisToolbox Documentation|'''''Tutorials''''': from the beginning]] 
[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSourceDownload_Science_Paper_2012/SectorAnalysisToolbox.zip '''''Download''''' ] 
(PC, Mac, Linux, uses Matlab no Mathworks toolboxes needed [http://www.mathworks.com/products/matlab/tryit.html Matlab 30 day free trial] and [http://www.mathworks.com/academia/student_version/?s_cid=global_nav student edition]) 
|width="50%"| The SectorAnalysisToolbox enables the user analyse the shapes of marked clones in a sheet of tissue.
|}

='''Algorithms'''=
==MSERs, extrema, connected-set filters and sieves==
====The algorithm finding MSER's starts with a connected-set opening or 'o' sieve====
[[Comparison of Matlab MSER's and 'o' sieve|Comparison of Matlab MSER's and 'o' sieve]] Essentially, no difference.
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="50%"| [[Image:Cameraman_iso_topview.jpg|300px|link=AAMToolbox Details|MSERs]] Cameraman image. Superimposed red spots are maximal extrema and blue spots are minima. Irregular cyan, blue and yellow regions illustrate regions associated with maxima and the magenta region is a minimum.
|[[Image:cameraman_iso_tree.jpg|300px|link=AAMToolbox Details|MSERs over scale-space]] Isometric view of the cameraman image with superimposed maxima (red) and minima (blue). The trees trace the maxima through increasing scale-space. Large spots have been identified as stable extrema.
|}

===Finding interest points, features and segmenting images. ===
#[[MSER and Sieve Details|'''Technical briefing''']] MSER's incorporate 'o' sieves.
#[[MSER's and Connected sets|'''The twist''': from restricted median filters to sieves and MSER's]]
#One dimensional sieves (measure length)
##[[Types of 1D sieve|Types of 1D sieve]]
##[[First applied to hydrophobicity plots|First applied to hydrophobicity plots]] but lets exploit their idempotency.
#Two dimensional sieves (measure areas)
##Properties
##Relation to MSER's
#Three dimensional sieves (measure volumes)
##[[Segment by volume|Segment by volume]] instant gratification.




===Art, extrema of light and shade: '''''PhotoArtMaster'''''===

Art created using ArtMaster, and ArtMaster itself was featured in an exhibit at the London Victoria and Albert (V&A) Museum exhibition 'Cheating? How to make Perfect Work of Art' (2003). The exhibition centered on the idea of [http://en.wikipedia.org/wiki/Hockney%E2%80%93Falco_thesis Hockney's] that advances in realism and accuracy in the history of Western art since the Renaissance were primarily the result of optical aids such as the camera obscura, camera lucida, and curved mirrors. My exhibit used a touch screen (rare in those days) and ArtMaster to help visitors create 'paintings' from photographs. [http://www.sciencemuseum.org.uk/visitmuseum/galleries/turing.aspx finding its name]. (It is entirely different in principle from the software more recently used by Hockney to paint with an iPad.) 

{| border="0" width=100% style="background-color:#ffffff;"
|-
|align="center"|[[Image:DegasLightAndShade.jpg|400px]][[Image:Emma_face_Art_C.jpg|300px]]
 
Illustration of PhotoArtMaster used to find and 'paint' with regions of light and shade crisply segmented from a photograph. Likewise, on the right, edges.
|}
=====PhotoArtMaster=====
Saturday 07/06/2014: Inspired Photographer of the Year 2013 Tony Bennett when asked whether his photograph [http://www.bbc.co.uk/programmes/galleries/p020hd8s Mists and Reflections] had been Photoshopped replied something like 
"A digital camera delivers an unemotional ''raw'' image of pixels that you have to manipulate to ''create your photograph''" Photographers manipulate as little as possible. 
However there is '''another path one that creates pictures'''. For this you need another piece of software: PhotoArtMaster (ArtMaster). Professional Photographer said ''"'''Forget any comparison whatsoever with the art filters in Photoshop - this software reaches out and enters different stratospheres'''"'' [[Professional Photographer]]. 
Early versions of PhotoArtMaster are still '''available from Amazon''' at low prices (I'm not sure where they come from.)
[http://www.amazon.co.uk/s/ref=nb_sb_noss?url=search-alias%3Daps&field-keywords=photoartmaster] . Some help for both the early versions and the latest version can be found in [http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/SieveWebPages/a4a_2_screensize.pdf ''''this document''''' ]).
=====Links to third party PhotoArtMastered pictures=====
*[https://picasaweb.google.com/113257474829608374943/InTheStyleOf Oliver Bangham] Colouful rounded shapes from, yes, my brother.
*[http://en.wikipedia.org/wiki/Wimbledon_%28film%29 The entry sequence of the comedy film 'Wimbledon']

====The final version of the Windows ArtMaster2.0 [http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSource_ArtMaster/ArtMaster2.0Release.zip '''''is downloadable here'''''] with no support.====
Unzip into (for example) the "Program Files" directory then set your system environment to include: ''C:\Program Files\Pam2.0 Release\jre\bin;C:\Program Files\Pam2.0 Release\bin;'' (You may need help for this. I right clicked 'computer' from the 'Start' menu, then selected 'Advanced system settings', then 'Environment Variables' and finally slid through the System variables until I found and selected 'Path'. This allowed me to edit the path by adding ';C:\Program Files\Pam2.0 Release\jre\bin;C:\Program Files\Pam2.0 Release\bin' to the end). Rather detailed help using the software is available in [http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/SieveWebPages/a4a_2_screensize.pdf ''''this essay''''' ]. 
[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/SieveWebPages/Art_For_All_a4a_3_web2.pdf '''''The sieve algorithms underpinning PhotoArtMaster software''''' ] are described in an extract of the
[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/SieveWebPages/a4a_2_screensize.pdf ''''essay''''' ]. These documents were written to support our Fo2Pix company. PhotoArtMaster originally sold >65,000 licences but ill health forced the closure of Fo2Pix.

{| border="0" width=100% style="background-color:#ffffff;"
|-
|align="center"|[[Image:Trees_1.jpg|600px]]
 
Illustration of PhotoArtMaster used to find and 'paint' with regions of colour crisply segmented from a photograph.
|}



==Reaction-diffusion and morphogenesis==
{| border="0" width=100% style="background-color:#000000;"
|-
|align="center"|
[[Image:tentacles_morphogenesis.png|600px]]
|}
Illustration of morphogenesis inspired by Turing's paper. 
[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/GPT_ReactionDiffusionTentacles_20121211.zip Example using growth toolbox GPT_ReactionDiffusionTentacles_20121211.zip]
 
===1 A===
{| border="0" cellpadding="5" cellspacing="3"
|- valign="top"
|<wikiflv width="800" height="900" logo="false" loop="true" background="white">Siv1-meanmedian_2.flv|Siv1-meanmedian.png</wikiflv>
 OK its a crap Figure. I spent ages getting the trace above each new one to show the moving window used to compute the output of each stage. 
Left panel: running mean. Stage (scale) 1 window of 3. Stage 2 window of 5 on the previous stage. And so forth. Each stage simplifies the signal until, at the bottom, it fades away. BUT it does not preserve [http://en.wikipedia.org/wiki/Scale_space scale-space] and that is '''''bad'''''.
Right panel: running median. Median filters had many followers. It was thought that they preserved the edges in a meaningful way. Stage (scale) 1 window of 3. The filter removes extrema of length (scale) 1. Stage 2 window of 5 on the previous stage and this filter removes extrema of scale 2. And so forth. Each stage simplifies the signal until, at the bottom, it fades away. It is tempting to imagine that extrema at each scale are removed in a nice regular way '''''BUT''''' no, it all falls apart at larger scales it does not preserve [http://en.wikipedia.org/wiki/Scale_space scale-space] and that is '''''bad'''''.
|}

=Open source systems to which we have contributed=
==OMERO==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>OMERO_DIAGRAM.jpg|100px|OMERO</imgicon>
|width="40%"|For working with the OME image database. See [http://www.openmicroscopy.org/site/products/omero ''Details''], [http://www.openmicroscopy.org/site/support/omero4/downloads ''Download''] [http://dmbi.nbi.bbsrc.ac.uk/index.php/OMEROWorkshop OMERO Workshop] 
(Windows, Mac, Linux)
|width="50%"| [http://openmicroscopy.org/site/support/omero4 Open Microscopy Environment Remote Objects (OMERO).] for visualising, managing, and annotating scientific image data. See also our [http://dmbi.nbi.bbsrc.ac.uk/index.php/OMEROWorkshop OMERO Workshop] training course we ran in April 2011.
|}

=Tools and Utilities=
==BioformatsConverter==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>BioformatsConverterZip.png|100px|BioformatsConverter</imgicon>
|width="40%"|For converting microscope manufacturer proprietary file formats. See [[BioformatsConverter|''Details'']] 
(Windows, Mac, Linux)
|width="50%"| This tool allows for the batch conversion of microscope manufacturer proprietary file formats, to the open source OME-TIFF standard. Uses the [http://www.loci.wisc.edu/software/bio-formats Bioformats] library.
|}
==Dependency Checking Tool==

Tool for recursively finding what further functions a function depends on. See [[myDepFun|''Details'']]

=In development=
==MTtbox==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>MTtboxA.jpg|100px|BioformatsConverter</imgicon>
|width="40%"|For modelling the behaviour of microtubules within a cell. 
See [[MTtbox documentation|''Details'']] 
(Windows, Mac, Linux)
|width="50%"| In development. The idea is to be able to model the behaviour of growing microtubules and factors as they react chemically and diffuse within the different cell compartments. 
The icon shows a spherical cell sliced open to show concentric components: cell wall (magenta), plasma-membrane (yellow), cytoplasm (green) and vacuole (yellow). Microtubules (blue) grow in 3D within the cytoplasm.
|}
=Historical=
==Robot arm: still in production after 30 years (serving local industry)==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="50%"|[[Image:2014-06-10 14.22.20 small robot.jpg|400px|]]
|width="40%"|For teaching '''production control''' and '''interrupt programming'''. 
1983 and we are in a world of '''Apple II and BBC B computers''' - the ''6502'' processor reigns. Particularly good for real-time control it responded very fast to hardware interrupts from, for example, the timer. To illustrate timer interrupts what better than digital servo-motors? Set up the on-board timers to produce a stream of 'heartbeat' of pulses, one every 20 ms out of the parallel port and control up to eight motors. Pulse widths, from 1 to 2 ms, control the position of each motor arm. Derek Fulton and I made some loose lab. money by writing a series of articles showing exactly how to build and, in particular, control this robot arm.[[Publications#.28G.29_Computer_control.2C_measurement_and_commercial_software |Bangham et al.]].
Our copyright, I took it to a local company LJ-Electronics ([http://www.ljcreate.com/products/product.asp?id=314&program=195&curr=2 now LJ-Creative]) who incorporated it detail for detail into their product line. Originally, they called it the Emu. Still in production: '''Lovely outcome.'''
|}

=Historical=

AndrewBangham:

Software

2014-07-31T14:40:50Z

AndrewBangham: /* The final version of the Windows ArtMaster2.0 is downloadable here with no support. */

__TOC__


'''Current activity: a collaboration''' with the [http://rico-coen.jic.ac.uk/index.php/Main_Page CoenLab] with the aim of understanding how patterns of gene activity in biological organs influence the developing shape. The BanghamLab is focussed on the conceptual underpinning: concepts captured in computational growth models, experimental data visualisation and analysis.

===Notes on documenting our software===

[[Tricks for documenting software|Notes for Lab members on how to contribute to this Wiki and where to put downloads. ]]
 Matlab tip: searching a large data structure for a particular field. Clear the command window. Evaluate the structure to list all the fields, then use the usual control-f search tool on the command window.

='''Computational biology'''=
==Quantitative understanding of growing shapes: '''GFtbox'''==
====We developed ''GFtbox'' to allow us to model the growth of complex shapes with the ultimate goal: to understand the relationships between genes, growth and form.====
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="400"| [[Image:Journal.pbio.1000537.g009.png|350px|Growth of a flower]] Example of a growing snapdragon flower and some mutants ( [http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1000537 Green et al 2011]). Growth is specified by factors (genes) according to the Growing Polarised Tissue Framework. Colours represent putative gene activity, arrows the polariser gradient and spots clones.
|<wikiflv width="300" height="313" logo="false" loop="true" background="white" position="right" autoplay='true'>GPT_Snapdragon_2010_Green_et_al-0002_1.flv|GPT_Snapdragon_2010_Green_et_al-0002.png</wikiflv>

|}

{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>GPT_thumbnail2.png|120px|GFtbox</imgicon>
|width="40%"|
For modelling the growth of shapes. 

[[Ready Reference Manual|'''''Ready Reference''''' Manual]] 
(PC, Mac, Linux, uses Matlab no Mathworks toolboxes needed [http://www.mathworks.com/products/matlab/tryit.html Matlab 30 day free trial] and [http://www.mathworks.com/academia/student_version/?s_cid=global_nav student edition]) 

[[Ready Reference Manual ancillary functions|'''''Ready Reference'for ancillary functions: in '''interaction function''' and external functions'''' Manual]] 

[[GFtbox|'''What? How? Where?''']] Background 
[[GFtbox Tutorial pages|'''''Tutorials''''': from the beginning]] Start here 
[[GFtbox Example pages|'''''Examples''''': from publications]] 

[https://sourceforge.net/p/gftbox/ '''''Download GFTbox''''' from SourceForge] 
'''''Download GFTbox project files:''''' 

[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSourceDownload_PLoS_SauretGueto_2013/GPT_Petal_PLoS_20130502.zip '''''Petals''''' Sauret-Güeto et al 2013] 

[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSourceDownload_Science_Paper_2012/GPT_ArabidopsisLeafModel_20120207.zip '''''Leaves''''' Kuchen et al 2012] 

[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSourceDownload_PLoS_Kennaway_2011/Kennaway-etal-2011.zip '''''Principles and concepts''''' Kennaway et al 2011] 

[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSourceDownload_PLoS_Green_2011/Green-etal-2010.zip '''''Snapdragon''''' Green et al 2011, Cui et al 2010] 

|width="50%"| ''GFtbox'' is an implementation of the Growing Polarised Tissue Framework (GPT-framework) for understanding and modelling the relationship between gene activity and the growth of shapes such leaves, flowers and animal embryos ([http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002071 Kennaway et al 2011]). 

The GPT-framework was used to capture an understanding of (to model) the growing petal ([http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1001550 Sauret-Güeto et al 2013]), leaf ([http://www.sciencemag.org/content/335/6072/1092.abstract Kuchen et al 2012]) and Snapdragon flower [http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1000537 Green et al 2011]. The Snapdragon model was validated by comparing the results with other mutant and transgenic flowers [http://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.1000538 Cui et al 2010.] 

The key point is how '''outgrowths can be specified by genes'''. The icon shows an asymmetrical outgrowth. Conceptually, it is specifed by two independent patterns under genetic control: a pattern of growth and a pattern of organisers. The outgrowth arises from a region of extra overall growth. Growth is aligned along axes set by two interacting systems. Organisers at the ends of the mesh create a lengthwise gradient. This gradient interacts with the second due to putative organisers that generate polariser sinks in the region that becomes the tips of the palette outgrowth. ([http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1002071 Kennaway et al 2011]). These hypotheses need to be tested in biological systems.
|}

==Viewing and measuring volume images: '''VolViewer'''==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>VolViewer-logo.png|120px|VolViewer</imgicon>
|width="40%"|For viewing and measuring '''volume images''' on both normal and '''stereo''' screens. Typical images from: confocal microscope and Optical Projection Tomography (OPT) images 
[[VolViewer#Description|'''What? How? Where?''']] 
[[VolViewer#User Documentation|'''''Tutorials''''': from the beginning]] 
[[VolViewer#Download| '''''Download''''']] 
(Windows, Mac, Linux) 
Output from VolViewer has appeared in: 

[http://www.cell.com/cell_picture_show-plantbio Cell: Online Gallery] | [http://www.amazon.co.uk/Handbook-Plant-Science-Keith-Roberts/dp/0470057238/ref=sr_1_19?s=books&ie=UTF8&qid=1289321357&sr=1-19 Front cover: Handbook of Plant Science] | [http://www.plantcell.org/content/18/9.toc Front cover: The Plant Cell] | [http://www.americanscientist.org/issues/pub/2013/1/3d-carnivorous-plants American Scientist] | [http://www.rms.org.uk/Resources/Royal%20Microscopical%20Society/infocus/Edgar%20article.pdf Royal Microscopical Society: Infocus Magazine] | [http://www.bioptonics.com/Home.htm Bundled with the Bioptonic 3001 scanner: Bioptonics Viewer] | [http://www.dailymail.co.uk/sciencetech/article-2215052/The-complexity-intricacy-Mother-Nature-revealed-incredible-pictures-plants--seen-inside.html The Daily Mail] | [http://www.guardian.co.uk/science/gallery/2007/sep/04/fruitflybrain#/?picture=330675671&index=1 The Guardian newspaper: 3D Fruit fly] | [http://qt.nokia.com/qt-in-use/ambassadors/project?id=a0F20000006LZ2pEAG Qt Ambassador program] | [http://www.triffidnurseries.co.uk/special3.php Triffid Nurseries website]

 
|width="50%"| VolViewer is used as a '''stand-alone''' app. or as a '''viewport for other systems''', e.g. Matlab programs. VolViewer uses [http://www.opengl.org/ OpenGL] and [http://qt.nokia.com/products/ Qt] to provide a user friendly application to interactively explore and quantify multi-dimensional biological images. It has been successfully used in our lab to explore and quantify confocal microscopy and optical projection tomography images. Written by Jerome Avondo it is open-source and is also compatible with the Open Microscopy Environment ([http://openmicroscopy.org/site OME]) (Chris Allen and Avondo, et. al. ''OMERO: flexible, model-driven data management for experimental biology'' Nature Methods 9, 245–253 (2012)) [[image:Silique.PNG|360px]]).
|}

==Analysing shapes in 2D and 3D: '''AAMToolbox'''==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>AAMToolbox_logo.jpg|120px|AAMToolbox</imgicon>
|width="40%"|For analysing populations of shapes and colours within the shapes using principal component analysis. 
[[AAMToolbox Details|'''What? How? Where?''']] 
[[Tutorials on the Shape modelling toolbox|'''''Tutorials''''': from the beginning]] 

[[AAMToolbox Download|'''''Download revised Nov2012''''' ]] 

(PC, Mac, Linux, uses Matlab no Mathworks toolboxes needed [http://www.mathworks.com/products/matlab/tryit.html Matlab 30 day free trial] and [http://www.mathworks.com/academia/student_version/?s_cid=global_nav student edition]) 
|width="50%"| The AAMToolbox enables the user analyse the shape and colour of collections of similar objects. Originally developed to analyse face shapes for lipreading ([http://ieeexplore.ieee.org/xpl/freeabs_all.jsp?arnumber=982900 Matthews ''et al''. 2002][http://www2.cmp.uea.ac.uk/~sjc/matthews-pami-01.pdf version of pdf]), we have used it extensively for analysing the shapes of leaves ([http://www.pnas.org/content/102/29/10221.short Langlade ''et al'' 2005.],[http://www.tandfonline.com/doi/abs/10.2976/1.2836738 Bensmihen ''et al.'' 2010]) and petals ([http://www.sciencemag.org/content/313/5789/963.short Whibley ''et al'' 2006],[http://www.mssaleshops.info/content/21/10/2999.short Feng ''et al''. 2010]). The analysis can be applied to art, for example, finding systematic differences between portraits by Rembrandt and Modigliani.
|}
==Analysing the shapes of clones: '''SectorAnalysisToolbox'''==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>Sector analysis icon.jpg|120px|SectorAnalysisToolbox</imgicon>
|width="40%"|For analysing the shapes of marked cell clones. 
[[SectorAnalysisToolbox Details|'''What? How? Where?''']] 
[[SectorAnalysisToolbox Documentation|'''''Tutorials''''': from the beginning]] 
[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSourceDownload_Science_Paper_2012/SectorAnalysisToolbox.zip '''''Download''''' ] 
(PC, Mac, Linux, uses Matlab no Mathworks toolboxes needed [http://www.mathworks.com/products/matlab/tryit.html Matlab 30 day free trial] and [http://www.mathworks.com/academia/student_version/?s_cid=global_nav student edition]) 
|width="50%"| The SectorAnalysisToolbox enables the user analyse the shapes of marked clones in a sheet of tissue.
|}

='''Algorithms'''=
==MSERs, extrema, connected-set filters and sieves==
====The algorithm finding MSER's starts with a connected-set opening or 'o' sieve====
[[Comparison of Matlab MSER's and 'o' sieve|Comparison of Matlab MSER's and 'o' sieve]] Essentially, no difference.
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="50%"| [[Image:Cameraman_iso_topview.jpg|300px|link=AAMToolbox Details|MSERs]] Cameraman image. Superimposed red spots are maximal extrema and blue spots are minima. Irregular cyan, blue and yellow regions illustrate regions associated with maxima and the magenta region is a minimum.
|[[Image:cameraman_iso_tree.jpg|300px|link=AAMToolbox Details|MSERs over scale-space]] Isometric view of the cameraman image with superimposed maxima (red) and minima (blue). The trees trace the maxima through increasing scale-space. Large spots have been identified as stable extrema.
|}

===Finding interest points, features and segmenting images. ===
#[[MSER and Sieve Details|'''Technical briefing''']] MSER's incorporate 'o' sieves.
#[[MSER's and Connected sets|'''The twist''': from restricted median filters to sieves and MSER's]]
#One dimensional sieves (measure length)
##[[First applied to hydrophobicity plots|First applied to hydrophobicity plots]] but lets exploit their idempotency.
#Two dimensional sieves (measure areas)
##Properties
##Relation to MSER's
#Three dimensional sieves (measure volumes)
##[[Segment by volume|Segment by volume]] instant gratification.




===Art, extrema of light and shade: '''''PhotoArtMaster'''''===

Art created using ArtMaster, and ArtMaster itself was featured in an exhibit at the London Victoria and Albert (V&A) Museum exhibition 'Cheating? How to make Perfect Work of Art' (2003). The exhibition centered on the idea of [http://en.wikipedia.org/wiki/Hockney%E2%80%93Falco_thesis Hockney's] that advances in realism and accuracy in the history of Western art since the Renaissance were primarily the result of optical aids such as the camera obscura, camera lucida, and curved mirrors. My exhibit used a touch screen (rare in those days) and ArtMaster to help visitors create 'paintings' from photographs. [http://www.sciencemuseum.org.uk/visitmuseum/galleries/turing.aspx finding its name]. (It is entirely different in principle from the software more recently used by Hockney to paint with an iPad.) 

{| border="0" width=100% style="background-color:#ffffff;"
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|align="center"|[[Image:DegasLightAndShade.jpg|400px]][[Image:Emma_face_Art_C.jpg|300px]]
 
Illustration of PhotoArtMaster used to find and 'paint' with regions of light and shade crisply segmented from a photograph. Likewise, on the right, edges.
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=====PhotoArtMaster=====
Saturday 07/06/2014: Inspired Photographer of the Year 2013 Tony Bennett when asked whether his photograph [http://www.bbc.co.uk/programmes/galleries/p020hd8s Mists and Reflections] had been Photoshopped replied something like 
"A digital camera delivers an unemotional ''raw'' image of pixels that you have to manipulate to ''create your photograph''" Photographers manipulate as little as possible. 
However there is '''another path one that creates pictures'''. For this you need another piece of software: PhotoArtMaster (ArtMaster). Professional Photographer said ''"'''Forget any comparison whatsoever with the art filters in Photoshop - this software reaches out and enters different stratospheres'''"'' [[Professional Photographer]]. 
Early versions of PhotoArtMaster are still '''available from Amazon''' at low prices (I'm not sure where they come from.)
[http://www.amazon.co.uk/s/ref=nb_sb_noss?url=search-alias%3Daps&field-keywords=photoartmaster] . Some help for both the early versions and the latest version can be found in [http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/SieveWebPages/a4a_2_screensize.pdf ''''this document''''' ]).
=====Links to third party PhotoArtMastered pictures=====
*[https://picasaweb.google.com/113257474829608374943/InTheStyleOf Oliver Bangham] Colouful rounded shapes from, yes, my brother.
*[http://en.wikipedia.org/wiki/Wimbledon_%28film%29 The entry sequence of the comedy film 'Wimbledon']

====The final version of the Windows ArtMaster2.0 [http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/OpenSource_ArtMaster/ArtMaster2.0Release.zip '''''is downloadable here'''''] with no support.====
Unzip into (for example) the "Program Files" directory then set your system environment to include: ''C:\Program Files\Pam2.0 Release\jre\bin;C:\Program Files\Pam2.0 Release\bin;'' (You may need help for this. I right clicked 'computer' from the 'Start' menu, then selected 'Advanced system settings', then 'Environment Variables' and finally slid through the System variables until I found and selected 'Path'. This allowed me to edit the path by adding ';C:\Program Files\Pam2.0 Release\jre\bin;C:\Program Files\Pam2.0 Release\bin' to the end). Rather detailed help using the software is available in [http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/SieveWebPages/a4a_2_screensize.pdf ''''this essay''''' ]. 
[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/SieveWebPages/Art_For_All_a4a_3_web2.pdf '''''The sieve algorithms underpinning PhotoArtMaster software''''' ] are described in an extract of the
[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/SieveWebPages/a4a_2_screensize.pdf ''''essay''''' ]. These documents were written to support our Fo2Pix company. PhotoArtMaster originally sold >65,000 licences but ill health forced the closure of Fo2Pix.

{| border="0" width=100% style="background-color:#ffffff;"
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|align="center"|[[Image:Trees_1.jpg|600px]]
 
Illustration of PhotoArtMaster used to find and 'paint' with regions of colour crisply segmented from a photograph.
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==Reaction-diffusion and morphogenesis==
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[[Image:tentacles_morphogenesis.png|600px]]
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Illustration of morphogenesis inspired by Turing's paper. 
[http://cmpdartsvr1.cmp.uea.ac.uk/downloads/software/GPT_ReactionDiffusionTentacles_20121211.zip Example using growth toolbox GPT_ReactionDiffusionTentacles_20121211.zip]
 
===1 A===
{| border="0" cellpadding="5" cellspacing="3"
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|width="300pt"|<wikiflv width="300" height="300" logo="false" loop="true" background="white">GPT_rd_rk_tentacles_20120417-0004.flv|GPT_rd_rk_tentacles_20120417-0004_First.png</wikiflv> A simple reaction-diffusion system develops a pattern of spots.
|<wikiflv width="300" height="300" logo="false" loop="true" background="white">GPT_rd_rk_tentacles_20120417-0001.flv|GPT_rd_rk_tentacles_20120417-0004.png</wikiflv>
 Two simple growth rules translate the pattern into directed growth. The changing geometry that arises through growth causes the reaction-diffusion patterning to continue to change. These movies were used in a London Science Museum exhibit in association with a video interview with me.
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=Open source systems to which we have contributed=
==OMERO==
{| border="0" cellpadding="5" cellspacing="5"
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|width="10%"| <imgicon>OMERO_DIAGRAM.jpg|100px|OMERO</imgicon>
|width="40%"|For working with the OME image database. See [http://www.openmicroscopy.org/site/products/omero ''Details''], [http://www.openmicroscopy.org/site/support/omero4/downloads ''Download''] [http://dmbi.nbi.bbsrc.ac.uk/index.php/OMEROWorkshop OMERO Workshop] 
(Windows, Mac, Linux)
|width="50%"| [http://openmicroscopy.org/site/support/omero4 Open Microscopy Environment Remote Objects (OMERO).] for visualising, managing, and annotating scientific image data. See also our [http://dmbi.nbi.bbsrc.ac.uk/index.php/OMEROWorkshop OMERO Workshop] training course we ran in April 2011.
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=Tools and Utilities=
==BioformatsConverter==
{| border="0" cellpadding="5" cellspacing="5"
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|width="10%"| <imgicon>BioformatsConverterZip.png|100px|BioformatsConverter</imgicon>
|width="40%"|For converting microscope manufacturer proprietary file formats. See [[BioformatsConverter|''Details'']] 
(Windows, Mac, Linux)
|width="50%"| This tool allows for the batch conversion of microscope manufacturer proprietary file formats, to the open source OME-TIFF standard. Uses the [http://www.loci.wisc.edu/software/bio-formats Bioformats] library.
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==Dependency Checking Tool==

Tool for recursively finding what further functions a function depends on. See [[myDepFun|''Details'']]

=In development=
==MTtbox==
{| border="0" cellpadding="5" cellspacing="5"
|- valign="top"
|width="10%"| <imgicon>MTtboxA.jpg|100px|BioformatsConverter</imgicon>
|width="40%"|For modelling the behaviour of microtubules within a cell. 
See [[MTtbox documentation|''Details'']] 
(Windows, Mac, Linux)
|width="50%"| In development. The idea is to be able to model the behaviour of growing microtubules and factors as they react chemically and diffuse within the different cell compartments. 
The icon shows a spherical cell sliced open to show concentric components: cell wall (magenta), plasma-membrane (yellow), cytoplasm (green) and vacuole (yellow). Microtubules (blue) grow in 3D within the cytoplasm.
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=Historical=
==Robot arm: still in production after 30 years (serving local industry)==
{| border="0" cellpadding="5" cellspacing="5"
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|width="50%"|[[Image:2014-06-10 14.22.20 small robot.jpg|400px|]]
|width="40%"|For teaching '''production control''' and '''interrupt programming'''. 
1983 and we are in a world of '''Apple II and BBC B computers''' - the ''6502'' processor reigns. Particularly good for real-time control it responded very fast to hardware interrupts from, for example, the timer. To illustrate timer interrupts what better than digital servo-motors? Set up the on-board timers to produce a stream of 'heartbeat' of pulses, one every 20 ms out of the parallel port and control up to eight motors. Pulse widths, from 1 to 2 ms, control the position of each motor arm. Derek Fulton and I made some loose lab. money by writing a series of articles showing exactly how to build and, in particular, control this robot arm.[[Publications#.28G.29_Computer_control.2C_measurement_and_commercial_software |Bangham et al.]].
Our copyright, I took it to a local company LJ-Electronics ([http://www.ljcreate.com/products/product.asp?id=314&program=195&curr=2 now LJ-Creative]) who incorporated it detail for detail into their product line. Originally, they called it the Emu. Still in production: '''Lovely outcome.'''
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=Historical=