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Velocity_Step4_Radon.m
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Velocity_Step4_Radon.m
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% Velocity_Step4_Radon
% Author: Aby Joseph, University of Rochester
% License: GPL-3.0-or-later
% Last modified: 01-24-2019
clear;close all;
f_No=0;
fontsize1=18;
% Variables typically not changed
moveFileAfterProcessing=1;
shuffleON=0; % toggle button for subtracting "shuffled" radon-variance from original radon to improve slope detection
calculateSNR1=1; % Recommended value=1. Switch to 0 if you want to speed up computation
includeOtherQuadrantON=1; % includes the entire 180 degress in the radon angle search space. The density of angles in quadrant without streaks is set low (typically 1 degree step size).
circularMaskingON=1;
radonClippingON=0;
radonMode=2; % Mode #1 - "peak variance of radon" approach. Mode #2 - "peak intensity of radon" approach.
featureDetectionON=0; % if OFF, conventional array of equal sized kernels will be used
findQuadrant=0;
% Variables typically changed
videoDurationToAnalyze_Step4=1; % in seconds
fractionalOverlapTime=1; % If equal to 4, 75% overlap in gliding boxes. If equal to 2, 50% overlap etc. Must be integer.
fractionalOverlapSpace=1;
dxMicrons=30; % in microns % REVISIT
nShuffles=3;
% quadrant=1;
Vmin=0; % in mm/s
Vmax=100; % in mm/s
Step5folder='E:\PhD\TRBF\Experimental DATA\Step 5 MAT files\';
Step4folder='E:\PhD\TRBF\Experimental DATA\Step 4 MAT files\';
Step3folder='E:\PhD\TRBF\Experimental DATA\Step 3 MAT files\';
Step2folder_Processed='E:\PhD\TRBF\Experimental DATA\Step 2 MAT files\PROCESSED\';
RawDir_Processed='E:\PhD\TRBF\Experimental DATA\RAW MAT files\PROCESSED\';
cd(Step3folder);
% Append current date and time to filenames of results
currentDateAndTime=clock;
year=num2str(currentDateAndTime(1));
month=num2str(currentDateAndTime(2),'%02d');
day=num2str(currentDateAndTime(3),'%02d');
hour=num2str(currentDateAndTime(4),'%02d');
minute=num2str(currentDateAndTime(5),'%02d');
appendToResults=['_',year,month,day,hour,minute];
namecontains='*_Step3*.mat*';
[dirFilenames(1).name,filePath,~]=uigetfile(namecontains,...
'Select file to process - click cancel to process all files in parent folder');
if filePath==0
dirFilenames=dir([namecontains]);
nFiles=numel(dirFilenames);
processDir=Step3folder;
else
processDir=[filePath];
nFiles=1;
end
screenSize=get(0, 'MonitorPositions');
cd(processDir);
for fileNo=1:nFiles
tic;
f_No=0;
fileName=dirFilenames(fileNo).name;
display(fileName);
% Loading RAW.mat
namecontains2=[fileName(1:25),'*RAW*.mat'];
dirFilenames2=dir([RawDir_Processed,namecontains2]);
nFiles2=numel(dirFilenames2);
if nFiles2==1
load([RawDir_Processed,dirFilenames2(1).name],'desinusoidON','postFPGA',...
'linescanDir','nFrames','height','width','FOV',...
'mic_pix','freq');
else
[RawFileName,RawFilePath,~]=uigetfile([RawDir_Processed,...
namecontains2],'Select RAW MAT file');
load([RawFilePath,RawFileName],'desinusoidON','postFPGA',...
'linescanDir','nFrames','height','width','FOV',...
'mic_pix','freq');
end
% Loading Step2.mat
namecontains3=[fileName(1:25),'*Step2*.mat'];
dirFilenames3=dir([Step2folder_Processed,namecontains3]);
nFiles3=numel(dirFilenames3);
if nFiles3==1
load([Step2folder_Processed,dirFilenames3(1).name],...
'insertNaNsWhenPoorRegistration',...
'crossCorrelationCoeffcientThreshold','referenceLine',...
'timeWindowAveraging','sizeStripRegistration',...
'dataRegisteredWithStaticLines','line_avg0','line_std0',...
'line_avg1','line_std1','timeAxisForMotionTrace','motionTrace',...
'data','analysisBoundaries','videoDurationToAnalyze_Step2','quadrant');
else
[Step2FileName,Step2FilePath,~]=uigetfile([Step2folder_Processed,...
namecontains3],'Select Step2 MAT file');
load([Step2FilePath,Step2FileName],'insertNaNsWhenPoorRegistration',...
'crossCorrelationCoeffcientThreshold','referenceLine',...
'timeWindowAveraging','sizeStripRegistration',...
'dataRegisteredWithStaticLines','line_avg0','line_std0',...
'line_avg1','line_std1','timeAxisForMotionTrace','motionTrace',...
'data','analysisBoundaries','videoDurationToAnalyze_Step2','quadrant');
end
% Loading Step3.mat
load([processDir,fileName],'vesselAngle');
if isnan(videoDurationToAnalyze_Step4)
videoDurationToAnalyze_Step4=size(data,2)/freq;
end
data=data(:,1:floor(freq*videoDurationToAnalyze_Step4));
data=single(data);
data=data./255;
dataWidth_Step4=size(data,2);
dataHeight_Step4=size(data,1);
NANthreshold=100; % Maximum allowed percetage occurrance of NaNs along the time dimension for a given radial coordinate to be considered to be inside the vessel lumen.
dx=round(dxMicrons/mic_pix); %kernel size in pixels
dx=dx+(1-mod(dx,2));
d=(dx-1)/2; % defines half-length of lines overlayed in space-time image (to visualize calculated slopes)
dtStep=round((dx-1)/fractionalOverlapTime);
dtStepSeconds=dtStep./freq;
maxExpectedHeartRate=400; % in beats per minute. For anesthetized mouse
measuredSamplesPerCardiacCycle=round((1/(maxExpectedHeartRate/60))/...
dtStepSeconds);
dxStep=round((dx-1)/fractionalOverlapSpace);
dxStepMicrons=dxStep*mic_pix;
nShufflesQD=3;
% creating circular mask
mask=zeros(dx);
for k=1:dx
for m=1:dx
if (sqrt((k-0.5-dx/2)^2+(m-0.5-dx/2)^2)<=dx/2)
mask(k,m)=1;
end
end
end
if circularMaskingON==0
mask=ones(dx);
end
%Quadrant determination (QD) for Radon angle search space --> quadrant=1 for 0 to 90 degrees in Radon space, quadrant=2 for 90 to 180 degrees in Radon space (follow MATLAB convention for Radon angles)
anglesQD=0:179;
kernelQD=data(analysisBoundaries(1):analysisBoundaries(2),1:1+...
diff(analysisBoundaries)); % diff(analysisBoundaries) forced to be even number in Step 3, such that kernelQD has odd number of rows and columns
kernelSquareQD=kernelQD;
dxQD=size(kernelQD,1);
maskQD=zeros(size(kernelQD,1),size(kernelQD,2));
for k=1:dxQD
for m=1:dxQD
if (sqrt((k-0.5-dxQD/2)^2+(m-0.5-dxQD/2)^2)<=dxQD/2)
maskQD(k,m)=1;
end
end
end
if circularMaskingON==0
maskQD=ones(dxQD);
end
if gaussianWindowingON==0
kernelQD=kernelQD.*maskQD;
else
gaussianSigmaQD=floor((dxQD-1)/4); %sigma of gaussian filter calculated such that when filter size is chosen to be exactly equal to kernel size, the relation "FilterSize=2*ceil(2*SIGMA)+1" approximately holds
hQD=fspecial('gaussian',dxQD,gaussianSigmaQD);
kernelQD=kernelQD.*hQD;
kernelQD=kernelQD-min(kernelQD(:));
kernelQD=kernelQD./max(kernelQD(:));
end
[rQD,xpQD]=radon(kernelQD,anglesQD);
stddevQD=std(rQD,0,1);
stddevShuffledQD=zeros(size(stddevQD));
for k=1:nShufflesQD
shuffledIndices=randperm(size(kernelQD,1));
kernelSquareShuffledQD=kernelSquareQD(:,shuffledIndices);
if gaussianWindowingON==0
kernelShuffledQD=kernelSquareShuffledQD.*maskQD;
else
kernelShuffledQD=kernelSquareShuffledQD.*hQD;
kernelShuffledQD=kernelShuffledQD-min(kernelShuffledQD(:));
kernelShuffledQD=kernelShuffledQD./max(kernelShuffledQD(:));
end
rShuffledQD=radon(kernelShuffledQD,anglesQD);
stddevShuffledQD=std(rShuffledQD,0,1)+stddevShuffledQD;
end
stddevShuffledQD=stddevShuffledQD./nShufflesQD;
stddevCleanQD=stddevQD-stddevShuffledQD;
stddevCleanQD_display=stddevCleanQD;
stddevCleanQD=stddevCleanQD-min(stddevCleanQD(:));
stddevCleanQD=stddevCleanQD./max(stddevCleanQD(:));
[~,locsClean]=findpeaks(stddevCleanQD,'SortStr','descend','NPeaks',1);
SNR_QD=stddevCleanQD(locsClean)./mean(stddevCleanQD(:));
thetaQD_Variance=anglesQD(locsClean(1));
[rQDMax,I]=max(rQD(:));
[I_row,I_col]=ind2sub(size(rQD),I);
thetaQD_Intensity=anglesQD(I_col);
if findQuadrant==1
if thetaQD_Variance<=90
quadrant=1;
else
quadrant=2;
end
end
if gaussianWindowingON==1
figure(4);imagesc(hQD);
end
% determining angles for radon transform
V_max_calculation_pixels=abs(cotd(thetaQD_Variance))*(1/...
abs(cosd(vesselAngle))); %Vx in pixel space
V_max_calculation=V_max_calculation_pixels*(1e-3)*mic_pix*freq; %Vx in mm/s
Vstep=1; % in mm/s
Vees=fliplr(Vmin:Vstep:Vmax);
nVees=numel(Vees);
if Vmin==0
angles=zeros(1,2*nVees-1);
Vees_display=zeros(1,2*nVees-1);
else
angles=zeros(1,2*nVees);
Vees_display=zeros(1,2*nVees);
end
angles(1:nVees)=acotd(Vees*(1e3)*abs(cosd(vesselAngle))/(mic_pix*freq)); % angles in degrees
Vees_display(1:nVees)=-1*Vees;
anglesComp=fliplr(180-angles(1:nVees));
if Vmin==0
angles(nVees:end)=anglesComp;
Vees_display(nVees:end)=fliplr(Vees);
else
angles(nVees+1:end)=anglesComp;
Vees_display(nVees+1:end)=fliplr(Vees);
end
anglesFullRange=angles;
if quadrant==1
angles=anglesFullRange(anglesFullRange<=90);
if includeOtherQuadrantON==1
angles=[angles 91:179];
end
else
angles=anglesFullRange(anglesFullRange>=90);
if includeOtherQuadrantON==1
angles=[1:89 angles];
end
end
anglesLinearlySpaced=linspace(angles(1),angles(end),numel(angles));
centAxis=round(mean(analysisBoundaries)); %REVISIT
ndt=round((dataWidth_Step4-dx+1)/dtStep);
ndx1=floor(min([centAxis-analysisBoundaries(1) centAxis-dx/2])/dxStep);
ndx2=floor(min([analysisBoundaries(2)-centAxis dataHeight_Step4-...
centAxis-dx/2])/dxStep);
ndx=2*min([ndx1 ndx2])+1;
theta_max90=zeros(ndx*ndt,1);
if featureDetectionON==0
theta_maxClean=NaN(ndx*ndt,1);
end
reachedEndT=0;
kernelStartT=1;
t=0;
kernelStartXfirst=round(centAxis-((ndx-1)/2)*dxStep-(dx-1)/2);
pos90=find(abs(angles-90)<0.001);
centerOfKernel=NaN(ndx*ndt,2);
hWaitbar1=waitbar(0,'Radon 0 % Completed');
kernelCounter1=0;
kernelCounter2=0;
if featureDetectionON==0
stddev=NaN(ndx*ndt,size(angles,2));
end
% Optional Vanzetta's Gaussian filtering technique (NOT CURRENTLY USED)
gaussianSigma=floor((dx-1)/4); %sigma of gaussian filter calculated such that when filter size is chosen to be exactly equal to kernel size, the relation "FilterSize=2*ceil(2*SIGMA)+1" approximately holds
h=fspecial('gaussian',dx,gaussianSigma);
% Initialising parameters for creating space-time image with overlaid slope information
if featureDetectionON==0
SNRofEachKernel_Mode1=NaN(ndx*ndt,1);
lineXYCoordinates=NaN(ndt*ndx,4);
end
if featureDetectionON==0
for t_counter=1:ndt
kernelStartX=kernelStartXfirst;
for x_counter=1:ndx
waitbar(((t_counter-1)*ndx+x_counter)/(ndt*ndx),hWaitbar1,...
['Radon ',...
num2str(single(100*((t_counter-1)*ndx+x_counter)/...
(ndt*ndx)),'%.0f'),' % completed']);
kernel=data(kernelStartX:kernelStartX+dx-1,...
kernelStartT:kernelStartT+dx-1);
kernelCounter1=kernelCounter1+1;
if prod(prod(~isnan(kernel)))~=0
kernelCounter2=kernelCounter2+1;
centerOfKernel(kernelCounter1,:)=[kernelStartX+dx/2 ...
kernelStartT+dx/2];
kernelSquare=kernel;
if gaussianWindowingON==0
kernel=kernel.*mask;
else
kernel=kernel.*h;
end
[r,xp]=radon(kernel,angles);
if kernelCounter2==1
if radonClippingON==1
rStart=(size(r,1)+1)/2-(dx+1)/2;
rEnd=(size(r,1)+1)/2+(dx+1)/2;
else
if radonClippingON==0
rStart=1;
rEnd=size(r,1);
end
end
end
r=r(rStart:rEnd,:);
xp=xp(rStart:rEnd);
if radonMode==1
stddev(kernelCounter1,:)=std(r,0,1);
% Shuffling
if shuffleON==1
stddevShuffled=zeros(size(stddev(kernelCounter1,:)));
for k=1:1
shuffledIndices=randperm(dx);
kernelShuffled=kernelSquare(:,shuffledIndices);
if gaussianWindowingON==0
kernelShuffled=kernelShuffled.*mask;
else
kernelShuffled=kernelShuffled.*h;
end
rShuffled=radon(kernelShuffled,angles);
rShuffled=rShuffled(rStart:rEnd,:);
stddevShuffled=std(rShuffled,0,1)+stddevShuffled;
end
stddevShuffled=stddevShuffled./1;
stddev(kernelCounter1,:)=stddev(kernelCounter1,...
:)-stddevShuffled;
end
% normalizing
stddevTEMP=stddev(kernelCounter1,:);
stddevTEMP=stddevTEMP-min(stddevTEMP(:));
stddevTEMP=stddevTEMP./max(stddevTEMP(:));
stddev(kernelCounter1,:)=stddevTEMP;
% SNR calculation only if peak intensity of Radon
% is used to define SNR. If peak variance is used
% instead, the calulation of the same is done later
% (~58 lines of code later)
else
if radonMode==2
[rMax,I]=max(r(:));
[I_row,I_col]=ind2sub(size(r),I);
theta_maxClean(kernelCounter1)=angles(I_col);
rInterpolated=interp2(angles,xp,r,...
anglesLinearlySpaced,xp);
rMean=mean(rInterpolated(:));
m2=tand(theta_maxClean(kernelCounter1)+90);
if m2==Inf
lineXYCoordinates(kernelCounter1,:)=...
[centerOfKernel(kernelCounter1,2) ...
centerOfKernel(kernelCounter1,1)+d ...
centerOfKernel(kernelCounter1,2) ...
centerOfKernel(kernelCounter1,1)-d];
else
lineXYCoordinates(kernelCounter1,:)=...
[centerOfKernel(kernelCounter1,2)-...
d/sqrt(1+m2^2) centerOfKernel(kernelCounter1,...
1)+m2*d/sqrt(1+m2^2) centerOfKernel(...
kernelCounter1,2)+d/sqrt(1+m2^2) ...
centerOfKernel(kernelCounter1,1)-...
m2*d/sqrt(1+m2^2)];
end
end
end
kernelStartX=kernelStartX+dxStep;
end
end
kernelStartT=kernelStartT+dtStep;
end
% Excluding array values which are NaN. Array values could be NaN at
% this stage if image has NaNs in it (inserted during registration)
arbitrary1D=centerOfKernel(:,2); % to get a 1D array
percentKernelsProcessedStage1=sum(isfinite(arbitrary1D))./...
numel(arbitrary1D);
centerOfKernel(isnan(arbitrary1D),:)=[];
stddev(isnan(arbitrary1D),:)=[];
lineXYCoordinates(isnan(arbitrary1D),:)=[];
theta_maxClean(isnan(arbitrary1D),:)=[];
SNRofEachKernel_Mode1(isnan(arbitrary1D),:)=[];
originalXYgrid=centerOfKernel;
totalKernels=kernelCounter2;
if radonMode==1
hWaitbar2=waitbar(0,'FindPeaks 0 % Completed');
end
cmap=colormap(jet);
close;
kernelCounter2=0;
x=centerOfKernel(:,2);
y=centerOfKernel(:,1);
if radonMode==1
for kernelCounter2=1:size(SNRofEachKernel_Mode1,1)
stddevTEMP=stddev(kernelCounter2,:)';
stddevInterpolated=interp1(angles,stddevTEMP,...
anglesLinearlySpaced);
[~,locsClean]=findpeaks(stddevTEMP,'SortStr','descend',...
'NPeaks',1);
if numel(locsClean)~=0
theta_maxClean(kernelCounter2)=angles(locsClean);
if calculateSNR1==1
SNRofEachKernel_Mode1(kernelCounter2)=stddevTEMP(...
locsClean)/mean(stddevInterpolated(:));
end
m=tand(theta_maxClean(kernelCounter2)+90);
lineXYCoordinates(kernelCounter2,:)=[x(kernelCounter2)-...
d/sqrt(1+m^2)...
y(kernelCounter2)+m*d/sqrt(1+m^2) ...
x(kernelCounter2)+d/sqrt(1+m^2) ...
y(kernelCounter2)-m*d/sqrt(1+m^2)];
end
waitbar(kernelCounter2/size(SNRofEachKernel_Mode1,1),...
hWaitbar2,['FindPeaks ',...
num2str(single(100*(kernelCounter2/size(...
SNRofEachKernel_Mode1,1))),'%.0f'),' % completed']);
end
end
% Excluding theta_maxClean values which are NaN. theta_maxClean could be NaN at
% this stage if findpeaks did not find any peak in stddev
percentKernelsProcessedStage2=sum(isfinite(theta_maxClean))./...
numel(theta_maxClean);
centerOfKernel(isnan(theta_maxClean),:)=[];
x(isnan(theta_maxClean),:)=[];
y(isnan(theta_maxClean),:)=[];
stddev(isnan(theta_maxClean),:)=[];
lineXYCoordinates(isnan(theta_maxClean),:)=[];
SNRofEachKernel_Mode1(isnan(theta_maxClean),:)=[];
theta_maxClean(isnan(theta_maxClean),:)=[];
end
clear data dataRegisteredWithStaticLines stddev;
close(hWaitbar1);
if radonMode==1
close(hWaitbar2);
end
% Saving copy of code (added 06-04-2018, 1.17 pm)
codeFileFullPath=mfilename('fullpath'); %does not store .m extension
[codeFilePath,codeFileName,~]=fileparts(codeFileFullPath);
newCodeFileName=['code_',fileName(1:25),'_Step4',appendToResults];
codeSource=[codeFilePath,'\',codeFileName,'.m'];
codeDestination=[Step5folder,newCodeFileName,'.m'];
copyfile(codeSource,codeDestination);
currentFolder=cd(Step4folder);
save([fileName(1:25),'_Step4',appendToResults]);
cd(currentFolder);
% moving processed file to separate folder
if moveFileAfterProcessing==1
movefile([processDir,fileName],[processDir,'PROCESSED\',fileName]);
end
elapsedTime=toc;disp(['Elapsed time is ',num2str(elapsedTime/60),' minutes.']);
end
beep