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Commit 5bff4fd4 authored by vpustova's avatar vpustova
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Update 94 files 

- /InVivoTours/Result/RSULM_MatOutTours10_Gridding.mat
- /InVivoTours/Result/RSULM_MatOutTours10.tif
- /InVivoTours/Result/SRPCA_MatOutTours10.tif
- /InVivoTours/Result/SRPCA_MatOutTours4.mat
- /InVivoTours/Result/SRPCA_MatOutTours10_Gridding.mat
- /InVivoTours/Result/RSULM_MatOutTours10.mat
- /InVivoTours/Result/SRPCANonInterpTracks.mat
- /InVivoTours/Result/SRPCA_MatOutTours10.mat
- /InVivoTours/Result/MatTracks/MatTracking1.mat
- /InVivoTours/Result/MatTracks/MatTracking10.mat
- /InVivoTours/Result/MatTracks/MatTracking11.mat
- /InVivoTours/Result/MatTracks/MatTracking12.mat
- /InVivoTours/Result/MatTracks/MatTracking13.mat
- /InVivoTours/Result/MatTracks/MatTracking14.mat
- /InVivoTours/Result/MatTracks/MatTracking15.mat
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- /InVivoTours/Result/MatTracks/MatTracking17.mat
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- /InVivoTours/Result/MatTracks/MatTracking2.mat
- /InVivoTours/Result/MatTracks/MatTracking20.mat
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- /InVivoTours/Result/MatTracks/MatTracking59.mat
- /InVivoTours/Result/MatTracks/MatTracking6.mat
- /InVivoTours/Result/MatTracks/MatTracking60.mat
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- /InVivoTours/Result/MatTracks/MatTracking61.mat
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- /InVivoTours/Result/MatTracks/MatTracking65.mat
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- /InVivoTours/Result/MatTracks/MatTracking69.mat
- /InVivoTours/Result/MatTracks/MatTracking7.mat
- /InVivoTours/Result/MatTracks/MatTracking70.mat
- /InVivoTours/Result/MatTracks/MatTracking71.mat
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- /InVivoTours/Result/MatTracks/MatTracking73.mat
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- /InVivoTours/Result/MatTracks/MatTracking75.mat
- /InVivoTours/Result/MatTracks/MatTracking76.mat
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- /InVivoTours/Result/MatTracks/MatTracking79.mat
- /InVivoTours/Result/MatTracks/MatTracking8.mat
- /InVivoTours/Result/MatTracks/MatTracking80.mat
- /InVivoTours/Result/MatTracks/MatTracking9.mat
- /InVivoTours/Fig6ac_InVivoTours_RSULM.m
- /InVivoTours/Fig6db_InVivoTours_SRPCA.m
- /InVivoTours/psf10Tours.mat
- /InVivoTours/psfSR4_Tours.mat
- /InVivoTours/SRPCATours.m
- /InVivoTours/ULM_localization2DSR_Tours.m
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%% InVivoTours_RSULM.m
%
%
% Based on the code created by Arthur Chavignon
% Adapted for the WKY in vivo data.
%
% DATE 2020.12.17 - VERSION 1.1
% AUTHORS: Arthur Chavignon, Baptiste Heiles, Vincent Hingot. CNRS, Sorbonne Universite, INSERM.
% Laboratoire d'Imagerie Biomedicale, Team PPM. 15 rue de l'Ecole de Medecine, 75006, Paris
% Code Available under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (see https://creativecommons.org/licenses/by-nc-sa/4.0/)
% ACADEMIC REFERENCES TO BE CITED
% Details of the code in the article by Heiles, Chavignon, Hingot, Lopez, Teston and Couture.
% Performance benchmarking of microbubble-localization algorithms for ultrasound localization microscopy, Nature Biomedical Engineering, 2021.
% General description of super-resolution in: Couture et al., Ultrasound localization microscopy and super-resolution: A state of the art, IEEE UFFC 2018
clear
%cd ./..
PALA_folder = fileparts(pwd); % location of the PALA folder
PALA_data_folder = fullfile(PALA_folder, 'PALA_data_folder');
% DEFINE THE ADDONS DIRECTORY ON YOUR COMPUTER
addpath(genpath(fullfile(PALA_folder, 'PALA_addons')));
%% Adapt parameters to your data
% A few parameters must be provided by the user depending of your input images (size of pixel, wavelength)
% These parameters will be copied and used later during the creation of the ULM structure.
% in this example, UF.TwFreq = 15MHz, UF.FrameRateUF = 1000Hz;
UF.TwFreq = 14.8;
UF.FrameRateUF = 1000;
% Here you put the size of your data
SizeOfBloc = [160 128 500];
% Here you put the size of pixel in the prefered unit. It can be um, mm, m, wavelength, or an arbitrary scale.
ScaleOfPixel = [1 1]; % [pixel_size_z, pixel_size_x]
% In that example, the size of pixels is lambda x lambda. The localization process will be
% performs in wavelength. For velocity rendering, velocities in [wavelength/s] will be converted in [mm/s].
% The imaging frame rate is required for velocity calculation, and temporal filtering.
framerate = 1000; % imaging framerate in [Hz]
% Number of blocs to process
Nbuffers = 80; % number of bloc to process (used in the parfor)
% If pixel sizes are in wavelength, lambda must be provided for a velocity maps in mm/s,
lambda = 1480/(UF.TwFreq*1e3);
%% ULM parameters
% this script can be run using different scaling, it can be wavelength, pixel size, mm, um.
% In this example, input pixel are isotropic and equal to lambda (pixelPitch_x = pixelPitch_y = lambda)
% All size defined later are expressed in lambda
res = 10; % final ratio of localization rendering, it's approximately resolution factor of localization in scale(1) units.
% for a pixel size of 100um, we can assume that ULM algorithm provides precision 10 (res) times
% smaller than pixel size. Final rendering will be reconstructed on a 10x10um grid.
ULM = struct('numberOfParticles', 90,... % Number of particles per frame. (30-100)
'size',[SizeOfBloc(1) SizeOfBloc(2) SizeOfBloc(3)],... % size of input data [nb_pixel_z nb_pixel_x nb_frame_per_bloc]
'scale',[ScaleOfPixel 1/framerate],...% Scale [z x dt], size of pixel in the scaling unit. (here, pixsize = 1*lambda)
'res',res,... % Resolution factor. Typically 10 for final image rendering at lambda/10.
'SVD_cutoff',[5 SizeOfBloc(3)],... % SVD filtering, to be adapted to your clutter/SNR levels
'max_linking_distance',2,... % Maximum linking distance between two frames to reject pairing, in pixels units (UF.scale(1)). (2-4 pixel).
'min_length', 15,... % Minimum allowed length of the tracks in time. (5-20 frames)
'fwhm',[1 1]*3,... % Size [pixel] of the mask for localization. (3x3 for pixel at lambda, 5x5 at lambda/2). [fmwhz fmwhx]
'max_gap_closing', 0,... % Allowed gap in microbubbles' pairing. (if you want to skip frames 0)
'interp_factor',1/res,... % Interpfactor (decimation of tracks)
'LocMethod','Radial'... % Select localization algorithm (WA,Interp,Radial,CurveFitting,NoLocalization)
);
ULM.ButterCuttofFreq = [50 249]; % Cutoff frequency (Hz) for additional filter. Typically [20 300] at 1kHz.
ULM.parameters.NLocalMax = 3; % Safeguard on the number of maxLocal in the fwhm*fwhm grid (3 for fwhm=3, 7 for fwhm=5)
[but_b,but_a] = butter(2,ULM.ButterCuttofFreq/(framerate/2),'bandpass');
ULM.lambda = lambda;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Load data and localize microbubbles %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Track_tot = {};
fprintf('--- ULM PROCESSING --- \n\n');t1=tic;
for hhh = 1:Nbuffers
fprintf('Processing bloc %d/%d\n',hhh,Nbuffers);
% Load IQ data
tmp = load(strcat(PALA_data_folder,'/IQTours/IQTours_',int2str(hhh),'.mat'),'IQ');
tmp.IQ = tmp.IQ(5:164,:,:);
% Filtering of IQ to remove clutter (optional)
IQ_filt = SVDfilter(tmp.IQ,ULM.SVD_cutoff);tmp = [];
% Temporal filtering
IQ_filt = filter(but_b,but_a,IQ_filt,[],3); %(optional)
IQ_filt(~isfinite(IQ_filt))=0;
% Detection and localization process (return a list of coordinates in pixel)
[MatTracking] = ULM_localization2D(abs(IQ_filt),ULM); IQ_filt=[];
% Convert pixel into isogrid (pixel are not necessary isometric);
MatTracking(:,2:3) = (MatTracking(:,2:3) - [1 1]).*ULM.scale(1:2);
% Tracking algorithm (list of tracks)
Track_tot_i = ULM_tracking2D(MatTracking,ULM);
Track_tot{hhh} = Track_tot_i;
Track_tot_i={};MatTracking = [];
end
Track_tot = cat(1,Track_tot{:});
Tend = toc(t1);disp('Done')
fprintf('ULM done in %d hours %.1f minutes.\n', floor(Tend/60/60), rem(Tend/60,60));
%% Create individual variable to save using v6 version.
% By cutting Tracks into different variables small than 2GB, the save v6 is faster than save v7.3
% CutTracks = round(linspace(1,numel(Track_tot),4));
% Track_tot_1 = Track_tot(CutTracks(1):CutTracks(2)-1);
% Track_tot_2 = Track_tot(CutTracks(2):CutTracks(3)-1);
% Track_tot_3 = Track_tot(CutTracks(3):end);
% save(['example_tracks.mat'],'Track_tot_1','Track_tot_2','Track_tot_3','Tend','ULM','-v6')
% clear Track_tot_1 Track_tot_2 Track_tot_3
% load([workingdir filesep filename 'example_tracks.mat'])
% Track_tot = cat(1,Track_tot_1,Track_tot_2,Track_tot_3);clear Track_tot_1 Track_tot_2 Track_tot_3
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Create MatOut %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% create the MatOut density with interpolated tracks for visual analysis, and with non interpolated tracks for aliasing index calculation.
% Define the size of SRpixel for displaying (default 10)
ULM.SRscale = ULM.scale(1)/ULM.res;
ULM.SRsize = round(ULM.size(1:2).*ULM.scale(1:2)/ULM.SRscale);
% Convert tracks into SRpixel
Track_matout = cellfun(@(x) (x(:,[1 2 3 4])+[1 1 0 0]*1)./[ULM.SRscale ULM.SRscale 1 1],Track_tot,'UniformOutput',0);
llz = [0:ULM.SRsize(1)]*ULM.SRscale;llx = [0:ULM.SRsize(2)]*ULM.SRscale;
%% Accumulate tracks on the final MatOut grid.
% fprintf('--- CREATING MATOUTS --- \n\n')
MatOut = ULM_Track2MatOut(Track_matout,ULM.SRsize+[1 1]*1); %pos in superpix [z x]
MatOut_zdir = ULM_Track2MatOut(Track_matout,ULM.SRsize+[1 1]*1,'mode','2D_vel_z'); %pos in superpix [z x]
MatOut_vel = ULM_Track2MatOut(Track_matout,ULM.SRsize+[1 1]*1,'mode','2D_velnorm'); %pos in superpix [z x]
MatOut_vel = MatOut_vel*ULM.lambda; % Convert into [mm/s]
save(strcat(pwd,'/Result/RSULM_MatOutTours10.mat'),'MatOut','MatOut_zdir','MatOut_vel','ULM','lambda','llx','llz')
%% Figures
ULM.SRscale=0.625/ULM.res; %for velocity maps in mm/s and scale-bars
maxSRPCA = 64;
IntPower = 1/2.3;
cmin = min(MatOut(:).^IntPower);
cmax = max(MatOut(:).^IntPower);
numTicks = 7; % Adjust as needed
h1=figure('WindowState', 'maximized');
im=imagesc((MatOut).^IntPower);
axis image
colormap hot
clbar = colorbar;
set(clbar, 'YTick', linspace(cmin, cmax, numTicks));
clbar.Label.String = 'Normalized localization density';
%clbar.TickLabels = clbar.Ticks.^2.3; %Not normalized
clbar.TickLabels = round(clbar.Ticks.^2.3 ./ maxSRPCA, 2);
set(gca,'XColor', 'none','YColor','none')
set(gca, 'color', 'none');
BarWidth = round(1./(ULM.SRscale*lambda)); % 1 mm
im.CData(size(MatOut,1)-50+[0:2],60+[0:BarWidth])=max(clim);
text(60+BarWidth/2, size(MatOut,1)-50+3 +15, '1 mm', ...
'Color', 'w', 'FontSize', 12, 'FontWeight', 'bold', ...
'HorizontalAlignment', 'center');
% Smaller Colorbar
% If there is a display issue, try executing the code below separately
% after you created the figure h1 as it depends on your screen size
% x1=get(gca,'position');
% x=get(clbar,'Position');
% x(1)=x(1)-0.003;
% x(3)=0.005;
% set(clbar,'Position',x)
% set(gca,'position',x1)
% clbar.Label.Position = [x(1)+2.5, x(2)+clbar.Ticks(end)/2, x(3)];
%%
IntPower = 1/2.3;
OriginalData = MatOut.^IntPower.*sign(imgaussfilt(MatOut_zdir,.8));
cmin = min(OriginalData(:));
cmax = max(OriginalData(:));
clear OriginalData;
numTicks = 9; % Adjust as needed
figure('WindowState', 'maximized');
velColormap = cat(1,flip(flip(hot(128),1),2),hot(128));
velColormap = velColormap(5:end-5,:);
im=imagesc(llx,llz,(MatOut).^IntPower.*sign(imgaussfilt(MatOut_zdir,.8)))
im.CData = im.CData - sign(im.CData)/2;axis image
colormap(gca,velColormap)
clbar = colorbar;
set(clbar, 'YTick', linspace(cmin*0.90, cmax*0.90, numTicks));
clbar.Label.String = 'Normalized localization density';
clbar.Ticks = clbar.Ticks;%customTicks;
TempTickLabels = round(sign(clbar.Ticks).*abs(clbar.Ticks/0.90).^2.3);
clbar.TickLabels = round(TempTickLabels ./ maxSRPCA,2);
set(gca,'XColor', 'none','YColor','none')
set(gca, 'color', 'none');
caxis([-1 1]*max(caxis)*.75)
BarWidth = round(1./(ULM.SRscale*lambda)); % 1 mm
im.CData(size(MatOut,1)-50+[0:3],60+[0:BarWidth])=max(caxis);
% Smaller Colorbar
% If there is a display issue, try executing the code below separately
% after you created the figure h1 as it depends on your screen size
% x1=get(gca,'position');
% x=get(clbar,'Position');
% x(1)=x(1)-0.003;
% x(3)=0.005;
% set(clbar,'Position',x)
% set(gca,'position',x1)
% clbar.Label.Position = [x(1)+2.5, x(2), x(3)];
%%
%vmax_disp = ceil(quantile(MatOut_vel(abs(MatOut_vel)>0),.98)/10)*10;
vmax_disp = 80;
h1=figure('WindowState', 'maximized'); clf,set(gcf,'Position',[652 393 941 585]);
clbsize = [180,50];
Mvel_rgb = MatOut_vel/vmax_disp; % normalization
% Mvel_rgb(1:clbsize(1),1:clbsize(2)) = repmat(linspace(1,0,clbsize(1))',1,clbsize(2)); % add velocity colorbar
Mvel_rgb = Mvel_rgb.^(1/2);Mvel_rgb(Mvel_rgb>1)=1;
Mvel_rgb = imgaussfilt(Mvel_rgb,.5);
Mvel_rgb = ind2rgb(round(Mvel_rgb*256),jet(256)); % convert ind into RGB
IntPower = 1/2.3;
MatShadow = MatOut;MatShadow = MatShadow./max(MatShadow(:)*.3);MatShadow(MatShadow>1)=1;
%MatShadow(1:clbsize(1),1:clbsize(2))=repmat(linspace(0,1,clbsize(2)),clbsize(1),1);
Mvel_rgb = Mvel_rgb.*(MatShadow.^IntPower);
Mvel_rgb = brighten(Mvel_rgb,.4);
im=imshow(Mvel_rgb,'XData',llx,'YData',llz);axis on
BarWidth = round(1./(ULM.SRscale*lambda)); % 1 mm
im.CData(size(MatOut,1)-50+[0:3],60+[0:BarWidth],1:3)=1;
set(gca,'XColor', 'none','YColor','none')
set(gca, 'color', 'none');
colormap(jet);
clbar = colorbar;
clim([0 vmax_disp]);
clbar.Label.String = 'Velocity magnitude (mm/s)';
% Smaller Colorbar
% If there is a display issue, try executing the code below separately
% after you created the figure h1 as it depends on your screen size
% x1=get(gca,'position');
% x=get(clbar,'Position');
% x(1)=x(1)-0.003;
% x(3)=0.005;
% set(clbar,'Position',x)
% set(gca,'position',x1)
% clbar.Label.Position = [x(1)+2.5, x(2)+clbar.Ticks(end)/2, x(3)];
%% Metrics
% Saturation Value
% load(strcat(pwd,'/Result/RSULM_MatOutTours10.mat'),'MatOut')
Saturation = nnz(MatOut()>0)/numel(MatOut());
% CR
% load(strcat(pwd,'/Result/RSULM_MatOutTours10.mat'),'MatOut')
CR = ContrastRatio(MatOut);
% Image for FRC estimation
% load(strcat(pwd,'/Result/RSULM_MatOutTours10.mat'),'MatOut')
figure(1);
IntPower = 1/2.3;
im=imagesc(llx,llz,MatOut.^IntPower);axis image
set(gca,'XColor', 'none','YColor','none')
set(gca, 'color', 'none');
im.CData = max(im.CData-.5,0);
colormap(gca,gray(128))
caxis(caxis*.7) % add saturation in image
ca = gca;
WriteTif(im.CData,ca.Colormap,strcat(pwd,'/Result/RSULM_MatOutTours10.tif'),'caxis',caxis,'Overwrite',1)
% Gridding index
load(strcat(pwd,'/Result/RSULM_MatOutTours10_Gridding.mat'),'MatOut')
Gridding_index = PALA_ComputeGriddingIndex({MatOut},1);
Gridding = 1-Gridding_index/30; % [100 at 0; 0 at -30]
InVivoTours/Fig6db_InVivoTours_SRPCA.m 0 → 100644
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%% InVivoTours_SRPCA.m
%
%
% Based on the code created by Arthur Chavignon
% Adapted for the WKY in vivo data.
%
% DATE 2020.12.17 - VERSION 1.1
% AUTHORS: Arthur Chavignon, Baptiste Heiles, Vincent Hingot. CNRS, Sorbonne Universite, INSERM.
% Laboratoire d'Imagerie Biomedicale, Team PPM. 15 rue de l'Ecole de Medecine, 75006, Paris
% Code Available under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (see https://creativecommons.org/licenses/by-nc-sa/4.0/)
% ACADEMIC REFERENCES TO BE CITED
% Details of the code in the article by Heiles, Chavignon, Hingot, Lopez, Teston and Couture.
% Performance benchmarking of microbubble-localization algorithms for ultrasound localization microscopy, Nature Biomedical Engineering, 2021.
% General description of super-resolution in: Couture et al., Ultrasound localization microscopy and super-resolution: A state of the art, IEEE UFFC 2018
clear
%cd ./..
PALA_folder = fileparts(pwd); % location of the PALA folder
PALA_data_folder = fullfile(PALA_folder, 'PALA_data_folder');
% DEFINE THE ADDONS DIRECTORY ON YOUR COMPUTER
addpath(genpath(fullfile(PALA_folder, 'PALA_addons')));
%% Adapt parameters to your data
% A few parameters must be provided by the user depending of your input images (size of pixel, wavelength)
% These parameters will be copied and used later during the creation of the ULM structure.
% in this example, UF.TwFreq = 15MHz, UF.FrameRateUF = 1000Hz;
SR = 10; %Super Resolution factor
UF.TwFreq = 14.8;
UF.FrameRateUF = 1000;
% Here you put the size of your data
SizeOfBloc = [SR*160 SR*128 500];
% Here you put the size of pixel in the prefered unit. It can be um, mm, m, wavelength, or an arbitrary scale.
ScaleOfPixel = [1 1]; % [pixel_size_z, pixel_size_x]
% In that example, the size of pixels is lambda x lambda. The localization process will be
% performs in wavelength. For velocity rendering, velocities in [wavelength/s] will be converted in [mm/s].
% The imaging frame rate is required for velocity calculation, and temporal filtering.
framerate = 1000; % imaging framerate in [Hz]
% Number of blocs to process
Nbuffers = 80; % number of bloc to process (used in the parfor)
% If pixel sizes are in wavelength, lambda must be provided for a velocity maps in mm/s,
lambda = 1480/(UF.TwFreq*1e3); % lambda = 1.002031144211239e-1
%% ULM parameters
% this script can be run using different scaling, it can be wavelength, pixel size, mm, um.
% In this example, input pixel are isotropic and equal to lambda (pixelPitch_x = pixelPitch_y = lambda)
% All size defined later are expressed in lambda
res = SR; % final ratio of localization rendering, it's approximately resolution factor of localization in scale(1) units.
% for a pixel size of 100um, we can assume that ULM algorithm provides precision 10 (res) times
% smaller than pixel size. Final rendering will be reconstructed on a 10x10um grid.
ULM = struct('numberOfParticles', 70,... % Number of particles per frame. (30-100)
'size',[SizeOfBloc(1) SizeOfBloc(2) SizeOfBloc(3)],... % size of input data [nb_pixel_z nb_pixel_x nb_frame_per_bloc]
'scale',[ScaleOfPixel 1/framerate],...% Scale [z x dt], size of pixel in the scaling unit. (here, pixsize = 1*lambda)
'res',res,... % Resolution factor. Typically 10 for final image rendering at lambda/10.
'SVD_cutoff',[25 SizeOfBloc(3)],... % SVD filtering, to be adapted to your clutter/SNR levels
'max_linking_distance',2,... % Maximum linking distance between two frames to reject pairing, in pixels units (UF.scale(1)). (2-4 pixel).
'min_length', 10,... % Minimum allowed length of the tracks in time. (5-20 frames)
'fwhm',[1 1]*7,... % Size [pixel] of the mask for localization. (3x3 for pixel at lambda, 5x5 at lambda/2). [fmwhz fmwhx]
'max_gap_closing', 1,... % Allowed gap in microbubbles' pairing. (if you want to skip frames 0)
'interp_factor',1/res,... % Interpfactor (decimation of tracks)
'LocMethod','Radial'... % Select localization algorithm (WA,Interp,Radial,CurveFitting,NoLocalization)
);
ULM.ButterCuttofFreq = [50 249]; % Cutoff frequency (Hz) for additional filter. Typically [20 300] at 1kHz.
ULM.parameters.NLocalMax = 3; % Safeguard on the number of maxLocal in the fwhm*fwhm grid (3 for fwhm=3, 7 for fwhm=5)
[but_b,but_a] = butter(2,ULM.ButterCuttofFreq/(framerate/2),'bandpass');
ULM.lambda = lambda; % Safeguard on the number of maxLocal in the fwhm*fwhm grid (3 for fwhm=3, 7 for fwhm=5)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Load data and localize microbubbles %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
myfun= @SRPCATours;
blksz = [336 272 500];
Track_tot = {};
fprintf('--- ULM PROCESSING --- \n\n');t1=tic;
for hhh = 1:Nbuffers
pixOffset = 2*floor((hhh-1) / 5) ;
fprintf('Processing bloc %d/%d\n',hhh,Nbuffers);
% Load IQ data
tmp = load(strcat(PALA_data_folder,'/IQTours/IQTours_',int2str(hhh),'.mat'),'IQ');
tmp.IQ = tmp.IQ(5:164,:,:);
tmp.IQ = imresize(tmp.IQ,SR,"bicubic");
% Temporal filter
tmp.IQ = filter(but_b,but_a,tmp.IQ,[],3); %(optional)
tmp.IQ(~isfinite(tmp.IQ))=0;
IQ = tmp.IQ/max(abs(tmp.IQ(:)));tmp = [];
IQ = padarray(IQ, [40 40]);
IQ = circshift(IQ, [-pixOffset -pixOffset]);
IQ_filt = blockproc3(IQ, blksz, myfun, [40 40 0]); IQ = [];
IQ_filt = circshift(IQ_filt, [pixOffset pixOffset]);
IQ_filt=IQ_filt(41:end-40,41:end-40,:);
% Detection process (return a list of super resolved coordinates in pixel)
[MatTracking] = ULM_localization2DSR_Tours(abs(IQ_filt),ULM,pixOffset); IQ_filt=[];
% Normalize for tracking
MatTracking(:,2:3) = MatTracking(:,2:3)/SR;
% Convert pixel into isogrid (pixel are not necessary isometric);
MatTracking(:,2:3) = (MatTracking(:,2:3) - [1 1]).*ULM.scale(1:2);
%save([pwd,'/Result/MatTracking',int2str(hhh),'.mat'],'MatTracking')
% Tracking algorithm (list of tracks)
Track_tot_i = ULM_tracking2D(MatTracking,ULM);
Track_tot{hhh} = Track_tot_i;
Track_tot_i={};MatTracking = [];
end
Track_tot = cat(1,Track_tot{:});
Tend = toc(t1);disp('Done')
fprintf('ULM done in %d hours %.1f minutes.\n', floor(Tend/60/60), rem(Tend/60,60));
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
ULM.SRscale = ULM.scale(1)/ULM.res;
ULM.SRsize = round(ULM.size(1:2).*ULM.scale(1:2));
%
% % Convert tracks into SRpixel
Track_matout = cellfun(@(x) (x(:,[1 2 3 4])+[1 1 0 0]*1)./[ULM.SRscale ULM.SRscale 1 1],Track_tot,'UniformOutput',0);
llz = [0:ULM.SRsize(1)]*ULM.SRscale;llx = [0:ULM.SRsize(2)]*ULM.SRscale;
%% Accumulate tracks on the final MatOut grid.
% fprintf('--- CREATING MATOUTS --- \n\n')
MatOut = ULM_Track2MatOut(Track_matout,ULM.SRsize+[1 1]*1); %pos in superpix [z x]
MatOut_zdir = ULM_Track2MatOut(Track_matout,ULM.SRsize+[1 1]*1,'mode','2D_vel_z'); %pos in superpix [z x]
MatOut_vel = ULM_Track2MatOut(Track_matout,ULM.SRsize+[1 1]*1,'mode','2D_velnorm'); %pos in superpix [z x]
MatOut_vel = MatOut_vel*ULM.lambda; % Convert into [mm/s]
save(strcat(pwd,'/Result/SRPCA_MatOutTours10.mat'),'MatOut','MatOut_zdir','MatOut_vel','ULM','lambda','llx','llz')
%% Figures
ULM.SRscale=0.625/ULM.res; %for velocity maps in mm/s and scale-bars
IntPower = 1/2.3;
cmin = min(MatOut(:).^IntPower);
cmax = max(MatOut(:).^IntPower);
numTicks = 7; % Adjust as needed
h1=figure('WindowState', 'maximized');
im=imagesc((MatOut).^IntPower);
axis image
colormap hot
clbar = colorbar;
set(clbar, 'YTick', linspace(cmin, cmax, numTicks));
clbar.Label.String = 'Normalized localization density';
%clbar.TickLabels = clbar.Ticks.^2.3; %Not normalized
clbar.TickLabels = round(clbar.Ticks.^2.3 ./ max(clbar.Ticks(:).^2.3),2);
set(gca,'XColor', 'none','YColor','none')
set(gca, 'color', 'none');
BarWidth = round(1./(ULM.SRscale*lambda)); % 1 mm
im.CData(size(MatOut,1)-50+[0:2],60+[0:BarWidth])=max(clim);
text(60+BarWidth/2, size(MatOut,1)-50+3 +15, '1 mm', ...
'Color', 'w', 'FontSize', 12, 'FontWeight', 'bold', ...
'HorizontalAlignment', 'center');
% Smaller Colorbar
% If there is a display issue, try executing the code below separately
% after you created the figure h1 as it depends on your screen size
% x1=get(gca,'position');
% x=get(clbar,'Position');
% x(1)=x(1)-0.003;
% x(3)=0.005;
% set(clbar,'Position',x)
% set(gca,'position',x1)
% clbar.Label.Position = [x(1)+2.5, x(2)+clbar.Ticks(end)/2, x(3)];
%%
IntPower = 1/2.3;
OriginalData = MatOut.^IntPower.*sign(imgaussfilt(MatOut_zdir,.8));
cmin = min(OriginalData(:));
cmax = max(OriginalData(:));
clear OriginalData;
numTicks = 9; % Adjust as needed
h1=figure('WindowState', 'maximized');
velColormap = cat(1,flip(flip(hot(128),1),2),hot(128));
velColormap = velColormap(5:end-5,:);
im=imagesc(llx,llz,(MatOut).^IntPower.*sign(imgaussfilt(MatOut_zdir,.8)))
im.CData = im.CData - sign(im.CData)/2;axis image
colormap(gca,velColormap)
clbar = colorbar;
set(clbar, 'YTick', linspace(cmin*0.90, cmax*0.90, numTicks));
clbar.Label.String = 'Normalized localization density';
clbar.Ticks = clbar.Ticks;%customTicks;
TempTickLabels = round(sign(clbar.Ticks).*abs(clbar.Ticks/0.90).^2.3);
clbar.TickLabels = round(TempTickLabels ./ max(TempTickLabels(:)),2);
set(gca,'XColor', 'none','YColor','none')
set(gca, 'color', 'none');
caxis([-1 1]*max(caxis)*.75)
BarWidth = round(1./(ULM.SRscale*lambda)); % 1 mm
im.CData(size(MatOut,1)-50+[0:3],60+[0:BarWidth])=max(caxis);
% Smaller Colorbar
% If there is a display issue, try executing the code below separately
% after you created the figure h1 as it depends on your screen size
% x1=get(gca,'position');
% x=get(clbar,'Position');
% x(1)=x(1)-0.003;
% x(3)=0.005;
% set(clbar,'Position',x)
% set(gca,'position',x1)
% clbar.Label.Position = [x(1)+2.5, x(2), x(3)];
%%
%vmax_disp = ceil(quantile(MatOut_vel(abs(MatOut_vel)>0),.98)/10)*10;
vmax_disp = 80;
h1=figure('WindowState', 'maximized'); clf,set(gcf,'Position',[652 393 941 585]);
clbsize = [180,50];
Mvel_rgb = MatOut_vel/vmax_disp; % normalization
% Mvel_rgb(1:clbsize(1),1:clbsize(2)) = repmat(linspace(1,0,clbsize(1))',1,clbsize(2)); % add velocity colorbar
Mvel_rgb = Mvel_rgb.^(1/2);Mvel_rgb(Mvel_rgb>1)=1;
Mvel_rgb = imgaussfilt(Mvel_rgb,.5);
Mvel_rgb = ind2rgb(round(Mvel_rgb*256),jet(256)); % convert ind into RGB
IntPower = 1/2.3;
MatShadow = MatOut;MatShadow = MatShadow./max(MatShadow(:)*.3);MatShadow(MatShadow>1)=1;
%MatShadow(1:clbsize(1),1:clbsize(2))=repmat(linspace(0,1,clbsize(2)),clbsize(1),1);
Mvel_rgb = Mvel_rgb.*(MatShadow.^IntPower);
Mvel_rgb = brighten(Mvel_rgb,.4);
im=imshow(Mvel_rgb,'XData',llx,'YData',llz);axis on
BarWidth = round(1./(ULM.SRscale*lambda)); % 1 mm
im.CData(size(MatOut,1)-50+[0:3],60+[0:BarWidth],1:3)=1;
set(gca,'XColor', 'none','YColor','none')
set(gca, 'color', 'none');
colormap(jet);
clbar = colorbar;
clim([0 vmax_disp]);
clbar.Label.String = 'Velocity magnitude (mm/s)';
% Smaller Colorbar
% If there is a display issue, try executing the code below separately
% after you created the figure h1 as it depends on your screen size
% x1=get(gca,'position');
% x=get(clbar,'Position');
% x(1)=x(1)-0.003;
% x(3)=0.005;
% set(clbar,'Position',x)
% set(gca,'position',x1)
% clbar.Label.Position = [x(1)+2.5, x(2)+clbar.Ticks(end)/2, x(3)];
%% Metrics
% Saturation Value
% load(strcat(pwd,'/Result/SRPCA_MatOutTours10.mat'),'MatOut')
Saturation = nnz(MatOut()>0)/numel(MatOut());
% CR
% load(strcat(pwd,'/Result/SRPCA_MatOutTours10.mat'),'MatOut')
CR = ContrastRatio(MatOut);
% Image for FRC estimation
% load(strcat(pwd,'/Result/SRPCA_MatOutTours10.mat'),'MatOut')
figure(1);
IntPower = 1/2.3;
im=imagesc(llx,llz,MatOut.^IntPower);axis image
% im=imagesc(llx,llz,PowDop2);axis image
set(gca,'XColor', 'none','YColor','none')
set(gca, 'color', 'none');
im.CData = max(im.CData-.5,0);
colormap(gca,gray(128))
caxis(caxis*.7) % add saturation in image
ca = gca;
WriteTif(im.CData,ca.Colormap,strcat(pwd,'/Result/SRPCA_MatOutTours10.tif'),'caxis',caxis,'Overwrite',1)
% Gridding index
load(strcat(pwd,'/Result/SRPCA_MatOutTours10_Gridding.mat'),'MatOut')
Gridding_index = PALA_ComputeGriddingIndex({MatOut},1);
Gridding = 1-Gridding_index/30; % [100 at 0; 0 at -30]
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