darkTubes cleanup

src/MATLAB/+RSF/darkTubes.m

@@ -3,7 +3,6 @@ function imfm = darkTubes(im,CONSTANTS,thickness)
 voxelSize = CONSTANTS.imageData.PixelPhysicalSize;
 voxelSize([1,2]) = voxelSize([2,1]); % swap (x,y,z) to matlab column major (y,x,z)    
 vx = max(voxelSize)./voxelSize;
-% vx = [1,1,1];
 sigma = 1/sqrt(3) * thickness * vx;
 
 cudaTarget = getCudaTarget;
@@ -12,17 +11,9 @@ imn = imf;
 imn(imn>0) = 0;
 imn = abs(imn);
 imp=imf;imp(imp<0)=0;
-
-bw = imbinarize(im);
-bw = bwareaopen(bw,1e3);
-bw = imdilate(bw,ones(4*thickness));
-
 imfm = fibermetric(imp);
-% NOTE as with imPreProcess, regional max first, then threshold
 imfm = imfm .* imregionalmax(imfm,6);
-imfm(~bw) = 0;
-
-imfm = RSF.clipRSF(imfm);
+% imfm = RSF.clipRSF(imfm);
 
 4;
 

src/MATLAB/clusterExamples/goDrawDarkTubes.m

+
+ROOT = '/g/leverjs/Schuman_OCT/OCT/qualifiedYes';
+PID = 'P10010'
+thickness = 5
+flist = dir(fullfile(ROOT,['/' PID '*.LEVER']));
+mx = regexp({flist.name},'P(?<PID>\d+)_(?<scanType>.+)_(?<date>\d+-\d+-\d+)_(?<time>\d+-\d+-\d+)_(?<eye>\w\w)_(?<scanID>.+?)_.*.LEVER','names');
+tblMeta = struct2table(vertcat(mx{:}));
+tblMeta.PID = str2double(tblMeta.PID);
+tblMeta.folder = {flist.folder}';
+tblMeta.filename = {flist.name}';
+tblMeta = tblMeta(contains(tblMeta.scanType,'Optic'),:);
+
+iid = 1;
+fname =  fullfile(tblMeta.folder{iid},tblMeta.filename{iid})
+[im,CONSTANTS] = leversc.loadImage(fname,1,1);
+im = mat2gray(im);
+voxelSize = CONSTANTS.imageData.PixelPhysicalSize;
+voxelSize([1,2]) = voxelSize([2,1]); % swap (x,y,z) to matlab column major (y,x,z)    
+vx = max(voxelSize)./voxelSize;
+sigma = 1/sqrt(3) * thickness./2 * vx;
+
+cudaTarget = getCudaTarget;
+imf = HIP.LoG(im,sigma,cudaTarget);
+imn = imf;
+imn(imn>0) = 0;
+imn = abs(imn);
+imp=imf;imp(imp<0)=0;
+% imp=imf;imp(imp<imn)=0;
+% imfb = mat2gray(imbinarize(imp));
+imfm = fibermetric((imp));
+% imfm = fibermetric(mat2gray(imp));
+% NOTE as with imPreProcess, regional max first, then threshold
+% imfm = imp;
+
+close all
+
+figure(1)
+
+clipLimits=[];
+clipLimits.dim = 1;
+clipLimits.range = [400:600];
+im1 = getClipFrame(im,clipLimits,gray());
+im2 = getClipFrame(imn,clipLimits);
+im3 = getClipFrame(imp,clipLimits);
+im4 = getClipFrame(imfm,clipLimits);
+
+imOut = [im1,im2;im3,im4];
+figure;axis equal;imagesc(imOut)
+set(gca,'XTick',[],'YTick',[])
+
+clipLimits = [];
+clipLimits.dim = 3;
+clipLimits.range = [70:110];
+imH = getClipFrame(im,clipLimits,gray());
+imHn = getClipFrame(imn,clipLimits);
+imHp = getClipFrame(imp,clipLimits);
+imHfm = getClipFrame(imfm,clipLimits);
+
+figure;imagesc([imH;imHn;imHp;imHfm])
+
+
+imfm = imfm .* imregionalmax(imfm);
+% imfm(~bw) = 0;
+
+imfm = RSF.clipRSF(imfm);
+
+
+
+
+
+4;

src/MATLAB/ncdVSvfmd/goKernelCorr.m

@@ -13,20 +13,17 @@ load('vfmd_meta.mat');
 % tblVFMD = getVFMD(eye);
 tblMeta = getMetaOCT(ROOT,eye,scanType);
 
+% load('../qualify/onh_rnfl_thickness.mat');
 
-load('../qualify/onh_rnfl_thickness.mat');
-
-% radii = {[0.5,8,8],[5,5,5],[8]}; % plate,blob
-% radii = {[0.5,8,8],[5,5,5],[0]}; % plate,blob
-% radii = {[0.5,8,8]}; % plate
-% radii = {[5,5,5]}; % plate
-% radii = {[7,4,4]}; % plate
-radii = {[8]};
+% radii = {[77,5,5]}; % 
+radii = {[5]}; % 
+% radii = {[0.5,8,8]}
 radii
 
-[rho2,tblVelo, pData, dxx]  = kernelCorr(radii,tblVFMD,tblMeta,tblRNFL);
+[rho2,tblVelo, pData, dxx]  = kernelCorr(radii,tblVFMD,tblMeta);
 
-[rmse1,~] = regnetCorr(tblVelo);median(rmse1)
+% optional train model here, e.g.
+% [rmse1,~] = regnetCorr(tblVelo);median(rmse1)
 
 % saveFile = fullfile(SAVE_FOLDER,['qualEns_ncdVSvfmd_' jsonencode(radii) '.mat']);
 % save(saveFile)