Several minor changes

- Updated README.md - Coil combination of TWIX data now performed using GLS - Added support for new JHU universal sequence for Siemens data - Turned off warnings of iteration limits in SpectralRegistrationHERMES.m - Some cosmetic changes
markmikkelsen · Oct 20, 2022 · 1ba4049 · 1ba4049
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Showing 5 changed files with 109 additions and 151 deletions.
diff --git a/GERead.m b/GERead.m
@@ -300,7 +300,7 @@
     MetabData = ShapeData(:,:,refframes+2:end,:) * mult / 2;
 
     totalframes = totalframes - (refframes + 1);
-    
+
     MRS_struct.p.nrows(ii) = totalframes;
     MRS_struct.p.Navg(ii) = dataframes * nex;
     MRS_struct.p.Nwateravg(ii) = refframes * nex;
@@ -335,20 +335,20 @@
 
     ShapeData = reshape(raw_data, [2 MRS_struct.p.npoints(ii) totalframes nreceivers]);
 
-    [X1,X2] = ndgrid(1:refframes, 1:nechoes);
-    X1 = X1'; X1 = X1(:);
-    X2 = X2'; X2 = X2(:);
-    Y1 = (-1).^(MRS_struct.p.GE.noadd(ii) * (X1-1));
-    Y1 = permute(repmat(Y1, [1 MRS_struct.p.npoints(ii) 2 nreceivers]), [3 2 1 4]);
-    Y2 = 1 + (totalframes/nechoes) * (X2-1) + X1;
+    [X1,X2]   = ndgrid(1:refframes, 1:nechoes);
+    X1        = X1'; X1 = X1(:);
+    X2        = X2'; X2 = X2(:);
+    Y1        = (-1).^(MRS_struct.p.GE.noadd(ii) * (X1-1));
+    Y1        = permute(repmat(Y1, [1 MRS_struct.p.npoints(ii) 2 nreceivers]), [3 2 1 4]);
+    Y2        = 1 + (totalframes/nechoes) * (X2-1) + X1;
     WaterData = Y1 .* ShapeData(:,:,Y2,:) * multw;
 
-    [X1,X2] = ndgrid(1:dataframes, 1:nechoes);
-    X1 = X1'; X1 = X1(:);
-    X2 = X2'; X2 = X2(:);
-    Y1 = (-1).^(MRS_struct.p.GE.noadd(ii) * (X1-1));
-    Y1 = permute(repmat(Y1, [1 MRS_struct.p.npoints(ii) 2 nreceivers]), [3 2 1 4]);
-    Y2 = 1 + refframes + (totalframes/nechoes) * (X2-1) + X1;
+    [X1,X2]   = ndgrid(1:dataframes, 1:nechoes);
+    X1        = X1'; X1 = X1(:);
+    X2        = X2'; X2 = X2(:);
+    Y1        = (-1).^(MRS_struct.p.GE.noadd(ii) * (X1-1));
+    Y1        = permute(repmat(Y1, [1 MRS_struct.p.npoints(ii) 2 nreceivers]), [3 2 1 4]);
+    Y2        = 1 + refframes + (totalframes/nechoes) * (X2-1) + X1;
     MetabData = Y1 .* ShapeData(:,:,Y2,:) * mult;
 
     totalframes = totalframes - (refframes + 1) * nechoes; % RTN 2017
@@ -362,30 +362,32 @@
 WaterData = permute(WaterData, [3 1 2]);
 
 % Generalized least squares method (An et al., JMRI, 2013, doi:10.1002/jmri.23941)
-[nCh, nPts, nReps] = size(WaterData);
-noise_pts = false(1,nPts);
+[nCh, nPts, nReps]             = size(WaterData);
+noise_pts                      = false(1,nPts);
 noise_pts(ceil(0.75*nPts):end) = true;
-noise_pts = repmat(noise_pts, [1 nReps]);
-tmpWaterData = reshape(WaterData, [nCh nPts*nReps]);
+noise_pts                      = repmat(noise_pts, [1 nReps]);
+tmpWaterData                   = reshape(WaterData, [nCh nPts*nReps]);
 
-e = tmpWaterData(:,noise_pts);
-Psi = e*e';
+e             = tmpWaterData(:,noise_pts);
+Psi           = e*e';
 WaterData_avg = mean(WaterData,3);
-S = WaterData_avg(:,1);
-w = (S'*(Psi\S))^-1 * S' / Psi;
-WaterData = w.' .* WaterData;
+S             = WaterData_avg(:,1);
+w             = (S'*(Psi\S))^-1 * S' / Psi;
+WaterData     = w.' .* WaterData;
+
 MRS_struct.fids.data_water = mean(squeeze(sum(WaterData,1)),2);
 
-[nCh, nPts, nReps] = size(MetabData);
-noise_pts = false(1,nPts);
+[nCh, nPts, nReps]             = size(MetabData);
+noise_pts                      = false(1,nPts);
 noise_pts(ceil(0.75*nPts):end) = true;
-noise_pts = repmat(noise_pts, [1 nReps]);
-tmpMetabData = reshape(MetabData, [nCh nPts*nReps]);
+noise_pts                      = repmat(noise_pts, [1 nReps]);
+tmpMetabData                   = reshape(MetabData, [nCh nPts*nReps]);
 
-e = tmpMetabData(:,noise_pts);
-Psi = e*e';
-w = (S'*(Psi\S))^-1 * S' / Psi;
+e         = tmpMetabData(:,noise_pts);
+Psi       = e*e';
+w         = (S'*(Psi\S))^-1 * S' / Psi;
 MetabData = w.' .* MetabData;
+
 MRS_struct.fids.data = squeeze(sum(MetabData,1));
 
 end

diff --git a/GannetPreInitialise.m b/GannetPreInitialise.m
@@ -38,7 +38,7 @@
     MRS_struct.p.mat      = 0; % Save MRS_struct as a .mat file
     MRS_struct.p.csv      = 0; % Extract useful data from MRS_struct and export them to a .csv file (applies to GannetFit,
                                % GannetSegment and GannetQuantify)
-    MRS_struct.p.append   = 0; % Append PDF outputs into one PDF (separately for each module) (requires export_fig in the Gannet
+    MRS_struct.p.append   = 1; % Append PDF outputs into one PDF (separately for each module) (requires export_fig in the Gannet
                                % folder to be added to the search path and GhostScript to be installed)
     MRS_struct.p.hide     = 0; % Do not display output figures
 

diff --git a/README.md b/README.md
@@ -60,7 +60,7 @@ __It is highly recommended that you only add the main SPM12 folder (_spm12_) to
 
 ## Compatibility
 
-Gannet is currently being developed in MATLAB R2021a in macOS 11.4 Big Sur. While reasonable effort is made to ensure legacy and cross-OS compatibility, an error-free user experience is not guaranteed.
+Gannet is currently being developed in MATLAB R2022b in macOS 12.6 Monterey. While reasonable effort is made to ensure legacy and cross-OS compatibility, an error-free user experience is not guaranteed.
 
 ## Supported file formats