IVIM free model fix:  was always returning "0" as the residual of the fit.

ABT test for Dynamic Modelling:  modified the test so that results are compared to Standard using the specified tolerance (1e-3) to avoid costly investigation into ABT trivial "red flags".

Mouse brain  PET-CT-Atlas workflow:  verified that workflow works with the complete 20-region atlas.

Produced a Mouse brain atlas of all 20 regions that can be now processed by the Layer Control dialog.

Expanded current Layer Control dialog to 22 layers to accommodate an entire Mouse Brain Atlas.

Fixed the .IM Save\Load problem.  When original file (Atlas template) was provided it had invalid Unit Names for the voxel.  After Saving it to MIDAS, loading as a layer and the saving to FVX was causing the crash loading the resulting FVX file.

Implemented a very early prototype of the new Layer Control dialog box.  This Control would provide handling of all hybrid types of the primitives present in the FireVoxel entity:  {Volumes,Landmarks,VROIs,Pollygons,Text, etc}.  This dialog supports an unlimited number of layers. During the prototyping stage this dialog is activated by F9.

Code improvement:  moved the CDlgLayerCtrl declaration within the class source module.

Dynamic Modelling module:  implemented the Parametric map "Input function correlation"

Femur ROI registratio: Implemented a dedicated menu item with parameters suitable for this application.  Default parameters provide speed of under 5 min on the WALS1-WALS2 sample.
Speed is variable and defined by the precision of the AutoFocus stage (such as rotation precision and range)

ROI->ROI registration:  during the reslicing operation in AutoFocus\Finetune iteration ROIs are transformed and partial volume voxels appear while the majority of voxels still remain binary ROI. Calculating of signal difference in the obvious way was not fast enough for comparing the massive images for Femur registration problem.
Developed the Signal difference calculation working directly with Run-length representation of ROIs (x10-20 memory compact) that resulted in x10 speed up during the AutoFocus on Subscale=3. Speed up is even higher on the Finetune phase approaching x30.

Femur registration of Bone ROI->ROI using "Signal Difference" Measure.  Matching result is good but takes more than 1hr.

Build 205 is released

"MainMenu>ROI>Split ROI by Threshold" - added the BiModal Laplacian with ration method for initial split.

Enabled accelerator "Ctrl+S" :  "Save FireVoxel document"

Implemented new rule to select threshold from 2 modelled distribution:  "Minimize Missclassification" rule.

BiModal Laplacian histogram

CT-PET-ATLAS workflow: Register ALL:  fixed the crash defect on case W73"Deep breathing" lung segmentation case:  no leaks after BiCal+EdgeWave

Mouse Brain, CT-PET-ATLAS wokflow:
Provided an additional registration function to register everything to the PET space to avoid any transforms\interpolation of the principal data (PET).

Mouse Brain   CT-PET-Atlas workfow:  finished the integrated "one-click" registration function

Added the functionality to extract only desired regions from the Atlas

Landmark co-registration:
a) When Source={3D,4D} 2-layer entity, registered to a 3D-volume, the timing information of the 4D volume was lost
b) Also corrected the defect when Alpha (transparency) and the color scheme of the source were lost after the regidstration.

Dialog RoiStats3D:  in Model-based Histogram segmentation added an option to view the "Modelling Cumulative" curve  (options are {None,All Curves,Cumulative"}
Also removed the "BiGauss Explore" and "BiGauss with Ratio Explore" options since they are superceded by the curves display now.

Histogram model-based segmentation {BiGauss,BiLaplace}: Implemented initial framework to show the modelling curves overlaid on top of the histogram

Implemented some improvements to Global Optimization algorithm and code.

Fixed crash defect while loading the DICOM folder obtained from Mr. Zhang under Win10. This was due to using the 32-bit truncation in CTreeCtrl::SetItemData during the DICOM tree construction.

Moved the main development environment to Windows 10.

Fixed the defect in RasterPaintbrush dialog box:  checking the "Allow paint on parametric Maps" had no effect and setting was not remembered.  Drawing on Parametric maps is now possible.

Fixed the paintbrush problem when drawing on integer volumes.

Registration by the landmarks:  provided more detailed analysis in case of the landmark mismatch between Source and Target.  

Registration by Landmarks:  upon the start of the procedure all the "invisible" (void) landmarks are unconditionally removed from ALL documents. This is to avoid frequent confusion during the registration.

"MainMenu>ROI>Split ROI by Threshold" - added the BiModal Laplacian with ration method for initial split.

Enabled accelerator "Ctrl+S" :  "Save FireVoxel document"

Implemented new rule to select threshold from 2 modelled distribution:  "Minimize Missclassification" rule. This rule does not use actual histogram values

Further extensions are possible with histogram value usage.

We have found good BiModal match of the Histogram.  Having two curves (Gaussian or Laplacian) what is the suitable algorithm to choose the threshold?  Presently we choose the lowest point between the peaks of two components, but now I have doubts about this.  Should it be the intersection of 2 curves instead?

BiModal Laplacian histogram segmentation (first result):

This is simplistic global optimization (without extremum checking so did not perform as well as BiGaussian with the same number of iterations = 200K)

Proposed semi-automatic "breast\chest wall" segmentation:

One way is to segment OUT the chest wall, after that breast segmentation is a simple EdgeWave operation.

To segment the chest wall:
1. On every 5th slice, draw the chestwall boundary as an ROI (see pic below).  In this prototype I recommend the boundary starting and ending at the margins of the image (later on we can eliminate this).

2. I will provide a specialized operation "MainMenu>Applications>Breast>Segment Chest wall from Contours".  Internally this operation would perform completing the contour, and then "Fill & Morph convex" to fill the skipped slices.

3.  Result of this operation would be a "CHEST ROI" that could be excluded from the image.  Then we would simply apply the EdgeWave to segment out the Air.

4. Manual processing time should be <1 min.  Computing time is <20 sec.

CT-PET-ATLAS workflow: Register ALL:  fixed the crash defect on case W73