Fixed the thread safety defect in MonoExponential fit function for Global optimization.

Fixed the parallel version of Global Optimization. Now all the Dynamic Framework subtests are checking out OK.

Test of the sub-algorithm for FGT-FAT segmentation. Are the white streaks identified by green arrow is FAT?

Dialog RoiStats3D: Added a histogram bin tracker feature.  User moves the mouse over the histogram and corresponding bin value and bin count are displayed.

Dialog RoiStats3D:  fixed the defect when the displayed histogram span was set with incompletely taking the ROI info into account.

Main Menu>ROI>Load Vector ROI function.  The last used directory is now remembered within the session. It is also saved into the configuration file between the sessions.

Layer Control dialog:  Implemented basic Copy\Paste volume operation to move the layers between documents.

Implemented and exposed GUI for the additional options of histogram thresholding.

Very preliminary test was performed of optimal histogram thresholding using "Bimodal Gaussian representation".  Case ZAMB.  Approximation done by Global optimization in R6 space, with 1M iterations in this experiment.

ZAMB: original histogram for Breast Mask

Original histogram thresholded by OTSU algotithm

BImodal Gaussian approximation and simple minima threshold 

Bimodal approximation threshold on the original histogram

Global optimization framework:  full parallelism of the main loop.  This allow the application programmer not to bother with parallelizing the cost function thus greatly simplifying the usage.

Dual peak (bi-modal?) histograms:  implemented an initial version of algorithm that find an optimal representation of histogram as the sum of 2 gaussians.  Global optimization framework is used.

Any distribution other than Gaussian would fit this algorithm too.

DicomTree load:  added extra diagnostics when composite series are present but some files are missing so the logical structure could not be constructed.

Mouse PET dynamic dataset (from Jean): latest version of FireVoxel loads it without problems as a dynamic  volume (33x26x26  with 48 timepoints)

On the sample brain from EdgeWave manual:
1.  applied N3
2. performed EdgeWave segmentation using default parameters.
3. Brain mask was automatically thresholded to get WM\GM masks.
4. First Otsu then Z-algorithm were used.

Auto histogram separation over the Brainmask:   Otsu  vs. Z-algorithm

Resulting Wm\Gm masks:  Otsu vs. Z-algorithm

IVIM- regular model:  extended to calculation to allow three b-values to be present.

IVIM segmented fit model: Provided the diagnostics and clear requirements message on b-values.

Provided new icons for the FireVoxel main toolbar.

Provided several variants of the Breast FGT processing module.

Dialog RoiStats3D:  integrated algorithm selection tool  {Otsu,Zigalga} for segmenting the Histogram.

Comparison of the Otsu algorithm vs. Zigalga on breast histogram:

Case ZAMB:  old Otsu algorithm

Case ZAMB:  new Zigalga algorithm