Completely Re-engineering K-trans model with 3 parameters {K-trans,Ve,Va}...

Completely re-engineering the 2-parameter K-trans model  {K-trans,Ve}.  Will verify on the MR4D from the PET-MR exam...

Major work finished, re-enabling and verifying the Automatic Build Test after partial phaseout of 24-bit processing.

Zoom-to-Display functionality:  converting internal processing from 24-bit  to 32-bit for simplicity and speed.

MR4D (from combined PET-MR exam):
Verifying the "K-trans model" = {K-trans, Ve}.  Adding a corresponding subtest to ABT....

Registration defect  fixed:  while registering two longitudal MPRAGE images, the registration crashes if one of 3 measures is used:  {SignalDiff, CrossCorrelation, RatioUniformity}


Added the ABT subtest for  sag1.im<->sag4.im registration for 5 additional measures:
  {SignalDiff, CrossCorrelation, RatioUniformity,MI,MI-norm}

Fixed the volume overlay problem, when 2 brain volumes with the resolution difference around
1e-4 were not able to overlay.

PET-MR  registration:  Removing optional  "PET resolution\Best resolution" option as it always to the best resolution now due to the new codec.

Verifying the ABT (automatic build test) due to the changes related to the NN-codec.

Providing the code to maintain the backward compatibility with the older FVX format, which has been updated with the new Codec.

Optimizing memory bandwidth around the single slice voxel CoDec.  Converting 24-bit based voxel  representation to 32-bits.

Fully coded,  Presently debugging the "NN-loseless codec"....  required for Hi-res  PET->MR registration.

Implementing highly efficient internal volume codec that is targeting the volumes upsampled using the NN-interpolation.  This is a critical function during the PET-4D to MR registration.
User optimally desires best available resolution for both registered volume, which is typically a MR resolution.  However, for high timepoint # the resulting volumes might reach upto 7 GB  (compressed with the regular FireVoxel compression).
This new codec will allow much higher compression of such registered PET volumes.

It is lossless.

High-accuracy PET-to-MR registration using an approximate BrainMask with 4X speed gain.

Presently, it is very hard to achieve PET-to-MR registration without additional guidance.
From previous registration experience, a quick  Brain ROI was obtained using the BrainMask\EdgeWave tool.

This ROI is just an approximation of an anatomically precise mask of the brain. FireVoxel can obtained a much more precise BrainMask by adding the non-uniformity correction to that workflow.



After obtaining BrainMask ROI, the regular  PET-to-MR registration runs that uses ROI as a guidance.  Resulting registration has a very high accuracy.
The whole processing is less than 4 minutes on the reference ($1K) PC.

Single volume Edge-constrained smoothing:  partially combined the code with the similar logic of "Inter-volume constrained smoothing".  Reused the dialog common for both functions.

Corrected the logic for the Registration3D: TargetROI.  Included a new  dialog item that explicitly displays the name of the layer to be used as a Target ROI.

Implemented an initial variant of the "Inter-volume Edge Constrained Smoothing".  In this  test:
a) MR and PET4D were registered with very high accuracy.
b) MR-edges (as 3D surfaces) were detected using the texture-edge detector (URAL)
c) PET-volume was smoothed, with smoothing apperture that was constrained by the presence
of edges within vicinity of every voxel.

This just a prototype as many options are available.
Specialized dialog box was developed.

Implemented the two-compartment Sokoloff'77 model (long formula) also used in Reivich'85. Results are identical (to 0.01% precision) with the Sokoloff'79 interpretation (short formula)
in the initial tests.

PET:  Latest version of the IDIF.  User does NOT have to specify the dominant direction anymore.  Also the meaning of the seed is changed - User just have to place the center of the seed on the vessel.  Other parameters, such as max vessel length, are enabled.

Added L1/L2 optional residual metric to  Sokoloff'79 (short) model.