PET4D+ROIs  registration to MRI4D+ROIs is finished.  When timelines are merged, new 4D volumes created for the merged timeline.  This results in substantial memory overhead at the moment. Implementing the design for efficient memory handling when the redundant timepoints are present.

Paralellized the  "Crop Out void voxels from Volume" function (part of the registration).

Sokoloff model, as in Sokoloff-Phelps paper (Annals of Neurology 1979, vol.6 No. 5) is

This  is the formula that was used by Dr. Wai Tsui (Mony's team). He sets k4=0.   So after that the expression could be rewritten:  alpha1 = 0,  alpha2 = k2+k3

This is exactly the formula used by Wai and is presently in FireVoxel Build 134 (the Anne was using for the abstract).

Now there is a second paper by Reivich (Journal of Cerebral Blood flow and Metabolism 5:179-192 1985), brought up by Fernando.  This paper references an earlier (Sokoloff 1977) paper: with

However, those 2 formulas are substantially different, which can be the easiest observe if we substitute k2=0 to both.  So which one should I use?

Fixing defect, when the 4D volume crop, the absolute values of times are lost and relative times are preserved.  This causes the problem for some registration functions.

Implemented functionality in "PET to Anatomy registration" when all of the MR entity layer (incl. ROIs) are transformed appropriately.  This realizes the "ROI Transfer" feature.  PET entity layers, if present,  are transformed appropriately too.

Impementing 4D to 4D registration in the context of the PET to Anatomy registration. The challenge here is to properly merge the different timings of PET and MR.

FireVoxel Build 134 is released.

Fixed defect and crash:  Dialog RoiStats4D, in multilayer entity, if there are several ROIs present and if one of them is empty, no stats would be displayed even if it was not an active ROI.

Finalized the Release Candidate for Liver DCDI model. All the concentration options discussed are included. This would appear in Build 134.

Liver DCDI:  revisiting the Monotail concept (AIF=VIF with t>3 min).  This might allow to perform a segmented fir for {F,Ve} only for this part of the curve thus stabilizing the kit.  This does not make any assumptions about the delays {Ta,Tv}, i.e. would work for any delays. Interestingly, Ki also can be derived as it is not an independent variable of in the trio of {F,Ve,Ki}

DCDI model:  added an User Interface option to select Linear (=1) or Logarithmic(=0) concentration conversion.

FireVoxel Build 133 is released.

DCDI model:  added an User Interface option to use the L1 or L2 metric for calculating the
fitness residual.

YL-case,   "DCDI - Stabilized V1"

Obtained a good fit with good parameter values except for the high flow. Perhaps high flow can be explained by the concentration conversion.
Note1:  ROI was drawn fairly large as in Sourbron's paper (i.e. 40-60 mm diameter)
Note2:  As in Sourbron's paper the Arterial delay exceeds the Venous delay.  Interestingly that would
mean that venous contrast arrives first, but this is exactly his primary mode.

Implemented automatic matching BATs of AIF and TACs. Result is inconclusive as fitting is very good but parameters are unrealistic.

Corrected the VolSetSlice function, in the binary (1-bit ROI) case.  The Source buffer was modified in this function causing the error.

New DCDI variant:   after BATs are matched, the arterial flow Fa can be calculated from the short initial period.

FireVoxel Build 132D is released.  This fixes the problem with MTT in the "DCDI  Stabilized-V1" model.

Dialog RoiStats4D: added a function button-"BAT". When user press this button the current time advances to the BAT for this curve.

Developing an automatic  BAT (bolus arrival time) function for dynamic studies.  At the moment it will be employed in the context of DCDI model:   BAT of AIF should be matched to BAT of ROI to determine the Arterial delay specific to the given ROI.

Quick FireVoxel Builds 132B, 132C are released reflecting the urgent work on the stabilization of the Liver DCDI (Dual compartment dual input models).
Particularly, in 132C, a "DCDI Stabilized - V1" is introduce.  It uses the integral form of DCDI equation to eliminate one of the independent optimization variables thus stabilizing the fit.

Implementing the "Liver DCDI  Monotail" model that allows to avoid an explicit calculation of {Ta,Tv} (arterial and venous delay).  As the first stage only 3 parameters are calculated {F,Ve,Ki}.

FireVoxel Build 132A is released.

Investigating defect of Saving\Loading RAW  (*.im\MIDAS) files.

Liver DCDI model:   removed the "Ve max" (extracellular volume limit) from the user interface since it is always in [0,1] range.

Dialog RoiStats4D:  added the Info button so the Information could be displayed more conveniently for the user.

Dialog RoiStats4D:   Implemented an intelligent background color management.

Dialog RoiStats4D:  User is now able to use   {LEFT,RIGHT} keyboard keys to scroll in time when this dialog is open.  The 4D volume and the Curves in the dialog box are updated correspondingly.

Among many uses this function allows to reuse this dialog in the BAT (Bolus Arrival Time)  verification procedure.

Fixed several issues related to 4D ROIs and the corresponding layer control dialog box:
a) 4D ROI default name RAW extension
b) 4D ROI default RAW save format
c) In RoiStat4D dialog box, the timepoints not containing the actual ROI are drawn as "white" nodes on the curve.

Liver DCDI model:  adding two implementations of this model to the UI. 
The "Standard" variant, has exact implementation of the Sourbron's paper with the addition of the Exam length parameter and the variables {TotalFlow,fa,Ve,ki}.
The "Experimental" variant hosts new investigations, such as independently derived "Ta" arterial delay time.

Fixed the defect in   "Roi>Convert 3D to 4D" function.  DICOM-style headers were not properly constructed for a newly created 4D entity.

URAL registration 3D/4D:   in case when non-textured URAL measure is selected, applied very efficient gradient interpolation technique that result in a significant speed up during the AutoFocus and especially the Finetune stage.

Completely re-engineered the image gradient field reslicing function.

Registration 4D:   Eliminated an excessive temporary memory allocation during the 4D registration.  This was the cause of the memory allocation failure during the registration of large 4D datasets.

Latest DCDI approach to  Arterial (Ta) and Venous (Tv) delay approach   was tested:

Arterial delay is defined graphically (at the moment) by analyzing the AIF and  roiTAC.
(blue-AIF,  red-VIF, green-roiTAC)

Define:   Ta = ContrastArrivalTimeROI - ContrastArrivalAIF.
For this specific ROI it was Ta = 16 sec.
At the moment User punches in this time delay, but will be entirely automatic later.

Then we perform 5 parameter fitting of DCDI model  {TotalFlow,fa,Ki,Ve,Tv}.  We set  Tv=[0,8] seconds.

Result is encouraging, with fa=0.33.  (Blue is the data curve, black is the Model curve)

ROI was made very small to avoid the blood vessels.

Time to Peak  (in seconds) parametric map for the liver  , case YL.
Vein network shows varying arrival times.  There seem to be a substantial delay between the main Portal Vein (where we sample VIF) and the peripheral (?) branches (which actually supply the tissue).
Delays seem to be upto 15 seconds.

Liver DCDI:  Based on the discussion with Dr. Rusinek, experimenting with the alternative ways to calculate the Arterial fraction and then substitute it into the Sourbron's equation for fitting.  Reminds me of "Segmented fit" in IVIM promoted by Eric Sigmund.

Stress testing correctness of the fitting procedure, substituting  AIF and VIF (in 2 separate experiments) as the Data curve and comparing to the analytically derived result.

Assembled {AIF,VIF,+6 ROI Tacs} package for the external verification of Liver DCDI model fitting.

Adding the allowed ranges of parameters {Fa,Fv,Ve,Ki} for Liver DCDI model, so the User\Researcher could control those parameters directly for investigations.

Provided to Hersh the full analysis \report on 3 cases   {KA,LP,YL} with the respect to Liver DCDI model.

Analysis of DCDI cases  ("Good": 1-KA, 2-LP,  "Bad":  3-YL