Performing rearrangement of Sourbron's DCDI equation, moving to new
optimization variables:


1. ETR = Ve/(Fa+Fv),
2. F = (Fa+Fv) ,
3.  fa = Fa/(Fa+Fv),
4. H = Ki/(Fa+Fv)

This might have definite advantages, due to simplified parameter ranges.
ETR is closely related to EMTT (extracellular mean transit time) and is in [0,100] sec interval.
F  is the total Inflow.

fa and H are just coefficients and should be in [0,1] range.

This seems to be a definite improvement over the {Ve,Fa,Fv,Ki }  variable set where all 4 nontrivial
intervals are required.

Calculated the Hepatic Uptake rate (Ki) for 2 patients. This is a very early and preliminary result.  Both maps use the same color scale. The units of measurement are "1/100/min" as per Sourbron's paper.

Implemented derived parameters as per Sourbron's paper.
Primary optimization parameters are Fa,Fv,Ve,Ki.
So far there was no need for the "Arterial Delay" as Henry had foreseen.

Performed DCDI calculation for two patients LP and KA.  Below are the "Total Inflow" maps (=Fa+Fv).  Color mapping is using the same color scale (see color bar on the right)

Liver DCDI modelling function is fast enough to process large ROIs on the voxel-wise basis
Below is the parametric map Arterial Flow (Fa) in  "ml/min/100ml" units as in Sourbron's paper.
Total calculation time is about 3 sec.

Liver DCDI model: 
a) Fully parallelized the "Grid search" preceding the iterative Amoeba  (Simplex) optimization
b) Integrated the Parallel Amoeba variant

Obtained first fitting result for the Liver DCDI model (Sourbron).
In this example 2 input functions are shown in Signal intensity units.
The target ROI is in red.
Fitted Concentration Curve (black) is overlaid on top of the Data Concentration Curve.
Optimal parameter values are shown at the bottom of the diagram. They are normalized
to Sourbron's unit from the paper and on a quick comparison are of the same order of magnitude.
Note:  Arterial delay of "0" was used.

Running tests of the Liver DCDI model, debugging and targeting the visualization of the model fit as the next waypoint.

DCDI (Dual Compartment Dual Input) model:  Implementing a fitting model, within the FireVoxel Dynamic Framework...

Implemented a support function, that in Play4D -  ALL the documents that have a compatible dynamic information will be played simultaneously.  This is very helpful for the displaying results of 4D registration,

In preparation to release Build 130:  Restoring several parts of the Automatic Build Test that use the .FVX file format. Format was changed recently due to the use of the new 3D Volumentric primitives.

Dialog "Split ROI by Threshold":
Implemented a feature, so user is able to enter the desired threshold manually.

Portal Vein Input function (obtained automatically) was compared between:
a)  Unregistered DCDI dataset
b) DCDI dataset registered for the whole liver (URAL-measure\Affine Transform)

difference is substantial, in line with the substantial motion across the axial plain which is eliminated as the result of the registration.

Compared the Portal Vein Input Function  derived from
a) Whole registered liver     VS.
b)  (starting from wholly registered liver) Local registration with the small ROI enveloping the Portal Vein.

There is small gross misregistration (during b.) on the initial timepoints due to the absence of features (contrast edges on early timepoint).  But besides that there seems to be little difference between a) and b).

So in the initial DCDI modelling we will restrict to the Whole liver registration only.

Developed a function, when given a 4D volume and an ROI (3D or 4D),   FVX advances to timepoint where amount of information (or entropy) over the given ROI is maximum. 

This is an extremely valuable function for all 4D registrations.  It allows user to automatically select an "Anchor" point for 4D registration.

Prior to this development, every individual workflow required an individually crafted recommendation which timepoint to use as an "anchor" for the registration.

Re-implementing the frequent {VolumeCropSlice, VolumeCropTimepoint} operations which are frequently used in processing.  Idea is to perform it through copying compressed blocks, instead of VolumeGetBox-VolumeSetBox sequence that require   Decompress\Compress.

Pair of this function is used extensively in Registrations and in over 70 locations inside the FireVoxel.

Attempting to correct Elastic (quadratic) transform on the 3D->3D liver registration. For some reason function is not performing as in the past.

After registering the Liver in 4D,  returned back to Axial projection.  Specified the Macroseed (green box on the right) over the portal vein.  Then ran fully automatic vessel (IDIF) segmenter.  (Peak time eps=30 sec, Vessel diam=10mm).  Resulting ROI is shown on Axial and Sagittal projections in Blue.
Corresponding Input function is displayed in concentration units as in the Sourbron's paper.

Registration:
Converted DCDI-(Dual Compartment Dual Input) Eovist Liver dataset to the isotropic sagittal.  For Registration purposes sagittal projection seems to be more suitable due to the liver motion mostly perpendicularly to the axial plain (is this true?). So it is easier to evaluate registration  quality.  Additionally, it is easier (at least for unexperienced in-anatomy users) to outline liver ROI in sagittal view (is this true?)

Question: after registration, for the remainder of the workflow, should we return to the axial projection? I assume yes, due to the higher resolution in the axial plain and further presentation of the results.

Applied automatic Image Derived Input Function segmenter to the Liver Eovist dataset.
Here is example for the aorta. As usual user just have to put the Macroseed around the artery.
The rest is automatic.  Default parameters from PET function worked, just vessel diameter was set for 10 mm.
Size of resulting ROI is 2500 voxel,  17.5 cm3.  ROI is guaranteed to be a tube in the prevalent Z direction.  Tube is continuous - an Interruption on the sagittal view is just due to the tube being curved.