The common input parameters of this function are:

IMPORTANT: The number of folders at the studies_path, the number of files at the reference_path and the number of files at the interest_path must be the same. The allowed formats for the masks are NIfTI and Analyze.

We have written a few code lines and suggestions on the way to implement the new model step by step:


STEP 1: Include your model

Change the newModel_Name text by the name you will give to your model. Also, you have to change the else condition.

And add a new case to the if command:
After the first step, for each study including at the studies_path, the main function QModeling_parametric_images.m loads this study in a variable called Cpet and obtain the target and reference TACs. These TACs are saved to the Ct and Cr variables.

STEP 2: Check input parameters

As an option, you could include a check for the number of input parameters, to make sure that it coincides with the number of parameters your model needs. It would also be useful to verify that the values are correct (non-negative values, correct numbers, between the allowed maximum and minimum,...). In that case, the program should save all the errors detected to the log-file.


STEP 3: Call your own model function

The implementation of the new model will be included in a new Matlab function, QModeling_newModel_Name. Each time a study is processed, the main program will call this function with the following input parameters:

STEP 4: Apply a "cut" to the generated images matrices (optional)

It is possible to ask the user for a threshold input parameter to "cut" the parametric images. All the values of the parametric images under a certain value obtain from the threshold will be set to zero.


STEP 5: Create and save the parametric images

Once you have run the main script, the images will be saved at the save_path directory.