Idif Necktangle

This module contains a collection of functions to calculate an image-derived input function (IDIF) given a “necktangle”. “Necktangles” are a 3D rectangular region of interest over the neck to help identify the carotid PET signal. This method was developed and provided for use in this software package by Dr. Karl Friedrichsen

Requires:

The module relies on the numpy module.

Functions

single_threshold_idif_from_4d_pet_with_necktangle(...)	Applies the single bolus percentile IDIF method to calculate the time-activity curve (TAC) from PET data.
average_across_4d_frames(→ numpy.ndarray)	Calculates the mean frame across the specified range of frames in the 4-dimensional PET data.
get_frame_time_midpoints(→ numpy.ndarray)	Calculates the midpoint times of each frame based on the start times and duration times.
load_fslmeants_to_numpy_3d(→ numpy.ndarray)	Loads fslmeants (--show-all) data from a file and converts it into a 3D numpy array.
double_threshold_idif_from_4d_pet_necktangle(...)	Computes the IDIF from a 4D PET necktangle matrix given a percentile for thresholding.