Parametric Images#

This module provides functions and a key class, GraphicalAnalysisParametricImage, for graphical analysis and creation of parametric images of 4D-PET scan data. It heavily utilizes numpy for data manipulation and assumes the input as 4D PET images along with other required inputs.

The GraphicalAnalysisParametricImage class encapsulates the main functionality of the module, and encompasses methods for initializing data, running and saving analysis, calculating various properties, and handling parametric image data.

Classes#

`ReferenceTissueParametricImage`	Class for generating parametric images of 4D-PET images using reference tissue model (RTM)
`GraphicalAnalysisParametricImage`	Class for generating parametric images of 4D-PET images using graphical analyses. It provides

Functions#

`apply_linearized_analysis_to_all_voxels`(...)	Generates parametric images for 4D-PET data using the provided analysis method.
`parametric_refregion_analysis`(→ Tuple[numpy.ndarray, ...)	Generates parametric images for 4D-PET data using the provided analysis method. This function
`generate_parametric_images_with_graphical_method`(...)	Generates parametric images for 4D-PET data using a specified graphical analysis method.
`apply_mrtm2_to_all_voxels`(→ Tuple[numpy.ndarray, ...)	Generates parametric images for 4D-PET data using the MRTM2 reference tissue method.
`apply_rtm2_to_all_voxels`(→ numpy.ndarray)	Generates parametric images for 4D-PET data using the SRTM2 reference tissue method.
`generate_cmrglc_parametric_image_from_ki_image`(...)	Generate and save a CMRglc image by rescaling a Patlak-Ki image.