pyfli.data_cc.roi#

Extract ROI-specific datasets from global fitted result dictionaries.

This module belongs to pyfli.data_cc and is part of PyFLI array preprocessing helpers for normalization, masking, ROI extraction, and IRF alignment. Public API includes classes ROIOperations.

Classes

ROIOperations()

Extract ROI-specific fit dictionaries from global fitted datasets.
class ROIOperations[source]#

Bases: object

Extract ROI-specific fit dictionaries from global fitted datasets. It uses integer ROI masks to separate parameter maps and decay arrays into per-region result collections.

extract_roi_datasets(global_dataset, multi_roi_mask, model_type='bi-exponential')[source]#

Run the extract ROI datasets routine.

Parameters:

  • global_dataset (np.ndarray) – Mapping containing datasets for all ROI groups.

  • multi_roi_mask (np.ndarray) – Labeled ROI mask used to split global results.

  • model_type (str) – FLI model family, such as mono- or bi-exponential.

Returns:

ROI-specific dataset arrays extracted from the global dataset.

Return type:

np.ndarray