Brief Description ================= The PyReliMRI package intergrates several modules designed to facilitate reliability estimation on MRI data. \ The code is simplified by leveraging features from `Nilearn `_. \ These modules can be categorized into two main groups: Similarity and Tetrachoric Correlation --------------------------------------- - `similarity.py`: Computes similarity coefficients (Dice, Jaccard, etc.) between 3D Nifti images. Includes functions like `image_similarity` for pairwise comparisons. - `tetrachoric_correlation.py`: Calculates the tetrachoric correlation between binary vectors, useful for certain types of data analysis. Intraclass Correlation ----------------------- - `icc.py`: Computes various components used in ICC calculations, such as ICC(1), ICC(2,1), or ICC(3,1), along with confidence intervals and variance components. - `brain_icc.py`: Calculates voxelwise and ROI-based ICCs across multiple runs/sessions. Integrates with Nilearn datasets for atlas options, facilitating quick atlas integration. - `conn_icc.py`: Estimates ICC for precomputed correlation matrices, useful for connectivity analyses. Stimulus-Locked TR-by-TR Timeseries ------------------------------------- The `masked_timeseries.py` module provides functionality for extracting and processing stimulus-locked timeseries data from BOLD images. It includes methods for ROI-based analysis and event-locked responses. Combined, these modules collectively support a wide range of reliability assessments in MRI studies, from basic similarity metrics to advanced ICC calculations and timeseries analysis.