NeuroHackademy2025/func-struct_extractor

AI Summary: Create a parent function that acts as a dispatcher, selecting and calling the correct data extraction utility function based on the desired output type (e.g., white matter tract profiles or qT1 map tissue properties). This function will enhance the flexibility of the func-struct_extractor package, allowing it to handle various data sources and extraction needs.

AI Summary: Test the functionality of code generated by ChatGPT for the func-struct_extractor project. This involves evaluating functions created to extract properties from structural data (like white matter tracts and qT1 maps) using surface and volumetric labels, and deciding whether to integrate them into the project.

AI Summary: Create a Python script to extract mean values of specified variables from regions of interest (ROIs) in volumetric neuroimaging data. The script should take as input volumetric NIfTI label files, structural images, and a list of variables. The output should be a Pandas DataFrame containing subject ID, ROI, and the mean values for each variable within each ROI.

AI Summary: Develop a function, `native_label_2_fsaverage`, that transforms a surface label from native brain space to fsaverage space. This is an extension of the `func-struct_extractor` project, enhancing its ability to handle surface labels from various structural data sources.

AI Summary: Create a function that transforms a surface label from fsaverage space to native surface space. This is part of a larger project to build a flexible package for extracting properties from various structural data using surface and volumetric labels.

AI Summary: Create a Python script that transforms a volumetric brain label from native space to MNI space. This script will be integrated into the func-struct_extractor package, expanding its functionality to handle various structural data types and coordinate systems.

AI Summary: Create a function, `vol_roi_2_surf`, that converts volumetric labels (e.g., from a 3D brain image) into surface labels. The output should be an array of indices corresponding to the vertices or voxels included within the specified volumetric label. This function will extend the functionality of the `func-struct_extractor` package to handle both surface and volumetric data for extracting structural properties.