Maintainer: Juan A. Arias (iguanamarina@protonmail.com)
Main Goal: To load PET data, re-organize it as a data.frame, estimate Simultaneous Confidence Corridors for one or multiple groups of patients, and compare them in order to find brain areas whose activity falls out of estimated confidence intervals, thus evidencing changes in brain activity in that region compared to the counterpart.
Description: This package provides auxiliary functions for calculating Simultaneous Confidence Corridors (SCCs) on PET neuroimaging data. It includes functions to load neuroimaging and demographic data in the standard format required, and assists in various tasks throughout the process. Overall, this package is designed to help with the replication process of a cornerstone paper from my thesis “Development of statistical methods for neuroimage data analysis towards early diagnostic of neurodegenerative diseases” and it is best followed using the scripts available at the designated GitHub Repository. Overall, this serves as a support package, although it can work as a stand-alone package for other projects related to PET imaging.
References:
Wang Y, Wang G, Wang L, Ogden RT. Simultaneous confidence corridors for mean functions in functional data analysis of imaging data. Biometrics. 2020 Jun;76(2):427-437. doi: 10.1111/biom.13156. Epub 2019 Nov 6. PMID: 31544958; PMCID: PMC7310608.