Neuroimaging Standardization Process
White matter hyperintensities are important markers for cerebral microvascular disease, lacunar infarcts and microhemorrhages. It is seen to be beneficial to keep track of the lesion load and locations at each evaluation. The study aims to develop a quantitative and validated framework for automates segmentation of T2-flair brain images in CCVS repository, which is acquired from high isotropic resolution. Developing this procedure using machine learning algorithms will increase the robustness of classifiers, allow scientists to use the data for future hypothesis testing and facilitate the reliable re-analysis as algorithms evolve or improve. Therefore, the study aims to develop a standard pipeline for automated and comparative white matter hypertension classifiers of T2-flair data sets in CCVS repository and allow the data to be available through open science for future re-analysis of the raw data set.