Estimation of Brain Tissue Composition and Voxel Location in MR Spectroscopy Using Neural Networks

This work presents a machine learning method to estimate the tissue partial volumes of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF), in a given MR spectroscopy voxel, providing an alternative to the standard time‑intensive MRI segmentation pipeline. The tissue composition was determined from quantified metabolic concentrations using a neural networks regression model. Moreover, a classification model was trained to determine the brain region corresponding to a measured spectrum from both metabolic components and tissue volumes.