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Abstract #0516

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

Eduardo Coello1, Molly F. Charney1, Tyler C. Starr1, Huijun Liao1, Marcia Louis2, and Alexander P. Lin1

1Radiology, Brigham and Women's Hospital, Boston, MA, United States, 2Electrical and Computer Engineering, Boston University, Boston, MA, United States

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.

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