Predicting Cerebral Partial Pathlength and Absorption Changes Using a Deep Learning Model: A Phantom Study

Abstract

We trained a deep learning model for predicting partial-pathlength and absorption changes in the brain. Evaluation on two-layer phantom experiments demonstrated the model’s efficacy in determining the partial-pathlength and absorption changes in the bottom layer.