Improved unsupervised physics-informed deep learning for intravoxel incoherent motion modeling and evaluation in pancreatic cancer patients.
Journal:
Magnetic resonance in medicine
Published Date:
Jun 9, 2021
Abstract
PURPOSE: Earlier work showed that IVIM-NET , an unsupervised physics-informed deep neural network, was faster and more accurate than other state-of-the-art intravoxel-incoherent motion (IVIM) fitting approaches to diffusion-weighted imaging (DWI). This study presents a substantially improved version, IVIM-NET , and characterizes its superior performance in pancreatic cancer patients.