Deep learning intravoxel incoherent motion modeling: Exploring the impact of training features and learning strategies.
Journal:
Magnetic resonance in medicine
Published Date:
Mar 13, 2023
Abstract
PURPOSE: The development of advanced estimators for intravoxel incoherent motion (IVIM) modeling is often motivated by a desire to produce smoother parameter maps than least squares (LSQ). Deep neural networks show promise to this end, yet performance may be conditional on a myriad of choices regarding the learning strategy. In this work, we have explored potential impacts of key training features in unsupervised and supervised learning for IVIM model fitting.