Ruud J. G. van Sloun

This paper presents a benchmark challenge to compare machine learning models for GABA-edited MRS reconstruction using reduced transients, finding that deep learning models achieve comparable metrics to conventional methods.

This study compares KalmanNet, an explainable BMI decoder, with deep-learning and Kalman filter models, finding it achieves comparable performance while offering interpretability.

The paper develops a deep learning model to automate fetal intracranial volume segmentation from 3D ultrasound and finds sex differences in ICV and growth.