William M. Wells

massNet uses deep learning to classify spatial mass spectrometry data without preprocessing, achieving higher accuracy and faster speed than classical methods for tumor delineation in mouse brain tissue.

DDMReg improves diffusion MRI registration by using whole-brain and tract-specific information, showing better performance across diverse datasets.

The paper introduces msiPL, a deep learning model for analyzing MSI data, enabling efficient non-linear visualization and identification of biologically relevant patterns.