Malte Hoffmann is a faculty member in Radiology at Harvard Medical School and Affiliated Faculty in the Health Sciences and Technology Division at MIT. He received a Bachelor’s degree in physics from the University of Paris XI and a Master’s degree and PhD from the University of Cambridge, specializing in the correction of subject motion for brain magnetic resonance imaging (MRI).
Dr. Hoffmann’s research focuses on algorithms for medical image processing and analysis using artificial intelligence. His work spans innovations in deep learning, computer vision, and MRI acquisition. He is particularly interested in registration, which captures the spatial relationship between objects from images, and in leveraging this information to advance applications with clinical impact, such as fetal MRI.
PhD in MRI Physics, University of Cambridge
1. Hoffmann M, Billot B, Greve DN, Iglesias JE, Fischl B, Dalca AV. SynthMorph: learning contrast-invariant registration without acquired images. IEEE Transactions on Medical Imaging (TMI). 2022;41(3):543-58.
2. Hoopes A, Mora JS, Dalca AV, Fischl B*, Hoffmann M* (*equal contribution). SynthStrip: skull-stripping for any brain image. NeuroImage. 2022;260:119474.
3. Hoopes A, Hoffmann M, Fischl B, Guttag J, Dalca AV. Learning the Effect of Registration Hyperparameters with HyperMorph. Journal of Machine Learning for Biomedical Imaging (MELBA). 2022;IPMI 2021 Special Issue:1-30.
2020, 2021 ISMRM Summa Cum Laude Merit Awards for top 5% abstract
2020 NIH K99/R00 Pathway to Independence Award
2019 ISMRM Detection & Correction of Motion in MRI & MRS Study Group Award