We have updated our histological atlas NextBrain with an improved version that better models the brainstem regions. Segmentation tool:

Our tool SynthSR has been featured in Stanford University’s AI Index Report 2024, as one of the AI medical breakthroughs of 2023; please see  Stanford’s “AI Index”

After seven (7!) years of work with over 20 researchers at 10 different institutions, we are super excited to release NextBrain, a next-generation probabilistic atlas of the human brain with

We have very excited to announce that we have been awarded a 3-year NIH grant (1RF1AG080371-01A1) to develop acquisition-independent machine learning for morphometric analysis of

It’s been a long journey, but our paper “Supervision by Denoising” (SUD) is available in PAMI! You can also find a preprint here. SUD is fairly easy to implement and allows

Changes in the LEMoN group! Sean I Young has been promoted to Instructor (congrats, Sean!). We have four incoming postdocs this summer: Kathleen E. Larson, joining from Vanderbilt (jointly

Our group has two early accepted papers at MICCAI 2023: “Domain-agnostic segmentation of thalamic nuclei from joint structural and diffusion MRI” (Henry Tregidgo et al): presents a

Our works on segmentation (SynthSeg) and joint super-resolution & synthesis of brain MRI scans of any orientation, resolution, and pulse sequence have been accepted for publication in

Our joint synthesis/super-resolution method for low-field MRI acquired with portable scanners has been featured in Physics World! You can read the article . SynthSR is a collaboration with

Our paper “Quantitative Brain Morphometry of Portable Low-Field-Strength MRI Using Super-Resolution Machine Learning” has been published in Radiology. We present a machine learning