First International Society of Tractography conference

We participated in the first conference organized by the International Society of Tractography

Oct 16, 2025

MINNELab at MICCAI 2025 — Reconnecting with the Community in Daejeon 🇰🇷

Minnelab members had an inspiring experience at MICCAI 2025 in Daejeon, reconnecting with the vibrant community, presenting their work on federated learning and the MONet Bundle, and enjoying the warmth and culture of Korea.

Oct 11, 2025

Study trip to LA organized by WASP

Our group was represented at a study trip in LA visiting universities including: Caltech, UCLA, UC Irvine and companies as Jet Propulsion Lab at NASA, Amazon Web Services and Google.

Oct 4, 2025

MAIA at AIDA TechDays Workshop

MINNELab presented MAIA at the AIDA TechDays Workshop on 17 September 2025, showcasing its end-to-end AI workflows, active learning, and federated learning capabilities to the Swedish medical AI community.

Sep 17, 2025

Decomposing the effect of normal aging and Alzheimer’s disease in brain morphological changes via learned aging templates

Alzheimer’s disease (AD) subjects usually show more profound morphological changes with time compared to cognitively normal (CN) individuals. These changes are the combination of two major biological processes: normal aging and AD pathology. Investigating normal aging and residual morphological changes separately can increase our understanding of the disease. This paper proposes two scores, the aging score (AS) and the AD-specific score (ADS), whose purpose is to measure these two components of brain atrophy independently. For this, in the first step, we estimate the atrophy due to the normal aging of CN subjects by computing the expected deformation required to match imaging templates generated at different ages. We used a state-of-the-art generative deep learning model for generating such imaging templates. In the second step, we apply deep learning-based diffeomorphic registration to align the given image of a subject with a reference imaging template. Parametrization of this deformation field is then decomposed voxel-wise into their parallel and perpendicular components with respect to the parametrization of the expected atrophy of CN individuals in one year computed in the first step. AS and ADS are the normalized scores of these two components, respectively. We evaluated these two scores on the OASIS-3 dataset with 1,014 T1-weighted MRI scans. Of these, 326 scans were from CN subjects, and 688 scans were from subjects diagnosed with AD at various stages of clinical severity, as defined by clinical dementia rating (CDR) scores. Our results reveal that AD is marked by both disease-specific brain changes and an accelerated aging process. Such changes affect brain regions differently. Moreover, the proposed scores were sensitive to detect changes in the early stages of the disease, which is promising for its potential future use in clinical studies. Our code is freely available at https://github.com/Fjr9516/DBM_with_DL.

Apr 7, 2025

MICCAI Conference 2024

Our lab is attending the MICCAI conference to present our latest research in biomedical imaging.

Oct 10, 2024

Bounding tractogram redundancy

Proposes a principled definition of redundancy in diffusion MRI tractograms and an algorithm to remove superfluous streamlines while preserving anatomical coverage and connectivity. Demonstrates on public datasets that large fractions of streamlines can be pruned without degrading downstream analyses, improving storage and computation.

Jul 23, 2024