About
MINNE Lab develops mathematically grounded computational tools for medical image analysis, at the Division of Biomedical Imaging, KTH Royal Institute of Technology. The group's work emphasises efficiency and clinical translation — building methods that ultimately support physicians in practice, across neuroimaging, oncology, and biomechanics.
Current research
-
Magnetic resonance elastography
Characterising the mechanical properties of the brain in Parkinson's disease, Alzheimer's disease, brain tumours, and multiple sclerosis — aiming at earlier diagnosis and better tracking of disease progression.
-
Brain connectivity analysis
AI-based methods for diffusion-MRI tractography, targeting improved specificity in the extraction of neural tracts and more reliable connectivity pipelines.
-
Synthetic MRI aging
Generative deep-learning models that produce MRI simulating age-related brain changes, validated against mild cognitive impairment and Alzheimer's cohorts.
-
Cancer image analysis
Deep-learning methods for 3D radiological imaging across modalities — digital breast tomosynthesis, ultrasound, PET, and MRI/CT — with a focus on quantitative, reproducible pipelines.
Earlier projects include Deep Segment (Eurostars-funded segmentation workflows), Biomechanics at Interactive Speed, Trabecular Bone Microstructure Analysis, Blood Vessel Analysis for atherosclerosis, and Tensor Voting in Medical Imaging (Swedish Research Council).
Group leader
Rodrigo Moreno
Professor · Division of Biomedical Imaging, Department of Biomedical Engineering and Health Systems, KTH
Rodrigo Moreno is Professor in the Division of Biomedical Imaging at KTH Royal Institute of Technology, with an affiliation to the Department of Neurobiology, Care Sciences and Society (NVS) at Karolinska Institute. He earned his PhD in computer vision at the Polytechnic University of Catalonia in 2010, and held postdoctoral and assistant-professor positions at Linköping University from 2010 to 2015 before joining KTH. His research concerns inverse problems in medical image processing — with a focus on mathematical modelling, perceptual methods, and efficiency.
Collaborations & funding
Division of Biomedical Imaging
Department of Biomedical Engineering and Health Systems, KTH Royal Institute of Technology — Hälsovägen 11 C, Stockholm.
Karolinska Institute & industry
Affiliated with the Department of Neurobiology, Care Sciences and Society (NVS) at Karolinska Institute. Active collaborations with industry partners on clinical product development.
Public and competitive grants
Projects have been supported by the Swedish Research Council, Eurostars, and institutional KTH funding. Specific acknowledgements appear in individual publications.
MINNE Lab — KTH Royal Institute of Technology
Department of Biomedical Engineering and Health Systems · Hälsovägen 11 C, Stockholm, Sweden
rodmore@kth.se →