Welcome to the Medical Image Computing Lab
We are a research group at the United Arab Emirates University, Department of Computer Science and Software Engineering, College of Information Technology. Our lab, led by Dr. Rafat Damseh, focuses on developing AI and machine learning solutions for medical image analysis, with applications spanning cancer diagnostics, cerebrovascular modeling, brain connectivity, and dental AI.
Dr. Damseh established MEDIC at UAEU in 2021 and co-directs the Cognition, AI and Robotics Lab (CAIR) under the Industry 4.0 Initiative. Prior to UAEU, he led machine learning projects at the Computational Clinical Neuroimaging Group at MGH Martinos Center for Biomedical Imaging, Harvard Medical School, and earned his Ph.D. in Biomedical/Computer Engineering from Polytechnique Montréal.
Research Focus
Our research applies AI and computational methods to high-dimensional, multi-scale medical imaging data for translational and fundamental studies. Key areas include:
- Cerebrovascular Analysis and Modeling: Automated reconstruction and geometric graph modeling of brain microvasculature, diffusion MRI biomarker development, and hemodynamic simulations for understanding microstrokes and cerebrovascular diseases.
- Brain Imaging & Connectivity: Diffusion MRI (dMRI) brain connectomics and structural connectivity analysis, MRI biomarker development for neurovascular conditions, multimodal EEG–fNIRS integration using transformer-based architectures for epileptic seizure pattern decoding, and anatomical modeling from MRI, CT, and two-photon microscopy.
- Medical Image Analysis & Cancer Diagnostics: Foundation models and large vision models for precision oncopathology, computational pathology for breast and colorectal cancer prognostics, and automated tissue characterization from whole-slide images (WSI).
- Dental AI: Deep learning frameworks for automated orthodontic assessment using 3D intraoral scans and 2D clinical images, including tooth rotation estimation and landmark detection.
Open Source Tools
We develop and maintain several open-source software tools used by leading laboratories worldwide, including at Harvard Medical School, Boston University, and the University of Illinois at Chicago:
- VascGraph — Vascular network segmentation, graph modeling, and anatomical analysis
- VirtualMRI — Monte Carlo simulation of MRI responses at the microscopic scale
- AngioPulse — Pulsatile blood flow dynamics simulation in cerebral microvascular networks
Collaborations
We collaborate with leading institutions worldwide, including McGill University, University of Montreal and Polytechnique Montréal, Harvard Medical School, Boston University, KU Lauven, Weill Cornell Medicine - Qatar, and the Brain Cognition and Brain Disease Institute at SIAT.
Funding
Our research is supported by competitive grants, including the UAEU Strategic Research Program (AED 737K) for AI-enhanced precision oncopathology, the AUA–UAEU Joint Research Program (AED 300K) for deep subclinical MRI predictions, the UAEU Program for Advanced Research (AED 715K) on neural processing in human-computer interaction with LLMs, and multiple SURE Plus and SDG research grants.
Join Us
We are always looking for motivated students and researchers to join our team. See our Openings page for current opportunities in medical AI, brain imaging, computational pathology and dental AI.
Contact
Location: E1 Building, Room 3070, Department of Computer Science and Software Engineering
Address: P.O. Box 15551, Al Ain, United Arab Emirates
Email: rdamseh@uaeu.ac.ae
