Exploring Multimodal Deep Learning Approaches for Coronary Artery Disease Diagnosis
Popov, Maxim
Popov, Maxim
Author
Supervisor
Department
Computer Vision
Embargo End Date
2025-05-30
Type
Thesis
Date
2025
License
Language
English
Collections
Research Projects
Organizational Units
Journal Issue
Abstract
Coronary Artery Disease (CAD) is a prevalent cause of death in the modern world, with about 20 million victims every year. Limited annotated data, inter-observer variability, and the intrinsic complexity of angiographic imaging challenge its diagnosis. This thesis presents a novel deeplearning framework to enhance coronary artery disease (CAD) diagnosis through multimodal analysis of Xray coronary angiograms. We develop several interrelated contributions to address these issues that combine advanced contrastive learning and vision-language modeling.
Citation
Maxim Popov, “Exploring Multimodal Deep Learning Approaches for Coronary Artery Disease Diagnosis,” Master of Science thesis, Computer Vision, MBZUAI, 2025.
Source
Conference
Keywords
Vision-Language Modeling, Medical Image Analysis, Grounding LLMs