Medical Image Analysis:
Medical images, such as those obtained through Magnetic resonance imaging (MRI), computerized tomorgrapy (CT) scan, Fundus photograph for the interior surface of the eye etc., are ubiquitous in modern medicine. With easy accessibility and affordability of these equipments, unprecedented amount of patient data is available, thus providing opportunities for automated prevention, diagnosis and treatment of diseases.
At Applied Computer Vision and Image Analysis lab we focus on designing and developing novel algorithms for:
- Accurate boundary detection and tracking of deforming structures from time-varying medical images (e.g., cardiac MRI).
- Early detection of glaucoma in retinal images.
- Shape analysis of human brain cortical structures using MRI volumes.
Computer vision aims to artificially replicate the human visual perceptions. It deals with the science and technology of processes related to the acquisition of images, analysis of images and sequence of images to extract useful information, and to the development of artificial cognitive systems that “see.” In our lab we focus on the following subfields of computer vision.
- Object Tracking
- Object detection and recognition
- Face alignment
Knowledge representation and reasoning, knowledge-based systems, medical information systems; machine learning; natural language processing; perceptual interfaces and human/computer interaction; robotics; speech understanding; vision.