Medical Image Analysis Technologies for Advanced Clinical Decision Support
Friday, Jan. 15, 2-3 p.m.
Faculty candidate seminar Dr. Karteek Popuri (Simon Fraser University)
Hospitals and clinics nowadays have easy access to digital medical image scanning systems such as magnetic resonance imaging (MRI), positron emission tomography (PET) and computed tomography (CT), that can provide physicians with detailed high-resolution images of the human body. Even though physicians have these vivid medical images at their disposal, presently they are limited to performing visual quantitative assessment of these images for clinical purposes, which is not only tedious and time-consuming, but also prone to intra- and inter-expert disagreement. My broad research goal is to address these challenges that are inherent in the manual interpretation of complex high-dimensional medical image data, through the development of computerized medical image analysis pipelines, that can automatically translate raw imaging data into clinically relevant inferences that can aid in the clinical decision-making processes related to disease diagnosis, prognosis and treatment planning. In this talk, I will present an overview of my research progress thus far in the area of medical image analysis and layout a roadmap for future research directions. The content of the presentation will touch upon several aspects of medical image analysis ranging from image segmentation and registration to the design of machine learning frameworks for disease status prediction using image features. Furthermore, I will briefly discuss my recent efforts towards building a cloud-based platform CERAMICCA that enables high throughput big data processing and aids in the translation of medical image analysis tools to the clinical end-user.
Presented by Department of Computer Science