Extending Automated Segmentation methods for Body Composition Analysis

Body composition, i.e., the proportion of fat and muscle tissues in the human body is related to the risk factors associated with a host of medical conditions. The muscle and fat tissues are target locations for the water- and fat-soluble drugs respectively used for cancer treatment. Consequently, the proportions of these tissues are believed to determine
the chemotherapy toxicity and efficacy. Therefore, the estimation of muscle and fat tissue proportions is an important task in research studies related to cancer prognosis and treatment.
I want to introduce a fully automatic framework for the segmentation of muscle and fat tissues from CT images to estimate body composition. TO BE CONT’D

Faculty Supervisor:

Mirza Faisal Beg

Student:

Partner:

Discipline:

Engineering

Sector:

Biotechnology; Health and Related Sciences & Technology; Technology

University:

Simon Fraser University

Program:

Globalink Research Award