STATISTICAL METHODS FOR MEDICAL IMAGE ANALYSIS

Prerequisites & course information

Requisites: Graduate/professional standing Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Fall 2026 Learning Outcomes: 1. Implement the key concepts of biomedical image processing and analysis Audience: Graduate 2. Describe the key concepts of statistical inference procedures for single and multiple images Audience: Graduate 3. Apply scalable computation in breaking bigger imaging problems into smaller computable problems Audience: Graduate 4. Describe functional data analysis (FA), geometric data analysis (GDA) and topological data analysis (TDA) methods in analyzing biomedical images Audience: Graduate Learning Outcomes: 1. Implement the key concepts of biomedical image processing and analysis Audience: Graduate 2. Describe the key concepts of statistical inference procedures for single and multiple images Audience: Graduate 3. Apply scalable computation in breaking bigger imaging problems into smaller computable problems Audience: Graduate 4. Describe functional data analysis (FA), geometric data analysis (GDA) and topological data analysis (TDA) methods in analyzing biomedical images Audience: Graduate