COMPUTATIONAL METHODS FOR MEDICAL IMAGE ANALYSIS
Review of advanced medical image analysis techniques. Covers advanced segmentation and registration methods. Describes the use and extension of statistical and machine learning methods for medical image analysis tasks.
Prerequisites & course information
Requisites: Graduate/professional standing Course Designation: Grad 50% - Counts toward 50% graduate coursework requirement Repeatable for Credit: No Last Taught: Spring 2026 Learning Outcomes: 1. Implement advanced ideas from machine learning, statistics, and computer vision for medical image analysis tasks. Audience: Graduate 2. Develop a deep technical understanding of the machine learning and statistical ideas being utilized in contemporary research in this area, and identification of blockers where research efforts can be focused Audience: Graduate Learning Outcomes: 1. Implement advanced ideas from machine learning, statistics, and computer vision for medical image analysis tasks. Audience: Graduate 2. Develop a deep technical understanding of the machine learning and statistical ideas being utilized in contemporary research in this area, and identification of blockers where research efforts can be focused Audience: Graduate
Sources
- Course catalogue ↗2026-2027
- Catalogue entry ↗
Catalogue variants
- COMPUTATIONAL METHODS FOR MEDICAL IMAGE ANALYSIS · 3 credits.