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CAP5516 – Spring 2024

Medical Image Computing (3 Credit Hours)

Course Description and learning outcome

Imaging science is experiencing tremendous growth in the US. Biomedical imaging and its analysis are fundamental to understanding, visualizing, and quantifying medical images in clinical applications. With the help of automated and quantitative image analysis techniques, disease diagnosis will be easier/faster and more accurate, and leading to significant development in medicine in general. This course provides students with the foundation necessary for understanding, visualizing, and quantifying medical images with computational methods. In this course, we will examine some central topics and key techniques in computer vision and medical image processing, in particular employing Deep Learning, through reading, writing reviews on, presenting, discussing the most recent papers published on computer vision and medical imaging conferences (e.g., CVPR, ICCV, ECCV, MICCAI) as well as working on course projects.

Course learning outcome: The goal of the course is to give students the background and skills for graduate research in medical image computing. Through the class, the students are expected to understand in-depth the state-of-the-art approaches to various topics in medical image processing. By the end of this course, the students will also develop the skills that are vital to their graduate research, such as writing paper reviews, presenting technical papers, analyzing the strengths and weaknesses of the research papers, and identifying open questions and directions for future research.

Course Syllabus