CSE 5504
Geometric Computing for Biomedicine
With the advance of imaging technologies deployed in medicine, engineering and science, there is a rapidly increasing amount of spatial data sets (e.g., images, volumes, point clouds) that need to be processed, visualized, and analyzed. This course will focus on a number of geometry-related computing problems that are essential in the knowledge discovery process in various spatial-data-driven biomedical applications. These problems include visualization, segmentation, mesh construction and processing, and shape representation and analysis. This course consists of lectures that cover theories and algorithms, and it includes a series of hands-on programming projects using real-world data collected by various imaging techniques (e.g., CT, MRI, electron cryomicroscopy). Prerequisites: CSE 332 (or proficiency in programming in C++ or Java or Python) and CSE 247.
Instructors
Reviews
So easy! Easiest 500 level class even easier than undergrad courses I took!
12/27/2025
He sometimes is a really mean person and would not be happy to help you understand some basic math concept, probably he think it's too easy and waste his time. However, a lot of extra credits which makes me can skip final project(18% of total). Expected to spend a lot of time on homework like a 6 credit class. Teaching is not bad.
12/20/2020
The amount of homework if you're not familiar with Mathematica is unreasonable, Ofttenly taking 20-40 hours for biweekly Homeworks
10/27/2020
Professor Ju is one of the best professors I've had ever. He knows what he's talking about, and tries to make things interesting, fun, and worthwhile. He is also a genuinely nice guy that cares for the students he teaches. His classes involve a lot of work though.
1/8/2012