COM SCI 168
Computational Methods for Medical Imaging
Description: Lecture, four hours; discussion, two hours; outside study, six hours. Requisites: course 32 or Program in Computing 10C with grade of C- or better, Mathematics 33A, one course from Civil and Environmental Engineering 110, Electrical and Computer Engineering 131A, Mathematics 170A, or Statistics 100A. Theory and practice of image acquisition including angiography, computed tomography (CT), and magnetic resonance (MR). Project-based course covers applied topics in medical imaging including image processing, atlasing, predictive modeling, personalized medicine, data driven and machine learning methods. Letter grading.
Units: 4.0
Units: 4.0
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Most Helpful Review
Spring 2020 - Overall this is a pretty chill class but you also learn a lot. You don't have to have ML experience coming into the class, and don't have to start working on the final project until Scalzo covers ML in class, which is nice. Workload is a couple homework assignments done in Google Colab using Python libraries to do image processing and stuff, plus the group project. Some of the homework problems seem tricky but the TAs do demos with extremely similar problems in discussion so it ends up being pretty straightforward. Most of the grade is the group project, which you work on for the later half of the quarter. You have a lot of leeway in choosing your topic and can have an advisor to help (mine was Scalzo and he was really good about explaining each part of the project and giving feedback on our progress). Scalzo doesn't grade it too strictly, but you do have to put effort into it.
Spring 2020 - Overall this is a pretty chill class but you also learn a lot. You don't have to have ML experience coming into the class, and don't have to start working on the final project until Scalzo covers ML in class, which is nice. Workload is a couple homework assignments done in Google Colab using Python libraries to do image processing and stuff, plus the group project. Some of the homework problems seem tricky but the TAs do demos with extremely similar problems in discussion so it ends up being pretty straightforward. Most of the grade is the group project, which you work on for the later half of the quarter. You have a lot of leeway in choosing your topic and can have an advisor to help (mine was Scalzo and he was really good about explaining each part of the project and giving feedback on our progress). Scalzo doesn't grade it too strictly, but you do have to put effort into it.
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