Graduate Courses BIOE 2630BIOE 2630 - Methods in Image AnalysisCross-listed at CMU as 16-725 and 42-735Instructor: John Galeotti (galeotti+miia AT cs.cmu.edu) Teaching Assistant: TBA Credits: 3 Term: Spring Location: Carnegie Mellon University CFA 213 Description: The fundamentals of computational medical image analysis will be explored, leading to current research in applying geometry and statistics to segmentation, registration, visualization, and image understanding. Student will develop practical experience through projects using the National Library of Medicine Insight Toolkit ( ITK ), a new software library developed by a consortium of institutions including the University of Pittsburgh. In addition to image analysis, the course will describe the major medical imaging modalities and include interaction with practicing radiologists at UPMC. Prerequisites: Permission of the instructor, <jgaleotti AT cmu.edu>, knowledge of C++, vector calculus and basic probability. Required Text: "Machine Vision", Wesley E. Snyder & Hairong Qi Optional Text: "Insight into Images: Principles and Practice for Segmentation, Registration and Image Analysis", Terry S., Ed. Yoo (Editor) Course Objectives: To gain theoretical and practical skills in image analysis. Topics Covered: Class/Labratory Schedule: Lectures - Tuesday and Thursday from 10:30 - 11:45 AM Course Webpage: BIOE
2630 - Methods in Image Analysis |
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