Students will gain theoretical and practical skills in medical image analysis, including skills relevant to general image analysis. 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 new v4 of the National Library of Medicine Insight Toolkit ( ITK ), a popular open- source software library developed by a consortium of institutions including Carnegie Mellon University and the University of Pittsburgh. In addition to image analysis, the course will include interaction with clinicians at UPMC.

NEW FOR S12: ITKv4 includes a new simplified interface and many new features, several of which will be explored in the class. Extensive expertise with C++ and templates is no longer necessary but still helpful).

*** Some or all of the class lectures may also be videoed for public distribution.

website: http://www.cs.cmu.edu/~galeotti/methods_course/

Prerequisites: Knowledge of vector calculus, basic probability, and C++ or python (most lectures will use C++).