Methods In Medical Image Analysis - Spring 2012

BioE 2630 (Pitt) : 16-725 (CMU RI) : 18-791 (CMU ECE) : 42-735 (CMU BME)

John Galeotti
Teaching Assistants

Vikas R.S.


“Jackie” Chen


Course Goals

To 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 via the Shadow Program.

Important Note about Videoing of Lectures

Some or all of the class lectures will be videoed for public distribution.  The camera will be in the back of the room, and we will attempt to point it over your heads. However, some students may at times be seen (usually only partially) by the camera. If you object to this, please see the instructor to discuss seating options to avoid ever being seen by the camera. Also, any audio in the classroom may be picked up and recorded by either the camera or the instructor's microphone. If on a particular occasion you want your voice removed from some part of the recording, then please inform the instructor after class that day.


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

NEW THIS YEAR:  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).

Requirements and Grading



Posted online at
The lecture schedule (and some topics) are subject to change, depending in part on class interest and involvement.