Methods In Medical Image Analysis - Spring 2008

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

Instructor: John Galeotti
(galeotti+miia ATcs.cmu.edu)

Teaching Assistant: Andrew Whitord
(asw35+miia ATpitt.edu)

Course Goals

To gain theoretical and practical skills in general image analysis, and medical image analysis in particular. 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 via the Shadow Program.

Prerequisites

knowledge of C++, vector calculus and basic probability

Requirements and Grading

• Method: The point system
  • Each question or problem in a quiz or homework is assigned a point value
  • Your cumulative grade for quizzes [or homeworks] is (the sum of points your earned on all quizzes) divided by (the sum of points you could have earned on all quizzes)
  • So, your course grade is equally affected whether you miss 1 point on a 3 point quiz, or you miss 1 point on a 10 point quiz. (This is not the case for the more typical "averaged percentages" method.)
• Attendance: Required
  • Checked using Quizzes
  • On some days the quiz may be signing your name on the roll.
  • Some days may not have any quiz at all (attendance not checked).
• Quizzes: 20%
  • Not present / not taken = 0
  • Lowest 3 are dropped (the 3 on which you missed the most points)
  • So, if you are gone for a week-long conference, then you will have only 1 quiz left to drop.
  • In case of extenuating circumstances requiring further absence, talk to me, but I must be fair to the class (= harder on you).
• Homework: 30%
• Shadow Program: 10%
  • You submit 5 reports, 1 for each of the 5 radiology stations.
  • The first time you miss a station for which you are scheduled (without good reason), you may contact your instructor to reschedule for 50% credit for that station.
  • If you do not show up a second time, you will be removed from the Shadow Program, get a 0 for all subsequent stations, and your instructor will be very unhappy with you.
• Final Project: 40%
  • 15% presentation
  • 25% code

Textbooks

• Required
  • Machine Vision, Wesley E. Snyder & Hairong Qi
• Officially Recommended
  • Insight into Images: Principles and Practice for Segmentation, Registration and Image Analysis, Terry S. Yoo (Editor)
• Useful if you want to build your bookshelf
  • Handbook of Medical Imaging: Processing and Analysis, Isaac Bankman (Editor)
  • Computer Vision, Linda Shapiro
  • Algorithms for Image Processing and Computer Vision, J. R. Parker
  • Machine Vision: Theory, Algorithms, Practicalities, E. R. Davies

Schedule

Posted online at http://www.cs.cmu.edu/~galeotti/methods_course/
The lecture schedule (and some topics) are subject to change, depending in part on class interest and involvement.