CSE 577 - Medical Imaging


General Info:

Instructor: Prof. Klaus Mueller
    Office hours: SUNY Korea B-471, W 2-3 pm (or send email for appointment)
    Phone:  032-626-1200
    Email: mueller@cs.sunysb.edu

    Office hours: 

Meeting time and venue:
    Class room 227, SUNY Korea, Tu Th 4:00-5:20 pm

    This course presents an introduction to the mathematical, physical, and computational principles underlying modern medical imaging systems. It will cover fundamentals of X-ray radiography, X-ray computed tomography (CT), ultrasonic imaging, nuclear imaging, magnetic resonance imaging (MRI), and functional MRI (fMRI), as well as more general concepts required for these, such as linear systems theory, the Fourier Transform, and numerical optimization. Popular techniques for the visualization, segmentation, and analysis of medical image data will also be discussed, as well as applications of medical imaging, such as image-guided intervention. The course material is well suited for students in computer science, biomedical engineering, and electrical engineering. It will be of appropriate difficulty for both undergraduate and graduate students.

   AMS 161 or MAT 127 or 132 or 142 (Calculus)
   AMS 210 or MAT 211 (Linear Algebra)
   or permission of instructor

   Required:  "Fundamentals of Medical Imaging, 2nd edition" by Paul Suetens, Cambridge University Press
    Lab projects: 50%
    Final project: 50%

Lab assignments:
    There will be 5-6 labs. We will use Matlab to implement these. Matlab is a fast way to prototype programs since most of the tedious routines (Fourier Transforms, linear algebra, etc.) have already been implemented. An introduction to Matlab will be given in class.

Final project:
    In the final project you can choose among several advanced topics or suggest your own. You will first write a proposal and then keep a log about your activites via a web page. At the end of the semester, you will present your project to the rest of the class and document your findings on the web page. The final project can use any programmig language (not only matlab). This is most useful when achieving high computational speed is also a goal.