Course Information


Image reconstruction methods are central to many of the new applications of medical imaging. This course will provide an introduction these techniques in a consistent framework by developing a sequence of software tools for the reconstruction of medical imaging data. The class will start with coverage of a number of common ideas that occur in a wide range of problems, including reconstructing images from non-uniformly sampled data, reconstruction from projection data, reconstruction from undersampled data, and automatically focusing images. Examples will be chosen from magnetic resonance imaging (MRI), x-ray computed tomography (CT) and positron emission tomography (PET).

Prerequisites: EE369A,B are recommended, but not required.

Class Time and Location

  • TTh 2:30-3:50

  • zoom link

  • Recordings available on canvas for Stanford affiliated people

Instructor Office Hours

  • Wednesday 1-2


  • Weekly homework and programming assignments (50%)

  • Project (50%)

  • People taking the P/NC will pass if they complete the homeworks.


The textbooks are available on-line, but you can also get them from Amazon.


Handbook of MRI Pulse Sequences
Matt A. Bernstein, Kevin F. King, Xiaohong Joe Zhou
Science Direct Link
amazon link

Principles of Computerized Tomographic Imaging
Aninash C. Kak, Malcolm Slaney
Link to On-Line PDF
amazon link


Student MATLAB
Now available free through Stanford

Other Useful Books

Computed Tomography Principles, Design, Artifacts, and Recent Advances
Jiang Hsieh
amazon link

Positron Emission Tomography: Basic Sciences
Dale L. Bailey, David W. Townsend, Peter E. Valk, Michael N. Maisey
Amazon Link