EE369C: Medical Image Reconstruction

Overview

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.

Course Information

See the information in the links on the left.

Announcements

Class for Nov 6 will be at the Glazer Learning Center over at the Lucas Center. This is the Ph.D. Oral Exam for Enho Gong, on the use of machine learning for medical image reconstrucion.

The talk starts at 1:30, with food at 1:15. If you don't know where the talk is, meet me in front of Packard at 1:15, and we can walk over together.

The final homework has been posted. It is due a week from Wednesday, due to the ISMRM abstract deadline this week.