EECS 755	Fall 2006
Topics in Signal Processing: Image Reconstruction Algorithms

MW 1:30-3PM, 3433 EECS.  (3 credits)

Instructor:	Professor Jeff Fessler,	 Email: fessler AT umich DOT edu
		Office Hours: Wed 3-5pm in 3401 EECS, Phone: 763-1434

Text: Draft of chapters of book: Image reconstruction algorithms and analysis,
supplemented by papers from the literature, presented in part by students.

Goal: Bridge gap between EECS 516,556,564 and modern image formation literature.

Topics:	Image restoration; tomographic image reconstruction (X-ray CT, PET);
	reconstruction from Fourier samples and MR image reconstruction;
	regularization; special optimization algorithms; analysis of
	spatial resolution / noise / detectability for nonlinear algorithms.

Prerequisites: at least one of EECS 516, 556, or 564, or instructor permission.
Two of the three would be even better, and the ideal preparation would be
all three courses!

Enrollment / prerequisites / auditing.
Students who have had any of EECS 516, 556, 564 should enroll for grade; you
may audit the class only with instructor permission.  Students who have not
had any of those courses (or an equivalent) may audit if enrolled officially
as a "visitor," space permitting.

Grading:
	Homework	50%
	Project		30%
	Participation	20%
Examples of participation (in case it is not obvious):
		attending class (when not traveling to conferences),
		asking questions in class and/or privately,
		finding errors in book,
		suggesting problems,
		providing latex source for problem solutions,
		solving "open problems" mentioned in the book
			(some of which could merit a publication),
		implementing and evaluating or comparing algorithms in the book.

Web: http://www.eecs.umich.edu/~fessler/course/755

Books on Reserve at UMMU:
	M Bertero  P Boccacci
	Introduction to inverse problems in imaging
	IoP London 1998
	
	Curtis R Vogel
	Computational methods for inverse problems
	SIAM 2002

	Heinz W Engl  Martin Hanke  Andreas Neubauer
	Regularization of inverse problems
	Kluwer Dordrecht 1996