Mathematical Image Analysis Group, Saarland University

Seminar Processing of Matrix-Valued Images

Summer Term 2008

Processing of Matrix-Valued Images

Dr. Stephan Didas (didas@mia.uni-saarland.de)

Summer Term 2008

Seminar (2h)

Notice for bachelor/master students of mathematics: This is a »Hauptseminar« in the sense of these study programs.

Important Dates – Description – Administrative details – Requirements – Overview of Topics

Important Dates

First meeting: Friday, February 22, 2008, 14:15, Bld. E1 1, Room 306

Sign-up deadline: Thursday, February 21, 2008.

Regular meetings during summer term 2008: Wednesdays, 16:15h, Bld. E1.1, room 306.

The schedule can be found here.
In addition, you can find some literature here.

Date of first regular meeting: Wednesday, April 30, 2008.

Description

Contents: The seminar will deal with the processing and visualisation of matrix-valued data. Such data is obtained, for example, from diffusion tensor magnetic resonance imaging (DT-MRI). We discuss imaging techniques where matrix-valued data arises, the question how to understand and visualise matrices, as well as regularisation and filtering methods. The images below show a section of a DT-MRI scan of the human brain and a filtered version of this data set with a modified nonlinear diffusion filter for matrix data.

Prerequisites: The seminar is suitable for students of visual computing, mathematics, and computer science with a basic background in mathematics and image analysis.

Language: Understanding scientific texts in English is indispensable. Talks and write-up can be in English or German.

Administrative details

Sessions: The first meeting has taken place Friday, February 22, 2008, 14:15h, Bld. E1.1, room 306. Regular sessions will be weekly during the summer term.

Requirements for successful participation («Schein»)

Regular attendance: It is expected that you attend all seminar meetings, except for provable important reasons (we check).

Talk: Talk duration is 30 min, plus 15 min for discussion. Please do not deviate significantly from this time schedule.
You may give a presentation using a data projector (»beamer«), overhead projector or blackboard, or mix these media appropriately. English is preferred as language of presentation; if you should decide to talk in German anyway, you must use slides in English.

Write-up: The write-up should summarise your talk, so some 3+ pages per speaker will be adequate in most cases. Electronic submission is preferred. File format for electronic submissions is PDF – text processor files (like .doc) are not acceptable. We recommend using LaTeX. Adhere to the standards of scientific referencing: Quotations and copied material (such as images) must be clearly marked as such, and a bibliography is required.

Mandatory consultation: Talk preparation has to be presented to your seminar supervisor not later than in the week before the talk is given. It's your responsibility to approach us timely and make your appointment!

Overview of Topics

Date	Speaker	Topic
30.04.	Waldemar Schefer	Adaptive structure tensors and their applications
	Sebastian Zimmer	A higher order structure tensor
07.05.	Jan Hendrik Dithmar	Diffusion tensor imaging: Introduction
	Markus Mainberger	Image processing for DT-MRI
14.05.	Franziska Huth	Visualisation of DT-MRI
	Nico Persch	Color schemes to represent the orientation of anisotropic tissues from diffusion tensor data
21.05.	Maria Luschkova	Oriented tensor reconstruction: tracing neural pathways from diffusion tensor MRI
	Luis Pizarro	Variational regularisation of multiple diffusion tensor fields
28.05.	Martin Simonovsky	Tensor visualisation and defect detection for nematic liquid crystals
04.06.	Yong-Chul Ju	Continuous tensor field approximation of diffusion tensor MRI data
	Yuliya Akkuzhyna	Tensor field interpolation with PDEs
11.06.	Alexey Bevetskiy	A local structure measure for anisotropic regularisation of tensor fields
	Oliver Demetz	PDEs for tensor image processing
18.06.	Verena Marold	A generic approach to diffusion filtering of matrix fields
	Gabriela Ghimpeteanu	Total variation regularization of matrix-valued images
25.06.	Nicolas Rickert	Bilateral filtering of diffusion tensor magnetic resonance imaging
	Muhammad Zeshen Afzal	Analysis of distance/similarity measures for diffusion tensor imaging
02.07.	Jonathan Bogdoll	Nonlocal means for diffusion tensor MRI
	Yan Cui	Tensor-valued median filtering and M-smoothing
09.07.	Sebastian Ziaja	A tensor approach to elastography analysis and visualisation

Stephan Didas / February 15 - July 10, 2008