14th IFAC Symposium on System Identification, SYSID 2006

SYSID-2006 Paper Abstract


Paper WeSP2.1

Van Huffel, Sabine (Katholieke Univ. Leuven), Laudadio, Teresa (Katholieke Univ. Leuven)

Magnetic Resonance Spectroscopic Imaging: A Survey of Quantification and Classification Algorithms

Scheduled for presentation during the Semi-Plenary Session "Semi-Plenary II" (WeSP2), Wednesday, March 29, 2006, 14:00−15:00, Banquet Room

14th IFAC Symposium on System Identification, March 29 - 31, 2006, Newcastle, Australia

This information is tentative and subject to change. Compiled on July 17, 2018

Keywords Biological Systems, Machine Learning and Data Mining


The purpose of this paper is to provide a survey of a few but significant methods currently used by the Nuclear Magnetic Resonance (NMR) community to quantify and classify MR Spectroscopic Imaging (MTSI) signals. In particular, several time-domain algorithms, able to extract from MRSI data useful information about metabolite concentrations, will be outlined. Furthermore, some methods able to exploit this information to detect tumors and classify their grade of malignancy will also be given. Finally, a very recent tissue typing technique, based on the use of a statistical method called canonical correlation analysis, will be described.