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Authors: Yuqian Li 1 ; Diana M. Sima 2 ; Sofie Van Cauter 3 ; Uwe Himmelreich 4 ; Yiming Pi 5 and Sabine Van Huffel 2

Affiliations: 1 University of Electronic Science and Technology of China, Katholieke Universiteit Leuven and IBBT-K.U.Leuven, China ; 2 Katholieke Universiteit Leuven and IBBT-K.U.Leuven, Belgium ; 3 University Hospitals of Leuven and Katholieke Universiteit Leuven, Belgium ; 4 Katholieke Universiteit Leuven, Belgium ; 5 University of Electronic Science and Technology of China, China

ISBN: 978-989-8425-89-8

Keyword(s): Glioma, Magnetic Resonance Spectroscopic Imaging (MRSI), Non-negative Matrix Factorization (NMF), Blind Source Separation (BSS).

Related Ontology Subjects/Areas/Topics: Applications and Services ; Biomedical Engineering ; Biomedical Signal Processing ; Computer Vision, Visualization and Computer Graphics ; Medical Image Detection, Acquisition, Analysis and Processing

Abstract: Finding the brain tumor tissue-specific magnetic resonance spectra and their corresponding spatial distribution is a typical Blind Source Separation (BSS) problem. Non-negative Matrix Factorization (NMF), which only requires non-negativity constraints, has become popular because of its advantages compared to other BSS methods. A variety of algorithms based on traditional NMF have been recently proposed. This study focuses on the performance comparison of several NMF implementations, including some newly released methods, in brain glioma tissue differentiation using simulated magnetic resonance spectroscopic imaging (MRSI) signals. Experimental results demonstrate the possibility of finding typical tissue types and their distributions using NMF algorithms. The (accelerated) hierarchical alternating least squares algorithm was found to be the most accurate.

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Paper citation in several formats:
Li, Y.; Sima, D.; Van Cauter, S.; Himmelreich, U.; Pi, Y. and Van Huffel, S. (2012). SIMULATION STUDY OF TISSUE TYPE DIFFERENTIATION USING NON-NEGATIVE MATRIX FACTORIZATION.In Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012) ISBN 978-989-8425-89-8, pages 212-217. DOI: 10.5220/0003734702120217

@conference{biosignals12,
author={Yuqian Li. and Diana M. Sima. and Sofie Van Cauter. and Uwe Himmelreich. and Yiming Pi. and Sabine Van Huffel.},
title={SIMULATION STUDY OF TISSUE TYPE DIFFERENTIATION USING NON-NEGATIVE MATRIX FACTORIZATION},
booktitle={Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012)},
year={2012},
pages={212-217},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003734702120217},
isbn={978-989-8425-89-8},
}

TY - CONF

JO - Proceedings of the International Conference on Bio-inspired Systems and Signal Processing - Volume 1: BIOSIGNALS, (BIOSTEC 2012)
TI - SIMULATION STUDY OF TISSUE TYPE DIFFERENTIATION USING NON-NEGATIVE MATRIX FACTORIZATION
SN - 978-989-8425-89-8
AU - Li, Y.
AU - Sima, D.
AU - Van Cauter, S.
AU - Himmelreich, U.
AU - Pi, Y.
AU - Van Huffel, S.
PY - 2012
SP - 212
EP - 217
DO - 10.5220/0003734702120217

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