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Comparison Of Brain Tissue Classification Algorithms With The Use Of Multimodal Efficiency Measure

Basic information
Original title:Comparison Of Brain Tissue Classification Algorithms With The Use Of Multimodal Efficiency Measure
Authors:Eva Janoušová, Daniel Schwarz
Further information
Citation:JANOUŠOVÁ, Eva and Daniel SCHWARZ. Comparison Of Brain Tissue Classification Algorithms With The Use Of Multimodal Efficiency Measure. In Analysis of Biomedical Signals and Images - Proceedings of 19th Biennal International Eurasip Conference BIOSIGNAL 2008. Brno: VUTIUM Press, 2008. p. 1-4, 4 pp. ISBN 978-80-214-3612-1.Export BibTeX
@inproceedings{771729,
author = {Janoušová, Eva and Schwarz, Daniel},
address = {Brno},
booktitle = {Analysis of Biomedical Signals and Images - Proceedings of 19th Biennal International Eurasip Conference BIOSIGNAL 2008},
keywords = {computational neuroanatomy;image analysis;classification;segmentation},
language = {eng},
location = {Brno},
isbn = {978-80-214-3612-1},
pages = {1-4},
publisher = {VUTIUM Press},
title = {Comparison Of Brain Tissue Classification Algorithms With The Use Of Multimodal Efficiency Measure},
year = {2008}
}
Original language:English
Field:Use of computers, robotics and its application
Type:Article in Proceedings
Keywords:computational neuroanatomy;image analysis;classification;segmentation

A multimodal measure for comparison of efficiency of classification algorithms is proposed. The algorithms selected for brain tissue classification in 3-D MRI images are the well-known k-NN and k-means classifiers which were adapted to the image data in the common stereotaxic space. The efficiency measure combines Jaccard coefficient, modified Rand index and Connectivity coefficient. Results are presented in 3-D plots with the use of ellipsoids instead of frequently used 1-D plots or tables.

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