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

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. ISBN 978-80-214-3612-1.

Basic information

Original name

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

Name in Czech

Srovnání klasifikačních algoritmů pro mozkové tkáně s využitím multimodální metriky efektivity

Authors

JANOUŠOVÁ, Eva and Daniel SCHWARZ

Edition

Brno, Analysis of Biomedical Signals and Images - Proceedings of 19th Biennal International Eurasip Conference BIOSIGNAL 2008, p. 1-4, 4 pp. 2008

Publisher

VUTIUM Press

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Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

20200 2.2 Electrical engineering, Electronic engineering, Information engineering

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

Organization unit

Faculty of Medicine

ISBN

978-80-214-3612-1

UT WoS

000303717200049

Keywords in English

computational neuroanatomy;image analysis;classification;segmentation

Tags

CLASSIFICATION, computational neuroanatomy, Image analysis, segmentation

Tags

International impact, Reviewed

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Abstract

V originále

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.

In Czech

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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Links

GP102/07/P263, research and development project

Name: Nelineární multimodální registrace pro automatickou morfometrii obrazů mozku z MRI založenou na anatomicky omezených prostorových deformacích Investor: Czech Science Foundation, Nonlinear multimodal registration for automatic morphometry of MRI brain images based on anatomically constrained spatial deformations