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.
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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
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 20200 2.2 Electrical engineering, Electronic engineering, Information engineering
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
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
Changed by Changed by: doc. Ing. Daniel Schwarz, Ph.D., učo 195581. Changed: 2/7/2008 16:06.
Abstract
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.
Abstract (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.
Links
GP102/07/P263, research and development projectName: 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
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