Comparison of traditional brain segmentation tools with 3D self-organizing maps

David Dean, Krishnamurthy Subramanyan, Janardhan Kamath, Fred Bookstein, David Wilson, David Kwon, Peter Buckley

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

Abstract

Algorithm-assisted 3D MR brain segmentation may be significantly faster than manual methods and produce visually pleasing results. We tested two- and three-dimensional region growing (2DRG and 3DRG) and selforganizing map (SOM) algorithms for segmentation of the cerebral ventricles. The SOM algorithm provides the greatest times savings, 12:1, over manual segmentation. Concern for reproducibility of algorithm-assisted segmentation motivated an intra-operator comparative study of these and manual segmentation methods. One of us, DK, segmented the cerebral ventricles from 5 3D MR-scan data sets three times manually and with the three algorithms. When variability is measured as the shape variance of derived landmarks sets, the three algorithm-assisted methods show less intra-operator variability than manual segmentation. The 2DRG and 3DRG segmentations show more variability than SOM. Of the 4 methods, SOM segmentation requires the fewest operator decisions.

Original languageEnglish (US)
Title of host publicationInformation Processing in Medical Imaging - 15th International Conference, IPMI 1997, Proceedings
EditorsGene Gindi, James Duncan
PublisherSpringer Verlag
Pages393-398
Number of pages6
ISBN (Print)3540630465, 9783540630463
StatePublished - Jan 1 1997
Event15th International Conference on Information Processing in Medical Imaging, IPMI 1997 - Poultney, United States
Duration: Jun 9 1997Jun 13 1997

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume1230
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other15th International Conference on Information Processing in Medical Imaging, IPMI 1997
CountryUnited States
CityPoultney
Period6/9/976/13/97

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ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Cite this

Dean, D., Subramanyan, K., Kamath, J., Bookstein, F., Wilson, D., Kwon, D., & Buckley, P. (1997). Comparison of traditional brain segmentation tools with 3D self-organizing maps. In G. Gindi, & J. Duncan (Eds.), Information Processing in Medical Imaging - 15th International Conference, IPMI 1997, Proceedings (pp. 393-398). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 1230). Springer Verlag.