Morphometric analysis of brain structures for improved discrimination

Li Shen, James Ford, Fillia Makedon, Yuhang Wang, Tilmann Steinberg, Song Ye, Andrew Saykin

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

8 Citations (Scopus)

Abstract

We perform discriminative analysis of brain structures using morphometric information. Spherical harmonics technique and point distribution model are used for shape description. Classification is performed using linear discriminants and support vector machines with several feature selection approaches. We consider both inclusion and exclusion of volume information in the discrimination. We perform extensive experimental studies by applying different combinations of techniques to hippocampal data in schizophrenia and achieve best jackknife classification accuracies of 95% (whole set) and 90% (right-handed males), respectively. Our results find that the left hippocampus is a better predictor than the right in the complete dataset, but that the right hippocampus is a stronger predictor than the left in the right-handed male subset. We also propose a new method for visualization of discriminative patterns.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science
EditorsR.E. Ellis, T.M. Peters
Pages513-520
Number of pages8
Volume2879
EditionPART 2
StatePublished - 2003
Externally publishedYes
EventMedical Image Computing and Computer-Assisted Intervention, MICCAI 2003 - 6th International Conference Proceedings - Montreal, Que., Canada
Duration: Nov 15 2003Nov 18 2003

Other

OtherMedical Image Computing and Computer-Assisted Intervention, MICCAI 2003 - 6th International Conference Proceedings
CountryCanada
CityMontreal, Que.
Period11/15/0311/18/03

Fingerprint

Brain
Support vector machines
Feature extraction
Visualization

ASJC Scopus subject areas

  • Computer Science (miscellaneous)
  • Engineering(all)

Cite this

Shen, L., Ford, J., Makedon, F., Wang, Y., Steinberg, T., Ye, S., & Saykin, A. (2003). Morphometric analysis of brain structures for improved discrimination. In R. E. Ellis, & T. M. Peters (Eds.), Lecture Notes in Computer Science (PART 2 ed., Vol. 2879, pp. 513-520)

Morphometric analysis of brain structures for improved discrimination. / Shen, Li; Ford, James; Makedon, Fillia; Wang, Yuhang; Steinberg, Tilmann; Ye, Song; Saykin, Andrew.

Lecture Notes in Computer Science. ed. / R.E. Ellis; T.M. Peters. Vol. 2879 PART 2. ed. 2003. p. 513-520.

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

Shen, L, Ford, J, Makedon, F, Wang, Y, Steinberg, T, Ye, S & Saykin, A 2003, Morphometric analysis of brain structures for improved discrimination. in RE Ellis & TM Peters (eds), Lecture Notes in Computer Science. PART 2 edn, vol. 2879, pp. 513-520, Medical Image Computing and Computer-Assisted Intervention, MICCAI 2003 - 6th International Conference Proceedings, Montreal, Que., Canada, 11/15/03.
Shen L, Ford J, Makedon F, Wang Y, Steinberg T, Ye S et al. Morphometric analysis of brain structures for improved discrimination. In Ellis RE, Peters TM, editors, Lecture Notes in Computer Science. PART 2 ed. Vol. 2879. 2003. p. 513-520
Shen, Li ; Ford, James ; Makedon, Fillia ; Wang, Yuhang ; Steinberg, Tilmann ; Ye, Song ; Saykin, Andrew. / Morphometric analysis of brain structures for improved discrimination. Lecture Notes in Computer Science. editor / R.E. Ellis ; T.M. Peters. Vol. 2879 PART 2. ed. 2003. pp. 513-520
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