Hippocampal shape analysis: Surface-based representation and classification

Li Shen, James Ford, Fillia Makedon, Andrew Saykin

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

32 Citations (Scopus)

Abstract

Surface-based representation and classification techniques are studied for hippocampal shape analysis. The goal is twofold: (1) develop a new framework of salient feature extraction and accurate classification for 3D shape data: (2) detect hippocampal abnormalities in schizophrenia using this technique. A fine-scale spherical harmonic expansion is employed to describe a closed 3D surface object. The expansion can then easily be transformed to extract only shape information (i.e., excluding translation, rotation, and scaling) and create a shape descriptor comparable across different individuals. This representation captures shape features and is flexible enough to do shape modeling, identify statistical group differences, and generate similar synthetic shapes. Principal component analysis is used to extract a small number of independent features from high dimensional shape descriptors, and Fisher's linear discriminant is applied for pattern classification. This framework is shown to be able to perform well in distinguishing clear group differences as well as small and noisy group differences using simulated shape data. In addition, the application of this technique to real data indicates that group shape differences exist in hippocampi between healthy controls and schizophrenic patients.

Original languageEnglish (US)
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsM. Sonka, J.M. Fitzpatrick
Pages253-264
Number of pages12
Volume5032 I
DOIs
StatePublished - 2003
Externally publishedYes
EventMedical Imaging 2003: Image Processing - San Diego, CA, United States
Duration: Feb 17 2003Feb 20 2003

Other

OtherMedical Imaging 2003: Image Processing
CountryUnited States
CitySan Diego, CA
Period2/17/032/20/03

Fingerprint

Surface analysis
Principal component analysis
Pattern recognition
Feature extraction
schizophrenia
hippocampus
expansion
abnormalities
spherical harmonics
principal components analysis
pattern recognition
scaling

Keywords

  • Classification
  • Hippocampus
  • MRI
  • Shape analysis
  • Surface modeling

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Condensed Matter Physics

Cite this

Shen, L., Ford, J., Makedon, F., & Saykin, A. (2003). Hippocampal shape analysis: Surface-based representation and classification. In M. Sonka, & J. M. Fitzpatrick (Eds.), Proceedings of SPIE - The International Society for Optical Engineering (Vol. 5032 I, pp. 253-264) https://doi.org/10.1117/12.480851

Hippocampal shape analysis : Surface-based representation and classification. / Shen, Li; Ford, James; Makedon, Fillia; Saykin, Andrew.

Proceedings of SPIE - The International Society for Optical Engineering. ed. / M. Sonka; J.M. Fitzpatrick. Vol. 5032 I 2003. p. 253-264.

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

Shen, L, Ford, J, Makedon, F & Saykin, A 2003, Hippocampal shape analysis: Surface-based representation and classification. in M Sonka & JM Fitzpatrick (eds), Proceedings of SPIE - The International Society for Optical Engineering. vol. 5032 I, pp. 253-264, Medical Imaging 2003: Image Processing, San Diego, CA, United States, 2/17/03. https://doi.org/10.1117/12.480851
Shen L, Ford J, Makedon F, Saykin A. Hippocampal shape analysis: Surface-based representation and classification. In Sonka M, Fitzpatrick JM, editors, Proceedings of SPIE - The International Society for Optical Engineering. Vol. 5032 I. 2003. p. 253-264 https://doi.org/10.1117/12.480851
Shen, Li ; Ford, James ; Makedon, Fillia ; Saykin, Andrew. / Hippocampal shape analysis : Surface-based representation and classification. Proceedings of SPIE - The International Society for Optical Engineering. editor / M. Sonka ; J.M. Fitzpatrick. Vol. 5032 I 2003. pp. 253-264
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