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Hippocampal shape analysis in the Laplace Beltrami feature space for temporal lobe epilepsy diagnosis and lateralization

Shishegar, R ; Sharif University of Technology | 2012

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  1. Type of Document: Article
  2. DOI: 10.1109/ISBI.2012.6235506
  3. Publisher: IEEE , 2012
  4. Abstract:
  5. Shape analysis plays an important role in many medical imaging studies. One of the recent shape analysis methods uses the Laplace Beltrami operator which is also used in this paper for hippocampal shape comparison. We proposed a feature vector which consists of size measures and shape descriptors based on Laplace Beltrami eigenvalues and eigenfunctions. The aforementioned feature space is utilised for automatic differentiating normal subjects from epileptic patients as well as distinguishing epileptic patients with left temporal lobe epilepsy (LTLE) from patients with right temporal lobe epilepsy (RTLE). Achieved results are diagnostic accuracy of 93% with 95% sensitivity and lateralization accuracy of 86%. The results are comparable to spherical harmonic based shape analysis results and notably improved in comparison to volumetric analysis results
  6. Keywords:
  7. Epilepsy disease ; Laplace Beltrami eigenvalues and eigenfunctions ; Beltrami ; Diagnostic accuracy ; Epileptic patients ; Feature space ; Feature vectors ; Hippocampus ; Laplace-Beltrami operator ; Lateralization ; MS complex ; Shape analysis ; Shape analysis method ; Shape comparison ; Shape descriptors ; Size measures ; Spherical harmonics ; Temporal lobe epilepsy ; Diagnosis ; Eigenvalues and eigenfunctions ; Face recognition ; Harmonic analysis ; Laplace transforms ; Medical imaging ; Neurology ; Volumetric analysis ; Brain
  8. Source: Proceedings - International Symposium on Biomedical Imaging ; 2012 , Pages 150-153 ; 19457928 (ISSN) ; 9781457718588 (ISBN)
  9. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6235506