Multiparametric tissue abnormality characterization using manifold regularization

Kayhan Batmanghelich, Xiaoying Wu, Evangelia Zacharaki, Clyde E. Markowitz, Christos Davatzikos, Ragini Verma

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

Abstract

Tissue abnormality characterization is a generalized segmentation problem which aims at determining a continuous score that can be assigned to the tissue which characterizes the extent of tissue deterioration, with completely healthy tissue being one end of the spectrum and fully abnormal tissue such as lesions, being on the other end. Our method is based on the assumptions that there is some tissue that is neither fully healthy or nor completely abnormal but lies in between the two in terms of abnormality; and that the voxel-wise score of tissue abnormality lies on a spatially and temporally smooth manifold of abnormality. Unlike in a pure classification problem which associates an independent label with each voxel without considering correlation with neighbors, or an absolute clustering problem which does not consider a priori knowledge of tissue type, we assume that diseased and healthy tissue lie on a manifold that encompasses the healthy tissue and diseased tissue, stretching from one to the other. We propose a semi-supervised method for determining such as abnormality manifold, using multi-parametric features incorporated into a support vector machine framework in combination with manifold regularization. We apply the framework towards the characterization of tissue abnormality to brains of multiple sclerosis patients.

Original languageEnglish (US)
Title of host publicationMedical Imaging 2008 - Computer-Aided Diagnosis
DOIs
StatePublished - Jun 2 2008
EventMedical Imaging 2008 - Computer-Aided Diagnosis - San Diego, CA, United States
Duration: Feb 19 2008Feb 21 2008

Publication series

NameProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume6915
ISSN (Print)1605-7422

Other

OtherMedical Imaging 2008 - Computer-Aided Diagnosis
CountryUnited States
CitySan Diego, CA
Period2/19/082/21/08

Keywords

  • Lesions
  • Manifold regularization
  • Multiple sclerosis
  • Normal appearing brain tissue
  • Support vector machine
  • Tissue abnormality characterization

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Atomic and Molecular Physics, and Optics
  • Radiology Nuclear Medicine and imaging

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  • Cite this

    Batmanghelich, K., Wu, X., Zacharaki, E., Markowitz, C. E., Davatzikos, C., & Verma, R. (2008). Multiparametric tissue abnormality characterization using manifold regularization. In Medical Imaging 2008 - Computer-Aided Diagnosis [691516] (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 6915). https://doi.org/10.1117/12.770837