Semi-supervised pattern classification: Application to structural MRI of Alzheimer's disease

Dong Hye Ye, Kilian M. Pohl, Christos Davatzikos

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

Abstract

This paper presents an image-based classification method, and applies it to classification of brain MRI scans of individuals with Mild Cognitive Impairment (MCI). The high dimensionality of the image data is reduced using nonlinear manifold learning techniques, thereby yielding a low-dimensional embedding. Features of the embedding are used in conjunction with a semi-supervised classifier, which utilizes both labeled and unlabeled images to boost performance. The method is applied to 237 scans of MCI patients in order to predict conversion from MCI to Alzheimer's Disease. Experimental results demonstrate better prediction accuracy compared to a state-of-the-art method.

Original languageEnglish (US)
Title of host publicationProceedings - International Workshop on Pattern Recognition in NeuroImaging, PRNI 2011
Pages1-4
Number of pages4
DOIs
StatePublished - Aug 29 2011
EventInternational Workshop on Pattern Recognition in NeuroImaging, PRNI 2011 - Seoul, Korea, Republic of
Duration: May 16 2011May 18 2011

Publication series

NameProceedings - International Workshop on Pattern Recognition in NeuroImaging, PRNI 2011

Other

OtherInternational Workshop on Pattern Recognition in NeuroImaging, PRNI 2011
CountryKorea, Republic of
CitySeoul
Period5/16/115/18/11

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Keywords

  • Alzheimer's disease
  • Early detection
  • Manifold learning
  • Mild cognitive impairment
  • Semi-supervised

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging

Cite this

Ye, D. H., Pohl, K. M., & Davatzikos, C. (2011). Semi-supervised pattern classification: Application to structural MRI of Alzheimer's disease. In Proceedings - International Workshop on Pattern Recognition in NeuroImaging, PRNI 2011 (pp. 1-4). [5961297] (Proceedings - International Workshop on Pattern Recognition in NeuroImaging, PRNI 2011). https://doi.org/10.1109/PRNI.2011.12