Multi-view classification for identification of Alzheimer’s disease

Xiaofeng Zhu, Heung-Il Suk, Yonghua Zhu, Kim Han Thung, Guorong Wu, Dinggang Shen

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

15 Citations (Scopus)

Abstract

In this paper, we propose a multi-view learning method using Magnetic Resonance Imaging (MRI) data for Alzheimer’s Disease (AD) diagnosis. Specifically, we extract both Region-Of-Interest (ROI) features and Histograms of Oriented Gradient (HOG) features from each MRI image, and then propose mapping HOG features onto the space of ROI features to make them comparable and to impose high intra-class similarity with low inter-class similarity. Finally, both mapped HOG features and original ROI features are input to the support vector machine for AD diagnosis. The purpose of mapping HOG features onto the space of ROI features is to provide complementary information so that features from different views can not only be comparable (i.e., homogeneous) but also be interpretable. For example, ROI features are robust to noise, but lack of reflecting small or subtle changes, while HOG features are diverse but less robust to noise. The proposed multi-view learning method is designed to learn the transformation between two spaces and to separate the classes under the supervision of class labels. The experimental results on the MRI images from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset show that the proposed multi-view method helps enhance disease status identification performance, outperforming both baseline methods and state-of-the-art methods.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages255-262
Number of pages8
Volume9352
ISBN (Print)9783319248875
DOIs
Publication statusPublished - 2015
Event6th International Workshop on Machine Learning in Medical Imaging, MLMI 2015 and Held in Conjunction with 18th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2015 - Munich, Germany
Duration: 2015 Oct 52015 Oct 5

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9352
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other6th International Workshop on Machine Learning in Medical Imaging, MLMI 2015 and Held in Conjunction with 18th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2015
CountryGermany
CityMunich
Period15/10/515/10/5

Fingerprint

Alzheimer's Disease
Region of Interest
Histogram
Gradient
Magnetic Resonance Imaging
Neuroimaging
Support vector machines
Labels
Baseline
Support Vector Machine
Class
Experimental Results

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Zhu, X., Suk, H-I., Zhu, Y., Thung, K. H., Wu, G., & Shen, D. (2015). Multi-view classification for identification of Alzheimer’s disease. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9352, pp. 255-262). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9352). Springer Verlag. https://doi.org/10.1007/978-3-319-24888-2_31

Multi-view classification for identification of Alzheimer’s disease. / Zhu, Xiaofeng; Suk, Heung-Il; Zhu, Yonghua; Thung, Kim Han; Wu, Guorong; Shen, Dinggang.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9352 Springer Verlag, 2015. p. 255-262 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9352).

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

Zhu, X, Suk, H-I, Zhu, Y, Thung, KH, Wu, G & Shen, D 2015, Multi-view classification for identification of Alzheimer’s disease. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 9352, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9352, Springer Verlag, pp. 255-262, 6th International Workshop on Machine Learning in Medical Imaging, MLMI 2015 and Held in Conjunction with 18th International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2015, Munich, Germany, 15/10/5. https://doi.org/10.1007/978-3-319-24888-2_31
Zhu X, Suk H-I, Zhu Y, Thung KH, Wu G, Shen D. Multi-view classification for identification of Alzheimer’s disease. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9352. Springer Verlag. 2015. p. 255-262. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-24888-2_31
Zhu, Xiaofeng ; Suk, Heung-Il ; Zhu, Yonghua ; Thung, Kim Han ; Wu, Guorong ; Shen, Dinggang. / Multi-view classification for identification of Alzheimer’s disease. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 9352 Springer Verlag, 2015. pp. 255-262 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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