Diagnosis of Alzheimer’s disease using view-aligned hypergraph learning with incomplete multi-modality data

Mingxia Liu, Jun Zhang, Pew Thian Yap, Dinggang Shen

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

5 Citations (Scopus)

Abstract

Effectively utilizing incomplete multi-modality data for diagnosis of Alzheimer’s disease (AD) is still an area of active research. Several multi-view learning methods have recently been developed to deal with missing data,with each view corresponding to a specific modality or a combination of several modalities. However,existing methods usually ignore the underlying coherence among views,which may lead to suboptimal learning performance. In this paper,we propose a view-aligned hypergraph learning (VAHL) method to explicitly model the coherence among the views. Specifically,we first divide the original data into several views based on possible combinations of modalities,followed by a sparse representation based hypergraph construction process in each view. A view-aligned hypergraph classification (VAHC) model is then proposed,by using a view-aligned regularizer to model the view coherence. We further assemble the class probability scores generated from VAHC via a multi-view label fusion method to make a final classification decision. We evaluate our method on the baseline ADNI-1 database having 807 subjects and three modalities (i.e.,MRI,PET,and CSF). Our method achieves at least a 4.6% improvement in classification accuracy compared with state-of-the-art methods for AD/MCI diagnosis.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention - MICCAI 2016 - 19th International Conference, Proceedings
EditorsGozde Unal, Mert R. Sabuncu, William Wells, Sebastian Ourselin, Leo Joskowicz
PublisherSpringer Verlag
Pages308-316
Number of pages9
ISBN (Print)9783319467191
DOIs
Publication statusPublished - 2016
Externally publishedYes
Event1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016 - Athens, Greece
Duration: 2016 Oct 212016 Oct 21

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9900 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other1st International Workshop on Simulation and Synthesis in Medical Imaging, SASHIMI 2016 held in conjunction with 19th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2016
Country/TerritoryGreece
CityAthens
Period16/10/2116/10/21

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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