A study of data fusion for Alzheimer's disease based on diffusion magnetic resonance imaging

Changle Zhang, Shuai Mao, Chunsing Wong, Edward S. Hui, Chenfei Ye, Hengtong Li, Jingbo Ma, Heather T. Ma

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)


Alzheimer's disease (AD) has become one of the most serious healthcare problems. As a result, early diagnosis for AD is important for intervention of its deterioration at an early stage. Diffusion tensor imaging (DTI) provides a non-intrusive examination of cranial nerve diseases, but the precise quantification is a problem for diagnosis. In current study, we proposed an AD recognition method based on quantitative analysis and data fusion of T1 and DTI images. Through segmentation on T1 image, feature extraction of DTI data, and data fusion based on multi-features, recognition accuracy of AD can attain as high as 95.4%. For details, patterns of different features from DTI data were investigated showing that the fusion of volume values, DTI and diffusion kurtosis imaging (DKI) parameters and the Gaussian Mixture Model (GMM) parameters of DTI and DKI are the most distinctive individual features in AD patients. It also implies that during the AD development, neural degeneration could be demyelination, reduction of structural complexity and decrease of brain microstructure connectivity, which can be reflected by different quantitative parameters from brain images, such as brain structure volume, DTI parameters and DKI parameters. Further study on the image features, including more image types, would provide valued method for AD screening or early diagnosis.

Original languageEnglish
Title of host publicationProceedings of the 2016 IEEE Region 10 Conference, TENCON 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages4
ISBN (Electronic)9781509025961
Publication statusPublished - 8 Feb 2017
Externally publishedYes
Event2016 IEEE Region 10 Conference, TENCON 2016 - Singapore, Singapore
Duration: 22 Nov 201625 Nov 2016

Publication series

NameIEEE Region 10 Annual International Conference, Proceedings/TENCON
ISSN (Print)2159-3442
ISSN (Electronic)2159-3450


Conference2016 IEEE Region 10 Conference, TENCON 2016

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering


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