Open AccessContent-Based Retrieval of Brain Diffusion Magnetic Resonance Image
Author(s) -
Siqi Liu,
Nur Fajri Al Faridi Hadi,
Sidong Liu,
Sonia Pujol,
Ron Kikinis,
Fan Zhang,
Dagan Feng,
Weidong Cai
Publication year - 2015
Publication title -
lecture notes in computer science
Language(s) - English
Resource type - Book series
SCImago Journal Rank - 0.249
H-Index - 400
eISSN - 1611-3349
pISSN - 0302-9743
DOI - 10.1007/978-3-319-24471-6_5
Subject(s) - computer science , diffusion mri , image retrieval , graph , content based image retrieval , tensor (intrinsic definition) , range (aeronautics) , functional magnetic resonance imaging , content (measure theory) , diffusion , baseline (sea) , information retrieval , artificial intelligence , magnetic resonance imaging , image (mathematics) , theoretical computer science , physics , mathematics , biology , materials science , mathematical analysis , oceanography , composite material , thermodynamics , radiology , medicine , neuroscience , pure mathematics , geology
The content-based retrieval of diffusion magnetic resonance dMR imaging data would enable a wide range of analyses on large databases with dMR images.This paper proposes a content-based retrieval framework for dMR images to explore the use of Diffusion Tensor Imaging DTI - derived parameters. The propagation graph algorithm is proposed for the query-centric retrieval of dMR subjects and the fusion of different features. The proposed framework was evaluated with ADNI database with 233 baseline dMR images. The preliminary results show that the proposed retrieval framework is able to retrieve subjects with similar neurodegenerative patterns.
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