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Tongue Images Classification Based on Constrained High Dispersal Network
Joint Authors
Duan, Ye
Xu, Jia-Tuo
Tu, Li Ping
Meng, Dan
Cao, Guitao
Zhu, Minghua
Xu, Dong
Source
Evidence-Based Complementary and Alternative Medicine
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-12, 12 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-03-30
Country of Publication
Egypt
No. of Pages
12
Main Subjects
Abstract EN
Computer aided tongue diagnosis has a great potential to play important roles in traditional Chinese medicine (TCM).
However, the majority of the existing tongue image analyses and classification methods are based on the low-level features, which may not provide a holistic view of the tongue.
Inspired by deep convolutional neural network (CNN), we propose a novel feature extraction framework called constrained high dispersal neural networks (CHDNet) to extract unbiased features and reduce human labor for tongue diagnosis in TCM.
Previous CNN models have mostly focused on learning convolutional filters and adapting weights between them, but these models have two major issues: redundancy and insufficient capability in handling unbalanced sample distribution.
We introduce high dispersal and local response normalization operation to address the issue of redundancy.
We also add multiscale feature analysis to avoid the problem of sensitivity to deformation.
Our proposed CHDNet learns high-level features and provides more classification information during training time, which may result in higher accuracy when predicting testing samples.
We tested the proposed method on a set of 267 gastritis patients and a control group of 48 healthy volunteers.
Test results show that CHDNet is a promising method in tongue image classification for the TCM study.
American Psychological Association (APA)
Meng, Dan& Cao, Guitao& Duan, Ye& Zhu, Minghua& Tu, Li Ping& Xu, Dong…[et al.]. 2017. Tongue Images Classification Based on Constrained High Dispersal Network. Evidence-Based Complementary and Alternative Medicine،Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1154552
Modern Language Association (MLA)
Meng, Dan…[et al.]. Tongue Images Classification Based on Constrained High Dispersal Network. Evidence-Based Complementary and Alternative Medicine No. 2017 (2017), pp.1-12.
https://search.emarefa.net/detail/BIM-1154552
American Medical Association (AMA)
Meng, Dan& Cao, Guitao& Duan, Ye& Zhu, Minghua& Tu, Li Ping& Xu, Dong…[et al.]. Tongue Images Classification Based on Constrained High Dispersal Network. Evidence-Based Complementary and Alternative Medicine. 2017. Vol. 2017, no. 2017, pp.1-12.
https://search.emarefa.net/detail/BIM-1154552
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1154552