Tongue Images Classification Based on Constrained High Dispersal Network
المؤلفون المشاركون
Duan, Ye
Xu, Jia-Tuo
Tu, Li Ping
Meng, Dan
Cao, Guitao
Zhu, Minghua
Xu, Dong
المصدر
Evidence-Based Complementary and Alternative Medicine
العدد
المجلد 2017، العدد 2017 (31 ديسمبر/كانون الأول 2017)، ص ص. 1-12، 12ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2017-03-30
دولة النشر
مصر
عدد الصفحات
12
التخصصات الرئيسية
الملخص 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.
نمط استشهاد جمعية علماء النفس الأمريكية (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
نمط استشهاد الجمعية الأمريكية للغات الحديثة (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
نمط استشهاد الجمعية الطبية الأمريكية (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
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1154552
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر