Image segmentation using deep learning for tongue diagnosis in traditional Chinese medicine

Dechao Xu, Yudong Yao, Lisheng Xu, Gang Xu, Yaochen Guo, Wei Qian

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Deep learning has the advantages of high efficiency, high speed, high accuracy, and strong objectivity, and is widely used in the fields of pathology and laboratory diagnosis. The diagnostic techniques of traditional Chinese medicine are world-famous, and the four basic methods for diagnosing diseases, namely inspection, auscultation-olfaction, inquiry, and palpation, are collectively referred to as”four diagnostics”. Tongue diagnosis is an important part of inspection, and it is also an effective diagnosis and treatment method for doctors to understand the changes of the patient's body through the tongue image. In order to realize automatic tongue diagnosis, one of the important tasks is to implement the automatic segmentation of tongue images. However, using feature engineering to segment tongue images requires a lot of work, and only hand-crafted features cannot represent the features of the tongue well. Therefore, this paper designs a tongue segmentation network (TSN). TSN consists of three parts: feature encoding extraction module, context-aware module and feature decoding module. This model can fully extract tongue feature vector and perform information fusion through context-aware module, so that Effectively segment the tongue from the image. Compared with various deep learning image segmentation methods, the TSN proposed in this paper achieves the best performance results with 97.20% mean intersection over union (mIoU) and 98.83% pixel accuracy (PA).

Original languageEnglish
Title of host publication5th International Conference on Computer Information Science and Application Technology, CISAT 2022
EditorsFuming Zhao
ISBN (Electronic)9781510660076
DOIs
StatePublished - 2022
Event5th International Conference on Computer Information Science and Application Technology, CISAT 2022 - Chongqing, China
Duration: 29 Jul 202231 Jul 2022

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume12451
ISSN (Print)0277-786X
ISSN (Electronic)1996-756X

Conference

Conference5th International Conference on Computer Information Science and Application Technology, CISAT 2022
Country/TerritoryChina
CityChongqing
Period29/07/2231/07/22

Keywords

  • Deep learning
  • Medical imaging
  • Tongue diagnosis
  • Tongue image segmentation

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