Computer aided tongue diagnosis system

H. Z. Zhang, K. Q. Wang, Dapeng Zhang, B. Pang, B. Huang

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

40 Citations (Scopus)

Abstract

To circumvent the subjective and qualitative problems of traditional tongue diagnosis, we present a novel computer aided tongue diagnosis system (CATDS). In this system, a standard acquisition device as well as a new color correction method is utilized to capture qualified tongue images. The system is constituted by five components: User Interface Module, Acquisition Module, Tongue Image Database, Image Preprocessing Module and Diagnosis Engine. In contrast to existing CATDS, the proposed system aims to establish the relationship between quantitative features and diseases via the Bayesian networks. System tests are carried out on a group of 544 patients affected by 9 common diseases and 56 healthy volunteers. The results show that the system can properly identify six groups: healthy, pulmonary heart disease, appendicitis, gastritis, pancreatitis and bronchitis with accuracy higher than 75%. Moreover, the execution time for the whole diagnosis process including image preprocessing and diagnosis is less than 5 seconds.
Original languageEnglish
Title of host publicationProceedings of the 2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
Pages6754-6757
Number of pages4
Volume7 VOLS
Publication statusPublished - 1 Dec 2005
Event2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005 - Shanghai, China
Duration: 1 Sep 20054 Sep 2005

Conference

Conference2005 27th Annual International Conference of the Engineering in Medicine and Biology Society, IEEE-EMBS 2005
CountryChina
CityShanghai
Period1/09/054/09/05

Keywords

  • Bayesian network
  • Color correction
  • Computer aided tongue diagnosis
  • TCM modernization

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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