Regional image analysis of the tongue color spectrum

Yamamoto, Satoshi; Tsumura, Norimichi; Nakaguchi, Toshiya; Namiki, Takao; Kasahara, Yuji; Terasawa, Katsutoshi; Miyake, Yoichi

doi:10.1007/s11548-010-0492-x

Cited by 37 publications

(28 citation statements)

References 18 publications

(27 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The hyperspectral imaging system, one of the objective measurement systems available, will help even lesser-trained people to perform this diagnosis of Kampo medicine. However, because a hyperspectral camera presents a major problem in terms of cost [3,Discussion], it is thought that tongue color spectra can be estimated from 3-band images as shown in skin images [11]. If a hyperspectral camera is replaced with a 3-band CCD camera and spectral property of the tongue is estimated for 3-band images, this system would be a new, easily applied, low-cost and noninvasive diagnostic tool for preventive medicine.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

Principal component vector rotation of the tongue color spectrum to predict “Mibyou” (disease-oriented state)

et al. 2010

Self Cite

View full text Add to dashboard Cite

A PCA-based algorithm was developed to objectively evaluate patients using color images of the tongue surface. Testing showed that this method was a feasible surrogate for expert visual tongue analysis. This tool should help non-trained people identify "Mibyou" health status for individuals. The algorithm is free of empirical criteria, and it may be it applicable to many hyperspectral image types.

show abstract

Section: Discussionmentioning

confidence: 99%

“…Details of the problems Kampo is facing are discussed in the first article [3,Introduction]. Also, we showed that uncoated tongue area can be segmented properly by focusing on spectral color difference among facial areas, which will help analyze tongue color without the effect of tongue coating.…”

Section: Introductionmentioning

confidence: 92%

Principal component vector rotation of the tongue color spectrum to predict “Mibyou” (disease-oriented state)

et al. 2010

Self Cite

View full text Add to dashboard Cite

show abstract

“…Many categories are not precise enough, but more like estimation, i.e. the judgment whether a tongue is purplish the tongue images within our device is still not standardized in that respect, that the subjective analysis of the examiner is replaced by a computer that quantitatively analyzes the images, as tried to establish by other research groups [26][27][28][29][30]. The complete standardization of tongue imaging with a standardized recording procedure as well as integrated quantitative analysis of the tongue by means of a computer could be a goal for the future.…”

Section: Discussionmentioning

confidence: 99%

Introducing a Computer-Assisted, Digital Tongue-Imaging Device for Standardization of Traditional Tongue Diagnosis

Gareus

Rampp²,

Liu³

et al. 2014

Complement Med Res

View full text Add to dashboard Cite

Background: In Traditional Chinese Medicine (TCM) tongue diagnosis and pulse diagnosis are the major diagnostic methods up till now. As western research has tended to focus on acupuncture, attempts to standardize the classic diagnostic methods have been few. Methods: A digital camera with a ring flash was fixed in a frame, so that the tongue-lens-distance and illumination were kept constant. A pilot study testing the inter-methods reliability, test-retest reliability, and interrater reliability of 2 observers was conducted: the tongues (1 ×) as well as the tongue images (2 ×) from 76 patients from our ward were assessed with a standardized rating list in a randomized order by both observers, who were mutually blinded. As primary outcome measure we used agreement beyond chance (Cohen's kappa). Results: The colors of the tongue body / the tongue coating were the main criteria for the authentic reproduction of the tongue in our images. Inter-methods reliability for the color of the tongue body/coating was kappa 0.35 / 0.34 (p < 0.001) for observer 1 and 0.59 / 0.57 (p < 0.001) for observer 2. Test-retest reliability for the color of the tongue body / the tongue coating was kappa 0.53 / 0.48 (p< 0.001) for observer 1 and 0.65 / 0.62 (p < 0.001) for observer 2. Interrater reliability was generally low. Conclusions: The introduced device represents a first step towards standardization of tongue diagnosis. However, inter-methods as well as test-retest reliability vary between observers and different morphological characteristics.

show abstract

“…In recent years, with ubiquitous application of advanced computer technologies in medical science, we cannot ignore new possibilities to improve TCM with computer technologies [4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22]; these possibilities for improvement have drawn attention from myriads of researchers. Chiu [4,5] built a computerized tongue examination system (CTES) based on computerized image analysis.…”

Section: Introductionmentioning

confidence: 99%

“…Before the process of tongue classification, an exact region of the tongue must be extracted from an image, [12][13] try to proposed automated tongue segmentation method. Some papers [14][15][16][17][18] designed image analysis system for feature extraction and diagnostics. Pang et al [18] even present a tongue-computing model for the diagnosis of appendicitis based on quantitative measurements that include chromatic and textural feature.…”

Section: Introductionmentioning

confidence: 99%

WLDF: Effective Statistical Shape Feature for Cracked Tongue Recognition

Li¹,

Wang²,

Cui³

2017

Journal of Electrical Engineering and Technology

View full text Add to dashboard Cite

-This paper proposes a new method using Wide Line Detector based statistical shape Feature (WLDF) to identify whether or not a tongue is cracked; a cracked tongue is one of the most frequently used visible features for diagnosis in traditional Chinese Medicine (TCM). We first detected a wide line in the tongue image, and then extracted WLDF, such as the maximum length of each detected region, and the ratio between maximum length and the area of the detected region. We trained a binary support vector machine (SVM) based on the WLDF to build a classifier for cracked tongues. We conducted an experiment based on our proposed scheme, using 196 samples of cracked tongues and 245 samples of non-cracked tongues. The results of the experiment indicate that the recognition accuracy of the proposed method is greater than 95%. In addition, we provide an analysis of the results of this experiment with different parameters, demonstrating the feasibility and effectiveness of the proposed scheme.

show abstract

Regional image analysis of the tongue color spectrum

Abstract: Using a hyperspectral camera and extraction algorithm, the tongue color of the uncoated part was automatically extracted. This technique is suitable for tongue color analysis and may help non-trained users to identify "Mibyou".

Cited by 37 publications

References 18 publications

Principal component vector rotation of the tongue color spectrum to predict “Mibyou” (disease-oriented state)

Principal component vector rotation of the tongue color spectrum to predict “Mibyou” (disease-oriented state)

Introducing a Computer-Assisted, Digital Tongue-Imaging Device for Standardization of Traditional Tongue Diagnosis

WLDF: Effective Statistical Shape Feature for Cracked Tongue Recognition

Contact Info

Product

Resources

About