Color Correction Parameter Estimation on the Smartphone and Its Application to Automatic Tongue Diagnosis

Hu, Min‐Chun; Cheng, Ming-Hsun; Lan, Kun-Chan

doi:10.1007/s10916-015-0387-z

Cited by 29 publications

(18 citation statements)

References 13 publications

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“…The lighting environment included with and without flashlights. They further improved their work and acquired better result 41 . To the best of authors’ knowledge, this is the best work done so far in the field of tongue diagnosis for light estimation and color correction.…”

Section: Tongue Diagnosis Systemsmentioning

confidence: 91%

“…Different approaches have been taken to solve the challenging problem of lighting condition estimation. These solutions include controlled environment,27, 29 color correction, 41 hardware based implementation, for example, tongue image acquisition device 20 and ColorChecker 42 . An image taken with the same camera may provide different tongue diagnosis due to the variation in the color properties at different lighting conditions.…”

Section: Tongue Diagnosis Systemsmentioning

confidence: 99%

“…Another passing fad is taking images in public office environment 26 . Hu et al 41 analyzed tongue features observed under different lighting conditions such as fluorescent, incandescent, and halogen illuminant. They used Support Vector Machine (SVM) to make the system independent of lighting environment.…”

Section: Tongue Diagnosis Systemsmentioning

confidence: 99%

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Advances in automated tongue diagnosis techniques

Tania

Lwin

2019

Integrative Medicine Research

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Tongue diagnosis can be an effective, noninvasive method to perform an auxiliary diagnosis any time anywhere, which can support the global need in the primary healthcare system. This work reviews the recent advances in tongue diagnosis, which is a significant constituent of traditional oriental medicinal technology, and explores the literature to evaluate the works done on the various aspects of computerized tongue diagnosis, namely preprocessing, tongue detection, segmentation, feature extraction, tongue analysis, especially in traditional Chinese medicine (TCM). In spite of huge volume of work done on automatic tongue diagnosis (ATD), there is a lack of adequate survey, especially to combine it with the current diagnosis trends. This paper studies the merits, capabilities, and associated research gaps in current works on ATD systems. After exploring the algorithms used in tongue diagnosis, the current trend and global requirements in health domain motivates us to propose a conceptual framework for the automated tongue diagnostic system on mobile enabled platform. This framework will be able to connect tongue diagnosis with the future point-of-care health system.

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Section: Tongue Diagnosis Systemsmentioning

confidence: 91%

Section: Tongue Diagnosis Systemsmentioning

confidence: 99%

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Advances in automated tongue diagnosis techniques

Tania

Lwin

2019

Integrative Medicine Research

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“…Most people carry mobile phones with them. The built-in sensors of smart phones (such as magnetometers, accelerometers, cameras) enable the development of new sensor systems to measure the status of telephone users and his surrounding environment, so the study of a person who monitors his health through a tongue diagnosis of a smartphone [20] is beginning to rise. The concept of computerized tongue diagnosis is not new, but the research on tongue diagnosis based on mobile phones is relatively rare.…”

Section: Tongue Feature Extraction Algorithmmentioning

confidence: 99%

Medical Diagnosis Algorithm Based on Tongue Image on Mobile Device

Zhou¹,

Peng²,

Gao³

et al. 2019

J Multimed Inf Syst

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In traditional Chinese medical (TCM) science, tongue images can be observed for medical diagnosis; however, the tongue diagnosis of TCM is influenced by the subjective factors of doctors, and the diagnosis results vary from person to person. Quantitative TCM tongue diagnosis can improve the accuracy of diagnosis and increase the application value. In this paper, digital image processing and pattern recognition technologies are employed on mobile device to classify tongue images collected in different health states. First, through grayscale integral projection processing, the trough is found to localize the tongue body. Then the tongue body image is transferred from RGB color space to HSV color space, and the average H and S values are considered as the color features. Finally, the diagnosis results are obtained according to the relationship between the color characteristics and physical symptoms.

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“…In the diagnosis method of traditional Chinese medicine, tongue and pulse are important objective diagnosis basis.They are comprehensive diagnostic methods based on the body's overall state, which are suitable for the comprehensive evaluation of the body's functional state and have become an important objective basis for health status evaluation and syndrome diagnosis.In recent years, data-driven research and application of tongue and pulse diagnosis have been carried out, and breakthroughs have been made in fatigue quanti cation and standardization. Arti cial Neural Network [13], Support Vector Machine [14], KNN [15]and other machine learning methods has realized the digitalization of TCM tongue and pulse diagnosis, and established the corresponding disease diagnosis model [16; 17]. Fatigue is closely related to human's physical and mental health, research of modern tongue and pulse diagnosis technology applied to fatigue is increasing day by day.…”

Section: Introductionmentioning

confidence: 99%

Clinical data mining on network of symptom and index and correlation of tongue-pulse data in fatigue population

Shi

Cui

et al. 2020

Preprint

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BackgroundFatigue is a kind of non-specific symptom, which is widely found in sub-health and various diseases. It is closely related to people's physical and mental health.Due to lack of objective evidence, it is often neglected in clinical diagnosis,especially in the early stage of disease.A large number of clinical practices and studies have shown that tongue and pulse image are reflection of overall state of the body.Establishing an objective evaluation method for diagnosis of disease fatigue and non-disease fatigue by combining clinical symptom and index and tongue and pulse data is of great significance for timely and effective clinical treatment.MethodsIn this study, 2362 physical examination subjects were divided into healthy control, the group of sub-health fatigue and disease fatigue ,used complex network technology to screen out the core symptoms and western medicine indexes of fatigue,respectively. Constructed the core symptom network and the core symptom-index network. At the same time, used canonical correlation analysis to get the associated relationship of tongue and pulse, and analyzed the characteristic of the tongue and pulse data.ResultsThere were some similarities between the core symptoms of sub-health fatigue and disease fatigue,as well as differences. Symptom-index associated analysis of disease fatigue showed that the core indexes in the group of disease fatigue group had a significant canonical correlation, with the canonical correlation coefficient was 0.42 (P < 0.05). There was no statistically significant correlation between the tongue and pulse data in sub-health fatigue group.ConclusionsThe complex network technology was suitable for the correlation analysis of symptoms and indexes in the fatigue population, and the tongue and pulse objective data had certain diagnostic contribution to the classification of fatigue population.Name of the registry: Chinese Clinical Trial RegistryTrial registration number: ChiCTR-IOR-15006502; ChiCTR1900026008Date of registration: Jun. 04th, 2015URL of trial registry record:http://www.chictr.org.cn/showprojen.aspx?proj=11119;http://www.chictr.org.cn/edit.aspx?pid=38828&htm=4 (This is a retrospective registration)

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Color Correction Parameter Estimation on the Smartphone and Its Application to Automatic Tongue Diagnosis

Cited by 29 publications

References 13 publications

Advances in automated tongue diagnosis techniques

Advances in automated tongue diagnosis techniques

Medical Diagnosis Algorithm Based on Tongue Image on Mobile Device

Clinical data mining on network of symptom and index and correlation of tongue-pulse data in fatigue population

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