Advances in automated tongue diagnosis techniques

This paper reviews the recent advances in a significant constituent of traditional oriental medicinal technology, called tongue diagnosis. 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 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

Review on the current trends in tongue diagnosis systems

AbstractTongue diagnosis is an essential process to noninvasively assess the condition of a patient's internal organs in traditional medicine. To obtain quantitative and objective diagnostic results, image acquisition and analysis devices called tongue diagnosis systems (TDSs) are required. These systems consist of hardware including cameras, light sources, and a ColorChecker, and software for color correction, segmentation of tongue region, and tongue classification. To improve the performance of TDSs, various types TDSs have been developed. Hyperspectral imaging TDSs have been suggested to acquire more information than a two-dimensional (2D) image with visible light waves, as it allows collection of data from multiple bands. Three-dimensional (3D) imaging TDSs have been suggested to provide 3D geometry. In the near future, mobile devices like the smart phone will offer applications for assessment of health condition using tongue images. Various technologies for the TDS have respective unique advantages and specificities according to the application and diagnostic environment, but this variation may cause inconsistent diagnoses in practical clinical applications. In this manuscript, we reviewed the current trends in TDSs for the standardization of systems. In conclusion, the standardization of TDSs can supply the general public and oriental medical doctors with convenient, prompt, and accurate information with diagnostic results for assessing the health condition

Research on Tongue Detection and Tongue Segmentation in Open Environment

中医舌诊以其无创与便捷性在全世界引起广泛关注，通过综合分析舌象的生理及病理特征得到诊断结果，然而传统的中医舌诊受限于医师的知识水平和主观意识，并受环境光线等因素影响。数字化舌诊分析系统正是解决了这一问题，通过临床经验结合计算机图像处理技术实现了舌诊的客观化、数字化及自动化，是舌诊信息化发展的主要方向。目前，数字化舌诊分析系统为了得到高质量的舌象图像，多是在密闭、固定光源的标准环境下采集舌象图像。然而，随着智能手机等移动设备的发展和普及，采用移动设备在开放环境下采集图像逐渐成为一个新的研究方向。但随之而来的问题是，开放环境下的舌象分析容易受光照强弱和复杂背景等因素的影响，因此，在进行舌象分析前，...Tongue diagnosis is an important diagnostic method in the Traditional Chinese Medicine (TCM) which has caused widespread concern worldwide due to its noninvasive and convenience. Traditional tongue diagnosis depends a comprehensive analysis of the physiological and pathological characteristics of tongue body, which is subjected to the clinicians’ knowledge and experience, and influenced by environ...学位：工学硕士院系专业：信息科学与技术学院_计算机科学与技术学号：2302014115316

Combining Artificial Intelligence with Traditional Chinese Medicine for Intelligent Health Management

The growth of artificial intelligence (AI) is being referred to as the beginning of "the fourth industrial revolution". With the rapid development of hardware, algorithms, and applications, AI not only provides a new concept and relevant solutions to solve the problem of complexity science but also provides a new concept and method to promote the development of traditional Chinese medicine (TCM). In this study, based on the research and development of AI technology applications in biomedical and clinical diagnosis and treatment, we introduce AI technologies in current TCM research. This can have applications in intelligent clinical information acquisition, intelligent clinical decision, and efficacy evaluation of TCM; intelligent classification management, intelligent prescription, and drug research in Chinese herbal medicine; and health management. Furthermore, we propose a framework of "intelligent TCM" and outline its development prospects

Dynamic contrast in scanning microscopic OCT

While optical coherence tomography (OCT) provides a resolution down to 1 micrometer it has difficulties to visualize cellular structures due to a lack of scattering contrast. By evaluating signal fluctuations, a significant contrast enhancement was demonstrated using time-domain full-field OCT (FF-OCT), which makes cellular and subcellular structures visible. The putative cause of the dynamic OCT signal is ATP-dependent motion of cellular structures in a sub-micrometer range, which provides histology-like contrast. Here we demonstrate dynamic contrast with a scanning frequency-domain OCT (FD-OCT). Given the inherent sectional imaging geometry, scanning FD-OCT provides depth-resolved images across tissue layers, a perspective known from histopathology, much faster and more efficiently than FF-OCT. Both, shorter acquisition times and tomographic depth-sectioning reduce the sensitivity of dynamic contrast for bulk tissue motion artifacts and simplify their correction in post-processing. The implementation of dynamic contrast makes microscopic FD-OCT a promising tool for histological analysis of unstained tissues.Comment: 7 pages, 3 figures, 1 Video available on reques

Markerless Analysis of Articulatory Movements in Patients With Parkinson's Disease

Objectives: A large percentage of patients with Parkinson's disease have hypokinetic dysarthria, exhibiting reduced peak velocities of jaw and lips during speech. This limitation implies a reduction of speech intelligibility for such patients. This work aims at testing a cost-effective markerless approach for assessing kinematic parameters of hypokinetic dysarthria. Study design: Kinematic parameters of the lips are calculated during a syllable repetition task from 14 Parkinsonian patients and 14 age-matched control subjects. Methods: Combining color and depth frames provided by a depth sensor (Microsoft Kinect), we computed the three-dimensional coordinates of main facial points. The peak velocities and accelerations of the lower lip during a syllable repetition task are considered to compare the two groups. Results: Results show that Parkinsonian patients exhibit reduced peak velocities of the lower lip, both during the opening and the closing phase of the mouth. In addition, peak values of acceleration are reduced in Parkinsonian patients, although with significant differences only in the opening phase with respect to healthy control subjects. Conclusions: The novel contribution of this work is the implementation of an entirely markerless technique capable to detect signs of hypokinetic dysarthria for the analysis of articulatory movements during speech. Although a large number of Parkinsonian patients have hypokinetic dysarthria, only a small percentage of them undergoes speech therapy to increase their articulatory movements. The system proposed here could be easily implemented in a home environment, thus, increasing the percentage of patients who can perform speech rehabilitation at home