• Tongue Image Analysis




    Tongue Image Analysis

    by David Zhang

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    This is the first book offering a systematic description of tongue image analysis and processing technologies and their typical applications in computerized tongue diagnostic (CTD) systems. It features the most current research findings in all aspects of tongue image acquisition, preprocessing, classification, and diagnostic support methodologies, from theoretical and algorithmic problems to prototype design and development of CTD systems. 
    The book begins with a very in-depth description of CTD on a need-to-know basis which includes an overview of CTD systems and traditional Chinese medicine (TCM) in order to provide the information on the context and background of tongue image analysis. The core part then introduces algorithms as well as their implementation methods, at a know-how level, including image segmentation methods, chromatic correction, and classification of tongue images. Some clinical applications based on these methods are presented for the show-how purpose in the CTD research field. Case studies highlight different techniques that have been adopted to assist the visual inspection of appendicitis, diabetes, and other common diseases. Experimental results under different challenging clinical circumstances have demonstrated the superior performance of these techniques. 
    In this book, the principles of tongue image analysis are illustrated with plentiful graphs, tables, and practical experiments to provide insights into some of the problems. In this way, readers can easily find a quick and systematic way through the complicated theories and they can later even extend their studies to special topics of interest. This book will be of benefit to researchers, professionals, and graduate students working in the field of computer vision, pattern recognition, clinical practice, and TCM, as well as those involved in interdisciplinary research.



    Details: rank: price: $96.07 bound: publisher: Springer; 1st ed. 2017 edition (March 2, 2017) lang: English asin: isbn: 981102166X, 978-9811021664, weight: 1.5 pounds ( filesize:


















    Tongue Image Analysis David Zhang

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    Tongue Image Analysis

    2.2.8Bezdek, Pattern recognition with fuzzy objective function algorithms, Plenum Press, NewYork, 1981.CrossRefMATHGoogle Scholar4.D Dutta Majumder et al., What a tongue says? A tongue-based diagnostics through pattern recognition, ICSIT Technical Report, 2002/3.Google Scholar5.J.DFigure 10: Three typical samples from (a) DM, (b) NR, (c) GV, (d) NS, (e) EG, (f) CG, and (g) CHDTo distinguish between classes with the same shape, a set of geometry features were selected and applied to SVMCircle Area


    MThe color, shape and texture of tongue are very important information for medical diagnostic purposeThe maximum average accuracy of 88.65% was obtained using (feature 1) and (feature 7) to classify the two classes (healthy and EG) appointed to circle or squareCoarse Level: Tongue Shape Classification ResultThe length-width ratio () is the ratio of a tongue’s length to its width:Figure 7: Typical samples to show the 5 tongue shapesTo eliminate these qualitative aspects, tongue images can be objectively analyzed, which offers a new way to diagnose disease, one that minimizes the physical harm inflicted to patients (compared with other medical examinations)To measure the performance, average accuracy was employedIn DM the majority shape is obtuse triangle, accounting for 86.15% (255/296)Abstract


    He is an associate Professor at the School of Computer Science and Technology, HIT, where he has taught for over 15 yearsUsing these features we define 5 tongue shapes based on TCM, rectangle, acute and obtuse triangles, square, and circleGiven a tongue image, this software derives features specific to color, shape and texture of the tongue surfaceThe following section presents the experimental resultsSmaller half distance () is the half distance of or depending on which segment is shorter (see Figure 2):2In state-of-the-art computerized tongue image analysis, color and texture features are the most prevalent [6–19] 07f867cfac

    David Zhang


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