Tongue image analysis / by David Zhang, Hongzhi Zhang, Bob Zhang.
Contributor(s): Zhang, Hongzhi [author. ] | Zhang, Bob [author. ] | SpringerLink (Online service).Material type: TextPublisher: Singapore : Springer Singapore : Imprint: Springer, 2017Description: xv, 335 pages : illustrations ; 23 cm.Content type: text Media type: unmediated Carrier type: volumeISBN: 9789811021664.Subject(s): Computer science | Health informatics | Image processing | Pattern recognition | Biometrics (Biology) | Biomedical engineering | Tongue -- diagnostic imagingDDC classification: 570.15195 Other classification: Ue:d Online resources: Table of Contents / Abstracts | Tillgñglig fr̲ anvñdare inom Stockholms universitet SpringerLink Books Computer Science Without Lecture Notes 2017:Full Text | Extern tillgn̄g endast anstl̃lda och studenter vid LiU Springer eBooks (Computer Science 2017) | Student portal login Springer DDA:Full Text | Online access for KTHB fulltext SpringerLink Books Computer Science Without Lecture Notes 2017
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|553.8 G.S. N 2004 نزهة الابصار فى خواص الاحجار /||553.8 G.S. N 2004 نزهة الابصار فى خواص الاحجار /||570.1 O.A. P 2005 Philosophy, biology and life /||570.15195 Z.D. T 2017 Tongue image analysis /||570.285 C.Y. B 2005 Bioinformatics technologies /||572.744 B.A. F 2017 Fundamentals of Enzyme Kinetics /||572.80285 M.S. I 2008 Introduction to machine learning and bioinformatics /|
1. Introduction to Tongue Image Analysis -- 2. Tongue Images Acquisition System Design -- 3. Tongue Image Segmentation by Bi-Elliptical Deformable Contour -- 4. A Snake-Based Approach to Automated Tongue Image Segmentation -- 5. Tongue Segmentation in Hyperspectral Images -- 6. Tongue Segmentation by Gradient Vector Flow and Region Merging -- 7. Tongue Segmentation by Fusing Region-based and Edge-based Approaches -- 8. Tongue Shape Classification by Geometric Features -- 9. Color Correction Scheme for Tongue Images -- 10. Tongue Color Checker for Precise Correction -- 11. Tongue Color Analysis for Medical Application -- 12. Statistical Analysis of Tongue Color and Its Applications in Diagnosis -- 13. Hyperspetral Tongue Image Classification -- 14. Computerized Tongue Diagnosis based on Bayesian Networks -- 15. Tongue Image Analysis for Appendicitis Diagnosis -- 16. Diagnosis Using Quantitative Tongue Feature Classification -- 17. Detecting Diabetes Mellitus and Non-Proliferative Diabetic Retinopathy Using CTD Introduction -- 18. Book Review and Future Word.
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.