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Tongue Image Analysis PDF

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David Zhang · Hongzhi Zhang Bob Zhang Tongue Image Analysis Tongue Image Analysis David Zhang Hongzhi Zhang (cid:129) Bob Zhang Tongue Image Analysis 123 DavidZhang BobZhang TheHong Kong Polytechnic University Department ofComputer andInformation Hong Kong Science China TheUniversity of Macau Taipa Hongzhi Zhang Macao Schoolof Computer Science andTechnology Harbin Institute of Technology Harbin China ISBN978-981-10-2166-4 ISBN978-981-10-2167-1 (eBook) DOI 10.1007/978-981-10-2167-1 LibraryofCongressControlNumber:2016963737 ©SpringerScience+BusinessMediaSingapore2017 Thisworkissubjecttocopyright.AllrightsarereservedbythePublisher,whetherthewholeorpart of the material is concerned, specifically the rights of translation, reprinting, reuse of illustrations, recitation, broadcasting, reproduction on microfilms or in any other physical way, and transmission orinformationstorageandretrieval,electronicadaptation,computersoftware,orbysimilarordissimilar methodologynowknownorhereafterdeveloped. The use of general descriptive names, registered names, trademarks, service marks, etc. in this publicationdoesnotimply,evenintheabsenceofaspecificstatement,thatsuchnamesareexemptfrom therelevantprotectivelawsandregulationsandthereforefreeforgeneraluse. The publisher, the authors and the editors are safe to assume that the advice and information in this book are believed to be true and accurate at the date of publication. Neither the publisher nor the authorsortheeditorsgiveawarranty,expressorimplied,withrespecttothematerialcontainedhereinor for any errors or omissions that may have been made. The publisher remains neutral with regard to jurisdictionalclaimsinpublishedmapsandinstitutionalaffiliations. Printedonacid-freepaper ThisSpringerimprintispublishedbySpringerNature TheregisteredcompanyisSpringerNatureSingaporePteLtd. Theregisteredcompanyaddressis:152BeachRoad,#22-06/08GatewayEast,Singapore189721,Singapore Preface The tongue, as the primary organ of gustation, conveys abundant valuable information about the health status of the human body, i.e., disorders or even pathological changes of internal organs can be reflected by the human tongue and observed by medical practitioners. Tongue diagnosis (TD), a noninvasive diag- nostic method using inspection of the appearance of human tongue, has played an indispensableroleinTraditionalChineseMedicine(TCM)forover2,000years.In recent years, for the purpose of academic research, significant information tech- nologies, including digitalized data acquisition, image processing, and pattern recognition have been widely used in tongue diagnosis to improve its diagnostic validity and accuracy. Computerized tongue diagnosis (CTD), as a result, has become a fundamental part of the revolution that has taken place at an ever-increasing pace over the past decade in TCM. The growing importance and rapidprogressinCTDhasbroughtaboutanindependentandburgeoningbranchin the TCM research field, and also resulted in urgent and extensive requirements for tongue image analytical techniques. Byitsverynature,tongueimageanalysisiscross-disciplinaryinseveralaspects. First, before a tongue image can be analyzed, it is imperative that the basic prin- ciples of TD should be mastered. For instance, we should know what kinds of visibleinformationarecrucialforthevisualinspectionprocessofTD.Thismainly includes several aspects in the TCM and computer vision (CV) research fields. Next, in order to get useful data, a special acquisition system should be carefully designed to guarantee that all the informationis included in the signal acquired by the imaging sensor. This incorporates the interaction of optics of matter to the geometry and radiometry of imaging and industrial design. Finally, after being captured and converted into digital form, the tongue image should be processed, analyzed, and classified by the computer. In this chain of processes, many areas from computer science and mathematics are involved, e.g., computer architecture, algebra, analysis, statistics, algorithm theory, graph theory, system theory, and numericalmathematics,allofwhichhaveapartialorstrongassociationwithtongue image analysis. v vi Preface Today, the field of modern tongue diagnosis is becoming more technical. Althoughpractitionersneedtounderstandthebasictheoryandpracticeofcomputer science such as image processing and pattern recognition, they also need guidance onhow toactually addressthornyproblems suchasautomaticsegmentation, color distortion, and robust classification of tongue images which are very helpful tothe practicing CTD scientist. It is the purpose of this book, as briefly and concisely as possible, to give the readerastraightforwardandintuitiveintroductiontobasicandadvancedtechniques in tongue image processing and analysis and their typical applications in CTD systems.Itfeaturesthemostcurrentresearchfindingsinallaspectsoftongueimage acquisition, preprocessing, classification, and diagnostic support methodologies, fromtheoreticalandalgorithmicproblemstoprototype designanddevelopmentof CTD systems. In the first two chapters, the book begins with a very high-level description of CTD on a need-to-know basis which includes an overview of CTD systems and TraditionalChineseMedicine(TCM)asthecontextandbackgroundknowledgeof tongue image analysis. From Chaps. 3 to 13, the principal part of the book then provides useful algorithms as well as their implementation methods of tongue imageanalysis.Themostnotableextensions,ataknow-howlevel,includedetailed discussions on segmentation, chromatic correction, and classification which are arranged in systematic order as follows. The first preprocessing step of tongue image processing and CTD, automated tongue image segmentation is difficult due to two special factors. First, there are manypathologicaldetailsonthesurfaceofthetongue,whichhavealargeinfluence on edge extraction. Second, the shapes of tongue bodies captured from various personsarequitedifferent.Sofar,thereisnosinglesolutionthatcanaddressallthe problems in automated tongue image segmentation. From Chaps. 3 to 7, the book presentsfivedifferentsegmentationapproachestosolvedomainproblemsbasedon different kinds of tongue images. These methods are robust to noise caused by a variety of shapes and irrelevant information from non-tongue parts such as lips, beard, and facial skin. After segmenting the tongue area from its surroundings, a study on tongue shape analysis by using the tongue contour and its geometric features is then introduced in Chap. 8 as the end of Part II. Part III makes a sound exposition of the quantitative classification of tongue images beginning with the correction of the color feature in tongue image. Color inconsistency is the second problem CTD scientists have to face before analyzing thetongueimage.Sincethecolorsofthetongueimageproducedbydigitalcameras are usually device-dependent, this is a serious problem in computer-aided tongue image analysis which relies on the accurate rendering of color information. In Chaps.9and10,thebookintroducesanoptimizedtongueimagecolorcheckerand correction scheme which enhances the color consistency between different acqui- sitiondevices.IthaslongbeenacontroversialtopicthattheTCMphysicianmainly explores the nonquantitative features in the traditional diagnosis process. To diagnose a wide range of health conditions, CTD should examine quantitative Preface vii features of the tongue. From Chaps. 11 to 13, the book describes three tongue classification methods with excellent comprehensive performances. In this book, some clinical applications based on the tongue image analyzing methods are also presented, for the show-how purpose, in the CTD research field. Case studies highlight different techniques that have been adopted to assist the diagnosis of diseases and health. From Chaps. 14 to 17, the book discusses rela- tionships between diseases and the appearance of the human tongue in terms of quantitative features. In Part IV, we present case studies in the field of visual inspection for appendicitis, diabetes, and some other common diseases. Experimental results of the performance under different challenging clinical cir- cumstances have shown the superiority of the techniques in this book. Theprinciplesoftongueimageanalysisinthisbookareillustratedwithplentiful graphs,tables,andpracticalexperimentstosimplifyproblems.Inthisway,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. All the tech- niques presented in the book are well supported by experimental results using a largetongueimagedatabase,whichwascollectedfrom5,222subjects(Over9,000 images) by our dedicated developed image acquisition device. All these subjects were diagnosed (patient-subjects) or labeled (healthcare-subjects) into different healthstatus(healthy,sub-healthy,andvariousdiseases)inthehospital.Tothebest of our knowledge, this is the largest and most comprehensive database in the researchcommunity.Thisbookwillbeofbenefittoresearchers,professionals,and graduate students working in the field of computer vision, pattern recognition, clinical practice, and TCM, and will also be useful for interdisciplinary research. We anticipate that physicians, biomedical scientists, engineers, programmers, and studentsofcomputerswillfindthisbookandtheassociatedalgorithmsuseful,and hopethatanyonewithaninterestincomputerized diagnosticresearchwillfindthe book enjoyable and informative. The book is the result of years of research on computational TCM diagnosis. Since 1998, under grant support from the National Natural Science Foundation of China (NSFC), Hong Kong Polytechnic University, and Harbin Institute of Technology, we have studied this topic. The authors would like to thank Dr. Zhaotian Zhang, Dr. Xiaoyun Xiong, and Dr. Ke Liu from NSFC for their consistent support to our research work. Some of the material in the book, e.g., the tongue images and acquisition devices, has been under development for almost a decade. Portions of the book appeared in earlier forms as conference papers, journal papers, or experiments by my research group at The Hong Kong Polytechnic University and Harbin Institute of Technology. Therefore, these parts of the text are the newest updates based on our research. I would like to gratefully acknowledge the Institute of Electrical and Electronic Engineers (IEEE) and Elsevier Publishers, for giving me permission to reuse texts and figures that have appeared in some earlier publications. WewouldliketothankourcolleaguesandPh.D.students,i.e.,Prof.Kuanquan Wang, Prof. Naimin Li, Prof. Edward C. Mignot, Dr. Bo Pang, Dr. Xingzheng viii Preface Wang, Dr. Zhi Liu, and Dr. Zhenchao Cui, for their contributions to the research achievements on computational TCM diagnosis. It is also our honor to collaborate with them in this fascinating and ever-growing research field. I would also like to expressmysincerethankstoallindividualsandorganizationswhohavecontributed visual material for this book. Finally,theworkinthisbookwasmainlysponsoredbytheNSFCProgramunder Grant No. 61332011, 61020106004, 61271093, 61272292, 61471146, and 61271344, Shenzhen Fundamental Science and Technology Development Fund (FDCT)ofMacaoSAR(FDCT/128/2013/AandFDCT/124/2014/A3),theUniversity of Macau (MRG026/ZYB/2015/FST), Research Fund (JCYJ20130401152508661), and the Key Laboratory of Network Oriented Intelligent Computation, Shenzhen, China. Kowloon, Hong Kong David Zhang June 2016 Contents Part I Background 1 Introduction to Tongue Image Analysis ... .... .... .... ..... .. 3 1.1 Tongue Inspection for Medical Applications .... .... ..... .. 3 1.2 Computerized Tongue Diagnosis System... .... .... ..... .. 6 1.3 Research Review on Tongue Image Analysis.... .... ..... .. 7 1.3.1 Tongue Image Acquisition ... .... .... .... ..... .. 7 1.3.2 Tongue Image Preprocessing . .... .... .... ..... .. 8 1.3.3 Qualitative Feature Extraction. .... .... .... ..... .. 10 1.3.4 Diagnostic Classification. .... .... .... .... ..... .. 11 1.4 Issues and Challenges ..... .... .... .... .... .... ..... .. 11 1.4.1 Inconsistent Image Acquisition.... .... .... ..... .. 12 1.4.2 Inaccurate Color Correction .. .... .... .... ..... .. 13 1.4.3 Subjective Tongue Color Extraction and Classification .. .... .... .... .... .... ..... .. 14 References .. .... .... .... ..... .... .... .... .... .... ..... .. 14 2 Tongue Images Acquisition System Design. .... .... .... ..... .. 19 2.1 Introduction .... .... ..... .... .... .... .... .... ..... .. 19 2.2 System Framework and Requirement Analysis... .... ..... .. 22 2.2.1 System Framework. .... .... .... .... .... ..... .. 23 2.2.2 Requirement Analysis... .... .... .... .... ..... .. 24 2.3 Optimal System Design .... .... .... .... .... .... ..... .. 27 2.3.1 Illuminant... ..... .... .... .... .... .... ..... .. 27 2.3.2 Lighting Condition . .... .... .... .... .... ..... .. 28 2.3.3 Imaging Camera ... .... .... .... .... .... ..... .. 30 2.3.4 Color Correction... .... .... .... .... .... ..... .. 32 2.3.5 System Implementation and Calibration . .... ..... .. 33 ix x Contents 2.4 Performance Analysis. ..... .... .... .... .... .... ..... .. 35 2.4.1 Illumination Uniformity . .... .... .... .... ..... .. 36 2.4.2 System Consistency .... .... .... .... .... ..... .. 37 2.4.3 Accuracy.... ..... .... .... .... .... .... ..... .. 41 2.4.4 Typical Tongue Images.. .... .... .... .... ..... .. 41 2.5 Summary .. .... .... ..... .... .... .... .... .... ..... .. 42 References .. .... .... .... ..... .... .... .... .... .... ..... .. 43 Part II Tongue Image Segmentation and Shape Classification 3 Tongue Image Segmentation by Bi-elliptical Deformable Contour.... .... .... .... ..... .... .... .... .... .... ..... .. 47 3.1 Introduction .... .... ..... .... .... .... .... .... ..... .. 47 3.2 Bi-elliptical Deformable Template for the Tongue.... ..... .. 50 3.2.1 Definitions and Notations .... .... .... .... ..... .. 50 3.2.2 The Tongue Template... .... .... .... .... ..... .. 51 3.2.3 Energy Function for the Tongue Template ... ..... .. 52 3.3 Combined Model for Tongue Segmentation. .... .... ..... .. 55 3.3.1 Two Kinds of Template Forces.... .... .... ..... .. 56 3.3.2 Bi-elliptical Deformable Contours.. .... .... ..... .. 59 3.4 Experiment Results and Analysis. .... .... .... .... ..... .. 62 3.5 Summary .. .... .... ..... .... .... .... .... .... ..... .. 69 References .. .... .... .... ..... .... .... .... .... .... ..... .. 69 4 A Snake-Based Approach to Automated Tongue Image Segmentation.... .... .... ..... .... .... .... .... .... ..... .. 71 4.1 Introduction .... .... ..... .... .... .... .... .... ..... .. 71 4.2 Automated Segmentation Algorithm for Tongue Images .... .. 73 4.2.1 Polar Edge Detection of Tongue Image . .... ..... .. 73 4.2.2 Filtering and Binarization of the Edge Image. ..... .. 75 4.2.3 Initialization and ACM.. .... .... .... .... ..... .. 76 4.2.4 Summary of the Automated Tongue Segmentation Method... .... .... .... .... ..... .. 78 4.3 Experiments and Discussion. .... .... .... .... .... ..... .. 80 4.3.1 Evaluation on the Edge Filtering Algorithm.. ..... .. 80 4.3.2 Qualitative Evaluation... .... .... .... .... ..... .. 80 4.3.3 Quantitative Evaluation.. .... .... .... .... ..... .. 82 4.4 Summary .. .... .... ..... .... .... .... .... .... ..... .. 87 References .. .... .... .... ..... .... .... .... .... .... ..... .. 87 5 Tongue Segmentation in Hyperspectral Images . .... .... ..... .. 89 5.1 Introduction .... .... ..... .... .... .... .... .... ..... .. 89 5.2 Setup of the Hyperspectral Device.... .... .... .... ..... .. 91

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