Medical Biometrics (häftad)
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Format
Häftad (Paperback / softback)
Språk
Engelska
Antal sidor
424
Utgivningsdatum
2010-06-09
Upplaga
2010 ed.
Förlag
Springer-Verlag Berlin and Heidelberg GmbH & Co. K
Medarbetare
Zhang, David (ed.), Sonka, Milan (ed.)
Illustrationer
220 Illustrations, black and white; XII, 424 p. 220 illus.
Dimensioner
234 x 155 x 23 mm
Vikt
658 g
Antal komponenter
1
Komponenter
1 Paperback / softback
ISBN
9783642139222
Medical Biometrics (häftad)

Medical Biometrics

Second International Conference, ICMB 2010, Hong Kong, China, June 28-30, 2010. Proceedings

Häftad Engelska, 2010-06-09
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In the medical ?eld, personalmedical feature data,especially digitalimages,can be referred to as medical biometrics. Such data are produced in ever-increasing quantities and used for diagnostics and therapy purposes. Medical biometric research aims to use personal medical features in di?erent formats such as - ages, signals and other sources to solve medical problems and to provide hi- performance services in the medical ?eld. Medical biometric systems integrate multidisciplinary technologies in biology, medicine, electronics, computing, and statistics. The importance of computer-aided diagnosis and therapy has drawn moreandmoreattentionworldwideandlaidthefoundationformodernmedicine withexcellentpotentialforpromisingapplicationssuchastelemedicineandW- based healthcare. The2010InternationalConferenceonMedicalBiometrics(ICMB2010)placed emphasis on e?cient and e?ective medical biometric technologies and systems. It provided a central forum for researchers,engineers and vendors from di?erent disciplines to exchange the most recent results, identify future directions and challenges, and initiate possible collaborative research and system development. We are pleased that this conference attracted a large number of high-quality research papers that re?ect the increasing interests and popularity in this fa- growing ?eld. The conference proceedingscontain 45 papers which were selected through a strict review process, with an acceptance rate at 38%. Each paper was assessed by three independent reviewers. All of the accepted papers were presented in either oral (20) or poster (25) sessions at the conference in conju- tion with three special sessions on State-of-the-Art of Computer-Aided Det- tion/Diagnosis (CAD), Modernization of Traditional Chinese Medicine (TCM) and E?ective Healthcare.
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Innehållsförteckning

Feature Extraction and Classification.- Fiber Segmentation Using Constrained Clustering.- A New Multi-Task Learning Technique to Predict Classification of Leukemia and Prostate Cancer.- A Benchmark for Geometric Facial Beauty Study.- An Effective Feature Extraction Method Used in Breath Analysis.- Classification of Diabetics with Various Degrees of Autonomic Neuropathy Based on Linear and Nonlinear Features Using Support Vector Machine.- Diabetes Identification and Classification by Means of a Breath Analysis System.- Automatic Measurement of Vertical Cup-to-Disc Ratio on Retinal Fundus Images.- Tongue Image Identification System on Congestion of Fungiform Papillae (CFP).- Newborn Footprint Recognition Using Band-Limited Phase-Only Correlation.- Radii Solaris Extraction through Primitive Modelling.- A DIAMOND Method for Classifying Biological Data.- Tongue Image Texture Segmentation Based on Gabor Filter Plus Normalized Cut.- Chaos Synchronization Detector Combining Radial Basis Network for Estimation of Lower Limb Peripheral Vascular Occlusive Disease.- Classification of Wrist Pulse Blood Flow Signal Using Time Warp Edit Distance.- Computerized Pork Quality Evaluation System.- Abnormal Image Detection Using Texton Method in Wireless Capsule Endoscopy Videos.- Active Contour Method Combining Local Fitting Energy and Global Fitting Energy Dynamically.- Optic Disc Detection by Multi-scale Gaussian Filtering with Scale Production and a Vessels' Directional Matched Filter.- Retinal Vessel Centerline Extraction Using Multiscale Matched Filter and Sparse Representation-Based Classifier.- Pulse Waveform Classification Using ERP-Based Difference-Weighted KNN Classifier.- Health Care.- Development of a Ubiquitous Emergency Medical Service System Based on Zigbee and 3.5G Wireless Communication Technologies.- Digital Skating Board with RFID Technique for Upper Extremity Rehabilitation.- Knowledge Acquisition and Reasoning in Web Based Epidemic Analysis.- Assistive Communication Robot for Pre-operative Health Care.- Design and Implementation of a Digital Auscultation System.- The Application of Non-invasive Oxygen Saturation Sensor to Evaluate Blood Flow in Human.- Context Aware Health Monitoring System.- Novel Two-Stage Analytic Approach in Extraction of Strong Herb-Herb Interactions in TCM Clinical Treatment of Insomnia.- Medical Diagnosis.- Clinical Usage Considerations in the Development and Evaluation of a Computer Aided Diagnosis System for Acute Intracranial Hemorrhage on Brain CT.- Research on the Meridian Diagnostic System Based on the Measuring Principle of the Electrical Properties of Well, Source and Sea Acupoints.- Atrial Fibrillation Analysis Based on Blind Source Separation in 12-Lead ECG Data.- State-of-the-Art of Computer-Aided Detection/Diagnosis (CAD).- Advances in Detecting Parkinson's Disease.- Using Formal Concept Analysis to Visualize Relationships of Syndromes in Traditional Chinese Medicine.- Wrist Pulse Diagnosis Using LDA.- Computerized Wrist Pulse Signal Diagnosis Using KPCA.- Framework of Computer-Assisted Instruction and Clinical Decision Support System for Orthodontics with Case-Based Reasoning.- Design of an Intelligent Reporting System for Cardiac Catheterization.- Presenting a Simplified Assistant Tool for Breast Cancer Diagnosis in Mammography to Radiologists.- Medical Image Processing and Registration.- Feature Based Non-rigid Registration Using Quaternion Subdivision.- A Sparse Decomposition Approach to Compressing Biomedical Signals.- A Comparative Study of Color Correction Algorithms for Tongue Image Inspection.- An Mean Shift Based Gray Level Co-occurrence Matrix for Endoscope Image Diagnosis.- A Novel Criterion for Characterizing Diffusion Anisotropy in HARDI Data Based on the MDL Technique.