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Proceedings of the First International Workshop on Pulmonary Image Analysis, held on September 6, 2008 in New York as part of the MICCAI workshop program.
Showcasing the most influential developments, experiments, and architectures impacting the digital, surveillance, automotive, industrial, and medical sciences, Image Processing Technologies tracks the evolution and advancement of computer vision and image processing (CVIP) technologies, examining methods and algorithms for image analysis, optimization, segmentation, and restoration. It focuses on recent approaches and techniques in CVIP applications development and explores various coding methods for individual types of 3-D images. This text/reference brings researchers and specialists up-to-date on the latest innovations affecting multiple image processing environments.
As the third volume of The Biomedical Engineering Handbook, Fourth Edition, this book covers broad areas such as biosignal processing, medical imaging, infrared imaging, and medical informatics. More than three dozen specific topics are examined including biomedical signal acquisition, thermographs, infrared cameras, mammography, computed tomography, positron-emission tomography, magnetic resonance imaging, hospital information systems, and computer-based patient records. The material is presented in a systematic manner and has been updated to reflect the latest applications and research findings.
This book provides a quick and systematic presentation of the principles of biomedical visualization and three-dimensional (3D) imaging. Topics discussed include basic principles and algorithms, surgical planning, neurosurgery, orthopedics, prosthesis design, brain imaging, cardio-pulmonary structure analysis and the assessment of clinical efficacy. Students, scientists, researchers, and radiologists will find 3D Imaging in Medicine a valuable source of information for a variety of actual and potential clinical applications for 3-D imaging.
The Handbook of Medical Image Processing and Analysis is a comprehensive compilation of concepts and techniques used for processing and analyzing medical images after they have been generated or digitized. The Handbook is organized into six sections that relate to the main functions: enhancement, segmentation, quantification, registration, visualization, and compression, storage and communication.The second edition is extensively revised and updated throughout, reflecting new technology and research, and includes new chapters on: higher order statistics for tissue segmentation; tumor growth modeling in oncological image analysis; analysis of cell nuclear features in fluorescence microscopy images; imaging and communication in medical and public health informatics; and dynamic mammogram retrieval from web-based image libraries.For those looking to explore advanced concepts and access essential information, this second edition of Handbook of Medical Image Processing and Analysis is an invaluable resource. It remains the most complete single volume reference for biomedical engineers, researchers, professionals and those working in medical imaging and medical image processing.Dr. Isaac N. Bankman is the supervisor of a group that specializes on imaging, laser and sensor systems, modeling, algorithms and testing at the Johns Hopkins University Applied Physics Laboratory. He received his BSc degree in Electrical Engineering from Bogazici University, Turkey, in 1977, the MSc degree in Electronics from University of Wales, Britain, in 1979, and a PhD in Biomedical Engineering from the Israel Institute of Technology, Israel, in 1985. He is a member of SPIE. - Includes contributions from internationally renowned authors from leading institutions - NEW! 35 of 56 chapters have been revised and updated. Additionally, five new chapters have been added on important topics incluling Nonlinear 3D Boundary Detection, Adaptive Algorithms for Cancer Cytological Diagnosis, Dynamic Mammogram Retrieval from Web-Based Image Libraries, Imaging and Communication in Health Informatics and Tumor Growth Modeling in Oncological Image Analysis. - Provides a complete collection of algorithms in computer processing of medical images - Contains over 60 pages of stunning, four-color images
This book offers a unique guide to the entire chain of biomedical imaging, explaining how image formation is done, and how the most appropriate algorithms are used to address demands and diagnoses. It is an exceptional tool for radiologists, research scientists, senior undergraduate and graduate students in health sciences and engineering, and university professors.
This volume comprises of 21 selected chapters, including two overview chapters devoted to abdominal imaging in clinical applications supported computer aided diagnosis approaches as well as different techniques for solving the pectoral muscle extraction problem in the preprocessing part of the CAD systems for detecting breast cancer in its early stage using digital mammograms. The aim of this book is to stimulate further research in medical imaging applications based algorithmic and computer based approaches and utilize them in real-world clinical applications. The book is divided into four parts, Part-I: Clinical Applications of Medical Imaging, Part-II: Classification and clustering, Part-III: Computer Aided Diagnosis (CAD) Tools and Case Studies and Part-IV: Bio-inspiring based Computer Aided diagnosis techniques.
This is the first edited book that deals with the special topic of signals and images within Case-Based Reasoning (CBR). Signal-interpreting systems are becoming increasingly popular in medical, industrial, ecological, biotechnological and many other applications. Existing statistical and knowledge-based techniques lack robustness, accuracy and flexibility. New strategies are needed that can adapt to changing environmental conditions, signal variation, user needs and process requirements. Introducing CBR strategies into signal-interpreting systems can satisfy these requirements.
MMVR offers solutions for problems in clinical care through the phenomenally expanding potential of computer technology. Computer-based tools promise to improve healthcare while reducing cost - a vital requirement in today's economic environment. This seventh annual MMVR focuses on the healthcare needs of women. Women every where demand more attention to breast cancer, cervical cancer, ageing-related conditions. Electronic tools provide the means to revolutionise diagnosis, treatment and education. The book demonstrates what new tools can improve the care of their female patients. As minimally invasive procedures are mainstreamed, advanced imaging and robotics tools become indispensable. The internet and other networks establish new venues for communication and research. Medical education, as well as clinical care, is enhanced by systems allowing instruction and professional interaction in ways never before possible and with efficiency never before achieved. Telemedicine networks now permit providers to meet patients needs where previously impossible. MMVR strengthens the link between healthcare providers and their patients. The volume contains selected papers authored by presenters at the conference. Areas of focus include Computer-Assisted Surgery, Data Fusion & Informatics, Diagnostic Tools, Education & Training, Mental Health, Modelling, Net Architecture, Robotics, Simulation, Telemedicine, Telepresence and Visualisation.
Statistical Shape and Deformation Analysis: Methods, Implementation and Applications contributes enormously to solving different problems in patient care and physical anthropology, ranging from improved automatic registration and segmentation in medical image computing to the study of genetics, evolution and comparative form in physical anthropology and biology. This book gives a clear description of the concepts, methods, algorithms and techniques developed over the last three decades that is followed by examples of their implementation using open source software. Applications of statistical shape and deformation analysis are given for a wide variety of fields, including biometry, anthropology, medical image analysis and clinical practice. - Presents an accessible introduction to the basic concepts, methods, algorithms and techniques in statistical shape and deformation analysis - Includes implementation examples using open source software - Covers real-life applications of statistical shape and deformation analysis methods