Rangaraj M. Rangayyan – författare

With the development of rapidly increasing medical imaging modalities and their applications, the need for computers and computing in image generation, processing, visualization, archival, transmission, modeling, and analysis has grown substantially. Computers are being integrated into almost every medical imaging system. Medical Image Analysis and Informatics demonstrates how quantitative analysis becomes possible by the application of computational procedures to medical images. Furthermore, it shows how quantitative and objective analysis facilitated by medical image informatics, CBIR, and CAD could lead to improved diagnosis by physicians. Whereas CAD has become a part of the clinical workflow in the detection of breast cancer with mammograms, it is not yet established in other applications. CBIR is an alternative and complementary approach for image retrieval based on measures derived from images, which could also facilitate CAD. This book shows how digital image processing techniques can assist in quantitative analysis of medical images, how pattern recognition and classification techniques can facilitate CAD, and how CAD systems can assist in achieving efficient diagnosis, in designing optimal treatment protocols, in analyzing the effects of or response to treatment, and in clinical management of various conditions. The book affirms that medical imaging, medical image analysis, medical image informatics, CBIR, and CAD are proven as well as essential techniques for health care.

Computers have become an integral part of medical imaging systems and are used for everything from data acquisition and image generation to image display and analysis. As the scope and complexity of imaging technology steadily increase, more advanced techniques are required to solve the emerging challenges.Biomedical Image Analysis demonstrates the benefits reaped from the application of digital image processing, computer vision, and pattern analysis techniques to biomedical images, such as adding objective strength and improving diagnostic confidence through quantitative analysis. The book focuses on post-acquisition challenges such as image enhancement, detection of edges and objects, analysis of shape, quantification of texture and sharpness, and pattern analysis, rather than on the imaging equipment and imaging techniques. Each chapter addresses several problems associated with imaging or image analysis, outlining the typical processes, then detailing more sophisticated methods directed to the specific problems of interest.Biomedical Image Analysis is useful for senior undergraduate and graduate biomedical engineering students, practicing engineers, and computer scientists working in diverse areas such as telecommunications, biomedical applications, and hospital information systems.

Biomedical Signal Analysis Comprehensive resource covering recent developments, applications of current interest, and advanced techniques for biomedical signal analysis Biomedical Signal Analysis provides extensive insight into digital signal processing techniques for filtering, identification, characterization, classification, and analysis of biomedical signals with the aim of computer-aided diagnosis, taking a unique approach by presenting case studies encountered in the authors’ research work. Each chapter begins with the statement of a biomedical signal problem, followed by a selection of real-life case studies and illustrations with the associated signals. Signal processing, modeling, or analysis techniques are then presented, starting with relatively simple “textbook” methods, followed by more sophisticated research-informed approaches. Each chapter concludes with solutions to practical applications. Illustrations of real-life biomedical signals and their derivatives are included throughout. The third edition expands on essential background material and advanced topics without altering the underlying pedagogical approach and philosophy of the successful first and second editions. The book is enhanced by a large number of study questions and laboratory exercises as well as an online repository with solutions to problems and data files for laboratory work and projects. Biomedical Signal Analysis provides theoretical and practical information on: The origin and characteristics of several biomedical signalsAnalysis of concurrent, coupled, and correlated processes, with applications in monitoring of sleep apneaFiltering for removal of artifacts, random noise, structured noise, and physiological interference in signals generated by stationary, nonstationary, and cyclostationary processesDetection and characterization of events, covering methods for QRS detection, identification of heart sounds, and detection of the dicrotic notchAnalysis of waveshape and waveform complexityInterpretation and analysis of biomedical signals in the frequency domainMathematical, electrical, mechanical, and physiological modeling of biomedical signals and systemsSophisticated analysis of nonstationary, multicomponent, and multisource signals using wavelets, time-frequency representations, signal decomposition, and dictionary-learning methods Pattern classification and computer-aided diagnosisBiomedical Signal Analysis is an ideal learning resource for senior undergraduate and graduate engineering students. Introductory sections on signals, systems, and transforms make this book accessible to students in disciplines other than electrical engineering.

Edited by and featuring contributions from world-class researchers, Ophthalmological Imaging and Applications offers a unified work of the latest human eye imaging and modeling techniques that have been proposed and applied to the diagnosis of ophthalmologic problems, including inflammation, cataracts, diabetic retinopathy, and glaucoma. With a focus on theory, basic principles, and results derived from research, the book: Explores various morphological, textural, higher-order spectral, and wavelet transformation techniques used to extract salient features from images of the human eyeExamines 2D and 3D finite element and boundary element models of the human eye developed to simulate thermal steady-state conditionsAddresses the difficult task of benchmarking the validity of human eye imaging techniques and computer-simulated results with experimental measurementsIntended to be a companion to Image Analysis and Modeling in Ophthalmology, this volume covers several aspects of multimodal ophthalmological imaging and applications, presenting information in an accessible manner to appeal to a wide audience of students, researchers, and practitioners. Ophthalmological Imaging and Applications considers promising simulations that pave the way for new possibilities in computational methods for eye health care.

Edited by and featuring contributions from world-class researchers, Ophthalmological Imaging and Applications offers a unified work of the latest human eye imaging and modeling techniques that have been proposed and applied to the diagnosis of ophthalmologic problems, including inflammation, cataracts, diabetic retinopathy, and glaucoma. With a focus on theory, basic principles, and results derived from research, the book: Explores various morphological, textural, higher-order spectral, and wavelet transformation techniques used to extract salient features from images of the human eyeExamines 2D and 3D finite element and boundary element models of the human eye developed to simulate thermal steady-state conditionsAddresses the difficult task of benchmarking the validity of human eye imaging techniques and computer-simulated results with experimental measurementsIntended to be a companion to Image Analysis and Modeling in Ophthalmology, this volume covers several aspects of multimodal ophthalmological imaging and applications, presenting information in an accessible manner to appeal to a wide audience of students, researchers, and practitioners. Ophthalmological Imaging and Applications considers promising simulations that pave the way for new possibilities in computational methods for eye health care.

With the development of rapidly increasing medical imaging modalities and their applications, the need for computers and computing in image generation, processing, visualization, archival, transmission, modeling, and analysis has grown substantially. Computers are being integrated into almost every medical imaging system. Medical Image Analysis and Informatics demonstrates how quantitative analysis becomes possible by the application of computational procedures to medical images. Furthermore, it shows how quantitative and objective analysis facilitated by medical image informatics, CBIR, and CAD could lead to improved diagnosis by physicians. Whereas CAD has become a part of the clinical workflow in the detection of breast cancer with mammograms, it is not yet established in other applications. CBIR is an alternative and complementary approach for image retrieval based on measures derived from images, which could also facilitate CAD. This book shows how digital image processing techniques can assist in quantitative analysis of medical images, how pattern recognition and classification techniques can facilitate CAD, and how CAD systems can assist in achieving efficient diagnosis, in designing optimal treatment protocols, in analyzing the effects of or response to treatment, and in clinical management of various conditions. The book affirms that medical imaging, medical image analysis, medical image informatics, CBIR, and CAD are proven as well as essential techniques for health care.

a measure of the local magnitude and orientation of oriented features over the entire region of analysis in the image is called the orientation field.

Table of Contents: Computer-Aided Diagnosis of Breast Cancer / Detection and Analysis of\newline Breast Masses / Datasets of Images of Breast Masses / Methods for Fractal Analysis / Pattern Classification / Results of Classification of Breast Masses / Concluding Remarks