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Pattern Recognition and Signal Analysis in Medical Imaging,9780124095458
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Pattern Recognition and Signal Analysis in Medical Imaging



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Academic Pr
List Price: $140.00

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This is the 2nd edition with a publication date of 3/1/2014.

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The new edition of this book presents readers with a comprehensive analysis of the authors' latest NIH-funded work into visualization and interpretation methods in biology and medicine. Since the first edition there has been a tremendous development of new, powerful technologies for detecting, storing, transmitting, analyzing, and displaying medical images. Computer aided analytical techniques, coupled with a continuing need to derive more information from medical images, has led to a growing application of digital processing techniques in cancer detection and elsewhere in medicine. The most challenging area for medical imaging lies in the development of integrated systems for the use in the clinical sector. This new edition responds to this challenge by presenting a complete overview and assessment of both proven and new methods in biomedical signal analysis and interpretation, as well as of automated systems with application to spatio-temporal medical imaging. Presents comprehensive analysis of the authors' latest NIH-funded work into visualization and interpretation methods in biology and medicine. The emphasis of the book lies in the compilation and organization of a breadth of new approaches, modeling, and applications for pattern recognition and image analysis in medical imaging. Only basic knowledge of digital signal processing, linear algebra, and probability is necessary to fully appreciate the topics considered in this book, in order to be used by the interdisciplinary scientific community. New edition expanded to cover signal analysis which was only superficially covered in the 1st edition New chapters on Cluster Validity Techniques, Computer-Aided Diagnosis Systems in Breast MRI, and Spatio-Temporal Models in MRI and Perfusion Cardiac Vascular MRI. 5 extended chapters, and updated content throughout.

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