Medical Image Recognition, Segmentation and Parsing: Machine Learning and Multiple Object Approaches (The MICCAI Society book Series)

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This book describes the technical problems and solutions for automatically recognizing and parsing a medical image into multiple objects, structures, or anatomies. It gives all the key methods, including state-of- the-art approaches based on machine learning, for recognizing or detecting, parsing or segmenting, a cohort of anatomical structures from a medical image.

Written by top experts in Medical Imaging, this book is ideal for university researchers and industry practitioners in medical imaging who want a complete reference on key methods, algorithms and applications in medical image recognition, segmentation and parsing of multiple objects.

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Research challenges and problems in medical image recognition, segmentation and parsing of multiple objectsMethods and theories for medical image recognition, segmentation and parsing of multiple objectsEfficient and effective machine learning solutions based on big datasetsSelected applications of medical image parsing using proven algorithmsProvides a comprehensive overview of state-of-the-art research on medical image recognition, segmentation, and parsing of multiple objectsPresents efficient and effective approaches based on machine learning paradigms to leverage the anatomical context in the medical images, best exemplified by large datasetsIncludes algorithms for recognizing and parsing of known anatomies for practical applications

Publisher ‏ : ‎ Academic Press; 1st edition (December 22, 2015)
Language ‏ : ‎ English
Hardcover ‏ : ‎ 542 pages
ISBN-10 ‏ : ‎ 0128025816
ISBN-13 ‏ : ‎ 978-0128025819
Item Weight ‏ : ‎ 3.97 pounds
Dimensions ‏ : ‎ 7.7 x 1.3 x 9.3 inches