Medical Image Recognition, Segmentation and Parsing: Machine Learning and Multiple Object Approaches (The Elsevier and Miccai Society Book Series)

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9780128025819: Medical Image Recognition, Segmentation and Parsing: Machine Learning and Multiple Object Approaches (The Elsevier and Miccai Society Book Series)

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.

Learn:

  • Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects
  • Methods and theories for medical image recognition, segmentation and parsing of multiple objects
  • Efficient and effective machine learning solutions based on big datasets
  • Selected applications of medical image parsing using proven algorithms
  • Provides a comprehensive overview of state-of-the-art research on medical image recognition, segmentation, and parsing of multiple objects
  • Presents efficient and effective approaches based on machine learning paradigms to leverage the anatomical context in the medical images, best exemplified by large datasets
  • Includes algorithms for recognizing and parsing of known anatomies for practical applications

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About the Author:

S. Kevin Zhou, Ph.D. is currently a Principal Key Expert Scientist at Siemens Healthcare Technology Center, leading a team of full time research scientists and students dedicated to researching and developing innovative solutions for medical and industrial imaging products. His research interests lie in computer vision and machine/deep learning and their applications to medical image analysis, face recognition and modeling, etc. He has published over 150 book chapters and peer-reviewed journal and conference papers, registered over 250 patents and inventions, written two research monographs, and edited three books. He has won multiple technology, patent and product awards, including R&D 100 Award and Siemens Inventor of the Year. He is an editorial board member for Medical Image Analysis journal and a fellow of American Institute of Medical and Biological Engineering (AIMBE).

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Book Description Elsevier Science Publishing Co Inc, United States, 2015. Hardback. Book Condition: New. 235 x 190 mm. Language: English . Brand New Book. 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. Learn: * Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects* Methods and theories for medical image recognition, segmentation and parsing of multiple objects* Efficient and effective machine learning solutions based on big datasets* Selected applications of medical image parsing using proven algorithms. Bookseller Inventory # AAZ9780128025819

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Book Description Elsevier Science Publishing Co Inc, United States, 2015. Hardback. Book Condition: New. 235 x 190 mm. Language: English . Brand New Book. 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. Learn: * Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects* Methods and theories for medical image recognition, segmentation and parsing of multiple objects* Efficient and effective machine learning solutions based on big datasets* Selected applications of medical image parsing using proven algorithms. Bookseller Inventory # AAZ9780128025819

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Book Description Elsevier Science Publishing Co Inc. Hardback. Book Condition: new. BRAND NEW, Medical Image Recognition, Segmentation and Parsing: Machine Learning and Multiple Object Approaches, Kevin Zhou, 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. Learn: * Research challenges and problems in medical image recognition, segmentation and parsing of multiple objects* Methods and theories for medical image recognition, segmentation and parsing of multiple objects* Efficient and effective machine learning solutions based on big datasets* Selected applications of medical image parsing using proven algorithms * Provides a comprehensive overview of state-of-the-art research on medical image recognition, segmentation, and parsing of multiple objects* Presents efficient and effective approaches based on machine learning paradigms to leverage the anatomical context in the medical images, best exemplified by large datasets* Includes algorithms for recognizing and parsing of known anatomies for practical applications. Bookseller Inventory # B9780128025819

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