Deep Learning for Medical Image Analysis, Zhou, Kevin

Название: Deep learning for medical image analysis
ISBN: 032385124X ISBN-13(EAN): 9780323851244
Издательство: Elsevier Science
Цена: 16835.00 р.
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Автор: Kathy McQuillen Martensen
Название: Workbook for Radiographic Image Analysis
ISBN: 0323280714 ISBN-13(EAN): 9780323280716
Издательство: Elsevier Science
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Цена: 9283.00 р.
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Описание: The companion workbook for Radiographic Analysis, 3rd Edition, provides you with ample opportunities to practice and apply information from the text. With study questions, additional suboptimal images for analysis, and an answer key to guide you through the problems, you'll have all the tools you need to hone your imaging and evaluation skills. Positioning and technique exercises prepare you for success in radiography practice.

Suboptimal images with questions ensure you know and understand what features need to be visible in an image and how to adjust when the images are incorrect or poor. Extra images offer additional practice with identifying poor quality images and recognizing how they are produced. Study questions reinforce text material and prepare you for certification.

NEW! More suboptimal images for analysis and correction help you hone your evaluation skills. NEW! Expansion of pediatric, obesity, and trauma sections provide pertinent information needed for clinical success.

Автор: Wu, Guorong
Название: Machine Learning and Medical Imaging
ISBN: 0128040769 ISBN-13(EAN): 9780128040768
Издательство: Elsevier Science
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Цена: 16505.00 р.
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Описание: Machine Learning and Medical Imaging presents state-of- the-art machine learning methods in medical image analysis. It first summarizes cutting-edge machine learning algorithms in medical imaging, including not only classical probabilistic modeling and learning methods, but also recent breakthroughs in deep learning, sparse representation/coding, and big data hashing. In the second part leading research groups around the world present a wide spectrum of machine learning methods with application to different medical imaging modalities, clinical domains, and organs. The biomedical imaging modalities include ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), histology, and microscopy images. The targeted organs span the lung, liver, brain, and prostate, while there is also a treatment of examining genetic associations. Machine Learning and Medical Imaging is an ideal reference for medical imaging researchers, industry scientists and engineers, advanced undergraduate and graduate students, and clinicians.

Автор: Zheng
Название: Marginal Space Learning for Medical Image Analysis
ISBN: 1493905996 ISBN-13(EAN): 9781493905997
Издательство: Springer
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Цена: 11179.00 р.
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Описание: Automatic detection and segmentation of anatomical structures in medical images are prerequisites to subsequent image measurements and disease quantification, and therefore have multiple clinical applications.