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Deep Learning for Medical Image Analysis

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Title: Deep Learning for Medical Image Analysis
Description: Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. - Covers common research problems in medical image analysis and their challenges - Describes deep learning methods and the theories behind approaches for medical image analysis - Teaches how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. - Includes a Foreword written by Nicholas Ayache
Authors: S. Kevin Zhou, Hayit Greenspan, Dinggang Shen
Resource Type: eBook.
Subjects: Image analysis, Diagnostic imaging--Data processing
Categories: COMPUTERS / Image Processing, COMPUTERS / Business & Productivity Software / Business Intelligence
Database: eBook Collection (EBSCOhost)
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  Data: Deep learning is providing exciting solutions for medical image analysis problems and is seen as a key method for future applications. This book gives a clear understanding of the principles and methods of neural network and deep learning concepts, showing how the algorithms that integrate deep learning as a core component have been applied to medical image detection, segmentation and registration, and computer-aided analysis, using a wide variety of application areas. Deep Learning for Medical Image Analysis is a great learning resource for academic and industry researchers in medical imaging analysis, and for graduate students taking courses on machine learning and deep learning for computer vision and medical image computing and analysis. - Covers common research problems in medical image analysis and their challenges - Describes deep learning methods and the theories behind approaches for medical image analysis - Teaches how algorithms are applied to a broad range of application areas, including Chest X-ray, breast CAD, lung and chest, microscopy and pathology, etc. - Includes a Foreword written by Nicholas Ayache
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      – Code: 616.0754
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Image analysis
        Type: general
      – SubjectFull: Diagnostic imaging--Data processing
        Type: general
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      – TitleFull: Deep Learning for Medical Image Analysis
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            NameFull: S. Kevin Zhou
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            NameFull: Hayit Greenspan
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            NameFull: Dinggang Shen
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            NameFull: S. Kevin Zhou
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            NameFull: Hayit Greenspan
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            NameFull: Dinggang Shen
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2017
            – D: 09
              M: 02
              Type: profile
              Y: 2017
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              Value: 9780128104088
            – Type: isbn-electronic
              Value: 9780128104095
          Titles:
            – TitleFull: Deep Learning for Medical Image Analysis
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