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Deep Learning for Medical Image Analysis, 1ed

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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

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).

Contents

۱ An Introduction to Neural Networks and Deep Learning
۲ An Introduction to Deep Convolutional Neural Nets for Computer Vision
۳ Efficient Medical Image Parsing
۴ Multi-Instance Multi-Stage Deep Learning for Medical Image Recognition
۵ Automatic Interpretation of Carotid Intima-Media Thickness Videos Using Convolutional Neural Networks
۶ Deep Cascaded Networks for Sparsely Distributed Object Detection from Medical Images
۷ Deep Voting and Structured Regression for Microscopy Image Analysis
۸ Deep Learning Tissue Segmentation in Cardiac Histopathology Images
۹ Deformable MR Prostate Segmentation via Deep Feature Learning and Sparse Patch Matching
۱۰ Characterization of Errors in Deep Learning-Based Brain MRI Segmentation
۱۱ Scalable High Performance Image Registration Framework by Unsupervised Deep Feature Representations Learning
۱۲ Convolutional Neural Networks for Robust and Real-Time 2-D/3-D Registration
۱۳ Chest Radiograph Pathology Categorization via Transfer Learning
۱۴ Deep Learning Models for Classifying Mammogram Exams Containing Unregistered Multi-View Images and Segmentation Maps of Lesions
۱۵ Randomized Deep Learning Methods for Clinical Trial Enrichment and Design in Alzheimer’s Disease
۱۶ Deep Networks and Mutual Information Maximization for Cross-Modal Medical Image Synthesis
۱۷ Natural Language Processing for Large-Scale Medical Image Analysis Using Deep Learning

قیمت : 5000 تومان
لینک کوتاه : https://bookbaz.ir/?p=101697
نویسنده : S. Kevin Zhou , Hayit Greenspan
ناشر : Academic Press; 1 edition
سال انتشار : 2017
زبان کتاب : انگلیسی
نوع فایل : PDF
تعداد صفحات : 459
(ISBN) شابک : 0128104082
قیمت کتاب درآمازون : $57.05
حجم فایل : 10 MB

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۵۰۰۰ تـومان – خرید