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Advances in Computer Vision and Pattern Recognition
cover

Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics

Editors: Le, L., Wang, X., Carneiro, G., Yang, L. (Eds.)

  • Reviews the state of the art in deep learning approaches to robust disease detection, organ segmentation in medical image computing, and the construction and mining of large-scale radiology databases
  • Particularly focuses on the application of convolutional neural networks, supporting the theory with numerous practical examples
  • Highlights how deep neural networks can be used to address new questions and protocols, and provide novel solutions 
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Buy this book

eBook 71,39 €
price for Spain (gross)
  • The eBook version of this title will be available soon
  • Due: November 25, 2019
  • ISBN 978-3-030-13969-8
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover 124,79 €
price for Spain (gross)
  • Due: November 25, 2019
  • ISBN 978-3-030-13968-1
  • Free shipping for individuals worldwide
  • The final prices may differ from the prices shown due to specifics of VAT rules
About this book

This book reviews the state of the art in deep learning approaches to high-performance robust disease detection, robust and accurate organ segmentation in medical image computing (radiological and pathological imaging modalities), and the construction and mining of large-scale radiology databases. It particularly focuses on the application of convolutional neural networks, and on recurrent neural networks like LSTM, using numerous practical examples to complement the theory. 
The book’s chief features are as follows: It highlights how deep neural networks can be used to address new questions and protocols, and to tackle current challenges in medical image computing; presents a comprehensive review of the latest research and literature; and describes a range of different methods that employ deep learning for object or landmark detection tasks in 2D and 3D medical imaging. In addition, the book examines a broad selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to text and image deep embedding for a large-scale chest x-ray image database; and discusses how deep learning relational graphs can be used to organize a sizable collection of radiology findings from real clinical practice, allowing semantic similarity-based retrieval.

The intended reader of this edited book is a professional engineer, scientist or a graduate student who is able to comprehend general concepts of image processing, computer vision and medical image analysis. They can apply computer science and mathematical principles into problem solving practices. It may be necessary to have a certain level of familiarity with a number of more advanced subjects: image formation and enhancement, image understanding, visual recognition in medical applications, statistical learning, deep neural networks, structured prediction and image segmentation.

 


About the authors

Dr. Le Lu is the Director of Ping An Technology US Research Labs, and an adjunct faculty member at Johns Hopkins University, USA.

Dr. Xiaosong Wang is a Senior Applied Research Scientist at Nvidia Corp., USA.

Dr. Gustavo Carneiro is an Associate Professor at the University of Adelaide, Australia.

Dr. Lin Yang is an Associate Professor at the University of Florida, USA.

Buy this book

eBook 71,39 €
price for Spain (gross)
  • The eBook version of this title will be available soon
  • Due: November 25, 2019
  • ISBN 978-3-030-13969-8
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover 124,79 €
price for Spain (gross)
  • Due: November 25, 2019
  • ISBN 978-3-030-13968-1
  • Free shipping for individuals worldwide
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Deep Learning and Convolutional Neural Networks for Medical Imaging and Clinical Informatics
Editors
  • Lu Le
  • Xiaosong Wang
  • Gustavo Carneiro
  • Lin Yang
Series Title
Advances in Computer Vision and Pattern Recognition
Copyright
2019
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-13969-8
DOI
10.1007/978-3-030-13969-8
Hardcover ISBN
978-3-030-13968-1
Series ISSN
2191-6586
Edition Number
1
Number of Pages
XI, 461
Number of Illustrations
12 b/w illustrations, 156 illustrations in colour
Topics