Published by Springer International Publishing, Springer International Publishing, 2017
ISBN 10: 3319429981 ISBN 13: 9783319429984
Language: English
Seller: AHA-BUCH GmbH, Einbeck, Germany
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Add to basketBuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.
Published by Springer Nature Switzerland, Springer International Publishing Jul 2017, 2017
ISBN 10: 3319429981 ISBN 13: 9783319429984
Language: English
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
US$ 204.36
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Add to basketBuch. Condition: Neu. Neuware -This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 340 pp. Englisch.
Seller: Books Puddle, New York, NY, U.S.A.
Condition: New.
Published by Springer International Publishing, 2017
ISBN 10: 3319429981 ISBN 13: 9783319429984
Language: English
Seller: moluna, Greven, Germany
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Add to basketGebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Addresses the challenges of applying deep learning for medical image analysisPresents insights from leading experts in the fieldDescribes principles and best practicesDr. Le Lu is a Staff Scientist in the Radiolo.
Published by Springer International Publishing Jul 2017, 2017
ISBN 10: 3319429981 ISBN 13: 9783319429984
Language: English
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
US$ 204.36
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Add to basketBuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book presents a detailed review of the state of the art in deep learning approaches for semantic object detection and segmentation in medical image computing, and large-scale radiology database mining. A particular focus is placed on the application of convolutional neural networks, with the theory supported by practical examples. Features: highlights how the use of deep neural networks can address new questions and protocols, as well as improve upon existing challenges in medical image computing; discusses the insightful research experience of Dr. Ronald M. Summers; presents a comprehensive review of the latest research and literature; describes a range of different methods that make use of deep learning for object or landmark detection tasks in 2D and 3D medical imaging; examines a varied selection of techniques for semantic segmentation using deep learning principles in medical imaging; introduces a novel approach to interleaved text and image deep mining on a large-scale radiology image database. 340 pp. Englisch.
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Seller: Biblios, Frankfurt am main, HESSE, Germany
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Add to basketCondition: New. PRINT ON DEMAND.