Deep Learning and Convolutional Neural Networks for Medical Image Computing
Precision Medicine, High Performance and Large-Scale Datasets
This timely text/reference 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.Topics and 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 computingDiscusses the insightful research experience and views of Dr. Ronald M. Summers in medical imaging-based computer-aide…
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Produktdetails
Weitere Autoren: Zheng, Yefeng (Hrsg.) / Carneiro, Gustavo (Hrsg.) / Yang, Lin (Hrsg.)
- ISBN: 978-3-319-42999-1
- EAN: 9783319429991
- Produktnummer: 23749930
- Verlag: Springer-Verlag GmbH
- Sprache: Englisch
- Erscheinungsjahr: 2017
- Seitenangabe: 326 S.
- Plattform: PDF
- Masse: 14'488 KB
- Auflage: 1st ed. 2017
- Abbildungen: 17 schwarz-weiße und 100 farbige Abbildungen, Bibliographie
Über den Autor
Dr. Le Lu is a Staff Scientist in the Radiology and Imaging Sciences Department of the National Institutes of Health Clinical Center, Bethesda, MD, USA.Dr. Yefeng Zheng is a Senior Staff Scientist at Siemens Healthcare Technology Center, Princeton, NJ, USA.Dr. Gustavo Carneiro is an Associate Professor in the School of Computer Science at The University of Adelaide, Australia.Dr. Lin Yang is an Associate Professor in the Department of Biomedical Engineering at the University of Florida, Gainesville, FL, USA.
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