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|a Machine Learning for Medical Image Reconstruction
|h [electronic resource] :
|b First International Workshop, MLMIR 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings /
|c edited by Florian Knoll, Andreas Maier, Daniel Rueckert.
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| 250 |
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|a 1st ed. 2018.
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| 264 |
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1 |
|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2018.
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| 300 |
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|a X, 158 p. 67 illus.
|b online resource.
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|a Image Processing, Computer Vision, Pattern Recognition, and Graphics ;
|v 11074
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| 490 |
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|a Springer eBook Collection
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| 505 |
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|a Deep learning for magnetic resonance imaging -- Deep learning for computed tomography -- Deep learning for general image reconstruction.
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| 520 |
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|a This book constitutes the refereed proceedings of the First International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2018, held in conjunction with MICCAI 2018, in Granada, Spain, in September 2018. The 17 full papers presented were carefully reviewed and selected from 21 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging; deep learning for computed tomography, and deep learning for general image reconstruction.
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| 590 |
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|a Loaded electronically.
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| 590 |
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|a Electronic access restricted to members of the Holy Cross Community.
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| 650 |
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|a Artificial intelligence.
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| 650 |
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|a Optical data processing.
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|a Computer communication systems.
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|a Logic design.
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|a Health informatics.
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| 690 |
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|a Electronic resources (E-books)
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|a Knoll, Florian.
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|a Maier, Andreas.
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|a Rueckert, Daniel.
|e editor.
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|a Image Processing, Computer Vision, Pattern Recognition, and Graphics ;
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