Machine Learning for Medical Image Reconstruction [electronic resource] : First International Workshop, MLMIR 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings / edited by Florian Knoll, Andreas Maier, Daniel Rueckert.
Contributor(s): Knoll, Florian [editor.]
| Maier, Andreas [editor.] | Rueckert, Daniel [editor.] | SpringerLink (Online service).
Material type: 
BookSeries: Image Processing, Computer Vision, Pattern Recognition, and Graphics: 11074Publisher: Cham : Springer International Publishing : Imprint: Springer, 2018Edition: 1st ed. 2018.Description: X, 158 p. 67 illus. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783030001292.Subject(s): Artificial intelligence | Computer vision | Computer networks | Logic design | Medical informatics | Artificial Intelligence | Computer Vision | Computer Communication Networks | Logic Design | Health InformaticsAdditional physical formats: Printed edition:: No title; Printed edition:: No titleDDC classification: 006.3 Online resources: Click here to access online Deep learning for magnetic resonance imaging -- Deep learning for computed tomography -- Deep learning for general image reconstruction.
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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