Machine Learning for Medical Image Reconstruction First International Workshop, MLMIR 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings
by
 
Knoll, Florian. editor. (orcid)0000-0001-5357-8656

Title
Machine Learning for Medical Image Reconstruction First International Workshop, MLMIR 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings

Author
Knoll, Florian. editor. (orcid)0000-0001-5357-8656

ISBN
9783030001292

Physical Description
X, 158 p. 67 illus. online resource.

Series
Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11074

Contents
Deep learning for magnetic resonance imaging -- Deep learning for computed tomography -- Deep learning for general image reconstruction.

Abstract
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.

Subject Term
Artificial intelligence.
 
Computer vision.
 
Computer Communication Networks.
 
Logic design.
 
Medical records -- Data processing.
 
Artificial Intelligence. http://scigraph.springernature.com/things/product-market-codes/I21000
 
Image Processing and Computer Vision. http://scigraph.springernature.com/things/product-market-codes/I22021
 
Computer Communication Networks. http://scigraph.springernature.com/things/product-market-codes/I13022
 
Logic Design. http://scigraph.springernature.com/things/product-market-codes/I12050
 
Health Informatics. http://scigraph.springernature.com/things/product-market-codes/I23060

Added Author
Knoll, Florian.
 
Maier, Andreas.
 
Rueckert, Daniel.

Added Corporate Author
SpringerLink (Online service)

Electronic Access
https://doi.org/10.1007/978-3-030-00129-2


LibraryMaterial TypeItem BarcodeShelf NumberStatus
IYTE LibraryE-Book2085398-1001Q334 -342Online Springer