Vai al contenuto principale della pagina
Titolo: | 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 |
Pubblicazione: | Cham : , : Springer International Publishing : , : Imprint : Springer, , 2018 |
Edizione: | 1st ed. 2018. |
Descrizione fisica: | 1 online resource (X, 158 p. 67 illus.) |
Disciplina: | 616.07540285 |
Soggetto topico: | Artificial intelligence |
Optical data processing | |
Computer communication systems | |
Logic design | |
Health informatics | |
Artificial Intelligence | |
Image Processing and Computer Vision | |
Computer Communication Networks | |
Logic Design | |
Health Informatics | |
Persona (resp. second.): | KnollFlorian |
MaierAndreas | |
RueckertDaniel | |
Nota di bibliografia: | Includes bibliographical references and index. |
Nota di contenuto: | Deep learning for magnetic resonance imaging -- Deep learning for computed tomography -- Deep learning for general image reconstruction. |
Sommario/riassunto: | 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. |
Titolo autorizzato: | Machine Learning for Medical Image Reconstruction |
ISBN: | 3-030-00129-6 |
Formato: | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione: | Inglese |
Record Nr.: | 996466192303316 |
Lo trovi qui: | Univ. di Salerno |
Opac: | Controlla la disponibilità qui |