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.
Tipo de material:
TextoSeries Image Processing, Computer Vision, Pattern Recognition, and Graphics ; 11074Editor: Cham : Springer International Publishing : Imprint: Springer, 2018Edición: 1st ed. 2018Descripción: X, 158 p. 67 illus. online resourceTipo de contenido: text Tipo de medio: computer Tipo de portador: online resourceISBN: 9783030001292Tema(s): 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 InformaticsFormatos físicos adicionales: Printed edition:: Sin título; Printed edition:: Sin títuloClasificación CDD: 006.3 Clasificación LoC:Q334-342Recursos en línea: Libro electrónico
Contenidos:
En: Springer Nature eBookResumen: 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.
Deep learning for magnetic resonance imaging -- Deep learning for computed tomography -- Deep learning for general image reconstruction.
| Tipo de ítem | Biblioteca actual | Colección | Signatura | Copia número | Estado | Fecha de vencimiento | Código de barras |
|---|---|---|---|---|---|---|---|
| Libro Electrónico | Biblioteca Electrónica | Colección de Libros Electrónicos | 1 | No para préstamo |
Acceso multiusuario
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.
UABC ; Temporal ; 01/01/2021-12/31/2023.
