TY  - GEN
N2  - This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2021, held in conjunction with MICCAI 2021, in October 2021. The workshop was planned to take place in Strasbourg, France, but was held virtually due to the COVID-19 pandemic. The 13 papers presented were carefully reviewed and selected from 20 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging and deep learning for general image reconstruction.
DO  - 10.1007/978-3-030-88552-6
DO  - doi
AB  - This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning for Medical Reconstruction, MLMIR 2021, held in conjunction with MICCAI 2021, in October 2021. The workshop was planned to take place in Strasbourg, France, but was held virtually due to the COVID-19 pandemic. The 13 papers presented were carefully reviewed and selected from 20 submissions. The papers are organized in the following topical sections: deep learning for magnetic resonance imaging and deep learning for general image reconstruction.
T1  - Machine learning for medical image reconstruction :4th International Workshop, MLMIR 2021, held in conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings /
DA  - 2021.
CY  - Cham :
AU  - Haq, Nandinee.
AU  - Johnson, Patricia.
AU  - Maier, Andreas.
AU  - Würfl, Tobias.
AU  - Yoo, Jaejun.
VL  - 12964
CN  - RC78.7.D53
PB  - Springer,
PP  - Cham :
PY  - 2021.
N1  - 4 Limitation, Discussion and Conclusion.
N1  - Includes author index.
ID  - 1440091
KW  - Diagnostic imaging
KW  - Artificial intelligence
KW  - Machine learning
KW  - Imagerie pour le diagnostic
KW  - Intelligence artificielle en médecine
KW  - Apprentissage automatique
SN  - 9783030885526
SN  - 3030885526
TI  - Machine learning for medical image reconstruction :4th International Workshop, MLMIR 2021, held in conjunction with MICCAI 2021, Strasbourg, France, October 1, 2021, Proceedings /
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-88552-6
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-88552-6
ER  -