TY  - GEN
AB  - This book constitutes the proceedings of the 12th International Workshop on Machine Learning in Medical Imaging, MLMI 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in September 2021.* The 71 papers presented in this volume were carefully reviewed and selected from 92 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc. *The workshop was held virtually.
AU  - Lian, Chunfeng,
AU  - Cao, Xiaohuan,
AU  - Rekik, Islem,
AU  - Xu, Xuanang,
AU  - Yan, Pingkun,
CN  - RC78.7.D53
DO  - 10.1007/978-3-030-87589-3
DO  - doi
ID  - 1439987
KW  - Machine learning
KW  - Diagnostic imaging
KW  - Artificial intelligence
KW  - Apprentissage automatique
KW  - Imagerie pour le diagnostic
KW  - Intelligence artificielle en médecine
LK  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-87589-3
N1  - International conference proceedings.
N1  - Includes author index.
N2  - This book constitutes the proceedings of the 12th International Workshop on Machine Learning in Medical Imaging, MLMI 2021, held in conjunction with MICCAI 2021, in Strasbourg, France, in September 2021.* The 71 papers presented in this volume were carefully reviewed and selected from 92 submissions. They focus on major trends and challenges in the above-mentioned area, aiming to identify new-cutting-edge techniques and their uses in medical imaging. Topics dealt with are: deep learning, generative adversarial learning, ensemble learning, sparse learning, multi-task learning, multi-view learning, manifold learning, and reinforcement learning, with their applications to medical image analysis, computer-aided detection and diagnosis, multi-modality fusion, image reconstruction, image retrieval, cellular image analysis, molecular imaging, digital pathology, etc. *The workshop was held virtually.
SN  - 9783030875893
SN  - 303087589X
T1  - Machine learning in medical imaging :12th International Workshop, MLMI 2021 : held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /
TI  - Machine learning in medical imaging :12th International Workshop, MLMI 2021 : held in conjunction with MICCAI 2021, Strasbourg, France, September 27, 2021 : proceedings /
UR  - https://univsouthin.idm.oclc.org/login?url=https://link.springer.com/10.1007/978-3-030-87589-3
VL  - 12966
ER  -