TY  - GEN
N2  - This book constitutes the refereed proceedings of the 8th International Workshop on Machine Learning in Medical Imaging, MLMI 2017, held in conjunction with MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 44 full papers presented in this volume were carefully reviewed and selected from 63 submissions. The main aim of this workshop is to help advance scientific research within the broad field of machine learning in medical imaging. The workshop focuses on major trends and challenges in this area, and presents works aimed to identify new cutting-edge techniques and their use in medical imaging.
DO  - 10.1007/978-3-319-67389-9
DO  - doi
AB  - This book constitutes the refereed proceedings of the 8th International Workshop on Machine Learning in Medical Imaging, MLMI 2017, held in conjunction with MICCAI 2017, in Quebec City, QC, Canada, in September 2017. The 44 full papers presented in this volume were carefully reviewed and selected from 63 submissions. The main aim of this workshop is to help advance scientific research within the broad field of machine learning in medical imaging. The workshop focuses on major trends and challenges in this area, and presents works aimed to identify new cutting-edge techniques and their use in medical imaging.
T1  - Machine learning in medical imaging :8th International Workshop, MLMI 2017, held in conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Proceedings /
AU  - Wang, Qian,
AU  - Shi, Yinghuan,
AU  - Suk, Heung-Il,
AU  - Suzuki, Kenji
VL  - 10541
CN  - RC78.7.D53
N1  - International conference proceedings.
N1  - Includes author index.
ID  - 799838
KW  - Machine learning
KW  - Diagnostic imaging
KW  - Artificial intelligence
SN  - 9783319673899
SN  - 3319673890
TI  - Machine learning in medical imaging :8th International Workshop, MLMI 2017, held in conjunction with MICCAI 2017, Quebec City, QC, Canada, September 10, 2017, Proceedings /
LK  - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-67389-9
UR  - https://univsouthin.idm.oclc.org/login?url=http://link.springer.com/10.1007/978-3-319-67389-9
ER  -