TY  - BOOK
AU  - Greenspan,Hayit
AU  - Madabhushi,Anant
AU  - Mousavi,Parvin
AU  - Salcudean,Septimiu
AU  - Duncan,James
AU  - Syeda-Mahmood,Tanveer
AU  - Taylor,Russell
ED  - SpringerLink (Online service)
TI  - Medical Image Computing and Computer Assisted Intervention - MICCAI 2023: 26th International Conference, Vancouver, BC, Canada, October 8-12, 2023, Proceedings, Part VII 
T2  - Lecture Notes in Computer Science,
SN  - 9783031439902
AV  - TA1501-1820 
U1  - 006 23
PY  - 2023///
CY  - Cham
PB  - Springer Nature Switzerland, Imprint: Springer
KW  - Image processing
KW  - Digital techniques
KW  - Computer vision
KW  - Application software
KW  - Machine learning
KW  - Education
KW  - Data processing
KW  - Information technology
KW  - Management
KW  - Biomedical engineering
KW  - Computer Imaging, Vision, Pattern Recognition and Graphics
KW  - Computer and Information Systems Applications
KW  - Machine Learning
KW  - Computers and Education
KW  - Computer Application in Administrative Data Processing
KW  - Biomedical Engineering and Bioengineering
N1  - Acceso multiusuario; Clinical applications - abdomen -- clinical applications - breast -- clinical applications - cardiac -- clinical applications - dermatology -- clinical applications - fetal imaging; clinical applications - lung -- clinical applications - musculoskeletal -- clinical applications - oncology -- clinical applications - ophthalmology -- clinical applications - vascular
N2  - The ten-volume set LNCS 14220, 14221, 14222, 14223, 14224, 14225, 14226, 14227, 14228, and 14229 constitutes the refereed proceedings of the 26th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2023, which was held in Vancouver, Canada, in October 2023. The 730 revised full papers presented were carefully reviewed and selected from a total of 2250 submissions. The papers are organized in the following topical sections: Part I: Machine learning with limited supervision and machine learning - transfer learning; Part II: Machine learning - learning strategies; machine learning - explainability, bias, and uncertainty; Part III: Machine learning - explainability, bias and uncertainty; image segmentation; Part IV: Image segmentation; Part V: Computer-aided diagnosis; Part VI: Computer-aided diagnosis; computational pathology; Part VII: Clinical applications - abdomen; clinical applications - breast; clinical applications - cardiac; clinical applications - dermatology; clinical applications - fetal imaging; clinical applications - lung; clinical applications - musculoskeletal; clinical applications - oncology; clinical applications - ophthalmology; clinical applications - vascular; Part VIII: Clinical applications - neuroimaging; microscopy; Part IX: Image-guided intervention, surgical planning, and data science; Part X: Image reconstruction and image registration
UR  - http://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-43990-2
ER  -