TY  - BOOK
AU  - Baid,Ujjwal
AU  - Dorent,Reuben
AU  - Malec,Sylwia
AU  - Pytlarz,Monika
AU  - Su,Ruisheng
AU  - Wijethilake,Navodini
AU  - Bakas,Spyridon
AU  - Crimi,Alessandro
ED  - SpringerLink (Online service)
TI  - Brain Tumor Segmentation, and Cross-Modality Domain Adaptation for Medical Image Segmentation: MICCAI Challenges, BraTS 2023 and CrossMoDA 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12 and 8, 2024, Proceedings 
T2  - Lecture Notes in Computer Science,
SN  - 9783031761638
AV  - TA1634 
U1  - 006.37 23
PY  - 2024///
CY  - Cham
PB  - Springer Nature Switzerland, Imprint: Springer
KW  - Computer vision
KW  - Medical informatics
KW  - Social sciences
KW  - Data processing
KW  - Application software
KW  - Education
KW  - Artificial intelligence
KW  - Computer Vision
KW  - Health Informatics
KW  - Computer Application in Social and Behavioral Sciences
KW  - Computer and Information Systems Applications
KW  - Computers and Education
KW  - Artificial Intelligence
N2  - This book constitutes the refereed proceedings of the Brain Tumor Segmentation Challenge, BraTS 2023, as well as the Cross-Modality Domain Adaptation Challenge, CrossMoDA 2023. These events were held in conjunction with the Medical Image Computing for Computer Assisted Intervention Conference, MICCAI 2023, during October 8-12, 2023. The 37 full papers presented in this volume were selected form 23 submissions. They describe the research of computational scientists and clinical researchers working on brain lesions, and specifically glioma, multiple sclerosis, cerebral stroke, traumatic brain injuries, vestibular schwannoma, and white matter hyper-intensities of presumed vascular origin
UR  - http://libcon.rec.uabc.mx:2048/login?url=https://doi.org/10.1007/978-3-031-76163-8
ER  -