@inproceedings{walsh:hal-04090598,
TITLE = {Expert Variability and Deep Learning Performance in Spinal Cord Lesion Segmentation for Multiple Sclerosis Patients},
AUTHOR = {Walsh, Ricky and Meur{\'e}e, C{\'e}dric and Kerbrat, Anne and Masson, Arthur and Hussein, Burhan Rashid and Gaubert, Malo and Galassi, Francesca and Comb{\'e}s, Benoit},
URL = {https://inria.hal.science/hal-04090598},
NOTE = {Accepted at 2023 IEEE 36th International Symposium on Computer-Based Medical Systems (CBMS).{\copyright} 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other work.},
BOOK
TITLE = {CBMS 2023 - 36th IEEE International Symposium on Computer-Based Medical Systems (CBMS)},
ADDRESS = {L'Aquila, Italy},
PUBLISHER = {IEEE},
PAGES = {1-8},
YEAR = {2023},
MONTH = Jun, DOI = {10.1109/CBMS58004.2023.00263},
KEYWORDS = {Multiple sclerosis ; spinal cord ; magnetic resonance imaging ; lesion segmentation ; inter-rater variability ; intra-rater variability ; deep learning ; automated segmentation ; Multiple sclerosis spinal cord magnetic resonance imaging lesion segmentation inter-rater variability intrarater variability deep learning automated segmentation ; intrarater variability},
PDF = {https://inria.hal.science/hal-04090598/file/IEEE_CBMS_Rater_Variability_Study_hal_2.pdf},
HAL_ID = {hal-04090598},
HAL_VERSION = {v1},
}