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Titel:

VerSe: A Vertebrae labelling and segmentation benchmark for multi-detector CT images.

Dokumenttyp:
Journal Article; Research Support, Non-U.S. Gov't
Autor(en):
Sekuboyina, Anjany; Husseini, Malek E; Bayat, Amirhossein; Löffler, Maximilian; Liebl, Hans; Li, Hongwei; Tetteh, Giles; Kukačka, Jan; Payer, Christian; Štern, Darko; Urschler, Martin; Chen, Maodong; Cheng, Dalong; Lessmann, Nikolas; Hu, Yujin; Wang, Tianfu; Yang, Dong; Xu, Daguang; Ambellan, Felix; Amiranashvili, Tamaz; Ehlke, Moritz; Lamecker, Hans; Lehnert, Sebastian; Lirio, Marilia; Olaguer, Nicolás Pérez de; Ramm, Heiko; Sahu, Manish; Tack, Alexander; Zachow, Stefan; Jiang, Tao; Ma, Xinjun;...     »
Abstract:
Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit clinical decision support systems for diagnosis, surgery planning, and population-based analysis of spine and bone health. However, designing automated algorithms for spine processing is challenging predominantly due to considerable variations in anatomy and acquisition protocols and due to a severe shortage of publicly...     »
Zeitschriftentitel:
Med Image Anal
Jahr:
2021
Band / Volume:
73
Volltext / DOI:
doi:10.1016/j.media.2021.102166
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/34340104
Print-ISSN:
1361-8415
TUM Einrichtung:
Fachgebiet Neuroradiologie (Prof. Zimmer)
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