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Titel:

The Liver Tumor Segmentation Benchmark (LiTS).

Dokumenttyp:
Journal Article
Autor(en):
Bilic, Patrick; Christ, Patrick; Li, Hongwei Bran; Vorontsov, Eugene; Ben-Cohen, Avi; Kaissis, Georgios; Szeskin, Adi; Jacobs, Colin; Mamani, Gabriel Efrain Humpire; Chartrand, Gabriel; Lohöfer, Fabian; Holch, Julian Walter; Sommer, Wieland; Hofmann, Felix; Hostettler, Alexandre; Lev-Cohain, Naama; Drozdzal, Michal; Amitai, Michal Marianne; Vivanti, Refael; Sosna, Jacob; Ezhov, Ivan; Sekuboyina, Anjany; Navarro, Fernando; Kofler, Florian; Paetzold, Johannes C; Shit, Suprosanna; Hu, Xiaobin; Lipk...     »
Abstract:
In this work, we report the set-up and results of the Liver Tumor Segmentation Benchmark (LiTS), which was organized in conjunction with the IEEE International Symposium on Biomedical Imaging (ISBI) 2017 and the International Conferences on Medical Image Computing and Computer-Assisted Intervention (MICCAI) 2017 and 2018. The image dataset is diverse and contains primary and secondary tumors with varied sizes and appearances with various lesion-to-background levels (hyper-/hypo-dense), created i...     »
Zeitschriftentitel:
Med Image Anal
Jahr:
2023
Band / Volume:
84
Volltext / DOI:
doi:10.1016/j.media.2022.102680
PubMed:
http://view.ncbi.nlm.nih.gov/pubmed/36481607
Print-ISSN:
1361-8415
TUM Einrichtung:
591; 595; 608; Institut für Diagnostische und Interventionelle Radiologie (Prof. Makowski); Institut für KI und Informatik in der Medizin (Prof. Rückert); Klinik und Poliklinik für RadioOnkologie und Strahlentherapie (Prof. Combs); Professur für AI for Image-Guided Diagnosis and Therapy (Prof. Wiestler); Professur für Neuroradiologie (Prof. Zimmer)
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