Browsing by Author "Saldanha, Oliver L"

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  • ItemOpen Access
    FedSurg EndoVis 2024: Challenge Subset of Appendix300
    (Technische Universität Dresden, 2026-08-27) Kirchner, Max; Kolbinger, Fiona R; Jenke, Alexander C; Saldanha, Oliver L; Pfeiffer, Kevin; Kanjo, Weam; Kather, Jakob N.; Bodenstedt, Sebastian; Speidel, Stefanie
    This deposit contains the supplementary data for the FedSurg EndoVis 2024 Challenge, the first federated learning challenge in Surgical Data Science, held at MICCAI 2024. The challenge used a preliminary subset of the Appendix300 dataset, a multi-institutional collection of laparoscopic appendectomy recordings from German university and community hospitals, annotated with intraoperative appendicitis severity grades 0 to 5 following Gomes et al. The challenge cohort comprises 223 recordings across four centers, split into 153 training and 70 test cases. The deposit includes a CSV file specifying which Appendix300 samples were used in the challenge and their assignment to centers and to the training and test splits, together with two recordings that were used in the challenge but excluded from the final Appendix300 dataset because the available footage was shorter than the nominal 100 second window or the appendix was not clearly visible at the annotated timestamp. This deposit does not contain the appendectomy video recordings themselves, with the exception of the two excluded cases named above. The video data and accompanying clinical metadata are available separately as the Appendix300 dataset at https://doi.org/10.25532/OPARA-1173. The challenge evaluation and ranking code is available at https://gitlab.com/nct_tso_public/challenges/miccai2024/snippet, and the example federated learning setup at https://gitlab.com/nct_tso_public/challenges/miccai2024/FedSurg24. Use of this material requires citation of both the FedSurg challenge paper and the Appendix300 data descriptor. Released under CC BY.