{"paper":{"title":"SurgT challenge: Benchmark of Soft-Tissue Trackers for Robotic Surgery","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.RO","eess.IV"],"primary_cat":"cs.CV","authors_text":"Alistair Weld, Bizhe Bai, Bruno Silva, Estevao Lima, Francisco Vasconcelos, Gwang Lee, Haozheng Xu, Hiroki Matsuzaki, Joao Cartucho, Joao L. Vilaca, Jonas Hajek, Kwang-Ju Kim, Lars Boecking, Leopold Muller, Lueder Kahrs, Minjun Kwon, Samyakh Tukra, Sandro Queiros, Simeon Allmendinger, Sophia Bano, Stamatia Giannarou, Taiyo Ishikawa, Wolfgang Reiter, Yitong Zhang, Yong Eun Jang, Yueming Jin","submitted_at":"2023-02-06T18:57:30Z","abstract_excerpt":"This paper introduces the ``SurgT: Surgical Tracking\" challenge which was organised in conjunction with MICCAI 2022. There were two purposes for the creation of this challenge: (1) the establishment of the first standardised benchmark for the research community to assess soft-tissue trackers; and (2) to encourage the development of unsupervised deep learning methods, given the lack of annotated data in surgery. A dataset of 157 stereo endoscopic videos from 20 clinical cases, along with stereo camera calibration parameters, have been provided. Participants were assigned the task of developing "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2302.03022","kind":"arxiv","version":3},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2302.03022/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}