2025年手术点追踪挑战赛，评测算法在红外手术标记上的追踪精度与效率。
Point Tracking in Surgery--The 2025 Surgical Tattoos in Infrared Challenge (STIRC2025)
- 基于红外手术标记数据集，评估算法在活体与离体序列中的追踪能力。
- 7支团队参与，挑战涵盖追踪精度与推理延迟两项量化指标。
- 结果与代码开源，适合医疗视觉与实时追踪研究者参考。
手术中的点追踪对分割、三维重建、虚拟组织定位、自主探头扫描及子任务自动化等下游应用至关重要。本文介绍了2025年点追踪挑战赛，参赛算法通过名为手术红外标记（Surgical Tattoos in Infrared, STIR）的数据集进行量化评估，该挑战称为STIR挑战2025（STIRC2025）。STIRC2025包含两项定量评估：准确性和效率。准确性测试覆盖活体和离体序列，效率测试评估算法推理延迟。挑战作为MICCAI EndoVis 2025的一部分举行，共有七支团队参与。本文总结了挑战结果与各参赛方法。挑战数据集可于https://zenodo.org/records/20191078获取，基准模型与评估代码见https://github.com/athaddius/STIRMetrics。
原文摘要 · Abstract (English)
Point tracking in surgery is crucial to enable applications in downstream tasks such as segmentation, 3D reconstruction, virtual tissue landmarking, autonomous probe-based scanning, and subtask autonomy. This paper introduces the 2025 iteration of a point tracking challenge to address this, wherein participants submit their algorithms for quantification. Their algorithms are evaluated using a dataset named surgical tattoos in infrared (STIR), with the challenge named the STIR Challenge 2025 (STIRC2025). The STIR Challenge 2025 comprises two quantitative components: accuracy and efficiency. The accuracy component tests the accuracy of algorithms on in vivo and ex vivo sequences. The efficiency component tests algorithm inference latency. The challenge was conducted as a part of MICCAI EndoVis 2025, and seven teams participated in this challenge. In this paper we summarize the challenge results and participant methods. The challenge dataset is available at: https://zenodo.org/records/20191078, and the code for baseline models and metrics calculation is available here: https://github.com/athaddius/STIRMetrics
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