DATA CHARACTERISTICS

Important: The dataset is available on Zenodo (https://zenodo.org/records/15740620) and described in the corresponding dataset publication:

• Rueckert, Tobias et al.: Video Dataset for Surgical Phase, Keypoint, and Instrument Recognition in Laparoscopic Surgery (PhaKIR). arXiv preprint, https://arxiv.org/abs/2511.06549. 2025.

The proposed dataset consists of real-world videos of human cholecystectomies ranging from 23 to 60 minutes in duration. The procedures were performed by experienced physicians, and the videos were recorded in three hospitals. In addition to existing datasets, our annotations provide pixel-wise instance segmentation masks of surgical instruments for a total of 19 categories, coordinates of relevant instrument keypoints (instrument tip(s), shaft-tip transition, shaft), both at an interval of one frame per second, and specifications regarding the intervention phases for a total of eight different phase categories for each individual frame in one dataset and thus comprehensively cover instrument localization and the context of the operation. Furthermore, the provision of the complete video sequences offers the opportunity to include the temporal information regarding the respective tasks and thus further optimize the resulting methods and outcomes.

A description regarding the structure of the provided dataset and the annotations as well as the applied labeling instructions can be found in the following document: PhaKIR_Data_Description_and_Labeling_Instructions_v2.pdf

Licensing: The dataset is published under a Creative Commons Attribution-NonCommercial-ShareAlike (CC BY-NC-SA) license, which means that it can be used for non-commercial purposes once the challenge has been conducted and the challenge paper has been published. If you wish to use or reference this dataset, you must cite this challenge paper that will appear after the challenge. The licensing of new creations must use the exact same licensing terms as in the current version of the dataset.