Datasets › HeiChole Benchmark
HeiChole Benchmark (Surgical Workflow and Skill Analysis Challenge (HeiChole Benchmark))
Analyzing the surgical workflow is a prerequisite for many applications in computer assisted surgery (CAS), such as context-aware visualization of navigation information, specifying the most probable tool required next by the surgeon or determining the remaining duration of surgery. Since laparoscopic surgeries are performed using an endoscopic camera, a video stream is always available during surgery, making it the obvious choice as input sensor data for workflow analysis. Moreover, this offers the opportunity for structured assessment of surgical skill for safety, teaching and quality management.
The sub-challenge “Surgical Workflow and Skill Analysis” focuses on the online workflow analysis of laparoscopic surgeries. Participants are challenged to segment laparoscopic surgeries for gallbladder removal (cholecystectomy) into surgical phases, to recognize instrument presence and surgical actions as well as to classify surgical skill based on video data. Participants are encouraged (but not required!) to submit different results for phase segmentation, action recognition, instrument presence and skill classification . This novel kind of challenge investigates the current state-of-the-art results on surgical workflow analysis and skill assessment on one comprehensive dataset.
Benchmarks archive 2025-07-28
All 2 leaderboards whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Surgical phase recognition | HeiChole Benchmark | MuST F1 77.25 | MuST: Multi-Scale Transformers for Surgical Phase Recognition | BCV-Uniandes/MuST | 5 | Compare |
| Surgical tool detection | HeiChole Benchmark | MoCo V2 Surg SSL - FCN head mAP 66.9 | Dissecting Self-Supervised Learning Methods for Surgical... | camma-public/selfsupsurg | 1 | Compare |
Papers archive 2025-07-28
3 shown of 3 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 4. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| MuST: Multi-Scale Transformers for Surgical Phase Recognition | 1 | 1 | 24 Jul 2024 | not harvested |
| Dissecting Self-Supervised Learning Methods for Surgical Computer Vision | 1 | 2 | 1 Jul 2022 | not harvested |
| Comparative Validation of Machine Learning Algorithms for Surgical Workflow and Skill Analysis with the HeiChole Benchmark | 0 | 3 | 30 Sep 2021 | not harvested |
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
No licence recorded in the archive. Absence here is not a statement about the dataset's terms.
Modalities archive 2025-07-28
No modality tagged.
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- HeiChole Benchmark
1 variant name, as the archive lists them.
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