mlsanityData to 14 Oct 2026

Objective Surgical Skills Assessment and Tool Localization: Results from the MICCAI 2021 SimSurgSkill Challenge

arXiv 2212.04448 ↗First posted 8 Dec 2022cs.CVcited by 6

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Abstract (arXiv)

Timely and effective feedback within surgical training plays a critical role in developing the skills required to perform safe and efficient surgery. Feedback from expert surgeons, while especially valuable in this regard, is challenging to acquire due to their typically busy schedules, and may be subject to biases. Formal assessment procedures like OSATS and GEARS attempt to provide objective measures of skill, but remain time-consuming. With advances in machine learning there is an opportunity for fast and objective automated feedback on technical skills. The SimSurgSkill 2021 challenge (hosted as a sub-challenge of EndoVis at MICCAI 2021) aimed to promote and foster work in this endeavor. Using virtual reality (VR) surgical tasks, competitors were tasked with localizing instruments and predicting surgical skill. Here we summarize the winning approaches and how they performed. Using this publicly available dataset and results as a springboard, future work may enable more efficient training of surgeons with advances in surgical data science. The dataset can be accessed from https://console.cloud.google.com/storage/browser/isi-simsurgskill-2021.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 14 of its 31 references that are in the map. First posted on arXiv 8 Dec 2022.

Builds on

14 of 31 references.

References · 14

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  3. 2021Comparative Validation of Machine Learning Algorithms for Surgical Workflow and Skill Analysis with the HeiChole Benchmarkcited by 60
  4. 2018Tool Detection and Operative Skill Assessment in Surgical Videos Using Region-Based Convolutional Neural Networkscited by 57
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  6. 2019BIAS: Transparent reporting of biomedical image analysis challengescited by 57
  7. 2022CholecTriplet2021: A benchmark challenge for surgical action triplet recognitioncited by 44
  8. 2017Video and Accelerometer-Based Motion Analysis for Automated Surgical Skills Assessmentcited by 28
  9. 2017Automated Surgical Skill Assessment in RMIS Trainingcited by 21
  10. 2018Surgical Activity Recognition in Robot-Assisted Radical Prostatectomy using Deep Learningcited by 18
  11. 2018Deep Learning with Convolutional Neural Network for Objective Skill Evaluation in Robot-assisted Surgerycited by 17
  12. 2021Surgical Visual Domain Adaptation: Results from the MICCAI 2020 SurgVisDom Challengecited by 14
2 more
  1. 2018Surgical Data Science: A Consensus Perspectivecited by 5
  2. 2019Novel evaluation of surgical activity recognition models using task-based efficiency metricscited by 3

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 3; 2026: 2.

6 papers.