Automated Performance Metrics for Objective Surgical Skill Assessment in Laparoscopic Training

Asaf Arad, Julia Leyva I. Torres, Kristian Nyborg Jespersen, Nicolaj Boelt Pedersen, Pablo Rey Valiente, Alaa El-Hussuna, Andreas Møgelmose

2025

Abstract

The assessment of surgical skill is critical in advancing surgical training and enhancing the performance of surgeons. Traditional evaluation methods relying on human observation and checklists are often biased and inefficient, prompting the need for automated and objective systems. This study explores the use of Automated Performance Metrics (APMs) in laparoscopic surgeries, using video-based data and advanced object tracking techniques. A pipeline was developed, combining a fine-tuned YOLO11 model for detection with state-of-the-art multi-object trackers (MOTs) for tracking surgical tools. Metrics such as path length, velocity, acceleration, jerk, and working area were calculated to assess technical performance. BoT-SORT emerged as the most effective tracker, achieving the highest HOTA and MOTA, enabling robust tool tracking. The system successfully extracted APMs to evaluate and compare surgical performance, demonstrating its potential for objective assessment. This work validates state-of-the-art algorithms for surgical video analysis, contributing to improved surgical training and performance evaluation. Future efforts should address limitations like pixel-based measurements and dataset variability to enhance the system’s accuracy and applicability, ultimately advancing patient safety and reducing training costs.

Paper Citation

in Harvard Style

Arad A., Leyva I. Torres J., Jespersen K., Pedersen N., Valiente P., El-Hussuna A. and Møgelmose A. (2025). Automated Performance Metrics for Objective Surgical Skill Assessment in Laparoscopic Training. In Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP; ISBN 978-989-758-728-3, SciTePress, pages 824-830. DOI: 10.5220/0013380300003912

in Bibtex Style

@conference{visapp25,
author={Asaf Arad and Julia Leyva I. Torres and Kristian Jespersen and Nicolaj Pedersen and Pablo Valiente and Alaa El-Hussuna and Andreas Møgelmose},
title={Automated Performance Metrics for Objective Surgical Skill Assessment in Laparoscopic Training},
booktitle={Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP},
year={2025},
pages={824-830},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013380300003912},
isbn={978-989-758-728-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 20th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 3: VISAPP
TI - Automated Performance Metrics for Objective Surgical Skill Assessment in Laparoscopic Training
SN - 978-989-758-728-3
AU - Arad A.
AU - Leyva I. Torres J.
AU - Jespersen K.
AU - Pedersen N.
AU - Valiente P.
AU - El-Hussuna A.
AU - Møgelmose A.
PY - 2025
SP - 824
EP - 830
DO - 10.5220/0013380300003912
PB - SciTePress