ArticleInternational journal of computer assisted radiology and surgery2018
Laparoscopic training using a quantitative assessment and instructional system.
Article in International journal of computer assisted radiology and surgery, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Automated assessment of simulated laparoscopic surgical skill performance using deep learning.Scientific reports · 2025Article
- Surgical tooltip motion metrics assessment using virtual marker: an objective approach to skill assessment for minimally invasive surgery.International journal of computer assisted radiology and surgery · 2023Article
- A system for real-time multivariate feature combination of endoscopic mitral valve simulator training data.International journal of computer assisted radiology and surgery · 2022Article
- Simulation platforms to assess laparoscopic suturing skills: a scoping review.Surgical endoscopy · 2019Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
purposeLaparoscopic surgery requires complex surgical skills; hence, surgeons require regular training to improve their surgical techniques. The quantitative assessment of a surgeon's skills and the provision of feedback are important processes for conducting effective training. The aim of this study was to develop an inexpensive training system that provides automatic technique evaluation and feedback.
methodsWe detected the instrument using image processing of commercial web camera images and calculated the motion analysis parameters (MAPs) of the instrument to quantify performance features. Upon receiving the results, we developed a method of evaluating the surgeon's skill level. The feedback system was developed using MAPs-based radar charts and scores for determining the skill level. These methods were evaluated using the videos of 38 surgeons performing a suturing task.
resultsThere were significant differences in MAPs among surgeons; therefore, MAPs can be effectively used to quantify a surgeon's performance features. The results of skill evaluation and feedback differed greatly between skilled and unskilled surgeons, and it was possible to indicate points of improvement for the procedure performed in this study. Furthermore, the results obtained for certain novice surgeons were similar to those obtained for skilled surgeons.
conclusionThis system can be used to assess the skill level of surgeons, independent of the years of experience, and provide an understanding of the individual's current surgical skill level effectively. We conclude that our system is useful as an inexpensive laparoscopic training system that might aid in skill improvement.
Indexed as
Identifiers
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.