SUGAR - Surgical sUturing GrAdeR
Year: 2025
Type: dissertation
Abstract: The work performed in this Master’s Thesis aims to deliver a Proof-of-Concept for an objective, reproducible, and cost-effective method to evaluate surgical suturingskills, using a robust combination of traditional and advanced Computer Vision (CV) techniques. The Master’s Thesis produces a Proof-of-Concept for a novel CV-based tool capable of delivering objective and cost-effective suture skills assessments, by automaticallyevaluating key suture quality parameters with a precision of 85.68% and a recall factor of 61.75%. This Thesis’s results exhibit a promising potential for the SUGAR system’s use as an educational tool that will allow students to further develop basic suturing proficiency using self-directed learning.
Author: Manso, Laura
Institution: National University of Ireland, Maynooth
Language: English
Subfield: Surgery
Field: Medicine
Domain: Health Sciences
SDG: Quality education
Open Access status: green
OpenAlex ID: W7106524909
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