A comprehensive survey on recent deep learning-based methods applied to surgical data

• URL: http://arxiv.org/abs/2209.01435v1
• Date: Sat, 3 Sep 2022 14:25:39 GMT
• Title: A comprehensive survey on recent deep learning-based methods applied to surgical data
• Authors: Mansoor Ali, Rafael Martinez Garcia Pena, Gilberto Ochoa Ruiz, Sharib Ali
• Abstract summary: Real-time systems can help surgeons to navigate and track tools, by providing clear understanding of scene and avoid miscalculations during operation. Recent machine learning-based approaches including surgical tool localisation, segmentation, tracking and 3D scene perception. We present current gaps and directions of these invented methods and provide rational behind clinical integration of these approaches.
• Score: 2.1506382989223782
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Minimally invasive surgery is highly operator dependant with lengthy procedural times causing fatigue and risk to patients. In order to mitigate these risks, real-time systems can help assist surgeons to navigate and track tools, by providing clear understanding of scene and avoid miscalculations during operation. While several efforts have been made in this direction, a lack of diverse datasets, as well as very dynamic scenes and its variability in each patient entails major hurdle in accomplishing robust systems. In this work, we present a systematic review of recent machine learning-based approaches including surgical tool localisation, segmentation, tracking and 3D scene perception. Furthermore, we present current gaps and directions of these invented methods and provide rational behind clinical integration of these approaches.

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