Literature DB >> 32986548

Augmented Reality Guided Laparoscopic Surgery of the Uterus.

T Collins, D Pizarro, S Gasparini, N Bourdel, P Chauvet, M Canis, L Calvet, A Bartoli.   

Abstract

A major research area in Computer Assisted Intervention (CAI) is to aid laparoscopic surgery teams with Augmented Reality (AR) guidance. This involves registering data from other modalities such as MR and fusing it with the laparoscopic video in real-time, to reveal the location of hidden critical structures. We present the first system for AR guided laparoscopic surgery of the uterus. This works with pre-operative MR or CT data and monocular laparoscopes, without requiring any additional interventional hardware such as optical trackers. We present novel and robust solutions to two main sub-problems: the initial registration, which is solved using a short exploratory video, and update registration, which is solved with real-time tracking-by-detection. These problems are challenging for the uterus because it is a weakly-textured, highly mobile organ that moves independently of surrounding structures. In the broader context, our system is the first that has successfully performed markerless real-time registration and AR of a mobile human organ with monocular laparoscopes in the OR.

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Mesh:

Year:  2020        PMID: 32986548     DOI: 10.1109/TMI.2020.3027442

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  3 in total

Review 1.  The Advances in Computer Vision That Are Enabling More Autonomous Actions in Surgery: A Systematic Review of the Literature.

Authors:  Andrew A Gumbs; Vincent Grasso; Nicolas Bourdel; Roland Croner; Gaya Spolverato; Isabella Frigerio; Alfredo Illanes; Mohammad Abu Hilal; Adrian Park; Eyad Elyan
Journal:  Sensors (Basel)       Date:  2022-06-29       Impact factor: 3.847

2.  Tracking better, tracking longer: automatic keyframe selection in model-based laparoscopic augmented reality.

Authors:  Kilian Chandelon; Adrien Bartoli
Journal:  Int J Comput Assist Radiol Surg       Date:  2022-05-09       Impact factor: 3.421

3.  Comparison of image registration methods for combining laparoscopic video and spectral image data.

Authors:  Hannes Köhler; Annekatrin Pfahl; Yusef Moulla; Madeleine T Thomaßen; Marianne Maktabi; Ines Gockel; Thomas Neumuth; Andreas Melzer; Claire Chalopin
Journal:  Sci Rep       Date:  2022-09-30       Impact factor: 4.996

  3 in total

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