Literature DB >> 23036905

Computer assisted minimally invasive surgery: is medical computer vision the answer to improving laparosurgery?

Adrien Bartoli1, Toby Collins, Nicolas Bourdel, Michel Canis.   

Abstract

Minimally Invasive Surgery (MIS) is one of the most effective methods of modern surgical intervention that has considerable advantages compared with open surgery, including reduced trauma, pain, and post-operative recovery time. MIS has improved substantially over the years, chiefly due to new hardware innovations, including HD cameras and flexible head endoscopes. However, MIS continues to be hindered by several problems. In addition to hardware innovation, Computer Vision (CV) has been proposed as a way to overcome some of its current limitations. However, the research literature lacks a coherent picture of how the limitations can be best overcome by hardware, CV or a combination of the two. In this paper we focus on laparoscopic MIS, and list these limitations into 5 clear categories. We detail the effectiveness of hardware and CV solutions with respect to each limitation, from which we base the following hypothesis: CV is both complementary and necessary to hardware development, to overcome all 5 limitations in laparoscopy. Our paper is of value to laparoscopy surgeons, by conveying what is expected to be achieved in computer-aided laparoscopy over the next decade. It is also of value to medical CV researchers, by clarifying which problems are best solved with CV, in light of the hardware developments likely to occur over the next decade.
Copyright © 2012 Elsevier Ltd. All rights reserved.

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Year:  2012        PMID: 23036905     DOI: 10.1016/j.mehy.2012.09.007

Source DB:  PubMed          Journal:  Med Hypotheses        ISSN: 0306-9877            Impact factor:   1.538


  4 in total

1.  Augmented reality in gynecologic surgery: evaluation of potential benefits for myomectomy in an experimental uterine model.

Authors:  Nicolas Bourdel; Toby Collins; Daniel Pizarro; Adrien Bartoli; David Da Ines; Bruno Perreira; Michel Canis
Journal:  Surg Endosc       Date:  2016-04-29       Impact factor: 4.584

2.  Global rigid registration of CT to video in laparoscopic liver surgery.

Authors:  Maria R Robu; João Ramalhinho; Stephen Thompson; Kurinchi Gurusamy; Brian Davidson; David Hawkes; Danail Stoyanov; Matthew J Clarkson
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-05-07       Impact factor: 2.924

3.  In vivo estimation of target registration errors during augmented reality laparoscopic surgery.

Authors:  Stephen Thompson; Crispin Schneider; Michele Bosi; Kurinchi Gurusamy; Sébastien Ourselin; Brian Davidson; David Hawkes; Matthew J Clarkson
Journal:  Int J Comput Assist Radiol Surg       Date:  2018-04-16       Impact factor: 2.924

4.  A Novel Unsupervised Approach for Minimally-invasive Video Segmentation.

Authors:  Toktam Khatibi; Mohammad Mehdi Sepehri; Pejman Shadpour
Journal:  J Med Signals Sens       Date:  2014-01
  4 in total

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