Literature DB >> 22012086

Surgical vision.

Danail Stoyanov1.   

Abstract

The emergence of Minimal Access Surgery (MAS) as a paradigm in modern healthcare treatment has created new challenges and opportunities for automated image understanding and computer vision. In MAS, images recovered from inside the body using specialized devices are used to visualize and operate on the surgical site but they can also be used to computationally infer in vivo 3D tissue surface shape, soft-tissue morphology, and surgical instrument motion. This information is important for facilitating in vivo biophotonic imaging modalities where the interaction between light and tissue is used to infer the structural and functional properties of the tissue. This article provides a review of the literature for computer vision and image understanding techniques applied to MAS images. The focus of this article is to elucidate a perspective on how computer vision techniques can be used to support and enhance the capabilities of biophotonic imaging modalities during surgery. Note that while MAS encompasses a variety of surgical specializations this review does not involve procedures performed in the interventional suite. The review has been carried out based on searches in the PubMed and IEEE databases using the article's keywords.

Mesh:

Year:  2011        PMID: 22012086     DOI: 10.1007/s10439-011-0441-z

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  14 in total

1.  Dense soft tissue 3D reconstruction refined with super-pixel segmentation for robotic abdominal surgery.

Authors:  Veronica Penza; Jesús Ortiz; Leonardo S Mattos; Antonello Forgione; Elena De Momi
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-09-26       Impact factor: 2.924

2.  Computer-assisted 3D bowel length measurement for quantitative laparoscopy.

Authors:  Martin Wagner; Benjamin Friedrich Berthold Mayer; Sebastian Bodenstedt; Katherine Stemmer; Arash Fereydooni; Stefanie Speidel; Rüdiger Dillmann; Felix Nickel; Lars Fischer; Hannes Götz Kenngott
Journal:  Surg Endosc       Date:  2018-03-05       Impact factor: 4.584

3.  Automated instrument-tracking for 4D video-rate imaging of ophthalmic surgical maneuvers.

Authors:  Eric M Tang; Mohamed T El-Haddad; Shriji N Patel; Yuankai K Tao
Journal:  Biomed Opt Express       Date:  2022-02-15       Impact factor: 3.732

4.  Computer vision distance measurement from endoscopic sequences: prospective evaluation in laparoscopic ventral hernia repair.

Authors:  Ernesto Bernal; Santiago Casado; Óscar G Grasa; J M M Montiel; Ismael Gil
Journal:  Surg Endosc       Date:  2014-06-25       Impact factor: 4.584

5.  Robust surface tracking combining features, intensity and illumination compensation.

Authors:  Xiaofei Du; Neil Clancy; Shobhit Arya; George B Hanna; John Kelly; Daniel S Elson; Danail Stoyanov
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-06-24       Impact factor: 2.924

Review 6.  Computer Vision in the Surgical Operating Room.

Authors:  François Chadebecq; Francisco Vasconcelos; Evangelos Mazomenos; Danail Stoyanov
Journal:  Visc Med       Date:  2020-10-15

7.  Image-guided Raman spectroscopy probe-tracking for tumor margin delineation.

Authors:  Conor C Horgan; Mads S Bergholt; May Zaw Thin; Anika Nagelkerke; Robert Kennedy; Tammy L Kalber; Daniel J Stuckey; Molly M Stevens
Journal:  J Biomed Opt       Date:  2021-03       Impact factor: 3.170

8.  Combined 2D and 3D tracking of surgical instruments for minimally invasive and robotic-assisted surgery.

Authors:  Xiaofei Du; Maximilian Allan; Alessio Dore; Sebastien Ourselin; David Hawkes; John D Kelly; Danail Stoyanov
Journal:  Int J Comput Assist Radiol Surg       Date:  2016-04-02       Impact factor: 2.924

9.  Variational based smoke removal in laparoscopic images.

Authors:  Congcong Wang; Faouzi Alaya Cheikh; Mounir Kaaniche; Azeddine Beghdadi; Ole Jacob Elle
Journal:  Biomed Eng Online       Date:  2018-10-19       Impact factor: 2.819

10.  Comparison of manual and semi-automatic registration in augmented reality image-guided liver surgery: a clinical feasibility study.

Authors:  C Schneider; S Thompson; J Totz; Y Song; M Allam; M H Sodergren; A E Desjardins; D Barratt; S Ourselin; K Gurusamy; D Stoyanov; M J Clarkson; D J Hawkes; B R Davidson
Journal:  Surg Endosc       Date:  2020-08-11       Impact factor: 4.584

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.