Literature DB >> 30849261

Machine and deep learning for workflow recognition during surgery.

Nicolas Padoy1.   

Abstract

Recent years have seen tremendous progress in artificial intelligence (AI), such as with the automatic and real-time recognition of objects and activities in videos in the field of computer vision. Due to its increasing digitalization, the operating room (OR) promises to directly benefit from this progress in the form of new assistance tools that can enhance the abilities and performance of surgical teams. Key for such tools is the recognition of the surgical workflow, because efficient assistance by an AI system requires this system to be aware of the surgical context, namely of all activities taking place inside the operating room. We present here how several recent techniques relying on machine and deep learning can be used to analyze the activities taking place during surgery, using videos captured from either endoscopic or ceiling-mounted cameras. We also present two potential clinical applications that we are developing at the University of Strasbourg with our clinical partners.

Keywords:  Activity recognition; RGB-D video; clinician pose estimation; endoscopic video; operating room; surgical control tower; surgical workflow; tool detection

Mesh:

Year:  2019        PMID: 30849261     DOI: 10.1080/13645706.2019.1584116

Source DB:  PubMed          Journal:  Minim Invasive Ther Allied Technol        ISSN: 1364-5706            Impact factor:   2.442


  13 in total

1.  CAI4CAI: The Rise of Contextual Artificial Intelligence in Computer Assisted Interventions.

Authors:  Tom Vercauteren; Mathias Unberath; Nicolas Padoy; Nassir Navab
Journal:  Proc IEEE Inst Electr Electron Eng       Date:  2019-10-23       Impact factor: 10.961

2.  Endoneering: A new perspective for basic research in gastrointestinal endoscopy.

Authors:  Alexander Meining
Journal:  United European Gastroenterol J       Date:  2020-04       Impact factor: 4.623

3.  Multicentric validation of EndoDigest: a computer vision platform for video documentation of the critical view of safety in laparoscopic cholecystectomy.

Authors:  Pietro Mascagni; Deepak Alapatt; Giovanni Guglielmo Laracca; Ludovica Guerriero; Andrea Spota; Claudio Fiorillo; Armine Vardazaryan; Giuseppe Quero; Sergio Alfieri; Ludovica Baldari; Elisa Cassinotti; Luigi Boni; Diego Cuccurullo; Guido Costamagna; Bernard Dallemagne; Nicolas Padoy
Journal:  Surg Endosc       Date:  2022-02-16       Impact factor: 4.584

4.  A Visual Deep Learning Model to Localize Parathyroid-Specific Autofluorescence on Near-Infrared Imaging : Localization of Parathyroid Autofluorescence with Deep Learning.

Authors:  Seyma Nazli Avci; Gizem Isiktas; Eren Berber
Journal:  Ann Surg Oncol       Date:  2022-03-28       Impact factor: 5.344

5.  Biomimetic Incremental Domain Generalization with a Graph Network for Surgical Scene Understanding.

Authors:  Lalithkumar Seenivasan; Mobarakol Islam; Chi-Fai Ng; Chwee Ming Lim; Hongliang Ren
Journal:  Biomimetics (Basel)       Date:  2022-05-28

6.  Artificial intelligence in cardiothoracic surgery.

Authors:  Roger D Dias; Julie A Shah; Marco A Zenati
Journal:  Minerva Cardioangiol       Date:  2020-09-29       Impact factor: 1.347

7.  Computer Vision in the Operating Room: Opportunities and Caveats.

Authors:  Lauren R Kennedy-Metz; Pietro Mascagni; Antonio Torralba; Roger D Dias; Pietro Perona; Julie A Shah; Nicolas Padoy; Marco A Zenati
Journal:  IEEE Trans Med Robot Bionics       Date:  2020-11-24

8.  How to Bring Surgery to the Next Level: Interpretable Skills Assessment in Robotic-Assisted Surgery.

Authors:  Kristen C Brown; Kiran D Bhattacharyya; Sue Kulason; Aneeq Zia; Anthony Jarc
Journal:  Visc Med       Date:  2020-10-28

Review 9.  Surgical data science - from concepts toward clinical translation.

Authors:  Lena Maier-Hein; Matthias Eisenmann; Duygu Sarikaya; Keno März; Toby Collins; Anand Malpani; Johannes Fallert; Hubertus Feussner; Stamatia Giannarou; Pietro Mascagni; Hirenkumar Nakawala; Adrian Park; Carla Pugh; Danail Stoyanov; Swaroop S Vedula; Kevin Cleary; Gabor Fichtinger; Germain Forestier; Bernard Gibaud; Teodor Grantcharov; Makoto Hashizume; Doreen Heckmann-Nötzel; Hannes G Kenngott; Ron Kikinis; Lars Mündermann; Nassir Navab; Sinan Onogur; Tobias Roß; Raphael Sznitman; Russell H Taylor; Minu D Tizabi; Martin Wagner; Gregory D Hager; Thomas Neumuth; Nicolas Padoy; Justin Collins; Ines Gockel; Jan Goedeke; Daniel A Hashimoto; Luc Joyeux; Kyle Lam; Daniel R Leff; Amin Madani; Hani J Marcus; Ozanan Meireles; Alexander Seitel; Dogu Teber; Frank Ückert; Beat P Müller-Stich; Pierre Jannin; Stefanie Speidel
Journal:  Med Image Anal       Date:  2021-11-18       Impact factor: 13.828

Review 10.  The potential and challenges of Health 4.0 to face COVID-19 pandemic: a rapid review.

Authors:  Cecilia-Irene Loeza-Mejía; Eddy Sánchez-DelaCruz; Pilar Pozos-Parra; Luis-Alfonso Landero-Hernández
Journal:  Health Technol (Berl)       Date:  2021-09-28
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