PhD Defense of Arthur Derathé on 06/04/20

PhD Defense of Arthur Derathé from TIMC GMCAO team on June, the 4th at 2:00 pm:

« Modelling the quality of surgical gestures in laparoscopy »

 

Place/Webcast : the defense will be broadcast at https://youtu.be/Brl3yJuhMr8.


Thesis supervision:

  • Sandrine VOROS, Chargée de Recherche, laboratoire TIMC UMR 5525, Communauté Université Grenoble Alpes, Director
  • Bernard Gibaud, Chargé de Recherche, UMR LTSI Inserm 1099, Co-director
  • Pierre Jannin, Directeur de Recherche, UMR LTSI U1099 INSERM, Co-director
  • Alexandre Moreau-Gaudry, Professeur des Universités - Praticien Hospitalier, laboratoire TIMC UMR 5525, Communauté Université Grenoble Alpes, Co-director

Jury:

  • Germain Forestier, Professeur, Université de Haute-Alsace, Reporter
  • Eric Vibert, Professeur des Universités - Praticien Hospitalier, Hôpital Paul Brousse, Reporter
  • Marie-Christine Jaulent, Directrice de Recherche, INSERM U 1142, Examiner
  • Jean-Luc Faucheron, Professeur des Universités - Praticien Hospitalier, CHU Grenoble Alpes, Examiner

 


bullet Abstract:
 

In laparoscopy, the surgical treatment improves greatly the patient care and its practice has become very common in clinical routine. However, this practice has its specific difficulties for the surgeon and the surgical training is lengthened for post-graduate students and young surgeons. To ease this training, new tools have emerged to assess and analyze the surgical practice.

In this context, we propose to study the feasibility of a methodology proposing clinically relevant analyses for the surgeon based on an algorithmic approach. To this end, I collected and annotated a dataset, I implemented a training environment to predict a specific aspect of the surgical practice, and I proposed an approach to translate my algorithmic results into a clinically relevant form for the surgeon. Whenever it was possible, we considered a validation for this different methodological steps.

 

 

bullet Keywords:

laparoscopic surgery, surgical practice, video data analysis