title: Non-linear temporal scaling of surgical processes.
abstract: OBJECTIVE
  Surgery is one of the riskiest and most important medical acts that is performed today. Understanding the ways in which surgeries are similar or different from each other is of major interest. Desires to improve patient outcomes and surgeon training, and to reduce the costs of surgery, all motivate a better understanding of surgical practices. To facilitate this, surgeons have started recording the activities that are performed during surgery. New methods have to be developed to be able to make the most of this extremely rich and complex data. The objective of this work is to enable the simultaneous comparison of a set of surgeries, in order to be able to extract high-level information about surgical practices.
  
  
  METHODS
  We introduce non-linear temporal scaling (NLTS): a method that finds a multiple alignment of a set of surgeries. Experiments are carried out on a set of lumbar disc neurosurgeries. We assess our method both on a highly standardised phase of the surgery (closure) and on the whole surgery.
  
  
  RESULTS
  Experiments show that NLTS makes it possible to consistently derive standards of surgical practice and to understand differences between groups of surgeries. We take the training of surgeons as the common theme for the evaluation of the results and highlight, for example, the main differences between the practices of junior and senior surgeons in the removal of a lumbar disc herniation.
  
  
  CONCLUSIONS
  NLTS is an effective and efficient method to find a multiple alignment of a set of surgeries. NLTS realigns a set of sequences along their intrinsic timeline, which makes it possible to extract standards of surgical practices.
authors.affiliation: MIPS EA 2332, University of Haute-Alsace, Mulhouse, France. Electronic address: germain.forestier@uha.fr.
authors.forename: Germain
authors.initials: G
authors.lastname: Forestier
authors.affiliation: Faculty of Information Technology, Monash University, Melbourne, Australia. Electronic address: francois.petitjean@monash.edu.
authors.forename: François
authors.initials: F
authors.lastname: Petitjean
authors.affiliation: INSERM MediCIS, Unit U1099 LTSI, University of Rennes 1, Rennes, France; Department of Neurosurgery, Pontchaillou University Hospital, Rennes, France. Electronic address: laurent.riffaud@chu-rennes.fr.
authors.forename: Laurent
authors.initials: L
authors.lastname: Riffaud
authors.affiliation: INSERM MediCIS, Unit U1099 LTSI, University of Rennes 1, Rennes, France. Electronic address: pierre.jannin@univ-rennes1.fr.
authors.forename: Pierre
authors.initials: P
authors.lastname: Jannin
mesh_terms: D017711:Nonlinear Dynamics; D013514:Surgical Procedures, Operative
keywords: Dynamic time warping; Surgery; Surgical process modelling; Surgical technical skills; Temporal analysis