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Surgical Data Science Workshop 2016

WORKSHOP GOALS​

To bring together leading experts from the field in order to identify, present and discuss key initiatives, potential standards, new results, and challenges in the context of surgical data modeling.

IMPORTANT DATES​

MilestoneDate
Submission deadlineMarch 5th, 2016
Registration deadlineJune 5th, 2016
Brainstorming workshopin conjunction with CARS 2016, June 20th, 2016

TOPICS OF INTEREST​

  • Surgical decision support
  • Context awareness in surgery
  • Surgical workflow optimization
  • Surgical training
  • Surgical quality analysis
  • Surgical skill assessment
  • Surgical data mining
  • Surgical ontologies
  • Recognition of surgical actions and events

OVERVIEW​

Surgical data science1 is an emerging scientific discipline with the objective of improving the safety, quality, effectiveness, and efficiency of surgical care by means of data acquisition, modeling, and analysis. Improvement may come from understanding of processes and strategies, assisting surgeons and controlling devices before, during and after surgery as well as from improvements to training, simulation and assessment. Surgical data science builds on principles and methods from other data-intensive disciplines such as computer science, engineering, information theory, statistics, mathematics, and epidemiology, and complements other information-enabled technologies such as surgical robotics, smart operating rooms, and electronic patient records.

The goal of this workshop was to bring together researchers working on diverse topics in surgical data science in order to discuss existing challenges, potential standards and new research directions in the field. It took place at the German Cancer Research Center (DKFZ) in Heidelberg, Germany.

On the workshop day, keynote lectures by leading experts in the field were complemented by short presentations of accepted workshop papers.

COMMITTEE​

GENERAL CHAIRS​

Lena Maier-Hein

Lena Maier-Hein
German Cancer Research Center (DKFZ)

Stefanie Speidel

Stefanie Speidel
NCT Dresden, Translational Surgical Oncology

Pierre Jannin

Pierre Jannin
University of Rennes 1

Board (17 members)
Bernard Gibaud

Bernard Gibaud
Inserm, University of Rennes 1

Carla Pugh

Carla Pugh
Stanford University

Danail Stoyanov

Danail Stoyanov
University College London

Germain Forestier

Germain Forestier
University of Haute-Alsace

Gregory Hager

Gregory Hager
Johns Hopkins University

Guang-Zhong Yang

Guang-Zhong Yang
Imperial College London

Hannes Kenngott

Hannes Kenngott
Heidelberg University Hospital

Heinz Lemke

Heinz Lemke
Leipzig University

Hubertus Feussner

Hubertus Feussner
Technical University of Munich

Jenny Dankelman

Jenny Dankelman
Delft University of Technology

Makoto Hashizume

Makoto Hashizume
Kyushu University

Nassir Navab

Nassir Navab
Technical University of Munich, Johns Hopkins University

Nicolas Padoy

Nicolas Padoy
University of Strasbourg

Ron Kikinis

Ron Kikinis
Harvard Medical School, University of Bremen, MEVIS Fraunhofer

Russell Taylor

Russell Taylor
Johns Hopkins University

Thomas Neumuth

Thomas Neumuth
Leipzig University

York Sure-Vetter

York Sure-Vetter
Karlsruhe Institute of Technology

Executive staff (3 members)
Carolin Feldmann

Carolin Feldmann
Master Student, DKFZ

Keno März

Keno März
PhD Student, DKFZ

Matthias Eisenmann

Matthias Eisenmann
Scientist, DKFZ

PROGRAM​

Four confirmed keynote speakers who are widely known pioneers in the field of surgical data science provided further insights into the most recent developments. To encourage discussion, the workshop format was inspired by the open space philosophy. Following the main event, a get-together including a buffet and drinks allowed more time for discussion. Registration for the event was free and mandatory.

Venue: The workshop took place in the main building of the German Cancer Research Center (DKFZ, Communication Center, Room K1).

Download program

WHITE PAPER​

The first article resulting from the Surgical Data Science workshop 2016 is published in Nature Biomedical Engineering: https://rdcu.be/K0ng

It provides a consensus definition for Surgical Data Science, identifies associated challenges and opportunities and provides a roadmap for advancing the field.

The article can be cited with the DOI 10.1038/s41551-017-0132-7 as follows:

Lena Maier-Hein, Swaroop S. Vedula, Stefanie Speidel, Nassir Navab, Ron Kikinis, Adrian Park, Matthias Eisenmann, Hubertus Feussner, Germain Forestier, Stamatia Giannarou, Makoto Hashizume, Darko Katic, Hannes Kenngott, Michael Kranzfelder, Anand Malpani, Keno März, Thomas Neumuth, Nicolas Padoy, Carla Pugh, Nicolai Schoch, Danail Stoyanov, Russell Taylor, Martin Wagner, Gregory D. Hager and Pierre Jannin. Surgical data science for next-generation interventions. Nature Biomedical Engineering 1(9), 691 (2017). DOI 10.1038/s41551-017-0132-7

@article{maier-hein2017surgical,
    author = {Maier-Hein, Lena and Vedula, Swaroop S. and Speidel, Stefanie and Navab, Nassir and Kikinis, Ron
                and Park, Adrian and Eisenmann, Matthias and Feussner, Hubertus and Forestier, Germain
                and Giannarou, Stamatia and Hashizume, Makoto and Katic, Darko and Kenngott, Hannes
                and Kranzfelder, Michael and Malpani, Anand and März, Keno and Neumuth, Thomas
                and Padoy, Nicolas and Pugh, Carla and Schoch, Nicolai and Stoyanov, Danail
                and Taylor, Russell and Wagner, Martin and Hager, Gregory D. and Jannin, Pierre},
    year = {2017},
    title = {Surgical data science for next-generation interventions},
    journal = {Nature Biomedical Engineering},
    publisher = {Nature Publishing Group},
    issn = {2157-846X},
    doi = {10.1038/s41551-017-0132-7},
    volume = {1},
    month = {9},
    pages = {691},
    number = {9},
    url = {https://doi.org/10.1038/s41551-017-0132-7},
    abstract = {Interventional healthcare will evolve from an artisanal craft based on the individual experiences,
                preferences and traditions of physicians into a discipline that relies on objective decision-making
                on the basis of large-scale data from heterogeneous sources.}
}

PARTNERS​

The workshop was funded by the Collaborative Research Center (SFB/TRR) 125 'Cognition-Guided Surgery' and was endorsed by the International Society for Computer Aided Surgery (ISCAS).

Footnotes​

  1. Acknowledgement: The title ‘surgical data science’ was suggested by Swaroop Vedula (Computational Interaction and Robotics Laboratory (Prof. Hager), Johns Hopkins University) ↩