- University of Rennes 1
Tuesday, July 9, 2019
Surgery is a complex professional activity where scientific innovations have the potential to bring support at various levels for better efficacy and efficiency. Whereas in the last decades surgery was rather considered as an art or a craft with knowledge transferred from masters to learners and technics learned by practicing on patients, it is now considered as a professional activity where rigor, deep analysis and holistic understanding for optimization are required. Recently the practitioner benefited from a high number of data and information to help decision and action. However, the move from data to information and information to knowledge is still individual specific with limited integration and automation.
Surgical data science, like any applicative filed of biomedical data science, aims to provide methods and systems for facilitating knowledge generation and usage. Despite classical biomedical data science, surgery involves human operators and teams whose impact is crucial on the outcome. Human activities and corresponding processes are important aspects of surgical data to be processed and understood. In this presentation, I will introduce the surgical data science approaches we studied, implemented and validated in different applicative contexts. The first application will be related to Deep Brain Stimulation for motor related brain diseases. I will show how surgical data science helps assisting surgical planning, performance and post-operative programming and evaluation to improve outcome and reduce side effects. The second area I will briefly introduce is about procedural knowledge modeling by studying surgical processes with applications on surgical skills analysis and surgical training.
Pierre Jannin is a INSERM Research Director at the Medical School of the University of Rennes (France). He is the head of the MediCIS research group from both UMR 1099 LTSI, Inserm research institute and University of Rennes. He was awarded the PhD degree from the University of Rennes in 1988 on multimodal 3D imaging in neurosurgery and the “Habilitation” (HDR) from the University of Rennes in 2005 on information and knowledge assisted neurosurgery. He has more than 30 year experience in designing and developing computer assisted surgery systems. His research topics include surgical data science, surgical robotics, image-guided surgery, augmented and virtual reality, modeling of surgical procedures and processes, study of surgical expertize, surgical training and validation methodology in medical image processing. He authored or co authored more than 90 peer-reviewed international journal papers. He was the President of the International Society of Computer Aided Surgery (ISCAS) from 2014 to 2018 and the General Secretary from 2004 to 2014. He was board member of the MICCAI society from 2014 to 2018. He is an elected MICCAI Fellow since 2018. He is senior member of the SPIE society. He is Deputy Editor for the International Journal of Computer Assisted Radiology and Surgery. He is acted as associate editor and reviewer for several journals (e.g., IEEE TMI, MedIA, IJCARS, Neuroimage, Yearbook of Medical Informatics). He is member of several Organizing and Program Committees of international conferences, such as MICCAI, CARS, SPIE Medical Imaging, and MMVR. He was President of CARS 2019 conference and Program Co-Chair of MICCAI 2017. He is co-founder of IPCAI conferences and was Co-General Chair from 2010 to 2016.
Contact Person: P. Fiorini
- Programme Director
- Publication date
July 4, 2019