Upcoming Seminars

Research Director, INSERM, Faculté de Médecine, Université de Rennes, France
Surgical Data Science for Decision Making Support and Knowledge Discovery in Deep Brain Stimulation
Friday, August 11, 2017 - 12:00
Fisher Conference Room, 2nd Floor, Robarts Research Institute


High frequency and continuous electrical stimulation of deep brain structures (DBS) has been demonstrated as an efficient, minimally invasive surgical treatment for motor related diseases and recently for severe neuropsychological diseases. The clinical improvement, and the occurrence of motor, neuropsychological or psychiatric side effects strongly depend on the location of the electrodes. However, despite excellent clinical results, there is no consensus in the neurosurgical community about the optimal location of the area to be stimulated, or the corresponding electrical parameters. The choice of the best target is usually based on a combination of patient specific and generic anatomical, functional and clinical information and knowledge. Patient specific data and information are based on multimodal medical images, clinical and electrophysiological data, whereas most of the generic information and knowledge are implicit, except some few digital anatomical atlases.

This talk will introduce the surgical data science approach we studied, implemented and validated in the context of Deep Brain Stimulation. The main characteristics of our approach include: 1) computation of pre, intra and post-operative patient-specific models from multimodal medical images, clinical and electrophysiological data, 2) analysis of patient population for outlining common patterns and outcome, and 3) computation of generic models from population analysis to help pre, intra and post operative decisions and actions. Our approach is based on numeric and symbolic surgical data analysis, aimed both at assisting surgical planning, performance and post-operative programming and evaluation to improve outcome and reduce side effects, as well as at better understanding neurological phenomenon for knowledge discovery.


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 30-years experience in designing and developing computer assisted surgery systems. His research topics include image-guided surgery, multimodal imaging data fusion, surgical data science, augmented reality, modeling of surgical procedures and processes, study of surgical expertize, surgical training and validation methodology in medical image processing. The main clinical application areas include functional neurosurgery and surgery of low-grade tumours in central areas. He is the President of the International Society of Computer Aided Surgery (ISCAS), Board Member of the MICCAI Society, and a senior member of the SPIE society. He also is Deputy Editor for the International Journal of Computer Assisted Radiology and Surgery. He has been Associate Editor and reviewer for several journals (IEEE TMI, MedIA, IJCARS, Neuroimage, and Yearbook of Medical Informatics). He is a member of several Organizing and Program Committees of international conferences, such as MICCAI, CARS, SPIE Medical Imaging, and MMVR. He is  co-founder of IPCAI conferences, serving as Co-General Chair from 2010 to 2016.