Real-time in silico experiments on gene regulatory networks and surgery simulation on handheld devices

Iciar Alfaro (1) , David Gonzalez (1) , Felipe Bordeu (2) , Adrien Leygue (2) , Amine Ammar (3) , Elías Cueto (2, 1) , Francisco Chinesta (2, 4)

1 I3A - Aragón Institute of Engineering Research [Zaragoza]
2 GeM - Institut de Recherche en Génie Civil et Mécanique
3 LAMPA - Laboratoire Angevin de Mécanique, Procédés et InnovAtion
4 IUF - Institut universitaire de France

Simulation of all phenomena taking place in a surgical procedure is a formidable task that involves, when possible, the use of supercomputing facilities over long time periods. However, decision taking in the operating room needs for fast methods that provide an accurate response in real time. To this end, Model Order Reduction (MOR) techniques have emerged recently in the field of Computational Surgery to help alleviate this burden. In this paper, we review the basics of classical MOR and explain how a technique recently developed by the authors and coined as Proper Generalized Decomposition could make real-time feedback available with the use of simple devices like smartphones or tablets. Examples are given on the performance of the technique for problems at different scales of the surgical procedure, form gene regulatory networks to macroscopic soft tissue deformation and cutting.

Mots clés: Model Order Reduction; Gene regulatory networks; Surgery simulation

Domaines: Ingénierie biomédicale

Iciar Alfaro, David Gonzalez, Felipe Bordeu, Adrien Leygue, Amine Ammar, et al.. Real-time in silico experiments on gene regulatory networks and surgery simulation on handheld devices. Journal of Computational Surgery, 2014, 1 (1), pp.1-14. ⟨10.1186/2194-3990-1-1⟩. ⟨hal-01206921⟩