High Performance Computing for Cognition-Guided Cardiac Surgery: Soft Tissue Simulation for Mitral Valve Reconstruction in Knowledge-Based Surgery Assistance

N. Schoch (), S. Engelhardt, R. De Simone, I. Wolf and V. Heuveline ()
Additional contact information
N. Schoch: Heidelberg University, Engineering Mathematics and Computing Lab (EMCL)
S. Engelhardt: German Cancer Research Center, Medical and Biological Informatics
R. De Simone: University Hospital of Heidelberg, Department of Cardiac Surgery
I. Wolf: German Cancer Research Center, Medical and Biological Informatics
V. Heuveline: Heidelberg University, Engineering Mathematics and Computing Lab (EMCL)

A chapter in Modeling, Simulation and Optimization of Complex Processes HPSC 2015, 2017, pp 205-221 from Springer

Abstract: Abstract Medical simulations play an increasingly important role in today’s clinical and surgical treatment processes. The scope of this work is the support of the surgical operation of a mitral valve reconstruction (MVR) by means of biomechanical simulations. Based on numerical simulation, the natural anatomical setting, the ring implantation and the valve closure are modelled and efficiently computed in order to provide surgeons during the operation with additional morphological and functional information. Our simulation is based on the Finite Element Method (FEM) and implemented using the open-source C++ FEM software HiFlow3. Integrating patient data and surgical expert knowledge, and making efficient use of High-Performance Computing (HPC) methods allows for obtaining valuable simulation results for surgery assistance in adequate times. In this work, we focus on the intelligent setup of the biomechanical model and the flexible interfaces of the HPC-based implementation of the resulting MVR simulation, thereby aiming at a cognition-guided, patient-specific integration into systems for surgery assistance.

Date: 2017
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-319-67168-0_17

Ordering information: This item can be ordered from
http://www.springer.com/9783319671680

DOI: 10.1007/978-3-319-67168-0_17

Access Statistics for this chapter

More chapters in Springer Books from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().