Title
From image to personalized cardiac simulation: encoding anatomical structures into a model-based segmentation framework
Abstract
Whole organ scale patient specific biophysical simulations contribute to the understanding, diagnosis and treatment of complex diseases such as cardiac arrhythmia. However, many individual steps are required to bridge the gap from an anatomical scan to a personalized biophysical model. In biophysical modeling, differential equations are solved on spatial domains represented by volumetric meshes of high resolution and in model-based segmentation, surface or volume meshes represent the patient's geometry. We simplify the personalization process by representing the simulation mesh and additional relevant structures relative to the segmentation mesh. Using a surface correspondence preserving model-based segmentation algorithm, we facilitate the integration of anatomical information into biophysical models avoiding a complex processing pipeline. In a simulation study, we observe surface correspondence of up to 1.6 mm accuracy for the four heart chambers. We compare isotropic and anisotropic atrial excitation propagation in a personalized simulation.
Year
DOI
Venue
2012
10.1007/978-3-642-36961-2_32
STACOM
Keywords
Field
DocType
personalized biophysical model,segmentation mesh,surface correspondence,anatomical structure,model-based segmentation,simulation mesh,model-based segmentation framework,personalized simulation,biophysical model,specific biophysical simulation,model-based segmentation algorithm,personalized cardiac simulation,biophysical modeling
Differential equation,Computer vision,Polygon mesh,Scale-space segmentation,Segmentation,Computer science,Volume mesh,Artificial intelligence,Anatomical structures,Personalization,Encoding (memory)
Conference
Citations 
PageRank 
References 
1
0.35
15
Authors
6
Name
Order
Citations
PageRank
Hannes Nickisch1146869.23
H Barschdorf2497.69
F M Weber38812.08
Martin W. Krueger49813.35
Olaf Dössel526456.10
Jürgen Weese677492.69