Level set-based integration of segmentation and computational fluid dynamics for flow correction in phase contrast angiography.

M. Watanabe, R. Kikinis, C.-F. Westin
Academic Radiology
Volume 10, Number 12, Pages 1416-23
2003

Download full paper

Abstract

A novel method to correct flow data from magnetic resonance phase contrast (MR-PC) angiography,based on combining computational fluid dynamics and segmentation in a level set framework, was developed and tested in this study.The MR-PC velocity data was used in a partial differential equation-based level set method for vessel segmentation. The results were supplied as the quantitative description of the vessel wall to the flow field solver using computational fluid dynamics, based on the level set method, to obtain a physically meaningful flow. The most significant characteristic of our novel approach is that it requires light computational loads, especially insofar as it avoids generation of complex computational grid system. The integration of segmentation and computational fluid dynamics in a level set framework is shown to be both robust and economic, and yet yields a physically correct velocity field and optimal vessel geometry.

Maximum intensity projection (MIP) of a clinical MR-PC data set provided to this work. (a) 25625660 brain vessel data. (b) Close up in the vicinity of common carotid, basilar and vertebral arteries. Applications of this method to vessels shown as "A" and "B" are presented.

Reference

Watanabe M, Kikinis R, Westin CF. Level set-based integration of segmentation and computational fluid dynamics for flow correction in phase contrast angiography. Academic Radiology 2003;10(12):1416-23.

Bibtex entry

@Article{watanabeAcademRad03,
  author         = {M. Watanabe and R. Kikinis and C.-F. Westin},              
  title          = {Level set-based integration of segmentation and            
                   computational fluid  dynamics for flow correction in phase  
                   contrast angiography.},                                     
  journal        = {Academic Radiology},                                       
  year           = {2003},                                                     
  volume         = {10},                                                       
  number         = {12},                                                       
  pages          = {1416--23}
}

Grants

NIH P41-RR13218 (NAC), CIMIT

Research area

Vascular