Riemannian Mean Curvature Flow

R. San Jose Estepar, S. Haker, C.-F. Westin
ISCV '05
Lecture Notes in Computer Science: ISVC05
Volume 3804, Pages 613-620
December, 2005

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Abstract

In this paper we explicitly derive a level set formulation for mean curvature flow in a Riemannian metric space. This extends the traditional geodesic active contour framework which is based on conformal flows. Curve evolution for image segmentation can be posed as a Riemannian evolution process where the induced metric is related to the local structure tensor. Examples on both synthetic and real data are shown.

Image segmentation by RMCF. (a) Segmentation result, in blue the initial contour and in red the final result. (b) Metric induced by the image.

Reference

San Jose Estepar R, Haker S, Westin CF. Riemannian mean curvature flow. In Lecture Notes in Computer Science: ISVC05, volume 3804 of Lecture Notes in Computer Science. 2005;613-620.

Bibtex entry

@InProceedings{san-joseISVC05,
  author         = {R. {San Jose Estepar} and S. Haker and C.-F. Westin},      
  title          = {Riemannian Mean Curvature Flow},                           
  booktitle      = {Lecture Notes in Computer Science: ISVC05},                
  series         = {Lecture Notes in Computer Science},                        
  pages          = {613--620},                                                 
  year           = {2005},                                                     
  volume         = {3804},                                                     
  month          = {December}
}

Grants

NIH P41-RR13218 (NAC)

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