Fast numerical scheme for gradient vector flow computation using a multigrid method

X. Han, C. Xu, Jerry Ladd Prince

Research output: Contribution to journalArticle

Abstract

The gradient vector flow (GVF) deformable model was introduced by Xu and Prince as an effective approach to overcome the limited capture range problem of classical deformable models and their inability to progress into boundary concavities. It has found many important applications in the area of medical image processing. The simple iterative method proposed in the original work on GVF, however, is slow to converge. A new multigrid method is proposed for GVF computation on 2D and 3D images. Experimental results show that the new implementation significantly improves the computational speed by at least an order of magnitude, which facilitates the application of GVF deformable models in processing large medical images.

Original languageEnglish (US)
Pages (from-to)48-55
Number of pages8
JournalIET Image Processing
Volume1
Issue number1
DOIs
StatePublished - 2007
Externally publishedYes

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Medical image processing
Iterative methods
Processing

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Software
  • Computer Vision and Pattern Recognition

Cite this

Fast numerical scheme for gradient vector flow computation using a multigrid method. / Han, X.; Xu, C.; Prince, Jerry Ladd.

In: IET Image Processing, Vol. 1, No. 1, 2007, p. 48-55.

Research output: Contribution to journalArticle

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