Paper Title:
Semi-Automatic Liver Segmentation Using Improved GVF Snake Model
  Abstract

Snakes are extensively used in computer vision and Image processing. However, when it comes to the liver segmentation from computed tomography (CT) image, the application of the models is limited because it can not extend to certain boundary indentations of the liver. In order to solve this problem, we developed an improved GVF snake model by adding an external force field which can efficiently attract the initial contour to these depression areas, such as the top of the left lobe of liver. The proposed method includes two steps. Firstly, combined with the threshold method and the morphology operation, our model can acquire the initial contour of the liver. Secondly, we create an imposed external force field through the interaction with the system, and we make the initial contour converge under the influence of both GVF field and imposed external force field to get the accurate contour of the liver. The application of this method on abdominal CT image is demonstrated, both qualitatively and quantitatively.

  Info
Periodical
Advanced Materials Research (Volumes 121-122)
Edited by
Donald C. Wunsch II, Honghua Tan, Dehuai Zeng, Qi Luo
Pages
435-440
DOI
10.4028/www.scientific.net/AMR.121-122.435
Citation
H. Y. Jiang, X. H. Gao, "Semi-Automatic Liver Segmentation Using Improved GVF Snake Model", Advanced Materials Research, Vols. 121-122, pp. 435-440, 2010
Online since
June 2010
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Price
$32.00
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