Medical Endoscopic Image Segmentation Using Snakes

Sung Won YOON  Hai Kwang LEE  Jeong Hoon KIM  Myoung Ho LEE  

IEICE TRANSACTIONS on Information and Systems   Vol.E87-D   No.3   pp.785-789
Publication Date: 2004/03/01
Online ISSN: 
Print ISSN: 0916-8532
Type of Manuscript: LETTER
Category: Image Processing, Image Pattern Recognition
active contour models,  deformable models,  GGF,  GVF,  segmentation,  snakes,  

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Image segmentation is an essential technique of image analysis. In spite of the issues in contour initialization and boundary concavities, active contour models (snakes) are popular and successful methods for segmentation. In this paper, we present a new active contour model, Gaussian Gradient Force snake (GGF snake), for segmentation of an endoscopic image. The GGF snake is less sensitive to contour initialization and it ensures a high accuracy, large capture range, and fast CPU time for computing an external force. It was observed that the GGF snake produced more reasonable results in various image types : simple synthetic images, commercial digital camera images, and endoscopic images, than previous snakes did.