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Reseach Article

Kidney Segmentation from Ultrasound Images using Gradient Vector Force

Published on None 2010 by Arpana M. Kop, Ravindra Hegadi
Recent Trends in Image Processing and Pattern Recognition
Foundation of Computer Science USA
RTIPPR - Number 2
None 2010
Authors: Arpana M. Kop, Ravindra Hegadi
320bd86d-d566-49ea-b3a6-b7d441c51114

Arpana M. Kop, Ravindra Hegadi . Kidney Segmentation from Ultrasound Images using Gradient Vector Force. Recent Trends in Image Processing and Pattern Recognition. RTIPPR, 2 (None 2010), 104-109.

@article{
author = { Arpana M. Kop, Ravindra Hegadi },
title = { Kidney Segmentation from Ultrasound Images using Gradient Vector Force },
journal = { Recent Trends in Image Processing and Pattern Recognition },
issue_date = { None 2010 },
volume = { RTIPPR },
number = { 2 },
month = { None },
year = { 2010 },
issn = 0975-8887,
pages = { 104-109 },
numpages = 6,
url = { /specialissues/rtippr/number2/983-106/ },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Special Issue Article
%1 Recent Trends in Image Processing and Pattern Recognition
%A Arpana M. Kop
%A Ravindra Hegadi
%T Kidney Segmentation from Ultrasound Images using Gradient Vector Force
%J Recent Trends in Image Processing and Pattern Recognition
%@ 0975-8887
%V RTIPPR
%N 2
%P 104-109
%D 2010
%I International Journal of Computer Applications
Abstract

Ultrasonography is said to be the safest technique in medical imaging and is hence used extensively. But the images are noisy with speckle, acoustic noise and other artifacts. The classical segmentation methods fail completely or require post processing step to remove invalid object boundaries in the segmentation results. Problems associated with traditional mode, initialization and poor convergence to concave boundaries of the snakes, however, have limited their utility. A new external force for active contours largely solves both problems. This external force, call gradient vector flow (GVF), is computed as a diffusion of the gradient vectors of a gray-level or binary edge map derived from the image. The resultant field has a large capture range and forces active contours into concave regions. The intensity images are input to the method and a GVF snake is initialized. The snake deforms and finally reveals the contour of the kidney. The proposed method has successfully segmented the kidney part from the ultrasound images.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Deformable models medical image segmentation active contours level sets GVF