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Abstract
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Article Information:
Evaluation of Level Set Segmentation for Medical Images with Intensity Inhomogeinity
M. Renugadevi, V. Vaithiyanathan, K.R. Sekar and N. Raju
Corresponding Author: M. Renugadevi
Submitted: March 18, 2012
Accepted: April 13, 2012
Published: December 15, 2012 |
Abstract:
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Image segmentation is an important area in the medical image guide surgery. Major advances in the
field of medical imaging provide richer information in clinical applications and support the advancement in the
biomedical knowledge. With the growing research on image segmentation, it has become crucial challenge for
the images with inhomogeneity in intensity. Level set is the most powerful and broadly used segmentation
technique in the medical image processing. This study aims at making a review on the current level set methods
such as Region Scalable Fitting (RSF), Statistical and Variational Multiphase Level Set (SVMLS) and Local
Clustering based Variational Level Set (LCVLS) developed for intensity inhomogeneous medical image
segmentation. Experiments that apply these algorithms to segment the medical images are presented to highlight
the distinct characteristics of each method. Results prove that the LCVLS method is most suitable and accurate
for intensity inhomogeneous medical image segmentation.
Key words: Biomedical imaging, Intensity Inhomogeneity (IIH) , level set method, segmentation, , ,
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Cite this Reference:
M. Renugadevi, V. Vaithiyanathan, K.R. Sekar and N. Raju, . Evaluation of Level Set Segmentation for Medical Images with Intensity Inhomogeinity. Research Journal of Applied Sciences, Engineering and Technology, (24): 5416-5422.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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