
Proceedings Paper
The level set method for medical image segmentation with a new regularizationFormat | Member Price | Non-Member Price |
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Paper Abstract
The local area information level set method is applied to segment the medical images with intensity inhomogeneous and
a new kind of Gaussian kernel regularization method is used to simplify operation, this regularization can not only
ensure the smoothness of the level set function, but also eliminate the requirement of re-initialization. This method which
we call Improved Local Binary Fitting method (ILBF) has a shorter time consuming compared with the LBF method, so
it can be widely used in medical image segmentation with its high efficiency and accuracy.
Paper Details
Date Published: 8 July 2011
PDF: 4 pages
Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80090J (8 July 2011); doi: 10.1117/12.896077
Published in SPIE Proceedings Vol. 8009:
Third International Conference on Digital Image Processing (ICDIP 2011)
Ting Zhang, Editor(s)
PDF: 4 pages
Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80090J (8 July 2011); doi: 10.1117/12.896077
Show Author Affiliations
Wei Zheng, Hebei Univ. (China)
Chunye Sun, Hebei Univ. (China)
Chunye Sun, Hebei Univ. (China)
Fang Wang, Hebei Univ. (China)
Min Li, Hebei Univ. (China)
Min Li, Hebei Univ. (China)
Published in SPIE Proceedings Vol. 8009:
Third International Conference on Digital Image Processing (ICDIP 2011)
Ting Zhang, Editor(s)
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