A New Model-CELBF for Medical Image Segmentation Based on Image Entropy
A new model (named CELBF) for medical image segmentation based on LBF and image entropy is proposed in this paper. We introduced image entropy to deal with the inhomogeneity of image gray level. Some real medical images are processed by using this new model and finite difference algorithm. The resul...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
EDP Sciences
2017-01-01
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| Series: | ITM Web of Conferences |
| Online Access: | https://doi.org/10.1051/itmconf/20171202001 |
| Summary: | A new model (named CELBF) for medical image segmentation based on LBF and image entropy is proposed in this paper. We introduced image entropy to deal with the inhomogeneity of image gray level. Some real medical images are processed by using this new model and finite difference algorithm. The results show that new model improves the speed of segmentation and increases noise robustness. Compared with LBF model, the new model can segment inhomogeneity medical image more quickly and more accurately. Meanwhile the CELBF model has more strong robustness with noise. |
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| ISSN: | 2271-2097 |