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| Liver Image Segmentation Algorithm Based on RBF Confidence Interval |
| Yongxiong Sun, Qiuyang Huang, Yu Zhang, Yinghan Li, Lipeng Liu |
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Abstract For the characteristics of liver images and the shortcomings of the
traditional region growing algorithm, a liver segmentation method
based on RBF-CI (RBF-Confidence Interval) is proposed. On the basis
of the application of window adjusting technology and the
anisotropic diffusion method, the RBF neural network learning
algorithm is introduced to calculate the coefficient of the
confidence interval in order to reduce users' interaction amount and
realize adaptive liver image segmentation. Simulation results show
that, the proposed RBF-CI region growth segmentation algorithm can
achieve effective segmentation results of liver images. For the ten
sets of the liver images, while our proposed segmentation algorithm
result achieves an average accuracy rate of 90.86\%, which indicates
the segmentation is accurate.
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| DOI:10.12733/jics20105532 |
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