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| Multi-threshhold Ultrasound Image Segmentation Based on Potential Function Clustering |
| Bo Peng, Fuliang Zhang, Xianfeng Yang |
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Abstract Ultrasound image segmentation is an important task for clinical
diagnosis. In this study, a multi-threshhold segmentation approach
was proposed to enhance ultrasound image segmentation accuracy. More
specifically, the proposed multi-threshhold segmentation approach,
combining an opening-closing morphological filter and potential
function clustering theory, attempted to provide better ultrasound
image segmentation visibility. This proposed approach was tested
using computer-simulated images and in $\textit{vivo}$ images.
Computer simulation results demonstrated that the method
significantly improved the accuracy of image segmentation. From in
$\textit{vivo}$ images investigation, we have found that, as compared
with the original images, better segmentation visibility were
obtained. Our initial results demonstrated that this method could be
useful for improving the segmentation quality of ultrasound images
as a post-processing tool.
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| Cite this article: |
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Bo Peng,Fuliang Zhang,Xianfeng Yang. Multi-threshhold Ultrasound Image Segmentation Based on Potential Function Clustering[J]. Journal of Fiber Bioengineering and Informatics, 2015, 8(2): 277-284.
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2015, Vol. 8 
