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Bounded Rayleigh Mixture Model for Ultrasound Image Segmentation

Abstract : The finite mixture model based on the Gaussian distribution is a flexible and powerful tool to address image segmentation. However, in the case of ultrasound images, the intensity distributions are non-symmetric whereas the Gaussian distribution is symmetric. In this study, a new finite bounded Rayleigh distribution is proposed. One advantage of the proposed model is that Rayleigh distribution is non-symmetric which has ability to fit the shape of medical ultrasound data. Another advantage is that each component of the proposed model is suitable for the ultrasound image segmentation. We also apply the bounded Rayleigh mixture model in order to improve the accuracy and to reduce the computational time. Experiments show that the proposed model outperforms the state-of-art methods on time consumption and accuracy.
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https://www.hal.inserm.fr/inserm-01426910
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Submitted on : Thursday, January 5, 2017 - 10:07:14 AM
Last modification on : Wednesday, April 14, 2021 - 6:44:05 PM
Long-term archiving on: : Thursday, April 6, 2017 - 12:20:16 PM

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Hui Bi, Hui Tang, Hua Zhong Shu, Jean-Louis Dillenseger. Bounded Rayleigh Mixture Model for Ultrasound Image Segmentation. 8th International Conference on Graphic and Image Processing, Oct 2016, Tokyo, Japan. ⟨10.1117/12.2266963⟩. ⟨inserm-01426910⟩

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