基于形态学运算和模糊聚类的超声图像分割

Haihua Liu, C. Xie, Zhouhui Chen, Yi Lei
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引用次数: 9

摘要

本文提出了一种超声图像分割系统。该系统由局部对比度增强和图像分割两部分组成。提出了一种基于多尺度形态学的无斑点噪声增强图像局部对比度的方法。对多尺度变换提取的图像尺度特征的强度值进行修改,增强局部对比度,抑制噪声。在此基础上,提出了一种新的模糊c均值分割算法(AFCM)。无监督分割算法可以进一步降低结构对超声成像的噪声影响。实验证明了该系统对超声图像分割的有效性。
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Segmentation of ultrasound image based on morphological operation and fuzzy clustering
This paper presents a system for segmentation of ultrasound images. The system consists of two parts: local contrast enhancement and segmentation. The scheme for enhancing local contrast of images without speckle noise emphasis based on multiscale morphology is presented in the system. The intensity values of the scale-specific features of the image extracted using multiscale transformation are modified so as to enhance local contrast and suppress noise. Then, a new algorithm, called an alternative fuzzy c-mean (AFCM), is used for segmentation of ultrasound image. The unsupervised segmentation algorithm can help further to reduce the ultrasound imaging noise effects originating from the structures. We demonstrate effectiveness of the system for ultrasound image segmentation in experiments.
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