基于图像分解的超声图像模糊聚类分割

Yan Xu
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引用次数: 9

摘要

由于散斑噪声的干扰和边界的模糊性,超声图像分割具有挑战性。本文提出了一种基于图像分解的空间信息模糊c均值聚类分割方案。首先,将超声图像分解为u+v两个函数的和,其中u表示图像强度,v表示纹理。然后,对图像强度分量采用空间FCM聚类方法进行分割。在模拟和临床超声图像的实验中,与其他预处理或分割方法相比,该方法可以得到更准确的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Image decomposition based ultrasound image segmentation by using fuzzy clustering
Ultrasound image segmentation is challenging due to the interference from speckle noise and fuzziness of boundaries. In this paper, we propose a segmentation scheme using fuzzy c-means (FCM) clustering incorporating spatial information based on image decomposition. First, an ultrasound image is decomposed into a sum of two functions, u+v, where u denotes the image intensity while v refers to the texture. And then, a spatial FCM clustering method is applied on the image intensity component for segmentation. In the experiments with simulated and clinical ultrasound images, the proposed method can get more accurate results than other preprocessing or segmentation methods.
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