基于相位的乳腺超声图像主动轮廓分割模型

Lingyun Cai, Yuanyuan Wang
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引用次数: 10

摘要

由于乳腺超声图像存在散斑噪声、对比度低、边界模糊等问题,图像边界的提取一直是一个难点。为了解决这一问题,提出了一种新的基于相位的活动轮廓模型。首先,我们利用局部相位信息,采用相位不对称的方法形成新的边缘指示器,大大提高了对强度不均匀的鲁棒性;然后,将一种新的基于相位的边缘指标纳入到具有局部区域分割能量的各种水平集公式中;实验分别在合成图像和真实图像上进行。结果表明,所提出的PBAC模型在定性和定量上都优于现有的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A phase-based active contour model for segmentation of breast ultrasound images
Due to the speckle noises, low contrast and blurry boundaries in breast ultrasound (BUS) images, extraction of the boundaries in BUS images is always a challenging task. To solve this problem, a novel phase-based active contour (PBAC) model is proposed. First, we utilize the local phase information and apply the phase asymmetry approach to form a new edge indicator, which dramatically increases the robustness to intensity inhomogeneous. Then, a novel phase-based edge indicator is incorporated into a various level set formulation with the local region-based segmentation energy. Experiments are performed on both synthetic and real BUS images. The results show that the proposed PBAC model outperforms the state-of-art methods both qualitatively and quantitatively.
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