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Semiautomatic Snake-Based Segmentation of Solid Breast Nodules on Ultrasonography

机译:基于超声的基于半自动蛇的乳腺实性结节分割

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摘要

Ultrasonography plays a crucial role in the diagnosis of breast cancer. However, it is one of the most difficult types of images to segment and analyze. The presence of speckle noise and low contrast areas limits the success of most noise reduction filters and segmentation algorithms. In this paper, we propose a combination of different techniques which provide quite satisfactory results in the segmentation of breast tumors on Ultrasonography. It is performed in a semiautomatic way, which eliminates the need for a manual delineation of the contour of the nodules. These techniques include the truncated median filter, a region-growing algorithm and active contours. Furthermore, this can be the initial phase for an exhaustive analysis of the diagnostic criteria in breast ultrasound.
机译:超声检查在乳腺癌的诊断中起着至关重要的作用。但是,它是最难分割和分析的图像类型之一。斑点噪声和低对比度区域的存在限制了大多数降噪滤波器和分割算法的成功。在本文中,我们提出了多种不同技术的组合,这些技术在超声检查中对乳腺肿瘤的分割中提供了令人满意的结果。它以半自动方式执行,从而无需手动描绘结核的轮廓。这些技术包括截断的中值滤波器,区域增长算法和活动轮廓。此外,这可能是对乳房超声诊断标准进行详尽分析的初始阶段。

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