超声乳腺肿块边界提取的自适应扩展b蛇模型

Chen Yintao, K. C. Keong, Wee Siew-Bock, Zou Qingsong
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引用次数: 1

摘要

本文引入一种新的自适应扩展b -蛇模型(AEBS)来提取二维超声乳腺肿块边界,利用b样条将整个蛇形能量分割成更小的部分,以实现整体变形和局部变化。由于超声乳腺肿块图像的噪声特性,将初始模型加载到肿块区域内,并使用膨胀力来降低乳腺组织的“噪声”。经过AEBS前的预处理后,性能得到了改善。利用局部单元的梯度作为轮廓变形的反馈,使膨胀力发挥智能作用。在t-n(正切和法向)坐标中所有定义的力的平衡被用作终止准则。一系列平行扫描的超声乳房肿块图像被用于测试,结果表明我们的方法是正确和一致的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Adaptive expanding B-snake model for extracting ultrasound breast lump boundary
In this paper we introduce a new adaptive expanding B-snake model (AEBS) to extract 2-D ultrasound breast lump boundaries, using B-spline to split the whole snake energy into smaller parts to achieve both global deformation and local variation. Due to the noisy property of ultrasound breast lump images, initial model is loaded inside lump area and an expanding force is used to reduce the 'noise' from the breast tissues. Which has been improved after a pre-processing before the AEBS. Local elements' gradient is used as a feedback of contour deformation to make the expanding force to act intelligently. The balance of all defined forces in t-n (tangent and normal) coordinates is used as a terminating criterion. A serial of parallel-scanned ultrasound breast lump images have been used in the testing and results show our method works correctly and consistently.
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