基于多尺度小波变换和GVF蛇形模型的颈部淋巴结超声图像轮廓提取

Qi Fei, Yujing Lu, Yufeng Zhang
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引用次数: 0

摘要

超声图像的轮廓提取对医学诊断具有积极意义。提出了一种结合多尺度小波变换模极大值和GVF蛇形算法提取颈部淋巴结轮廓的方法。该方法首先利用小波变换模极大值边缘检测算法获得超声图像的初始轮廓,然后利用梯度矢量流场蛇形模型提取图像的精确轮廓。实验表明,该方法克服了小波分析得到不连续边缘的缺点;与传统的GVF蛇形模型相比,该模型具有更好的抗噪声能力和抗伪干扰能力。此外,初始轮廓更接近给定图像的真实边缘,从而减少了梯度矢量流场的迭代次数,提高了轮廓的收敛速度。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The contour extraction of neck lymph node ultrasound image based on multi-scale wavelet transform and GVF snake model
It is of positive significance to extract the contour of ultrasound images for medical diagnosis. The paper proposes a method which combines with multi-scale wavelet transform modulus maxima and GVF snake algorithm to extract the contour of cervical lymph node. Firstly, the proposed method obtains the initial contour of the ultrasound image with using an algorithm of edge detection called wavelet transform modulus maxima, and then using GVF snake model can extract the accurate contour of the image. Experiments show that the method overcomes the disadvantages of the wavelet analysis getting the discontinuous edge; it is better in noise immunity and anti-artifact interference compared with the traditional GVF snake model. In addition, the initial contour is close to the real edge of the given image, thus it reduces the iteration number of gradient vector flow (GVF) field and improves the convergence speed of the contour.
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