一种改进的水平集超声成像血管壁检测方法

Yousheng Wang, Yuexia Shu, B. Hu, Jianxin Chen
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引用次数: 5

摘要

提出了一种基于几何活动轮廓的血管内超声图像边缘检测新方法。医学图像分割方法是将传统的水平集方法与b样条模型相结合的方法。该方法只需要几个控制点,就能达到平滑剧烈变化曲线的效果。与传统的水平集函数相比,该方法具有无需重新初始化有符号距离函数、曲线平滑度更高、演化简单等优点。实验结果表明,该算法能够快速准确地获得医学图像的分割结果,并且该方法在图像处理中具有可重复性和鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An improved level set method of ultrasound imaging to detect blood vessel walls
This paper presents a new method for detecting the edge of intravascular ultrasound images, based on geometric active contours. The medical image segmentation method is based on the combination of traditional Level Set method and B-Spline models. The new method only needs a few control points to achieve the effect of smoothing curves with drastic changes. Compared with the traditional level set function, this method has many advantages, such as no re-initializing to signed distance function, a higher curve smoothness and simple evolution and so on. Experimental results show that the algorithm can obtain segmentation results of medical image fast and accurately, and the method is reproducible and robust in image processing.
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