Multiscale Non-Parametric Level Set Segmentation of Ultrasound Echocardiography

doi:10.7652/xjtuxb201302009

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Multiscale Non-Parametric Level Set Segmentation of Ultrasound Echocardiography

更新时间：2025-07-09

- Multiscale Non-Parametric Level Set Segmentation of Ultrasound Echocardiography
- Vol. 47, Issue 2, Pages: 53-57+96(2013)
- 作者机构：
  
  西安交通大学第三附属医院,西安,710068
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb201302009
  CLC： TN911.7
- Online First：10 February 2013，
  
  Published：2013
- 稿件说明：
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Multiscale Non-Parametric Level Set Segmentation of Ultrasound Echocardiography[J]. 2013, 47(2): 53-57+96.
DOI：

Multiscale Non-Parametric Level Set Segmentation of Ultrasound Echocardiography[J]. 2013, 47(2): 53-57+96. DOI： 10.7652/xjtuxb201302009.

摘要

针对超声心动图噪声很大、提取目标区域边界不够平滑完整的问题

将非参数技术与水平集相结合

提出了多尺度非参数化的水平集图像分割方法。利用非局域均值滤波建立尺度空间

保护图像特征

在粗尺度预分割

然后在细尺度优化分割。采用Parzen窗技术对超声心动图的亮度分布进行统计建模

不需要先验假设

引入到水平集框架中

设计了非参数化水平集分割模型。分割实验证明:预分割结果和真实边界的平均绝对距离为2.162

优化后为0.710。该方法可以精确地自动提取感兴趣区域

在图像分割鲁棒性和精确性方面优于常规分割方法。

Abstract

To solve difficulty that the boundary of segmented objective region is not enough smooth and complete due to ultrasound echocardiography with serious noise

a multiscale segmentation approach combined non-parametric technique with level set

is presented. The nonlocal means filtering(NLM)is performed to create scale space and preserve image features. Pre-segmentation is firstly carried out in a coarser scale image

then an optimized segmentation in a finer scale image

the intensity distribution of the ultrasound echo images is modeled by Parzen window technique without prior assumption. A non-parametric model on level set framework is designed to segment the ultrasound echocardiography. The segmentation experiments show that the mean absolute distance(MAD)between real boundary and pre-segmentation result gets to 2.162

but

and the optimized result only 0.710. The approach outperforms the conventional segmentation methods by accurately and automatically extracting the regions of interest.

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references

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