计算机应用 ›› 2021, Vol. 41 ›› Issue (10): 3089-3096.DOI: 10.11772/j.issn.1001-9081.2020121948

所属专题: 前沿与综合应用

• 前沿与综合应用 • 上一篇    

基于超声谐波包络Nakagami参数图像的微波消融区域自动分割方法

卓禹心1, 韩素雅1,2, 张榆锋1, 李支尧3, 董毅峰1   

  1. 1. 云南省高校高原医学电子信息智能检测处理重点实验室(云南大学), 昆明 650091;
    2. 郑州大学 信息工程学院, 郑州 450001;
    3. 云南省肿瘤医院 超声科, 昆明 650031
  • 收稿日期:2020-12-11 修回日期:2021-05-05 出版日期:2021-10-10 发布日期:2021-07-16
  • 通讯作者: 韩素雅
  • 作者简介:卓禹心(1996-),女,四川成都人,硕士研究生,主要研究方向:生物医学信号处理、图像处理;韩素雅(1992-),女,河南平顶山人,讲师,博士,主要研究方向:生物医学信号处理;张榆锋(1965-),男,云南昆明人,教授,博士,主要研究方向:生物医学信号处理;李支尧(1967-),男,云南德宏人,副教授,博士,主要研究方向:临床超声;董毅峰(1994-),男,江苏盐城人,硕士研究生,主要研究方向:医学图像处理。
  • 基金资助:
    国家自然科学基金资助面上项目(81771928)基金项目:。

Automatic segmentation method of microwave ablation region based on Nakagami parameters images of ultrasonic harmonic envelope

ZHUO Yuxin1, HAN Suya1,2, ZHANG Yufeng1, LI Zhiyao3, DONG Yifeng1   

  1. 1. Yunnan Province University Key Laboratory of Electronic Information Processing of High Altitude Medicine(Yunnan University), Kunming Yunnan 650091, China;
    2. School of Information Engineering, Zhengzhou University, Zhengzhou Henan 450001, China;
    3. Department of Ultrasound, Yunnan Cancer Hospital, Kunming Yunnan 650000, China
  • Received:2020-12-11 Revised:2021-05-05 Online:2021-10-10 Published:2021-07-16
  • Supported by:
    This work is partially supported by the Surface Program of National Natural Science Foundation of China (81771928).

摘要: 针对现有超声谐波包络信号的Nakagami参数成像能够实现对消融过程的无创监测,然而并不能精确估计消融区域的问题,提出了一种基于超声谐波包络Nakagami参数图像的高斯逼近自适应阈值分割(GATS)方法用于微波消融区域的准确有效监测。首先,使用高通滤波器获得超声回波射频信号的谐波分量;然后,估计谐波信号包络的Nakagami形状参数,并使用复合窗口成像生成Nakagami参数图像;最后,对Nakagami参数图像进行高斯逼近以呈现消融区域,对逼近图像进行各向异性平滑预处理,并使用对平滑后图像进行自适应阈值分割来精确估计消融区域。微波消融实验结果表明,基于P-M(Perona-Malik)算法的各向异性平滑后的阈值分割消融区域与实际消融区域的长、短轴误差相较基于Catte算法得到的误差分别减小了2.95个百分点和1.15个百分点,与基于中值滤波改进(Median)算法得到的误差相比分别减小了6.52个百分点和2.33个百分点。可见对超声谐波包络Nakagami参数图像使用P-M算法的GATS能够更为精确地估计消融区域,为临床消融手术提供有效监测。

关键词: 微波消融, 超声谐波, 包络Nakagami参数成像, 高斯逼近, 阈值分割

Abstract: The existing Nakagami parametric imaging of ultrasonic harmonic envelope signals can realize non-invasive monitoring of the ablation process, but it cannot estimate the ablation area accurately. In order to solve the problem, a Gaussian Approximation adaptive Threshold Segmentation (GATS) method based on ultrasonic harmonic envelope Nakagami parameter images was proposed to monitor microwave ablation areas accurately and effectively. Firstly, a high-pass filter was used to obtain the harmonic components of the ultrasound echo Radio Frequency (RF) signal. Then, the Nakagami shape parameters of the harmonic signal envelope were estimated, and Nakagami parameter image was generated by composite window imaging. Finally, Gaussian approximation of Nakagami parameter image was applied to present the ablation area, the anisotropic smoothing preprocessing was performed to the approximated image, and the threshold segmentation of the smoothed image was used to accurately estimate the ablation area. The results of microwave ablation experiments show that, the long and short axis errors of the threshold segmentation ablation area after anisotropic smoothing based on Perona-Malik (P-M) algorithm and the actual ablation area are reduced by 3.15 percentage points and 2.21 percentage points respectively compared with the errors obtained by using Catte algorithm, and decreased by 7.87 percentage points and 5.74 percentage points compared with the errors obtained by using Median algorithm. It can be seen that GATS using P-M algorithm for ultrasonic harmonic envelope Nakagami parameter images can estimate the ablation area more accurately and provide effective monitoring for clinical ablation surgery.

Key words: microwave ablation, ultrasound harmonic, envelope Nakagami parametric imaging, Gaussian approximation, threshold segmentation

中图分类号: