[1]潘晓畅,冯乃章,陈思平.二维Savitzky-Golay数字差分器剪切波弹性成像方法[J].深圳大学学报理工版,2018,35(1):22-28.[doi:10.3724/SP.J.1249.2018.01022]
　PAN Xiaochang,FENG Naizhang,et al.A shear wave elastography method based on 2D Savitzky-Golay digital differentiator[J].Journal of Shenzhen University Science and Engineering,2018,35(1):22-28.[doi:10.3724/SP.J.1249.2018.01022]
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二维Savitzky-Golay数字差分器剪切波弹性成像方法()
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《深圳大学学报理工版》[ISSN:1000-2618/CN:44-1401/N]

卷:
第35卷
期数:
2018年第1期
页码:
22-28
栏目:
生物工程
出版日期:
2018-01-12

文章信息/Info

Title:
A shear wave elastography method based on 2D Savitzky-Golay digital differentiator
文章编号:
201801004
作者:
潘晓畅1; 2; 冯乃章2; 陈思平1
1）医学超声关键技术国家地方联合工程实验室，广东省生物医学信息监测与超声成像重点实验室，深圳大学生物医学工程学院，广东深圳 518060
2）深圳开立生物医疗科技股份有限公司，广东深圳 518052
Author(s):
PAN Xiaochang1;  2;  FENG Naizhang2;  and CHEN Siping1
1) National-Regional Key Technology Engineering Laboratory for Medical Ultrasound, Guangdong Key Laboratory for Biomedical Measurements and Ultrasound Imaging, School of Biomedical Engineering, Shenzhen University, Shenzhen 518060, Guangdong Province, P.R.China
2) Sonoscape Corporation, Shenzhen 518052, Guangdong Province, P.R.China
关键词:
生物医学工程; 医学影像; 超声成像; 剪切波弹性成像; 剪切波速度估计; 杨氏模量
Keywords:
biomedical engineering;  medical imaging;  ultrasound imaging;  shear wave elastography;  shear wave speed estimation;  Young’s modulus
分类号:
TB 559；TB 551
DOI:
10.3724/SP.J.1249.2018.01022
文献标志码:
A
摘要:
提出一种新的剪切波弹性成像方法，将2D SG(Savitzky-Golay）数字差分器用于剪切波计算中，使用二维曲面拟合来近似剪切波波前到达时刻，该方法相比传统的线性回归方法不易受异常数据影响，鲁棒性更强. 通过超声弹性仿体实验评估这两种方法，比较不同尺寸下的2D SG数字差分器和线性回归的剪切波弹性图. 结果表明，在图像的横向分辨率相同的情况下，本研究方法得到的剪切波弹性图像更平滑，噪声更小，且剪切波弹性图像的信噪比和对比度噪声均比传统方法要高，表明该方法能提高剪切波弹性图像的质量.
Abstract:
We propose a new shear wave elastography method based on the 2D Savitzky-Golay （SG） digital differentiator in the shear wave speed estimation. The 2D SG digital differentiator utilizes two dimensional surface fitting method to obtain the arrival time of shear wave’s wave-front. In comparison with the linear regression method, the 2D SG digital differentiator is not only less affected by the outlier data but also more robust. Moreover, we use the ultrasound elastic phantom experiments to evaluate the two methods and compare the shear wave elastograms obtained by the two methods. The elastograms obtained by our proposed method are smoother and have lower noise than those of linear regression method, while the lateral resolutions of images are the same. In our phantom experiment, the shear wave elastograms for our new method have higher signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). The research shows that the new proposed method effectively improves the quality of shear wave elastogram.

参考文献/References:

［1］ GARRA B S. Elastography: history, principles, and technique comparison［J］.Abdominal Imaging,2015,40(4):680-697.
［2］ PALMERI M L, WANG M H, DAHL J J, et al. Quantifying hepatic shear modulus in vivo using acoustic radiation force［J］.Ultrasound in Medicine & Biology,2008,34(4):546-558.
［3］ LEE E J, JUNG H K, KO K H, et al. Diagnostic performances of shear wave elastography: which parameter to use in differential diagnosis of solid breast masses?［J］.European Radiology,2013,23(7):1803-1811.
［4］ FERRAIOLI G, TINELLI C, DAL BELLO B, et al. Accuracy of real-time shear wave elastography for assessing liver fibrosis in chronic hepatitis C: a pilot study［J］. Hepatology, 2012, 56(6):2125-2133.
［5］ SARVAZYAN A P, RUDENKO O V, SWANSON S D, et al. Shear wave elasticity imaging: a new ultrasonic technology of medical diagnostics［J］. Ultrasound in Medicine & Biology,1998,24(9):1419-1435.
［6］ BERCOFF J, TANTER M, FINK M.Supersonic shear imaging: a new technique for soft tissue elasticity mapping［J］.IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control,2004,51(4):396-409.
［7］ WANG M H, PALMERI M L, ROTEMBERG V M, et al.Improving the robustness of time-of-flight based shear wave speed reconstruction methods using RANSAC in human liver in vivo［J］.Ultrasound in Medicine & Biology,2010,36(5):802-813.
［8］ ROUZE N C, WANG M H, PALMERI M L,et al.Robust estimation of time-of-flight shear wave speed using a radon sum transformation［J］. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control,2010,57(12):2662-2670.
［9］ ROUZE N C, WANG M H, PALMERI M L,et al. Parameters affecting the resolution and accuracy of 2-D quantitative shear wave images［J］. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control,2012,59(8):1729-1740.
［10］ AMADOR CARRASCAL C, CHEN Shigao, MANDUCA A,et al.Improved shear wave group velocity estimation method based on spatiotemporal peak and thresholding motion search［J］. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control,2017,64(4):660-668.
［11］ LIPMAN S L, ROUZE N C, PALMERI M L,et al. Evaluating the improvement in shear wave speed image quality using multidimensional directional filters in the presence of reflection artifacts［J］.IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control,2016,63(8):1049-1063.
［12］ YOON H, AGLYAMOV S R, EMELIANOV S Y. Dual-phase transmit focusing for multi-angle compound shear-wave elasticity imaging［J］.IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control,2017,64(10): 1439-1449.
［13］ LUO Jianwen, YING Kui, HE Ping, et al. Properties of Savitzky—Golay digital differentiators［J］.Digital Signal Processing,2005,15(2):122-136.
［14］ LUO Jianwen, BAI Jing, HE Ping,et al. Axial strain calculation using a low-pass digital differentiator in ultrasound elastography［J］. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control,2004,51(9):1119-1127.
［15］ GOWRI B G, HARIHARAN V, THARA S, et al. 2D image data approximation using Savitzky Golay filter-smoothing and differencing［J］. IEEE. 2013, 7903: 365-371.
［16］ DENG Yufeng, ROUZE N C, PALMERI M L, et al. Ultrasonic shear wave elasticity imaging sequencing and data processing using a verasonics research scanner［J］. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control,2017,64(1):164-176.
［17］ DENG Yufeng, ROUZE N C, PALMERI M L,et al. On system-dependent sources of uncertainty and bias in ultrasonic quantitative shear-wave imaging［J］. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control,2016,63(3):381-393.
［18］ KASAI C, NAMEKAWA K, KOYANO A, et al. Real-time two-dimensional blood-flow imaging using an auto-correlation technique［J］. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control,1985,32(3):458-464.
［19］ DEFFIEUX T, GENNISSON J, BERCOFF J,et al. On the effects of reflected waves in transient shear wave elastography［J］. IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control,2011,58(10):2032-2035.
［20］ VARGHESE T, OPHIR J. An analysis of elastographic contrast-to-noise ratio［J］. Ultrasound in Medicine & Biology,1998,24(6):915-924.

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备注/Memo

备注/Memo:
Received：2017-09-19；Accepted：2017-11-24
Foundation：National Science Foundation for Post-doctoral Scientists of China (2017M612740)；National Natural Science Foundation of China (61701319, 61372006, 61427806)
Corresponding author：Professor CHEN Siping. E-mail: chensiping@szu.edu.cn
Citation：PAN Xiaochang, FENG Naizhang, CHEN Siping. A shear wave elastography method based on 2D Savitzky-Golay digital differentiator［J］. Journal of Shenzhen University Science and Engineering, 2018, 35(1): 22-28.（in Chinese）
基金项目：国家博士后基金资助项目 (2017M612740)；国家自然科学基金资助项目 (61701319，61372006，61427806)
作者简介：潘晓畅(1987—)，男，深圳大学博士后研究人员．研究方向：超声成像．E-mail：xcpan@pku.edu.cn
引文：潘晓畅，冯乃章，陈思平. 二维Savitzky-Golay数字差分器剪切波弹性成像方法［J］. 深圳大学学报理工版，2018，35(1)：22-28.
更新日期/Last Update: 2017-12-22