Research on Calculation of the Regional Cerebral Blood Volume Based on Minimum Mean Square Error Method_Journal of Biomedical Engineering

Authors：

CHENJie ¹ ,  LIYing ¹ , WANGRongren ² , HERenjie ³ , RAOLiyun ⁴

1. Province-Ministry Joint Key Laboratory of Electromagnetic Field and Electrical Apparatus Reliability, School of Electrical Engineering, Hebei University of Technology, Tianjin 300130, China;
2. Department of Imaging, Tianjin People's Hospital, Tianjin 300121, China;
3. Department of Imaging Physics, M. D. Anderson Cancer Center, The University of Texas Health Science Center at Houston, Houston, TX 77054, USA;
4. Department of Cardiology, The Methodist Hospital Research Institute, Houston, TX 77030, USA;

Corresponding author：

LIYing, Email: yli@hebut.edu.cn

Keywords：

magnetic resonance perfusion imaging; regional cerebral blood volume; minimum mean square error method; signal-to-noise ratio

DOI：

10.7507/1001-5515.20140229

Video：

Export PDF Favorites Scan Get Citation

Abstract Full text Figures/Tables Video References Cited by

In this paper, the Fourier transform based minimum mean square error (FT-based MMSE) method is used to calculate the regional cerebral blood volume (rCBV) in magnetic resonance (MR) perfusion imaging, and the method is improved to handle the existing noise in the imaging process. In the experiments with signal-to-noise ratio (SNR) of 50 dB, the rCBV values were compared with the results using MMSE method. The effects of different SNRs on the estimation of rCBV were analyzed. The experimental results showed that MMSE was a simple way to filter the measurement noise, and could calculate rCBV accurately. Compared with other existing methods, the present method is not sensitive to environment, and furthermore, it is suitable to deal with the perfusion images acquired from the environment with larger SNR.

Citation： CHENJie, LIYing, WANGRongren, HERenjie, RAOLiyun. Research on Calculation of the Regional Cerebral Blood Volume Based on Minimum Mean Square Error Method. Journal of Biomedical Engineering, 2014, 31(6): 1207-1211. doi: 10.7507/1001-5515.20140229 Copy

1.	胡新韬,李晖晖,郭雷.磁共振灌注成像血容量优化量化[J].计算机工程与应用,2010,46(31):25-27,31.
2.	孟令雷.磁共振灌注成像在高血压脑血管病的应用进展[J].磁共振成像,2011,2(5):384-387.
3.	倪萍,陈自谦.MRI临床应用新进展[J].医疗设备信息,2006,21(9):43-45,48.
4.	PETRELLA J R, PROVENZALE J M. MR perfusion imaging of the brain:techniques and applications[J]. Am J Roentgenology, 2000, 175(1):207-219.
5.	秦福双.脑灌注成像在急性脑血管病诊断中的应用[J].中国实用神经疾病杂志,2011,14(23):80-81.
6.	史瑞华,翟仁友,钱晓军,等.磁共振灌注成像诊断良恶性脑膜瘤[J].中国医学影像技术,2010,26(2):243-246.
7.	OSTERGAARD L, WEISSKOFF R M, CHESLER D A, et al. High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part Ⅰ:Mathematical approach and statistical analysis[J]. Magn Reson Med, 1996, 36(5):715-725.
8.	王凯,张伟伟,唐一源.磁共振脑功能成像信号——噪声及分析处理研究[J].国际生物医学工程杂志,2006,29(5):277-279,312.
9.	SAKOGLU U, SOOD R. Cerebral blood flow estimation from perfusion-weighted MRI using FT-based MMSE filtering method[J]. Magn Reson Imaging, 2008, 26(3):313-322.
10.	吴素珍,焦计平,周又玲.一种因果维纳滤波器的推导方法[J].通信技术,2011,44(3):136-138.
11.	李承锋.利用曲线拟合找到血流灌注磁振影像的血液动力参数[D].台湾:国立阳明大学,2006.
12.	马栋敏,李颖,彭川,等.奇异值分解法用于MR灌注成像脑血流量估计的仿真研究[J].中国生物医学工程学报,2011,30(6):813-819.
13.	LI Y, MA D M, HE R J, et al. The application of magnetic resonance perfusion imaging in the estimation of brain function using SVD method[J]. IEEE Trans Magn, 2012, 48(11):2850-2853.
14.	SALLUZZI M, FRAYNE R, SMITH M R. An alternative viewpoint of the similarities and differences of SVD and FT deconvolution algorithms used for quantitative MR perfusion studies[J]. Magn Reson Imaging, 2005, 23(3):481-492.
15.	KNUTSSON L, STÅHLBERG F, WIRESTAM R. Aspects on the accuracy of cerebral perfusion parameters obtained by dynamic susceptibility contrast MRI:a simulation study[J]. Magn Reson Imaging, 2004, 22(6):789-798.
16.	姜旭栋,周益,侯海燕,等.正常成人256层极速CT全脑灌注成像的脑血流动力学定量研究[J].现代中西医结合杂志,2013,22(3):302-304.

1. 胡新韬,李晖晖,郭雷.磁共振灌注成像血容量优化量化[J].计算机工程与应用,2010,46(31):25-27,31.
2. 孟令雷.磁共振灌注成像在高血压脑血管病的应用进展[J].磁共振成像,2011,2(5):384-387.
3. 倪萍,陈自谦.MRI临床应用新进展[J].医疗设备信息,2006,21(9):43-45,48.
4. PETRELLA J R, PROVENZALE J M. MR perfusion imaging of the brain:techniques and applications[J]. Am J Roentgenology, 2000, 175(1):207-219.
5. 秦福双.脑灌注成像在急性脑血管病诊断中的应用[J].中国实用神经疾病杂志,2011,14(23):80-81.
6. 史瑞华,翟仁友,钱晓军,等.磁共振灌注成像诊断良恶性脑膜瘤[J].中国医学影像技术,2010,26(2):243-246.
7. OSTERGAARD L, WEISSKOFF R M, CHESLER D A, et al. High resolution measurement of cerebral blood flow using intravascular tracer bolus passages. Part Ⅰ:Mathematical approach and statistical analysis[J]. Magn Reson Med, 1996, 36(5):715-725.
8. 王凯,张伟伟,唐一源.磁共振脑功能成像信号——噪声及分析处理研究[J].国际生物医学工程杂志,2006,29(5):277-279,312.
9. SAKOGLU U, SOOD R. Cerebral blood flow estimation from perfusion-weighted MRI using FT-based MMSE filtering method[J]. Magn Reson Imaging, 2008, 26(3):313-322.
10. 吴素珍,焦计平,周又玲.一种因果维纳滤波器的推导方法[J].通信技术,2011,44(3):136-138.
11. 李承锋.利用曲线拟合找到血流灌注磁振影像的血液动力参数[D].台湾:国立阳明大学,2006.
12. 马栋敏,李颖,彭川,等.奇异值分解法用于MR灌注成像脑血流量估计的仿真研究[J].中国生物医学工程学报,2011,30(6):813-819.
13. LI Y, MA D M, HE R J, et al. The application of magnetic resonance perfusion imaging in the estimation of brain function using SVD method[J]. IEEE Trans Magn, 2012, 48(11):2850-2853.
14. SALLUZZI M, FRAYNE R, SMITH M R. An alternative viewpoint of the similarities and differences of SVD and FT deconvolution algorithms used for quantitative MR perfusion studies[J]. Magn Reson Imaging, 2005, 23(3):481-492.
15. KNUTSSON L, STÅHLBERG F, WIRESTAM R. Aspects on the accuracy of cerebral perfusion parameters obtained by dynamic susceptibility contrast MRI:a simulation study[J]. Magn Reson Imaging, 2004, 22(6):789-798.
16. 姜旭栋,周益,侯海燕,等.正常成人256层极速CT全脑灌注成像的脑血流动力学定量研究[J].现代中西医结合杂志,2013,22(3):302-304.

Journal of Biomedical Engineering

Research on Calculation of the Regional Cerebral Blood Volume Based on Minimum Mean Square Error Method

Abstract Full text Figures/Tables Video References Cited by

Previous Article

Next Article

Format

Content