电子学报2025，Vol.53Issue(8)：2843-2853,11.DOI:10.12263/DZXB.20241148
基于DCNN的超快超声彩色血流成像
Ultrafast Ultrasound Color Blood Flow Imaging Based on the DCNN
摘要
Abstract
Multi-angle plane wave coherent compounding(MPWCC)can achieve high frame rate ultrasound scan-ning,which aids color flow imaging technology in providing more accurate blood flow information and tissue images.How-ever,the low-pass effect of the MPWCC results in underestimated blood flow velocities and the optimal threshold for clut-ter suppression filters cannot be determined computationally.To address this,this paper proposes an ultra fast ultrasound color blood flow imaging based on deep convolutional neural networks(DCNN).Based on the Field II ultrasound simula-tor,the carotid artery model is built to acquire ultrasound doppler signals with different blood flow velocities.These signals are processed with the singular value decomposition(SVD)and then normalized to generate training dataset.The DCNN model learns the characteristics of Doppler signals with different velocities through supervised learning,enabling clutter suppression and conversion of feature information into velocity information for color flow imaging.Compared to the auto-correlation velocimetry by combining high pass filtering(HPF)or SVD,the superior performance of the proposed method has been demonstrated in both simulation and human carotid artery test dataset.When blood flow velocity profiles in both forward and reverse directions are estimated,the normalized root mean square error(NRMSE)of the proposed method is re-duced by an average of 45.65%and 41.95%than these of the HPF and SVD,respectively.In the results of color flow imag-ing in simulation and human data,the proposed method shows the best clutter suppression effect and vessel integrity.In summary,this method achieves ultrafast ultrasound color blood flow imaging and is applicable for visualizing blood flow dynamics.关键词
医学超声/超声平面波/彩色血流成像/深度卷积神经网络/奇异值分解Key words
medical ultrasound/ultrasound plane wave/color flow imaging/deep convolutional neural network/sin-gular value decomposition分类
信息技术与安全科学引用本文复制引用
崔旺,何冰冰,邹良辰,王婷婷,李海燕..基于DCNN的超快超声彩色血流成像[J].电子学报,2025,53(8):2843-2853,11.基金项目
国家自然科学基金(No.62201495) National Natural Science Foundation of China(No.62201495) （No.62201495）
