摘要
为解决颅骨声阻抗失配导致平面波经颅超声成像质量下降的问题,提出一种基于深度学习的颅骨重建技术,结合快速行进法可实现平面波经颅成像的相位畸变校正。根据人类颅骨CT图像设置颅骨形状进行数值仿真,颅骨重建的时间开销为0.97 s,基于重建结果计算平面波的走时平均相对误差约为0.25%,单点目标散射波走时平均相对误差约为0.76%。经颅仿体实验中,强回声点目标图像经过校正之后,平均位置偏移从1.42 mm减少为0.28 mm,半峰全宽从1.82 mm减少为0.99 mm;圆形目标图像经过校正后对比度噪声比从7.5 dB提升为9.8 dB,偏心率从0.31降低为0.24。以上结果表明,该方法能够准确计算经颅超声的走时并且显著改善成像的质量,可用于经颅脑超声成像的相位畸变校正。
The acoustic impedance mismatch between the skull and surrounding tissues can lead to a decrease in the quality of transcranial plane-wave imaging.A deep learning-based skull reconstruction technique was proposed,which combined fast marching method to achieve aberration correction in transcranial plane-wave imaging.In numerical simulations,an aberrator was set based on the CT image of the human skull,and results show that the time cost of the skull reconstruction is 0.97 s.The average error in the travel time of the plane-wave calculated based on the reconstruction result is 0.25%,while the average error in the travel time of the single point target scattered wave is 0.76%.In phantom experiments,aberration correction resulted in the reduction of the average position deviation of the point target image from 1.42 mm to 0.28 mm and the full-width-at-half-maximum from 1.82 mm to 0.99 mm.Additionally,the average contrast-to-noise ratio of circular targets was improved from 7.5 dB to 9.8 dB,and the eccentricity was simultaneously reduced from 0.31 to 0.24 after the correction.These results indicate that the proposed method can accurately calculate the travel time of transcranial ultrasound and significantly improve the quality of imaging,which holds the capability for high-quality plane-wave imaging of the brain through the skull,and exhibits the potential for application in transcranial Doppler imaging for cerebral blood flow.
作者
周江锦
郭远洋
周宸宸
许凯亮
ZHOU Jiangjin;GUO Yuanyang;ZHOU Chenchen;XU Kailiang(Department of Biomedical Engineering,School of Information Science and Technology,Fudan University,Shanghai 200438;MOE Frontiers Center for Brain Science,Fudan University,Shanghai 200432;State Key Laboratory of Integrated Chips and Systems,Fudan University,Shanghai 201203)
出处
《声学学报》
EI
CAS
CSCD
北大核心
2024年第3期381-391,共11页
Acta Acustica
基金
国家重点研发计划项目(2023YFC2410900)
上海市国际科技合作项目(23490713500)资助。
关键词
平面波成像
经颅超声
相位畸变校正
快速行进法
深度学习
Plane-wave imaging
Transcranial ultrasound
Aberration correction
Fast marching method
Deep learning
