Yang Yuming, Jiang Dong, Zhang Qiongwen, Le Xiaoxia, Chen Tao, Duan Huilong, Zheng Yinfei
College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, Zhejiang 310027, China.
Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Material Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201, China.
BME Front. 2023 Sep 25;4:0030. doi: 10.34133/bmef.0030. eCollection 2023.
The objective of this work is to investigate the mapping relationship between transcranial ultrasound image quality and transcranial acoustic metamaterial parameters using inverse design methods. Our study provides insights into inverse design methods and opens the route to guide the preparation of transcranial acoustic metamaterials. The development of acoustic metamaterials has enabled the exploration of cranial ultrasound, and it has been found that the influence of the skull distortion layer on acoustic waves can be effectively eliminated by adjusting the parameters of the acoustic metamaterial. However, the interaction mechanism between transcranial ultrasound images and transcranial acoustic metamaterial parameters is unknown. In this study, 1,456 transcranial ultrasound image datasets were used to explore the mapping relationship between the quality of transcranial ultrasound images and the parameters of transcranial acoustic metamaterials. The multioutput parameter prediction model of transcranial metamaterials based on deep back-propagation neural network was built, and metamaterial parameters under transcranial image evaluation indices are predicted using the prediction model. This inverse big data design approach paves the way for guiding the preparation of transcranial metamaterials.
这项工作的目的是使用逆向设计方法研究经颅超声图像质量与经颅声学超材料参数之间的映射关系。我们的研究为逆向设计方法提供了见解，并开辟了指导经颅声学超材料制备的途径。声学超材料的发展使得颅骨超声的探索成为可能，并且已经发现通过调整声学超材料的参数可以有效地消除颅骨畸变层对声波的影响。然而，经颅超声图像与经颅声学超材料参数之间的相互作用机制尚不清楚。在本研究中，使用1456个经颅超声图像数据集来探索经颅超声图像质量与经颅声学超材料参数之间的映射关系。建立了基于深度反向传播神经网络的经颅超材料多输出参数预测模型，并使用该预测模型预测经颅图像评估指标下的超材料参数。这种逆向大数据设计方法为指导经颅超材料的制备铺平了道路。
