中国物理B ›› 2025, Vol. 34 ›› Issue (8): 84301-084301.doi: 10.1088/1674-1056/add4f3
Stabilized adaptive waveform inversion for enhanced robustness in Gaussian penalty matrix parameterization and transcranial ultrasound imaging
Jun-Jie Zhao(赵俊杰)1,†, Shan-Mu Jin(金山木)2,†, Yue-Kun Wang(王月坤)2, Yu Wang(王裕)2,‡, and Ya-Hui Peng(彭亚辉)1,§
- 1 School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China;
2 Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT Alliance, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
Stabilized adaptive waveform inversion for enhanced robustness in Gaussian penalty matrix parameterization and transcranial ultrasound imaging
Jun-Jie Zhao(赵俊杰)1,†, Shan-Mu Jin(金山木)2,†, Yue-Kun Wang(王月坤)2, Yu Wang(王裕)2,‡, and Ya-Hui Peng(彭亚辉)1,§
- 1 School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China;
2 Department of Neurosurgery, Center for Malignant Brain Tumors, National Glioma MDT Alliance, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100730, China
摘要： Achieving high-resolution intracranial imaging in a safe and portable manner is critical for the diagnosis of intracranial diseases, preoperative planning of craniotomies and intraoperative management during craniotomy procedures. Adaptive waveform inversion (AWI), a variant of full waveform inversion (FWI), has shown potential in intracranial ultrasound imaging. However, the robustness of AWI is affected by the parameterization of the Gaussian penalty matrix and the challenges posed by transcranial scenarios. Conventional AWI struggles to produce accurate images in these cases, limiting its application in critical medical settings. To address these issues, we propose a stabilized adaptive waveform inversion (SAWI) method, which introduces a user-defined zero-lag position for the Wiener filter. Numerical experiments demonstrate that SAWI can achieve accurate imaging under Gaussian penalty matrix parameter settings where AWI fails, perform successful transcranial imaging in configurations where AWI cannot, and maintain the same imaging accuracy as AWI. The advantage of this method is that it achieves these advancements without modifying the AWI framework or increasing computational costs, which helps to promote the application of AWI in medical fields, particularly in transcranial scenarios.
中图分类号: (Acoustic imaging, displays, pattern recognition, feature extraction)
- 43.60.Lq