Full waveform autofocus inversion based microwave induced transcranial thermoacoustic tomography with a human skull validated

Abstract

Stroke is the third leading cause of mortality in many countries. Thermoacoustic imaging has the potential for stroke detection. However, some parameters in thermoacoustic imaging, such as speed of sound, are difficult to be obtained in advance, and a constant velocity value is assumed in the reconstructed algorithm. Thermoacoustic signals propagate through the soft brain tissue and the skull in actual stroke detection. This mismatch between the assumed and actual sound velocity will degrade the imaging quality. In this Letter, we propose a full waveform autofocus inversion method to reconstruct thermoacoustic images for stroke noninvasive and non-ionizing detection. Employing the difference between the simulation forward sensor signals and the measured signals, the approximate speed of sound distribution is updated continuously. The numerical simulation of a real human brain model and the experiment of a real human skull help us to validate the performance of the proposed method in clinical transcranial thermoacoustic detection.

Emerging paradigms in microwave imaging technology for biomedical applications: unleashing the power of artificial intelligence

“…The system is validated through numerical and experimental testing, demonstrating accurate localization and monitoring of hemorrhage and ischemia zones with centimetric spatial resolution. Liu et al 84 proposed full-waveform autofocus inversion thermoacoustic image reconstruction for non-contact, radiation-free stroke diagnosis. Simulations and measurements update a sound speed distribution-numerical simulation of a human brain model and experimental validation of transcranial thermoacoustic detection in the clinic.…”