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

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.