A deep‐learning model for one‐shot transcranial ultrasound simulation and phase aberration correction

TUSNet demonstrates that deep learning can provide accurate and rapid estimates of phase aberrations and transcranial pressure fields, offering a promising direction for accelerating ultrasound treatment planning. While the present validation is based on simulated, noise-free ultrasound fields, the results establish a foundation that future experimental studies can build on to assess performance under real-world clinical conditions.