LAUSR

In therapeutic high intensity focused ultrasound (HIFU) applications, cavitation mapping is a powerful tool to monitor and guide the treatment procedure. Furthermore, the frequency spectrum of the cavitation activity can be used to classify the mode of cavitation (stable/inertial), enabling a means for increasing the safety of the application. In this study, we formulate the cavitation mapping as a group sparse constrained optimization problem, minimizing l2,1 -norm of the solution. The frequency bins related to a class of cavitation activity (harmonic, ultra-harmonic, or broadband) are grouped using l2-norm for each voxel, and l1 -norm of the image is minimized. We solve this problem using an Augmented Lagrangian Method, specifically the Alternating Direction Method of Multipliers (ADMM). We used a simulation model to test this method on a 300 mm diameter 128-element hemispherical receiver array application. We calculate the radiated pressure from the microbubbles inside the HIFU beam using a rigid vesse...