De-aberration for transcranial photoacoustic computed tomography through an adult human skull.

Noninvasive transcranial photoacoustic computed tomography (PACT) of the human brain, despite its clinical potential, remains impeded by the acoustic distortion induced by the human skull. The distortion, which is attributed to the markedly different material properties of the skull relative to soft tissue, results in heavily aberrated PACT images -- a problem that has remained unsolved in the past two decades. Herein, we report the first successful experimental demonstration of the de-aberration of PACT images through an ex-vivo adult human skull using a homogeneous elastic model for the skull. Using only the geometry, position, and orientation of the skull, we accurately de-aberrate the PACT images of light-absorbing phantoms acquired through an ex-vivo human skull, in terms of the recovered phantom features, for different levels of phantom complexity and positions. Our work addresses the longstanding challenge of skull-induced aberrations in transcranial PACT and advances the field towards unlocking the full potential of transcranial human brain PACT.

A method for the geometric calibration of ultrasound transducer arrays with arbitrary geometries.

Geometric calibration of ultrasound transducer arrays is critical to optimizing the performance of photoacoustic computed tomography (PACT) systems. We present a geometric calibration method that is applicable to a wide range of PACT systems. We obtain the speed of sound and point source locations using surrogate methods, which results in a linear problem in the transducer coordinates. We characterize the estimation error, which informs our choice of the point source arrangement. We demonstrate our method in a three-dimensional PACT system and show that our method improves the contrast-to-noise ratio, the size, and the spread of point source reconstructions by 80±19%, 19±3%, and 7±1%, respectively. We reconstruct the images of a healthy human breast before and after calibration and find that the calibrated image reveals vasculatures that were previously invisible. Our work introduces a method for geometric calibration in PACT and paves the way for improving PACT image quality.

Compressive sensing approaches for the prediction of scattered electromagnetic fields.

We present a novel method based on Huygens' principle and compressive sensing to predict the electromagnetic (EM) fields in arbitrary scattering environments by making a few measurements of the field. In doing so, we assume a homogeneous medium between the scatterers, though we do not assume prior knowledge of the permittivities or the exact geometry of the scatterers. The major contribution of this work is a compressive sensing-based subspace optimization method (CS-SOM). Using this, we show that the EM fields in an indoor situation with up to four scattering objects can be reconstructed with approximately 12% error, when the number of measurements is only 55% of the number of variables used to formulate the problem. Our technique departs significantly from traditional ray tracing approaches. We use a surface integral formulation which captures wave-matter interactions exactly, leverage compressive sensing techniques so that field measurements at a few random locations suffice, and apply Huygens' principle to predict the fields at any location in space.