Model-Based X-Ray-Induced Acoustic Computed Tomography

Abstract

X-ray-induced acoustic computed tomography (XACT) provides X-ray absorption-based contrast with acoustic detection. For its clinical translation, XACT imaging often has a limited field of view. This can result in image artifacts and overall loss of quantification accuracy. In this article, we aim to demonstrate model-based XACT image reconstruction to address these problems. An efficient matrix-free implementation of the regularized LSQR (MF-LSQR)-based minimization scheme and a noniterative model back-projection (MBP) scheme for computing XACT reconstructions have been demonstrated in this article. The proposed algorithms have been numerically validated and then used to perform reconstructions from experimental measurements obtained from an XACT setup. While the commonly used back-projection (BP) algorithm produces limited-view and noisy artifacts in the region of interest (ROI), model-based LSQR minimization overcomes these issues. The model-based algorithms also reduce the ring artifacts caused due to the nonuniformity response of the multichannel data acquisition. Using the model-based reconstruction algorithms, we are able to obtain reasonable XACT reconstructions for acoustic measurements of up to 120° view. Although the MBP is more efficient than the model-based LSQR algorithm, it provides only the structural information of the ROI. Overall, it has been demonstrated that the model-based image reconstruction yields better image quality for XACT than the standard BP. Moreover, the combination of model-based image reconstruction with different regularization methods can solve the limited-view problem for XACT imaging (in many realistic cases where the full-view dataset is unavailable), and hence pave the way for future clinical translation.

Fig. 1.

(a) Arc of integration for a detector at distance d from the center of the ROI at time t and corresponding range of θ. The quadrature points on the arc are denoted by small circles. (b) Full and limited-view detection geometries, and the cross-sections of the initial pressure sources (c) I and (d) II.

Fig. 2.

Unregularized (a,b,c) and Laplacian-regularized (d,e,f) model-matrix-based reconstructions and back-projection reconstructions (g,h,i) obtained from 360°, 180° and 120° views, respectively.

Fig. 3.

Model-matrix free reconstruction results: Laplacian-regularized (first row: a,b,c) and model-back-projection (second row: d,e,f) reconstructions obtained from 360°, 180° and 120° views, respectively.

Fig. 4.

Schematic of XACT experimental setup.

Fig. 5.

XACT experimental reconstruction results: (a) true phantom, (b) full and limited-view measurement geometry, and Laplacian-regularized MF-LSQR (c,e,g), model-back-projection MBP (d,f,h), and traditional back-projection (BP) (i,j,k) reconstructions obtained from 360°, 180° and 120° views, respectively.