Investigation of iterative image reconstruction in three-dimensional optoacoustic tomography

Purpose: Optoacoustic tomography (OAT) is inherently a three-dimensional (3D) inverse problem. However, most studies of OAT image reconstruction still employ two-dimensional imaging models. One important reason is because 3D image reconstruction is computationally burdensome. The aim of this work is to accelerate existing image reconstruction algorithms for 3D OAT by use of parallel programming techniques. Methods: Parallelization strategies are proposed to accelerate a filtered backprojection (FBP) algorithm and two different pairs of projection/backprojection operations that correspond to two different numerical imaging models. The algorithms are designed to fully exploit the parallel computing power of graphics processing units (GPUs). In order to evaluate the parallelization strategies for the projection/backprojection pairs, an iterative image reconstruction algorithm is implemented. Computer simulation and experimental studies are conducted to investigate the computational efficiency and numerical accuracy of the developed algorithms. Results: The GPU implementations improve the computational efficiency by factors of 1000, 125, and 250 for the FBP algorithm and the two pairs of projection/backprojection operators, respectively. Accurate images are reconstructed by use of the FBP and iterative image reconstruction algorithms from both computer-simulated and experimental data. Conclusions: Parallelization strategies for 3D OAT image reconstruction are proposed for the first time. These GPU-based implementations significantly reduce the computational time for 3D image reconstruction, complementing our earlier work on 3D OAT iterative image reconstruction.

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“…When sampling effects are considered, an OAT system is properly described as a continuous-to-discrete (C-D) imaging model 14,22,35,38,39 […”

Section: Iib Discrete-to-discrete Imaging Models and Iterative Imagmentioning

confidence: 99%

Accelerating image reconstruction in three-dimensional optoacoustic tomography on graphics processing units

et al. 2013

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“…[11,19]), which provides impressive image quality as shown in Figure 9(d). The image quality of our detector can be improved with the use of a deconvolution operation as is performed by several groups [49][50][51][52] regions. In such a case our detector is eminently suited to faithfully image a collection of small absorbing structures, which makes up the tumor mass.…”

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confidence: 99%

An optimized ultrasound detector for photoacoustic breast tomography

et al. 2013

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15Purpose: Photoacoustic imaging has proven to be able to detect vascularization-driven optical absorption contrast associated with tumors. In order to detect breast tumors located a few centimeter deep in tissue, a sensitive ultrasound detector is of crucial importance for photoacoustic mammography. Further, because the expected photoacoustic frequency bandwidth (a few MHz to tens of kHz) is inversely proportional to the dimensions of light absorbing structures (0.5 to 10+ 20 mm), proper choices of materials and their geometries and proper considerations in design have to be made to implement optimal photoacoustic detectors. In this study, we design and evaluate a specialized ultrasound detector for photoacoustic mammography.Methods: Based on the required detector sensitivity and its frequency response, a selection of active material and matching layers and their geometries is made leading to a functional detector

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“…The speed-of-sound was assumed to be constant and set at c 0 = 1.5 mm/µs. At each transducer, a data vector was formed by use of the C-D imaging model, 9 and therefore no inverse crime was committed. We calculated 600 equally spaced temporal samples over the interval [10,25) µs.…”

Section: Generation Of Pressure Datamentioning

confidence: 99%

Photoacoustic computed tomography without accurate ultrasonic transducer responses

et al. 2015

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Photoacoustic computed tomography (PACT) holds great promise for biomedical imaging. When the imaging system employs conventional piezoelectric ultrasonic transducers, the ideal photoacoustic (PA) signals are degraded by the transducers' acousto-electric impulse responses (EIRs) during the measurement process. If unaccounted for, this can degrade the accuracy of the reconstructed image. In principle, the effect of the EIRs on the measured PA signals can be ameliorated via deconvolution; images can be reconstructed subsequently by application of a reconstruction method that assumes an idealized EIR. Alternatively, the effect of the EIR can be incorporated into an imaging model and implicitly compensated for during reconstruction. In either case, the efficacy of the correction can be limited by errors in the assumed EIRs. In this work, a joint optimization approach to PACT image reconstruction is proposed for mitigating errors in reconstructed images that are caused by use of an inaccurate EIR. A variable projection method is employed to refine the measured EIR during the process of reconstructing the sought-after absorbed optical energy density. Computer-simulation and experimental studies are conducted to investigate the numerical properties of the method and demonstrate its value for mitigating image distortions and enhancing the visibility of fine structures.

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Investigation of iterative image reconstruction in three-dimensional optoacoustic tomography

Cited by 177 publications

References 49 publications

Accelerating image reconstruction in three-dimensional optoacoustic tomography on graphics processing units

Accelerating image reconstruction in three-dimensional optoacoustic tomography on graphics processing units

An optimized ultrasound detector for photoacoustic breast tomography

Photoacoustic computed tomography without accurate ultrasonic transducer responses

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