13 March 2017 Simulation of photoacoustic tomography (PAT) system in COMSOL and comparison of two popular reconstruction techniques
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Abstract
Photoacoustic imaging is a molecular cum functional imaging modality based on differential optical absorption of the incident laser pulse by the endogeneous tissue chromophores. Several numerical simulations and finite element models have been developed in the past to describe and study Photoacoustic (PA) signal generation principles and study the effect of variation in PA parameters. Most of these simulation work concentrate on analyzing extracted 1D PA signals and each of them mostly describe only few of the building blocks of a Photoacoustic Tomography (PAT) imaging system. Papers describing simulation of the entire PAT system in one simulation platform, along with reconstruction is seemingly rare. This study attempts to describe how a commercially available Finite Element software (COMSOL(R)), can serve as a single platform for simulating PAT that couples the electromagnetic, thermodynamic and acoustic pressure physics involved in PA phenomena. Further, an array of detector elements placed at the boundary in the FE model can provide acoustic pressure data that can be exported to Matlab(R) to perform tomographic image reconstruction. The performance of two most commonly used image reconstruction techniques; namely, Filtered Backprojection (FBP) and Synthetic Aperture (SA) beamforming are compared. Results obtained showed that the lateral resolution obtained using FBP vs. SA largely depends on the aperture parameters. FBP reconstruction was able to provide a slightly better lateral resolution for smaller aperture while SA worked better for larger aperture. This interesting effect is currently being investigated further. Computationally FBP was faster, but it had artifacts along the spherical shell on which the data is projected.
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Sowmiya C., Arun K. Thittai, "Simulation of photoacoustic tomography (PAT) system in COMSOL and comparison of two popular reconstruction techniques", Proc. SPIE 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging, 101371O (13 March 2017); doi: 10.1117/12.2254450; https://doi.org/10.1117/12.2254450
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