Paper
19 February 2018 3D quantitative photoacoustic image reconstruction using Monte Carlo method and linearization
Shinpei Okawa, Takeshi Hirasawa, Kazuhiro Tsujita, Toshihiro Kushibiki, Miya Ishihara
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Abstract
To quantify the functional and structural information of peripheral blood vessels for diagnoses of diseases which affects peripheral blood vessels such as diabetes and peripheral vascular disease, a 3D quantitative photoacoustic tomography (QPAT) reconstructing the optical properties such as the absorption coefficient reflecting microvascular structures and hemoglobin concentration and oxygenation saturation is studied. QPAT image reconstruction algorithms based on radiative transfer equation (RTE) and photon diffusion equation (PDE) have been proposed. However, it is not easy to use RTE in the clinical practice because of the huge computational load and long calculation time. On the other hand, it is always considered problematic to use PDE, because it does not approximate RTE well near the illuminating position. In this study, we developed the 3D QPAT image reconstruction using Monte Carlo (MC) method which approximates RTE better than PDE to reconstruct the optical properties in the region near the illuminating surface. To reduce the calculation time, we applied linearization. The QPAT image reconstruction algorithm with MC method and linearization was examined in numerical simulations and phantom experiment by use of a scanning system with a single probe consisting of P(VDF-TrFE) piezo electric film and optical fiber.
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Shinpei Okawa, Takeshi Hirasawa, Kazuhiro Tsujita, Toshihiro Kushibiki, and Miya Ishihara "3D quantitative photoacoustic image reconstruction using Monte Carlo method and linearization", Proc. SPIE 10494, Photons Plus Ultrasound: Imaging and Sensing 2018, 104944Y (19 February 2018); https://doi.org/10.1117/12.2293229
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Cited by 2 scholarly publications.
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KEYWORDS
Reconstruction algorithms

Monte Carlo methods

3D modeling

3D image reconstruction

Numerical simulations

Photoacoustic imaging

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