In quantitative photoacoustic tomography (QPAT), distributions of optical parameters inside the target are reconstructed from photoacoustic images. In this work, we utilize the Monte Carlo (MC) method for light transport in the image reconstruction of QPAT. Modeling light transport accurately with the MC requires simulating a large number of photon packets, which can be computationally expensive. On the other hand, too low number of photon packets results in a high level of stochastic noise, which can lead to significant errors in reconstructed images. In this work, we use an adaptive approach, where the number of simulated photon packets is adjusted during an iterative image reconstruction. It is based on a norm test where the expected relative error of the minimization direction is controlled. The adaptive approach automatically determines the number of simulated photon packets to provide sufficiently accurate light transport modeling without unnecessary computational burden. The presented approach is studied with two-dimensional simulations.


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    Title :

    Image reconstruction in quantitative photoacoustic tomography using adaptive optical Monte Carlo


    Contributors:

    Conference:

    Photons Plus Ultrasound: Imaging and Sensing 2023 ; 2023 ; San Francisco,California,United States


    Published in:

    Proc. SPIE ; 12379


    Publication date :

    2023-03-09





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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