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      Joint Reconstruction of Absorbed Optical Energy Density and Sound Speed Distributions in Photoacoustic Computed Tomography: A Numerical Investigation

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          Abstract

          <p class="first" id="P1">Photoacoustic computed tomography (PACT) is a rapidly emerging bioimaging modality that seeks to reconstruct an estimate of the absorbed optical energy density within an object. Conventional PACT image reconstruction methods assume a constant speed-of-sound (SOS), which can result in image artifacts when acoustic aberrations are significant. It has been demonstrated that incorporating knowledge of an object’s SOS distribution into a PACT image reconstruction method can improve image quality. However, in many cases, the SOS distribution cannot be accurately and/or conveniently estimated prior to the PACT experiment. Because variations in the SOS distribution induce aberrations in the measured photoacoustic wavefields, certain information regarding an object’s SOS distribution is encoded in the PACT measurement data. Based on this observation, a joint reconstruction (JR) problem has been proposed in which the SOS distribution is concurrently estimated along with the sought-after absorbed optical energy density from the photoacoustic measurement data. A broad understanding of the extent to which the JR problem can be accurately and reliably solved has not been reported. In this work, a series of numerical experiments is described that elucidate some important properties of the JR problem that pertain to its practical feasibility. To accomplish this, an optimization-based formulation of the JR problem is developed that yields a non-linear iterative algorithm that alternatively updates the two image estimates. Heuristic analytic insights into the reconstruction problem are also provided. These results confirm the ill-conditioned nature of the joint reconstruction problem that will present significant challenges for practical applications. </p>

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          Author and article information

          Journal
          IEEE Transactions on Computational Imaging
          IEEE Trans. Comput. Imaging
          Institute of Electrical and Electronics Engineers (IEEE)
          2333-9403
          2334-0118
          June 2016
          June 2016
          : 2
          : 2
          : 136-149
          Article
          10.1109/TCI.2016.2523427
          5693255
          29152545
          b6f85a15-c1ed-4015-b63b-ed2dfcdc5232
          © 2016
          History

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