Open Access
Joint reconstruction of initial pressure distribution and spatial distribution of acoustic properties of elastic media with application to transcranial photoacoustic tomography
Author(s) -
Joemini Poudel,
Mark A. Anastasio
Publication year - 2020
Publication title -
inverse problems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.003
H-Index - 119
eISSN - 1361-6420
pISSN - 0266-5611
DOI - 10.1088/1361-6420/abc7ce
Subject(s) - tomography , iterative reconstruction , inverse problem , regularization (linguistics) , acoustics , projection (relational algebra) , photoacoustic tomography , computer science , computer vision , mathematics , optics , artificial intelligence , algorithm , physics , mathematical analysis
Photoacoustic computed tomography (PACT) is an emerging computed imaging modality that exploits optical contrast and ultrasonic detection principles to form images of the photoacoustically induced initial pressure distribution within tissue. The PACT reconstruction problem corresponds to a time-domain inverse source problem, where the initial pressure distribution is recovered from the measurements recorded on an aperture outside the support of the source. A major challenge in transcranial PACT brain imaging is to compensate for aberrations in the measured acoustic data that are induced by propagation of the photoacoustic wavefields through the skull. To properly account for these effects, previously proposed image reconstruction methods for transcranial PACT require knowledge of the spatial distribution of the elastic parameters of the skull. However, estimating the spatial distribution of these parameters prior to the PACT experiment remains challenging. To circumvent this issue, in this work a method to jointly reconstruct the initial pressure distribution and a low-dimensional representation of the elastic parameters of the skull is developed and investigated. The joint reconstruction (JR) problem is solved by use of a proximal optimization method that allows constraints and non-smooth regularization terms. The proposed method is evaluated by use of large-scale three-dimensional (3D) computer-simulation studies that mimic transcranial PACT experiments.