Weighted model‐based optoacoustic reconstruction for partial‐view geometries

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Abstract
Acoustic heterogeneities in biological samples are known to cause artifacts in tomographic optoacoustic (photoacoustic) image reconstruction. A statistical weighted model‐based reconstruction approach was previously introduced to mitigate such artifacts. However, this approach does not reliably provide high‐quality reconstructions for partial‐view imaging systems, which are common in preclinical and clinical optoacoustics. In this article, the capability of the weighted model‐based algorithm is extended to generate optoacoustic reconstructions with less distortions for partial‐view geometry data. This is achieved by manipulating the weighting scheme based on the detector geometry. Using partial‐view optoacoustic tomography data from a tissue‐mimicking phantom containing a strong acoustic reflector, tumors grafted onto mice, and a mouse brain with intact skull, the proposed partial‐view‐corrected weighted model‐based algorithm is shown to mitigate reflection artifacts in reconstructed images without distorting structures or boundaries, compared with both conventional model‐based and the weighted model‐based algorithms. It is also demonstrated that the partial‐view‐corrected weighted model‐based algorithm has the additional advantage of suppressing streaking artifacts due to the partial‐view geometry itself in the presence of a very strong optoacoustic chromophore. Due to its enhanced performance, the partial‐view‐corrected weighted model‐based algorithm may prove useful for improving the quality of partial‐view multispectral optoacoustic tomography, leading to enhanced visualization of functional parameters such as tissue oxygenation.
Funding Information
  • Alexander von Humboldt-Stiftung
  • FP7 People: Marie-Curie Actions (605162)
  • Horizon 2020 Framework Programme (694968)

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