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Biomed Opt Express. 2014 Apr 2;5(5):1363-77. doi: 10.1364/BOE.5.001363. eCollection 2014.

Basis pursuit deconvolution for improving model-based reconstructed images in photoacoustic tomography.

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  • 1Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore, 560012 India.
  • 2Department of Electrical Engineering, Indian Institute of Science, Bangalore, 560012 India ; School of Chemical and Biomedical Engineering, Nanyang Technological University, 637457 Singapore ;
  • 3Supercomputer Education and Research Centre, Indian Institute of Science, Bangalore, 560012 India ;


The model-based image reconstruction approaches in photoacoustic tomography have a distinct advantage compared to traditional analytical methods for cases where limited data is available. These methods typically deploy Tikhonov based regularization scheme to reconstruct the initial pressure from the boundary acoustic data. The model-resolution for these cases represents the blur induced by the regularization scheme. A method that utilizes this blurring model and performs the basis pursuit deconvolution to improve the quantitative accuracy of the reconstructed photoacoustic image is proposed and shown to be superior compared to other traditional methods via three numerical experiments. Moreover, this deconvolution including the building of an approximate blur matrix is achieved via the Lanczos bidagonalization (least-squares QR) making this approach attractive in real-time.


(170.0170) Medical optics and biotechnology; (170.3010) Image reconstruction techniques; (170.5120) Photoacoustic imaging

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