Basis pursuit deconvolution for improving model-based reconstructed images in photoacoustic tomography
Raju, Aditi Subramani
Shaw, Calvin B.
Yalavarthy, Phaneendra K.
Date of Issue2014
School of Chemical and Biomedical Engineering
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.
Biomedical optics express
© 2014 Optical Society of America. This paper was published in Biomedical optics express and is made available as an electronic reprint (preprint) with permission of Optical Society of America. The paper can be found at the following official DOI: [http://dx.doi.org/10.1364/BOE.5.001363]. One print or electronic copy may be made for personal use only. Systematic or multiple reproduction, distribution to multiple locations via electronic or other means, duplication of any material in this paper for a fee or for commercial purposes, or modification of the content of the paper is prohibited and is subject to penalties under law.