Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Quantitative photoacoustic tomography is an emerging imaging technique aimed at estimating the distribution of optical parameters inside tissues from photoacoustic images, which are formed by combining optical information and ultrasonic propagation. This optical parameter estimation problem is ill-posed and needs to be approached within the framework of inverse problems. Photoacoustic images are three-dimensional and high-resolution. Furthermore, high-resolution reconstructions of the optical parameters are targeted. Therefore, in order to provide a practical method for quantitative photoacoustic tomography, the inversion algorithm needs to be able to perform successfully with problems of prominent size. In this work, an efficient approach for the inverse problem of quantitative photoacoustic tomography is proposed, assuming an edge-preferring prior for the optical parameters. The method is based on iteratively combining priorconditioned LSQR with a lagged diffusivity step and a linearization of the measu...
['Antti Hannukainen', 'Nuutti Hyvönen', 'Helle Majander', 'Tanja Tarvainen']
I am writing a research paper on a idea Efficient inclusion of total variation type priors in quantitative photoacoustic tomography
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