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Alternating total variation minimisation for PET reconstruction

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We present a novel reconstruction technique for image reconstruction in positron emission tomography (PET). This technique provides an effective combination of accurately inverting the Radon transform and of implementing an appropriate regularisation for noise removal. In contrast to the majority of existing algorithms which apply denoising to the reconstructed image, our work applies a regularisation both in the measurement and the image space. For this task we use an alternating total variation algorithm. This is joint work with P. E. Barbano and T. Fokas.

This talk is part of the Isaac Newton Institute Seminar Series series.

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