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Sparsity seeking total generalized variation for undersampled tomographic reconstruction

Kazantsev, D; Ovtchinnikov, E; Withers, PJ; Lionheart, WRB; Lee, PD; (2016) Sparsity seeking total generalized variation for undersampled tomographic reconstruction. In: (Proceedings) IEEE 13th International Symposium on Biomedical Imaging (ISBI). (pp. pp. 731-734). IEEE Green open access

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Abstract

Here we present a novel iterative approach for tomographic image reconstruction which improves image quality for undersampled and limited view projection measurements. Recently, the Total Generalized Variation (TGV) penalty has been proposed to establish a desirable balance between smooth and piecewise-constant solutions. Piecewise-smooth reconstructions are particularly important for biomedical applications, where the image surface slowly varies. The TGV penalty convexly combines the first and higher order derivatives, which means that for some regions (e.g. uniform background) it can be more challenging to find a sparser solution due to the weight of the higher order term. Therefore we propose a simple heuristic modification over the Chambolle-Pock reconstruction scheme for TGV which consists of adding the wavelet thresholding step which helps to suppress aliasing artifacts and noise while preserve piecewise-smooth appearance. Preliminary numerical results with two piecewise-smooth phantoms show strong improvement of the proposed method over TGV and TV penalties. The resulting images are smooth with sharp edges and fewer artifacts visible.

Type: Proceedings paper
Title: Sparsity seeking total generalized variation for undersampled tomographic reconstruction
Event: IEEE 13th International Symposium on Biomedical Imaging (ISBI)
Location: Prague, CZECH REPUBLIC
Dates: 13 April 2016 - 16 April 2016
ISBN-13: 978-1-4799-2350-2
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/ISBI.2016.7493370
Publisher version: https://doi.org/10.1109/ISBI.2016.7493370
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Science & Technology, Technology, Life Sciences & Biomedicine, Engineering, Biomedical, Radiology, Nuclear Medicine & Medical Imaging, Engineering, Iterative reconstruction, regularization, missing wedge, limited data, hard thresholding, wavelets
UCL classification: UCL
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UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Mechanical Engineering
URI: https://discovery.ucl.ac.uk/id/eprint/10049202
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