Kazantsev, D;
Pasca, E;
Basham, M;
Turner, M;
Ehrhardt, MJ;
Thielemans, K;
Thomas, BA;
... Ashton, AW; + view all
(2019)
Versatile regularisation toolkit for iterative image reconstruction with proximal splitting algorithms.
In:
Proceedings of SPIE - The International Society for Optical Engineering.
SPIE: Philadelphia, United States.
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Abstract
Ill-posed image recovery requires regularisation to ensure stability. The presented open-source regularisation toolkit consists of state-of-the-art variational algorithms which can be embedded in a plug-and-play fashion into the general framework of proximal splitting methods. The packaged regularisers aim to satisfy various prior expectations of the investigated objects, e.g., their structural characteristics, smooth or non-smooth surface morphology. The flexibility of the toolkit helps with the design of more advanced model-based iterative reconstruction methods for different imaging modalities while operating with simpler building blocks. The toolkit is written for CPU and GPU architectures and wrapped for Python/MATLAB. We demonstrate the functionality of the toolkit in application to Positron Emission Tomography (PET) and X-ray synchrotron computed tomography (CT).
| Type: | Proceedings paper |
|---|---|
| Title: | Versatile regularisation toolkit for iterative image reconstruction with proximal splitting algorithms |
| Event: | Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, 2019 |
| ISBN-13: | 9781510628373 |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1117/12.2534289 |
| Publisher version: | https://doi.org/10.1117/12.2534289 |
| Language: | English |
| Additional information: | This version is the version of record. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | X-ray CT, PET, iterative methods, model-based, proximal-dual, regularization. |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Department of Imaging |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10085809 |
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