Versatile regularisation toolkit for iterative image reconstruction with proximal splitting algorithms

Daniil Kazantsev; Edoardo Pasca; Mark Basham; Martin Turner; Matthias J. Ehrhardt; Kris Thielemans; Benjamin A. Thomas; Evgueni Ovtchinnikov; Philip J. Withers; Alun W. Ashton

doi:10.1117/12.2534289

Versatile regularisation toolkit for iterative image reconstruction with proximal splitting algorithms

Daniil Kazantsev, Edoardo Pasca, Mark Basham, Martin Turner, Matthias J. Ehrhardt, Kris Thielemans, Benjamin A. Thomas, Evgueni Ovtchinnikov, Philip J. Withers, Alun W. Ashton

Institute for Mathematical Innovation (IMI)

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

1 Citation (SciVal)

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).

Original language	English
Title of host publication	15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine
Editors	Samuel Matej, Scott D. Metzler
Place of Publication	U. S. A.
Publisher	SPIE
Pages	1-6
Number of pages	6
ISBN (Electronic)	9781510628373
DOIs	https://doi.org/10.1117/12.2534289
Publication status	Published - 28 May 2019
Event	15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Fully3D 2019 - Philadelphia, USA United States Duration: 2 Jun 2019 → 6 Jun 2019

Publication series

Name	Proceedings of SPIE - The International Society for Optical Engineering
Volume	11072
ISSN (Print)	0277-786X
ISSN (Electronic)	1996-756X

Conference

Conference	15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Fully3D 2019
Country/Territory	USA United States
City	Philadelphia
Period	2/06/19 → 6/06/19

Funding

This work has been partly funded by the Collabora-tive Computational Project (CCP) in Tomographic Imaging (CCPi) (EP/M022498/1, EP/P02226X/1) and CCP PET-MRI (EP/M022587/1). The authors acknowledge facilities and the support provided by the Research Complex at Harwell and Diamond Light Source. This work made use of computational support by CoSeC, the Computational Science Centre for Research Communities, through CCPi and CCP PET-MR.

Keywords

Iterative methods
Model-based
PET
Proximal-dual
Regularization
X-ray CT

ASJC Scopus subject areas

Electronic, Optical and Magnetic Materials
Condensed Matter Physics
Computer Science Applications
Applied Mathematics
Electrical and Electronic Engineering

Access to Document

10.1117/12.2534289

Cite this

Kazantsev, D., Pasca, E., Basham, M., Turner, M., Ehrhardt, M. J., Thielemans, K., Thomas, B. A., Ovtchinnikov, E., Withers, P. J., & Ashton, A. W. (2019). Versatile regularisation toolkit for iterative image reconstruction with proximal splitting algorithms. In S. Matej, & S. D. Metzler (Eds.), 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine (pp. 1-6). Article 110722D (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11072). SPIE. https://doi.org/10.1117/12.2534289

Versatile regularisation toolkit for iterative image reconstruction with proximal splitting algorithms. / Kazantsev, Daniil; Pasca, Edoardo; Basham, Mark et al.
15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine. ed. / Samuel Matej; Scott D. Metzler. U. S. A.: SPIE, 2019. p. 1-6 110722D (Proceedings of SPIE - The International Society for Optical Engineering; Vol. 11072).

Research output: Chapter or section in a book/report/conference proceeding › Chapter in a published conference proceeding

Kazantsev, D, Pasca, E, Basham, M, Turner, M, Ehrhardt, MJ, Thielemans, K, Thomas, BA, Ovtchinnikov, E, Withers, PJ & Ashton, AW 2019, Versatile regularisation toolkit for iterative image reconstruction with proximal splitting algorithms. in S Matej & SD Metzler (eds), 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine., 110722D, Proceedings of SPIE - The International Society for Optical Engineering, vol. 11072, SPIE, U. S. A., pp. 1-6, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine, Fully3D 2019, Philadelphia, USA United States, 2/06/19. https://doi.org/10.1117/12.2534289

Kazantsev D, Pasca E, Basham M, Turner M, Ehrhardt MJ, Thielemans K et al. Versatile regularisation toolkit for iterative image reconstruction with proximal splitting algorithms. In Matej S, Metzler SD, editors, 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine. U. S. A.: SPIE. 2019. p. 1-6. 110722D. (Proceedings of SPIE - The International Society for Optical Engineering). doi: 10.1117/12.2534289

Kazantsev, Daniil ; Pasca, Edoardo ; Basham, Mark et al. / Versatile regularisation toolkit for iterative image reconstruction with proximal splitting algorithms. 15th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine. editor / Samuel Matej ; Scott D. Metzler. U. S. A. : SPIE, 2019. pp. 1-6 (Proceedings of SPIE - The International Society for Optical Engineering).

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Versatile regularisation toolkit for iterative image reconstruction with proximal splitting algorithms

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