PET reconstruction with non-smooth gradient-based priors

Schramm G, Holler M, Koesters T, Boada F, Knoll F, Bredies K, Nuyts J (2017)


Publication Type: Conference contribution

Publication year: 2017

Publisher: Institute of Electrical and Electronics Engineers Inc.

Book Volume: 2017-January

Conference Proceedings Title: 2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop, NSS/MIC/RTSD 2016

Event location: Strasbourg, FRA

ISBN: 9781509016426

DOI: 10.1109/NSSMIC.2016.8069447

Abstract

Quantitative PET imaging is hindered by limited spatial resolution and high Poisson noise. A way to overcome those limitations, especially in brain PET/MR examinations, is the inclusion of anatomical prior knowledge in the image reconstruction process. Recently, the concept of Parallel Level Sets (PLS) [1]-[3] has been introduced as a promising anatomical prior for PET reconstruction. This prior relies on the exchange of gradient information. However, PLS is a non-smooth function which hampers the optimization process in iterative reconstruction. In this proceeding we show how to use the EM-TV algorithm by Sawatzki et al. [4] to solve the non-smooth PLS-regularized PET reconstruction problem efficiently which enables application to 3D clinical PET data.

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How to cite

APA:

Schramm, G., Holler, M., Koesters, T., Boada, F., Knoll, F., Bredies, K., & Nuyts, J. (2017). PET reconstruction with non-smooth gradient-based priors. In 2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop, NSS/MIC/RTSD 2016. Strasbourg, FRA: Institute of Electrical and Electronics Engineers Inc..

MLA:

Schramm, G., et al. "PET reconstruction with non-smooth gradient-based priors." Proceedings of the 2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop, NSS/MIC/RTSD 2016, Strasbourg, FRA Institute of Electrical and Electronics Engineers Inc., 2017.

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