Deep learning image denoising in PET : quantitative impact on kinetic modelling and clinical metrics
- Author
- Florence Marie Muller (UGent) , Elizabeth J. Li, Min Gao, Austin R. Pantel, Michael J. Parma, Suleman Surti, Christian Vanhove (UGent) , Stefaan Vandenberghe (UGent) , Margaret E. Daube-Witherspoon and Joel S. Karp
- Organization
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Citation
Please use this url to cite or link to this publication: http://hdl.handle.net/1854/LU-01H2KBJS4D3PDEC56Z3EX7C3Y5
- MLA
- Muller, Florence Marie, et al. “Deep Learning Image Denoising in PET : Quantitative Impact on Kinetic Modelling and Clinical Metrics.” Pendergrass Research Symposium, Abstracts, 2023.
- APA
- Muller, F. M., Li, E. J., Gao, M., Pantel, A. R., Parma, M. J., Surti, S., … Karp, J. S. (2023). Deep learning image denoising in PET : quantitative impact on kinetic modelling and clinical metrics. Pendergrass Research Symposium, Abstracts. Presented at the Pendergrass Research Symposium, Philadelphia, Pennsylvania.
- Chicago author-date
- Muller, Florence Marie, Elizabeth J. Li, Min Gao, Austin R. Pantel, Michael J. Parma, Suleman Surti, Christian Vanhove, Stefaan Vandenberghe, Margaret E. Daube-Witherspoon, and Joel S. Karp. 2023. “Deep Learning Image Denoising in PET : Quantitative Impact on Kinetic Modelling and Clinical Metrics.” In Pendergrass Research Symposium, Abstracts.
- Chicago author-date (all authors)
- Muller, Florence Marie, Elizabeth J. Li, Min Gao, Austin R. Pantel, Michael J. Parma, Suleman Surti, Christian Vanhove, Stefaan Vandenberghe, Margaret E. Daube-Witherspoon, and Joel S. Karp. 2023. “Deep Learning Image Denoising in PET : Quantitative Impact on Kinetic Modelling and Clinical Metrics.” In Pendergrass Research Symposium, Abstracts.
- Vancouver
- 1.Muller FM, Li EJ, Gao M, Pantel AR, Parma MJ, Surti S, et al. Deep learning image denoising in PET : quantitative impact on kinetic modelling and clinical metrics. In: Pendergrass Research Symposium, Abstracts. 2023.
- IEEE
- [1]F. M. Muller et al., “Deep learning image denoising in PET : quantitative impact on kinetic modelling and clinical metrics,” in Pendergrass Research Symposium, Abstracts, Philadelphia, Pennsylvania, 2023.
@inproceedings{01H2KBJS4D3PDEC56Z3EX7C3Y5,
author = {{Muller, Florence Marie and Li, Elizabeth J. and Gao, Min and Pantel, Austin R. and Parma, Michael J. and Surti, Suleman and Vanhove, Christian and Vandenberghe, Stefaan and Daube-Witherspoon, Margaret E. and Karp, Joel S.}},
booktitle = {{Pendergrass Research Symposium, Abstracts}},
language = {{eng}},
location = {{Philadelphia, Pennsylvania}},
pages = {{1}},
title = {{Deep learning image denoising in PET : quantitative impact on kinetic modelling and clinical metrics}},
year = {{2023}},
}