Convolutional neural networks for improving image quality with noisy PET data

GOAL: PET is a relatively noisy process compared to other imaging modalities, and sparsity of acquisition data leads to noise in the images. Recent work has focused on machine learning techniques to improve PET images, and this study investigates a deep learning approach to improve the quality of re...

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Bibliographische Detailangaben
Veröffentlicht in:EJNMMI Res
Hauptverfasser: Schaefferkoetter, Josh, Yan, Jianhua, Ortega, Claudia, Sertic, Andrew, Lechtman, Eli, Eshet, Yael, Metser, Ur, Veit-Haibach, Patrick
Format: Artigo
Sprache:Inglês
Veröffentlicht: Springer Berlin Heidelberg 2020
Schlagworte:
Original Research
Online Zugang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7505915/
https://ncbi.nlm.nih.gov/pubmed/32955669
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s13550-020-00695-1
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