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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Detalles Bibliográficos
Autores principales: Schaefferkoetter, Josh, Yan, Jianhua, Ortega, Claudia, Sertic, Andrew, Lechtman, Eli, Eshet, Yael, Metser, Ur, Veit-Haibach, Patrick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2020
Materias:
Original Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7505915/
https://www.ncbi.nlm.nih.gov/pubmed/32955669
http://dx.doi.org/10.1186/s13550-020-00695-1

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7505915/
https://www.ncbi.nlm.nih.gov/pubmed/32955669
http://dx.doi.org/10.1186/s13550-020-00695-1

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