Large Cone Beam CT SCan Image Quality Improvement Using a Deep Learning U-Net Model

Joel Ruhe, Valeriu Codreanu, Pascal Wiggers

Research output: Contribution to conferencePaperAcademic

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Abstract

Cone beam CT scanners use much less radiation than to normal CT scans. However, compared to normal CT scans the images are noisy, showing several artifacts. The UNet Convolutional Neural Network may provide a way to reconstruct the a CT image from cone beam scans.
Original languageEnglish
Number of pages2
Publication statusPublished - 19 Nov 2020
EventBNAIC / BeneLearn 2020 - Leiden, Netherlands
Duration: 19 Nov 202020 Nov 2020
https://bnaic.liacs.leidenuniv.nl/

Conference

ConferenceBNAIC / BeneLearn 2020
Country/TerritoryNetherlands
CityLeiden
Period19/11/2020/11/20
Internet address

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