AI Denoising Improves Image Quality and Radiological Workflows in Pediatric Ultra-Low-Dose Thorax Computed Tomography Scans

(1) This study evaluates the impact of an AI denoising algorithm on image quality, diagnostic accuracy, and radiological workflows in pediatric chest ultra-low-dose CT (ULDCT). (2) Methods: 100 consecutive pediatric thorax ULDCT were included and reconstructed using weighted filtered back projection...

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Detalles Bibliográficos
Autores principales: Brendlin, Andreas S., Schmid, Ulrich, Plajer, David, Chaika, Maryanna, Mader, Markus, Wrazidlo, Robin, Männlin, Simon, Spogis, Jakob, Estler, Arne, Esser, Michael, Schäfer, Jürgen, Afat, Saif, Tsiflikas, Ilias
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9326759/
https://www.ncbi.nlm.nih.gov/pubmed/35894005
http://dx.doi.org/10.3390/tomography8040140

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9326759/
https://www.ncbi.nlm.nih.gov/pubmed/35894005
http://dx.doi.org/10.3390/tomography8040140

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