Deianira Pedoto, Riccardo Troncone, Margherita Massitti, Luigi Greco, Renata Auricchio
Adherence to Gluten-Free Diet in Coeliac Paediatric Patients Assessed through a Questionnaire Positively Influences Growth and Quality of Life
Nutrients
evaluate effect vendoragnostic deep learning denoising dld algorithm diagnostic image quality noncontrast cranial computed tomography ncct across five ct scannersthis retrospective singlecenter study included ncct data 150 consecutive patients 30 five scanners undergone routine imaging minor head trauma images reconstructed using filtered back projection fbp vendoragnostic dld method using 4point likert scale three readers performed subjective evaluation assessing following quality criteria overall diagnostic image quality image noise gray matterwhite matter differentiation gmwm artifacts sharpness diagnostic confidence objective analysis included evaluation noise contrasttonoise ratio cnr signaltonoise ratio snr artifact index posterior fossain subjective image quality assessment dld showed constantly superior results compared fbp categories scanners p005 across readers objective image quality analysis showed significant improvement noise snr cnr well artifact index using dld scanners p0001the vendoragnostic deep learning denoising algorithm provided significantly superior results subjective well objective analysis ncct images patients minor head trauma concerning parameters compared fbp reconstruction effect observed five included scanners significant improvement image quality 5 scanners due vendoragnostic dld subjects patients routine imaging minor head trauma reduction artifacts posterior fossa due dld access improved image quality even older scanners different vendors kapper c mller l kronfeld et al value vendoragnostic deep learning image denoising brain computed tomography multiscanner study fortschr rntgenstr 2024 doi 101055a22904781