Low-dose liver CT: image quality and diagnostic accuracy of deep learning image reconstruction algorithm.

Damiano CarusoDomenico De SantisAntonella Del GaudioGisella GuidoMarta ZerunianMichela PoliciDaniela ValanzuoloDominga PuglieseRaffaello PersechinoAntonio CremonaLuca BarbatoAndrea CaloisiElsa IannicelliAndrea Laghi

Published in: European radiology (2023)

• Iterative reconstruction algorithm impacts image texture, with negative effects on diagnostic capabilities. • Medium-strength deep learning image reconstruction algorithm outperforms iterative reconstruction in the diagnostic accuracy of ≤ 0.5 cm hypovascular liver lesions (93.9% vs 78.8%), also granting higher objective and subjective image quality. • Deep learning image reconstruction algorithm can be safely implemented in routine abdominal CT protocols in place of iterative reconstruction.

Keyphrases

deep learning
image quality
computed tomography
dual energy
artificial intelligence
convolutional neural network
machine learning
low dose
positron emission tomography
physical activity
depressive symptoms
magnetic resonance
pet ct
neural network
sleep quality