Deep learning reconstruction algorithm and high-concentration contrast medium: feasibility of a double-low protocol in coronary computed tomography angiography.
Damiano CarusoDomenico De SantisGiuseppe TremamunnoCurzio SantangeliTiziano PolidoriGiovanna G BonaMarta ZerunianAntonella Del GaudioLuca PuglieseAndrea LaghiPublished in: European radiology (2024)
Minimizing the radiation and contrast medium dose while maintaining CT image quality is highly desirable. High-strength deep learning iterative reconstruction protocol yielded 42% radiation dose reduction compared to conventional protocol. "Double-low" coronary CTA is feasible with high-strength deep learning reconstruction without compromising image quality in non-obese patients.
Keyphrases
- image quality
- deep learning
- computed tomography
- obese patients
- dual energy
- randomized controlled trial
- artificial intelligence
- convolutional neural network
- bariatric surgery
- machine learning
- coronary artery disease
- coronary artery
- magnetic resonance
- roux en y gastric bypass
- positron emission tomography
- magnetic resonance imaging
- radiation induced
- neural network