Deep Learning Algorithm-Reconstructed Triple-Rule-Out CT: Image Quality and Performance in Evaluating Coronary Lumen Stenosis.

Feasibility of deep learning reconstruction algorithm combined with the "ultra triple-low" protocol at 60 kVp in CTPA: An image quality and radiation dose assessment.

PURPOSE To evaluate the feasibility of a deep learning-based reconstruction algorithm (Clear Infinity, CI) combined with an "ultra triple-low" protocol (60 kVp, 10 ml iodine contrast, 2.5 ml/s) for pulmonary CT angiography (CTPA). METHOD Seventy patients (body mass index (BMI) < 28 kg/m2) were randomised to Group A (...

Application of 80 kVp combined with deep learning reconstruction algorithm in overweight patients coronary CT angiography: reduced radiation dose and contrast agent dose

Background Coronary CT angiography (CCTA) has become a key imaging technique for clinical screening of coronary artery disease (CAD). Overweight patients have a higher prevalence of CAD, however, they face increased risks of radiation exposure and contrast-induced nephropathy during CCTA examinations. This study aimed...

Evaluation of deep-learning iterative reconstruction combined with high-frequency kernels in CT: a task-based image quality study

DLIR combined with high-frequency kernels reduced image noise while preserving spatial resolution and FBP-like noise texture, outperforming IR in detectability for most lesion sizes, concentrations, and dose levels.

Feasibility of reducing radiation dose and contrast dose while improving image quality in dual-energy CT pulmonary angiography : Use of low-energy virtual monochromatic images with deep learning image reconstruction algorithm.

Improved virtual non-contrast images in liver dual-energy CT with deep learning algorithm for image reconstruction.

Improved upper abdominal MRI with VIBE sequences using deep learning-supported k-space sampling in a cohort undergoing MRI for gynecologic diseases.

DL VIBE improves image quality and reduces artifacts, particularly in NC imaging, particularly in NC imaging.