Robotic-assisted TKA (RATKA) is a rapidly emerging technique that has been shown to improve precision and accuracy in implant alignment in TKA. Robotic-assisted TKA (RATKA) uses computer software to create a three-dimensional model of the patient's k...
Journal of cardiovascular computed tomography
Mar 12, 2024
BACKGROUND: ECG-gated cardiac CT is now widely used in infants with congenital heart disease (CHD). Deep Learning Image Reconstruction (DLIR) could improve image quality while minimizing the radiation dose.
OBJECTIVES: In interventional bronchial artery embolization (BAE), periprocedural cone beam CT (CBCT) improves guiding and localization. However, a trade-off exists between 6-second runs (high radiation dose and motion artifacts, but low noise) and 3...
OBJECTIVE: The purpose of this study was to compare the accuracy and safety of robot-assisted (RA) cervical screw placement with conventional freehand (FH) technique.
OBJECTIVES: Cardiac computed tomography (CT) is essential in diagnosing coronary heart disease. However, a disadvantage is the associated radiation exposure to the patient which depends in part on the scan range. This study aimed to develop a deep ne...
Coronary computed tomography angiography (CCTA) is a medical imaging technique that produces detailed images of the coronary arteries. Our work focuses on the optimization of the prospectively ECG-triggered scan technique, which delivers the radiatio...
Accurate and precise positioning of the acetabular cup remains a prevalent challenge in total hip arthroplasty (THA). Robotic assistance for THA has increased over the past decade due to the potential to improve the accuracy of implant placement. How...
OBJECTIVES: The lung nodule volume determined by CT is used for nodule diagnoses and monitoring tumor responses to therapy. Increased image noise on low-dose CT degrades the measurement accuracy of the lung nodule volume. We compared the volumetric a...
BACKGROUND: To evaluate the performance of a Deep Learning Image Reconstruction (DLIR) algorithm in pediatric head CT for improving image quality and lesion detection with 0.625 mm thin-slice images.
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