PURPOSE: CT is routinely used to detect cranial abnormalities in pediatric patients with head trauma or craniosynostosis. This study aimed to develop a deep learning method to synthesize pseudo-CT (pCT) images for MR high-resolution pediatric cranial...
PURPOSE: To investigate whether the image quality of a specific deep learning-based synthetic CT (sCT) of the cervical spine is noninferior to conventional CT.
We report the use of robot assistance for computed tomography-guided celiac plexus neurolysis for the first time. Four patients of upper abdominal cancer with intractable pain despite opioids were positioned prone on the PET-computed tomography sca...
The characteristics of bone fragments are the main influencing factors for the choice of treatment in intertrochanteric fractures. This study aimed to develop a deep learning algorithm for recognizing and segmenting individual fragments in CT images ...
Arteriosclerosis, thrombosis, and vascular biology
Jun 16, 2022
BACKGROUND: Coronary calcification associates closely with cardiovascular risk, but its progress is accelerated in response to some interventions widely used to reduce risk. This paradox suggests that qualitative, not just quantitative, changes in ca...
Segmenting liver from CT images is the first step for doctors to diagnose a patient's disease. Processing medical images with deep learning models has become a current research trend. Although it can automate segmenting region of interest of medical ...
Computational and mathematical methods in medicine
Jun 16, 2022
Image reconstruction in magnetic resonance imaging (MRI) and computed tomography (CT) is a mathematical process that generates images at many different angles around the patient. Image reconstruction has a fundamental impact on image quality. In rece...
Computational intelligence and neuroscience
Jun 16, 2022
The objective of this research was to investigate the application value of deep learning-based computed tomography (CT) images in the diagnosis of liver tumors. Fifty-eight patients with liver tumors were selected, and their CT images were segmented ...
AJR. American journal of roentgenology
Jun 15, 2022
Deep learning-based convolutional neural networks have enabled major advances in development of artificial intelligence (AI) software applications. Modern AI applications offer comprehensive multiorgan evaluation. The purpose of this article was to...
OBJECTIVE: To investigate clinical applicability of deep learning(DL)-based reconstruction of virtual monoenergetic images(VMIs) of arterial phase liver CT obtained by rapid kVp-switching dual-energy CT for evaluation of hypervascular liver lesions.
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