Journal of computer assisted tomography
May 20, 2022
PURPOSE: This study aimed to evaluate the feasibility of a deep learning method for imaging artifact and noise reduction in coronal reformation of contrast-enhanced chest computed tomography (CT).
Advanced materials (Deerfield Beach, Fla.)
May 16, 2022
Wearable respiratory monitoring is a fast, non-invasive, and convenient approach to provide early recognition of human health abnormalities like restrictive and obstructive lung diseases. Here, a computational fluid dynamics assisted on-mask sensor n...
Biomedical physics & engineering express
May 13, 2022
. Previous studies have proposed deep-learning techniques to reconstruct CT images from sinograms. However, these techniques employ large fully-connected (FC) layers for projection-to-image domain transformation, producing large models requiring subs...
Computer methods and programs in biomedicine
May 8, 2022
BACKGROUND AND OBJECTIVE: Low-dose computed tomography (LDCT) has become increasingly important for alleviating X-ray radiation damage. However, reducing the administered radiation dose may lead to degraded CT images with amplified mottle noise and n...
BACKGROUND: T2-weighted imaging (T2WI) is a key sequence of MRI studies of the pancreas. The single-shot fast spin echo (single-shot FSE) sequence is an accelerated form of T2WI. We hypothesized that denoising approach with deep learning-based recons...
Computational intelligence and neuroscience
Apr 25, 2022
Because of the nonlinearity and nonstationarity in the vibration signals of some rotating machinery, the analysis of these signals using conventional time- or frequency-domain methods has some drawbacks, and the results can be misleading. In this pap...
Computational and mathematical methods in medicine
Apr 19, 2022
The study focused on the diagnostic value of deep learning-based ultrasound combined with gastroscope examination for upper gastrointestinal submucous lesions and nursing. A total of 104 patients with upper gastrointestinal submucous lesions diagnose...
Low-field MRI scanners are significantly less expensive than their high-field counterparts, which gives them the potential to make MRI technology more accessible all around the world. In general, images acquired using low-field MRI scanners tend to b...
OBJECTIVE: This feasibility study aimed to use optimized virtual contrast enhancement through generative adversarial networks (GAN) to reduce the dose of iodine-based contrast medium (CM) during abdominal computed tomography (CT) in a large animal mo...
OBJECTIVES: To evaluate the diagnostic value of deep learning model (DLM) reconstructed dual-energy CT (DECT) low-keV virtual monoenergetic imaging (VMI) for assessing hypoenhancing hepatic metastases.
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.