Latest AI and machine learning research in radiology for healthcare professionals.
. Model based deep learning (MBDL) has been challenging to apply to the reconstruction of 3D non-Car...
Breast cancer is the most common form of cancer and is still the second leading cause of death for w...
Lung cancer is a common malignant tumor disease with high clinical disability and death rates. Curre...
OBJECTIVE: Advancements in computed tomography (CT) reconstruction have enabled image quality improv...
PURPOSE: The usage of iodinated contrast media (ICM) can improve the sensitivity and specificity of ...
BACKGROUND: Aortic stenosis (AS) is a common form of valvular heart disease, present in over 12% of ...
Cardiac magnetic resonance imaging (CMRI) is a non-invasive imaging technique to analyse the structu...
BACKGROUND: Magnetic resonance imaging scanner faults can be missed during routine quality assurance...
The purpose is to evaluate whether deep learning-based denoising (DLD) algorithm provides sufficient...
BACKGROUND: Assessment of cortical bone porosity and geometry by imaging in vivo can provide useful ...
The homodyned-K (HK) distribution model is a generalized backscatter envelope statistical model for ...
Artificial intelligence (AI) now enables automated interpretation of medical images. However, AI's p...
OBJECTIVE: To investigate the image quality and lesion conspicuity of a deep-learning-based contrast...
The purpose of this study is to test the feasibility for deep CNN-based artificial intelligence meth...
PURPOSE: This study aimed to develop a deep learning model for predicting distal aortic remodeling a...
PURPOSE: Brain MRI with high spatial resolution allows for a more detailed delineation of multiple s...
The visual inspection of coronary artery stenosis is known to be significantly affected by variation...
Generative models, such as DALL-E 2 (OpenAI), could represent promising future tools for image gener...
BACKGROUND: Collateral status is an important predictor for the outcome of acute ischemic stroke wit...
The aim of the study was to evaluate the impact of the newly developed Similar patient search (SPS) ...
The application of convolutional neural networks (CNNs) to MRI data has emerged as a promising appro...