Latest AI and machine learning research in radiology for healthcare professionals.
BACKGROUND AND OBJECTIVE: Precisely segmenting brain tumors using multimodal Magnetic Resonance Imag...
PURPOSE: This study aimed to assess and externally validate the performance of a deep learning (DL) ...
We aimed to evaluate the image quality of brain computed tomography (CT) images reconstructed using ...
BACKGROUND: Interstitial lung diseases (ILD), such as idiopathic pulmonary fibrosis (IPF) and non-sp...
BACKGROUND: F-fluorodeoxyglucose (FDG) positron emission tomography (PET) is valuable for determini...
RATIONALE AND OBJECTIVES: To carry out radiomics analysis/deep convolutional neural network (CNN) ba...
Quantifying uncertainty of predictions has been identified as one way to develop more trustworthy ar...
The long acquisition time has limited the accessibility of magnetic resonance imaging (MRI) because ...
Low-rank technique has emerged as a powerful calibrationless alternative for parallel magnetic reson...
PURPOSE: Neuromelanin-sensitive MRI (NM-MRI) has proven useful for diagnosing Parkinson's disease (P...
OBJECTIVE: Scanning protocols for lung ultrasound often include 8 or more lung zones, which may limi...
PURPOSE: Accuracy of image-guided liver surgery is challenged by deformation of the liver during the...
Magnetic resonance (MR) and computer tomography (CT) images are two typical types of medical images ...
Subacromial motion metrics can be extracted from dynamic shoulder ultrasonography, which is useful f...
Traditional Chinese medicine (TCM) is the treasure of China, and the quality control of TCM is of cr...
Structured reporting may improve the radiological workflow and communication among physicians. Artif...
BACKGROUND: Segmentation of the Gross Tumor Volume (GTV) is a crucial step in the brachytherapy (BT)...
At present, MRI scans are typically performed inside fully enclosed radiofrequency (RF) shielding ro...
Optical coherence tomography (OCT) is a non-invasive optical imaging modality, which provides rapid,...
PURPOSE: To develop a deep learning method to synthesize conventional contrast-weighted images in th...
BACKGROUND: Double reading of screening mammograms is associated with a higher rate of screen-detect...