The growing demand for head magnetic resonance imaging (MRI) examinations, along with a global shortage of radiologists, has led to an increase in the time taken to report head MRI scans in recent years. For many neurological conditions, this delay c...
In MRI, deep neural networks have been proposed to reconstruct diffusion model parameters. However, the inputs of the networks were designed for a specific diffusion gradient scheme (i.e., diffusion gradient directions and numbers) and a specific b-v...
Background Deep learning reconstruction (DLR) may improve image quality. However, its impact on diffusion-weighted imaging (DWI) of the prostate has yet to be assessed. Purpose To determine whether DLR can improve image quality of diffusion-weighted ...
PURPOSE: While advanced diffusion techniques have been found valuable in many studies, their clinical availability has been hampered partly due to their long scan times. Moreover, each diffusion technique can only extract a few relevant microstructur...
Convolutional neural networks have achieved state-of-the-art performance for white matterĀ (WM) tract segmentation based on diffusion magnetic resonance imaging (dMRI). However, the segmentation can still be difficult for challenging WM tracts with th...
Journal of magnetic resonance imaging : JMRI
Jan 22, 2022
BACKGROUND: Dynamic-exponential intravoxel incoherent motion (IVIM) imaging is a potential technique for prediction, monitoring, and differential diagnosis of hepatic diseases, especially liver tumors. However, the use of such technique at voxel leve...
PURPOSE: To develop a machine-learning-based radiomics signature of ADC for discriminating between benign and malignant testicular masses and compare its classification performance with that of minimum and mean ADC.
PURPOSE: We introduce and validate an artificial intelligence (AI)-accelerated multi-shot echo-planar imaging (msEPI)-based method that provides T1w, T2w, , T2-FLAIR, and DWI images with high SNR, high tissue contrast, low specific absorption rates ...