There is little evidence on the applicability of deep learning (DL) in the segmentation of acute ischemic lesions on diffusion-weighted imaging (DWI) between magnetic resonance imaging (MRI) scanners of different manufacturers. We retrospectively inc...
PURPOSE: Earlier work showed that IVIM-NET , an unsupervised physics-informed deep neural network, was faster and more accurate than other state-of-the-art intravoxel-incoherent motion (IVIM) fitting approaches to diffusion-weighted imaging (DWI). Th...
This study was to explore the application value of magnetic resonance imaging (MRI) image reconstruction model based on complex convolutional neural network (CCNN) in the diagnosis and prognosis of cerebral infarction. Two image reconstruction method...
Our study investigated the feasibility and clinical relevance of brain age prediction using axial T2-weighted images (T2-WIs) with a deep convolutional neural network (CNN) algorithm. The CNN model was trained by 1,530 scans in our institution. The p...
Super-resolvedq-space deep learning (SR-q-DL) has been developed to estimate high-resolution (HR) tissue microstructure maps from low-quality diffusion magnetic resonance imaging (dMRI) scans acquired with a reduced number of diffusion gradients and ...
The accuracy in diagnosing prostate cancer (PCa) has increased with the development of multiparametric magnetic resonance imaging (mpMRI). Biparametric magnetic resonance imaging (bpMRI) was found to have a diagnostic accuracy comparable to mpMRI in ...
This work presents a single-step deep-learning framework for longitudinal image analysis, coined Segis-Net. To optimally exploit information available in longitudinal data, this method concurrently learns a multi-class segmentation and nonlinear regi...
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Mar 27, 2021
PURPOSE: To explore a new approach mainly based on deep learning residual network (ResNet) to detect infarct cores on non-contrast CT images and improve the accuracy of acute ischemic stroke diagnosis.
AJNR. American journal of neuroradiology
Mar 25, 2021
BACKGROUND AND PURPOSE: In acute stroke patients with large vessel occlusions, it would be helpful to be able to predict the difference in the size and location of the final infarct based on the outcome of reperfusion therapy. Our aim was to demonstr...
Segmentation of brain tissue types from diffusion MRI (dMRI) is an important task, required for quantification of brain microstructure and for improving tractography. Current dMRI segmentation is mostly based on anatomical MRI (e.g., T1- and T2-weigh...