AIMC Topic: Magnetic Resonance Angiography
Clear Filters Showing 51 to 60 of 112 articles
Deep Learning-Based Magnetic Resonance Imaging in Diagnosis and Treatment of Intracranial Aneurysm.
Computational and mathematical methods in medicine
Jun 13, 2022
This study was focused on the positioning of the intracranial aneurysm in the magnetic resonance imaging (MRI) images using the deep learning-based U-Net model, to realize the computer-aided diagnosis of the intracranial aneurysm. First, a network wa...
High relaxivity Gd-based organic nanoparticles for efficient magnetic resonance angiography.
Journal of nanobiotechnology
Mar 31, 2022
Contrast-enhanced MR angiography (MRA) is a critical technique for vascular imaging. Nevertheless, the efficacy of MRA is often limited by the low rate of relaxation, short blood-circulation time, and metal ion-released potential long-term toxicity o...
Dense, deep learning-based intracranial aneurysm detection on TOF MRI using two-stage regularized U-Net.
Journal of neuroradiology = Journal de neuroradiologie
Mar 17, 2022
BACKGROUND AND PURPOSE: The prevalence of unruptured intracranial aneurysms in the general population is high and aneurysms are usually asymptomatic. Their diagnosis is often fortuitous on MRI and might be difficult and time consuming for the radiolo...
Quantitative Analysis of DCE and DSC-MRI: From Kinetic Modeling to Deep Learning.
RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
Feb 24, 2022
BACKGROUND: Perfusion MRI is a well-established imaging modality with a multitude of applications in oncological and cardiovascular imaging. Clinically used processing methods, while stable and robust, have remained largely unchanged in recent years....
Stable patients with suspected myocardial ischemia: comparison of machine-learning computed tomography-based fractional flow reserve and stress perfusion cardiovascular magnetic resonance imaging to detect myocardial ischemia.
BMC cardiovascular disorders
Feb 5, 2022
BACKGROUND: Machine-Learning Computed Tomography-Based Fractional Flow Reserve (CT-FFR) is a novel tool for the assessment of hemodynamic relevance of coronary artery stenoses. We examined the diagnostic performance of CT-FFR compared to stress perfu...
Automated segmentation of multiparametric magnetic resonance images for cerebral AVM radiosurgery planning: a deep learning approach.
Scientific reports
Jan 17, 2022
Stereotactic radiosurgery planning for cerebral arteriovenous malformations (AVM) is complicated by the variability in appearance of an AVM nidus across different imaging modalities. We developed a deep learning approach to automatically segment cere...
Impact of deep learning reconstruction on intracranial 1.5 T magnetic resonance angiography.
Japanese journal of radiology
Dec 1, 2021
PURPOSE: The purpose of this study was to evaluate whether deep learning reconstruction (DLR) improves the image quality of intracranial magnetic resonance angiography (MRA) at 1.5 T.
A nested parallel multiscale convolution for cerebrovascular segmentation.
Medical physics
Oct 31, 2021
PURPOSE: Cerebrovascular segmentation in magnetic resonance imaging (MRI) plays an important role in the diagnosis and treatment of cerebrovascular diseases. Many segmentation frameworks based on convolutional neural networks (CNNs) or U-Net-like str...
Combining multi-site magnetic resonance imaging with machine learning predicts survival in pediatric brain tumors.
Scientific reports
Sep 23, 2021
Brain tumors represent the highest cause of mortality in the pediatric oncological population. Diagnosis is commonly performed with magnetic resonance imaging. Survival biomarkers are challenging to identify due to the relatively low numbers of indiv...
Machine Learning
Child
Brain
Image Processing, Computer-Assisted
Female
Bayes Theorem
Infant, Newborn
Neoplasm Grading
Humans
Infant
Biopsy
Brain Neoplasms
Adolescent
Survival Analysis
Male
Child, Preschool
Kaplan-Meier Estimate
Risk Assessment
Magnetic Resonance Angiography
Diffusion Magnetic Resonance Imaging
Image Features of Magnetic Resonance Angiography under Deep Learning in Exploring the Effect of Comprehensive Rehabilitation Nursing on the Neurological Function Recovery of Patients with Acute Stroke.
Contrast media & molecular imaging
Sep 10, 2021
This study was to explore the effects of imaging characteristics of magnetic resonance angiography (MRA) based on deep learning on the comprehensive rehabilitation nursing on the neurological recovery of patients with acute stroke. In this study, 84 ...
Stay Ahead of Medical AI
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.
Subscribe NowPopular Topics
- Machine Learning 30978
- Neural Networks, Computer 29696
- Algorithms 26813
- Deep Learning 26324
- Artificial Intelligence 24267
- Robotics 13307
- Image Processing, Computer-Assisted 9512
- Retrospective Studies 9097
- Magnetic Resonance Imaging 6173
- Reproducibility of Results 5589
- Tomography, X-Ray Computed 4765
- Support Vector Machine 4678
- Computational Biology 4229
- Brain 4045
- Computer Simulation 3877
Recent Journals
- Scientific reports 5865
- Sensors (Basel, Switzerland) 4794
- PloS one 4011
- Neural networks : the official journal of the International Neural Network Society 2928
- Computational intelligence and neuroscience 1931
- Computers in biology and medicine 1839
- Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference 1686
- Studies in health technology and informatics 1278
- IEEE journal of biomedical and health informatics 1129
- Journal of chemical information and modeling 994
- Nature communications 938
- Computer methods and programs in biomedicine 883
- Bioinformatics (Oxford, England) 861
- Briefings in bioinformatics 850
- IEEE transactions on neural networks and learning systems 823