AIMC Topic: Magnetic Resonance Angiography
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Reconstruction of undersampled 3D non-Cartesian image-based navigators for coronary MRA using an unrolled deep learning model.
Magnetic resonance in medicine
Feb 3, 2020
PURPOSE: To rapidly reconstruct undersampled 3D non-Cartesian image-based navigators (iNAVs) using an unrolled deep learning (DL) model, enabling nonrigid motion correction in coronary magnetic resonance angiography (CMRA).
Feasibility of a sub-3-minute imaging strategy for ungated quiescent interval slice-selective MRA of the extracranial carotid arteries using radial k-space sampling and deep learning-based image processing.
Magnetic resonance in medicine
Jan 23, 2020
PURPOSE: To develop and test the feasibility of a sub-3-minute imaging strategy for non-contrast evaluation of the extracranial carotid arteries using ungated quiescent interval slice-selective (QISS) MRA, combining single-shot radial sampling with d...
Denoising arterial spin labeling perfusion MRI with deep machine learning.
Magnetic resonance imaging
Jan 15, 2020
PURPOSE: Arterial spin labeling (ASL) perfusion MRI is a noninvasive technique for measuring cerebral blood flow (CBF) in a quantitative manner. A technical challenge in ASL MRI is data processing because of the inherently low signal-to-noise-ratio (...
Deep Learning Detection of Penumbral Tissue on Arterial Spin Labeling in Stroke.
Stroke
Dec 30, 2019
Background and Purpose- Selection of patients with acute ischemic stroke for endovascular treatment generally relies on dynamic susceptibility contrast magnetic resonance imaging or computed tomography perfusion. Dynamic susceptibility contrast magne...
A novel computer-aided diagnosis system for the early detection of hypertension based on cerebrovascular alterations.
NeuroImage. Clinical
Dec 2, 2019
Hypertension is a leading cause of mortality in the USA. While simple tools such as the sphygmomanometer are widely used to diagnose hypertension, they could not predict the disease before its onset. Clinical studies suggest that alterations in the s...
Statistical modeling and knowledge-based segmentation of cerebral artery based on TOF-MRA and MR-T1.
Computer methods and programs in biomedicine
Nov 14, 2019
BACKGROUND AND OBJECTIVE: For cerebrovascular segmentation from time-of-flight (TOF) magnetic resonance angiography (MRA), the focused issues are segmentation accuracy, vascular network coverage ratio, and cerebral artery and vein (CA/CV) separation....
Tracing in 2D to reduce the annotation effort for 3D deep delineation of linear structures.
Medical image analysis
Nov 9, 2019
The difficulty of obtaining annotations to build training databases still slows down the adoption of recent deep learning approaches for biomedical image analysis. In this paper, we show that we can train a Deep Net to perform 3D volumetric delineati...
Automatic myocardial segmentation in dynamic contrast enhanced perfusion MRI using Monte Carlo dropout in an encoder-decoder convolutional neural network.
Computer methods and programs in biomedicine
Oct 22, 2019
BACKGROUND AND OBJECTIVE: Cardiac perfusion magnetic resonance imaging (MRI) with first pass dynamic contrast enhancement (DCE) is a useful tool to identify perfusion defects in myocardial tissues. Automatic segmentation of the myocardium can lead to...
Automated diagnosis of heart valve degradation using novelty detection algorithms and machine learning.
PloS one
Sep 26, 2019
The blood flow through the major vessels holds great diagnostic potential for the identification of cardiovascular complications and is therefore routinely assessed with current diagnostic modalities. Heart valves are subject to high hydrodynamic loa...
Performance of a Deep-Learning Neural Network to Detect Intracranial Aneurysms from 3D TOF-MRA Compared to Human Readers.
Clinical neuroradiology
Jun 21, 2019
PURPOSE: To study the clinical potential of a deep learning neural network (convolutional neural networks [CNN]) as a supportive tool for detection of intracranial aneurysms from 3D time-of-flight magnetic resonance angiography (TOF-MRA) by comparing...
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