AIMC Topic: Magnetic Resonance Imaging, Cine

Clear Filters Showing 131 to 140 of 175 articles

Machine Learning-Based Three-Dimensional Echocardiographic Quantification of Right Ventricular Size and Function: Validation Against Cardiac Magnetic Resonance.

Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography Jun 4, 2019
BACKGROUND: Three-dimensional echocardiography (3DE) allows accurate and reproducible measurements of right ventricular (RV) size and function. However, widespread implementation of 3DE in routine clinical practice is limited because the existing sof...
Humans Machine Learning Female Image Interpretation, Computer-Assisted Echocardiography, Three-Dimensional Magnetic Resonance Imaging, Cine Ventricular Function, Right Reproducibility of Results Male Middle Aged Heart Ventricles
View on PubMed DOI

Quantitative CMR population imaging on 20,000 subjects of the UK Biobank imaging study: LV/RV quantification pipeline and its evaluation.

Medical image analysis May 25, 2019
Population imaging studies generate data for developing and implementing personalised health strategies to prevent, or more effectively treat disease. Large prospective epidemiological studies acquire imaging for pre-symptomatic populations. These st...
Heart Ventricles Biological Specimen Banks Image Interpretation, Computer-Assisted United Kingdom Pattern Recognition, Automated Female Magnetic Resonance Imaging, Cine Male Imaging, Three-Dimensional Models, Statistical Humans Neural Networks, Computer
View on PubMed DOI

Putting machine learning into motion: applications in cardiovascular imaging.

Clinical radiology May 9, 2019
Heart and circulatory diseases cause a quarter of all deaths in the UK and cardiac imaging offers an effective tool for early diagnosis and risk-stratification to improve premature death and disability. This domain of radiology is unique in that asse...
Magnetic Resonance Imaging, Cine Machine Learning Cardiovascular Diseases Image Interpretation, Computer-Assisted Humans
View on PubMed DOI

Deep Learning for Diagnosis of Chronic Myocardial Infarction on Nonenhanced Cardiac Cine MRI.

Radiology Apr 30, 2019
Background Renal impairment is common in patients with coronary artery disease and, if severe, late gadolinium enhancement (LGE) imaging for myocardial infarction (MI) evaluation cannot be performed. Purpose To develop a fully automatic framework for...
Databases, Factual Retrospective Studies Female Aged Humans Deep Learning Chronic Disease Myocardial Infarction Image Interpretation, Computer-Assisted Adult Sensitivity and Specificity Male Middle Aged Magnetic Resonance Imaging, Cine
View on PubMed DOI

Automatic CNN-based detection of cardiac MR motion artefacts using k-space data augmentation and curriculum learning.

Medical image analysis Apr 22, 2019
Good quality of medical images is a prerequisite for the success of subsequent image analysis pipelines. Quality assessment of medical images is therefore an essential activity and for large population studies such as the UK Biobank (UKBB), manual id...
Artifacts Magnetic Resonance Imaging, Cine Neural Networks, Computer Machine Learning Algorithms Imaging, Three-Dimensional Image Processing, Computer-Assisted Heart Motion Humans
View on PubMed DOI

Identifying Ventricular Arrhythmias and Their Predictors by Applying Machine Learning Methods to Electronic Health Records in Patients With Hypertrophic Cardiomyopathy (HCM-VAr-Risk Model).

The American journal of cardiology Feb 27, 2019
Clinical risk stratification for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HC) employs rules derived from American College of Cardiology Foundation/American Heart Association (ACCF/AHA) guidelines or the HCM Risk-SCD model (C-index ∼...
Male Middle Aged Risk Assessment Electrocardiography Predictive Value of Tests Registries Cardiomyopathy, Hypertrophic Humans Electronic Health Records Female Machine Learning Reproducibility of Results Tachycardia, Ventricular Risk Factors Prognosis Echocardiography, Stress Retrospective Studies Magnetic Resonance Imaging, Cine
View on PubMed DOI

Constrained-CNN losses for weakly supervised segmentation.

Medical image analysis Feb 13, 2019
Weakly-supervised learning based on, e.g., partially labelled images or image-tags, is currently attracting significant attention in CNN segmentation as it can mitigate the need for full and laborious pixel/voxel annotations. Enforcing high-order (gl...
Image Processing, Computer-Assisted Magnetic Resonance Imaging Prostate Spine Heart Ventricles Humans Supervised Machine Learning Neural Networks, Computer Magnetic Resonance Imaging, Cine Male Imaging, Three-Dimensional
View on PubMed DOI

Learning a Probabilistic Model for Diffeomorphic Registration.

IEEE transactions on medical imaging Feb 4, 2019
We propose to learn a low-dimensional probabilistic deformation model from data which can be used for the registration and the analysis of deformations. The latent variable model maps similar deformations close to each other in an encoding space. It ...
Models, Statistical Heart Algorithms Magnetic Resonance Imaging, Cine Humans Deep Learning Image Processing, Computer-Assisted
View on PubMed DOI

Automatic 3D Bi-Ventricular Segmentation of Cardiac Images by a Shape-Refined Multi- Task Deep Learning Approach.

IEEE transactions on medical imaging Jan 23, 2019
Deep learning approaches have achieved state-of-the-art performance in cardiac magnetic resonance (CMR) image segmentation. However, most approaches have focused on learning image intensity features for segmentation, whereas the incorporation of anat...
Imaging, Three-Dimensional Humans Heart Algorithms Magnetic Resonance Imaging, Cine Deep Learning Cardiac Imaging Techniques
View on PubMed DOI

Machine learning derived segmentation of phase velocity encoded cardiovascular magnetic resonance for fully automated aortic flow quantification.

Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance Jan 7, 2019
BACKGROUND: Phase contrast (PC) cardiovascular magnetic resonance (CMR) is widely employed for flow quantification, but analysis typically requires time consuming manual segmentation which can require human correction. Advances in machine learning ha...
United States Humans Aortic Valve Machine Learning Male Aorta Predictive Value of Tests Prospective Studies Middle Aged Myocardial Perfusion Imaging Heart Diseases Retrospective Studies Hemodynamics Image Interpretation, Computer-Assisted Magnetic Resonance Imaging, Cine Female Automation Reproducibility of Results Proof of Concept Study Aged Blood Flow Velocity
View on PubMed DOI
Popular Topics
Recent Journals