AIMC Topic: Magnetic Resonance Imaging, Cine

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Knowledge-based reconstruction for measurement of right ventricular volumes on cardiovascular magnetic resonance images in a mixed population.

Congenital heart disease Jun 5, 2017
OBJECTIVE: Follow-up of right ventricular performance is important for patients with congenital heart disease. Cardiac magnetic resonance imaging is optimal for this purpose. However, observer-dependency of manual analysis of right ventricular volume...
Young Adult Adult Male Adolescent Child Humans Retrospective Studies Female Reproducibility of Results Image Interpretation, Computer-Assisted Heart Defects, Congenital Magnetic Resonance Imaging, Cine Cardiac Volume ROC Curve Follow-Up Studies Heart Ventricles Knowledge Bases
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Direct Multitype Cardiac Indices Estimation via Joint Representation and Regression Learning.

IEEE transactions on medical imaging May 26, 2017
Cardiac indices estimation is of great importance during identification and diagnosis of cardiac disease in clinical routine. However, estimation of multitype cardiac indices with consistently reliable and high accuracy is still a great challenge due...
Regression Analysis Heart Image Interpretation, Computer-Assisted Heart Function Tests Magnetic Resonance Imaging, Cine Humans Neural Networks, Computer Machine Learning
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Impact of knowledge-based iterative model reconstruction on myocardial late iodine enhancement in computed tomography and comparison with cardiac magnetic resonance.

The international journal of cardiovascular imaging Apr 13, 2017
We evaluated the image quality and diagnostic performance of late iodine enhancement computed tomography (LIE-CT) with knowledge-based iterative model reconstruction (IMR) for the detection of myocardial infarction (MI) in comparison with late gadoli...
Iopamidol Knowledge Bases Myocardium Observer Variation Humans Middle Aged Coronary Angiography Coronary Circulation Multidetector Computed Tomography Electrocardiography Retrospective Studies Radiographic Image Interpretation, Computer-Assisted Computed Tomography Angiography Myocardial Perfusion Imaging Contrast Media Female Coronary Artery Disease Gadolinium DTPA Predictive Value of Tests Reproducibility of Results Myocardial Infarction Magnetic Resonance Imaging, Cine Aged Cardiac-Gated Imaging Techniques Male
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Convolutional neural network regression for short-axis left ventricle segmentation in cardiac cine MR sequences.

Medical image analysis Apr 12, 2017
Automated left ventricular (LV) segmentation is crucial for efficient quantification of cardiac function and morphology to aid subsequent management of cardiac pathologies. In this paper, we parameterize the complete (all short axis slices and phases...
Regression Analysis Heart Ventricles Image Interpretation, Computer-Assisted Magnetic Resonance Imaging, Cine Humans Neural Networks, Computer Machine Learning Reproducibility of Results
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Evaluation of knowledge-based reconstruction for magnetic resonance volumetry of the right ventricle after arterial switch operation for dextro-transposition of the great arteries.

The international journal of cardiovascular imaging Jun 2, 2016
Right ventricular (RV) volume and function evaluation is essential in the follow-up of patients after arterial switch operation (ASO) for dextro-transposition of the great arteries (d-TGA). Cardiac magnetic resonance (CMR) imaging using the Simpson's...
Treatment Outcome Predictive Value of Tests Anatomic Landmarks Feasibility Studies Ventricular Dysfunction, Right Heart Ventricles Knowledge Bases Image Interpretation, Computer-Assisted Observer Variation Reproducibility of Results Male Adolescent Time Factors Ontario Humans Retrospective Studies Female Transposition of Great Vessels Magnetic Resonance Imaging, Cine Arterial Switch Operation Hypertrophy, Right Ventricular Ventricular Function, Right
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Combining deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance.

Medical image analysis May 26, 2016
We introduce a new methodology that combines deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance (MR) data. This combination is relevant for segmentation problems, where t...
Magnetic Resonance Imaging, Cine Machine Learning Reproducibility of Results Image Processing, Computer-Assisted Heart Ventricles Pattern Recognition, Automated Humans
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A combined deep-learning and deformable-model approach to fully automatic segmentation of the left ventricle in cardiac MRI.

Medical image analysis Feb 6, 2016
Segmentation of the left ventricle (LV) from cardiac magnetic resonance imaging (MRI) datasets is an essential step for calculation of clinical indices such as ventricular volume and ejection fraction. In this work, we employ deep learning algorithms...
Heart Ventricles Ventricular Dysfunction, Left Image Interpretation, Computer-Assisted Humans Pattern Recognition, Automated Models, Cardiovascular Algorithms Machine Learning Image Enhancement Subtraction Technique Computer Simulation Reproducibility of Results Magnetic Resonance Imaging, Cine Sensitivity and Specificity
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Efficient method for analyzing MR real-time cines: Toward accurate quantification of left ventricular function.

Journal of magnetic resonance imaging : JMRI Mar 2, 2015
BACKGROUND: To develop and assess an efficient method to identify end-expiratory end-diastolic (ED) and end-systolic (ES) images for accurate quantification of left ventricular (LV) function in real-time cine imaging.
Computer Systems Young Adult Image Enhancement Humans Image Interpretation, Computer-Assisted Adult History, Ancient Machine Learning Observer Variation Sensitivity and Specificity Magnetic Resonance Imaging, Cine Algorithms Pattern Recognition, Automated Male Reproducibility of Results Ventricular Function, Left
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Assessment of biventricular cardiac function using free-breathing artificial intelligence cine with motion correction: Comparison with standard multiple breath-holding cine.

European journal of radiology Jul 1, 2025
PURPOSE: To assess the image quality and biventricular function utilizing a free-breathing artificial intelligence cine method with motion correction (FB AI MOCO).
Humans Artificial Intelligence Prospective Studies Female Reproducibility of Results Motion Adult Image Interpretation, Computer-Assisted Sensitivity and Specificity Artifacts Cross-Sectional Studies Breath Holding Male Magnetic Resonance Imaging, Cine Middle Aged
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Deep Learning-based Aligned Strain from Cine Cardiac MRI for Detection of Fibrotic Myocardial Tissue in Patients with Duchenne Muscular Dystrophy.

Radiology. Artificial intelligence May 1, 2025
Purpose To develop a deep learning (DL) model that derives aligned strain values from cine (noncontrast) cardiac MRI and evaluate performance of these values to predict myocardial fibrosis in patients with Duchenne muscular dystrophy (DMD). Materials...
Image Interpretation, Computer-Assisted Cardiomyopathies Retrospective Studies Magnetic Resonance Imaging, Cine Muscular Dystrophy, Duchenne Reproducibility of Results Humans Male Adolescent Deep Learning Child Myocardium Heart Fibrosis
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