AIMC Topic: Endocardium

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Machine learning based quantification of ejection and filling parameters by fully automated dynamic measurement of left ventricular volumes from cardiac magnetic resonance images.

Magnetic resonance imaging Dec 12, 2019
BACKGROUND: Although analysis of cardiac magnetic resonance (CMR) images provides accurate and reproducible measurements of left ventricular (LV) volumes, these measurements are usually not performed throughout the cardiac cycle because of lack of to...
Humans Machine Learning Software Algorithms Prospective Studies Female Reproducibility of Results Aged Adult Male Ventricular Function, Left Middle Aged Image Processing, Computer-Assisted Magnetic Resonance Imaging Heart Heart Ventricles Automation Endocardium
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Fully Automated Quantification of Cardiac Indices from Cine MRI Using a Combination of Convolution Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Cardiovascular magnetic resonance imaging (CMRI) is one of the most accurate non-invasive modalities for evaluation of cardiac function, especially the left ventricle (LV). In this modality, the manual or semi-automatic delineation of LV by experts i...
Humans Neural Networks, Computer Magnetic Resonance Imaging Heart Ventricles Magnetic Resonance Imaging, Cine Endocardium
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A Multi-channel Deep Learning Approach for Segmentation of the Left Ventricular Endocardium from Cardiac Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Cardiac segmentation is the first most important step in assessing cardiac diseases. However, it still remains challenging owing to the complicated information of myocardium's boundary. In this work, we investigate approaches based on deep learning f...
Humans Neural Networks, Computer Algorithms Deep Learning Image Processing, Computer-Assisted Heart Ventricles Endocardium
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Computational Platform Based on Deep Learning for Segmenting Ventricular Endocardium in Long-axis Cardiac MR Imaging.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2018
This paper presents an automated computational platform based on deep learning (DL) approach for left ventricular (LV) and right ventricular (RV) endocardium segmentation in long-axis cine cardiovascular magnetic resonance (CMR). The proposed method ...
Humans Neural Networks, Computer Algorithms Reproducibility of Results Deep Learning Heart Ventricles Image Interpretation, Computer-Assisted Models, Cardiovascular Magnetic Resonance Imaging, Cine Endocardium
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