Purpose: Segmentation of left ventricular myocardium (LVM) in coronary computed tomography angiography (CCTA) is important for diagnosis of cardiovascular ...
Feb 3, 2020 · Purpose. Segmentation of left ventricular myocardium (LVM) in coronary computed tomography angiography (CCTA) is important for diagnosis of ...
In this work, we propose to use a 3D deep attention U-Net method to segment the LVM ... Left ventricular myocardium, segmentation, deep learning, deep attention U ...
Corrigendum: "Automated Left Ventricular Myocardium Segmentation Using 3D Deeply Supervised Attention U-Net for Coronary Computed Tomography Angiography" ...
Left ventricular myocardium segmentation in coronary computed tomography angiography using 3D deep attention u-net ... Abstract. Cardiovascular diseases (CVD) are ...
Jan 13, 2024 · Automated Left Ventricular Myocardium Segmentation Using 3D Deeply Supervised Attention U-Net for Coronary Computed Tomography Angiography.
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Corrigendum: "Automated Left Ventricular Myocardium Segmentation Using 3D Deeply Supervised Attention U‑Net for Coronary Computed Tomography Angiography" ...
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The results demonstrate that automatic segmentation of the LV in CCTA scans using voxel classification with convolutional neural networks is feasible.
May 14, 2024 · We developed a 3D deeply supervised U-Net, which incorporates attention gates (AGs) to focus on the myocardial boundary structures, to segment ...
Jan 22, 2024 · Validation of a whole heart segmentation from computed tomography imaging using a deep-learning approach. J Cardiovasc Transl Res. (2021) 15 ...