Automatic segmentation and quantification of epicardial adipose tissue from coronary computed tomography angiography
Author:
Publisher
IOP Publishing
Subject
Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology
Link
https://iopscience.iop.org/article/10.1088/1361-6560/ab8077/pdf
Reference47 articles.
1. Harmonizing the Metabolic Syndrome
2. The story of fatty heart. A disease of Victorian times.
3. Pericardial Fat Burden on ECG-Gated Noncontrast CT in Asymptomatic Patients Who Subsequently Experience Adverse Cardiovascular Events
4. 3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation
5. Deep Learning for Quantification of Epicardial and Thoracic Adipose Tissue From Non-Contrast CT
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