AI-based, automated chamber volumetry from gated, non-contrast CT
Author:
Funder
Siemens Medical Solutions USA
Publisher
Elsevier BV
Subject
Cardiology and Cardiovascular Medicine,Radiology, Nuclear Medicine and imaging
Reference4 articles.
1. Aquino GJ, Chamberlin J, Mercer M, et al. Deep learning model to quantify left atrium volume on routine non-contrast chest CT and predict adverse outcomes. J Cardiovasc Comput Tomogr. Published online December 2021:S1934592521004809. https://doi.org/10.1016/j.jcct.2021.12.005
2. Four-chamber heart modeling and automatic segmentation for 3-D cardiac CT volumes using marginal space learning and steerable features;Zheng;IEEE Trans Med Imag,2008
3. Aquino GJ, Chamberlin J, Yacoub B, et al. Diagnostic accuracy and performance of artificial intelligence in measuring left atrial volumes and function on multiphasic CT in patients with atrial fibrillation. Eur Radiol. Published online March 11, 2022. https://doi.org/10.1007/s00330-022-08657-y
4. Normal values of left ventricular mass and cardiac chamber volumes assessed by 320-detector computed tomography angiography in the Copenhagen General Population Study;Fuchs;Eur Heart J – Cardiovasc Imaging,2016
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