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Convolutional Neural Network for Automatic Detection and Characterization of Abdominal Aortic Aneurysm

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Date 2023 Feb 28
PMID 36852321
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References
1.
Lareyre F, Raffort J . Looking for the Optimal Evaluation of Abdominal Aortic Aneurysm Risk of Rupture. J Endovasc Ther. 2020; 27(2):345-346. DOI: 10.1177/1526602820908055. View

2.
Camara J, Tomihama R, Pop A, Shedd M, Dobrowski B, Knox C . Development of a convolutional neural network to detect abdominal aortic aneurysms. J Vasc Surg Cases Innov Tech. 2022; 8(2):305-311. PMC: 9178344. DOI: 10.1016/j.jvscit.2022.04.003. View

3.
Raffort J, Adam C, Carrier M, Ballaith A, Coscas R, Jean-Baptiste E . Artificial intelligence in abdominal aortic aneurysm. J Vasc Surg. 2020; 72(1):321-333.e1. DOI: 10.1016/j.jvs.2019.12.026. View

4.
Caradu C, Spampinato B, Vrancianu A, Berard X, Ducasse E . Fully automatic volume segmentation of infrarenal abdominal aortic aneurysm computed tomography images with deep learning approaches versus physician controlled manual segmentation. J Vasc Surg. 2020; 74(1):246-256.e6. DOI: 10.1016/j.jvs.2020.11.036. View

5.
Adam C, Fabre D, Mougin J, Zins M, Azarine A, Ardon R . Pre-surgical and Post-surgical Aortic Aneurysm Maximum Diameter Measurement: Full Automation by Artificial Intelligence. Eur J Vasc Endovasc Surg. 2021; 62(6):869-877. DOI: 10.1016/j.ejvs.2021.07.013. View