A Deep Learning-Based and Fully Automated Pipeline for Thoracic Aorta Geometric Analysis and Planning for Endovascular Repair from Computed Tomography.
Feasibility assessment and planning of thoracic endovascular aortic repair (TEVAR) require computed tomography (CT)-based analysis of geometric aortic features to identify adequate landing zones (LZs) for endograft deployment. However, no consensus exists on how to take the necessary measurements fr...
| Published in: | Journal of Digital Imaging Vol. 35; no. 2; pp. 226 - 240 |
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| Main Authors: | , , , , , , , , , , , |
| Format: | pictorial research tables/charts Journal Article |
| Published: |
Springer Nature
Apr2022
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| Online Access: | View this record in EBSCOhost |