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Selected Publication:
SHR Neuro Cancer Cardio Lipid Metab Microb
Pepe, A; Li, J; Rolf-Pissarczyk, M; Gsaxner, C; Chen, X; Holzapfel, GA; Egger, J.
Detection, segmentation, simulation and visualization of aortic dissections: A review.
MED IMAGE ANAL. 2020; 65(1): 101773-101773.
Doi: 10.1016/j.media.2020.101773
Web of Science
PubMed
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FullText_MUG
- Leading authors Med Uni Graz
- Egger Jan
- Co-authors Med Uni Graz
- Schwarz-Gsaxner Christina
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- Abstract:
- Aortic dissection (AD) is a condition of the main artery of the human body, resulting in the formation of a new flow channel, or false lumen. The disease is usually diagnosed with a computed tomography angiography scan during the acute phase. A better understanding of the causes of AD requires knowledge of the aortic geometry (segmentation), including the true and false lumina, which is very time-consuming to reconstruct when performed manually on a slice-by-slice basis. Hence, different automatic and semi-automatic medical image analysis approaches have been proposed for this task over the last years. In this review, we present and discuss these computing techniques used to segment dissected aortas, also in regard to the detection and visualization of clinically relevant information and features from dissected aortas for customized patient-specific treatments. Copyright © 2020 Elsevier B.V. All rights reserved.
- Find related publications in this database (Keywords)
- Aorta
- Dissection
- Detection
- Segmentation
- Visualization
- Simulation
- Computed tomography