Detection, segmentation, simulation and visualization of aortic dissections: A review
| Autor: | Malte Rolf-Pissarczyk, Christina Gsaxner, Antonio Pepe, Xiaojun Chen, Jan Egger, Gerhard Holzapfel, Jianning Li |
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| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
Computed Tomography Angiography Computer science False lumen Health Informatics 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine medicine.artery medicine Humans Computer Simulation Radiology Nuclear Medicine and imaging Segmentation Aorta Computed tomography angiography Aortic dissection Radiological and Ultrasound Technology medicine.diagnostic_test medicine.disease Computer Graphics and Computer-Aided Design Visualization Aortic Dissection Dissection Computer Vision and Pattern Recognition Radiology Tomography X-Ray Computed Relevant information 030217 neurology & neurosurgery |
| Zdroj: | Medical Image Analysis. 65:101773 |
| ISSN: | 1361-8415 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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