Automated aortic anatomy analysis: From image to clinical indicators
Résumé
Most cerebrovascular diseases (including strokes and aneurysms) are treated endovascularly with catheters
that are navigated from the groin through the vessels to the brain. Many patients have complex anatomy of the aortic arch and supra-aortic vessels, which can make it difficult to select the best catheters for navigation, resulting in longer procedures and more complications or failures. To this end, we propose a framework dedicated to the analysis of the aortic arch and supra-aortic trunks. This framework can automatically compute anatomical and geometrical features from meshes segmented beforehand via CNN-based pipeline. These features such as arch type, tortuosity and angulations describe the navigational difficulties encountered during catheterization. Quantitative and qualitative validation was performed by experienced neuroradiologists, leading to reliable vessel characterization.
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EMBC___Automated_aortic_anatomy_analysis__From_image_to_clinical_indicators.pdf (1.59 Mo)
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Lahlouh_EMBC_2023_Poster.pdf (915.45 Ko)
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| Origine | Fichiers produits par l'(les) auteur(s) |
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| Origine | Fichiers produits par l'(les) auteur(s) |
|---|