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Title: A cloud-based centerline algorithm for Studierfenster
Authors: Dionysio, Christina
Wild, Daniel
Pepe, Antonio
Gsaxner, Christina
Li, Jianning
Alvarez, Luis 
Egger, Jan
UNESCO Clasification: 1203 Ciencia de los ordenadores
120601 Construcción de algoritmos
220990 Tratamiento digital. Imágenes
Keywords: Aorta
Studierfenster, et al
Issue Date: 2021
Journal: Progress in Biomedical Optics and Imaging - Proceedings of SPIE 
Conference: Medical Imaging 2021
Abstract: Downloading of the abstract is permitted for personal use only.A practical method to analyze blood vessels, like the aorta, is to calculate the vessel's centerline and evaluate its shape in a CT or CTA scan. This contribution introduces a cloud-based centerline tool for the aorta, which computes an initial centerline from a CTA scan with two user given seed points. Afterwards, this initial centerline can be smoothed in a second step. The work done for this contribution was implemented into an existing online tool for medical image analysis, called Studierfenster. In order to evaluate the outcome of this contribution, we tested the smoothed centerline computed within Studierfenster against 40 baseline centerlines from a public available CTA challenge dataset. In doing so, we computed a minimum, maximum, and mean distance between the two centerlines in mm for every data sample, resulting in the smallest distance of 0.59mm, an overall maximum distance of 14.18mm, and a mean distance for all samples of 3.86mm with a standard deviation of 0.99mm.
ISBN: 978-151064031-3
ISSN: 1605-7422
DOI: 10.1117/12.2588268
Source: Progress in Biomedical Optics and Imaging - Proceedings of SPIE [ISSN 1605-7422], v. 11601, (Enero 2021)
Appears in Collections:Actas de congresos
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