17 November 2017 A robustness test of the braided device foreshortening algorithm
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Proceedings Volume 10572, 13th International Conference on Medical Information Processing and Analysis; 105721H (2017) https://doi.org/10.1117/12.2286328
Event: 13th International Symposium on Medical Information Processing and Analysis, 2017, San Andres Island, Colombia
Abstract
Different computational methods have been recently proposed to simulate the virtual deployment of a braided stent inside a patient vasculature. Those methods are primarily based on the segmentation of the region of interest to obtain the local vessel morphology descriptors. The goal of this work is to evaluate the influence of the segmentation quality on the method named "Braided Device Foreshortening" (BDF). METHODS: We used the 3DRA images of 10 aneurysmatic patients (cases). The cases were segmented by applying a marching cubes algorithm with a broad range of thresholds in order to generate 10 surface models each. We selected a braided device to apply the BDF algorithm to each surface model. The range of the computed flow diverter lengths for each case was obtained to calculate the variability of the method against the threshold segmentation values. RESULTS: An evaluation study over 10 clinical cases indicates that the final length of the deployed flow diverter in each vessel model is stable, shielding maximum difference of 11.19% in vessel diameter and maximum of 9.14% in the simulated stent length for the threshold values. The average coefficient of variation was found to be 4.08 %. CONCLUSION: A study evaluating how the threshold segmentation affects the simulated length of the deployed FD, was presented. The segmentation algorithm used to segment intracranial aneurysm 3D angiography images presents small variation in the resulting stent simulation.
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Raquel Kale Moyano, Hector Fernandez, Juan M. Macho, Jordi Blasco, Luis San Roman, Ana Paula Narata, Ignacio Larrabide, "A robustness test of the braided device foreshortening algorithm", Proc. SPIE 10572, 13th International Conference on Medical Information Processing and Analysis, 105721H (17 November 2017); doi: 10.1117/12.2286328; https://doi.org/10.1117/12.2286328
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