Abstract
The segmentation of the thoracic aorta and its main branches from medical image data is an important task in vascular image analysis. We introduce a new model-based approach for the segmentation of these vessels from follow-up 3D MRA images of children. For robust segmentation we propose an extended parametric cylinder model which requires only relatively few parameters. The new model is used in conjunction with a two-step fitting scheme for refining the segmentation result yielding an accurate segmentation of the vascular shape. Moreover, we include a novel adaptive background masking scheme and we use a spatial normalization scheme to align the segmentation results from follow-up examinations. We have evaluated our proposed approach using 3D synthetic images and we have successfully applied the approach to follow-up 3D MRA images of children.
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© 2014 Springer-Verlag Berlin Heidelberg
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Wörz, S. et al. (2014). Quantification of the Aortic Morphology in Follow-Up 3D-MRA Images of Children. In: Deserno, T., Handels, H., Meinzer, HP., Tolxdorff, T. (eds) Bildverarbeitung für die Medizin 2014. Informatik aktuell. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-54111-7_38
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DOI: https://doi.org/10.1007/978-3-642-54111-7_38
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