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Segmentation-free and multiscale-free extraction of medial information using Gradient Vector Flow — Application to vascular structures

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5 Author(s)
Pizaine, G. ; Medisys Res. Lab., Philips Healthcare, Suresnes, France ; Prevost, R. ; Angelini, E.D. ; Bloch, I.
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Gradient Vector Flow has become a popular method to recover medial information in medical imaging, in particular for vessels centerline extraction. This renewed interest has been motivated by its ability to process gray-scale images without prior segmentation. However, another interesting property lies in the diffusion process used to solve the underlying variational problem. We propose a method to recover scale information in the context of vascular structures extraction, relying on analytical properties of the Gradient Vector Flow only, with no multiscale analysis. Through simple one-dimensional considerations, we demonstrate the ability of our approach to estimate the radii of the vessels with an error of 10% only in the presence of noise and less than 3% without noise. Our approach is evaluated on convolved bar-like templates and is illustrated on 2D X-ray angiographic images.

Published in:

Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on

Date of Conference:

2-5 May 2012

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