Filtering and segmentation of 3D angiographic data: Advances based on mathematical morphologyReport as inadecuate

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1 LSIIT - Laboratoire des Sciences de l-Image, de l-Informatique et de la Télédétection 2 LINC - Laboratoire d-Imagerie et de Neurosciences Cognitives 3 LISSI - Laboratoire Images, Signaux et Systèmes Intelligents 4 LIGM - Laboratoire d-Informatique Gaspard-Monge 5 CMM - Centre de Morphologie Mathématique

Abstract : In the last 20 years, 3D angiographic imaging proved its usefulness in the context of various clinical applications. However, angiographic images are generally difficult to analyse due to their size and the fact that useful information is easily hidden in noise and artifacts. Therefore, there is an ongoing necessity to provide tools facilitating their visualization and analysis, while vessel segmentation from such images remains a challenging task. This article presents new vessel segmentation and filtering techniques, relying on recent advances in mathematical morphology. In particular, methodological results related to variant mathematical morphology and connected filtering are stated, and involved in an angiographic data processing framework. These filtering and segmentation methods are validated on real and synthetic 3D angiographic data.

Keywords : Vessel segmentation vessel filtering mathematical morphology MRA

Author: Alice Dufour - Olena Tankyevych - Benoît Naegel - Hugues Talbot - Christian Ronse - Joseph Baruthio - Petr Dokládal - Nicolas P



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