Literature DB >> 22256315

Segmentation of brain blood vessels using projections in 3-D CT angiography images.

Danilo Babin1, Ewout Vansteenkiste, Aleksandra Pizurica, Wilfried Philips.   

Abstract

Segmenting cerebral blood vessels is of great importance in diagnostic and clinical applications, especially in quantitative diagnostics and surgery on aneurysms and arteriovenous malformations (AVM). Segmentation of CT angiography images requires algorithms robust to high intensity noise, while being able to segment low-contrast vessels. Because of this, most of the existing methods require user intervention. In this work we propose an automatic algorithm for efficient segmentation of 3-D CT angiography images of cerebral blood vessels. Our method is robust to high intensity noise and is able to accurately segment blood vessels with high range of luminance values, as well as low-contrast vessels.

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Year:  2011        PMID: 22256315     DOI: 10.1109/IEMBS.2011.6092091

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  2 in total

1.  Elaboration of a semi-automated algorithm for brain arteriovenous malformation segmentation: initial results.

Authors:  Frédéric Clarençon; Franck Maizeroi-Eugène; Damien Bresson; Flavien Maingreaud; Nader Sourour; Claude Couquet; David Ayoub; Jacques Chiras; Catherine Yardin; Charbel Mounayer
Journal:  Eur Radiol       Date:  2014-09-20       Impact factor: 5.315

Review 2.  Segmentation techniques of brain arteriovenous malformations for 3D visualization: a systematic review.

Authors:  Elisa Colombo; Tim Fick; Giuseppe Esposito; Menno Germans; Luca Regli; Tristan van Doormaal
Journal:  Radiol Med       Date:  2022-10-18       Impact factor: 6.313

  2 in total

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