Risser, Laurent and Plouraboué, Franck
and Descombes, Xavier
Gap Filling of 3-D Microvascular Networks by Tensor Voting.
(2008)
IEEE Transactions on Medical Imaging, 27 (5). 674-687. ISSN 0278-0062
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(Document in English)
PDF (Author's version) - Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader 464kB |
Official URL: http://dx.doi.org/10.1109/TMI.2007.913248
Abstract
We present a new algorithm which merges discontinuities in 3-D images of tubular structures presenting undesirable gaps. The application of the proposed method is mainly associated to large 3-D images of microvascular networks. In order to recover the real network topology, we need to fill the gaps between the closest discontinuous vessels. The algorithm presented in this paper aims at achieving this goal. This algorithm is based on the skeletonization of the segmented network followed by a tensor voting method. It permits to merge the most common kinds of discontinuities found in microvascular networks. It is robust, easy to use, and relatively fast. The microvascular network images were obtained using synchrotron tomography imaging at the European Synchrotron Radiation Facility. These images exhibit samples of intracortical networks. Representative results are illustrated.
Item Type: | Article |
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Additional Information: | Thanks to IEEE editor. The original PDF is available at http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=42 |
HAL Id: | hal-01576034 |
Audience (journal): | International peer-reviewed journal |
Uncontrolled Keywords: | |
Institution: | French research institutions > Centre National de la Recherche Scientifique - CNRS (FRANCE) Université de Toulouse > Institut National Polytechnique de Toulouse - Toulouse INP (FRANCE) French research institutions > Institut National de la Recherche en Informatique et en Automatique - INRIA (FRANCE) Université de Toulouse > Université Toulouse III - Paul Sabatier - UT3 (FRANCE) |
Laboratory name: | |
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Deposited On: | 25 Apr 2012 09:24 |
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