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Fast detection and characterization of vessels in very large 3-D data sets using geometrical moments.

Abstract : An improved and very fast algorithm dealing with the extraction of vessels in three-dimensional imaging is described. The approach is based on geometrical moments and a local cylindrical approximation. A robust estimation of vessel and background intensity levels, position, orientation, and diameter of the vessels with adaptive control of key parameters, is provided during vessel tracking. Experimental results are presented for lower limb arteries in multidetector computed tomography scanner.
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https://www.hal.inserm.fr/inserm-00134957
Contributor : Jean-Louis Dillenseger <>
Submitted on : Thursday, November 11, 2010 - 3:48:49 PM
Last modification on : Tuesday, September 3, 2019 - 6:02:02 PM
Long-term archiving on: : Saturday, February 12, 2011 - 2:16:10 AM

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  • HAL Id : inserm-00134957, version 1
  • PUBMED : 11341536

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Christine Toumoulin, Cezary Boldak, Jean-Louis Dillenseger, Jean-Louis Coatrieux, Yan Rolland. Fast detection and characterization of vessels in very large 3-D data sets using geometrical moments.. IEEE Transactions on Biomedical Engineering, Institute of Electrical and Electronics Engineers, 2001, 48 (5), pp.604-6. ⟨inserm-00134957⟩

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