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FAST 3D PRE-SEGMENTATION OF ARTERIES IN COMPUTED TOMOGRAPHY ANGIOGRAMS

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Book cover Computer Vision and Graphics

Part of the book series: Computational Imaging and Vision ((CIVI,volume 32))

Abstract

A pre-segmentation algorithm for computed tomography angiograms (CTA) is described. It is based on adaptive thresholding. The median axis of the binarized image provides arterial centerlines and estimates of the local radii. Boundary location is refined by analyzing radial intensity profiles in the vicinity of their intersections with the thresholds. The thresholding rule was learned on CTAs of 60 patients. The method was successfully evaluated in 10 patients.

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REFERENCES

  • Boskamp, T., Rinck, D., Link, F., Kummerlen, B., Stamm, G., and Mildenberger, P. (2004). New vessel analysis tool for morphometric quantification and visualization of vessels in CT and MR imaging data sets. RadioGraphics, 24:287–297.

    Google Scholar 

  • Danielsson, P. E. (1980). Euclidean distance mapping. Comp Graph and Image Proc, 14:227–248.

    Google Scholar 

  • Flórez, L., Montagnat, J., and Orkisz, M. (2002). 3D graphical models for vascular-stent pose simulation. In Int Conf Comp Vision Graph.

    Google Scholar 

  • Frangi, A. F., Niessen, W. J., Hoogeveen, R. M., Walsum, T., and Viergever, M. A. (1999). Quantitation of vessel morphology from 3-d mra. In MICCAI, LNCS, pages 358–367.

    Google Scholar 

  • Hernández, M., Orkisz, M., Puech, P., Mansard, C., Douek, P. C., and Magnin, I. E. (2002). Computer-assisted analysis of 3-dimensional angiograms. RadioGraphics, 22:421–436.

    Google Scholar 

  • Nonent, M., Serfaty, J. M., Nighoghossian, N., Rouhart, F., Derex, L., Rotaru, C., Chirossel, P., Guias, B., Heautot, J. F., Gouny, P., Langella, B., Buthion, V., Jars, I., Pachai, C., Veyret, C., Gauvrit, J. Y., Lamure, M., and Douek, P. C. (2004). Concordance Rate Differences of 3 Noninvasive Imaging Techniques to Measure Carotid Stenosis in Clinical Routine Practice: Results of the CARMEDAS Multicenter Study. Stroke, 35(3):682–686.

    Article  Google Scholar 

  • Yim, P. J., Vasbinder, G. B. C., Ho, V. B., and Choyke, P. L. (2003). Isosurfaces as deformable models for magnetic resonance angiography. IEEE Trans. Med. Imaging, 22(7):875–881.

    Article  Google Scholar 

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© 2006 Springer

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Flórez-Valencia, L., Vincent, F., Orkisz, M. (2006). FAST 3D PRE-SEGMENTATION OF ARTERIES IN COMPUTED TOMOGRAPHY ANGIOGRAMS. In: Wojciechowski, K., Smolka, B., Palus, H., Kozera, R., Skarbek, W., Noakes, L. (eds) Computer Vision and Graphics. Computational Imaging and Vision, vol 32. Springer, Dordrecht. https://doi.org/10.1007/1-4020-4179-9_52

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  • DOI: https://doi.org/10.1007/1-4020-4179-9_52

  • Publisher Name: Springer, Dordrecht

  • Print ISBN: 978-1-4020-4178-5

  • Online ISBN: 978-1-4020-4179-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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