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An improved model-based vessel tracking algorithm with application to computed tomography angiography

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
This paper reports newest improvements proposed for the segmentation and the characterisation of three-dimensional vessels observed through Computed Tomography Angiography using geometrical moments. Several adaptive controls are introduced, which allow to deal with pathological patterns such as dense and scaterred calcifications. The reduced time computation makes the algorithm capable to face clinical constraints in routine use. Examples are given on several data sets that highlight critical situations to handle.
Twórcy
autor
  • Computer Science Departament, Technical University Białystok, Poland; Laboratoire de Traitment du Signal et de l'Image, Université de Rennes 1, France
autor
  • Laboratoire de Traitment du Signal et de l'Image, Université de Rennes 1, France; Departament d'Imagerie Medicale, Hospital Sud de Rennes, France
autor
  • Laboratoire de Traitment du Signal et de l'Image, Université de Rennes 1, France
Bibliografia
  • [1] Chen S.-Y.J., Carroll J.D.: Computer assisted coronary intervention by use of on-line 3D reconstruction and optimal view strategy. MICCAI 1998, 377-385.
  • [2] Coatrieux J.L., Haigron P., Dillenseger J.L., Stanghellini L: From algorithms to applications in medical imaging: present and future. State of art report. Eurographics, Poitiers 1996, 1-46.
  • [3] Dillenseger J.L., Hamitouche C., Coatrieux J.L.: An integrated multi-purpose ray tracing framework for visualisation of medical images. Proc. of 13th An. Int. Conf. IEEE-EMBS, Orlando, 13, 3, 1125-1126, October 1991.
  • [4] Du Y.P., Parker D.L., Davis W.L., Cao G.C.: Reduction of partial volume artefacts with zero-filled interpolation in three-dimensional MR angiography. J. Magn. Reson. Imag. 1994, 4, 5, 733-741.
  • [5] Du Y.P., Parker D.L., Davis W.L.: Vessel enhancement filtering in three-dimensional MR angiography. Journal of Magnetic Resonance Imaging 1995, 5, 2, 151-157.
  • [6] Niessen W.J., Vincken K.L., Viergever M.A.: Multiscale vessel enhancement filtering. A.F. Frangi, MICCAI 1998, 130-137.
  • [7] Frangi A.F., Niessen W.J., Hoogeveen R.M., van Walsum T, Viergever M.A.: Model-based quantification of 3-D Magnetic Resonance Angiographic Images. IEEE Transaction on Medical Imaging 1999, 18, 10.
  • [8] Greig G., Koller Th., Szekely G., Brechbiihler Ch., Kiibler O.: Symbolic description of 3-D structures applied to cerebral vessel tree obtained from MR angiography volume data. Information Processeing in Medical Imaging 1993, 94-111.
  • [9] Greig G., Kubler O., Kikinis R., Jolesz F.A.: Nonlinear anisotropic filtering of MRI data. IEEE Transactions on Medical Imaging 1995 (92), 11, 2, 221-232.
  • [10] Hernandez-Hoyos M., Anwander A., Orkisz M., Roux J.-P., Douek P, Magnin I.E.: A deformable vessel model with single point initialisation for segmentation, quantification and visualisation of blood vessels in 3D MRA. MICCAI 2000, 735-745, Pittsburgh.
  • [11] Juhan V., Nazarian B., Malkani K., Bulot R., Bartoli J.M., Sequeira J.: Geometrical modelling of abdominal aortic aneurysms. CVRMed 1997, 243-252.
  • [12] Klose U., Petersen D., Martos T.J.: Tracking of cerebral vessels in MR angiography after higlipass filtering. Magnetic Resonance Imaging 1995, 13, 1, 45-51.
  • [13] Lehmann T.M., Gonner C., Spitzer K.: Survey: interpolation methods in medical image processing. IEEE Transactions on Medical Imaging 1999, 18, 11, 1049-1075.
  • [14] Lock T., Westin C.-F., Haglund L., et al.: Multidimensional adaptive filtering of MRA data. In Proceedings of Society of Magnetic Resonance and European Society for Magnetic Resonance in Medicine and Biology joint meeting, Nice, France, August 1995.
  • [15] Lorenz C., Carlsen I.-C., Buzug T.M., Fassnacht C., Wesse J.: Multi-scale line segmentation with automatic estimation of width, contrast and tangential direction in 2D an 3D medical images. CVRMed-MRCAS’97, Lecture Notes in Computer Science, Berlin, Germany: Springer-Verlag, 1205, 233-242, 1997.
  • [16] Lorigo L.M., Faugeras O., Grimson W.E.L., Keriven R., Kikinis R., Westin C.-F.: Codimension 2 geodesic active contours for MRA segmentation. IPMI 1999; 126-139, Lecture Notes in Computer Science, 1613, Springer 1999.
  • [17] Masutani Y., Schiemann T., Holme K.-H.: Vascular' shape segmentation and structure extraction using a shape-based region-growing model. MICCAI 1998, 1242-1249.
  • [18] Mclnerney T., Terzopoulos D.: Deformable models in medical image analysis: a survey. Medical Image Analysis 1996, 1, 2, 91-108.
  • [19] Mclnerney T., Terzopoulos D.: Medical image segmentation using topologically adaptable surface. CVRMed-MRCAS’97, Lecture Notes in Computer Science, Berlin, Germany: Springer-Verlag, 1205, 23-32, 1997.
  • [20] Meijering E.H.W., Zuidervelt K.J., Viergever M.A.: Image reconstruction by convolution with symmetrical piecewise nth order polynomial kernels. IEEE Transaction Image Processing 1999, 8, 192-201, February.
  • [21] Orkisz M., Douek P.C., Magnin I.E.: Anisotropic non-linear filtering for image improvements in MR angiography. Computer Assisted Radiology, International Compress Series 1996, 1224, 322-328.
  • [22] Reuze P., Coatrieux J.L., Luo L.M., Dillenseger J.L.: A 3-D moment based approach for blood vessel detection and quantification in MRA. Technology and Health Care 1993. 1. 181-188.
  • [23] Reuze P.: Analyse d’images de resonance magnetique, application a la segmentation des vaisseaux et a la characterisation des textures. Ph.D. Thesis, LTniversite de Rennesl, 1995.
  • [24] Roux C., Coatrieux J.L.: Contemporary Perspectives in Three-dimentional Biomedical Imaging. IOS Press, Amsterdam 1997.
  • [25] Sato Y., Nakajima S., Atsumi H., Roller T., Greig G., Yoshida S., Kikinis R.: 3D multi-scale line filter for segmentation and visualisation of curvilinear structures in medical images. CVRMed-MRCAS’97, Lecture Notes in Computer Science, Berlin. Germany: Springer-Verlag, 1205, 213-222, 1997.
  • [26] Sun Y., Parker D.L.: Performance analysis of maximum intensity projection algorithm for display of MRA images. IEEE Transactions on Medical Imaging 1999, 18, 12, 1154-1168.
  • [27] Toumoulin C., Boldak C., Dillenseger J.L., Coatrieux J.L., Rolland Y.: Fast detection and characterisation of vessels in very large 3-D data sets using geometrical moments. IEEE Transactions on Biomedical Engineering 2001, 48, 5, 604-606.
  • [28] Triki O., Boldak C., Rolland Y., Lebruno B., Toumoulin C.: Visualisation of lower limbs vessels on angio-scanner images by removing bones. Proc. lleme Forum des Jeunes Chercheurs GBM, 74-75, Compiegne, 5-6 June 2001.
  • [29] Trousset Y., Schieber D., Knoplioch J.: An algorithm for tracking vessels in three-dimensional angiograms. Proc. of the 14th IEEE-EMBS conf., Paris, 5, 2053-2054, October 1992.
  • [30] Vandermeulen D., Delaere D., Suetens P., et al.: Local filtering and global optimisation methods for 3D magnetic resonance angiography (MRA) image enhancement. Proc. VBC’92, 274-278, 1992.
  • [31] Wang K.C., Dutton R.W., Taylor Ch.A.: Improving geometric model construction for blood flow modeling. IEEE Engineering in Medicine and Biology 1999, 18, 6, 33-39.
  • [32] Wilson D.L., Noble J.A.: An adaptive segmentation algorithm for time-of-flight MRA data. IEEE Transactions on Medical Imaging 2000, 18, 10, 938-945.
  • [33] Wink O., Niessen W.J., Vierger M.A.: Fast Delineation and Visualisation of Vessels in 3-D Angiographic Images. IEEE Transactions on Medical Imaging, 19, 4, 337-346, April 2000.
  • [34] Yim P.J., Choyke P.L., Summers R.M.: Grey-scale skeletonisation of small vessels in magnetic resonance angiography. IEEE Transactions on Medical Imaging 2000, 19, 6, 568-576.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPZ1-0003-0037
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