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3D thinning and its applications to medical image processing

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
A skeleton is a frequently-used feature to represent the general form of an object. The importance of this region-based shape feature is growing in medical image processing, too. This paper summarizes the major skeletonization approaches, the 3D parallel thinning methodologies and some emerging medical applications. An application to calculate the cross-sectional profiles of blood vessels is also presented.
Rocznik
Strony
397--408
Opis fizyczny
Bibliogr. 32 poz., rys.
Twórcy
autor
  • Department of Applied Informatics, Jozsef Attila University, H-6701 Szeged P.O. Box 652, Hungary
autor
  • Department of Radiology, Karl Franzens University, Auengruggerplatz 34, A-8036, Graz, Austria
autor
  • Department of Applied Informatics, Jozsef Attila University, H-6701 Szeged P.O. Box 652, Hungary
autor
  • Department of Applied Informatics, Jozsef Attila University, H-6701 Szeged P.O. Box 652, Hungary
Bibliografia
  • [1] Bertrand G. and Aktouf Z., A 3D thinning algorithms using subfields, in Proc. SPIE Conf. on Vision Geometry III 2356,113-124,1994
  • [2] Bertrand G., A parallel thinning algorithm for medial surfaces, Pattern Recognition Letters 16,979-986,1995
  • [3] Blum H., A transformation for extracting new descriptors of shape, Symposium on Models for the perception of Speech and Visual Form, 1964
  • [4] Borgefors G., Distance transformations in arbitrary dimensions, Computer Vision, Graphics, and Image Processing 27,321 -345,1984
  • [5] Borgefors G., Hierarchical chamfer matching: A parametric edge matching algorithm, IEEE Transactions on Pattern Analysis and Machine Intelligence 10, 849-865,1988
  • [6] Brandt J.W. and Algazi V.R., Continuous skeleton computation by Voronoi diagram, CVGIP: Image Understanding 55,329-338,1992
  • [7] Calabi L. and Hartnett W.E., Shape recognition, prairie fires, convex deficiencies and skeletons, Am. Math. Monthly 75,335-342, 1968
  • [8] Carey R. and Bell G., The Annotated VRML 2.0 Reference Manual, in The VRML 2.0 Handbook: Building Moving Worlds on the Web, Eds.: Hartmann J„ Wemecke J., Carey R., Addison-Wesley Devekopers Press, 197,1996
  • [9] Connan T.H., Leiserson C.E. and Rivest R.L., Introduction to Algorithms, MIT Press, 1993
  • [10] Ge Y., Stelts D.R. and Vining D.J., 3D skeleton for virtual colonoscopy, in Proc. 4lh Int. Conf. Visualization in Biomedical Computing, VBC’96, Lecture Notes in Computer Science 1131, Springer, 449-454,1996
  • [11] Gerig G., Roller Th., Szekely G., Brechbiihler Ch. and Kiibler O., Symbolic description of 3-D structures applied to cerebral vessel tree obtained from MR angiography volume data, in Proc. 13th Int. Conf. Information Processing in Medical Imaging, IPMI’93, Lecture Notes in Computer Science 687, Springer-Verlag, 94—111,1993
  • [12] Gong W.X. and Bertrand G., A simple parallel 3D thinning algorithm, in Proceedings 10th IEEE International Conference on Pattern Recognition, 188-190,1990
  • [13] Jiang H., Robb A. and Holton K.S., A new approach to 3-D registration of multimodality medical images by surface matching, in Proc. SPIE Conf. on Visualization in biomedical computing 1808,196-213,1992
  • [14] Kong T.Y. and Rosenfeld A., Digital topology: Introduction and survey. Computer Vision, Graphics, and Image Processing 48,357-393,1989
  • [15] Kong T.Y., On topology’ preservation in 2-D and 3-D thinning, Int. J. of Pattern Recognition and Artifical Intelligence 9, 813-844, 1995
  • [16] Lee T., Kashyap R.L. and Chu C., Building skeleton models via 3-D medial surface/ axis thinning algorithms, CVGIP: Graphical Models and Image Processing 56,462- 478,1994
  • [17] Ma C.M., A 3D fully parallel thinning algorithm for generating medial faces, Pattern Recognition Letters 16,83-87,1995
  • [18] Ma C.M. and Sonka M., A fully parallel 3D thinning algorithm and its applications, Computer Vision and Image Understanding 64,420^-33, 1996
  • [19] Manzanera A., Bernard T.M., Preteux F. and Longuet B., Medial faces from a concise 3D thinning algorithm, in Proc. 7th IEEE Int. Corif. on Computer Vision, ICCV’99,1999, to appear
  • [20] Morgenthaler D.G., Three-dimensional simple points: Serial erosion, parallel thinning and skeletonization, TR-1005, Computer Vision Laboratory, Computer Science Center, Univ. of Maryland, College Park, MD., 1981
  • [21] Naf M„ Szekely G., Kikinis R., Shenton M.E. and Kiibler G., 3D Voronoi skeletons and their usage for the characterization and recognition of 3D organ shape, Computer Vision, Graphics, and Image Processing 66,147-161,1997
  • [22] Palagyi K. and Kuba A., A 3D 6-subiteration thinning algorithm for extracting medial lines, Pattern Recognition Letters 19,613-627,1998
  • [23] Palagyi K. and Kuba A., A hybrid thinning algorithm for 3D medical images, Journal ofComputing and Information Technology 6,149-164, 1998
  • [24] Palagyi K. and Kuba A., Directional 3D thinning using 8 subiterations, in Proc. 8,h Int. Conf. on Discrete Geometry for Computer Imagery, DGCI’99, Lecture Notes in Computer Science 1568, Springer, 325-336,1999
  • [25] Palagyi K. and Kuba A., A parallel 3D 12-subiteration thinning algorithm, Graphical Models and Image Processing 61,199-221,1999
  • [26] Rubin P. and Johnston N., Measurement of the Aorta and Its Branches with Helical CT, Radiology 206,823-829,1998
  • [27] Saha P.K., Chaudhury B.B. and Majumder D.D., A new shape-preserving parallel thinning algorithm for 3D digital images, Pattern Recognition 30, 1939-1955, 199'
  • [28] Szekely G., KollerTh., Kikinis R. and Gerig G., Structural description and combined 3-D display for superior analysis of cerebral vascularity from MRA, in Medical Imaging: Analysis of multimodality 2D/3D images, !OS Press, 183-194,1995
  • [29] Szekely G., Shape characterization by local symmetries, Habilitationsschrift, Institute for Communication Technology, Image Science Division, ETH Zurich, 1996
  • [30] Tari S., Shah J. and Pien H., Extraction of shape skeletons from grayscale images, Computer Vision and Image Understanding 66,133-146,1997
  • [31] Tsao Y.F. and Fu K.S., A parallel thinning algorithm for 3-D pictures, Computer Graphics and Image Processing 17,315-331,1981
  • [32] Van den Elsen P. A., Maintz J.B.A., Pol E.J.D. and Viergever M. A., Image fusion using geometrical features, in Proc. SP1E Conf. on Visualization in biomedical computing 1808,172-186,1992
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BAT3-0018-0033
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