Abstract
Morphological connected set filters for extraction of filamentous details from medical images are developed. The advantages of these filters are that they are shape preserving and do not amplify noise. Two approaches are compared: (i) multi-scale filtering (ii) single-step shape filtering using connected set (or attribute) thinnings. The latter method highlights all filamentous structure in a single filtering stage, regardless of the scale. The second approach is an order of magnitude faster than the first, filtering a 2563 volume in 41.65 s on a 400 MHz Pentium II.
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References
E. J. Breen and R. Jones. Attribute openings, thinnings and granulometries. Computer Vision and Image Understanding, 64(3):377–389, 1996.
F. Cheng and A. N. Venetsanopoulos. An adaptive morphological filter for image processing. IEEE Trans. Image Proc., 1:533–539, 1992.
Y. P. Du and D. L. Parker. Vessel enhancement filtering in three-dimensional MR angiograms using long-range signal correlation. J. Magn. Reson. Imag., 7:447–450, 1997.
A. F. Frangi, W. J. Niessen, K. L. Vincken, and M. A. Viergever. Multiscale vessel enhancement filtering. In W. M. Wells, A. Colchester, and S. Delp, editors, Medical Image Computing and Computer-Assisted Intervention–MICCAI’98, volume 1496 of Lecture Notes in Computer Science, pages 130–137. Springer, 1998.
H. J. A. M. Heijmans. Connected morphological operators for binary images. Comput. Vis. Image Understand., 73:99–120, 1999.
M. Orkisz, M. Hernández-Hoyos, P. Douek, and I. Magnin. Advances of blood vessel morphology analysis in 3D magnetic resonance images. Mach. Vis. Graph., 9:463–471, 2000.
P. Salembier, A. Oliveras, and L. Garrido. Anti-extensive connected operators for image and sequence processing. IEEE Transactions on Image Processing, 7:555–570, 1998.
Y. Sato, S. Nakajima, N. Shiraga, H. Atsumi, S. Yoshida, T. Koller, G. Gerig, and R. Kinikis. 3D multi-scale line filter for segmentation and visualization of curvilinear structures in medical images. Medical Image Analysis, 2:143–168, 1998.
A. Spohr, T. Agger, M. Carlsen, and J. Nielsen. Quantitative morphology of filamentous micro-organisms. In M. H. F. Wilkinson and F. Schut, editors, Digital Image Analysis of Microbes, pages 373–410. John Wiley and Sons, Ltd, Chichester, UK, 1998.
E. R. Urbach and M. H. F. Wilkinson. Shape distributions and decomposition of grey scale images. IWI-report 2000-9-15, Institute for Mathematics and Computing Science, University of Groningen, 2001.
L. Vincent. Morphological grayscale reconstruction in image analysis: application and efficient algorithm. IEEE Transactions on Image Processing, 2:176–201, 1993.
M. H. F. Wilkinson and J. B. T. M. Roerdink. Fast morphological attribute operations using Tarjan’s union-find algorithm. In Proceedings of the ISMM2000, pages 311–320, Palo Alto, CA, June 2000.
O. Wink, W. J. Niessen, and M. A. Viergever. Fast delineation and visualization of vessels in 3-D angiographic images. IEEE Transactions on Medical Imaging, 19:337–346, 2000.
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© 2001 Springer-Verlag Berlin Heidelberg
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Wilkinson, M.H.F., Westenberg, M.A. (2001). Shape Preserving Filament Enhancement Filtering. In: Niessen, W.J., Viergever, M.A. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2001. MICCAI 2001. Lecture Notes in Computer Science, vol 2208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45468-3_92
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DOI: https://doi.org/10.1007/3-540-45468-3_92
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