Abstract
A multi-scale segmentation technique for line-like structures in 2D and 3D medical images is presented. It is based on normalized second derivatives and on the eigenvector analysis of the Hessian matrix. The method allows for the estimation of the local diameter, the longitudinal direction and the contrast of line-structures and for the distinction between edge-like and line-like structures. The characteristics of the method in respect to several analytic line-profiles as well as the influence of neighboring structures and line-bending is discussed. The method is applied to 3D medical images.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
G. Gerig, Th. Koller, G. Székely, Ch. Brechbühler & O. Kübier, Segmentation and Symbolic Description of Cerebral Vessel Structure based on MR Angiography Volume Data, Computer Assisted Radiology, Proceedings of the International Symposium. CAR'93 Berlin 359 (1993).
Th. M. Koller, G. Gerig, G. Székely & D. Dettwiler, Multiscale Detection of Curvilinear Structures in 2-D and 3D Image Data, Fifth International Conference on Computer Vision (June 20–23), Cambridge, MA, USA, 864 (1995).
C. Lorenz, I.-C. Carlsen, Th. M. Buzug, C. Fassnacht & J. Weese, Multi-scale line segmentation with automatic estimation of width, contrast and tangential direction in 2D and 3D medical images Computer Vision, Virtual Reality and Robotics in Medicine, CVRMed, Grenoble April 1997, No. 1205 in Lecture Notes in Computer Science (Springer-Verlag, Berlin Heidelberg, 1997), p. 233–242.
D. Ziou, Line detection using an optimal IIR filter, Pattern Recognition 24, 465 (1991).
J. Canny, A Computational Approach to Edge Detection, IEEE Trans. Patt. Anal. Mach. Intel. 8, 679 (1986).
V. S. Nalwa & T. O. Binford, On Detecting Edges, IEEE Trans. Patt. Anal. Mach. Intel. 8, 699 (1986).
V. Torre & T. A. Poggio, On Edge Detection, IEEE Trans. Patt. Anal. Mach. Intel. 8, 147 (1986).
W. T. Freeman & E. H. Adelson, The Design and Use of Steerable Filters, IEEE Trans. Patt. Anal. Mach. Intel. 13, 891 (1991).
T. Lindeberg, in Scale-Space Theory in Computer Vision (Kluwer Academic Publishers, Dordrecht, 1994).
K. Ottenberg, H. Neumann & H. S. Stiehl, Quantitative Description and Reconstruction of Intensity Functions using Scale-Space and Multiresolution Processing in Signal Processing VI, Theories and Applications, (Proceedings of EUSIPCO-92) (Elsevier, Amsterdam, 1992), Vol. III, p. 1425–1429.
W. Beil, Line detection discrete scale-space in Proceedings ICIP-94 (IEEE Comput. Soc. Press, Los Alamitos, CA, USA, 1994), p. 915–18.
D. Eberly, R. Gardner, B. Morse, S. Pizer & C. Scharlach, Ridges for Image Analysis, Technical Report TR93-055, University of North Carolina Chapel Hill, USA (1994).
L. M. J. Florack, B. M. ter Haar Romeny, J. J. Koenderink & M. A. Viergever, Scale and the differential structure of images, Image and vision computing 10, 376 (1992).
T. Lindeberg, On scale selection for differential operators, 8th SCIA 857 (1993).
T. Lindeberg, Edge detection and ridge detection with automatic scale selection, Proc. IEEE Comp. Soc. Conf. on Computer Vision and Pattern Recognition (San Francisco, California) 465 (1996).
Th. M. Koller, From Data to Information: Segmentation, Description and Analysis of the Cerebral Vascularity (ETH PhD 11367), Dissertation, Swiss Federal Insitute of Technology, Zürich, 1996.
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1997 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Lorenz, C., Carlsen, I.C., Buzug, T.M., Fassnacht, C., Weese, J. (1997). A multi-scale line filter with automatic scale selection based on the Hessian matrix for medical image segmentation. In: ter Haar Romeny, B., Florack, L., Koenderink, J., Viergever, M. (eds) Scale-Space Theory in Computer Vision. Scale-Space 1997. Lecture Notes in Computer Science, vol 1252. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-63167-4_47
Download citation
DOI: https://doi.org/10.1007/3-540-63167-4_47
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-63167-5
Online ISBN: 978-3-540-69196-9
eBook Packages: Springer Book Archive