Abstract
This paper presents an improved method for detection of “significant” low-level objects in medical images. Information derived from watershed regions is used to select and refine saddle points in the discrete domain and to construct the watersheds & watercourses (ridges and valleys). The method overcomes previous topological problems where multiple redundant saddle points are detected in digital images. We also demonstrate an improved method of pruning the tessellation from which salient objects are defined. Preliminary evaluation was based on theoretical analysis, visual inspection of a set of medical images, and human observer experiments with promising result.
Chapter PDF
Similar content being viewed by others
References
Bieniek, A.: An efficient watershed algorithm based on connected components. Pattern Recognition 33, 907–916 (2000)
Chen, Z., Molloi, S.: Vascular tree object segmentation by deskeletonization of valley courses. Computerized Medical Imaging and Graphics 26, 419–128 (2002)
Gauch, J.M., Pizer, S.M.: The Intensity Axis of Symmetry and Its Application to Image Segmentation. IEEE Transaction on PAMI 15(8), 753–770 (1993)
Griffin, L.D., Colchester, A.C.F., Robinson, G.P.: Scale and segmentation of greylevel images using maximum gradient paths. Image and Vision Computing 10(6), 389–402 (1992)
Lopez, A.M.: Multilocal Methods for Ridge and Valley Delineation in Image Analysis. PhD thesis, The Universitat Autonoma de Barcelona (2000)
Nackman, L.R.: Tow-Dimensional Critical Point Configuration Graphs. IEEE Transaction on PAMI 6(4), 442–450 (1984)
Rosin, P.L.: Early Image Representation by Slope Districts. Journal of Visual Communication and Image Representation 6(3), 228–243 (1995)
Scott, P.: An Algorithm to Extract Critical Points from Lattice Height Data. International Journal of Machine Tools and Manufacture 41, 1889–1897 (2001)
Stewart, I.: A Swift Trip over Rugged Terrain-Mathematical recreations. Scientific American, 89–91 (June 1991)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2003 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Fu, G., Hojjat, S.A., Colchester, A.C.F. (2003). Detection of Objects by Integrating Watersheds and Critical Point Analysis. In: Ellis, R.E., Peters, T.M. (eds) Medical Image Computing and Computer-Assisted Intervention - MICCAI 2003. MICCAI 2003. Lecture Notes in Computer Science, vol 2879. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-39903-2_14
Download citation
DOI: https://doi.org/10.1007/978-3-540-39903-2_14
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-20464-0
Online ISBN: 978-3-540-39903-2
eBook Packages: Springer Book Archive