Abstract
This paper studies the problem of detecting significant regions in medical image analysis. The solution of this non well-defined problem requires in general several criteria to attempt to measure the relevance of an input image features. Criteria properties are important in medical imaging in order to permit their application in a variety of situations. We adopt in this paper the morphological framework, which facilitates the study of the problem and, in addition, provides useful pre-processing and image analysis techniques.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Coster, M., Chermant, J.: Précis d’Analyse d’Images. Presses du CNRS (1989)
Haralick, R., Shapiro, L.: Computer and Robot Vision. Vol. I. Reading, Massachusetts: Adison-Wesley Publishing Company (1992)
Haralick, R., Shapiro, L.: Computer and Robot Vision. Vol. II. Reading, Massachusetts: Adison-Wesley Publishing Company (1992)
Serra, J.: Mathematical Morphology. Volume I. London: Academic Press (1982)
Serra, J., ed.: Mathematical Morphology. Volume II: theoretical advances. London: Academic Press (1988)
Giardina, C., Dougherty, E.: Morphological Methods in Image and Signal Processing. Englewood Clliffs: Prentice-Hall (1988)
Beucher, S., Meyer, F.: The morphological approach to segmentation: the watershed transformation. In Dougherty, E., ed.: Mathematical morphology in image processing. New York: Marcel Dekker (1993) 433–481
Soille, P.: Morphological Image Analysis: Principles And Applications. Springer-Verlag Berlin, Heidelberg, New York (1999)
Salembier, P., Serra, J.: Flat zones filtering, connected operators, and filters by reconstruction. IEEE Transactions on Image Processing 4 (1995) 1153–1160
Crespo, J., Serra, J., Schafer, R.: Theoretical aspects of morphological filters by reconstruction. 47 (1995) 201–225
Crespo, J., Schafer, R.: Locality and adjacency stability constraints for morphological connected operators. Journal of Mathematical Imaging and Vision 7 (1997) 85–102
Crespo, J., Maojo, V.: New results on the theory of morphological filters by reconstruction. Pattern Recognition 31 (1998) 419–429
Crespo, J., Maojo, V.: Shape preservation in morphological filtering and segmentation. In: XII Brazilian Symposium on Computer Graphics and Image Processing, IEEE Computer Society Press. (1999) 247–256
Crespo, J., Schafer, R., Maojo, V.: Image segmentation using intra-region averaging techniques. Optical Engineering 37 (1998) 2926–2936
Vincent, L., Soille, P.: Watersheds in digital spaces: An efficient algorithm based on immersion simulations. IEEE Trans. Pattern Anal. Machine Intell. 13 (1991) 583–598
Crespo, J., Schafer, R., Serra, J., Gratin, C., Meyer, F.: The flat zone approach: A general low-level region merging segmentation method. Signal Processing 62 (1997) 37–60
Salembier, P.: Morphological multiscale segmentation for image coding. Signal Processing 38 (1994) 359–386
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Crespo, J., Billhardt, H., Rodríguez-Pedrosa, J., Sanandrés, J.A. (2001). Methods and Criteria for Detecting Significant Regions in Medical Image Analysis. In: Crespo, J., Maojo, V., Martin, F. (eds) Medical Data Analysis. ISMDA 2001. Lecture Notes in Computer Science, vol 2199. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45497-7_3
Download citation
DOI: https://doi.org/10.1007/3-540-45497-7_3
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42734-6
Online ISBN: 978-3-540-45497-7
eBook Packages: Springer Book Archive