Abstract
A stochastic model is developed to enable pattern classification in mammograms based on Bayesian decision theory. Labeling of the image is performed by a deterministic relaxation scheme in which both image data and prior beliefs are weighted simultaneously. The image data is represented by two parameter images representing local contrast and shape. Involving shape is necessary to distinguish thin patches of connective tissue from microcalcifications. A random field models contextual relations between pixel labels. Long range interaction is introduced to express the fact that calcifications do occur in clusters. This ensures that faint spots are only interpreted as calcifications if they are in the neighborhood of others.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
References
Astley S M and Taylor C J (1990) Combining cues for mammographic abnormalities. Proc. 1st. Brit. Mach. Vision Conf., 253–258.
Ballard D H (1984) Parameter nets. Artificial Intelligence 22:235–267
Besag J E (1986) On the statistical analysis of dirty pictures. J. Royal. Statist. Soc., Ser. B 48:259–302
Chan H P, Doi K, Vyborny C J, Lam K L and Schmidt R A (1988) Computer-Aided detection of micro-calcifications in mammograms. Invest. Radiol. 23 (9): 664–671.
Davies D H and Dance D R (1990) Automatic computer detection of clustered calcifications in digital mammograms. Phys. Med. Biol. 35 (8): 1111–1118.
Dubes R C, Jain A K (1989) Random field models in image analysis. Journal of Applied Statistics 16 (2):131–164
Fam B H, Olson S L, Winter P F and Scholz F J (1988) Algorithm for the detection of fine clustered calcifications on film mammograms. Radiology 169 (2):333–337
Geman S, Geman D (1984) Stochastic relaxation, Gibbs distributions and the Bayesian restoration of images. IEEE Trans. Pattern. Anal. Machine. Intell. 6:721–741
Holland R, Hendriks J H C L, Verbeek A L M, Mravunac M, and Schuurmans J H (1990) Extent, distribution, and mammographic/histological correlations of breast ductal carcinoma in situ. Lancet, 335:519–522.
Illingworth J and Kittler J (1988) A survey of the Hough Transform. Comp. Vision, Graph. and Im. Proc. 44:87–116
Karssemeijer N (1989) A statistical method for automatic labeling of tissues in medical images. Mach. Vision and Appl. 3:75–86
Karssemeijer N and van Erning L J Th O (1991) Iso-precision scaling of digitized mammograms to facilitate image analysis. SPIE Med. Im. V, Image Processing (in press)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 1991 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Karssemeijer, N. (1991). A stochastic model for automated detection of calcifications in digital mammograms. In: Colchester, A.C.F., Hawkes, D.J. (eds) Information Processing in Medical Imaging. IPMI 1991. Lecture Notes in Computer Science, vol 511. Springer, Berlin, Heidelberg. https://doi.org/10.1007/BFb0033756
Download citation
DOI: https://doi.org/10.1007/BFb0033756
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-54246-9
Online ISBN: 978-3-540-47521-7
eBook Packages: Springer Book Archive