Normalization of local contrast in mammograms

  title={Normalization of local contrast in mammograms},
  author={Wouter J. H. Veldkamp and Nico Karssemeijer},
  journal={IEEE Transactions on Medical Imaging},
Equalizing image noise has been shown to be an important step in automatic detection of microcalcifications in digital mammograms. In this study, an accurate adaptive approach for noise equalization is presented and investigated. No additional information obtained from phantom recordings is improved in the method, which makes the approach robust and independent of film type and film development characteristics. Furthermore, it is possible to apply the method on direct digital mammograms as well… CONTINUE READING

From This Paper

Figures, tables, and topics from this paper.


Publications citing this paper.
Showing 1-10 of 36 extracted citations

Multimodal representation learning with neural networks

John Edilson Arevalo Ovalle
View 1 Excerpt

Case-adaptive decision rule for detection of clustered microcalcifications in mammograms

2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI) • 2015
View 1 Excerpt

Improving uniformity in detection performance of clustered microcalcifications in mammograms

2015 IEEE International Conference on Image Processing (ICIP) • 2015
View 1 Excerpt


Publications referenced by this paper.
Showing 1-10 of 16 references

Development of a Multi-Feature Cad System for Mammography

Digital Mammography / IWDM • 1998
View 1 Excerpt

Physical and psychophysical evaluation of digital systems for mammography

H. Roehrig, E. Krupinski, T. Yu
Proc. SPIE 2436 , 1995, pp. 124–134. • 1995
View 1 Excerpt

Dense feature maps for detection of calcifications

W. P. Kegelmeyer, M. C. Allmen
inDigital Mammography , A. G. Gale, S. M. Astley, D. R. Dance, and A. Y. Cairns, Eds. Amsterdam: Elsevier, 1994, pp. 3–12. • 1994
View 2 Excerpts

Similar Papers

Loading similar papers…