Normalization of local contrast in mammograms

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...

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Bibliographic Details
Published in:IEEE transactions on medical imaging 2000-07, Vol.19 (7), p.731-738
Main Authors: Veldkamp, W.J.H., Karssemeijer, N.
Format: Article
Language:English
Subjects:
Adaptive equalizers
Additive noise
Biological and medical sciences
Breast cancer
Breast Neoplasms - diagnostic imaging
Calcinosis - diagnostic imaging
Female
Gray-scale
Gynecology. Andrology. Obstetrics
Humans
Image Processing, Computer-Assisted - methods
Imaging phantoms
Mammary gland diseases
Mammography
Mammography - methods
Medical sciences
Noise
Noise level
Noise measurement
Noise robustness
Radiographic Image Enhancement - methods
Studies
Tumors
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Summary: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. In this study, the adaptive approach is optimized by investigating a number of alternative approaches to estimate the image noise. The estimation of high-frequency noise as a function of the grayscale is improved by a new technique for dividing the grayscale in sample intervals and by using a model for additive high-frequency noise. It is shown that the adaptive noise equalization gives substantially better detection results than does a fixed noise equalization. A large database of 245 digitized mammograms with 341 clusters was used for evaluation of the method.
ISSN:0278-0062
1558-254X
DOI:10.1109/42.875197