The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
Region-based contrast enhancement of mammograms
Abstract
Diagnostic features in mammograms vary widely in size and shape. Classical image enhancement techniques cannot adapt to the varying characteristics of such features. An adaptive method for enhancing the contrast of mammographic features of varying size and shape is presented. The method uses each pixel in the image as a seed to grow a region. The extent and shape of the region adapt to local image gray-level variations, corresponding to an image feature. The contrast of each region is calculated with respect to its individual background. Contrast is then enhanced by applying an empirical transformation based on each region's seed pixel value, its contrast, and its background. A quantitative measure of image contrast improvement is also defined based on a histogram of region contrast and used for comparison of results. Using mammogram images digitized at high resolution (less than 0.1 mm pixel size), it is shown that the validity of microcalcification clusters and anatomic details is considerably improved in the processed images.
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Cites
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An evaluation of the effectiveness of adaptive histogram equalization for contrast enhancement
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Cited by
Transform coefficient histogram-based image enhancement algorithms using contrast entropy
Agaian, S. S., Silver, B., & Panetta, K. A. (2007) · IEEE Transactions on Image Processing · doi:10.1109/tip.2006.888338 · Cited by 575
Approaches for automated detection and classification of masses in mammograms
Cheng, H. D., Shi, X. J., Min, R., Hu, L. M., Cai, X. P., & Du, H. N. (2006) · Pattern Recognition · doi:10.1016/j.patcog.2005.07.006 · Cited by 538
Transform-based image enhancement algorithms with performance measure
Agaian, S. S., Panetta, K., & Grigoryan, A. M. (2001) · IEEE Transactions on Image Processing · doi:10.1109/83.908502 · Cited by 411
A review of computer-aided diagnosis of breast cancer: Toward the detection of subtle signs
Rangayyan, R. M., Ayres, F. J., & Leo Desautels, J. E. (2007) · Journal of the Franklin Institute · doi:10.1016/j.jfranklin.2006.09.003 · Cited by 337
Self-citationImage enhancement using a contrast measure in the compressed domain
Tang, J., Peli, E., & Acton, S. (2003) · IEEE Signal Processing Letters · doi:10.1109/lsp.2003.817178 · Cited by 287
Metadata
- Authors
- Morrow, W. M., Paranjape, R. B., Rangayyan, R. M., & Desautels, J. E. L.
- Venue
- IEEE Transactions on Medical Imaging
- Published
- 1992
- Volume
- 11
- Issue
- 3
- Pages
- 392-406
- ISSN
- 0278-0062 (ISSN-L)
- OpenAlex
- W2076293758
- Cited by
- 337
- References
- 19
- FWCI
- 6.81
- Type
- journal article
- Language
- en
- Open access
- closed
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- Morrow, W. M., Paranjape, R. B., Rangayyan, R. M., & Desautels, J. E. L. (1992). Region-based contrast enhancement of mammograms. IEEE Transactions on Medical Imaging. https://doi.org/10.1109/42.158944
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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