Histogram Modified Local Contrast Enhancement for mammogram images

Early detection of breast cancer in the mammograms is very essential in the field of medicine. Contrast enhancement of mammograms based on Histogram Equalization (HE) is presented. Histogram equalization is an effective and simple technique for contrast enhancement. The standard histogram equalization (HE) usually results in excessive contrast enhancement because of lack of control on the level of enhancement. The Histogram Modified Local Contrast Enhancement (HM-LCE) is introduced in this paper to adjust the level of contrast enhancement, which in turn gives the resultant image a strong contrast and also brings the local details present in the original image for more relevant interpretation. It incorporates a two stage processing both histogram modifications as an optimization technique and a local contrast enhancement technique. This method is tested for Mias mammogram images. The performance of this method is determined using three parameters like Enhancement Measure (EME), Absolute Mean Brightness Error (AMBE) and Discrete Entropy (H) for all 22 numbers of Mias mammogram images with microcalcification. It's enhancement potential is also tested by sobel and otsu methods for the detection of microcalcification in the mammogram image. From the subjective and quantitative measures it is interesting that this proposed technique provides optimum results by giving better contrast enhancement and preserving the local information of the original mammogram images in the Mias data base and the method has increased the detectability of micro calcifications present in the given mammogram image.

[1]  Rangaraj M. Rangayyan,et al.  Adaptive-neighborhood histogram equalization for image enhancement , 1992, CVGIP Graph. Model. Image Process..

[2]  Daniel S. Miller,et al.  Annual report to the nation on the status of cancer, 1973-1996, with a special section on lung cancer and tobacco smoking. , 1999, Journal of the National Cancer Institute.

[3]  Rafael C. González,et al.  Local Determination of a Moving Contrast Edge , 1985, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Giovanni Ramponi,et al.  Image enhancement via adaptive unsharp masking , 2000, IEEE Trans. Image Process..

[5]  L P Clarke,et al.  Interpretation of calcifications in screen/film, digitized, and wavelet-enhanced monitor-displayed mammograms: a receiver operating characteristic study. , 1996, Academic radiology.

[6]  R M Rangayyan,et al.  Feature enhancement of film mammograms using fixed and adaptive neighborhoods. , 1984, Applied optics.

[7]  Karel J. Zuiderveld,et al.  Contrast Limited Adaptive Histogram Equalization , 1994, Graphics Gems.

[8]  Alberto Costa,et al.  Cancer of the breast , 1962 .

[9]  Jong Kook Kim,et al.  Adaptive mammographic image enhancement using first derivative and local statistics , 1997, IEEE Transactions on Medical Imaging.

[10]  Azeddine Beghdadi,et al.  Contrast enhancement technique based on local detection of edges , 1989, Comput. Vis. Graph. Image Process..

[11]  Abd. Rahman Ramli,et al.  Minimum mean brightness error bi-histogram equalization in contrast enhancement , 2003, IEEE Trans. Consumer Electron..

[12]  Malur K. Sundareshan,et al.  Adaptive image contrast enhancement based on human visual properties , 1994, IEEE Trans. Medical Imaging.

[13]  Andrew S. Glassner,et al.  Graphics Gems , 1990 .

[14]  M. Säbel,et al.  Recent developments in breast imaging. , 1996, Physics in medicine and biology.

[15]  R. Sivaramakrishna,et al.  Detection of breast cancer at a smaller size can reduce the likelihood of metastatic spread: a quantitative analysis. , 1997, Academic radiology.

[16]  John D. Austin,et al.  Adaptive histogram equalization and its variations , 1987 .

[17]  Sos S. Agaian,et al.  Transform-based image enhancement algorithms with performance measure , 2001, IEEE Trans. Image Process..

[18]  J. Alex Stark,et al.  Adaptive image contrast enhancement using generalizations of histogram equalization , 2000, IEEE Trans. Image Process..

[19]  Timothy J. Terry,et al.  Improvement of sensitivity of breast cancer diagnosis with adaptive neighborhood contrast enhancement of mammograms , 1997, IEEE Transactions on Information Technology in Biomedicine.

[20]  Theodore L. Economopoulos,et al.  Contrast enhancement of images using Partitioned Iterated Function Systems , 2010, Image Vis. Comput..

[21]  R. Gordon,et al.  Enhancement of Mammographic Features by Optimal Adaptive Neighborhood Image Processing , 1986, IEEE Transactions on Medical Imaging.

[22]  William J. Fitzgerald,et al.  An Alternative Algorithm for Adaptive Histogram Equalization , 1996, CVGIP Graph. Model. Image Process..