Mammography is widely used technique for breast cancer screening. There are
various other techniques for breast cancer screening but mammography is the most reliable
and effective technique. The images obtained through mammography are of low contra
st
which causes problem for the radiologists to interpret. Hence, a high quality image is
mandatory for the processing of the image for extracting any kind of information. Many
contrast enhancement algorithms have been developed over the years. This work presents a
method to enhancement Microcalcifications in digitized mammograms. The method is
based Mainly on the combination of Image Processing. The top-Hat and bottom–hat
transforms are a techniques based on Mathematical morphology operations. This
algorithm has been tested on mini-Mias database which have three types of breast tissues .
For evaluation of performance of image enhancement algorithm, the Contrast
Improvement Index (CII) and Peak Signal to Noise Ratio (PSNR) have been used.
Experimental results suggest that algorithm can be improve significantly overall
detection of the Computer-Aided Diagnosis (CAD) system especially for dense breast.