Enhancement of Mammographic Images
Prachi Mujawar · IOSR Journal of Engineering · 2014
Mammography is an effective method for breast cancer detection and breast tumour analysis.In mammography, low dose x-ray is used for imaging, due to which the images are poor in contrast and are contaminated by noise.Hence it is difficult for the radiologist to screen the mammograms for diagnostic signs such as micro calcifications and masses.This ensures the need for image enhancement to aid radiologist.In this paper, we present an algorithm for enhancement of digital mammographic images.The proposed methodology uses mathematical morphology for contrast enhancement and wavelet for denoising.The main contribution of this report is in differentiating the edge pixels from noise.We adopt wavelet-based level dependent thresholding algorithm and modified mathematical morphology algorithm to increase the contrast in mammograms to ease extraction of suspicious regions known as regions of interest (ROIs).The proposed algorithm has been tested on a large number of clinical images, comparing the results with those obtained by several other algorithms.A quantitative measure of Contrast Improvement Index (CII) is used to evaluate the performance of the algorithm.Experimental results show that the proposed algorithm gives significantly superior image quality and better Contrast Improvement Index (Cll).Here, to prove the efficiency of this method, we have compared this with various well-known algorithms like VisuShrink and NormalShrink.Through preliminary tests; the method seems to meaningfully improve the diagnosis in the early breast cancer detection with respect to other approaches.