Abstract
A new algorithm for feature and contrast enhancement of mammographic images is proposed in this paper. The approach is based on multiscale transform and mathematical morphology. First of all, the Laplacian Gaussian pyramid transform is applied to decompose the mammography into different multiscale subband sub-images. In addition, the detail or high frequency sub-images are equalized by the contrast limited adaptive histogram equalization (CLAHE) and low frequency sub-images are processed by mathematical morphology. Finally, the enhanced image of feature and contrast is reconstructed from the Laplacian Gaussian pyramid coefficients modified at one or more levels by CLAHE and mathematical morphology. The enhanced image is processed by global non-linear operator in order to obtain natural result. The experimental results show that the presented algorithm is effective for feature and contrast enhancement of mammogram. The performance evaluation of the proposed algorithm is contrast evaluation criterion for image, signal-noise-ratio (SNR) and contrast improvement index (CII).
Highlights
Breast cancer has been a significant public health problem for women in the world and early detection of breast cancer is very essential in the field of medicine before the means to prevent breast cancer have not yet been found
To demonstrate the effectiveness of our method, we compared its results with the existing popular methods of histogram equalization (HE), adaptive histogram equalization (AHE), the algorithm of nonlinear multiscale processing based on Laplace pyramid proposed in [10], and the method based on morphology and wavelet transform
We take the advantage of the metrics of contrast evaluation criterion, SNR, and contrast improvement index (CII) to measure the quantitative performance analysis of the proposed method
Summary
Breast cancer has been a significant public health problem for women in the world and early detection of breast cancer is very essential in the field of medicine before the means to prevent breast cancer have not yet been found. It is well known that the early detection and treatment of breast cancer are the most effective key means of reducing mortality. Mammography is widely recognized as being the only effective and primary imaging modality for the early detection and diagnosis of breast cancer [3,4,5]. Low dose X-ray is used for imaging. The mammographic images are poor in contrast and contaminated due to the low dose Xray for imaging. [6] introduced that mammographers miss about
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