Quality Assessment of Mammogram Image Enhancement

In this article, we present a MATLAB-based framework for quality assessment of mammogram image enhancement. The implementation employs two quantitative evaluation methods: contrast measurement and Detail Strength Measure (DSM) analysis, providing objective metrics to compare different enhancement techniques. The contrast evaluation algorithm calculates pixel intensity variations using histogram analysis and standard deviation metrics, while the DSM method assesses detail preservation through frequency domain analysis and edge detection filters. The code structure includes preprocessing modules for image normalization, enhancement algorithm interfaces, and post-processing evaluation functions using MATLAB's Image Processing Toolbox. Key functions involve imread() for image loading, imadjust() for contrast manipulation, and custom implementations for Fourier transform-based frequency analysis. Additional discussions cover fundamental concepts in mammogram enhancement, including noise reduction techniques, contrast-limited adaptive histogram equalization (CLAHE) implementation, and multi-scale enhancement approaches. This comprehensive analysis enables deeper understanding of mammogram enhancement methodologies and their quantitative assessment.