Enhancing Breast Cancer Detection: A Comparative Analysis of Pre-Processing Techniques for Mammogram Image
Guru Maheswari M, K. Karthigadevi, Elizabeth Rani G, M Sakthimohan · 2024
In this paper, we have applied several strategies for noise reduction, picture enhancement, and feature extraction and presented an overview of mammography image preprocessing techniques. A number of approaches are used during the preprocessing of mammography images with the goal of increasing the detection accuracy of breast cancer. Noise reduction is one of the methods. A number of things, including movements from the patient, image collecting equipment, and random fluctuations in the data, might produce noise. Gaussian noise and salt and pepper have an impact on the image's accuracy. Finding and diagnosing breast cancer requires preprocessing the mammography pictures. Preprocessing aims to minimize picture complexity, eliminate noise and artefacts, and improve the quality of the mammography images. The preparation methods for mammography images—such as image filtering, segmentation, normalization, and feature extraction—were covered in our proposed study. By enhancing the mammography pictures' contrast, sharpness, and clarity, these methods facilitate the identification and diagnosis of breast cancer. Because preprocessing can assist uncover anomalies in the breast tissue that may suggest the existence of breast cancer, preprocessing mammogram pictures is essential to enhancing the accuracy and efficiency of mammography analysis.