Multi-stage System for Preprocessing Mammograms

다국어 초록 (Multilingual Abstract)

Breast image analysis is important for the detection and diagnosis of various diseases, but more specifically, breast cancer. The most popular and widely used screening tool is mammography. It gives a better result than other screening tools for breast image analysis. Mammograms are difficult to analyze because of noise, poor quality, artifacts, and the inclusion of pectoral muscle. The technique proposed in this paper has several stages for preprocessing mammograms. First, artifacts and the background are removed by changing the original image into a binary image using Otsu’s thresholding. The medio-lateral view of mammography images has two orientations: left or right. Orientation detection in the next step is important for pectoral muscle removal, which is done using the line segment method. Contrast is enhanced using contrast limited adaptive histogram equalization, and noise is reduced using a median filter. The proposed technique was applied to a publicly available dataset from the Mammographic Image Analysis Society, from which 322 images were analyzed, and performance parameters calculated. After calculations for accuracy, sensitivity, and specificity, the accuracy achieved was 94.62%, sensitivity achieved was 90.21%, and specificity was 97.20%.

목차 (Table of Contents)

• Abstract
• 1. Introduction
• 2. Related Work
• 3. The Proposed Scheme
• 4. Performance Parameters
• 6. Conclusion and Future Work
• 5. Results
• References

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