Enhancement and segmentation of suspicious regions of a thermal breast image are among the most significant challenges facing radiologists while examining and interpreting the thermogram images. The proposed focuses to following problems: How can increase the contrast between cancer regions and the background, how to adjust the intensity of the presence of BC region to be more homogeneous in the infrared image; how to efficiently segment tumors as suspicious regions with a very weak contrast to their background and how to extract the relevant features which separate tumors from background. The proposed cancer segmentation scheme composed of three main stages: (i) image enhancement; (ii) detection of the tumor region; (iii) features extraction from the segmented tumor area followed by coloring the segmented region. The performance of the proposed enhancement and segmentation method was evaluated on DMR-IR database and the average segmentation Accuracy, MCC, Dice and Jaccard obtained are 98.8%, 47.96%, 43.03%, and 34.8% respectively which is better than FCM, LCV-LSM, and EM-GMM methods. Besides, we also investigate the role of thermal image enhancement in tumor characterization and feature extraction.
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