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Presentation + Paper
21 April 2020 Enhancement and segmentation of breast thermograms
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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.
Conference Presentation
© (2020) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Thaweesak Trongtirakul, Adel Oulefki, Sos Agaian, and Werapon Chiracharit "Enhancement and segmentation of breast thermograms", Proc. SPIE 11399, Mobile Multimedia/Image Processing, Security, and Applications 2020, 113990F (21 April 2020);

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