Tehran University of Medical Sciences

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Directional Susan Image Boundary Detection of Breast Thermogram Publisher



Mahmoudzadeh E1 ; Zekri M1 ; Montazeri MA1 ; Sadri S1 ; Dabbagh ST2
Authors

Source: IET Image Processing Published:2016


Abstract

Thermography of the breast has been shown to be well suited to detect early signs of breast cancer. This study proposes a novel method for boundary detection of breast thermography images using directional SUSAN method. Among breast thermography image processing steps, breast isolation from background and from each other is an essential stage for proper detection of breast cancer. For this purpose, in this study, breast boundary is grouped into three regions depending on the region property. The algorithm of boundary detection is different for each region. Specially, for bottom breast boundary, directional SUSAN edge detector is presented that uses two rectangle masks to create a directional SUSAN gradient image with emphasis on oblique useful edges and omitting undesirable ones. Then cubic parabolic interpolation is implemented to determine a set of edge points on the boundaries. At last, an effective search algorithm is executed to correct some false points in order to extract breast boundaries accurately. The performance of the proposed approach illustrated by applying on the images of three databases. Experimental results show that this method acts effectively and confirm the accurate boundary detection. Moreover, statistical measures are calculated to indicate the remarkable capabilities of the proposed approach. © The Institution of Engineering and Technology 2016.
1. Breast-Region Segmentation in Mri Using Chest Region Atlas and Svm, Turkish Journal of Electrical Engineering and Computer Sciences (2017)
2. Localized-Atlas-Based Segmentation of Breast Mri in a Decision-Making Framework, Australasian Physical and Engineering Sciences in Medicine (2017)
3. Extraction of Vessel Structure in Thermal Images to Help Early Breast Cancer Detection, Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization (2020)
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