A Proposed Approach for Tumor Edge Detection in Mammogram Images
This paper describes an approach to the edge detection of a tumor in mammogram images. This is a complex problem because of specifics of the mammogram and breast tissue. In addition, the mammogram image is severely affected by various types of noise, including Gaussian, Salt and Pepper, Poisson, and Speckle. Mammogram preprocessing and noise reduction techniques may veil some crucial features of the image. To solve this problem, we propose a new framework that includes an optimization method algorithm for solving a multi-level threshold value problem based on the generalization of exponential entropy for breast cancer edge detection. The proposed framework will be compared with some standard edge detection methods on tested images of mammographic acquired from a wellknown reference database to demonstrate the effectiveness of the proposed techniques.
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