Breast Cancer Detection Using Histogram Based Decomposition
Journal Title: International Journal of Modern Engineering Research (IJMER) - Year 2013, Vol 3, Issue 2
Abstract
Abstract: Breast disease are continues to be a common health problem in the world for womens. The mammographic diagnostic method is very famous method for detecting breast cancer. But sometimes in some cases, it is not so easy for the radiologist for detecting the typical diagnostic symptoms, such as masses and micro calcifications on the mammograms. Compact region in digital mammographic images are usually contain noisy and have very low contras and the infected regions are very difficult to recognize by radiologist. In this paper, we develop a Histogram base adaptive thresholding to detect suspicious cancerous location in mammograms. The algorithm consumes the combination of adaptive histogram thresholding segmentation and adaptive wavelet based thresholding segmentation on a multiresolution representation of the original mammogram. At last it shows adaptive wavelet techniques to produce the best denoised mammographic image using efficient thresholding algorithm. The algorithm has been checked with different types of around 100 mammograms in the Mammographic Image Analysis Society. Mini Mammographic database the experimental results show that the detection method has a Shows 94% correct result with exact micro calcified area.
Authors and Affiliations
Ms. Jayashree R. Parate
Keywords
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