Performance Assessment of Carcinoma With Segmentation Techniques By Statistical Analysis

Abstract

Carcinoma is the most deadly disease of which   Lung cancer and Breast cancer are of high risk. This approach target at diagnosing carcinoma by considering certain techniques. In this approach, a mammogram image and microscopic Lung image are considered. These images are applied through different image segmentation techniques. Later, Binarization technique is applied to improve the contrast of the images within the affected area. Median filter is used for removing noise within the image. To the noise-free images, some of the statistical parameters are calculated. Correlation is calculated between the reference parameters and cancerous parameters. These approaches are done for the detection of cancer in statistical approach. Results are processed using MATLAB and Xilinx.