IJMTES – CANCER TISSUE IDENTIFICATION USING MONTE CARLO SIMULATION AND ICM ALGORITHM

Journal Title : International Journal of Modern Trends in Engineering and Science

Author’s Name : S Gowri | A Kanagaraj

Volume 02 Issue 11  Year 2015

ISSN no: 2348-3121

Page no: 1-6

Abstract Acute myelogenous leukaemia (AML) is a subtype of acute leukaemia. The average age of the person is 65 years. Cancer tissue can be identified be size, shape and weight age of the each cell. The proposed method can differ from others in: First the images can be converted to another format; Second segmentation can be performed by clustering algorithm to segment the complete images; Third feature can be extracted be using several features; Fourth Classification can be used to classify the begin stage and malignant stages from complete images. It also classified by their characteristics of each tissue samples. Computer simulation can involved the following tests: comparing the Hausdorff dimension on the system before and after the local binary pattern, the proposed algorithm can compare the normal images and abnormal images. Blood images can be tested and the cells can be separate it from the sub images and complete images.

Keywords— Acute Myelogenous Leukemia (AML), classification, ICM, segmentation, SVM, LBP

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