Journal of Chemical and Pharmaceutical Research (ISSN : 0975-7384)

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Original Articles: 2016 Vol: 8 Issue: 6

PSO, Genetic Optimization and SVM Algorithm used for Lung Cancer Detection


This paper discusses the formation of Lung cancer detection system by using the techniques of Image processing. The system formed can take any type of medical image within the three choices consisting of CT, MRI and Ultrasound images. Here the proposed model is developed using PSO, Genetic Optimization and SVM algorithm used for feature selection and classification. This paper is an extension of image processing using lung cancer detection and produces the results of feature extraction and feature selection after segmentation. The system formed accepts any one of medical image within the three choices consisting of MRI, CT and Ultrasound image as input. After preprocessing of image, canny filter is used for Edge detection. This present work proposes a method to detect the cancerous cells effectively from the CT, MRI scan and Ultrasound images. Super pixel Segmentation has been used for segmentation and Gabor filter is used for De-noising the medical images. Simulation results are obtained for the cancer detection system using MATLAB and comparison is done between the three medical images.

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