Lung Cancer Detection Using SVM Algorithm

In this study investigates the formation of Lung cancer detection using the techniques image processing. The oncologist considered for blood test result. The system formed can take any of medical image within the three choices consisting of CT, MRI and Ultrasound image. This study explores the application of Support Vector Machine (SVM) classification algorithms for the detection of lung cancer, this improves its ability to handle high-dimensional data and provide robust classification result. The model proposed here is developed using PSO, genetic optimization and SVM algorithm used for feature selection and classification. This paper uses image processing to detect lung cancer and separates the lung image into its parts(segmentation)Find important features in the image (features extraction). Choose the most important features to use (features selection). The computer format accepts any clinical image within three choices of MRI, CT and Ultrasound image as input. SVM tool works very well for early detection and treatment of this lung cancer.