Title: SVM classifier based CAD system for Lung Cancer Detection
Author(s): Apoorva Mahale1, Chetan Rawool2, Dinesh Tolani3, Deepesh Bathija4, Prof. Kajal Jewani5
1,2,3,4Dept. of Computer Engineering, VESIT, Mumbai, India5Asst. Prof., Dept. of Computer Engineering, VESIT, Mumbai, India
This paper discusses the formulation of a Computer Aided Detection (CAD) system for Lung cancer detection by using an interdisciplinary approach based on the techniques of Image Processing and Machine Learning. This paper is an extension of image processing using lung cancer detection and produces the results of feature extraction and feature selection after segmentation. Here the proposed model is developed using SVM algorithm for feature selection and classification. The system accepts Lung CT(Computed Tomography) images as input. This present work proposes a method to detect the cancerous cells effectively from the CT scan and images. Modified Fuzzy Possibilistic C Means (MFPCM) has been used for segmentation and Gabor filter has been used for De-noising the medical images. Simulation results are obtained for the cancer detection system using the MATLAB software.