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Abstract

Many people dying with any types of cancers colon cancer, Brest cancer, skin cancer and lung cancer. Every year 7.6 million people die with cancer. Existing techniques are very costly for detecting the lung cancer such as Chest Radiography (x-ray), computed Tomography (CT), Magnetic Resonance Imaging (MRI scan) and Sputum Cytology. So the requirement of techniques to detect the occurrence of cancer nodule in early stage is increasing. In The model consists of an input layer, a hidden layer and an output layer. The network is trained with one hidden layer and one output layer by giving twelve inputs. One of the most common forms of medical malpractices globally is an error in diagnosis. Inbuilt Neural Network toolbox and SVM has been executed using two steps training and testing phases. So I am proposed Hybrid technique combination of SVM and N/N. In order to provide better accuracy and comparison will be done on the basis of three parameter FRR,FAR, Accuracy apply on the DICOM images.

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Keywords

SVM, Neural Network, Lung Cancer, SIFT, FAR, FRR, Accuracy