DIAGNOSIS OF MELANOMA SKIN CANCER USING NEURAL NETWORK - Sivaranjani, N.; Kalaimani, Ms.M. (IJRDO-Journal of Applied Science, 2015)
Malignant melanoma is theappearance of sores that cause bleedingand is the deadliest form of skin cancer.Incidence rates of melanoma have beenincreasing, but survival rates are high ifdetected early. With the advancement oftechnology, early detection of skin canceris possible. The proposed frameworkconsists of image segmentation, followedby comprehensive feature set extractionand neural network classification withhigher segmentation accuracy. The systemuses enhanced image processing tosegment the images without manualintervention. From the segmented image, itextracts a comprehensive set of pixelfeatures and RGB colour components ofthe digital image. As the experience andtraining-based learning is an importantcharacteristic of neural networks, thefeatures were fed automatically to a BackPropagation Neural Network (BPNN)classifier. It classifies the given data setinto cancerous or non-cancerous toidentify the skin cancer easily.