Abstract: In today’s modern world, Skin cancer is the most common cause of death amongst humans. Skin cancer is abnormal growth of skin cells most frequently develops on body exposed to the daylight but can occur anywhere on the body. Most of the skin cancers are curable at early stages. So, an early and fast detection of skin cancer can save the patient’s life. With the new technology, early detection of carcinoma is feasible at initial stage. Formal method for diagnosis skin cancer detection is Biopsy method. It is done by removing skin cells which sample goes to varied laboratory testing. It is painful and time-consuming process. The skin cancer detection system using convolution neural network for early detection of skin cancer disease is proposed. It is more advantageous to patients. The diagnosing methodology uses Image processing methods algorithm. The dermoscopy image of skin cancer is taken and it goes under various pre-processing technique for noise removal and image enhancement. Then the image is undergone to segmentation. These features are given as the input to classifier. Convolution neural network is used for classification purpose. It classifies the given image into cancerous or non-cancerous.
Keywords: Skin Cancer, Deep Convolution Neural Networking, Image Processing, MATLAB
| DOI: 10.17148/IJIREEICE.2019.8313