
Image processing is a commonly used method for skin cancer detection from the appearance of affected area on the skin. In this work, a computerised method has been developed to make use of Neural Networks in the field of medical image processing. The ultimate aim of this paper is to implement cost-effective emergency support systems to process the medical images. It is more advantageous to patients. The dermoscopy image of suspect area 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 using Thresholding method. Some features of image have to be extracted using ABCD rules. In this work, Asymmetry index and Geometric features are extracted from the segmented image. These features are given as the input to classifier. Artificial Neural Network ANN with feed forward architecture is used for classification purpose. It classifies the given image into cancerous or non-cancerous.
The proposed algorithm has been tested on the ISIC International Skin Imaging Collaboration 2017 training and test datasets. The ground truth data of each image is available as well, so performance of this work can evaluate quantitatively.
BY Khaing Thazin Oo | Dr. Moe Mon Myint | Dr. Khin Thuzar Win "Skin Cancer Detection using Digital Image Processing and Implementation using ANN and ABCD Features"
Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018,
URL: http://www.ijtsrd.com/papers/ijtsrd18751.pdf
Direct Link: http://www.ijtsrd.com/engineering/electronics-and-communication-engineering/18751/skin-cancer-detection-using-digital-image-processing-and-implementation-using-ann-and-abcd-features/khaing-thazin-oo
review papers, ugc approved journals for engineering, special issue publication
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