Developing a Computer-Assisted System for Malignant Melanoma-Skin Cancer Detection Using Convolutional Neural Network

In recent years, Melanoma-Skin Cancer has emerged as a major health issue worldwide. Early detection plays a vital role in improving the prognosis of the disease. Leveraging computer vision in both the industrial and medical sectors presents promising opportunities. Our study focuses on introducing a computer-assisted approach based on deep learning for the detection and classification of Melanoma. We utilized three public datasets-ISIC-2017, ISIC-2020, and the Complete mednode dataset. Our methodology involved image processing, followed by inputting the processed images into a deep convolutional neural network (CNN) for automatic feature extraction and categorization as Malignant(melanoma) or Benign(non-melanoma). The experimental outcomes of our proposed framework showcased enhanced classification accuracy compared to existing CNN models.