Identification of skin melanoma based on microscopic hyperspectral imaging technology

Screening and diagnosing of the melanoma are crucial for the early diagnosis. As the deterioration of melanoma, it can be easily separated from the other materials based on the spectral features and spatial features. With the image of microscopic hyperspectral, this paper applies spectral math to preprocess the image firstly and the utilizes three traditional supervised classifications-maximum likelihood classification (MLC), convolution neural networks (CNN) and support vector machine (SVM) to make the segmentation after preprocess. Finally, we evaluate the accuracy of results generated by three to get the best segmentation method among them. This experiment shows practical value in pathological diagnosis.