Identification of skin melanoma based on microscopic hyperspectral imaging technology

Tingyi Fan; Yanxi Long; Xisheng Zhang; Zijing Peng; Qingli Li

doi:10.1117/12.2588969

20 January 2021 Identification of skin melanoma based on microscopic hyperspectral imaging technology

Tingyi Fan, Yanxi Long, Xisheng Zhang, Zijing Peng, Qingli Li

Author Affiliations +

Proceedings Volume 11719, Twelfth International Conference on Signal Processing Systems; 1171908 (2021) https://doi.org/10.1117/12.2588969
Event: Twelfth International Conference on Signal Processing Systems, 2020, Shanghai, China

Abstract

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.

Citation Download Citation

Tingyi Fan, Yanxi Long, Xisheng Zhang, Zijing Peng, and Qingli Li "Identification of skin melanoma based on microscopic hyperspectral imaging technology", Proc. SPIE 11719, Twelfth International Conference on Signal Processing Systems, 1171908 (20 January 2021); https://doi.org/10.1117/12.2588969

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