Paper
21 March 2023 Dermoscopic image segmentation combining pigment separation and deep learning networks
Yongzhong Zhang, Hexiao Huang, Junzhu Zhang, Yan Ma
Author Affiliations +
Proceedings Volume 12609, International Conference on Computer Application and Information Security (ICCAIS 2022); 1260910 (2023) https://doi.org/10.1117/12.2671702
Event: International Conference on Computer Application and Information Security (ICCAIS 2022), 2022, ONLINE, ONLINE
Abstract
Dermoscopic image segmentation aims to detect damaged skin areas. It is difficult to detect skin lesions accurately due to factors such as the method of image acquisition, the characteristics of the lesion, and the texture of the skin. This paper proposes a dermatoscopic image segmentation algorithm that combines the pigment separation algorithm with the Segnet network model. First, pigment separation is performed on the dermatoscopic images to obtain the corresponding melanin and hemosiderin images. Afterwards, the melanin and hemosiderin images are converted to single-channel grayscale maps and merged with the original images to produce image data with a channel number of 5. The channel-expanded images are then segmented using Segnet deep neural network. Experimental results on the ISIC-2018 dermoscopy image dataset show that the proposed algorithm achieves better segmentation results in terms of accuracy, sensitivity, and specificity.
© (2023) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yongzhong Zhang, Hexiao Huang, Junzhu Zhang, and Yan Ma "Dermoscopic image segmentation combining pigment separation and deep learning networks", Proc. SPIE 12609, International Conference on Computer Application and Information Security (ICCAIS 2022), 1260910 (21 March 2023); https://doi.org/10.1117/12.2671702
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KEYWORDS
Image segmentation

Education and training

Skin

Pigments

Image processing algorithms and systems

Image processing

Deep learning

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