Unet based Image Segmentation of Sweat Droplets for Assisting Assessment of Atopic Dermatitis

In this paper, we describe an automatic analysis that identifies skin structure and sweat droplets from skin surface images. The analysis uses a discriminator based on deep learning and has succeeded in producing results that in some cases exceed the diagnosis of a medical experts. The discriminator...

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Bibliographic Details
Published in2022 37th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) pp. 124 - 127
Main Authors Miyaji, Yuma, Michida, Ryuichi, Koide, Tetsushi, Hayashida, Yuki, Aoyama, Yumi
Format Conference Proceeding
LanguageEnglish
Published IEEE 05.07.2022
Subjects
Computers
Deep learning
Image segmentation
Impression Mold Technique (IMT)
Medical diagnostic imaging
Skin
Skin Surface Structure
Sweat Droplets
U-Net
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Summary:In this paper, we describe an automatic analysis that identifies skin structure and sweat droplets from skin surface images. The analysis uses a discriminator based on deep learning and has succeeded in producing results that in some cases exceed the diagnosis of a medical experts. The discriminator is built based on U-Net, which is used for image segmentation.
DOI:10.1109/ITC-CSCC55581.2022.9894957