Facial UV photo imaging for skin pigmentation assessment using conditional generative adversarial networks

Kaname Kojima, Kosuke Shido, Gen Tamiya, Kenshi Yamasaki, Kengo Kinoshita, Setsuya Aiba

研究成果: Article査読

1 被引用数 (Scopus)

抄録

Skin pigmentation is associated with skin damages and skin cancers, and ultraviolet (UV) photography is used as a minimally invasive mean for the assessment of pigmentation. Since UV photography equipment is not usually available in general practice, technologies emphasizing pigmentation in color photo images are desired for daily care. We propose a new method using conditional generative adversarial networks, named UV-photo Net, to generate synthetic UV images from color photo images. Evaluations using color and UV photo image pairs taken by a UV photography system demonstrated that pigment spots were well reproduced in synthetic UV images by UV-photo Net, and some of the reproduced pigment spots were difficult to be recognized in color photo images. In the pigment spot detection analysis, the rate of pigment spot areas in cheek regions for synthetic UV images was highly correlated with the rate for UV photo images (Pearson’s correlation coefficient 0.92). We also demonstrated that UV-photo Net was effective for floating up pigment spots for photo images taken by a smartphone camera. UV-photo Net enables an easy assessment of pigmentation from color photo images and will promote self-care of skin damages and early signs of skin cancers for preventive medicine.

本文言語English
論文番号1213
ジャーナルScientific reports
11
1
DOI
出版ステータスPublished - 2021 12

ASJC Scopus subject areas

  • 一般

フィンガープリント

「Facial UV photo imaging for skin pigmentation assessment using conditional generative adversarial networks」の研究トピックを掘り下げます。これらがまとまってユニークなフィンガープリントを構成します。

引用スタイル