TY - JOUR
T1 - Facial UV photo imaging for skin pigmentation assessment using conditional generative adversarial networks
AU - Kojima, Kaname
AU - Shido, Kosuke
AU - Tamiya, Gen
AU - Yamasaki, Kenshi
AU - Kinoshita, Kengo
AU - Aiba, Setsuya
N1 - Funding Information:
This study was supported by Grant-in-Aid for Scientific Research (C) KAKENHI from the Japan Society for the Promotion of Science (Grant no: JP20K12058) and by the Japan Agency for Medical Research and Development (Grant no: JP20lk1010034).
Publisher Copyright:
© 2021, The Author(s).
PY - 2021/12
Y1 - 2021/12
N2 - 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.
AB - 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.
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U2 - 10.1038/s41598-020-79995-4
DO - 10.1038/s41598-020-79995-4
M3 - Article
C2 - 33441756
AN - SCOPUS:85099380981
SN - 2045-2322
VL - 11
JO - Scientific Reports
JF - Scientific Reports
IS - 1
M1 - 1213
ER -
