Your browser doesn't support javascript.
loading
Development of a camera-based remote diagnostic system focused on color reproduction using color charts.
Takahashi, Masato; Takahashi, Ryo; Morihara, Yasuhiro; Kin, Isseki; Ogawa-Ochiai, Keiko; Tsumura, Norimichi.
Afiliação
  • Takahashi M; Graduate School of Science and Engineering, Chiba University, Chiba, Japan.
  • Takahashi R; New Business Planning Department, DIC Corporation, Tokyo, Japan.
  • Morihara Y; Graduate School of Science and Engineering, Chiba University, Chiba, Japan.
  • Kin I; Business Promotion & New Development Department, DIC Graphics Corporation, Tokyo, Japan.
  • Ogawa-Ochiai K; Sensing Corporation, Tokyo, Japan.
  • Tsumura N; Department of Japanese-Traditional (Kampo) Medicine, Kanazawa University, Kanazawa, Japan.
Artif Life Robot ; 25(3): 370-376, 2020.
Article em En | MEDLINE | ID: mdl-32837297
In this paper, we propose a color reproduction method using color charts to improve the color quality of a telemedicine system. Owing to the spread of COVID-19, the need for telemedicine is rapidly increasing to prevent infections more effectively. However, in practices such as traditional Japanese (Kampo) medicine, where color is used as an important examination factor, an accurate diagnosis cannot be made without adequate color reproduction. In telemedicine using a commercially available smartphone, color reproducibility may deteriorate owing to differences in the devices and lighting, which may result in a misdiagnosis. Therefore, we created a color chart that includes the colors of the human skin and tongue as a tool to help doctors identify the color of patients more accurately when conducting a telemedicine examination. Through a subjective evaluation by eight medical doctors, it was unanimously found that the proposed method is practical in terms of a color examination. The developed color chart can also be used for an automatic color correction.
Palavras-chave

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Idioma: En Ano de publicação: 2020 Tipo de documento: Article