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Development of a camera-based remote diagnostic system focused on color reproduction using color charts
- Source :
- Artificial Life and Robotics
- Publication Year :
- 2020
- Publisher :
- Springer Japan, 2020.
-
Abstract
- 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.
- Subjects :
- Telemedicine
Coronavirus disease 2019 (COVID-19)
Computer science
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)
0206 medical engineering
Color reproduction
02 engineering and technology
Diagnostic system
General Biochemistry, Genetics and Molecular Biology
03 medical and health sciences
0302 clinical medicine
Artificial Intelligence
Color chart
Computer vision
Color quality
business.industry
Color correction
COVID-19
020601 biomedical engineering
Color-chart
Original Article
Artificial intelligence
business
Remote diagnostic
030217 neurology & neurosurgery
Subjects
Details
- Language :
- English
- ISSN :
- 16147456 and 14335298
- Database :
- OpenAIRE
- Journal :
- Artificial Life and Robotics
- Accession number :
- edsair.doi.dedup.....e0981c1e0d8547b20910b17bf7171d8b