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Smartphone-based multispectral imaging and machine-learning based analysis for discrimination between seborrheic dermatitis and psoriasis on the scalp
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- Title
- Smartphone-based multispectral imaging and machine-learning based analysis for discrimination between seborrheic dermatitis and psoriasis on the scalp
- DGIST Authors
- Jang, Jae Eun ; Hwang, Jae Youn
- Issued Date
- 2019-02
- Citation
- Kim, Sewoong. (2019-02). Smartphone-based multispectral imaging and machine-learning based analysis for discrimination between seborrheic dermatitis and psoriasis on the scalp. doi: 10.1364/BOE.10.000879
- Type
- Article
- Article Type
- Article
- Keywords
- COLORIMETRIC ANALYSIS ; MICROSCOPY ; DERMOSCOPY ; SYSTEM
- ISSN
- 2156-7085
- Abstract
-
For appropriate treatment, accurate discrimination between seborrheic dermatitis and psoriasis in a timely manner is crucial to avoid complications. However, when they occur on the scalp, differential diagnosis can be challenging using conventional dermascopes. Thus, we employed smartphone-based multispectral imaging and analysis to discriminate between them with high accuracy. A smartphone-based multispectral imaging system, suited for scalp disease diagnosis, was redesigned. We compared the outcomes obtained using machine learning-based and conventional spectral classification methods to achieve better discrimination. The results demonstrated that smartphone-based multispectral imaging and analysis has great potential for discriminating between these diseases. © 2019 Optical Society of America.
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- Publisher
- The Optical Society
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Related Researcher
- Jang, Jae Eun장재은
-
Department of Electrical Engineering and Computer Science
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