Smartphone-based multispectral imaging and machine-learning based analysis for discrimination between seborrheic dermatitis and psoriasis on the scalp.

Authors:
Sewoong Kim
Sewoong Kim
CHA Bundang Medical Center
Jihun Kim
Jihun Kim
Asan Medical Center
South Korea
Manjae Kim
Manjae Kim
Daegu Gyeongbuk Institute of Science & Technology
Seong Jin Jo
Seong Jin Jo
Seoul National University College of Medicine
Jae Eun Jang
Jae Eun Jang
Samsung Advanced Institute of Technology
Dong Hun Lee
Dong Hun Lee
Konkuk University

Biomed Opt Express 2019 Feb 24;10(2):879-891. Epub 2019 Jan 24.

Department of Information and Communication Engineering, Daegu Gyeongbuk Institute of Science & Technology, Daegu, 42988, South Korea.

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.

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http://dx.doi.org/10.1364/BOE.10.000879DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6377911PMC
February 2019
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