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

Sewoong Kim, Jihun Kim, Minjoo Hwang, Manjae Kim, Seong Jin Jo, Minkyu Je, Jae Eun Jang, Dong Hun Lee, Jae Youn Hwang

Research output: Contribution to journalArticlepeer-review

38 Scopus citations

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.

Original languageEnglish
Pages (from-to)879-891
Number of pages13
JournalBiomedical Optics Express
Volume10
Issue number2
DOIs
StatePublished - 2019

Bibliographical note

Publisher Copyright:
© 2019 Optical Society of America.

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