Exploring the color feature power for psoriasis risk stratification and classification: A data mining paradigm
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- 作者：Vimal K. Shrivastavaa ; lky.vml@gmail.com" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Narendra D. Londhea ; c ; nlondhe.ele@nitrr.ac.in" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Rajendra S. Sonawaneb ; drrajss@gmail.com" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae ; Jasjit S. Suric ; d ; jsuri@comcast.net" class="auth_mail" title="E-mail the corresponding authorAuthor Vitae
- 关键词：Psoriasis ; Color space ; PCA ; Classification ; Feature power ; Reliability
- 刊名：Computers in Biology and Medicine
- 出版年：2015
- 出版时间：1 October 2015
- 年：2015
- 卷：65
- 期：Complete
- 页码：54-68
- 全文大小：1460 K
文摘
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Exploration of 14 color spaces (86 color features).
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Exploration of 8 grayscale feature extraction techniques (60 grayscale features).
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PCA-based dominant feature selection without altering their original feature values.
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Introducing feature power for three spaces: color, grayscale and combined.
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Introducing a reliability factor for psoriasis based CADx system.