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  2019, Vol. 32 Issue (7): 577-588    DOI: 10.16451/j.cnki.issn1003-6059.201907001
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Parallel Skin: A Vision-Based Dermatological Analysis Framework
WANG Fei-Yue1,3, GOU Chao1, WANG Jiangong1,2, SHEN Tianyu1,3, ZHENG Wenbo1,4, YU Hui3
1.The State Key Laboratory of Management and Control of Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190
2.Parallel Healthcare Technology Innovation Center, Qingdao Academy of Intelligent Industries, Qingdao 266109
3.School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049
4.School of Software Engineering, Xi′an Jiaotong University, Xi′an 710049
5.School of Creative Technologies, University of Portsmouth, Portsmouth, PO1 2DJ

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Abstract  

With the rapid development of computer and artificial intelligence, image-based methods for skin analysis have achieved preferable results. However, the performance of computer aided diagnosis systems based on deep learning methods relies on big medical data labeled by domain experts. In addition, there is limitation of interpretability for the diagnosis results. To address aforementioned problems, a vision-based unified framework for dermatological analysis termed as parallel skin is proposed. Inspired by the ACP method and the parallel medical image analysis framework, the artificial skin image system to perform data selection and generation is constructed. Then, computational experiments are conducted with predictive learning for model building and evaluation. Descriptive and prescriptive learning to leverage the power of domain knowledge to guide data selection and generation are further introduced. In the proposed parallel-skin framework, the closed-loop diagnostic analysis model can be optimized.

Key wordsParallel Skin      Parallel Intelligence      Generative Models     
Received: 21 June 2019     
ZTFLH: TP 391  
Fund:

Supported by National Natural Science Foundation of China(No.61806198,61304200,61533019)

About author:: WANG Fei-Yue(Corresponding author),Ph.D., professor. His research interests include modeling, analysis, and control of intelligent systems and complex systems.GOU Chao, Ph.D., assistant professor. His research interests include computer vision, pattern recognition and machine learning.WANG Jiangong, Ph.D. candidate. His research interests include computer graphics, medical image processing and machine lear-ning.SHEN Tianyu, Ph.D. candidate. Her research interests include computer vision, medical image processing and machine lear-ning.ZHENG Wenbo, Ph.D. candidate. His research interests include computer vision, medical image processing and machine lear-ning.YU Hui, Ph.D., professor. His research interests include face analysis, human motion analysis and human-computer interaction.
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WANG Fei-Yue
GOU Chao
WANG Jiangong
SHEN Tianyu
ZHENG Wenbo
YU Hui
Cite this article:   
WANG Fei-Yue,GOU Chao,WANG Jiangong等. Parallel Skin: A Vision-Based Dermatological Analysis Framework[J]. , 2019, 32(7): 577-588.
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http://manu46.magtech.com.cn/Jweb_prai/EN/10.16451/j.cnki.issn1003-6059.201907001      OR     http://manu46.magtech.com.cn/Jweb_prai/EN/Y2019/V32/I7/577
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