Deep learning based classification of facial dermatological disorders.

Computers in Biology and Medicine
Evgin Goceri

Abstract

Common properties of dermatological diseases are mostly lesions with abnormal pattern and skin color (usually redness). Therefore, dermatology is one of the most appropriate areas in medicine for automated diagnosis from images using pattern recognition techniques to provide accurate, objective, early diagnosis and interventions. Also, automated techniques provide diagnosis without depending on location and time. In addition, the number of patients in dermatology departments and costs of dermatologist visits can be reduced. Therefore, in this work, an automated method is proposed to classify dermatological diseases from color digital photographs. Efficiency of the proposed approach is provided by 2 stages. In the 1st stage, lesions are detected and extracted by using a variational level set technique after noise reduction and intensity normalization steps. In the 2nd stage, lesions are classified using a pre-trained DenseNet201 architecture with an efficient loss function. In this study, five common facial dermatological diseases are handled since they also cause anxiety, depression and even suicide death. The main contributions provided by this work can be identified as follows: (i) A comprehensive survey about the state-of-th...Continue Reading

Citations

Mar 5, 2021·Computer Methods and Programs in Biomedicine·Yixin WangZhiqiang He
May 30, 2021·Computer Methods and Programs in Biomedicine·Tong Min KimDong-Jin Chang
Oct 5, 2021·International Journal of Computer Assisted Radiology and Surgery·Sheng LiRuibiao Fu

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