Dermatological Disease Classification utilizing Image Processing and Neural Networks

Skin diseases are a frequent problem among all age groups. Application of Machine Learning (ML) is exceedingly suitable for skin diseases identification as it has large clinical image database that can be used to train models and interpret diagnosis for better patient outcomes. Researchers have used various image processing techniques and classification methods. Color and Texture based features are most commonly used for image analysis and Convolutional Neural Network (CNN) has become current standard practice in classifying skin disorders. This paper presents a thorough survey of image processing techniques and classifiers for skin diseases detection.

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Dermatological Disease Classification utilizing Image Processing and Neural Networks

Semantic Scholar · Medicine · 2020

Abstract

Skin diseases are a frequent problem among all age groups. Application of Machine Learning (ML) is exceedingly suitable for skin diseases identification as it has large clinical image database that can be used to train models and interpret diagnosis for better patient outcomes. Researchers have used various image processing techniques and classification methods. Color and Texture based features are most commonly used for image analysis and Convolutional Neural Network (CNN) has become current standard practice in classifying skin disorders. This paper presents a thorough survey of image processing techniques and classifiers for skin diseases detection.

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