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Shengnan Hao, Haotian Wu, Yanyan Jiang, Zhanlin Ji, Li Zhao, Linyun Liu and Ivan Ganchev
Accurate segmentation of lesions can provide strong evidence for early skin cancer diagnosis by doctors, enabling timely treatment of patients and effectively reducing cancer mortality rates. In recent years, some deep learning models have utilized compl...
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Luzhou Liu, Xiaoxia Zhang, Yingwei Li and Zhinan Xu
Accurate segmentation of skin lesions is still a challenging task for automatic diagnostic systems because of the significant shape variations and blurred boundaries of the lesions. This paper proposes a multi-scale convolutional neural network, REDAUNet...
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Long Hoang, Suk-Hwan Lee, Eung-Joo Lee and Ki-Ryong Kwon
Skin lesion classification has recently attracted significant attention. Regularly, physicians take much time to analyze the skin lesions because of the high similarity between these skin lesions. An automated classification system using deep learning ca...
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Giuliana Ramella
Hair removal is a preliminary and often necessary step in the automatic processing of dermoscopic images since hair can negatively affect or compromise the distinction of a lesion region from the normal surrounding healthy skin. A featured application is...
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Karshiev Sanjar, Olimov Bekhzod, Jaeil Kim, Jaesoo Kim, Anand Paul and Jeonghong Kim
The early and accurate diagnosis of skin cancer is crucial for providing patients with advanced treatment by focusing medical personnel on specific parts of the skin. Networks based on encoder?decoder architectures have been effectively implemented for n...
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