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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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Flavia Grignaffini, Maurizio Troiano, Francesco Barbuto, Patrizio Simeoni, Fabio Mangini, Gabriele D?Andrea, Lorenzo Piazzo, Carmen Cantisani, Noah Musolff, Costantino Ricciuti and Fabrizio Frezza
Skin cancer (SC) is one of the most common cancers in the world and is a leading cause of death in humans. Melanoma (M) is the most aggressive form of skin cancer and has an increasing incidence rate. Early and accurate diagnosis of M is critical to incr...
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Damilola A. Okuboyejo and Oludayo O. Olugbara
The conventional dermatology practice of performing noninvasive screening tests to detect skin diseases is a source of escapable diagnostic inaccuracies. Literature suggests that automated diagnosis is essential for improving diagnostic accuracies in med...
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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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Saumya Salian, Sudhir Sawarkar
Pág. 59 - 72
The rise of incidences of melanoma skin cancer is a global health problem. Skin cancer, if diagnosed at an early stage, enhances the chances of a patient?s survival. Building an automated and effective melanoma classification system is the need of the ho...
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Flavia Grignaffini, Francesco Barbuto, Lorenzo Piazzo, Maurizio Troiano, Patrizio Simeoni, Fabio Mangini, Giovanni Pellacani, Carmen Cantisani and Fabrizio Frezza
Skin cancer (SC) is one of the most prevalent cancers worldwide. Clinical evaluation of skin lesions is necessary to assess the characteristics of the disease; however, it is limited by long timelines and variety in interpretation. As early and accurate ...
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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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Felicia Anisoara Damian, Simona Moldovanu, Nilanjan Dey, Amira S. Ashour and Luminita Moraru
(1) Background: In this research, we aimed to identify and validate a set of relevant features to distinguish between benign nevi and melanoma lesions. (2) Methods: Two datasets with 70 melanomas and 100 nevi were investigated. The first one contained ra...
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