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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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Jacinth Poornima Jeyakumar, Anitha Jude, Asha Gnana Priya and Jude Hemanth
Melanoma is one of the skin cancer types that is more dangerous to human society. It easily spreads to other parts of the human body. An early diagnosis is necessary for a higher survival rate. Computer-aided diagnosis (CAD) is suitable for providing pre...
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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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Zhihao Liao, Neng Fan and Kai Xu
The proposed Swin-PANet can be utilized for computer-aided diagnosis (CAD) of skin cancer or cell cancer to improve the segmentation efficiency and accuracy, considered as a significant technique for the accurate screening of diseased or abnormal area of...
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Premaladha Jayaraman, Nirmala Veeramani, Raghunathan Krishankumar, Kattur Soundarapandian Ravichandran, Fausto Cavallaro, Pratibha Rani and Abbas Mardani
In recent years, skin cancer diagnosis has been aided by the most sophisticated and advanced machine learning algorithms, primarily implemented in the spatial domain. In this research work, we concentrated on two crucial phases of a computer-aided diagno...
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