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Hassan El-khatib, Ana-Maria ?tefan and Dan Popescu
The incidence of melanoma cases continues to rise, underscoring the critical need for early detection and treatment. Recent studies highlight the significance of deep learning in melanoma detection, leading to improved accuracy. The field of computer-ass...
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Javed Rashid, Maryam Ishfaq, Ghulam Ali, Muhammad R. Saeed, Mubasher Hussain, Tamim Alkhalifah, Fahad Alturise and Noor Samand
Melanoma is a fatal type of skin cancer; the fury spread results in a high fatality rate when the malignancy is not treated at an initial stage. The patients? lives can be saved by accurately detecting skin cancer at an initial stage. A quick and precise...
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Catur Supriyanto, Abu Salam, Junta Zeniarja and Adi Wijaya
This research paper presents a deep-learning approach to early detection of skin cancer using image augmentation techniques. We introduce a two-stage image augmentation process utilizing geometric augmentation and a generative adversarial network (GAN) t...
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Qaisar Abbas, Misbah Sadaf and Anum Akram
A differentiation between all types of melanocytic and non-melanocytic skin lesions (MnM?SK) is a challenging task for both computer-aided diagnosis (CAD) and dermatologists due to the complex structure of patterns. The dermatologists are widely using pa...
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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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Luz-María Sánchez-Reyes, Juvenal Rodríguez-Reséndiz, Sebastián Salazar-Colores, Gloria Nélida Avecilla-Ramírez and Gerardo Israel Pérez-Soto
According to the World Health Organization (WHO), melanoma is the most severe type of skin cancer and is the leading cause of death from skin cancer worldwide. Certain features of melanoma include size, shape, color, or texture changes of a mole. In this...
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Sufiyan Bashir Mukadam and Hemprasad Yashwant Patil
Skin cancer is one of the most fatal diseases for mankind. The early detection of skin cancer will facilitate its overall treatment and contribute towards lowering the mortalities. This paper presents the deep learning-based algorithm along with pre-proc...
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Giampaolo D?Alessandro, Pantea Tavakolian and Stefano Sfarra
The present review aims to analyze the application of infrared thermal imaging, aided by bio-heat models, as a tool for the diagnosis of skin and breast cancers. The state of the art of the related technical procedures, bio-heat transfer modeling, and th...
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Khalil Aljohani and Turki Turki
Melanoma skin cancer is one of the most dangerous types of skin cancer, which, if not diagnosed early, may lead to death. Therefore, an accurate diagnosis is needed to detect melanoma. Traditionally, a dermatologist utilizes a microscope to inspect and t...
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Rajesh P,Murugan A,Murugamantham B,Ganesh Kumar S
Pág. pp. 189 - 203
Cancer has become very common in this evolving world. Technology advancements, increased radiations have made cancer a common syndrome. Various types of cancers like Skin Cancer, Breast Cancer, Prostate Cancer, Blood Cancer, Colorectal cancer, Kidney Can...
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Pedro F. Durães and Mário P. Véstias
The very good results achieved with recent algorithms for image classification based on deep learning have enabled new applications in many domains. The medical field is one that can greatly benefit from these algorithms in order to help the medical prof...
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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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