Computer-aided systems for skin lesion diagnosis is a growing area of research. Recently,
researchers have shown an increasing interest in developing computer-aided diagnosis …

In machine learning, deep learning is the most popular topic having a wide range of
applications such as computer vision, natural language processing, speech recognition …

Abstract Computer-Aided Diagnosis (CAD) for dermatological diseases offers one of the
most notable showcases where deep learning technologies display their impressive …

Melanoma is a type of skin cancer with a high mortality rate. The different types of skin
lesions result in an inaccurate diagnosis due to their high similarity. Accurate classification of …

Automatic skin lesion segmentation in dermoscopic images is a challenging task due to the
low contrast between lesion and the surrounding skin, the irregular and fuzzy lesion borders …

Skin lesions are a severe disease globally. Early detection of melanoma in dermoscopy
images significantly increases the survival rate. However, the accurate recognition of …

Background Application of deep‐learning technology to skin cancer classification can
potentially improve the sensitivity and specificity of skin cancer screening, but the number of …

Background Multiphoton microscopy (MPM) offers a feasible approach for the biopsy in
clinical medicine, but it has not been used in clinical applications due to the lack of efficient …

Objective: Segmentation of skin lesions is an important step in the automated computer
aided diagnosis of melanoma. However, existing segmentation methods have a tendency to …

Skin diseases remain a major cause of disability worldwide and contribute approximately
1.79% of the global burden of disease measured in disability-adjusted life years. In the …