Melanoma is a serious skin disease. Automatic recognition of this lesion by dermoscopic
images is a difficult task. Recently, the deep learning paradigm has become a good …

Skin lesion segmentation is an important step in computer aided diagnosis for automated
melanoma diagnosis. However, in the field of medical images analysis, skin lesion …

Skin lesion segmentation is a primary step for skin lesion analysis, which can benefit the
subsequent classification task. It is a challenging task since the boundaries of pigment …

Automated skin lesion diagnosis from dermoscopic images is a difficult process due to
several notable problems such as artefacts (hairs), irregularity, lesion shape, and irrelevant …

In this paper, we propose an automatic approach to skin lesion region segmentation based
on a deep learning architecture with multi-scale residual connections. The architecture of the …

Melanoma is the deadliest form of skin cancer. Distinguishing melanoma lesions from non-
melanoma lesions has however been a challenging task. Many Computer Aided Diagnosis …

The incidence of skin cancer around the world is increasing year by year. However, early
diagnosis and treatment can greatly improve the survival rate of patients. Skin lesion …

Skin cancer is the most common type of cancer in the world and it is more treatable if
diagnosed early. The diagnosis process usually starts with segmenting the skin lesion area …

Segmentation of skin lesions is a challenging task because of the wide range of skin lesion
shapes, sizes, colors, and texture types. In the past few years, deep learning networks such …

Recent state-of-the-art methods for skin lesion segmentation are based on convolutional
neural networks (CNNs). Even though these CNN-based segmentation approaches are …