Patients diagnosed with skin cancer like melanoma are prone to a high mortality rate.
Automatic lesion analysis is critical in skin cancer diagnosis and ensures effective treatment …

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

Skin lesion segmentation has a critical role in the early and accurate diagnosis of skin
cancer by computerized systems. However, automatic segmentation of skin lesions in …

Automatic skin lesion analysis of dermoscopy images remains a challenging topic. In this
paper, we propose an end-to-end multi-task deep learning framework for automatic skin …

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 …

Automatic skin lesion segmentation in dermoscopic images is an essential requirement for
making the computer-aided diagnosis (CADs) system, but efficiently segmenting skin lesions …

Melanoma is a life-threatening form of skin cancer when left undiagnosed at the early
stages. Although there are more cases of non-melanoma cancer than melanoma cancer …

In the last few years, a great attention was paid to the deep learning Techniques used for
image analysis because of their ability to use machine learning techniques to transform …

Skin cancer has a significant impact across the world. Melanoma is a malignant form of skin
cancer. Skin lesion segmentation is an important step in computer-aided diagnosis (CAD) …

Reliable and accurate segmentation of skin lesions images is an essential step in analysing
skin lesions for the clinical diagnosis and treatment of melanoma skin cancer. Skin cancer …