Abstract The Computer-aided Diagnosis or Detection (CAD) approach for skin lesion
analysis is an emerging field of research that has the potential to alleviate the burden and …

Deep learning models are efficient in learning the features that assist in understanding
complex patterns precisely. This study proposed a computerized process of classifying skin …

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 …

ABSTRACT The International Skin Imaging Collaboration (ISIC) datasets are pivotal
resources for researchers in machine learning for medical image analysis, especially in skin …

This study proposes an approach for segmentation of skin lesions from dermoscopic images
based on fully convolutional neural network and active contour model (ACM). The …

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 diseases and lesions can be ambiguous to recognize due to the similarity of lesions
and enhanced imaging features. In this study, we compared three cutting-edge deep …

The number of deaths due to melanoma skin cancer has rapidly increased in recent years.
The timely diagnosis of the lesions of melanoma skin cancer can potentially increase the …

Recognizing skin cancer in time could greatly increase patients' chances of recovery. For
this reason, in recent years, numerous decision support systems have been proposed to …

Melanoma is considered the deadliest form of skin cancer, and the number of cases is
increasing day by day. The early diagnosis of melanoma is critical, as it significantly …