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 …

Abstract Analysis of skin lesion images via visual inspection and manual examination to
diagnose skin cancer has always been cumbersome. This manual examination of skin …

How does the accuracy of deep neural network models trained to classify clinical images of
skin conditions vary across skin color? While recent studies demonstrate computer vision …

Although many efforts have been made through past years, skin cancer recognition from
medical images is still an active area of research aiming at more accurate results. Many …

Segmentation is essential for medical image analysis to identify and localize diseases,
monitor morphological changes, and extract discriminative features for further diagnosis …

The automatic detection of dermoscopic features is a task that provides the specialists with
an image with indications about the different patterns present in it. This information can help …

Convolutional neural networks (CNNs) deliver exceptional results for computer vision,
including medical image analysis. With the growing number of available architectures …

Abstract Background and Objective Deep learning (DL) models have been used for medical
imaging for a long time but they did not achieve their full potential in the past because of …

Melanoma, a very severe form of skin cancer, spreads quickly and has a high mortality rate if
not treated early. Recently, machine learning, deep learning, and other related technologies …

Melanoma is one kind of dangerous cancer that has been increasing rapidly in the world.
Initial diagnosis is essential to survival, but often the disease is diagnosed in the fatal stage …