U-net is an image segmentation technique developed primarily for image segmentation
tasks. These traits provide U-net with a high utility within the medical imaging community …

Accurate diagnosis and segmentation of skin lesion is critical for early detection and
diagnosis of skin cancer. Recent multi-task learning methods require expensive annotations …

Skin biopsy histopathological analysis is one of the primary methods used for pathologists to
assess the presence and deterioration of melanoma in clinical. A comprehensive and …

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 …

In this study, an innovative hybrid machine learning‐technique is used for the early skin
cancer diagnosis fusing Convolutional Neural Network and Multilayer Perceptron to analyze …

Automated diagnosis systems provide a huge improvement in early detection of skin cancer,
and consequently, contribute to successful treatment. Recent research on convolutional …

Among various types of skin diseases, skin cancer is the deadliest form of the disease. This
paper classifies seven types of skin diseases: Actinic keratosis and intraepithelial …

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 …

Accurate morphological reconstruction of neurons in whole brain images is critical for brain
science research. However, due to the wide range of whole brain imaging, uneven staining …

Abstract Machine learning algorithms are progressively assuming an important role as a
computational tool to support clinical diagnosis, namely in the classification of pigmented …