Skin cancer is a major public health problem that could benefit from computer-aided
diagnosis to reduce the burden of this common disease. Skin lesion segmentation from …

Skin lesion segmentation from dermoscopic image is essential for improving the quantitative
analysis of melanoma. However, it is still a challenging task due to the large scale variations …

Skin lesion segmentation is a computer-aided diagnosis method for quantitative analysis of
melanoma that can improve efficiency and accuracy. Although many methods based on U …

Witnessing the success of deep learning neural networks in natural image processing, an
increasing number of studies have been proposed to develop deep-learning-based …

The continuous rise in skin cancer cases, especially in malignant melanoma, has resulted in
a high mortality rate of the affected patients due to late detection. Some challenges affecting …

Abstract Fully Convolution Networks have recently become popular for tackling semantic
segmentation problems. However, its performance is dependent on the hyper-parameters it …

Medical tools used to bolster decision-making by medical specialists who offer malaria
treatment include image processing equipment and a computer-aided diagnostic system …

Image segmentation has a key role in computer vision and image processing. Superiority of
deep learning based segmentation techniques has been shown in various studies in the …

Deep learning techniques have shown their superior performance in dermatologist clinical
inspection. Nevertheless, melanoma diagnosis is still a challenging task due to the difficulty …

Over the last decade, supervised deep learning on manually annotated big data has been
progressing significantly on computer vision tasks. But, the application of deep learning in …