Abstract Machine vision is being employed in defect detection, size measurement, pattern
recognition, image fusion, target tracking and 3D reconstruction. Traditional cancer detection …

Skin cancer is the most common form of cancer and is globally rising. Historically, the
diagnosis of skin cancers has depended on various conventional techniques which are of …

Whole slide digital imaging technology enables researchers to study pathologists'
interpretive behavior as they view digital slides and gain new understanding of the …

Well-curated sets of pathology image features will be critical to clinical studies that aim to
evaluate and predict treatment responses. Researchers require information synthesized …

Melanoma is the most aggressive type of skin cancer, and the pathological examination
remains the gold standard for the final diagnosis. Traditionally, the histopathology slides are …

Biomedical image analysis has been exploited considerably by recent technology
involvements, carrying about a pattern shift towards 'automation'and 'error free diagnosis' …

While deep learning models have demonstrated outstanding performance in medical image
segmentation tasks, histological annotations for training deep learning models are usually …

In traditional hospital systems, diagnosis and localization of melanoma are the critical
challenges for pathological analysis, treatment instructions, and prognosis evaluation …

In this research, we present a semi-supervised segmentation solution using convolutional
autoencoders to solve the problem of segmentation tasks having a small number of ground …

In this paper, we propose an efficient method for segmenting cell nuclei in the skin
histopathological images. The proposed technique consists of four modules. First, it …