In this paper, we first describe the basics of the field of cancer diagnosis, which includes
steps of cancer diagnosis followed by the typical classification methods used by doctors …

Deep learning has emerged as a leading machine learning tool in object detection and has
attracted attention with its achievements in progressing medical image analysis …

Medical image segmentation is a critical component in clinical practice, facilitating accurate
diagnosis, treatment planning, and disease monitoring. However, existing methods, often …

Image-based machine learning and deep learning in particular has recently shown expert-
level accuracy in medical image classification. In this study, we combine convolutional and …

In this paper, we aim to provide a survey on the applications of deep learning for cancer
detection and diagnosis and hope to provide an overview of the progress in this field. In the …

With the rise in whole slide scanner technology, large numbers of tissue slides are being
scanned and represented and archived digitally. While digital pathology has substantial …

Colorectal adenocarcinoma originating in intestinal glandular structures is the most common
form of colon cancer. In clinical practice, the morphology of intestinal glands, including …

The morphology of glands has been used routinely by pathologists to assess the
malignancy degree of adenocarcinomas. Accurate segmentation of glands from histology …

The use of AI systems in healthcare for the early screening of diseases is of great clinical
importance. Deep learning has shown great promise in medical imaging, but the reliability …

Deep learning (DL) has achieved state-of-the-art performance in many digital pathology
analysis tasks. Traditional methods usually require hand-crafted domain-specific features …