Nowadays, digital pathology plays a major role in the diagnosis and prognosis of tumours.
Unfortunately, existing methods remain limited when faced with the high resolution and size …

Hyperspectral imaging (HSI) and multispectral imaging (MSI) technologies have the
potential to transform the fields of digital and computational pathology. Traditional digitized …

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 …

Abstract Machine-assisted pathological recognition has been focused on supervised
learning (SL) that suffers from a significant annotation bottleneck. We propose a semi …

Colorectal cancer (CRC) is the second most common cancer in women and the third most
common in men, with an increasing incidence. Pathology diagnosis complemented with …

Background Accurate and robust pathological image analysis for colorectal cancer (CRC)
diagnosis is time-consuming and knowledge-intensive, but is essential for CRC patients' …

A clinically comparable Convolutional Neural Network framework-based technique for
performing automated classification of cancer grades and tissue structures in hematoxylin …

Background The cancer of colon is one of the important cause of morbidity and mortality in
adults. For the management of colonic carcinoma, the definitive diagnosis depends on the …

Artificial intelligence (AI) is a relatively new branch of computer science involving many
disciplines and technologies, including robotics, speech recognition, natural language and …

Colorectal cancer (CRC) is one of the most common cancers worldwide. Accurate early
detection and diagnosis, comprehensive assessment of treatment response, and precise …