Colorectal Cancer (CRC) is currently one of the most common and deadly cancers. CRC is
the third most common malignancy and the fourth leading cause of cancer death worldwide …

Colon cancer causes deaths of about half a million people every year. Common method of
its detection is histopathological tissue analysis, which, though leads to vital diagnosis, is …

Cancer causes deviations in the distribution of cells, leading to changes in biological
structures that they form. Correct localization and characterization of these structures are …

Deep learning models have exhibited exceptional effectiveness in Computational Pathology
(CPath) by tackling intricate tasks across an array of histology image analysis applications …

This paper presents a review of the state-of-the-art in histopathology image representation
used in automatic image analysis tasks. Automatic analysis of histopathology images is …

Colon Cancer detection is an important task for the histopathologist as they have to analyze
morphology of the images at different magnifications thereby leading to intra and inter …

Objective. Automated cell nuclei segmentation is vital for the histopathological diagnosis of
cancer. However, nuclei segmentation from'hematoxylin and eosin'(HE) stained'whole slide …

Automated segmentation of tumor epithelial tissue from histological images is a fundamental
aspiration of digital pathology to improve biomarker assessment and tissue diagnosis …

This paper presents a new approach for the effective representation and classification of
images of histopathological colon tissues stained with hematoxylin and eosin. In this …

In digital pathology, devising effective image representations is crucial to design robust
automated diagnosis systems. To this end, many studies have proposed to develop object …