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 …

Despite the remarkable advances in cancer diagnosis, treatment, and management over the
past decade, malignant tumors remain a major public health problem. Further progress in …

Abstract Computational Pathology (CPath) is an interdisciplinary science that augments
developments of computational approaches to analyze and model medical histopathology …

Nuclear detection, segmentation and morphometric profiling are essential in hel** us
further understand the relationship between histology and patient outcome. To drive …

The digitalization of clinical workflows and the increasing performance of deep learning
algorithms are paving the way towards new methods for tackling cancer diagnosis …

Abstract Multiple Instance Learning (MIL) methods have become increasingly popular for
classifying gigapixel-sized Whole-Slide Images (WSIs) in digital pathology. Most MIL …

Computational pathology targets the automatic analysis of Whole Slide Images (WSI). WSIs
are high-resolution digitized histopathology images, stained with chemical reagents to …

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 …

Training machine learning models for artificial intelligence (AI) applications in pathology
often requires extensive annotation by human experts, but there is little guidance on the …

The field of computational pathology has been transformed with recent advances in
foundation models that encode histopathology region-of-interests (ROIs) into versatile and …