Understanding intratumoral heterogeneity—the molecular variation among cells within a
tumor—promises to address outstanding questions in cancer biology and improve the …

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

In this paper, a feature learning enhanced convolutional neural network (FLE-CNN) is
proposed for cancer detection from histopathology images. To build a highly generalized …

Purpose: The liver is the most frequent metastatic site for colorectal cancer. Its
microenvironment is modified to provide a niche that is conducive for colorectal cancer cell …

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 …

Diffuse large B cell lymphoma (DLBCL) is an aggressive blood cancer known for its rapid
progression and high incidence. The growing use of immunohistochemistry (IHC) has …

Molecular and genomic properties are critical in selecting cancer treatments to target
individual tumors, particularly for immunotherapy. However, the methods to assess such …

The alignment of tissue between histopathological whole-slide-images (WSI) is crucial for
research and clinical applications. Advances in computing, deep learning, and availability of …

The analysis of FFPE tissue sections stained with haematoxylin and eosin (H&E) or
immunohistochemistry (IHC) is essential for the pathologic assessment of surgically …

Timely detection of Barrett's esophagus, the pre-malignant condition of esophageal
adenocarcinoma, can improve patient survival rates. The Cytosponge-TFF3 test, a non …