Clinical routine in hepatology involves the diagnosis and treatment of a wide spectrum of
metabolic, infectious, autoimmune and neoplastic diseases. Clinicians integrate qualitative …

Nucleus segmentation is an imperative step in the qualitative study of imaging datasets,
considered as an intricate task in histopathology image analysis. Segmenting a nucleus is …

Histopathology tissue analysis is considered the gold standard in cancer diagnosis and
prognosis. Whole-slide imaging (WSI), ie, the scanning and digitization of entire histology …

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

Background: Artificial Intelligence (AI)-based Deep Neural Networks (DNNs) can handle a
wide range of applications in image analysis, ranging from automated segmentation to …

Simple Summary The use of neoadjuvant therapy (NAT) in patients with pancreatic ductal
adenocarcinoma (PDAC) is increasing. Objective quantification of the histopathological …

Background We developed and validated a prognostic and predictive computational
pathology risk score (CoRiS) using H&E stained tissue images from patients with early-stage …

Automatic multi-organ segmentation in medical images is crucial for many clinical
applications. The art methods have reported promising results but rely on massive …

Digital pathology technologies, including whole slide imaging (WSI), have significantly
improved modern clinical practices by facilitating storing, viewing, processing, and sharing …

Hepatocellular carcinoma (HCC) constitutes the fifth most frequent malignancy worldwide
and the third most frequent cause of cancer-related deaths. Currently, treatment selection is …