Fibrosis is a progressive biological condition, leading to organ dysfunction in various clinical
settings. Although fibroblasts and macrophages are known as key cellular players for …

Abstract Background and Objective Histopathological image registration is an essential
component in digital pathology and biomedical image analysis. Deep-learning-based …

Manual screening of large-scale histopathological images is an extremely time-consuming,
laborious and subjective procedure. Accurate evaluation of diagnostic information from multi …

Virtual stain transfer is a promising area of research in Computational Pathology, which has
a great potential to alleviate important limitations when applying deep-learning-based …

The kidneys, often overlooked yet vital for bodily equilibrium, serve a multifaceted role
beyond filtration, governing crucial regulatory functions necessary for sustaining life. They …

Abstract Background and Objective The effective application of deep learning to digital
histopathology is hampered by the shortage of high-quality annotated images. In this paper …

In a context of limited data availability, we consider the supervised segmentation of
glomerular structures in patches of renal histopathological whole slide images. These …

Fibrosis is a progressive biological process leading to organ dysfunction in different clinical
settings. As fibroblasts and macrophages are known as key cellular players for fibrosis …

The annotation of histological images through different stains is an important task for
diagnosis of diseases such as cancer, but it is also very time-consuming. Despite its …

Microstructural studies of raw meat and products are becoming more and more popular and
informative methods for studying the composition and quality of meat. Histological studies …