Histological staining is the gold standard for tissue examination in clinical pathology and life-
science research, which visualizes the tissue and cellular structures using chromatic dyes or …

Advances in digitizing tissue slides and the fast-paced progress in artificial intelligence,
including deep learning, have boosted the field of computational pathology. This field holds …

Artificial intelligence and machine learning (AI/ML) models have been adopted in a wide
range of healthcare applications, from medical image computing and analysis to continuous …

Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …

Processing giga-pixel whole slide histopathology images (WSI) is a computationally
expensive task. Multiple instance learning (MIL) has become the conventional approach to …

To comprehensively understand tissue and organism physiology and pathophysiology, it is
essential to create complete three-dimensional (3D) cellular maps. These maps require …

Systemic amyloidosis involves the deposition of misfolded proteins in organs/tissues,
leading to progressive organ dysfunction and failure. Congo red is the gold-standard …

Until recently, conventional biochemical staining had the undisputed status as well-
established benchmark for most biomedical problems related to clinical diagnostics …

Organoid models have provided a powerful platform for mechanistic investigations into
fundamental biological processes involved in the development and function of organs …

In digital pathology, the spatial context of cells is important for cell classification, cancer
diagnosis and prognosis. To model such complex cell context, however, is challenging …