In this paper, a multi-scale visual transformer model, referred as GasHis-Transformer, is
proposed for Gastric Histopathological Image Detection (GHID), which enables the …

Gastric cancer is a common and deadly cancer in the world. The gold standard for the
detection of gastric cancer is the histological examination by pathologists, where Gastric …

Cancer diagnosis, prognosis, and therapy response predictions from tissue specimens
highly depend on the phenotype and topological distribution of constituting histological …

Explainability of deep learning methods is imperative to facilitate their clinical adoption in
digital pathology. However, popular deep learning methods and explainability techniques …

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

Background and objective Gastric cancer is the fifth most common cancer globally, and early
detection of gastric cancer is essential to save lives. Histopathological examination of gastric …

Advances in entity-graph analysis of histopathology images have brought in a new
paradigm to describe tissue composition, and learn the tissue structure-to-function …

Abstract In the Gastric Histopathology Image Classification (GHIC) tasks, which are usually
weakly supervised learning missions, there is inevitably redundant information in the …

Gastric cancer is a leading cause of cancer-related deaths worldwide, underscoring the
need for early detection to improve patient survival rates. The current clinical gold standard …

Gastric cancer (GC) is one of the leading causes of cancer-related death worldwide. It takes
some time from chronic gastritis to develop in GC. Early detection of GC will help patients …