Tag: digital pathology

FDA researchers have built HistoART, a system that uses a fine-tuned pathology foundation model to detect six common artifact types ...

A semi-supervised deep learning system called TBMNet accurately quantifies tumor budding in colorectal cancer slides and reveals molecularly distinct budding ...

Researchers at the University of Naples Federico II have developed a hierarchical graph neural network framework that represents breast tissue ...

Researchers have developed CROWN, a self-supervised visual foundation model pretrained on more than ten million cytology images that achieved top ...

Researchers at the National Cancer Institute have unveiled TMA-Grid, an open-source, zero-footprint web application that combines a convolutional neural network ...

Researchers have developed SlideChat, a multimodal generative AI assistant that interprets gigapixel whole-slide pathology images across 31 cancer types and ...

Researchers in China have developed a Transformer-CNN deep learning framework that segments and grades gastric intestinal metaplasia in whole slide ...

Every slide of tissue that a pathologist examines under the microscope has, for more than a century, passed through the ...

Pathology has entered an era in which a single medical image can contain more information than any human can comfortably ...

In a groundbreaking study published in BMC Cancer, researchers have unveiled novel insights into the spatial complexity of TGF/BMP signalling ...