The adoption of digital pathology has enabled the curation of large repositories of gigapixel
whole-slide images (WSIs). Computationally identifying WSIs with similar morphologic …

A quantitative model to genetically interpret the histology in whole microscopy slide images
is desirable to guide downstream immuno-histochemistry, genomics, and precision medicine…

Pathologists are responsible for rapidly providing a diagnosis on critical health issues.
Challenging cases benefit from additional opinions of pathologist colleagues. In addition to on-…

Spatially organized macromolecular complexes are essential for cell and tissue function, but
the mechanisms that organize micron-scale structures within cells are not well understood. …

Modern digital pathology departments have grown to produce whole-slide image data at
petabyte scale, an unprecedented treasure chest for medical machine learning tasks. …

Large-scale annotated image datasets like ImageNet and CIFAR-10 have been essential in
developing and testing sophisticated new machine learning algorithms for natural vision …

The expanding adoption of digital pathology has enabled the curation of large repositories
of histology whole slide images (WSIs), which contain a wealth of information. Similar …

Problem The past decades have yielded an explosion of research using artificial intelligence
for cancer detection and diagnosis in the field of computational pathology. Yet, an often …

The adoption of digital pathology has enabled the curation of large repositories of gigapixel
whole-slide images (WSIs). Computationally identifying WSIs with similar morphologic …

Pathologists must rapidly interpret microscopic images of a tissue specimen to provide a
diagnosis. To diagnose, a pathologist may additionally consider or interpret patient history, …