Editorial Computational Pathology

Abstract

Until recent years, histopathologists have analyzed tissue sections and diagnosed diseases including cancer primarily by using a microscope. The introduction of high resolution and high throughput digital scanners has enabled digitizing entire glass slides to generate high-resolution whole-slide images (WSI), de facto giving rise to the field of Digital Pathology. Since then, an increasing number of pathology laboratories have transitioned to a digital pipeline, which offers advantages such as remote diagnosis (e.g., for a second opinion), reduction of some routine work in the lab and partly reduction of physical storage. However, perhaps the most revolutionizing aspect of digital pathology is that it enables image analysis in pathology using machine learning. This field has come to be known as Computational Pathology.