Computational pathology for nephropathology

Trillium Pathology, pp. 10–12

Abstract

Digitisation of pathology enables computational pathology. Due to their excellent performance, deep learning-based systems are used primarily. In computational nephropathology, the focus of many studies is on large-scale extraction of comprehensible quantitative data from histological structures. The resulting data can be used for various downstream analyses, including prediction of the disease course. Such systems could significantly support nephropathological diagnostics in the future.

Authors 1

1. Roman David Bülow corresponding Aachen Institute of Pathology

   RWTH Aachen University · Universitätsklinikum Aachen

   Affiliation as printed

   Institute of Pathology RWTH Aachen University Hospital