DIAG Research Software Engineering
The Research Software Engineering Team is part of the Diagnostic Image Analysis Group at Radboud University Medical Center in Nijmegen, The Netherlands.
We use industry best practices to develop software that enables researchers to rapidly develop novel machine learning algorithms that we can integrate into research workstations for clinical validation.
Software
ASAP - Fluid whole-slide image viewer
ASAP (Automated Slide Analysis Platform) is a fast and fluid viewer for digitized multi-resolution histopathology images. ASAP offers several tools to make annotations in an intuitive way. Dots, rectangles, polygons are all supported. ASAP allows on-slide visualization of image analysis and machine learning results such as segmentation masks with customizable lookup-tables.
Read more →CIRRUS Lung Screening
This workstation is a highly optimized reading platform that allows fast and standardized reading of lung screening CT scans.
Read more →Ophthalmology workstation
The goal of this project is to develop a software solution that assists researchers and specialists to view and annotate retinal images.
Read more →SOL
DIAG's deep learning cluster for training and applying automated image analysis tools.
Read more →
