RTC Artificial Intelligence
We use artificial intelligence to analyze medical images and other medical data. We have set up a high-performance GPU cluster on which deep learning systems can be trained and deployed. We provide advise and develop algorithms and web-based image analysis and data analytics software.
Services and expertise
AI internships
AI internships at the Radboudumc for Master students. Do you have an idea for an AI innovation? Submit a project proposal for an AI internship.
Read more →
Services
RTC AI can provide expert guidance and services for big data analysis and deep learning, specifically in the field of image analysis, but also on predictive analytics in general.
Read more →
Projects
ASSET: Automatic Fetal Biometry in First Trimester 3D Volumetric Ultrasound
AI-supported sonographic tomography for first-trimester fetal examination
Read more →
MSKAssist: AI-assisted assessment of hand and wrist radiographs
Comprehensive analysis of hand and wrist radiographs with the help of artificial intelligence
Read more →
Text mining to extract lifestyle classifications for prevention-related research
Extracting lifestyle information for prevention-related research from clinical notes using text mining and NLP techniques
Read more →
MHub/IDC/Grand Challenge algorithm exchange
A collaboration between Radboudumc, MHub, and Imaging Data Commons (IDC), aimed at exchanging algorithms and investigating interoperability regarding exchange of data and algorithms.
Read more →
PARADIGM: The diagnostic potential of 3D ultrasound with AI in maternity care
Determining the diagnostic potential of 3D ultrasound images acquired in the first trimester of pregnancy and analyzed with Artificial Intelligence
Read more →
Quantifying IHC pathology stains
For the Pathology department we are developing an application that can unmix different IHC stains to aid analysist in quantifying pathology scans.
Read more →
Coronary artery segmentation
For the department of Cardiology we are developing an application for the segmentation of coronary arteries in cardiac OCT recordings.
Read more →
Adipose and muscular tissue segmentation
For the department of Health Evidence we are developing an application for the segmentation and quantification of adipose and muscular tissue in non-contrast abdominal CT.
Read more →
Brain MRI classification
In the context of the “Nationale Wetenschapsagenda” (NWA) roadmap for Value Creation through Responsible Access to and use of Big Data (VWdata) we are collecting data and setting up a challenge for the identification of healthy or abnormal MRI scans of the brain.
Read more →Infrastructure & Software
