RTC Deep Learning
We use Artificial Intelligence, specifically Deep Learning, 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
Services
RTC Deep Learning 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 →
What is deep learning?
Deep learning is an AI technique that is able to learn complex patterns in large data sets.
Read more →
Projects
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 →
AI for health
A collaboration between Radboud University and Radboudumc aimed at developing innovations based on artificial intelligence that solve clinical problems.
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 →
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 →
ICH and PHE segmentation
For the CONTRAST consortium and Dutch ICH Surgery Trial (DIST) we are developing an application for the segmentation and quantification of intracerebral hemorrhage and peri-hematomal edema in non-contrast CT.
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 →
Knee segmentation
For the Orthopedics department we are developing an application for the segmentation of the tibia, patella and fibula in non-contrast CT images of the legs.
Read more →
Muscle ultrasound classification
For the Neurophysiology department we have developed an algorithm for the identification of abnormal muscle tissue in ultrasound images of the tibialis anterior.
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 →Infrastructure & Software
SOL
RTC Deep Learning's cluster for training and applying automated image analysis tools.
Read more →