Radiomics is our main product and now available as a research software. We also offer consultancy, providing you with our expertise and tools to facilitate or even perform the complete Radiomic analysis for you.
Radiomics for research
Radiomics is now available as a research software. Our research software solution allows you to fully explore the potential of quantitative imaging biomarkers. Please contact us for more information and we will gladly make you a quotation.
Get Radiomics for research now - contact us
Note: the Radiomics research software is not a medical device and is therefore not approved for clinical use. As such, the outputs of the software may not be used for any clinical purpose, or for clinical decision making.
At OncoRadiomics we offer consultancy, which will provide you with our expertise and tools to facility your Radiomics analyses. We can also perform the complete Radiomic analysis for you. Please contact us for more information.
Get Radiomics consultancy - contact us
Note: acquired results are for research purposes only. They may not be used for any clinical purpose, or for clinical decision making.
Radiomics for clinical use
We are currently developing RADIOMICS™ as a CE certified standalone software and plug-in to be integrated in marketed software packages, and later with FDA approval. RADIOMICS™ will be developed in a modular way and a RADIOMICS™ module can be easily incorporated into treatment planning and diagnostic radiology software from companies such as RaySearch, Varian, Aquilab, Siemens, Philips, Intuitim and Elekta. In addition, RADIOMICS™ will be offered as a (SaaS) service for patient stratification and response assessment in pharma-sponsored clinical trials. New research and development activities are needed to expand the applicability of RADIOMICS™ for PET imaging and the development of DeltaRadiomics™ to monitor longitudinal treatment response.
DISTRIM is currently under development. More information about DISTRIM can be found below.
Biomarkers including Radiomics-based QIBs strongly rely on the large independent data sets. There is a need to continuously update and refine the radiomics signatures which increase the predictive power of these algorithms. In order to do so, there is a need to have access to many different and large data sets. However, these data sets are distributed among many different centres and access is restricted due to privacy reasons. This means that these data sets cannot leave the hospitals.
Distributed learning of medical data (DISTRIM™) is a new approach to use distributed medical data sets from all over the world without the need of data leaving the hospital firewalls. DISTRIM™ will enable us to mine large amount of images without the images leaving the firewall of the hospitals. Distributed learning is an emerging topic in the field of machine learning; it was created and studied in order to achieve performance optimisation and solving optimisation problems with a large number of variables and items as a typical implementation of parallel computing. This approach can be exploited both to the aim of preserving data privacy and to protect data property. The added values of Distributed Learning are: 1) the privacy issues resolutions: the data do not leave each centre, less organisational and bureaucratic issues, with possibility to exploit validated standard. It will facilitate the participation of more centres in the data sharing and 2) Scalability of the computation processes: map-reduce approach.