Medexprim’s Radiomics Enabler goes open-source to support big data projects in biomedical imaging
Quantitative medical imaging biomarkers discovery (radiomics) and cognitive imaging analytics are transforming radiology. These developments require that researchers access large amounts of imaging data, sufficient in quality, quantity, and diversity. These data exist and are stored by hospitals in clinical PACS (Picture Archiving and Communication System). However, the exploitation of this treasure of resources is hampered by the tedious task of selecting, extracting, and de-identifying relevant image sequences.
Medexprim’s Radiomics Enabler is an ETL (Extract-Transform-Load) for medical imaging. It automates the qualification and extraction of relevant imaging sequences from any PACS, for secondary use in research. The solution can be integrated within a Clinical Data Warehouse (CDW) to create unified and harmonized patient cohorts, with a complete access to their clinical and imaging data. Instead of spending months in manual/ low value tasks extracting and preparing data, researchers can focus on their key expertise in data science and medicine.
Medexprim chose to distribute its software as open-source, in order to foster a fast adoption by the imaging community at large, and specifically by research groups working on radiomics or developing AI algorithms. The ultimate goal is to optimize translational research and accelerate access to personalized medicine for all patients. This move adds to the range of open source solutions available for research in biomedical imaging, among which RSNA’s Clinical Trials Processor (CTP) or XNAT, for which Medexprim also provides commercial support.
Radiomics Enabler will be featured on Medexprim’s booth at RSNA 2017, on the Startup Showcase Kiosk (North – Hall B: 6455B).
