Fully automated solutions
for voxel-based multi-parametric
data analysis
of advanced MRI
About us
Mission
Getting closer and deeper understanding of the physicians.
Vision
We provide fully automated solutions for physicians who are doing their best to diagnose and treat patients.
Our team
The Dynapex team has long experience in neuroimaging, especially imaging of brain tumors and dementia. Through voxel-based multi-parametric data analysis of advanced MRI, we aim to free our customers from the labor-intensive work of image processing.
Our solutions
Research only, not for clinical use.
Glioma: 3D CE-T1WI in the left side and FLAIR in the right side showing AI-powered automatic tumor segmentation (Green: enhancing tumor, Blue: edema, Red: necrosis)
Metastasis: 3D CE-T1WI (GRE in the left side and FSE in the right side) showing AI-powered automatic small tumor segmentation (Red)
High-accuracy AI-powered segmentation is key for consistent and reproducible neuroimaging analysis. Get analysis results faster by using models proven by many studies.
- Brain tumor segmentations including necrosis, tumor enhancement, and edema using MRI.
- Segmentations of small metastasis that are hardly recognizable to the human eye
- Pre-treatment tumor volume, post-treatment tumor response, and their temporal changes during the course of the treatment
Glioma: 3D CE-T1WI, Lt and FLAIR, Rt with rCBV overlay (Cercare Medical)
In medical image analysis, complex and time-consuming pre-processing is one of the main barriers that make analysis difficult. Leave these time-consuming and repetitive tasks to DYNAPEX’s fast and flexible data pipeline.
- Automatic co-registration and image resampling for multi-parametric data
- Longitudinal analysis for single/multi-patient data, different time points
Glioma: ADC, Lt and CBV, Rt co-registered to 3D CE-T1WI with tumor habitat segmentation
You can systematically track and easily analyze data at large scale for advanced research. Get insights from your data with DYNAPEX.
- Evaluate spatial and temporal tumor heterogeneity using multi-parametric imaging
- Tumor treatment response during the course of the treatment including evaluation of pseudoprogression and pseudoresponse
Key
features
- AI-powered Segmentation
- Glioma
- Metastasis
- Dementia
- Automated pre-processing
- Multi-parametric data analysis
- Vendor-neutral integration
- Co-registration
- Normalization
- Task execution in parallel
- Advanced quantification
- Volume tracking
- Statistics
- Histogram
- Habitat (Cluster analysis)
- Add-on
- Cercare Perfusion (DSC/DCE)
- Cercare Stroke (Core/Penumbra)
Publications
Spatiotemporal Heterogeneity in Multiparametric Physiologic MRI Is Associated with Patient Outcomes in IDH-Wildtype Glioblastoma
Clinical Cancer Research / January 2021
Tumor habitat analysis by magnetic resonance imaging distinguishes tumor progression from radiation necrosis in brain metastases after stereotactic radiosurgery
European Radiology / August 2021
Low conductivity on electrical properties tomography demonstrates unique tumor habitats indicating progression in glioblastoma
European Radiology / September 2021
Hypovascular Cellular Tumor in Primary Central Nervous System Lymphoma is Associated with Treatment Resistance: Tumor Habitat Analysis Using Physiologic MRI
American Jounal of Neuroradiology / January 2022
Work in progress
Partners
