Fully automated solution for quantifying MR brain scans.
cNeuro cMRI is a tool for quantitative assessment of brain images providing clinical decision support in neurological disorders.
- Cloud-based tool running in a standard browser.
- Quantitative information about volumes of brain
structures, and computed MTA & GCA.
- Quantitative assessment of vascular burden including
- Statistical comparison with a large reference database
of cognitively normal subjects.
- Interactive viewing of images and results.
- Easy reporting.
- Cloud-based – software runs in a standard web browser.
- Computation of volumes of 102 cortical and 31 subcortical regions from T1 images.
- Computation of vascular burden from FLAIR images.
- Computation of MTA, GCA (global & lobes) and Fazekas (EU only).
- Computation of relative atrophy between anterior and posterior regions.
- Interactive review of images with the ability to toggle overlays on/off for easy assessment of segmentation results.
- Visualization of gray-matter concentration map supporting assessment of brain atrophy.
- Quantitative information corrected for age, gender and head size.
- Quantitative results presented in tabular form or as age and gender corrected plots.
- Summary report for streamlined communication with referring physicians.
List of publications
SELECTED PUBLICATIONS RELEVANT TO cMRI
- M. Bruun et al. Detecting frontotemporal dementia syndromes using MRI biomarkers. NeuroImage Clinical 22: 101711, 2019. https://doi.org/10.1016/j.nicl.2019.101711
- Koikkalainen et al. Automatically computed rating scales from MRI for patients with cognitive disorders. European Radiology, 2019. https://doi.org/10.1007/s00330-019-06067-1
- Rhodius-Meester et al. Computer-assisted prediction of clinical progression in the earliest stages of AD. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring (2018). https://www.sciencedirect.com/science/article/pii/S2352872918300666
- Bruun et al. Evaluating combinations of diagnostic tests to discriminate different dementia types. Alzheimer’s & Dementia: Diagnosis, Assessment & Disease Monitoring 10, 509-518, 2018. https://doi.org/10.1016/j.dadm.2018.07.003
- Koikkalainen et al. Differential diagnosis of neurodegenerative diseases using structural MRI data. NeuroImage Clinical 11: 435-449, 2016.
- Lötjönen et al. Fast and robust extraction of hippocampus from MR images for diagnostics of Alzheimer’s disease. NeuroImage 56: 185-196, 2011.
- Koikkalainen et al. Multi-Template Tensor-Based Morphometry: Application to Analysis of Alzheimer’s Disease, NeuroImage 56: 1134-1144, 2011.
- Wolz et al. Multi-Method Analysis of MRI Images in Early Diagnostics of Alzheimer’s Disease. PLoS One 6(10):e25446, 2011. Epub 2011 Oct 13.
- Lötjönen et al. Fast and robust multi-atlas segmentation of brain magnetic resonance images. NeuroImage 49: 2352-2365, 2010.
All data transfer uses SSL encryption. Stored data are encrypted and anonymized.
More information is available in a separate security statement.
Supported web browsers:
- Google Chrome 61 or later
- Firefox 56 or later
- Internet Explorer 11 or later.
Recommended display resolution 1680 x 1050 or higher.
This product complies with the following requirements: European Council Directive 93/42/EEC concerning medical devices. cNeuro cMRI has received 510(k) clearance from the FDA for commercial sale in US market.
Indications for Use
cNeuro cMRI is intended for automatic labeling, quantification and visualization of segmentable brain structures from a set of MR images. The software is intended to automate the current manual process of identifying, labeling and quantifying the segmentable brain structures identified on MR images. The intended user profile covers medical professionals who work with medical imaging. The intended operational environment is an office-like environment with a computer.