What if an AI solution could automatically quantify brain white matter abnormalities in your patients?
Objectively track disease progression in individual multiple sclerosis patients.
Objectively quantify relevant brain structures in individual dementia patients.
- Objective radiological reporting via accurate and standardized measurements to monitor neurological disorders.
- Better patient care and communication with normative reference values and color-coded segmentations to help conceptualize the patient’s condition.
- Fast and consistent radiological reading thanks to complementary color-coded segmentations in DICOM-format to assist with radiological reporting.
- Earlier prediction of disability, disease progression and treatment response.
What Radiologists are saying
“Like icobrain, brain biomarker measurements need to be extremely reproducible and sensitive enough to detect relevant clinical changes.”
Dr. Max Wintermark, Professor of Radiology and Chief of Neuroradiology at Stanford University Medical Center, USA.
“icobrain has been a really valuable addition to our clinical practice as patients can conceptually understand much better what we are looking for in their brain scans.”
Prof. Jeffrey Dunn, MD.
- Fragoso, Yara Dadalti, Paulo Roberto Wille, Marcelo Abreu, Joseph Bruno B. Brooks, Ronaldo Maciel Dias, Juliana Avila Duarte, Luciano Farage, et al. “Correlation of Clinical Findings and Brain Volume Data in Multiple Sclerosis.” Journal of Clinical Neuroscience 44 (October 2017): 155–57. https://doi.org/10.1016/j.jocn.2017.06.006.
- Jain, Saurabh, Diana M. Sima, Annemie Ribbens, Melissa Cambron, Anke Maertens, Wim Van Hecke, Johan De Mey, et al. “Automatic Segmentation and Volumetry of Multiple Sclerosis Brain Lesions from MR Images.” NeuroImage: Clinical 8 (2015): 367–75. https://doi.org/10.1016/j.nicl.2015.05.003.
- Lysandropoulos, Andreas P., Julie Absil, Thierry Metens, Nicolas Mavroudakis, François Guisset, Eline Van Vlierberghe, Dirk Smeets, Philippe David, Anke Maertens, and Wim Van Hecke. “Quantifying Brain Volumes for Multiple Sclerosis Patients Follow-up in Clinical Practice – Comparison of 1.5 and 3 Tesla Magnetic Resonance Imaging.” Brain and Behavior 6, no. 2 (February 2016): n/a-n/a. https://doi.org/10.1002/brb3.422.
- Smeets, Dirk, Annemie Ribbens, Diana M. Sima, Melissa Cambron, Dana Horakova, Saurabh Jain, Anke Maertens, et al. “Reliable Measurements of Brain Atrophy in Individual Patients with Multiple Sclerosis.” Brain and Behavior 6, no. 9 (September 2016): e00518. https://doi.org/10.1002/brb3.518.
- Wang, C, H N Beadnall, S N Hatton, G Bader, D Tomic, D G Silva, and M H Barnett. “Automated Brain Volumetrics in Multiple Sclerosis: A Step Closer to Clinical Application.” Journal of Neurology, Neurosurgery & Psychiatry 87, no. 7 (July 2016): 754–57. https://doi.org/10.1136/jnnp-2015-312304.
- Wintermark, Max, Ying Li, Victoria Y. Ding, Yingding Xu, Bin Jiang, Robyn L. Ball, Michael Zeineh, Alisa Gean, and Pina Sanelli. “Neuroimaging Radiological Interpretation System for Acute Traumatic Brain Injury.” Journal of Neurotrauma 35, no. 22 (November 15, 2018): 2665–72. https://doi.org/10.1089/neu.2017.5311.