Pixyl.Neuro by Pixyl

Neuroimaging Insight powered by AI

Winners of the JFR Data Challenge 2019

A solution for quantifying neurological biomarkers

The analysis of MRI slices as part of the follow-up of neurodegenerative and neuroinflammatory diseases, such as Multiple Sclerosis, is essential. In fact, it allows to evaluate and predict disease time trends and response to treatment where appropriate. This analytical work is essential for radiologists whose image analysis workload is increasing by 10% each year (for a stable number of radiologists).

What if an AI solution could quantify automatically
brain abnormalities of the white substance?

Based on advanced Artificial Intelligence technology for brain MRI analysis. Pixyl.neuro allows you to quantify and track the progress of the disease in your patients with multiple sclerosis or dementia.
The software is compatible with any type of MR exam.

The results are provided, directly into your clinical workflow in a fully automated way and in about 5 minutes.

Expected benefits

What Specialist are saying

  • Objective radiological report through accurate and standardized measurements.
  • Quick reading through segmentation using an intuitive color code.
  • An Automatic tool assist in decision making in your workflow, avalaible in about 5 minutes.
  • Earlier prediction of disability, disease progression and treatment response.

The high sensitivity achieved by Pixyl analysis allows to detect earlier disease progression, leading to a better care pathway for the patient.

Dr Arnaud Attye, Neuroradiologist, CHU Grenoble.


  1. Use of Software Analytics of Brain MRI (with & without contrast) As Objective Metric in Neurological Disorders and Degenerative Diseases. Int Phys Med Rehab J 2017, 2(2): 00046
  2. The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS). Menze et al. DOI 10.1109/TMI.2014.2377694
  3. Objective Evaluation of Multiple Sclerosis Lesion Segmentation using a Data Management and Processing Infrastructure. Nature Scientific Reports | (2018) 8:13650 | DOI:10.1038/s41598-018-31911-7