Pixyl.Neuro.MS is a deep learning tool assisting radiologists in MRI diagnosis and monitoring of multiple sclerosis (MS) patients. For each region of the brain, Pixyl.Neuro.MS counts the lesions present and calculates their overall volume, integrating the results fully automatically in the radiologist’s usual reading environment. The algorithm studies T2 FLAIR or T1 GADO sequences to identify hypersignals caused by white matter inflammation in MS.
Automatic detection, quantification and characterization of lesions in anatomical areas of interest
Pixyl.Neuro.MS measures the volume and lesion load for the entire brain and for every brain regions of interest (periventricular, juxtacortical, infratentorial, deep white matter) with regard to McDonald’s criteria (2017 revision)).
Longitudinal analysis of disease evolution if prior exam is present in the PACS
Pixyl.Neuro.MS automatically measures disease activity by segmenting and characterizing white matter evolution of lesions based on prior exams.
Automated production of a structured report and a segmented series (lesion outline) directly in the PACS
Pixyl.neuro provides the radiologist with a complete quantitative report on the lesions, their characteristics and evolution, as well as their visualization on the annotated brain images.
- multiple sclerosis
- T2 FLAIR
- T1 GADO
- lesion load
- longitudinal analysis
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- 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