AI Medical
Jazz is software for the digitalization of radiological findings, with quantitative single lesion tracking. Jazz is aimed at improving the assessment of the evolution of complex brain pathologies such as chronic multiple sclerosis or multi-metastatic brain disease.
Information source: Vendor
Last updated: March 24, 2024

General Information

Product name Jazz
Company AI Medical
Subspeciality Neuro
Modality MR
Disease targeted Multiple sclerosis (MS), brain metastasis
Key-features Brain lesion detection, volume quantification
Suggested use During: interactive decision support (shows abnormalities/results only on demand), report suggestion

Technical Specifications

Data characteristics
Population Patients with known diagnosis of multiple sclerosis or brain metastasis
Input Any brain MRI
Input format DICOM
Output Report with user prefered items such as evolution, anatomical position, mcDonald criteria (for MS), lesion treatment (for metastasis), etc
Output format DICOM, pdf, rtf
Integration Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Integration CIS (Clinical Information System)
Deployment Locally on dedicated hardware
Trigger for analysis Automatically, right after the image acquisition
Processing time 3 - 10 seconds


Certified, Class IIa , MDR
FDA 510(k) cleared , Class II
Intended Use Statements
Intended use (according to CE) Jazz is intended for the labeling, visualization and volumetric quantification of segmentable brain structures from a set of CT or MR images, and the production of a radiological report.


Market presence
On market since 02-2023
Distribution channels
Countries present (clinical, non-research use)
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing model Subscription
Based on


Peer reviewed papers on performance

  • Evaluation of the quality and the productivity of neuroradiological reading of multiple sclerosis follow-up MRI scans using an intelligent automation software (read)

Non-peer reviewed papers on performance

  • Improved Detection, Description and Efficiency of Multiple Sclerosis Neuroradiological Lesions’ Assessment using a Semi-Automatic Dedicated Deep-Learning Based Software Jazz (read)

Other relevant papers