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StrokeViewer
StrokeViewer
Nicolab
StrokeViewer aims to aid physicians in the stroke setting by workflow solutions and algorithm support. After a patient is scanned images are automatically analysed by AI and radiologists receive a mobile notification. Physicians can review the scans by logging into the system through workstation or mobile phone, and can choose to forward images to an intervention center.
Information source:
Vendor
Last updated:
Aug. 20, 2023
General Information
Technical Specifications
Regulatory
Market
Evidence
General Information
General
Product name
StrokeViewer
Company
Nicolab
Subspeciality
Neuro
Modality
CT
Disease targeted
Stroke
Key-features
LVO detection (CE, FDA), LVO location (CE), ICH detection (CE), CT Perfusion analysis (CE, FDA), Collateral assessment (CE), ASPECT scoring (CE)
Suggested use
Before: adapting worklist order, flagging acute findings
During: perception aid (prompting all abnormalities/results/heatmaps), interactive decision support (shows abnormalities/results only on demand)
Technical Specifications
Data characteristics
Population
CT suspicion of stroke
Input
NCCT, CTA, CTP
Input format
DICOM
Output
Interactive view in DICOM viewer (AI presented as overlay on CT)
Output format
DICOM
Technology
Integration
Integration in standard reading environment (PACS), Stand-alone webbased
Deployment
Cloud-based
Trigger for analysis
Automatically, right after the image acquisition
Processing time
1 - 10 minutes
Regulatory
Certification
CE
Certified, Class I
, MDD
FDA
510(k) cleared , Class II
Intended Use Statements
Intended use (according to CE)
Market
Market presence
On market since
12-2019
Distribution channels
Countries present (clinical, non-research use)
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing
Pricing model
Subscription
Based on
Category Small/Medium/Large based on number stroke patients
Evidence
Evidence
Peer reviewed papers on performance
AI-support for the detection of intracranial large vessel occlusions: One-year prospective evaluation
(read)
Artificial intelligence software for diagnosing intracranial arterial occlusion in patients with acute ischemic stroke
(read)
Value of Quantitative Collateral Scoring on CT Angiography in Patients with Acute Ischemic Stroke
(read)
Diagnostic performance of an algorithm for automated large vessel occlusion detection on CT angiography
(read)
Non-peer reviewed papers on performance
Other relevant papers