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Saige Lung (Veye Lung Nodules)
Saige Lung (Veye Lung Nodules)
DeepHealth
This AI assistant supports radiologists with detecting, classifying and tracking the growth of pulmonary nodules. Saige Lung (previously Veye Lung Nodules by Aidence) integrates into the PACS and is currently in use across Europe in both routine clinical practice and lung cancer screening programs.
Information source:
Vendor
Last updated:
Nov. 30, 2023
General Information
Technical Specifications
Regulatory
Market
Evidence
General Information
General
Product name
Saige Lung (Veye Lung Nodules)
Company
DeepHealth
Subspeciality
Chest
Modality
CT
Disease targeted
Lung cancer
Key-features
Nodule detection, nodule classification, volume quantification, growth calculation (prior study retrieval)
Suggested use
During: perception aid (prompting all abnormalities/results/heatmaps), interactive decision support (shows abnormalities/results only on demand), report suggestion
Technical Specifications
Data characteristics
Population
Input
low or standard dose CT scans, maximum axial slice thickness of 3mm, non-contrast or post-contrast, multi-slice
Input format
DICOM
Output
Image annotations, grayscale presentation state (GSPS), burn-in series, table of quantified values
Output format
DICOM, PDF
Technology
Integration
Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform
Deployment
Locally on dedicated hardware, Locally virtualized (virtual machine, docker), Cloud-based
Trigger for analysis
Automatically, right after the image acquisition
Processing time
1 - 10 minutes
Regulatory
Certification
CE
Certified, Class IIb
, MDR
FDA
No or not yet
Intended Use Statements
Intended use (according to CE)
Assist physicians in their review of CT scans in the detection, classification, quantification and growth assessment of solid and sub-solid pulmonary nodules using low-dose or standard-dose and non-contrast or post-contrast scans with a maximum axial slice thickness of ≤3mm. Veye lung Nodules is intended for use as a second or concurrent reader.
Market
Market presence
On market since
12-2017
Distribution channels
Nuance PIN, Incepto, Sectra, deepcOS, Blackford, Nordic Medtech, Inobe
Countries present (clinical, non-research use)
7
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing
Pricing model
Pay-per-use
Based on
Number of scans analysed
Evidence
Evidence
Peer reviewed papers on performance
Performance of AI for preoperative CT assessment of lung metastases: Retrospective analysis of 167 patients
(read)
Higher agreement between readers with deep learning CAD software for reporting pulmonary nodules on CT
(read)
Validation of a deep learning computer aided system for CT based lung nodule detection, classification, and growth rate estimation in a routine clinical population
(read)
Clinical evaluation of a deep-learning-based computer-aided detection system for the detection of pulmonary nodules in a large teaching hospital
(read)
Effect of CT reconstruction settings on the performance of a deep learning based lung nodule CAD system
(read)
Non-peer reviewed papers on performance
Other relevant papers