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InferRead CT Lung
InferRead CT Lung
Infervision
InferRead CT Lung is a processing solution for lung cancer screening. It recognizes the core features of lung cancer, determine the characteristics of suspected lung nodules in different image sequences and aims to aid early-stage diagnosis. This solution provides information on nodules, including position, size, density, malignancy rate and evolution.
Information source:
Vendor
Last updated:
November 6, 2024
General Information
Technical Specifications
Regulatory
Market
Evidence
General Information
General
Product name
InferRead CT Lung
Company
Infervision
Subspeciality
Chest
Modality
CT
Disease targeted
Lung cancer
Key-features
Lung nodule detection, report generation, multi-timepoint analysis
Suggested use
During: interactive decision support (shows abnormalities/results only on demand), report suggestion
After: diagnosis verification
Technical Specifications
Data characteristics
Population
Input
CT thorax
Input format
DICOM
Output
Type of lesions (solid, calcified, GGN nodules, semi-solid, etc.), location of each lesion (layer and anatomical location), density of the lesion, volume of the lesion, degree of malignancy of the lesion, draft report
Output format
DICOM overlay, pdf file (draft report), DICOM GSPS, webviewer (description of lesion features)
Technology
Integration
Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Integration CIS (Clinical Information System), Stand-alone third party application, Stand-alone webbased
Deployment
Locally on dedicated hardware, Locally virtualized (virtual machine, docker), Cloud-based
Trigger for analysis
Automatically, right after the image acquisition, On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time
1 - 10 minutes
Regulatory
Certification
CE
Certified, Class IIb
, MDR
FDA
510(k) cleared , Class II
Intended Use Statements
Intended use (according to CE)
The design, Development and Manufacture of Computer aided diagnostic software for viewing and analyzing DICOM images to assist physicians with abnormality detection and diagnosis.
Market
Market presence
On market since
01-2020
Distribution channels
deepcOS
Countries present (clinical, non-research use)
7
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing
Pricing model
Subscription
Based on
Number of installations
Evidence
Evidence
Peer reviewed papers on performance
Artificial intelligence-driven computer aided diagnosis system provides similar diagnosis value compared with doctors' evaluation in lung cancer screening
(read)
Non-peer reviewed papers on performance
Other relevant papers