Veolity thumbnail 1
Veolity thumbnail 2
Veolity thumbnail 3

Key Features

  • Nodule detection
  • Report generation according to guidelines
  • Segmentation and quantification
  • Temporal registration and nodule comparison

General Information

Product name

Veolity

Subspeciality

Chest

Modality

CT

Disease targeted

Lung Cancer

Main task

Not specified

Technical Specifications

Population

Chest CTs on an asymptomatic population

Patient population age

Not specified

Input

3D chest CT

Input format

DICOM

Output

CAD report, CAD overlay, radiology report

Output format

DICOM GSPS, DICOM SC, DICOM SR, PDF, TXT, XML

Integration

Integration CIS (Clinical Information System), Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Stand-alone third party application

Deployment

Locally on dedicated hardware, Locally virtualized (virtual machine, Docker)

Trigger for analysis

Automatically, Right after the image acquisition

Processing time

Not specified

Regulatory Information

CE Certification

Pathway:

MDR

Class:

Class IIa

Verified by Health AI Register
FDA Certification

Pathway:

510(k) cleared

Class:

Class II

Verified by Health AI Register

Other certifications

Not specified

Market Presence

On market since

03-2015

AI Platforms

Blackford Analysis, Intrasense

Resellers

Not specified

Countries present

25+ (including Europe, USA, Canada, Australia, Republik of Korea, Hong Kong, New Zealand)

Paying clinical customers

500+

Research/test users

Veolity is used in several clinical trials world-wide

Pricing Information

Pricing model

Not specified

Based on

Not specified

Evidence & Research

Peer-Reviewed Papers

Peer-Reviewed

View

Assisted versus Manual Interpretation of Low-Dose CT Scans for Lung Cancer Screening: Impact on Lung-RADS Agreement

Source: vendor | First published: May 26, 2024 | Last updated: Jul 9, 2025