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ChestView

Key Features

  • Consolidation
  • Detection and localization of pneumothorax
  • Mediastinal or hilar mass
  • Nodule
  • Pleural effusion
  • Triage
  • Worklist prioritization

General Information

Product name

ChestView

Company

Subspeciality

Chest

Modality

X-ray

Disease targeted

Pneumothorax, pleural effusion, consolidation, nodule, mediastinal or hilar mass

Main task

Not specified

Technical Specifications

Population

Adults and Children (> 15 years old)

Patient population age

Not specified

Input

Chest X-rays AP, PA, lateral, bed side

Input format

DICOM

Output

Summary table, bounding boxes showing regions of interest

Output format

DICOM SC

Integration

Integration in standard reading environment (PACS), Integration RIS (Radiological Information System), Integration via AI marketplace or distribution platform

Deployment

Cloud-based, Locally on dedicated hardware, Locally virtualized (virtual machine, Docker)

Trigger for analysis

Automatically, Right after the image acquisition

Processing time

10 - 60 seconds

Regulatory Information

CE Certification

Pathway:

MDR

Class:

Class IIa

Not verified by Health AI Register

Other certifications

Not specified

Market Presence

On market since

05-2021

AI Platforms

Agfa Healthcare, Aidoc, Blackford Analysis, CARPL.AI, Deepc, Ferrum Health, Fujifilm, Incepto, Nuance, Sectra, Siemens Healthineers, TeraRecon

Resellers

RMS Medical Devices

Countries present

>36

Paying clinical customers

>350

Research/test users

Not specified

Pricing Information

Pricing model

Pay-per-use, Subscription

Based on

Number of analyses, Number of installations

Evidence & Research

Peer-Reviewed Papers

Peer-Reviewed

View

Efficacy of a deep learning-based software for chest X-ray analysis in an emergency department

Peer-Reviewed

View

Using AI to Improve Radiologist Performance in Detection of Abnormalities on Chest Radiographs

Peer-Reviewed

View

Learning from the machine: AI assistance is not an effective learning tool for resident education in chest x-ray interpretation

Technical Papers

Technical

View

Abstract ECR 2023 (RPS 504-2): Evaluation of radiologists’ performance compared to a deep learning algorithm for the detection of thoracic abnormalities on chest X-ray

Source: vendor | First published: Apr 11, 2024 | Last updated: Jul 9, 2025