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Key Features

  • Lesion detection
  • PI-RADS 2.1 structured report
  • Prostate segmentation

General Information

Product name

QP-Prostate

Company

Subspeciality

Abdomen

Modality

MR

Disease targeted

Prostate Cancer

Main task

Not specified

Technical Specifications

Population

Male adult population. Exclusion: patients with endorectal coil, radical prostatectomy or hip prosthesis.

Patient population age

Not specified

Input

T2w, DWI sequence, DCE (not needed for lesion detection)

Input format

DICOM

Output

Lesion detection overlay, prostate segmentation overlay, quantitative information (ADC, high b-value, Ktrans, Kep, Ve), structured report based on PI-RADS 2.1

Output format

DICOM SC

Integration

Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform, Stand-alone webbased

Deployment

Cloud-based

Trigger for analysis

Automatically, Right after the image acquisition

Processing time

1 - 10 minutes

Regulatory Information

CE Certification

Pathway:

MDR

Class:

Class IIb

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

CE/UKCA 10-2022. 510(k) clearance since 12-2020.

AI Platforms

Philips Healthcare

Resellers

Not specified

Countries present

10

Paying clinical customers

Not specified

Research/test users

Not specified

Pricing Information

Pricing model

Subscription

Based on

Number of analyses

Evidence & Research

Peer-Reviewed Papers

Peer-Reviewed

View

Automated prostate multi-regional segmentation in magnetic resonance using fully convolutional neural networks

Other Articles

Other

View

Automatic individual arterial input functions calculated from PCA outperform manual and population-averaged approaches for the pharmacokinetic modeling of DCE-MR images

Source: vendor | First published: Jan 30, 2024 | Last updated: Jul 9, 2025