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Key Features

  • Exporting results in rtss format
  • Lesion candidate localization and classification
  • Pre-populated pi-rads report
  • Prostate gland segmentation and volumetric assessment
  • Suspicion map highlighting the lesion candidates

General Information

Product name

Prostate MR on syngo.via

Subspeciality

Abdomen

Modality

MR

Disease targeted

Prostate cancer

Main task

Not specified

Technical Specifications

Population

Men with suspected cancer in treatment-naïve prostate glands

Patient population age

Not specified

Input

Transversal T2-weighted image, low and high b-value DWI

Input format

DICOM

Output

Prostate gland and lesion contours, suspicion heatmap, structured report with volumetrics, PSA density and classification, RTSS

Output format

DICOM, DICOM RT-STRUCT

Integration

Integration in Advanced Visualization and Post-Processing Platform

Deployment

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

Trigger for analysis

Automatically, Etc., Image upload, In pre-processing, On demand, Right after the image acquisition, Triggered by a user through e.g. a button click

Processing time

3 - 10 seconds

Regulatory Information

CE Certification

Pathway:

MDD

Class:

Class IIa

Verified by Health AI Register

Other certifications

Not specified

Market Presence

On market since

08-2020

AI Platforms

Siemens Healthineers

Resellers

Not specified

Countries present

Not specified

Paying clinical customers

>10

Research/test users

>10

Pricing Information

Pricing model

Subscription

Based on

Number of analyses

Evidence & Research

Peer-Reviewed Papers

Peer-Reviewed

View

MRI-based Deep Learning Algorithm for Assisting Clinically Significant Prostate Cancer Detection: A Bicenter Prospective Study

Peer-Reviewed

View

Prediction of upgrade to clinically significant prostate cancer in patients under active surveillance: Performance of a fully automated AI‐algorithm for lesion detection and classification

Peer-Reviewed

View

Multi-Center Benchmarking of a Commercially Available Artificial Intelligence Algorithm for Prostate Imaging Reporting and Data System (PI-RADS) Score Assignment and Lesion Detection in Prostate MRI

Peer-Reviewed

View

A Novel Deep Learning Based Computer-Aided Diagnosis System Improves the Accuracy and Efficiency of Radiologists in Reading Biparametric Magnetic Resonance Images of the Prostate

Peer-Reviewed

View

Detection and PI-RADS classification of focal lesions in prostate MRI: Performance comparison between a deep learning-based algorithm (DLA) and radiologists with various levels of experience

Peer-Reviewed

View

A concurrent, deep learning–based computer-aided detection system for prostate multiparametric MRI: a performance study involving experienced and less-experienced radiologists

Other Articles

Other

View

Automated deep-learning system in the assessment of MRI-visible prostate cancer: comparison of advanced zoomed diffusion-weighted imaging and conventional technique. _x000D_

Other

View

False Positive Reduction using Multiscale Contextual Features for Prostate Cancer Detection in Multi-Parametric MRI Scans

Source: vendor | First published: Jul 19, 2023 | Last updated: Jul 10, 2025