Key Features

  • Detection Aid
  • Exam Score
  • Region Analysis
  • Risk score

General Information

Product name

Transpara

Subspeciality

Breast

Modality

Mammography

Disease targeted

Breast cancer

Main task

Not specified

Technical Specifications

Population

Asymptomatic women

Patient population age

Not specified

Input

2D Full-Field Digital Mammography, 3D Digital Breast Tomosynthesis

Input format

DICOM

Output

Region findings, region scores and an exam score

Output format

DICOM Mammography CAD Structured Report

Integration

Integration in standard reading environment (PACS), 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

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

09-2015

AI Platforms

Agfa Healthcare, Aidoc, Bayer Pharmaceuticals, Blackford Analysis, Fujifilm, Incepto, Sectra, Siemens Healthineers

Resellers

Fomei and Medical Solutions, Human Bytes, Volpara Health

Countries present

30+

Paying clinical customers

Non-disclosed

Research/test users

Non-disclosed

Pricing Information

Pricing model

Not specified

Based on

Not specified

Evidence & Research

Peer-Reviewed Papers

Peer-Reviewed

View

Screening performance and characteristics of breast cancer detected in the Mammography Screening with Artificial Intelligence trial (MASAI): a randomised, controlled, parallel-group, non-inferiority, single-blinded, screening accuracy study

Peer-Reviewed

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Using AI to Select Women with Intermediate Breast Cancer Risk for Breast Screening with MRI

Peer-Reviewed

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AI-enhanced Mammography With Digital Breast Tomosynthesis for Breast Cancer Detection: Clinical Value and Comparison With Human Performance

Peer-Reviewed

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Early Indicators of the Impact of Using AI in Mammography Screening for Breast Cancer

Peer-Reviewed

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The efficacy of artificial intelligence (AI) in detecting interval cancers in the national screening program of a middle-income country

Peer-Reviewed

View

AI performance by mammographic density in a retrospective cohort study of 99,489 participants in BreastScreen Norway

Peer-Reviewed

View

Breast cancer detection accuracy of AI in an entire screening population: a retrospective, multicentre study

Peer-Reviewed

View

Impact of real-life use of artificial intelligence as support for human reading in a population-based breast cancer screening program with mammography and tomosynthesis

Peer-Reviewed

View

AI Risk Score on Screening Mammograms Preceding Breast Cancer Diagnosis

Peer-Reviewed

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Artificial intelligence-supported screen reading versus standard double reading in the Mammography Screening with Artificial Intelligence trial (MASAI): a clinical safety analysis of a randomised, controlled, non-inferiority, single-blinded, screening accuracy study

Peer-Reviewed

View

Artificial intelligence in BreastScreen Norway: a retrospective analysis of a cancer-enriched sample including 1254 breast cancer cases

Peer-Reviewed

View

Multi-modal artificial intelligence for the combination of automated 3D breast ultrasound and mammograms in a population of women with predominantly dense breasts

Peer-Reviewed

View

Artificial Intelligence Evaluation of 122 969 Mammography Examinations from a Population-based Screening Program

Peer-Reviewed

View

Stand-Alone Use of Artificial Intelligence for Digital Mammography and Digital Breast Tomosynthesis Screening: A Retrospective Evaluation

Peer-Reviewed

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Artificial Intelligence Detection of Missed Cancers at Digital Mammography That Were Detected at Digital Breast Tomosynthesis

Peer-Reviewed

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Impact of Artificial Intelligence Decision Support Using Deep Learning on Breast Cancer Screening Interpretation with Single-View Wide-Angle Digital Breast Tomosynthesis

Peer-Reviewed

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AI-based Strategies to Reduce Workload in Breast Cancer Screening with Mammography and Tomosynthesis: A Retrospective Evaluation

Peer-Reviewed

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Impact of artificial intelligence support on accuracy and reading time in breast tomosynthesis image interpretation: a multi-reader multi-case study

Peer-Reviewed

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Can artificial intelligence reduce the interval cancer rate in mammography screening?

Peer-Reviewed

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Artificial intelligence for breast cancer detection in mammography: experience of use of the ScreenPoint Medical Transpara system in 310 Japanese women

Peer-Reviewed

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Identifying normal mammograms in a large screening population using artificial intelligence

Peer-Reviewed

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Can we reduce the workload of mammographic screening by automatic identification of normal exams with artificial intelligence? A feasibility study

Peer-Reviewed

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Detection of Breast Cancer with Mammography: Effect of an Artificial Intelligence Support System

Peer-Reviewed

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Stand-Alone Artificial Intelligence for Breast Cancer Detection in Mammography: Comparison With 101 Radiologists

Other Articles

Other

View

Assessing Breast Cancer Risk by Combining AI for Lesion Detection and Mammographic Texture

Other

View

Impact of Artificial Intelligence System and Volumetric Density on Risk Prediction of Interval, Screen-Detected, and Advanced Breast Cancer

Other

View

Computer-aided Detection of Masses at Mammography: Interactive Decision Support versus Prompts

Other

View

Standalone computer-aided detection compared to radiologists' performance for the detection of mammographic masses

Other

View

Using Computer Aided Detection in Mammography as a Decision Support

Source: vendor | First published: May 2, 2024 | Last updated: Jul 9, 2025