Vendor source

Reviewed 8 Oct 2026

Completeness Comprehensive (81%)

Transpara provides decision support during reading of 2D Full-Field Digital Mammography (FFDM) and 3D Digital Breast Tomosynthetis (DBT) to help improve clinical accuracy, reduce workload and optimize workflow. Transpara is intended to support healthcare professionals with detection and diagnosis of breast lesions or for assessment of breast density and breast cancer risk using radiological images of the breast. Version 2.1 includes temporal comparison up to 3 exams.

Supported by 40 papers

Key Features

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

General Information

Product name

Transpara

Modality

Mammography

Main task

Not specified

Subspeciality

Breast

Disease targeted

Breast cancer

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

Evidence & Research

Peer-Reviewed Papers

Comparison of Artificial Intelligence Detection and Short-Term Breast Cancer Risk Models within and beyond Their Intended Use in Mammography Screening

Radiology: Imaging Cancer · Sep 2026

Outcomes of Single-View Asymmetries Recalled From Screening Mammography and Exploratory Analysis of AI Detection

Canadian Association of Radiologists Journal · Aug 2026

Artificial Intelligence for Digital Breast Tomosynthesis Screening with and without Prior Examinations in BreastScreen Norway

Radiology: Artificial Intelligence · May 2026

AI-based triage and decision support in mammography and digital tomosynthesis for breast cancer screening: a paired, noninferiority trial

Nature Medicine · Mar 2026

Interval cancer, sensitivity, and specificity comparing AI-supported mammography screening with standard double reading without AI in the MASAI study: a randomised, controlled, non-inferiority, single-blinded, population-based, screening-accuracy trial

The Lancet · Jan 2026

Performance across different versions of an artificial intelligence model for screen-reading of mammograms

European Radiology · Jan 2026

Performance of an Artificial Intelligence Support System on Screening Mammography Cases Proceeding to Stereotactic Biopsy

Cancers · Dec 2025

Invasion prediction with artificial intelligence in ductal carcinoma in situ (DCIS) patients: a proof-of-concept study

BMC Surgery · Oct 2025

Mammographic features in screening mammograms with high AI scores but a true-negative screening result

Acta Radiologica · Sep 2025

Commercial Artificial Intelligence Versus Radiologists: NPV and Recall Rate in Large Population-Based Digital Mammography and Tomosynthesis Screening Mammography Cohorts

American Journal of Roentgenology · Sep 2025

Combined use of two artificial intelligence-based algorithms for mammography triaging: a retrospective simulation study

European Radiology · Aug 2025

AI Should Read Mammograms Only When Confident: A Hybrid Breast Cancer Screening Reading Strategy

Radiology · Aug 2025

The use of artificial intelligence (AI) to safely reduce the workload of breast cancer screening: a retrospective simulation study

Acta Radiologica · Aug 2025

AI as an independent second reader in detection of clinically relevant breast cancers within a population-based screening programme in the Netherlands: a retrospective cohort study

The Lancet Digital Health · Aug 2025

Results from a Swedish model-based analysis of the cost-effectiveness of AI-assisted digital mammography

European Radiology · Jul 2025

Mammographic classification of interval breast cancers and artificial intelligence performance

JNCI: Journal of the National Cancer Institute · Apr 2025

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

Radiology · Feb 2025

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

The Lancet Digital Health · Feb 2025

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

Radiology: Imaging Cancer · Jul 2024

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

Radiology · Jun 2024

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

Clinical Radiology · Mar 2024

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

European Radiology · Mar 2024

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

Cancer Imaging · Dec 2023

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

European Radiology · Nov 2023

AI Risk Score on Screening Mammograms Preceding Breast Cancer Diagnosis

Radiology · Oct 2023

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

The Lancet Oncology · Aug 2023

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

European Radiology · Mar 2023

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

Insights into Imaging · Jan 2023

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

Radiology · Mar 2022

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

Radiology · Dec 2021

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

Radiology: Artificial Intelligence · Sep 2021

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

Radiology · Jul 2021

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

European Radiology · May 2021

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

Radiology · May 2021

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

European Radiology · Jan 2021

Identifying normal mammograms in a large screening population using artificial intelligence

European Radiology · Sep 2020

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

Breast Cancer · Feb 2020

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

European Radiology · Apr 2019

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

JNCI: Journal of the National Cancer Institute · Nov 2018

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

Radiology · Nov 2018

Technical Specifications

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

Population

Asymptomatic women

Market Presence

On market since

09-2015

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

Source: Vendor | First published: May 2, 2024 | Last updated: Oct 8, 2026