Breast-SlimView

Hera-MI

Breast-SlimView is a clinical decision support solution for 2D/3D mammography. It has learnt to detect what is normal from a database of mammograms, then, based on this normalized database, it learns to detect and highlight suspicious areas. Breast-SlimView’s algorithm automatically detects and removes all normal physiological areas (vessels, glandular tissue, fatty tissue and mammary gland) and replace them by artificial fat.

Information source: Vendor
Last updated: August 3, 2020

General Information

General
Product name	Breast-SlimView
Company	Hera-MI
Subspeciality	Breast
Modality	Mammography
Disease targeted	Breast cancer
Key-features	Images negativation, risk mapping, breast density.
Suggested use	Before: stratifying reading process (non, single, double read) During: perception aid (prompting all abnormalities/results/heatmaps), interactive decision support (shows abnormalities/results only on demand) After: diagnosis verification

Technical Specifications

Data characteristics
Population	Breast cancer screening population
Input	2D & 3D mammography, reports.
Input format	DICOM
Output	2D & 3D negativated mammography, density results.
Output format	DICOM
Technology
Integration	Integration in standard reading environment (PACS), Integration via AI marketplace or distribution platform, Stand-alone third party application
Deployment	Locally on dedicated hardware, Locally virtualized (virtual machine, docker)
Trigger for analysis	Automatically, right after the image acquisition, On demand, triggered by a user through e.g. a button click, image upload, etc.
Processing time	10 - 60 seconds

Regulatory

Certification
CE	Certified, Class IIa , MDD
FDA	No or not yet
Intended Use Statements
Intended use (according to CE)

Market

Market presence
On market since	02-2020
Distribution channels
Countries present (clinical, non-research use)
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing
Pricing model	Pay-per-use, Subscription
Based on	Number of users, Number of installations, Number of analyses

Evidence

Evidence
Peer reviewed papers on performance
Non-peer reviewed papers on performance
Other relevant papers