Kheiron Medical Technologies
Mia supports radiologists in making the recall decision in breast cancer screening. Available to use in various configurations such as an independent second reader, a concurrent reader or in double reader triage. It also offers an AI-enabled breast positioning and image quality assurance tool: Mia IQ.
Information source: Vendor
Last updated: Nov. 24, 2023

General Information

Product name Mia
Company Kheiron Medical Technologies
Subspeciality Breast
Modality Mammography
Disease targeted Breast cancer
Key-features Independent second read, recall suggestion, suspicious region marking, image indications
Suggested use Before: stratifying reading process (non, single, double read)
During: perception aid (prompting all abnormalities/results/heatmaps)
After: diagnosis verification

Technical Specifications

Data characteristics
Population Mammography screening population
Input 2D Full-Field Digital Mammography
Input format DICOM
Output Recall or no recall suggestion, image indications, auxiliary regions of interest
Output format DICOM Mammography Structured Report or Presentation State
Integration Integration in standard reading environment (PACS)
Deployment Cloud-based, Hybrid solution
Trigger for analysis Automatically, right after the image acquisition
Processing time 10 - 60 seconds


Certified, Class IIa , MDD
FDA No or not yet
Intended Use Statements
Intended use (according to CE) Mia is indicated to aid readers in the interpretation of breast imaging examinations for the early detection and diagnosis of breast cancer. The device can serve as a concurrent reader in all reading workflows, including single and/or double reading workflows. Additionally, the device can serve as an independent second or third reader in blinded or unblinded workflows. The device can also be used in the triaging of examinations for workflow prioritisation, and resource management. Output of the device may include classification information such as case-wise suggestion (suspicion of malignancy and/or recommendation that the subject/patient ‘should be recalled’ or ‘should not be recalled’ for further assessment), and localisation information of suspected malignancies such as left and/or right side, projection (e.g. CC and/or MLO views), and region(s) of interest (ROI).


Market presence
On market since 10-2018
Distribution channels Various
Countries present (clinical, non-research use) 10+
Paying clinical customers (institutes)
Research/test users (institutes)
Pricing model
Based on


Peer reviewed papers on performance

  • Cost-effectiveness requirements for implementing artificial intelligence technology in the Women’s UK Breast Cancer Screening service (read)

  • Prospective implementation of AI-assisted screen reading to improve early detection of breast cancer (read)

Non-peer reviewed papers on performance

  • Large-scale evaluation of an AI system as an independent reader for double reading in breast cancer screening (read)

Other relevant papers

  • Comparison of Mammography AI Algorithms with a Clinical Risk Model for 5-year Breast Cancer Risk Prediction: An Observational Study (read)