iCAD PowerLook® Density Assessment

Multi-vendor deep learning algorithm for standardizing breast density assessments.



Dense breasts can make it challenging to detect breast cancer during annual screenings as overlapping tissue can hide or mimic breast cancer. Breast density assessment has traditionally been determined by the radiologist’s visual assessment, but studies show that these can vary and clinicians may even disagree with their own assessment year to year.(1, 2) 

PowerLook Density Assessment software removes the challenges of subjectivity in breast density reporting. Using full field digital mammography (FFDM) or synthetic 2D images, it analyses the dispersion and texture of breast tissue, delivering clinicians a consistent, accurate, and reliable patient-specific breast density assessment. 



PowerLook Density Assessment reports on: 

• Overall BI-RADS 5th Edition breast density category 
• Value of the BI-RADS 5th Edition breast density score and where it falls on the BI-RADS breast density scale 

The solution places a ‘+’ or ‘-’ next to the overall BI-RADS 5th Edition breast density category to designate whether the BI-RADS breast density score is within the upper 75% or the lower 25% of the BIRADS breast density category. 


• Provides objective and consistent breast density assessments. 
• Ability to integrate and automate breast density reporting within the facility’s RIS/MIS.
• High matching accuracy for dense and non-dense assessment.

Image examples

Example of ProFound AI Reporting including the Case Score, Density Evaluation and Risk Score 
Density Scorecard

If you’re interested in learning more about this solution, or the 100+ other applications we have available on Blackford platform book a call with our friendly team now!

review image 1

Book a meeting

We’d welcome the opportunity to learn more about your AI needs and to explain how partnering with Blackford can drive efficiency and provide ongoing value.

Book a Meeting

(1) Berg WA, Campassi C, Langenberg P, Sexton MJ. Breast Imaging Reporting and Data System. American Journal of Roentgenology. 2000 Jun;174(6):1769–77.

(2) Kerlikowske K, Grady D, Barclay J, Ernster V, Frankel SD, Ominsky SH, et al. Variability and Accuracy in Mammographic Interpretation Using the American College of Radiology Breast Imaging Reporting and Data System. JNCI Journal of the National Cancer Institute. 1998 Dec 2;90(23):1801–9.