b-box plus

Breast imaging solutions, including breast density classification (ACR BI-RADS), image quality assessment and reporting, and lesion and microcalcification detection, enhanced with DANAI self-calibrating technology.

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b-rayz dashboard

Overview

Recognizing that point solutions for tumor detection may not be meeting the variety of needs of breast imaging professionals, b-box plus addresses a range of workflow requirements in mammography, encompassing both 2D and 3D applications. b-box plus delivers results in real-time, presenting them through an intuitive dashboard. b-box plus includes DANAI™-Technology, leveraging the ability to customize AI models on-site through a patented process.

b-box plus - b-rayz logo

Features

B-box Plus consists of 4 modules:
  • the b-smart dashboard provides a comprehensive view on breast unit(s) and monitors the team’s performance with automated image quality metrics. (FDA and CE cleared)
  • b-density provides an evaluation of breast density according to BI-RADS 5th edition. (CE only)
  • b-quality provides an evaluation of the quality of the images according to the PGMI-criteria. (FDA and CE cleared)
  • b-diagnostics evaluates lesions and calcifications and rates them according to the BI-RADS standard as suspicious or non-suspicious. (CE only)

Benefits

  • Provides standardized and observer-independent classification of breast density based on the ACR BI-RADS system with 90% accuracy in the differentiation between ACR A/B and ACR C/D.¹
  • Automates quality assessment with real-time feedback to radiographers, helping them reduce positioning errors² and aim to reduce the number of recalls needed.
  • Aims to help breast units optimize procedures and identify areas for improvement and training by monitoring their performance.
  • Can generate automatic quality reporting for authorities and reduce repetitive tasks. 
  • Aims to reduce radiologist reading time by automatic detection and classification of breast lesions.

Image examples

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dashboard (1)

To find out more about this solution or any of the other 140+ applications on the Blackford Platform, please book a discovery call with our team.

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¹Sexauer R, Hejduk P, Borkowski K, Ruppert C, Weikert T, Dellas S, et al. Diagnostic accuracy of automated ACR BI-RADS breast density classification using deep convolutional neural networks. European Radiology [Internet]. 2023 Mar 1 [cited 2024 Mar 22];33(7):4589–96. ‌

²Hejduk P, Sexauer R, Ruppert C, Borkowski K, Unkelbach J, Schmidt N. Automatic and standardized quality assurance of digital mammography and tomosynthesis with deep convolutional neural networks. 2023 May 18;14(1).‌