An integrated workflow to seamlessly review calcium scoring and CCTA data

• Deep Learning based automated Calcium Score

  • Deep Learning model automatically labels coronary artery territories.
  • Deep learning model automatically segments calcifications within the coronary artery territories and provides total and per territory scores.
  • Deep learning models were developed and trained based on a variety of clinical datasets from a global population, spanning multiple scanners types and vendors.
  • Ability to assign calcifications to individual coronary artery branches.
  • Ability to score and label calcifications found in the aorta and cardiac valves.
• CCTA 2D Review

  • Easily transition from Calcium Scoring to CCTA review through the integrated workflow.
  • Load multi-phase data for motion analysis of chamber mobility or identification of target phase for coronary review.
  • Help evaluate coronary artery disease using oblique reference lines to generate views through the arteries.
  • Easy access to additional rendering modes (MIP, MinIP and Average) for enhanced visualization.
  • Measurement tools for distance and ROI generation.