CardIQ Suite

An integrated suite of CT Cardiac post-processing tools, built for automation and workflow efficiency.
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At a glance

Consistency

>90% concordance with CACS‑DRS classification grouping1

Identification

>95% correct identification of the presence of coronary artery calcifications1

Labeling

>90% accurately labeled coronary artery territories1

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 scanner 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.
  • 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.
 
References
  1. Data on file.

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