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  • AVIEW CAC

Coronary artery disease, the number one cause of death worldwide,
can be diagnosed in advance by calcification score using CT images.

Artificial intelligence accurately detects coronary artery calcification
at an expert level (99.2%).

Artificial intelligence accurately detects coronary artery calcification
at an expert level (99.2%).

MFDS • FDA • CE • PMDA • TFDA Clearance

Accurate and detailed segmentation

With CAC’s automatic segmentation of the heart and surrounding structures, CAC can accurately analyze the calcified plaques in coronary arteries.

Accurate calcification detection in coronary arteries

ROBINSCA* clinical examination of 997 non-contrast ECG CT images Performance evaluation was performed through CAC detection and quantification.

*ROBINSCA : Risk Or Benefit IN Screening for CArdiovascular disease

  • Medical AI diagnostic accuracy: 99.2%
  • Detection and classification concordance: 87%
  • Agatston score concordance: 95%

Diagnoses are also available from chest CTs

Coronary artery calcification can be quantified not only on heart CT images but also on chest CT images, helping early detection, and reducing patient exposure.

  • Kernel conversion AI technology is applied.

Entirely automated process

Pre-analysis is possible with fully automatic work procedures, and reports containing accurate and detailed results can be used in clinical practice.

Evidence

  • Fully automated deep learning powered calcium scoring in patients undergoing myocardial perfusion imaging

    J Nucl Cardiol., 2022

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  • Warranty Period of a Calcium Score of Zero: Comprehensive Analysis from Multi-Ethnic Study of Atherosclerosis

    JACC Cardiovascular Imaging, 2021

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  • Deep learning for automatic calcium scoring in population based cardiovascular screening

    ESC Congress, 2021

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  • Fully Automatic Coronary Calcium Score Software Empowered by Artificial Intelligence Technology: Validation Study Using Three CT Cohorts

    Korean Journal of Radiology, 2021

    view detail

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