AIMEDIC 논문

A Comparative Analysis of Deep Learning-Based Location-Adaptive Threshold Method Software Against Other Commercially Available Software

분류

Pub

일자

2024-04-18

출처

The International Journal of Cardiovascular Imaging

This study compares the performance of a deep learning-based location-adaptive threshold method (DL-LATM) software for coronary artery segmentation using coronary computed tomography angiography (CCTA) against other commercially available software. The study utilizes intravascular ultrasound (IVUS) data as the gold standard. The DL-LATM software demonstrated the highest accuracy in detecting lumen or plaque volume in stenotic regions, suggesting its potential as a supportive tool in diagnosing coronary artery disease (CAD).

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