Novel deep learning method for coronary artery tortuosity detection through coronary angiography.

ABSTRACT: Coronary artery tortuosity is usually an undetected condition in patients undergoing coronary angiography. This condition requires a longer examination by the specialist to be detected. Yet, detailed knowledge of the morphology of coronary arteries is essential for planning any interventional treatment, such as stenting. We aimed to analyze coronary artery tortuosity in coronary angiography with artificial intelligence techniques to develop an algorithm capable of automatically detecting this condition in patients. This work uses deep learning techniques, in particular, convolutional neural networks, to classify patients into tortuous or non-tortuous based on their coronary angiography. The developed model was trained both on left (Spider) and right (45°/0°) coronary angiographies followin

SUBMITTER: Cobo M 

PROVIDER: S-EPMC10333289 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature