The discipline of artificial intelligence (AI), which trains computers to
comprehend and analyse pictures using computer vision, is flourishing, particularly in
the medical industry. The well-known non-invasive diagnostic procedure known as
CCTA (Coronary Computerized Tomography Angiography) is used to diagnose
cardiovascular disease (CD). Pre-processing CT Angiography pictures is a crucial step
in computer vision-based medical diagnosis. Implementing image enhancement
preprocess to reduce noise or blur pixels and weak edges in a picture marks the
beginning of the research stages. Using Python and PyCharm(IDE) editor, we can build
Edge detection routines, smoothing/filtering functions, and edge sharpening functions
as a first step in the pre-processing of CCTA pictures.
Keywords: Artificial intelligence (AI), Cardiovascular diseases (CVD), Coronary computed tomography angiography (CCTA), Coronary artery diseases (CAD), Stenosis.
