Intelligent Technologies for Automated Electronic Systems

Pre-process Methods for Cardio Vascular Diseases Diagnosis Using CT (Computed Tomography) Angiography Images

Author(s): T. Santhi Punitha* and S.K. Piramu Preethika

Pp: 148-157 (10)

DOI: 10.2174/9789815179514124010014

* (Excluding Mailing and Handling)


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.

Related Journals
Related Books
© 2024 Bentham Science Publishers | Privacy Policy