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)

Abstract

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. 

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