Pre-process Methods for Cardio Vascular Diseases Diagnosis Using CT (Computed Tomography) Angiography Images
- Authors: T. Santhi Punitha1, S.K. Piramu Preethika2
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View Affiliations Hide Affiliations1 School of Computing Sciences, VISTAS, Pallavaram, Chennai, Tamil Nadu, India 2 School of Computing Sciences, VISTAS, Pallavaram, Chennai, Tamil Nadu, India
- Source: Intelligent Technologies for Automated Electronic Systems , pp 148-157
- Publication Date: March 2024
- Language: English
Pre-process Methods for Cardio Vascular Diseases Diagnosis Using CT (Computed Tomography) Angiography Images, Page 1 of 1
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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. <br>
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