• Ashika H
• Mrs. Meenakumari K S

Medical image analysis has become a cornerstone in the advancement of cardiovascular analysis, offering unprecedented insights and precision in diagnosis and treatment. This review paper synthesizes findings from recent research articles and conference papers, highlighting the latest developments in medical image analysis techniques and their applications in cardiovascular interventions. The review covers a range of methodologies including machine learning, deep learning, and traditional image processing techniques, and evaluates their effectiveness in various clinical scenarios such as coronary artery disease, structural heart disease, and electrophysiological disorders. Key advancements in imaging modalities like MRI, CT, and ultrasound are discussed, along with their integration into clinical practices. In addition, this paper addresses the limitations, and the challenges faced in the field, like data heterogeneity, computational demands, and the need for standardized valuation metrics. By providing a thorough overview of current research, this review intends to provide information for future studies and support the continued evolution of medical image analysis in cardiovascular care.

Deep Learning, Cardiovascular, MRI

"Leveraging Deep Learning Methodology for Medical Image Analysis of Cardiovascular Anatomy", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.12, Issue 5, page no.c604-c610, May-2025, Available :http://www.jetir.org/papers/JETIR2505280.pdf

"Leveraging Deep Learning Methodology for Medical Image Analysis of Cardiovascular Anatomy", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.12, Issue 5, page no. ppc604-c610, May-2025, Available at : http://www.jetir.org/papers/JETIR2505280.pdf