Citation

Jabbar, Muhammad Kashif and Jianjun, Huang and Jabbar, Ayesha and Ur Rehman, Zaka (2025) Mamba-Based VoxelMorph Framework for Cardiovascular Disease Imaging and Risk Assessment. IEEE Access, 13. pp. 78120-78137. ISSN 2169-3536

Text Mamba-Based VoxelMorph Framework for Cardiovascular Disease Imaging and Risk Assessment.pdf - Published Version Restricted to Repository staff only Download (3MB)

Abstract

Cardiovascular diseases (CVDs), particularly coronary artery disease (CAD), remain the leading cause of global mortality, necessitating advanced diagnostic solutions. Accurate deformable image registration plays a crucial role in enhancing segmentation precision and classification performance in cardiovascular imaging. However, existing registration methods, including VoxelMorph, face limitations in computational efficiency and memory usage, restricting their real-time applicability for high-resolution cardiac imaging. This study proposes the Mamba-Optimized VoxelMorph framework, which leverages GPU-based parallelization and memory optimization to address these challenges. The framework achieves superior registration accuracy, yielding a Dice Similarity Coefficient (DSC) of 0.95 and Normalized CrossCorrelation (NCC) of 0.90, while reducing computational time by 40% and memory usage to 800 MB. These advancements ensure efficient alignment of complex cardiac structures, thereby improving segmentation accuracy and classification reliability. By addressing these critical limitations, the Mamba-Optimized VoxelMorph framework significantly enhances cardiovascular imaging, enabling precise, scalable, and real-time deformable image registration for improved CAD diagnosis and treatment planning.

Item Type:	Article
Uncontrolled Keywords:	Cardiovascular disease (CVD), imaging component analysis
Subjects:	R Medicine > RA Public aspects of medicine > RA421-790.95 Public health. Hygiene. Preventive medicine
Divisions:	Faculty of Engineering (FOE)
Depositing User:	Ms Rosnani Abd Wahab
Date Deposited:	30 May 2025 02:11
Last Modified:	30 May 2025 02:11
URII:	http://shdl.mmu.edu.my/id/eprint/13887

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