CardioTrackNet: A Hybrid Active Mesh and PWC Model for Enhanced Cardiac MRI Motion Analysis and Visualization

Abstract

Accurate motion tracking and visualization of cardiac structures in MRI images are crucial for diagnosing and treating heart diseases. This paper introduces CardioTrackNet, a novel hybrid model that integrates an Active Mesh Model with a Pyramidal Warping and Cost Volume (PWC) Model for advanced cardiac MRI motion analysis and visualization. CardSegNet is first utilized for precise heart region segmentation. Subsequently, the Active Mesh and PWC models track the motion of each volume across frames. The Active Mesh Model provides a detailed, flexible representation of cardiac structures, while the PWC Model excels in optical flow estimation. These motion estimates are synthesized within CardioTrackNet, combining segmented and tracked data. The final output is refined using six bull's-eye data from CVI42 software, ensuring clinically relevant motion visualization. Experimental results demonstrate that CardioTrackNet significantly improves the accuracy of cardiac motion tracking, achieving a Dice Similarity Coefficient (DSC) of 93 ± 1%. Additionally, the system offers clear and informative visualizations, potentially enhancing clinical workflows and supporting better diagnostic and therapeutic decisions. © 2024 IEEE.