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Multi-constraint point set registration with redundant point removal for the registration of coronary arteries
Bu Xu1, Lu Wang2, Jinzhong Yang1
1College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.
Insights
A new algorithm, MPSR-RPR, effectively registers coronary artery data, addressing missing endpoint information crucial for diagnosing coronary artery disease (CAD) and improving patient outcomes.
Area of Science:
- Medical Imaging
- Cardiovascular Research
- Computational Anatomy
Background:
- Coronary artery disease (CAD) is a major global health concern.
- Accurate registration of coronary arteries aids in diagnosing CAD by analyzing motion patterns.
- Current methods lack automatic solutions for missing data at coronary artery tree endpoints.
Purpose of the Study:
- To introduce a novel non-rigid multi-constraint point set registration with redundant point removal (MPSR-RPR) algorithm.
- To address the challenge of missing data at coronary artery endpoints.
- To improve the accuracy of coronary artery registration for diagnostic purposes.
Main Methods:
- The MPSR-RPR algorithm performs initial registration using smoothness regularization and Gaussian filtering.
- It utilizes constraints including moving coherence, local features, and bifurcation point correspondences.
- Spatial geometry analysis identifies vessel endpoints and removes redundant points for refined registration.
Main Results:
- The MPSR-RPR algorithm significantly reduced the mean modified Hausdorff distance (MHD) compared to existing methods.
- It effectively handled substantial missing data in both left and right coronary arteries.
- Demonstrated superior performance in aligning coronary artery point sets.
Conclusions:
- The MPSR-RPR algorithm is effective for coronary artery alignment.
- It offers significant value in assisting the diagnosis of coronary artery disease and myocardial lesions.
- The method provides a robust solution for handling missing data in coronary artery imaging.
Background:
Coronary artery disease (CAD) is the leading cause of death worldwide. The registration of the coronary artery at different phases can help radiologists explore the motion patterns of the coronary artery and assist in the diagnosis of CAD. However, there is no automatic and easy-to-execute method to solve the missing data problem that occurs at the endpoints of the coronary artery tree. This paper proposed a non-rigid multi-constraint point set registration with redundant point removal (MPSR-RPR) algorithm to tackle this challenge.
Methods:
Firstly, the MPSR-RPR algorithm roughly registered two coronary artery point sets with the pre-set smoothness regularization parameter and Gaussian filter width value. The moving coherent, local feature, and the corresponding relationship between bifurcation point pairs were exploited as the constraints. Next, the spatial geometry information of the coronary artery was utilized to automatically recognize the vessel endpoints and to delete the redundant points of the coronary artery. Finally, the algorithm continued carrying out the multi-constraint registration with another group of the pre-set parameters to improve the alignment performance.
Results:
The experimental results demonstrated that the MPSR-RPR algorithm achieved a significantly lower mean value of the modified Hausdorff distance (MHD) compared to the other state-of-the-art methods for addressing the serious missing data in the left and right coronary arteries.
Conclusion:
This study demonstrated the effectiveness of the proposed algorithm in aligning coronary arteries, providing significant value in assisting in the diagnosis of coronary artery and myocardial lesions.
