الملخص
Sparse-view 3D coronary reconstruction commonly relies on cross-view correspondence and triangulation, which are vulnerable to vessel overlap and foreshortening, or on volumetric prediction followed by vascular-graph extraction, which does not directly provide centrelines and radii. We introduce PPCAR-Net, a projection-refined parametric coronary artery reconstruction network that directly predicts a branch-structured centreline-and-radius representation without explicit point matching, triangulation, or an intermediate volume. Given a variable number of segmented views, a coarse predictor combines frozen VGGT features with learned branch queries to estimate branch presence, B-spline centreline trajectories, and dense radius profiles. Projection-guided geometry and radius refiners then sample local evidence from the input views and apply residual corrections learned with 3D supervision. We evaluate representation fidelity and sparse-view reconstruction quantitatively and qualitatively. On simulated angiographic masks generated from CT-derived coronary anatomy, PPCAR-Net produces better connected artery reconstructions and achieves strong centreline accuracy, particularly for RCA, while maintaining competitive volumetric overlap. Coarse-to-fine inference takes 121 ms, enabling real-time reconstruction.
الكلمات المفتاحية
الموضوع
بيانات النشر
- المجلة
- غير متاح
- وصول مفتوح
- وصول مفتوح أخضر
اقتبس هذه المقالة
APA 7
Ren, Y., Lee, H. K., Cham, T. J., Yap, J., & Yeo, K. K. (2026). PPCAR-Net: Projection-Refined Parametric 3D Coronary Artery Reconstruction from Sparse X-ray Angiographic Views. https://omanscience.com/ar/articles/ppcar-net-projection-refined-parametric-3d-coronary-artery-reconstruction-from-sparse-x-ray-angiographic-views
MLA 9
Ren, Yu, et al. "PPCAR-Net: Projection-Refined Parametric 3D Coronary Artery Reconstruction from Sparse X-ray Angiographic Views." https://omanscience.com/ar/articles/ppcar-net-projection-refined-parametric-3d-coronary-artery-reconstruction-from-sparse-x-ray-angiographic-views.
شيكاغو (المؤلف–التاريخ)
Ren, Yu, Hwee Kuan Lee, Tat-Jen Cham, Jonathan Yap, and Khung Keong Yeo. 2026. "PPCAR-Net: Projection-Refined Parametric 3D Coronary Artery Reconstruction from Sparse X-ray Angiographic Views." https://omanscience.com/ar/articles/ppcar-net-projection-refined-parametric-3d-coronary-artery-reconstruction-from-sparse-x-ray-angiographic-views.
هارفارد
Ren, Y., Lee, H. K., Cham, T. J., Yap, J. and Yeo, K. K. (2026) 'PPCAR-Net: Projection-Refined Parametric 3D Coronary Artery Reconstruction from Sparse X-ray Angiographic Views', Available at: https://omanscience.com/ar/articles/ppcar-net-projection-refined-parametric-3d-coronary-artery-reconstruction-from-sparse-x-ray-angiographic-views.
فانكوفر
Ren Y, Lee HK, Cham TJ, Yap J, Yeo KK. PPCAR-Net: Projection-Refined Parametric 3D Coronary Artery Reconstruction from Sparse X-ray Angiographic Views. https://omanscience.com/ar/articles/ppcar-net-projection-refined-parametric-3d-coronary-artery-reconstruction-from-sparse-x-ray-angiographic-views
IEEE
Y. Ren, H. K. Lee, T. J. Cham, J. Yap, and K. K. Yeo, "PPCAR-Net: Projection-Refined Parametric 3D Coronary Artery Reconstruction from Sparse X-ray Angiographic Views," https://omanscience.com/ar/articles/ppcar-net-projection-refined-parametric-3d-coronary-artery-reconstruction-from-sparse-x-ray-angiographic-views.