Are Pixel-Wise Metrics Reliable for Sparse-View Computed Tomography Reconstruction?
Journal:
arXiv
Published Date:
Jun 2, 2025
Abstract
Widely adopted evaluation metrics for sparse-view CT reconstruction--such as
Structural Similarity Index Measure and Peak Signal-to-Noise Ratio--prioritize
pixel-wise fidelity but often fail to capture the completeness of critical
anatomical structures, particularly small or thin regions that are easily
missed. To address this limitation, we propose a suite of novel anatomy-aware
evaluation metrics designed to assess structural completeness across anatomical
structures, including large organs, small organs, intestines, and vessels.
Building on these metrics, we introduce CARE, a Completeness-Aware
Reconstruction Enhancement framework that incorporates structural penalties
during training to encourage anatomical preservation of significant structures.
CARE is model-agnostic and can be seamlessly integrated into analytical,
implicit, and generative methods. When applied to these methods, CARE
substantially improves structural completeness in CT reconstructions, achieving
up to +32% improvement for large organs, +22% for small organs, +40% for
intestines, and +36% for vessels.
