The pelvis, the lower part of the trunk, supports and balances the trunk.
Landmark detection from a pelvic X-ray (PXR) facilitates downstream analysis
and computer-assisted diagnosis and treatment of pelvic diseases. Although PXRs
have the advantages of low radiation and reduced cost compared to computed
tomography (CT) images, their 2D pelvis-tissue superposition of 3D structures
confuses clinical decision-making. In this paper, we propose a PELvis
Extraction (PELE) module that utilizes 3D prior anatomical knowledge in CT to
guide and well isolate the pelvis from PXRs, thereby eliminating the influence
of soft tissue. We conduct an extensive evaluation based on two public datasets
and one private dataset, totaling 850 PXRs. The experimental results show that
the proposed PELE module significantly improves the accuracy of PXRs landmark
detection and achieves state-of-the-art performances in several benchmark
metrics, thus better serving downstream tasks.

该研究提出 PELvis Extraction（PELE）模块，利用 CT 中的 3D 解剖知识引导和很好地分离 PXRs 中的盆骨，从而消除软组织的影响，从而显著提高 PXRs 的地标检测准确性，并在几个基准度量上实现了最先进的性能。