论文标题
脊柱X射线图像中的两分距离用于形状感知的具有里程碑意义的检测
Bipartite Distance for Shape-Aware Landmark Detection in Spinal X-Ray Images
论文作者
论文摘要
脊柱侧弯是一种先天性疾病，会导致脊柱横向曲率。它的评估依赖于脊柱X射线图像中椎骨的识别和定位，这是通过繁琐且耗时的手动射线照相手术，这些手术易于主观性和观察性变异性。可以通过自动检测和脊柱地标定位来提高可靠性。为了指导CNN学习脊柱形状的同时检测X射线图像中的地标，我们提出了基于两部分距离（BPD）度量的新型损失，并表明它始终如一地改善了地标检测性能。
Scoliosis is a congenital disease that causes lateral curvature in the spine. Its assessment relies on the identification and localization of vertebrae in spinal X-ray images, conventionally via tedious and time-consuming manual radiographic procedures that are prone to subjectivity and observational variability. Reliability can be improved through the automatic detection and localization of spinal landmarks. To guide a CNN in the learning of spinal shape while detecting landmarks in X-ray images, we propose a novel loss based on a bipartite distance (BPD) measure, and show that it consistently improves landmark detection performance.
