股骨髋臼撞击
计算机科学
点云
边界(拓扑)
人工智能
表达式(计算机科学)
高斯分布
计算机视觉
模式识别(心理学)
数学
放射科
医学
数学分析
物理
量子力学
程序设计语言
作者
Peng Du,Baijia Ni,Xiaodong Ju,Xingce Wang,Zhongke Wu,Gege Lou,Keying Hua
标识
DOI:10.1109/icassp48485.2024.10446215
摘要
This paper presents a geometric model for achieving automatic 3D quantitative calculation of the femoroacetabular impingement (FAI) index on computed tomography (CT) images. The result is then used in subsequent work to reduce errors due to perspective differences in existing clinical measurements. This is the first automated quantitative method for a comprehensive FAI diagnostic index that does not rely on datasets. First, the geometric description and equation expression of the hip point cloud were obtained from CT images, fitting the key points and outlines required for the diagnostic index according to such geometric properties as Gaussian curvature. Then, an objective quantitative expression of the FAI index was calculated based on the 3D morphological definition. Next, we statistically analyzed 37 clinical data cases to verify our method's effectiveness. Especially for the cases of hip dysplasia and acetabular boundary, there were unclear, strong correlations between manual and automatic measures (r = 0.88, ICC = 0.84).
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