分割
计算机科学
人工智能
椎体
坐标系
职位(财务)
骨矿物
体积热力学
骨质疏松症
计算机视觉
数学
解剖
医学
物理
财务
量子力学
经济
内分泌学
作者
André Mastmeyer,Klaus Engelke,Christina Fuchs,Willi A. Kalender
标识
DOI:10.1016/j.media.2006.05.005
摘要
We have developed a new hierarchical 3D technique to segment the vertebral bodies in order to measure bone mineral density (BMD) with high trueness and precision in volumetric CT datasets. The hierarchical approach starts with a coarse separation of the individual vertebrae, applies a variety of techniques to segment the vertebral bodies with increasing detail and ends with the definition of an anatomic coordinate system for each vertebral body, relative to which up to 41 trabecular and cortical volumes of interest are positioned. In a pre-segmentation step constraints consisting of Boolean combinations of simple geometric shapes are determined that enclose each individual vertebral body. Bound by these constraints viscous deformable models are used to segment the main shape of the vertebral bodies. Volume growing and morphological operations then capture the fine details of the bone-soft tissue interface. In the volumes of interest bone mineral density and content are determined. In addition, in the segmented vertebral bodies geometric parameters such as volume or the length of the main axes of inertia can be measured. Intra- and inter-operator precision errors of the segmentation procedure were analyzed using existing clinical patient datasets. Results for segmented volume, BMD, and coordinate system position were below 2.0%, 0.6%, and 0.7%, respectively. Trueness was analyzed using phantom scans. The bias of the segmented volume was below 4%; for BMD it was below 1.5%. The long-term goal of this work is improved fracture prediction and patient monitoring in the field of osteoporosis. A true 3D segmentation also enables an accurate measurement of geometrical parameters that may augment the clinical value of a pure BMD analysis.
科研通智能强力驱动
Strongly Powered by AbleSci AI