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一种基于 pQCT 采集的股骨颈图像区域分析的自动分割方法。

An automatic segmentation method for regional analysis of femoral neck images acquired by pQCT.

机构信息

Institute of Molecular Bioimaging and Physiology (IBFM)-CNR, Palazzo LITA, via Fratelli Cervi 93, 20090, Segrate, Milan, Italy.

出版信息

Ann Biomed Eng. 2011 Jan;39(1):172-84. doi: 10.1007/s10439-010-0154-8. Epub 2010 Sep 8.

Abstract

We developed an automatic method for regional analysis of femoral neck images acquired by peripheral quantitative computed tomography (pQCT), based on automatic spatial re-alignment and segmentation; the segmentation method, based on a morphological approach, explicitly accounts for the presence of three different bone compartments: cortical region, trabecular region, and transition zone between cortical and trabecular compartments. The proposed method was applied on 13 femoral neck sections derived from female donors who were undergoing hip replacement surgery for primary degenerative arthritis or fracture, and a typical densitometric and structural analysis was performed both globally and regionally. The proposed segmentation method was quantitatively evaluated by comparing automatic contour and the corresponding manual contours delineated by three operators using metrics based on surface distance (average symmetric distance, ASD) and volumetric overlapping (dice similarity coefficient, DSC). The same approach was used to validate the automatic spatial orientation, considering as metric the difference between manual and automatic angle orientation. Results confirm a satisfactory agreement between automatic and manual performances (ASD < 0.41 mm, DSC > 0.91, orientation difference = 3.61°) and show that globally our algorithm performs very well. Concerning regional analysis application, from our results we can observe that significant differences are present among the four bone quadrants.

摘要

我们开发了一种基于自动空间重配准和分割的外周定量 CT(pQCT)股骨颈图像区域分析的自动方法;该分割方法基于形态学方法,明确考虑了三种不同的骨区:皮质区、松质骨区和皮质区与松质骨区之间的过渡区。该方法应用于 13 个来自因原发性退行性关节炎或骨折而行髋关节置换术的女性供体的股骨颈节段,进行了全局和区域的典型密度和结构分析。通过使用基于表面距离(平均对称距离,ASD)和体积重叠(骰子相似系数,DSC)的度量标准,比较自动轮廓和三位操作员手动勾勒的相应轮廓,对提出的分割方法进行了定量评估。使用相同的方法验证自动空间定向,将手动和自动角度定向之间的差异作为度量标准。结果证实了自动和手动性能之间具有令人满意的一致性(ASD<0.41mm,DSC>0.91,定向差异=3.61°),并且表明全局上我们的算法性能非常好。关于区域分析应用,从我们的结果可以观察到四个骨象限之间存在显著差异。

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