Exploiting typical clinical imaging constraints for 3D outer bone surface segmentation

Chris Mack, Vishali Mogallapu, Andrew Willis, T. Weldon
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引用次数: 1

Abstract

We present a method for extracting outer bone surfaces from a 3D CT (computer tomography) image sequence using a novel segmentation scheme on each image. A 3D mesh of the bone surface is then generated using the marching cubes algorithm. The new segmentation algorithm makes use of several imaging constraints which greatly simplify the problem including : (i) the cross-sectional size of a bone is approximately known and (ii) the geometric shape of a cross-section is approximately known. In clinical practice using commercial CT scanners, these quantities are typically known and serve to greatly simplify the segmentation problem. By segmenting the image data, the algorithm is capable of uniquely extracting the bone outer surface in contrast to other methods which often include extra surfaces or surfaces with holes. This paper presents the segmentation method and shows results for extracting tibia bone outer surfaces.
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利用典型临床影像约束进行三维骨外表面分割
我们提出了一种从3D CT(计算机断层扫描)图像序列中提取外骨表面的方法,使用一种新的分割方案对每个图像进行分割。然后使用行进立方体算法生成骨表面的3D网格。新的分割算法利用了几个成像约束,极大地简化了问题,包括:(i)骨头的横截面尺寸是近似已知的;(ii)横截面的几何形状是近似已知的。在使用商用CT扫描仪的临床实践中,这些量通常是已知的,可以极大地简化分割问题。通过分割图像数据,该算法能够独特地提取骨骼外表面,而其他方法通常包括额外的表面或有孔的表面。本文介绍了胫骨外表面的分割方法,并给出了分割结果。
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