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Exploiting Typical Clinical Imaging Constraints for 3D Outer Bone Surface Segmentation

机译:利用3D外骨表面分割的典型临床成像约束

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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.
机译:我们在每个图像上使用新颖的分段方案提出一种从3D CT(计算机断层扫描)图像序列中提取外骨表面的方法。然后使用行进的立方体算法生成骨表面的3D网格。新的分割算法利用多种成像约束,这大大简化了存在的问题:(i)骨的横截面尺寸约为已知,并且(ii)横截面的几何形状约为已知。在使用商业CT扫描仪的临床实践中,这些数量通常是已知的并且用于大大简化分割问题。通过分割图像数据,该算法能够与通常包括具有孔的额外表面或表面的其他方法唯一地提取骨外表面。本文介绍了分段方法,并显示提取胫骨外表面的结果。

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