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Volumetric Topological Analysis: A Novel Method for Trabecular Bone Characterization on the Continuum between Plate and Rods

机译:体积拓扑分析:板材与杆间连续骨骨骼表征的一种新方法

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Trabecular bone (TB) is a complex quasi-random network of interconnected struts and plates. TB constantly remodels to adapt dynamically to the stresses to which it is subjected (Wolff s Law). In osteoporosis, this dynamic equilibrium between bone formation and resorption is perturbed, leading to bone loss and structural deterioration, both increasing fracture risk. Bone's mechanical competence can only be partly explained by variations in bone mineral density, which led to the notion of bone structural quality. Previously, we developed digital topological analysis or DTA which classifies plates, rods, profiles, edges and junctions in a TB skeletal representation. Although the method has become quite popular, a major limitation is that DTA produces hard classifications only, failing to distinguish between narrow and wide plates. Here, we present a new method called volumetric topological analysis or VTA for quantification of regional topology in complex quasi-random TB networks. At each TB voxel, the method uniquely classifies the topology on the continuum between perfect plates and rods. Therefore, the method is capable of detecting early alterations of trabeculae from plates to rods according to the known etiology of osteoporotic bone loss. Here, novel ideas of geodesic distance transform, geodesic scale and feature propagation have been introduced and combined with DTA and fuzzy distance transform methods conceiving the new VTA technology. The method has been applied to MDCT and μCT images of a cadaveric distal tibia specimen and the results have been quantitatively evaluated. Specifically, intra- and inter-modality reproducibility of the method has been examined and the results are found very promising.
机译:骨小梁(TB)是相互连接的支柱和板的复杂的准随机网络。 TB不断重塑动态地适应于其所经受的应力(沃尔夫定律)。在骨质疏松症,骨形成和骨吸收之间的动态平衡被扰动,导致骨损失和结构劣化,既增加骨折的风险。骨的机械能力只能通过骨矿物质密度的变化,而导致骨的结构质量的概念被部分地说明。以前,我们开发了在一个TB骨架表示分类板,棒,型材,边缘和结数字拓扑分析或DTA。尽管该方法已经变得相当流行,一个主要限制是DTA只生产硬分类,未能窄的和宽的板之间进行区分。在这里,我们提出了一个所谓的体积拓扑分析或VTA在复杂的准随机TB网络拓扑区域的量化新方法。在每个体素TB,该方法唯一地分类上完美板和杆之间的连续体的拓扑。因此,该方法能够根据骨质疏松的骨损失的已知病因学检测小梁的早期改变从板到棒。这里,测地距离的新奇的想法变换,测地规模和特征传播已被引入,并用DTA组合和模糊距离变换构思新VTA技术方法。该方法已被应用到尸体远端胫骨样本的MDCT和μCT图像和结果已被定量评价。具体而言,帧内和帧间模式的方法的再现性已经检查,结果发现很有希望的。

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