Roberts M G, Cootes T F, Adams J E
Department of Imaging Science and Biomedical Engineering, University of Manchester, Manchester M13 9PL, UK.
Med Image Comput Comput Assist Interv. 2005;8(Pt 2):733-40. doi: 10.1007/11566489_90.
The shape and appearance of vertebrae on lateral dual x-ray absorptiometry (DXA) scans were statistically modelled. The spine was modelled by a sequence of overlapping triplets of vertebrae, using Active Appearance Models (AAMs). To automate vertebral morphometry, the sequence of trained models was matched to previously unseen scans. The dataset includes a significant number of pathologies. A new dynamic ordering algorithm was assessed for the model fitting sequence, using the best quality of fit achieved by multiple sub-model candidates. The accuracy of the search was improved by dynamically imposing the best quality candidate first. The results confirm the feasibility of substantially automating vertebral morphometry measurements even with fractures or noisy images.
对双能X线吸收法(DXA)侧位扫描中椎骨的形状和外观进行了统计建模。使用主动外观模型(AAM),通过一系列重叠的三联椎骨对脊柱进行建模。为了实现椎体形态测量的自动化,将训练好的模型序列与之前未见过的扫描图像进行匹配。该数据集包含大量的病变情况。使用多个子模型候选者实现的最佳拟合质量,对一种新的动态排序算法进行了模型拟合序列评估。通过首先动态施加最佳质量候选者,提高了搜索的准确性。结果证实,即使存在骨折或图像噪声,大幅自动化椎体形态测量也是可行的。