Sun Hui, Frangi Alejandro F, Wang Hongzhi, Sukno Federico M, Tobon-Gomez Catalina, Yushkevich Paul A
Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, Philadelphia, USA.
Med Image Comput Comput Assist Interv. 2010;13(Pt 1):468-75. doi: 10.1007/978-3-642-15705-9_57.
We present a novel approach for automatic segmentation of the myocardium in short-axis MRI using deformable medial models with an explicit representation of thickness. Segmentation is constrained by a Markov prior on myocardial thickness. Best practices from Active Shape Modeling (global PCA shape prior, statistical appearance model, local search) are adapted to the medial model. Segmentation performance is evaluated by comparing to manual segmentation in a heterogeneous adult MRI dataset. Average boundary displacement error is under 1.4 mm for left and right ventricles, comparing favorably with published work.
我们提出了一种新颖的方法，用于在短轴磁共振成像（MRI）中使用具有厚度显式表示的可变形中轴模型自动分割心肌。分割受心肌厚度的马尔可夫先验约束。主动形状模型的最佳实践（全局主成分分析形状先验、统计外观模型、局部搜索）被应用于中轴模型。通过与异质成人MRI数据集中的手动分割进行比较来评估分割性能。左心室和右心室的平均边界位移误差均在1.4毫米以下，与已发表的工作相比具有优势。
