Lekadir Karim, Yang Guang-Zhong
Visual Information Processing, Department of Computing Imperial College London, United Kingdom.
Med Image Comput Comput Assist Interv. 2008;11(Pt 1):434-41. doi: 10.1007/978-3-540-85988-8_52.
This paper presents a novel approach for robust and fully automatic segmentation with active shape model search. The proposed method incorporates global geometric constraints during feature point search by using interlandmark conditional probabilities. The A* graph search algorithm is adapted to identify in the image the optimal set of valid feature points. The technique is extended to enable reliable and fast automatic initialization of the ASM search. Validation with 2-D and 3-D MR segmentation of the left ventricular epicardial border demonstrates significant improvement in robustness and overall accuracy, while eliminating the need for manual initialization.
本文提出了一种通过主动形状模型搜索进行鲁棒且全自动分割的新方法。所提出的方法在特征点搜索过程中通过使用地标间条件概率纳入全局几何约束。采用A*图搜索算法在图像中识别有效特征点的最优集。该技术得到扩展，以实现主动形状模型搜索的可靠且快速自动初始化。对左心室心外膜边界的二维和三维磁共振分割进行验证表明，在鲁棒性和整体准确性方面有显著提高，同时无需手动初始化。
