Lekadir Karim, Keenan Niall, Pennell Dudley, Yang Guang-Zhong
Visual Information Processing, Department of Computing, Imperial College London, UK.
Med Image Comput Comput Assist Interv. 2007;10(Pt 2):834-41. doi: 10.1007/978-3-540-75759-7_101.
This paper presents a new approach to regional myocardial contractility analysis based on inter-landmark motion (ILM) vectors and multivariate outlier detection. The proposed spatio-temporal representation is used to describe the coupled changes occurring at pairs of regions of the left ventricle, thus enabling the detection of geometrical and dynamic inconsistencies. Multivariate tolerance regions are derived from training samples to describe the variability within the normal population using the ILM vectors. For new left ventricular datasets, outlier detection enables the localization of extreme ILM observations and the corresponding myocardial abnormalities. The framework is validated on a relatively large sample of 50 subjects and the results show promise in localization and visualization of regional left ventricular dysfunctions.
本文提出了一种基于地标间运动（ILM）向量和多变量异常值检测的区域心肌收缩性分析新方法。所提出的时空表示用于描述左心室区域对处发生的耦合变化，从而能够检测几何和动态不一致性。从训练样本中导出多变量容忍区域，以使用ILM向量描述正常人群中的变异性。对于新的左心室数据集，异常值检测能够定位极端的ILM观测值和相应的心肌异常。该框架在50名受试者的相对大样本上得到验证，结果在区域左心室功能障碍的定位和可视化方面显示出前景。
