Modeling left ventricle shape from 2D CT images using wavelets and mean regular hexagon

T. Ali, P. Akhtar, M. I. Bhatti
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Abstract

We present modeling of left ventricle (LV) shape from 2D CT images, acquired from a 64-slice CT medical imaging modality, using wavelets, regular hexagonal boundary tracing, and simple statistical moments. Our proposed algorithm uses a regular hexagonal approximation model corresponding to interactive labeling of LV segmented texture using wavelet-based techniques. We generate LV shape model, as the mean regular hexagonal approximation. We demonstrate application and usefulness of our shape model for successful identification of end-diastolic and end-systolic stages of a normal human cardiac cycle.
利用小波和平均正六边形对二维CT图像左心室形状进行建模
我们利用小波、正六边形边界跟踪和简单的统计矩,从64层CT医学成像模式获得的2D CT图像中建立左心室(LV)形状模型。我们提出的算法使用正则六边形近似模型,对应于基于小波技术的LV分割纹理的交互标记。我们生成LV形状模型,作为平均正六边形逼近。我们展示了我们的形状模型在成功识别正常人类心脏周期舒张末期和收缩末期阶段的应用和实用性。
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