基于统计形状模型量化肝硬化分期进展

Yenwei Chen, Chunhua Dong, X. Han, T. Tateyama, S. Kanasaki, A. Furukawa
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引用次数: 0

摘要

众所周知,在慢性肝病的临床过程中,肝脏和脾脏会发生形态学改变。在本文中,我们展示了一项基于统计形状模型(SSMs)量化肝硬化阶段进展的初步研究。我们不仅构建了肝脏SSM,还构建了脾脏SSM和肝脏与脾脏的联合SSM,用于肝硬化CT图像的形态学分析。根据其累积贡献率和与医生意见(阶段标签)的相关性来选择有效模式。包括时间序列数据在内的正常和异常肝脏用所选择的模式投影到子空间。大部分正常数据位于中心,而异常数据则分散在正常数据周围。如果病情恶化,数据就会转移到外部。到中心的距离可以用来量化肝硬化的阶段进展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantifying stage progress of cirrhotic livers based on statistic shape models
It is widely known that morphological changes of the liver and the spleen occur during the clinical course of chronic liver diseases. In this paper, we show a preliminary study on quantifying stage progress of cirrhotic liver based on statistical shape models (SSMs). We constructed not only the liver SSM, but also the spleen SSM and a joint SSM of the liver and the spleen for a morphologic analysis of the cirrhotic liver in CT images. The effective modes are selected based on both its accumulation contribution rate and its correlation with doctor's opinions (stage labels). Both normal and abnormal livers including temporal sequence data are projected to the subspace with the selected modes. Most of the normal data are located in the center, while abnormal data are scattered around the normal data. If the disease progresses, data will move outside. The distance to the center can be used to quantify the stage progress of the cirrhotic liver.
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