Automatic multisegmentation of abdominal organs by level set with weighted global and local forces

Malinda Vania, Sunhee Kim, Deukhee Lee
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引用次数: 3

Abstract

The automatic multisegmentation of computed tomography (CT) data of the upper abdomen poses a challenge with regard to accuracy, automation, and strength. In this paper, we propose automatic organ segmentation to segment the kidney, vena, and liver on the basis of a gray-level analysis. Furthermore, the method has been developed by utilizing the level set with weighted global and local forces to handle the topological data of organs and tissues to improve the accuracy of multi organ segmentation. The proposed methods were tested by performing segmentation of three abdominal organs (liver, kidneys, and inferior vena cava) from several CT datasets, and good segmentation results and visualization of 3D models were obtained.
基于加权全局力和局部力的水平集腹部器官自动多分割
上腹部计算机断层扫描(CT)数据的自动多重分割在准确性、自动化和强度方面提出了挑战。在本文中,我们提出了一种基于灰度分析的自动器官分割方法来分割肾脏、静脉和肝脏。在此基础上,利用全局力和局部力加权的水平集对器官和组织的拓扑数据进行处理,提高了多器官分割的精度。通过对多个CT数据集的三个腹部器官(肝脏、肾脏和下腔静脉)进行分割,验证了所提方法的有效性,获得了良好的分割效果和三维模型的可视化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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