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使用体模对心脏超声分割算法进行评估。

Evaluation of a cardiac ultrasound segmentation algorithm using a phantom.

作者信息

Yue Yong, Tagare Hemant D, Madsen Ernest L, Frank Gary R, Hobson Maritza A

机构信息

Department of Diagnostic Radiology, School of Medicine, Yale University, New Haven, CT 06511, USA.

出版信息

Med Image Comput Comput Assist Interv. 2008;11(Pt 1):101-9. doi: 10.1007/978-3-540-85988-8_13.

DOI:10.1007/978-3-540-85988-8_13
PMID:18979737
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2840385/
Abstract

This paper evaluates the performance of a level set algorithm for segmenting the endocardium in short-axis ultrasound images. The evaluation is carried out using an anthropomorphic ultrasound phantom. Details of the phantom design, including comparison of the ultrasound parameters with in-vitro measurements, are included. In addition to measuring segmentation accuracy, the effectiveness of the energy minimization scheme is also determined. It is argued that using the phantom along with global minimization algorithms (simulated annealing and random search) makes is possible to assess the minimization strategy.

摘要

本文评估了一种用于在短轴超声图像中分割心内膜的水平集算法的性能。评估是使用一个拟人化超声体模进行的。文中包含了体模设计的细节，包括将超声参数与体外测量结果进行比较。除了测量分割精度外，还确定了能量最小化方案的有效性。有人认为，将体模与全局最小化算法（模拟退火和随机搜索）一起使用能够评估最小化策略。

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