Suppr超能文献

通过耦合可变形曲面实现三维超声心动图半自动双心室分割

Semiautomated biventricular segmentation in three-dimensional echocardiography by coupled deformable surfaces.

作者信息

Bersvendsen Jørn, Orderud Fredrik, Lie Øyvind, Massey Richard John, Fosså Kristian, Estépar Raúl San José, Urheim Stig, Samset Eigil

机构信息

GE Vingmed Ultrasound AS, Horten, Norway.

University of Oslo, Department of Informatics, Oslo, Norway.

出版信息

J Med Imaging (Bellingham). 2017 Apr;4(2):024005. doi: 10.1117/1.JMI.4.2.024005. Epub 2017 May 24.

Abstract

With the advancement of three-dimensional (3-D) real-time echocardiography in recent years, automatic creation of patient specific geometric models is becoming feasible and important in clinical decision making. However, the vast majority of echocardiographic segmentation methods presented in the literature focus on the left ventricle (LV) endocardial border, leaving segmentation of the right ventricle (RV) a largely unexplored problem, despite the increasing recognition of the RV's role in cardiovascular disease. We present a method for coupled segmentation of the endo- and epicardial borders of both the LV and RV in 3-D ultrasound images. To solve the segmentation problem, we propose an extension of a successful state-estimation segmentation framework with a geometrical representation of coupled surfaces, as well as the introduction of myocardial incompressibility to regularize the segmentation. The method was validated against manual measurements and segmentations in images of 16 patients. Mean absolute distances of [Formula: see text], [Formula: see text], and [Formula: see text] between the proposed and reference segmentations were observed for the LV endocardium, RV endocardium, and LV epicardium surfaces, respectively. The method was computationally efficient, with a computation time of [Formula: see text].

摘要

近年来,随着三维(3-D)实时超声心动图技术的进步,自动创建患者特异性几何模型在临床决策中变得可行且重要。然而,文献中提出的绝大多数超声心动图分割方法都集中在左心室(LV)的心内膜边界,尽管右心室(RV)在心血管疾病中的作用日益受到认可,但右心室的分割在很大程度上仍是一个未被充分探索的问题。我们提出了一种在三维超声图像中对左心室和右心室的心内膜和心外膜边界进行联合分割的方法。为了解决分割问题,我们提出了一种成功的状态估计分割框架的扩展,该框架具有耦合表面的几何表示,并引入心肌不可压缩性来规范分割。该方法在16例患者的图像中与手动测量和分割进行了验证。对于左心室心内膜、右心室心内膜和左心室心外膜表面,分别观察到所提出的分割与参考分割之间的平均绝对距离为[公式:见原文]、[公式:见原文]和[公式:见原文]。该方法计算效率高,计算时间为[公式:见原文]。

相似文献

本文引用的文献

1
Robust Spatio-Temporal Registration of 4D Cardiac Ultrasound Sequences.4D心脏超声序列的稳健时空配准
Proc SPIE Int Soc Opt Eng. 2016 Feb 27;9790. doi: 10.1117/12.2217005. Epub 2016 Apr 1.

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验