Automated Three-Dimensional Reconstruction of the Left Ventricle From Multiple-Axis Echocardiography

Author:

Krishnan Rajan Navaneetha1,Song Zeying1,Hoffmann Kenneth R.2,Belohlavek Marek3,McMahon Eileen M.3,Borazjani Iman4

Affiliation:

1. Department of Mechanical and Aerospace Engineering, University at Buffalo, SUNY, Buffalo, NY 14260

2. Department of Neurosurgery, University at Buffalo, SUNY, Buffalo, NY 14214

3. Division of Cardiovascular Diseases, Department of Internal Medicine, Mayo Clinic, Scottsdale, AZ 85259

4. Department of Mechanical and Aerospace Engineering, University at Buffalo, SUNY, Buffalo, NY 14260 e-mail:

Abstract

Two-dimensional echocardiography (echo) is the method of choice for noninvasive evaluation of the left ventricle (LV) function owing to its low cost, fast acquisition time, and high temporal resolution. However, it only provides the LV boundaries in discrete 2D planes, and the 3D LV geometry needs to be reconstructed from those planes to quantify LV wall motion, acceleration, and strain, or to carry out flow simulations. An automated method is developed for the reconstruction of the 3D LV endocardial surface using echo from a few standard cross sections, in contrast with the previous work that has used a series of 2D scans in a linear or rotational manner for 3D reconstruction. The concept is based on a generalized approach so that the number or type (long-axis (LA) or short-axis (SA)) of sectional data is not constrained. The location of the cross sections is optimized to minimize the difference between the reconstructed and measured cross sections, and the reconstructed LV surface is meshed in a standard format. Temporal smoothing is implemented to smooth the motion of the LV and the flow rate. This software tool can be used with existing clinical 2D echo systems to reconstruct the 3D LV geometry and motion to quantify the regional akinesis/dyskinesis, 3D strain, acceleration, and velocities, or to be used in ventricular flow simulations.

Publisher

ASME International

Subject

Physiology (medical),Biomedical Engineering

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Automatic segmentation of the left ventricle in echocardiographic images using convolutional neural networks;Quantitative Imaging in Medicine and Surgery;2021-05

2. A hybrid echocardiography‐CFD framework for ventricular flow simulations;International Journal for Numerical Methods in Biomedical Engineering;2020-06-08

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3