Computational tools and algorithms for impedance imaging

阻抗成像的计算工具和算法

• 批准号: RGPIN-2017-06249
• 负责人: Adler, Andy
• 金额: $ 2.7万
• 依托单位: Carleton University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2018
• 资助国家: 加拿大
• 起止时间: 2018-01-01 至 2019-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=643492
• 关键词: Computational; tools; algorithms; impedance; imaging

Electrical impedance tomography (EIT) uses measurements at body surface electrodes to calculate an image of the internal electrical properties. Such images provide useful information in medicine (i.e. blood and air flow), geophysics (i.e. ground water and mineral localization), and industrial process monitoring. The applicant is an internationally recognized expert in algorithms for EIT imaging and functional image analysis. In the past grant period, contributions have been disseminated by a) leading of consensus projects on algorithms and data analysis, b) an open-source software tool which has become the most widely used in the field, c) in the scientific literature (53 journal papers), and d) supervising 21 graduate students, 4 PDFs and 60 undergraduate students. Software developed by the research team is a core component of three companies' products.******Overall, research will focus on two streams: first, a Robust Algorithms and Validation theme (funded by this grant), which will develop an image evaluation and “debugging” framework, and, using the core technology developed, an Applications theme (funded by collaborators and industrial partners).******Despite its successes, EIT has been criticized for a lack of robustness, as the inverse problem inherent to image reconstruction is ill-conditioned, so that small data or model inaccuracies can result in large image artefacts. This research program will address this issue by developing a set of tools to analyse and correct inverse problem solutions. While several individual tools have been developed (by the applicant and others), the core innovation of this project is an integrated evaluation/debugging software framework. Three new components will be developed: a model and data validation tool, models of non-ideal characteristics of electronics hardware and electrodes (such as amplifier input impedance and crosstalk), and an image inspection tool to query the data contributing to suspected artefacts.******At the same time, work will be pursued on applications of EIT technology for medical and geophysical applications. Medical applications will focus on dynamic lung imaging (for use with neonatal, intensive care, and obstructive lung disease patients) and hemodynamic monitoring (non-invasive blood pressure and cardiac output measures). Geophysical applications will focus on monitoring of groundwater and surface movement in unstable (landslide-prone) soils and permafrost regions.

电阻抗断层扫描（EIT）使用体表电极的测量值来计算内部电特性的图像。这些图像在医学（即血液和空气流动）、生物物理学（即地下水和矿物定位）和工业过程监控中提供有用的信息。申请人是国际公认的EIT成像和功能图像分析算法专家。在过去的赠款期内，通过以下方式传播了捐款：a）领导关于算法和数据分析的共识项目，B）已成为该领域最广泛使用的开源软件工具，c）科学文献（53篇期刊论文），以及d）指导21名研究生，4名PDF和60名本科生。该研究团队开发的软件是三家公司产品的核心组成部分。总的来说，研究将集中在两个方面：第一，鲁棒算法和验证主题（由该基金资助），将开发图像评估和“调试”框架，以及使用开发的核心技术，应用主题（由合作者和工业合作伙伴资助）。尽管取得了成功，但EIT因缺乏鲁棒性而受到批评，因为图像重建所固有的逆问题是病态的，因此小数据或模型不准确可能导致大的图像伪影。这项研究计划将通过开发一套工具来分析和纠正逆问题的解决方案来解决这个问题。虽然已经开发了几个单独的工具（由申请人和其他人），该项目的核心创新是一个综合的评估/调试软件框架。将开发三个新的组件：模型和数据验证工具，电子硬件和电极的非理想特性模型（如放大器输入阻抗和串扰），以及用于查询导致可疑伪影的数据的图像检查工具。与此同时，还将开展将电磁感应成像技术应用于医疗和地球物理方面的工作。医疗应用将集中在动态肺成像（用于新生儿，重症监护和阻塞性肺病患者）和血流动力学监测（无创血压和心输出量测量）。地球物理应用将侧重于监测不稳定（易滑坡）土壤和永久冻土区的地下水和地表移动。