Computational tools for Impedance Imaging

电阻抗断层扫描（EIT）用体表电极研究组织的电特性。申请人是国际公认的EIT图像重建和分析算法专家。在过去的资助期间，通过编辑主要教科书和领导算法和数据分析共识项目（已成为该领域最广泛使用的开源软件工具），在科学文献（47篇期刊论文）中传播贡献，并指导16名研究生，4份pdf文件和60名本科生。研究团队开发的软件是三家公司产品的核心组成部分。这笔拨款将侧重于两个特定的EIT应用：用于监测心力衰竭的无创肺动脉压（PAP）测量；支气管收缩的敏感指标监测阻塞性肺疾病。这些疾病影响的人群非常多，早期的结果是有希望的。心力衰竭（HF）影响了很大一部分老年人，当瓣膜退化或心脏变得太弱而不能充分泵血时就会发生心力衰竭。当右心代偿心衰时，PAP增加，高血压将液体挤压到空气中，导致肺部水肿、充血和呼吸短促。心力衰竭加重需要接受紧急护理；然而，导致这些恶化的PAP增加可在症状出现前数天或数周检测到，在此期间的干预可显著改善患者的预后。开发将侧重于最近的工作，表明PAP可以用EIT进行无创测量。对hr同步滤波后的数据进行重构，提取肺区EIT信号。本文将研究该算法的两个改进：毫秒级精度图像的计算和容错算法。哮喘和慢性阻塞性肺病等疾病是由于接触刺激物，特别是烟雾引起的肺部炎症造成的，并导致咳嗽、粘液产生和喘息。通过适当的护理和监测，大多数患者可以控制症状并改善生活质量。监测阻塞性肺疾病是不方便的，也只能给出一个高度异质性肺的全局图像。最近的研究表明，通过分析流量-体积参数的区域分布，EIT可以更灵敏地检测气流限制。在这笔拨款中，我们将研究优化的电极位置，强大的3D成像和区域流量参数。结果将传递给加拿大的合作伙伴公司。在研究具体技术应用的同时，这项拨款也将进一步发展强大的算法和计算工具，以提高企业信息技术的准确性和灵敏度，并通过开源软件提供这些成果。

Electrical Impedance Tomography (EIT) investigates the electrical properties of tissue with body-surface electrodes. The applicant is an internationally recognized expert in EIT image reconstruction and analysis algorithms. In the past grant period, contributions have been disseminated by editing of the main textbook and leading consensus projects on algorithms and data analysis, an open-source software tool which has become the most widely used in the field, in the scientific literature (47 journal papers), and supervising 16 graduate students, 4 PDFs and 60 undergraduate students. Software developed by the research team is a core component of three companies' products. This grant will focus on two specific EIT applications: non-invasive measurement of pulmonary arterial pressure (PAP) for monitoring of heart-failure; and sensitive measures of bronchoconstriction to monitor obstructive lung disease. These conditions affect very large populations, and early results are promising. Heart failure (HF) affects a large fraction of the elderly popultion, and occurs when the valves degrade or the heart becomes too weak to pump blood adequately. When the right heart compensates for HF, PAP increases, and the high blood pressure squeezes fluid into the airspaces leading tolung edema, congestion and shortness of breath. An exacerbation of heart failure requires admission to urgent care; however, the increases in PAP which lead to these exacerbations are detectable days or weeks before symptoms, and interventions during this window dramatically improve patient outcomes. Development will focus on recent work showing PAP can be measured non-invasively with EIT. HR-synchronized filtered data are reconstructed and the EIT signal in the lung region extracted. Two improvements to this algorithm will be researched: calcultion of millisecond-accuracy images, and error-tolerant algorithms. Diseases such as asthma and chronic obstructive lung disease, result from lung inflammation due to exposure to irritants and particularly smoke, and result in cough, mucus production and wheezing. With proper care and monitoring most patients can control symptoms and improve their quality of life. Monitoring of obstructive lung disease is inconvenient, and also gives only a global picture of the highly-heterogeneous lung. Recent work suggests that EIT can detect airflow limitation in a more sensitive way by analyzing the regional distribution of flow-volume parameters. Within this grant, we will research optimized electrode locations, robust 3D imaging, and regional flow-volume parameters. Results will be translated to Canadian partner companies. While working on specific technology applications, this grant will also further develop robust algorithms and computational tools useful to improve the accuracy and sensitivity of EIT, and make these contributions available through open-source software.