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Research on Hihg-Performance Electrical Impedance Tomography

高性能电阻抗层析成像技术的研究

基本信息

批准号：
07409002
负责人：
KOSUGI Yukio
金额：
$ 6.72万
依托单位：
Tokyo Institute of Technology
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (A)
财政年份：
1995
资助国家：
日本
起止时间：
1995 至 1996
项目状态：
已结题

来源：
https://kaken.nii.ac.jp/grant/KAKENHI-PROJECT-07409002/
关键词：
impedance tomography neural networks magnetically controlled tetrapolar method segmentation dynamic regularization ill-posed problems blood pulsatile wave inverse problems MR援用デコンボリューション Impedance Tomagraphy Neural Networks Blood Flo

项目摘要

Electrical impedance tomography (EIT) is capable of visualizing the electrical impedance distribution and its changes related to the anatomical disorders or physiological activities in the living body, to be applied for monitoring the biological conditions such as blood-flow changes in the brain, swellings and urinary bladder content etc.In this research we developed neural network methods to solve the inverse problems in estimating the conductivity distribution from the superficial potential distribution measured via a set of electrodes densely placed on the body surface. For improving the resolution of the conductivity profile, MR-based deconvolution will be effective used when we want to identify the localized blood-flow increment in the brain ; in this case ill-posedness of the inverse problem can be well improved by applying the dynamic regularization technique. We also developed a GA method to select the best indices for MR segmentation, which is a key-technology for incorporating the MR data to the deconvolution network after segmenting the CSF,the gray-matter and the white-matter of the brain automatically.Another topic, we investigated is the use of magnetically controlled tetrapolar method to monitor the pulsatile impedance changes in the brain : we experimentally tested the system to prove the effectiveness of the method in estimating the blood-glow increment during the mental-loading tests.We are now planning to improve the resolution of magnetically controlled tetrapolar method by deconvolving the series of data obtained in the measurement with the magnetic field continuously shifted.

电阻抗断层成像(EIT)能够直观地显示与活体解剖障碍或生理活动相关的电阻抗分布及其变化，用于监测脑血流变化、肿胀和膀胱内容物等生物状况。在本研究中，我们开发了神经网络方法来解决通过密集放置在人体表面的一组电极测量表面电位分布来估计电导率分布的逆问题。为了提高电导率剖面的分辨率，当我们想要识别大脑中局部的血流增量时，基于MR的反卷积将是有效的；在这种情况下，应用动态正则化技术可以很好地改善逆问题的不适定性。我们还开发了一种选择最佳MR分割指标的GA方法，这是自动分割脑脊液、灰质和白质后将MR数据合并到反卷积网络中的关键技术。另一个主题是使用磁控四极法来监测大脑的脉动阻抗变化：我们通过实验测试系统来证明该方法在心理负荷测试中估计血液辉光增量的有效性。我们现在计划通过对测量中获得的一系列数据进行反卷积来提高磁控四极法的分辨率。