.png){kind=icon}
返回
Shape-Driven Difference Electrical Impedance Tomography
.png){kind=icon}
PRE
AI
DOI：10.1109/TMI.2020.3004806.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
This work proposes a novel shape-driven reconstruction approach for difference electrical impedance tomography (EIT). In the proposed approach, the reconstruction problem is formulated as a shape reconstruction problem and solved via an explicit and geometrical methodology, where the geometry of the embedded inclusions is represented by a shape and topology description function (STDF). To incorporate more geometry and prior information directly into the reconstruction and to provide better flexibility in the solution process, the concept of a moving morphable component (MMC) is applied here implying that MMC is treated as the basic building block of the embedded inclusions. Simulations, phantom studies, and in vivo pig data are used to test the proposed approach for the most popular biomedical application of EIT - lung imaging - and the performance is compared with the conventional linear approach. In addition, the modality's robustness is studied in cases where (i) modeling errors are caused by inhomogeneity in the background conductivity, and (ii) uncertainties in the contact impedances and reference state are present. The results of this work indicate that the proposed approach is tolerant to modeling errors and is fairly robust to typical EIT uncertainties, producing greatly improved image quality compared to the conventional linear approach.
Keyword:
Tomography
Conductivity
Image reconstruction
Shape
Computational modeling
Conductivity measurement
Electrical impedance tomography
difference imaging
linearization
moving morphable component
shape reconstruction
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
9.8
论文数:
6.2K
被引数:
3.7W
机构
引用论文
Semiconductor channel-mediated photodoping in h-BN encapsulated monolayer MoSe
2
phototransistors.png)
2D Materials
OAAI
2D MaterialsIF0
OAAI分享收藏
查看更多内容