Please use this identifier to cite or link to this item: https://ir.swu.ac.th/jspui/handle/123456789/13073
ชื่อเรื่อง: Constrained modeling for image reconstruction in the application of Electrical Impedance Tomography to the head
ผู้แต่ง: Ouypornkochagorn T.
Keywords: Electric impedance
Electric impedance measurement
Electric impedance tomography
Image processing
Medical imaging
Tomography
Conductivity distributions
Constrained models
Difference imaging
Electrical impe dance tomography (EIT)
Electrical impedance tomography
Localization performance
Model errors
Tissue conductivity
Image reconstruction
วันที่เผยแพร่: 2017
บทคัดย่อ: Electrical Impedance Tomography (EIT) is an alternative way to image brain functions, in the form of conductivity distribution image, by using the boundary voltage information while a small current is injected. In head applications, due to the lack of accurate head models and the high-degree nonlinearity, the image reconstruction tends to fail. Recently, a nonlinear difference imaging approach has been proposed to mitigate modeling error. This approach, however, is based on unconstrained modeling that allows tissue conductivity values to be unrealistically negative. Consequently, substantial image artifacts are possibly conducted. In this work, two methods of constrained modeling were demonstrated they are able to substantially reduce artifacts and improve localization performance. New images of conductivity distribution of the mapped constraint domains, derived from the use of constrained modeling, are also exhibited here. The simulation result shows that the new images achieve better localization performance than those of using unconstrained modeling. © 2017 IEEE.
URI: https://ir.swu.ac.th/jspui/handle/123456789/13073
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85023190801&doi=10.1109%2fISBI.2017.7950580&partnerID=40&md5=5c02834c42d12041f86aefc5a52ce29d
ISSN: 19457928
Appears in Collections:Scopus 1983-2021

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