Assessing the impact of a structural prior mask on EIT images with different thorax excursion models
Abstract: Electrical Impedance Tomography (EIT) has shown promising results as a low-cost imaging method for visualizing ventilation distribution within the lungs. However, clinical interpretation of EIT images is often hindered by blurred anatomical alignment and reconstruction artifacts. Integrating structural priors into the EIT reconstruction process has the potential to enhance the interpretability of the EIT images. Thus, a patient-specific structural prior mask is introduced in this contribution, which restricts the reconstruction of conductivity changes within the lung regions.We conducted numerical simulations on four finite element models representing four different thorax excursions to investigate the impact of the structural prior mask on EIT images. Simulations were performed under four different ventilation statuses. EIT images were reconstructed using the Gauss-Newton and discrete cosine transform-based EIT algorithms.We conducted a quantitative analysis using figures of merit to evaluate the images of the two reconstruction algorithms. The results show the structural prior mask preserves the morphological structures of the lungs and limits reconstruction artifacts.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Assessing the impact of a structural prior mask on EIT images with different thorax excursion models ; volume:9 ; number:1 ; year:2023 ; pages:367-370 ; extent:4
Current directions in biomedical engineering ; 9, Heft 1 (2023), 367-370 (gesamt 4)
- Creator
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Chen, Rongqing
Battistel, Alberto
Krueger-Ziolek, Sabine
Möller, Knut
Chase, James Geoffrey
Rupitsch, Stefan J.
- DOI
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10.1515/cdbme-2023-1092
- URN
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urn:nbn:de:101:1-2023092214221780070952
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 10:59 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Chen, Rongqing
- Battistel, Alberto
- Krueger-Ziolek, Sabine
- Möller, Knut
- Chase, James Geoffrey
- Rupitsch, Stefan J.