Current constrained voltage scaled reconstruction (CCVSR) algorithm for MR-EIT and its performance with different probing current patterns
dc.citation.epage | 671 | en_US |
dc.citation.issueNumber | 5 | en_US |
dc.citation.spage | 653 | en_US |
dc.citation.volumeNumber | 48 | en_US |
dc.contributor.author | Birgül, Ö. | en_US |
dc.contributor.author | Eyüboğlu, B. M. | en_US |
dc.contributor.author | İder, Y. Z. | en_US |
dc.date.accessioned | 2018-04-12T13:50:53Z | |
dc.date.available | 2018-04-12T13:50:53Z | |
dc.date.issued | 2003 | en_US |
dc.department | Department of Electrical and Electronics Engineering | en_US |
dc.description.abstract | Conventional injected-current electrical impedance tomography (EIT) and magnetic resonance imaging (MRI) techniques can be combined to reconstruct high resolution true conductivity images. The magnetic flux density distribution generated by the internal current density distribution is extracted from MR phase images. This information is used to form a fine detailed conductivity image using an Ohm's law based update equation. The reconstructed conductivity image is assumed to differ from the true image by a scale factor. EIT surface potential measurements are then used to scale the reconstructed image in order to find the true conductivity values. This process is iterated until a stopping criterion is met. Several simulations are carried out for opposite and cosine current injection patterns to select the best current injection pattern for a 2D thorax model. The contrast resolution and accuracy of the proposed algorithm are also studied. In all simulation studies, realistic noise models for voltage and magnetic flux density measurements are used. It is shown that, in contrast to the conventional EIT techniques, the proposed method has the capability of reconstructing conductivity images with uniform and high spatial resolution. The spatial resolution is limited by the larger element size of the finite element mesh and twice the magnetic resonance image pixel size. | en_US |
dc.description.provenance | Made available in DSpace on 2018-04-12T13:50:53Z (GMT). No. of bitstreams: 1 bilkent-research-paper.pdf: 179475 bytes, checksum: ea0bedeb05ac9ccfb983c327e155f0c2 (MD5) Previous issue date: 2003 | en |
dc.identifier.doi | 10.1088/0031-9155/48/5/307 | en_US |
dc.identifier.issn | 0031-9155 | |
dc.identifier.uri | http://hdl.handle.net/11693/38214 | |
dc.language.iso | English | en_US |
dc.publisher | Institute of Physics Publishing | en_US |
dc.relation.isversionof | http://dx.doi.org/10.1088/0031-9155/48/5/307 | en_US |
dc.source.title | Physics in Medicine and Biology | en_US |
dc.subject | Algorithms | en_US |
dc.subject | Computer simulation | en_US |
dc.subject | Current density | en_US |
dc.subject | Electric impedance tomography | en_US |
dc.subject | Image reconstruction | en_US |
dc.subject | Magnetic flux | en_US |
dc.subject | Phase images | en_US |
dc.subject | Magnetic resonance imaging | en_US |
dc.subject | Accuracy | en_US |
dc.subject | Algorithm | en_US |
dc.subject | Analytical error | en_US |
dc.subject | Computer assisted impedance tomography | en_US |
dc.subject | Contrast enhancement | en_US |
dc.subject | Controlled study | en_US |
dc.subject | Electric conductivity | en_US |
dc.subject | Electric current | en_US |
dc.subject | Electric potential | en_US |
dc.subject | Image analysis | en_US |
dc.subject | Image processing | en_US |
dc.subject | Image reconstruction | en_US |
dc.subject | Mathematical computing | en_US |
dc.subject | Noise measurement | en_US |
dc.subject | Nuclear magnetic resonance imaging | en_US |
dc.subject | Radiation dose distribution | en_US |
dc.subject | Simulation | en_US |
dc.subject | Thorax | en_US |
dc.subject | Algorithms | en_US |
dc.subject | Electric Impedance | en_US |
dc.subject | Electromagnetic Fields | en_US |
dc.subject | Humans | en_US |
dc.subject | Image Interpretation, Computer-Assisted | en_US |
dc.subject | Magnetic resonance imaging | en_US |
dc.subject | Radiometry | en_US |
dc.subject | Reproducibility of results | en_US |
dc.subject | Sensitivity and specificity | en_US |
dc.subject | Tomography | en_US |
dc.title | Current constrained voltage scaled reconstruction (CCVSR) algorithm for MR-EIT and its performance with different probing current patterns | en_US |
dc.type | Review | en_US |
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