Use of statistical parametric mapping (SPM) to enhance electrical impedance tomography (EIT) image sets
Autor: | David Holder, Rebecca J. Yerworth, Richard Bayford, T. Tidswell, Yan Zhang |
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Rok vydání: | 2007 |
Předmět: |
Point spread function
Physiology Computer science Image quality media_common.quotation_subject Models Neurological Biomedical Engineering Biophysics Sodium Chloride Statistical parametric mapping Physiology (medical) Electric Impedance Image Processing Computer-Assisted Humans Contrast (vision) Computer Simulation Point (geometry) Computer vision Tomography Electrical impedance tomography media_common Brain Mapping Blood Volume Epilepsy Small data Human head Phantoms Imaging business.industry Skull fungi Brain Magnetic Resonance Imaging Radiography Stroke Positron-Emission Tomography Evoked Potentials Visual Artificial intelligence Artifacts business |
Zdroj: | Physiological Measurement. 28:S141-S151 |
ISSN: | 1361-6579 0967-3334 |
Popis: | Use of statistical parametric mapping (SPM), which is widely used in analysis of neuroimaging studies with fMRI and PET, has the potential to improve quality of EIT images for clinical use. Minimal modification to SPM is needed, but statistical analysis based on height, not extent thresholds, should be employed, due to the 20-80% variation of the point spread function, across EIT images. SPM was assessed in EIT images reconstructed with a linear time difference algorithm utilizing an anatomically realistic finite element model of the human head. Images of the average of data sets were compared with those produced using SPM over 10-40 individual image data sets without averaging. For a point disturbance, a sponge 15% of the diameter of an anatomically realistic saline-filled tank including a skull, with a contrast of 15%, and for visual evoked response data in 14 normal human volunteers, images produced with SPM were less noisy than the average images. For the human data, no consistent physiologically realistic changes were seen with either SPM or direct reconstruction; however, only a small data set was available, limiting the power of the SPM analysis. SPM may be used on EIT images and has the potential to extract improved images from clinical data series with a low signal-to-noise ratio. |
Databáze: | OpenAIRE |
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