Estimating regional pulmonary blood flow in EIT with regularized deconvolution with a Tikhonov regularization

• Main Authors: Augustin Xenia, Kircher Michael, Dössel Olaf, Stender Birgit, Bluth Thomas, Gama de Abreu Marcelo
• Format: Article
• Language: English
• Published: De Gruyter 2020-09-01
• Series: Current Directions in Biomedical Engineering
• Subjects: eit; perfusion measurement; rbf; tikhonov regularization; maximum slope; image reconstruction
• Online Access: https://doi.org/10.1515/cdbme-2020-3016

Electrical Impedance Tomography (EIT) is a clinically used tool for bed-side monitoring of ventilation. Previous work also showed a high potential for lung perfusion monitoring with indicator-enhanced EIT. However, many research questions have yet to be answered before it can be broadly applied in clinical everyday life. The goal of this work is to evaluate a new method to improve EIT perfusion measurements. Pulmonary hemodynamic transfer functions were estimated using regularized deconvolution with Tikhonov regularization to estimate spatial perfusion parameters. The final comparison between EIT images and PET scans showed a median correlation of 0.897 for the images which were reconstructed using the regularized deconvolution. In comparison the previously used maximum slope method led to a median correlation of 0.868.