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Cross\u2010sectional dynamic images are formed by reconstructing the conductivity distribution from measured voltage data arising from applied alternating currents on electrodes placed circumferentially around the chest. Since the conductivity of lung tissue depends on air content, blood flow, and the presence of pathology, the dynamic images provide regional information about ventilation, pulsatile perfusion, and abnormalities. However, due to the ill\u2010posedness of the inverse conductivity problem, EIT images have a coarse spatial resolution. One method of improving the resolution is to include prior information in the\u00a0reconstruction.<\/jats:p><\/jats:sec><jats:sec><jats:title>Purpose<\/jats:title><jats:p>In this work, we propose a technique in which a statistical prior built from an anatomical atlas is used to postprocess EIT reconstructions of human chest data. The effectiveness of the method is demonstrated on data from two patients with cystic\u00a0fibrosis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods<\/jats:title><jats:p>A direct reconstruction algorithm known as the D\u2010bar method was used to compute a two\u2010dimensional reconstruction of the conductivity distribution in the plane of the electrodes. Reconstructions using one step in an iterative (regularized) Newton's method were also computed for comparison. An anatomical atlas consisting of 1589 synthetic EIT images computed from X\u2010ray computed tomography (CT) scans of 74 adult male subjects was computed for use as a statistical prior. The resolution of the D\u2010bar images was then improved by maximizing the conditional probability density function of an image that is consistent with the a priori information and the statistical model. A new method to evaluate the accuracy of the EIT images using CT scans of the imaged patient as ground truth is presented. The novel approach is tested on data from two patients with cystic\u00a0fibrosis.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results and Conclusions<\/jats:title><jats:p>The D\u2010bar images resulted in better structural similarity index measures (SSIM) and multiscale (MS) SSIM measures for both subjects using the mask or amplitude evaluation approach than the one\u2010step (regularized) Newton's method. Further improvement was achieved using the Schur complement (SC) approach, with MS\u2010SSIM values of 0.718 and 0.682 using SC evaluated with the mask and amplitude approach, respectively, for Patient 1, and MS\u2010SSIM values of 0.726 and 0.692 using SC evaluated with the mask and amplitude approach, respectively, for Patient 2. The results from applying an anatomical atlas and statistical prior to EIT data from two patients with cystic fibrosis suggest that the spatial resolution of the EIT image can be improved to reveal pathology that may be difficult to discern in the original EIT image. The novel metric of evaluation is consistent with the appearance of improved spatial resolution and provides a new way to evaluate the accuracy of EIT reconstructions when a CT scan is\u00a0available.<\/jats:p><\/jats:sec>","DOI":"10.1002\/mp.15669","type":"journal-article","created":{"date-parts":[[2022,4,12]],"date-time":"2022-04-12T08:29:00Z","timestamp":1649752140000},"page":"4653-4670","update-policy":"http:\/\/dx.doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":9,"title":["Improved resolution of D\u2010bar images of ventilation using a Schur complement property and an anatomical atlas"],"prefix":"10.1002","volume":"49","author":[{"given":"Talles Batista Rattis","family":"Santos","sequence":"first","affiliation":[{"name":"Department of Mathematics Colorado State University Colorado USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rafael Mikio","family":"Nakanishi","sequence":"additional","affiliation":[{"name":"Mechanical Engineering Department Polytechnic School of the University of S\u00e3o Paulo S\u00e3o Paulo SP Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Erick Dario Le\u00f3n Bueno","family":"de Camargo","sequence":"additional","affiliation":[{"name":"Engineering, Modeling and Applied Social Sciences Centre Federal University of ABC Santo Andr\u00e9 SP Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Marcelo Brito Passos","family":"Amato","sequence":"additional","affiliation":[{"name":"Respiratory Intensive Care Unit Pulmonary Division Hospital das Cl\u00ednicas University of S\u00e3o Paulo SP Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jari P.","family":"Kaipio","sequence":"additional","affiliation":[{"name":"Department of Mathematics University of Auckland New Zealand"},{"name":"Department of Applied Physics University of Eastern Finland Kuopio Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Raul Gonzalez","family":"Lima","sequence":"additional","affiliation":[{"name":"Mechanical Engineering Department Polytechnic School of the University of S\u00e3o Paulo S\u00e3o Paulo SP Brazil"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jennifer L.","family":"Mueller","sequence":"additional","affiliation":[{"name":"Department of Mathematics and School of Biomedical Engineering and the Department of Electrical and Computer Engineering Colorado State University Colorado USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2022,5,5]]},"reference":[{"key":"e_1_2_7_2_1","unstructured":"Drager. website.Drager;2021.https:\/\/www.draeger.com\/en_aunz\/Hospital\/Non\u2010Invasive\u2010Ventilation\/Electrical\u2010Impedance\u2010TomographyAccessed: December 16 2021."},{"key":"e_1_2_7_3_1","unstructured":"Timpel 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