title: Level-set-based reconstruction algorithm for EIT lung images: first clinical results.
abstract: We show the first clinical results using the level-set-based reconstruction algorithm for electrical impedance tomography (EIT) data. The level-set-based reconstruction method (LSRM) allows the reconstruction of non-smooth interfaces between image regions, which are typically smoothed by traditional voxel-based reconstruction methods (VBRMs). We develop a time difference formulation of the LSRM for 2D images. The proposed reconstruction method is applied to reconstruct clinical EIT data of a slow flow inflation pressure-volume manoeuvre in lung-healthy and adult lung-injury patients. Images from the LSRM and the VBRM are compared. The results show comparable reconstructed images, but with an improved ability to reconstruct sharp conductivity changes in the distribution of lung ventilation using the LSRM.
authors.affiliation: Department of Systems and Computer Eng., Carleton University, ON, Canada. prahmati@sce.carleton.ca
authors.forename: Peyman
authors.initials: P
authors.lastname: Rahmati
authors.forename: Manuchehr
authors.initials: M
authors.lastname: Soleimani
authors.forename: Sven
authors.initials: S
authors.lastname: Pulletz
authors.forename: Inéz
authors.initials: I
authors.lastname: Frerichs
authors.forename: Andy
authors.initials: A
authors.lastname: Adler
mesh_terms: D055371:Acute Lung Injury / Q000175:diagnosis / Q000628:therapy; D000328:Adult; D000465:Algorithms; D017097:Electric Impedance; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008168:Lung; D008875:Middle Aged; D012121:Respiration, Artificial; D014054:Tomography / Q000379:methods*