Mutual information as a measure of image quality for 3D dynamic lung imaging with EIT

M. G. Crabb*, J. L. Davidson, R. Little, P. Wright, A. R. Morgan, C. A. Miller, J. H. Naish, G. J. M. Parker, R. Kikinis, H. McCann, W. R. B. Lionheart

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

We report on a pilot study of dynamic lung electrical impedance tomography (EIT) at the University of Manchester. Low-noise EIT data at 100 frames per second were obtained from healthy male subjects during controlled breathing, followed by magnetic resonance imaging (MRI) subsequently used for spatial validation of the EIT reconstruction. The torso surface in the MR image and electrode positions obtained using MRI fiducial markers informed the construction of a 3D finite element model extruded along the caudal-distal axis of the subject. Small changes in the boundary that occur during respiration were accounted for by incorporating the sensitivity with respect to boundary shape into a robust temporal difference reconstruction algorithm. EIT and MRI images were co-registered using the open source medical imaging software, 3D Slicer. A quantitative comparison of quality of different EIT reconstructions was achieved through calculation of the mutual information with a lung-segmented MR image. EIT reconstructions using a linear shape correction algorithm reduced boundary image artefacts, yielding better contrast of the lungs, and had 10% greater mutual information compared with a standard linear EIT reconstruction.

Original languageEnglish
Pages (from-to)863-879
Number of pages17
JournalPhysiological Measurement
Volume35
Issue number5
Early online date8 Apr 2014
DOIs
Publication statusPublished - 31 May 2014

Keywords

  • 3D lung EIT
  • MRI
  • mutual information
  • image co-registration
  • ELECTRICAL-IMPEDANCE TOMOGRAPHY
  • BOUNDARY SHAPE
  • HIGH-SPEED
  • VENTILATION
  • RECONSTRUCTION
  • CONDUCTIVITY
  • RESISTIVITY
  • REGISTRATION
  • UNIQUENESS
  • PERFUSION

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