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Clinical Imaging of Microwave Mammography
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MEFS - MIND electrical impedance tomography forward solver.

Fei Yang1, Jie Zhang, Robert Patterson

  • 1Department of Radiation Oncology, Washington University School of Medicine, 4921 Parkview Place, Campus box 8224, St Louis, MO 63110, USA. fyang@radonc.wustl.edu

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
|November 25, 2010
PubMed
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Electrical impedance tomography (EIT) monitoring needs standardized algorithms. MEFS software provides realistic thoracic models for developing and comparing EIT reconstruction methods like GREIT, improving ventilation assessment.

Area of Science:

  • Biomedical Engineering
  • Medical Imaging
  • Computational Modeling

Background:

  • Electrical impedance tomography (EIT) is a low-cost, safe method for monitoring mechanical ventilation.
  • Variability in EIT image reconstruction algorithms hinders cross-institutional interpretation of regional ventilation.
  • The GREIT (Graz consensus Reconstruction algorithm for EIT) algorithm was proposed to standardize EIT reconstruction.

Purpose of the Study:

  • To develop a high-resolution, image-based electrical thoracic modeling software environment, MEFS (MIND EIT Forward Solver).
  • To generate necessary electrical measurements for EIT image reconstruction.
  • To provide a platform for comparing different EIT reconstruction algorithms, including GREIT.

Main Methods:

  • Developed MEFS software utilizing anatomically realistic thoracic geometry.

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  • Enabled interactive placement of electrodes of arbitrary shapes.
  • Simulated detailed electrical field information within the thoracic volume.

    • Main Results:

    • MEFS software successfully generates electrical measurements for EIT.
    • The software provides a platform for simulating and comparing EIT reconstruction algorithms.
    • Facilitates the assessment of standardized algorithms like GREIT using realistic models.

    Conclusions:

    • MEFS is an indispensable tool for assessing GREIT and other EIT reconstruction algorithms.
    • This software environment supports the development of standardized EIT monitoring for mechanical ventilation.
    • MEFS enables more reliable and comparable regional ventilation assessments across different institutions.