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Brain Imaging

Brain Imaging

Brain imaging technologies provide critical insights into both the structure and function of the human brain, enabling medical professionals and researchers to diagnose, study, and treat neurological disorders or psychiatric disorders more effectively.
These technologies include computerized axial tomography (CAT or CT scans), positron-emission tomography (PET scans), magnetic resonance imaging (MRI), functional magnetic resonance imaging (fMRI), and Transcranial Magnetic...

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Updated: Oct 2, 2025

Monitoring Lung Function with Electrical Impedance Tomography in the Intensive Care Unit

Monitoring Lung Function with Electrical Impedance Tomography in the Intensive Care Unit

Published on: September 6, 2024

Advances in electrical impedance tomography-based brain imaging.

Xi-Yang Ke^1,2,3, Wei Hou^1,2,3, Qi Huang⁴

¹Department of Radiation Oncology and Therapy, The First Hospital of Jilin University, 130021, Changchun, China.

Military Medical Research

|March 1, 2022

Summary

This summary is machine-generated.

Electrical impedance tomography (EIT) offers a promising non-invasive brain imaging method for diagnosing neurological conditions like epilepsy and stroke. Further research is needed to overcome current limitations and establish EIT as a routine clinical tool.

Keywords:

Brain diseases Electrical impedance tomography (EIT)Microelectrode array Tissue impedance

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Area of Science:

Medical Imaging
Biomedical Engineering
Neuroscience

Background:

Novel brain imaging advances enhance disease diagnosis and treatment.
Electrical impedance tomography (EIT) estimates tissue electrical properties using surface electrodes.
EIT presents advantages for clinical neuroimaging applications.

Purpose of the Study:

To review the principles, algorithms, and system design of EIT.
To discuss recent EIT advancements in neurological disease imaging.
To identify limitations and future prospects for brain EIT.

Main Methods:

Qualitative review of existing literature on EIT.
Discussion of EIT applications in epilepsy, stroke, and brain injuries.
Analysis of factors influencing EIT accuracy and development.

Main Results:

EIT shows progress in imaging depth for epilepsy, from cortical to subcortical regions.
A bedside EIT system for stroke monitoring is developed, supporting its role in multi-modal diagnosis.
EIT monitors brain water content changes for early edema detection and treatment evaluation.

Conclusions:

EIT demonstrates potential for diagnosing and monitoring various brain conditions.
Improving EIT accuracy requires addressing anatomical realism, inhomogeneity, and skull properties.
Further evidence is necessary to establish EIT as a standard diagnostic technique.