Fuzzy Modeling of Electrical Impedance Tomography Image of the Lungs

TL;DR

This paper introduces a fuzzy modeling approach to enhance the resolution of Electrical Impedance Tomography (EIT) images of the lungs, enabling better bedside clinical imaging for critical care.

Contribution

The study develops a novel fuzzy model integrating pulmonary perfusion and ventilation signals to improve EIT image quality and anatomical resolution.

Findings

Fuzzy model images closely match CT scans.

ROC curve area of 0.93 indicates high accuracy.

Model enables potential bedside clinical applications.

Abstract

Electrical Impedance Tomography (EIT) is a functional imaging method that is being developed for bedside use in critical care medicine. Aiming at improving the chest anatomical resolution of EIT images we developed a fuzzy model based on EIT high temporal resolution and the functional information contained in the pulmonary perfusion and ventilation signals. EIT data from an experimental animal model were collected during normal ventilation and apnea while an injection of hypertonic saline was used as a reference . The fuzzy model was elaborated in three parts: a modeling of the heart, a pulmonary map from ventilation images and, a pulmonary map from perfusion images. Image segmentation was performed using a threshold method and a ventilation/perfusion map was generated. EIT images treated by the fuzzy model were compared with the hypertonic saline injection method and CT-scan images, presenting good results in both qualitative (the image obtained by the model was very similar to that of the CT-scan) and quantitative (the ROC curve provided an area equal to 0.93) point of view. Undoubtedly, these results represent an important step in the EIT images area, since they open the possibility of developing EIT-based bedside clinical methods, which are not available nowadays. These achievements could serve as the base to develop EIT diagnosis system for some life-threatening diseases commonly found in critical care medicine.