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Intelligent Diagnosis of Lung Cancer and Respiratory Diseases

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Absolute Images Reconstruction in Heart and Lungs for COVID-19 Patients using Multifrequencial Electrical Impedance Tomography System and D-Bar Method

Author(s): Julia G. B. Wolff*, Wellington P. dos Santos and Pedro Bertemes-Filho

Pp: 130-225 (96)

DOI: 10.2174/9789815050509122010010

* (Excluding Mailing and Handling)

Abstract

Brazil is one of the countries most affected by the COVID-19 pandemic.
Since the beginning of November 2020, Brazil has been experiencing an acute crisis of
the disease, with an increase in cases, hospitalizations and deaths, including among the
youngest. During the month of April 2021, as intensive care units they were working
almost at full capacity throughout the country. Since the beginning of the pandemic, in
March 2020, without total, Brazil has reported more than 14 million cases of COVID-
19 and more than 400 thousand deaths. Due to the rapid spread of the virus and due to
the fact that the health systems of different countries are not prepared to serve the large
number of patients affected by this disease, we have proposed the use of
multifrequency electrical impedance tomography (MfEIT) in the management of
pulmonary disease in ICU beds. There are several other forms of tomographic imaging
that deliver better image resolution, however, MfEIT has some advantages over CT
Scan and X-rays, which are: the absence of ionizing radiation, the portability of the
equipment, the possibility of access remote control of the patient's clinical data by the
medical team, the visualization of dynamic pulmonary and cardiac parameters that are
not seen in computed tomography images, nor in ultrasound images. However, an
application of the D-Bar algorithms developed by Siltanen and his team, from 2012 to
2020, at the University of Helsinki, Finland, for viewing images in patients with
COVID-19 was evaluated. Various scenarios and criteria were proposed in the text and
the results obtained promising evidence for imaging internal organs in the radio
frequency range. As expected, codes cannot be considered in extremely low frequency
situations, as reconstructions are not considered. In the future, we seek to work with
deep neural networks to speed up the simulation of images and to compare results.

Keywords: 2D D-Bar Method, Cardiac parameters, COVID-19, Dynamic pulmonary, Heart image, ICU beds, Image reconstruction, Lung image, Multi-frequencial Electric Impedance Tomography, Pandemic, Remote control, SARS-CoV-2.

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