Application of Supervised Descent Method to MRI Electrical Properties Tomography

Sabrina Zumbo; Stefano Mandija; Flavio Meliado; Cornelis A.T. Van Den Berg; Tommaso Isernia; Martina T. Bevacqua

doi:10.23919/EuCAP53622.2022.9768930

Application of Supervised Descent Method to MRI Electrical Properties Tomography

Sabrina Zumbo
, Stefano Mandija
, Flavio Meliado
, Cornelis A.T. Van Den Berg
, Tommaso Isernia
, Martina T. Bevacqua

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Electrical properties of biological tissues, conductivity and permittivity, are widely investigated because they provide crucial knowledge in different biomedical applications, for example in electromagnetic dosimetry and hyperthermia treatment planning, where is very important to quantify the induced specific absorption rate by a radiofrequency field. In this framework, a possibility is to retrieve the electrical properties starting from the measurements of the radiofrequency field collected inside a magnetic resonance scanner. To this end, in this paper, a learning approach based on supervised descent method is proposed in order to improve the efficiency of the reconstruction methods typically used in the literature. The approach is tested in the case of a 2D scenario mimicking a human head.

Original language	English
Title of host publication	2022 16th European Conference on Antennas and Propagation, EuCAP 2022
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9788831299046
DOIs	https://doi.org/10.23919/EuCAP53622.2022.9768930
Publication status	Published - 2022
Event	16th European Conference on Antennas and Propagation, EuCAP 2022 - Madrid, Spain Duration: 27 Mar 2022 → 1 Apr 2022

Conference

Conference	16th European Conference on Antennas and Propagation, EuCAP 2022
Country/Territory	Spain
City	Madrid
Period	27/03/22 → 1/04/22

Keywords

electrical properties
electromagnetic inverse scattering
image reconstruction
learning methods
magnetic resonance imaging

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10.23919/EuCAP53622.2022.9768930

Cite this

@inproceedings{8e4e3de3996240fc8e5687b869af1c3e,

title = "Application of Supervised Descent Method to MRI Electrical Properties Tomography",

abstract = "Electrical properties of biological tissues, conductivity and permittivity, are widely investigated because they provide crucial knowledge in different biomedical applications, for example in electromagnetic dosimetry and hyperthermia treatment planning, where is very important to quantify the induced specific absorption rate by a radiofrequency field. In this framework, a possibility is to retrieve the electrical properties starting from the measurements of the radiofrequency field collected inside a magnetic resonance scanner. To this end, in this paper, a learning approach based on supervised descent method is proposed in order to improve the efficiency of the reconstruction methods typically used in the literature. The approach is tested in the case of a 2D scenario mimicking a human head. ",

keywords = "electrical properties, electromagnetic inverse scattering, image reconstruction, learning methods, magnetic resonance imaging",

author = "Sabrina Zumbo and Stefano Mandija and Flavio Meliado and \{Van Den Berg\}, \{Cornelis A.T.\} and Tommaso Isernia and Bevacqua, \{Martina T.\}",

note = "Funding Information: This work was supported by the European Commission, Fondo Sociale Europeo and Regione Calabria, “Mobilit{\`a} internazionale di dottorandi” - POR Calabria FSE 2014/20. Publisher Copyright: {\textcopyright} 2022 European Association for Antennas and Propagation.; 16th European Conference on Antennas and Propagation, EuCAP 2022 ; Conference date: 27-03-2022 Through 01-04-2022",

year = "2022",

doi = "10.23919/EuCAP53622.2022.9768930",

language = "English",

booktitle = "2022 16th European Conference on Antennas and Propagation, EuCAP 2022",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

address = "United States",

}

Zumbo, S, Mandija, S, Meliado, F, Van Den Berg, CAT, Isernia, T & Bevacqua, MT 2022, Application of Supervised Descent Method to MRI Electrical Properties Tomography. in 2022 16th European Conference on Antennas and Propagation, EuCAP 2022. Institute of Electrical and Electronics Engineers Inc., 16th European Conference on Antennas and Propagation, EuCAP 2022, Madrid, Spain, 27/03/22. https://doi.org/10.23919/EuCAP53622.2022.9768930

Application of Supervised Descent Method to MRI Electrical Properties Tomography. / Zumbo, Sabrina; Mandija, Stefano; Meliado, Flavio et al.
2022 16th European Conference on Antennas and Propagation, EuCAP 2022. Institute of Electrical and Electronics Engineers Inc., 2022.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Application of Supervised Descent Method to MRI Electrical Properties Tomography

AU - Zumbo, Sabrina

AU - Mandija, Stefano

AU - Meliado, Flavio

AU - Van Den Berg, Cornelis A.T.

AU - Isernia, Tommaso

AU - Bevacqua, Martina T.

N1 - Funding Information: This work was supported by the European Commission, Fondo Sociale Europeo and Regione Calabria, “Mobilità internazionale di dottorandi” - POR Calabria FSE 2014/20. Publisher Copyright: © 2022 European Association for Antennas and Propagation.

PY - 2022

Y1 - 2022

N2 - Electrical properties of biological tissues, conductivity and permittivity, are widely investigated because they provide crucial knowledge in different biomedical applications, for example in electromagnetic dosimetry and hyperthermia treatment planning, where is very important to quantify the induced specific absorption rate by a radiofrequency field. In this framework, a possibility is to retrieve the electrical properties starting from the measurements of the radiofrequency field collected inside a magnetic resonance scanner. To this end, in this paper, a learning approach based on supervised descent method is proposed in order to improve the efficiency of the reconstruction methods typically used in the literature. The approach is tested in the case of a 2D scenario mimicking a human head.

AB - Electrical properties of biological tissues, conductivity and permittivity, are widely investigated because they provide crucial knowledge in different biomedical applications, for example in electromagnetic dosimetry and hyperthermia treatment planning, where is very important to quantify the induced specific absorption rate by a radiofrequency field. In this framework, a possibility is to retrieve the electrical properties starting from the measurements of the radiofrequency field collected inside a magnetic resonance scanner. To this end, in this paper, a learning approach based on supervised descent method is proposed in order to improve the efficiency of the reconstruction methods typically used in the literature. The approach is tested in the case of a 2D scenario mimicking a human head.

KW - electrical properties

KW - electromagnetic inverse scattering

KW - image reconstruction

KW - learning methods

KW - magnetic resonance imaging

UR - https://www.scopus.com/pages/publications/85130594907

U2 - 10.23919/EuCAP53622.2022.9768930

DO - 10.23919/EuCAP53622.2022.9768930

M3 - Conference contribution

AN - SCOPUS:85130594907

BT - 2022 16th European Conference on Antennas and Propagation, EuCAP 2022

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 16th European Conference on Antennas and Propagation, EuCAP 2022

Y2 - 27 March 2022 through 1 April 2022

ER -

Application of Supervised Descent Method to MRI Electrical Properties Tomography

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Keywords

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