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.

Application of Supervised Descent Method to MRI Electrical Properties Tomography

Zumbo S.;Isernia T.;Bevacqua M.
2022-01-01

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.
2022
electrical properties
electromagnetic inverse scattering
image reconstruction
learning methods
magnetic resonance imaging
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/142380
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