The aim of this paper is to describe and compare the performances of three image reconstruction algorithms that can be used for brain stroke microwave imaging. The algorithms belong to the class of non-linear iterative algorithms and are capable of providing a quantitative map of the imaged scenario. The first algorithm is the Contrast Source Inversion (CSI) method, which uses the Finite Element Method (FEM) to discretize the domain of interest. The second one is the Subspace-Based Optimization Method (SOM) that has some properties in common with the CSI method, and it also uses FEM to discretize the domain. The last one is the Distorted Born Iterative Method with the inverse solver Two-step Iterative Shrinkage/Thresholding (DBIM-TwIST), which exploits the forward Finite Difference Time Domain (FDTD) solver. The reconstruction examples are created with 3-D synthetic data modelling realistic brain tissues with the presence of a blood region, representing the stroke area in the brain, whereas the inversion step is carried out using a 2-D model.

Comparison of Reconstruction Algorithms for Brain Stroke Microwave Imaging / Mariano, V.; Tobon Vasquez, J. A.; Scapaticci, R.; Crocco, L.; Kosmas, P.; Vipiana, F.. - ELETTRONICO. - (2020). ((Intervento presentato al convegno 2020 IEEE MTT-S International Microwave Biomedical Conference, IMBioC 2020 tenutosi a Toulouse, France nel 14-17 Dec. 2020 [10.1109/IMBIoC47321.2020.9385032].

Comparison of Reconstruction Algorithms for Brain Stroke Microwave Imaging

Mariano V.;Tobon Vasquez J. A.;Vipiana F.
2020

Abstract

The aim of this paper is to describe and compare the performances of three image reconstruction algorithms that can be used for brain stroke microwave imaging. The algorithms belong to the class of non-linear iterative algorithms and are capable of providing a quantitative map of the imaged scenario. The first algorithm is the Contrast Source Inversion (CSI) method, which uses the Finite Element Method (FEM) to discretize the domain of interest. The second one is the Subspace-Based Optimization Method (SOM) that has some properties in common with the CSI method, and it also uses FEM to discretize the domain. The last one is the Distorted Born Iterative Method with the inverse solver Two-step Iterative Shrinkage/Thresholding (DBIM-TwIST), which exploits the forward Finite Difference Time Domain (FDTD) solver. The reconstruction examples are created with 3-D synthetic data modelling realistic brain tissues with the presence of a blood region, representing the stroke area in the brain, whereas the inversion step is carried out using a 2-D model.
978-1-7281-5866-2
File in questo prodotto:
File Dimensione Formato  
Comparison_of_Reconstruction_Algorithms_for_Brain_Stroke_Microwave_Imaging.pdf

non disponibili

Descrizione: Articolo principale
Tipologia: 2a Post-print versione editoriale / Version of Record
Licenza: Non Pubblico - Accesso privato/ristretto
Dimensione 382.27 kB
Formato Adobe PDF
382.27 kB Adobe PDF   Visualizza/Apri   Richiedi una copia
1570630735.pdf

accesso aperto

Descrizione: post print
Tipologia: 2. Post-print / Author's Accepted Manuscript
Licenza: PUBBLICO - Tutti i diritti riservati
Dimensione 359.11 kB
Formato Adobe PDF
359.11 kB Adobe PDF Visualizza/Apri
Pubblicazioni consigliate

Caricamento pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11583/2906652