Comparison of three scattering models for ultrasound blood characterization - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control Année : 2013

Comparison of three scattering models for ultrasound blood characterization

Résumé

Ultrasonic backscattered signals from blood contain frequency-dependent information that can be used to obtain quantitative parameters reflecting the aggregation level of red blood cells (RBCs). The approach consists in estimating structural aggregate parameters by fitting the spectrum of the backscattered radio-frequency echoes from blood to an estimated spectrum considering a theoretical scattering model. In this study, three scattering models were examined: a new implementation of the Gaussian Model (GM), the Structure Factor Size Estimator (SFSE) and the new Effective Medium Theory combined with the Structure Factor Model (EMTSFM). The accuracy of the three scattering models in determining mean aggregate size and compactness was compared by two- and three-dimensional (2D and 3D) computer simulations where RBC structural parameters are controlled. Two clustering conditions were studied: (1) when the aggregate size varied and the aggregate compactness was fixed in both 2D and 3D cases, and (2) when the aggregate size was fixed and the aggregate compactness varied in the 2D case. For both clustering conditions, the EMTSFM was found more suitable than the GM and SFSE for characterizing RBC aggregation.
Fichier principal
Vignette du fichier
Franceschini_IEEE2013_VF.pdf (611.92 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-00908520 , version 1 (24-11-2013)

Identifiants

Citer

Emilie Franceschini, Ratan K Saha, Guy Cloutier. Comparison of three scattering models for ultrasound blood characterization. IEEE Transactions on Ultrasonics, Ferroelectrics and Frequency Control, 2013, 60 (11), pp.2321-2334. ⟨10.1109/TUFFC.2013.6644736⟩. ⟨hal-00908520⟩
105 Consultations
364 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More