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Your search keyword '"Mohanty, Kaustav"' showing total 23 results
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23 results on '"Mohanty, Kaustav"'

1. Predicting Structural Properties of Cortical Bone by Combining Ultrasonic Attenuation and an Artificial Neural Network (ANN): 2-D FDTD Study

Author

Mohanty, Kaustav, Yousefian, Omid, Karbalaeisadegh, Yasamin, Ulrich, Micah, Muller, Marie, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Karray, Fakhri, editor, Campilho, Aurélio, editor, and Yu, Alfred, editor

Published
2019
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4. Characterization of porous media using Singular Value Distribution (SVD), application to cortical bone - A phantom-based study

Author

Yousefian, Omid, Karbalaeisadegh, Yasamin, Mohanty, Kaustav, Muller, Marie, North Carolina State University [Raleigh] (NC State), University of North Carolina System (UNC), Nutrition-Génétique et Exposition aux Risques Environnementaux (NGERE), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Service d'Hépato-gastro-entérologie [CHRU Nancy], and Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy)

Subjects
[PHYS.MECA.VIBR]Physics [physics]/Mechanics [physics]/Vibrations [physics.class-ph], Backscatter, Porous media, Cortical porosity, Singular Value Decomposition, [PHYS.MECA.ACOU]Physics [physics]/Mechanics [physics]/Acoustics [physics.class-ph]
Abstract

International audience; We use singular value decomposition (SVD) of backscattered signals to detect micro-structural changes in porous media . SVD is estimated using a Probability Density Function (PDF) of which two parameters are studied: Maximum singular value (𝜆max) and Expected singular value E(X). In order to see how 𝜆max and E(X) change with changes in the micro-structure, we generated numerical structures consisting of solid scatterers randomly distributed within a fluid phase with 5 different area fractions. For each structure, the distribution of singular values is evaluated and the behaviour of 𝜆max and E(X) as a function of porosity is studied. The results indicate that as the pore area fraction increases 𝜆max and E(X) start by decreasing and increasing respectively until they both reach a plateau at 20% porosity. Then we demonstrate the applicability of this technique to differentiate between low and high porosity Gelatin-Glass Beads phantoms mimicking highly scattering media at 5 and 8 MHz frequency using multi-element linear array transducers. The results show that at 5MHz, both 𝜆max and E(X) are capable of differentiating between low and high porosities. However in the 8 MHz range (kϕ>5) the difference may not be significant. Finally we examine whether this method is applicable in weakly scattering media. Phantoms including Barium-Titanate particles inside a PDMS matrix are made at 3-25% mass ratios. We investigate how 𝜆max varies as the speed of sound changes in the phantoms. The result show that 𝜆max can be used to differentiate between media when there is a significant difference (p

Published
2020
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22. Microstructural characterization of trabecular bone using ultrasonic backscattering and diffusion parameters.

Author

Hualong Du, Mohanty, Kaustav, and Muller, Marie

Subjects
*CANCELLOUS bone, *ULTRASONIC imaging, *DIFFUSION, *ANISOTROPY, *BACKSCATTERING, *MICROSTRUCTURE, *COMPUTED tomography
Abstract

Finite differences time domain methods were utilized to simulate ultrasound propagation and scattering in anisotropic trabecular bone structures obtained from high resolution Computed Tomography (CT). The backscattered signals were collected and the incoherent contribution was extracted. The diffusion constant was calculated for propagations along and across the main direction of anisotropy, and was used to characterize the anisotropy of the trabecular microstructures. In anisotropic structures, the diffusion constant was significantly different in both directions, and the anisotropy of the diffusion constant was strongly correlated to the structural anisotropy measured on the CT images. These results indicate that metrics based on diffusion can be used to quantify the anisotropy of complex structures such as trabecular bone. [ABSTRACT FROM AUTHOR]

Published
2017
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