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1.
Sci Rep ; 14(1): 15560, 2024 Jul 06.
Artigo em Inglês | MEDLINE | ID: mdl-38969673

RESUMO

Plastic foams, near-ubiquitous in everyday life and industry, show properties that depend primarily on density. Density measurement, although straightforward in principle, is not always easy. As such, while several methods are available, plastic foam industry is not yet supported with a standard technique that effectively enables to control density maps. To overcome this issue, this paper proposes Terahertz (THz) time-of-flight imaging using normal reflection measurements as a fast, relatively cheap, contactless, non-destructive and non-dangerous way to map plastic foam density, based on the expected relationship between density and refractive index. The approach is demonstrated in the case of polypropylene foams. First, the relationship between the estimated effective refractive index and the polypropylene foam density is derived by characterizing a set of carefully crafted samples having uniform density in the range 70-900 kg/m3. The obtained calibration curve subtends a linear relationship between the density and the refractive index in the range of interest. This relationship is validated against a set of test samples, whose estimated average densities are consistent with the nominal ones, with an absolute error lower than 10 kg/m3 and a percentage error on the estimate of 5%. Exploiting the calibration curve, it is possible to build quantitative images depicting the spatial distribution of the sample density. THz images are able to reveal the non-uniform density distribution of some samples, which cannot be appreciated from visual inspection. Finally, the complex spatial density pattern of a graded foam sample is characterized and quantitatively compared with the density map obtained via X-ray microscopy. The comparison confirms that the proposed THz approach successfully determines the density pattern with an accuracy and a spatial scale variability compliant with those commonly required for plastic foam density estimate.

2.
Sensors (Basel) ; 24(14)2024 Jul 11.
Artigo em Inglês | MEDLINE | ID: mdl-39065893

RESUMO

We propose an artificial intelligence approach based on deep neural networks to tackle a canonical 2D scalar inverse source problem. The learned singular value decomposition (L-SVD) based on hybrid autoencoding is considered. We compare the reconstruction performance of L-SVD to the Truncated SVD (TSVD) regularized inversion, which is a canonical regularization scheme, to solve an ill-posed linear inverse problem. Numerical tests referring to far-field acquisitions show that L-SVD provides, with proper training on a well-organized dataset, superior performance in terms of reconstruction errors as compared to TSVD, allowing for the retrieval of faster spatial variations of the source. Indeed, L-SVD accommodates a priori information on the set of relevant unknown current distributions. Different from TSVD, which performs linear processing on a linear problem, L-SVD operates non-linearly on the data. A numerical analysis also underlines how the performance of the L-SVD degrades when the unknown source does not match the training dataset.

3.
Sensors (Basel) ; 24(10)2024 May 20.
Artigo em Inglês | MEDLINE | ID: mdl-38794097

RESUMO

The paper deals with a combined time-depth conversion strategy able to improve the reconstruction of voids embedded in an opaque medium, such as cavities, caves, empty hypogeal rooms, and similar targets. The combined time-depth conversion accounts for the propagation velocity of the electromagnetic waves both in free space and in the embedding medium, and it allows better imaging and interpretation of the underground scenario. To assess the strategy's effectiveness, ground penetrating radar (GPR) data referred to as an experimental test in controlled conditions are accounted for and processed by two different approaches to achieve focused images of the scenario under test. The first approach is based on a classical migration algorithm, while the second one faces the imaging as a linear inverse scattering approach. The results corroborate that the combined time-depth conversion improves the imaging in both cases.

4.
IEEE Trans Biomed Eng ; 69(6): 2029-2040, 2022 06.
Artigo em Inglês | MEDLINE | ID: mdl-34882544

RESUMO

Magnetic scaffolds have been investigated as promising tools for the interstitial hyperthermia treatment of bone cancers, to control local recurrence by enhancing radio- and chemotherapy effectiveness. The potential of magnetic scaffolds motivates the development of production strategies enabling tunability of the resulting magnetic properties. Within this framework, deposition and drop-casting of magnetic nanoparticles on suitable scaffolds offer advantages such as ease of production and high loading, although these approaches are often associated with a non-uniform final spatial distribution of nanoparticles in the biomaterial. The implications and the influences of nanoparticle distribution on the final therapeutic application have not yet been investigated thoroughly. In this work, poly-caprolactone scaffolds are magnetized by loading them with synthetic magnetic nanoparticles through a drop-casting deposition and tuned to obtain different distributions of magnetic nanoparticles in the biomaterial. The physicochemical properties of the magnetic scaffolds are analyzed. The microstructure and the morphological alterations due to the reworked drop-casting process are evaluated and correlated to static magnetic measurements. THz tomography is used as an innovative investigation technique to derive the spatial distribution of nanoparticles. Finally, multiphysics simulations are used to investigate the influence on the loading patterns on the interstitial bone tumor hyperthermia treatment.


Assuntos
Neoplasias Ósseas , Alicerces Teciduais , Materiais Biocompatíveis/química , Neoplasias Ósseas/diagnóstico por imagem , Neoplasias Ósseas/terapia , Humanos , Fenômenos Magnéticos , Magnetismo , Engenharia Tecidual/métodos , Alicerces Teciduais/química
5.
IEEE Trans Biomed Eng ; 61(4): 1071-9, 2014 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-24658232

RESUMO

Magnetic nanoparticles-enhanced microwave imaging has been recently proposed to overcome the limitations of conventional microwave imaging methods for breast cancer monitoring. In this paper, we discuss how to tackle the linear inverse scattering problem underlying this novel technique in an effective way. In particular, our aim is to minimize the required a priori patient-specific information, avoid occurrence of false positives, and keep the computational burden low. By relying on an extensive numerical analysis in realistic conditions, we show that the method can provide accurate and reliable images without information on the inner structure of the inspected breast and with an only rough knowledge of its shape. Notably, this allows moving to an offline stage the computationally intensive part of the image formation procedure. In addition, we show how to appraise the total amount of magnetic contrast agent targeted in the tumor.


Assuntos
Neoplasias da Mama/patologia , Meios de Contraste/química , Diagnóstico por Imagem/métodos , Nanopartículas de Magnetita , Micro-Ondas , Mama/patologia , Feminino , Humanos , Processamento de Imagem Assistida por Computador , Modelos Biológicos , Imagens de Fantasmas
6.
IEEE Trans Biomed Eng ; 58(9): 2528-36, 2011 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-21642036

RESUMO

In this paper, a microwave technique for breast cancer imaging is presented. The approach is based on the use of magnetic nanoparticles as contrast agent to induce a nonnull magnetic contrast selectively localized within the tumor. This allows us to face cancer imaging as the reconstruction of a magnetic contrast from the corresponding scattered field. To extract, from the measured data the contribution due to the magnetic contrast, i.e., the signal meaningful for cancer imaging, the approach exploits the possibility of modulating the magnetic response of magnetic nanoparticles by means of a polarizing magnetic field. The achievable reconstruction capabilities and the robustness against uncertainties on the electric features of the surrounding electric scenario are assessed by means of numerical examples.


Assuntos
Neoplasias da Mama/diagnóstico , Meios de Contraste , Diagnóstico por Imagem/métodos , Nanopartículas de Magnetita , Micro-Ondas , Algoritmos , Neoplasias da Mama/patologia , Feminino , Humanos , Processamento de Imagem Assistida por Computador , Campos Magnéticos , Imagens de Fantasmas , Processamento de Sinais Assistido por Computador
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