969 resultados para 3D imaging


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A ray tracing based path length calculation is investigated for polarized light transport in a pixel space. Tomographic imaging using polarized light transport is promising for applications in optical projection tomography of small animal imaging and turbid media with low scattering. Polarized light transport through a medium can have complex effects due to interactions such as optical rotation of linearly polarized light, birefringence, diattenuation and interior refraction. Here we investigate the effects of refraction of polarized light in a non-scattering medium. This step is used to obtain the initial absorption estimate. This estimate can be used as prior in Monte Carlo (MC) program that simulates the transport of polarized light through a scattering medium to assist in faster convergence of the final estimate. The reflectance for p-polarized (parallel) and s-polarized (perpendicular) are different and hence there is a difference in the intensities that reach the detector end. The algorithm computes the length of the ray in each pixel along the refracted path and this is used to build the weight matrix. This weight matrix with corrected ray path length and the resultant intensity reaching the detector for each ray is used in the algebraic reconstruction (ART) method. The proposed method is tested with numerical phantoms for various noise levels. The refraction errors due to regions of different refractive index are discussed, the difference in intensities with polarization is considered. The improvements in reconstruction using the correction so applied is presented. This is achieved by tracking the path of the ray as well as the intensity of the ray as it traverses through the medium.

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Metastasis is clinically the most challenging and lethal aspect of breast cancer. While animal-based xenograft models are expensive and time-consuming, conventional two-dimensional (2D) cell culture systems fail to mimic in vivo signaling. In this study we have developed a three-dimensional (3D) scaffold system that better mimics the topography and mechanical properties of the breast tumor, thus recreating the tumor microenvironment in vitro to study breast cancer metastasis. Porous poly(e-caprolactone) (PCL) scaffolds of modulus 7.0 +/- 0.5 kPa, comparable to that of breast tumor tissue were fabricated, on which MDA-MB-231 cells proliferated forming tumoroids. A comparative gene expression analysis revealed that cells growing in the scaffolds expressed increased levels of genes implicated in the three major events of metastasis, viz., initiation, progression, and the site-specific colonization compared to cells grown in conventional 2D tissue culture polystyrene (TCPS) dishes. The cells cultured in scaffolds showed increased invasiveness and sphere efficiency in vitro and increased lung metastasis in vivo. A global gene expression analysis revealed a significant increase in the expression of genes involved in cell cell and cell matrix interactions and tissue remodeling, cancer inflammation, and the PI3K/Akt, Wnt, NF-kappaB, and HIFI signaling pathways all of which are implicated in metastasis. Thus, culturing breast cancer cells in 3D scaffolds that mimic the in vivo tumor-like microenvironment enhances their metastatic potential. This system could serve as a comprehensive in vitro model to investigate the manifold mechanisms of breast cancer metastasis.

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In an attempt to develop new coloured inorganic oxides, we have investigated the substitution of 3d transition-metal ions in LiMgBO3 host where Mg-II has a trigonal bipyramidal (TBP) oxygen coordination]. We find that single-phase materials are formed for (LiMg1-xCoxBO3)-B-II (0 < x 1.0), (LiMg1-xNixBO3)-B-II (0 < x 0.1), (LiMg1-xCuxBO3)-B-II (0 < x 0.1) and also (Li1-xMg1-xFexBO3)-B-III (0 < x 0.1) of which the Co-II and Ni-II derivatives are strongly coloured, purple-blue and beige-red, respectively, thus identifying TBP CoO5 and NiO5 as new chromophores for these colours.

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In the case of metallic ferromagnets there has always been a controversy, i.e. whether the magnetic interaction is itinerant or localized. For example SrRuO3 is known to be an itinerant ferromagnet where the spin-spin interaction is expected to be mean field in nature. However, it is reported to behave like Ising, Heisenberg or mean field by different groups. Despite several theoretical and experimental studies and the importance of strongly correlated systems, the experimental conclusion regarding the type of spin-spin interaction in SrRuO3 is lacking. To resolve this issue, we have investigated the critical behaviour in the vicinity of the paramagnetic-ferromagnetic phase transition using various techniques on polycrystalline as well as (001) oriented SrRuO3 films. Our analysis reveals that the application of a scaling law in the field-cooled magnetization data extracts the value of the critical exponent only when it is measured at H -> 0. To substantiate the actual nature without any ambiguity, the critical behavior is studied across the phase transition using the modified Arrott plot, Kouvel-Fisher plot and M-H isotherms. The critical analysis yields self-consistent beta, gamma and delta values and the spin interaction follows the long-range mean field model. Further the directional dependence of the critical exponent is studied in thin films and it reveals the isotropic nature. It is elucidated that the different experimental protocols followed by different groups are the reason for the ambiguity in determining the critical exponents in SrRuO3.

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The irradiation of selective regions in a polymer gel dosimeter results in an increase in optical density and refractive index (RI) at those regions. An optical tomography-based dosimeter depends on rayline path through the dosimeter to estimate and reconstruct the dose distribution. The refraction of light passing through a dose region results in artefacts in the reconstructed images. These refraction errors are dependant on the scanning geometry and collection optics. We developed a fully 3D image reconstruction algorithm, algebraic reconstruction technique-refraction correction (ART-rc) that corrects for the refractive index mismatches present in a gel dosimeter scanner not only at the boundary, but also for any rayline refraction due to multiple dose regions inside the dosimeter. In this study, simulation and experimental studies have been carried out to reconstruct a 3D dose volume using 2D CCD measurements taken for various views. The study also focuses on the effectiveness of using different refractive-index matching media surrounding the gel dosimeter. Since the optical density is assumed to be low for a dosimeter, the filtered backprojection is routinely used for reconstruction. We carry out the reconstructions using conventional algebraic reconstruction (ART) and refractive index corrected ART (ART-rc) algorithms. The reconstructions based on FDK algorithm for cone-beam tomography has also been carried out for comparison. Line scanners and point detectors, are used to obtain reconstructions plane by plane. The rays passing through dose region with a RI mismatch does not reach the detector in the same plane depending on the angle of incidence and RI. In the fully 3D scanning setup using 2D array detectors, light rays that undergo refraction are still collected and hence can still be accounted for in the reconstruction algorithm. It is found that, for the central region of the dosimeter, the usable radius using ART-rc algorithm with water as RI matched medium is 71.8%, an increase of 6.4% compared to that achieved using conventional ART algorithm. Smaller diameter dosimeters are scanned with dry air scanning by using a wide-angle lens that collects refracted light. The images reconstructed using cone beam geometry is seen to deteriorate in some planes as those regions are not scanned. Refraction correction is important and needs to be taken in to consideration to achieve quantitatively accurate dose reconstructions. Refraction modeling is crucial in array based scanners as it is not possible to identify refracted rays in the sinogram space.

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In the case of metallic ferromagnets there has always been a controversy, i.e. whether the magnetic interaction is itinerant or localized. For example SrRuO3 is known to be an itinerant ferromagnet where the spin-spin interaction is expected to be mean field in nature. However, it is reported to behave like Ising, Heisenberg or mean field by different groups. Despite several theoretical and experimental studies and the importance of strongly correlated systems, the experimental conclusion regarding the type of spin-spin interaction in SrRuO3 is lacking. To resolve this issue, we have investigated the critical behaviour in the vicinity of the paramagnetic-ferromagnetic phase transition using various techniques on polycrystalline as well as (001) oriented SrRuO3 films. Our analysis reveals that the application of a scaling law in the field-cooled magnetization data extracts the value of the critical exponent only when it is measured at H -> 0. To substantiate the actual nature without any ambiguity, the critical behavior is studied across the phase transition using the modified Arrott plot, Kouvel-Fisher plot and M-H isotherms. The critical analysis yields self-consistent beta, gamma and delta values and the spin interaction follows the long-range mean field model. Further the directional dependence of the critical exponent is studied in thin films and it reveals the isotropic nature. It is elucidated that the different experimental protocols followed by different groups are the reason for the ambiguity in determining the critical exponents in SrRuO3.

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In this article, a Field Programmable Gate Array (FPGA)-based hardware accelerator for 3D electromagnetic extraction, using Method of Moments (MoM) is presented. As the number of nets or ports in a system increases, leading to a corresponding increase in the number of right-hand-side (RHS) vectors, the computational cost for multiple matrix-vector products presents a time bottleneck in a linear-complexity fast solver framework. In this work, an FPGA-based hardware implementation is proposed toward a two-level parallelization scheme: (i) matrix level parallelization for single RHS and (ii) pipelining for multiple-RHS. The method is applied to accelerate electrostatic parasitic capacitance extraction of multiple nets in a Ball Grid Array (BGA) package. The acceleration is shown to be linearly scalable with FPGA resources and speed-ups over 10x against equivalent software implementation on a 2.4GHz Intel Core i5 processor is achieved using a Virtex-6 XC6VLX240T FPGA on Xilinx's ML605 board with the implemented design operating at 200MHz clock frequency. (c) 2016 Wiley Periodicals, Inc. Microwave Opt Technol Lett 58:776-783, 2016

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Imaging flow cytometry is an emerging technology that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy. It allows high-throughput imaging of cells with good spatial resolution, while they are in flow. This paper proposes a general framework for the processing/classification of cells imaged using imaging flow cytometer. Each cell is localized by finding an accurate cell contour. Then, features reflecting cell size, circularity and complexity are extracted for the classification using SVM. Unlike the conventional iterative, semi-automatic segmentation algorithms such as active contour, we propose a noniterative, fully automatic graph-based cell localization. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using custom fabricated cost-effective microfluidics-based imaging flow cytometer. The proposed system is a significant development in the direction of building a cost-effective cell analysis platform that would facilitate affordable mass screening camps looking cellular morphology for disease diagnosis. Lay description In this article, we propose a novel framework for processing the raw data generated using microfluidics based imaging flow cytometers. Microfluidics microscopy or microfluidics based imaging flow cytometry (mIFC) is a recent microscopy paradigm, that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy, which allows us imaging cells while they are in flow. In comparison to the conventional slide-based imaging systems, mIFC is a nascent technology enabling high throughput imaging of cells and is yet to take the form of a clinical diagnostic tool. The proposed framework process the raw data generated by the mIFC systems. The framework incorporates several steps: beginning from pre-processing of the raw video frames to enhance the contents of the cell, localising the cell by a novel, fully automatic, non-iterative graph based algorithm, extraction of different quantitative morphological parameters and subsequent classification of cells. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using cost-effective microfluidics based imaging flow cytometer. The cell lines of HL60, K562 and MOLT were obtained from ATCC (American Type Culture Collection) and are separately cultured in the lab. Thus, each culture contains cells from its own category alone and thereby provides the ground truth. Each cell is localised by finding a closed cell contour by defining a directed, weighted graph from the Canny edge images of the cell such that the closed contour lies along the shortest weighted path surrounding the centroid of the cell from a starting point on a good curve segment to an immediate endpoint. Once the cell is localised, morphological features reflecting size, shape and complexity of the cells are extracted and used to develop a support vector machine based classification system. We could classify the cell-lines with good accuracy and the results were quite consistent across different cross validation experiments. We hope that imaging flow cytometers equipped with the proposed framework for image processing would enable cost-effective, automated and reliable disease screening in over-loaded facilities, which cannot afford to hire skilled personnel in large numbers. Such platforms would potentially facilitate screening camps in low income group countries; thereby transforming the current health care paradigms by enabling rapid, automated diagnosis for diseases like cancer.

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Graphene oxide-CoFe2O4 nanoparticle composites were synthesized using a two step synthesis method in which graphene oxide was initially synthesized followed by precipitation of CoFe2O4 nanoparticles in a reaction mixture containing graphene oxide. Samples were extracted from the reaction mixture at different times at 80 degrees C. All the extracted samples contained CoFe2O4 nanoparticles formed over the graphene oxide. It was observed that the increase in the reflux time significantly increased the saturation magnetization value for the superparamagnetic nanoparticles in the composite. It was also noticed that the size of the nanoparticles increased with increase in the reflux time. Transverse relaxivity of the water protons increased monotonically with increase in the reflux time. Whereas, the longitudinal relaxivity value initially increased and then decreased with the reflux time. Graphene oxide-CoFe2O4 nanoparticle composites also exhibit biocompatibility towards the MCF-7 cell line.

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Biomolecular structure elucidation is one of the major techniques for studying the basic processes of life. These processes get modulated, hindered or altered due to various causes like diseases, which is why biomolecular analysis and imaging play an important role in diagnosis, treatment prognosis and monitoring. Vibrational spectroscopy (IR and Raman), which is a molecular bond specific technique, can assist the researcher in chemical structure interpretation. Based on the combination with microscopy, vibrational microspectroscopy is currently emerging as an important tool for biomedical research, with a spatial resolution at the cellular and sub-cellular level. These techniques offer various advantages, enabling label-free, biomolecular fingerprinting in the native state. However, the complexity involved in deciphering the required information from a spectrum hampered their entry into the clinic. Today with the advent of automated algorithms, vibrational microspectroscopy excels in the field of spectropathology. However, researchers should be aware of how quantification based on absolute band intensities may be affected by instrumental parameters, sample thickness, water content, substrate backgrounds and other possible artefacts. In this review these practical issues and their effects on the quantification of biomolecules will be discussed in detail. In many cases ratiometric analysis can help to circumvent these problems and enable the quantitative study of biological samples, including ratiometric imaging in 1D, 2D and 3D. We provide an extensive overview from the recent scientific literature on IR and Raman band ratios used for studying biological systems and for disease diagnosis and treatment prognosis.

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We report a facile synthesis of three-dimensional (3D) nanodendrites of Pd nanoparticles (NPs) and nitrogen-doped carbon NPs (N-CNPs) by electroless deposition of Pd2+ ions. N-CNPs being an electron-enriched material act as a reducing agent. Moreover, the availability of a variety of nitrogen species in N-CNPs promotes the open arm structure as well as stabilizes the oriented 3D assembly of primary Pd NPs. The dendrites exhibit superior catalytic activity for methanol (0.5 M) oxidation in alkaline media (1 M NaOH) which is ascribed to the large electrochemical active surface area and the enhanced mass activity with repeated use. Further mass activity improvement has been realized after acid-treatment of dendrites which is attributed to the increment in the -OH group. The dendrites show higher mass activity (J(f) similar to 653 A g(-1)) in comparison with a commercial Pt-carbon/Pd-carbon (Pt-C/Pd-C) catalyst (J(f) similar to 46 and 163 A g(-1), respectively), better operational stability, superior CO tolerance with I-f/I-b (similar to 3.7) over a commercial Pt-C/Pd-C catalyst (I-f/I-b similar to 1.6 and 1.75, respectively) and may serve as a promising alternative to commercial Pt-C catalysts for anode application in alkaline fuel cells. To ensure the adaptability of our 3D-nanodendrites for other catalytic activities, we studied 4-nitrophenol reduction at room temperature. The 3D-nanodendrites show excellent catalytic activity toward 4-nitrophenol reduction, as well.

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Graphene-based polymer nanocomposites are being studied for biomedical applications. Polymer nanocomposites can be processed differently to generate planar two-dimensional (2D) substrates and porous three-dimensional (3D) scaffolds. The objective of this work was to investigate potential differences in biological response to graphene in polymer composites in the form of 2D substrates and 3D scaffolds. Polycaprolactone (PCL) nanocomposites were prepared by incorporating 1% of graphene oxide (GO) and reduced graphene oxide (RGO). GO increased modulus and strength of PCL by 44 and 22% respectively, whereas RGO increased modulus and strength by 22 and 16%, respectively. RGO increased the water contact angle of PCL from 81 degrees to 87 degrees whereas GO decreased it to 77 degrees. In 2D, osteoblast proliferated 15% more on GO composites than on PCL whereas RGO composite showed 17% decrease in cell proliferation, which may be attributed to differences in water wettability. In 3D, initial cell proliferation was markedly retarded in both GO (36% lower) and RGO (55% lower) composites owing to increased roughness due to the presence of the protruding nanoparticles. Cells organized into aggregates in 3D in contrast to spread and randomly distributed cells on 2D discs due to the macro-porous architecture of the scaffolds. Increased cell-cell contact and altered cellular morphology led to significantly higher mineralization in 3D. This study demonstrates that the cellular response to nanoparticles in composites can change markedly by varying the processing route and has implications for designing orthopedic implants such as resorbable fracture fixation devices and tissue scaffolds using such nanocomposites. (c) 2015 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 104B: 732-749, 2016.

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3D porous membranes were developed by etching one of the phases (here PEO, polyethylene oxide) from melt-mixed PE/PEO binary blends. Herein, we have systematically discussed the development of these membranes using X-ray micro-computed tomography. The 3D tomograms of the extruded strands and hot-pressed samples revealed a clear picture as to how the morphology develops and coarsens over a function of time during post-processing operations like compression molding. The coarsening of PE/PEO blends was traced using X-ray micro-computed tomography and scanning electron microscopy (SEM) of annealed blends at different times. It is now understood from X-ray micro-computed tomography that by the addition of a compatibilizer (here lightly maleated PE), a stable morphology can be visualized in 3D. In order to anchor biocidal graphene oxide sheets onto these 3D porous membranes, the PE membranes were chemically modified with acid/ethylene diamine treatment to anchor the GO sheets which were further confirmed by Fourier transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS) and surface Raman mapping. The transport properties through the membrane clearly reveal unimpeded permeation of water which suggests that anchoring GO on to the membranes does not clog the pores. Antibacterial studies through the direct contact of bacteria with GO anchored PE membranes resulted in 99% of bacterial inactivation. The possible bacterial inactivation through physical disruption of the bacterial cell wall and/or reactive oxygen species (ROS) is discussed herein. Thus this study opens new avenues in designing polyolefin based antibacterial 3D porous membranes for water purification.

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The boundary knot method (BKM) of very recent origin is an inherently meshless, integration-free, boundary-type, radial basis function collocation technique for the numerical discretization of general partial differential equation systems. Unlike the method of fundamental solutions, the use of non-singular general solution in the BKM avoids the unnecessary requirement of constructing a controversial artificial boundary outside the physical domain. The purpose of this paper is to extend the BKM to solve 2D Helmholtz and convection-diffusion problems under rather complicated irregular geometry. The method is also first applied to 3D problems. Numerical experiments validate that the BKM can produce highly accurate solutions using a relatively small number of knots. For inhomogeneous cases, some inner knots are found necessary to guarantee accuracy and stability. The stability and convergence of the BKM are numerically illustrated and the completeness issue is also discussed.

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Displacement estimation is a key step in the evaluation of tissue elasticity by quasistatic strain imaging. An efficient approach may incorporate a tracking strategy whereby each estimate is initially obtained from its neighbours' displacements and then refined through a localized search. This increases the accuracy and reduces the computational expense compared with exhaustive search. However, simple tracking strategies fail when the target displacement map exhibits complex structure. For example, there may be discontinuities and regions of indeterminate displacement caused by decorrelation between the pre- and post-deformation radio frequency (RF) echo signals. This paper introduces a novel displacement tracking algorithm, with a search strategy guided by a data quality indicator. Comparisons with existing methods show that the proposed algorithm is more robust when the displacement distribution is challenging.