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Humanos , Masculino , Femenino , Oftalmología , Biometría/métodos , Visión Ocular , Pruebas de Visión , Imagen Óptica , CatarataRESUMEN
Purpose: To compare the reliability and agreement of axial length (AL), anterior chamber depth (ACD), and lens thickness (LT) measurements obtained with optical biometry based on swept-source optical coherence tomography (IOLMaster 700; Carl Zeiss, Germany) and an ultrasound biometry device (Nidek; US-4000 Echoscan, Japan) in different qualities of AL measurement. Methods: A total of 239 consecutive eyes of 239 cataract surgery candidates with a mean age of 56 ± 14 years were included. The quality measurements were grouped according to the quartiles of SD of the measured AL by IOLMaster 700. The first and fourth quartile's SD are defined as high and low-quality measurement, respectively, and the second and third quartiles SD is defined as moderate-quality. Results: The reliability of AL and ACD between the two devices in all patients and in different quality measurement groups was excellent with highly statistically significant (AL: all ICC=0.999 and P<0.001, ACD: all ICC>0.920 and P<0.001). AL and ACD in all quality measurements showed a very strong correlation between devices with highly statistically significant. However, there was poor (ICC=0.305), moderate (ICC=0.742), and good (ICC=0.843) reliability in measuring LT in low-, moderate-, and high-quality measurements, respectively. LT showed a very strong correlation (r = 0.854) with highly statistically significant (P<0.001) between devices only in patients with high-quality measurements. Conclusions: AL and ACD of the IOLMaster700 had outstanding agreements with the US-4000 ultrasound in different quality measurements of AL and can be used interchangeably. But LT should be used interchangeably cautiously only in the high-quality measurements group. (AU)
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Humanos , Adulto , Persona de Mediana Edad , Anciano , Identificación Biométrica , Longitud Axial del Ojo , Extracción de Catarata , Biometría/métodos , Reproducibilidad de los ResultadosRESUMEN
This research aims to investigate a ternary nanocomposite based on High Density Polyethylene/ Bismuth Oxide/Graphene Oxide (HDPE/Bi2O3/GO) at various concentrations. Solution method was used to fabricate the samples. FESEM-EDX mapping, AFM, TEM, XRD, XPS, FTIR, and TGA/DTG analyses were carried out on the samples. XRD analysis demonstrated a semi-crystalline behavior for the samples. TEM analysis exhibited a cauliflower-like structure of the material. The sample was irradiated by gamma-rays of 60Co source over the dose rate of 30-254 mGy/min and the electric current was measured as the response of the real-time dosimeter. Thus, various dosimetric characteristics were performed, namely linearity, angular dependence, energy dependence, bias-polarity, field size, and repeatability of the data. Results showed that response of the dosimeter was linear in the range of the investigated dose rate. The sensitivity of the 60 wt% Bi2O3 sample was measured as 3.4 nC·mGy-1. The angular response variation was 20% for normal beam incidence. The response of the dosimeter to assess the energy dependency was obtained as 2.2% at the radiation field of the 137Cs and 60Co beams. The dosimeter response was dependent on the bias-polarity, with maximum discrepancy of 11.1%. The dosimetry response was highly dependent upon the radiation field size. The repeatability of the dosimeter response was measured with standard deviation less than 1%. As well, the dosimeter response during the one-hour irradiation was stable with a standard deviation of 0.66%. Results showed that considering some correction factors, this material can be used for dosimetry of gamma-rays at the therapy level.
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Nanocompuestos , Polietileno , Radiometría/métodosRESUMEN
Exposure buildup factor values of tungsten for a point isotropic source in energy range 0.05-15 MeV up to 15 mfp are computed using Monte Carlo N-Particle code. Buildup factors of this study and ANSI/ANS-6.4.3 at some selected energies and penetration depths are compared. Highest discrepancies are observed for high-energy and/or high penetration depths. Highest error occurs at 15 MeV, amounting to 32%. In the energy range 2-6 MeV, our results show smaller values for all penetration depths and vice versa at higher energies.
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Liver-shape analysis and quantification is still an open research subject. Quantitative assessment of the liver is of clinical importance in various procedures such as diagnosis, treatment planning, and monitoring. Liver-shape classification is of clinical importance for corresponding intra-subject and inter-subject studies. In this research, we propose a novel technique for the liver-shape classification based on Spherical Harmonics (SH) coefficients. The proposed liver-shape classification algorithm consists of the following steps: (a) Preprocessing, including mesh generation and simplification, point-set matching, and surface to template alignment; (b) Liver-shape parameterization, including surface normalization, SH expansion followed by parameter space registration; (c) Feature selection and classification, including frequency based feature selection, feature space reduction by Principal Component Analysis (PCA), and classification. The above multi-step approach is novel in the sense that registration and feature selection for liver-shape classification is proposed and implemented and validated for the normal and diseases liver in the SH domain. Various groups of SH features after applying conventional PCA and/or ordered by p-value PCA are employed in two classifiers including Support Vector Machine (SVM) and k-Nearest Neighbor (k-NN) in the presence of 101 liver data sets. Results show that the proposed specific features combined with classifiers outperform existing liver-shape classification techniques that employ liver surface information in the spatial domain. In the available data sets, the proposed method can successful classify normal and diseased livers with a correct classification rate of above 90 %. The performed result in average is higher than conventional liver-shape classification method. Several standard metrics such as Leave-one-out cross-validation and Receiver Operating Characteristic (ROC) analysis are employed in the experiments and confirm the effectiveness of the proposed liver-shape classification with respect to conventional techniques.
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Hepatopatías/clasificación , Hepatopatías/diagnóstico , Hígado/anatomía & histología , Hígado/diagnóstico por imagen , Reconocimiento de Normas Patrones Automatizadas/métodos , Interpretación de Imagen Radiográfica Asistida por Computador/estadística & datos numéricos , Algoritmos , Inteligencia Artificial , Humanos , Imagenología Tridimensional/métodos , Análisis de Componente Principal , Curva ROCRESUMEN
A computational framework is presented, based on statistical shape modelling, for construction of race-specific organ models for internal radionuclide dosimetry and other nuclear-medicine applications. This approach was applied to the construction of a Japanese liver phantom, using the liver of the digital Zubal phantom as the template and 35 liver computed tomography (CT) scans of male Japanese individuals as a training set. The first step was the automated object-space registration (to align all the liver surfaces in one orientation), using a coherent-point-drift maximum-likelihood alignment algorithm, of each CT scan-derived manually contoured liver surface and the template Zubal liver phantom. Six landmark points, corresponding to the intersection of the contours of the maximum-area sagittal, transaxial and coronal liver sections were employed to perform the above task. To find correspondence points in livers (i.e. 2000 points for each liver), each liver surface was transformed into a mesh, was mapped for the parameter space of a sphere (parameterisation), yielding spherical harmonics (SPHARMs) shape descriptors. The resulting spherical transforms were then registered by minimising the root-mean-square distance among the SPHARMs coefficients. A mean shape (i.e. liver) and its dispersion (i.e. covariance matrix) were next calculated and analysed by principal components. Leave-one-out-tests using 5-35 principal components (or modes) demonstrated the fidelity of the foregoing statistical analysis. Finally, a voxelisation algorithm and a point-based registration is utilised to convert the SPHARM surfaces into its corresponding voxelised and adjusted the Zubal phantom data, respectively. The proposed technique used to create the race-specific statistical phantom maintains anatomic realism and provides the statistical parameters for application to radionuclide dosimetry.