Cooking Methods for a Soft Diet Using Chicken Based on Food Texture Analysis.

Science.gov (United States)

Watanabe, Emi; Maeno, Masami; Kayashita, Jun; Miyamoto, Ken-Ichi; Kogirima, Miho

2017-01-01

Undernutrition caused by difficulties in masticating is of growing concern among the elderly. Soft diets are often served at nursing homes; however, the styles differ with nursing homes. Improperly modified food texture and consistency may lead to further loss of nutritive value. Therefore, we developed a method to produce a soft diet using chicken. The texture-modified chicken was prepared by boiling a mixture of minced chicken and additive foodstuff that softened the meat. The best food additive was determined through testing cooking process, size after modification and texture. The optimum proportions of each component in the mixture were determined measuring food texture using a creep meter. Teriyaki chicken was cooked using the texture-modified chicken, and provided to a nursing home. The amount of food intake by elderly residents was subsequently surveyed. This study involved 22 residents (1 man and 21 women; mean age 91.4±5.3 y). Consequently, yakifu, which was made from wheat gluten, was the most suitable additive foodstuff. The hardness of the texture-modified chicken, with proportions of minced chicken, yakifu, and water being 50%, 10%, and 40% respectively, was under 40,000 N/m 2 . The intake amount of the texture-modified chicken of subjects whose intake amount of conventional chicken using chicken thigh was not 100% was significantly higher. These findings suggest that properly modified food textures could contribute to improve the quality of meals by preventing undernutrition among the elderly with mastication difficulties.

A Spectral-Texture Kernel-Based Classification Method for Hyperspectral Images

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Yi Wang

2016-11-01

Full Text Available Classification of hyperspectral images always suffers from high dimensionality and very limited labeled samples. Recently, the spectral-spatial classification has attracted considerable attention and can achieve higher classification accuracy and smoother classification maps. In this paper, a novel spectral-spatial classification method for hyperspectral images by using kernel methods is investigated. For a given hyperspectral image, the principle component analysis (PCA transform is first performed. Then, the first principle component of the input image is segmented into non-overlapping homogeneous regions by using the entropy rate superpixel (ERS algorithm. Next, the local spectral histogram model is applied to each homogeneous region to obtain the corresponding texture features. Because this step is performed within each homogenous region, instead of within a fixed-size image window, the obtained local texture features in the image are more accurate, which can effectively benefit the improvement of classification accuracy. In the following step, a contextual spectral-texture kernel is constructed by combining spectral information in the image and the extracted texture information using the linearity property of the kernel methods. Finally, the classification map is achieved by the support vector machines (SVM classifier using the proposed spectral-texture kernel. Experiments on two benchmark airborne hyperspectral datasets demonstrate that our method can effectively improve classification accuracies, even though only a very limited training sample is available. Specifically, our method can achieve from 8.26% to 15.1% higher in terms of overall accuracy than the traditional SVM classifier. The performance of our method was further compared to several state-of-the-art classification methods of hyperspectral images using objective quantitative measures and a visual qualitative evaluation.

Application of texture analysis method for classification of benign and malignant thyroid nodules in ultrasound images.

Science.gov (United States)

Abbasian Ardakani, Ali; Gharbali, Akbar; Mohammadi, Afshin

2015-01-01

The aim of this study was to evaluate computer aided diagnosis (CAD) system with texture analysis (TA) to improve radiologists' accuracy in identification of thyroid nodules as malignant or benign. A total of 70 cases (26 benign and 44 malignant) were analyzed in this study. We extracted up to 270 statistical texture features as a descriptor for each selected region of interests (ROIs) in three normalization schemes (default, 3s and 1%-99%). Then features by the lowest probability of classification error and average correlation coefficients (POE+ACC), and Fisher coefficient (Fisher) eliminated to 10 best and most effective features. These features were analyzed under standard and nonstandard states. For TA of the thyroid nodules, Principle Component Analysis (PCA), Linear Discriminant Analysis (LDA) and Non-Linear Discriminant Analysis (NDA) were applied. First Nearest-Neighbour (1-NN) classifier was performed for the features resulting from PCA and LDA. NDA features were classified by artificial neural network (A-NN). Receiver operating characteristic (ROC) curve analysis was used for examining the performance of TA methods. The best results were driven in 1-99% normalization with features extracted by POE+ACC algorithm and analyzed by NDA with the area under the ROC curve ( Az) of 0.9722 which correspond to sensitivity of 94.45%, specificity of 100%, and accuracy of 97.14%. Our results indicate that TA is a reliable method, can provide useful information help radiologist in detection and classification of benign and malignant thyroid nodules.

Evaluation of color representation for texture analysis

NARCIS (Netherlands)

Verbrugge, R.; van den Broek, Egon; van Rikxoort, E.M.; Taatgen, N.; Schomaker, L.

2004-01-01

Since more than 50 years texture in image material is a topic of research. Hereby, color was ignored mostly. This study compares 70 different configurations for texture analysis, using four features. For the configurations we used: (i) a gray value texture descriptor: the co-occurrence matrix and a

Anorexia Nervosa: Analysis of Trabecular Texture with CT.

Science.gov (United States)

Tabari, Azadeh; Torriani, Martin; Miller, Karen K; Klibanski, Anne; Kalra, Mannudeep K; Bredella, Miriam A

2017-04-01

Purpose To determine indexes of skeletal integrity by using computed tomographic (CT) trabecular texture analysis of the lumbar spine in patients with anorexia nervosa and normal-weight control subjects and to determine body composition predictors of trabecular texture. Materials and Methods This cross-sectional study was approved by the institutional review board and compliant with HIPAA. Written informed consent was obtained. The study included 30 women with anorexia nervosa (mean age ± standard deviation, 26 years ± 6) and 30 normal-weight age-matched women (control group). All participants underwent low-dose single-section quantitative CT of the L4 vertebral body with use of a calibration phantom. Trabecular texture analysis was performed by using software. Skewness (asymmetry of gray-level pixel distribution), kurtosis (pointiness of pixel distribution), entropy (inhomogeneity of pixel distribution), and mean value of positive pixels (MPP) were assessed. Bone mineral density and abdominal fat and paraspinal muscle areas were quantified with quantitative CT. Women with anorexia nervosa and normal-weight control subjects were compared by using the Student t test. Linear regression analyses were performed to determine associations between trabecular texture and body composition. Results Women with anorexia nervosa had higher skewness and kurtosis, lower MPP (P anorexia nervosa. Conclusion Patients with anorexia nervosa had increased skewness and kurtosis and decreased entropy and MPP compared with normal-weight control subjects. These parameters were associated with lowest lifetime weight and duration of amenorrhea, but there were no such associations with bone mineral density. These findings suggest that trabecular texture analysis might contribute information about bone health in anorexia nervosa that is independent of that provided with bone mineral density. © RSNA, 2016.

Texture, residual stress and structural analysis of thin films using a combined X-ray analysis

International Nuclear Information System (INIS)

Lutterotti, L.; Chateigner, D.; Ferrari, S.; Ricote, J.

2004-01-01

Advanced thin films for today's industrial and research needs require highly specialized methodologies for a successful quantitative characterization. In particular, in the case of multilayer and/or unknown phases a global approach is necessary to obtain some or all the required information. A full approach has been developed integrating novel texture and residual stress methodologies with the Rietveld method (Acta Cryst. 22 (1967) 151) (for crystal structure analysis) and it has been coupled with the reflectivity analysis. The complete analysis can be done at once and offers several benefits: the thicknesses obtained from reflectivity can be used to correct the diffraction spectra, the phase analysis help to identify the layers and to determine the electron density profile for reflectivity; quantitative texture is needed for quantitative phase and residual stress analyses; crystal structure determination benefits of the previous. To achieve this result, it was necessary to develop some new methods, especially for texture and residual stresses. So it was possible to integrate them in the Rietveld, full profile fitting of the patterns. The measurement of these spectra required a special reflectometer/diffractometer that combines a thin parallel beam (for reflectivity) and a texture/stress goniometer with a curved large position sensitive detector. This new diffraction/reflectivity X-ray machine has been used to test the combined approach. Several spectra and the reflectivity patterns have been collected at different tilting angles and processed at once by the special software incorporating the aforementioned methodologies. Some analysis examples will be given to show the possibilities offered by the method

Quantitative phase analysis of a highly textured industrial sample using a Rietveld profile analysis

International Nuclear Information System (INIS)

Shin, Eunjoo; Huh, Moo-Young; Seong, Baek-Seok; Lee, Chang-Hee

2001-01-01

For the quantitative phase analysis on highly textured two-phase materials, samples with known weight fractions of zirconium and aluminum were prepared. Strong texture components prevailed in both zirconium and aluminum sheet. The diffraction patterns of samples were measured by the neutron and refined by the Rietveld method. The preferred orientation correction of diffraction patterns was carried out by means of recalculated pole figures from the ODF. The present Rietveld analysis of various samples with different weight fractions showed that the absolute error of the calculated weight fractions was less than 7.1%. (author)

Digitisation of films and texture analysis for digital classification of pulmonary opacities

International Nuclear Information System (INIS)

Desaga, J.F.; Dengler, J.; Wolf, T.; Engelmann, U.; Scheppelmann, D.; Meinzer, H.P.

1988-01-01

The study aimed at evaluating the effect of different methods of digitisation of radiographic films on the digital classification of pulmonary opacities. Test sets from the standard of the International Labour Office (ILO) Classification of Radiographs of Pneumoconiosis were prepared by film digitsation using a scanning microdensitometer or a video digitiser based on a personal computer equipped with a real time digitiser board and a vidicon or a Charge Coupled Device (CCD) camera. Seven different algorithms were used for texture analysis resulting in 16 texture parameters for each region. All methods used for texture analysis were independent of the mean grey value level and the size of the image analysed. Classification was performed by discriminant analysis using the classes from the ILO classification. A hit ratio of at least 85% was achieved for a digitisation by scanner digitisation or the vidicon, while the corresponding results of the CCD camera were significantly less good. Classification by texture analysis of opacities of chest X-rays of pneumoconiosis digitised by a personal computer based video digitiser and a vidicon are of equal quality compared to digitisation by a scanning microdensitometer. Correct classification of 90% was achieved via the described statistical approach. (orig.) [de

3D Texture Analysis in Renal Cell Carcinoma Tissue Image Grading

Science.gov (United States)

Cho, Nam-Hoon; Choi, Heung-Kook

2014-01-01

One of the most significant processes in cancer cell and tissue image analysis is the efficient extraction of features for grading purposes. This research applied two types of three-dimensional texture analysis methods to the extraction of feature values from renal cell carcinoma tissue images, and then evaluated the validity of the methods statistically through grade classification. First, we used a confocal laser scanning microscope to obtain image slices of four grades of renal cell carcinoma, which were then reconstructed into 3D volumes. Next, we extracted quantitative values using a 3D gray level cooccurrence matrix (GLCM) and a 3D wavelet based on two types of basis functions. To evaluate their validity, we predefined 6 different statistical classifiers and applied these to the extracted feature sets. In the grade classification results, 3D Haar wavelet texture features combined with principal component analysis showed the best discrimination results. Classification using 3D wavelet texture features was significantly better than 3D GLCM, suggesting that the former has potential for use in a computer-based grading system. PMID:25371701

3D Texture Analysis in Renal Cell Carcinoma Tissue Image Grading

Directory of Open Access Journals (Sweden)

Tae-Yun Kim

2014-01-01

Full Text Available One of the most significant processes in cancer cell and tissue image analysis is the efficient extraction of features for grading purposes. This research applied two types of three-dimensional texture analysis methods to the extraction of feature values from renal cell carcinoma tissue images, and then evaluated the validity of the methods statistically through grade classification. First, we used a confocal laser scanning microscope to obtain image slices of four grades of renal cell carcinoma, which were then reconstructed into 3D volumes. Next, we extracted quantitative values using a 3D gray level cooccurrence matrix (GLCM and a 3D wavelet based on two types of basis functions. To evaluate their validity, we predefined 6 different statistical classifiers and applied these to the extracted feature sets. In the grade classification results, 3D Haar wavelet texture features combined with principal component analysis showed the best discrimination results. Classification using 3D wavelet texture features was significantly better than 3D GLCM, suggesting that the former has potential for use in a computer-based grading system.

UAV Remote Sensing for Urban Vegetation Mapping Using Random Forest and Texture Analysis

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Quanlong Feng

2015-01-01

Full Text Available Unmanned aerial vehicle (UAV remote sensing has great potential for vegetation mapping in complex urban landscapes due to the ultra-high resolution imagery acquired at low altitudes. Because of payload capacity restrictions, off-the-shelf digital cameras are widely used on medium and small sized UAVs. The limitation of low spectral resolution in digital cameras for vegetation mapping can be reduced by incorporating texture features and robust classifiers. Random Forest has been widely used in satellite remote sensing applications, but its usage in UAV image classification has not been well documented. The objectives of this paper were to propose a hybrid method using Random Forest and texture analysis to accurately differentiate land covers of urban vegetated areas, and analyze how classification accuracy changes with texture window size. Six least correlated second-order texture measures were calculated at nine different window sizes and added to original Red-Green-Blue (RGB images as ancillary data. A Random Forest classifier consisting of 200 decision trees was used for classification in the spectral-textural feature space. Results indicated the following: (1 Random Forest outperformed traditional Maximum Likelihood classifier and showed similar performance to object-based image analysis in urban vegetation classification; (2 the inclusion of texture features improved classification accuracy significantly; (3 classification accuracy followed an inverted U relationship with texture window size. The results demonstrate that UAV provides an efficient and ideal platform for urban vegetation mapping. The hybrid method proposed in this paper shows good performance in differentiating urban vegetation mapping. The drawbacks of off-the-shelf digital cameras can be reduced by adopting Random Forest and texture analysis at the same time.

Correlation between macro texture measures carried out by the volumetric method and by different laser texture meter

International Nuclear Information System (INIS)

Parra Ruiz, L.; Yanguas Gonzalez, S. J.

2013-01-01

The reference value for the measurement of surface macro texture in the Spanish Main Road Network is the MTD or Mean Texture Depth (PMT, Profundidad Media de Textura), obtained by means of the volumetric methods, in accordance with the standard UNE EN 13036-1:12010. The fact that it is a spot measurement that requires road closures makes it an expensive procedure as well as slow and dangerous. In addition to this, the test results are relatively sensitive to the operator, being the procedure not too suitable for systematic surveys. These are some of the reasons that have contributed to the development of texture meter laser devices that can be assembled on board of vehicles, circulating without interfering with the normal traffic flow and providing a parameter named the MPD (Mean Depth Profile). According to the standard UNE-EN ISO 13473-1:2006, it is possible to estimate the texture obtained by volumetric methods, with the parameter ETD (Estimated Texture Depth) through the equation: ETD=0,8 x MPD+0.2 In 2008 CEDEX conducted a study that correlated macro texture measures obtained by means of the volumetric method with such carried out by different laser texture meters. The equations yield a better relation between MPD and MTD were dependent on the measurement device used and were not linear equations type, as is it indicated in the standard, but exponential type equations. (Author) 6 refs.

Texture analysis using Gabor wavelets

Science.gov (United States)

Naghdy, Golshah A.; Wang, Jian; Ogunbona, Philip O.

1996-04-01

Receptive field profiles of simple cells in the visual cortex have been shown to resemble even- symmetric or odd-symmetric Gabor filters. Computational models employed in the analysis of textures have been motivated by two-dimensional Gabor functions arranged in a multi-channel architecture. More recently wavelets have emerged as a powerful tool for non-stationary signal analysis capable of encoding scale-space information efficiently. A multi-resolution implementation in the form of a dyadic decomposition of the signal of interest has been popularized by many researchers. In this paper, Gabor wavelet configured in a 'rosette' fashion is used as a multi-channel filter-bank feature extractor for texture classification. The 'rosette' spans 360 degrees of orientation and covers frequencies from dc. In the proposed algorithm, the texture images are decomposed by the Gabor wavelet configuration and the feature vectors corresponding to the mean of the outputs of the multi-channel filters extracted. A minimum distance classifier is used in the classification procedure. As a comparison the Gabor filter has been used to classify the same texture images from the Brodatz album and the results indicate the superior discriminatory characteristics of the Gabor wavelet. With the test images used it can be concluded that the Gabor wavelet model is a better approximation of the cortical cell receptive field profiles.

Heterogeneous patterns enhancing static and dynamic texture classification

International Nuclear Information System (INIS)

Silva, Núbia Rosa da; Martinez Bruno, Odemir

2013-01-01

Some mixtures, such as colloids like milk, blood, and gelatin, have homogeneous appearance when viewed with the naked eye, however, to observe them at the nanoscale is possible to understand the heterogeneity of its components. The same phenomenon can occur in pattern recognition in which it is possible to see heterogeneous patterns in texture images. However, current methods of texture analysis can not adequately describe such heterogeneous patterns. Common methods used by researchers analyse the image information in a global way, taking all its features in an integrated manner. Furthermore, multi-scale analysis verifies the patterns at different scales, but still preserving the homogeneous analysis. On the other hand various methods use textons to represent the texture, breaking texture down into its smallest unit. To tackle this problem, we propose a method to identify texture patterns not small as textons at distinct scales enhancing the separability among different types of texture. We find sub patterns of texture according to the scale and then group similar patterns for a more refined analysis. Tests were performed in four static texture databases and one dynamical one. Results show that our method provide better classification rate compared with conventional approaches both in static and in dynamic texture.

Texture analysis of pulmonary parenchymateous changes related to pulmonary thromboembolism in dogs - a novel approach using quantitative methods.

Science.gov (United States)

Marschner, C B; Kokla, M; Amigo, J M; Rozanski, E A; Wiinberg, B; McEvoy, F J

2017-07-11

Diagnosis of pulmonary thromboembolism (PTE) in dogs relies on computed tomography pulmonary angiography (CTPA), but detailed interpretation of CTPA images is demanding for the radiologist and only large vessels may be evaluated. New approaches for better detection of smaller thrombi include dual energy computed tomography (DECT) as well as computer assisted diagnosis (CAD) techniques. The purpose of this study was to investigate the performance of quantitative texture analysis for detecting dogs with PTE using grey-level co-occurrence matrices (GLCM) and multivariate statistical classification analyses. CT images from healthy (n = 6) and diseased (n = 29) dogs with and without PTE confirmed on CTPA were segmented so that only tissue with CT numbers between -1024 and -250 Houndsfield Units (HU) was preserved. GLCM analysis and subsequent multivariate classification analyses were performed on texture parameters extracted from these images. Leave-one-dog-out cross validation and receiver operator characteristic (ROC) showed that the models generated from the texture analysis were able to predict healthy dogs with optimal levels of performance. Partial Least Square Discriminant Analysis (PLS-DA) obtained a sensitivity of 94% and a specificity of 96%, while Support Vector Machines (SVM) yielded a sensitivity of 99% and a specificity of 100%. The models, however, performed worse in classifying the type of disease in the diseased dog group: In diseased dogs with PTE sensitivities were 30% (PLS-DA) and 38% (SVM), and specificities were 80% (PLS-DA) and 89% (SVM). In diseased dogs without PTE the sensitivities of the models were 59% (PLS-DA) and 79% (SVM) and specificities were 79% (PLS-DA) and 82% (SVM). The results indicate that texture analysis of CTPA images using GLCM is an effective tool for distinguishing healthy from abnormal lung. Furthermore the texture of pulmonary parenchyma in dogs with PTE is altered, when compared to the texture of pulmonary parenchyma

Development and testing of texture discriminators for the analysis of trabecular bone in proximal femur radiographs

International Nuclear Information System (INIS)

Huber, M. B.; Carballido-Gamio, J.; Fritscher, K.; Schubert, R.; Haenni, M.; Hengg, C.; Majumdar, S.; Link, T. M.

2009-01-01

Purpose: Texture analysis of femur radiographs may serve as a potential low cost technique to predict osteoporotic fracture risk and has received considerable attention in the past years. A further application of this technique may be the measurement of the quality of specific bone compartments to provide useful information for treatment of bone fractures. Two challenges of texture analysis are the selection of the best suitable texture measure and reproducible placement of regions of interest (ROIs). The goal of this in vitro study was to automatically place ROIs in radiographs of proximal femur specimens and to calculate correlations between various different texture analysis methods and the femurs' anchorage strength. Methods: Radiographs were obtained from 14 femoral specimens and bone mineral density (BMD) was measured in the femoral neck. Biomechanical testing was performed to assess the anchorage strength in terms of failure load, breakaway torque, and number of cycles. Images were segmented using a framework that is based on the usage of level sets and statistical in-shape models. Five ROIs were automatically placed in the head, upper and lower neck, trochanteric, and shaft compartment in an atlas subject. All other subjects were registered rigidly, affinely, and nonlinearly, and the resulting transformation was used to map the five ROIs onto the individual femora. Results: In each ROI, texture features were extracted using gray level co-occurence matrices (GLCM), third-order GLCM, morphological gradients (MGs), Minkowski dimensions (MDs), Minkowski functionals (MFs), Gaussian Markov random fields, and scaling index method (SIM). Coefficients of determination for each texture feature with parameters of anchorage strength were computed. In a stepwise multiregression analysis, the most predictive parameters were identified in different models. Texture features were highly correlated with anchorage strength estimated by the failure load of up to R 2 =0.61 (MF

SURFACE TEXTURE ANALYSIS FOR FUNCTIONALITY CONTROL

DEFF Research Database (Denmark)

De Chiffre, Leonardo; Andreasen, Jan Lasson; Tosello, Guido

This document is used in connection with three exercises of 3 hours duration as a part of the course VISION ONLINE – One week course on Precision & Nanometrology. The exercises concern surface texture analysis for functionality control, in connection with three different case stories. This docume...... contains a short description of each case story, 3-D roughness parameters analysis and relation with the product’s functionality.......This document is used in connection with three exercises of 3 hours duration as a part of the course VISION ONLINE – One week course on Precision & Nanometrology. The exercises concern surface texture analysis for functionality control, in connection with three different case stories. This document...

Quantitative Ultrasound Using Texture Analysis of Myofascial Pain Syndrome in the Trapezius.

Science.gov (United States)

Kumbhare, Dinesh A; Ahmed, Sara; Behr, Michael G; Noseworthy, Michael D

2018-01-01

Objective-The objective of this study is to assess the discriminative ability of textural analyses to assist in the differentiation of the myofascial trigger point (MTrP) region from normal regions of skeletal muscle. Also, to measure the ability to reliably differentiate between three clinically relevant groups: healthy asymptomatic, latent MTrPs, and active MTrP. Methods-18 and 19 patients were identified with having active and latent MTrPs in the trapezius muscle, respectively. We included 24 healthy volunteers. Images were obtained by research personnel, who were blinded with respect to the clinical status of the study participant. Histograms provided first-order parameters associated with image grayscale. Haralick, Galloway, and histogram-related features were used in texture analysis. Blob analysis was conducted on the regions of interest (ROIs). Principal component analysis (PCA) was performed followed by multivariate analysis of variance (MANOVA) to determine the statistical significance of the features. Results-92 texture features were analyzed for factorability using Bartlett's test of sphericity, which was significant. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.94. PCA demonstrated rotated eigenvalues of the first eight components (each comprised of multiple texture features) explained 94.92% of the cumulative variance in the ultrasound image characteristics. The 24 features identified by PCA were included in the MANOVA as dependent variables, and the presence of a latent or active MTrP or healthy muscle were independent variables. Conclusion-Texture analysis techniques can discriminate between the three clinically relevant groups.

Development and testing of texture discriminators for the analysis of trabecular bone in proximal femur radiographs

Energy Technology Data Exchange (ETDEWEB)

Huber, M. B.; Carballido-Gamio, J.; Fritscher, K.; Schubert, R.; Haenni, M.; Hengg, C.; Majumdar, S.; Link, T. M. [Department of Radiology and Biomedical Imaging, University of California, 400 Parnassus Avenue, San Francisco, California 94143 (United States); University of Health Sciences, Medical Informatics and Technology, 6060 Hall (Austria); AO Development Institute, 7270 Davos Platz (Switzerland); Medical University Innsbruck, 6020 Innsbruck (Austria); Department of Radiology and Biomedical Imaging, University of California, 400 Parnassus Avenue, San Francisco, California 94143 (United States)

2009-11-15

Purpose: Texture analysis of femur radiographs may serve as a potential low cost technique to predict osteoporotic fracture risk and has received considerable attention in the past years. A further application of this technique may be the measurement of the quality of specific bone compartments to provide useful information for treatment of bone fractures. Two challenges of texture analysis are the selection of the best suitable texture measure and reproducible placement of regions of interest (ROIs). The goal of this in vitro study was to automatically place ROIs in radiographs of proximal femur specimens and to calculate correlations between various different texture analysis methods and the femurs' anchorage strength. Methods: Radiographs were obtained from 14 femoral specimens and bone mineral density (BMD) was measured in the femoral neck. Biomechanical testing was performed to assess the anchorage strength in terms of failure load, breakaway torque, and number of cycles. Images were segmented using a framework that is based on the usage of level sets and statistical in-shape models. Five ROIs were automatically placed in the head, upper and lower neck, trochanteric, and shaft compartment in an atlas subject. All other subjects were registered rigidly, affinely, and nonlinearly, and the resulting transformation was used to map the five ROIs onto the individual femora. Results: In each ROI, texture features were extracted using gray level co-occurence matrices (GLCM), third-order GLCM, morphological gradients (MGs), Minkowski dimensions (MDs), Minkowski functionals (MFs), Gaussian Markov random fields, and scaling index method (SIM). Coefficients of determination for each texture feature with parameters of anchorage strength were computed. In a stepwise multiregression analysis, the most predictive parameters were identified in different models. Texture features were highly correlated with anchorage strength estimated by the failure load of up to R{sup 2

Aesthetic Perception of Visual Textures: A Holistic Exploration using Texture Analysis, Psychological Experiment and Perception Modeling

Directory of Open Access Journals (Sweden)

Jianli eLiu

2015-11-01

Full Text Available Modeling human aesthetic perception of visual textures is important and valuable in numerous industrial domains, such as product design, architectural design and decoration. Based on results from a semantic differential rating experiment, we modeled the relationship between low-level basic texture features and aesthetic properties involved in human aesthetic texture perception. First, we compute basic texture features from textural images using four classical methods. These features are neutral, objective and independent of the socio-cultural context of the visual textures. Then, we conduct a semantic differential rating experiment to collect from evaluators their aesthetic perceptions of selected textural stimuli. In semantic differential rating experiment, eights pairs of aesthetic properties are chosen, which are strongly related to the socio-cultural context of the selected textures and to human emotions. They are easily understood and connected to everyday life. We propose a hierarchical feed-forward layer model of aesthetic texture perception and assign 8 pairs of aesthetic properties to different layers. Finally, we describe the generation of multiple linear and nonlinear regression models for aesthetic prediction by taking dimensionality-reduced texture features and aesthetic properties of visual textures as dependent and independent variables, respectively. Our experimental results indicate that the relationships between each layer and its neighbors in the hierarchical feed-forward layer model of aesthetic texture perception can be fitted well by linear functions, and the models thus generated can successfully bridge the gap between computational texture features and aesthetic texture properties.

About normal distribution on SO(3) group in texture analysis

Science.gov (United States)

Savyolova, T. I.; Filatov, S. V.

2017-12-01

This article studies and compares different normal distributions (NDs) on SO(3) group, which are used in texture analysis. Those NDs are: Fisher normal distribution (FND), Bunge normal distribution (BND), central normal distribution (CND) and wrapped normal distribution (WND). All of the previously mentioned NDs are central functions on SO(3) group. CND is a subcase for normal CLT-motivated distributions on SO(3) (CLT here is Parthasarathy’s central limit theorem). WND is motivated by CLT in R 3 and mapped to SO(3) group. A Monte Carlo method for modeling normally distributed values was studied for both CND and WND. All of the NDs mentioned above are used for modeling different components of crystallites orientation distribution function in texture analysis.

Novel 3D Compression Methods for Geometry, Connectivity and Texture

Science.gov (United States)

Siddeq, M. M.; Rodrigues, M. A.

2016-06-01

A large number of applications in medical visualization, games, engineering design, entertainment, heritage, e-commerce and so on require the transmission of 3D models over the Internet or over local networks. 3D data compression is an important requirement for fast data storage, access and transmission within bandwidth limitations. The Wavefront OBJ (object) file format is commonly used to share models due to its clear simple design. Normally each OBJ file contains a large amount of data (e.g. vertices and triangulated faces, normals, texture coordinates and other parameters) describing the mesh surface. In this paper we introduce a new method to compress geometry, connectivity and texture coordinates by a novel Geometry Minimization Algorithm (GM-Algorithm) in connection with arithmetic coding. First, each vertex ( x, y, z) coordinates are encoded to a single value by the GM-Algorithm. Second, triangle faces are encoded by computing the differences between two adjacent vertex locations, which are compressed by arithmetic coding together with texture coordinates. We demonstrate the method on large data sets achieving compression ratios between 87 and 99 % without reduction in the number of reconstructed vertices and triangle faces. The decompression step is based on a Parallel Fast Matching Search Algorithm (Parallel-FMS) to recover the structure of the 3D mesh. A comparative analysis of compression ratios is provided with a number of commonly used 3D file formats such as VRML, OpenCTM and STL highlighting the performance and effectiveness of the proposed method.

Computer Texture Mapping for Laser Texturing of Injection Mold

Directory of Open Access Journals (Sweden)

Yongquan Zhou

2014-04-01

Full Text Available Laser texturing is a relatively new multiprocess technique that has been used for machining 3D curved surfaces; it is more flexible and efficient to create decorative texture on 3D curved surfaces of injection molds so as to improve the surface quality and achieve cosmetic surface of molded plastic parts. In this paper, a novel method of laser texturing 3D curved surface based on 3-axis galvanometer scanning unit has been presented to prevent the texturing of injection mold surface from much distortion which is often caused by traditional texturing processes. The novel method has been based on the computer texture mapping technology which has been developed and presented. The developed texture mapping algorithm includes surface triangulation, notations, distortion measurement, control, and numerical method. An interface of computer texture mapping has been built to implement the algorithm of texture mapping approach to controlled distortion rate of 3D texture math model from 2D original texture applied to curvature surface. Through a case study of laser texturing of a high curvature surface of injection mold of a mice top case, it shows that the novel method of laser texturing meets the quality standard of laser texturing of injection mold.

Texture analysis using angle dispersive neutron nuclear scattering

International Nuclear Information System (INIS)

Brokmeier, H.G.

1995-01-01

This paper describes in detail the method of texture determination using neutron diffraction. The main advantages of neutron diffraction arise from the high penetration depth for most materials which is a factor of 10 2 -10 4 higher than for X-ray diffraction. Consequently neutron diffraction is an efficient tool for the investigation of global textures and coarse grained materials. Moreover, the measurement of large sample volumes gives excellent grain statistics, allows the influence of texture inhomogeneities to be neglected and allows the measurement of complete pole figures even of minority phases. A number of examples show the application of neutron diffraction to measure textures of metals, alloys, composites, intermetallic compounds and rocks. A detailed description of TEX-2 the neutron texture diffractometer at GKSS Research Centre is given which is completed by a comparison to other neutron texture diffractometers. (orig.) [de

Measurement of food texture by an acoustic vibration method

Science.gov (United States)

Sakurai, Naoki; Taniwaki, Mitsuru; Iwatani, Shin-ichiro; Akimoto, Hidemi

2011-09-01

Food texture was measured by a new acoustic vibration method. A piezoelectric sensor sandwiched between a probe and piston was inserted into a food sample by delivery of silicon oil to a cylinder by a pump. Vibration emitted from the food sample on insertion of the probe was monitored by voltage outputs of the sensor. The voltage signals were passed through 19 half octave bands to calculate texture index for each band. The texture index was defined as vibration energy of the probe caused by the food rupture and/or breakage per unit time.

A novel method of estimating dose responses for polymer gels using texture analysis of scanning electron microscopy images.

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Cheng-Ting Shih

Full Text Available Polymer gels are regarded as a potential dosimeter for independent validation of absorbed doses in clinical radiotherapy. Several imaging modalities have been used to convert radiation-induced polymerization to absorbed doses from a macro-scale viewpoint. This study developed a novel dose conversion mechanism by texture analysis of scanning electron microscopy (SEM images. The modified N-isopropyl-acrylamide (NIPAM gels were prepared under normoxic conditions, and were administered radiation doses from 5 to 20 Gy. After freeze drying, the gel samples were sliced for SEM scanning with 50×, 500×, and 3500× magnifications. Four texture indices were calculated based on the gray level co-occurrence matrix (GLCM. The results showed that entropy and homogeneity were more suitable than contrast and energy as dose indices for higher linearity and sensitivity of the dose response curves. After parameter optimization, an R (2 value of 0.993 can be achieved for homogeneity using 500× magnified SEM images with 27 pixel offsets and no outlier exclusion. For dose verification, the percentage errors between the prescribed dose and the measured dose for 5, 10, 15, and 20 Gy were -7.60%, 5.80%, 2.53%, and -0.95%, respectively. We conclude that texture analysis can be applied to the SEM images of gel dosimeters to accurately convert micro-scale structural features to absorbed doses. The proposed method may extend the feasibility of applying gel dosimeters in the fields of diagnostic radiology and radiation protection.

Medullar fat influences texture analysis of trabecular microarchitecture on X-ray radiographs

International Nuclear Information System (INIS)

Chappard, Daniel; Pascaretti-Grizon, Florence; Gallois, Yves; Mercier, Philippe; Basle, Michel F.; Audran, Maurice

2006-01-01

Alteration of trabecular architecture is a predictor of fracture risk in osteoporosis. Until now, microarchitecture analysis is difficult to evaluate in routine clinical practice for osteoporosis. Texture analysis on X-ray images has been advocated to be a suitable method to assess microarchitecture in bone diseases. The X-ray acquisition conditions have been often taken into consideration; however, the influence of anatomical conditions on texture parameters has received little interest. Because fat is a well-known problem with computed tomography and densitometry, we have designed a cadaver study to compare the influence of marrow lipids on numerous texture parameters. Twenty-one human distal radii were obtained, radiographed, and analyzed using a software that measures: heterogeneity, skeletonized parameters, run-lengths and fractal dimensions. Texture parameters were measured before, and after an extensive delipidation period lasting 3 weeks. Quality of the radiographs was improved after defatting. Delipidation had a very significant effect on measurements: afterwards defatting, the images were less blurred, and a better delineation of trabeculae and marrow cavities was obtained. This provoked an increase of parameters based on the grey level distribution but had no influence on parameters describing the reticulated honeycomb microarchitecture of the trabeculae (i.e., fractal dimension). Some parameters appeared anisotropy-sensitive, due to the different constitution and size of the trabeculae. The fat content of bone marrow induces noise that can modify some texture parameters. One should take into account the fat content of the marrow when using texture analysis to compare patients with osteoporosis due to various etiologies

Diagnosis and prognosis of Ostheoarthritis by texture analysis using sparse linear models

DEFF Research Database (Denmark)

Marques, Joselene; Clemmensen, Line Katrine Harder; Dam, Erik

We present a texture analysis methodology that combines uncommitted machine-learning techniques and sparse feature transformation methods in a fully automatic framework. We compare the performances of a partial least squares (PLS) forward feature selection strategy to a hard threshold sparse PLS...... algorithm and a sparse linear discriminant model. The texture analysis framework was applied to diagnosis of knee osteoarthritis (OA) and prognosis of cartilage loss. For this investigation, a generic texture feature bank was extracted from magnetic resonance images of tibial knee bone. The features were...... used as input to the sparse algorithms, which dened the best features to retain in the model. To cope with the limited number of samples, the data was evaluated using 10 fold cross validation (CV). The diagnosis evaluation using sparse PLS reached a generalization area-under-the-ROC curve (AUC) of 0...

A recognition method research based on the heart sound texture map

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Huizhong Cheng

2016-06-01

Full Text Available In order to improve the Heart Sound recognition rate and reduce the recognition time, in this paper, we introduces a new method for Heart Sound pattern recognition by using Heart Sound Texture Map. Based on the Heart Sound model, we give the Heart Sound time-frequency diagram and the Heart Sound Texture Map definition, we study the structure of the Heart Sound Window Function principle and realization method, and then discusses how to use the Heart Sound Window Function and the Short-time Fourier Transform to obtain two-dimensional Heart Sound time-frequency diagram, propose corner correlation recognition algorithm based on the Heart Sound Texture Map according to the characteristics of Heart Sound. The simulation results show that the Heart Sound Window Function compared with the traditional window function makes the first (S1 and the second (S2 Heart Sound texture clearer. And the corner correlation recognition algorithm based on the Heart Sound Texture Map can significantly improve the recognition rate and reduce the expense, which is an effective Heart Sound recognition method.

Texture analysis of pulmonary parenchymateous changes related to pulmonary thromboembolism in dogs - a novel approach using quantitative methods

DEFF Research Database (Denmark)

Marschner, Clara Büchner; Kokla, Marietta; Amigo Rubio, Jose Manuel

2017-01-01

include dual energy computed tomography (DECT) as well as computer assisted diagnosis (CAD) techniques. The purpose of this study was to investigate the performance of quantitative texture analysis for detecting dogs with PTE using grey-level co-occurrence matrices (GLCM) and multivariate statistical...... classification analyses. CT images from healthy (n = 6) and diseased (n = 29) dogs with and without PTE confirmed on CTPA were segmented so that only tissue with CT numbers between −1024 and −250 Houndsfield Units (HU) was preserved. GLCM analysis and subsequent multivariate classification analyses were...... using GLCM is an effective tool for distinguishing healthy from abnormal lung. Furthermore the texture of pulmonary parenchyma in dogs with PTE is altered, when compared to the texture of pulmonary parenchyma of healthy dogs. The models’ poorer performance in classifying dogs within the diseased group...

The use of texture analysis in the vertebral morphometric study of a lordotic chub (Squalius cephalus L.

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Maurizio Manera

2014-08-01

Full Text Available Objective: To characterise vertebral aspects of a lordotic chub (Squalius cephalus L. using texture analysis by radiograph and to verify possible alterations in the vertebral microarchitecture of the lordotic tract. Methods: Four vertebrae belonging to the lordotic tract were analyzed for their texture features by means of a software package (MaZda vers. 4.6 and were compared, for the same features, to other four vertebrae cranial (anterior to the lordotic vertebrae. Results: Two representative features were selected out of 259 extracted texture features by means of the convex hull selection method. In particular, (5, 5 sum of squares (according to cooccurrence matrix method and 45° short run emphasis (according to run-length matrix method were used to classify, without classification errors, two selected spinal tracts (the lordotic one and the immediately cranial one, both corresponding to the anal fin pterigiophores vertebral portion according to the following methods: linear discriminant analysis and hierarchical clustering. Conclusions: This is the first known application of texture analysis in medical imaging applied to fish species and represents a start point for further studies in aquariology and in aquaculture, where spinal deformities occur relative frequently and are cause of economic losses.

The promise and limits of PET texture analysis.

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Cheng, Nai-Ming; Fang, Yu-Hua Dean; Yen, Tzu-Chen

2013-11-01

Metabolic heterogeneity is a recognized characteristic of malignant tumors. Positron emission tomography (PET) texture analysis evaluated intratumoral heterogeneity in the uptake of (18)F-fluorodeoxyglucose. There were recent evidences that PET textural features were of prognostic significance in patients with different solid tumors. Unfortunately, there are still crucial standardization challenges to transform PET texture parameters from their current use as research tools into the arena of validated technologies for use in oncology practice. Testing its generalizability, robustness, consistency, and limitations is necessary before implementing it in daily patient care.

Texture analysis of computed tomography images of acute ischemic stroke patients

International Nuclear Information System (INIS)

Oliveira, M.S.; Castellano, G.; Fernandes, P.T.; Avelar, W.M.; Santos, S.L.M.; Li, L.M.

2009-01-01

Computed tomography (CT) images are routinely used to assess ischemic brain stroke in the acute phase. They can provide important clues about whether to treat the patient by thrombolysis with tissue plasminogen activator. However, in the acute phase, the lesions may be difficult to detect in the images using standard visual analysis. The objective of the present study was to determine if texture analysis techniques applied to CT images of stroke patients could differentiate between normal tissue and affected areas that usually go unperceived under visual analysis. We performed a pilot study in which texture analysis, based on the gray level co-occurrence matrix, was applied to the CT brain images of 5 patients and of 5 control subjects and the results were compared by discriminant analysis. Thirteen regions of interest, regarding areas that may be potentially affected by ischemic stroke, were selected for calculation of texture parameters. All regions of interest for all subjects were classified as lesional or non-lesional tissue by an expert neuroradiologist. Visual assessment of the discriminant analysis graphs showed differences in the values of texture parameters between patients and controls, and also between texture parameters for lesional and non-lesional tissue of the patients. This suggests that texture analysis can indeed be a useful tool to help neurologists in the early assessment of ischemic stroke and quantification of the extent of the affected areas. (author)

A robust automatic leukocyte recognition method based on island-clustering texture

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Xiaoshun Li

2016-01-01

Full Text Available A leukocyte recognition method for human peripheral blood smear based on island-clustering texture (ICT is proposed. By analyzing the features of the five typical classes of leukocyte images, a new ICT model is established. Firstly, some feature points are extracted in a gray leukocyte image by mean-shift clustering to be the centers of islands. Secondly, the growing region is employed to create regions of the islands in which the seeds are just these feature points. These islands distribution can describe a new texture. Finally, a distinguished parameter vector of these islands is created as the ICT features by combining the ICT features with the geometric features of the leukocyte. Then the five typical classes of leukocytes can be recognized successfully at the correct recognition rate of more than 92.3% with a total sample of 1310 leukocytes. Experimental results show the feasibility of the proposed method. Further analysis reveals that the method is robust and results can provide important information for disease diagnosis.

Neutronographic Texture Analysis of Zirconium Based Alloys

International Nuclear Information System (INIS)

Kruz'elová, M; Vratislav, S; Kalvoda, L; Dlouhá, M

2012-01-01

Neutron diffraction is a very powerful tool in texture analysis of zirconium based alloys used in nuclear technique. Textures of five samples (two rolled sheets and three tubes) were investigated by using basal pole figures, inversion pole figures, and ODF distribution function. The texture measurement was performed at diffractometer KSN2 on the Laboratory of Neutron Diffraction, Department of Solid State Engineering, Faculty of Nuclear Sciences and Physical Engineering, CTU in Prague. Procedures for studying textures with thermal neutrons and procedures for obtaining texture parameters (direct and inverse pole figures, three dimensional orientation distribution function) are also described. Observed data were processed by software packages HEXAL and GSAS. Our results can be summarized as follows: i) All samples of zirconium alloys show the distribution of middle area into two maxima in basal pole figures. This is caused by alloying elements. A characteristic split of the basal pole maxima tilted from the normal direction toward the transverse direction can be observed for all samples, ii) Sheet samples prefer orientation of planes (100) and (110) perpendicular to rolling direction and orientation of planes (002) perpendicular to normal direction, iii) Basal planes of tubes are oriented parallel to tube axis, meanwhile (100) planes are oriented perpendicular to tube axis. Level of resulting texture and maxima position is different for tubes and for sheets. The obtained results are characteristic for zirconium based alloys.

Chemometric approach to texture profile analysis of kombucha fermented milk products.

Science.gov (United States)

Malbaša, Radomir; Jevrić, Lidija; Lončar, Eva; Vitas, Jasmina; Podunavac-Kuzmanović, Sanja; Milanović, Spasenija; Kovačević, Strahinja

2015-09-01

In the present work, relationships between the textural characteristics of fermented milk products obtained by kombucha inoculums with various teas were investigated by using chemometric analysis. The presented data which describe numerically the textural characteristics (firmness, consistency, cohesiveness and index of viscosity) were analysed. The quadratic correlation was determined between the textural characteristics of fermented milk products obtained at fermentation temperatures of 40 and 43 °C, using milk with 0.8, 1.6 and 2.8% milk fat and kombucha inoculums cultivated on the extracts of peppermint, stinging nettle, wild thyme and winter savory. Hierarchical cluster analysis (HCA) was performed to identify the similarities among the fermented products. The best mathematical models predicting the textural characteristics of investigated samples were developed. The results of this study indicate that textural characteristics of sample based on winter savory have a significant effect on textural characteristics of samples based on peppermint, stinging nettle and wild thyme, which can be very useful in the determination of products texture profile.

Characterization of microcirculation in multiple sclerosis lesions by dynamic texture parameter analysis (DTPA.

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Rajeev Kumar Verma

Full Text Available OBJECTIVE: Texture analysis is an alternative method to quantitatively assess MR-images. In this study, we introduce dynamic texture parameter analysis (DTPA, a novel technique to investigate the temporal evolution of texture parameters using dynamic susceptibility contrast enhanced (DSCE imaging. Here, we aim to introduce the method and its application on enhancing lesions (EL, non-enhancing lesions (NEL and normal appearing white matter (NAWM in multiple sclerosis (MS. METHODS: We investigated 18 patients with MS and clinical isolated syndrome (CIS, according to the 2010 McDonald's criteria using DSCE imaging at different field strengths (1.5 and 3 Tesla. Tissues of interest (TOIs were defined within 27 EL, 29 NEL and 37 NAWM areas after normalization and eight histogram-based texture parameter maps (TPMs were computed. TPMs quantify the heterogeneity of the TOI. For every TOI, the average, variance, skewness, kurtosis and variance-of-the-variance statistical parameters were calculated. These TOI parameters were further analyzed using one-way ANOVA followed by multiple Wilcoxon sum rank testing corrected for multiple comparisons. RESULTS: Tissue- and time-dependent differences were observed in the dynamics of computed texture parameters. Sixteen parameters discriminated between EL, NEL and NAWM (pAVG = 0.0005. Significant differences in the DTPA texture maps were found during inflow (52 parameters, outflow (40 parameters and reperfusion (62 parameters. The strongest discriminators among the TPMs were observed in the variance-related parameters, while skewness and kurtosis TPMs were in general less sensitive to detect differences between the tissues. CONCLUSION: DTPA of DSCE image time series revealed characteristic time responses for ELs, NELs and NAWM. This may be further used for a refined quantitative grading of MS lesions during their evolution from acute to chronic state. DTPA discriminates lesions beyond features of enhancement or T2

CRUMB TEXTURE OF SPELT BREAD

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Joanna Korczyk-Szabó

2013-12-01

Full Text Available Abstract The bread quality is considerably dependent on the texture characteristic of bread crumb. Crumb texture is an important quality indicator, as consumer prefer different bread taste. Texture analysis is primarily concerned with the evaluation of mechanical characteristics where a material is subjected to a controlled force from which a deformation curve of its response is generated. It is an objective physical examination of baked products and gives direct information on the product quality, oppositely to dough rheology tests what inform on the baking suitability of the flour, as raw material. This is why the texture analysis is one of the most helpful analytical methods of the product development. In the framework of our research during the years 2008 – 2009 were analyzed selected indicators for bread texture quality of five Triticum spelta L. varieties – Altgold, Oberkulmer Rotkorn, Ostro, Rubiota and Franckenkorn grown in an ecological system. The bread texture quality was evaluated on texture analyzer TA.XT Plus (Stable Micro Systems, Surrey, UK, following the AACC (74-09 standard method and expressed as crumb firmness (N, stiffness (N.mm-1 and relative elasticity (%. Our research proved that all selected indicators were significantly influenced by the year of growing and variety. The most soft bread was achieved in Rubiota, whereas bread crumb samples from Franckenkorn and Altgold were the most firm and stiff. Correlation analysis showed strong negative correlation between relative elasticity and bread crumb firmness as well as bread stiffness (-0.81++, -0.78++. The spelt grain can be a good source for making bread flour, but is closely dependent on choice of spelt variety. The spelt wheat bread crumb texture need further investigation as it can be a reliable quality parameter.

Characterizing commercial pureed foods: sensory, nutritional, and textural analysis.

Science.gov (United States)

Ettinger, Laurel; Keller, Heather H; Duizer, Lisa M

2014-01-01

Dysphagia (swallowing impairment) is a common consequence of stroke and degenerative diseases such as Parkinson's and Alzheimer's. Limited research is available on pureed foods, specifically the qualities of commercial products. Because research has linked pureed foods, specifically in-house pureed products, to malnutrition due to inferior sensory and nutritional qualities, commercial purees also need to be investigated. Proprietary research on sensory attributes of commercial foods is available; however direct comparisons of commercial pureed foods have never been reported. Descriptive sensory analysis as well as nutritional and texture analysis of commercially pureed prepared products was performed using a trained descriptive analysis panel. The pureed foods tested included four brands of carrots, of turkey, and two of bread. Each commercial puree was analyzed for fat (Soxhlet), protein (Dumas), carbohydrate (proximate analysis), fiber (total fiber), and sodium content (Quantab titrator strips). The purees were also texturally compared with a line spread test and a back extrusion test. Differences were found in the purees for sensory attributes as well as nutritional and textural properties. Findings suggest that implementation of standards is required to reduce variability between products, specifically regarding the textural components of the products. This would ensure all commercial products available in Canada meet standards established as being considered safe for swallowing.

Second order statistical analysis of US image texture

International Nuclear Information System (INIS)

Tanzi, F.; Novario, R.

1999-01-01

The study reports the sonographic image texture of the neonatal heart in different stages of development by calculating numerical parameters extracted from the gray scale co-occurrence matrix. To show pixel values differences and enhance texture structure, images were equalized and then the gray level range was reduced to 16 to allow sufficiently high occupancy frequency of the co-occurrence matrix. Differences are so little significant that they may be due to different factors affecting image texture and the variability introduced by manual ROI positioning; therefore no definitive conclusions can be drawn as to considering this kind of analysis capable of discriminating different stages of myocardial development [it

Texture analysis for the assessment of structural changes in parotid glands induced by radiotherapy

International Nuclear Information System (INIS)

Scalco, Elisa; Fiorino, Claudio; Cattaneo, Giovanni Mauro; Sanguineti, Giuseppe; Rizzo, Giovanna

2013-01-01

Background and purpose: During radiotherapy (RT) for head-and-neck cancer, parotid glands undergo significant anatomic, functional and structural changes which could characterize pre-clinical signs of an increased risk of xerostomia. Texture analysis is proposed to assess structural changes of parotids induced by RT, and to investigate whether early variations of textural parameters (such as mean intensity and fractal dimension) can predict parotid shrinkage at the end of treatment. Material and methods: Textural parameters and volumes of 42 parotids from 21 patients treated with intensity-modulated RT for nasopharyngeal cancer were extracted from CT images. To individuate which parameters changed during RT, a Wilcoxon signed-rank test between textural indices (first and second RT week; first and last RT week) was performed. Discriminant analysis was applied to variations of these parameters in the first two weeks of RT to assess their power in predicting parotid shrinkage at the end of RT. Results: A significant decrease in mean intensity (1.7 HU and 3.8 HU after the second and last weeks, respectively) and fractal dimension (0.016 and 0.021) was found. Discriminant analysis, based on volume and fractal dimension, was able to predict the final parotid shrinkage (accuracy of 71.4%). Conclusion: Textural features could be used in combination with volume to characterize structural modifications on parotid glands and to predict parotid shrinkage at the end of RT

Texture Analysis using The Neutron Diffraction Method on The Non Standardized Austenitic Steel Process by Machining,Annealing, and Rolling

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Tri Hardi Priyanto

2016-04-01

Full Text Available Austenitic steel is one type of stainless steel which is widely used in the industry. Many studies on  austenitic stainless steel have been performed to determine the physicalproperties using various types of equipment and methods. In this study, the neutron diffraction method is used to characterize the materials which have been made from  minerals extracted from the mines in Indonesia. The materials consist of a granular ferro-scrap, nickel, ferro-chrome, ferro-manganese, and ferro-silicon added with a little titanium. Characterization of the materials was carried out in threeprocesses, namely: machining, annealing, and rolling. Experimental results obtained from the machining process generally produces a texture in the 〈100〉direction. From the machining to annealing process, the texture index decreases from 3.0164 to 2.434.Texture strength in the machining process (BA2N sample is  8.13 mrd and it then decreases to 6.99 in the annealing process (A2DO sample. In the annealing process the three-component texture appears, cube-on-edge type texture{110}〈001〉, cube-type texture {001}〈100〉, and brass-type {110}〈112〉. The texture is very strong leading to the direction of orientation {100}〈001〉, while the {011}〈100〉is weaker than that of the {001}, and texture withorientation {110}〈112〉is weak. In the annealing process stress release occurred, and this was shown by more randomly pole compared to stress release by the machining process. In the rolling process a brass-type texture{110}〈112〉with a spread towards the goss-type texture {110}〈001〉 appeared,  and  the  brass  component  is markedly  reinforced  compared  to  the undeformed state (before rolling. Moreover, the presence of an additional {110} component was observed at the center of the (110 pole figure. The pole density of three components increases withthe increasing degree of thickness reduction. By increasing degrees

Maximum Entropy Method in Moessbauer Spectroscopy - a Problem of Magnetic Texture

International Nuclear Information System (INIS)

Satula, D.; Szymanski, K.; Dobrzynski, L.

2011-01-01

A reconstruction of the three dimensional distribution of the hyperfine magnetic field, isomer shift and texture parameter z from the Moessbauer spectra by the maximum entropy method is presented. The method was tested on the simulated spectrum consisting of two Gaussian hyperfine field distributions with different values of the texture parameters. It is shown that proper prior has to be chosen in order to arrive at the physically meaningful results. (authors)

Fast Image Texture Classification Using Decision Trees

Science.gov (United States)

Thompson, David R.

2011-01-01

Texture analysis would permit improved autonomous, onboard science data interpretation for adaptive navigation, sampling, and downlink decisions. These analyses would assist with terrain analysis and instrument placement in both macroscopic and microscopic image data products. Unfortunately, most state-of-the-art texture analysis demands computationally expensive convolutions of filters involving many floating-point operations. This makes them infeasible for radiation- hardened computers and spaceflight hardware. A new method approximates traditional texture classification of each image pixel with a fast decision-tree classifier. The classifier uses image features derived from simple filtering operations involving integer arithmetic. The texture analysis method is therefore amenable to implementation on FPGA (field-programmable gate array) hardware. Image features based on the "integral image" transform produce descriptive and efficient texture descriptors. Training the decision tree on a set of training data yields a classification scheme that produces reasonable approximations of optimal "texton" analysis at a fraction of the computational cost. A decision-tree learning algorithm employing the traditional k-means criterion of inter-cluster variance is used to learn tree structure from training data. The result is an efficient and accurate summary of surface morphology in images. This work is an evolutionary advance that unites several previous algorithms (k-means clustering, integral images, decision trees) and applies them to a new problem domain (morphology analysis for autonomous science during remote exploration). Advantages include order-of-magnitude improvements in runtime, feasibility for FPGA hardware, and significant improvements in texture classification accuracy.

"Textural analysis of multiparametric MRI detects transition zone prostate cancer".

Science.gov (United States)

Sidhu, Harbir S; Benigno, Salvatore; Ganeshan, Balaji; Dikaios, Nikos; Johnston, Edward W; Allen, Clare; Kirkham, Alex; Groves, Ashley M; Ahmed, Hashim U; Emberton, Mark; Taylor, Stuart A; Halligan, Steve; Punwani, Shonit

2017-06-01

To evaluate multiparametric-MRI (mpMRI) derived histogram textural-analysis parameters for detection of transition zone (TZ) prostatic tumour. Sixty-seven consecutive men with suspected prostate cancer underwent 1.5T mpMRI prior to template-mapping-biopsy (TPM). Twenty-six men had 'significant' TZ tumour. Two radiologists in consensus matched TPM to the single axial slice best depicting tumour, or largest TZ diameter for those with benign histology, to define single-slice whole TZ-regions-of-interest (ROIs). Textural-parameter differences between single-slice whole TZ-ROI containing significant tumour versus benign/insignificant tumour were analysed using Mann Whitney U test. Diagnostic accuracy was assessed by receiver operating characteristic area under curve (ROC-AUC) analysis cross-validated with leave-one-out (LOO) analysis. ADC kurtosis was significantly lower (p Textural features of the whole prostate TZ can discriminate significant prostatic cancer through reduced kurtosis of the ADC-histogram where significant tumour is included in TZ-ROI and reduced T1 entropy independent of tumour inclusion. • MR textural features of prostate transition zone may discriminate significant prostatic cancer. • Transition zone (TZ) containing significant tumour demonstrates a less peaked ADC histogram. • TZ containing significant tumour reveals higher post-contrast T1-weighted homogeneity. • The utility of MR texture analysis in prostate cancer merits further investigation.

A Study of Feature Extraction Using Divergence Analysis of Texture Features

Science.gov (United States)

Hallada, W. A.; Bly, B. G.; Boyd, R. K.; Cox, S.

1982-01-01

An empirical study of texture analysis for feature extraction and classification of high spatial resolution remotely sensed imagery (10 meters) is presented in terms of specific land cover types. The principal method examined is the use of spatial gray tone dependence (SGTD). The SGTD method reduces the gray levels within a moving window into a two-dimensional spatial gray tone dependence matrix which can be interpreted as a probability matrix of gray tone pairs. Haralick et al (1973) used a number of information theory measures to extract texture features from these matrices, including angular second moment (inertia), correlation, entropy, homogeneity, and energy. The derivation of the SGTD matrix is a function of: (1) the number of gray tones in an image; (2) the angle along which the frequency of SGTD is calculated; (3) the size of the moving window; and (4) the distance between gray tone pairs. The first three parameters were varied and tested on a 10 meter resolution panchromatic image of Maryville, Tennessee using the five SGTD measures. A transformed divergence measure was used to determine the statistical separability between four land cover categories forest, new residential, old residential, and industrial for each variation in texture parameters.

Texture-based analysis of COPD

DEFF Research Database (Denmark)

Sørensen, Lauge; Nielsen, Mads; Lo, Pechin Chien Pau

2012-01-01

This study presents a fully automatic, data-driven approach for texture-based quantitative analysis of chronic obstructive pulmonary disease (COPD) in pulmonary computed tomography (CT) images. The approach uses supervised learning where the class labels are, in contrast to previous work, based...... on measured lung function instead of on manually annotated regions of interest (ROIs). A quantitative measure of COPD is obtained by fusing COPD probabilities computed in ROIs within the lung fields where the individual ROI probabilities are computed using a k nearest neighbor (kNN ) classifier. The distance...... and subsequently applied to classify 200 independent images from the same screening trial. The texture-based measure was significantly better at discriminating between subjects with and without COPD than were the two most common quantitative measures of COPD in the literature, which are based on density...

Ion-beam texturing of uniaxially textured Ni films

International Nuclear Information System (INIS)

Park, S.J.; Norton, D.P.; Selvamanickam, Venkat

2005-01-01

The formation of biaxial texture in uniaxially textured Ni thin films via Ar-ion irradiation is reported. The ion-beam irradiation was not simultaneous with deposition. Instead, the ion beam irradiates the uniaxially textured film surface with no impinging deposition flux, which differs from conventional ion-beam-assisted deposition. The uniaxial texture is established via a nonion beam process, with the in-plane texture imposed on the uniaxial film via ion beam bombardment. Within this sequential ion beam texturing method, grain alignment is driven by selective etching and grain overgrowth

X-ray texture analysis of paper coating pigments and the correlation with chemical composition analysis

Science.gov (United States)

Roine, J.; Tenho, M.; Murtomaa, M.; Lehto, V.-P.; Kansanaho, R.

2007-10-01

The present research experiments the applicability of x-ray texture analysis in investigating the properties of paper coatings. The preferred orientations of kaolin, talc, ground calcium carbonate, and precipitated calcium carbonate particles used in four different paper coatings were determined qualitatively based on the measured crystal orientation data. The extent of the orientation, namely, the degree of the texture of each pigment, was characterized quantitatively using a single parameter. As a result, the effect of paper calendering is clearly seen as an increase on the degree of texture of the coating pigments. The effect of calendering on the preferred orientation of kaolin was also evident in an independent energy dispersive spectrometer analysis on micrometer scale and an electron spectroscopy for chemical analysis on nanometer scale. Thus, the present work proves x-ray texture analysis to be a potential research tool for characterizing the properties of paper coating layers.

A standardised protocol for texture feature analysis of endoscopic images in gynaecological cancer

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Pattichis Marios S

2007-11-01

Full Text Available Abstract Background In the development of tissue classification methods, classifiers rely on significant differences between texture features extracted from normal and abnormal regions. Yet, significant differences can arise due to variations in the image acquisition method. For endoscopic imaging of the endometrium, we propose a standardized image acquisition protocol to eliminate significant statistical differences due to variations in: (i the distance from the tissue (panoramic vs close up, (ii difference in viewing angles and (iii color correction. Methods We investigate texture feature variability for a variety of targets encountered in clinical endoscopy. All images were captured at clinically optimum illumination and focus using 720 × 576 pixels and 24 bits color for: (i a variety of testing targets from a color palette with a known color distribution, (ii different viewing angles, (iv two different distances from a calf endometrial and from a chicken cavity. Also, human images from the endometrium were captured and analysed. For texture feature analysis, three different sets were considered: (i Statistical Features (SF, (ii Spatial Gray Level Dependence Matrices (SGLDM, and (iii Gray Level Difference Statistics (GLDS. All images were gamma corrected and the extracted texture feature values were compared against the texture feature values extracted from the uncorrected images. Statistical tests were applied to compare images from different viewing conditions so as to determine any significant differences. Results For the proposed acquisition procedure, results indicate that there is no significant difference in texture features between the panoramic and close up views and between angles. For a calibrated target image, gamma correction provided an acquired image that was a significantly better approximation to the original target image. In turn, this implies that the texture features extracted from the corrected images provided for better

A dynamical system approach to texel identification in regular textures

NARCIS (Netherlands)

Grigorescu, S.E.; Petkov, N.; Loncaric, S; Neri, A; Babic, H

2003-01-01

We propose a texture analysis method based on Rényi’s entropies. The method aims at identifying texels in regular textures by searching for the smallest window through which the minimum number of different visual patterns is observed when moving the window over a given texture. The experimental

Wavelet-packet-based texture analysis for differentiation between benign and malignant liver tumours in ultrasound images

International Nuclear Information System (INIS)

Yoshida, Hiroyuki; Casalino, David D; Keserci, Bilgin; Coskun, Abdulhakim; Ozturk, Omer; Savranlar, Ahmet

2003-01-01

The purpose of this study was to apply a novel method of multiscale echo texture analysis for distinguishing benign (hemangiomas) from malignant (hepatocellular carcinomas (HCCs) and metastases) focal liver lesions in B-mode ultrasound images. In this method, regions of interest (ROIs) extracted from within the lesions were decomposed into subimages by wavelet packets. Multiscale texture features that quantify homogeneity of the echogenicity were calculated from these subimages and were combined by an artificial neural network (ANN). A subset of the multiscale features was selected that yielded the highest performance in the classification of lesions measured by the area under the receiver operating characteristic curve (A z ). In an analysis of 193 ROIs consisting of 50 hemangiomas, 87 hepatocellular carcinomas and 56 metastases, the multiscale features yielded a high A z value of 0.92 in distinguishing benign from malignant lesions, 0.93 in distinguishing hemangiomas from HCCs and 0.94 in distinguishing hemangiomas from metastases. Our new multiscale texture analysis method can effectively differentiate malignant from benign lesions, and thus has the potential to increase the accuracy of diagnosis of focal liver lesions in ultrasound images

Method for forming biaxially textured articles by powder metallurgy

Science.gov (United States)

Goyal, Amit; Williams, Robert K.; Kroeger, Donald M.

2002-01-01

A method of preparing a biaxially textured alloy article comprises the steps of preparing a mixture comprising Ni powder and at least one powder selected from the group consisting of Cr, W, V, Mo, Cu, Al, Ce, YSZ, Y, Rare Earths, (RE), MgO, CeO.sub.2, and Y.sub.2 O.sub.3 ; compacting the mixture, followed by heat treating and rapidly recrystallizing to produce a biaxial texture on the article. In some embodiments the alloy article further comprises electromagnetic or electro-optical devices and possesses superconducting properties.

Inferring species richness and turnover by statistical multiresolution texture analysis of satellite imagery.

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Matteo Convertino

Full Text Available BACKGROUND: The quantification of species-richness and species-turnover is essential to effective monitoring of ecosystems. Wetland ecosystems are particularly in need of such monitoring due to their sensitivity to rainfall, water management and other external factors that affect hydrology, soil, and species patterns. A key challenge for environmental scientists is determining the linkage between natural and human stressors, and the effect of that linkage at the species level in space and time. We propose pixel intensity based Shannon entropy for estimating species-richness, and introduce a method based on statistical wavelet multiresolution texture analysis to quantitatively assess interseasonal and interannual species turnover. METHODOLOGY/PRINCIPAL FINDINGS: We model satellite images of regions of interest as textures. We define a texture in an image as a spatial domain where the variations in pixel intensity across the image are both stochastic and multiscale. To compare two textures quantitatively, we first obtain a multiresolution wavelet decomposition of each. Either an appropriate probability density function (pdf model for the coefficients at each subband is selected, and its parameters estimated, or, a non-parametric approach using histograms is adopted. We choose the former, where the wavelet coefficients of the multiresolution decomposition at each subband are modeled as samples from the generalized Gaussian pdf. We then obtain the joint pdf for the coefficients for all subbands, assuming independence across subbands; an approximation that simplifies the computational burden significantly without sacrificing the ability to statistically distinguish textures. We measure the difference between two textures' representative pdf's via the Kullback-Leibler divergence (KL. Species turnover, or [Formula: see text] diversity, is estimated using both this KL divergence and the difference in Shannon entropy. Additionally, we predict species

Comparison of demons deformable registration-based methods for texture analysis of serial thoracic CT scans

Science.gov (United States)

Cunliffe, Alexandra R.; Al-Hallaq, Hania A.; Fei, Xianhan M.; Tuohy, Rachel E.; Armato, Samuel G.

2013-02-01

To determine how 19 image texture features may be altered by three image registration methods, "normal" baseline and follow-up computed tomography (CT) scans from 27 patients were analyzed. Nineteen texture feature values were calculated in over 1,000 32x32-pixel regions of interest (ROIs) randomly placed in each baseline scan. All three methods used demons registration to map baseline scan ROIs to anatomically matched locations in the corresponding transformed follow-up scan. For the first method, the follow-up scan transformation was subsampled to achieve a voxel size identical to that of the baseline scan. For the second method, the follow-up scan was transformed through affine registration to achieve global alignment with the baseline scan. For the third method, the follow-up scan was directly deformed to the baseline scan using demons deformable registration. Feature values in matched ROIs were compared using Bland- Altman 95% limits of agreement. For each feature, the range spanned by the 95% limits was normalized to the mean feature value to obtain the normalized range of agreement, nRoA. Wilcoxon signed-rank tests were used to compare nRoA values across features for the three methods. Significance for individual tests was adjusted using the Bonferroni method. nRoA was significantly smaller for affine-registered scans than for the resampled scans (p=0.003), indicating lower feature value variability between baseline and follow-up scan ROIs using this method. For both of these methods, however, nRoA was significantly higher than when feature values were calculated directly on demons-deformed followup scans (p<0.001). Across features and methods, nRoA values remained below 26%.

Texture Control During the Manufacturing of Nonoriented Electrical Steels

NARCIS (Netherlands)

Kestens, L.; Jacobs, S.

2008-01-01

Methods of modern quantitative texture analysis are applied in order to characterize the crystallographic texture of various non-oriented electrical steel grades in view of their relation with the magnetic properties of the steel sheet. A texture parameter is defined which quantifies the density of

Diagnostic Performance of Mammographic Texture Analysis in the Differential Diagnosis of Benign and Malignant Breast Tumors.

Science.gov (United States)

Li, Zhiming; Yu, Lan; Wang, Xin; Yu, Haiyang; Gao, Yuanxiang; Ren, Yande; Wang, Gang; Zhou, Xiaoming

2017-11-09

The purpose of this study was to investigate the diagnostic performance of mammographic texture analysis in the differential diagnosis of benign and malignant breast tumors. Digital mammography images were obtained from the Picture Archiving and Communication System at our institute. Texture features of mammographic images were calculated. Mann-Whitney U test was used to identify differences between the benign and malignant group. The receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic performance of texture features. Significant differences of texture features of histogram, gray-level co-occurrence matrix (GLCM) and run length matrix (RLM) were found between the benign and malignant breast group (P  .05). The AUROCs of imaging-based diagnosis, texture analysis, and imaging-based diagnosis combined with texture analysis were 0.873, 0.863, and 0.961, respectively. When imaging-based diagnosis was combined with texture analysis, the AUROC was higher than that of imaging-based diagnosis or texture analysis (P benign and malignant breast tumors. Furthermore, the combination of imaging-based diagnosis and texture analysis can significantly improve diagnostic performance. Copyright © 2017 Elsevier Inc. All rights reserved.

Multi Texture Analysis of Colorectal Cancer Continuum Using Multispectral Imagery.

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Ahmad Chaddad

Full Text Available This paper proposes to characterize the continuum of colorectal cancer (CRC using multiple texture features extracted from multispectral optical microscopy images. Three types of pathological tissues (PT are considered: benign hyperplasia, intraepithelial neoplasia and carcinoma.In the proposed approach, the region of interest containing PT is first extracted from multispectral images using active contour segmentation. This region is then encoded using texture features based on the Laplacian-of-Gaussian (LoG filter, discrete wavelets (DW and gray level co-occurrence matrices (GLCM. To assess the significance of textural differences between PT types, a statistical analysis based on the Kruskal-Wallis test is performed. The usefulness of texture features is then evaluated quantitatively in terms of their ability to predict PT types using various classifier models.Preliminary results show significant texture differences between PT types, for all texture features (p-value < 0.01. Individually, GLCM texture features outperform LoG and DW features in terms of PT type prediction. However, a higher performance can be achieved by combining all texture features, resulting in a mean classification accuracy of 98.92%, sensitivity of 98.12%, and specificity of 99.67%.These results demonstrate the efficiency and effectiveness of combining multiple texture features for characterizing the continuum of CRC and discriminating between pathological tissues in multispectral images.

Personal recognition using finger knuckle shape oriented features and texture analysis

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K. Usha

2016-10-01

Full Text Available Finger knuckle print is considered as one of the emerging hand biometric traits due to its potentiality toward the identification of individuals. This paper contributes a new method for personal recognition using finger knuckle print based on two approaches namely, geometric and texture analyses. In the first approach, the shape oriented features of the finger knuckle print are extracted by means of angular geometric analysis and then integrated to achieve better precision rate. Whereas, the knuckle texture feature analysis is carried out by means of multi-resolution transform known as Curvelet transform. This Curvelet transform has the ability to approximate curved singularities with minimum number of Curvelet coefficients. Since, finger knuckle patterns mainly consist of lines and curves, Curvelet transform is highly suitable for its representation. Further, the Curvelet transform decomposes the finger knuckle image into Curvelet sub-bands which are termed as ‘Curvelet knuckle’. Finally, principle component analysis is applied on each Curvelet knuckle for extracting its feature vector through the covariance matrix derived from their Curvelet coefficients. Extensive experiments were conducted using PolyU database and IIT finger knuckle database. The experimental results confirm that, our proposed method shows a high recognition rate of 98.72% with lower false acceptance rate of 0.06%.

Soil texture analysis by laser diffraction - standardization needed

DEFF Research Database (Denmark)

Callesen, Ingeborg; Palviainen, M.; Kjønaas, O. Janne

2017-01-01

Soil texture is a central soil quality property. Laser diffraction (LD) for determination of particle size distribution (PSD) is now widespread due to easy analysis and low cost. However, pretreatment methods and interpretation of the resulting soil PSD’s are not standardized. Comparison of LD data...... with sedimentation and sieving data may cause misinterpretation and confusion. In literature that reports PSD’s based on LD, pretreatment methods, operating procedures and data methods are often underreported or not reported, although literature stressing the importance exists (e.g. Konert and Vandenberghe, 1997...... and many newer; ISO 13320:2009). PSD uncertainty caused by pretreatments and PSD bias caused by plate-shaped clay particles still calls for more method standardization work. If LD is used more generally, new pedotransfer functions for other soil properties (e.g water retention) based on sieving...

Application of Texture Analysis to Study Small Vessel Disease and Blood–Brain Barrier Integrity

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Maria del C. Valdés Hernández

2017-07-01

Full Text Available ObjectivesWe evaluate the alternative use of texture analysis for evaluating the role of blood–brain barrier (BBB in small vessel disease (SVD.MethodsWe used brain magnetic resonance imaging from 204 stroke patients, acquired before and 20 min after intravenous gadolinium administration. We segmented tissues, white matter hyperintensities (WMH and applied validated visual scores. We measured textural features in all tissues pre- and post-contrast and used ANCOVA to evaluate the effect of SVD indicators on the pre-/post-contrast change, Kruskal–Wallis for significance between patient groups and linear mixed models for pre-/post-contrast variations in cerebrospinal fluid (CSF with Fazekas scores.ResultsTextural “homogeneity” increase in normal tissues with higher presence of SVD indicators was consistently more overt than in abnormal tissues. Textural “homogeneity” increased with age, basal ganglia perivascular spaces scores (p < 0.01 and SVD scores (p < 0.05 and was significantly higher in hypertensive patients (p < 0.002 and lacunar stroke (p = 0.04. Hypertension (74% patients, WMH load (median = 1.5 ± 1.6% of intracranial volume, and age (mean = 65.6 years, SD = 11.3 predicted the pre/post-contrast change in normal white matter, WMH, and index stroke lesion. CSF signal increased with increasing SVD post-contrast.ConclusionA consistent general pattern of increasing textural “homogeneity” with increasing SVD and post-contrast change in CSF with increasing WMH suggest that texture analysis may be useful for the study of BBB integrity.

Diabetic peripheral neuropathy assessment through texture based analysis of corneal nerve images

Science.gov (United States)

Silva, Susana F.; Gouveia, Sofia; Gomes, Leonor; Negrão, Luís; João Quadrado, Maria; Domingues, José Paulo; Morgado, António Miguel

2015-05-01

Diabetic peripheral neuropathy (DPN) is one common complication of diabetes. Early diagnosis of DPN often fails due to the non-availability of a simple, reliable, non-invasive method. Several published studies show that corneal confocal microscopy (CCM) can identify small nerve fibre damage and quantify the severity of DPN, using nerve morphometric parameters. Here, we used image texture features, extracted from corneal sub-basal nerve plexus images, obtained in vivo by CCM, to identify DPN patients, using classification techniques. A SVM classifier using image texture features was used to identify (DPN vs. No DPN) DPN patients. The accuracies were 80.6%, when excluding diabetic patients without neuropathy, and 73.5%, when including diabetic patients without diabetic neuropathy jointly with healthy controls. The results suggest that texture analysis might be used as a complementing technique for DPN diagnosis, without requiring nerve segmentation in CCM images. The results also suggest that this technique has enough sensitivity to detect early disorders in the corneal nerves of diabetic patients.

Characterization of PET/CT images using texture analysis: the past, the present... any future?

Energy Technology Data Exchange (ETDEWEB)

Hatt, Mathieu; Visvikis, Dimitris [University of Brest IBSAM, INSERM, UMR 1101, LaTIM, Brest (France); Tixier, Florent; Le Rest, Catherine Cheze [University Hospital, Nuclear Medicine, Poitiers (France); University of Poitiers, Medical school, EE DACTIM, Poitiers (France); Pierce, Larry; Kinahan, Paul E. [University of Washington, Imaging Research Laboratory, Seattle, WA (United States)

2017-01-15

After seminal papers over the period 2009 - 2011, the use of texture analysis of PET/CT images for quantification of intratumour uptake heterogeneity has received increasing attention in the last 4 years. Results are difficult to compare due to the heterogeneity of studies and lack of standardization. There are also numerous challenges to address. In this review we provide critical insights into the recent development of texture analysis for quantifying the heterogeneity in PET/CT images, identify issues and challenges, and offer recommendations for the use of texture analysis in clinical research. Numerous potentially confounding issues have been identified, related to the complex workflow for the calculation of textural features, and the dependency of features on various factors such as acquisition, image reconstruction, preprocessing, functional volume segmentation, and methods of establishing and quantifying correspondences with genomic and clinical metrics of interest. A lack of understanding of what the features may represent in terms of the underlying pathophysiological processes and the variability of technical implementation practices makes comparing results in the literature challenging, if not impossible. Since progress as a field requires pooling results, there is an urgent need for standardization and recommendations/guidelines to enable the field to move forward. We provide a list of correct formulae for usual features and recommendations regarding implementation. Studies on larger cohorts with robust statistical analysis and machine learning approaches are promising directions to evaluate the potential of this approach. (orig.)

Characterization of PET/CT images using texture analysis: the past, the present... any future?

International Nuclear Information System (INIS)

Hatt, Mathieu; Visvikis, Dimitris; Tixier, Florent; Le Rest, Catherine Cheze; Pierce, Larry; Kinahan, Paul E.

2017-01-01

After seminal papers over the period 2009 - 2011, the use of texture analysis of PET/CT images for quantification of intratumour uptake heterogeneity has received increasing attention in the last 4 years. Results are difficult to compare due to the heterogeneity of studies and lack of standardization. There are also numerous challenges to address. In this review we provide critical insights into the recent development of texture analysis for quantifying the heterogeneity in PET/CT images, identify issues and challenges, and offer recommendations for the use of texture analysis in clinical research. Numerous potentially confounding issues have been identified, related to the complex workflow for the calculation of textural features, and the dependency of features on various factors such as acquisition, image reconstruction, preprocessing, functional volume segmentation, and methods of establishing and quantifying correspondences with genomic and clinical metrics of interest. A lack of understanding of what the features may represent in terms of the underlying pathophysiological processes and the variability of technical implementation practices makes comparing results in the literature challenging, if not impossible. Since progress as a field requires pooling results, there is an urgent need for standardization and recommendations/guidelines to enable the field to move forward. We provide a list of correct formulae for usual features and recommendations regarding implementation. Studies on larger cohorts with robust statistical analysis and machine learning approaches are promising directions to evaluate the potential of this approach. (orig.)

Stato dell’arte nella sintesi di texture sonore

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Diemo Schwarz

2016-06-01

Full Text Available The synthesis of sound textures, such as rain, wind, or crowds, is an important application for cinema, multimedia creation, games and installations. However, despite the clearly defined requirements of naturalness and flexibility, no automatic method has yet found widespread use. After clarifying the definition, terminology, and usages of sound texture synthesis, we will give an overview of the many existing methods and approaches, and the few available software implementations, and classify them by the synthesis model they are based on, such as subtractive or additive synthesis, granular synthesis, corpus-based concatenative synthesis, wavelets, or physical modeling. Additionally, an overview is given over analysis methods used for sound texture synthesis, such as segmentation, statistical modeling, timbral analysis, and modeling of transitions.

In-Situ Synchrotron X-ray Study of the Phase and Texture Evolution of Ceria and Superconductor Films Deposited by Chemical Solution Method

DEFF Research Database (Denmark)

Yue, Zhao; Grivel, Jean-Claude; He, Dong

2012-01-01

In situ synchrotron x-ray diffraction is used to study the phase and texture formation of ceria based films and superconductor films deposited by the chemical solution method on technical substrates. Combined analysis using in situ synchrotron x-ray diffraction, thermogravimetry/differential ther......In situ synchrotron x-ray diffraction is used to study the phase and texture formation of ceria based films and superconductor films deposited by the chemical solution method on technical substrates. Combined analysis using in situ synchrotron x-ray diffraction, thermogravimetry...

Texture recognition of medical images with the ICM method

International Nuclear Information System (INIS)

Kinser, Jason M.; Wang Guisong

2004-01-01

The Integrated Cortical Model (ICM) is based upon several models of the mammalian visual cortex and produces pulse images over several iterations. These pulse images tend to isolate segments, edges, and textures that are inherent in the input image. To create a texture recognition engine the pulse spectrum of individual pixels are collected and used to develop a recognition library. Recognition is performed by comparing pulse spectra of unclassified regions of images with the known regions. Because signatures are smaller than images, signature-based computation is quite efficient and parasites can be recognized quickly. The precision of this method depends on the representative of signatures and classification. Our experiment results support the theoretical findings and show perspectives of practical applications of ICM-based method. The advantage of ICM method is using signatures to represent objects. ICM can extract the internal features of objects and represent them with signatures. Signature classification is critical for the precision of recognition

Textural Maturity Analysis and Sedimentary Environment Discrimination Based on Grain Shape Data

Science.gov (United States)

Tunwal, M.; Mulchrone, K. F.; Meere, P. A.

2017-12-01

Morphological analysis of clastic sedimentary grains is an important source of information regarding the processes involved in their formation, transportation and deposition. However, a standardised approach for quantitative grain shape analysis is generally lacking. In this contribution we report on a study where fully automated image analysis techniques were applied to loose sediment samples collected from glacial, aeolian, beach and fluvial environments. A range of shape parameters are evaluated for their usefulness in textural characterisation of populations of grains. The utility of grain shape data in ranking textural maturity of samples within a given sedimentary environment is evaluated. Furthermore, discrimination of sedimentary environment on the basis of grain shape information is explored. The data gathered demonstrates a clear progression in textural maturity in terms of roundness, angularity, irregularity, fractal dimension, convexity, solidity and rectangularity. Textural maturity can be readily categorised using automated grain shape parameter analysis. However, absolute discrimination between different depositional environments on the basis of shape parameters alone is less certain. For example, the aeolian environment is quite distinct whereas fluvial, glacial and beach samples are inherently variable and tend to overlap each other in terms of textural maturity. This is most likely due to a collection of similar processes and sources operating within these environments. This study strongly demonstrates the merit of quantitative population-based shape parameter analysis of texture and indicates that it can play a key role in characterising both loose and consolidated sediments. This project is funded by the Irish Petroleum Infrastructure Programme (www.pip.ie)

In Vivo Imaging of Tau Pathology Using Magnetic Resonance Imaging Textural Analysis

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Niall Colgan

2017-11-01

Full Text Available Background: Non-invasive characterization of the pathological features of Alzheimer's disease (AD could enhance patient management and the development of therapeutic strategies. Magnetic resonance imaging texture analysis (MRTA has been used previously to extract texture descriptors from structural clinical scans in AD to determine cerebral tissue heterogeneity. In this study, we examined the potential of MRTA to specifically identify tau pathology in an AD mouse model and compared the MRTA metrics to histological measures of tau burden.Methods: MRTA was applied to T2 weighted high-resolution MR images of nine 8.5-month-old rTg4510 tau pathology (TG mice and 16 litter matched wild-type (WT mice. MRTA comprised of the filtration-histogram technique, where the filtration step extracted and enhanced features of different sizes (fine, medium, and coarse texture scales, followed by quantification of texture using histogram analysis (mean gray level intensity, mean intensity, entropy, uniformity, skewness, standard-deviation, and kurtosis. MRTA was applied to manually segmented regions of interest (ROI drawn within the cortex, hippocampus, and thalamus regions and the level of tau burden was assessed in equivalent regions using histology.Results: Texture parameters were markedly different between WT and TG in the cortex (E, p < 0.01, K, p < 0.01, the hippocampus (K, p < 0.05 and in the thalamus (K, p < 0.01. In addition, we observed significant correlations between histological measurements of tau burden and kurtosis in the cortex, hippocampus and thalamus.Conclusions: MRTA successfully differentiated WT and TG in brain regions with varying degrees of tau pathology (cortex, hippocampus, and thalamus based on T2 weighted MR images. Furthermore, the kurtosis measurement correlated with histological measures of tau burden. This initial study indicates that MRTA may have a role in the early diagnosis of AD and the assessment of tau pathology using

Texture analysis of articular cartilage traumatic changes in the knee calculated from morphological 3.0 T MR imaging

International Nuclear Information System (INIS)

Boutsikou, Konstantina; Kostopoulos, Spiros; Glotsos, Dimitris; Cavouras, Dionisis; Lavdas, Eleftherios; Oikonomou, Georgia; Malizos, Konstantinos; Fezoulidis, Ioannis V.; Vlychou, Marianna

2013-01-01

Objectives: In the present work, we aim to identify changes in the cartilage texture of the injured knee in young, physically active, patients by computer analysis of MRI images based on 3.0 T morphological sequences. Methods: Fifty-three young patients with training injury or trauma in one knee underwent MRI and arthroscopy. Textural features were computed from the MRI images of the knee-cartilages and two classes were formed of 28 normal and 16 with pathology only in the medial femoral condyle (MFC) cartilage. Results: Textural features with statistically significant differences between the two classes were found only at the MFC and the medial tibial condyle (MTC) areas. Three features-combinations, at the MFC or the MTC, maximized the between classes separation, thus, rendering alterations in cartilage texture due to injury more evident. The MFC cartilage in the pathology class was found more inhomogeneous in the distribution of gray-levels and of lower texture anisotropy and the opposed MTC cartilage, though normal on MRI and arthroscopy, was found to have lower texture anisotropy than cartilage in the normal class. Conclusion: Texture analysis may be used as an adjunct to morphological MR imaging for improving the detection of subtle cartilage changes and contributes to early therapeutic approach

Texture analysis of articular cartilage traumatic changes in the knee calculated from morphological 3.0 T MR imaging

Energy Technology Data Exchange (ETDEWEB)

Boutsikou, Konstantina [Department of Medical Radiologic Technology, Technological Educational Institute of Athens, Ag.Spyridonos, Egaleo, Athens 12210 (Greece); Kostopoulos, Spiros; Glotsos, Dimitris; Cavouras, Dionisis [Department of Medical Instruments Technology, Technological Educational Institute of Athens, Ag.Spyridonos, Egaleo, Athens 12210 (Greece); Lavdas, Eleftherios; Oikonomou, Georgia [Department of Medical Radiologic Technology, Technological Educational Institute of Athens, Ag.Spyridonos, Egaleo, Athens 12210 (Greece); Malizos, Konstantinos [Department of Orthopaedic Surgery, University of Thessaly, School of Health Sciences, University Hospital of Larissa, Biopolis, Larissa 41110 (Greece); Fezoulidis, Ioannis V. [Department of Radiology, University of Thessaly, School of Health Sciences, University Hospital of Larissa, Biopolis, Larissa 41110 (Greece); Vlychou, Marianna, E-mail: mvlychou@med.uth.gr [Department of Radiology, University of Thessaly, School of Health Sciences, University Hospital of Larissa, Biopolis, Larissa 41110 (Greece)

2013-08-15

Objectives: In the present work, we aim to identify changes in the cartilage texture of the injured knee in young, physically active, patients by computer analysis of MRI images based on 3.0 T morphological sequences. Methods: Fifty-three young patients with training injury or trauma in one knee underwent MRI and arthroscopy. Textural features were computed from the MRI images of the knee-cartilages and two classes were formed of 28 normal and 16 with pathology only in the medial femoral condyle (MFC) cartilage. Results: Textural features with statistically significant differences between the two classes were found only at the MFC and the medial tibial condyle (MTC) areas. Three features-combinations, at the MFC or the MTC, maximized the between classes separation, thus, rendering alterations in cartilage texture due to injury more evident. The MFC cartilage in the pathology class was found more inhomogeneous in the distribution of gray-levels and of lower texture anisotropy and the opposed MTC cartilage, though normal on MRI and arthroscopy, was found to have lower texture anisotropy than cartilage in the normal class. Conclusion: Texture analysis may be used as an adjunct to morphological MR imaging for improving the detection of subtle cartilage changes and contributes to early therapeutic approach.

Seismic texture classification. Final report

Energy Technology Data Exchange (ETDEWEB)

Vinther, R.

1997-12-31

The seismic texture classification method, is a seismic attribute that can both recognize the general reflectivity styles and locate variations from these. The seismic texture classification performs a statistic analysis for the seismic section (or volume) aiming at describing the reflectivity. Based on a set of reference reflectivities the seismic textures are classified. The result of the seismic texture classification is a display of seismic texture categories showing both the styles of reflectivity from the reference set and interpolations and extrapolations from these. The display is interpreted as statistical variations in the seismic data. The seismic texture classification is applied to seismic sections and volumes from the Danish North Sea representing both horizontal stratifications and salt diapers. The attribute succeeded in recognizing both general structure of successions and variations from these. Also, the seismic texture classification is not only able to display variations in prospective areas (1-7 sec. TWT) but can also be applied to deep seismic sections. The seismic texture classification is tested on a deep reflection seismic section (13-18 sec. TWT) from the Baltic Sea. Applied to this section the seismic texture classification succeeded in locating the Moho, which could not be located using conventional interpretation tools. The seismic texture classification is a seismic attribute which can display general reflectivity styles and deviations from these and enhance variations not found by conventional interpretation tools. (LN)

A procedure for the evaluation of 2D radiographic texture analysis to assess 3D bone micro-architecture

International Nuclear Information System (INIS)

Apostol, L.; Peyrin, F.; Yot, S.; Basset, O.; Odet, Ch.; Apostal, L.; Peyrin, F.; Boller, E.; Tabary, J.; Dinten, J.M.; Boudousq, V.; Kotzki, P.O.

2004-01-01

Although the diagnosis of osteoporosis is mainly based on Dual X-ray Absorptiometry, it has been shown that trabecular bone micro-architecture is also an important factor in regards of fracture risk, which can be efficiently assessed in vitro using three-dimensional x-ray microtomography (μCT). In vivo, techniques based on high-resolution x-ray radiography associated to texture analysis have been proposed to investigate bone micro-architecture, but their relevance for giving pertinent 3D information is unclear. The purpose of this work was to develop a method for evaluating the relationships between 3D micro-architecture and 2D texture parameters, and optimizing the conditions for radiographic imaging. Bone sample images taken from cortical to cortical were acquired using 3D-synchrotron x-ray μCT at the ESRF. The 3D digital images were further used for two purposes: 1) quantification of three-dimensional bone micro-architecture, 2) simulation of realistic x-ray radiographs under different acquisition conditions. Texture analysis was then applied to these 2D radiographs using a large variety of methods (co-occurrence, spectrum, fractal...). First results of the statistical analysis between 2D and 3D parameters allowed identifying the most relevant 2D texture parameters. (authors)

Usefulness of texture analysis in differentiating transient from persistent part-solid nodules(PSNs: a retrospective study.

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Sang Hwan Lee

Full Text Available BACKGROUND: Early discrimination between transient and persistent par-solid ground-glass nodules (PSNs at CT is essential for patient management. The objective of our study was to retrospectively investigate the value of texture analysis in differentiating pulmonary transient and persistent PSNs in addition to clinical and CT features. METHODS: This retrospective study was performed with IRB approval and a waiver of the requirement for patients' informed consent. From January 2007 to October 2009, we identified 77 individuals (39 men and 38 women; mean age, 55 years with 86 PSNs on thin-section chest CT. Thirty-nine PSNs in 31 individuals were transient and 47 PSNs in 46 patients were persistent. The clinical, CT, and texture features of PSNs were evaluated. To investigate the additional value of texture analysis in differentiating transient from persistent PSNs, logistic regression analysis and C-statistics were performed. RESULTS: Between transient and persistent PSNs, there were significant differences in age, gender, smoking history, and eosinophil count among the clinical features. As for thin-section CT features, there were significant differences in lesion size, solid portion size, and lesion multiplicity. In terms of texture features, there were significant differences in mean attenuation, skewness of whole PSN, attenuation ratio of whole PSN to inner solid portion, and 5-, 10-, 25-, 50-percentile CT numbers of whole PSN. Multivariate analysis revealed eosinophilia, lesion size, lesion multiplicity, mean attenuation of whole PSN, skewness of whole PSN, and 5-percentile CT number were significant independent predictors of transient PSNs. (P<0.05 C-statistics revealed that texture analysis incorporating clinical and CT features (AUC, 92.9% showed significantly higher differentiating performance of transient from persistent PSNs compared with the clinical and CT features alone (AUC, 79.0%. (P =  0.004. CONCLUSION: Texture analysis of

SU-E-T-30: Absorbed Doses Determined by Texture Analysis of Gafchromic EBT3 Films Using Scanning Electron Microscopy: A Feasibility Study

International Nuclear Information System (INIS)

Park, S; Kim, H; Ye, S

2014-01-01

Purpose: The texture analysis method is useful to estimate structural features of images as color, size, and shape. The study aims to determine a dose-response curve by texture analysis of Gafchromic EBT3 film images using scanning electron microscopy (SEM). Methods: The uncoated Gafchromic EBT3 films were prepared to directly scan over the active surface layer of EBT3 film using SEM. The EBT3 films were exposed at a dose range of 0 to 10 Gy using a 6 MV photon beam. The exposed film samples were SEM-scanned at 100X, 1000X, and 3000X magnifications. The four texture features (Homogeneity, Correlation, Contrast, and Energy) were calculated based on the gray level co-occurrence matrix (GLCM) derived from the SEM images at each dose. To validate a correlation between delivered doses and texture features, an R-squared value in linear regression was tested. Results: The results showed that the Correlation index was more suitable as dose indices than the other three texture features due to higher linearity and sensitivity of the dose response curves. Further the Correlation index of 3000X magnified SEM images with 9 pixel offsets had an R-squared value of 0.964. The differences between the delivered doses and the doses measured by this method were 0.9, 1.2, 0.2, and 0.2 Gy at 5, 10, 15, and 20 Gy, respectively. Conclusion: It seems to be feasible to convert micro-scale structural features of χ t χχχ he EBT3 films to absorbed doses using the texture analysis method

Non-Hodgkin lymphoma response evaluation with MRI texture classification

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Heinonen Tomi T

2009-06-01

Full Text Available Abstract Background To show magnetic resonance imaging (MRI texture appearance change in non-Hodgkin lymphoma (NHL during treatment with response controlled by quantitative volume analysis. Methods A total of 19 patients having NHL with an evaluable lymphoma lesion were scanned at three imaging timepoints with 1.5T device during clinical treatment evaluation. Texture characteristics of images were analyzed and classified with MaZda application and statistical tests. Results NHL tissue MRI texture imaged before treatment and under chemotherapy was classified within several subgroups, showing best discrimination with 96% correct classification in non-linear discriminant analysis of T2-weighted images. Texture parameters of MRI data were successfully tested with statistical tests to assess the impact of the separability of the parameters in evaluating chemotherapy response in lymphoma tissue. Conclusion Texture characteristics of MRI data were classified successfully; this proved texture analysis to be potential quantitative means of representing lymphoma tissue changes during chemotherapy response monitoring.

Combining fine texture and coarse color features for color texture classification

Science.gov (United States)

Wang, Junmin; Fan, Yangyu; Li, Ning

2017-11-01

Color texture classification plays an important role in computer vision applications because texture and color are two fundamental visual features. To classify the color texture via extracting discriminative color texture features in real time, we present an approach of combining the fine texture and coarse color features for color texture classification. First, the input image is transformed from RGB to HSV color space to separate texture and color information. Second, the scale-selective completed local binary count (CLBC) algorithm is introduced to extract the fine texture feature from the V component in HSV color space. Third, both H and S components are quantized at an optimal coarse level. Furthermore, the joint histogram of H and S components is calculated, which is considered as the coarse color feature. Finally, the fine texture and coarse color features are combined as the final descriptor and the nearest subspace classifier is used for classification. Experimental results on CUReT, KTH-TIPS, and New-BarkTex databases demonstrate that the proposed method achieves state-of-the-art classification performance. Moreover, the proposed method is fast enough for real-time applications.

An improved high order texture features extraction method with application to pathological diagnosis of colon lesions for CT colonography

Science.gov (United States)

Song, Bowen; Zhang, Guopeng; Lu, Hongbing; Wang, Huafeng; Han, Fangfang; Zhu, Wei; Liang, Zhengrong

2014-03-01

Differentiation of colon lesions according to underlying pathology, e.g., neoplastic and non-neoplastic, is of fundamental importance for patient management. Image intensity based textural features have been recognized as a useful biomarker for the differentiation task. In this paper, we introduce high order texture features, beyond the intensity, such as gradient and curvature, for that task. Based on the Haralick texture analysis method, we introduce a virtual pathological method to explore the utility of texture features from high order differentiations, i.e., gradient and curvature, of the image intensity distribution. The texture features were validated on database consisting of 148 colon lesions, of which 35 are non-neoplastic lesions, using the random forest classifier and the merit of area under the curve (AUC) of the receiver operating characteristics. The results show that after applying the high order features, the AUC was improved from 0.8069 to 0.8544 in differentiating non-neoplastic lesion from neoplastic ones, e.g., hyperplastic polyps from tubular adenomas, tubulovillous adenomas and adenocarcinomas. The experimental results demonstrated that texture features from the higher order images can significantly improve the classification accuracy in pathological differentiation of colorectal lesions. The gain in differentiation capability shall increase the potential of computed tomography (CT) colonography for colorectal cancer screening by not only detecting polyps but also classifying them from optimal polyp management for the best outcome in personalized medicine.

Efficient iris texture analysis method based on Gabor ordinal measures

Science.gov (United States)

Tajouri, Imen; Aydi, Walid; Ghorbel, Ahmed; Masmoudi, Nouri

2017-07-01

With the remarkably increasing interest directed to the security dimension, the iris recognition process is considered to stand as one of the most versatile technique critically useful for the biometric identification and authentication process. This is mainly due to every individual's unique iris texture. A modestly conceived efficient approach relevant to the feature extraction process is proposed. In the first place, iris zigzag "collarette" is extracted from the rest of the image by means of the circular Hough transform, as it includes the most significant regions lying in the iris texture. In the second place, the linear Hough transform is used for the eyelids' detection purpose while the median filter is applied for the eyelashes' removal. Then, a special technique combining the richness of Gabor features and the compactness of ordinal measures is implemented for the feature extraction process, so that a discriminative feature representation for every individual can be achieved. Subsequently, the modified Hamming distance is used for the matching process. Indeed, the advanced procedure turns out to be reliable, as compared to some of the state-of-the-art approaches, with a recognition rate of 99.98%, 98.12%, and 95.02% on CASIAV1.0, CASIAV3.0, and IIT Delhi V1 iris databases, respectively.

X-ray stress analysis in textured polycrystalline materials

International Nuclear Information System (INIS)

Yokoyama, Ryouichi; Harada, Jimpei

2010-01-01

The relationship between stress and strain in polycrystalline materials with fibre texture is examined on the basis of the strain analysis in the constituent crystallites within the Reuss approximation. By introducing the symmetry of reciprocal lattices for the constituent crystallites, the physical meaning of taking an average of the strains observed by X-ray diffraction (XRD) is made clear. By using formulae obtained by the present treatment for the stress-strain relation in cubic specimens with fibre texture in the Laue classes m3-bar m hkl Bragg reflections with h≠k≠l split into doublets owing to the existence of crystallites with two different orientations under the stress field. This technique was confirmed by the profile analysis in XRD data observed for reflections of 222 and 420 in a cubic TiN thin film sputtered on a polyimide film. The technique of the stress analysis and its confirmation are introduced. (author)

Fabrication of textured Ni–9.3at.%W substrate by electropulsing intermediate annealing method

International Nuclear Information System (INIS)

Liu, Jianan; Liu, Wei; Tang, Guoyi; Zhu, Rufei

2014-01-01

Highlights: •It’s the first time that EIA is used on Ni9 W substrate production. •Compared with CIA, EIA trends to sharpen the rolling texture. •Improved cube recrystallization texture is obtained by EIA. •EIA provides a highly efficient approach for Ni9 W substrate manufacture. -- Abstract: Sharp cube texture is difficult to obtain in high W content Ni–W alloy substrates used for coated conductors. In this paper, a new method called electropulsing intermediate annealing (EIA) is adopted to optimize the rolling and recrystallization texture of Ni–9.3 at.%W substrate. It is found that, compared with conventional intermediate annealing (CIA) at the same temperature, EIA trends to increase the Copper, S and Brass components, suppress the Goss component in rolling texture. Higher cube recrystallization texture is obtained at relatively low temperature by EIA in a shorter time. The effect of EIA on texture is attributed to the enhancement of recovery process resulting from the athermal effects

Texture analysis for mapping Tamarix parviflora using aerial photographs along the Cache Creek, California.

Science.gov (United States)

Ge, Shaokui; Carruthers, Raymond; Gong, Peng; Herrera, Angelica

2006-03-01

Natural color photographs were used to detect the coverage of saltcedar, Tamarix parviflora, along a 40 km portion of Cache Creek near Woodland, California. Historical aerial photographs from 2001 were retrospectively evaluated and compared with actual ground-based information to assess accuracy of the assessment process. The color aerial photos were sequentially digitized, georeferenced, classified using color and texture methods, and mosaiced into maps for field use. Eight types of ground cover (Tamarix, agricultural crops, roads, rocks, water bodies, evergreen trees, non-evergreen trees and shrubs (excluding Tamarix)) were selected from the digitized photos for separability analysis and supervised classification. Due to color similarities among the eight cover types, the average separability, based originally only on color, was very low. The separability was improved significantly through the inclusion of texture analysis. Six types of texture measures with various window sizes were evaluated. The best texture was used as an additional feature along with the color, for identifying Tamarix. A total of 29 color photographs were processed to detect Tamarix infestations using a combination of the original digital images and optimal texture features. It was found that the saltcedar covered a total of 3.96 km(2) (396 hectares) within the study area. For the accuracy assessment, 95 classified samples from the resulting map were checked in the field with a global position system (GPS) unit to verify Tamarix presence. The producer's accuracy was 77.89%. In addition, 157 independently located ground sites containing saltcedar were compared with the classified maps, producing a user's accuracy of 71.33%.

Comparison of textural atributes of selected meat sausages using instrumental analysis

OpenAIRE

Vladimír Vietoris; Ľubomír Lopašovský; Peter Zajác; Jozef Čurlej; Jozef Čapla

2013-01-01

The aim of the study was to compare textural atributes of selected meat sausages using instrumental analysis. For this purpose, seven different meat sausage samples were treated by instrumental analysis, by the use of Warner-Bratzler probe,  to find differences for two selected textural parameter firmness and work of shear. As expected, various values of mentioned atributes were obtained for different samples tested in fresh stage and after storage under controlled conditions (48 hrs., 30 °...

Characterising the disintegration properties of tablets in opaque media using texture analysis

OpenAIRE

Scheuerle, Rebekah L.; Gerrard, Stephen E.; Kendall, Richard A.; Tuleu, Catherine; Slater, Nigel K.H.; Mahbubani, Krishnaa T.

2015-01-01

Tablet disintegration characterisation is used in pharmaceutical research, development, and quality control. Standard methods used to characterise tablet disintegration are often dependent on visual observation in measurement of disintegration times. This presents a challenge for disintegration studies of tablets in opaque, physiologically relevant media that could be useful for tablet formulation optimisation. In this study is explored an application of texture analysis disintegration testin...

The quantitative representation of fiber-and sheet-texture in metals of cubic system

International Nuclear Information System (INIS)

Kim, H.J.; Kim, S.C.; Chun, B.C.; Lee, C.Y.

1983-01-01

This is the first article of a series dealing with studies on the quantitative representation of fiber-and sheet-type textures in metals of cubic crystal system. Texture measurements by neutron diffraction method are analyzed using Bunge's series expansion method and the effect of series truncation is studied for samples of various texture sharpness. The present article describes two computer programs, TXFIB and TXSHT, develped for the analysis of the respective fiber-and sheet-type texture. Using these computer programs, the orientation distribution function can be expanded in the series of generalized spherical harmonics up to 58th term from 6 experimental pole figures as input. Estimations of various errors involved in the texture analysis and texture sharpness index are also included in the programs. (Author)

An Adaptive Dense Matching Method for Airborne Images Using Texture Information

Directory of Open Access Journals (Sweden)

ZHU Qing

2017-01-01

Full Text Available Semi-global matching (SGM is essentially a discrete optimization for the disparity value of each pixel, under the assumption of disparity continuities. SGM overcomes the influence of the disparity discontinuities by a set of parameters. Using smaller parameters, the continuity constraint is weakened, which will cause significant noises in planar and textureless areas, reflected as the fluctuations on the final surface reconstruction. On the other hands, larger parameters will impose too much constraints on continuities, which may lead to losses of sharp features. To address this problem, this paper proposes an adaptive dense stereo matching methods for airborne images using with texture information. Firstly, the texture is quantified, and under the assumption that disparity variation is directly proportional to the texture information, the adaptive parameters are gauged accordingly. Second, SGM is adopted to optimize the discrete disparities using the adaptively tuned parameters. Experimental evaluations using the ISPRS benchmark dataset and images obtained by the SWDC-5 have revealed that the proposed method will significantly improve the visual qualities of the point clouds.

SU-D-9A-03: STAMP: Simulator for Texture Analysis in MRI/PET

Energy Technology Data Exchange (ETDEWEB)

Laberge, S; Vallieres, M; Levesque, I R.; El Naqa, I [McGill University, Montreal, QC (Canada)

2014-06-01

Purpose: To develop a convenient simulation platform to facilitate PET/MR image analysis with the prospect of gaining a better understanding of the influence of acquisition parameters on PET/MRI textural features. The simulation platform is demonstrated by showing textural variations of a representative case study using different image acquisition parameters. Methods: The simulation platform is composed of MRI simulators JEMRIS and SIMRI to achieve simulations of customized MRI sequences on sample tumor models. The PET simulator GATE is used to get 2D and 3D Monte Carlo acquisitions of voxelized PET sources using a phantom geometry and a customized scanner architecture. The platform incorporates a series of graphical user interfaces written in Matlab. Two GUIs are used to facilitate communication with the simulation executables installed on a computer cluster. A third GUI is used to collect and display the clinical and simulated images, as well as fused PET/MRI images, and perform computation of textural features.To illustrate the capabilities of this platform, one FDG-PET and T1-weighted (T1w) digitized tumor models were generated from clinical images of a soft-tissue sarcoma patient. Numerically simulated MR images were produced using 3 different echo times (TE) and 5 different repetition times (TR). PET 2D images were simulated using an OSEM algorithm with 1 to 32 iterations and a post-reconstruction Gaussian filter of 0, 2, 4 or 6 mm width. Results: STAMP was successfully used to produce numerically simulated FDG-PET and MRI images, and to calculate their corresponding textures. Three typical textures (GLCM-Contrast, GLSZM-ZSV and NGTDM-Coarseness) were found to vary by a range of 45% on average compared to reference scanning conditions in the case of FDG-PET, and by a range of 40% in the case of T1w MRI. Conclusion: We have successfully developed a Matlab-based simulation platform to facilitate PET/MRI texture image analysis for outcome prediction.

Characterization of Enhancing MS Lesions by Dynamic Texture Parameter Analysis of Dynamic Susceptibility Perfusion Imaging

Directory of Open Access Journals (Sweden)

Rajeev K. Verma

2016-01-01

Full Text Available Purpose. The purpose of this study was to investigate statistical differences with MR perfusion imaging features that reflect the dynamics of Gadolinium-uptake in MS lesions using dynamic texture parameter analysis (DTPA. Methods. We investigated 51 MS lesions (25 enhancing, 26 nonenhancing lesions of 12 patients. Enhancing lesions (n=25 were prestratified into enhancing lesions with increased permeability (EL+; n=11 and enhancing lesions with subtle permeability (EL−; n=14. Histogram-based feature maps were computed from the raw DSC-image time series and the corresponding texture parameters were analyzed during the inflow, outflow, and reperfusion time intervals. Results. Significant differences (p<0.05 were found between EL+ and EL− and between EL+ and nonenhancing inactive lesions (NEL. Main effects between EL+ versus EL− and EL+ versus NEL were observed during reperfusion (mainly in mean and standard deviation (SD: EL+ versus EL− and EL+ versus NEL, while EL− and NEL differed only in their SD during outflow. Conclusion. DTPA allows grading enhancing MS lesions according to their perfusion characteristics. Texture parameters of EL− were similar to NEL, while EL+ differed significantly from EL− and NEL. Dynamic texture analysis may thus be further investigated as noninvasive endogenous marker of lesion formation and restoration.

Textural features for radar image analysis

Science.gov (United States)

Shanmugan, K. S.; Narayanan, V.; Frost, V. S.; Stiles, J. A.; Holtzman, J. C.

1981-01-01

Texture is seen as an important spatial feature useful for identifying objects or regions of interest in an image. While textural features have been widely used in analyzing a variety of photographic images, they have not been used in processing radar images. A procedure for extracting a set of textural features for characterizing small areas in radar images is presented, and it is shown that these features can be used in classifying segments of radar images corresponding to different geological formations.

TOPICAL REVIEW Textured silicon nitride: processing and anisotropic properties

Directory of Open Access Journals (Sweden)

Xinwen Zhu and Yoshio Sakka

2008-01-01

Full Text Available Textured silicon nitride (Si3N4 has been intensively studied over the past 15 years because of its use for achieving its superthermal and mechanical properties. In this review we present the fundamental aspects of the processing and anisotropic properties of textured Si3N4, with emphasis on the anisotropic and abnormal grain growth of β-Si3N4, texture structure and texture analysis, processing methods and anisotropic properties. On the basis of the texturing mechanisms, the processing methods described in this article have been classified into two types: hot-working (HW and templated grain growth (TGG. The HW method includes the hot-pressing, hot-forging and sinter-forging techniques, and the TGG method includes the cold-pressing, extrusion, tape-casting and strong magnetic field alignment techniques for β-Si3N4 seed crystals. Each processing technique is thoroughly discussed in terms of theoretical models and experimental data, including the texturing mechanisms and the factors affecting texture development. Also, methods of synthesizing the rodlike β-Si3N4 single crystals are presented. Various anisotropic properties of textured Si3 N4 and their origins are thoroughly described and discussed, such as hardness, elastic modulus, bending strength, fracture toughness, fracture energy, creep behavior, tribological and wear behavior, erosion behavior, contact damage behavior and thermal conductivity. Models are analyzed to determine the thermal anisotropy by considering the intrinsic thermal anisotropy, degree of orientation and various microstructure factors. Textured porous Si3N4 with a unique microstructure composed of oriented elongated β-Si3N4 and anisotropic pores is also described for the first time, with emphasis on its unique mechanical and thermal-mechanical properties. Moreover, as an important related material, textured α-Sialon is also reviewed, because the presence of elongated α-Sialon grains allows the production of textured �

Prostate-specific membrane antigen PET/MRI validation of MR textural analysis for detection of transition zone prostate cancer.

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Bates, Anthony; Miles, Kenneth

2017-12-01

To validate MR textural analysis (MRTA) for detection of transition zone (TZ) prostate cancer through comparison with co-registered prostate-specific membrane antigen (PSMA) PET-MR. Retrospective analysis was performed for 30 men who underwent simultaneous PSMA PET-MR imaging for staging of prostate cancer. Thirty texture features were derived from each manually contoured T2-weighted, transaxial, prostatic TZ using texture analysis software that applies a spatial band-pass filter and quantifies texture through histogram analysis. Texture features of the TZ were compared to PSMA expression on the corresponding PET images. The Benjamini-Hochberg correction controlled the false discovery rate at prostate cancer. • Prostate transition zone (TZ) MR texture analysis may assist in prostate cancer detection. • Abnormal transition zone PSMA expression correlates with altered texture on T2-weighted MR. • TZ with abnormal PSMA expression demonstrates significantly reduced MI, SD and MPP.

Directional fractal signature methods for trabecular bone texture in hand radiographs: Data from the Osteoarthritis Initiative

International Nuclear Information System (INIS)

Wolski, M.; Podsiadlo, P.; Stachowiak, G. W.

2014-01-01

Purpose: To develop directional fractal signature methods for the analysis of trabecular bone (TB) texture in hand radiographs. Problems associated with the small size of hand bones and the orientation of fingers were addressed. Methods: An augmented variance orientation transform (AVOT) and a quadrant rotating grid (QRG) methods were developed. The methods calculate fractal signatures (FSs) in different directions. Unlike other methods they have the search region adjusted according to the size of bone region of interest (ROI) to be analyzed and they produce FSs defined with respect to any chosen reference direction, i.e., they work for arbitrary orientation of fingers. Five parameters at scales ranging from 2 to 14 pixels (depending on image size and method) were derived from rose plots of Hurst coefficients, i.e., FS in dominating roughness (FS Sta ), vertical (FS V ) and horizontal (FS H ) directions, aspect ratio (StrS), and direction signatures (StdS), respectively. The accuracy in measuring surface roughness and isotropy/anisotropy was evaluated using 3600 isotropic and 800 anisotropic fractal surface images of sizes between 20 × 20 and 64 × 64 pixels. The isotropic surfaces had FDs ranging from 2.1 to 2.9 in steps of 0.1, and the anisotropic surfaces had two dominating directions of 30° and 120°. The methods were used to find differences in hand TB textures between 20 matched pairs of subjects with (cases: approximate Kellgren-Lawrence (KL) grade ≥2) and without (controls: approximate KL grade <2) radiographic hand osteoarthritis (OA). The OA Initiative public database was used and 20 × 20 pixel bone ROIs were selected on 5th distal and middle phalanges. The performance of the AVOT and QRG methods was compared against a variance orientation transform (VOT) method developed earlier [M. Wolski, P. Podsiadlo, and G. W. Stachowiak, “Directional fractal signature analysis of trabecular bone: evaluation of different methods to detect early osteoarthritis

Application of CT texture analysis in predicting histopathological characteristics of gastric cancers

International Nuclear Information System (INIS)

Liu, Shunli; Liu, Song; Ji, Changfeng; Zheng, Huanhuan; Pan, Xia; Zhang, Yujuan; He, Jian; Zhou, Zhengyang; Guan, Wenxian; Chen, Ling; Guan, Yue; Li, Weifeng; Ge, Yun

2017-01-01

To explore the application of computed tomography (CT) texture analysis in predicting histopathological features of gastric cancers. Preoperative contrast-enhanced CT images and postoperative histopathological features of 107 patients (82 men, 25 women) with gastric cancers were retrospectively reviewed. CT texture analysis generated: (1) mean attenuation, (2) standard deviation, (3) max frequency, (4) mode, (5) minimum attenuation, (6) maximum attenuation, (7) the fifth, 10th, 25th, 50th, 75th and 90th percentiles, and (8) entropy. Correlations between CT texture parameters and histopathological features were analysed. Mean attenuation, maximum attenuation, all percentiles and mode derived from portal venous CT images correlated significantly with differentiation degree and Lauren classification of gastric cancers (r, -0.231 ∝-0.324, 0.228 ∝ 0.321, respectively). Standard deviation and entropy derived from arterial CT images also correlated significantly with Lauren classification of gastric cancers (r = -0.265, -0.222, respectively). In arterial phase analysis, standard deviation and entropy were significantly lower in gastric cancers with than those without vascular invasion; however, minimum attenuation was significantly higher in gastric cancers with than those without vascular invasion. CT texture analysis held great potential in predicting differentiation degree, Lauren classification and vascular invasion status of gastric cancers. (orig.)

Application of CT texture analysis in predicting histopathological characteristics of gastric cancers

Energy Technology Data Exchange (ETDEWEB)

Liu, Shunli; Liu, Song; Ji, Changfeng; Zheng, Huanhuan; Pan, Xia; Zhang, Yujuan; He, Jian; Zhou, Zhengyang [The Affiliated Hospital of Nanjing University Medical School, Department of Radiology, Nanjing Drum Tower Hospital, Nanjing, Jiangsu Province (China); Guan, Wenxian [The Affiliated Hospital of Nanjing University Medical School, Department of Gastrointestinal Surgery, Nanjing Drum Tower Hospital, Nanjing (China); Chen, Ling [The Affiliated Hospital of Nanjing University Medical School, Department of Pathology, Nanjing Drum Tower Hospital, Nanjing, Jiangsu Province (China); Guan, Yue; Li, Weifeng; Ge, Yun [Nanjing University, School of Electronic Science and Engineering, Nanjing (China)

2017-12-15

To explore the application of computed tomography (CT) texture analysis in predicting histopathological features of gastric cancers. Preoperative contrast-enhanced CT images and postoperative histopathological features of 107 patients (82 men, 25 women) with gastric cancers were retrospectively reviewed. CT texture analysis generated: (1) mean attenuation, (2) standard deviation, (3) max frequency, (4) mode, (5) minimum attenuation, (6) maximum attenuation, (7) the fifth, 10th, 25th, 50th, 75th and 90th percentiles, and (8) entropy. Correlations between CT texture parameters and histopathological features were analysed. Mean attenuation, maximum attenuation, all percentiles and mode derived from portal venous CT images correlated significantly with differentiation degree and Lauren classification of gastric cancers (r, -0.231 ∝-0.324, 0.228 ∝ 0.321, respectively). Standard deviation and entropy derived from arterial CT images also correlated significantly with Lauren classification of gastric cancers (r = -0.265, -0.222, respectively). In arterial phase analysis, standard deviation and entropy were significantly lower in gastric cancers with than those without vascular invasion; however, minimum attenuation was significantly higher in gastric cancers with than those without vascular invasion. CT texture analysis held great potential in predicting differentiation degree, Lauren classification and vascular invasion status of gastric cancers. (orig.)

Gastric cancer: texture analysis from multidetector computed tomography as a potential preoperative prognostic biomarker

Energy Technology Data Exchange (ETDEWEB)

Giganti, Francesco; Salerno, Annalaura; Marra, Paolo; Esposito, Antonio; Del Maschio, Alessandro; De Cobelli, Francesco [Department of Radiology and Centre for Experimental Imaging San Raffaele Scientific Institute, Milan (Italy); San Raffaele Vita-Salute University, Milan (Italy); Antunes, Sofia [San Raffaele Scientific Institute, Centre for Experimental Imaging, Milan (Italy); Ambrosi, Alessandro [San Raffaele Vita-Salute University, Milan (Italy); Nicoletti, Roberto [Department of Radiology and Centre for Experimental Imaging San Raffaele Scientific Institute, Milan (Italy); Orsenigo, Elena [San Raffaele Scientific Institute, Department of Surgery, Milan (Italy); Chiari, Damiano; Staudacher, Carlo [San Raffaele Vita-Salute University, Milan (Italy); San Raffaele Scientific Institute, Department of Surgery, Milan (Italy); Albarello, Luca [San Raffaele Scientific Institute, Pathology Unit, Milan (Italy)

2017-05-15

To investigate the association between preoperative texture analysis from multidetector computed tomography (MDCT) and overall survival in patients with gastric cancer. Institutional review board approval and informed consent were obtained. Fifty-six patients with biopsy-proved gastric cancer were examined by MDCT and treated with surgery. Image features from texture analysis were quantified, with and without filters for fine to coarse textures. The association with survival time was assessed using Kaplan-Meier and Cox analysis. The following parameters were significantly associated with a negative prognosis, according to different thresholds: energy [no filter] - Logarithm of relative risk (Log RR): 3.25; p = 0.046; entropy [no filter] (Log RR: 5.96; p = 0.002); entropy [filter 1.5] (Log RR: 3.54; p = 0.027); maximum Hounsfield unit value [filter 1.5] (Log RR: 3.44; p = 0.027); skewness [filter 2] (Log RR: 5.83; p = 0.004); root mean square [filter 1] (Log RR: - 2.66; p = 0.024) and mean absolute deviation [filter 2] (Log RR: - 4.22; p = 0.007). Texture analysis could increase the performance of a multivariate prognostic model for risk stratification in gastric cancer. Further evaluations are warranted to clarify the clinical role of texture analysis from MDCT. (orig.)

Semantic attributes based texture generation

Science.gov (United States)

Chi, Huifang; Gan, Yanhai; Qi, Lin; Dong, Junyu; Madessa, Amanuel Hirpa

2018-04-01

Semantic attributes are commonly used for texture description. They can be used to describe the information of a texture, such as patterns, textons, distributions, brightness, and so on. Generally speaking, semantic attributes are more concrete descriptors than perceptual features. Therefore, it is practical to generate texture images from semantic attributes. In this paper, we propose to generate high-quality texture images from semantic attributes. Over the last two decades, several works have been done on texture synthesis and generation. Most of them focusing on example-based texture synthesis and procedural texture generation. Semantic attributes based texture generation still deserves more devotion. Gan et al. proposed a useful joint model for perception driven texture generation. However, perceptual features are nonobjective spatial statistics used by humans to distinguish different textures in pre-attentive situations. To give more describing information about texture appearance, semantic attributes which are more in line with human description habits are desired. In this paper, we use sigmoid cross entropy loss in an auxiliary model to provide enough information for a generator. Consequently, the discriminator is released from the relatively intractable mission of figuring out the joint distribution of condition vectors and samples. To demonstrate the validity of our method, we compare our method to Gan et al.'s method on generating textures by designing experiments on PTD and DTD. All experimental results show that our model can generate textures from semantic attributes.

Characterisation of radiotherapy planning volumes using textural analysis

Energy Technology Data Exchange (ETDEWEB)

Nailon, William H.; Redpath, Anthony T.; McLaren, Duncan B. (Dept. of Oncology Physics, Edinburgh Cancer Centre, Western General Hospital, Edinburgh (United Kingdom))

2008-08-15

Computer-based artificial intelligence methods for classification and delineation of the gross tumour volume (GTV) on computerised tomography (CT) and magnetic resonance (MR) images do not, at present, provide the accuracy required for radiotherapy applications. This paper describes an image analysis method for classification of distinct regions within the GTV, and other clinically relevant regions, on CT images acquired on eight bladder cancer patients at the radiotherapy planning stage and thereafter at regular intervals during treatment. Statistical and fractal textural features (N=27) were calculated on the bladder, rectum and a control region identified on axial, coronal and sagittal CT images. Unsupervised classification results demonstrate that with a reduced feature set (N=3) the approach offers significant classification accuracy on axial, coronal and sagittal CT image planes and has the potential to be developed further for radiotherapy applications, particularly towards an automatic outlining approach

Characterisation of radiotherapy planning volumes using textural analysis

International Nuclear Information System (INIS)

Nailon, William H.; Redpath, Anthony T.; McLaren, Duncan B.

2008-01-01

Computer-based artificial intelligence methods for classification and delineation of the gross tumour volume (GTV) on computerised tomography (CT) and magnetic resonance (MR) images do not, at present, provide the accuracy required for radiotherapy applications. This paper describes an image analysis method for classification of distinct regions within the GTV, and other clinically relevant regions, on CT images acquired on eight bladder cancer patients at the radiotherapy planning stage and thereafter at regular intervals during treatment. Statistical and fractal textural features (N=27) were calculated on the bladder, rectum and a control region identified on axial, coronal and sagittal CT images. Unsupervised classification results demonstrate that with a reduced feature set (N=3) the approach offers significant classification accuracy on axial, coronal and sagittal CT image planes and has the potential to be developed further for radiotherapy applications, particularly towards an automatic outlining approach

Texture-based classification for characterizing regions on remote sensing images

Science.gov (United States)

Borne, Frédéric; Viennois, Gaëlle

2017-07-01

Remote sensing classification methods mostly use only the physical properties of pixels or complex texture indexes but do not lead to recommendation for practical applications. Our objective was to design a texture-based method, called the Paysages A PRIori method (PAPRI), which works both at pixel and neighborhood level and which can handle different spatial scales of analysis. The aim was to stay close to the logic of a human expert and to deal with co-occurrences in a more efficient way than other methods. The PAPRI method is pixelwise and based on a comparison of statistical and spatial reference properties provided by the expert with local properties computed in varying size windows centered on the pixel. A specific distance is computed for different windows around the pixel and a local minimum leads to choosing the class in which the pixel is to be placed. The PAPRI method brings a significant improvement in classification quality for different kinds of images, including aerial, lidar, high-resolution satellite images as well as texture images from the Brodatz and Vistex databases. This work shows the importance of texture analysis in understanding remote sensing images and for future developments.

Quantitative analysis of textures produced in a hot-extruded zirconium plate

International Nuclear Information System (INIS)

Couterne, J.

1967-01-01

The textures produced in zirconium by the extrusion at 730 deg C of a cylindrical billet in the form of a plate having a rectangular cross-section, have been studied by the Schulz method using an isotropic standard. These textures have been determined both parallel to the plane of the plate and parallel to the plane of the sides, All the results are analyzed in a final discussion which makes it possible to show, in particular near the edges of the plate, that certain components of the textures observed in the two series of recordings are in fact aspects of the same texture seen from two different angles, It is shown furthermore that the zirconium thus shaped has cold-work textures and als recrystallisation textures formed after the preceding cold-working, If the observed textures are considered schematically, it can be see that two of these have already been described in the literature and are similar to those found in rolled products: these textures are such that the (0001) planes are inclined at 36 deg C and 60 deg C respectively with respect to a plan tangential to the curve (envelope of transverse flow rates) resulting from the extrusion geometry under consideration; the third texture is defined. by the fact that the (0001) plane is orthogonal to the exterior surfaces of the plate. The direction of extrusion associated with these planes and common to the three textures is of the type , Dilatometric tests have been carried out on samples taken both parallel and perpendicular to the extrusion direction, These tests show that the zirconium is dilatometrically anisotropic and that a plot of (α v )-a against temperature shows a change of gradient at 400 deg C, this latter effect may be due to the change in the electronic configuration of the metal occurring at this temperature. (author) [fr

Statistical-techniques-based computer-aided diagnosis (CAD) using texture feature analysis: application in computed tomography (CT) imaging to fatty liver disease

Science.gov (United States)

Chung, Woon-Kwan; Park, Hyong-Hu; Im, In-Chul; Lee, Jae-Seung; Goo, Eun-Hoe; Dong, Kyung-Rae

2012-09-01

This paper proposes a computer-aided diagnosis (CAD) system based on texture feature analysis and statistical wavelet transformation technology to diagnose fatty liver disease with computed tomography (CT) imaging. In the target image, a wavelet transformation was performed for each lesion area to set the region of analysis (ROA, window size: 50 × 50 pixels) and define the texture feature of a pixel. Based on the extracted texture feature values, six parameters (average gray level, average contrast, relative smoothness, skewness, uniformity, and entropy) were determined to calculate the recognition rate for a fatty liver. In addition, a multivariate analysis of the variance (MANOVA) method was used to perform a discriminant analysis to verify the significance of the extracted texture feature values and the recognition rate for a fatty liver. According to the results, each texture feature value was significant for a comparison of the recognition rate for a fatty liver ( p fatty liver had the same scale as that for the F-value, showing 100% (average gray level) at the maximum and 80% (average contrast) at the minimum. Therefore, the recognition rate is believed to be a useful clinical value for the automatic detection and computer-aided diagnosis (CAD) using the texture feature value. Nevertheless, further study on various diseases and singular diseases will be needed in the future.

Characterising the disintegration properties of tablets in opaque media using texture analysis.

Science.gov (United States)

Scheuerle, Rebekah L; Gerrard, Stephen E; Kendall, Richard A; Tuleu, Catherine; Slater, Nigel K H; Mahbubani, Krishnaa T

2015-01-01

Tablet disintegration characterisation is used in pharmaceutical research, development, and quality control. Standard methods used to characterise tablet disintegration are often dependent on visual observation in measurement of disintegration times. This presents a challenge for disintegration studies of tablets in opaque, physiologically relevant media that could be useful for tablet formulation optimisation. This study has explored an application of texture analysis disintegration testing, a non-visual, quantitative means of determining tablet disintegration end point, by analysing the disintegration behaviour of two tablet formulations in opaque media. In this study, the disintegration behaviour of one tablet formulation manufactured in-house, and Sybedia Flashtab placebo tablets in water, bovine, and human milk were characterised. A novel method is presented to characterise the disintegration process and to quantify the disintegration end points of the tablets in various media using load data generated by a texture analyser probe. The disintegration times in the different media were found to be statistically different (Pdisintegration times from each other in human versus bovine milk (adjusted P value 0.1685). Copyright © 2015 Elsevier B.V. All rights reserved.

On uniform resampling and gaze analysis of bidirectional texture functions

Czech Academy of Sciences Publication Activity Database

Filip, Jiří; Chantler, M.J.; Haindl, Michal

2009-01-01

Roč. 6, č. 3 (2009), s. 1-15 ISSN 1544-3558 R&D Projects: GA MŠk 1M0572; GA ČR GA102/08/0593 Grant - others:EC Marie Curie(BE) 41358 Institutional research plan: CEZ:AV0Z10750506 Keywords : BTF * texture * eye tracking Subject RIV: BD - Theory of Information Impact factor: 1.447, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-on uniform resampling and gaze analysis of bidirectional texture functions.pdf

Multi-Parametric MRI and Texture Analysis to Visualize Spatial Histologic Heterogeneity and Tumor Extent in Glioblastoma.

Directory of Open Access Journals (Sweden)

Leland S Hu

Full Text Available Genetic profiling represents the future of neuro-oncology but suffers from inadequate biopsies in heterogeneous tumors like Glioblastoma (GBM. Contrast-enhanced MRI (CE-MRI targets enhancing core (ENH but yields adequate tumor in only ~60% of cases. Further, CE-MRI poorly localizes infiltrative tumor within surrounding non-enhancing parenchyma, or brain-around-tumor (BAT, despite the importance of characterizing this tumor segment, which universally recurs. In this study, we use multiple texture analysis and machine learning (ML algorithms to analyze multi-parametric MRI, and produce new images indicating tumor-rich targets in GBM.We recruited primary GBM patients undergoing image-guided biopsies and acquired pre-operative MRI: CE-MRI, Dynamic-Susceptibility-weighted-Contrast-enhanced-MRI, and Diffusion Tensor Imaging. Following image coregistration and region of interest placement at biopsy locations, we compared MRI metrics and regional texture with histologic diagnoses of high- vs low-tumor content (≥80% vs <80% tumor nuclei for corresponding samples. In a training set, we used three texture analysis algorithms and three ML methods to identify MRI-texture features that optimized model accuracy to distinguish tumor content. We confirmed model accuracy in a separate validation set.We collected 82 biopsies from 18 GBMs throughout ENH and BAT. The MRI-based model achieved 85% cross-validated accuracy to diagnose high- vs low-tumor in the training set (60 biopsies, 11 patients. The model achieved 81.8% accuracy in the validation set (22 biopsies, 7 patients.Multi-parametric MRI and texture analysis can help characterize and visualize GBM's spatial histologic heterogeneity to identify regional tumor-rich biopsy targets.

A Framework for Establishing Standard Reference Scale of Texture by Multivariate Statistical Analysis Based on Instrumental Measurement and Sensory Evaluation.

Science.gov (United States)

Zhi, Ruicong; Zhao, Lei; Xie, Nan; Wang, Houyin; Shi, Bolin; Shi, Jingye

2016-01-13

A framework of establishing standard reference scale (texture) is proposed by multivariate statistical analysis according to instrumental measurement and sensory evaluation. Multivariate statistical analysis is conducted to rapidly select typical reference samples with characteristics of universality, representativeness, stability, substitutability, and traceability. The reasonableness of the framework method is verified by establishing standard reference scale of texture attribute (hardness) with Chinese well-known food. More than 100 food products in 16 categories were tested using instrumental measurement (TPA test), and the result was analyzed with clustering analysis, principal component analysis, relative standard deviation, and analysis of variance. As a result, nine kinds of foods were determined to construct the hardness standard reference scale. The results indicate that the regression coefficient between the estimated sensory value and the instrumentally measured value is significant (R(2) = 0.9765), which fits well with Stevens's theory. The research provides reliable a theoretical basis and practical guide for quantitative standard reference scale establishment on food texture characteristics.

Application of Image Texture Analysis for Evaluation of X-Ray Images of Fungal-Infected Maize Kernels

DEFF Research Database (Denmark)

Orina, Irene; Manley, Marena; Kucheryavskiy, Sergey V.

2018-01-01

The feasibility of image texture analysis to evaluate X-ray images of fungal-infected maize kernels was investigated. X-ray images of maize kernels infected with Fusarium verticillioides and control kernels were acquired using high-resolution X-ray micro-computed tomography. After image acquisition...... developed using partial least squares discriminant analysis (PLS-DA), and accuracies of 67 and 73% were achieved using first-order statistical features and GLCM extracted features, respectively. This work provides information on the possible application of image texture as method for analysing X-ray images......., homogeneity and contrast) were extracted from the side, front and top views of each kernel and used as inputs for principal component analysis (PCA). The first-order statistical image features gave a better separation of the control from infected kernels on day 8 post-inoculation. Classification models were...

Characterization of Tumor Heterogeneity by Texture Analysis in 18F-FDG PET images: A Pilot Study

Energy Technology Data Exchange (ETDEWEB)

Manso, M.; Martino, M.E.; Rodriguez, E.A.; Landaeta, L.C.; Carreras, J.L.; Calvo, F.A.; Desco, M.; Pascau, J.; Muñoz-Barrutia, M.

2016-07-01

2-Deoxy-2-[18F]-fluoro-D-glucose (FDG) positron emission tomography (PET) is often used in clinic for cancer diagnosis, staging, therapy planning and monitoring. Alternative features to the classical semi-quantitative variables have been recently proposed to study the heterogeneity of tumors. The method to extract such characteristics is texture analysis, which quantifies variations of uptake distribution within the lesions. Methods: Fifty-three head and neck and twelve rectal cancer patients were included in the analysis. A workflow in an open-source software, 3D slicer, was designed and expert clinicians were trained on its use, sixty six features were calculated including metabolic and texture parameters. Statistical analysis and dimensionality reduction techniques were performed on the data. Results: After observing a high correlation between variables, dimensions were reduced to five and three independent components for head and neck and rectal cancer cohort, respectively. Conclusion: Tumor heterogeneity parameters could be expressing important information about tumor and cancer disease, information that could be used to assess disease staging, patients’ prognosis, therapy plan and survival. (Author)

Directional fractal signature methods for trabecular bone texture in hand radiographs: Data from the Osteoarthritis Initiative

Energy Technology Data Exchange (ETDEWEB)

Wolski, M., E-mail: marcin.wolski@curtin.edu.au; Podsiadlo, P.; Stachowiak, G. W. [Tribology Laboratory, School of Civil and Mechanical Engineering, Curtin University, Bentley, Western Australia 6102 (Australia)

2014-08-15

Purpose: To develop directional fractal signature methods for the analysis of trabecular bone (TB) texture in hand radiographs. Problems associated with the small size of hand bones and the orientation of fingers were addressed. Methods: An augmented variance orientation transform (AVOT) and a quadrant rotating grid (QRG) methods were developed. The methods calculate fractal signatures (FSs) in different directions. Unlike other methods they have the search region adjusted according to the size of bone region of interest (ROI) to be analyzed and they produce FSs defined with respect to any chosen reference direction, i.e., they work for arbitrary orientation of fingers. Five parameters at scales ranging from 2 to 14 pixels (depending on image size and method) were derived from rose plots of Hurst coefficients, i.e., FS in dominating roughness (FS{sub Sta}), vertical (FS{sub V}) and horizontal (FS{sub H}) directions, aspect ratio (StrS), and direction signatures (StdS), respectively. The accuracy in measuring surface roughness and isotropy/anisotropy was evaluated using 3600 isotropic and 800 anisotropic fractal surface images of sizes between 20 × 20 and 64 × 64 pixels. The isotropic surfaces had FDs ranging from 2.1 to 2.9 in steps of 0.1, and the anisotropic surfaces had two dominating directions of 30° and 120°. The methods were used to find differences in hand TB textures between 20 matched pairs of subjects with (cases: approximate Kellgren-Lawrence (KL) grade ≥2) and without (controls: approximate KL grade <2) radiographic hand osteoarthritis (OA). The OA Initiative public database was used and 20 × 20 pixel bone ROIs were selected on 5th distal and middle phalanges. The performance of the AVOT and QRG methods was compared against a variance orientation transform (VOT) method developed earlier [M. Wolski, P. Podsiadlo, and G. W. Stachowiak, “Directional fractal signature analysis of trabecular bone: evaluation of different methods to detect early

Identification of components of fibroadenoma in cytology preparations using texture analysis: a morphometric study.

Science.gov (United States)

Singh, S; Gupta, R

2012-06-01

To evaluate the utility of image analysis using textural parameters obtained from a co-occurrence matrix in differentiating the three components of fibroadenoma of the breast, in fine needle aspirate smears. Sixty cases of histologically proven fibroadenoma were included in this study. Of these, 40 cases were used as a training set and 20 cases were taken as a test set for the discriminant analysis. Digital images were acquired from cytological preparations of all the cases and three components of fibroadenoma (namely, monolayered cell clusters, stromal fragments and background with bare nuclei) were selected for image analysis. A co-occurrence matrix was generated and a texture parameter vector (sum mean, energy, entropy, contrast, cluster tendency and homogeneity) was calculated for each pixel. The percentage of pixels correctly classified to a component of fibroadenoma on discriminant analysis was noted. The textural parameters, when considered in isolation, showed considerable overlap in their values of the three cytological components of fibroadenoma. However, the stepwise discriminant analysis revealed that all six textural parameters contributed significantly to the discriminant functions. Discriminant analysis using all the six parameters showed that the numbers of pixels correctly classified in training and tests sets were 96.7% and 93.0%, respectively. Textural analysis using a co-occurrence matrix appears to be useful in differentiating the three cytological components of fibroadenoma. These results could further be utilized in developing algorithms for image segmentation and automated diagnosis, but need to be confirmed in further studies. © 2011 Blackwell Publishing Ltd.

SAR Image Classification Based on Its Texture Features

Institute of Scientific and Technical Information of China (English)

LI Pingxiang; FANG Shenghui

2003-01-01

SAR images not only have the characteristics of all-ay, all-eather, but also provide object information which is different from visible and infrared sensors. However, SAR images have some faults, such as more speckles and fewer bands. The authors conducted the experiments of texture statistics analysis on SAR image features in order to improve the accuracy of SAR image interpretation.It is found that the texture analysis is an effective method for improving the accuracy of the SAR image interpretation.

The role of textures in the forming of automotive sheet steels

International Nuclear Information System (INIS)

Sanak Mishra

1996-01-01

Crystallographic textures generally have a strong bearing on the drawability of sheet steels. Particularly in the case of automotive sheets, texture control is of paramount importance. In the last two decades, therefore, texture research has assumed much significance in the steel industry. X-ray diffraction continues to remain the most used tool for the study of textures. Early researches, from about 1940 to 1980, were invariably carried out by the pole figure method. However, for more quantitative results the ODF (Orientation Distribution Functions) analysis technique was developed. Since 1980, the ODF analysis has come to be used extensively. In the present paper, several unique features of textures in automotive grade deep drawing steels, as revealed from X-ray ODFS, will be presented. The relative importance of the various textural components with respect to forming will also be dealt with

Quantitative evaluation methods of skin condition based on texture feature parameters

Directory of Open Access Journals (Sweden)

Hui Pang

2017-03-01

Full Text Available In order to quantitatively evaluate the improvement of the skin condition after using skin care products and beauty, a quantitative evaluation method for skin surface state and texture is presented, which is convenient, fast and non-destructive. Human skin images were collected by image sensors. Firstly, the median filter of the 3 × 3 window is used and then the location of the hairy pixels on the skin is accurately detected according to the gray mean value and color information. The bilinear interpolation is used to modify the gray value of the hairy pixels in order to eliminate the negative effect of noise and tiny hairs on the texture. After the above pretreatment, the gray level co-occurrence matrix (GLCM is calculated. On the basis of this, the four characteristic parameters, including the second moment, contrast, entropy and correlation, and their mean value are calculated at 45 ° intervals. The quantitative evaluation model of skin texture based on GLCM is established, which can calculate the comprehensive parameters of skin condition. Experiments show that using this method evaluates the skin condition, both based on biochemical indicators of skin evaluation methods in line, but also fully consistent with the human visual experience. This method overcomes the shortcomings of the biochemical evaluation method of skin damage and long waiting time, also the subjectivity and fuzziness of the visual evaluation, which achieves the non-destructive, rapid and quantitative evaluation of skin condition. It can be used for health assessment or classification of the skin condition, also can quantitatively evaluate the subtle improvement of skin condition after using skin care products or stage beauty.

Quantitative evaluation methods of skin condition based on texture feature parameters.

Science.gov (United States)

Pang, Hui; Chen, Tianhua; Wang, Xiaoyi; Chang, Zhineng; Shao, Siqi; Zhao, Jing

2017-03-01

In order to quantitatively evaluate the improvement of the skin condition after using skin care products and beauty, a quantitative evaluation method for skin surface state and texture is presented, which is convenient, fast and non-destructive. Human skin images were collected by image sensors. Firstly, the median filter of the 3 × 3 window is used and then the location of the hairy pixels on the skin is accurately detected according to the gray mean value and color information. The bilinear interpolation is used to modify the gray value of the hairy pixels in order to eliminate the negative effect of noise and tiny hairs on the texture. After the above pretreatment, the gray level co-occurrence matrix (GLCM) is calculated. On the basis of this, the four characteristic parameters, including the second moment, contrast, entropy and correlation, and their mean value are calculated at 45 ° intervals. The quantitative evaluation model of skin texture based on GLCM is established, which can calculate the comprehensive parameters of skin condition. Experiments show that using this method evaluates the skin condition, both based on biochemical indicators of skin evaluation methods in line, but also fully consistent with the human visual experience. This method overcomes the shortcomings of the biochemical evaluation method of skin damage and long waiting time, also the subjectivity and fuzziness of the visual evaluation, which achieves the non-destructive, rapid and quantitative evaluation of skin condition. It can be used for health assessment or classification of the skin condition, also can quantitatively evaluate the subtle improvement of skin condition after using skin care products or stage beauty.

On the use of a composite moderator at the IBR-2 reactor: Advantages for the neutron-diffraction texture analysis of rocks

Czech Academy of Sciences Publication Activity Database

Bulavin, M. V.; Vasin, R.N.; Kulikov, S.A.; Lokajíček, Tomáš; Levin, D.M.

2016-01-01

Roč. 10, č. 4 (2016), s. 677-686 ISSN 1027-4510 Institutional support: RVO:67985831 Keywords : cold moderator * neutron-diffraction texture analysis * phase analysis * Rietveld method Subject RIV: DB - Geology ; Mineralogy

Texture and microstructure analysis of epitaxial oxide layers prepared on textured Ni-12wt%Cr tapes

Energy Technology Data Exchange (ETDEWEB)

Huehne, R; Kursumovic, A; Tomov, R I; Glowacki, B A [Department of Materials Science and IRC in Superconductivity, University of Cambridge, Pembroke Street, Cambridge, CB2 3QZ (United Kingdom); Holzapfel, B [Institut fuer Festkoerper- und Werkstoffforschung, Helmholtzstrasse 20, 01069 Dresden (Germany); Evetts, J E [Department of Materials Science and IRC in Superconductivity, University of Cambridge, Pembroke Street, Cambridge, CB2 3QZ (United Kingdom)

2003-05-07

Oxide layers for the preparation of YBa{sub 2}Cu{sub 3}O{sub 7-x} coated conductors were grown on highly textured Ni-12wt%Cr tapes in pure oxygen using surface oxidation epitaxy at temperatures between 1000 deg. C and 1300 deg. C. Microstructural investigations revealed a layered oxide structure. The upper layer consists mainly of dense cube textured NiO. This is followed by a porous layer containing NiO and NiCr{sub 2}O{sub 4} particles. A detailed texture analysis showed a cube-on-cube relationship of the NiCr{sub 2}O{sub 4} spinel to the metal substrate. Untextured Cr{sub 2}O{sub 3} particles in a nickel matrix were found in a third layer arising from internal oxidation of the alloy. A high surface roughness and mechanical instability of the oxide were observed, depending on oxidation temperature and film thickness. However, mechanically stable oxide layers have been prepared using an additional annealing step in a protective atmosphere. Additionally, mechanical polishing or a second buffer layer, which grows with a higher smoothness, may be applied to reduce the surface roughness for coated conductor applications.

Advanced measurement and analysis of surface textures produced by micro-machining processes

International Nuclear Information System (INIS)

Bordatchev, Evgueni V; Hafiz, Abdullah M K

2014-01-01

Surface texture of a part or a product has significant effects on its functionality, physical-mechanical properties and visual appearance. In particular for miniature products, the implication of surface quality becomes critical owing to the presence of geometrical features with micro/nano-scale dimensions. Qualitative and quantitative assessments of surface texture are carried out predominantly by profile parameters, which are often insufficient to address the contribution of constituent spatial components with varied amplitudes and wavelengths. In this context, this article presents a novel approach for advanced measurement and analysis of profile average roughness (R a ) and its spatial distribution at different wavelength intervals. The applicability of the proposed approach was verified for three different surface topographies prepared by grinding, laser micro-polishing and micro-milling processes. From the measurement and analysis results, R a (λ) spatial distribution was found to be an effective measure of revealing the contributions of various spatial components within specific wavelength intervals towards formation of the entire surface profile. In addition, the approach was extended to the measurement and analysis of areal average roughness S a (λ) spatial distribution within different wavelength intervals. Besides, the proposed method was demonstrated to be a useful technique in developing a functional correlation between a manufacturing process and its corresponding surface profile. (paper)

Modern methods of experimental construction of texture complete direct pole figures by using X-ray data

Science.gov (United States)

Isaenkova, M.; Perlovich, Yu; Fesenko, V.

2016-04-01

Currently used methods for constructing texture complete direct pole figure (CDPF) based on the results of X-ray diffractometric measurements were considered with respect to the products of Zr-based alloys and, in particular, used in a nuclear reactor cladding tubes, for which the accuracy of determination of integral texture parameters is of the especial importance. The main attention was devoted to technical issues which are solved by means of computer processing of large arrays of obtained experimental data. Among considered questions there are amendments of the defocusing, techniques for constructing of complete direct pole figures and determination of integral textural parameters. The methods of reconstruction of complete direct pole figures by partial direct pole figures recorded up to tilt angles of sample ψ=70-80°: the method of extrapolation of data to an uninvestigated region of the stereographic projection, and the method of "sewing" of partial pole figures measured for three mutually perpendicular plane sections of the product. The limits of applicability of these methods, depending on the shape of the test product and the degree of inhomogeneity of the layer-by-layer texture, were revealed. On the basis of a large number of experimental data, the accuracy of the integral parameters used for calculation of the physical and mechanical properties of metals with a hexagonal crystal structure was found to be equal to 0.02, when taking into account the texture heterogeneity of regular products from Zr-based alloys.

Assessment Of Mold-Design Dependent Textures In CIM-Components By Polarized Light Optical Texture Analysis (PLOTA)

International Nuclear Information System (INIS)

Kern, Frank; Rauch, Johannes; Gadow, Rainer

2007-01-01

By thermoplastic ceramic injection moulding (CIM) ceramic components of high complexity can be produced in a large number of items at low dimensional tolerances. The cost advantage by the high degree of automation leads to an economical mass-production. The structure of injection-moulded components is determined by the form filling behaviour and viscosity of the feedstock, the machine parameters, the design of the mold and the gate design. With an adapted mold- and gate-design CIM-components without textures are possible. The ''Polarized Light Optical Texture analysis'' (PLOTA) makes it possible to inspect the components and detect and quantify the textures produced by a new mold. Based on the work of R. Fischer (2004) the PLOTA procedure was improved by including the possibility to measure the inclination angle and thus describe the orientation of the grains in three dimensions. Sampled thin sections of ceramic components are analysed under the polarization microscope and are brought in diagonal position. Pictures are taken with a digital camera. The pictures are converted in the L*a*b*- colour space and the crystals color values a* and b* in the picture are measured. The color values are compared with the values of a quartz wedge, which serves as universal standard. From the received values the inclination angle can be calculated relative to the microscope axis. It is possible to use the received data quantitatively e.g. for the FEM supported simulation of texture-conditioned divergences of mechanical values. Thus the injection molding parameters can be optimized to obtain improved mechanical properties

MRI Texture Analysis Reflects Histopathology Parameters in Thyroid Cancer – A First Preliminary Study

Directory of Open Access Journals (Sweden)

Hans-Jonas Meyer

2017-12-01

Full Text Available OBJECT: Thyroid cancer represents the most frequent malignancy of the endocrine system with an increasing incidence worldwide. Novel imaging techniques are able to further characterize tumors and even predict histopathology features. Texture analysis is an emergent imaging technique to extract extensive data from an radiology images. The present study was therefore conducted to identify possible associations between texture analysis and histopathology parameters in thyroid cancer. METHODS: The radiological database was retrospectively reviewed for thyroid carcinoma. Overall, 13 patients (3 females, 23.1% with a mean age of 61.6 years were identified. The MaZda program was used for texture analysis. The T1-precontrast and T2-weighted images were analyzed and overall 279 texture feature for each sequence was investigated. For every patient cell count, Ki67-index and p53 count were investigated. RESULTS: Several significant correlations between texture features and histopathology were identified. Regarding T1-weighted images, S(0;1Sum Averg correlated the most with cell count (r = 0.82. An inverse correlations with S(5;0AngScMom, S(5;0DifVarnc S(5;0, DiffEntrp and GrNonZeros (r = −0.69, −0.66, −0.69 and −0.63, respectively was also identified. For T2-weighted images, Variance with r = 0.63 was the highest coefficient, WavEnLL_S3 correlated inversely with cell count (r = −0.57. WavEnLL_S2 derived from T1-weighted images was the highest coefficient r = −0.80, S(0;5SumVarnc was positively with r = 0.74. Regarding T2-weighted images WavEnHL_s-1 was inverse correlated with Ki67 index (r = −0.77. S(1;0Correlat was with r = 0.75 the best correlation with Ki67 index. For T1-weighed images S(5;0SumofSqs was the best with r = 0.65 with p53 count. For T2-weighted images S(1;−1SumEntrp was the inverse correlation with r = −0.72, whereas S(0;4AngScMom correlated positively with r = 0.63. CONCLUSIONS: MRI texture analysis

Differentiating pheochromocytoma from lipid-poor adrenocortical adenoma by CT texture analysis: feasibility study.

Science.gov (United States)

Zhang, Gu-Mu-Yang; Shi, Bing; Sun, Hao; Jin, Zheng-Yu; Xue, Hua-Dan

2017-09-01

To investigate the feasibility of using CT texture analysis (CTTA) to differentiate pheochromocytoma from lipid-poor adrenocortical adenoma (lp-ACA). Ninety-eight pheochromocytomas and 66 lp-ACAs were included in this retrospective study. CTTA was performed on unenhanced and enhanced images. Receiver operating characteristic (ROC) analysis was performed, and the area under the ROC curve (AUC) was calculated for texture parameters that were significantly different for the objective. Diagnostic accuracies were evaluated using the cutoff values of texture parameters with the highest AUCs. Compared to lp-ACAs, pheochromocytomas had significantly higher mean gray-level intensity (Mean), entropy, and mean of positive pixels (MPP), but lower skewness and kurtosis on unenhanced images (P feasible to use CTTA to differentiate pheochromocytoma from lp-ACA.

3-D Solid Texture Classification Using Locally-Oriented Wavelet Transforms

OpenAIRE

Dicente Cid Yashin; Müller Henning; Platon Alexandra; Poletti Pierre-Alexandre; Depeursinge Adrien

2017-01-01

Many image acquisition techniques used in biomedical imaging material analysis and structural geology are capable of acquiring 3D solid images. Computational analysis of these images is complex but necessary since it is difficult for humans to visualize and quantify their detailed 3D content. One of the most common methods to analyze 3D data is to characterize the volumetric texture patterns. Texture analysis generally consists of encoding the local organization of image scales and directions...

SU-E-J-249: Characterization of Gynecological Tumor Heterogeneity Using Texture Analysis in the Context of An 18F-FDG PET Adaptive Protocol

Energy Technology Data Exchange (ETDEWEB)

Nawrocki, J [Duke University Medical Physics Graduate Program, Durham, NC (United States); Chino, J; Craciunescu, O [Duke University Medical Center Department of Radiation Oncology, Durham, NC (United States); Das, S [University of North Carolina School of Medicine, Chapel Hill, NC (United States)

2015-06-15

Purpose: We propose a method to examine gynecological tumor heterogeneity using texture analysis in the context of an adaptive PET protocol in order to establish if texture metrics from baseline PET-CT predict tumor response better than SUV metrics alone as well as determine texture features correlating with tumor response during radiation therapy. Methods: This IRB approved protocol included 29 women with node positive gynecological cancers visible on FDG-PET treated with EBRT to the PET positive nodes. A baseline and intra-treatment PET-CT was obtained. Tumor outcome was determined based on RECIST on posttreatment PET-CT. Primary GTVs were segmented using 40% threshold and a semi-automatic gradient-based contouring tool, PET Edge (MIM Software Inc., Cleveland, OH). SUV histogram features, Metabolic Volume (MV), and Total Lesion Glycolysis (TLG) were calculated. Four 3D texture matrices describing local and regional relationships between voxel intensities in the GTV were generated: co-occurrence, run length, size zone, and neighborhood difference. From these, 39 texture features were calculated. Prognostic power of baseline features derived from gradientbased and threshold GTVs were determined using the Wilcoxon rank-sum test. Receiver Operating Characteristics and logistic regression was performed using JMP (SAS Institute Inc., Cary, NC) to find probabilities of predicting response. Changes in features during treatment were determined using the Wilcoxon signed-rank test. Results: Of the 29 patients, there were 16 complete responders, 7 partial responders, and 6 non-responders. Comparing CR/PR vs. NR for gradient-based GTVs, 7 texture values, TLG, and SUV kurtosis had a p < 0.05. Threshold GTVs yielded 4 texture features and TLG with p < 0.05. From baseline to intra-treatment, 14 texture features, SUVmean, SUVmax, MV, and TLG changed with p < 0.05. Conclusion: Texture analysis of PET imaged gynecological tumors is an effective method for early prognosis and should

SU-E-J-249: Characterization of Gynecological Tumor Heterogeneity Using Texture Analysis in the Context of An 18F-FDG PET Adaptive Protocol

International Nuclear Information System (INIS)

Nawrocki, J; Chino, J; Craciunescu, O; Das, S

2015-01-01

Purpose: We propose a method to examine gynecological tumor heterogeneity using texture analysis in the context of an adaptive PET protocol in order to establish if texture metrics from baseline PET-CT predict tumor response better than SUV metrics alone as well as determine texture features correlating with tumor response during radiation therapy. Methods: This IRB approved protocol included 29 women with node positive gynecological cancers visible on FDG-PET treated with EBRT to the PET positive nodes. A baseline and intra-treatment PET-CT was obtained. Tumor outcome was determined based on RECIST on posttreatment PET-CT. Primary GTVs were segmented using 40% threshold and a semi-automatic gradient-based contouring tool, PET Edge (MIM Software Inc., Cleveland, OH). SUV histogram features, Metabolic Volume (MV), and Total Lesion Glycolysis (TLG) were calculated. Four 3D texture matrices describing local and regional relationships between voxel intensities in the GTV were generated: co-occurrence, run length, size zone, and neighborhood difference. From these, 39 texture features were calculated. Prognostic power of baseline features derived from gradientbased and threshold GTVs were determined using the Wilcoxon rank-sum test. Receiver Operating Characteristics and logistic regression was performed using JMP (SAS Institute Inc., Cary, NC) to find probabilities of predicting response. Changes in features during treatment were determined using the Wilcoxon signed-rank test. Results: Of the 29 patients, there were 16 complete responders, 7 partial responders, and 6 non-responders. Comparing CR/PR vs. NR for gradient-based GTVs, 7 texture values, TLG, and SUV kurtosis had a p < 0.05. Threshold GTVs yielded 4 texture features and TLG with p < 0.05. From baseline to intra-treatment, 14 texture features, SUVmean, SUVmax, MV, and TLG changed with p < 0.05. Conclusion: Texture analysis of PET imaged gynecological tumors is an effective method for early prognosis and should

Evaluation of Liver Fibrosis Using Texture Analysis on Combined-Contrast-Enhanced Magnetic Resonance Images at 3.0T

Directory of Open Access Journals (Sweden)

Takeshi Yokoo

2015-01-01

Full Text Available Purpose. To noninvasively assess liver fibrosis using combined-contrast-enhanced (CCE magnetic resonance imaging (MRI and texture analysis. Materials and Methods. In this IRB-approved, HIPAA-compliant prospective study, 46 adults with newly diagnosed HCV infection and recent liver biopsy underwent CCE liver MRI following intravenous administration of superparamagnetic iron oxides (ferumoxides and gadolinium DTPA (gadopentetate dimeglumine. The image texture of the liver was quantified in regions-of-interest by calculating 165 texture features. Liver biopsy specimens were stained with Masson trichrome and assessed qualitatively (METAVIR fibrosis score and quantitatively (% collagen stained area. Using L1 regularization path algorithm, two texture-based multivariate linear models were constructed, one for quantitative and the other for quantitative histology prediction. The prediction performance of each model was assessed using receiver operating characteristics (ROC and correlation analyses. Results. The texture-based predicted fibrosis score significantly correlated with qualitative (r=0.698, P<0.001 and quantitative (r=0.757, P<0.001 histology. The prediction model for qualitative histology had 0.814–0.976 areas under the curve (AUC, 0.659–1.000 sensitivity, 0.778–0.930 specificity, and 0.674–0.935 accuracy, depending on the binary classification threshold. The prediction model for quantitative histology had 0.742–0.950 AUC, 0.688–1.000 sensitivity, 0.679–0.857 specificity, and 0.696–0.848 accuracy, depending on the binary classification threshold. Conclusion. CCE MRI and texture analysis may permit noninvasive assessment of liver fibrosis.

Classification of high resolution imagery based on fusion of multiscale texture features

International Nuclear Information System (INIS)

Liu, Jinxiu; Liu, Huiping; Lv, Ying; Xue, Xiaojuan

2014-01-01

In high resolution data classification process, combining texture features with spectral bands can effectively improve the classification accuracy. However, the window size which is difficult to choose is regarded as an important factor influencing overall classification accuracy in textural classification and current approaches to image texture analysis only depend on a single moving window which ignores different scale features of various land cover types. In this paper, we propose a new method based on the fusion of multiscale texture features to overcome these problems. The main steps in new method include the classification of fixed window size spectral/textural images from 3×3 to 15×15 and comparison of all the posterior possibility values for every pixel, as a result the biggest probability value is given to the pixel and the pixel belongs to a certain land cover type automatically. The proposed approach is tested on University of Pavia ROSIS data. The results indicate that the new method improve the classification accuracy compared to results of methods based on fixed window size textural classification

On Texture and Geometry in Image Analysis

DEFF Research Database (Denmark)

Gustafsson, David Karl John

2009-01-01

fields and Maximum Entropy (FRAME) model [213, 214] is used for inpaining texture. We argue that many ’textures’ contain details that must be inpainted exactly. Simultaneous reconstruction of geometric structure and texture is a difficult problem, therefore, a two-phase reconstruction procedure...... is proposed. An inverse temperature is added to the FRAME model. In the first phase, the geometric structure is reconstructed by cooling the distribution, and in the second phase, the texture is added by heating the distribution. Empirically, we show that the long range geometric structure is inpainted...

DCE-MRI texture analysis with tumor subregion partitioning for predicting Ki-67 status of estrogen receptor-positive breast cancers

KAUST Repository

Fan, Ming

2017-12-08

Breast tumor heterogeneity is related to risk factors that lead to worse prognosis, yet such heterogeneity has not been well studied.To predict the Ki-67 status of estrogen receptor (ER)-positive breast cancer patients via analysis of tumor heterogeneity with subgroup identification based on patterns of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI).Retrospective study.Seventy-seven breast cancer patients with ER-positive breast cancer were investigated, of whom 51 had low Ki-67 expression.T1 -weighted 3.0T DCE-MR images.Each tumor was partitioned into multiple subregions using three methods based on patterns of dynamic enhancement: 1) time to peak (TTP), 2) peak enhancement rate (PER), and 3) kinetic pattern clustering (KPC). In each tumor subregion, 18 texture features were computed.Univariate and multivariate logistic regression analyses were performed using a leave-one-out-based cross-validation (LOOCV) method. The partitioning results were compared with the same feature extraction methods across the whole tumor.In the univariate analysis, the best-performing feature was the texture statistic of sum variance in the tumor subregion with early TTP for differentiating between patients with high and low Ki-67 expression (area under the receiver operating characteristic curves, AUC = 0.748). Multivariate analysis showed that features from the tumor subregion associated with early TTP yielded the highest performance (AUC = 0.807) among the subregions for predicting the Ki-67 status. Among all regions, the tumor area with high PER at a precontrast MR image achieved the highest performance (AUC = 0.722), while the subregion that exhibited the highest overall enhancement rate based on KPC had an AUC of 0.731. These three models based on intratumoral texture analysis significantly (P < 0.01) outperformed the model using features from the whole tumor (AUC = 0.59).Texture analysis of intratumoral heterogeneity has the potential to serve as a valuable

Geometric Total Variation for Texture Deformation

DEFF Research Database (Denmark)

Bespalov, Dmitriy; Dahl, Anders Lindbjerg; Shokoufandeh, Ali

2010-01-01

In this work we propose a novel variational method that we intend to use for estimating non-rigid texture deformation. The method is able to capture variation in grayscale images with respect to the geometry of its features. Our experimental evaluations demonstrate that accounting for geometry...... of features in texture images leads to significant improvements in localization of these features, when textures undergo geometrical transformations. Accurate localization of features in the presense of unkown deformations is a crucial property for texture characterization methods, and we intend to expoit...

Texture Feature Extraction and Classification for Iris Diagnosis

Science.gov (United States)

Ma, Lin; Li, Naimin

Appling computer aided techniques in iris image processing, and combining occidental iridology with the traditional Chinese medicine is a challenging research area in digital image processing and artificial intelligence. This paper proposes an iridology model that consists the iris image pre-processing, texture feature analysis and disease classification. To the pre-processing, a 2-step iris localization approach is proposed; a 2-D Gabor filter based texture analysis and a texture fractal dimension estimation method are proposed for pathological feature extraction; and at last support vector machines are constructed to recognize 2 typical diseases such as the alimentary canal disease and the nerve system disease. Experimental results show that the proposed iridology diagnosis model is quite effective and promising for medical diagnosis and health surveillance for both hospital and public use.

Cellular automata rule characterization and classification using texture descriptors

Science.gov (United States)

Machicao, Jeaneth; Ribas, Lucas C.; Scabini, Leonardo F. S.; Bruno, Odermir M.

2018-05-01

The cellular automata (CA) spatio-temporal patterns have attracted the attention from many researchers since it can provide emergent behavior resulting from the dynamics of each individual cell. In this manuscript, we propose an approach of texture image analysis to characterize and classify CA rules. The proposed method converts the CA spatio-temporal patterns into a gray-scale image. The gray-scale is obtained by creating a binary number based on the 8-connected neighborhood of each dot of the CA spatio-temporal pattern. We demonstrate that this technique enhances the CA rule characterization and allow to use different texture image analysis algorithms. Thus, various texture descriptors were evaluated in a supervised training approach aiming to characterize the CA's global evolution. Our results show the efficiency of the proposed method for the classification of the elementary CA (ECAs), reaching a maximum of 99.57% of accuracy rate according to the Li-Packard scheme (6 classes) and 94.36% for the classification of the 88 rules scheme. Moreover, within the image analysis context, we found a better performance of the method by means of a transformation of the binary states to a gray-scale.

A procedure for the evaluation of 2D radiographic texture analysis to assess 3D bone micro-architecture; Evaluation de l'analyse de la texture de radiographies 2D pour evaluer les micro architecture 3D d'os

Energy Technology Data Exchange (ETDEWEB)

Apostol, L.; Peyrin, F.; Yot, S.; Basset, O.; Odet, Ch. [CREATIS - Centre National de la Recherche Scientifique (UMR CNRS 5515), 69 - Villeurbanne (France); Apostal, L.; Boller, E. [European Synchrotron Radiation Facility (ESRF), 38 - Grenoble (France); Tabary, J.; Dinten, J.M. [CEA Grenoble, Lab. d' Electronique et de Technologie de l' Informatique (LETI), 38 (France); Boudousq, V.; Kotzki, P.O. [Faculte de Medecine, Lab. de Biophysique Medicale, 30 - Nimes (France)

2004-07-01

Although the diagnosis of osteoporosis is mainly based on Dual X-ray Absorptiometry, it has been shown that trabecular bone micro-architecture is also an important factor in regards of fracture risk, which can be efficiently assessed in vitro using three-dimensional x-ray microtomography ({mu}CT). In vivo, techniques based on high-resolution x-ray radiography associated to texture analysis have been proposed to investigate bone micro-architecture, but their relevance for giving pertinent 3D information is unclear. The purpose of this work was to develop a method for evaluating the relationships between 3D micro-architecture and 2D texture parameters, and optimizing the conditions for radiographic imaging. Bone sample images taken from cortical to cortical were acquired using 3D-synchrotron x-ray {mu}CT at the ESRF. The 3D digital images were further used for two purposes: 1) quantification of three-dimensional bone micro-architecture, 2) simulation of realistic x-ray radiographs under different acquisition conditions. Texture analysis was then applied to these 2D radiographs using a large variety of methods (co-occurrence, spectrum, fractal...). First results of the statistical analysis between 2D and 3D parameters allowed identifying the most relevant 2D texture parameters. (authors)

Wavelet analysis enables system-independent texture analysis of optical coherence tomography images

Science.gov (United States)

Lingley-Papadopoulos, Colleen A.; Loew, Murray H.; Zara, Jason M.

2009-07-01

Texture analysis for tissue characterization is a current area of optical coherence tomography (OCT) research. We discuss some of the differences between OCT systems and the effects those differences have on the resulting images and subsequent image analysis. In addition, as an example, two algorithms for the automatic recognition of bladder cancer are compared: one that was developed on a single system with no consideration for system differences, and one that was developed to address the issues associated with system differences. The first algorithm had a sensitivity of 73% and specificity of 69% when tested using leave-one-out cross-validation on data taken from a single system. When tested on images from another system with a different central wavelength, however, the method classified all images as cancerous regardless of the true pathology. By contrast, with the use of wavelet analysis and the removal of system-dependent features, the second algorithm reported sensitivity and specificity values of 87 and 58%, respectively, when trained on images taken with one imaging system and tested on images taken with another.

Wavelet analysis enables system-independent texture analysis of optical coherence tomography images.

Science.gov (United States)

Lingley-Papadopoulos, Colleen A; Loew, Murray H; Zara, Jason M

2009-01-01

Texture analysis for tissue characterization is a current area of optical coherence tomography (OCT) research. We discuss some of the differences between OCT systems and the effects those differences have on the resulting images and subsequent image analysis. In addition, as an example, two algorithms for the automatic recognition of bladder cancer are compared: one that was developed on a single system with no consideration for system differences, and one that was developed to address the issues associated with system differences. The first algorithm had a sensitivity of 73% and specificity of 69% when tested using leave-one-out cross-validation on data taken from a single system. When tested on images from another system with a different central wavelength, however, the method classified all images as cancerous regardless of the true pathology. By contrast, with the use of wavelet analysis and the removal of system-dependent features, the second algorithm reported sensitivity and specificity values of 87 and 58%, respectively, when trained on images taken with one imaging system and tested on images taken with another.

Surface inspection of flat products by means of texture analysis: on-line implementation using neural networks

Science.gov (United States)

Fernandez, Carlos; Platero, Carlos; Campoy, Pascual; Aracil, Rafael

1994-11-01

This paper describes some texture-based techniques that can be applied to quality assessment of flat products continuously produced (metal strips, wooden surfaces, cork, textile products, ...). Since the most difficult task is that of inspecting for product appearance, human-like inspection ability is required. A common feature to all these products is the presence of non- deterministic texture on their surfaces. Two main subjects are discussed: statistical techniques for both surface finishing determination and surface defect analysis as well as real-time implementation for on-line inspection in high-speed applications. For surface finishing determination a Gray Level Difference technique is presented to perform over low resolution images, that is, no-zoomed images. Defect analysis is performed by means of statistical texture analysis over defective portions of the surface. On-line implementation is accomplished by means of neural networks. When a defect arises, textural analysis is applied which result in a data-vector, acting as input of a neural net, previously trained in a supervised way. This approach tries to reach on-line performance in automated visual inspection applications when texture is presented in flat product surfaces.

Breast Cancer Risk Estimation Using Parenchymal Texture Analysis in Digital Breast Tomosynthesis

International Nuclear Information System (INIS)

Ikejimba, Lynda C.; Kontos, Despina; Maidment, Andrew D. A.

2010-01-01

Mammographic parenchymal texture has been shown to correlate with genetic markers of developing breast cancer. Digital breast tomosynthesis (DBT) is a novel x-ray imaging technique in which tomographic images of the breast are reconstructed from multiple source projections acquired at different angles of the x-ray tube. Compared to digital mammography (DM), DBT eliminates breast tissue overlap, offering superior parenchymal tissue visualization. We hypothesize that texture analysis in DBT could potentially provide a better assessment of parenchymal texture and ultimately result in more accurate assessment of breast cancer risk. As a first step towards validating this hypothesis, we investigated the association between DBT parenchymal texture and breast percent density (PD), a known breast cancer risk factor, and compared it to DM. Bilateral DBT and DM images from 71 women participating in a breast cancer screening trial were analyzed. Filtered-backprojection was used to reconstruct DBT tomographic planes in 1 mm increments with 0.22 mm in-plane resolution. Corresponding DM images were acquired at 0.1 mm pixel resolution. Retroareolar regions of interest (ROIs) equivalent to 2.5 cm 3 were segmented from the DBT images and corresponding 2.5 cm 2 ROIs were segmented from the DM images. Breast PD was mammographically estimated using the Cumulus scale. Overall, DBT texture features demonstrated a stronger correlation than DM to PD. The Pearson correlation coefficients for DBT were r = 0.40 (p 2 = 0.39) compared to DM (R 2 = 0.33). We attribute these observations to the superior parenchymal tissue visualization in DBT. Our study is the first to perform DBT texture analysis in a screening population of women, showing that DBT could potentially provide better breast cancer risk assessment in the future.

2D magnetic texture analysis of Co-Cu films

Energy Technology Data Exchange (ETDEWEB)

Bayirli, Mehmet; Karaagac, Oznur; Kockar, Hakan [Balikesir Univ. (Turkey). Physics Dept.; Alper, Mursel [Uludag Univ., Bursa (Turkey). Physics Dept.

2017-08-01

The magnetic textures for the produced magnetic materials are important concepts in accordance with technical applications. Therefore, the aim of this article is to determine 2D magnetic textures of electrodeposited Co-Cu films by the measurement of hysteresis loops at the incremented angles. For that, Co-Cu films were deposited with different Co{sup 2+} in the electrolyte. In addition, the easy-axis orientation in the films from the squareness values of the angles, M{sub p}(β) obtained by the hysteresis loops have been numerically studied using the Fourier series analysis. The differences observed in the magnetic easy-axis distributions were attributed to changes of the incorporation of Co in the films with the change of Co{sup 2+} in the electrolyte. The coefficients of Fourier series (A{sub 0} and A{sub 2n}) were also computed for 2D films. It is seen that a systematic and small decrease in A{sub 0} and an obvious decrease in A{sub 2n} (n=1) were observed with increasing incorporated Co in the films. Results imply that interactions cause slightly demagnetization effect accordance with higher incorporation of Co in the films. Furthermore, the crystal structure of the Co-Cu films analysed by X-ray diffraction revealed that the films have dominantly face-centred cubic structure. Film contents analysed by energy-dispersive X-ray spectroscopy and film morphologies observed by scanning electron microscope also support the magnetic texture analysis results found by numerical computation.

2D magnetic texture analysis of Co-Cu films

International Nuclear Information System (INIS)

Bayirli, Mehmet; Karaagac, Oznur; Kockar, Hakan; Alper, Mursel

2017-01-01

The magnetic textures for the produced magnetic materials are important concepts in accordance with technical applications. Therefore, the aim of this article is to determine 2D magnetic textures of electrodeposited Co-Cu films by the measurement of hysteresis loops at the incremented angles. For that, Co-Cu films were deposited with different Co"2"+ in the electrolyte. In addition, the easy-axis orientation in the films from the squareness values of the angles, M_p(β) obtained by the hysteresis loops have been numerically studied using the Fourier series analysis. The differences observed in the magnetic easy-axis distributions were attributed to changes of the incorporation of Co in the films with the change of Co"2"+ in the electrolyte. The coefficients of Fourier series (A_0 and A_2_n) were also computed for 2D films. It is seen that a systematic and small decrease in A_0 and an obvious decrease in A_2_n (n=1) were observed with increasing incorporated Co in the films. Results imply that interactions cause slightly demagnetization effect accordance with higher incorporation of Co in the films. Furthermore, the crystal structure of the Co-Cu films analysed by X-ray diffraction revealed that the films have dominantly face-centred cubic structure. Film contents analysed by energy-dispersive X-ray spectroscopy and film morphologies observed by scanning electron microscope also support the magnetic texture analysis results found by numerical computation.

Machine learning-based quantitative texture analysis of CT images of small renal masses: Differentiation of angiomyolipoma without visible fat from renal cell carcinoma.

Science.gov (United States)

Feng, Zhichao; Rong, Pengfei; Cao, Peng; Zhou, Qingyu; Zhu, Wenwei; Yan, Zhimin; Liu, Qianyun; Wang, Wei

2018-04-01

To evaluate the diagnostic performance of machine-learning based quantitative texture analysis of CT images to differentiate small (≤ 4 cm) angiomyolipoma without visible fat (AMLwvf) from renal cell carcinoma (RCC). This single-institutional retrospective study included 58 patients with pathologically proven small renal mass (17 in AMLwvf and 41 in RCC groups). Texture features were extracted from the largest possible tumorous regions of interest (ROIs) by manual segmentation in preoperative three-phase CT images. Interobserver reliability and the Mann-Whitney U test were applied to select features preliminarily. Then support vector machine with recursive feature elimination (SVM-RFE) and synthetic minority oversampling technique (SMOTE) were adopted to establish discriminative classifiers, and the performance of classifiers was assessed. Of the 42 extracted features, 16 candidate features showed significant intergroup differences (P Machine learning analysis of CT texture features can facilitate the accurate differentiation of small AMLwvf from RCC. • Although conventional CT is useful for diagnosis of SRMs, it has limitations. • Machine-learning based CT texture analysis facilitate differentiation of small AMLwvf from RCC. • The highest accuracy of SVM-RFE+SMOTE classifier reached 93.9 %. • Texture analysis combined with machine-learning methods might spare unnecessary surgery for AMLwvf.

Transformations in destination texture

DEFF Research Database (Denmark)

Gyimóthy, Szilvia

2018-01-01

This article takes heterogeographical approaches to understand Bollywood-induced destination transformations in Switzerland. Positioned within the theoretical field of mediatized mobility, the study contextualizes Bollywood-induced tourism in Europe the concept of texture. Textural analysis (base...

Assessment of textural differentiations in forest resources in Romania using fractal analysis

DEFF Research Database (Denmark)

Andronache, Ion; Fensholt, Rasmus; Ahammer, Helmut

2017-01-01

regions in Romania affected by both deforestation and reforestation using a non-Euclidean method based on fractal analysis.We calculated four fractal dimensions of forest areas: the fractal box-counting dimension of the forest areas, the fractal box-counting dimension of the dilated forest areas......, the fractal dilation dimension and the box-counting dimension of the border of the dilated forest areas. Fractal analysis revealed morpho-structural and textural differentiations of forested, deforested and reforested areas in development regions with dominant mountain relief and high hills (more forested...... and compact organization) in comparison to the development regions dominated by plains or low hills (less forested, more fragmented with small and isolated clusters). Our analysis used the fractal analysis that has the advantage of analyzing the entire image, rather than studying local information, thereby...

Intratumoral Heterogeneity of Breast Cancer Xenograft Models: Texture Analysis of Diffusion-Weighted MR Imaging

Energy Technology Data Exchange (ETDEWEB)

Yun, Bo La; Cho, Nariya; Li, Mulun; Song, In Chan; Moon, Woo Kyung [Dept. of Radiology, Seoul National University Hospital, Seoul National University College of Medicine, Seoul (Korea, Republic of); Jang, Min Hye; Park, So Yeon; Kim, Bo Young [Seoul National University Bundang Hospital, Seongnam (Korea, Republic of); Kang, Ho Chul [Dept. of Computer Science and Engineering, Seoul National University, Seoul (Korea, Republic of)

2014-10-15

To investigate whether there is a relationship between texture analysis parameters of apparent diffusion coefficient (ADC) maps and histopathologic features of MCF-7 and MDA-MB-231 xenograft models. MCF-7 estradiol (+), MCF-7 estradiol (-), and MDA-MB-231 xenograft models were made with approval of the animal care committee. Twelve tumors of MCF-7 estradiol (+), 9 tumors of MCF-7 estradiol (-), and 6 tumors in MDA-MB-231 were included. Diffusion-weighted MR images were obtained on a 9.4-T system. An analysis of the first and second order texture analysis of ADC maps was performed. The texture analysis parameters and histopathologic features were compared among these groups by the analysis of variance test. Correlations between texture parameters and histopathologic features were analyzed. We also evaluated the intraobserver agreement in assessing the texture parameters. MCF-7 estradiol (+) showed a higher standard deviation, maximum, skewness, and kurtosis of ADC values than MCF-7 estradiol (-) and MDA-MB-231 (p < 0.01 for all). The contrast of the MCF-7 groups was higher than that of the MDA-MB-231 (p 0.004). The correlation (COR) of the texture analysis of MCF-7 groups was lower than that of MDA-MB-231 (p < 0.001). The histopathologic analysis showed that Ki-67mean and Ki-67diff of MCF-7 estradiol (+) were higher than that of MCF-7 estradiol (-) or MDA-MB-231 (p < 0.05). The microvessel density (MVD)mean and MVDdiff of MDA-MB-231 were higher than those of MCF-7 groups (p < 0.001). A diffuse-multifocal necrosis was more frequently found in MDA-MB-231 (p < 0.001). The proportion of necrosis moderately correlated with the contrast (r = -0.438, p = 0.022) and strongly with COR (r = 0.540, p 0.004). Standard deviation (r = 0.622, r = 0.437), skewness (r = 0.404, r 0.484), and kurtosis (r = 0.408, r = 0.452) correlated with Ki-67 mean and Ki-67diff (p < 0.05 for all). COR moderately correlated with Ki-67diff (r -0.388, p = 0.045). Skewness (r = -0.643, r = -0

Adaptive multiresolution Hermite-Binomial filters for image edge and texture analysis

NARCIS (Netherlands)

Gu, Y.H.; Katsaggelos, A.K.

1994-01-01

A new multiresolution image analysis approach using adaptive Hermite-Binomial filters is presented in this paper. According to the local image structural and textural properties, the analysis filter kernels are made adaptive both in their scales and orders. Applications of such an adaptive filtering

Texture Based Quality Analysis of Simulated Synthetic Ultrasound Images Using Local Binary Patterns †

Directory of Open Access Journals (Sweden)

Prerna Singh

2017-12-01

Full Text Available Speckle noise reduction is an important area of research in the field of ultrasound image processing. Several algorithms for speckle noise characterization and analysis have been recently proposed in the area. Synthetic ultrasound images can play a key role in noise evaluation methods as they can be used to generate a variety of speckle noise models under different interpolation and sampling schemes, and can also provide valuable ground truth data for estimating the accuracy of the chosen methods. However, not much work has been done in the area of modeling synthetic ultrasound images, and in simulating speckle noise generation to get images that are as close as possible to real ultrasound images. An important aspect of simulated synthetic ultrasound images is the requirement for extensive quality assessment for ensuring that they have the texture characteristics and gray-tone features of real images. This paper presents texture feature analysis of synthetic ultrasound images using local binary patterns (LBP and demonstrates the usefulness of a set of LBP features for image quality assessment. Experimental results presented in the paper clearly show how these features could provide an accurate quality metric that correlates very well with subjective evaluations performed by clinical experts.

Sensory texture analysis of thickened liquids during ingestion.

Science.gov (United States)

Chambers, Edgar; Jenkins, Alicia; Mertz Garcia, Jane

2017-12-01

Practitioners support the use of thickened liquids for many patients with disordered swallowing. Although physical measures have highlighted differences among products there are questions about the ability of the measures to fully explain the sensory texture effects during swallowing of thickened liquids. This study used a trained sensory panel to describe the textural aspects of liquids during ingestion and swallowing. The lexicon was able to characterize differences in beverages, thickeners, and thickness levels with the most important attribute being viscosity, which loaded heavily in the almost one-dimensional space that resulted from the sensory analysis of these beverages. Other effects, such as slipperiness provided some minimal additional information on the products. Trained sensory panelists were shown to be useful in the measurement of differences in thickened liquid products prescribed for patients with dysphagia. They were able to differentiate products based on perceived differences related to flow speed, viscosity, and other parameters suggesting their use in further studies of swallowing behavior and for development of products for disordered swallowing should be considered. Understanding how these variables might relate to clinical decision making about product selection or modification to best meet the nutritional needs of a person with disordered swallowing could be helpful. This is especially true given the difficulties in measuring texture instrumentally in these products. © 2017 Wiley Periodicals, Inc.

Dilatometry study of textures

International Nuclear Information System (INIS)

Sofrenovic, R.; Lazarevic, Dj.

1965-01-01

Presence of textures in the metal uranium fuel is harmful because of anisotropy properties of uranium during thermal treatment, and especially during irradiation. Anisotropic radiation swelling of uranium can cause deformation of fuel element due to existence of textures. The objective of this work was studying of the influence of phase transformations on textures in uranium which has undergone plastic deformation due to rotational casting. Dilatometry method was adopted for testing the textures. This report describes the device for dilatometry testing and the measured preliminary results are shown

Statistical-techniques-based computer-aided diagnosis (CAD) using texture feature analysis: application in computed tomography (CT) imaging to fatty liver disease

International Nuclear Information System (INIS)

Chung, Woon-Kwan; Park, Hyong-Hu; Im, In-Chul; Lee, Jae-Seung; Goo, Eun-Hoe; Dong, Kyung-Rae

2012-01-01

This paper proposes a computer-aided diagnosis (CAD) system based on texture feature analysis and statistical wavelet transformation technology to diagnose fatty liver disease with computed tomography (CT) imaging. In the target image, a wavelet transformation was performed for each lesion area to set the region of analysis (ROA, window size: 50 x 50 pixels) and define the texture feature of a pixel. Based on the extracted texture feature values, six parameters (average gray level, average contrast, relative smoothness, skewness, uniformity, and entropy) were determined to calculate the recognition rate for a fatty liver. In addition, a multivariate analysis of the variance (MANOVA) method was used to perform a discriminant analysis to verify the significance of the extracted texture feature values and the recognition rate for a fatty liver. According to the results, each texture feature value was significant for a comparison of the recognition rate for a fatty liver (p < 0.05). Furthermore, the F-value, which was used as a scale for the difference in recognition rates, was highest in the average gray level, relatively high in the skewness and the entropy, and relatively low in the uniformity, the relative smoothness and the average contrast. The recognition rate for a fatty liver had the same scale as that for the F-value, showing 100% (average gray level) at the maximum and 80% (average contrast) at the minimum. Therefore, the recognition rate is believed to be a useful clinical value for the automatic detection and computer-aided diagnosis (CAD) using the texture feature value. Nevertheless, further study on various diseases and singular diseases will be needed in the future.

Quantitative analysis of textures produced in a hot-extruded zirconium plate; Analyse quantitative des textures developpees dans une plaque de zirconium filee a chaud

Energy Technology Data Exchange (ETDEWEB)

Couterne, J. [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires. Institut national des sciences et techniques nucleaires, laboratoire de metallurgie

1967-01-01

The textures produced in zirconium by the extrusion at 730 deg C of a cylindrical billet in the form of a plate having a rectangular cross-section, have been studied by the Schulz method using an isotropic standard. These textures have been determined both parallel to the plane of the plate and parallel to the plane of the sides, All the results are analyzed in a final discussion which makes it possible to show, in particular near the edges of the plate, that certain components of the textures observed in the two series of recordings are in fact aspects of the same texture seen from two different angles, It is shown furthermore that the zirconium thus shaped has cold-work textures and als recrystallisation textures formed after the preceding cold-working, If the observed textures are considered schematically, it can be see that two of these have already been described in the literature and are similar to those found in rolled products: these textures are such that the (0001) planes are inclined at 36 deg C and 60 deg C respectively with respect to a plan tangential to the curve (envelope of transverse flow rates) resulting from the extrusion geometry under consideration; the third texture is defined. by the fact that the (0001) plane is orthogonal to the exterior surfaces of the plate. The direction of extrusion associated with these planes and common to the three textures is of the type <1010>, Dilatometric tests have been carried out on samples taken both parallel and perpendicular to the extrusion direction, These tests show that the zirconium is dilatometrically anisotropic and that a plot of ({alpha}{sub v})-a against temperature shows a change of gradient at 400 deg C, this latter effect may be due to the change in the electronic configuration of the metal occurring at this temperature. (author) [French] Les textures conferees au zirconium par filage a chaud a 730 deg C d'une billette cylindrique sous forme d'une plaque de section rectangulaire, ont

Quantitative analysis of textures produced in a hot-extruded zirconium plate; Analyse quantitative des textures developpees dans une plaque de zirconium filee a chaud

Energy Technology Data Exchange (ETDEWEB)

Couterne, J [Commissariat a l' Energie Atomique, Saclay (France). Centre d' Etudes Nucleaires. Institut national des sciences et techniques nucleaires, laboratoire de metallurgie

1967-01-01

The textures produced in zirconium by the extrusion at 730 deg C of a cylindrical billet in the form of a plate having a rectangular cross-section, have been studied by the Schulz method using an isotropic standard. These textures have been determined both parallel to the plane of the plate and parallel to the plane of the sides, All the results are analyzed in a final discussion which makes it possible to show, in particular near the edges of the plate, that certain components of the textures observed in the two series of recordings are in fact aspects of the same texture seen from two different angles, It is shown furthermore that the zirconium thus shaped has cold-work textures and als recrystallisation textures formed after the preceding cold-working, If the observed textures are considered schematically, it can be see that two of these have already been described in the literature and are similar to those found in rolled products: these textures are such that the (0001) planes are inclined at 36 deg C and 60 deg C respectively with respect to a plan tangential to the curve (envelope of transverse flow rates) resulting from the extrusion geometry under consideration; the third texture is defined. by the fact that the (0001) plane is orthogonal to the exterior surfaces of the plate. The direction of extrusion associated with these planes and common to the three textures is of the type <1010>, Dilatometric tests have been carried out on samples taken both parallel and perpendicular to the extrusion direction, These tests show that the zirconium is dilatometrically anisotropic and that a plot of ({alpha}{sub v})-a against temperature shows a change of gradient at 400 deg C, this latter effect may be due to the change in the electronic configuration of the metal occurring at this temperature. (author) [French] Les textures conferees au zirconium par filage a chaud a 730 deg C d'une billette cylindrique sous forme d'une plaque de section rectangulaire, ont ete

Inference of segmented color and texture description by tensor voting.

Science.gov (United States)

Jia, Jiaya; Tang, Chi-Keung

2004-06-01

A robust synthesis method is proposed to automatically infer missing color and texture information from a damaged 2D image by (N)D tensor voting (N > 3). The same approach is generalized to range and 3D data in the presence of occlusion, missing data and noise. Our method translates texture information into an adaptive (N)D tensor, followed by a voting process that infers noniteratively the optimal color values in the (N)D texture space. A two-step method is proposed. First, we perform segmentation based on insufficient geometry, color, and texture information in the input, and extrapolate partitioning boundaries by either 2D or 3D tensor voting to generate a complete segmentation for the input. Missing colors are synthesized using (N)D tensor voting in each segment. Different feature scales in the input are automatically adapted by our tensor scale analysis. Results on a variety of difficult inputs demonstrate the effectiveness of our tensor voting approach.

Understanding Crystal Populations: The Role of Textural Analysis in Determining Magmatic Timescales

Science.gov (United States)

Jerram, D. A.

2006-12-01

Crystal populations in igneous rocks that erupt at the Earths surface act as records of magma chamber processes at depth, predominantly recording episodes of growth/nucleation and geochemical changes within the host body. Detailed inspection of such crystal populations, however, reveals a complex crystal cargo that comprises crystals which have grown directly from the host, crystals that have spent one or more protracted periods being isolated from the host magma and crystals that originated from a completely different magma body and/or country rock. To further interrogate this crystal cargo we can use textural analysis techniques to fully quantify the crystal population and gather important information about the population, such as crystal morphology, spatial distribution and size relationships. When quantified, such data can be used to better constrain the different components of the resultant crystal population and how they relate to each other. Additionally, by combining textural analysis information with geochemical analysis, a powerful measure of magma timescales and magma chamber processes results. In this contribution the different types of textural analysis techniques in 2D and 3D are introduced with examples from both plutonic and volcanic systems presented to highlight the roll of this approach to quantifying magma timescales.

A Review Paper on Camouflage Texture Evaluation

OpenAIRE

Amol Patil; Girraj Prasad Rathode

2013-01-01

Traditional evaluation method of camouflage texture effect is subjective evaluation. It’s very tedious and inconvenient to direct the texture designing. In this project, a systemic and rational method for direction and evaluation of camouflage texture designing is proposed. Camouflage consists of things such as leaves, branches, or brown and green paint, which are used to make it difficult for an enemy to see military forces and equipment. A camouflage texture evaluation method based on WSSIM...

Use of digital image analysis combined with fractal theory to determine particle morphology and surface texture of quartz sands

Directory of Open Access Journals (Sweden)

Georgia S. Araujo

2017-12-01

Full Text Available The particle morphology and surface texture play a major role in influencing mechanical and hydraulic behaviors of sandy soils. This paper presents the use of digital image analysis combined with fractal theory as a tool to quantify the particle morphology and surface texture of two types of quartz sands widely used in the region of Vitória, Espírito Santo, southeast of Brazil. The two investigated sands are sampled from different locations. The purpose of this paper is to present a simple, straightforward, reliable and reproducible methodology that can identify representative sandy soil texture parameters. The test results of the soil samples of the two sands separated by sieving into six size fractions are presented and discussed. The main advantages of the adopted methodology are its simplicity, reliability of the results, and relatively low cost. The results show that sands from the coastal spit (BS have a greater degree of roundness and a smoother surface texture than river sands (RS. The values obtained in the test are statistically analyzed, and again it is confirmed that the BS sand has a slightly greater degree of sphericity than that of the RS sand. Moreover, the RS sand with rough surface texture has larger specific surface area values than the similar BS sand, which agree with the obtained roughness fractal dimensions. The consistent experimental results demonstrate that image analysis combined with fractal theory is an accurate and efficient method to quantify the differences in particle morphology and surface texture of quartz sands.

Comparison of textural atributes of selected meat sausages using instrumental analysis

Directory of Open Access Journals (Sweden)

Vladimír Vietoris

2013-03-01

Full Text Available Normal 0 21 false false false SK X-NONE X-NONE The aim of the study was to compare textural atributes of selected meat sausages using instrumental analysis. For this purpose, seven different meat sausage samples were treated by instrumental analysis, by the use of Warner-Bratzler probe,  to find differences for two selected textural parameter firmness and work of shear. As expected, various values of mentioned atributes were obtained for different samples tested in fresh stage and after storage under controlled conditions (48 hrs., 30 °C temp., and 60 % R.H. before and after cooking. For statistical evaluation of results, paired T test was used, statistically significant differences were taken at pdoi:10.5219/273

Automatic Segmenting Structures in MRI's Based on Texture Analysis and Fuzzy Logic

Science.gov (United States)

Kaur, Mandeep; Rattan, Munish; Singh, Pushpinder

2017-12-01

The purpose of this paper is to present the variational method for geometric contours which helps the level set function remain close to the sign distance function, therefor it remove the need of expensive re-initialization procedure and thus, level set method is applied on magnetic resonance images (MRI) to track the irregularities in them as medical imaging plays a substantial part in the treatment, therapy and diagnosis of various organs, tumors and various abnormalities. It favors the patient with more speedy and decisive disease controlling with lesser side effects. The geometrical shape, the tumor's size and tissue's abnormal growth can be calculated by the segmentation of that particular image. It is still a great challenge for the researchers to tackle with an automatic segmentation in the medical imaging. Based on the texture analysis, different images are processed by optimization of level set segmentation. Traditionally, optimization was manual for every image where each parameter is selected one after another. By applying fuzzy logic, the segmentation of image is correlated based on texture features, to make it automatic and more effective. There is no initialization of parameters and it works like an intelligent system. It segments the different MRI images without tuning the level set parameters and give optimized results for all MRI's.

Texture Repairing by Unified Low Rank Optimization

Institute of Scientific and Technical Information of China (English)

Xiao Liang; Xiang Ren; Zhengdong Zhang; Yi Ma

2016-01-01

In this paper, we show how to harness both low-rank and sparse structures in regular or near-regular textures for image completion. Our method is based on a unified formulation for both random and contiguous corruption. In addition to the low rank property of texture, the algorithm also uses the sparse assumption of the natural image: because the natural image is piecewise smooth, it is sparse in certain transformed domain (such as Fourier or wavelet transform). We combine low-rank and sparsity properties of the texture image together in the proposed algorithm. Our algorithm based on convex optimization can automatically and correctly repair the global structure of a corrupted texture, even without precise information about the regions to be completed. This algorithm integrates texture rectification and repairing into one optimization problem. Through extensive simulations, we show our method can complete and repair textures corrupted by errors with both random and contiguous supports better than existing low-rank matrix recovery methods. Our method demonstrates significant advantage over local patch based texture synthesis techniques in dealing with large corruption, non-uniform texture, and large perspective deformation.

Correlation between macro texture measures carried out by the volumetric method and by different laser texture meter; Correlacion de medidas de macrotextura tomadas con el metodo volumetrico y con diferentes texturometros lasar

Energy Technology Data Exchange (ETDEWEB)

Parra Ruiz, L.; Yanguas Gonzalez, S. J.

2013-06-01

The reference value for the measurement of surface macro texture in the Spanish Main Road Network is the MTD or Mean Texture Depth (PMT, Profundidad Media de Textura), obtained by means of the volumetric methods, in accordance with the standard UNE EN 13036-1:12010. The fact that it is a spot measurement that requires road closures makes it an expensive procedure as well as slow and dangerous. In addition to this, the test results are relatively sensitive to the operator, being the procedure not too suitable for systematic surveys. These are some of the reasons that have contributed to the development of texture meter laser devices that can be assembled on board of vehicles, circulating without interfering with the normal traffic flow and providing a parameter named the MPD (Mean Depth Profile). According to the standard UNE-EN ISO 13473-1:2006, it is possible to estimate the texture obtained by volumetric methods, with the parameter ETD (Estimated Texture Depth) through the equation: ETD=0,8 x MPD+0.2 In 2008 CEDEX conducted a study that correlated macro texture measures obtained by means of the volumetric method with such carried out by different laser texture meters. The equations yield a better relation between MPD and MTD were dependent on the measurement device used and were not linear equations type, as is it indicated in the standard, but exponential type equations. (Author) 6 refs.

Prostate-specific membrane antigen PET/MRI validation of MR textural analysis for detection of transition zone prostate cancer

Energy Technology Data Exchange (ETDEWEB)

Bates, Anthony [Princess Alexandra Hospital, Brisbane (Australia); Miles, Kenneth [Princess Alexandra Hospital, Department of Diagnostic Radiology, Brisbane, QLD (Australia); University College London, Institute of Nuclear Medicine, London (United Kingdom)

2017-12-15

To validate MR textural analysis (MRTA) for detection of transition zone (TZ) prostate cancer through comparison with co-registered prostate-specific membrane antigen (PSMA) PET-MR. Retrospective analysis was performed for 30 men who underwent simultaneous PSMA PET-MR imaging for staging of prostate cancer. Thirty texture features were derived from each manually contoured T2-weighted, transaxial, prostatic TZ using texture analysis software that applies a spatial band-pass filter and quantifies texture through histogram analysis. Texture features of the TZ were compared to PSMA expression on the corresponding PET images. The Benjamini-Hochberg correction controlled the false discovery rate at <5%. Eighty-eight T2-weighted images in 18 patients demonstrated abnormal PSMA expression within the TZ on PET-MR. 123 images were PSMA negative. Based on the corrected p-value of 0.005, significant differences between PSMA positive and negative slices were found for 16 texture parameters: Standard deviation and mean of positive pixels for all spatial filters (p = <0.0001 for both at all spatial scaling factor (SSF) values) and mean intensity following filtration for SSF 3-6 mm (p = 0.0002-0.0018). Abnormal expression of PSMA within the TZ is associated with altered texture on T2-weighted MR, providing validation of MRTA for the detection of TZ prostate cancer. (orig.)

Prostate-specific membrane antigen PET/MRI validation of MR textural analysis for detection of transition zone prostate cancer

International Nuclear Information System (INIS)

Bates, Anthony; Miles, Kenneth

2017-01-01

To validate MR textural analysis (MRTA) for detection of transition zone (TZ) prostate cancer through comparison with co-registered prostate-specific membrane antigen (PSMA) PET-MR. Retrospective analysis was performed for 30 men who underwent simultaneous PSMA PET-MR imaging for staging of prostate cancer. Thirty texture features were derived from each manually contoured T2-weighted, transaxial, prostatic TZ using texture analysis software that applies a spatial band-pass filter and quantifies texture through histogram analysis. Texture features of the TZ were compared to PSMA expression on the corresponding PET images. The Benjamini-Hochberg correction controlled the false discovery rate at <5%. Eighty-eight T2-weighted images in 18 patients demonstrated abnormal PSMA expression within the TZ on PET-MR. 123 images were PSMA negative. Based on the corrected p-value of 0.005, significant differences between PSMA positive and negative slices were found for 16 texture parameters: Standard deviation and mean of positive pixels for all spatial filters (p = <0.0001 for both at all spatial scaling factor (SSF) values) and mean intensity following filtration for SSF 3-6 mm (p = 0.0002-0.0018). Abnormal expression of PSMA within the TZ is associated with altered texture on T2-weighted MR, providing validation of MRTA for the detection of TZ prostate cancer. (orig.)

Bone marrow cavity segmentation using graph-cuts with wavelet-based texture feature.

Science.gov (United States)

Shigeta, Hironori; Mashita, Tomohiro; Kikuta, Junichi; Seno, Shigeto; Takemura, Haruo; Ishii, Masaru; Matsuda, Hideo

2017-10-01

Emerging bioimaging technologies enable us to capture various dynamic cellular activities [Formula: see text]. As large amounts of data are obtained these days and it is becoming unrealistic to manually process massive number of images, automatic analysis methods are required. One of the issues for automatic image segmentation is that image-taking conditions are variable. Thus, commonly, many manual inputs are required according to each image. In this paper, we propose a bone marrow cavity (BMC) segmentation method for bone images as BMC is considered to be related to the mechanism of bone remodeling, osteoporosis, and so on. To reduce manual inputs to segment BMC, we classified the texture pattern using wavelet transformation and support vector machine. We also integrated the result of texture pattern classification into the graph-cuts-based image segmentation method because texture analysis does not consider spatial continuity. Our method is applicable to a particular frame in an image sequence in which the condition of fluorescent material is variable. In the experiment, we evaluated our method with nine types of mother wavelets and several sets of scale parameters. The proposed method with graph-cuts and texture pattern classification performs well without manual inputs by a user.

Macroscopic Rock Texture Image Classification Using a Hierarchical Neuro-Fuzzy Class Method

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Laercio B. Gonçalves

2010-01-01

Full Text Available We used a Hierarchical Neuro-Fuzzy Class Method based on binary space partitioning (NFHB-Class Method for macroscopic rock texture classification. The relevance of this study is in helping Geologists in the diagnosis and planning of oil reservoir exploration. The proposed method is capable of generating its own decision structure, with automatic extraction of fuzzy rules. These rules are linguistically interpretable, thus explaining the obtained data structure. The presented image classification for macroscopic rocks is based on texture descriptors, such as spatial variation coefficient, Hurst coefficient, entropy, and cooccurrence matrix. Four rock classes have been evaluated by the NFHB-Class Method: gneiss (two subclasses, basalt (four subclasses, diabase (five subclasses, and rhyolite (five subclasses. These four rock classes are of great interest in the evaluation of oil boreholes, which is considered a complex task by geologists. We present a computer method to solve this problem. In order to evaluate system performance, we used 50 RGB images for each rock classes and subclasses, thus producing a total of 800 images. For all rock classes, the NFHB-Class Method achieved a percentage of correct hits over 73%. The proposed method converged for all tests presented in the case study.

3D tooth microwear texture analysis in fishes as a test of dietary hypotheses of durophagy

Science.gov (United States)

Purnell, Mark A.; Darras, Laurent P. G.

2016-03-01

An understanding of how extinct animals functioned underpins our understanding of past evolutionary events, including adaptive radiations, and the role of functional innovation and adaptation as drivers of both micro- and macroevolution. Yet analysis of function in extinct animals is fraught with difficulty. Hypotheses that interpret molariform teeth in fishes as evidence of durophagous (shell-crushing) diets provide a good example of the particular problems inherent in the methods of functional morphology. This is because the assumed close coupling of form and function upon which the approach is based is weakened by, among other things, behavioural flexibility and the absence of a clear one to one relationship between structures and functions. Here we show that ISO 25178-2 standard parameters for surface texture, derived from analysis of worn surfaces of molariform teeth of fishes, vary significantly between species that differ in the amount of hard-shelled prey they consume. Two populations of the Sheepshead Seabream (Archosargus probatocephalus) were studied. This fish is not a dietary specialist, and one of the populations is known to consume more vegetation and less hard-shelled prey than the other; this is reflected in significant differences in their microwear textures. The Archosargus populations differ significantly in their microwear from the specialist shell-crusher Anarhichas lupus (the Atlantic Wolffish). Multivariate analysis of these three groups of fishes lends further support to the relationship between diet and tooth microwear, and provides robust validation of the approach. Application of the multivariate models derived from microwear texture in Archosargus and Anarhichas to a third fish species—the cichlid Astatoreochromis alluaudi—successfully separates wild caught fish that ate hard-shelled prey from lab-raised fish that did not. This cross-taxon validation demonstrates that quantitative analysis of tooth microwear texture can

3D tooth microwear texture analysis in fishes as a test of dietary hypotheses of durophagy

International Nuclear Information System (INIS)

Purnell, Mark A; Darras, Laurent P G

2016-01-01

An understanding of how extinct animals functioned underpins our understanding of past evolutionary events, including adaptive radiations, and the role of functional innovation and adaptation as drivers of both micro- and macroevolution. Yet analysis of function in extinct animals is fraught with difficulty. Hypotheses that interpret molariform teeth in fishes as evidence of durophagous (shell-crushing) diets provide a good example of the particular problems inherent in the methods of functional morphology. This is because the assumed close coupling of form and function upon which the approach is based is weakened by, among other things, behavioural flexibility and the absence of a clear one to one relationship between structures and functions. Here we show that ISO 25178-2 standard parameters for surface texture, derived from analysis of worn surfaces of molariform teeth of fishes, vary significantly between species that differ in the amount of hard-shelled prey they consume. Two populations of the Sheepshead Seabream (Archosargus probatocephalus) were studied. This fish is not a dietary specialist, and one of the populations is known to consume more vegetation and less hard-shelled prey than the other; this is reflected in significant differences in their microwear textures. The Archosargus populations differ significantly in their microwear from the specialist shell-crusher Anarhichas lupus (the Atlantic Wolffish). Multivariate analysis of these three groups of fishes lends further support to the relationship between diet and tooth microwear, and provides robust validation of the approach. Application of the multivariate models derived from microwear texture in Archosargus and Anarhichas to a third fish species—the cichlid Astatoreochromis alluaudi—successfully separates wild caught fish that ate hard-shelled prey from lab-raised fish that did not. This cross-taxon validation demonstrates that quantitative analysis of tooth microwear texture can

Symmetry realization of texture zeros

International Nuclear Information System (INIS)

Grimus, W.; Joshipura, A.S.; Lavoura, L.; Tanimoto, M.

2004-01-01

We show that it is possible to enforce texture zeros in arbitrary entries of the fermion mass matrices by means of Abelian symmetries; in this way, many popular mass-matrix textures find a symmetry justification. We propose two alternative methods which allow one to place zeros in any number of elements of the mass matrices that one wants. They are applicable simultaneously in the quark and lepton sectors. They are also applicable in grand unified theories. The number of scalar fields required by our methods may be large; still, in many interesting cases this number can be reduced considerably. The larger the desired number of texture zeros is, the simpler are the models which reproduce the texture. (orig.)

Deep neural networks for texture classification-A theoretical analysis.

Science.gov (United States)

Basu, Saikat; Mukhopadhyay, Supratik; Karki, Manohar; DiBiano, Robert; Ganguly, Sangram; Nemani, Ramakrishna; Gayaka, Shreekant

2018-01-01

We investigate the use of Deep Neural Networks for the classification of image datasets where texture features are important for generating class-conditional discriminative representations. To this end, we first derive the size of the feature space for some standard textural features extracted from the input dataset and then use the theory of Vapnik-Chervonenkis dimension to show that hand-crafted feature extraction creates low-dimensional representations which help in reducing the overall excess error rate. As a corollary to this analysis, we derive for the first time upper bounds on the VC dimension of Convolutional Neural Network as well as Dropout and Dropconnect networks and the relation between excess error rate of Dropout and Dropconnect networks. The concept of intrinsic dimension is used to validate the intuition that texture-based datasets are inherently higher dimensional as compared to handwritten digits or other object recognition datasets and hence more difficult to be shattered by neural networks. We then derive the mean distance from the centroid to the nearest and farthest sampling points in an n-dimensional manifold and show that the Relative Contrast of the sample data vanishes as dimensionality of the underlying vector space tends to infinity. Copyright © 2017 Elsevier Ltd. All rights reserved.

Classifying brain metastases by their primary site of origin using a radiomics approach based on texture analysis: a feasibility study.

Science.gov (United States)

Ortiz-Ramón, Rafael; Larroza, Andrés; Ruiz-España, Silvia; Arana, Estanislao; Moratal, David

2018-05-14

To examine the capability of MRI texture analysis to differentiate the primary site of origin of brain metastases following a radiomics approach. Sixty-seven untreated brain metastases (BM) were found in 3D T1-weighted MRI of 38 patients with cancer: 27 from lung cancer, 23 from melanoma and 17 from breast cancer. These lesions were segmented in 2D and 3D to compare the discriminative power of 2D and 3D texture features. The images were quantized using different number of gray-levels to test the influence of quantization. Forty-three rotation-invariant texture features were examined. Feature selection and random forest classification were implemented within a nested cross-validation structure. Classification was evaluated with the area under receiver operating characteristic curve (AUC) considering two strategies: multiclass and one-versus-one. In the multiclass approach, 3D texture features were more discriminative than 2D features. The best results were achieved for images quantized with 32 gray-levels (AUC = 0.873 ± 0.064) using the top four features provided by the feature selection method based on the p-value. In the one-versus-one approach, high accuracy was obtained when differentiating lung cancer BM from breast cancer BM (four features, AUC = 0.963 ± 0.054) and melanoma BM (eight features, AUC = 0.936 ± 0.070) using the optimal dataset (3D features, 32 gray-levels). Classification of breast cancer and melanoma BM was unsatisfactory (AUC = 0.607 ± 0.180). Volumetric MRI texture features can be useful to differentiate brain metastases from different primary cancers after quantizing the images with the proper number of gray-levels. • Texture analysis is a promising source of biomarkers for classifying brain neoplasms. • MRI texture features of brain metastases could help identifying the primary cancer. • Volumetric texture features are more discriminative than traditional 2D texture features.

Quantitative texture analysis of electrodeposited line patterns

DEFF Research Database (Denmark)

Pantleon, Karen; Somers, Marcel A.J.

2005-01-01

Free-standing line patterns of Cu and Ni were manufactured by electrochemical deposition into lithographically prepared patterns. Electrodeposition was carried out on top of a highly oriented Au-layer physically vapor deposited on glass. Quantitative texture analysis carried out by means of x......-ray diffraction for both the substrate layer and the electrodeposits yielded experimental evidence for epitaxy between Cu and Au. An orientation relation between film and substrate was discussed with respect to various concepts of epitaxy. While the conventional mode of epitaxy fails for the Cu...

Can Laws Be a Potential PET Image Texture Analysis Approach for Evaluation of Tumor Heterogeneity and Histopathological Characteristics in NSCLC?

Science.gov (United States)

Karacavus, Seyhan; Yılmaz, Bülent; Tasdemir, Arzu; Kayaaltı, Ömer; Kaya, Eser; İçer, Semra; Ayyıldız, Oguzhan

2018-04-01

We investigated the association between the textural features obtained from 18 F-FDG images, metabolic parameters (SUVmax , SUVmean, MTV, TLG), and tumor histopathological characteristics (stage and Ki-67 proliferation index) in non-small cell lung cancer (NSCLC). The FDG-PET images of 67 patients with NSCLC were evaluated. MATLAB technical computing language was employed in the extraction of 137 features by using first order statistics (FOS), gray-level co-occurrence matrix (GLCM), gray-level run length matrix (GLRLM), and Laws' texture filters. Textural features and metabolic parameters were statistically analyzed in terms of good discrimination power between tumor stages, and selected features/parameters were used in the automatic classification by k-nearest neighbors (k-NN) and support vector machines (SVM). We showed that one textural feature (gray-level nonuniformity, GLN) obtained using GLRLM approach and nine textural features using Laws' approach were successful in discriminating all tumor stages, unlike metabolic parameters. There were significant correlations between Ki-67 index and some of the textural features computed using Laws' method (r = 0.6, p = 0.013). In terms of automatic classification of tumor stage, the accuracy was approximately 84% with k-NN classifier (k = 3) and SVM, using selected five features. Texture analysis of FDG-PET images has a potential to be an objective tool to assess tumor histopathological characteristics. The textural features obtained using Laws' approach could be useful in the discrimination of tumor stage.

Feasibility of opportunistic osteoporosis screening in routine contrast-enhanced multi detector computed tomography (MDCT) using texture analysis.

Science.gov (United States)

Mookiah, M R K; Rohrmeier, A; Dieckmeyer, M; Mei, K; Kopp, F K; Noel, P B; Kirschke, J S; Baum, T; Subburaj, K

2018-04-01

This study investigated the feasibility of opportunistic osteoporosis screening in routine contrast-enhanced MDCT exams using texture analysis. The results showed an acceptable reproducibility of texture features, and these features could discriminate healthy/osteoporotic fracture cohort with an accuracy of 83%. This aim of this study is to investigate the feasibility of opportunistic osteoporosis screening in routine contrast-enhanced MDCT exams using texture analysis. We performed texture analysis at the spine in routine MDCT exams and investigated the effect of intravenous contrast medium (IVCM) (n = 7), slice thickness (n = 7), the long-term reproducibility (n = 9), and the ability to differentiate healthy/osteoporotic fracture cohort (n = 9 age and gender matched pairs). Eight texture features were extracted using gray level co-occurrence matrix (GLCM). The independent sample t test was used to rank the features of healthy/fracture cohort and classification was performed using support vector machine (SVM). The results revealed significant correlations between texture parameters derived from MDCT scans with and without IVCM (r up to 0.91) slice thickness of 1 mm versus 2 and 3 mm (r up to 0.96) and scan-rescan (r up to 0.59). The performance of the SVM classifier was evaluated using 10-fold cross-validation and revealed an average classification accuracy of 83%. Opportunistic osteoporosis screening at the spine using specific texture parameters (energy, entropy, and homogeneity) and SVM can be performed in routine contrast-enhanced MDCT exams.

A neural network detection model of spilled oil based on the texture analysis of SAR image

Science.gov (United States)

An, Jubai; Zhu, Lisong

2006-01-01

A Radial Basis Function Neural Network (RBFNN) Model is investigated for the detection of spilled oil based on the texture analysis of SAR imagery. In this paper, to take the advantage of the abundant texture information of SAR imagery, the texture features are extracted by both wavelet transform and the Gray Level Co-occurrence matrix. The RBFNN Model is fed with a vector of these texture features. The RBFNN Model is trained and tested by the sample data set of the feature vectors. Finally, a SAR image is classified by this model. The classification results of a spilled oil SAR image show that the classification accuracy for oil spill is 86.2 by the RBFNN Model using both wavelet texture and gray texture, while the classification accuracy for oil spill is 78.0 by same RBFNN Model using only wavelet texture as the input of this RBFNN model. The model using both wavelet transform and the Gray Level Co-occurrence matrix is more effective than that only using wavelet texture. Furthermore, it keeps the complicated proximity and has a good performance of classification.

Template characterization and correlation algorithm created from segmentation for the iris biometric authentication based on analysis of textures implemented on a FPGA

International Nuclear Information System (INIS)

Giacometto, F J; Vilardy, J M; Torres, C O; Mattos, L

2011-01-01

Among the most used biometric signals to set personal security permissions, taker increasingly importance biometric iris recognition based on their textures and images of blood vessels due to the rich in these two unique characteristics that are unique to each individual. This paper presents an implementation of an algorithm characterization and correlation of templates created for biometric authentication based on iris texture analysis programmed on a FPGA (Field Programmable Gate Array), authentication is based on processes like characterization methods based on frequency analysis of the sample, and frequency correlation to obtain the expected results of authentication.

Feature-aware natural texture synthesis

KAUST Repository

Wu, Fuzhang

2014-12-04

This article presents a framework for natural texture synthesis and processing. This framework is motivated by the observation that given examples captured in natural scene, texture synthesis addresses a critical problem, namely, that synthesis quality can be affected adversely if the texture elements in an example display spatially varied patterns, such as perspective distortion, the composition of different sub-textures, and variations in global color pattern as a result of complex illumination. This issue is common in natural textures and is a fundamental challenge for previously developed methods. Thus, we address it from a feature point of view and propose a feature-aware approach to synthesize natural textures. The synthesis process is guided by a feature map that represents the visual characteristics of the input texture. Moreover, we present a novel adaptive initialization algorithm that can effectively avoid the repeat and verbatim copying artifacts. Our approach improves texture synthesis in many images that cannot be handled effectively with traditional technologies.

TEXTURAL DESCRIPTORS FOR MULTIPHASIC ORE PARTICLES

Directory of Open Access Journals (Sweden)

Laura Pérez-Barnuevo

2012-11-01

Full Text Available Monitoring of mineral processing circuits by means of particle liberation analysis through quantitative image analysis has become a routine technique within the last decades. Usually, liberation indices are computed as weight proportions, which is not informative enough when complex texture ores are treated by flotation. In these cases, liberation has to be computed as phase surface exposed to reactants, and textural relationships between minerals have to be characterized to determine the possibility of increasing exposure. In this paper, some indices to achieve a complete texture characterization have been developed in terms of 2D phase contact and mineral surfaces exposure. Indices suggested by other authors are also compared. The response of this set of parameters against textural changes has been explored on simple synthetic textures ranging from single to multiple inclusions and single to multiple veins and their ability to discriminate between different textural features is analyzed over real mineral particles with known internal structure.

Application of texture analysis in tear film surface assessment based on videokeratoscopy

Directory of Open Access Journals (Sweden)

David Alonso-Caneiro

2013-10-01

Conclusions: Texture analysis of videokeratoscopy images is applicable to study tear film anomalies in dry eye subjects. The proposed technique appears to have demonstrated its clinical relevance and utility.

TEXTURE ANALYSIS OF EXTRUDED APPLE POMACE - WHEAT SEMOLINA BLENDS

Directory of Open Access Journals (Sweden)

Ivan Bakalov

2016-03-01

Full Text Available Apple pomace - wheat semolina blends were extruded in a laboratory single screw extruder (Brabender 20 DN, Germany. Effects apple pomace content, moisture content, screw speed, and temperature of final cooking zone on texture of extrudates were studied applying response surface methodology. The texture characteristics of the extrudates were measured using a TA.XT Plus Texture Analyser, Stable Micro Systems.

Review of relationships between grey-tone co-occurrence, semivariance, and autocorrelation based image texture analysis approaches

NARCIS (Netherlands)

Sanden, van der J.J.; Hoekman, D.H.

2005-01-01

In the present paper we review relationships between commonly used statistical approaches to analysis of image texture. The approaches considered characterize image texture by means of the statistics of grey- tone co- occurrence contrast, grey- tone co- occurrence correlation, semivariance, and

MRI Texture Analysis Reflects Histopathology Parameters in Thyroid Cancer - A First Preliminary Study.

Science.gov (United States)

Meyer, Hans-Jonas; Schob, Stefan; Höhn, Anne Kathrin; Surov, Alexey

2017-12-01

Thyroid cancer represents the most frequent malignancy of the endocrine system with an increasing incidence worldwide. Novel imaging techniques are able to further characterize tumors and even predict histopathology features. Texture analysis is an emergent imaging technique to extract extensive data from an radiology images. The present study was therefore conducted to identify possible associations between texture analysis and histopathology parameters in thyroid cancer. The radiological database was retrospectively reviewed for thyroid carcinoma. Overall, 13 patients (3 females, 23.1%) with a mean age of 61.6 years were identified. The MaZda program was used for texture analysis. The T1-precontrast and T2-weighted images were analyzed and overall 279 texture feature for each sequence was investigated. For every patient cell count, Ki67-index and p53 count were investigated. Several significant correlations between texture features and histopathology were identified. Regarding T1-weighted images, S(0;1)Sum Averg correlated the most with cell count (r=0.82). An inverse correlations with S(5;0)AngScMom, S(5;0)DifVarnc S(5;0), DiffEntrp and GrNonZeros (r=-0.69, -0.66, -0.69 and -0.63, respectively) was also identified. For T2-weighted images, Variance with r=0.63 was the highest coefficient, WavEnLL_S3 correlated inversely with cell count (r=-0.57). WavEnLL_S2 derived from T1-weighted images was the highest coefficient r=-0.80, S(0;5)SumVarnc was positively with r=0.74. Regarding T2-weighted images WavEnHL_s-1 was inverse correlated with Ki67 index (r=-0.77). S(1;0)Correlat was with r=0.75 the best correlation with Ki67 index. For T1-weighed images S(5;0)SumofSqs was the best with r=0.65 with p53 count. For T2-weighted images S(1;-1)SumEntrp was the inverse correlation with r=-0.72, whereas S(0;4)AngScMom correlated positively with r=0.63. MRI texture analysis derived from conventional sequences reflects histopathology features in thyroid cancer. This technique

Investigation on the evolution of microstructure and texture of electroplated Ni–Ti composite coating by Rietveld method

Energy Technology Data Exchange (ETDEWEB)

Zhao, Yuantao, E-mail: zhaoyuantao@sjtu.edu.cn; Cai, Fei, E-mail: caifei32@126.com; Wang, Chengxi, E-mail: sjtucxw@sjtu.edu.cn; Chai, Ze, E-mail: zechaisjtu@163.com; Zhu, Kaiyuan, E-mail: xrd125@163.com; Xu, Zhou, E-mail: xuzhou@sjtu.edu.cn; Jiang, Chuanhai, E-mail: chjiang-sjtu@hotmail.com

2015-10-30

Highlights: • Ni–Ti composite coatings were prepared by electroplating. • Morphology and Ti content of Ni–Ti coatings were studied upon SEM and EDXS. • Microstructures of Ni–Ti coatings were studied upon the Rietveld method. • The texture of Ni–Ti coatings was studied upon the pole figure. - Abstract: Rietveld refinement was utilized to investigate the evolution of microstructure and texture of the Ni–Ti composite coatings electroplated at different applied current densities. Scanning Electron Microscope and Energy Dispersive Spectroscopy were utilized to investigate the morphology and chemical composition of the coatings. Relative texture coefficients (RTC) and measured pole figures were utilized to investigate the texture evolution of the coatings. The results showed that the surface morphology of the coatings changed from a colonial structure to a polyhedral one. And the incorporated Ti content decreased with increasing applied current density. As the applied current density increased, the crystallite sizes increased and their distribution got less uniform, and the microstrain and dislocation density decreased. The results of simulated pole figures obtained from Rietveld refinement illustrated that the texture of the coatings changed from no obvious texture to a strong [2 0 0] fiber texture with increasing applied current density. The texture evolution obtained from simulated pole figures was confirmed by the result of RTC and the measured pole figures. The evolutions of the microstructure and texture were derived from the change of the applied current density and incorporated Ti content in the Ni–Ti composite coatings.

Spectral multi-energy CT texture analysis with machine learning for tissue classification: an investigation using classification of benign parotid tumours as a testing paradigm.

Science.gov (United States)

Al Ajmi, Eiman; Forghani, Behzad; Reinhold, Caroline; Bayat, Maryam; Forghani, Reza

2018-06-01

There is a rich amount of quantitative information in spectral datasets generated from dual-energy CT (DECT). In this study, we compare the performance of texture analysis performed on multi-energy datasets to that of virtual monochromatic images (VMIs) at 65 keV only, using classification of the two most common benign parotid neoplasms as a testing paradigm. Forty-two patients with pathologically proven Warthin tumour (n = 25) or pleomorphic adenoma (n = 17) were evaluated. Texture analysis was performed on VMIs ranging from 40 to 140 keV in 5-keV increments (multi-energy analysis) or 65-keV VMIs only, which is typically considered equivalent to single-energy CT. Random forest (RF) models were constructed for outcome prediction using separate randomly selected training and testing sets or the entire patient set. Using multi-energy texture analysis, tumour classification in the independent testing set had accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of 92%, 86%, 100%, 100%, and 83%, compared to 75%, 57%, 100%, 100%, and 63%, respectively, for single-energy analysis. Multi-energy texture analysis demonstrates superior performance compared to single-energy texture analysis of VMIs at 65 keV for classification of benign parotid tumours. • We present and validate a paradigm for texture analysis of DECT scans. • Multi-energy dataset texture analysis is superior to single-energy dataset texture analysis. • DECT texture analysis has high accura\\cy for diagnosis of benign parotid tumours. • DECT texture analysis with machine learning can enhance non-invasive diagnostic tumour evaluation.

Cascaded Amplitude Modulations in Sound Texture Perception

Directory of Open Access Journals (Sweden)

Richard McWalter

2017-09-01

Full Text Available Sound textures, such as crackling fire or chirping crickets, represent a broad class of sounds defined by their homogeneous temporal structure. It has been suggested that the perception of texture is mediated by time-averaged summary statistics measured from early auditory representations. In this study, we investigated the perception of sound textures that contain rhythmic structure, specifically second-order amplitude modulations that arise from the interaction of different modulation rates, previously described as “beating” in the envelope-frequency domain. We developed an auditory texture model that utilizes a cascade of modulation filterbanks that capture the structure of simple rhythmic patterns. The model was examined in a series of psychophysical listening experiments using synthetic sound textures—stimuli generated using time-averaged statistics measured from real-world textures. In a texture identification task, our results indicated that second-order amplitude modulation sensitivity enhanced recognition. Next, we examined the contribution of the second-order modulation analysis in a preference task, where the proposed auditory texture model was preferred over a range of model deviants that lacked second-order modulation rate sensitivity. Lastly, the discriminability of textures that included second-order amplitude modulations appeared to be perceived using a time-averaging process. Overall, our results demonstrate that the inclusion of second-order modulation analysis generates improvements in the perceived quality of synthetic textures compared to the first-order modulation analysis considered in previous approaches.

Automated detection of regions of interest for tissue microarray experiments: an image texture analysis

International Nuclear Information System (INIS)

Karaçali, Bilge; Tözeren, Aydin

2007-01-01

Recent research with tissue microarrays led to a rapid progress toward quantifying the expressions of large sets of biomarkers in normal and diseased tissue. However, standard procedures for sampling tissue for molecular profiling have not yet been established. This study presents a high throughput analysis of texture heterogeneity on breast tissue images for the purpose of identifying regions of interest in the tissue for molecular profiling via tissue microarray technology. Image texture of breast histology slides was described in terms of three parameters: the percentage of area occupied in an image block by chromatin (B), percentage occupied by stroma-like regions (P), and a statistical heterogeneity index H commonly used in image analysis. Texture parameters were defined and computed for each of the thousands of image blocks in our dataset using both the gray scale and color segmentation. The image blocks were then classified into three categories using the texture feature parameters in a novel statistical learning algorithm. These categories are as follows: image blocks specific to normal breast tissue, blocks specific to cancerous tissue, and those image blocks that are non-specific to normal and disease states. Gray scale and color segmentation techniques led to identification of same regions in histology slides as cancer-specific. Moreover the image blocks identified as cancer-specific belonged to those cell crowded regions in whole section image slides that were marked by two pathologists as regions of interest for further histological studies. These results indicate the high efficiency of our automated method for identifying pathologic regions of interest on histology slides. Automation of critical region identification will help minimize the inter-rater variability among different raters (pathologists) as hundreds of tumors that are used to develop an array have typically been evaluated (graded) by different pathologists. The region of interest

3D texture analysis reveals imperceptible MRI textural alterations in the thalamus and putamen in progressive myoclonic epilepsy type 1, EPM1.

Directory of Open Access Journals (Sweden)

Sanna Suoranta

Full Text Available Progressive myoclonic epilepsy type 1 (EPM1 is an autosomal recessively inherited neurodegenerative disorder characterized by young onset age, myoclonus and tonic-clonic epileptic seizures. At the time of diagnosis, the visual assessment of the brain MRI is usually normal, with no major changes found later. Therefore, we utilized texture analysis (TA to characterize and classify the underlying properties of the affected brain tissue by means of 3D texture features. Sixteen genetically verified patients with EPM1 and 16 healthy controls were included in the study. TA was performed upon 3D volumes of interest that were placed bilaterally in the thalamus, amygdala, hippocampus, caudate nucleus and putamen. Compared to the healthy controls, EPM1 patients had significant textural differences especially in the thalamus and right putamen. The most significantly differing texture features included parameters that measure the complexity and heterogeneity of the tissue, such as the co-occurrence matrix-based entropy and angular second moment, and also the run-length matrix-based parameters of gray-level non-uniformity, short run emphasis and long run emphasis. This study demonstrates the usability of 3D TA for extracting additional information from MR images. Textural alterations which suggest complex, coarse and heterogeneous appearance were found bilaterally in the thalamus, supporting the previous literature on thalamic pathology in EPM1. The observed putamenal involvement is a novel finding. Our results encourage further studies on the clinical applications, feasibility, reproducibility and reliability of 3D TA.

Wettability transition of laser textured brass surfaces inside different mediums

Science.gov (United States)

Yan, Huangping; Abdul Rashid, Mohamed Raiz B.; Khew, Si Ying; Li, Fengping; Hong, Minghui

2018-01-01

Hydrophobic surface on brass has attracted intensive attention owing to its importance in scientific research and practical applications. Laser texturing provides a simple and promising method to achieve it. Reducing wettability transition time from hydrophilicity to hydrophobicity or superhydrophobicity remains a challenge. Herein, wettability transition of brass surfaces with hybrid micro/nano-structures fabricated by laser texturing was investigated by immersing the samples inside different mediums. Scanning electron microscopy, energy-dispersive X-ray analysis, X-ray photoelectron spectroscopy and surface contact angle measurement were employed to characterize surface morphology, chemical composition and wettability of the fabricated surfaces of brass samples. Wettability transition time from hydrophilicity to hydrophobicity was shortened by immersion into isopropyl alcohol for a period of 3 h as a result of the absorption and accumulation of organic substances on the textured brass surface. When the textured brass sample was immersed into sodium bicarbonate solution, flower-like structures on the sample surface played a key role in slowing down wettability transition. Moreover, it had the smallest steady state contact angle as compared to the others. This study provides a facile method to construct textured surfaces with tunable wetting behaviors and effectively extend the industrial applications of brass.

Automatic Texture Optimization for 3D Urban Reconstruction

Directory of Open Access Journals (Sweden)

LI Ming

2017-03-01

Full Text Available In order to solve the problem of texture optimization in 3D city reconstruction by using multi-lens oblique images, the paper presents a method of seamless texture model reconstruction. At first, it corrects the radiation information of images by camera response functions and image dark channel. Then, according to the corresponding relevance between terrain triangular mesh surface model to image, implements occlusion detection by sparse triangulation method, and establishes the triangles' texture list of visible. Finally, combines with triangles' topology relationship in 3D triangular mesh surface model and means and variances of image, constructs a graph-cuts-based texture optimization algorithm under the framework of MRF(Markov random filed, to solve the discrete label problem of texture optimization selection and clustering, ensures the consistency of the adjacent triangles in texture mapping, achieves the seamless texture reconstruction of city. The experimental results verify the validity and superiority of our proposed method.

Coupled X-ray computed tomography and grey level co-occurrence matrices as a method for quantification of mineralogy and texture in 3D

Science.gov (United States)

Jardine, M. A.; Miller, J. A.; Becker, M.

2018-02-01

Texture is one of the most basic descriptors used in the geological sciences. The value derived from textural characterisation extends into engineering applications associated with mining, mineral processing and metal extraction where quantitative textural information is required for models predicting the response of the ore through a particular process. This study extends the well-known 2D grey level co-occurrence matrices methodology into 3D as a method for image analysis of 3D x-ray computed tomography grey scale volumes of drill core. Subsequent interrogation of the information embedded within the grey level occurrence matrices (GLCM) indicates they are sensitive to changes in mineralogy and texture of samples derived from a magmatic nickel sulfide ore. The position of the peaks in the GLCM is an indication of the relative density (specific gravity, SG) of the minerals and when interpreted using a working knowledge of the mineralogy of the ore presented a means to determine the relative abundance of the sulfide minerals (SG > 4), dense silicate minerals (SG > 3), and lighter silicate minerals (SG < 3). The spread of the peaks in the GLCM away from the diagonal is an indication of the degree of grain boundary interaction with wide peaks representing fine grain sizes and narrow peaks representing coarse grain sizes. The method lends itself to application as part of a generic methodology for routine use on large XCT volumes providing quantitative, timely, meaningful and automated information on mineralogy and texture in 3D.

Performance Recognition for Sulphur Flotation Process Based on Froth Texture Unit Distribution

Directory of Open Access Journals (Sweden)

Mingfang He

2013-01-01

Full Text Available As an important indicator of flotation performance, froth texture is believed to be related to operational condition in sulphur flotation process. A novel fault detection method based on froth texture unit distribution (TUD is proposed to recognize the fault condition of sulphur flotation in real time. The froth texture unit number is calculated based on texture spectrum, and the probability density function (PDF of froth texture unit number is defined as texture unit distribution, which can describe the actual textual feature more accurately than the grey level dependence matrix approach. As the type of the froth TUD is unknown, a nonparametric kernel estimation method based on the fixed kernel basis is proposed, which can overcome the difficulty when comparing different TUDs under various conditions is impossible using the traditional varying kernel basis. Through transforming nonparametric description into dynamic kernel weight vectors, a principle component analysis (PCA model is established to reduce the dimensionality of the vectors. Then a threshold criterion determined by the TQ statistic based on the PCA model is proposed to realize the performance recognition. The industrial application results show that the accurate performance recognition of froth flotation can be achieved by using the proposed method.

Human versus artificial texture perception

NARCIS (Netherlands)

Petiet, Peter J.; van Erp, J.; Drullman, R.; van den Broek, Egon; Beintema, J.; van Wijngaarden, S.

2006-01-01

The performances of current texture analysis algorithms are still poor, especially when applied to a large, diffuse texture domain. Most of these purely computationally driven techniques are created to function within a highly restricted domain. When applied as computer vision techniques, frequently

INLINING 3D RECONSTRUCTION, MULTI-SOURCE TEXTURE MAPPING AND SEMANTIC ANALYSIS USING OBLIQUE AERIAL IMAGERY

Directory of Open Access Journals (Sweden)

D. Frommholz

2016-06-01

Full Text Available This paper proposes an in-line method for the simplified reconstruction of city buildings from nadir and oblique aerial images that at the same time are being used for multi-source texture mapping with minimal resampling. Further, the resulting unrectified texture atlases are analyzed for fac¸ade elements like windows to be reintegrated into the original 3D models. Tests on real-world data of Heligoland/ Germany comprising more than 800 buildings exposed a median positional deviation of 0.31 m at the fac¸ades compared to the cadastral map, a correctness of 67% for the detected windows and good visual quality when being rendered with GPU-based perspective correction. As part of the process building reconstruction takes the oriented input images and transforms them into dense point clouds by semi-global matching (SGM. The point sets undergo local RANSAC-based regression and topology analysis to detect adjacent planar surfaces and determine their semantics. Based on this information the roof, wall and ground surfaces found get intersected and limited in their extension to form a closed 3D building hull. For texture mapping the hull polygons are projected into each possible input bitmap to find suitable color sources regarding the coverage and resolution. Occlusions are detected by ray-casting a full-scale digital surface model (DSM of the scene and stored in pixel-precise visibility maps. These maps are used to derive overlap statistics and radiometric adjustment coefficients to be applied when the visible image parts for each building polygon are being copied into a compact texture atlas without resampling whenever possible. The atlas bitmap is passed to a commercial object-based image analysis (OBIA tool running a custom rule set to identify windows on the contained fac¸ade patches. Following multi-resolution segmentation and classification based on brightness and contrast differences potential window objects are evaluated against geometric

Pneumothorax detection in chest radiographs using local and global texture signatures

Science.gov (United States)

Geva, Ofer; Zimmerman-Moreno, Gali; Lieberman, Sivan; Konen, Eli; Greenspan, Hayit

2015-03-01

A novel framework for automatic detection of pneumothorax abnormality in chest radiographs is presented. The suggested method is based on a texture analysis approach combined with supervised learning techniques. The proposed framework consists of two main steps: at first, a texture analysis process is performed for detection of local abnormalities. Labeled image patches are extracted in the texture analysis procedure following which local analysis values are incorporated into a novel global image representation. The global representation is used for training and detection of the abnormality at the image level. The presented global representation is designed based on the distinctive shape of the lung, taking into account the characteristics of typical pneumothorax abnormalities. A supervised learning process was performed on both the local and global data, leading to trained detection system. The system was tested on a dataset of 108 upright chest radiographs. Several state of the art texture feature sets were experimented with (Local Binary Patterns, Maximum Response filters). The optimal configuration yielded sensitivity of 81% with specificity of 87%. The results of the evaluation are promising, establishing the current framework as a basis for additional improvements and extensions.

Geometrical conditions at the quantitative neutronographic texture analysis

International Nuclear Information System (INIS)

Tobisch, J.; Kleinstueck, K.

1975-10-01

The beam geometry for measuring quantitative pole figures by a neutronographic texture diffractometer is explained for transmission and reflection arrangement of spherical samples and sheets. For given dimensions of counter aperture the maximum possible cross sections of the incident beam are calculated as a function of sample dimensions and the Bragg angle theta. Methods for the calculation of absorption factors and volume correction are given. Under special conditions advantages result in the transmission case for sample motion into the direction +α. (author)

Effects of Different Grinding Methods on Morphological, Textural Properties and Pasting Profiles of MR220 Rice Flour

International Nuclear Information System (INIS)

Noorlaila Ahmad; Asmeda Rajab; Norziah Mohd Hani

2016-01-01

Three different grinding techniques (dry, semi-wet, and wet) were employed in rice flour production. Investigation on the effects of the grinding techniques on starch damage percentage, particle size distribution, pasting profiles, morphological and textural properties of rice flours produced were evaluated. Wet grinding resulted in significantly (p<0.05) has lower percentage of damaged starch (3.24 %) than other grinding methods. Morphological studies (microscopy and particle size analysis) have reflected significant differences among rice flours granule shapes. The granules displaying different shapes of polygonal, round and angular forms, with some as an individual granule while others tend to attached together. Wet grinding technique also yielded flour that exhibit significantly (p<0.05) with higher gel hardness (16.62 g). Pasting profiles showed that pasting temperature for rice flour produce using these three grinding methods varied between 80.15 - 80.42 degree Celcius. Results revealed that the three grinding techniques clearly affected the physicochemical properties of rice flour. The results from this study play an important role in the selection criteria of rice flour with desirable pasting and textural properties for manufacturing rice-based product. (author)

Haralick texture features from apparent diffusion coefficient (ADC) MRI images depend on imaging and pre-processing parameters.

Science.gov (United States)

Brynolfsson, Patrik; Nilsson, David; Torheim, Turid; Asklund, Thomas; Karlsson, Camilla Thellenberg; Trygg, Johan; Nyholm, Tufve; Garpebring, Anders

2017-06-22

In recent years, texture analysis of medical images has become increasingly popular in studies investigating diagnosis, classification and treatment response assessment of cancerous disease. Despite numerous applications in oncology and medical imaging in general, there is no consensus regarding texture analysis workflow, or reporting of parameter settings crucial for replication of results. The aim of this study was to assess how sensitive Haralick texture features of apparent diffusion coefficient (ADC) MR images are to changes in five parameters related to image acquisition and pre-processing: noise, resolution, how the ADC map is constructed, the choice of quantization method, and the number of gray levels in the quantized image. We found that noise, resolution, choice of quantization method and the number of gray levels in the quantized images had a significant influence on most texture features, and that the effect size varied between different features. Different methods for constructing the ADC maps did not have an impact on any texture feature. Based on our results, we recommend using images with similar resolutions and noise levels, using one quantization method, and the same number of gray levels in all quantized images, to make meaningful comparisons of texture feature results between different subjects.

Computer-assisted liver graft steatosis assessment via learning-based texture analysis.

Science.gov (United States)

Moccia, Sara; Mattos, Leonardo S; Patrini, Ilaria; Ruperti, Michela; Poté, Nicolas; Dondero, Federica; Cauchy, François; Sepulveda, Ailton; Soubrane, Olivier; De Momi, Elena; Diaspro, Alberto; Cesaretti, Manuela

2018-05-23

Fast and accurate graft hepatic steatosis (HS) assessment is of primary importance for lowering liver dysfunction risks after transplantation. Histopathological analysis of biopsied liver is the gold standard for assessing HS, despite being invasive and time consuming. Due to the short time availability between liver procurement and transplantation, surgeons perform HS assessment through clinical evaluation (medical history, blood tests) and liver texture visual analysis. Despite visual analysis being recognized as challenging in the clinical literature, few efforts have been invested to develop computer-assisted solutions for HS assessment. The objective of this paper is to investigate the automatic analysis of liver texture with machine learning algorithms to automate the HS assessment process and offer support for the surgeon decision process. Forty RGB images of forty different donors were analyzed. The images were captured with an RGB smartphone camera in the operating room (OR). Twenty images refer to livers that were accepted and 20 to discarded livers. Fifteen randomly selected liver patches were extracted from each image. Patch size was [Formula: see text]. This way, a balanced dataset of 600 patches was obtained. Intensity-based features (INT), histogram of local binary pattern ([Formula: see text]), and gray-level co-occurrence matrix ([Formula: see text]) were investigated. Blood-sample features (Blo) were included in the analysis, too. Supervised and semisupervised learning approaches were investigated for feature classification. The leave-one-patient-out cross-validation was performed to estimate the classification performance. With the best-performing feature set ([Formula: see text]) and semisupervised learning, the achieved classification sensitivity, specificity, and accuracy were 95, 81, and 88%, respectively. This research represents the first attempt to use machine learning and automatic texture analysis of RGB images from ubiquitous smartphone

Grinding as a method of meat texture evaluation.

Science.gov (United States)

Kenmegne Kamdem, A T; Hardy, J

1995-01-01

An electric grinder equipped with a torque/speed sensor was used to evaluate maximum grinding torque (T(max)) and total energy (TE) necessary to grind 150 g of uncooked meat. Texture profile analysis (TPA), relaxation and cutting tests were carried out and sample compositions were also determined. The degree of dependence between grinding, TPA, relaxation, cutting parameters and sample composition was checked. Results showed that grinding parameters (T(max) and TE) correlated better with TPA, relaxation and cutting parameters than with composition. In particular correlation coefficient of -0·92, -0·92 and 0·97 were obtained, respectively, between T(max) and relaxation percentage (%R), T(max) and destructuring coefficient at 25% conmpression (De(25)) and between T(max) and maximum cutting force (F(c)).

Analysis of elastic strain and crystallographic texture in poled rhombohedral PZT ceramics

International Nuclear Information System (INIS)

Hall, D.A.; Steuwer, A.; Cherdhirunkorn, B.; Mori, T.; Withers, P.J.

2006-01-01

The elastic strain and crystallographic texture of a rhombohedral lead zirconate titanate ceramic have been characterised in the remanent state, after poling, using high-energy synchrotron X-ray diffraction as a function of the grain orientation ψ relative to the poling direction. It is observed that the (2 0 0) diffraction peak exhibits pronounced shifts as a function of ψ, indicating an elastic lattice strain, while others ({1 1 1}, {1 1 2} and {2 2 0}) show marked changes in intensity as a result of preferred ferroelectric domain orientation. It is shown that the (2 0 0) peak is not affected by the domain switching itself but rather acts like an elastic macrostrain sensor. A simple Eshelby analysis is used to demonstrate that both the elastic strain and texture vary systematically with ψ according to the factor (3cos 2 ψ - 1). This angular dependence is evaluated through micromechanics modelling. The physical meaning of the texture variations with ψ is also discussed

Texture analysis of speckle in optical coherence tomography images of tissue phantoms

International Nuclear Information System (INIS)

Gossage, Kirk W; Smith, Cynthia M; Kanter, Elizabeth M; Hariri, Lida P; Stone, Alice L; Rodriguez, Jeffrey J; Williams, Stuart K; Barton, Jennifer K

2006-01-01

Optical coherence tomography (OCT) is an imaging modality capable of acquiring cross-sectional images of tissue using back-reflected light. Conventional OCT images have a resolution of 10-15 μm, and are thus best suited for visualizing tissue layers and structures. OCT images of collagen (with and without endothelial cells) have no resolvable features and may appear to simply show an exponential decrease in intensity with depth. However, examination of these images reveals that they display a characteristic repetitive structure due to speckle.The purpose of this study is to evaluate the application of statistical and spectral texture analysis techniques for differentiating living and non-living tissue phantoms containing various sizes and distributions of scatterers based on speckle content in OCT images. Statistically significant differences between texture parameters and excellent classification rates were obtained when comparing various endothelial cell concentrations ranging from 0 cells/ml to 25 million cells/ml. Statistically significant results and excellent classification rates were also obtained using various sizes of microspheres with concentrations ranging from 0 microspheres/ml to 500 million microspheres/ml. This study has shown that texture analysis of OCT images may be capable of differentiating tissue phantoms containing various sizes and distributions of scatterers

Three-dimensional textural analysis of brain images reveals distributed grey-matter abnormalities in schizophrenia

International Nuclear Information System (INIS)

Ganeshan, Balaji; Miles, Kenneth A.; Critchley, Hugo D.; Young, Rupert C.D.; Chatwin, Christopher R.; Gurling, Hugh M.D.

2010-01-01

Three-dimensional (3-D) selective- and relative-scale texture analysis (TA) was applied to structural magnetic resonance (MR) brain images to quantify the presence of grey-matter (GM) and white-matter (WM) textural abnormalities associated with schizophrenia. Brain TA comprised volume filtration using the Laplacian of Gaussian filter to highlight fine, medium and coarse textures within GM and WM, followed by texture quantification. Relative TA (e.g. ratio of fine to medium) was also computed. T1-weighted MR whole-brain images from 32 participants with diagnosis of schizophrenia (n = 10) and healthy controls (n = 22) were examined. Five patients possessed marker alleles (SZ8) associated with schizophrenia on chromosome 8 in the pericentriolar material 1 gene while the remaining five had not inherited any of the alleles (SZ0). Filtered fine GM texture (mean grey-level intensity; MGI) most significantly differentiated schizophrenic patients from controls (P = 0.0058; area under the receiver-operating characteristic curve = 0.809, sensitivity = 90%, specificity = 70%). WM measurements did not distinguish the two groups. Filtered GM and WM textures (MGI) correlated with total GM and WM volume respectively. Medium-to-coarse GM entropy distinguished SZ0 from controls (P = 0.0069) while measures from SZ8 were intermediate between the two. 3-D TA of brain MR enables detection of subtle distributed morphological features associated with schizophrenia, determined partly by susceptibility genes. (orig.)

Three-dimensional textural analysis of brain images reveals distributed grey-matter abnormalities in schizophrenia

Energy Technology Data Exchange (ETDEWEB)

Ganeshan, Balaji [University of Sussex, Falmer, Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, Brighton (United Kingdom); University of Sussex, Falmer, Department of Engineering and Design, Brighton (United Kingdom); Miles, Kenneth A.; Critchley, Hugo D. [University of Sussex, Falmer, Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, Brighton (United Kingdom); Young, Rupert C.D.; Chatwin, Christopher R. [University of Sussex, Falmer, Department of Engineering and Design, Brighton (United Kingdom); Gurling, Hugh M.D. [University College London, Department of Mental Health Sciences, London (United Kingdom)

2010-04-15

Three-dimensional (3-D) selective- and relative-scale texture analysis (TA) was applied to structural magnetic resonance (MR) brain images to quantify the presence of grey-matter (GM) and white-matter (WM) textural abnormalities associated with schizophrenia. Brain TA comprised volume filtration using the Laplacian of Gaussian filter to highlight fine, medium and coarse textures within GM and WM, followed by texture quantification. Relative TA (e.g. ratio of fine to medium) was also computed. T1-weighted MR whole-brain images from 32 participants with diagnosis of schizophrenia (n = 10) and healthy controls (n = 22) were examined. Five patients possessed marker alleles (SZ8) associated with schizophrenia on chromosome 8 in the pericentriolar material 1 gene while the remaining five had not inherited any of the alleles (SZ0). Filtered fine GM texture (mean grey-level intensity; MGI) most significantly differentiated schizophrenic patients from controls (P = 0.0058; area under the receiver-operating characteristic curve = 0.809, sensitivity = 90%, specificity = 70%). WM measurements did not distinguish the two groups. Filtered GM and WM textures (MGI) correlated with total GM and WM volume respectively. Medium-to-coarse GM entropy distinguished SZ0 from controls (P = 0.0069) while measures from SZ8 were intermediate between the two. 3-D TA of brain MR enables detection of subtle distributed morphological features associated with schizophrenia, determined partly by susceptibility genes. (orig.)

Magnetic resonance imaging textural evaluation of posterior cranial fossa tumors in childhood; Avaliacao textural por ressonancia magnetica dos tumores da fossa posterior em criancas

Energy Technology Data Exchange (ETDEWEB)

Santos, Joelson Alves dos; Costa, Maria Olivia Rodrigues da; Otaduy, Maria Concepcion Garcia; Lacerda, Maria Teresa Carvalho de; Leite, Claudia da Costa [Sao Paulo Univ., SP (Brazil). Faculdade de Medicina. Dept. de Radiologia]. E-mail: joelson_alves@ig.com.br; Matsushita, Hamilton [Sao Paulo Univ., SP (Brazil). Faculdade de Medicina. Dept. de Neurologia

2004-08-01

Objective: To distinguish healthy from pathological tissues in pediatric patients with posterior cranial fossa tumors using calculated textural parameters from magnetic resonance images. Materials And Methods: We evaluated 14 pediatric patients with posterior cranial fossa tumors using the software MaZda to define the texture parameters in selected regions of interest representing healthy and pathological tissues based on T2-weighted magnetic resonance images. Results: There was a statistically significant difference between normal and tumoral tissues as well as between supposedly normal tissues adjacent and distant from the tumoral lesion. Conclusion: Magnetic resonance textural evaluation is an useful tool for determining differences among various tissues, including tissues that appear apparently normal on visual analysis. (author)

Method of depositing an electrically conductive oxide film on a textured metallic substrate and articles formed therefrom

Science.gov (United States)

Christen, David K.; He, Qing

2001-01-01

The present invention provides a biaxially textured laminate article having a polycrystalline biaxially textured metallic substrate with an electrically conductive oxide layer epitaxially deposited thereon and methods for producing same. In one embodiment a biaxially texture Ni substrate has a layer of LaNiO.sub.3 deposited thereon. An initial layer of electrically conductive oxide buffer is epitaxially deposited using a sputtering technique using a sputtering gas which is an inert or forming gas. A subsequent layer of an electrically conductive oxide layer is then epitaxially deposited onto the initial layer using a sputtering gas comprising oxygen. The present invention will enable the formation of biaxially textured devices which include HTS wires and interconnects, large area or long length ferromagnetic and/or ferroelectric memory devices, large area or long length, flexible light emitting semiconductors, ferroelectric tapes, and electrodes.

Quantitative Characterisation of Surface Texture

DEFF Research Database (Denmark)

De Chiffre, Leonardo; Lonardo, P.M.; Trumpold, H.

2000-01-01

This paper reviews the different methods used to give a quantitative characterisation of surface texture. The paper contains a review of conventional 2D as well as 3D roughness parameters, with particular emphasis on recent international standards and developments. It presents new texture...

Image sequence analysis using spatio-temporal texture

International Nuclear Information System (INIS)

Sengupta, S.K.; Clark, G.A.; Barnes, F.L.; Schaich, P.C.

1994-01-01

The authors have developed and coded an algorithm for motion pattern classification based on spatio-temporal texture. The algorithm has been implemented and tested for the detection of wakes in simulated data with a relatively low signal-to-noise ratio (0.7 dB). Using a open-quote hold one out close-quote method, a detection probability of 100% with a 0% false alarm rate has been achieved on the limited number of samples (47 in each category) tested. The actual detection can be displayed in the form of a movie that can effectively show the submarine tracks based on the detected wake locations

Appraisal on Textured Grain Growth and Photoconductivity of ZnO Thin Film SILAR

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Deepu Thomas

2014-01-01

Full Text Available ZnO thin films were prepared by successive ionic layer adsorption reaction (SILAR method. The textured grain growth along c-axis in pure ZnO thin films and doped with Sn was studied. The structural analysis of the thin films was done by X-ray diffraction and surface morphology by scanning electron microscopy. Textured grain growth of the samples was measured by comparing the peak intensities. Textured grain growth and photo current in ZnO thin films were found to be enhanced by doping with Sn. ZnO thin film having good crystallinity with preferential (002 orientation is a semiconductor with photonic properties of potential benefit to biophotonics. From energy dispersive X-ray analysis, it is inferred that oxygen vacancy creation is responsible for the enhanced textured grain growth in ZnO thin films.

Topological patterns of mesh textures in serpentinites

Science.gov (United States)

Miyazawa, M.; Suzuki, A.; Shimizu, H.; Okamoto, A.; Hiraoka, Y.; Obayashi, I.; Tsuji, T.; Ito, T.

2017-12-01

Serpentinization is a hydration process that forms serpentine minerals and magnetite within the oceanic lithosphere. Microfractures crosscut these minerals during the reactions, and the structures look like mesh textures. It has been known that the patterns of microfractures and the system evolutions are affected by the hydration reaction and fluid transport in fractures and within matrices. This study aims at quantifying the topological patterns of the mesh textures and understanding possible conditions of fluid transport and reaction during serpentinization in the oceanic lithosphere. Two-dimensional simulation by the distinct element method (DEM) generates fracture patterns due to serpentinization. The microfracture patterns are evaluated by persistent homology, which measures features of connected components of a topological space and encodes multi-scale topological features in the persistence diagrams. The persistence diagrams of the different mesh textures are evaluated by principal component analysis to bring out the strong patterns of persistence diagrams. This approach help extract feature values of fracture patterns from high-dimensional and complex datasets.

An automated classification system for the differentiation of obstructive lung diseases based on the textural analysis of HRCT images

International Nuclear Information System (INIS)

Park, Seong Hoon; Seo, Joon Beom; Kim, Nam Kug; Lee, Young Kyung; Kim, Song Soo; Chae, Eun Jin; Lee, June Goo

2007-01-01

To develop an automated classification system for the differentiation of obstructive lung diseases based on the textural analysis of HRCT images, and to evaluate the accuracy and usefulness of the system. For textural analysis, histogram features, gradient features, run length encoding, and a co-occurrence matrix were employed. A Bayesian classifier was used for automated classification. The images (image number n = 256) were selected from the HRCT images obtained from 17 healthy subjects (n = 67), 26 patients with bronchiolitis obliterans (n = 70), 28 patients with mild centrilobular emphysema (n = 65), and 21 patients with panlobular emphysema or severe centrilobular emphysema (n = 63). An five-fold cross-validation method was used to assess the performance of the system. Class-specific sensitivities were analyzed and the overall accuracy of the system was assessed with kappa statistics. The sensitivity of the system for each class was as follows: normal lung 84.9%, bronchiolitis obliterans 83.8%, mild centrilobular emphysema 77.0%, and panlobular emphysema or severe centrilobular emphysema 95.8%. The overall performance for differentiating each disease and the normal lung was satisfactory with a kappa value of 0.779. An automated classification system for the differentiation between obstructive lung diseases based on the textural analysis of HRCT images was developed. The proposed system discriminates well between the various obstructive lung diseases and the normal lung

Soil texture and climatc conditions for biocrust growth limitation: a meta analysis

Science.gov (United States)

Fischer, Thomas; Subbotina, Mariia

2015-04-01

Along with afforestation, attempts have been made to combat desertification by managing soil crusts, and is has been reported that recovery rates of biocrusts are dependent on many factors, including the type, severity, and extent of disturbance; structure of the vascular plant community; conditions of adjoining substrates; availability of inoculation material; and climate during and after disturbance (Belnap & Eldridge 2001). Because biological soil crusts are known to be more stable on and to prefer fine substrates (Belnap 2001), the question arises as to how successful crust management practices can be applied to coarser soil. In previous studies we observed similar crust biomasses on finer soils under arid and on coarser soils under temperate conditions. We hypothesized that the higher water holding capacity of finer substrates would favor crust development, and that the amount of silt and clay in the substrate that is required for enhanced crust development would vary with changes in climatic conditions. In a global meta study, climatic and soil texture threshold values promoting BSC growth were derived. While examining literature sources, it became evident that the amount of studies to be incorporated into this meta analysis was reversely related to the amount of common environmental parameters they share. We selected annual mean precipitaion, mean temperature and the amount of silt and clay as driving variables for crust growth. Response variable was the "relative crust biomass", which was computed per literature source as the ratio between each individual crust biomass value of the given study to the study maximum value reported. We distinguished lichen, green algal, cyanobacterial and moss crusts. To quantify threshold conditions at which crust biomass responded to differences in texture and climate, we (I) determined correlations between bioclimatic variables, (II) calculated linear models to determine the effect of typical climatic variables with soil

Towards true 3D textural analysis; using your crystal mush wisely.

Science.gov (United States)

Jerram, D. A.; Morgan, D. J.; Pankhurst, M. J.

2014-12-01

The crystal cargo that is found in volcanic and plutonic rocks contains a wealth of information about magmatic mush processes, crystallisation history, crystal entrainment and recycling. Phenocryst populations predominantly record episodes of growth/nucleation and bulk geochemical changes within an evolving crystal-melt body. Ante- and xeno-crysts provide useful clues to the nature of mush interaction with wall rock and with principal magma(s). Furthermore, crystal evolutions (core to rim) record pathways through pressure, temperature and compositional space. These can often illustrate complex recycling within systems, describing the plumbing architecture. Understanding this architecture underpins our knowledge of how igneous systems can interact with the crust, grow, freeze, re-mobilise and prime for eruption. Initially, 2D studies produced corrected 3D crystal size distributions to help provide information about nucleation and residence times. It immediately became clear that crystal shape is an important factor in determining the confidence placed upon 3D reconstructions of 2D data. Additionally studies utilised serial sections of medium- to coarse-grain-size populations which allowed 3D reconstruction using modelling software to be improved, since size and shape etc. can be directly constrained. Finally the advent of textural studies using X-ray tomography has revolutionised the way in which we can inspect the crystal cargo in mushy systems, allowing us to image in great detail crystal packing arrangements, 3D CSDs, shapes and orientations etc. The latest most innovative studies use X-ray micro-computed tomography to rapidly characterise chemical populations within the crystal cargo, adding a further dimension to this approach, and implies the ability to untangle magmatic chemical components to better understand their individual and combined evolution. In this contribution key examples of the different types of textural analysis techniques in 2D and 3D

Fusion of geometric and texture features for finger knuckle surface recognition

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K. Usha

2016-03-01

Full Text Available Hand-based biometrics plays a significant role in establishing security for real-time environments involving human interaction and is found to be more successful in terms of high speed and accuracy. This paper investigates on an integrated approach for personal authentication using Finger Back Knuckle Surface (FBKS based on two methodologies viz., Angular Geometric Analysis based Feature Extraction Method (AGFEM and Contourlet Transform based Feature Extraction Method (CTFEM. Based on these methods, this personal authentication system simultaneously extracts shape oriented feature information and textural pattern information of FBKS for authenticating an individual. Furthermore, the proposed geometric and textural analysis methods extract feature information from both proximal phalanx and distal phalanx knuckle regions (FBKS, while the existing works of the literature concentrate only on the features of proximal phalanx knuckle region. The finger joint region found nearer to the tip of the finger is called distal phalanx region of FBKS, which is a unique feature and has greater potentiality toward identification. Extensive experiments conducted using newly created database with 5400 FBKS images and the obtained results infer that the integration of shape oriented features with texture feature information yields excellent accuracy rate of 99.12% with lowest equal error rate of 1.04%.

Soil Texture Aanalysis by Laser Diffraction – Standardisation Needed

DEFF Research Database (Denmark)

Callesen, Ingeborg; Palviainen, Marjo; Kjoenaas, O. Janne

2017-01-01

sedimentation and sieving methods have been well-defined. From literature and a mini-survey, we know already that laser diffraction is a commonly used analytical method for soil PSD determination in scientific environmental studies that involve soils. A body of literature has documented that colloid......-sized fraction results obtained by laser diffraction analysis of fine-textured soil samples are not comparable to those obtained with sedimentation and sieving methods, when translating to the traditional particle size limits clay, silt and sand. Also, operating procedures for pretreatment of soil samples...... content. We conclude that PSD’s obtained by the laser diffraction method are repeatable and mostly reproducible given standardised pretreatment. Translation to texture class using traditional separates does not work well, and more work and new PTF’s for soils are needed that can translate a laser...

Rapidly 3D Texture Reconstruction Based on Oblique Photography

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ZHANG Chunsen

2015-07-01

Full Text Available This paper proposes a city texture fast reconstruction method based on aerial tilt image for reconstruction of three-dimensional city model. Based on the photogrammetry and computer vision theory and using the city building digital surface model obtained by prior treatment, through collinear equation calculation geometric projection of object and image space, to obtain the three-dimensional information and texture information of the structure and through certain the optimal algorithm selecting the optimal texture on the surface of the object, realize automatic extraction of the building side texture and occlusion handling of the dense building texture. The real image texture reconstruction results show that: the method to the 3D city model texture reconstruction has the characteristics of high degree of automation, vivid effect and low cost and provides a means of effective implementation for rapid and widespread real texture rapid reconstruction of city 3D model.

SU-C-201-04: Quantification of Perfusion Heterogeneity Based On Texture Analysis for Fully Automatic Detection of Ischemic Deficits From Myocardial Perfusion Imaging

International Nuclear Information System (INIS)

Fang, Y; Huang, H; Su, T

2015-01-01

Purpose: Texture-based quantification of image heterogeneity has been a popular topic for imaging studies in recent years. As previous studies mainly focus on oncological applications, we report our recent efforts of applying such techniques on cardiac perfusion imaging. A fully automated procedure has been developed to perform texture analysis for measuring the image heterogeneity. Clinical data were used to evaluate the preliminary performance of such methods. Methods: Myocardial perfusion images of Thallium-201 scans were collected from 293 patients with suspected coronary artery disease. Each subject underwent a Tl-201 scan and a percutaneous coronary intervention (PCI) within three months. The PCI Result was used as the gold standard of coronary ischemia of more than 70% stenosis. Each Tl-201 scan was spatially normalized to an image template for fully automatic segmentation of the LV. The segmented voxel intensities were then carried into the texture analysis with our open-source software Chang Gung Image Texture Analysis toolbox (CGITA). To evaluate the clinical performance of the image heterogeneity for detecting the coronary stenosis, receiver operating characteristic (ROC) analysis was used to compute the overall accuracy, sensitivity and specificity as well as the area under curve (AUC). Those indices were compared to those obtained from the commercially available semi-automatic software QPS. Results: With the fully automatic procedure to quantify heterogeneity from Tl-201 scans, we were able to achieve a good discrimination with good accuracy (74%), sensitivity (73%), specificity (77%) and AUC of 0.82. Such performance is similar to those obtained from the semi-automatic QPS software that gives a sensitivity of 71% and specificity of 77%. Conclusion: Based on fully automatic procedures of data processing, our preliminary data indicate that the image heterogeneity of myocardial perfusion imaging can provide useful information for automatic determination

Effect of surface texturing on friction properties of WC/Co cemented carbide

International Nuclear Information System (INIS)

Wu, Ze; Deng, Jianxin; Xing, Youqiang; Cheng, Hongwei; Zhao, Jun

2012-01-01

Highlights: ► Tribological properties of surface textured WC/Co cemented carbide were studied. ► Textured surfaces have better performance of antifriction and antiwear. ► Area density of textures has significant effect on tribological performance. -- Abstract: An experimental study was carried out to investigate the tribological properties of different surface textured WC/Co cemented carbide. The influence of applied load, sliding speed and area density of textures on frictional performance of surface textured patterns was investigated by Taguchi method. Results show that the textured surfaces filled with molybdenum disulfide solid lubricants can reduce the average friction coefficient, wear rates of Ti–6Al–4V alloy balls and adhesion of Ti–6Al–4V alloy materials on the worn track of cemented carbide compared with un-textured ones. Variance analysis of the experimental data indicates that the area density of textures plays major contribution of both average friction coefficient and wear rate of Ti–6Al–4V alloy balls. Higher area density of textures is beneficial to improve tribological performance of the cemented carbide samples. Sliding speed seems to have no effect on the tribological performance of textured surfaces within the reliability interval of 90%. Applied load has effect on both average friction coefficient and wear rate of Ti–6Al–4V alloy balls at the reliability interval of 95%.

Textured ZnO thin films by RF magnetron sputtering

CERN Document Server

Ginting, M; Kang, K H; Kim, S K; Yoon, K H; Park, I J; Song, J S

1999-01-01

Textured thin films ZnO has been successfully grown by rf magnetron sputtering method using a special technique of introducing a small amount of water and methanol on the deposition chamber. The grain size of the textured surface is highly dependent on the argon pressure during the deposition. The pressure in this experiment was varied from 50 mTorr down to 5 mTorr and the highest grain size of the film is obtained at 5 mTorr. The total transmittance of the films are more than 85% in the wavelength of 400 to 800 nm, and haze ratio of about 14% is obtained at 400 nm wavelength. Beside the textured surface, these films also have very low resistivity, which is lower than 1.4x10 sup - sup 3 OMEGA centre dot cm. X-ray analysis shows that the films with textured surface have four diffraction peaks on the direction of (110), (002), (101) and (112), while the non-textured films have only (110) and (002) peaks. Due to the excellent characteristics of this film, it will make the film very good TCO alternatives for the ...

Efficient rolling texture predictions and texture-sensitive thermomechanical properties of α-uranium foils

Science.gov (United States)

Steiner, Matthew A.; Klein, Robert W.; Calhoun, Christopher A.; Knezevic, Marko; Garlea, Elena; Agnew, Sean R.

2017-11-01

Finite element (FE) analysis was used to simulate the strain history of an α-uranium foil during cold straight-rolling, with the sheet modeled as an isotropic elastoplastic continuum. The resulting strain history was then used as input for a viscoplastic self-consistent (VPSC) polycrystal plasticity model to simulate crystallographic texture evolution. Mid-plane textures predicted via the combined FE→VPSC approach show alignment of the (010) poles along the rolling direction (RD), and the (001) poles along the normal direction (ND) with a symmetric splitting along RD. The surface texture is similar to that of the mid-plane, but with a shear-induced asymmetry that favors one of the RD split features of the (001) pole figure. Both the mid-plane and surface textures predicted by the FE→VPSC approach agree with published experimental results for cold straight-rolled α-uranium plates, as well as predictions made by a more computationally intensive full-field crystal plasticity based finite element model. α-uranium foils produced by cold-rolling must typically undergo a recrystallization anneal to restore ductility prior to their final application, resulting in significant texture evolution from the cold-rolled plate deformation texture. Using the texture measured from a foil in the final recrystallized state, coefficients of thermal expansion and the elastic stiffness tensors were calculated using a thermo-elastic self-consistent model, and the anisotropic yield loci and flow curves along the RD, TD, and ND were predicted using the VPSC code.

WE-E-17A-05: Complementary Prognostic Value of CT and 18F-FDG PET Non-Small Cell Lung Cancer Tumor Heterogeneity Features Quantified Through Texture Analysis

Energy Technology Data Exchange (ETDEWEB)

Desseroit, M; Cheze Le Rest, C; Tixier, F [CHU Poitiers Poitiers (France); INSERM LaTIM UMR 1101, Brest (France); Majdoub, M; Visvikis, D; Hatt, M [INSERM LaTIM UMR 1101, Brest (France); Guillevin, R; Perdrisot, R [CHU Poitiers Poitiers (France)

2014-06-15

Purpose: Previous studies have shown that CT or 18F-FDG PET intratumor heterogeneity features computed using texture analysis may have prognostic value in Non-Small Cell Lung Cancer (NSCLC), but have been mostly investigated separately. The purpose of this study was to evaluate the potential added value with respect to prognosis regarding the combination of non-enhanced CT and 18F-FDG PET heterogeneity textural features on primary NSCLC tumors. Methods: One hundred patients with non-metastatic NSCLC (stage I–III), treated with surgery and/or (chemo)radiotherapy, that underwent staging 18F-FDG PET/CT images, were retrospectively included. Morphological tumor volumes were semi-automatically delineated on non-enhanced CT using 3D SlicerTM. Metabolically active tumor volumes (MATV) were automatically delineated on PET using the Fuzzy Locally Adaptive Bayesian (FLAB) method. Intratumoral tissue density and FDG uptake heterogeneities were quantified using texture parameters calculated from co-occurrence, difference, and run-length matrices. In addition to these textural features, first order histogram-derived metrics were computed on the whole morphological CT tumor volume, as well as on sub-volumes corresponding to fine, medium or coarse textures determined through various levels of LoG-filtering. Association with survival regarding all extracted features was assessed using Cox regression for both univariate and multivariate analysis. Results: Several PET and CT heterogeneity features were prognostic factors of overall survival in the univariate analysis. CT histogram-derived kurtosis and uniformity, as well as Low Grey-level High Run Emphasis (LGHRE), and PET local entropy were independent prognostic factors. Combined with stage and MATV, they led to a powerful prognostic model (p<0.0001), with median survival of 49 vs. 12.6 months and a hazard ratio of 3.5. Conclusion: Intratumoral heterogeneity quantified through textural features extracted from both CT and FDG PET

An Adaptive Method For Texture Characterization In Medical Images Implemented on a Parallel Virtual Machine

Directory of Open Access Journals (Sweden)

Socrates A. Mylonas

2003-06-01

Full Text Available This paper describes the application of a new texture characterization algorithm for the segmentation of medical ultrasound images. The morphology of these images poses significant problems for the application of traditional image processing techniques and their analysis has been the subject of research for several years. The basis of the algorithm is an optimum signal modelling algorithm (Least Mean Squares-based, which estimates a set of parameters from small image regions. The algorithm has been converted to a structure suitable for implementation on a Parallel Virtual Machine (PVM consisting of a Network of Workstations (NoW, to improve processing speed. Tests were initially carried out on standard textured images. This paper describes preliminary results of the application of the algorithm in texture discrimination and segmentation of medical ultrasound images. The images examined are primarily used in the diagnosis of carotid plaques, which are linked to the risk of stroke.

Mineralogical and textural characteristics of Kakul (Hazara) phosphate rock, NWFP, Pakistan

International Nuclear Information System (INIS)

Mehmood, R.; Bhatti, M.A.; Kazmi, K.R.; Mehmood, A.; Sheikh, S.T.; Aleem Shah, S.A.

2010-01-01

Various types of minerals, present in phosphate rock of Hazara area of Khyber Pukhtoonkhwa Province of Pakistan, were identified and their concentration was determined using a suitable method. The characteristics of the rock were defined by petrography, X-ray diffraction, and chemical analysis and the textural characteristics such as grain size, grain shape and their arrangement in the rock body were also investigated. The degree of liberation of phosphate-bearing mineral was studied by the particle-counting method. Mineralogical and textural observations indicated that fine-grained rock may be suitable for beneficiation by the froth flotation separation technique. (author)

An Analysis of the Max-Min Texture Measure.

Science.gov (United States)

1982-01-01

PANC 33 D2 Confusion Matrices for Scene A, IR 34 D3 Confusion Matrices for Scene B, PANC 35 D4 Confusion Matrices for Scene B, IR 36 D5 Confusion...Matrices for Scene C, PANC 37 D6 Confusion Matrices for Scene C, IR 38 D7 Confusion Matrices for Scene E, PANC 39 D8 Confusion Matrices for Scene E, IR 40...D9 Confusion Matrices for Scene H, PANC 41 DIO Confusion Matrices for Scene H, JR 42 3 .D 10CnuinMtie o cn ,IR4 AN ANALYSIS OF THE MAX-MIN TEXTURE

Effect of zooming on texture features of ultrasonic images

Directory of Open Access Journals (Sweden)

Kyriacou Efthyvoulos

2006-01-01

Full Text Available Abstract Background Unstable carotid plaques on subjective, visual, assessment using B-mode ultrasound scanning appear as echolucent and heterogeneous. Although previous studies on computer assisted plaque characterisation have standardised B-mode images for brightness, improving the objective assessment of echolucency, little progress has been made towards standardisation of texture analysis methods, which assess plaque heterogeneity. The aim of the present study was to investigate the influence of image zooming during ultrasound scanning on textural features and to test whether or not resolution standardisation decreases the variability introduced. Methods Eighteen still B-mode images of carotid plaques were zoomed during carotid scanning (zoom factor 1.3 and both images were transferred to a PC and normalised. Using bilinear and bicubic interpolation, the original images were interpolated in a process of simulating off-line zoom using the same interpolation factor. With the aid of the colour-coded image, carotid plaques of the original, zoomed and two resampled images for each case were outlined and histogram, first order and second order statistics were subsequently calculated. Results Most second order statistics (21/25, 84% were significantly (p Conclusion Texture analysis of ultrasonic plaques should be performed under standardised resolution settings; otherwise a resolution normalisation algorithm should be applied.

Prediction of the therapeutic response after FOLFOX and FOLFIRI treatment for patients with liver metastasis from colorectal cancer using computerized CT texture analysis

Energy Technology Data Exchange (ETDEWEB)

Ahn, Su Joa, E-mail: joa0827@gmail.com [Department of Radiology, Seoul National University Hospital, Seoul (Korea, Republic of); Kim, Jung Hoon, E-mail: jhkim2008@gmail.com [Department of Radiology, Seoul National University Hospital, Seoul (Korea, Republic of); Institute of Radiation Medicine, Seoul National University College of Medicine, Seoul (Korea, Republic of); Park, Sang Joon, E-mail: lunao78@naver.com [Department of Radiology, Seoul National University Hospital, Seoul (Korea, Republic of); Cancer Research Institute, Seoul National University, Seoul (Korea, Republic of); Han, Joon Koo, E-mail: hanjk@snu.ac.kr [Department of Radiology, Seoul National University Hospital, Seoul (Korea, Republic of); Institute of Radiation Medicine, Seoul National University College of Medicine, Seoul (Korea, Republic of)

2016-10-15

Purpose: To determine whether baseline CT texture analysis of hepatic metastasis from colorectal cancer (CRC) is predictive of therapeutic response after cytotoxic chemotherapy. Materials and methods: 235 patients with liver metastasis from CRC who underwent CT and cytotoxic chemotherapy using FOLFOX and FOLFIRI were divided into derivation cohort (n = 145) and validation cohort (n = 90). The CT texture of the hepatic metastasis was quantified using baseline CT. We analyzed the independent predictor for the response from derivation cohort and validated it using validation cohort. We also compared texture features between included four CT scanners. Results: 89 responding and 146 non-responding patients were evaluated. In the derivation cohort, lower skewness (OR, 6.739) in 2D, higher mean attenuation (OR, 2.587), and narrower standard deviation (SD) (OR, 3.163) in 3D were independently associated with response to chemotherapy. However, only lower skewness (P=0.213) on 2D and narrower SD on 3D analysis (P=0.097) did not show a significant difference on either CT scanner. When applied to the validation set, the lower skewness on 2D (AUC = 0.797) and narrower SD on 3D (AUC = 0.785) showed good performance. Conclusion: CT texture analysis is useful for prediction of therapeutic response after cytotoxic chemotherapy in patients with liver metastasis from colorectal cancer.

Assessing breast cancer masking risk in full field digital mammography with automated texture analysis

DEFF Research Database (Denmark)

Kallenberg, Michiel Gijsbertus J; Lillholm, Martin; Diao, Pengfei

2015-01-01

Purpose: The goal of this work is to develop a method to assess the risk of breast cancer masking, based on image characteristics beyond breast density. Method: From the Dutch breast cancer screening program we collected 285 screen detected cancers, and 109 cancers that were screen negative...... and subsequently appeared as interval cancers. To obtain mammograms without cancerous tissue, we took the contralateral mammograms. We developed a novel machine learning based method called convolutional sparse autoencoder to characterize mammographic texture. The method was trained and tested on raw mammograms...... to determine cancer detection status in a five-fold cross validation. To assess the interaction of the texture scores with breast density, Volpara Density Grade was determined for each image. Results: We grouped women into low (VDG 1/2) versus high (VDG 3/4) dense, and low (Quartile 1/2) versus high (Q 3...

Aboveground biomass mapping of African forest mosaics using canopy texture analysis: toward a regional approach.

Science.gov (United States)

Bastin, Jean-François; Barbier, Nicolas; Couteron, Pierre; Adams, Benoît; Shapiro, Aurélie; Bogaert, Jan; De Cannière, Charles

In the context of the reduction of greenhouse gas emissions caused by deforestation and forest degradation (the REDD+ program), optical very high resolution (VHR) satellite images provide an opportunity to characterize forest canopy structure and to quantify aboveground biomass (AGB) at less expense than methods based on airborne remote sensing data. Among the methods for processing these VHR images, Fourier textural ordination (FOTO) presents a good method to detect forest canopy structural heterogeneity and therefore to predict AGB variations. Notably, the method does not saturate at intermediate AGB values as do pixelwise processing of available space borne optical and radar signals. However, a regional-scale application requires overcoming two difficulties: (1) instrumental effects due to variations in sun–scene–sensor geometry or sensor-specific responses that preclude the use of wide arrays of images acquired under heterogeneous conditions and (2) forest structural diversity including monodominant or open canopy forests, which are of particular importance in Central Africa. In this study, we demonstrate the feasibility of a rigorous regional study of canopy texture by harmonizing FOTO indices of images acquired from two different sensors (Geoeye-1 and QuickBird-2) and different sun–scene–sensor geometries and by calibrating a piecewise biomass inversion model using 26 inventory plots (1 ha) sampled across very heterogeneous forest types. A good agreement was found between observed and predicted AGB (residual standard error [RSE] = 15%; R2 = 0.85; P biomass map (100-m pixels) was produced for a 400-km2 area, and predictions obtained from both imagery sources were consistent with each other (r = 0.86; slope = 1.03; intercept = 12.01 Mg/ha). These results highlight the horizontal structure of forest canopy as a powerful descriptor of the entire forest stand structure and heterogeneity. In particular, we show that quantitative metrics resulting from such

Texture-based classification of different gastric tumors at contrast-enhanced CT

Energy Technology Data Exchange (ETDEWEB)

Ba-Ssalamah, Ahmed, E-mail: ahmed.ba-ssalamah@meduniwien.ac.at [Department of Radiology, Medical University of Vienna (Austria); Muin, Dina; Schernthaner, Ruediger; Kulinna-Cosentini, Christiana; Bastati, Nina [Department of Radiology, Medical University of Vienna (Austria); Stift, Judith [Department of Pathology, Medical University of Vienna (Austria); Gore, Richard [Department of Radiology, University of Chicago Pritzker School of Medicine, Chicago, IL (United States); Mayerhoefer, Marius E. [Department of Radiology, Medical University of Vienna (Austria)

2013-10-01

Purpose: To determine the feasibility of texture analysis for the classification of gastric adenocarcinoma, lymphoma, and gastrointestinal stromal tumors on contrast-enhanced hydrodynamic-MDCT images. Materials and methods: The arterial phase scans of 47 patients with adenocarcinoma (AC) and a histologic tumor grade of [AC-G1, n = 4, G1, n = 4; AC-G2, n = 7; AC-G3, n = 16]; GIST, n = 15; and lymphoma, n = 5, and the venous phase scans of 48 patients with AC-G1, n = 3; AC-G2, n = 6; AC-G3, n = 14; GIST, n = 17; lymphoma, n = 8, were retrospectively reviewed. Based on regions of interest, texture analysis was performed, and features derived from the gray-level histogram, run-length and co-occurrence matrix, absolute gradient, autoregressive model, and wavelet transform were calculated. Fisher coefficients, probability of classification error, average correlation coefficients, and mutual information coefficients were used to create combinations of texture features that were optimized for tumor differentiation. Linear discriminant analysis in combination with a k-nearest neighbor classifier was used for tumor classification. Results: On arterial-phase scans, texture-based lesion classification was highly successful in differentiating between AC and lymphoma, and GIST and lymphoma, with misclassification rates of 3.1% and 0%, respectively. On venous-phase scans, texture-based classification was slightly less successful for AC vs. lymphoma (9.7% misclassification) and GIST vs. lymphoma (8% misclassification), but enabled the differentiation between AC and GIST (10% misclassification), and between the different grades of AC (4.4% misclassification). No texture feature combination was able to adequately distinguish between all three tumor types. Conclusion: Classification of different gastric tumors based on textural information may aid radiologists in establishing the correct diagnosis, at least in cases where the differential diagnosis can be narrowed down to two

Texture-based classification of different gastric tumors at contrast-enhanced CT

International Nuclear Information System (INIS)

Ba-Ssalamah, Ahmed; Muin, Dina; Schernthaner, Ruediger; Kulinna-Cosentini, Christiana; Bastati, Nina; Stift, Judith; Gore, Richard; Mayerhoefer, Marius E.

2013-01-01

Purpose: To determine the feasibility of texture analysis for the classification of gastric adenocarcinoma, lymphoma, and gastrointestinal stromal tumors on contrast-enhanced hydrodynamic-MDCT images. Materials and methods: The arterial phase scans of 47 patients with adenocarcinoma (AC) and a histologic tumor grade of [AC-G1, n = 4, G1, n = 4; AC-G2, n = 7; AC-G3, n = 16]; GIST, n = 15; and lymphoma, n = 5, and the venous phase scans of 48 patients with AC-G1, n = 3; AC-G2, n = 6; AC-G3, n = 14; GIST, n = 17; lymphoma, n = 8, were retrospectively reviewed. Based on regions of interest, texture analysis was performed, and features derived from the gray-level histogram, run-length and co-occurrence matrix, absolute gradient, autoregressive model, and wavelet transform were calculated. Fisher coefficients, probability of classification error, average correlation coefficients, and mutual information coefficients were used to create combinations of texture features that were optimized for tumor differentiation. Linear discriminant analysis in combination with a k-nearest neighbor classifier was used for tumor classification. Results: On arterial-phase scans, texture-based lesion classification was highly successful in differentiating between AC and lymphoma, and GIST and lymphoma, with misclassification rates of 3.1% and 0%, respectively. On venous-phase scans, texture-based classification was slightly less successful for AC vs. lymphoma (9.7% misclassification) and GIST vs. lymphoma (8% misclassification), but enabled the differentiation between AC and GIST (10% misclassification), and between the different grades of AC (4.4% misclassification). No texture feature combination was able to adequately distinguish between all three tumor types. Conclusion: Classification of different gastric tumors based on textural information may aid radiologists in establishing the correct diagnosis, at least in cases where the differential diagnosis can be narrowed down to two

The distribution function of crystalline orientation's usefulness in crystallographic texture analysis

International Nuclear Information System (INIS)

Hermida, J.D.; Pochettino, A.A.

1982-01-01

The theoretical fundaments of the Distribution Function of Crystalline Orientations (DFCO) are described and this method is compared with the usual description of the crystallographic texture by direct pole figures. Such function is applied to the study of a Zry-4 sample obtained from a tube belonging to a CANDU type fuel element. The DFCO is obtained from the pole figures (0002), (101-bar0) and (101-bar1). The results show the existence of six fundamental components of texture, which are enunciated below, in decreasing order of importance: (2-bar115) ; (3-bar128) ; (1-bar013) ; (2-bar114) ; (0001) ; (0001) . A much more complete view of the crystals' orientation state of such sample can be obtained by analyzing the weight and the distribution of the different components. (M.E.L.) [es

BREAD CRUMBS TEXTURE OF SPELT

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Joanna Korczyk – Szabó

2014-02-01

Full Text Available Texture analysis is an objective physical examination of baked products and gives direct information on the product quality, oppositely to dough rheology tests what inform on the baking suitability of the flour, as raw material. Evaluation of the mechanical properties of bread crumb is important not only for quality assurance in the bakeries, but also for assessing the effects of changes in dough ingredients and processing condition and also for describing the changes in bread crumb during storage. Crumb cellular structure is an important quality criterion used in commercial baking and research laboratories to judge bread quality alongside taste, crumb colour and crumb physical texture. In the framework of our research during the years 2010 – 2011 were analyzed selected indicators of bread crumb for texture quality of three Triticum spelta L. cultivars – Altgold, Rubiota and Ostro grown in an ecological system. The bread texture quality was evaluated on texture analyzer TA.XT Plus (Stable Micro Systems, Surrey, UK, following the AACC (74-09 standard and expressed as crumb firmness (N, stiffness (N.mm-1 and relative elasticity (%. Our research proved that all selected indicators were significantly influenced by the year of growing and variety. The most soft bread was achieved in Rubiota, whereas bread crumb samples from Altgold and Ostro were the most firm and stiff. Correlation analysis showed strong negative correlation between relative elasticity and bread crumb firmness as well as bread stiffness (-0.65++, -0.66++. The spelt wheat bread crumb texture need further investigation as it can be a reliable quality parameter.

A universal meteorological method to identify potential risk of wind erosion on heavy-textured soils

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Středová Hana

2015-06-01

Full Text Available The climate of Central Europe, mainly winter seasons with no snow cover at lower altitudes and a spring drought as well, might cause erosion events on heavy-textured soils. The aim of this paper is to define a universal method to identify the potential risk of wind erosion on heavy-textured soils. The categorization of potential wind erosion risk due to meteorological conditions is based on: (i an evaluation of the number of freeze-thaw episodes forming bare soil surfaces during the cold period of year; and (ii, an evaluation of the number of days with wet soil surfaces during the cold period of year. In the period 2001–2012 (from November to March, episodes with temperature changes from positive to negative and vice versa (thaw-freeze and freeze-thaw cycles and the effects of wet soil surfaces in connection with aggregate disintegration, are identified. The data are spatially interpolated by GIS tools for areas in the Czech Republic with heavy-textured soils. Blending critical categories is used to locate potential risks. The level of risk is divided into six classes. Those areas identified as potentially most vulnerable are the same localities where the highest number of erosive episodes on heavy-textured soils was documented.

Minimizing inter-microscope variability in dental microwear texture analysis

Science.gov (United States)

Arman, Samuel D.; Ungar, Peter S.; Brown, Christopher A.; DeSantis, Larisa R. G.; Schmidt, Christopher; Prideaux, Gavin J.

2016-06-01

A common approach to dental microwear texture analysis (DMTA) uses confocal profilometry in concert with scale-sensitive fractal analysis to help understand the diets of extinct mammals. One of the main benefits of DMTA over other methods is the repeatable, objective manner of data collection. This repeatability, however, is threatened by variation in results of DMTA of the same dental surfaces yielded by different microscopes. Here we compare DMTA data of five species of kangaroos measured on seven profilers of varying specifications. Comparison between microscopes confirms that inter-microscope differences are present, but we show that deployment of a number of automated treatments to remove measurement noise can help minimize inter-microscope differences. Applying these same treatments to a published hominin DMTA dataset shows that they alter some significant differences between dietary groups. Minimising microscope variability while maintaining interspecific dietary differences requires then that these factors are balanced in determining appropriate treatments. The process outlined here offers a solution for allowing comparison of data between microscopes, which is essential for ongoing DMTA research. In addition, the process undertaken, including considerations of other elements of DMTA protocols also promises to streamline methodology, remove measurement noise and in doing so, optimize recovery of a reliable dietary signature.

Femtosecond laser surface texturing of titanium as a method to reduce the adhesion of Staphylococcus aureus and biofilm formation

Energy Technology Data Exchange (ETDEWEB)

Cunha, Alexandre [Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Bordeaux University, Institute of Chemistry & Biology of Membranes & Nanoobjects (CBMN UMR 5248, CNRS), European Institute of Chemistry and Biology, 2 Rue Robert Escarpit, 33607 Pessac (France); Elie, Anne-Marie [Bordeaux University, CBMN UMR 5248, CNRS, Bordeaux Science Agro, 1 Rue du G. de Gaulle, 33170 Gradignan (France); Plawinski, Laurent [Bordeaux University, Institute of Chemistry & Biology of Membranes & Nanoobjects (CBMN UMR 5248, CNRS), European Institute of Chemistry and Biology, 2 Rue Robert Escarpit, 33607 Pessac (France); Serro, Ana Paula [Instituto Superior Técnico, Universidade de Lisboa, CQE-Centro de Química Estrutural, Av. Rovisco Pais 1, 1049-001 Lisbon (Portugal); Botelho do Rego, Ana Maria [Instituto Superior Técnico, Universidade de Lisboa, CQFM-Centro de Química-Física Molecular and Institute of Nanoscience and Nanotechnology - IN, Av. Rovisco Pais 1, 1049-001 Lisbon (Portugal); Almeida, Amélia [Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal); Urdaci, Maria C. [Bordeaux University, CBMN UMR 5248, CNRS, Bordeaux Science Agro, 1 Rue du G. de Gaulle, 33170 Gradignan (France); Durrieu, Marie-Christine [Bordeaux University, Institute of Chemistry & Biology of Membranes & Nanoobjects (CBMN UMR 5248, CNRS), European Institute of Chemistry and Biology, 2 Rue Robert Escarpit, 33607 Pessac (France); Vilar, Rui, E-mail: rui.vilar@tecnico.ulisboa.pt [Instituto Superior Técnico, Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisboa (Portugal)

2016-01-01

Graphical abstract: - Highlights: • The short-term adhesion of Staphylococcus aureus onto femtosecond laser textured surfaces of titanium was investigated. • The laser textured surfaces consist of laser-induced periodic surface structures (LIPSS) and nanopillars. • The laser treatment enhances the hydrophilicity and the surface free energy of the material. • The laser treatment reduces significantly the adhesion of S. aureus and biofilm formation. • Femtosecond laser surface texturing of titanium is a simple and promising method for endowing dental and orthopedic implants with antibacterial properties. - Abstract: The aim of the present work was to investigate the possibility of using femtosecond laser surface texturing as a method to reduce the colonization of Grade 2 Titanium alloy surfaces by Staphylococcus aureus and the subsequent formation of biofilm. The laser treatments were carried out with a Yb:KYW chirped-pulse-regenerative amplification laser system with a central wavelength of 1030 nm and a pulse duration of 500 fs. Two types of surface textures, consisting of laser-induced periodic surface structures (LIPSS) and nanopillars, were produced. The topography, chemical composition and phase constitution of these surfaces were investigated by atomic force microscopy, scanning electron microscopy, X-ray photoelectron spectroscopy, micro-Raman spectroscopy, and X-ray diffraction. Surface wettability was assessed by the sessile drop method using water and diiodomethane as testing liquids. The response of S. aureus put into contact with the laser treated surfaces in controlled conditions was investigated by epifluorescence microscopy and scanning electron microscopy 48 h after cell seeding. The results achieved show that the laser treatment reduces significantly the bacterial adhesion to the surface as well as biofilm formation as compared to a reference polished surfaces and suggest that femtosecond laser texturing is a simple and promising method

Texture and deformation mechanism of yttrium

International Nuclear Information System (INIS)

Adamesku, R.A.; Grebenkin, S.V.; Stepanenko, A.V.

1992-01-01

X-ray pole figure analysis was applied to study texture and deformation mechanism in pure and commercial polycrystalline yttrium on cold working. It was found that in cast yttrium the texture manifected itself weakly enough both for pure and commercial metal. Analysis of the data obtained made it possible to assert that cold deformation of pure yttrium in the initial stage occurred mainly by slip the role of which decreased at strains higher than 36%. The texture of heavily deformed commercial yttrium contained two components, these were an 'ideal' basic orientation and an axial one with the angle of inclination about 20 deg. Twinning mechanism was revealed to be also possible in commercial yttrium

Classification of Textures Using Filter Based Local Feature Extraction

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Bocekci Veysel Gokhan

2016-01-01

Full Text Available In this work local features are used in feature extraction process in image processing for textures. The local binary pattern feature extraction method from textures are introduced. Filtering is also used during the feature extraction process for getting discriminative features. To show the effectiveness of the algorithm before the extraction process, three different noise are added to both train and test images. Wiener filter and median filter are used to remove the noise from images. We evaluate the performance of the method with Naïve Bayesian classifier. We conduct the comparative analysis on benchmark dataset with different filtering and size. Our experiments demonstrate that feature extraction process combine with filtering give promising results on noisy images.

Morphological and textural characterization of functionalized particulate silica xerogels

Science.gov (United States)

de Miranda, Lazaro A.; Mohallem, Nelcy D. S.; de Magalhães, Welington F.

2006-03-01

The functionalization of xerogels for use in chromatography and catalysis was carried out by solubilization of amorphous silica using a soxhlet extractor. Xerogels were prepared by sol-gel method using tetraethoxysilane, TEOS, ethanol, and water in a 1/3/10 molar ratio with HCl and HF as catalysts. The samples were prepared in monolithic form and dried at 70 °C and 550 °C for 1 h each. After functionalization, changes in textural and morphological characteristics of xerogels were investigated by means of nitrogen gas adsorption, positron annihilation lifetime spectroscopy (PALS), and scanning electron microscopy (SEM). As the analysis methods are based on different physical principles, the results are complementary, leading to a good knowledge of the texture of the samples studied.

Morphological and textural characterization of functionalized particulate silica xerogels

International Nuclear Information System (INIS)

Miranda, Lazaro A. de; Mohallem, Nelcy D.S.; Magalhaes, Welington F. de

2006-01-01

The functionalization of xerogels for use in chromatography and catalysis was carried out by solubilization of amorphous silica using a soxhlet extractor. Xerogels were prepared by sol-gel method using tetraethoxysilane, TEOS, ethanol, and water in a 1/3/10 molar ratio with HCl and HF as catalysts. The samples were prepared in monolithic form and dried at 70 deg. C and 550 deg. C for 1 h each. After functionalization, changes in textural and morphological characteristics of xerogels were investigated by means of nitrogen gas adsorption, positron annihilation lifetime spectroscopy (PALS), and scanning electron microscopy (SEM). As the analysis methods are based on different physical principles, the results are complementary, leading to a good knowledge of the texture of the samples studied

Tumor spatial heterogeneity in myxoid-containing soft tissue using texture analysis of diffusion-weighted MRI.

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Hyun Su Kim

Full Text Available The objective of this study was to examine the tumor spatial heterogeneity in myxoid-containing soft-tissue tumors (STTs using texture analysis of diffusion-weighted imaging (DWI. A total of 40 patients with myxoid-containing STTs (23 benign and 17 malignant were included in this study. The region of interest (ROI was manually drawn on the apparent diffusion coefficient (ADC map. For texture analysis, the global (mean, standard deviation, skewness, and kurtosis, regional (intensity variability and size-zone variability, and local features (energy, entropy, correlation, contrast, homogeneity, variance, and maximum probability were extracted from the ADC map. Student's t-test was used to test the difference between group means. Analysis of covariance (ANCOVA was performed with adjustments for age, sex, and tumor volume. The receiver operating characteristic (ROC analysis was performed to compare diagnostic performances. Malignant myxoid-containing STTs had significantly higher kurtosis (P = 0.040, energy (P = 0.034, correlation (P<0.001, and homogeneity (P = 0.003, but significantly lower contrast (P<0.001 and variance (P = 0.001 compared with benign myxoid-containing STTs. Contrast showed the highest area under the curve (AUC = 0.923, P<0.001, sensitivity (94.12%, and specificity (86.96%. Our results reveal the potential utility of texture analysis of ADC maps for differentiating benign and malignant myxoid-containing STTs.

Detection of neovascularization based on fractal and texture analysis with interaction effects in diabetic retinopathy.

Science.gov (United States)

Lee, Jack; Zee, Benny Chung Ying; Li, Qing

2013-01-01

Diabetic retinopathy is a major cause of blindness. Proliferative diabetic retinopathy is a result of severe vascular complication and is visible as neovascularization of the retina. Automatic detection of such new vessels would be useful for the severity grading of diabetic retinopathy, and it is an important part of screening process to identify those who may require immediate treatment for their diabetic retinopathy. We proposed a novel new vessels detection method including statistical texture analysis (STA), high order spectrum analysis (HOS), fractal analysis (FA), and most importantly we have shown that by incorporating their associated interactions the accuracy of new vessels detection can be greatly improved. To assess its performance, the sensitivity, specificity and accuracy (AUC) are obtained. They are 96.3%, 99.1% and 98.5% (99.3%), respectively. It is found that the proposed method can improve the accuracy of new vessels detection significantly over previous methods. The algorithm can be automated and is valuable to detect relatively severe cases of diabetic retinopathy among diabetes patients.

Detection of neovascularization based on fractal and texture analysis with interaction effects in diabetic retinopathy.

Directory of Open Access Journals (Sweden)

Jack Lee

Full Text Available Diabetic retinopathy is a major cause of blindness. Proliferative diabetic retinopathy is a result of severe vascular complication and is visible as neovascularization of the retina. Automatic detection of such new vessels would be useful for the severity grading of diabetic retinopathy, and it is an important part of screening process to identify those who may require immediate treatment for their diabetic retinopathy. We proposed a novel new vessels detection method including statistical texture analysis (STA, high order spectrum analysis (HOS, fractal analysis (FA, and most importantly we have shown that by incorporating their associated interactions the accuracy of new vessels detection can be greatly improved. To assess its performance, the sensitivity, specificity and accuracy (AUC are obtained. They are 96.3%, 99.1% and 98.5% (99.3%, respectively. It is found that the proposed method can improve the accuracy of new vessels detection significantly over previous methods. The algorithm can be automated and is valuable to detect relatively severe cases of diabetic retinopathy among diabetes patients.

SU-E-J-262: Variability in Texture Analysis of Gynecological Tumors in the Context of An 18F-FDG PET Adaptive Protocol

Energy Technology Data Exchange (ETDEWEB)

Nawrocki, J [Duke University Medical Physics Graduate Program, Durham, NC (United States); Chino, J; Das, S; Craciunescu, O [Duke University Medical Center, Durham, NC (United States)

2015-06-15

Purpose: This study examines the effect on texture analysis due to variable reconstruction of PET images in the context of an adaptive FDG PET protocol for node positive gynecologic cancer patients. By measuring variability in texture features from baseline and intra-treatment PET-CT, we can isolate unreliable texture features due to large variation. Methods: A subset of seven patients with node positive gynecological cancers visible on PET was selected for this study. Prescribed dose varied between 45–50.4Gy, with a 55–70Gy boost to the PET positive nodes. A baseline and intratreatment (between 30–36Gy) PET-CT were obtained on a Siemens Biograph mCT. Each clinical PET image set was reconstructed 6 times using a TrueX+TOF algorithm with varying iterations and Gaussian filter. Baseline and intra-treatment primary GTVs were segmented using PET Edge (MIM Software Inc., Cleveland, OH), a semi-automatic gradient-based algorithm, on the clinical PET and transferred to the other reconstructed sets. Using an in-house MATLAB program, four 3D texture matrices describing relationships between voxel intensities in the GTV were generated: co-occurrence, run length, size zone, and neighborhood difference. From these, 39 textural features characterizing texture were calculated in addition to SUV histogram features. The percent variability among parameters was first calculated. Each reconstructed texture feature from baseline and intra-treatment per patient was normalized to the clinical baseline scan and compared using the Wilcoxon signed-rank test in order to isolate variations due to reconstruction parameters. Results: For the baseline scans, 13 texture features showed a mean range greater than 10%. For the intra scans, 28 texture features showed a mean range greater than 10%. Comparing baseline to intra scans, 25 texture features showed p <0.05. Conclusion: Variability due to different reconstruction parameters increased with treatment, however, the majority of texture

SU-E-J-262: Variability in Texture Analysis of Gynecological Tumors in the Context of An 18F-FDG PET Adaptive Protocol

International Nuclear Information System (INIS)

Nawrocki, J; Chino, J; Das, S; Craciunescu, O

2015-01-01

Purpose: This study examines the effect on texture analysis due to variable reconstruction of PET images in the context of an adaptive FDG PET protocol for node positive gynecologic cancer patients. By measuring variability in texture features from baseline and intra-treatment PET-CT, we can isolate unreliable texture features due to large variation. Methods: A subset of seven patients with node positive gynecological cancers visible on PET was selected for this study. Prescribed dose varied between 45–50.4Gy, with a 55–70Gy boost to the PET positive nodes. A baseline and intratreatment (between 30–36Gy) PET-CT were obtained on a Siemens Biograph mCT. Each clinical PET image set was reconstructed 6 times using a TrueX+TOF algorithm with varying iterations and Gaussian filter. Baseline and intra-treatment primary GTVs were segmented using PET Edge (MIM Software Inc., Cleveland, OH), a semi-automatic gradient-based algorithm, on the clinical PET and transferred to the other reconstructed sets. Using an in-house MATLAB program, four 3D texture matrices describing relationships between voxel intensities in the GTV were generated: co-occurrence, run length, size zone, and neighborhood difference. From these, 39 textural features characterizing texture were calculated in addition to SUV histogram features. The percent variability among parameters was first calculated. Each reconstructed texture feature from baseline and intra-treatment per patient was normalized to the clinical baseline scan and compared using the Wilcoxon signed-rank test in order to isolate variations due to reconstruction parameters. Results: For the baseline scans, 13 texture features showed a mean range greater than 10%. For the intra scans, 28 texture features showed a mean range greater than 10%. Comparing baseline to intra scans, 25 texture features showed p <0.05. Conclusion: Variability due to different reconstruction parameters increased with treatment, however, the majority of texture

Cascaded Amplitude Modulations in Sound Texture Perception

DEFF Research Database (Denmark)

McWalter, Richard Ian; Dau, Torsten

2017-01-01

. In this study, we investigated the perception of sound textures that contain rhythmic structure, specifically second-order amplitude modulations that arise from the interaction of different modulation rates, previously described as "beating" in the envelope-frequency domain. We developed an auditory texture...... model that utilizes a cascade of modulation filterbanks that capture the structure of simple rhythmic patterns. The model was examined in a series of psychophysical listening experiments using synthetic sound textures-stimuli generated using time-averaged statistics measured from real-world textures....... In a texture identification task, our results indicated that second-order amplitude modulation sensitivity enhanced recognition. Next, we examined the contribution of the second-order modulation analysis in a preference task, where the proposed auditory texture model was preferred over a range of model...

Experience in determination of the composition and texture of Y-Ba high-Tc superconductors

International Nuclear Information System (INIS)

Shamraj, V.F.; Efimov, Yu.V.; Babarehko, A.A.; Myasnikova, E.A.; Bolokhova, T.A.; Shul'gin, A.I.

1990-01-01

A method for the determination of phase composition and texture of powder and strip samples of Y-Ba HTSC has been developed. Phase analysis was conducted by comparing X-ray patterns of analyzed and model patterns of various phases in the system Y-Ba-Cu-O using literature data on crystal structures of the phases. The texture of rolled strips was studied by the method of plotting direct polar figures using an automate diffractometer. It is shown that combination of standard method of micro X-ray diffraction analysis with the study of oxygen content in HTSC, usign ultralong wave spectroprobe, provides for the determination of the important component and permits to reveal microheterogeneity of the samples

Utilization of Advanced Diagnostic Methods for Texture and Rut Depth Analysis on a Testing Pavement Section

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Slabej Martin

2015-05-01

Full Text Available Qualitative characteristics of pavement in wide range reflects the pavement serviceability, which is a summary of the characteristics of the pavement, providing a fast, smooth, economical and especially safe driving of motor-vehicles. The target factor of pavement serviceability and safety of roads represents the quality of their surface properties. In the framework of research activities performed in the Research Centre founded under the auspices of University of Žilina, individual parameters of pavement serviceability were monitored by pavement surface scanning. This paper describes the creation of a 3D - road surface model and its analysis and evaluation from the viewpoint of two pavement serviceability parameters - the rut depth and texture. Measurements were performed on an experimental pavement section used contemporary in an Accelerated Pavement Testing experiment. The long-term goal is to ascertain functions predicting degradation of these two pavement serviceability parameters.

Textural analysis of pre-therapeutic [18F]-FET-PET and its correlation with tumor grade and patient survival in high-grade gliomas

Energy Technology Data Exchange (ETDEWEB)

Pyka, Thomas; Hiob, Daniela; Wester, Hans-Juergen [Klinikum Rechts der Isar der TU Muenchen, Department of Nuclear Medicine, Munich (Germany); Gempt, Jens; Ringel, Florian; Meyer, Bernhard [Klinikum Rechts der Isar der TU Muenchen, Neurosurgic Department, Munich (Germany); Schlegel, Juergen [Klinikum Rechts der Isar der TU Muenchen, Institute of Pathology and Neuropathology, Munich (Germany); Bette, Stefanie [Klinikum Rechts der Isar der TU Muenchen, Neuroradiologic department, Munich (Germany); Foerster, Stefan [Klinikum Rechts der Isar der TU Muenchen, Department of Nuclear Medicine, Munich (Germany); Klinikum Rechts der Isar der TU Muenchen, TUM Neuroimaging Center (TUM-NIC), Munich (Germany)

2016-01-15

Amino acid positron emission tomography (PET) with [18F]-fluoroethyl-L-tyrosine (FET) is well established in the diagnostic work-up of malignant brain tumors. Analysis of FET-PET data using tumor-to-background ratios (TBR) has been shown to be highly valuable for the detection of viable hypermetabolic brain tumor tissue; however, it has not proven equally useful for tumor grading. Recently, textural features in 18-fluorodeoxyglucose-PET have been proposed as a method to quantify the heterogeneity of glucose metabolism in a variety of tumor entities. Herein we evaluate whether textural FET-PET features are of utility for grading and prognostication in patients with high-grade gliomas. One hundred thirteen patients (70 men, 43 women) with histologically proven high-grade gliomas were included in this retrospective study. All patients received static FET-PET scans prior to first-line therapy. TBR (max and mean), volumetric parameters and textural parameters based on gray-level neighborhood difference matrices were derived from static FET-PET images. Receiver operating characteristic (ROC) and discriminant function analyses were used to assess the value for tumor grading. Kaplan-Meier curves and univariate and multivariate Cox regression were employed for analysis of progression-free and overall survival. All FET-PET textural parameters showed the ability to differentiate between World Health Organization (WHO) grade III and IV tumors (p < 0.001; AUC 0.775). Further improvement in discriminatory power was possible through a combination of texture and metabolic tumor volume, classifying 85 % of tumors correctly (AUC 0.830). TBR and volumetric parameters alone were correlated with tumor grade, but showed lower AUC values (0.644 and 0.710, respectively). Furthermore, a correlation of FET-PET texture but not TBR was shown with patient PFS and OS, proving significant in multivariate analysis as well. Volumetric parameters were predictive for OS, but this correlation did not

A vegetation height classification approach based on texture analysis of a single VHR image

International Nuclear Information System (INIS)

Petrou, Z I; Manakos, I; Stathaki, T; Tarantino, C; Adamo, M; Blonda, P

2014-01-01

Vegetation height is a crucial feature in various applications related to ecological mapping, enhancing the discrimination among different land cover or habitat categories and facilitating a series of environmental tasks, ranging from biodiversity monitoring and assessment to landscape characterization, disaster management and conservation planning. Primary sources of information on vegetation height include in situ measurements and data from active satellite or airborne sensors, which, however, may often be non-affordable or unavailable for certain regions. Alternative approaches on extracting height information from very high resolution (VHR) satellite imagery based on texture analysis, have recently been presented, with promising results. Following the notion that multispectral image bands may often be highly correlated, data transformation and dimensionality reduction techniques are expected to reduce redundant information, and thus, the computational cost of the approaches, without significantly compromising their accuracy. In this paper, dimensionality reduction is performed on a VHR image and textural characteristics are calculated on its reconstructed approximations, to show that their discriminatory capabilities are maintained up to a large degree. Texture analysis is also performed on the projected data to investigate whether the different height categories can be distinguished in a similar way

A Variable Order Fractional Differential-Based Texture Enhancement Algorithm with Application in Medical Imaging.

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Qiang Yu

Full Text Available Texture enhancement is one of the most important techniques in digital image processing and plays an essential role in medical imaging since textures discriminate information. Most image texture enhancement techniques use classical integral order differential mask operators or fractional differential mask operators using fixed fractional order. These masks can produce excessive enhancement of low spatial frequency content, insufficient enhancement of large spatial frequency content, and retention of high spatial frequency noise. To improve upon existing approaches of texture enhancement, we derive an improved Variable Order Fractional Centered Difference (VOFCD scheme which dynamically adjusts the fractional differential order instead of fixing it. The new VOFCD technique is based on the second order Riesz fractional differential operator using a Lagrange 3-point interpolation formula, for both grey scale and colour image enhancement. We then use this method to enhance photographs and a set of medical images related to patients with stroke and Parkinson's disease. The experiments show that our improved fractional differential mask has a higher signal to noise ratio value than the other fractional differential mask operators. Based on the corresponding quantitative analysis we conclude that the new method offers a superior texture enhancement over existing methods.

Texture Analysis of Hydrophobic Polycarbonate and Polydimethylsiloxane Surfaces via Persistent Homology

Directory of Open Access Journals (Sweden)

Ali Nabi Duman

2017-09-01

Full Text Available Due to recent climate change-triggered, regular dust storms in the Middle East, dust mitigation has become the critical issue for solar energy harvesting devices. One of the methods to minimize and prevent dust adhesion and create self-cleaning abilities is to generate hydrophobic characteristics on surfaces. The purpose of this study is to explore the topological features of hydrophobic surfaces. We use non-standard techniques from topological data analysis to extract morphological features from the AFM images. Our method recovers most of the previous qualitative observations in a robust and quantitative way. Persistence diagrams, which is a summary of topological structures, witness quantitatively that the crystallized polycarbonate (PC surface possesses spherulites, voids, and fibrils, and the texture height and spherulite concentration increases with the increased immersion period. The approach also shows that the polydimethylsiloxane (PDMS exactly copied the structures at the PC surface but 80 to 90 percent of the nanofibrils were not copied at PDMS surface. We next extract a feature vector from each persistence diagram to show which experiments hold features with similar variance using principal component analysis (PCA. The K-means clustering algorithm is applied to the matrix of feature vectors to support the PCA result, grouping experiments with similar features.

Enhancement of Stereo Imagery by Artificial Texture Projection Generated Using a LIDAR

Science.gov (United States)

Veitch-Michaelis, Joshua; Muller, Jan-Peter; Walton, David; Storey, Jonathan; Foster, Michael; Crutchley, Benjamin

2016-06-01

Passive stereo imaging is capable of producing dense 3D data, but image matching algorithms generally perform poorly on images with large regions of homogenous texture due to ambiguous match costs. Stereo systems can be augmented with an additional light source that can project some form of unique texture onto surfaces in the scene. Methods include structured light, laser projection through diffractive optical elements, data projectors and laser speckle. Pattern projection using lasers has the advantage of producing images with a high signal to noise ratio. We have investigated the use of a scanning visible-beam LIDAR to simultaneously provide enhanced texture within the scene and to provide additional opportunities for data fusion in unmatched regions. The use of a LIDAR rather than a laser alone allows us to generate highly accurate ground truth data sets by scanning the scene at high resolution. This is necessary for evaluating different pattern projection schemes. Results from LIDAR generated random dots are presented and compared to other texture projection techniques. Finally, we investigate the use of image texture analysis to intelligently project texture where it is required while exploiting the texture available in the ambient light image.

ENHANCEMENT OF STEREO IMAGERY BY ARTIFICIAL TEXTURE PROJECTION GENERATED USING A LIDAR

Directory of Open Access Journals (Sweden)

J. Veitch-Michaelis

2016-06-01

Full Text Available Passive stereo imaging is capable of producing dense 3D data, but image matching algorithms generally perform poorly on images with large regions of homogenous texture due to ambiguous match costs. Stereo systems can be augmented with an additional light source that can project some form of unique texture onto surfaces in the scene. Methods include structured light, laser projection through diffractive optical elements, data projectors and laser speckle. Pattern projection using lasers has the advantage of producing images with a high signal to noise ratio. We have investigated the use of a scanning visible-beam LIDAR to simultaneously provide enhanced texture within the scene and to provide additional opportunities for data fusion in unmatched regions. The use of a LIDAR rather than a laser alone allows us to generate highly accurate ground truth data sets by scanning the scene at high resolution. This is necessary for evaluating different pattern projection schemes. Results from LIDAR generated random dots are presented and compared to other texture projection techniques. Finally, we investigate the use of image texture analysis to intelligently project texture where it is required while exploiting the texture available in the ambient light image.

Assessing breast cancer masking risk with automated texture analysis in full field digital mammography

DEFF Research Database (Denmark)

Kallenberg, Michiel Gijsbertus J; Lillholm, Martin; Diao, Pengfei

2015-01-01

PURPOSE The goal of this work is to develop a method to assess the risk of breast cancer masking, based on image characteristics beyond breast density. METHOD AND MATERIALS From the Dutch breast cancer screening program we collected 285 screen detected cancers, and 109 cancers that were screen...... negative and subsequently appeared as interval cancers. To obtain mammograms without cancerous tissue, we took the contralateral mammograms. We developed a novel machine learning based method called convolutional sparse autoencoder to characterize mammographic texture. The reason for focusing...... status in a five-fold cross validation. To assess the interaction of the texture scores with breast density, Volpara Density Grade (VDG) was determined for each image using Volpara, Matakina Technology, New Zealand. RESULTS We grouped women into low (VDG 1/2) versus high (VDG 3/4) dense, and low...

Visual texture perception via graph-based semi-supervised learning

Science.gov (United States)

Zhang, Qin; Dong, Junyu; Zhong, Guoqiang

2018-04-01

Perceptual features, for example direction, contrast and repetitiveness, are important visual factors for human to perceive a texture. However, it needs to perform psychophysical experiment to quantify these perceptual features' scale, which requires a large amount of human labor and time. This paper focuses on the task of obtaining perceptual features' scale of textures by small number of textures with perceptual scales through a rating psychophysical experiment (what we call labeled textures) and a mass of unlabeled textures. This is the scenario that the semi-supervised learning is naturally suitable for. This is meaningful for texture perception research, and really helpful for the perceptual texture database expansion. A graph-based semi-supervised learning method called random multi-graphs, RMG for short, is proposed to deal with this task. We evaluate different kinds of features including LBP, Gabor, and a kind of unsupervised deep features extracted by a PCA-based deep network. The experimental results show that our method can achieve satisfactory effects no matter what kind of texture features are used.

Natural texture retrieval based on perceptual similarity measurement

Science.gov (United States)

Gao, Ying; Dong, Junyu; Lou, Jianwen; Qi, Lin; Liu, Jun

2018-04-01

A typical texture retrieval system performs feature comparison and might not be able to make human-like judgments of image similarity. Meanwhile, it is commonly known that perceptual texture similarity is difficult to be described by traditional image features. In this paper, we propose a new texture retrieval scheme based on texture perceptual similarity. The key of the proposed scheme is that prediction of perceptual similarity is performed by learning a non-linear mapping from image features space to perceptual texture space by using Random Forest. We test the method on natural texture dataset and apply it on a new wallpapers dataset. Experimental results demonstrate that the proposed texture retrieval scheme with perceptual similarity improves the retrieval performance over traditional image features.

Texture Feature Analysis for Different Resolution Level of Kidney Ultrasound Images

Science.gov (United States)

Kairuddin, Wan Nur Hafsha Wan; Mahmud, Wan Mahani Hafizah Wan

2017-08-01

Image feature extraction is a technique to identify the characteristic of the image. The objective of this work is to discover the texture features that best describe a tissue characteristic of a healthy kidney from ultrasound (US) image. Three ultrasound machines that have different specifications are used in order to get a different quality (different resolution) of the image. Initially, the acquired images are pre-processed to de-noise the speckle to ensure the image preserve the pixels in a region of interest (ROI) for further extraction. Gaussian Low- pass Filter is chosen as the filtering method in this work. 150 of enhanced images then are segmented by creating a foreground and background of image where the mask is created to eliminate some unwanted intensity values. Statistical based texture features method is used namely Intensity Histogram (IH), Gray-Level Co-Occurance Matrix (GLCM) and Gray-level run-length matrix (GLRLM).This method is depends on the spatial distribution of intensity values or gray levels in the kidney region. By using One-Way ANOVA in SPSS, the result indicated that three features (Contrast, Difference Variance and Inverse Difference Moment Normalized) from GLCM are not statistically significant; this concludes that these three features describe a healthy kidney characteristics regardless of the ultrasound image quality.

Electrochemically grown rough-textured nanowires

International Nuclear Information System (INIS)

Tyagi, Pawan; Postetter, David; Saragnese, Daniel; Papadakis, Stergios J.; Gracias, David H.

2010-01-01

Nanowires with a rough surface texture show unusual electronic, optical, and chemical properties; however, there are only a few existing methods for producing these nanowires. Here, we describe two methods for growing both free standing and lithographically patterned gold (Au) nanowires with a rough surface texture. The first strategy is based on the deposition of nanowires from a silver (Ag)-Au plating solution mixture that precipitates an Ag-Au cyanide complex during electrodeposition at low current densities. This complex disperses in the plating solution, thereby altering the nanowire growth to yield a rough surface texture. These nanowires are mass produced in alumina membranes. The second strategy produces long and rough Au nanowires on lithographically patternable nickel edge templates with corrugations formed by partial etching. These rough nanowires can be easily arrayed and integrated with microscale devices.

Enhancing the discrimination accuracy between metastases, gliomas and meningiomas on brain MRI by volumetric textural features and ensemble pattern recognition methods.

Science.gov (United States)

Georgiadis, Pantelis; Cavouras, Dionisis; Kalatzis, Ioannis; Glotsos, Dimitris; Athanasiadis, Emmanouil; Kostopoulos, Spiros; Sifaki, Koralia; Malamas, Menelaos; Nikiforidis, George; Solomou, Ekaterini

2009-01-01

Three-dimensional (3D) texture analysis of volumetric brain magnetic resonance (MR) images has been identified as an important indicator for discriminating among different brain pathologies. The purpose of this study was to evaluate the efficiency of 3D textural features using a pattern recognition system in the task of discriminating benign, malignant and metastatic brain tissues on T1 postcontrast MR imaging (MRI) series. The dataset consisted of 67 brain MRI series obtained from patients with verified and untreated intracranial tumors. The pattern recognition system was designed as an ensemble classification scheme employing a support vector machine classifier, specially modified in order to integrate the least squares features transformation logic in its kernel function. The latter, in conjunction with using 3D textural features, enabled boosting up the performance of the system in discriminating metastatic, malignant and benign brain tumors with 77.14%, 89.19% and 93.33% accuracy, respectively. The method was evaluated using an external cross-validation process; thus, results might be considered indicative of the generalization performance of the system to "unseen" cases. The proposed system might be used as an assisting tool for brain tumor characterization on volumetric MRI series.

Associations Between PET Textural Features and GLUT1 Expression, and the Prognostic Significance of Textural Features in Lung Adenocarcinoma.

Science.gov (United States)

Koh, Young Wha; Park, Seong Yong; Hyun, Seung Hyup; Lee, Su Jin

2018-02-01

We evaluated the association between positron emission tomography (PET) textural features and glucose transporter 1 (GLUT1) expression level and further investigated the prognostic significance of textural features in lung adenocarcinoma. We evaluated 105 adenocarcinoma patients. We extracted texture-based PET parameters of primary tumors. Conventional PET parameters were also measured. The relationships between PET parameters and GLUT1 expression levels were evaluated. The association between PET parameters and overall survival (OS) was assessed using Cox's proportional hazard regression models. In terms of PET textural features, tumors expressing high levels of GLUT1 exhibited significantly lower coarseness, contrast, complexity, and strength, but significantly higher busyness. On univariate analysis, the metabolic tumor volume, total lesion glycolysis, contrast, busyness, complexity, and strength were significant predictors of OS. Multivariate analysis showed that lower complexity (HR=2.017, 95%CI=1.032-3.942, p=0.040) was independently associated with poorer survival. PET textural features may aid risk stratification in lung adenocarcinoma patients. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Assessment of Textural Differentiations in Forest Resources in Romania Using Fractal Analysis

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Ion Andronache

2017-02-01

Full Text Available Deforestation and forest degradation have several negative effects on the environment including a loss of species habitats, disturbance of the water cycle and reduced ability to retain CO2, with consequences for global warming. We investigated the evolution of forest resources from development regions in Romania affected by both deforestation and reforestation using a non-Euclidean method based on fractal analysis. We calculated four fractal dimensions of forest areas: the fractal box-counting dimension of the forest areas, the fractal box-counting dimension of the dilated forest areas, the fractal dilation dimension and the box-counting dimension of the border of the dilated forest areas. Fractal analysis revealed morpho-structural and textural differentiations of forested, deforested and reforested areas in development regions with dominant mountain relief and high hills (more forested and compact organization in comparison to the development regions dominated by plains or low hills (less forested, more fragmented with small and isolated clusters. Our analysis used the fractal analysis that has the advantage of analyzing the entire image, rather than studying local information, thereby enabling quantification of the uniformity, fragmentation, heterogeneity and homogeneity of forests.

Diagnostic value of MRI-based 3D texture analysis for tissue characterisation and discrimination of low-grade chondrosarcoma from enchondroma. A pilot study

Energy Technology Data Exchange (ETDEWEB)

Lisson, Catharina S.; Lisson, Christoph G.; Flosdorf, Kerstin; Meier, Reinhard; Beer, Meinrad; Schmidt, Stefan A. [University Hospital of Ulm, Department of Diagnostic and Interventional Radiology, Ulm (Germany); Mayer-Steinacker, Regine [University Hospital of Ulm, Department of Internal Medicine III, Ulm (Germany); Schultheiss, Markus; Baer, Alexandra von [University Hospital of Ulm, Department of Trauma Surgery, Ulm (Germany); Barth, Thomas F.E. [University of Ulm, Institute of Pathology, Ulm (Germany); Beer, Ambros J. [University Hospital of Ulm, Department of Nuclear Medicine, Ulm (Germany); Baumhauer, Matthias [Mint Medical, Dossenheim (Germany)

2018-02-15

To explore the diagnostic value of MRI-based 3D texture analysis to identify texture features that can be used for discrimination of low-grade chondrosarcoma from enchondroma. Eleven patients with low-grade chondrosarcoma and 11 patients with enchondroma were retrospectively evaluated. Texture analysis was performed using mint Lesion: Kurtosis, entropy, skewness, mean of positive pixels (MPP) and uniformity of positive pixel distribution (UPP) were obtained in four MRI sequences and correlated with histopathology. The Mann-Whitney U-test and receiver operating characteristic (ROC) analysis were performed to identify most discriminative texture features. Sensitivity, specificity, accuracy and optimal cut-off values were calculated. Significant differences were found in four of 20 texture parameters with regard to the different MRI sequences (p<0.01). The area under the ROC curve values to discriminate chondrosarcoma from enchondroma were 0.876 and 0.826 for kurtosis and skewness in contrast-enhanced T1 (ceT1w), respectively; in non-contrast T1, values were 0.851 and 0.822 for entropy and UPP, respectively. The highest discriminatory power had kurtosis in ceT1w with a cut-off ≥3.15 to identify low-grade chondrosarcoma (82 % sensitivity, 91 % specificity, accuracy 86 %). MRI-based 3D texture analysis might be able to discriminate low-grade chondrosarcoma from enchondroma by a variety of texture parameters. (orig.)

The Heeger & Bergen Pyramid Based Texture Synthesis Algorithm

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Thibaud Briand

2014-11-01

Full Text Available This contribution deals with the Heeger-Bergen pyramid-based texture analysis/synthesis algorithm. It brings a detailed explanation of the original algorithm tested on many characteristic examples. Our analysis reproduces the original results, but also brings a minor improvement concerning non-periodic textures. Inspired by visual perception theories, Heeger and Bergen proposed to characterize a texture by its first-order statistics of both its color and its responses to multiscale and multi-orientation filters, namely the steerable pyramid. The Heeger-Bergen algorithm consists in the following procedure: starting from a white noise image, histogram matchings are performed to the noise alternatively in both the image domain and steerable pyramid domain, so that the corresponding histograms match the ones of the input texture.

RHEED transmission mode and pole figures thin film and nanostructure texture analysis

CERN Document Server

Wang, Gwo-Ching

2014-01-01

This unique book covers the fundamental principle of electron diffraction, basic instrumentation of RHEED, definitions of textures in thin films and nanostructures, mechanisms and control of texture formation, and examples of RHEED transmission mode measurements of texture and texture evolution of thin films and nanostructures. Also presented is a new application of RHEED in the transmission mode called RHEED pole figure technique that can be used to monitor the texture evolution in thin film growth and nanostructures and is not limited to single crystal epitaxial film growth. Details of the construction of RHEED pole figures and the interpretation of observed pole figures are presented.  Materials covered include metals, semiconductors, and thin insulators. This book also: Presents a new application of RHEED in the transmission mode Introduces a variety of textures from metals, semiconductors, compound semiconductors, and their characteristics in RHEED pole figures Provides examples of RHEED measurements o...

A multi-topographical-instrument analysis: the breast implant texture measurement

Science.gov (United States)

Garabédian, Charles; Delille, Rémi; Deltombe, Raphaël; Anselme, Karine; Atlan, Michael; Bigerelle, Maxence

2017-06-01

Capsular contracture is a major complication after implant-based breast augmentation. To address this tissue reaction, most manufacturers texture the outer breast implant surfaces with calibrated salt grains. However, the analysis of these surfaces on sub-micron scales has been under-studied. This scale range is of interest to understand the future of silicone particles potentially released from the implant surface and the aetiology of newly reported complications, such as Anaplastic Large Cell Lymphoma. The surface measurements were accomplished by tomography and by two optical devices based on interferometry and on focus variation. The robustness of the measurements was investigated from the tissue scale to the cellular scale. The macroscopic pore-based structure of the textured implant surfaces is consistently measured by the three instruments. However, the multi-scale analyses start to be discrepant in a scale range between 50 µm and 500 µm characteristic of a finer secondary roughness regardless of the pore shape. The focus variation and the micro-tomography would fail to capture this roughness regime because of a focus-related optical artefact and of step-shaped artefact respectively.

Texture analysis in quantitative MR imaging. Tissue characterisation of normal brain and intracranial tumours at 1.5 T

DEFF Research Database (Denmark)

Kjaer, L; Ring, P; Thomsen, C

1995-01-01

The diagnostic potential of texture analysis in quantitative tissue characterisation by MR imaging at 1.5 T was evaluated in the brain of 6 healthy volunteers and in 88 patients with intracranial tumours. Texture images were computed from calculated T1 and T2 parameter images by applying groups o...... to be successful in some cases of clinical importance. However, no discrimination between benign and malignant tumour growth was possible. Much texture information seems to be contained in MR images, which may prove useful for classification and image segmentation....

Texture analysis for survival prediction of pancreatic ductal adenocarcinoma patients with neoadjuvant chemotherapy

Science.gov (United States)

Chakraborty, Jayasree; Langdon-Embry, Liana; Escalon, Joanna G.; Allen, Peter J.; Lowery, Maeve A.; O'Reilly, Eileen M.; Do, Richard K. G.; Simpson, Amber L.

2016-03-01

Pancreatic ductal adenocarcinoma (PDAC) is the fourth leading cause of cancer-related death in the United States. The five-year survival rate for all stages is approximately 6%, and approximately 2% when presenting with distant disease.1 Only 10-20% of all patients present with resectable disease, but recurrence rates are high with only 5 to 15% remaining free of disease at 5 years. At this time, we are unable to distinguish between resectable PDAC patients with occult metastatic disease from those with potentially curable disease. Early classification of these tumor types may eventually lead to changes in initial management including the use of neoadjuvant chemotherapy or radiation, or in the choice of postoperative adjuvant treatments. Texture analysis is an emerging methodology in oncologic imaging for quantitatively assessing tumor heterogeneity that could potentially aid in the stratification of these patients. The present study derives several texture-based features from CT images of PDAC patients, acquired prior to neoadjuvant chemotherapy, and analyzes their performance, individually as well as in combination, as prognostic markers. A fuzzy minimum redundancy maximum relevance method with leave-one-image-out technique is included to select discriminating features from the set of extracted features. With a naive Bayes classifier, the proposed method predicts the 5-year overall survival of PDAC patients prior to neoadjuvant therapy and achieves the best results in terms of the area under the receiver operating characteristic curve of 0:858 and accuracy of 83:0% with four-fold cross-validation techniques.

Physical and textural characteristics of fermented milk products obtained by kombucha inoculums with herbal teas

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Malbaša Radomir V.

2012-01-01

Full Text Available In this investigation, kombucha fermented milk products were produced from milk with 1.6% milk fat using 10% (v/v kombucha inoculums cultivated on the extracts of peppermint and stinging nettle. The fermentation process was conducted at temperatures of 37, 40 and 43°C. Fermentation was stopped when the pH value of 4.5 was reached. The fermentation process was shortened with an increase of temperature. Physical characteristics of the fermented products were determined by using standard methods of analysis. Textural characteristics were determined by texture profile analysis. The obtained products showed good physical and textural characteristics, typical for the yoghurt-like products. [Projekat Ministarstva nauke Republike Srbije, br. III-46009

Cloud field classification based on textural features

Science.gov (United States)

Sengupta, Sailes Kumar

1989-01-01

An essential component in global climate research is accurate cloud cover and type determination. Of the two approaches to texture-based classification (statistical and textural), only the former is effective in the classification of natural scenes such as land, ocean, and atmosphere. In the statistical approach that was adopted, parameters characterizing the stochastic properties of the spatial distribution of grey levels in an image are estimated and then used as features for cloud classification. Two types of textural measures were used. One is based on the distribution of the grey level difference vector (GLDV), and the other on a set of textural features derived from the MaxMin cooccurrence matrix (MMCM). The GLDV method looks at the difference D of grey levels at pixels separated by a horizontal distance d and computes several statistics based on this distribution. These are then used as features in subsequent classification. The MaxMin tectural features on the other hand are based on the MMCM, a matrix whose (I,J)th entry give the relative frequency of occurrences of the grey level pair (I,J) that are consecutive and thresholded local extremes separated by a given pixel distance d. Textural measures are then computed based on this matrix in much the same manner as is done in texture computation using the grey level cooccurrence matrix. The database consists of 37 cloud field scenes from LANDSAT imagery using a near IR visible channel. The classification algorithm used is the well known Stepwise Discriminant Analysis. The overall accuracy was estimated by the percentage or correct classifications in each case. It turns out that both types of classifiers, at their best combination of features, and at any given spatial resolution give approximately the same classification accuracy. A neural network based classifier with a feed forward architecture and a back propagation training algorithm is used to increase the classification accuracy, using these two classes

MRI texture analysis in differentiating luminal A and luminal B breast cancer molecular subtypes - a feasibility study.

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Holli-Helenius, Kirsi; Salminen, Annukka; Rinta-Kiikka, Irina; Koskivuo, Ilkka; Brück, Nina; Boström, Pia; Parkkola, Riitta

2017-12-29

The aim of this study was to use texture analysis (TA) of breast magnetic resonance (MR) images to assist in differentiating estrogen receptor (ER) positive breast cancer molecular subtypes. Twenty-seven patients with histopathologically proven invasive ductal breast cancer were selected in preliminary study. Tumors were classified into molecular subtypes: luminal A (ER-positive and/or progesterone receptor (PR)-positive, human epidermal growth factor receptor type 2 (HER2) -negative, proliferation marker Ki-67 MaZda. Texture parameters and tumour volumes were correlated with tumour prognostic factors. Textural differences were observed mainly in precontrast images. The two most discriminative texture parameters to differentiate luminal A and luminal B subtypes were sum entropy and sum variance (p = 0.003). The AUCs were 0.828 for sum entropy (p = 0.004), and 0.833 for sum variance (p = 0.003), and 0.878 for the model combining texture features sum entropy, sum variance (p = 0.001). In the LOOCV, the AUC for model combining features sum entropy and sum variance was 0.876. Sum entropy and sum variance showed positive correlation with higher Ki-67 index. Luminal B types were larger in volume and moderate correlation between larger tumour volume and higher Ki-67 index was also observed (r = 0.499, p = 0.008). Texture features which measure randomness, heterogeneity or smoothness and homogeneity may either directly or indirectly reflect underlying growth patterns of breast tumours. TA and volumetric analysis may provide a way to evaluate the biologic aggressiveness of breast tumours and provide aid in decisions regarding therapeutic efficacy.

LOCAL TEXTURE DESCRIPTION FRAMEWORK FOR TEXTURE BASED FACE RECOGNITION

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R. Reena Rose

2014-02-01

Full Text Available Texture descriptors have an important role in recognizing face images. However, almost all the existing local texture descriptors use nearest neighbors to encode a texture pattern around a pixel. But in face images, most of the pixels have similar characteristics with that of its nearest neighbors because the skin covers large area in a face and the skin tone at neighboring regions are same. Therefore this paper presents a general framework called Local Texture Description Framework that uses only eight pixels which are at certain distance apart either circular or elliptical from the referenced pixel. Local texture description can be done using the foundation of any existing local texture descriptors. In this paper, the performance of the proposed framework is verified with three existing local texture descriptors Local Binary Pattern (LBP, Local Texture Pattern (LTP and Local Tetra Patterns (LTrPs for the five issues viz. facial expression, partial occlusion, illumination variation, pose variation and general recognition. Five benchmark databases JAFFE, Essex, Indian faces, AT&T and Georgia Tech are used for the experiments. Experimental results demonstrate that even with less number of patterns, the proposed framework could achieve higher recognition accuracy than that of their base models.

Quinoa Starch Characteristics and Their Correlations with the Texture Profile Analysis (TPA) of Cooked Quinoa.

Science.gov (United States)

Wu, Geyang; Morris, Craig F; Murphy, Kevin M

2017-10-01

Starch characteristics significantly influence the functionality and end-use quality of cereals and pseudo-cereals. This study examined the composition and properties of starch from 11 pure varieties and 2 commercial samples of quinoa in relationship to the texture of cooked quinoa. Nearly all starch properties and characteristics differed among these samples. Results showed that total starch content of seeds ranged from 53.2 to 75.1 g/100 g apparent amylose content ranged from 2.7% to 16.9%; total amylose ranged from 4.7% to 17.3%; and the degree of amylose-lipid complex ranged from 3.4% to 43.3%. Amylose leaching ranged from 31 mg/100 g starch in "Japanese Strain" to 862 mg/100 g starch in "49ALC." "Japanese Strain" starch also exhibited the highest water solubility (4.5%) and the lowest swelling power (17). α-Amylase activity in "1ESP," "Col.#6197," "Japanese Strain," "QQ63," "Yellow Commercial," and "Red Commercial" (0.03 to 0.09 CU) were significantly lower than the levels of the other quinoa samples (0.20 to 1.16 CU). Additionally, gel texture, thermal properties, and pasting properties of quinoa starches were investigated. Lastly, correlation analysis showed that the quinoa samples with higher amylose content tended to yield harder, stickier, more cohesive, more gummy, and more chewy texture after cooking. A higher degree of amylose-lipid complex and amylose leaching were associated with softer and less chewy cooked quinoa TPA texture. Higher starch enthalpy correlated with firmer, more adhesive, more cohesive, and chewier texture. In sum, starch plays a significant role in the texture of cooked quinoa. The research determined starch characteristics among a diverse set of pure quinoa varieties and commercial samples, and identified the relationships between starch properties and cooked quinoa texture. The results can help breeders and food manufacturers to understand better the relationships among quinoa starch characteristics, cooked quinoa texture, and

Magnetic resonance imaging textural evaluation of posterior cranial fossa tumors in childhood

International Nuclear Information System (INIS)

Santos, Joelson Alves dos; Costa, Maria Olivia Rodrigues da; Otaduy, Maria Concepcion Garcia; Lacerda, Maria Teresa Carvalho de; Leite, Claudia da Costa; Matsushita, Hamilton

2004-01-01

Objective: To distinguish healthy from pathological tissues in pediatric patients with posterior cranial fossa tumors using calculated textural parameters from magnetic resonance images. Materials And Methods: We evaluated 14 pediatric patients with posterior cranial fossa tumors using the software MaZda to define the texture parameters in selected regions of interest representing healthy and pathological tissues based on T2-weighted magnetic resonance images. Results: There was a statistically significant difference between normal and tumoral tissues as well as between supposedly normal tissues adjacent and distant from the tumoral lesion. Conclusion: Magnetic resonance textural evaluation is an useful tool for determining differences among various tissues, including tissues that appear apparently normal on visual analysis. (author)

17th International Conference on Textures of Materials (ICOTOM 17)

International Nuclear Information System (INIS)

Skrotzki, Werner; Oertel, Carl-Georg

2015-01-01

The 17th International Conference on Textures of Materials (ICOTOM 17) took place in Dresden, Germany, August 24-29, 2014. It belongs to the 'triennial' series of ICOTOM meetings with a long tradition, starting in 1969 - Clausthal, 1971 - Cracow, 1973 - Pont-à-Mousson, 1975 - Cambridge, 1978 - Aachen, 1981 - Tokyo, 1984 - Noordwijkerhout, 1987 - Santa Fe, 1990 - Avignon, 1993 - Clausthal, 1996 - Xian, 1999 - Montreal, 2002 - Seoul, 2005 - Leuven, 2008 - Pittsburgh, 2011 - Mumbai, 2014 - Dresden. ICOTOM 17 was hosted by the Dresden University of Technology, Institute of Structural Physics. Following the tradition of the ICOTOM conferences, the main focus of ICOTOM-17 was to promote and strengthen the fundamental understanding of the basic processes that govern the formation of texture and its relation to the properties of polycrystalline materials. Nonetheless, it was the aim to forge links between basic research on model materials and applied research on engineering materials of technical importance. Thus, ICOTOM 17 provided a forum for the presentation and discussion of recent progress in research of texture and related anisotropy of mechanical and functional properties of all kinds of polycrystalline materials including natural materials like rocks. Particular attention was paid to recent advances in texture measurement and analysis as well as modeling of texture development for all kinds of processes like solidification, plastic deformation, recrystallization and grain growth, phase transformations, thin film deposition, etc. Hence, ICOTOM 17 was of great interest to materials scientists, engineers from many different areas and geoscientists. The topics covered by ICOTOM 17 were: 1. Mathematical, numerical and statistical methods of texture analysis 2. Deformation textures 3. Crystallization, recrystallization and growth textures 4. Transformation textures 5. Textures in functional materials 6. Textures in advanced materials 7. Textures in rocks 8

Extraction of Homogeneous Fine-Grained Texture Segments in Visual Images

Czech Academy of Sciences Publication Activity Database

Golcev, A.; Gritsenko, V.; Húsek, Dušan

2017-01-01

Roč. 27, č. 5 (2017), s. 447-477 ISSN 1210-0552 Institutional support: RVO:67985807 Keywords : texture feature * texture window * homogeneous fine-grained texture segment * extraction of texture segment * texture segmentation * ”float” coding method Subject RIV: IN - Informatics, Computer Science OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 0.394, year: 2016

Pressure distribution-based texture sensing by using a simple artificial mastication system.

Science.gov (United States)

Yamamoto, Takeshi; Higashimori, Mitsuru; Nakauma, Makoto; Nakao, Satomi; Ikegami, Akira; Ishihara, Sayaka

2014-01-01

This paper proposes a novel texture sensing method for nursing-care gel by using an artificial mastication system, in which not only mechanical characteristics but also geometrical ones are objectively and quantitatively evaluated. When human masticates gel food, she or he perceives the changes of the shape and contact force simultaneously. Based on the impressions, they evaluate the texture. For reproducing such a procedure, the pressure distribution of gel is measured in the simple artificial mastication, and the information associated to both the geometrical and mechanical characteristics is simultaneously acquired. The relationship between the value of sensory evaluation (i.e. impression human perceives), and the pressure distribution data is numerically modeled by applying the image texture analysis. Experimental results show that the proposed method succeeds in estimating the values of sensory evaluation of nine kinds of gel with the coefficient of determination greater than 0.93.

Measurement of kinaesthetic properties of in-brine table olives by microstructure of fracture surface, sensory evaluation and texture profile analysis (TPA).

Science.gov (United States)

Lanza, Barbara; Amoruso, Filomena

2018-02-02

A series of transformations occur in olive fruit both during ripening and processing. In particular, significant changes in the microstructural composition affect the flavour, texture, nutrients and overall quality of the end product. Texture is one of the sensory quality attributes of greatest importance to consumer acceptance. In the present work, kinaesthetic properties of in-brine table olives of three cultivars of Olea europaea L. (Bella di Cerignola, Peranzana and Taggiasca cvs) were provided by several measurements of olive tissue texture by sensory, rheological and microstructural approaches. Olives at the same stage of ripening and processed with the same technology, but belonging to different cultivars, showed significant differences at microstructural, sensorial and rheological levels. To describe the relationship between the three variables, multiple regression analysis and principal component analysis were chosen. Differences in microstructure were closely related both in terms of hardness measured by texture profile analysis and hardness measured by sensory analysis. The information provided could be an aid for screening and training of a sensory panel. © 2018 Society of Chemical Industry. © 2018 Society of Chemical Industry.

Epitaxial hexagonal materials on IBAD-textured substrates

Science.gov (United States)

Matias, Vladimir; Yung, Christopher

2017-08-15

A multilayer structure including a hexagonal epitaxial layer, such as GaN or other group III-nitride (III-N) semiconductors, a oriented textured layer, and a non-single crystal substrate, and methods for making the same. The textured layer has a crystalline alignment preferably formed by the ion-beam assisted deposition (IBAD) texturing process and can be biaxially aligned. The in-plane crystalline texture of the textured layer is sufficiently low to allow growth of high quality hexagonal material, but can still be significantly greater than the required in-plane crystalline texture of the hexagonal material. The IBAD process enables low-cost, large-area, flexible metal foil substrates to be used as potential alternatives to single-crystal sapphire and silicon for manufacture of electronic devices, enabling scaled-up roll-to-roll, sheet-to-sheet, or similar fabrication processes to be used. The user is able to choose a substrate for its mechanical and thermal properties, such as how well its coefficient of thermal expansion matches that of the hexagonal epitaxial layer, while choosing a textured layer that more closely lattice matches that layer.

Ion beam texturing

Science.gov (United States)

Hudson, W. R.

1977-01-01

A microscopic surface texture was created by sputter-etching a surface while simultaneously sputter-depositing a lower sputter yield material onto the surface. A xenon ion-beam source was used to perform the texturing process on samples as large as 3-cm diameter. Textured surfaces have been characterized with SEM photomicrographs for a large number of materials including Cu, Al, Si, Ti, Ni, Fe, stainless steel, Au, and Ag. A number of texturing parameters are studied including the variation of texture with ion-beam powder, surface temperature, and the rate of texture growth with sputter etching time.

Effects of alkali on protein polymerization and textural characteristics of textured wheat protein.

Science.gov (United States)

Li, Ting; Guo, Xiao-Na; Zhu, Ke-Xue; Zhou, Hui-Ming

2018-01-15

The impact of alkali addition on the degree of gluten polymerization and textural characteristics of textured wheat protein was investigated. Results showed that the extrusion process increased the average molecular weight of gluten as evidenced by SDS-PAGE and SDS extractable protein. The addition of alkali not only promoted the degree of gluten polymerization, but also induced dehydroalanine-derived cross-linking. Alkali addition decreased the content of cystine and increased the contents of dehydroalanine and lanthionine. The obvious decrease of free SH showed that dehydroalanine-derived cross-linking was quantitatively less crucial than disulfide cross-linking. Furthermore, the protein cross-linking induced by alkali improved the texture properties of gluten extrudates. SEM analysis showed extrusion under alkaline condition conferred a more fibrous microstructure as a consequence of a compact gluten network. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spectral analysis of the stick-slip phenomenon in "oral" tribological texture evaluation.

Science.gov (United States)

Sanahuja, Solange; Upadhyay, Rutuja; Briesen, Heiko; Chen, Jianshe

2017-08-01

"Oral" tribology has become a new paradigm in food texture studies to understand complex texture attributes, such as creaminess, oiliness, and astringency, which could not be successfully characterized by traditional texture analysis nor by rheology. Stick-slip effects resulting from intermittent sliding motion during kinetic friction of oral mucosa could constitute an additional determining factor of sensory perception where traditional friction coefficient values and their Stribeck regimes fail in predicting different lubricant (food bolus and saliva) behaviors. It was hypothesized that the observed jagged behavior of most sliding force curves are due to stick-slip effects and depend on test velocity, normal load, surface roughness as well as lubricant type. Therefore, different measurement set-ups were investigated: sliding velocities from 0.01 to 40 mm/s, loads of 0.5 and 2.5 N as well as a smooth and a textured silicone contact surface. Moreover, dry contact measurements were compared to model food systems, such as water, oil, and oil-in-water emulsions. Spectral analysis permitted to extract the distribution of stick-slip magnitudes for specific wave numbers, characterizing the occurrence of jagged force peaks per unit sliding distance, similar to frequencies per unit time. The spectral features were affected by all the above mentioned tested factors. Stick-slip created vibration frequencies in the range of those detected by oral mechanoreceptors (0.3-400 Hz). The study thus provides a new insight into the use of tribology in food psychophysics. Dynamic spectral analysis has been applied for the first time to the force-displacement curves in "oral" tribology. Analyzing the stick-slip phenomenon in the dynamic friction provides new information that is generally overlooked or confused with machine noise and which may help to understand friction-related sensory attributes. This approach allows us to differentiate samples that have similar friction coefficient

Automated Texture Analysis and Determination of Fibre Orientation of Heart Tissue: A Morphometric Study.

Science.gov (United States)

Zach, Bernhard; Hofer, Ernst; Asslaber, Martin; Ahammer, Helmut

2016-01-01

The human heart has a heterogeneous structure, which is characterized by different cell types and their spatial configurations. The physical structure, especially the fibre orientation and the interstitial fibrosis, determines the electrical excitation and in further consequence the contractility in macroscopic as well as in microscopic areas. Modern image processing methods and parameters could be used to describe the image content and image texture. In most cases the description of the texture is not satisfying because the fibre orientation, detected with common algorithms, is biased by elements such as fibrocytes or endothelial nuclei. The goal of this work is to figure out if cardiac tissue can be analysed and classified on a microscopic level by automated image processing methods with a focus on an accurate detection of the fibre orientation. Quantitative parameters for identification of textures of different complexity or pathological attributes inside the heart were determined. The focus was set on the detection of the fibre orientation, which was calculated on the basis of the cardiomyocytes' nuclei. It turned out that the orientation of these nuclei corresponded with a high precision to the fibre orientation in the image plane. Additionally, these nuclei also indicated very well the inclination of the fibre.

Dominant color and texture feature extraction for banknote discrimination

Science.gov (United States)

Wang, Junmin; Fan, Yangyu; Li, Ning

2017-07-01

Banknote discrimination with image recognition technology is significant in many applications. The traditional methods based on image recognition only recognize the banknote denomination without discriminating the counterfeit banknote. To solve this problem, we propose a systematical banknote discrimination approach with the dominant color and texture features. After capturing the visible and infrared images of the test banknote, we first implement the tilt correction based on the principal component analysis (PCA) algorithm. Second, we extract the dominant color feature of the visible banknote image to recognize the denomination. Third, we propose an adaptively weighted local binary pattern with "delta" tolerance algorithm to extract the texture features of the infrared banknote image. At last, we discriminate the genuine or counterfeit banknote by comparing the texture features between the test banknote and the benchmark banknote. The proposed approach is tested using 14,000 banknotes of six different denominations from Chinese yuan (CNY). The experimental results show 100% accuracy for denomination recognition and 99.92% accuracy for counterfeit banknote discrimination.

Radiation injury vs. recurrent brain metastasis: combining textural feature radiomics analysis and standard parameters may increase 18F-FET PET accuracy without dynamic scans.

Science.gov (United States)

Lohmann, Philipp; Stoffels, Gabriele; Ceccon, Garry; Rapp, Marion; Sabel, Michael; Filss, Christian P; Kamp, Marcel A; Stegmayr, Carina; Neumaier, Bernd; Shah, Nadim J; Langen, Karl-Josef; Galldiks, Norbert

2017-07-01

We investigated the potential of textural feature analysis of O-(2-[ 18 F]fluoroethyl)-L-tyrosine ( 18 F-FET) PET to differentiate radiation injury from brain metastasis recurrence. Forty-seven patients with contrast-enhancing brain lesions (n = 54) on MRI after radiotherapy of brain metastases underwent dynamic 18 F-FET PET. Tumour-to-brain ratios (TBRs) of 18 F-FET uptake and 62 textural parameters were determined on summed images 20-40 min post-injection. Tracer uptake kinetics, i.e., time-to-peak (TTP) and patterns of time-activity curves (TAC) were evaluated on dynamic PET data from 0-50 min post-injection. Diagnostic accuracy of investigated parameters and combinations thereof to discriminate between brain metastasis recurrence and radiation injury was compared. Diagnostic accuracy increased from 81 % for TBR mean alone to 85 % when combined with the textural parameter Coarseness or Short-zone emphasis. The accuracy of TBR max alone was 83 % and increased to 85 % after combination with the textural parameters Coarseness, Short-zone emphasis, or Correlation. Analysis of TACs resulted in an accuracy of 70 % for kinetic pattern alone and increased to 83 % when combined with TBR max . Textural feature analysis in combination with TBRs may have the potential to increase diagnostic accuracy for discrimination between brain metastasis recurrence and radiation injury, without the need for dynamic 18 F-FET PET scans. • Textural feature analysis provides quantitative information about tumour heterogeneity • Textural features help improve discrimination between brain metastasis recurrence and radiation injury • Textural features might be helpful to further understand tumour heterogeneity • Analysis does not require a more time consuming dynamic PET acquisition.

Shape-Tailored Features and their Application to Texture Segmentation

KAUST Repository

Khan, Naeemullah

2014-04-01

Texture Segmentation is one of the most challenging areas of computer vision. One reason for this difficulty is the huge variety and variability of textures occurring in real world, making it very difficult to quantitatively study textures. One of the key tools used for texture segmentation is local invariant descriptors. Texture consists of textons, the basic building block of textures, that may vary by small nuisances like illumination variation, deformations, and noise. Local invariant descriptors are robust to these nuisances making them beneficial for texture segmentation. However, grouping dense descriptors directly for segmentation presents a problem: existing descriptors aggregate data from neighborhoods that may contain different textured regions, making descriptors from these neighborhoods difficult to group, leading to significant errors in segmentation. This work addresses this issue by proposing dense local descriptors, called Shape-Tailored Features, which are tailored to an arbitrarily shaped region, aggregating data only within the region of interest. Since the segmentation, i.e., the regions, are not known a-priori, we propose a joint problem for Shape-Tailored Features and the regions. We present a framework based on variational methods. Extensive experiments on a new large texture dataset, which we introduce, show that the joint approach with Shape-Tailored Features leads to better segmentations over the non-joint non Shape-Tailored approach, and the method out-performs existing state-of-the-art.

Reproducibility of tumor uptake heterogeneity characterization through textural feature analysis in 18F-FDG PET.

Science.gov (United States)

Tixier, Florent; Hatt, Mathieu; Le Rest, Catherine Cheze; Le Pogam, Adrien; Corcos, Laurent; Visvikis, Dimitris

2012-05-01

(18)F-FDG PET measurement of standardized uptake value (SUV) is increasingly used for monitoring therapy response and predicting outcome. Alternative parameters computed through textural analysis were recently proposed to quantify the heterogeneity of tracer uptake by tumors as a significant predictor of response. The primary objective of this study was to evaluate the reproducibility of these heterogeneity measurements. Double baseline (18)F-FDG PET scans were acquired within 4 d of each other for 16 patients before any treatment was considered. A Bland-Altman analysis was performed on 8 parameters based on histogram measurements and 17 parameters based on textural heterogeneity features after discretization with values between 8 and 128. The reproducibility of maximum and mean SUV was similar to that in previously reported studies, with a mean percentage difference of 4.7% ± 19.5% and 5.5% ± 21.2%, respectively. By comparison, better reproducibility was measured for some textural features describing local heterogeneity of tracer uptake, such as entropy and homogeneity, with a mean percentage difference of -2% ± 5.4% and 1.8% ± 11.5%, respectively. Several regional heterogeneity parameters such as variability in the intensity and size of regions of homogeneous activity distribution had reproducibility similar to that of SUV measurements, with 95% confidence intervals of -22.5% to 3.1% and -1.1% to 23.5%, respectively. These parameters were largely insensitive to the discretization range. Several parameters derived from textural analysis describing heterogeneity of tracer uptake by tumors on local and regional scales had reproducibility similar to or better than that of simple SUV measurements. These reproducibility results suggest that these (18)F-FDG PET-derived parameters, which have already been shown to have predictive and prognostic value in certain cancer models, may be used to monitor therapy response and predict patient outcome.

Time-Frequency Feature Representation Using Multi-Resolution Texture Analysis and Acoustic Activity Detector for Real-Life Speech Emotion Recognition

Directory of Open Access Journals (Sweden)

Kun-Ching Wang

2015-01-01

Full Text Available The classification of emotional speech is mostly considered in speech-related research on human-computer interaction (HCI. In this paper, the purpose is to present a novel feature extraction based on multi-resolutions texture image information (MRTII. The MRTII feature set is derived from multi-resolution texture analysis for characterization and classification of different emotions in a speech signal. The motivation is that we have to consider emotions have different intensity values in different frequency bands. In terms of human visual perceptual, the texture property on multi-resolution of emotional speech spectrogram should be a good feature set for emotion classification in speech. Furthermore, the multi-resolution analysis on texture can give a clearer discrimination between each emotion than uniform-resolution analysis on texture. In order to provide high accuracy of emotional discrimination especially in real-life, an acoustic activity detection (AAD algorithm must be applied into the MRTII-based feature extraction. Considering the presence of many blended emotions in real life, in this paper make use of two corpora of naturally-occurring dialogs recorded in real-life call centers. Compared with the traditional Mel-scale Frequency Cepstral Coefficients (MFCC and the state-of-the-art features, the MRTII features also can improve the correct classification rates of proposed systems among different language databases. Experimental results show that the proposed MRTII-based feature information inspired by human visual perception of the spectrogram image can provide significant classification for real-life emotional recognition in speech.

Texture-Based Analysis of 100 MR Examinations of Head and Neck Tumors - Is It Possible to Discriminate Between Benign and Malignant Masses in a Multicenter Trial?

Science.gov (United States)

Fruehwald-Pallamar, J; Hesselink, J R; Mafee, M F; Holzer-Fruehwald, L; Czerny, C; Mayerhoefer, M E

2016-02-01

To evaluate whether texture-based analysis of standard MRI sequences can help in the discrimination between benign and malignant head and neck tumors. The MR images of 100 patients with a histologically clarified head or neck mass, from two different institutions, were analyzed. Texture-based analysis was performed using texture analysis software, with region of interest measurements for 2 D and 3 D evaluation independently for all axial sequences. COC, RUN, GRA, ARM, and WAV features were calculated for all ROIs. 10 texture feature subsets were used for a linear discriminant analysis, in combination with k-nearest-neighbor classification. Benign and malignant tumors were compared with regard to texture-based values. There were differences in the images from different field-strength scanners, as well as from different vendors. For the differentiation of benign and malignant tumors, we found differences on STIR and T2-weighted images for 2 D, and on contrast-enhanced T1-TSE with fat saturation for 3 D evaluation. In a separate analysis of the subgroups 1.5 and 3 Tesla, more discriminating features were found. Texture-based analysis is a useful tool in the discrimination of benign and malignant tumors when performed on one scanner with the same protocol. We cannot recommend this technique for the use of multicenter studies with clinical data. 2 D/3 D texture-based analysis can be performed in head and neck tumors. Texture-based analysis can differentiate between benign and malignant masses. Analyzed MR images should originate from one scanner with an identical protocol. © Georg Thieme Verlag KG Stuttgart · New York.

A Comparative Study of Land Cover Classification by Using Multispectral and Texture Data

Directory of Open Access Journals (Sweden)

Salman Qadri

2016-01-01

Full Text Available The main objective of this study is to find out the importance of machine vision approach for the classification of five types of land cover data such as bare land, desert rangeland, green pasture, fertile cultivated land, and Sutlej river land. A novel spectra-statistical framework is designed to classify the subjective land cover data types accurately. Multispectral data of these land covers were acquired by using a handheld device named multispectral radiometer in the form of five spectral bands (blue, green, red, near infrared, and shortwave infrared while texture data were acquired with a digital camera by the transformation of acquired images into 229 texture features for each image. The most discriminant 30 features of each image were obtained by integrating the three statistical features selection techniques such as Fisher, Probability of Error plus Average Correlation, and Mutual Information (F + PA + MI. Selected texture data clustering was verified by nonlinear discriminant analysis while linear discriminant analysis approach was applied for multispectral data. For classification, the texture and multispectral data were deployed to artificial neural network (ANN: n-class. By implementing a cross validation method (80-20, we received an accuracy of 91.332% for texture data and 96.40% for multispectral data, respectively.

The brass-type texture and its deviation from the copper-type texture

DEFF Research Database (Denmark)

Leffers, Torben; Ray, R.K.

2009-01-01

Our basic aim with the present review is to address the classical problem of the “fcc rolling texture transition” – the fact that fcc materials may, depending on material parameters and rolling conditions, develop two different types of rolling textures, the copper-type texture and the brass...... the subject and sketch our approach for dealing with it. We then recapitulate the decisive progress made during the nineteen sixties in the empirical description of the fcc rolling texture transition and in lining up a number of possible explanations. Then follows a section about experimental investigations...... of the brass-type texture after the nineteen sixties covering texture measurements and microstructural investigations. The main observations are: (1) The brass-type texture deviates from the copper-type texture from an early stage of texture development. (2) Deformation twinning has a decisive effect...

Pedestrian count estimation using texture feature with spatial distribution

Directory of Open Access Journals (Sweden)

Hongyu Hu

2016-12-01

Full Text Available We present a novel pedestrian count estimation approach based on global image descriptors formed from multi-scale texture features that considers spatial distribution. For regions of interest, local texture features are represented based on histograms of multi-scale block local binary pattern, which jointly constitute the feature vector of the whole image. Therefore, to achieve an effective estimation of pedestrian count, principal component analysis is used to reduce the dimension of the global representation features, and a fitting model between image global features and pedestrian count is constructed via support vector regression. The experimental result shows that the proposed method exhibits high accuracy on pedestrian count estimation and can be applied well in the real world.

A Noise Robust Statistical Texture Model

DEFF Research Database (Denmark)

Hilger, Klaus Baggesen; Stegmann, Mikkel Bille; Larsen, Rasmus

2002-01-01

Appearance Models segmentation framework. This is accomplished by augmenting the model with an estimate of the covariance of the noise present in the training data. This results in a more compact model maximising the signal-to-noise ratio, thus favouring subspaces rich on signal, but low on noise......This paper presents a novel approach to the problem of obtaining a low dimensional representation of texture (pixel intensity) variation present in a training set after alignment using a Generalised Procrustes analysis.We extend the conventional analysis of training textures in the Active...

Evaluation of the effect of initial texture on the development of deformation texture

DEFF Research Database (Denmark)

Leffers, Torben; Juul Jensen, Dorte

1986-01-01

The authors describe a computer procedure which allows them to introduce experimental initial textures as starting conditions for texture simulation (instead of a theoretical random texture). They apply the procedure on two batches of copper with weak initial textures and on fine-grained and coarse......-grained aluminium with moderately strong initial textures. In copper the initial texture turns out to be too weak to have any significant effect. In aluminium the initial texture has a very significant effect on the simulated textures-similar to the effect it has on the experimental textures. However......, there are differences between the simulated and the experimental aluminium textures that can only be explained as a grain-size effect. Possible future applications of the procedure are discussed...

Highly textured KNN-based piezoelectric ceramics by conventional sintering

International Nuclear Information System (INIS)

Zapata, Angelica Maria Mazuera; Silva Junior, Paulo Sergio da; Zambrano, Michel Venet

2016-01-01

Full text: Texturing in ferroelectric ceramics has played an important role in the enhancement of their piezoelectric properties. Common methods for ceramic texturing are hot pressing and template grain ground; nevertheless, the needed facilities to apply hot pressing and the processing of single crystal make the texture of ceramics expensive and very difficult. In this study, a novel method was investigated to obtain highly textured lead-free ceramics. A (K 0.5 Na 0.5 ) 0.97 Li 0. 0 3 Nb 0.8 Ta 0. 2 matrix (KNLNT), with CuO excess was sintered between 1070 and 1110 °C following a solid state reaction procedure. The CuO excess promotes liquid phase formation and a partial melting of the material. XRD patterns showed the intensity of (100) family peaks became much stronger with the increasing of sintering temperature and CuO. In addition, Lotgering factor was calculated and exhibited a texture degree between 40 % and 70 % for sintered samples having 13 and 16 wt. % CuO, respectively. These, highly textured ceramics, with adequate cut, can be used as substitutes single crystals for texturing of KNN-based lead-free ceramics. (author)

Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps.

Science.gov (United States)

Sadeghi-Naini, Ali; Suraweera, Harini; Tran, William Tyler; Hadizad, Farnoosh; Bruni, Giancarlo; Rastegar, Rashin Fallah; Curpen, Belinda; Czarnota, Gregory J

2017-10-20

This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic.

A plateau–valley separation method for textured surfaces with a deterministic pattern

DEFF Research Database (Denmark)

Godi, Alessandro; Kühle, Anders; De Chiffre, Leonardo

2014-01-01

The effective characterization of textured surfaces presenting a deterministic pattern of lubricant reservoirs is an issue with which many researchers are nowadays struggling. Existing standards are not suitable for the characterization of such surfaces, providing at times values without physical...... meaning. A new method based on the separation between the plateau and valley regions is hereby presented allowing independent functional analyses of the detected features. The determination of a proper threshold between plateaus and valleys is the first step of a procedure resulting in an efficient...

Self-Similarity Based Corresponding-Point Extraction from Weakly Textured Stereo Pairs

Directory of Open Access Journals (Sweden)

Min Mao

2014-01-01

Full Text Available For the areas of low textured in image pairs, there is nearly no point that can be detected by traditional methods. The information in these areas will not be extracted by classical interest-point detectors. In this paper, a novel weakly textured point detection method is presented. The points with weakly textured characteristic are detected by the symmetry concept. The proposed approach considers the gray variability of the weakly textured local regions. The detection mechanism can be separated into three steps: region-similarity computation, candidate point searching, and refinement of weakly textured point set. The mechanism of radius scale selection and texture strength conception are used in the second step and the third step, respectively. The matching algorithm based on sparse representation (SRM is used for matching the detected points in different images. The results obtained on image sets with different objects show high robustness of the method to background and intraclass variations as well as to different photometric and geometric transformations; the points detected by this method are also the complement of points detected by classical detectors from the literature. And we also verify the efficacy of SRM by comparing with classical algorithms under the occlusion and corruption situations for matching the weakly textured points. Experiments demonstrate the effectiveness of the proposed weakly textured point detection algorithm.

Texture classification of vegetation cover in high altitude wetlands zone

International Nuclear Information System (INIS)

Wentao, Zou; Bingfang, Wu; Hongbo, Ju; Hua, Liu

2014-01-01

The aim of this study was to investigate the utility of datasets composed of texture measures and other features for the classification of vegetation cover, specifically wetlands. QUEST decision tree classifier was applied to a SPOT-5 image sub-scene covering the typical wetlands area in Three River Sources region in Qinghai province, China. The dataset used for the classification comprised of: (1) spectral data and the components of principal component analysis; (2) texture measures derived from pixel basis; (3) DEM and other ancillary data covering the research area. Image textures is an important characteristic of remote sensing images; it can represent spatial variations with spectral brightness in digital numbers. When the spectral information is not enough to separate the different land covers, the texture information can be used to increase the classification accuracy. The texture measures used in this study were calculated from GLCM (Gray level Co-occurrence Matrix); eight frequently used measures were chosen to conduct the classification procedure. The results showed that variance, mean and entropy calculated by GLCM with a 9*9 size window were effective in distinguishing different vegetation types in wetlands zone. The overall accuracy of this method was 84.19% and the Kappa coefficient was 0.8261. The result indicated that the introduction of texture measures can improve the overall accuracy by 12.05% and the overall kappa coefficient by 0.1407 compared with the result using spectral and ancillary data

''Textural analysis of multiparametric MRI detects transition zone prostate cancer''

Energy Technology Data Exchange (ETDEWEB)

Sidhu, Harbir S.; Johnston, Edward W.; Taylor, Stuart A.; Halligan, Steve [Centre for Medical Imaging, University College London, London (United Kingdom); University College London Hospitals NHS Foundation Trust, London (United Kingdom); Benigno, Salvatore; Dikaios, Nikos [Centre for Medical Imaging, University College London, London (United Kingdom); Ganeshan, Balaji [Institute of Nuclear Medicine, University College London, University College Hospital, London (United Kingdom); Allen, Clare; Kirkham, Alex [University College London Hospitals NHS Foundation Trust, London (United Kingdom); Groves, Ashley M. [University College London Hospitals NHS Foundation Trust, London (United Kingdom); Institute of Nuclear Medicine, University College London, University College Hospital, London (United Kingdom); Ahmed, Hashim U.; Emberton, Mark [University College London Hospitals NHS Foundation Trust, London (United Kingdom); University College London, Research Department of Urology, London (United Kingdom); Punwani, Shonit [Centre for Medical Imaging, University College London, London (United Kingdom); University College London Hospitals NHS Foundation Trust, London (United Kingdom); Centre for Medical Imaging, University College London and University College London Hospitals NIHR Biomedical Research Centre, London (United Kingdom)

2017-06-15

To evaluate multiparametric-MRI (mpMRI) derived histogram textural-analysis parameters for detection of transition zone (TZ) prostatic tumour. Sixty-seven consecutive men with suspected prostate cancer underwent 1.5T mpMRI prior to template-mapping-biopsy (TPM). Twenty-six men had 'significant' TZ tumour. Two radiologists in consensus matched TPM to the single axial slice best depicting tumour, or largest TZ diameter for those with benign histology, to define single-slice whole TZ-regions-of-interest (ROIs). Textural-parameter differences between single-slice whole TZ-ROI containing significant tumour versus benign/insignificant tumour were analysed using Mann Whitney U test. Diagnostic accuracy was assessed by receiver operating characteristic area under curve (ROC-AUC) analysis cross-validated with leave-one-out (LOO) analysis. ADC kurtosis was significantly lower (p < 0.001) in TZ containing significant tumour with ROC-AUC 0.80 (LOO-AUC 0.78); the difference became non-significant following exclusion of significant tumour from single-slice whole TZ-ROI (p = 0.23). T1-entropy was significantly lower (p = 0.004) in TZ containing significant tumour with ROC-AUC 0.70 (LOO-AUC 0.66) and was unaffected by excluding significant tumour from TZ-ROI (p = 0.004). Combining these parameters yielded ROC-AUC 0.86 (LOO-AUC 0.83). Textural features of the whole prostate TZ can discriminate significant prostatic cancer through reduced kurtosis of the ADC-histogram where significant tumour is included in TZ-ROI and reduced T1 entropy independent of tumour inclusion. (orig.)

Assessment of tumor heterogeneity by CT texture analysis: Can the largest cross-sectional area be used as an alternative to whole tumor analysis?

International Nuclear Information System (INIS)

Ng, Francesca; Kozarski, Robert; Ganeshan, Balaji; Goh, Vicky

2013-01-01

Objective: To determine if there is a difference between contrast enhanced CT texture features from the largest cross-sectional area versus the whole tumor, and its effect on clinical outcome prediction. Methods: Entropy (E) and uniformity (U) were derived for different filter values (1.0–2.5: fine to coarse textures) for the largest primary tumor cross-sectional area and the whole tumor of the staging contrast enhanced CT in 55 patients with primary colorectal cancer. Parameters were compared using non-parametric Wilcoxon test. Kaplan–Meier analysis was performed to determine the relationship between CT texture and 5-year overall survival. Results: E was higher and U lower for the whole tumor indicating greater heterogeneity at all filter levels (1.0–2.5): median (range) for E and U for whole tumor versus largest cross-sectional area of 7.89 (7.43–8.31) versus 7.62 (6.94–8.08) and 0.005 (0.004–0.01) versus 0.006 (0.005–0.01) for filter 1.0; 7.88 (7.22–8.48) versus 7.54 (6.86–8.1) and 0.005 (0.003–0.01) versus 0.007 (0.004–0.01) for filter 1.5; 7.88 (7.17–8.54) versus 7.48 (5.84–8.25) and 0.005 (0.003–0.01) versus 0.007 (0.004–0.02) for filter 2.0; and 7.83 (7.03–8.57) versus 7.42 (5.19–8.26) and 0.005 (0.003–0.01) versus 0.006 (0.004–0.03) for filter 2.5 respectively (p ≤ 0.001). Kaplan–Meier analysis demonstrated better separation of E and U for whole tumor analysis for 5-year overall survival. Conclusion: Whole tumor analysis appears more representative of tumor heterogeneity

Epitaxial hexagonal materials on IBAD-textured substrates

Energy Technology Data Exchange (ETDEWEB)

Matias, Vladimir; Yung, Christopher

2017-08-15

A multilayer structure including a hexagonal epitaxial layer, such as GaN or other group III-nitride (III-N) semiconductors, a <111> oriented textured layer, and a non-single crystal substrate, and methods for making the same. The textured layer has a crystalline alignment preferably formed by the ion-beam assisted deposition (IBAD) texturing process and can be biaxially aligned. The in-plane crystalline texture of the textured layer is sufficiently low to allow growth of high quality hexagonal material, but can still be significantly greater than the required in-plane crystalline texture of the hexagonal material. The IBAD process enables low-cost, large-area, flexible metal foil substrates to be used as potential alternatives to single-crystal sapphire and silicon for manufacture of electronic devices, enabling scaled-up roll-to-roll, sheet-to-sheet, or similar fabrication processes to be used. The user is able to choose a substrate for its mechanical and thermal properties, such as how well its coefficient of thermal expansion matches that of the hexagonal epitaxial layer, while choosing a textured layer that more closely lattice matches that layer.

PREFACE: 17th International Conference on Textures of Materials (ICOTOM 17)

Science.gov (United States)

Skrotzki, Werner; Oertel, Carl-Georg

2015-04-01

The 17th International Conference on Textures of Materials (ICOTOM 17) took place in Dresden, Germany, August 24-29, 2014. It belongs to the "triennial" series of ICOTOM meetings with a long tradition, starting in 1969 - Clausthal, 1971 - Cracow, 1973 - Pont-à-Mousson, 1975 - Cambridge, 1978 - Aachen, 1981 - Tokyo, 1984 - Noordwijkerhout, 1987 - Santa Fe, 1990 - Avignon, 1993 - Clausthal, 1996 - Xian, 1999 - Montreal, 2002 - Seoul, 2005 - Leuven, 2008 - Pittsburgh, 2011 - Mumbai, 2014 - Dresden. ICOTOM 17 was hosted by the Dresden University of Technology, Institute of Structural Physics. Following the tradition of the ICOTOM conferences, the main focus of ICOTOM-17 was to promote and strengthen the fundamental understanding of the basic processes that govern the formation of texture and its relation to the properties of polycrystalline materials. Nonetheless, it was the aim to forge links between basic research on model materials and applied research on engineering materials of technical importance. Thus, ICOTOM 17 provided a forum for the presentation and discussion of recent progress in research of texture and related anisotropy of mechanical and functional properties of all kinds of polycrystalline materials including natural materials like rocks. Particular attention was paid to recent advances in texture measurement and analysis as well as modeling of texture development for all kinds of processes like solidification, plastic deformation, recrystallization and grain growth, phase transformations, thin film deposition, etc. Hence, ICOTOM 17 was of great interest to materials scientists, engineers from many different areas and geoscientists. The topics covered by ICOTOM 17 were: 1. Mathematical, numerical and statistical methods of texture analysis 2. Deformation textures 3. Crystallization, recrystallization and growth textures 4. Transformation textures 5. Textures in functional materials 6. Textures in advanced materials 7. Textures in rocks 8. Texture

Pure Surface Texture Mapping Technology and it's Application for Mirror Image

Directory of Open Access Journals (Sweden)

Wei Feng Wang

2013-02-01

Full Text Available Based on the study of pure surface texture mapping technology, pure texture surface rendering method is proposed. The method is combined pure surface texture rendering and view mirror, real-time rendering has an index of refraction, reflection, and the flow of water ripple effect. Through the experimental verification of the validity of the algorithm.

New tools to investigate textures of pyroclastic deposits

Energy Technology Data Exchange (ETDEWEB)

Sarocchi, Damiano [Instituto de GeologIa / Fac. IngenierIa UASLP, Dr. M. Nava No 5, Zona Universitaria 78240, San Luis PotosI (Mexico); Borselli, Lorenzo [Istituto di Ricerca per la Protezione Idrogeologica, Consiglio Nazionale delle Ricerche, Via Madonna del Piano 10, 50019, Sesto Fiorentino (Italy); MacIas, Jose Luis [Departamento de VulcanologIa, Instituto de Geofisica, Universidad Nacional Autonoma de Mexico, Coyoacan 04510, D.F. (Mexico)

2008-10-01

A pyroclastic flow deposit keeps a fingerprint of the physical processes that occurred in the flow during transport and settling. Part of this information is recorded in the texture of the deposit offering an instantaneous view of the flow prior to freezing. In this work we introduce some texture's analysis techniques, based on image analysis, that we have developed or tuned during the last years.

Soil texture derived from topography in North-eastern Amazonia

OpenAIRE

Laurent, François; Poccard-Chapuis, René; Plassin, Sophie; Pimentel Martinez, Gustavo

2017-01-01

We present a 1:100,000 scale soil texture map of Paragominas county (Pará, Brazil), covering 19,330 km2. The method allows rapid production of a soil texture map of a large area where the strength of a duricrust controls the relief. It is based on an easily accessible explanatory variable, topography, which is represented using a Digital Elevation Model. The method makes it possible to map the spatial distribution of the texture of the topsoil layer. Modelling was complemented by field observ...

Study on tribological properties of multi-layer surface texture on Babbitt alloys surface

Science.gov (United States)

Zhang, Dongya; Zhao, Feifei; Li, Yan; Li, Pengyang; Zeng, Qunfeng; Dong, Guangneng

2016-12-01

To improve tribological properties of Babbitt alloys, multi-layer surface texture consisted of the main grooves and secondary micro-dimples are fabricated on the Babbitt substrate through laser pulse ablation. The tribological behaviors of multi-layer surface texture are investigated using a rotating type pin-on-disc tribo-meter under variation sliding speeds, and the film pressure distributions on the textured surfaces are simulated using computational fluid dynamics (CFD) method for elucidating the possible mechanisms. The results suggest that: (i) the multi-layer surface texture can reduce friction coefficient of Babbitt alloy, which has lowest friction coefficient of 0.03, in case of the groove parameter of 300 μm width and 15% of area density; (ii) the improvement effect may be more sensitive to the groove area density and the siding speed, and the textured surface with lower area density has lower friction coefficient under high sliding speed. Based on the reasons of (i) the secondary micro-dimples on Babbitt alloy possesses a hydrophobicity surface and (ii) the CFD analysis indicates that main grooves enhancing hydrodynamic effect, thus the multi-layer surface texture is regarded as dramatically improve the lubricating properties of the Babbitt alloy.

On-line transmission electron microscopic image analysis of chromatin texture for differentiation of thyroid gland tumors.

Science.gov (United States)

Kriete, A; Schäffer, R; Harms, H; Aus, H M

1987-06-01

Nuclei of the cells from the thyroid gland were analyzed in a transmission electron microscope by direct TV scanning and on-line image processing. The method uses the advantages of a visual-perception model to detect structures in noisy and low-contrast images. The features analyzed include area, a form factor and texture parameters from the second derivative stage. Three tumor-free thyroid tissues, three follicular adenomas, three follicular carcinomas and three papillary carcinomas were studied. The computer-aided cytophotometric method showed that the most significant differences were the statistics of the chromatin texture features of homogeneity and regularity. These findings document the possibility of an automated differentiation of tumors at the ultrastructural level.

M-HinTS: Mimicking Humans in Texture Sorting

NARCIS (Netherlands)

van den Broek, Egon; Rogowitz, Bernice E.; van Rikxoort, Eva M.; Pappas, Thrasyvoulos N.; Kok, Thijs; Daly, Scott J.; Schouten, Theo E.

2006-01-01

Various texture analysis algorithms have been developed the last decades. However, no computational model has arisen that mimics human texture perception adequately. In 2000, Payne, Hepplewhite, and Stoneham and in 2005, Van Rikxoort, Van den Broek, and Schouten achieved mappings between humans and

Dental microwear textures: reconstructing diets of fossil mammals

International Nuclear Information System (INIS)

DeSantis, Larisa R G

2016-01-01

Dietary information of fossil mammals can be revealed via the analysis of tooth morphology, tooth wear, tooth geochemistry, and the microscopic wear patterns on tooth surfaces resulting from food processing. Although dental microwear has long been used by anthropologists and paleontologists to clarify diets in a diversity of mammals, until recently these methods focused on the counting of wear features (e.g., pits and scratches) from two-dimensional surfaces (typically via scanning electron microscopes or low-magnification light microscopes). The analysis of dental microwear textures can instead reveal dietary information in a broad range of herbivorous, omnivorous, and carnivorous mammals by characterizing microscopic tooth surfaces in three-dimensions, without the counting of individual surface features. To date, dental microwear textures in ungulates, xenarthrans, marsupials, carnivorans, and primates (including humans and their ancestors) are correlated with known dietary behavior in extant taxa and reconstruct ancient diets in a diversity of prehistoric mammals. For example, tough versus hard object feeding can be characterized across disparate phylogenetic groups and can distinguish grazers, folivorous, and flesh consumers (tougher food consumers) from woody browsers, frugivores, and bone consumers (harder object feeders). This paper reviews how dental microwear textures can be useful to reconstructing diets in a broad array of living and extinct mammals, with commentary on areas of future research. (topical review)

Some distinguishing characteristics of contour and texture phenomena in images

Science.gov (United States)

Jobson, Daniel J.

1992-01-01

The development of generalized contour/texture discrimination techniques is a central element necessary for machine vision recognition and interpretation of arbitrary images. Here, the visual perception of texture, selected studies of texture analysis in machine vision, and diverse small samples of contour and texture are all used to provide insights into the fundamental characteristics of contour and texture. From these, an experimental discrimination scheme is developed and tested on a battery of natural images. The visual perception of texture defined fine texture as a subclass which is interpreted as shading and is distinct from coarse figural similarity textures. Also, perception defined the smallest scale for contour/texture discrimination as eight to nine visual acuity units. Three contour/texture discrimination parameters were found to be moderately successful for this scale discrimination: (1) lightness change in a blurred version of the image, (2) change in lightness change in the original image, and (3) percent change in edge counts relative to local maximum.

Tensile properties of cooked meat sausages and their correlation with texture profile analysis (TPA) parameters and physico-chemical characteristics.

Science.gov (United States)

Herrero, A M; de la Hoz, L; Ordóñez, J A; Herranz, B; Romero de Ávila, M D; Cambero, M I

2008-11-01

The possibilities of using breaking strength (BS) and energy to fracture (EF) for monitoring textural properties of some cooked meat sausages (chopped, mortadella and galantines) were studied. Texture profile analysis (TPA), folding test and physico-chemical measurements were also performed. Principal component analysis enabled these meat products to be grouped into three textural profiles which showed significant (p<0.05) differences mainly for BS, hardness, adhesiveness and cohesiveness. Multivariate analysis indicated that BS, EF and TPA parameters were correlated (p<0.05) for every individual meat product (chopped, mortadella and galantines) and all products together. On the basis of these results, TPA parameters could be used for constructing regression models to predict BS. The resulting regression model for all cooked meat products was BS=-0.160+6.600∗cohesiveness-1.255∗adhesiveness+0.048∗hardness-506.31∗springiness (R(2)=0.745, p<0.00005). Simple linear regression analysis showed significant coefficients of determination between BS (R(2)=0.586, p<0.0001) versus folding test grade (FG) and EF versus FG (R(2)=0.564, p<0.0001).

Laws' masks descriptors applied to bone texture analysis: an innovative and discriminant tool in osteoporosis

International Nuclear Information System (INIS)

Rachidi, M.; Marchadier, A.; Gadois, C.; Lespessailles, E.; Chappard, C.; Benhamou, C.L.

2008-01-01

The objective of this study was to explore Laws' masks analysis to describe structural variations of trabecular bone due to osteoporosis on high-resolution digital radiographs and to check its dependence on the spatial resolution. Laws' masks are well established as one of the best methods for texture analysis in image processing and are used in various applications, but not in bone tissue characterisation. This method is based on masks that aim to filter the images. From each mask, five classical statistical parameters can be calculated. The study was performed on 182 healthy postmenopausal women with no fractures and 114 age-matched women with fractures [26 hip fractures (HFs), 29 vertebrae fractures (VFs), 29 wrist fractures (WFs) and 30 other fractures (OFs)]. For all subjects radiographs were obtained of the calcaneus with a new high-resolution X-ray device with direct digitisation (BMA, D3A, France). The lumbar spine, femoral neck, and total hip bone mineral density (BMD) were assessed by dual-energy X-ray absorptiometry. In terms of reproducibility, the best results were obtained with the TR E5E5 mask, especially for three parameters: ''mean'', ''standard deviation'' and ''entropy'' with, respectively, in vivo mid-term root mean square average coefficient of variation (RMSCV)%=1.79, 4.24 and 2.05. The ''mean'' and ''entropy'' parameters had a better reproducibility but ''standard deviation'' showed a better discriminant power. Thus, for univariate analysis, the difference between subjects with fractures and controls was significant (P -3 ) and significant for each fracture group independently (P -4 for HF, P=0.025 for VF and P -3 for OF). After multivariate analysis with adjustment for age and total hip BMD, the difference concerning the ''standard deviation'' parameter remained statistically significant between the control group and the HF and VF groups (P -5 , and P=0.04, respectively). No significant correlation between these Laws' masks parameters and

Comparing predictive ability of Laser-Induced Breakdown Spectroscopy to Near Infrared Spectroscopy for soil texture and organic carbon determination

DEFF Research Database (Denmark)

Knadel, Maria; Peng, Yi; Gislum, René

Soil organic carbon (SOC) and texture have a practical value for agronomy and the environment. Thus, alternative techniques to supplement or substitute for the expensive conventional analysis of soil are developed. Here the feasibility of laser-induced breakdown spectroscopy (LIBS) to determine SOC...... and texture was tested and compared with near infrared spectroscopy (NIRS) technique and traditional laboratory analysis. Calibration models were developed on 50 topsoil samples. For all properties except silt, higher predictive ability of LIBS than NIRS models was obtained. Successful calibrations indicate...... that LIBS can be used as a fast and reliable method for SOC and texture estimation....

Method for producing textured substrates for thin-film photovoltaic cells

Science.gov (United States)

Lauf, Robert J.

1994-01-01

The invention pertains to the production of ceramic substrates used in the manufacture of thin-film photovoltaic cells used for directly converting solar energy to electrical energy. Elongated ribbon-like sheets of substrate precursor containing a mixture of ceramic particulates, a binder, and a plasticizer are formed and then while green provided with a mechanically textured surface region used for supporting the thin film semiconductor of the photovoltaic cell when the sheets of the substrate precursor are subsequently cut into substrate-sized shapes and then sintered. The textured surface pattern on the substrate provides enhanced light trapping and collection for substantially increasing the solar energy conversion efficiency of thin-film photovoltaic cells.

Through-process modelling of texture and anisotropy in AA5182

Science.gov (United States)

Crumbach, M.; Neumann, L.; Goerdeler, M.; Aretz, H.; Gottstein, G.; Kopp, R.

2006-07-01

A through-process texture and anisotropy prediction for AA5182 sheet production from hot rolling through cold rolling and annealing is reported. Thermo-mechanical process data predicted by the finite element method (FEM) package T-Pack based on the software LARSTRAN were fed into a combination of physics based microstructure models for deformation texture (GIA), work hardening (3IVM), nucleation texture (ReNuc), and recrystallization texture (StaRT). The final simulated sheet texture was fed into a FEM simulation of cup drawing employing a new concept of interactively updated texture based yield locus predictions. The modelling results of texture development and anisotropy were compared to experimental data. The applicability to other alloys and processes is discussed.

Textural features of the beach sediments of Wast Water Lake, Northwest England

Directory of Open Access Journals (Sweden)

Bala Emilia

2016-06-01

Full Text Available This study is dedicated to Wast Water Lake (Northwest England, Great Britain and the character of its beach sediments. The aim of the study is to identify the textural features of the lake’s beach sediments based on two methods. The first is a granulometric analysis and the second a pebble shape analysis according to Zingg (1935 and Sneed & Folk (1958. Both analyses were carried out for all of the lake’s accessible beaches and the cliffs adjacent to them. The transport and deposition history of the examined sediments was identified through field research and laboratory analysis. The results show that the textural features of the sediments at Wast Water are more often typical of a fluvial environment, rather than having been changed by lacustrine water movements.

Quantitative Evaluation of Trabecular Bone Structure by Calcaneus MR Images Texture Analysis of Healthy Volunteers and Osteoporotic Subjects

National Research Council Canada - National Science Library

Herlidou, S

2001-01-01

...), Texture analysis is not used very, frequently since the interpretation of the large number of calculated parameters is difficult, We here apply multiparametric data analyses such as Correspondence Factorial Analysis (CFA...

Clustering document fragments using background color and texture information

Science.gov (United States)

Chanda, Sukalpa; Franke, Katrin; Pal, Umapada

2012-01-01

Forensic analysis of questioned documents sometimes can be extensively data intensive. A forensic expert might need to analyze a heap of document fragments and in such cases to ensure reliability he/she should focus only on relevant evidences hidden in those document fragments. Relevant document retrieval needs finding of similar document fragments. One notion of obtaining such similar documents could be by using document fragment's physical characteristics like color, texture, etc. In this article we propose an automatic scheme to retrieve similar document fragments based on visual appearance of document paper and texture. Multispectral color characteristics using biologically inspired color differentiation techniques are implemented here. This is done by projecting document color characteristics to Lab color space. Gabor filter-based texture analysis is used to identify document texture. It is desired that document fragments from same source will have similar color and texture. For clustering similar document fragments of our test dataset we use a Self Organizing Map (SOM) of dimension 5×5, where the document color and texture information are used as features. We obtained an encouraging accuracy of 97.17% from 1063 test images.

Subacute and Chronic Left Ventricular Myocardial Scar: Accuracy of Texture Analysis on Nonenhanced Cine MR Images.

Science.gov (United States)

Baessler, Bettina; Mannil, Manoj; Oebel, Sabrina; Maintz, David; Alkadhi, Hatem; Manka, Robert

2018-01-01

Purpose To test whether texture analysis (TA) allows for the diagnosis of subacute and chronic myocardial infarction (MI) on noncontrast material-enhanced cine cardiac magnetic resonance (MR) images. Materials and Methods In this retrospective, institutional review board-approved study, 120 patients who underwent cardiac MR imaging and showed large transmural (volume of enhancement on late gadolinium enhancement [LGE] images >20%, n = 72) or small (enhanced volume ≤20%, n = 48) subacute or chronic ischemic scars were included. Sixty patients with normal cardiac MR imaging findings served as control subjects. Regions of interest for TA encompassing the left ventricle were drawn by two blinded, independent readers on cine images in end systole by using a freely available software package. Stepwise dimension reduction and texture feature selection based on reproducibility, machine learning, and correlation analyses were performed for selecting features, enabling the diagnosis of MI on nonenhanced cine MR images by using LGE imaging as the standard of reference. Results Five independent texture features allowed for differentiation between ischemic scar and normal myocardium on cine MR images in both subgroups: Teta1, Perc.01, Variance, WavEnHH.s-3, and S(5,5)SumEntrp (in patients with large MI: all P values cine MR images, with an area under the curve of 0.93 and 0.92, respectively. Conclusion This proof-of-concept study indicates that TA of nonenhanced cine MR images allows for the diagnosis of subacute and chronic MI with high accuracy. © RSNA, 2017 Online supplemental material is available for this article.

Whole-lesion ADC histogram and texture analysis in predicting recurrence of cervical cancer treated with CCRT.

Science.gov (United States)

Meng, Jie; Zhu, Lijing; Zhu, Li; Xie, Li; Wang, Huanhuan; Liu, Song; Yan, Jing; Liu, Baorui; Guan, Yue; He, Jian; Ge, Yun; Zhou, Zhengyang; Yang, Xiaofeng

2017-11-03

To explore the value of whole-lesion apparent diffusion coefficient (ADC) histogram and texture analysis in predicting tumor recurrence of advanced cervical cancer treated with concurrent chemo-radiotherapy (CCRT). 36 women with pathologically confirmed advanced cervical squamous carcinomas were enrolled in this prospective study. 3.0 T pelvic MR examinations including diffusion weighted imaging (b = 0, 800 s/mm 2 ) were performed before CCRT (pre-CCRT) and at the end of 2nd week of CCRT (mid-CCRT). ADC histogram and texture features were derived from the whole volume of cervical cancers. With a mean follow-up of 25 months (range, 11 ∼ 43), 10/36 (27.8%) patients ended with recurrence. Pre-CCRT 75th, 90th, correlation, autocorrelation and mid-CCRT ADC mean , 10th, 25th, 50th, 75th, 90th, autocorrelation can effectively differentiate the recurrence from nonrecurrence group with area under the curve ranging from 0.742 to 0.850 (P values range, 0.001 ∼ 0.038). Pre- and mid-treatment whole-lesion ADC histogram and texture analysis hold great potential in predicting tumor recurrence of advanced cervical cancer treated with CCRT.

Quantitative radiomics: impact of stochastic effects on textural feature analysis implies the need for standards.

Science.gov (United States)

Nyflot, Matthew J; Yang, Fei; Byrd, Darrin; Bowen, Stephen R; Sandison, George A; Kinahan, Paul E

2015-10-01

Image heterogeneity metrics such as textural features are an active area of research for evaluating clinical outcomes with positron emission tomography (PET) imaging and other modalities. However, the effects of stochastic image acquisition noise on these metrics are poorly understood. We performed a simulation study by generating 50 statistically independent PET images of the NEMA IQ phantom with realistic noise and resolution properties. Heterogeneity metrics based on gray-level intensity histograms, co-occurrence matrices, neighborhood difference matrices, and zone size matrices were evaluated within regions of interest surrounding the lesions. The impact of stochastic variability was evaluated with percent difference from the mean of the 50 realizations, coefficient of variation and estimated sample size for clinical trials. Additionally, sensitivity studies were performed to simulate the effects of patient size and image reconstruction method on the quantitative performance of these metrics. Complex trends in variability were revealed as a function of textural feature, lesion size, patient size, and reconstruction parameters. In conclusion, the sensitivity of PET textural features to normal stochastic image variation and imaging parameters can be large and is feature-dependent. Standards are needed to ensure that prospective studies that incorporate textural features are properly designed to measure true effects that may impact clinical outcomes.

A fully-automated software pipeline for integrating breast density and parenchymal texture analysis for digital mammograms: parameter optimization in a case-control breast cancer risk assessment study

Science.gov (United States)

Zheng, Yuanjie; Wang, Yan; Keller, Brad M.; Conant, Emily; Gee, James C.; Kontos, Despina

2013-02-01

Estimating a woman's risk of breast cancer is becoming increasingly important in clinical practice. Mammographic density, estimated as the percent of dense (PD) tissue area within the breast, has been shown to be a strong risk factor. Studies also support a relationship between mammographic texture and breast cancer risk. We have developed a fullyautomated software pipeline for computerized analysis of digital mammography parenchymal patterns by quantitatively measuring both breast density and texture properties. Our pipeline combines advanced computer algorithms of pattern recognition, computer vision, and machine learning and offers a standardized tool for breast cancer risk assessment studies. Different from many existing methods performing parenchymal texture analysis within specific breast subregions, our pipeline extracts texture descriptors for points on a spatial regular lattice and from a surrounding window of each lattice point, to characterize the local mammographic appearance throughout the whole breast. To demonstrate the utility of our pipeline, and optimize its parameters, we perform a case-control study by retrospectively analyzing a total of 472 digital mammography studies. Specifically, we investigate the window size, which is a lattice related parameter, and compare the performance of texture features to that of breast PD in classifying case-control status. Our results suggest that different window sizes may be optimal for raw (12.7mm2) versus vendor post-processed images (6.3mm2). We also show that the combination of PD and texture features outperforms PD alone. The improvement is significant (p=0.03) when raw images and window size of 12.7mm2 are used, having an ROC AUC of 0.66. The combination of PD and our texture features computed from post-processed images with a window size of 6.3 mm2 achieves an ROC AUC of 0.75.

Slice simulation from a model of the parenchymous vascularization to evaluate texture features: work in progress.

Science.gov (United States)

Rolland, Y; Bézy-Wendling, J; Duvauferrier, R; Coatrieux, J L

1999-03-01

To demonstrate the usefulness of a model of the parenchymous vascularization to evaluate texture analysis methods. Slices with thickness varying from 1 to 4 mm were reformatted from a 3D vascular model corresponding to either normal tissue perfusion or local hypervascularization. Parameters of statistical methods were measured on 16128x128 regions of interest, and mean values and standard deviation were calculated. For each parameter, the performances (discrimination power and stability) were evaluated. Among 11 calculated statistical parameters, three (homogeneity, entropy, mean of gradients) were found to have a good discriminating power to differentiate normal perfusion from hypervascularization, but only the gradient mean was found to have a good stability with respect to the thickness. Five parameters (run percentage, run length distribution, long run emphasis, contrast, and gray level distribution) were found to have intermediate results. In the remaining three, curtosis and correlation was found to have little discrimination power, skewness none. This 3D vascular model, which allows the generation of various examples of vascular textures, is a powerful tool to assess the performance of texture analysis methods. This improves our knowledge of the methods and should contribute to their a priori choice when designing clinical studies.

Surface Textural Analysis of Quartz Grains from Modern Point Bar Deposits in Lower Reaches of the Yellow River

Science.gov (United States)

Cheng, Yong; Liu, Cong; Lu, Ping; Zhang, Yu; Nie, Qi; Wen, Yiming

2018-01-01

The surfaces of quartz grains contain characteristic textures formed during the process of transport, due to their stable physical and chemical properties. The surface textures include the information about source area, transporting force, sedimentary environment and evolution history of sediment. Surface textures of quartz grains from modern point bar deposits in the lower reaches of the Yellow River are observed and studied by scanning electron microscopy (SEM). Results indicate that there are 22 kinds of surface textures. The overall surface morphology of quartz grains shows short transporting time and distance and weak abrasive action of the river water. The combined surface textures caused by mechanical action indicate that quartz grains are transporting in a high-energy hydrodynamic condition and suffer a strong mechanical impact and abrasion. The common solution pits prove that the chemical property of transportation medium is very active and quartz grains receive an obvious chemical action. The combination of these surface textures can be an identification mark of fluvial environment, and that is: quartz grains are main subangular outline, whose roundness is higher with the farther motion distance; Surface fluctuation degree of quartz grains is relatively high, and gives priority to high and medium relief; V-shaped percussion marks are very abundant caused by mechanical action; The conchoidal of different sizes and steps are common-developed with paragenesis relationship; Solution pits are common-developed as well. The study makes up for the blank of surface textures analysis of quartz grains from modern fluvial deposits in China. It provides new ideas and evidence for studies of the sedimentary process and environmental significance, although the deep meanings of these micro textures remain to be further researched.

SU-D-BRA-06: Dual-Energy Chest CT: The Effects of Virtual Monochromatic Reconstructions On Texture Analysis Features

International Nuclear Information System (INIS)

Sorensen, J; Duran, C; Stingo, F; Wei, W; Rao, A; Zhang, L; Court, L; Erasmus, J; Godoy, M

2015-01-01

Purpose: To characterize the effect of virtual monochromatic reconstructions on several commonly used texture analysis features in DECT of the chest. Further, to assess the effect of monochromatic energy levels on the ability of these textural features to identify tissue types. Methods: 20 consecutive patients underwent chest CTs for evaluation of lung nodules using Siemens Somatom Definition Flash DECT. Virtual monochromatic images were constructed at 10keV intervals from 40–190keV. For each patient, an ROI delineated the lesion under investigation, and cylindrical ROI’s were placed within 5 different healthy tissues (blood, fat, muscle, lung, and liver). Several histogram- and Grey Level Cooccurrence Matrix (GLCM)-based texture features were then evaluated in each ROI at each energy level. As a means of validation, these feature values were then used in a random forest classifier to attempt to identify the tissue types present within each ROI. Their predictive accuracy at each energy level was recorded. Results: All textural features changed considerably with virtual monochromatic energy, particularly below 70keV. Most features exhibited a global minimum or maximum around 80keV, and while feature values changed with energy above this, patient ranking was generally unaffected. As expected, blood demonstrated the lowest inter-patient variability, for all features, while lung lesions (encompassing many different pathologies) exhibited the highest. The accuracy of these features in identifying tissues (76% accuracy) was highest at 80keV, but no clear relationship between energy and classification accuracy was found. Two common misclassifications (blood vs liver and muscle vs fat) accounted for the majority (24 of the 28) errors observed. Conclusion: All textural features were highly dependent on virtual monochromatic energy level, especially below 80keV, and were more stable above this energy. However, in a random forest model, these commonly used features were

SU-D-BRA-06: Dual-Energy Chest CT: The Effects of Virtual Monochromatic Reconstructions On Texture Analysis Features

Energy Technology Data Exchange (ETDEWEB)

Sorensen, J; Duran, C; Stingo, F; Wei, W; Rao, A; Zhang, L; Court, L; Erasmus, J; Godoy, M [UT MD Anderson Cancer Center, Houston, TX (United States)

2015-06-15

Purpose: To characterize the effect of virtual monochromatic reconstructions on several commonly used texture analysis features in DECT of the chest. Further, to assess the effect of monochromatic energy levels on the ability of these textural features to identify tissue types. Methods: 20 consecutive patients underwent chest CTs for evaluation of lung nodules using Siemens Somatom Definition Flash DECT. Virtual monochromatic images were constructed at 10keV intervals from 40–190keV. For each patient, an ROI delineated the lesion under investigation, and cylindrical ROI’s were placed within 5 different healthy tissues (blood, fat, muscle, lung, and liver). Several histogram- and Grey Level Cooccurrence Matrix (GLCM)-based texture features were then evaluated in each ROI at each energy level. As a means of validation, these feature values were then used in a random forest classifier to attempt to identify the tissue types present within each ROI. Their predictive accuracy at each energy level was recorded. Results: All textural features changed considerably with virtual monochromatic energy, particularly below 70keV. Most features exhibited a global minimum or maximum around 80keV, and while feature values changed with energy above this, patient ranking was generally unaffected. As expected, blood demonstrated the lowest inter-patient variability, for all features, while lung lesions (encompassing many different pathologies) exhibited the highest. The accuracy of these features in identifying tissues (76% accuracy) was highest at 80keV, but no clear relationship between energy and classification accuracy was found. Two common misclassifications (blood vs liver and muscle vs fat) accounted for the majority (24 of the 28) errors observed. Conclusion: All textural features were highly dependent on virtual monochromatic energy level, especially below 80keV, and were more stable above this energy. However, in a random forest model, these commonly used features were

Relating microstructure, sensory and instrumental texture of processed oat

Directory of Open Access Journals (Sweden)

M. SALMENKALLIO-MARTTILA

2008-12-01

Full Text Available This study is a part of a larger project aiming to produce new, healthy, and tasty food ingredients from oat. Germination and different heating processes can be used to improve the texture and flavour of cereals. In this study effects of germination and wet and dry heating on the microstructure, instrumental structure and sensory properties of two oat varieties were assessed. The microstructure of native, germinated, autoclaved and extruded grains of the hulled cv. Veli and hull-less cv. Lisbeth was examined by light microscopy, the texture was measured by determining the milling energy and hardness of the grains and sensory characteristics were evaluated with descriptive sensory profile analysis. In cv. Veli the cells of the starchy endosperm were smaller than in cv. Lisbeth and ß-glucan was concentrated in the subaleurone layer. In cv. Lisbeth ß-glucan was evenly distributed in the starchy endosperm. The grains of cv. Lisbeth were more extensively modified in the germination process than the grains of cv. Veli, otherwise the effects of processing on the grains of the two cultivars were similar. Germination caused cell wall degradation, autoclaving and extrusion cooking caused starch gelatinization. Autoclaving resulted in the hardest perceived texture in oat. Gelatinization of starch appeared to contribute more to the hardness of oat groats than the cell wall structure. Of the instrumental methods used in this study the milling energy measurement appeared to be the most useful method for the analysis of the effects of processing on grain structure.;

TEXTURAL, FLOW AND SENSORY PROPERTIES OF FIVE “FRUZELINA” WITH SOUR CHERRIES

Directory of Open Access Journals (Sweden)

Irena Bojdo Tomasiak

2010-05-01

Full Text Available Gel with sour cherries called “Fruzelina” is a new product in the Polish market widely used in food industry as a decorative element or filling for pastries, as an ingredient in fruit desserts, as an additive to ice creams, whipped cream and waffles. The cherry gels are the product prepared using different types of chemically modified starches. Starch is an additive used to ensure rich and short texture and high viscosity of “Fruzelina”. Food texture and viscosity may be measured by senses and instrumentally. Because of fact that sensory analysis is time consuming and very costly, it is easier and cheaper to determine food properties, especially their texture and flow behaviour by appropriate mechanical tests. The aim of this work was to study the rheological behavior of five cherry gels and evaluate the correlation between textural, flow and sensory properties of these gels measured instrumentally and by human senses. The back extrusion test has been found to be applicable to study the textural properties of cherry gels. There was high positive correlation between gel texture measured by senses and texture parameters measured in back extrusion test. Similar high correlation was identified for consistency coefficient K obtained in Ostwald de Waele model and gel texture assessed by sensory panel. It was found that values of sensory parameters such as taste and odour decreased as the rheological parameters increased. High negative correlations were observed in these cases. Therefore, instrumental measurements can be alternative for more expensive sensory methods. doi:10.5219/53

Investigation of magnetic resonance imaging texture analysis as an aid tool for characterization of refractory epilepsies

Directory of Open Access Journals (Sweden)

Mauricio Martins Baldissin

2013-12-01

Full Text Available Refractory epilepsies are syndromes for which therapies that employ two or more antiepileptic drugs, separately or in association, do not result in control of crisis. Patients may present focal cortical dysplasia or diffuse dysplasia and/or hippocampal atrophic alterations that may not be detectable by a simple visual analysis in magnetic resonance imaging. The aim of this study was to evaluate MRI texture in regions of interest located in the hippocampi, limbic association cortex and prefrontal cortex of 20 patients with refractory epilepsy and to compare them with the same areas in 20 healthy individuals, in order to find out if the texture parameters could be related to the presence of the disease. Of the 11 texture parameters calculated, three indicated the existence of statistically significant differences between the studied groups. Such findings suggest the possibility of this technique contributing to studies of refractory epilepsies.

Texture-based analysis of 100 MR examinations of head and neck tumors. Is it possible to discriminate between benign and malignant masses in a multicenter trial?

International Nuclear Information System (INIS)

Fruehwald-Pallamar, J.; Czerny, C.; Hesselink, J.R.; Mafee, M.F.; Holzer-Fruehwald, L.; Mayerhoefer, M.E.

2016-01-01

To evaluate whether texture-based analysis of standard MRI sequences can help in the discrimination between benign and malignant head and neck tumors. The MR images of 100 patients with a histologically clarified head or neck mass, from two different institutions, were analyzed. Texture-based analysis was performed using texture analysis software, with region of interest measurements for 2D and 3D evaluation independently for all axial sequences. COC, RUN, GRA, ARM, and WAV features were calculated for all ROIs. 10 texture feature subsets were used for a linear discriminant analysis, in combination with k-nearest-neighbor classification. Benign and malignant tumors were compared with regard to texture-based values. There were differences in the images from different field-strength scanners, as well as from different vendors. For the differentiation of benign and malignant tumors, we found differences on STIR and T2-weighted images for 2D, and on contrast-enhanced T1-TSE with fat saturation for 3D evaluation. In a separate analysis of the subgroups 1.5 and 3 Tesla, more discriminating features were found. Texture-based analysis is a useful tool in the discrimination of benign and malignant tumors when performed on one scanner with the same protocol. We cannot recommend this technique for the use of multicenter studies with clinical data.

Texture-based analysis of 100 MR examinations of head and neck tumors. Is it possible to discriminate between benign and malignant masses in a multicenter trial?

Energy Technology Data Exchange (ETDEWEB)

Fruehwald-Pallamar, J.; Czerny, C. [Medical University of Vienna (Austria). Subdiv. of Neuroradiology and Musculoskeletal Radiology; Hesselink, J.R.; Mafee, M.F. [UCSD Medical Center, San Diego, CA (United States). Dept. of Radiology; Holzer-Fruehwald, L.; Mayerhoefer, M.E. [Medical University of Vienna (Austria). Dept. of Biomedical Imaging and Image-Guided Therapy

2016-02-15

To evaluate whether texture-based analysis of standard MRI sequences can help in the discrimination between benign and malignant head and neck tumors. The MR images of 100 patients with a histologically clarified head or neck mass, from two different institutions, were analyzed. Texture-based analysis was performed using texture analysis software, with region of interest measurements for 2D and 3D evaluation independently for all axial sequences. COC, RUN, GRA, ARM, and WAV features were calculated for all ROIs. 10 texture feature subsets were used for a linear discriminant analysis, in combination with k-nearest-neighbor classification. Benign and malignant tumors were compared with regard to texture-based values. There were differences in the images from different field-strength scanners, as well as from different vendors. For the differentiation of benign and malignant tumors, we found differences on STIR and T2-weighted images for 2D, and on contrast-enhanced T1-TSE with fat saturation for 3D evaluation. In a separate analysis of the subgroups 1.5 and 3 Tesla, more discriminating features were found. Texture-based analysis is a useful tool in the discrimination of benign and malignant tumors when performed on one scanner with the same protocol. We cannot recommend this technique for the use of multicenter studies with clinical data.

Machine learning-based quantitative texture analysis of CT images of small renal masses. Differentiation of angiomyolipoma without visible fat from renal cell carcinoma

International Nuclear Information System (INIS)

Feng, Zhichao; Rong, Pengfei; Zhou, Qingyu; Zhu, Wenwei; Yan, Zhimin; Liu, Qianyun; Wang, Wei; Cao, Peng

2018-01-01

To evaluate the diagnostic performance of machine-learning based quantitative texture analysis of CT images to differentiate small (≤ 4 cm) angiomyolipoma without visible fat (AMLwvf) from renal cell carcinoma (RCC). This single-institutional retrospective study included 58 patients with pathologically proven small renal mass (17 in AMLwvf and 41 in RCC groups). Texture features were extracted from the largest possible tumorous regions of interest (ROIs) by manual segmentation in preoperative three-phase CT images. Interobserver reliability and the Mann-Whitney U test were applied to select features preliminarily. Then support vector machine with recursive feature elimination (SVM-RFE) and synthetic minority oversampling technique (SMOTE) were adopted to establish discriminative classifiers, and the performance of classifiers was assessed. Of the 42 extracted features, 16 candidate features showed significant intergroup differences (P < 0.05) and had good interobserver agreement. An optimal feature subset including 11 features was further selected by the SVM-RFE method. The SVM-RFE+SMOTE classifier achieved the best performance in discriminating between small AMLwvf and RCC, with the highest accuracy, sensitivity, specificity and AUC of 93.9 %, 87.8 %, 100 % and 0.955, respectively. Machine learning analysis of CT texture features can facilitate the accurate differentiation of small AMLwvf from RCC. (orig.)

Colour and texture associations in voice-induced synaesthesia

Directory of Open Access Journals (Sweden)

Anja eMoos

2013-09-01

Full Text Available Voice-induced synaesthesia, a form of synaesthesia in which synaesthetic perceptions are induced by the sounds of people’s voices, appears to be relatively rare and has not been systematically studied. In this study we investigated the synaesthetic colour and visual texture perceptions experienced in response to different types of voice quality (e.g. nasal, whisper, falsetto. Experiences of three different groups – self-reported voice synaesthetes, phoneticians and controls – were compared using both qualitative and quantitative analysis in a study conducted online. Whilst, in the qualitative analysis, synaesthetes used more colour and texture terms to describe voices than either phoneticians or controls, only weak differences, and many similarities, between groups were found in the quantitative analysis. Notable consistent results between groups were the matching of higher speech fundamental frequencies with lighter and redder colours, the matching of whispery voices with smoke-like textures and the matching of harsh and creaky voices with textures resembling dry cracked soil. These data are discussed in the light of current thinking about definitions and categorizations of synaesthesia, especially in cases where individuals apparently have a range of different synaesthetic inducers.

Color and texture associations in voice-induced synesthesia

Science.gov (United States)

Moos, Anja; Simmons, David; Simner, Julia; Smith, Rachel

2013-01-01

Voice-induced synesthesia, a form of synesthesia in which synesthetic perceptions are induced by the sounds of people's voices, appears to be relatively rare and has not been systematically studied. In this study we investigated the synesthetic color and visual texture perceptions experienced in response to different types of “voice quality” (e.g., nasal, whisper, falsetto). Experiences of three different groups—self-reported voice synesthetes, phoneticians, and controls—were compared using both qualitative and quantitative analysis in a study conducted online. Whilst, in the qualitative analysis, synesthetes used more color and texture terms to describe voices than either phoneticians or controls, only weak differences, and many similarities, between groups were found in the quantitative analysis. Notable consistent results between groups were the matching of higher speech fundamental frequencies with lighter and redder colors, the matching of “whispery” voices with smoke-like textures, and the matching of “harsh” and “creaky” voices with textures resembling dry cracked soil. These data are discussed in the light of current thinking about definitions and categorizations of synesthesia, especially in cases where individuals apparently have a range of different synesthetic inducers. PMID:24032023

Prediction of oral disintegration time of fast disintegrating tablets using texture analyzer and computational optimization.

Science.gov (United States)

Szakonyi, G; Zelkó, R

2013-05-20

One of the promising approaches to predict in vivo disintegration time of orally disintegrating tablets (ODT) is the use of texture analyzer instrument. Once the method is able to provide good in vitro in vivo correlation (IVIVC) in the case of different tablets, it might be able to predict the oral disintegration time of similar products. However, there are many tablet parameters that influence the in vivo and the in vitro disintegration time of ODT products. Therefore, the measured in vitro and in vivo disintegration times can occasionally differ, even if they coincide in most cases of the investigated products and the in vivo disintegration times may also change if the aimed patient group is suffering from a special illness. If the method is no longer able to provide good IVIVC, then the modification of a single instrumental parameter may not be successful and the in vitro method must be re-set in a complex manner in order to provide satisfactory results. In the present experiment, an optimization process was developed based on texture analysis measurements using five different tablets in order to predict their in vivo disintegration times, and the optimized texture analysis method was evaluated using independent tablets. Copyright © 2013 Elsevier B.V. All rights reserved.

X-ray elastic constants in textured Zr-base materials

International Nuclear Information System (INIS)

Ortiz, M.; Pochettino, A.A.; Lebrun, J.L.; Maeder, G.

1993-01-01

A general method for the calculation of the X-ray elastic constants (XREC) for textured hexagonal close-packed (hcp) materials was developed by using the orientation distribution function (ODF) and the Reuss hypothesis. This method was applied to textured zirconium (Zr) sheets and zircaloy 4 (Zry 4) extruded tubes. For these samples, where the elastic anisotropy is not very strong, an 'isotropic approximation' method is proposed using the ODF data. In that case, the classical XREC 1/2S 2 and S, values are calculated and experimentally verified for (10 bar 14) diffracting planes. Theoretical XREC values are also given for different (hkil) that could be chosen according to the experimental conditions, considering texture effects on diffracting peak intensities

Software phantom with realistic speckle modeling for validation of image analysis methods in echocardiography

Science.gov (United States)

Law, Yuen C.; Tenbrinck, Daniel; Jiang, Xiaoyi; Kuhlen, Torsten

2014-03-01

Computer-assisted processing and interpretation of medical ultrasound images is one of the most challenging tasks within image analysis. Physical phenomena in ultrasonographic images, e.g., the characteristic speckle noise and shadowing effects, make the majority of standard methods from image analysis non optimal. Furthermore, validation of adapted computer vision methods proves to be difficult due to missing ground truth information. There is no widely accepted software phantom in the community and existing software phantoms are not exible enough to support the use of specific speckle models for different tissue types, e.g., muscle and fat tissue. In this work we propose an anatomical software phantom with a realistic speckle pattern simulation to _ll this gap and provide a exible tool for validation purposes in medical ultrasound image analysis. We discuss the generation of speckle patterns and perform statistical analysis of the simulated textures to obtain quantitative measures of the realism and accuracy regarding the resulting textures.

Forward impact extrusion of surface textured steel blanks using coated tooling

Science.gov (United States)

Hild, Rafael; Feuerhack, Andreas; Trauth, Daniel; Arghavani, Mostafa; Kruppe, Nathan C.; Brögelmann, Tobias; Bobzin, Kirsten; Klocke, Fritz

2017-10-01

A method to enable dry metal forming by the means of a self-lubricating coating and surface textures was researched using an innovative Pin-On-Cylinder-Tribometer. The experimental analysis was complemented by a numerical model of the complex contact conditions between coated tools and the surface textured specimen at the micro-level. Based on the results, the explanation of the tribological interactions between surface textured specimens and the tool in dry full forward extrusion is the objective of this work. Therefore, experimental dry extrusion tests were performed using a tool system. The extruded specimens were evaluated regarding their geometry as well as by the required punch force. Thereby, the effectiveness and the feasibility of dry metal forming on the example of full forward extrusion was evaluated. Thus, one more step towards the technical realization of dry metal forming of low alloy steels under industrial conditions was realized.

Gender and age effects in structural brain asymmetry as measured by MRI texture analysis.

Science.gov (United States)

Kovalev, Vassili A; Kruggel, Frithjof; von Cramon, D Yves

2003-07-01

Effects of gender and age on structural brain asymmetry were studied by 3D texture analysis in 380 adults. Asymmetry is detected by comparing the complex 3D gray-scale image patterns in the left and right cerebral hemispheres as revealed by anatomical T1-weighted MRI datasets. The Talairach and Tournoux parcellation system was applied to study the asymmetry on five levels: the whole cerebrum, nine coronal sections, 12 axial sections, boxes resulting from both coronal and axial subdivisions, and by a sliding spherical window of 9 mm diameter. The analysis revealed that the brain asymmetry increases in the anterior-posterior direction starting from the central region onward. Male brains were found to be more asymmetric than female. This gender-related effect is noticeable in all brain areas but is most significant in the superior temporal gyrus, Heschl's gyrus, the adjacent white matter regions in the temporal stem and the knee of the optic radiation, the thalamus, and the posterior cingulate. The brain asymmetry increases significantly with age in the inferior frontal gyrus, anterior insula, anterior cingulate, parahippocampal gyrus, retrosplenial cortex, coronal radiata, and knee region of the internal capsule. Asymmetry decreases with age in the optic radiation, precentral gyrus, and angular gyrus. The texture-based method reported here is based on extended multisort cooccurrence matrices that employ intensity, gradient, and anisotropy features in a uniform way. It is sensitive, simple to reproduce, robust, and unbiased in the sense that segmentation of brain compartments and spatial transformations are not necessary. Thus, it should be considered as another tool for digital morphometry in neuroscience.

Detection of architectural distortion in prior screening mammograms using Gabor filters, phase portraits, fractal dimension, and texture analysis

International Nuclear Information System (INIS)

Rangayyan, Rangaraj M.; Prajna, Shormistha; Ayres, Fabio J.; Desautels, J.E.L.

2008-01-01

Mammography is a widely used screening tool for the early detection of breast cancer. One of the commonly missed signs of breast cancer is architectural distortion. The purpose of this study is to explore the application of fractal analysis and texture measures for the detection of architectural distortion in screening mammograms taken prior to the detection of breast cancer. A method based on Gabor filters and phase portrait analysis was used to detect initial candidates for sites of architectural distortion. A total of 386 regions of interest (ROIs) were automatically obtained from 14 ''prior mammograms'', including 21 ROIs related to architectural distortion. From the corresponding set of 14 ''detection mammograms'', 398 ROIs were obtained, including 18 related to breast cancer. For each ROI, the fractal dimension and Haralick's texture features were computed. The fractal dimension of the ROIs was calculated using the circular average power spectrum technique. The average fractal dimension of the normal (false-positive) ROIs was significantly higher than that of the ROIs with architectural distortion (p = 0.006). For the ''prior mammograms'', the best receiver operating characteristics (ROC) performance achieved, in terms of the area under the ROC curve, was 0.80 with a Bayesian classifier using four features including fractal dimension, entropy, sum entropy, and inverse difference moment. Analysis of the performance of the methods with free-response receiver operating characteristics indicated a sensitivity of 0.79 at 8.4 false positives per image in the detection of sites of architectural distortion in the ''prior mammograms''. Fractal dimension offers a promising way to detect the presence of architectural distortion in prior mammograms. (orig.)

Appearance and characterization of fruit image textures for quality sorting using wavelet transform and genetic algorithms.

Science.gov (United States)

Khoje, Suchitra

2018-02-01

Images of four qualities of mangoes and guavas are evaluated for color and textural features to characterize and classify them, and to model the fruit appearance grading. The paper discusses three approaches to identify most discriminating texture features of both the fruits. In the first approach, fruit's color and texture features are selected using Mahalanobis distance. A total of 20 color features and 40 textural features are extracted for analysis. Using Mahalanobis distance and feature intercorrelation analyses, one best color feature (mean of a* [L*a*b* color space]) and two textural features (energy a*, contrast of H*) are selected as features for Guava while two best color features (R std, H std) and one textural features (energy b*) are selected as features for mangoes with the highest discriminate power. The second approach studies some common wavelet families for searching the best classification model for fruit quality grading. The wavelet features extracted from five basic mother wavelets (db, bior, rbior, Coif, Sym) are explored to characterize fruits texture appearance. In third approach, genetic algorithm is used to select only those color and wavelet texture features that are relevant to the separation of the class, from a large universe of features. The study shows that image color and texture features which were identified using a genetic algorithm can distinguish between various qualities classes of fruits. The experimental results showed that support vector machine classifier is elected for Guava grading with an accuracy of 97.61% and artificial neural network is elected from Mango grading with an accuracy of 95.65%. The proposed method is nondestructive fruit quality assessment method. The experimental results has proven that Genetic algorithm along with wavelet textures feature has potential to discriminate fruit quality. Finally, it can be concluded that discussed method is an accurate, reliable, and objective tool to determine fruit

Automated prostate cancer detection via comprehensive multi-parametric magnetic resonance imaging texture feature models

International Nuclear Information System (INIS)

Khalvati, Farzad; Wong, Alexander; Haider, Masoom A.

2015-01-01

Prostate cancer is the most common form of cancer and the second leading cause of cancer death in North America. Auto-detection of prostate cancer can play a major role in early detection of prostate cancer, which has a significant impact on patient survival rates. While multi-parametric magnetic resonance imaging (MP-MRI) has shown promise in diagnosis of prostate cancer, the existing auto-detection algorithms do not take advantage of abundance of data available in MP-MRI to improve detection accuracy. The goal of this research was to design a radiomics-based auto-detection method for prostate cancer via utilizing MP-MRI data. In this work, we present new MP-MRI texture feature models for radiomics-driven detection of prostate cancer. In addition to commonly used non-invasive imaging sequences in conventional MP-MRI, namely T2-weighted MRI (T2w) and diffusion-weighted imaging (DWI), our proposed MP-MRI texture feature models incorporate computed high-b DWI (CHB-DWI) and a new diffusion imaging modality called correlated diffusion imaging (CDI). Moreover, the proposed texture feature models incorporate features from individual b-value images. A comprehensive set of texture features was calculated for both the conventional MP-MRI and new MP-MRI texture feature models. We performed feature selection analysis for each individual modality and then combined best features from each modality to construct the optimized texture feature models. The performance of the proposed MP-MRI texture feature models was evaluated via leave-one-patient-out cross-validation using a support vector machine (SVM) classifier trained on 40,975 cancerous and healthy tissue samples obtained from real clinical MP-MRI datasets. The proposed MP-MRI texture feature models outperformed the conventional model (i.e., T2w+DWI) with regard to cancer detection accuracy. Comprehensive texture feature models were developed for improved radiomics-driven detection of prostate cancer using MP-MRI. Using a

Anisotropic 3D texture synthesis with application to volume rendering

DEFF Research Database (Denmark)

Laursen, Lasse Farnung; Ersbøll, Bjarne Kjær; Bærentzen, Jakob Andreas

2011-01-01

images using a 12.1 megapixel camera. Next, we extend the volume rendering pipeline by creating a transfer function which yields not only color and opacity from the input intensity, but also texture coordinates for our synthesized 3D texture. Thus, we add texture to the volume rendered images....... This method is applied to a high quality visualization of a pig carcass, where samples of meat, bone, and fat have been used to produce the anisotropic 3D textures....

SU-E-I-100: Heterogeneity Studying for Primary and Lymphoma Tumors by Using Multi-Scale Image Texture Analysis with PET-CT Images

Energy Technology Data Exchange (ETDEWEB)

Li, Dengwang [Shandong Normal University, Jinan, Shandong Province (China); Wang, Qinfen [Shandong Normal University, Jinan, Shandong (China); Li, H; Chen, J [Shandong Cancer Hospital and Institute, Jinan, Shandong (China)

2014-06-01

Purpose: The purpose of this research is studying tumor heterogeneity of the primary and lymphoma by using multi-scale texture analysis with PET-CT images, where the tumor heterogeneity is expressed by texture features. Methods: Datasets were collected from 12 lung cancer patients, and both of primary and lymphoma tumors were detected with all these patients. All patients underwent whole-body 18F-FDG PET/CT scan before treatment.The regions of interest (ROI) of primary and lymphoma tumor were contoured by experienced clinical doctors. Then the ROI of primary and lymphoma tumor is extracted automatically by using Matlab software. According to the geometry size of contour structure, the images of tumor are decomposed by multi-scale method.Wavelet transform was performed on ROI structures within images by L layers sampling, and then wavelet sub-bands which have the same size of the original image are obtained. The number of sub-bands is 3L+1.The gray level co-occurrence matrix (GLCM) is calculated within different sub-bands, thenenergy, inertia, correlation and gray in-homogeneity were extracted from GLCM.Finally, heterogeneity statistical analysis was studied for primary and lymphoma tumor using the texture features. Results: Energy, inertia, correlation and gray in-homogeneity are calculated with our experiments for heterogeneity statistical analysis.Energy for primary and lymphomatumor is equal with the same patient, while gray in-homogeneity and inertia of primaryare 2.59595±0.00855, 0.6439±0.0007 respectively. Gray in-homogeneity and inertia of lymphoma are 2.60115±0.00635, 0.64435±0.00055 respectively. The experiments showed that the volume of lymphoma is smaller than primary tumor, but thegray in-homogeneity and inertia were higher than primary tumor with the same patient, and the correlation with lymphoma tumors is zero, while the correlation with primary tumor isslightly strong. Conclusion: This studying showed that there were effective heterogeneity

Bayesian exploration for intelligent identification of textures

Directory of Open Access Journals (Sweden)

Jeremy A. Fishel

2012-06-01

Full Text Available In order to endow robots with humanlike abilities to characterize and identify objects, they must be provided with tactile sensors and intelligent algorithms to select, control and interpret data from useful exploratory movements. Humans make informed decisions on the sequence of exploratory movements that would yield the most information for the task, depending on what the object may be and prior knowledge of what to expect from possible exploratory movements. This study is focused on texture discrimination, a subset of a much larger group of exploratory movements and percepts that humans use to discriminate, characterize, and identify objects. Using a testbed equipped with a biologically inspired tactile sensor (the BioTac® we produced sliding movements similar to those that humans make when exploring textures. Measurement of tactile vibrations and reaction forces when exploring textures were used to extract measures of textural properties inspired from psychophysical literature (traction, roughness, and fineness. Different combinations of normal force and velocity were identified to be useful for each of these three properties. A total of 117 textures were explored with these three movements to create a database of prior experience to use for identifying these same textures in future encounters. When exploring a texture, the discrimination algorithm adaptively selects the optimal movement to make and property to measure based on previous experience to differentiate the texture from a set of plausible candidates, a process we call Bayesian exploration. Performance of 99.6% in correctly discriminating pairs of similar textures was found to exceed human capabilities. Absolute classification from the entire set of 117 textures generally required a small number of well-chosen exploratory movements (median=5 and yielded a 95.4% success rate. The method of Bayesian exploration developed and tested in this paper may generalize well to other

Tumour heterogeneity in oesophageal cancer assessed by CT texture analysis: Preliminary evidence of an association with tumour metabolism, stage, and survival

International Nuclear Information System (INIS)

Ganeshan, B.; Skogen, K.; Pressney, I.; Coutroubis, D.; Miles, K.

2012-01-01

Aim: To undertake a pilot study assessing whether tumour heterogeneity evaluated using computed tomography texture analysis (CTTA) has the potential to provide a marker of tumour aggression and prognosis in oesophageal cancer. Materials and methods: In 21 patients, unenhanced CT images of the primary oesophageal lesion obtained using positron-emission tomography (PET)-CT examinations underwent CTTA. CTTA was carried out using a software algorithm that selectively filters and extracts textures at different anatomical scales between filter values 1.0 (fine detail) and 2.5 (coarse features) with quantification as entropy and uniformity (measures image heterogeneity). Texture parameters were correlated with average tumour 2-[ 18 F]-fluoro-2-deoxy-D-glucose (FDG) uptake [standardized uptake values (SUV mean and SUV max )] and clinical staging as determined by endoscopic ultrasound (nodal involvement) and PET-CT (distant metastases). The relationship between tumour stage, FDG uptake, and texture with survival was assessed using Kaplan–Meier analysis. Results: Tumour heterogeneity correlated with SUV max and SUV mean . The closest correlations were found for SUV mean measured as uniformity and entropy with coarse filtration (r = –0.754, p < 0.0001; and r = 0.748, p = 0.0001 respectively). Heterogeneity was also significantly greater in patients with clinical stage III or IV for filter values between 1.0 and 2.0 (maximum difference at filter value 1.5: entropy: p = 0.027; uniformity p = 0.032). The median (range) survival was 21 (4–34) months. Tumour heterogeneity assessed by CTTA (coarse uniformity) was an independent predictor of survival [odds ratio (OR)=4.45 (95% CI: 1.08, 18.37); p = 0.039]. Conclusion: CTTA assessment of tumour heterogeneity has the potential to identify oesophageal cancers with adverse biological features and provide a prognostic indicator of survival.

Prediction of troponin-T degradation using color image texture features in 10d aged beef longissimus steaks.

Science.gov (United States)

Sun, X; Chen, K J; Berg, E P; Newman, D J; Schwartz, C A; Keller, W L; Maddock Carlin, K R

2014-02-01

The objective was to use digital color image texture features to predict troponin-T degradation in beef. Image texture features, including 88 gray level co-occurrence texture features, 81 two-dimension fast Fourier transformation texture features, and 48 Gabor wavelet filter texture features, were extracted from color images of beef strip steaks (longissimus dorsi, n = 102) aged for 10d obtained using a digital camera and additional lighting. Steaks were designated degraded or not-degraded based on troponin-T degradation determined on d 3 and d 10 postmortem by immunoblotting. Statistical analysis (STEPWISE regression model) and artificial neural network (support vector machine model, SVM) methods were designed to classify protein degradation. The d 3 and d 10 STEPWISE models were 94% and 86% accurate, respectively, while the d 3 and d 10 SVM models were 63% and 71%, respectively, in predicting protein degradation in aged meat. STEPWISE and SVM models based on image texture features show potential to predict troponin-T degradation in meat. © 2013.

Hardwood species classification with DWT based hybrid texture ...

Indian Academy of Sciences (India)

to decompose the image up to 7 levels using Daubechies (db3) wavelet as decom ... binary pattern (DWTFOSLBPu2) texture features at the 4th level of image decomposi ...... In addition, inclusion of further levels of image decomposition gives rise to ..... Texture analysis of SAR sea ice imagery using gray level co-occurrence.

A quasi-in-situ EBSD observation of the transformation from rolling texture to recrystallization texture in V-4Cr-4Ti alloy

Energy Technology Data Exchange (ETDEWEB)

Peng, Lixia [Institute of Materials Research, China Academy of Engineering Physics, Jiangyou, Sichuan Province 621908 (China); Li, Xiongwei [Institute of Metal Research, China Academy of Sciences, 72 Wenhua Road, Shenyang 110016 (China); Fan, Zhijian [Institute of Nuclear Physics and Chemistry, China Academy of Engineering Physics, Mianyang, Sichuan Province 621900 (China); Jiang, Chunli; Zhou, Ping [Institute of Materials Research, China Academy of Engineering Physics, Jiangyou, Sichuan Province 621908 (China); Lai, Xinchun, E-mail: laixinchun@caep.cn [Institute of Materials Research, China Academy of Engineering Physics, Jiangyou, Sichuan Province 621908 (China)

2017-04-15

Recrystallization texture evolution of rolled V-4Cr-4Ti alloy has been investigated by quasi-in-situ EBSD (electron back-scattering diffraction) method. Concurrently, the precipitates were characterized by SEM (Scanning Electron Microscopy). It was found that both the initial rolling textures and the distribution of the precipitates affected the formation of the recrystallization texture. It was revealed that the texture transformations of (558) 〈110〉 + (665) 〈110〉 to (334) 〈483〉 + (665) 〈1 1 2.4〉 were possibly attributed to the selective drag induced by the sparsely dispersed Ti-rich precipitates. While the densely distributed Ti-rich precipitates were responsible for the randomized recrystallization texture. Finally, when the precipitates were absent, the orientation changes from (112) 〈110〉 and (558) 〈110〉 to (111) 〈112〉 and (001) <110> to (001) <520> were observed. - Highlights: • Micro recrystallization texture evolution in V-4Cr-4Ti alloys is reported for the first time. • The volume fraction of Ti-rich precipitates has significant effect on the recrystallization texture evolution. • The dissolution of the Ti-rich precipitates above 1100 °C induces the strengthening of (111) <112> texture.

Texture analysis of ultrahigh field T2*-weighted MR images of the brain: application to Huntington's disease.

Science.gov (United States)

Doan, Nhat Trung; van den Bogaard, Simon J A; Dumas, Eve M; Webb, Andrew G; van Buchem, Mark A; Roos, Raymund A C; van der Grond, Jeroen; Reiber, Johan H C; Milles, Julien

2014-03-01

To develop a framework for quantitative detection of between-group textural differences in ultrahigh field T2*-weighted MR images of the brain. MR images were acquired using a three-dimensional (3D) T2*-weighted gradient echo sequence on a 7 Tesla MRI system. The phase images were high-pass filtered to remove phase wraps. Thirteen textural features were computed for both the magnitude and phase images of a region of interest based on 3D Gray-Level Co-occurrence Matrix, and subsequently evaluated to detect between-group differences using a Mann-Whitney U-test. We applied the framework to study textural differences in subcortical structures between premanifest Huntington's disease (HD), manifest HD patients, and controls. In premanifest HD, four phase-based features showed a difference in the caudate nucleus. In manifest HD, 7 magnitude-based features showed a difference in the pallidum, 6 phase-based features in the caudate nucleus, and 10 phase-based features in the putamen. After multiple comparison correction, significant differences were shown in the putamen in manifest HD by two phase-based features (both adjusted P values=0.04). This study provides the first evidence of textural heterogeneity of subcortical structures in HD. Texture analysis of ultrahigh field T2*-weighted MR images can be useful for noninvasive monitoring of neurodegenerative diseases. Copyright © 2013 Wiley Periodicals, Inc.

An Active Patch Model for Real World Texture and Appearance Classification.

Science.gov (United States)

Mao, Junhua; Zhu, Jun; Yuille, Alan L

2014-09-06

This paper addresses the task of natural texture and appearance classification. Our goal is to develop a simple and intuitive method that performs at state of the art on datasets ranging from homogeneous texture (e.g., material texture), to less homogeneous texture (e.g., the fur of animals), and to inhomogeneous texture (the appearance patterns of vehicles). Our method uses a bag-of-words model where the features are based on a dictionary of active patches. Active patches are raw intensity patches which can undergo spatial transformations (e.g., rotation and scaling) and adjust themselves to best match the image regions. The dictionary of active patches is required to be compact and representative, in the sense that we can use it to approximately reconstruct the images that we want to classify. We propose a probabilistic model to quantify the quality of image reconstruction and design a greedy learning algorithm to obtain the dictionary. We classify images using the occurrence frequency of the active patches. Feature extraction is fast (about 100 ms per image) using the GPU. The experimental results show that our method improves the state of the art on a challenging material texture benchmark dataset (KTH-TIPS2). To test our method on less homogeneous or inhomogeneous images, we construct two new datasets consisting of appearance image patches of animals and vehicles cropped from the PASCAL VOC dataset. Our method outperforms competing methods on these datasets.

Texturing in titanium grade 2 surface irradiate with ultrashort pulse laser

International Nuclear Information System (INIS)

Nogueira, Alessandro Francelino

2015-01-01

The texturing laser micromachining is an important alternative to improve the bonding adhesion between composites and titanium, which are applied to structural components in the aerospace industry. The texturing running on titanium plates is due to the fact that the preferred joining technique for many composite materials is the adhesive bonding. In this work, titanium plates were texturized using laser ultrashort pulses temporal widths of femtoseconds. This process resulted in minimal heat transfer to the material, avoiding deformation of the titanium plate surface as well as the formation of resolidified material in the ablated region. These drawbacks have occurred with the use of nanoseconds pulses. Were performed three types of texturing using laser with femtosecond pulses, with variations in the distances between the machined lines. The analysis of the obtained surfaces found that the wettability increases when there is the increased distance between the texturing lines. Advancing in the analysis by optical profilometry of textured surfaces was observed that there is substantial increase in the volume available for penetration of structural adhesive when the distances between the textured lines are diminished. In tensile tests conducted it was observed that there is an increase in shear strength of the adhesive joint by reducing the distance between the textured lines. (author)

Comparison of features response in texture-based iris segmentation

CSIR Research Space (South Africa)

Bachoo, A

2009-03-01

Full Text Available the Fisher linear discriminant and the iris region of interest is extracted. Four texture description methods are compared for segmenting iris texture using a region based pattern classification approach: Grey Level Co-occurrence Matrix (GLCM), Discrete...

Dental microwear texture analysis of late Pliocene Procynocephalus subhimalayanus (Primates: Cercopithecidae) of the Upper Siwaliks, India

Science.gov (United States)

Williams, Frank L'Engle; Holmes, Noelle A.

2012-09-01

Late Pliocene Procynocephalus subhimalayanus from the Upper Siwaliks, India is known from only three specimens. The dietary proclivities of this taxon have implications for reconstructing the paleoecology of the Upper Siwaliks. The dental microwear texture properties of Procynocephalus are compared to those from extant tropical forest primates including Alouatta palliata (n = 11), Cebus apella (n = 13), Gorilla gorilla (n = 9), Lophocebus albigena (n = 15) and Trachypithecus cristatus (n = 12). Dental microwear textures are generated by scanning the surface enamel of Facet 9 using white-light confocal microscopy at 100x. Four variables were extracted from scale-sensitive fractal analysis, and the data were ranked before ANOVA with post-hoc tests of significance and multivariate analyses were performed. Procynocephalus clusters closest to Lophocebus, Cebus and some Gorilla specimens suggesting hard-object feeding characterized a portion of its diet. The dental microwear texture of Procynocephalus supports interpretations of widespread grasslands of the Late Pliocene Kansal Formation (Pinjor zone). The extreme enamel complexity characterizing Procynocephalus may derive from consumption of underground storage organs, or other foods with high grit loads. Foods consumed near ground level carry a heavy load of abrasive minerals possibly contributing to greater enamel surface complexity and textural fill volume.

Historical Texture Analysis of Küçük Kumla Village and Preservation Proposals

Directory of Open Access Journals (Sweden)

Tülay ESİN

2013-08-01

Full Text Available Küçük Kumla Village, which is situated in the Marmara region, Bursa City and Gemlik District embraces traces of different cultures with respect to its fertile soil character, mild climate and location. In this study, the features of the traditional neighbourhood in Küçük Kumla Village are sought to research. Through the coverage of analysis made, it is found out that the traditional texture of the village has been deteriorating gradually. Due to the fact that the varying life styles and new comfort necessities are not fulfilled by the traditional civil architectural samples, the society leads to new building production rather than traditional building usage. Another issue that results with the abandonment is the immigration to the towns and city centres from the region regarding various reasons. Not providing necessary care on the abandoned buildings tends to accelerate the deterioration process. The buildings constructs on the previous historical buildings contradicting with the original thus preventing the sense of traditional texture of the village. Through contemporary and applicable proposals provided in this study, it is predicted that historical textural deterioration of the region can be prevented and the texture of the village can be rehabilitated and preserved

Symmetric textures

International Nuclear Information System (INIS)

Ramond, P.

1993-01-01

The Wolfenstein parametrization is extended to the quark masses in the deep ultraviolet, and an algorithm to derive symmetric textures which are compatible with existing data is developed. It is found that there are only five such textures

Formation of biaxial texture in metal films by selective ion beam etching

Energy Technology Data Exchange (ETDEWEB)

Park, S.J. [Department of Materials Science and Engineering, University of Florida, 106 Rhines Hall, P.O. Box 116400, Gainesville, FL 32611 (United States); Norton, D.P. [Department of Materials Science and Engineering, University of Florida, 106 Rhines Hall, P.O. Box 116400, Gainesville, FL 32611 (United States)]. E-mail: dnort@mse.ufl.edu; Selvamanickam, Venkat [IGC-SuperPower, LLC, 450 Duane Avenue, Schenectady, NY 12304 (United States)

2006-05-15

The formation of in-plane texture via ion bombardment of uniaxially textured metal films was investigated. In particular, selective grain Ar ion beam etching of uniaxially textured (0 0 1) Ni was used to achieve in-plane aligned Ni grains. Unlike conventional ion beam assisted deposition, the ion beam irradiates the uniaxially textured film surface with no impinging deposition flux. The initial uniaxial texture is established via surface energy minimization with no ion irradiation. Within this sequential texturing method, in-plane grain alignment is driven by selective etching and grain overgrowth. Biaxial texture was achieved for ion beam irradiation at elevated temperature.

Formation of biaxial texture in metal films by selective ion beam etching

International Nuclear Information System (INIS)

Park, S.J.; Norton, D.P.; Selvamanickam, Venkat

2006-01-01

The formation of in-plane texture via ion bombardment of uniaxially textured metal films was investigated. In particular, selective grain Ar ion beam etching of uniaxially textured (0 0 1) Ni was used to achieve in-plane aligned Ni grains. Unlike conventional ion beam assisted deposition, the ion beam irradiates the uniaxially textured film surface with no impinging deposition flux. The initial uniaxial texture is established via surface energy minimization with no ion irradiation. Within this sequential texturing method, in-plane grain alignment is driven by selective etching and grain overgrowth. Biaxial texture was achieved for ion beam irradiation at elevated temperature

Adobe photoshop quantification (PSQ) rather than point-counting: A rapid and precise method for quantifying rock textural data and porosities

Science.gov (United States)

Zhang, Xuefeng; Liu, Bo; Wang, Jieqiong; Zhang, Zhe; Shi, Kaibo; Wu, Shuanglin

2014-08-01

Commonly used petrological quantification methods are visual estimation, counting, and image analyses. However, in this article, an Adobe Photoshop-based analyzing method (PSQ) is recommended for quantifying the rock textural data and porosities. Adobe Photoshop system provides versatile abilities in selecting an area of interest and the pixel number of a selection could be read and used to calculate its area percentage. Therefore, Adobe Photoshop could be used to rapidly quantify textural components, such as content of grains, cements, and porosities including total porosities and different genetic type porosities. This method was named as Adobe Photoshop Quantification (PSQ). The workflow of the PSQ method was introduced with the oolitic dolomite samples from the Triassic Feixianguan Formation, Northeastern Sichuan Basin, China, for example. And the method was tested by comparing with the Folk's and Shvetsov's "standard" diagrams. In both cases, there is a close agreement between the "standard" percentages and those determined by the PSQ method with really small counting errors and operator errors, small standard deviations and high confidence levels. The porosities quantified by PSQ were evaluated against those determined by the whole rock helium gas expansion method to test the specimen errors. Results have shown that the porosities quantified by the PSQ are well correlated to the porosities determined by the conventional helium gas expansion method. Generally small discrepancies (mostly ranging from -3% to 3%) are caused by microporosities which would cause systematic underestimation of 2% and/or by macroporosities causing underestimation or overestimation in different cases. Adobe Photoshop could be used to quantify rock textural components and porosities. This method has been tested to be precise and accurate. It is time saving compared with usual methods.

Conductive and robust nitride buffer layers on biaxially textured substrates

Science.gov (United States)

Sankar, Sambasivan [Chicago, IL; Goyal, Amit [Knoxville, TN; Barnett, Scott A [Evanston, IL; Kim, Ilwon [Skokie, IL; Kroeger, Donald M [Knoxville, TN

2009-03-31

The present invention relates to epitaxial, electrically conducting and mechanically robust, cubic nitride buffer layers deposited epitaxially on biaxially textured substrates such as metals and alloys. The invention comprises of a biaxially textured substrate with epitaxial layers of nitrides. The invention also discloses a method to form such epitaxial layers using a high rate deposition method as well as without the use of forming gases. The invention further comprises epitaxial layers of oxides on the biaxially textured nitride layer. In some embodiments the article further comprises electromagnetic devices which may have superconducting properties.

Classification of interstitial lung disease patterns with topological texture features

Science.gov (United States)

Huber, Markus B.; Nagarajan, Mahesh; Leinsinger, Gerda; Ray, Lawrence A.; Wismüller, Axel

2010-03-01

Topological texture features were compared in their ability to classify morphological patterns known as 'honeycombing' that are considered indicative for the presence of fibrotic interstitial lung diseases in high-resolution computed tomography (HRCT) images. For 14 patients with known occurrence of honey-combing, a stack of 70 axial, lung kernel reconstructed images were acquired from HRCT chest exams. A set of 241 regions of interest of both healthy and pathological (89) lung tissue were identified by an experienced radiologist. Texture features were extracted using six properties calculated from gray-level co-occurrence matrices (GLCM), Minkowski Dimensions (MDs), and three Minkowski Functionals (MFs, e.g. MF.euler). A k-nearest-neighbor (k-NN) classifier and a Multilayer Radial Basis Functions Network (RBFN) were optimized in a 10-fold cross-validation for each texture vector, and the classification accuracy was calculated on independent test sets as a quantitative measure of automated tissue characterization. A Wilcoxon signed-rank test was used to compare two accuracy distributions and the significance thresholds were adjusted for multiple comparisons by the Bonferroni correction. The best classification results were obtained by the MF features, which performed significantly better than all the standard GLCM and MD features (p < 0.005) for both classifiers. The highest accuracy was found for MF.euler (97.5%, 96.6%; for the k-NN and RBFN classifier, respectively). The best standard texture features were the GLCM features 'homogeneity' (91.8%, 87.2%) and 'absolute value' (90.2%, 88.5%). The results indicate that advanced topological texture features can provide superior classification performance in computer-assisted diagnosis of interstitial lung diseases when compared to standard texture analysis methods.

TU-G-204-06: Correlation Between Texture Analysis-Based Model Observer and Human Observer in Diagnosis of Ischemic Infarct in Non-Contrast Head CT of Adults

International Nuclear Information System (INIS)

Li, B; Fujita, A; Buch, K; Sakai, O

2015-01-01

Purpose: To investigate the correlation between texture analysis-based model observer and human observer in the task of diagnosis of ischemic infarct in non-contrast head CT of adults. Methods: Non-contrast head CTs of five patients (2 M, 3 F; 58–83 y) with ischemic infarcts were retro-reconstructed using FBP and Adaptive Statistical Iterative Reconstruction (ASIR) of various levels (10–100%). Six neuro -radiologists reviewed each image and scored image quality for diagnosing acute infarcts by a 9-point Likert scale in a blinded test. These scores were averaged across the observers to produce the average human observer responses. The chief neuro-radiologist placed multiple ROIs over the infarcts. These ROIs were entered into a texture analysis software package. Forty-two features per image, including 11 GLRL, 5 GLCM, 4 GLGM, 9 Laws, and 13 2-D features, were computed and averaged over the images per dataset. The Fisher-coefficient (ratio of between-class variance to in-class variance) was calculated for each feature to identify the most discriminating features from each matrix that separate the different confidence scores most efficiently. The 15 features with the highest Fisher -coefficient were entered into linear multivariate regression for iterative modeling. Results: Multivariate regression analysis resulted in the best prediction model of the confidence scores after three iterations (df=11, F=11.7, p-value<0.0001). The model predicted scores and human observers were highly correlated (R=0.88, R-sq=0.77). The root-mean-square and maximal residual were 0.21 and 0.44, respectively. The residual scatter plot appeared random, symmetric, and unbiased. Conclusion: For diagnosis of ischemic infarct in non-contrast head CT in adults, the predicted image quality scores from texture analysis-based model observer was highly correlated with that of human observers for various noise levels. Texture-based model observer can characterize image quality of low contrast

TU-G-204-06: Correlation Between Texture Analysis-Based Model Observer and Human Observer in Diagnosis of Ischemic Infarct in Non-Contrast Head CT of Adults

Energy Technology Data Exchange (ETDEWEB)

Li, B; Fujita, A; Buch, K; Sakai, O [Boston University Medical Center, Boston, MA (United States)

2015-06-15

Purpose: To investigate the correlation between texture analysis-based model observer and human observer in the task of diagnosis of ischemic infarct in non-contrast head CT of adults. Methods: Non-contrast head CTs of five patients (2 M, 3 F; 58–83 y) with ischemic infarcts were retro-reconstructed using FBP and Adaptive Statistical Iterative Reconstruction (ASIR) of various levels (10–100%). Six neuro -radiologists reviewed each image and scored image quality for diagnosing acute infarcts by a 9-point Likert scale in a blinded test. These scores were averaged across the observers to produce the average human observer responses. The chief neuro-radiologist placed multiple ROIs over the infarcts. These ROIs were entered into a texture analysis software package. Forty-two features per image, including 11 GLRL, 5 GLCM, 4 GLGM, 9 Laws, and 13 2-D features, were computed and averaged over the images per dataset. The Fisher-coefficient (ratio of between-class variance to in-class variance) was calculated for each feature to identify the most discriminating features from each matrix that separate the different confidence scores most efficiently. The 15 features with the highest Fisher -coefficient were entered into linear multivariate regression for iterative modeling. Results: Multivariate regression analysis resulted in the best prediction model of the confidence scores after three iterations (df=11, F=11.7, p-value<0.0001). The model predicted scores and human observers were highly correlated (R=0.88, R-sq=0.77). The root-mean-square and maximal residual were 0.21 and 0.44, respectively. The residual scatter plot appeared random, symmetric, and unbiased. Conclusion: For diagnosis of ischemic infarct in non-contrast head CT in adults, the predicted image quality scores from texture analysis-based model observer was highly correlated with that of human observers for various noise levels. Texture-based model observer can characterize image quality of low contrast

Selective Extraction of Entangled Textures via Adaptive PDE Transform

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Yang Wang

2012-01-01

Full Text Available Texture and feature extraction is an important research area with a wide range of applications in science and technology. Selective extraction of entangled textures is a challenging task due to spatial entanglement, orientation mixing, and high-frequency overlapping. The partial differential equation (PDE transform is an efficient method for functional mode decomposition. The present work introduces adaptive PDE transform algorithm to appropriately threshold the statistical variance of the local variation of functional modes. The proposed adaptive PDE transform is applied to the selective extraction of entangled textures. Successful separations of human face, clothes, background, natural landscape, text, forest, camouflaged sniper and neuron skeletons have validated the proposed method.

COMPARING PARTICLE SIZE DISTRIBUTION ANALYSIS BY SEDIMENTATION AND LASER DIFFRACTION METHOD

OpenAIRE

Vito Ferro; Stefano Mirabile

2009-01-01

In this paper a brief review of the laser diffraction method is firstly carried out. Then, for 30 soil samples having a different texture classification sampled in Sicilian basin, a comparison between the two techniques is developed. The analysis demonstrated that the sand content measured by Sieve-Hydrometer method can be assumed equal to the one determinated by laser diffraction technique while an overestimation of the clay fraction measured by Sieve-Hydrometer method respect to laser diffr...

Femtosecond laser surface texturing of titanium as a method to reduce the adhesion of Staphylococcus aureus and biofilm formation

Science.gov (United States)

Cunha, Alexandre; Elie, Anne-Marie; Plawinski, Laurent; Serro, Ana Paula; Botelho do Rego, Ana Maria; Almeida, Amélia; Urdaci, Maria C.; Durrieu, Marie-Christine; Vilar, Rui

2016-01-01

The aim of the present work was to investigate the possibility of using femtosecond laser surface texturing as a method to reduce the colonization of Grade 2 Titanium alloy surfaces by Staphylococcus aureus and the subsequent formation of biofilm. The laser treatments were carried out with a Yb:KYW chirped-pulse-regenerative amplification laser system with a central wavelength of 1030 nm and a pulse duration of 500 fs. Two types of surface textures, consisting of laser-induced periodic surface structures (LIPSS) and nanopillars, were produced. The topography, chemical composition and phase constitution of these surfaces were investigated by atomic force microscopy, scanning electron microscopy, X-ray photoelectron spectroscopy, micro-Raman spectroscopy, and X-ray diffraction. Surface wettability was assessed by the sessile drop method using water and diiodomethane as testing liquids. The response of S. aureus put into contact with the laser treated surfaces in controlled conditions was investigated by epifluorescence microscopy and scanning electron microscopy 48 h after cell seeding. The results achieved show that the laser treatment reduces significantly the bacterial adhesion to the surface as well as biofilm formation as compared to a reference polished surfaces and suggest that femtosecond laser texturing is a simple and promising method for endowing dental and orthopedic titanium implants with antibacterial properties, reducing the risk of implant-associated infections without requiring immobilized antibacterial substances, nanoparticles or coatings.

Cold rolling texture development of α/γ duplex stainless steels

International Nuclear Information System (INIS)

Akdut, N.; Foct, J.; Gottstein, G.

1996-01-01

The cold rolling texture development of two α/γ duplex stainless steels (DSS) with similar volume fractions of both phases but with totally different microstructures were investigated. Due to the limited number of available pole figures using X-rays, for the calculation of the ODFs both a direct method and a recent iterative series expansion method were used. The results were checked by neutron diffraction measurements. The austenitic phases of both DSS behave similarly to single phase materials with a low stacking fault energy which develop a brass-type rolling texture. In contrast, the texture development of the ferritic phases strongly differs from those of single phase ferrites. Instead of a fibre type texture the α-phase in both DSS exhibits a peak dominated texture regardless of whether it is the matrix phase or not. These differences, as well as the sharpness of both phases, are explained by the presence of the second phase. (orig.)

Quantitative CT texture and shape analysis: Can it differentiate benign and malignant mediastinal lymph nodes in patients with primary lung cancer?

Energy Technology Data Exchange (ETDEWEB)

Bayanati, Hamid; Thornhill, Rebecca E.; Souza, Carolina A.; Sethi-Virmani, Vineeta; Gupta, Ashish; Dennie, Carole [University of Ottawa, The Ottawa Hospital Research Institute, Department of Medical Imaging, The Ottawa Hospital, 501 Smyth Road, Box 232, Ottawa, ON (Canada); Maziak, Donna [University of Ottawa, The Ottawa Hospital Research Institute, Department of Surgery - Division of Thoracic Surgery, The Ottawa Hospital, Ottawa, ON (Canada); Amjadi, Kayvan [University of Ottawa, The Ottawa Hospital Research Institute, Department of Respiratory Medicine, The Ottawa Hospital, Ottawa, ON (Canada)

2014-09-13

To assess the accuracy of CT texture and shape analysis in the differentiation of benign and malignant mediastinal nodes in lung cancer. Forty-three patients with biopsy-proven primary lung malignancy with pathological mediastinal nodal staging and unenhanced CT of the thorax were studied retrospectively. Grey-level co-occurrence and run-length matrix textural features, as well as morphological features, were extracted from 72 nodes. Differences between benign and malignant features were assessed using Mann-Whitney U tests. Receiver operating characteristic (ROC) curves for each were constructed and the area under the curve (AUC) calculated with histopathology diagnosis as outcome. Combinations of features were also entered as predictors in logistic regression models and optimal threshold criteria were used to estimate sensitivity and specificity. Using optimum-threshold criteria, the combined textural and shape features identified malignant mediastinal nodes with 81 % sensitivity and 80 % specificity (AUC = 0.87, P < 0.0001). Using this combination, 84 % malignant and 71 % benign nodes were correctly classified. Quantitative CT texture and shape analysis has the potential to accurately differentiate malignant and benign mediastinal nodes in lung cancer. (orig.)

Assessing Asphalt and Concrete Pavement Surface Texture in the Field

Directory of Open Access Journals (Sweden)

Saad I. Sarsam

2016-06-01

Full Text Available The incorporation of safety characteristics into the traditional pavement structural design or in the functional evaluation of pavement condition has not been established yet. The design has focused on the structural capacity of the roadway so that the pavement can withstand specific level of repetitive loading over the design life. On the other hand, the surface texture condition was neither included in the AASHTO design procedure nor in the present serviceability index measurements. The pavement surface course should provide adequate levels of friction and ride quality and maintain low levels of noise and roughness. Many transportation departments perform routine skid resistant testing, the type of equipment used for testing varies depending on the preference of each transportation department. It was felt that modeling of the surface texture condition using different methods of testing may assist in solving such problem. In this work, Macro texture and Micro texture of asphalt and cement concrete pavement surface have been investigated in the field using four different methods (The Sand Patch Method, Outflow Time Method, British Pendulum Tester and Photogrammetry Technique. Two different grain sizes of sand have been utilized in conducting the Sand Patch while the Micro texture was investigated using the British Pendulum tester method at wet pavement surface conditions. The test results of the four methods were correlated to the skid number. It was concluded that such modeling could provide instant data in the field for pavement condition which may help in pavement maintenance management.

Magnetic resonance imaging texture analysis classification of primary breast cancer

International Nuclear Information System (INIS)

Waugh, S.A.; Lerski, R.A.; Purdie, C.A.; Jordan, L.B.; Vinnicombe, S.; Martin, P.; Thompson, A.M.

2016-01-01

Patient-tailored treatments for breast cancer are based on histological and immunohistochemical (IHC) subtypes. Magnetic Resonance Imaging (MRI) texture analysis (TA) may be useful in non-invasive lesion subtype classification. Women with newly diagnosed primary breast cancer underwent pre-treatment dynamic contrast-enhanced breast MRI. TA was performed using co-occurrence matrix (COM) features, by creating a model on retrospective training data, then prospectively applying to a test set. Analyses were blinded to breast pathology. Subtype classifications were performed using a cross-validated k-nearest-neighbour (k = 3) technique, with accuracy relative to pathology assessed and receiver operator curve (AUROC) calculated. Mann-Whitney U and Kruskal-Wallis tests were used to assess raw entropy feature values. Histological subtype classifications were similar across training (n = 148 cancers) and test sets (n = 73 lesions) using all COM features (training: 75 %, AUROC = 0.816; test: 72.5 %, AUROC = 0.823). Entropy features were significantly different between lobular and ductal cancers (p < 0.001; Mann-Whitney U). IHC classifications using COM features were also similar for training and test data (training: 57.2 %, AUROC = 0.754; test: 57.0 %, AUROC = 0.750). Hormone receptor positive and negative cancers demonstrated significantly different entropy features. Entropy features alone were unable to create a robust classification model. Textural differences on contrast-enhanced MR images may reflect underlying lesion subtypes, which merits testing against treatment response. (orig.)

Magnetic resonance imaging texture analysis classification of primary breast cancer

Energy Technology Data Exchange (ETDEWEB)

Waugh, S.A.; Lerski, R.A. [Ninewells Hospital and Medical School, Department of Medical Physics, Dundee (United Kingdom); Purdie, C.A.; Jordan, L.B. [Ninewells Hospital and Medical School, Department of Pathology, Dundee (United Kingdom); Vinnicombe, S. [University of Dundee, Division of Imaging and Technology, Ninewells Hospital and Medical School, Dundee (United Kingdom); Martin, P. [Ninewells Hospital and Medical School, Department of Clinical Radiology, Dundee (United Kingdom); Thompson, A.M. [University of Texas MD Anderson Cancer Center, Department of Surgical Oncology, Houston, TX (United States)

2016-02-15

Patient-tailored treatments for breast cancer are based on histological and immunohistochemical (IHC) subtypes. Magnetic Resonance Imaging (MRI) texture analysis (TA) may be useful in non-invasive lesion subtype classification. Women with newly diagnosed primary breast cancer underwent pre-treatment dynamic contrast-enhanced breast MRI. TA was performed using co-occurrence matrix (COM) features, by creating a model on retrospective training data, then prospectively applying to a test set. Analyses were blinded to breast pathology. Subtype classifications were performed using a cross-validated k-nearest-neighbour (k = 3) technique, with accuracy relative to pathology assessed and receiver operator curve (AUROC) calculated. Mann-Whitney U and Kruskal-Wallis tests were used to assess raw entropy feature values. Histological subtype classifications were similar across training (n = 148 cancers) and test sets (n = 73 lesions) using all COM features (training: 75 %, AUROC = 0.816; test: 72.5 %, AUROC = 0.823). Entropy features were significantly different between lobular and ductal cancers (p < 0.001; Mann-Whitney U). IHC classifications using COM features were also similar for training and test data (training: 57.2 %, AUROC = 0.754; test: 57.0 %, AUROC = 0.750). Hormone receptor positive and negative cancers demonstrated significantly different entropy features. Entropy features alone were unable to create a robust classification model. Textural differences on contrast-enhanced MR images may reflect underlying lesion subtypes, which merits testing against treatment response. (orig.)

Texture analysis of MR images of patients with Mild Traumatic Brain Injury

International Nuclear Information System (INIS)

Holli, Kirsi K; Harrison, Lara; Dastidar, Prasun; Wäljas, Minna; Liimatainen, Suvi; Luukkaala, Tiina; Öhman, Juha; Soimakallio, Seppo; Eskola, Hannu

2010-01-01

Our objective was to study the effect of trauma on texture features in cerebral tissue in mild traumatic brain injury (MTBI). Our hypothesis was that a mild trauma may cause microstructural changes, which are not necessarily perceptible by visual inspection but could be detected with texture analysis (TA). We imaged 42 MTBI patients by using 1.5 T MRI within three weeks of onset of trauma. TA was performed on the area of mesencephalon, cerebral white matter at the levels of mesencephalon, corona radiata and centrum semiovale and in different segments of corpus callosum (CC) which have been found to be sensitive to damage. The same procedure was carried out on a control group of ten healthy volunteers. Patients' TA data was compared with the TA results of the control group comparing the amount of statistically significantly differing TA parameters between the left and right sides of the cerebral tissue and comparing the most discriminative parameters. There were statistically significant differences especially in several co-occurrence and run-length matrix based parameters between left and right side in the area of mesencephalon, in cerebral white matter at the level of corona radiata and in the segments of CC in patients. Considerably less difference was observed in the healthy controls. TA revealed significant changes in texture parameters of cerebral tissue between hemispheres and CC segments in TBI patients. TA may serve as a novel additional tool for detecting the conventionally invisible changes in cerebral tissue in MTBI and help the clinicians to make an early diagnosis

Textural states of a hot-worked MA2-1 magnesium alloy

Science.gov (United States)

Serebryany, V. N.; Kochubei, A. Ya.; Kurtasov, S. F.; Mel'Nikov, K. E.

2007-02-01

Quantitative texture analysis is used to study texture formation in an MA2-1 magnesium alloy subjected to axisymmetric upsetting at temperatures of 250-450°C and strain rates of 10-4-100 -1. The deformed structure is examined by optical microscopy, and the results obtained are used to plot the structural-state diagram of the alloy after 50% upsetting. The experimental textures are compared with the textures calculated in terms of a thermoactivation model.

X-ray diffraction from thin films : Residual stress and texture analysis

Energy Technology Data Exchange (ETDEWEB)

Leoni, M; Scardi, [Trento Univ. (Italy). Dept. of Materials Engineering

1996-09-01

In this short contribution the attention will be drawn to the use of XRD-based non-destructive techniques for the study of the stress state and the orientation (texture) of various technologically valuable films. The cases in which the texture is important will be presented and they are: applicative examples, spacing in a wide variety of application areas and regarding growth-induced and machining-induced orientation.

Microstructure and texture evolution of ultra-thin grain-oriented silicon steel sheet fabricated using strip casting and three-stage cold rolling method

Energy Technology Data Exchange (ETDEWEB)

Song, Hong-Yu; Liu, Hai-Tao, E-mail: liuht@ral.neu.edu.cn; Wang, Yin-Ping; Wang, Guo-Dong

2017-03-15

A 0.1 mm-thick grain-oriented silicon steel sheet was successfully produced using strip casting and three-stage cold rolling method. The microstructure, texture and inhibitor evolution during the processing was briefly analyzed. It was found that Goss texture was absent in the hot rolled sheet because of the lack of shear deformation. After normalizing, a large number of dispersed MnS precipitates with the size range of 15–90 nm were produced. During first cold rolling, dense shear bands were generated in the deformed ferrite grains, resulting in the intense Goss texture after first intermediate annealing. The microstructure was further refined and homogenized during the subsequent cold rolling and annealing processes. After primary recrystallization annealing, a homogeneous microstructure consisting of fine and equiaxed grains was produced while the associated texture was characterized by a strong γ-fiber texture. Finally, a complete secondary recrystallization microstructure consisting of entirely large Goss grains was produced. The magnetic induction B{sub 8} and iron loss P{sub 10/400} was 1.79 T and 6.9 W/kg, respectively. - Highlights: • Ultra-thin grain-oriented silicon steel was produced by strip casting process. • Microstructure, texture and inhibitor evolution was briefly investigated. • Goss texture was absent in primary recrystallization annealed sheet. • MnS precipitates with a size range of 15–90 nm formed after normalizing. • A complete secondary recrystallization microstructure was produced.

Experimental and Numerical Investigation on Tribological Performance of Grooved Texture

Directory of Open Access Journals (Sweden)

CHEN Ping

2016-06-01

Full Text Available In order to study the influence of the angle and arrangement forms of micro-grooves on the tribological performance of the contact surface, the finite element analysis software was used to simulate the grooved textures with different angles and arrangements. The YLP-20 laser processing system was used to process grooved texture on stainless steel disk surfaces, and the Tribometer (UMT-2 was also used to conduct tribological test under the condition of rotation. The results show that the numerical simulation values are basically consistent with experimental results of grooved textures, and the tribological performance of the friction pairs with textures is also improved. The grooved textures with different angles and arrangement forms have different influence on tribological performance of friction pairs. When the friction velocity is less than 300r/min, the parallel texture with 0° has smaller friction coefficients. While the friction velocity is larger than 300r/min, the parallel texture with 90° has a better ability of reducing friction. Therefore, different grooved textures should be chosen according to operation conditions.

Introduction of High Throughput Magnetic Resonance T2-Weighted Image Texture Analysis for WHO Grade 2 and 3 Gliomas.

Science.gov (United States)

Kinoshita, Manabu; Sakai, Mio; Arita, Hideyuki; Shofuda, Tomoko; Chiba, Yasuyoshi; Kagawa, Naoki; Watanabe, Yoshiyuki; Hashimoto, Naoya; Fujimoto, Yasunori; Yoshimine, Toshiki; Nakanishi, Katsuyuki; Kanemura, Yonehiro

2016-01-01

Reports have suggested that tumor textures presented on T2-weighted images correlate with the genetic status of glioma. Therefore, development of an image analyzing framework that is capable of objective and high throughput image texture analysis for large scale image data collection is needed. The current study aimed to address the development of such a framework by introducing two novel parameters for image textures on T2-weighted images, i.e., Shannon entropy and Prewitt filtering. Twenty-two WHO grade 2 and 28 grade 3 glioma patients were collected whose pre-surgical MRI and IDH1 mutation status were available. Heterogeneous lesions showed statistically higher Shannon entropy than homogenous lesions (p = 0.006) and ROC curve analysis proved that Shannon entropy on T2WI was a reliable indicator for discrimination of homogenous and heterogeneous lesions (p = 0.015, AUC = 0.73). Lesions with well-defined borders exhibited statistically higher Edge mean and Edge median values using Prewitt filtering than those with vague lesion borders (p = 0.0003 and p = 0.0005 respectively). ROC curve analysis also proved that both Edge mean and median values were promising indicators for discrimination of lesions with vague and well defined borders and both Edge mean and median values performed in a comparable manner (p = 0.0002, AUC = 0.81 and p image metrics that reflect lesion texture described on T2WI. These two metrics were validated by readings of a neuro-radiologist who was blinded to the results. This observation will facilitate further use of this technique in future large scale image analysis of glioma.

Silicate glasses corrosion. Texture analysis of the corrosion layer

International Nuclear Information System (INIS)

Portal, Sabine

2001-01-01

We have studied the kinetic and the texture evolution of the corroded layer that forms on glass surfaces exposed to acidic solutions. The corroded layer is depleted in alkali cations and is produced by an ion exchange mechanism. It is porous and shows a lower refractive index than the one of the bulk glass. Spectroscopic ellipsometry allows determining the thickness of the layer and its refractive index. Several other techniques have been developed for characterizing the corrosion behaviour of glass surfaces: porosity is thus investigated by adsorption-desorption of nitrogen; the thickness and the composition of the layer are studied by secondary ion mass spectroscopy (S.I.M.S.); sodium concentration in the solution has been analyzed by atomic absorption. This study shows the importance of leaching conditions and glass preparation. The type of drying employed is susceptible to modify the texture and the structure of the layer. The layers produced in the early stages of the leaching process are not easily detectable. The different results lead however to the same conclusion: after a strong increase of porosity, a densification of the layer is observed with increasing time. The evolution of the layer texture could therefore modify the kinetic of the glass corrosion. (author) [fr

SU-F-J-207: Non-Small Cell Lung Cancer Patient Survival Prediction with Quantitative Tumor Textures Analysis in Baseline CT

Energy Technology Data Exchange (ETDEWEB)

Wu, Y; Zou, J; Murillo, P; Nosher, J; Amorosa, J; Bramwit, M; Yue, N; Jabbour, S; Foran, D [Rutgers University, New Brunswick, NJ (United States)

2016-06-15

Purpose: Chemo-radiation therapy (CRT) is widely used in treating patients with locally advanced non-small cell lung cancer (NSCLC). Determination of the likelihood of patient response to treatment and optimization of treatment regime is of clinical significance. Up to date, no imaging biomarker has reliably correlated to NSCLC patient survival rate. This pilot study is to extract CT texture information from tumor regions for patient survival prediction. Methods: Thirteen patients with stage II-III NSCLC were treated using CRT with a median dose of 6210 cGy. Non-contrast-enhanced CT images were acquired for treatment planning and retrospectively collected for this study. Texture analysis was applied in segmented tumor regions using the Local Binary Pattern method (LBP). By comparing its HU with neighboring voxels, the LBPs of a voxel were measured in multiple scales with different group radiuses and numbers of neighbors. The LBP histograms formed a multi-dimensional texture vector for each patient, which was then used to establish and test a Support Vector Machine (SVM) model to predict patients’ one year survival. The leave-one-out cross validation strategy was used recursively to enlarge the training set and derive a reliable predictor. The predictions were compared with the true clinical outcomes. Results: A 10-dimensional LBP histogram was extracted from 3D segmented tumor region for each of the 13 patients. Using the SVM model with the leave-one-out strategy, only 1 out of 13 patients was misclassified. The experiments showed an accuracy of 93%, sensitivity of 100%, and specificity of 86%. Conclusion: Within the framework of a Support Vector Machine based model, the Local Binary Pattern method is able to extract a quantitative imaging biomarker in the prediction of NSCLC patient survival. More patients are to be included in the study.

SU-F-J-207: Non-Small Cell Lung Cancer Patient Survival Prediction with Quantitative Tumor Textures Analysis in Baseline CT

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