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

Texture Analysis Using Rényi’s Generalized Entropies

NARCIS (Netherlands)

Grigorescu, S.E.; Petkov, N.

2003-01-01

We propose a texture analysis method based on Rényi’s generalized 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

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.

Research of second harmonic generation images based on texture analysis

Science.gov (United States)

Liu, Yao; Li, Yan; Gong, Haiming; Zhu, Xiaoqin; Huang, Zufang; Chen, Guannan

2014-09-01

Texture analysis plays a crucial role in identifying objects or regions of interest in an image. It has been applied to a variety of medical image processing, ranging from the detection of disease and the segmentation of specific anatomical structures, to differentiation between healthy and pathological tissues. Second harmonic generation (SHG) microscopy as a potential noninvasive tool for imaging biological tissues has been widely used in medicine, with reduced phototoxicity and photobleaching. In this paper, we clarified the principles of texture analysis including statistical, transform, structural and model-based methods and gave examples of its applications, reviewing studies of the technique. Moreover, we tried to apply texture analysis to the SHG images for the differentiation of human skin scar tissues. Texture analysis method based on local binary pattern (LBP) and wavelet transform was used to extract texture features of SHG images from collagen in normal and abnormal scars, and then the scar SHG images were classified into normal or abnormal ones. Compared with other texture analysis methods with respect to the receiver operating characteristic analysis, LBP combined with wavelet transform was demonstrated to achieve higher accuracy. It can provide a new way for clinical diagnosis of scar types. At last, future development of texture analysis in SHG images were discussed.

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.)

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...

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.

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...

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)

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.

Texture analysis of Napoleonic War Era copper bolts

Science.gov (United States)

Malamud, Florencia; Northover, Shirley; James, Jon; Northover, Peter; Kelleher, Joe

2016-04-01

Neutron diffraction techniques are suitable for volume texture analyses due to high penetration of thermal neutrons in most materials. We have implemented a new data analysis methodology that employed the spatial resolution achievable by a time-of-flight neutron strain scanner to non-destructively determine the crystallographic texture at selected locations within a macroscopic sample. The method is based on defining the orientation distribution function of the crystallites from several incomplete pole figures, and it has been implemented on ENGIN-X, a neutron strain scanner at the Isis Facility in the UK. Here, we demonstrate the application of this new texture analysis methodology in determining the crystallographic texture at selected locations within museum quality archaeological objects up to 1 m in length. The results were verified using samples of similar, but less valuable, objects by comparing the results of applying this method with those obtained using both electron backscatter diffraction and X-ray diffraction on their cross sections.

Personal recognition using finger knuckle shape oriented features and texture analysis

Directory of Open Access Journals (Sweden)

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%.

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.

The promise and limits of PET texture analysis.

Science.gov (United States)

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)

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.

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.

Application of texture analysis method for mammogram density classification

Science.gov (United States)

Nithya, R.; Santhi, B.

2017-07-01

Mammographic density is considered a major risk factor for developing breast cancer. This paper proposes an automated approach to classify breast tissue types in digital mammogram. The main objective of the proposed Computer-Aided Diagnosis (CAD) system is to investigate various feature extraction methods and classifiers to improve the diagnostic accuracy in mammogram density classification. Texture analysis methods are used to extract the features from the mammogram. Texture features are extracted by using histogram, Gray Level Co-Occurrence Matrix (GLCM), Gray Level Run Length Matrix (GLRLM), Gray Level Difference Matrix (GLDM), Local Binary Pattern (LBP), Entropy, Discrete Wavelet Transform (DWT), Wavelet Packet Transform (WPT), Gabor transform and trace transform. These extracted features are selected using Analysis of Variance (ANOVA). The features selected by ANOVA are fed into the classifiers to characterize the mammogram into two-class (fatty/dense) and three-class (fatty/glandular/dense) breast density classification. This work has been carried out by using the mini-Mammographic Image Analysis Society (MIAS) database. Five classifiers are employed namely, Artificial Neural Network (ANN), Linear Discriminant Analysis (LDA), Naive Bayes (NB), K-Nearest Neighbor (KNN), and Support Vector Machine (SVM). Experimental results show that ANN provides better performance than LDA, NB, KNN and SVM classifiers. The proposed methodology has achieved 97.5% accuracy for three-class and 99.37% for two-class density classification.

Quantitative Analysis of Patellar Tendon Abnormality in Asymptomatic Professional “Pallapugno” Players: A Texture-Based Ultrasound Approach

Directory of Open Access Journals (Sweden)

Kristen M. Meiburger

2018-04-01

Full Text Available Abnormalities in B-mode ultrasound images of the patellar tendon often take place in asymptomatic athletes but it is still not clear if these modifications forego or can predict the development of tendinopathy. Subclinical tendinopathy can be arbitrarily defined as either (1 the presence of light structural changes in B-mode ultrasound images in association with mild neovascularization (determined with Power Doppler images or (2 the presence of moderate/severe structural changes with or without neovascularization. Up to now, the structural changes and neovascularization of the tendon are evaluated qualitatively by visual inspection of ultrasound images. The aim of this study is to investigate the capability of a quantitative texture-based approach to determine tendon abnormality of “pallapugno” players. B-mode ultrasound images of the patellar tendon were acquired in 14 players and quantitative texture parameters were calculated within a Region of Interest (ROI of both the non-dominant and the dominant tendon. A total of 90 features were calculated for each ROI, including 6 first-order descriptors, 24 Haralick features, and 60 higher-order spectra and entropy features. These features on the dominant and non-dominant side were used to perform a multivariate linear regression analysis (MANOVA and our results show that the descriptors can be effectively used to determine tendon abnormality and, more importantly, the occurrence of subclinical tendinopathy.

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

Linear feature selection in texture analysis - A PLS based method

DEFF Research Database (Denmark)

Marques, Joselene; Igel, Christian; Lillholm, Martin

2013-01-01

We present a texture analysis methodology that combined uncommitted machine-learning techniques and partial least square (PLS) in a fully automatic framework. Our approach introduces a robust PLS-based dimensionality reduction (DR) step to specifically address outliers and high-dimensional feature...... and considering all CV groups, the methods selected 36 % of the original features available. The diagnosis evaluation reached a generalization area-under-the-ROC curve of 0.92, which was higher than established cartilage-based markers known to relate to OA diagnosis....

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.

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.

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

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

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.

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.

"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.

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.

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 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...

Textural Analysis of Fatique Crack Surfaces: Image Pre-processing

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H. Lauschmann

2000-01-01

Full Text Available For the fatique crack history reconstitution, new methods of quantitative microfractography are beeing developed based on the image processing and textural analysis. SEM magnifications between micro- and macrofractography are used. Two image pre-processing operatins were suggested and proved to prepare the crack surface images for analytical treatment: 1. Normalization is used to transform the image to a stationary form. Compared to the generally used equalization, it conserves the shape of brightness distribution and saves the character of the texture. 2. Binarization is used to transform the grayscale image to a system of thick fibres. An objective criterion for the threshold brightness value was found as that resulting into the maximum number of objects. Both methods were succesfully applied together with the following textural analysis.

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

Textural analysis of early-phase spatiotemporal changes in contrast enhancement of breast lesions imaged with an ultrafast DCE-MRI protocol.

Science.gov (United States)

Milenković, Jana; Dalmış, Mehmet Ufuk; Žgajnar, Janez; Platel, Bram

2017-09-01

New ultrafast view-sharing sequences have enabled breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to be performed at high spatial and temporal resolution. The aim of this study is to evaluate the diagnostic potential of textural features that quantify the spatiotemporal changes of the contrast-agent uptake in computer-aided diagnosis of malignant and benign breast lesions imaged with high spatial and temporal resolution DCE-MRI. The proposed approach is based on the textural analysis quantifying the spatial variation of six dynamic features of the early-phase contrast-agent uptake of a lesion's largest cross-sectional area. The textural analysis is performed by means of the second-order gray-level co-occurrence matrix, gray-level run-length matrix and gray-level difference matrix. This yields 35 textural features to quantify the spatial variation of each of the six dynamic features, providing a feature set of 210 features in total. The proposed feature set is evaluated based on receiver operating characteristic (ROC) curve analysis in a cross-validation scheme for random forests (RF) and two support vector machine classifiers, with linear and radial basis function (RBF) kernel. Evaluation is done on a dataset with 154 breast lesions (83 malignant and 71 benign) and compared to a previous approach based on 3D morphological features and the average and standard deviation of the same dynamic features over the entire lesion volume as well as their average for the smaller region of the strongest uptake rate. The area under the ROC curve (AUC) obtained by the proposed approach with the RF classifier was 0.8997, which was significantly higher (P = 0.0198) than the performance achieved by the previous approach (AUC = 0.8704) on the same dataset. Similarly, the proposed approach obtained a significantly higher result for both SVM classifiers with RBF (P = 0.0096) and linear kernel (P = 0.0417) obtaining AUC of 0.8876 and 0.8548, respectively

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.

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

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.

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...

Fractal Dimension Analysis of Texture Formation of Whey Protein-Based Foods

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Robi Andoyo

2018-01-01

Full Text Available Whey protein in the form of isolate or concentrate is widely used in food industries due to its functionality to form gel under certain condition and its nutritive value. Controlling or manipulating the formation of gel aggregates is used often to evaluate food texture. Many researchers made use of fractal analysis that provides the quantitative data (i.e., fractal dimension for fundamentally and rationally analyzing and designing whey protein-based food texture. This quantitative analysis is also done to better understand how the texture of whey protein-based food is formed. Two methods for fractal analysis were discussed in this review: image analysis (microscopy and rheology. These methods, however, have several limitations which greatly affect the accuracy of both fractal dimension values and types of aggregation obtained. This review therefore also discussed problem encountered and ways to reduce the potential errors during fractal analysis of each method.

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

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.

TEXTURAL FRACTOGRAPHY

Directory of Open Access Journals (Sweden)

Hynek Lauschmann

2011-05-01

Full Text Available The reconstitution of the history of a fatigue process is based on the knowledge of any correspondences between the morphology of the crack surface and the velocity of the crack growth (crack growth rate - CGR. The textural fractography is oriented to mezoscopic SEM magnifications (30 to 500x. Images contain complicated textures without distinct borders. The aim is to find any characteristics of this texture, which correlate with CGR. Pre-processing of images is necessary to obtain a homogeneous texture. Three methods of textural analysis have been developed and realized as computational programs: the method based on the spectral structure of the image, the method based on a Gibbs random field (GRF model, and the method based on the idealization of light objects into a fibre process. In order to extract and analyze the fibre process, special methods - tracing fibres and a database-oriented analysis of a fibre process - have been developed.

Stato dell’arte nella sintesi di texture sonore

Directory of Open Access Journals (Sweden)

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.

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.

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)

Idiopathic interstitial pneumonias and emphysema: detection and classification using a texture-discriminative approach

Science.gov (United States)

Fetita, C.; Chang-Chien, K. C.; Brillet, P. Y.; Pr"teux, F.; Chang, R. F.

2012-03-01

Our study aims at developing a computer-aided diagnosis (CAD) system for fully automatic detection and classification of pathological lung parenchyma patterns in idiopathic interstitial pneumonias (IIP) and emphysema using multi-detector computed tomography (MDCT). The proposed CAD system is based on three-dimensional (3-D) mathematical morphology, texture and fuzzy logic analysis, and can be divided into four stages: (1) a multi-resolution decomposition scheme based on a 3-D morphological filter was exploited to discriminate the lung region patterns at different analysis scales. (2) An additional spatial lung partitioning based on the lung tissue texture was introduced to reinforce the spatial separation between patterns extracted at the same resolution level in the decomposition pyramid. Then, (3) a hierarchic tree structure was exploited to describe the relationship between patterns at different resolution levels, and for each pattern, six fuzzy membership functions were established for assigning a probability of association with a normal tissue or a pathological target. Finally, (4) a decision step exploiting the fuzzy-logic assignments selects the target class of each lung pattern among the following categories: normal (N), emphysema (EM), fibrosis/honeycombing (FHC), and ground glass (GDG). According to a preliminary evaluation on an extended database, the proposed method can overcome the drawbacks of a previously developed approach and achieve higher sensitivity and specificity.

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.

A dynamic texture based approach to recognition of facial actions and their temporal models

NARCIS (Netherlands)

Koelstra, Sander; Pantic, Maja; Patras, Ioannis (Yannis)

2010-01-01

In this work, we propose a dynamic texture-based approach to the recognition of facial Action Units (AUs, atomic facial gestures) and their temporal models (i.e., sequences of temporal segments: neutral, onset, apex, and offset) in near-frontal-view face videos. Two approaches to modeling the

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 °...

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.

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)

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

Directory of Open Access Journals (Sweden)

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.

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.

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

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.

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.

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.)

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.

Texture Analysis of satellite imagery in the field of biodiversity and forest structure of the Colombian Andes

International Nuclear Information System (INIS)

Anaya A, Jesus A; Duque L, Rosa A; Valencia H, German M

2008-01-01

The relationship between texture calculated from an Ikonos image with diversity and structure was evaluated along a corridor with 43 field plots in the Colombian Andes. Diversity indexes were calculated at the 43 plots and Land Use maps were used as an approach to vegetation structure. Texture was obtained from an Ikonos image using Gray Level Co-occurrence Matrix GLCM and Gray Level Difference Vector GLDV. Traditionally, texture has been interpreted from a qualitatively point of view from smooth to rough, however our approach using a matrix allows for a quantitative measurement. Texture was related to field information at two different detail levels: first with diversity measurements (Shannon Index and Richness) established at forest plots and second, with classes of a land use map (primary forest, secondary forests, forest plantation, crops and pastures) considered to be representative of vegetation structure. Results are based on relations between structure diversity,texture diversity and texture structure. Ikonos texture presents a large potential to classify forests at different successional stages however, the relation between diversity and data gathered with remote sensing is still weak. Landsat images are mentioned throughout the text as a reference or comparison with Ikonos images.

Texture analysis of cardiac cine magnetic resonance imaging to detect nonviable segments in patients with chronic myocardial infarction.

Science.gov (United States)

Larroza, Andrés; López-Lereu, María P; Monmeneu, José V; Gavara, Jose; Chorro, Francisco J; Bodí, Vicente; Moratal, David

2018-04-01

To investigate the ability of texture analysis to differentiate between infarcted nonviable, viable, and remote segments on cardiac cine magnetic resonance imaging (MRI). This retrospective study included 50 patients suffering chronic myocardial infarction. The data were randomly split into training (30 patients) and testing (20 patients) sets. The left ventricular myocardium was segmented according to the 17-segment model in both cine and late gadolinium enhancement (LGE) MRI. Infarcted myocardium regions were identified on LGE in short-axis views. Nonviable segments were identified as those showing LGE ≥ 50%, and viable segments those showing 0 cine images. A support vector machine (SVM) classifier was trained with different combination of texture features to obtain a model that provided optimal classification performance. The best classification on testing set was achieved with local binary patterns features using a 2D + t approach, in which the features are computed by including information of the time dimension available in cine sequences. The best overall area under the receiver operating characteristic curve (AUC) were: 0.849, sensitivity of 92% to detect nonviable segments, 72% to detect viable segments, and 85% to detect remote segments. Nonviable segments can be detected on cine MRI using texture analysis and this may be used as hypothesis for future research aiming to detect the infarcted myocardium by means of a gadolinium-free approach. © 2018 American Association of Physicists in Medicine.

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

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.

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.

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

textural analysis offer new opportunities to characterize the spatial and temporal variation of the structure of dense forests and may complement the toolbox used by tropical forest ecologists, managers or REDD+ national monitoring, reporting and verification bodies.

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

Comparation of instrumental and sensory methods in fermented milk beverages texture quality analysis

Directory of Open Access Journals (Sweden)

Jovica Hardi

2001-04-01

Full Text Available The texture of the curd of fermented dairy products is one of the primary factors of their overall quality. The flow properties of fermented dairy products have characteristic of thixotropic (pseudoplastic type of liquids. At the same time, these products are viscoelastic systems, i.e. they are capable of texture renewal after applied deformation. Complex analysis of some of the properties is essentional for the system description . The aim of the present work was to completely describe the texture of fermented milk beverages . Three basic parameters were taken into consideration: structure, hardness (consistency and stability of the curd. The description model of these three parameters was applied on the basis of the experimental results obteined. Results obtained by present model were compared with the results of sensory analysis. Influence of milk fat content and skimmed milk powder addition on acidophilus milk texture quality was also examined using this model. It was shawn that, by using this model – on the basis of instrumental and sensory analyses, a complete and objective determination of texture quality of the fermented milk beverages can be obtained. High degree of correlation between instrumental and sensory results (r =0.8975 is obtained results of this work indicated that both factors (milk fat content and skimmed milk powder addition had an influence on texture quality. Samples with higher milk fat content had a better texture properties in comparsion with low fat content samples. Texture of all examined samples was improved by increasing skimmed milk powder content. Optimal amounts of skimmed milk powder addition with regard to milk fat content, in milk, is determined using the proposed model.

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.

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

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.

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.

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...

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

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

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.

EFFECTIVE MULTI-RESOLUTION TRANSFORM IDENTIFICATION FOR CHARACTERIZATION AND CLASSIFICATION OF TEXTURE GROUPS

Directory of Open Access Journals (Sweden)

S. Arivazhagan

2011-11-01

Full Text Available Texture classification is important in applications of computer image analysis for characterization or classification of images based on local spatial variations of intensity or color. Texture can be defined as consisting of mutually related elements. This paper proposes an experimental approach for identification of suitable multi-resolution transform for characterization and classification of different texture groups based on statistical and co-occurrence features derived from multi-resolution transformed sub bands. The statistical and co-occurrence feature sets are extracted for various multi-resolution transforms such as Discrete Wavelet Transform (DWT, Stationary Wavelet Transform (SWT, Double Density Wavelet Transform (DDWT and Dual Tree Complex Wavelet Transform (DTCWT and then, the transform that maximizes the texture classification performance for the particular texture group is identified.

Texture studies of hot-pressed K2Pb4Nb10O30 ceramics

International Nuclear Information System (INIS)

Filip'ev, V.S.; Zav'yalov, V.P.; Bunina, O.A.; Gavrilyachenko, S.V.; Fesenko, E.G.

1984-01-01

An X-ray diffraction analysis was used to investigate the texture in sampl es of K 2 Pb 4 Nb 10 O 30 ferroelectric produced by powder hot pressing and sintering at 1370-1500 k. A spontaneous formation of the secondary texture during ferroelectric phase transformation was revealed. An important role of internal stresses in the secondary texture formation was supported. The ceramic s with a high-grade texture is noted to be characterized by a high anisotropy of dielectric and piezoelectric properties, its parameters approaching to those of a monocrystal

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.

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...

Decision Tree and Texture Analysis for Mapping Debris-Covered Glaciers in the Kangchenjunga Area, Eastern Himalaya

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Adina Racoviteanu

2012-10-01

Full Text Available In this study we use visible, short-wave infrared and thermal Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER data validated with high-resolution Quickbird (QB and Worldview2 (WV2 for mapping debris cover in the eastern Himalaya using two independent approaches: (a a decision tree algorithm, and (b texture analysis. The decision tree algorithm was based on multi-spectral and topographic variables, such as band ratios, surface reflectance, kinetic temperature from ASTER bands 10 and 12, slope angle, and elevation. The decision tree algorithm resulted in 64 km2 classified as debris-covered ice, which represents 11% of the glacierized area. Overall, for ten glacier tongues in the Kangchenjunga area, there was an area difference of 16.2 km2 (25% between the ASTER and the QB areas, with mapping errors mainly due to clouds and shadows. Texture analysis techniques included co-occurrence measures, geostatistics and filtering in spatial/frequency domain. Debris cover had the highest variance of all terrain classes, highest entropy and lowest homogeneity compared to the other classes, for example a mean variance of 15.27 compared to 0 for clouds and 0.06 for clean ice. Results of the texture image for debris-covered areas were comparable with those from the decision tree algorithm, with 8% area difference between the two techniques.

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

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

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.

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.

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.

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

Textural pattern classification for oral squamous cell carcinoma.

Science.gov (United States)

Rahman, T Y; Mahanta, L B; Chakraborty, C; DAS, A K; Sarma, J D

2018-01-01

Despite being an area of cancer with highest worldwide incidence, oral cancer yet remains to be widely researched. Studies on computer-aided analysis of pathological slides of oral cancer contribute a lot to the diagnosis and treatment of the disease. Some researches in this direction have been carried out on oral submucous fibrosis. In this work an approach for analysing abnormality based on textural features present in squamous cell carcinoma histological slides have been considered. Histogram and grey-level co-occurrence matrix approaches for extraction of textural features from biopsy images with normal and malignant cells are used here. Further, we have used linear support vector machine classifier for automated diagnosis of the oral cancer, which gives 100% accuracy. © 2017 The Authors Journal of Microscopy © 2017 Royal Microscopical Society.

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

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.

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

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

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.

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.)

Automatic system for radar echoes filtering based on textural features and artificial intelligence

Science.gov (United States)

Hedir, Mehdia; Haddad, Boualem

2017-10-01

Among the very popular Artificial Intelligence (AI) techniques, Artificial Neural Network (ANN) and Support Vector Machine (SVM) have been retained to process Ground Echoes (GE) on meteorological radar images taken from Setif (Algeria) and Bordeaux (France) with different climates and topologies. To achieve this task, AI techniques were associated with textural approaches. We used Gray Level Co-occurrence Matrix (GLCM) and Completed Local Binary Pattern (CLBP); both methods were largely used in image analysis. The obtained results show the efficiency of texture to preserve precipitations forecast on both sites with the accuracy of 98% on Bordeaux and 95% on Setif despite the AI technique used. 98% of GE are suppressed with SVM, this rate is outperforming ANN skills. CLBP approach associated to SVM eliminates 98% of GE and preserves precipitations forecast on Bordeaux site better than on Setif's, while it exhibits lower accuracy with ANN. SVM classifier is well adapted to the proposed application since the average filtering rate is 95-98% with texture and 92-93% with CLBP. These approaches allow removing Anomalous Propagations (APs) too with a better accuracy of 97.15% with texture and SVM. In fact, textural features associated to AI techniques are an efficient tool for incoherent radars to surpass spurious echoes.

Deep neural networks for texture classification-A theoretical analysis.

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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.

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...

Watermarking textures in video games

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Liu, Huajian; Berchtold, Waldemar; Schäfer, Marcel; Lieb, Patrick; Steinebach, Martin

2014-02-01

Digital watermarking is a promising solution to video game piracy. In this paper, based on the analysis of special challenges and requirements in terms of watermarking textures in video games, a novel watermarking scheme for DDS textures in video games is proposed. To meet the performance requirements in video game applications, the proposed algorithm embeds the watermark message directly in the compressed stream in DDS files and can be straightforwardly applied in watermark container technique for real-time embedding. Furthermore, the embedding approach achieves high watermark payload to handle collusion secure fingerprinting codes with extreme length. Hence, the scheme is resistant to collusion attacks, which is indispensable in video game applications. The proposed scheme is evaluated in aspects of transparency, robustness, security and performance. Especially, in addition to classical objective evaluation, the visual quality and playing experience of watermarked games is assessed subjectively in game playing.

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.

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

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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

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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.

TEXTURAL DESCRIPTORS FOR MULTIPHASIC ORE PARTICLES

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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.

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

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.

Efficient iris texture analysis method based on Gabor ordinal measures

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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.

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

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

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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

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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.

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

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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

Minimizing inter-microscope variability in dental microwear texture analysis

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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.

Differentiation of Uterine Leiomyosarcoma from Atypical Leiomyoma: Diagnostic Accuracy of Qualitative MR Imaging Features and Feasibility of Texture Analysis.

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Lakhman, Yulia; Veeraraghavan, Harini; Chaim, Joshua; Feier, Diana; Goldman, Debra A; Moskowitz, Chaya S; Nougaret, Stephanie; Sosa, Ramon E; Vargas, Hebert Alberto; Soslow, Robert A; Abu-Rustum, Nadeem R; Hricak, Hedvig; Sala, Evis

2017-07-01

To investigate whether qualitative magnetic resonance (MR) features can distinguish leiomyosarcoma (LMS) from atypical leiomyoma (ALM) and assess the feasibility of texture analysis (TA). This retrospective study included 41 women (ALM = 22, LMS = 19) imaged with MRI prior to surgery. Two readers (R1, R2) evaluated each lesion for qualitative MR features. Associations between MR features and LMS were evaluated with Fisher's exact test. Accuracy measures were calculated for the four most significant features. TA was performed for 24 patients (ALM = 14, LMS = 10) with uniform imaging following lesion segmentation on axial T2-weighted images. Texture features were pre-selected using Wilcoxon signed-rank test with Bonferroni correction and analyzed with unsupervised clustering to separate LMS from ALM. Four qualitative MR features most strongly associated with LMS were nodular borders, haemorrhage, "T2 dark" area(s), and central unenhanced area(s) (p ≤ 0.0001 each feature/reader). The highest sensitivity [1.00 (95%CI:0.82-1.00)/0.95 (95%CI: 0.74-1.00)] and specificity [0.95 (95%CI:0.77-1.00)/1.00 (95%CI:0.85-1.00)] were achieved for R1/R2, respectively, when a lesion had ≥3 of these four features. Sixteen texture features differed significantly between LMS and ALM (p-values: feasible. • Four qualitative MR features demonstrated the strongest statistical association with LMS. • Combination of ≥3 these features could accurately differentiate LMS from ALM. • Texture analysis was a feasible semi-automated approach for lesion categorization.

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

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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.

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

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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.

Characterization of Adrenal Lesions on Unenhanced MRI Using Texture Analysis: A Machine-Learning Approach.

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Romeo, Valeria; Maurea, Simone; Cuocolo, Renato; Petretta, Mario; Mainenti, Pier Paolo; Verde, Francesco; Coppola, Milena; Dell'Aversana, Serena; Brunetti, Arturo

2018-01-17

Adrenal adenomas (AA) are the most common benign adrenal lesions, often characterized based on intralesional fat content as either lipid-rich (LRA) or lipid-poor (LPA). The differentiation of AA, particularly LPA, from nonadenoma adrenal lesions (NAL) may be challenging. Texture analysis (TA) can extract quantitative parameters from MR images. Machine learning is a technique for recognizing patterns that can be applied to medical images by identifying the best combination of TA features to create a predictive model for the diagnosis of interest. To assess the diagnostic efficacy of TA-derived parameters extracted from MR images in characterizing LRA, LPA, and NAL using a machine-learning approach. Retrospective, observational study. Sixty MR examinations, including 20 LRA, 20 LPA, and 20 NAL. Unenhanced T 1 -weighted in-phase (IP) and out-of-phase (OP) as well as T 2 -weighted (T 2 -w) MR images acquired at 3T. Adrenal lesions were manually segmented, placing a spherical volume of interest on IP, OP, and T 2 -w images. Different selection methods were trained and tested using the J48 machine-learning classifiers. The feature selection method that obtained the highest diagnostic performance using the J48 classifier was identified; the diagnostic performance was also compared with that of a senior radiologist by means of McNemar's test. A total of 138 TA-derived features were extracted; among these, four features were selected, extracted from the IP (Short_Run_High_Gray_Level_Emphasis), OP (Mean_Intensity and Maximum_3D_Diameter), and T 2 -w (Standard_Deviation) images; the J48 classifier obtained a diagnostic accuracy of 80%. The expert radiologist obtained a diagnostic accuracy of 73%. McNemar's test did not show significant differences in terms of diagnostic performance between the J48 classifier and the expert radiologist. Machine learning conducted on MR TA-derived features is a potential tool to characterize adrenal lesions. 4 Technical Efficacy: Stage 2 J

Image-Based Three-Dimensional Analysis to Characterize the Texture of Porous Scaffolds

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Diana Massai

2014-01-01

Full Text Available The aim of the present study is to characterize the microstructure of composite scaffolds for bone tissue regeneration containing different ratios of chitosan/gelatin blend and bioactive glasses. Starting from realistic 3D models of the scaffolds reconstructed from micro-CT images, the level of heterogeneity of scaffold architecture is evaluated performing a lacunarity analysis. The results demonstrate that the presence of the bioactive glass component affects not only macroscopic features such as porosity, but mainly scaffold microarchitecture giving rise to structural heterogeneity, which could have an impact on the local cell-scaffold interaction and scaffold performances. The adopted approach allows to investigate the scale-dependent pore distribution within the scaffold and the related structural heterogeneity features, providing a comprehensive characterization of the scaffold texture.

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

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

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.

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)

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.

AUTOMATIC TEXTURE RECONSTRUCTION OF 3D CITY MODEL FROM OBLIQUE IMAGES

Directory of Open Access Journals (Sweden)

J. Kang

2016-06-01

Full Text Available In recent years, the photorealistic 3D city models are increasingly important in various geospatial applications related to virtual city tourism, 3D GIS, urban planning, real-estate management. Besides the acquisition of high-precision 3D geometric data, texture reconstruction is also a crucial step for generating high-quality and visually realistic 3D models. However, most of the texture reconstruction approaches are probably leading to texture fragmentation and memory inefficiency. In this paper, we introduce an automatic framework of texture reconstruction to generate textures from oblique images for photorealistic visualization. Our approach include three major steps as follows: mesh parameterization, texture atlas generation and texture blending. Firstly, mesh parameterization procedure referring to mesh segmentation and mesh unfolding is performed to reduce geometric distortion in the process of mapping 2D texture to 3D model. Secondly, in the texture atlas generation step, the texture of each segmented region in texture domain is reconstructed from all visible images with exterior orientation and interior orientation parameters. Thirdly, to avoid color discontinuities at boundaries between texture regions, the final texture map is generated by blending texture maps from several corresponding images. We evaluated our texture reconstruction framework on a dataset of a city. The resulting mesh model can get textured by created texture without resampling. Experiment results show that our method can effectively mitigate the occurrence of texture fragmentation. It is demonstrated that the proposed framework is effective and useful for automatic texture reconstruction of 3D city model.

Fast color/texture segmentation for outdoor robots

DEFF Research Database (Denmark)

Blas, Morten Rufus; Agrawal, Motilal; Sundaresan, Aravind

2008-01-01

We present a fast integrated approach for online segmentation of images for outdoor robots. A compact color and texture descriptor has been developed to describe local color and texture variations in an image. This descriptor is then used in a two-stage fast clustering framework using K...

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

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.

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

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.

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

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

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%.

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.)

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

Directory of Open Access Journals (Sweden)

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

Analysis of the right-handed Majorana neutrino mass in an S U (4 )×S U (2 )L×S U (2 )R Pati-Salam model with democratic texture

Science.gov (United States)

Yang, Masaki J. S.

2017-03-01

In this paper, we attempt to build a unified model with the democratic texture, that has some unification between up-type Yukawa interactions Yν and Yu . Since the S3 L×S3 R flavor symmetry is chiral, the unified gauge group is assumed to be Pati-Salam type S U (4 )c×S U (2 )L×S U (2 )R. The breaking scheme of the flavor symmetry is considered to be S3 L×S3 R→S2 L×S2 R→0 . In this picture, the four-zero texture is desirable for realistic masses and mixings. This texture is realized by a specific representation for the second breaking of the S3 L×S3 R flavor symmetry. Assuming only renormalizable Yukawa interactions, type-I seesaw mechanism, and neglecting C P phases for simplicity, the right-handed neutrino mass matrix MR can be reconstructed from low energy input values. Numerical analysis shows that the texture of MR basically behaves like the "waterfall texture." Since MR tends to be the "cascade texture" in the democratic texture approach, a model with type-I seesaw and up-type Yukawa unification Yν≃Yu basically requires fine-tunings between parameters. Therefore, it seems to be more realistic to consider universal waterfall textures for both Yf and MR, e.g., by the radiative mass generation or the Froggatt-Nielsen mechanism. Moreover, analysis of eigenvalues shows that the lightest mass eigenvalue MR 1 is too light to achieve successful thermal leptogenesis. Although the resonant leptogenesis might be possible, it also requires fine-tunings of parameters.

Visualizing Organic Textures and Biosignatures: Analysis of the Deep Biosphere, Meteorites, and Mars

Science.gov (United States)

Bhartia, R.

2017-12-01

Understanding life in the subsurface offers a unique understanding of how we can search for potential biosignatures on Mars. The spatial distri- bution of communities in this nutrient limited envi- ronment can be co-located with mineral facies, associ- ated to morphological features, or bound to zones of high potential energy. Comparing these organic textures to abotically driven processes in meteorites, when coupled to characterization of the organic con- tent, spatial relationships to mineralogical and ele- mental textures, and morphology will aid in our under- standing of the likely provenance of organics on Mars. Often we approach biosignatures detection with an earth-centric perspective where we assume that extant or ancient life leaves behind visible indicators; either as pigments used to absorb energy from the sun/radiation, protectant from UV radiation, or as veri- gated mineral facies that may persist in the rock rec- ord. Our analysis of subsurface life, a region that is decoupled from the photozone (decoupled from photo- synthesis) and/or exists in a nutrient limited environ- ment, has shown that we need to capitalize on a wider range of the electromagnetic spectrum over multiple spatial scales to understand where microbial life may exist, how they make a living, and how/if their signa- tures will persist geological time. Similar to the approach of the NAI Life Under- ground program, the Mars 2020 project includes a suite of instruments operating over the meter to micrometer scale that will observe the surface (and near subsur- face) of Mars from gamma rays to the IR - a range where minerals and organics reflect, absorb, and vi- brate. More specifically, the combined capabilities of both SHERLOC (a deep UV Raman/fluorescence spectrometer) and PIXL (an X-ray fluorescence spectrometer), spatial maps of organics minerals and elements will be correlated to morphology and textures to assess potential biosignatures. We present here our results of a spectral

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 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.

Texturing and modeling a procedural approach

CERN Document Server

Ebert, David S

1994-01-01

Congratulations to Ken Perlin for his 1997 Technical Achievement Award from the Academy of Motion Picture Arts and Science Board of Governors, given in recognition of the development of ""Turbulence"", Perlin Noise, a technique discussed in this book which is used to produce natural appearing textures on computer-generated surfaces for motion picture visual effects. Dr. Perlin joins Darwyn Peachey (co-developer of RenderMan(R), also discussed in the book) in being honored with this prestigious award.* * Written at a usable level by the developers of the techniques* Serves as a source book for

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

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

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.

Non-Hodgkin lymphoma response evaluation with MRI texture classification

Directory of Open Access Journals (Sweden)

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.

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

Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach.

Science.gov (United States)

Irshad, Humayun; Jalali, Sepehr; Roux, Ludovic; Racoceanu, Daniel; Hwee, Lim Joo; Naour, Gilles Le; Capron, Frédérique

2013-01-01

According to Nottingham grading system, mitosis count in breast cancer histopathology is one of three components required for cancer grading and prognosis. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. The aim is to investigate the various texture features and Hierarchical Model and X (HMAX) biologically inspired approach for mitosis detection using machine-learning techniques. We propose an approach that assists pathologists in automated mitosis detection and counting. The proposed method, which is based on the most favorable texture features combination, examines the separability between different channels of color space. Blue-ratio channel provides more discriminative information for mitosis detection in histopathological images. Co-occurrence features, run-length features, and Scale-invariant feature transform (SIFT) features were extracted and used in the classification of mitosis. Finally, a classification is performed to put the candidate patch either in the mitosis class or in the non-mitosis class. Three different classifiers have been evaluated: Decision tree, linear kernel Support Vector Machine (SVM), and non-linear kernel SVM. We also evaluate the performance of the proposed framework using the modified biologically inspired model of HMAX and compare the results with other feature extraction methods such as dense SIFT. The proposed method has been tested on Mitosis detection in breast cancer histological images (MITOS) dataset provided for an International Conference on Pattern Recognition (ICPR) 2012 contest. The proposed framework achieved 76% recall, 75% precision and 76% F-measure. Different frameworks for classification have been evaluated for mitosis detection. In future work, instead of regions, we intend to compute features on the results of mitosis contour segmentation and use them to improve detection and classification rate.

Profile fitting and the two-stage method in neutron powder diffractometry for structure and texture analysis

International Nuclear Information System (INIS)

Jansen, E.; Schaefer, W.; Will, G.; Kernforschungsanlage Juelich G.m.b.H.

1988-01-01

An outline and an application of the two-stage method in neutron powder diffractometry are presented. Stage (1): Individual reflection data like position, half-width and integrated intensity are analysed by profile fitting. The profile analysis is based on an experimentally determined instrument function and can be applied without prior knowledge of a structural model. A mathematical procedure is described which results in a variance-covariance matrix containing standard deviations and correlations of the refined reflection parameters. Stage (2): The individual reflection data derived from the profile fitting procedure can be used for appropriate purposes either in structure determination or in texture and strain or stress analysis. The integrated intensities are used in the non-diagonal weighted least-squares routine POWLS for structure refinement. The weight matrix is given by the inverted variance-covariance matrix of stage (1). This procedure is the basis for reliable and real Bragg R values and for a realistic estimation of standard deviations of structural parameters. In the case of texture analysis the integrated intensities are compiled into pole figures representing the intensity distribution for all sample orientations of individual hkl. Various examples for the wide application of the two-stage method in structure and texture analysis are given: Structure refinement of a standard quartz specimen, magnetic ordering in the system Tb x Y 1-x Ag, preferred orientation effects in deformed marble and texture investigations of a triclinic plagioclase. (orig.)

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

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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

Texture and anisotropy in ferroelectric lead metaniobate

Science.gov (United States)

Iverson, Benjamin John

Ferroelectric lead metaniobate, PbNb2O6, is a piezoelectric ceramic typically used because of its elevated Curie temperature and anisotropic properties. However, the piezoelectric constant, d33, is relatively low in randomly oriented ceramics when compared to other ferroelectrics. Crystallographic texturing is often employed to increase the piezoelectric constant because the spontaneous polarization axes of grains are better aligned. In this research, crystallographic textures induced through tape casting are distinguished from textures induced through electrical poling. Texture is described using multiple quantitative approaches utilizing X-ray and neutron time-of-flight diffraction. Tape casting lead metaniobate with an inclusion of acicular template particles induces an orthotropic texture distribution. Templated grain growth from seed particles oriented during casting results in anisotropic grain structures. The degree of preferred orientation is directly linked to the shear behavior of the tape cast slurry. Increases in template concentration, slurry viscosity, and casting velocity lead to larger textures by inducing more particle orientation in the tape casting plane. The maximum 010 texture distributions were two and a half multiples of a random distribution. Ferroelectric texture was induced by electrical poling. Electric poling increases the volume of material oriented with the spontaneous polarization direction in the material. Samples with an initial paraelectric texture exhibit a greater change in the domain volume fraction during electrical poling than randomly oriented ceramics. In tape cast samples, the resulting piezoelectric response is proportional to the 010 texture present prior to poling. This results in property anisotropy dependent on initial texture. Piezoelectric properties measured on the most textured ceramics were similar to those obtained with a commercial standard.

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.

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...

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

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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.

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

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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.

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

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.

Texture classification using non-Euclidean Minkowski dilation

Science.gov (United States)

Florindo, Joao B.; Bruno, Odemir M.

2018-03-01

This study presents a new method to extract meaningful descriptors of gray-scale texture images using Minkowski morphological dilation based on the Lp metric. The proposed approach is motivated by the success previously achieved by Bouligand-Minkowski fractal descriptors on texture classification. In essence, such descriptors are directly derived from the morphological dilation of a three-dimensional representation of the gray-level pixels using the classical Euclidean metric. In this way, we generalize the dilation for different values of p in the Lp metric (Euclidean is a particular case when p = 2) and obtain the descriptors from the cumulated distribution of the distance transform computed over the texture image. The proposed method is compared to other state-of-the-art approaches (such as local binary patterns and textons for example) in the classification of two benchmark data sets (UIUC and Outex). The proposed descriptors outperformed all the other approaches in terms of rate of images correctly classified. The interesting results suggest the potential of these descriptors in this type of task, with a wide range of possible applications to real-world problems.

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...

Measuring multiple nano-textured areas simultaneously with imaging scatterometry

DEFF Research Database (Denmark)

Madsen, Jonas Skovlund; Hansen, Poul Erik; Bilenberg, Brian

2017-01-01

and areas with defects can be avoided. These advantages make imaging scatterometry a very effective and user-friendly characterization method and allow us to determine the homogeneity of a nano- Textured surface by performing pixel-wise analyses. In the analysis an inverse modelling approach is used, where...... measured diffraction efficiencies are compared to simulated diffraction efficiencies using a least-square fitting approach. We demonstrate an imaging scatterometry setup built into an optical microscope. The setup is capable of measuring multiple 2D gratings with pitches of 200 nm simultaneously...

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.

Processing, properties, and application of textured 0.72lead(magnesium niobate)-0.28lead titanate ceramics

Science.gov (United States)

Brosnan, Kristen H.

In this study, XRD and electron backscatter diffraction (EBSD) techniques were used to characterize the fiber texture in oriented PMN-28PT and the intensity data were fit with a texture model (the March-Dollase equation) that describes the texture in terms of texture fraction (f), and the width of the orientation distribution (r). EBSD analysis confirmed the orientation of the microstructure, with no distinguishable randomly oriented, fine grain matrix. Although XRD rocking curve and EBSD data analysis gave similar f and r values, XRD rocking curve analysis was the most efficient and gave a complete description of texture fraction and texture orientation (f = 0.81 and r = 0.21, respectively). XRD rocking curve analysis was the preferred approach for characterization of the texture volume and the orientation distribution of texture in fiber-oriented PMN-PT. The dielectric, piezoelectric and electromechanical properties for random ceramic, 69 vol% textured, 81 vol% textured, and single crystal PMN-28PT were fully characterized and compared. The room temperature dielectric constant at 1 kHz for highly textured PMN-28PT was epsilonr ≥ 3600 with low dielectric loss (tan delta = 0.004). The temperature dependence of the dielectric constant for 81 vol% textured ceramic followed a similar trend as the single crystal PMN-28PT up to the rhombohedral to tetragonal transition temperature (TRT) at 104°C. 81 vol% textured PMN-28PT consistently displayed 60 to 65% of the single crystal PMN-28PT piezoelectric coefficient (d33) and 1.5 to 3.0 times greater than the random ceramic d33 (measured by Berlincourt meter, unipolar strain-field curves, IEEE standard resonance method, and laser vibrometry). The 81 vol% textured PMN-28PT displayed similarly low piezoelectric hysteresis as single crystal PMN-28PT measured by strain-field curves at 5 kV/cm. 81 vol% textured PMN-28PT and single crystal PMN-28PT displayed similar mechanical quality factors of QM = 74 and 76, respectively. The

Quaternion-Based Texture Analysis of Multiband Satellite Images: Application to the Estimation of Aboveground Biomass in the East Region of Cameroon.

Science.gov (United States)

Djiongo Kenfack, Cedrigue Boris; Monga, Olivier; Mpong, Serge Moto; Ndoundam, René

2018-03-01

Within the last decade, several approaches using quaternion numbers to handle and model multiband images in a holistic manner were introduced. The quaternion Fourier transform can be efficiently used to model texture in multidimensional data such as color images. For practical application, multispectral satellite data appear as a primary source for measuring past trends and monitoring changes in forest carbon stocks. In this work, we propose a texture-color descriptor based on the quaternion Fourier transform to extract relevant information from multiband satellite images. We propose a new multiband image texture model extraction, called FOTO++, in order to address biomass estimation issues. The first stage consists in removing noise from the multispectral data while preserving the edges of canopies. Afterward, color texture descriptors are extracted thanks to a discrete form of the quaternion Fourier transform, and finally the support vector regression method is used to deduce biomass estimation from texture indices. Our texture features are modeled using a vector composed with the radial spectrum coming from the amplitude of the quaternion Fourier transform. We conduct several experiments in order to study the sensitivity of our model to acquisition parameters. We also assess its performance both on synthetic images and on real multispectral images of Cameroonian forest. The results show that our model is more robust to acquisition parameters than the classical Fourier Texture Ordination model (FOTO). Our scheme is also more accurate for aboveground biomass estimation. We stress that a similar methodology could be implemented using quaternion wavelets. These results highlight the potential of the quaternion-based approach to study multispectral satellite images.

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.

Adaptive Matrices for Color Texture Classification

NARCIS (Netherlands)

Bunte, Kerstin; Giotis, Ioannis; Petkov, Nicolai; Biehl, Michael; Real, P; DiazPernil, D; MolinaAbril, H; Berciano, A; Kropatsch, W

2011-01-01

In this paper we introduce an integrative approach towards color texture classification learned by a supervised framework. Our approach is based on the Generalized Learning Vector Quantization (GLVQ), extended by an adaptive distance measure which is defined in the Fourier domain and 2D Gabor

Automated mitosis detection using texture, SIFT features and HMAX biologically inspired approach

Directory of Open Access Journals (Sweden)

Humayun Irshad

2013-01-01

Full Text Available Context: According to Nottingham grading system, mitosis count in breast cancer histopathology is one of three components required for cancer grading and prognosis. Manual counting of mitosis is tedious and subject to considerable inter- and intra-reader variations. Aims: The aim is to investigate the various texture features and Hierarchical Model and X (HMAX biologically inspired approach for mitosis detection using machine-learning techniques. Materials and Methods: We propose an approach that assists pathologists in automated mitosis detection and counting. The proposed method, which is based on the most favorable texture features combination, examines the separability between different channels of color space. Blue-ratio channel provides more discriminative information for mitosis detection in histopathological images. Co-occurrence features, run-length features, and Scale-invariant feature transform (SIFT features were extracted and used in the classification of mitosis. Finally, a classification is performed to put the candidate patch either in the mitosis class or in the non-mitosis class. Three different classifiers have been evaluated: Decision tree, linear kernel Support Vector Machine (SVM, and non-linear kernel SVM. We also evaluate the performance of the proposed framework using the modified biologically inspired model of HMAX and compare the results with other feature extraction methods such as dense SIFT. Results: The proposed method has been tested on Mitosis detection in breast cancer histological images (MITOS dataset provided for an International Conference on Pattern Recognition (ICPR 2012 contest. The proposed framework achieved 76% recall, 75% precision and 76% F-measure. Conclusions: Different frameworks for classification have been evaluated for mitosis detection. In future work, instead of regions, we intend to compute features on the results of mitosis contour segmentation and use them to improve detection and

Ultrasound image texture processing for evaluating fatty liver in peripartal dairy cows

Science.gov (United States)

Amin, Viren R.; Bobe, Gerd; Young, Jerry; Ametaj, Burim; Beitz, Donald

2001-07-01

The objective of this work is to characterize the liver ultrasound texture as it changes in diffuse disease of fatty liver. This technology could allow non-invasive diagnosis of fatty liver, a major metabolic disorder in early lactation dairy cows. More than 100 liver biopsies were taken from fourteen dairy cows, as a part of the USDA-funded study for effects of glucagon on prevention and treatment of fatty liver. Up to nine liver biopsies were taken from each cow during peripartal period of seven weeks and total lipid content was determined chemically. Just before each liver biopsy was taken, ultrasonic B-mode images were digitally captured using a 3.5 or 5 MHz transducer. Effort was made to capture images that were non-blurred, void of large blood vessels and multiple echoes, and of consistent texture. From each image, a region-of-interest of size 100-by-100 pixels was processed. Texture parameters were calculated using algorithms such as first and second order statistics, 2D Fourier transformation, co-occurrence matrix, and gradient analysis. Many cows had normal liver (3% to 6% total lipid) and a few had developed fatty liver with total lipid up to 15%. The selected texture parameters showed consistent change with changing lipid content and could potentially be used to diagnose early fatty liver non-invasively. The approach of texture analysis algorithms and initial results on their potential in evaluating total lipid percentage is presented here.

Local binary pattern variants-based adaptive texture features analysis for posed and nonposed facial expression recognition

Science.gov (United States)

Sultana, Maryam; Bhatti, Naeem; Javed, Sajid; Jung, Soon Ki

2017-09-01

Facial expression recognition (FER) is an important task for various computer vision applications. The task becomes challenging when it requires the detection and encoding of macro- and micropatterns of facial expressions. We present a two-stage texture feature extraction framework based on the local binary pattern (LBP) variants and evaluate its significance in recognizing posed and nonposed facial expressions. We focus on the parametric limitations of the LBP variants and investigate their effects for optimal FER. The size of the local neighborhood is an important parameter of the LBP technique for its extraction in images. To make the LBP adaptive, we exploit the granulometric information of the facial images to find the local neighborhood size for the extraction of center-symmetric LBP (CS-LBP) features. Our two-stage texture representations consist of an LBP variant and the adaptive CS-LBP features. Among the presented two-stage texture feature extractions, the binarized statistical image features and adaptive CS-LBP features were found showing high FER rates. Evaluation of the adaptive texture features shows competitive and higher performance than the nonadaptive features and other state-of-the-art approaches, respectively.

Automatic brain MR image denoising based on texture feature-based artificial neural networks.

Science.gov (United States)

Chang, Yu-Ning; Chang, Herng-Hua

2015-01-01

Noise is one of the main sources of quality deterioration not only for visual inspection but also in computerized processing in brain magnetic resonance (MR) image analysis such as tissue classification, segmentation and registration. Accordingly, noise removal in brain MR images is important for a wide variety of subsequent processing applications. However, most existing denoising algorithms require laborious tuning of parameters that are often sensitive to specific image features and textures. Automation of these parameters through artificial intelligence techniques will be highly beneficial. In the present study, an artificial neural network associated with image texture feature analysis is proposed to establish a predictable parameter model and automate the denoising procedure. In the proposed approach, a total of 83 image attributes were extracted based on four categories: 1) Basic image statistics. 2) Gray-level co-occurrence matrix (GLCM). 3) Gray-level run-length matrix (GLRLM) and 4) Tamura texture features. To obtain the ranking of discrimination in these texture features, a paired-samples t-test was applied to each individual image feature computed in every image. Subsequently, the sequential forward selection (SFS) method was used to select the best texture features according to the ranking of discrimination. The selected optimal features were further incorporated into a back propagation neural network to establish a predictable parameter model. A wide variety of MR images with various scenarios were adopted to evaluate the performance of the proposed framework. Experimental results indicated that this new automation system accurately predicted the bilateral filtering parameters and effectively removed the noise in a number of MR images. Comparing to the manually tuned filtering process, our approach not only produced better denoised results but also saved significant processing time.

Synthesis of nano-textured biocompatible scaffolds from chicken eggshells

International Nuclear Information System (INIS)

Asghar, Waseem; Ilyas, Azhar; Sankaran, Jeyantt; Wan Yuan; Iqbal, Samir M; Kim, Young-Tae

2012-01-01

Cell adhesion, morphology and growth are influenced by surface topography at nano and micrometer scales. Nano-textured surfaces are prepared using photolithography, plasma etching and long polymer chemical etching which are cost prohibitive and require specialized equipment. This article demonstrates a simple approach to synthesize nano-textured scaffolds from chicken eggshells. Varieties of pattern are made on the eggshells like micro-needle forests and nanopores, giving very uniform nano-textures to the surfaces. The surfaces are characterized for chemical composition and crystal phase. The novel patterns are transferred to PDMS surfaces and the nano-textured PDMS surfaces are used to study the effect of texturing on human fibroblast cell growth and attachment. The effects of surface topographies, along with laminin coating on cell cultures, are also studied. We find an exciting phenomenon that the initial seeding density of the fibroblast cells affects the influence of the nano-texturing on cell growth. These nano-textured surfaces give 16 times more fibroblast growth when compared to flat PDMS surfaces. The novel nano-textured patterns also double the laminin adsorption on PDMS. (paper)

Two-dimensional numerical simulation of boron diffusion for pyramidally textured silicon

International Nuclear Information System (INIS)

Ma, Fa-Jun; Duttagupta, Shubham; Shetty, Kishan Devappa; Meng, Lei; Hoex, Bram; Peters, Ian Marius; Samudra, Ganesh S.

2014-01-01

Multidimensional numerical simulation of boron diffusion is of great relevance for the improvement of industrial n-type crystalline silicon wafer solar cells. However, surface passivation of boron diffused area is typically studied in one dimension on planar lifetime samples. This approach neglects the effects of the solar cell pyramidal texture on the boron doping process and resulting doping profile. In this work, we present a theoretical study using a two-dimensional surface morphology for pyramidally textured samples. The boron diffusivity and segregation coefficient between oxide and silicon in simulation are determined by reproducing measured one-dimensional boron depth profiles prepared using different boron diffusion recipes on planar samples. The established parameters are subsequently used to simulate the boron diffusion process on textured samples. The simulated junction depth is found to agree quantitatively well with electron beam induced current measurements. Finally, chemical passivation on planar and textured samples is compared in device simulation. Particularly, a two-dimensional approach is adopted for textured samples to evaluate chemical passivation. The intrinsic emitter saturation current density, which is only related to Auger and radiative recombination, is also simulated for both planar and textured samples. The differences between planar and textured samples are discussed

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.

Clinical applications of textural analysis in non-small cell lung cancer.

Science.gov (United States)

Phillips, Iain; Ajaz, Mazhar; Ezhil, Veni; Prakash, Vineet; Alobaidli, Sheaka; McQuaid, Sarah J; South, Christopher; Scuffham, James; Nisbet, Andrew; Evans, Philip

2018-01-01

Lung cancer is the leading cause of cancer mortality worldwide. Treatment pathways include regular cross-sectional imaging, generating large data sets which present intriguing possibilities for exploitation beyond standard visual interpretation. This additional data mining has been termed "radiomics" and includes semantic and agnostic approaches. Textural analysis (TA) is an example of the latter, and uses a range of mathematically derived features to describe an image or region of an image. Often TA is used to describe a suspected or known tumour. TA is an attractive tool as large existing image sets can be submitted to diverse techniques for data processing, presentation, interpretation and hypothesis testing with annotated clinical outcomes. There is a growing anthology of published data using different TA techniques to differentiate between benign and malignant lung nodules, differentiate tissue subtypes of lung cancer, prognosticate and predict outcome and treatment response, as well as predict treatment side effects and potentially aid radiotherapy planning. The aim of this systematic review is to summarize the current published data and understand the potential future role of TA in managing lung cancer.

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.

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 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....

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.

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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

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

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)

A statistical-textural-features based approach for classification of solid drugs using surface microscopic images.

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Tahir, Fahima; Fahiem, Muhammad Abuzar

2014-01-01

The quality of pharmaceutical products plays an important role in pharmaceutical industry as well as in our lives. Usage of defective tablets can be harmful for patients. In this research we proposed a nondestructive method to identify defective and nondefective tablets using their surface morphology. Three different environmental factors temperature, humidity and moisture are analyzed to evaluate the performance of the proposed method. Multiple textural features are extracted from the surface of the defective and nondefective tablets. These textural features are gray level cooccurrence matrix, run length matrix, histogram, autoregressive model and HAAR wavelet. Total textural features extracted from images are 281. We performed an analysis on all those 281, top 15, and top 2 features. Top 15 features are extracted using three different feature reduction techniques: chi-square, gain ratio and relief-F. In this research we have used three different classifiers: support vector machine, K-nearest neighbors and naïve Bayes to calculate the accuracies against proposed method using two experiments, that is, leave-one-out cross-validation technique and train test models. We tested each classifier against all selected features and then performed the comparison of their results. The experimental work resulted in that in most of the cases SVM performed better than the other two classifiers.

Binary patterns encoded convolutional neural networks for texture recognition and remote sensing scene classification

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Anwer, Rao Muhammad; Khan, Fahad Shahbaz; van de Weijer, Joost; Molinier, Matthieu; Laaksonen, Jorma

2018-04-01

Designing discriminative powerful texture features robust to realistic imaging conditions is a challenging computer vision problem with many applications, including material recognition and analysis of satellite or aerial imagery. In the past, most texture description approaches were based on dense orderless statistical distribution of local features. However, most recent approaches to texture recognition and remote sensing scene classification are based on Convolutional Neural Networks (CNNs). The de facto practice when learning these CNN models is to use RGB patches as input with training performed on large amounts of labeled data (ImageNet). In this paper, we show that Local Binary Patterns (LBP) encoded CNN models, codenamed TEX-Nets, trained using mapped coded images with explicit LBP based texture information provide complementary information to the standard RGB deep models. Additionally, two deep architectures, namely early and late fusion, are investigated to combine the texture and color information. To the best of our knowledge, we are the first to investigate Binary Patterns encoded CNNs and different deep network fusion architectures for texture recognition and remote sensing scene classification. We perform comprehensive experiments on four texture recognition datasets and four remote sensing scene classification benchmarks: UC-Merced with 21 scene categories, WHU-RS19 with 19 scene classes, RSSCN7 with 7 categories and the recently introduced large scale aerial image dataset (AID) with 30 aerial scene types. We demonstrate that TEX-Nets provide complementary information to standard RGB deep model of the same network architecture. Our late fusion TEX-Net architecture always improves the overall performance compared to the standard RGB network on both recognition problems. Furthermore, our final combination leads to consistent improvement over the state-of-the-art for remote sensing scene classification.

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

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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.

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.

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.

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 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.

Reliable Fault Classification of Induction Motors Using Texture Feature Extraction and a Multiclass Support Vector Machine

Directory of Open Access Journals (Sweden)

Jia Uddin

2014-01-01

Full Text Available This paper proposes a method for the reliable fault detection and classification of induction motors using two-dimensional (2D texture features and a multiclass support vector machine (MCSVM. The proposed model first converts time-domain vibration signals to 2D gray images, resulting in texture patterns (or repetitive patterns, and extracts these texture features by generating the dominant neighborhood structure (DNS map. The principal component analysis (PCA is then used for the purpose of dimensionality reduction of the high-dimensional feature vector including the extracted texture features due to the fact that the high-dimensional feature vector can degrade classification performance, and this paper configures an effective feature vector including discriminative fault features for diagnosis. Finally, the proposed approach utilizes the one-against-all (OAA multiclass support vector machines (MCSVMs to identify induction motor failures. In this study, the Gaussian radial basis function kernel cooperates with OAA MCSVMs to deal with nonlinear fault features. Experimental results demonstrate that the proposed approach outperforms three state-of-the-art fault diagnosis algorithms in terms of fault classification accuracy, yielding an average classification accuracy of 100% even in noisy environments.

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...

Artificial intelligence systems based on texture descriptors for vaccine development.

Science.gov (United States)

Nanni, Loris; Brahnam, Sheryl; Lumini, Alessandra

2011-02-01

The aim of this work is to analyze and compare several feature extraction methods for peptide classification that are based on the calculation of texture descriptors starting from a matrix representation of the peptide. This texture-based representation of the peptide is then used to train a support vector machine classifier. In our experiments, the best results are obtained using local binary patterns variants and the discrete cosine transform with selected coefficients. These results are better than those previously reported that employed texture descriptors for peptide representation. In addition, we perform experiments that combine standard approaches based on amino acid sequence. The experimental section reports several tests performed on a vaccine dataset for the prediction of peptides that bind human leukocyte antigens and on a human immunodeficiency virus (HIV-1). Experimental results confirm the usefulness of our novel descriptors. The matlab implementation of our approaches is available at http://bias.csr.unibo.it/nanni/TexturePeptide.zip.

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

Directory of Open Access Journals (Sweden)

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.

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

''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.)

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.

Fusion of geometric and texture features for finger knuckle surface recognition

Directory of Open Access Journals (Sweden)

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%.

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.

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

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...

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...

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).

Automated migration analysis based on cell texture: method & reliability

Directory of Open Access Journals (Sweden)

Chittenden Thomas W

2005-03-01

Full Text Available Abstract Background In this paper, we present and validate a way to measure automatically the extent of cell migration based on automated examination of a series of digital photographs. It was designed specifically to identify the impact of Second Hand Smoke (SHS on endothelial cell migration but has broader applications. The analysis has two stages: (1 preprocessing of image texture, and (2 migration analysis. Results The output is a graphic overlay that indicates the front lines of cell migration superimposed on each original image, with automated reporting of the distance traversed vs. time. Expert preference compares to manual placement of leading edge shows complete equivalence of automated vs. manual leading edge definition for cell migration measurement. Conclusion Our method is indistinguishable from careful manual determinations of cell front lines, with the advantages of full automation, objectivity, and speed.

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.

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 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.

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.

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.

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.

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.

Adaptive Matrices and Filters for Color Texture Classification

NARCIS (Netherlands)

Giotis, Ioannis; Bunte, Kerstin; Petkov, Nicolai; Biehl, Michael

In this paper we introduce an integrative approach towards color texture classification and recognition using a supervised learning framework. Our approach is based on Generalized Learning Vector Quantization (GLVQ), extended by an adaptive distance measure, which is defined in the Fourier domain,

Texture collapse

International Nuclear Information System (INIS)

Prokopec, T.; Sornborger, A.; Brandenberger, R.H.

1992-01-01

We study single-texture collapse using a leapfrog discretization method on a 30x30x30 spatial lattice. We investigate the influence of boundary conditions, physical size of the lattice, type of space-time background (flat, i.e., nonexpanding, vs radiation-dominated and matter-dominated universes), and spatial distribution of the initial texture configuration on collapse time and critical winding. For a spherically symmetric initial configuration of size equal to the horizon size on a lattice containing 12 (30) horizon volumes, the critical winding is found to be 0.621±0.001 (0.602±0.003) (flat case), 0.624±0.002 (0.604±0.005) (radiation era), 0.628±0.002 (0.612±0.003) (matter era). The larger the physical size of the lattice (in units of the horizon size), the smaller is the critical winding, and in the limit of an infinite lattice, we argue that the critical winding approaches 0.5. For radially asymmetric cases, contraction of one axis ( /Ipancake case) slightly reduces collapse time and critical winding, and contraction of two axes (d/Icigar case) reduces collapse time and critical winding significantly

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.

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

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.

AUTOMATIC APPROACH TO VHR SATELLITE IMAGE CLASSIFICATION

Directory of Open Access Journals (Sweden)

P. Kupidura

2016-06-01

Full Text Available In this paper, we present a proposition of a fully automatic classification of VHR satellite images. Unlike the most widespread approaches: supervised classification, which requires prior defining of class signatures, or unsupervised classification, which must be followed by an interpretation of its results, the proposed method requires no human intervention except for the setting of the initial parameters. The presented approach bases on both spectral and textural analysis of the image and consists of 3 steps. The first step, the analysis of spectral data, relies on NDVI values. Its purpose is to distinguish between basic classes, such as water, vegetation and non-vegetation, which all differ significantly spectrally, thus they can be easily extracted basing on spectral analysis. The second step relies on granulometric maps. These are the product of local granulometric analysis of an image and present information on the texture of each pixel neighbourhood, depending on the texture grain. The purpose of texture analysis is to distinguish between different classes, spectrally similar, but yet of different texture, e.g. bare soil from a built-up area, or low vegetation from a wooded area. Due to the use of granulometric analysis, based on mathematical morphology opening and closing, the results are resistant to the border effect (qualifying borders of objects in an image as spaces of high texture, which affect other methods of texture analysis like GLCM statistics or fractal analysis. Therefore, the effectiveness of the analysis is relatively high. Several indices based on values of different granulometric maps have been developed to simplify the extraction of classes of different texture. The third and final step of the process relies on a vegetation index, based on near infrared and blue bands. Its purpose is to correct partially misclassified pixels. All the indices used in the classification model developed relate to reflectance values, so the

Texture analysis by the Schulz reflection method: Defocalization corrections for thin films

International Nuclear Information System (INIS)

Chateigner, D.; Germi, P.; Pernet, M.

1992-01-01

A new method is described for correcting experimental data obtained from the texture analysis of thin films. The analysis employed for correcting the data usually requires the experimental curves of defocalization for a randomly oriented specimen. In view of difficulties in finding non-oriented films, a theoretical method for these corrections is proposed which uses the defocalization evolution for a bulk sample, the film thickness and the penetration depth of the incident beam in the material. This correction method is applied to a film of YBa 2 CU 3 O 7-δ on an SrTiO 3 single-crystal substrate. (orig.)

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...

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

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.

Epitaxial YBa2Cu3O7 on biaxially textured (001) Ni: An approach to high critical current density superconducting tapes

International Nuclear Information System (INIS)

Norton, D.P.; Goyal, A.; Budai, J.D.

1997-01-01

In-plane aligned, c-axis oriented YBa 2 Cu 3 O 7 (YBCO) films with superconducting critical current densities, J c , as high as 700,000 amperes per square centimeter at 77 kelvin have been grown on thermo-mechanically, rolled-textured (001) Ni tapes using pulsed-laser deposition. Epitaxial growth of oxide buffer layers directly on biaxially textured Ni, formed by recrystallization of cold-rolled pure Ni, enables the growth of 1.5 micrometer-thick YBCO films with superconducting properties that are comparable to those observed for epitaxial films on single crystal oxide substrates. This result represents a viable approach for producing long-length superconducting tapes for high current, high field applications at 77 kelvin

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

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.

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

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)

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

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)

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

Using texture analysis to improve per-pixel classification of very high resolution images for mapping plastic greenhouses

Science.gov (United States)

Agüera, Francisco; Aguilar, Fernando J.; Aguilar, Manuel A.

The area occupied by plastic-covered greenhouses has undergone rapid growth in recent years, currently exceeding 500,000 ha worldwide. Due to the vast amount of input (water, fertilisers, fuel, etc.) required, and output of different agricultural wastes (vegetable, plastic, chemical, etc.), the environmental impact of this type of production system can be serious if not accompanied by sound and sustainable territorial planning. For this, the new generation of satellites which provide very high resolution imagery, such as QuickBird and IKONOS can be useful. In this study, one QuickBird and one IKONOS satellite image have been used to cover the same area under similar circumstances. The aim of this work was an exhaustive comparison of QuickBird vs. IKONOS images in land-cover detection. In terms of plastic greenhouse mapping, comparative tests were designed and implemented, each with separate objectives. Firstly, the Maximum Likelihood Classification (MLC) was applied using five different approaches combining R, G, B, NIR, and panchromatic bands. The combinations of the bands used, significantly influenced some of the indexes used to classify quality in this work. Furthermore, the quality classification of the QuickBird image was higher in all cases than that of the IKONOS image. Secondly, texture features derived from the panchromatic images at different window sizes and with different grey levels were added as a fifth band to the R, G, B, NIR images to carry out the MLC. The inclusion of texture information in the classification did not improve the classification quality. For classifications with texture information, the best accuracies were found in both images for mean and angular second moment texture parameters. The optimum window size in these texture parameters was 3×3 for IK images, while for QB images it depended on the quality index studied, but the optimum window size was around 15×15. With regard to the grey level, the optimum was 128. Thus, the

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.

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.)

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.

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.

Dark texture in artworks

Science.gov (United States)

Parraman, Carinna

2012-01-01

This presentation highlights issues relating to the digital capture printing of 2D and 3D artefacts and accurate colour reproduction of 3D objects. There are a range of opportunities and technologies for the scanning and printing of two-dimensional and threedimensional artefacts [1]. A successful approach of Polynomial Texture Mapping (PTM) technique, to create a Reflectance Transformation Image (RTI) [2-4] is being used for the conservation and heritage of artworks as these methods are non invasive or non destructive of fragile artefacts. This approach captures surface detail of twodimensional artworks using a multidimensional approach that by using a hemispherical dome comprising 64 lamps to create an entire surface topography. The benefits of this approach are to provide a highly detailed visualization of the surface of materials and objects.

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.

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...

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

Saturated hydraulic conductivity of US soils grouped according textural class and bulk density

Science.gov (United States)

Importance of the saturated hydraulic conductivity as soil hydraulic property led to the development of multiple pedotransfer functions for estimating it. One approach to estimating Ksat was using textural classes rather than specific textural fraction contents as pedotransfer inputs. The objective...

Automatic Detection of Optic Disc in Retinal Image by Using Keypoint Detection, Texture Analysis, and Visual Dictionary Techniques

Directory of Open Access Journals (Sweden)

Kemal Akyol

2016-01-01

Full Text Available With the advances in the computer field, methods and techniques in automatic image processing and analysis provide the opportunity to detect automatically the change and degeneration in retinal images. Localization of the optic disc is extremely important for determining the hard exudate lesions or neovascularization, which is the later phase of diabetic retinopathy, in computer aided eye disease diagnosis systems. Whereas optic disc detection is fairly an easy process in normal retinal images, detecting this region in the retinal image which is diabetic retinopathy disease may be difficult. Sometimes information related to optic disc and hard exudate information may be the same in terms of machine learning. We presented a novel approach for efficient and accurate localization of optic disc in retinal images having noise and other lesions. This approach is comprised of five main steps which are image processing, keypoint extraction, texture analysis, visual dictionary, and classifier techniques. We tested our proposed technique on 3 public datasets and obtained quantitative results. Experimental results show that an average optic disc detection accuracy of 94.38%, 95.00%, and 90.00% is achieved, respectively, on the following public datasets: DIARETDB1, DRIVE, and ROC.

SU-E-J-265: Feasibility Study of Texture Analysis for Prognosis of Local Tumor Recurrence Within 5-Years for Pharyngeal-Laryngeal Carcinoma Patients Received Radiotherapy Treatment

Energy Technology Data Exchange (ETDEWEB)

Huang, W; Tu, S [Chang Gung University, Kwei-shan, Tao-Yuan, Taiwan (China)

2015-06-15

Purpose: Pharyngeal and laryngeal carcinomas (PLC) are among the top leading cancers in Asian populations. Typically the tumor may recur and progress in a short period of time if radiotherapy fails to deliver a successful treatment. Here we used image texture features extracted from images of computed tomography (CT) planning and conducted a retrospective study to evaluate whether texture analysis is a feasible approach to predict local tumor recurrence for PLC patients received radiotherapy treatment. Methods: CT planning images of 100 patients with PLC treated by radiotherapy at our facility between 2001 and 2010 are collected. These patients were received two separate CT scans, before and mid-course of the treatment delivery. Before the radiotherapy, a CT scanning was used for the first treatment planning. A total of 30 fractions were used in the treatment and patients were scanned with a second CT around the end of the fifteenth delivery for an adaptive treatment planning. Only patients who were treated with intensity modulated radiation therapy and RapidArc were selected. Treatment planning software of Eclipse was used. The changes of texture parameters between two CT acquisitions were computed to determine whether they were correlated to the local tumor recurrence. The following texture parameters were used in the preliminary assessment: mean, variance, standard deviation, skewness, kurtosis, energy, entropy, inverse difference moment, cluster shade, inertia, cluster prominence, gray-level co-occurrence matrix, and gray-level run-length matrix. The study was reviewed and approved by the committee of our institutional review board. Results: Our calculations suggested the following texture parameters were correlated with the local tumor recurrence: skewness, kurtosis, entropy, and inertia (p<0.0.05). Conclusion: The preliminary results were positive. However some works remain crucial to be completed, including addition of texture parameters for different image

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.

Texture analysis of B-mode ultrasound images to stage hepatic lipidosis in the dairy cow: A methodological study.

Science.gov (United States)

Banzato, Tommaso; Fiore, Enrico; Morgante, Massimo; Manuali, Elisabetta; Zotti, Alessandro

2016-10-01

Hepatic lipidosis is the most diffused hepatic disease in the lactating cow. A new methodology to estimate the degree of fatty infiltration of the liver in lactating cows by means of texture analysis of B-mode ultrasound images is proposed. B-mode ultrasonography of the liver was performed in 48 Holstein Friesian cows using standardized ultrasound parameters. Liver biopsies to determine the triacylglycerol content of the liver (TAGqa) were obtained from each animal. A large number of texture parameters were calculated on the ultrasound images by means of a free software. Based on the TAGqa content of the liver, 29 samples were classified as mild (TAGqa100mg/g) and 13 as severe (TAG>100mg/g) in steatosis. Stepwise linear regression analysis was performed to predict the TAGqa content of the liver (TAGpred) from the texture parameters calculated on the ultrasound images. A five-variable model was used to predict the TAG content from the ultrasound images. The regression model explained 83.4% of the variance. An area under the curve (AUC) of 0.949 was calculated for 50mg/g of TAGqa; using an optimal cut-off value of 72mg/g TAGpred had a sensitivity of 86.2% and a specificity of 84.2%. An AUC of 0.978 for 100mg/g of TAGqa was calculated; using an optimal cut-off value of 89mg/g, TAGpred sensitivity was 92.3% and specificity was 88.6%. Texture analysis of B-mode ultrasound images may therefore be used to accurately predict the TAG content of the liver in lactating cows. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analysis of Crystallographic Textures in Aluminum Plates Processed by Equal Channel Angular Extrusion

DEFF Research Database (Denmark)

Li, Saiyi; Mishin, Oleg

2014-01-01

A modeling and experimental investigation has been conducted to explore the effect of processing route on texture evolution during equal channel angular extrusion (ECAE) of aluminum plate samples. It is found that although the textures in the plates develop along orientation fibers previously ide...... identified for ECAE-processed rods and bars, the main components and strength of these textures vary significantly with processing route, which may lead to considerable differences in the plastic anisotropy of the plates....

Breast tissue classification in digital breast tomosynthesis images using texture features: a feasibility study

Science.gov (United States)

Kontos, Despina; Berger, Rachelle; Bakic, Predrag R.; Maidment, Andrew D. A.

2009-02-01

Mammographic breast density is a known breast cancer risk factor. Studies have shown the potential to automate breast density estimation by using computerized texture-based segmentation of the dense tissue in mammograms. Digital breast tomosynthesis (DBT) is a tomographic x-ray breast imaging modality that could allow volumetric breast density estimation. We evaluated the feasibility of distinguishing between dense and fatty breast regions in DBT using computer-extracted texture features. Our long-term hypothesis is that DBT texture analysis can be used to develop 3D dense tissue segmentation algorithms for estimating volumetric breast density. DBT images from 40 women were analyzed. The dense tissue area was delineated within each central source projection (CSP) image using a thresholding technique (Cumulus, Univ. Toronto). Two (2.5cm)2 ROIs were manually selected: one within the dense tissue region and another within the fatty region. Corresponding (2.5cm)3 ROIs were placed within the reconstructed DBT images. Texture features, previously used for mammographic dense tissue segmentation, were computed. Receiver operating characteristic (ROC) curve analysis was performed to evaluate feature classification performance. Different texture features appeared to perform best in the 3D reconstructed DBT compared to the 2D CSP images. Fractal dimension was superior in DBT (AUC=0.90), while contrast was best in CSP images (AUC=0.92). We attribute these differences to the effects of tissue superimposition in CSP and the volumetric visualization of the breast tissue in DBT. Our results suggest that novel approaches, different than those conventionally used in projection mammography, need to be investigated in order to develop DBT dense tissue segmentation algorithms for estimating volumetric breast density.

Texture operator for snow particle classification into snowflake and graupel

Science.gov (United States)

Nurzyńska, Karolina; Kubo, Mamoru; Muramoto, Ken-ichiro

2012-11-01

In order to improve the estimation of precipitation, the coefficients of Z-R relation should be determined for each snow type. Therefore, it is necessary to identify the type of falling snow. Consequently, this research addresses a problem of snow particle classification into snowflake and graupel in an automatic manner (as these types are the most common in the study region). Having correctly classified precipitation events, it is believed that it will be possible to estimate the related parameters accurately. The automatic classification system presented here describes the images with texture operators. Some of them are well-known from the literature: first order features, co-occurrence matrix, grey-tone difference matrix, run length matrix, and local binary pattern, but also a novel approach to design simple local statistic operators is introduced. In this work the following texture operators are defined: mean histogram, min-max histogram, and mean-variance histogram. Moreover, building a feature vector, which is based on the structure created in many from mentioned algorithms is also suggested. For classification, the k-nearest neighbourhood classifier was applied. The results showed that it is possible to achieve correct classification accuracy above 80% by most of the techniques. The best result of 86.06%, was achieved for operator built from a structure achieved in the middle stage of the co-occurrence matrix calculation. Next, it was noticed that describing an image with two texture operators does not improve the classification results considerably. In the best case the correct classification efficiency was 87.89% for a pair of texture operators created from local binary pattern and structure build in a middle stage of grey-tone difference matrix calculation. This also suggests that the information gathered by each texture operator is redundant. Therefore, the principal component analysis was applied in order to remove the unnecessary information and

Intrinsic Problems In Determination Of Soil Texture In Calcareous Soils Of Arid Zones

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Mozna A. Ahmed

2017-08-01

Full Text Available This study aimed at studying the effect of removal of CaCO3 on the texture of the soil profile and that of the control section in some Aridisols of the Sudan. Sixty soil profiles were sampled from Shendi area latitude1636 and longitude 33 48 River Nile State Sudan. These soils were analyzed for CaCO3 and 20 of these profiles were found to be of relatively appreciable calcareousness and were therefore selected for this study. The following three weighted soil textures were determined 1 before any removal of the CaCO3 Texture1 2 after the removal of CaCO3 Texture2 3 after amending the texture by adding the clay sized CaCO3 to the silt fraction Texture 3. Statistical analysis revealed significant differences among soil separates in the three textures except between clay of T2 and clay of T3 and among sand fractions in the three textures. That was not unexpected because the first texture included both mineral separates plus their equivalent size of CaCO3 the second texture included only the mineral separates in complete absence of CaCO3 while texture 3 was an amended texture. The change in the textural class amounted to 72 of the profiles. Statistical analysis in the weighted texture of the control section revealed that this texture was not affected except in two profiles. That could be attributed to the fact that the clay content of the soils of the study area did not fall at or near the boundary between any two major textural classes used in the Soil Taxonomy. The size of the CaCO3 was found in the order of clay size silt size sand size.

Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

Science.gov (United States)

Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.; Schultz, Peter F.; George, John S.

2015-07-28

An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.

Object detection approach using generative sparse, hierarchical networks with top-down and lateral connections for combining texture/color detection and shape/contour detection

Energy Technology Data Exchange (ETDEWEB)

Paiton, Dylan M.; Kenyon, Garrett T.; Brumby, Steven P.; Schultz, Peter F.; George, John S.

2016-10-25

An approach to detecting objects in an image dataset may combine texture/color detection, shape/contour detection, and/or motion detection using sparse, generative, hierarchical models with lateral and top-down connections. A first independent representation of objects in an image dataset may be produced using a color/texture detection algorithm. A second independent representation of objects in the image dataset may be produced using a shape/contour detection algorithm. A third independent representation of objects in the image dataset may be produced using a motion detection algorithm. The first, second, and third independent representations may then be combined into a single coherent output using a combinatorial algorithm.

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)

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...

Texture and microstructure evolution in nickel electrodeposited from an additive-free Watts electrolyte

DEFF Research Database (Denmark)

Alimadadi, Hossein; da Silva Fanta, Alice Bastos; Kasama, Takeshi

2016-01-01

Nickel layers with 〈100〉, 〈210〉, 〈110〉 and 〈211〉 fiber textures were electrodeposited from additive-free Watts type electrolytes by adjusting both the pH and the applied current density. Quantitative crystallographic texture analysis by XRD was supplemented by micro-texture analysis applying EBSD....... While XRD results correspond to absorption-weighted averages over the top part of the layer, EBSD on the cross section allowed studying the texture evolution as a function of distance to the substrate. Although layer growth started on amorphous substrates, implying that nucleation occurs unbiased...

Relation between consumers' perceptions of color and texture of dairy desserts and instrumental measurements using a generalized procrustes analysis.

Science.gov (United States)

González-Tomás, L; Costell, E

2006-12-01

Consumers' perceptions of the color and texture of 8 commercial vanilla dairy desserts were studied and related to color and rheological measurements. First, the 8 desserts were evaluated by a group of consumers by means of the Free Choice Profile. For both color and texture, a 2-dimensional solution was chosen, with dimension 1 highly related to yellow color intensity in the case of color and to thickness in the case of texture. Second, mechanical spectra, flow behavior, and instrumental color were determined. All the samples showed a time-dependent and shear-thinning flow and a mechanical spectrum typical of a weak gel. Differences were found in the flow index, in the apparent viscosity at 10 s(-1), and in the values of the storage modulus, the loss modulus, the loss angle tangent, and the complex viscosity at 1 Hz, as well as in the color parameters. Finally, sensory and instrumental relationships were investigated by a generalized Procrustes analysis. For both color and texture, a 3-dimensional solution explained a high percentage of the total variance (>80%). In these particular samples, the instrumental color parameters provided more accurate information on consumers' color perceptions than was provided by the rheological parameters of consumers' perceptions of texture.

Some Numerical Characteristics of Image Texture

Directory of Open Access Journals (Sweden)

O. Samarina

2012-05-01

Full Text Available Texture classification is one of the basic images processing tasks. In this paper we present some numerical characteristics to the images analysis and processing. It can be used at the solving of images classification problems, their recognition, problems of remote sounding, biomedical images analysis, geological researches.

Estimating spatially distributed soil texture using time series of thermal remote sensing - a case study in central Europe

Science.gov (United States)

Müller, Benjamin; Bernhardt, Matthias; Jackisch, Conrad; Schulz, Karsten

2016-09-01

For understanding water and solute transport processes, knowledge about the respective hydraulic properties is necessary. Commonly, hydraulic parameters are estimated via pedo-transfer functions using soil texture data to avoid cost-intensive measurements of hydraulic parameters in the laboratory. Therefore, current soil texture information is only available at a coarse spatial resolution of 250 to 1000 m. Here, a method is presented to derive high-resolution (15 m) spatial topsoil texture patterns for the meso-scale Attert catchment (Luxembourg, 288 km2) from 28 images of ASTER (advanced spaceborne thermal emission and reflection radiometer) thermal remote sensing. A principle component analysis of the images reveals the most dominant thermal patterns (principle components, PCs) that are related to 212 fractional soil texture samples. Within a multiple linear regression framework, distributed soil texture information is estimated and related uncertainties are assessed. An overall root mean squared error (RMSE) of 12.7 percentage points (pp) lies well within and even below the range of recent studies on soil texture estimation, while requiring sparser sample setups and a less diverse set of basic spatial input. This approach will improve the generation of spatially distributed topsoil maps, particularly for hydrologic modeling purposes, and will expand the usage of thermal remote sensing products.

Land use/land cover mapping using multi-scale texture processing of high resolution data

Science.gov (United States)

Wong, S. N.; Sarker, M. L. R.

2014-02-01

Land use/land cover (LULC) maps are useful for many purposes, and for a long time remote sensing techniques have been used for LULC mapping using different types of data and image processing techniques. In this research, high resolution satellite data from IKONOS was used to perform land use/land cover mapping in Johor Bahru city and adjacent areas (Malaysia). Spatial image processing was carried out using the six texture algorithms (mean, variance, contrast, homogeneity, entropy, and GLDV angular second moment) with five difference window sizes (from 3×3 to 11×11). Three different classifiers i.e. Maximum Likelihood Classifier (MLC), Artificial Neural Network (ANN) and Supported Vector Machine (SVM) were used to classify the texture parameters of different spectral bands individually and all bands together using the same training and validation samples. Results indicated that texture parameters of all bands together generally showed a better performance (overall accuracy = 90.10%) for land LULC mapping, however, single spectral band could only achieve an overall accuracy of 72.67%. This research also found an improvement of the overall accuracy (OA) using single-texture multi-scales approach (OA = 89.10%) and single-scale multi-textures approach (OA = 90.10%) compared with all original bands (OA = 84.02%) because of the complementary information from different bands and different texture algorithms. On the other hand, all of the three different classifiers have showed high accuracy when using different texture approaches, but SVM generally showed higher accuracy (90.10%) compared to MLC (89.10%) and ANN (89.67%) especially for the complex classes such as urban and road.

Land use/land cover mapping using multi-scale texture processing of high resolution data

International Nuclear Information System (INIS)

Wong, S N; Sarker, M L R

2014-01-01

Land use/land cover (LULC) maps are useful for many purposes, and for a long time remote sensing techniques have been used for LULC mapping using different types of data and image processing techniques. In this research, high resolution satellite data from IKONOS was used to perform land use/land cover mapping in Johor Bahru city and adjacent areas (Malaysia). Spatial image processing was carried out using the six texture algorithms (mean, variance, contrast, homogeneity, entropy, and GLDV angular second moment) with five difference window sizes (from 3×3 to 11×11). Three different classifiers i.e. Maximum Likelihood Classifier (MLC), Artificial Neural Network (ANN) and Supported Vector Machine (SVM) were used to classify the texture parameters of different spectral bands individually and all bands together using the same training and validation samples. Results indicated that texture parameters of all bands together generally showed a better performance (overall accuracy = 90.10%) for land LULC mapping, however, single spectral band could only achieve an overall accuracy of 72.67%. This research also found an improvement of the overall accuracy (OA) using single-texture multi-scales approach (OA = 89.10%) and single-scale multi-textures approach (OA = 90.10%) compared with all original bands (OA = 84.02%) because of the complementary information from different bands and different texture algorithms. On the other hand, all of the three different classifiers have showed high accuracy when using different texture approaches, but SVM generally showed higher accuracy (90.10%) compared to MLC (89.10%) and ANN (89.67%) especially for the complex classes such as urban and road

[Visual Texture Agnosia in Humans].

Science.gov (United States)

Suzuki, Kyoko

2015-06-01

Visual object recognition requires the processing of both geometric and surface properties. Patients with occipital lesions may have visual agnosia, which is impairment in the recognition and identification of visually presented objects primarily through their geometric features. An analogous condition involving the failure to recognize an object by its texture may exist, which can be called visual texture agnosia. Here we present two cases with visual texture agnosia. Case 1 had left homonymous hemianopia and right upper quadrantanopia, along with achromatopsia, prosopagnosia, and texture agnosia, because of damage to his left ventromedial occipitotemporal cortex and right lateral occipito-temporo-parietal cortex due to multiple cerebral embolisms. Although he showed difficulty matching and naming textures of real materials, he could readily name visually presented objects by their contours. Case 2 had right lower quadrantanopia, along with impairment in stereopsis and recognition of texture in 2D images, because of subcortical hemorrhage in the left occipitotemporal region. He failed to recognize shapes based on texture information, whereas shape recognition based on contours was well preserved. Our findings, along with those of three reported cases with texture agnosia, indicate that there are separate channels for processing texture, color, and geometric features, and that the regions around the left collateral sulcus are crucial for texture processing.

Surface Texture-Based Surface Treatments on Ti6Al4V Titanium Alloys for Tribological and Biological Applications: A Mini Review

Directory of Open Access Journals (Sweden)

Naiming Lin

2018-03-01

Full Text Available Surface texture (ST has been confirmed as an effective and economical surface treatment technique that can be applied to a great range of materials and presents growing interests in various engineering fields. Ti6Al4V which is the most frequently and successfully used titanium alloy has long been restricted in tribological-related operations due to the shortcomings of low surface hardness, high friction coefficient, and poor abrasive wear resistance. Ti6Al4V has benefited from surface texture-based surface treatments over the last decade. This review begins with a brief introduction, analysis approaches, and processing methods of surface texture. The specific applications of the surface texture-based surface treatments for improving surface performance of Ti6Al4V are thoroughly reviewed from the point of view of tribology and biology.

Can we trust the calculation of texture indices of CT images? A phantom study.

Science.gov (United States)

Caramella, Caroline; Allorant, Adrien; Orlhac, Fanny; Bidault, Francois; Asselain, Bernard; Ammari, Samy; Jaranowski, Patricia; Moussier, Aurelie; Balleyguier, Corinne; Lassau, Nathalie; Pitre-Champagnat, Stephanie

2018-04-01

Texture analysis is an emerging tool in the field of medical imaging analysis. However, many issues have been raised in terms of its use in assessing patient images and it is crucial to harmonize and standardize this new imaging measurement tool. This study was designed to evaluate the reliability of texture indices of CT images on a phantom including a reproducibility study, to assess the discriminatory capacity of indices potentially relevant in CT medical images and to determine their redundancy. For the reproducibility and discriminatory analysis, eight identical CT acquisitions were performed on a phantom including one homogeneous insert and two close heterogeneous inserts. Texture indices were selected for their high reproducibility and capability of discriminating different textures. For the redundancy analysis, 39 acquisitions of the same phantom were performed using varying acquisition parameters and a correlation matrix was used to explore the 2 × 2 relationships. LIFEx software was used to explore 34 different parameters including first order and texture indices. Only eight indices of 34 exhibited high reproducibility and discriminated textures from each other. Skewness and kurtosis from histogram were independent from the six other indices but were intercorrelated, the other six indices correlated in diverse degrees (entropy, dissimilarity, and contrast of the co-occurrence matrix, contrast of the Neighborhood Gray Level difference matrix, SZE, ZLNU of the Gray-Level Size Zone Matrix). Care should be taken when using texture analysis as a tool to characterize CT images because changes in quantitation may be primarily due to internal variability rather than from real physio-pathological effects. Some textural indices appear to be sufficiently reliable and capable to discriminate close textures on CT images. © 2018 American Association of Physicists in Medicine.

Texture analysis on MR images helps predicting non-response to NAC in breast cancer

International Nuclear Information System (INIS)

Michoux, N.; Van den Broeck, S.; Lacoste, L.; Fellah, L.; Galant, C.; Berlière, M.; Leconte, I.

2015-01-01

To assess the performance of a predictive model of non-response to neoadjuvant chemotherapy (NAC) in patients with breast cancer based on texture, kinetic, and BI-RADS parameters measured from dynamic MRI. Sixty-nine patients with invasive ductal carcinoma of the breast who underwent pre-treatment MRI were studied. Morphological parameters and biological markers were measured. Pathological complete response was defined as the absence of invasive and in situ cancer in breast and nodes. Pathological non-responders, partial and complete responders were identified. Dynamic imaging was performed at 1.5 T with a 3D axial T1W GRE fat-suppressed sequence. Visual texture, kinetic and BI-RADS parameters were measured in each lesion. ROC analysis and leave-one-out cross-validation were used to assess the performance of individual parameters, then the performance of multi-parametric models in predicting non-response to NAC. A model based on four pre-NAC parameters (inverse difference moment, GLN, LRHGE, wash-in) and k-means clustering as statistical classifier identified non-responders with 84 % sensitivity. BI-RADS mass/non-mass enhancement, biological markers and histological grade did not contribute significantly to the prediction. Pre-NAC texture and kinetic parameters help predicting non-benefit to NAC. Further testing including larger groups of patients with different tumor subtypes is needed to improve the generalization properties and validate the performance of the predictive model

FCC Rolling Textures Reviewed in the Light of Quantitative Comparisons between Simulated and Experimental Textures

DEFF Research Database (Denmark)

Wierzbanowski, Krzysztof; Wroński, Marcin; Leffers, Torben

2014-01-01

The crystallographic texture of metallic materials has a very strong effect on the properties of the materials. In the present article, we look at the rolling textures of fcc metals and alloys, where the classical problem is the existence of two different types of texture, the "copper-type texture......" and the "brass-type texture." The type of texture developed is determined by the stacking fault energy of the material, the rolling temperature and the strain rate of the rolling process. Recent texture simulations by the present authors provide the basis for a renewed discussion of the whole field of fcc......} slip without or with deformation twinning, but we also consider slip on other slip planes and slip by partial dislocations. We consistently make quantitative comparison of the simulation results and the experimental textures by means of a scalar correlation factor. We find that the development...

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

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.

Saturated hydraulic conductivity of US soils grouped according to textural class and bulk density

Science.gov (United States)

Importance of the saturated hydraulic conductivity as soil hydraulic property led to the development of multiple pedotransfer functions for estimating it. One approach to estimating Ksat was using textural classes rather than specific textural fraction contents as pedotransfer inputs. The objective...

Differentiation between acute and chronic myocardial infarction by means of texture analysis of late gadolinium enhancement and cine cardiac magnetic resonance imaging.

Science.gov (United States)

Larroza, Andrés; Materka, Andrzej; López-Lereu, María P; Monmeneu, José V; Bodí, Vicente; Moratal, David

2017-07-01

The purpose of this study was to differentiate acute from chronic myocardial infarction using machine learning techniques and texture features extracted from cardiac magnetic resonance imaging (MRI). The study group comprised 22 cases with acute myocardial infarction (AMI) and 22 cases with chronic myocardial infarction (CMI). Cine and late gadolinium enhancement (LGE) MRI were analyzed independently to differentiate AMI from CMI. A total of 279 texture features were extracted from predefined regions of interest (ROIs): the infarcted area on LGE MRI, and the entire myocardium on cine MRI. Classification performance was evaluated by a nested cross-validation approach combining a feature selection technique with three predictive models: random forest, support vector machine (SVM) with Gaussian Kernel, and SVM with polynomial kernel. The polynomial SVM yielded the best classification performance. Receiver operating characteristic curves provided area-under-the-curve (AUC) (mean±standard deviation) of 0.86±0.06 on LGE MRI using 72 features; AMI sensitivity=0.81±0.08 and specificity=0.84±0.09. On cine MRI, AUC=0.82±0.06 using 75 features; AMI sensitivity=0.79±0.10 and specificity=0.80±0.10. We concluded that texture analysis can be used for differentiation of AMI from CMI on cardiac LGE MRI, and also on standard cine sequences in which the infarction is visually imperceptible in most cases. Copyright © 2017 Elsevier B.V. All rights reserved.

Low-order non-spatial effects dominate second-order spatial effects in the texture quantifier analysis of 18F-FDG-PET images.

Directory of Open Access Journals (Sweden)

Frank J Brooks

Full Text Available There is increasing interest in applying image texture quantifiers to assess the intra-tumor heterogeneity observed in FDG-PET images of various cancers. Use of these quantifiers as prognostic indicators of disease outcome and/or treatment response has yielded inconsistent results. We study the general applicability of some well-established texture quantifiers to the image data unique to FDG-PET.We first created computer-simulated test images with statistical properties consistent with clinical image data for cancers of the uterine cervix. We specifically isolated second-order statistical effects from low-order effects and analyzed the resulting variation in common texture quantifiers in response to contrived image variations. We then analyzed the quantifiers computed for FIGOIIb cervical cancers via receiver operating characteristic (ROC curves and via contingency table analysis of detrended quantifier values.We found that image texture quantifiers depend strongly on low-effects such as tumor volume and SUV distribution. When low-order effects are controlled, the image texture quantifiers tested were not able to discern only the second-order effects. Furthermore, the results of clinical tumor heterogeneity studies might be tunable via choice of patient population analyzed.Some image texture quantifiers are strongly affected by factors distinct from the second-order effects researchers ostensibly seek to assess via those quantifiers.

TEXTURE OF COOKED SPELT WHEAT NOODLES

Directory of Open Access Journals (Sweden)

Magdaléna Lacko - Bartošová

2013-02-01

Full Text Available At present, there are limited and incomplete data on the ability of spelt to produce alimentary pasta of suitable quality. Noodles are traditional cereal-based food that is becoming increasingly popular worldwide because of its convenience, nutritional qualities, and palatability. It is generally accepted that texture is the main criterion for assessing overall quality of cooked noodles. We present selected indicators of noodle texture of three spelt cultivars – Oberkulmer Rotkorn, Rubiota and Franckenkorn grown in an ecological system at the locality of Dolna Malanta near Nitra. A texture analyzer TA.XT PLUS was used to determine cooked spelt wheat noodle firmness (N (AACC 66-50. The texture of cooked spelt wheat noodles was expressed also as elasticity (N and extensibility (mm. Statistical analysis showed significant influence of the variety and year of growing on the firmness, elasticity and extensibility of cooked noodles. The wholemeal spelt wheat noodles were characterized with lower cutting firmness than the flour noodles. Flour noodles were more tensile than wholemeal noodles. The best elasticity and extensibility of flour noodles was found in noodles prepared from Rubiota however from wholemeal noodles it was Oberkulmer Rotkorn. Spelt wheat is suitable for noodle production, however also here it is necessary to differentiate between varieties. According to achieved results, wholemeal noodles prepared from Oberkulmer Rotkorn can be recommended for noodle industry due to their consistent structure and better texture quality after cooking.

Microstructure and Texture Evolution in Temper Rolled Fe-Si Steels with New System Nano-Inhibitors Under the Dynamic Annealing Conditions

Directory of Open Access Journals (Sweden)

Kováč F.

2017-09-01

Full Text Available This work investigates the microstructure and texture evolution in grain-oriented electrotechnical steel with a new inhibition system based on vanadium carbides nano-particles. The novel approach for the preparation of this steel with appropriate final magnetic properties combines not only nanoinhibitors based on the vanadium carbides precipitations but also includes straininduced grain growth mechanism in combination with dynamic continuous annealing during the secondary recrystallization. The experimental grain-oriented steel with proposed new chemical composition was prepared in laboratory conditions. The texture analysis has shown that suggested procedure led the formation of sufficiently strong {110} Goss texture during the short time period of a final annealing process, which is comparable to that obtained in the conventionally treated grain-oriented steels.

Methods of making textured catalysts

Science.gov (United States)

Werpy, Todd [West Richland, WA; Frye, Jr., John G.; Wang, Yong [Richland, WA; Zacher, Alan H [Kennewick, WA

2010-08-17

A textured catalyst having a hydrothermally-stable support, a metal oxide and a catalyst component is described. Methods of conducting aqueous phase reactions that are catalyzed by a textured catalyst are also described. The invention also provides methods of making textured catalysts and methods of making chemical products using a textured catalyst.

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

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

Computer-aided mass detection in mammography: False positive reduction via gray-scale invariant ranklet texture features

International Nuclear Information System (INIS)

Masotti, Matteo; Lanconelli, Nico; Campanini, Renato

2009-01-01

In this work, gray-scale invariant ranklet texture features are proposed for false positive reduction (FPR) in computer-aided detection (CAD) of breast masses. Two main considerations are at the basis of this proposal. First, false positive (FP) marks surviving our previous CAD system seem to be characterized by specific texture properties that can be used to discriminate them from masses. Second, our previous CAD system achieves invariance to linear/nonlinear monotonic gray-scale transformations by encoding regions of interest into ranklet images through the ranklet transform, an image transformation similar to the wavelet transform, yet dealing with pixels' ranks rather than with their gray-scale values. Therefore, the new FPR approach proposed herein defines a set of texture features which are calculated directly from the ranklet images corresponding to the regions of interest surviving our previous CAD system, hence, ranklet texture features; then, a support vector machine (SVM) classifier is used for discrimination. As a result of this approach, texture-based information is used to discriminate FP marks surviving our previous CAD system; at the same time, invariance to linear/nonlinear monotonic gray-scale transformations of the new CAD system is guaranteed, as ranklet texture features are calculated from ranklet images that have this property themselves by construction. To emphasize the gray-scale invariance of both the previous and new CAD systems, training and testing are carried out without any in-between parameters' adjustment on mammograms having different gray-scale dynamics; in particular, training is carried out on analog digitized mammograms taken from a publicly available digital database, whereas testing is performed on full-field digital mammograms taken from an in-house database. Free-response receiver operating characteristic (FROC) curve analysis of the two CAD systems demonstrates that the new approach achieves a higher reduction of FP marks

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)

Defect Detection in Alphonso using Statistical Method and Principal Component Analysis: A Non-Destructive Approach

OpenAIRE

Sandeep S. Musale; Pradeep M. Patil

2014-01-01

Natural image analysis uses textural property of the surface. Texture is defined as a spatial arrangement of local intensity attributes that are correlated within areas of visual scene corresponding to surface regions. Texture exhibits some sort of periodicity of the basic pattern of Spongy Tissue in alphonso mango. This leads to use textural property to identify different patterns of Spongy Tissue in alphonso for detection of defects in alphonso mango. Visual assessment of texture made by hu...

Micro-Texture Synthesis by Phase Randomization

Directory of Open Access Journals (Sweden)

Bruno Galerne

2011-09-01

Full Text Available This contribution is concerned with texture synthesis by example, the process of generating new texture images from a given sample. The Random Phase Noise algorithm presented here synthesizes a texture from an original image by simply randomizing its Fourier phase. It is able to reproduce textures which are characterized by their Fourier modulus, namely the random phase textures (or micro-textures.

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

Microstructure, crystallographic texture and mechanical properties of friction stir welded AA2017A

Energy Technology Data Exchange (ETDEWEB)

Ahmed, M.M.Z., E-mail: mohamed_ahmed4@s-petrol.suez.edu.eg [Institute for Microstructural and Mechanical Processing Engineering, University of Sheffield (IMMPETUS), Mappin Street, Sheffield S1 3JD (United Kingdom); Department of Metallurgical and Materials Engineering, Suez Canal University, Suez 43721 (Egypt); Wynne, B.P.; Rainforth, W.M. [Institute for Microstructural and Mechanical Processing Engineering, University of Sheffield (IMMPETUS), Mappin Street, Sheffield S1 3JD (United Kingdom); Threadgill, P.L. [TWI LTD, Granta Park, Great Abington, Cambridge CB21 6AL (United Kingdom)

2012-02-15

In this study a thick section (20 mm) friction stir welded AA2017A-T451 has been characterized in terms of microstructure, crystallographic texture and mechanical properties. For microstructural analysis both optical and scanning electron microscopes have been used. A detailed crystallographic texture analysis has been carried out using the electron back scattering diffraction technique. Crystallographic texture has been examined in both shoulder and probe affected regions of the weld NG. An entirely weak texture is observed at the shoulder affected region which is mainly explained by the effect of the sequential multi pass deformation experienced by both tool probe and tool shoulder. The texture in the probe dominated region at the AS side of the weld is relatively weak but still assembles the simple shear texture of FCC metals with B/B{sup Macron} and C components existing across the whole map. However, the texture is stronger at the RS than at the AS of the weld, mainly dominated byB/B{sup Macron} components and with C component almost absent across the map. An alternating bands between (B) components and (B{sup Macron }) component are observed only at the AS side of the weld. - Highlights: Black-Right-Pointing-Pointer Detailed investigation of microstructure and crystallographic texture. Black-Right-Pointing-Pointer The grain size is varied from the top to the bottom of the NG. Black-Right-Pointing-Pointer An entirely weak texture is observed at the shoulder affected region. Black-Right-Pointing-Pointer The texture in the probe affected region is dominated by simple shear texture.

Do textured breast implants decrease the rate of capsular contracture compared to smooth implants?

Science.gov (United States)

Cifuentes, Ignacio; Dagnino, Bruno; Rada, Gabriel

2017-08-31

The use of breast implants for aesthetic and reconstructive purposes has become one of the most common procedures performed by plastic surgeons. Several breast implants models exist. They differ in their size, filling, shape and characteristic of the shell, which can be smooth or textured. Capsular contracture is one of the main complications of breast implants. It has been suggested that the use of textured implants could reduce the incidence of capsular contracture. To answer this question, we used Epistemonikos, the largest database of systematic reviews in health, which is maintained by screening multiple information sources, including MEDLINE, EMBASE, Cochrane, among others. We identified 15 studies overall, of which 13 were randomized trials relevant for the question of interest. We extracted data from the systematic reviews, reanalyzed data of primary studies, conducted a meta-analysis and generated a summary of findings table using the GRADE approach. We concluded the use of textured breast implants probably decreases the risk of capsular contracture, however, they might be associated to an increased risk of anaplastic large cell lymphoma.

Red textures and the work of juxtaposition

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Corinne A. Kratz

Full Text Available Simon Gush's evocative work Red is an installation, an exhibit, a film, a website, and a provocation to think about what these different forms convey and do, and how they do so. What kinds of engagement, work and knowledge production are involved in curating, designing and creating work in different formats, each of which combines varied media and forms of expression? This article considers the design and interpretive possibilities of Red's different forms, paying particular attention to juxtaposition as a fundamental technique in designing and constructing exhibits, films and websites. The analysis examines the layerings, interactions, timings and textures involved and draws in other exhibitions to highlight the ways that Red and history museums approach their work and relations to time, history and historiography.

Can CT and MR Shape and Textural Features Differentiate Benign Versus Malignant Pleural Lesions?

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Pena, Elena; Ojiaku, MacArinze; Inacio, Joao R; Gupta, Ashish; Macdonald, D Blair; Shabana, Wael; Seely, Jean M; Rybicki, Frank J; Dennie, Carole; Thornhill, Rebecca E

2017-10-01

The study aimed to identify a radiomic approach based on CT and or magnetic resonance (MR) features (shape and texture) that may help differentiate benign versus malignant pleural lesions, and to assess if the radiomic model may improve confidence and accuracy of radiologists with different subspecialty backgrounds. Twenty-nine patients with pleural lesions studied on both contrast-enhanced CT and MR imaging were reviewed retrospectively. Three texture and three shape features were extracted. Combinations of features were used to generate logistic regression models using histopathology as outcome. Two thoracic and two abdominal radiologists evaluated their degree of confidence in malignancy. Diagnostic accuracy of radiologists was determined using contingency tables. Cohen's kappa coefficient was used to assess inter-reader agreement. Using optimal threshold criteria, sensitivity, specificity, and accuracy of each feature and combination of features were obtained and compared to the accuracy and confidence of radiologists. The CT model that best discriminated malignant from benign lesions revealed an AUC CT  = 0.92 ± 0.05 (P textural and shape analysis may help distinguish malignant from benign lesions. A radiomics-based approach may increase diagnostic confidence of abdominal radiologists on CT and MR and may potentially improve radiologists' accuracy in the assessment of pleural lesions characterized by MR. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Influence of grain size and texture prior to warm rolling on microstructure, texture and magnetic properties of Fe-6.5 wt% Si steel

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Xu, H. J.; Xu, Y. B.; Jiao, H. T.; Cheng, S. F.; Misra, R. D. K.; Li, J. P.

2018-05-01

Fe-6.5 wt% Si steel hot bands with different initial grain size and texture were obtained through different annealing treatment. These bands were then warm rolled and annealed. An analysis on the evolution of microstructure and texture, particularly the formation of recrystallization texture was studied. The results indicated that initial grain size and texture had a significant effect on texture evolution and magnetic properties. Large initial grains led to coarse deformed grains with dense and long shear bands after warm rolling. Such long shear bands resulted in growth advantage for {1 1 3} 〈3 6 1〉 oriented grains during recrystallization. On the other hand, sharp {11 h} 〈1, 2, 1/h〉 (α∗-fiber) texture in the coarse-grained sample led to dominant {1 1 2} 〈1 1 0〉 texture after warm rolling. Such {1 1 2} 〈1 1 0〉 deformed grains provided massive nucleation sites for {1 1 3} 〈3 6 1〉 oriented grains during subsequent recrystallization. These {1 1 3} 〈3 6 1〉 grains were confirmed to exhibit an advantage on grain growth compared to γ-fiber grains. As a result, significant {1 1 3} 〈3 6 1〉 texture was developed and unfavorable γ-fiber texture was inhibited in the final annealed sheet. Both these aspects led to superior magnetic properties in the sample with largest initial grain size. The magnetic induction B8 was 1.36 T and the high frequency core loss P10/400 was 17.07 W/kg.

TOPICAL REVIEW Textured silicon nitride: processing and anisotropic properties

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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 �

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

Parameter optimization of parenchymal texture analysis for prediction of false-positive recalls from screening mammography

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Ray, Shonket; Keller, Brad M.; Chen, Jinbo; Conant, Emily F.; Kontos, Despina

2016-03-01

This work details a methodology to obtain optimal parameter values for a locally-adaptive texture analysis algorithm that extracts mammographic texture features representative of breast parenchymal complexity for predicting falsepositive (FP) recalls from breast cancer screening with digital mammography. The algorithm has two components: (1) adaptive selection of localized regions of interest (ROIs) and (2) Haralick texture feature extraction via Gray- Level Co-Occurrence Matrices (GLCM). The following parameters were systematically varied: mammographic views used, upper limit of the ROI window size used for adaptive ROI selection, GLCM distance offsets, and gray levels (binning) used for feature extraction. Each iteration per parameter set had logistic regression with stepwise feature selection performed on a clinical screening cohort of 474 non-recalled women and 68 FP recalled women; FP recall prediction was evaluated using area under the curve (AUC) of the receiver operating characteristic (ROC) and associations between the extracted features and FP recall were assessed via odds ratios (OR). A default instance of mediolateral (MLO) view, upper ROI size limit of 143.36 mm (2048 pixels2), GLCM distance offset combination range of 0.07 to 0.84 mm (1 to 12 pixels) and 16 GLCM gray levels was set. The highest ROC performance value of AUC=0.77 [95% confidence intervals: 0.71-0.83] was obtained at three specific instances: the default instance, upper ROI window equal to 17.92 mm (256 pixels2), and gray levels set to 128. The texture feature of sum average was chosen as a statistically significant (p<0.05) predictor and associated with higher odds of FP recall for 12 out of 14 total instances.

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 evolution in upset-forged P/M and wrought tantalum: Experimentation and modeling

International Nuclear Information System (INIS)

Bingert, J.F.; Desch, P.B.; Bingert, S.R.; Maudlin, P.J.; Tome, C.N.

1997-11-01

Preferred orientations in polycrystalline materials can significantly affect their physical and mechanical response through the retention of anisotropic properties inherent to the single crystal. In this study the texture evolution in upset-forged PIM and wrought tantalum was measured as a function of initial texture, compressive strain, and relative position in the pressing. A / duplex fiber texture parallel to the compression axis was generally observed, with varying degrees of a radial component evident in the wrought material. The development of deformation textures derives from restricted crystallographic slip conditions that generate lattice rotations, and these grain reorientations can be modeled as a function of the prescribed deformation gradient. Texture development was simulated for equivalent deformations using both a modified Taylor approach and a viscoplastic self-consistent (VPSC) model. A comparison between the predicted evolution and experimental results shows a good correlation with the texture components, but an overly sharp prediction at large strains from both the Taylor and VPSC models

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

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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.

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

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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

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

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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

AUTOMATIC TEXTURE MAPPING OF ARCHITECTURAL AND ARCHAEOLOGICAL 3D MODELS

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T. P. Kersten

2012-07-01

Full Text Available Today, detailed, complete and exact 3D models with photo-realistic textures are increasingly demanded for numerous applications in architecture and archaeology. Manual texture mapping of 3D models by digital photographs with software packages, such as Maxon Cinema 4D, Autodesk 3Ds Max or Maya, still requires a complex and time-consuming workflow. So, procedures for automatic texture mapping of 3D models are in demand. In this paper two automatic procedures are presented. The first procedure generates 3D surface models with textures by web services, while the second procedure textures already existing 3D models with the software tmapper. The program tmapper is based on the Multi Layer 3D image (ML3DImage algorithm and developed in the programming language C++. The studies showing that the visibility analysis using the ML3DImage algorithm is not sufficient to obtain acceptable results of automatic texture mapping. To overcome the visibility problem the Point Cloud Painter algorithm in combination with the Z-buffer-procedure will be applied in the future.

Automatic Texture Mapping of Architectural and Archaeological 3d Models

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Kersten, T. P.; Stallmann, D.

2012-07-01

Today, detailed, complete and exact 3D models with photo-realistic textures are increasingly demanded for numerous applications in architecture and archaeology. Manual texture mapping of 3D models by digital photographs with software packages, such as Maxon Cinema 4D, Autodesk 3Ds Max or Maya, still requires a complex and time-consuming workflow. So, procedures for automatic texture mapping of 3D models are in demand. In this paper two automatic procedures are presented. The first procedure generates 3D surface models with textures by web services, while the second procedure textures already existing 3D models with the software tmapper. The program tmapper is based on the Multi Layer 3D image (ML3DImage) algorithm and developed in the programming language C++. The studies showing that the visibility analysis using the ML3DImage algorithm is not sufficient to obtain acceptable results of automatic texture mapping. To overcome the visibility problem the Point Cloud Painter algorithm in combination with the Z-buffer-procedure will be applied in the future.

Thermal Texture Selection and Correction for Building Facade Inspection Based on Thermal Radiant Characteristics

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Lin, D.; Jarzabek-Rychard, M.; Schneider, D.; Maas, H.-G.

2018-05-01

An automatic building façade thermal texture mapping approach, using uncooled thermal camera data, is proposed in this paper. First, a shutter-less radiometric thermal camera calibration method is implemented to remove the large offset deviations caused by changing ambient environment. Then, a 3D façade model is generated from a RGB image sequence using structure-from-motion (SfM) techniques. Subsequently, for each triangle in the 3D model, the optimal texture is selected by taking into consideration local image scale, object incident angle, image viewing angle as well as occlusions. Afterwards, the selected textures can be further corrected using thermal radiant characteristics. Finally, the Gauss filter outperforms the voted texture strategy at the seams smoothing and thus for instance helping to reduce the false alarm rate in façade thermal leakages detection. Our approach is evaluated on a building row façade located at Dresden, Germany.

Calculation of skid resistance from texture measurements

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Andreas Ueckermann

2015-02-01

Full Text Available There is a wide range of routine skid resistance measurement devices on the market. All of them are measuring the friction force between a rubber wheel and the wetted road surface. Common to all of them is that they are relatively complex and costly because generally a truck carrying a large water tank is needed to wet the surface with a defined water layer. Because of the limited amount of water they can carry they are limited in range. Besides that the measurement is depending on factors like water film thickness, temperature, measurement speed, rubber aging, rubber wear and even road evenness and curviness. All of these factors will affect the skid resistance and are difficult to control. We present a concept of contactless skid resistance measurement which is based on optical texture measurement and consists of two components: measurement of the pavement texture by means of an optical measuring system and calculation of the skid resistance based on the measured texture by means of a rubber friction model. The basic assumptions underlying the theoretical approach and the model itself based on the theory of Persson are presented. The concept is applied to a laboratory device called Wehner/Schulze (W/S machine to prove the theoretical approach. The results are very promising. A strong indication could be provided that skid resistance could be measured without contact in the future.

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

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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.

Statistical analysis of textural features for improved classification of oral histopathological images.

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Muthu Rama Krishnan, M; Shah, Pratik; Chakraborty, Chandan; Ray, Ajoy K

2012-04-01

The objective of this paper is to provide an improved technique, which can assist oncopathologists in correct screening of oral precancerous conditions specially oral submucous fibrosis (OSF) with significant accuracy on the basis of collagen fibres in the sub-epithelial connective tissue. The proposed scheme is composed of collagen fibres segmentation, its textural feature extraction and selection, screening perfomance enhancement under Gaussian transformation and finally classification. In this study, collagen fibres are segmented on R,G,B color channels using back-probagation neural network from 60 normal and 59 OSF histological images followed by histogram specification for reducing the stain intensity variation. Henceforth, textural features of collgen area are extracted using fractal approaches viz., differential box counting and brownian motion curve . Feature selection is done using Kullback-Leibler (KL) divergence criterion and the screening performance is evaluated based on various statistical tests to conform Gaussian nature. Here, the screening performance is enhanced under Gaussian transformation of the non-Gaussian features using hybrid distribution. Moreover, the routine screening is designed based on two statistical classifiers viz., Bayesian classification and support vector machines (SVM) to classify normal and OSF. It is observed that SVM with linear kernel function provides better classification accuracy (91.64%) as compared to Bayesian classifier. The addition of fractal features of collagen under Gaussian transformation improves Bayesian classifier's performance from 80.69% to 90.75%. Results are here studied and discussed.

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

Height perception influenced by texture gradient.

Science.gov (United States)

Tozawa, Junko

2012-01-01

Three experiments were carried out to examine whether a texture gradient influences perception of relative object height. Previous research implicated texture cues in judgments of object width, but similar influences have not been demonstrated for relative height. In this study, I evaluate a hypothesis that the projective ratio of the number of texture elements covered by the objects combined with the ratio of the retinal object heights determines percepts of relative object height. Density of texture background was varied: four density conditions ranged from no-texture to very dense texture. In experiments 1 and 2, participants judged the height of comparison bar compared to the standard bar positioned on no-texture or textured backgrounds. Results showed relative height judgments differed with texture manipulations, consistent with predictions from a hypothesised combination of the number of texture elements with retinal height (experiment 1), or partially consistent with this hypothesis (experiment 2). In experiment 2, variations in the position of a comparison object showed that comparisons located far from the horizon were judged more poorly than in other positions. In experiment 3 I examined distance perception; relative distance judgments were found to be also affected by textured backgrounds. Results are discussed in terms of Gibson's relational theory and distance calibration theory.

MRI Texture Analysis Reveals Deep Gray Nuclei Damage in Amyotrophic Lateral Sclerosis.

Science.gov (United States)

de Albuquerque, Milena; Anjos, Lara G V; Maia Tavares de Andrade, Helen; de Oliveira, Márcia S; Castellano, Gabriela; Junqueira Ribeiro de Rezende, Thiago; Nucci, Anamarli; França Junior, Marcondes Cavalcante

2016-01-01

Amyotrophic Lateral Sclerosis (ALS) is characterized by extensive corticospinal damage, but extrapyramidal involvement is suggested in pathological studies. Texture analysis (TA) is an image processing technique that evaluates the distribution of gray levels between pixels in a given region of interest (ROI). It provides quantitative data and has been employed in several neurodegenerative disorders. Here, we used TA to investigate possible deep gray nuclei (DGN) abnormalities in a cohort of ALS patients. Thirty-two ALS patients and 32 healthy controls underwent MRI in a 3T scanner. The T1 volumetric sequence was used for DGN segmentation and extraction of 11 texture parameters using the MaZda software. Statistical analyses were performed using the Mann-Whitney non-parametric test, with a significance level set at α = 0.025 (FDR-corrected) for TA. Patients had significantly higher values for the parameter correlation (CO) in both thalami and in the right caudate nucleus compared to healthy controls. Also, the parameter Inverse Difference Moment or Homogeneity (IDM) presented significantly smaller values in the ALS group in both thalami. TA of T1 weighted images revealed DGN alterations in patients with ALS, namely in the thalami and caudate nuclei. Copyright © 2015 by the American Society of Neuroimaging.

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

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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.

Automated kidney morphology measurements from ultrasound images using texture and edge analysis

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Ravishankar, Hariharan; Annangi, Pavan; Washburn, Michael; Lanning, Justin

2016-04-01

In a typical ultrasound scan, a sonographer measures Kidney morphology to assess renal abnormalities. Kidney morphology can also help to discriminate between chronic and acute kidney failure. The caliper placements and volume measurements are often time consuming and an automated solution will help to improve accuracy, repeatability and throughput. In this work, we developed an automated Kidney morphology measurement solution from long axis Ultrasound scans. Automated kidney segmentation is challenging due to wide variability in kidney shape, size, weak contrast of the kidney boundaries and presence of strong edges like diaphragm, fat layers. To address the challenges and be able to accurately localize and detect kidney regions, we present a two-step algorithm that makes use of edge and texture information in combination with anatomical cues. First, we use an edge analysis technique to localize kidney region by matching the edge map with predefined templates. To accurately estimate the kidney morphology, we use textural information in a machine learning algorithm framework using Haar features and Gradient boosting classifier. We have tested the algorithm on 45 unseen cases and the performance against ground truth is measured by computing Dice overlap, % error in major and minor axis of kidney. The algorithm shows successful performance on 80% cases.

Cloud field classification based upon high spatial resolution textural features. I - Gray level co-occurrence matrix approach

Science.gov (United States)

Welch, R. M.; Sengupta, S. K.; Chen, D. W.

1988-01-01

Stratocumulus, cumulus, and cirrus clouds were identified on the basis of cloud textural features which were derived from a single high-resolution Landsat MSS NIR channel using a stepwise linear discriminant analysis. It is shown that, using this method, it is possible to distinguish high cirrus clouds from low clouds with high accuracy on the basis of spatial brightness patterns. The largest probability of misclassification is associated with confusion between the stratocumulus breakup regions and the fair-weather cumulus.

BMI and WHR Are Reflected in Female Facial Shape and Texture: A Geometric Morphometric Image Analysis.

Directory of Open Access Journals (Sweden)

Christine Mayer

Full Text Available Facial markers of body composition are frequently studied in evolutionary psychology and are important in computational and forensic face recognition. We assessed the association of body mass index (BMI and waist-to-hip ratio (WHR with facial shape and texture (color pattern in a sample of young Middle European women by a combination of geometric morphometrics and image analysis. Faces of women with high BMI had a wider and rounder facial outline relative to the size of the eyes and lips, and relatively lower eyebrows. Furthermore, women with high BMI had a brighter and more reddish skin color than women with lower BMI. The same facial features were associated with WHR, even though BMI and WHR were only moderately correlated. Yet BMI was better predictable than WHR from facial attributes. After leave-one-out cross-validation, we were able to predict 25% of variation in BMI and 10% of variation in WHR by facial shape. Facial texture predicted only about 3-10% of variation in BMI and WHR. This indicates that facial shape primarily reflects total fat proportion, rather than the distribution of fat within the body. The association of reddish facial texture in high-BMI women may be mediated by increased blood pressure and superficial blood flow as well as diet. Our study elucidates how geometric morphometric image analysis serves to quantify the effect of biological factors such as BMI and WHR to facial shape and color, which in turn contributes to social perception.

Introduction of High Throughput Magnetic Resonance T2-Weighted Image Texture Analysis for WHO Grade 2 and 3 Gliomas.

Directory of Open Access Journals (Sweden)

Manabu Kinoshita

Full Text Available 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 < 0.0001, AUC = 0.83, respectively. Finally, IDH1 wild type gliomas showed statistically lower Shannon entropy on T2WI than IDH1 mutated gliomas (p = 0.007 but no difference was observed between IDH1 wild type and mutated gliomas in Edge median values using Prewitt filtering. The current study introduced two 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.

Catalogue of X-Ray Texture Data for Al-Cu-Li Alloy 1460, 2090, 2096 and 2195 Near-Net-Shape Extrusions, Sheet and Plate

Science.gov (United States)

Hales, Stephen J.; Hafley, Robert A.; Alexa, Joel A.

1998-01-01

The effect of crystallographic texture on the mechanical properties of near-net-shape extrusions is of major interest ff these products are to find application in launch vehicle or aircraft structures. The objective of this research was to produce a catalogue containing quantitative texture information for extruded product, sheet and plate. The material characterized was extracted from wide, integrally stiffened panels fabricated from the Al-Cu-Li alloys 1460, 2090, 2096 and 2195. The textural characteristics of sheet and plate products of the same alloys were determined for comparison purposes. The approach involved using X-ray diffraction to generate pole figures in combination with orientation distribution function analysis. The data were compiled as a function of location in the extruded cross-sections and the variation in the major deformation- and recrystallization-related texture components was identified.

Visual perception of procedural textures: identifying perceptual dimensions and predicting generation models.

Science.gov (United States)

Liu, Jun; Dong, Junyu; Cai, Xiaoxu; Qi, Lin; Chantler, Mike

2015-01-01

Procedural models are widely used in computer graphics for generating realistic, natural-looking textures. However, these mathematical models are not perceptually meaningful, whereas the users, such as artists and designers, would prefer to make descriptions using intuitive and perceptual characteristics like "repetitive," "directional," "structured," and so on. To make up for this gap, we investigated the perceptual dimensions of textures generated by a collection of procedural models. Two psychophysical experiments were conducted: free-grouping and rating. We applied Hierarchical Cluster Analysis (HCA) and Singular Value Decomposition (SVD) to discover the perceptual features used by the observers in grouping similar textures. The results suggested that existing dimensions in literature cannot accommodate random textures. We therefore utilized isometric feature mapping (Isomap) to establish a three-dimensional perceptual texture space which better explains the features used by humans in texture similarity judgment. Finally, we proposed computational models to map perceptual features to the perceptual texture space, which can suggest a procedural model to produce textures according to user-defined perceptual scales.

Visual perception of procedural textures: identifying perceptual dimensions and predicting generation models.

Directory of Open Access Journals (Sweden)

Jun Liu

Full Text Available Procedural models are widely used in computer graphics for generating realistic, natural-looking textures. However, these mathematical models are not perceptually meaningful, whereas the users, such as artists and designers, would prefer to make descriptions using intuitive and perceptual characteristics like "repetitive," "directional," "structured," and so on. To make up for this gap, we investigated the perceptual dimensions of textures generated by a collection of procedural models. Two psychophysical experiments were conducted: free-grouping and rating. We applied Hierarchical Cluster Analysis (HCA and Singular Value Decomposition (SVD to discover the perceptual features used by the observers in grouping similar textures. The results suggested that existing dimensions in literature cannot accommodate random textures. We therefore utilized isometric feature mapping (Isomap to establish a three-dimensional perceptual texture space which better explains the features used by humans in texture similarity judgment. Finally, we proposed computational models to map perceptual features to the perceptual texture space, which can suggest a procedural model to produce textures according to user-defined perceptual scales.

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.

Texture memory and strain-texture mapping in a NiTi shape memory alloy

International Nuclear Information System (INIS)

Ye, B.; Majumdar, B. S.; Dutta, I.

2007-01-01

The authors report on the near-reversible strain hysteresis during thermal cycling of a polycrystalline NiTi shape memory alloy at a constant stress that is below the yield strength of the martensite. In situ neutron diffraction experiments are used to demonstrate that the strain hysteresis occurs due to a texture memory effect, where the martensite develops a texture when it is cooled under load from the austenite phase and is thereafter ''remembered.'' Further, the authors quantitatively relate the texture to the strain by developing a calculated strain-texture map or pole figure for the martensite phase, and indicate its applicability in other martensitic transformations

Combining different views of mammographic texture resemblance (MTR) marker of breast cancer risk

DEFF Research Database (Denmark)

Sun, S.; Karemore, Gopal; Chernoff, Konstantin

the subsequent 4 years whereas 245 cases had a diagnosis 2-4 years post mammography. We employed the MTR supervised texture learning framework to perform risk evaluation from a single mammography view. In the framework 20,000 pixels were sampled and classified by a kNN pixel classifier. A feature selection step......PURPOSE Mammographic density is a well established breast cancer risk factor. Texture analysis in terms of the Mammographoc Texture Resemblance (MTR) marker has recently shown to add to risk segregation. Hitherto only single view MTR analysis has been performed. Standard mammography examinations...

Adding Texture to Color: Quantitative Analysis of Color Emotions

NARCIS (Netherlands)

Lucassen, M.P.; Gevers, T.; Gijsenij, A.

2010-01-01

What happens to color emotion responses when texture is added to color samples? To quantify this we performed an experiment in which subjects ordered samples (displayed on a computer monitor) along four scales: Warm-Cool, Masculine-Feminine, Hard-Soft and Heavy-Light. Three sample types were used:

Extruded snacks from whole wheat supplemented with textured soy flour: Effect on instrumental and sensory textural characteristics.

Science.gov (United States)

Rodríguez-Vidal, Arturo; Martínez-Flores, Héctor Eduardo; González Jasso, Eva; Velázquez de la Cruz, Gonzalo; Ramírez-Jiménez, Aurea K; Morales-Sánchez, Eduardo

2017-06-01

The quality of extruded snacks can be affected not only by processing conditions, but also by some factors like the concentration and type of ingredients incorporated in their formulation and the working conditions used. Although the process conditions have been established with measurable textural properties, sensory qualities have not been correlated with these responses in expanded extruded snacks made with added functional ingredients. Therefore, in this study the effect of adding textured soy flour (TSF) and whole wheat flour (WWF) to refined wheat flour in the production of extruded snacks and expanded with hot air was evaluated. A response surface design using two levels with five central points was applied to obtain the best combinations of functional ingredients added, holding the parameters of the extrusion process and moisture of treatments. Some texture characteristics and sensory analysis were used as response variables, such as, hardness, fracturability, toughness, crispness, granularity, and chewiness. Likewise, the rate of expansion was evaluated. The results showed that the level of substitution of WWF, especially levels of 15%, had a significant effect on the hardness perceived by the panelist during sensory evaluation. The TSF at concentrations of ≥15%, favored the fracturability and crispness of the samples. It was found that the best expansion index was with the combination of 5% TSF and 15% WWF. Although a correlation between instrumental and sensory tests carried out on the extruded snacks expanded was not found. The physical characteristics of the extruded snacks such as expansion, hardness, and density are important parameters in terms of consumer acceptability of the final product as well as their functional properties. In other words, the appearance and texture are two of the most important attributes that can be seen in snack foods. In particular, the texture can be measured by intrinsic tests: objective (instrumental) and subjective

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%.

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

Inline inspection of textured plastics surfaces

Science.gov (United States)

Michaeli, Walter; Berdel, Klaus

2011-02-01

This article focuses on the inspection of plastics web materials exhibiting irregular textures such as imitation wood or leather. They are produced in a continuous process at high speed. In this process, various defects occur sporadically. However, current inspection systems for plastics surfaces are able to inspect unstructured products or products with regular, i.e., highly periodic, textures, only. The proposed inspection algorithm uses the local binary pattern operator for texture feature extraction. For classification, semisupervised as well as supervised approaches are used. A simple concept for semisupervised classification is presented and applied for defect detection. The resulting defect-maps are presented to the operator. He assigns class labels that are used to train the supervised classifier in order to distinguish between different defect types. A concept for parallelization is presented allowing the efficient use of standard multicore processor PC hardware. Experiments with images of a typical product acquired in an industrial setting show a detection rate of 97% while achieving a false alarm rate below 1%. Real-time tests show that defects can be reliably detected even at haul-off speeds of 30 m/min. Further applications of the presented concept can be found in the inspection of other materials.

Textured perovskite cells

NARCIS (Netherlands)

Deelen, J. van; Tezsevin, Y.; Barink, M.

2017-01-01

Most research of texturization of solar cells has been devoted to Si based cells. For perovskites, it was assumed that texturization would not have much of an impact because of the relatively low refractive indexes lead to relatively low reflection as compared to the Si based cells. However, our

Image segmentation and particles classification using texture analysis method

Directory of Open Access Journals (Sweden)

Mayar Aly Atteya

Full Text Available Introduction: Ingredients of oily fish include a large amount of polyunsaturated fatty acids, which are important elements in various metabolic processes of humans, and have also been used to prevent diseases. However, in an attempt to reduce cost, recent developments are starting a replace the ingredients of fish oil with products of microalgae, that also produce polyunsaturated fatty acids. To do so, it is important to closely monitor morphological changes in algae cells and monitor their age in order to achieve the best results. This paper aims to describe an advanced vision-based system to automatically detect, classify, and track the organic cells using a recently developed SOPAT-System (Smart On-line Particle Analysis Technology, a photo-optical image acquisition device combined with innovative image analysis software. Methods The proposed method includes image de-noising, binarization and Enhancement, as well as object recognition, localization and classification based on the analysis of particles’ size and texture. Results The methods allowed for correctly computing cell’s size for each particle separately. By computing an area histogram for the input images (1h, 18h, and 42h, the variation could be observed showing a clear increase in cell. Conclusion The proposed method allows for algae particles to be correctly identified with accuracies up to 99% and classified correctly with accuracies up to 100%.

Filter and Filter Bank Design for Image Texture Recognition

Energy Technology Data Exchange (ETDEWEB)

Randen, Trygve

1997-12-31

The relevance of this thesis to energy and environment lies in its application to remote sensing such as for instance sea floor mapping and seismic pattern recognition. The focus is on the design of two-dimensional filters for feature extraction, segmentation, and classification of digital images with textural content. The features are extracted by filtering with a linear filter and estimating the local energy in the filter response. The thesis gives a review covering broadly most previous approaches to texture feature extraction and continues with proposals of some new techniques. 143 refs., 59 figs., 7 tabs.

ROLLING PROCESS WITH OHSAS AND TEXTURE FORMATION– A REVIEW

Directory of Open Access Journals (Sweden)

P. CHANDRAMOHAN

2009-03-01

Full Text Available Rolling is a mechanical treatment, which plays an important part in the processing of ferrous and nonferrous alloys. Texturing is an important phenomenon that occurs after rolling process. Preferred orientation increases the strength of the material enormously. Hence the research is focused on the rolling studies and the texture formation, which occurs after rolling process. This review mainly focuses on rolling process carried out in different alloys. It also highlights the analysis made on various rolling parameters for improving the mechanical properties. Texture studies carried on various ferrous and non-ferrous alloys; particularly in nitrogen alloyed duplex stainless steel is discussed. Finally the need for implementation of occupational health and safety during a thermomechanical treatment is also discussed. The state of art in this field is encouraging and showing positive signs of commercializing rolled nitrogen alloyed duplex stainless steel after proper texture control.

Textures of iron oxide ores by neutron diffraction and topotactical relation

International Nuclear Information System (INIS)

Wagner, F.; Esling, C.; Baro, R.; Englander, M.

1977-01-01

Two samples are cut from a polycrystalline haematite block. The first one is directly submitted to texture analysis by neutron diffraction, whereas the second one is first reduced into magnetite. The comparison of both textures is in agreement with a topotactical relationship previously reported for monocrystals. (orig.) [de

Perceptual asymmetry in texture perception.

OpenAIRE

Williams, D; Julesz, B

1992-01-01

A fundamental property of human visual perception is our ability to distinguish between textures. A concerted effort has been made to account for texture segregation in terms of linear spatial filter models and their nonlinear extensions. However, for certain texture pairs the ease of discrimination changes when the role of figure and ground are reversed. This asymmetry poses a problem for both linear and nonlinear models. We have isolated a property of texture perception that can account for...

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.

Computerized image analysis: Texture-field orientation method for pectoral muscle identification on MLO-view mammograms

International Nuclear Information System (INIS)

Zhou Chuan; Wei Jun; Chan, Heang-Ping; Paramagul, Chintana; Hadjiiski, Lubomir M.; Sahiner, Berkman; Douglas, Julie A.

2010-01-01

Purpose: To develop a new texture-field orientation (TFO) method that combines a priori knowledge, local and global information for the automated identification of pectoral muscle on mammograms. Methods: The authors designed a gradient-based directional kernel (GDK) filter to enhance the linear texture structures, and a gradient-based texture analysis to extract a texture orientation image that represented the dominant texture orientation at each pixel. The texture orientation image was enhanced by a second GDK filter for ridge point extraction. The extracted ridge points were validated and the ridges that were less likely to lie on the pectoral boundary were removed automatically. A shortest-path finding method was used to generate a probability image that represented the likelihood that each remaining ridge point lay on the true pectoral boundary. Finally, the pectoral boundary was tracked by searching for the ridge points with the highest probability lying on the pectoral boundary. A data set of 130 MLO-view digitized film mammograms (DFMs) from 65 patients was used to train the TFO algorithm. An independent data set of 637 MLO-view DFMs from 562 patients was used to evaluate its performance. Another independent data set of 92 MLO-view full field digital mammograms (FFDMs) from 92 patients was used to assess the adaptability of the TFO algorithm to FFDMs. The pectoral boundary detection accuracy of the TFO method was quantified by comparison with an experienced radiologist's manually drawn pectoral boundary using three performance metrics: The percent overlap area (POA), the Hausdorff distance (Hdist), and the average distance (AvgDist). Results: The mean and standard deviation of POA, Hdist, and AvgDist were 95.0±3.6%, 3.45±2.16 mm, and 1.12±0.82 mm, respectively. For the POA measure, 91.5%, 97.3%, and 98.9% of the computer detected pectoral muscles had POA larger than 90%, 85%, and 80%, respectively. For the distance measures, 85.4% and 98.0% of the

The effect of substrate texture and oxidation temperature on oxide texture development in zirconium alloys

Energy Technology Data Exchange (ETDEWEB)

Garner, A., E-mail: alistair.garner@manchester.ac.uk [Materials Performance Centre, University of Manchester, Grosvenor Street, Manchester, M17HS (United Kingdom); Frankel, P. [Materials Performance Centre, University of Manchester, Grosvenor Street, Manchester, M17HS (United Kingdom); Partezana, J. [Westinghouse Electric Company, 1332 Beulah Road, Pittsburgh, PA 15235 (United States); Preuss, M. [Materials Performance Centre, University of Manchester, Grosvenor Street, Manchester, M17HS (United Kingdom)

2017-02-15

During corrosion of zirconium alloys a highly textured oxide is formed, the degree of this preferred orientation has previously been shown to be an important factor in determining the corrosion behaviour of these alloys. Two distinct experiments were designed in order to investigate the origin of this oxide texture development on two commercial alloys. Firstly, sheet samples of Zircaloy-4 were oxidised between 500 and 800 °C in air. The resulting monoclinic oxide texture strength was observed to decrease with increasing oxidation temperature. In a second experiment, orthogonal faces of Low Tin ZIRLO{sub ™} were oxidised in 360 °C water, providing different substrate textures but identical microstructures. The substrate texture was observed to have a negligible effect on the corrosion performance whilst the major orientation of both oxide phases was found to be independent of substrate orientation. It is concluded that the main driving force for oxide texture development in single-phase zirconium alloys is the compressive stress caused by the Zr−ZrO{sub 2} transformation. - Highlights: • Substrate orientation does not significantly affect oxide texture development. • Corrosion performance is independent of substrate texture. • Monoclinic oxide texture strength decreases with increasing oxidation temperature. • The main driving force for texture development is the oxidation-induced stress.

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

Energy Technology Data Exchange (ETDEWEB)

Lohmann, Philipp; Stoffels, Gabriele; Stegmayr, Carina; Neumaier, Bernd [Forschungszentrum Juelich, Institute of Neuroscience and Medicine, Juelich (Germany); Ceccon, Garry [University of Cologne, Department of Neurology, Cologne (Germany); Rapp, Marion; Sabel, Michael; Kamp, Marcel A. [Heinrich Heine University Duesseldorf, Department of Neurosurgery, Duesseldorf (Germany); Filss, Christian P. [Forschungszentrum Juelich, Institute of Neuroscience and Medicine, Juelich (Germany); RWTH Aachen University Hospital, Department of Nuclear Medicine, Aachen (Germany); Shah, Nadim J. [Forschungszentrum Juelich, Institute of Neuroscience and Medicine, Juelich (Germany); RWTH Aachen University Hospital, Department of Neurology, Aachen (Germany); Juelich-Aachen Research Alliance (JARA) - Section JARA-Brain, Department of Neurology, Juelich (Germany); Langen, Karl-Josef [Forschungszentrum Juelich, Institute of Neuroscience and Medicine, Juelich (Germany); RWTH Aachen University Hospital, Department of Nuclear Medicine, Aachen (Germany); Juelich-Aachen Research Alliance (JARA) - Section JARA-Brain, Department of Neurology, Juelich (Germany); Galldiks, Norbert [Forschungszentrum Juelich, Institute of Neuroscience and Medicine, Juelich (Germany); University of Cologne, Department of Neurology, Cologne (Germany); University of Cologne, Center of Integrated Oncology (CIO), Cologne (Germany)

2017-07-15

We investigated the potential of textural feature analysis of O-(2-[{sup 18}F]fluoroethyl)-L-tyrosine ({sup 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 {sup 18}F-FET PET. Tumour-to-brain ratios (TBRs) of {sup 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{sub mean} alone to 85 % when combined with the textural parameter Coarseness or Short-zone emphasis. The accuracy of TBR{sub 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{sub 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 {sup 18}F-FET PET scans. (orig.)

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.

Effects of gluten and transglutaminase on microstructure, sensory characteristics and instrumental texture of oat bread

Directory of Open Access Journals (Sweden)

M. SALMENKALLIO-MARTTILA

2008-12-01

Full Text Available Effects of added gluten and transglutaminase on microstructure, instrumental texture and sensory characteristics of bread baked with 51% wholemeal oat flour were compared in order to determine how changes in the state of macromolecules – protein and starch – correlate with changes in sensory and instrumental structure. Light microscopy, instrumental texture profile analysis, and descriptive sensory analysis were used to analyse the test breads. Addition of gluten and transglutaminase affected the structure of the protein network and distribution of water between the protein and starch phases. The differences in microstructure were quantified by determining the areas of starch and protein in the micrographs by image analysis. Breads baked with added gluten and water were softer and less gummy than the oat and wheat reference breads in the texture profile analysis. Addition of transglutaminase made the breads harder and gummier than the breads baked without the added enzyme. In the descriptive sensory analysis breads baked with added gluten or added gluten and water were evaluated as more soft and springy than the reference oat bread. Sensory characteristics of bread texture correlated well with the texture and microstructure measured instrumentally.;

Perceptual asymmetry in texture perception.

Science.gov (United States)

Williams, D; Julesz, B

1992-07-15

A fundamental property of human visual perception is our ability to distinguish between textures. A concerted effort has been made to account for texture segregation in terms of linear spatial filter models and their nonlinear extensions. However, for certain texture pairs the ease of discrimination changes when the role of figure and ground are reversed. This asymmetry poses a problem for both linear and nonlinear models. We have isolated a property of texture perception that can account for this asymmetry in discrimination: subjective closure. This property, which is also responsible for visual illusions, appears to be explainable by early visual processes alone. Our results force a reexamination of the process of human texture segregation and of some recent models that were introduced to explain it.

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 ...

Control of texture in Ag and Ag-alloy substrates for superconducting tapes

International Nuclear Information System (INIS)

Gladstone, T.A.

2000-01-01

The use of a biaxially textured silver tape as a substrate for high temperature superconductor (HTS) phases is one possible route towards the fabrication of high-J c superconducting tape. Using a cold-rolling and annealing process we have reproducibly fabricated {110} textured silver which is stable up to 900 deg. C. We have found that there are two critical process requirements for the formation of this texture; a low oxygen content in the material prior to deformation, and a cold-rolling thickness reduction of less than 97%. To overcome the problems associated with the poor mechanical strength of pure silver, texture development in Ag-Mg and Ag-Hf alloys with improved mechanical properties has been studied. Heat treatments in a reducing atmosphere allow the {110} annealing texture to be obtained in Ag-0.1 wt%Mg. The recrystallization behaviour of a Ag-Pd alloy with an increased stacking fault energy was also investigated and a partial cube texture was obtained in this material. Using orientation distribution function (ODF) analysis we have shown that minor variations in the deformation texture of both pure silver and Ag-based alloys can lead to significant differences in the recrystallization textures obtained. (author)

Texturing of sodium bismuth titanate-barium titanate ceramics by templated grain growth

Science.gov (United States)

Yilmaz, Huseyin

2002-01-01

Sodium bismuth titanate modified with barium titanate, (Na1/2Bi 1/2)TiO3-BaTiO3 (NBT-BT), is a candidate lead-free piezoelectric material which has been shown to have comparatively high piezoelectric response. In this work, textured (Na1/2Bi1/2)TiO 3-BaTiO3 (5.5mol% BaTiO3) ceramics with pc (where pc denotes the pseudocubic perovskite cell) orientation were fabricated by Templated Grain Growth (TGG) or Reactive Templated Grain Growth (RTGG) using anisotropically shaped template particles. In the case of TGG, molten salt synthesized SrTiO3 platelets were tape cast with a (Na1/2Bi1/2)TiO3-5.5mol%BaTiO3 powder and sintered at 1200°C for up to 12 hours. For the RTGG approach, Bi4Ti3O12 (BiT) platelets were tape cast with a Na2CO3, Bi2O3, TiO 2, and BaCO3 powder mixture and reactively sintered. The TGG approach using SrTiO3 templates gave stronger texture along [001] compared to the RTGG approach using BiT templates. The textured ceramics were characterized by X-ray and electron backscatter diffraction for the quality of texture. The texture function was quantified by the Lotgering factor, rocking curve, pole figures, inverse pole figures, and orientation imaging microscopy. Electrical and electromechanical property characterization of randomly oriented and pc textured (Na1/2Bi1/2)TiO 3-5.5 mol% BaTiO3 rhombohedral ceramics showed 0.26% strain at 70 kV/cm, d33 coefficients over 500 pC/N have been obtained for highly textured samples (f ˜ 90%). The piezoelectric coefficient from Berlincourt was d33 ˜ 200 pC/N. The materials show considerable hysteresis. The presence of hysteresis in the unipolar-electric field curve is probably linked to the ferroelastic phase transition seen in the (Na 1/2Bi1/2)TiO3 system on cooling from high temperature at ˜520°C. The macroscopic physical properties (remanent polarization, dielectric constant, and piezoelectric coefficient) of random and textured ([001] pc) rhombohedral perovskites were estimated by linear averaging of single

Computer-aided diagnosis with textural features for breast lesions in sonograms.

Science.gov (United States)

Chen, Dar-Ren; Huang, Yu-Len; Lin, Sheng-Hsiung

2011-04-01

Computer-aided diagnosis (CAD) systems provided second beneficial support reference and enhance the diagnostic accuracy. This paper was aimed to develop and evaluate a CAD with texture analysis in the classification of breast tumors for ultrasound images. The ultrasound (US) dataset evaluated in this study composed of 1020 sonograms of region of interest (ROI) subimages from 255 patients. Two-view sonogram (longitudinal and transverse views) and four different rectangular regions were utilized to analyze each tumor. Six practical textural features from the US images were performed to classify breast tumors as benign or malignant. However, the textural features always perform as a high dimensional vector; high dimensional vector is unfavorable to differentiate breast tumors in practice. The principal component analysis (PCA) was used to reduce the dimension of textural feature vector and then the image retrieval technique was performed to differentiate between benign and malignant tumors. In the experiments, all the cases were sampled with k-fold cross-validation (k=10) to evaluate the performance with receiver operating characteristic (ROC) curve. The area (A(Z)) under the ROC curve for the proposed CAD system with the specific textural features was 0.925±0.019. The classification ability for breast tumor with textural information is satisfactory. This system differentiates benign from malignant breast tumors with a good result and is therefore clinically useful to provide a second opinion. Copyright © 2010 Elsevier Ltd. All rights reserved.

Relating instrumental texture, determined relating instrumental texture, determined attachments, to sensory analysis of rainbow trout, Oncorhynchus mykiss, fillets

Science.gov (United States)

Texture is one of the most important quality attributes of fish fillets, and accurate assessment of variation in this attribute, as affected by storage and handling, is critical in providing consistent quality product. Trout fillets received 4 treatments: 3-d refrigeration (R3), 7-d refrigeration (R...

Adaptive weighted local textural features for illumination, expression, and occlusion invariant face recognition

Science.gov (United States)

Cui, Chen; Asari, Vijayan K.

2014-03-01

Biometric features such as fingerprints, iris patterns, and face features help to identify people and restrict access to secure areas by performing advanced pattern analysis and matching. Face recognition is one of the most promising biometric methodologies for human identification in a non-cooperative security environment. However, the recognition results obtained by face recognition systems are a affected by several variations that may happen to the patterns in an unrestricted environment. As a result, several algorithms have been developed for extracting different facial features for face recognition. Due to the various possible challenges of data captured at different lighting conditions, viewing angles, facial expressions, and partial occlusions in natural environmental conditions, automatic facial recognition still remains as a difficult issue that needs to be resolved. In this paper, we propose a novel approach to tackling some of these issues by analyzing the local textural descriptions for facial feature representation. The textural information is extracted by an enhanced local binary pattern (ELBP) description of all the local regions of the face. The relationship of each pixel with respect to its neighborhood is extracted and employed to calculate the new representation. ELBP reconstructs a much better textural feature extraction vector from an original gray level image in different lighting conditions. The dimensionality of the texture image is reduced by principal component analysis performed on each local face region. Each low dimensional vector representing a local region is now weighted based on the significance of the sub-region. The weight of each sub-region is determined by employing the local variance estimate of the respective region, which represents the significance of the region. The final facial textural feature vector is obtained by concatenating the reduced dimensional weight sets of all the modules (sub-regions) of the face image

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.

Gravitational effects of global textures

International Nuclear Information System (INIS)

Noetzold, D.

1990-03-01

A solution for the dynamics of global textures is obtained. Their gravitational field during the collapse and the subsequent evolution is found to be given solely by a space-time dependent ''deficit solid angle.'' The frequency shift of photons traversing this gravitational field is calculated. The space-time dependent texture metric locally contracts the volume of three-space and thereby induces overdensities in homogeneous matter distributions. There are no gravitational forces unless matter has a nonzero angular momentum with respect to the texture origin which would be the case for moving textures

Examples of neutron diffraction texture analysis on one and the same chalcopyrite sample before and after experimental deformation

International Nuclear Information System (INIS)

Jansen, E.M.; Brokmeier, H.G.; Siemes, H.

1994-01-01

Natural chalcopyrite specimens from Mt. Isa, Australia were investigated by neutron diffraction texture analysis. The preferred orientation of the specimens consists of 3 main orientation components. After axial shortening at a temperature of 25 C the initial orientation components became weaker, a new component was detected. (orig.)

Textural properties of chars as determined by petrographic analysis: comparison between air-blown, oxygen-blown and oxygen-enriched gasification

CSIR Research Space (South Africa)

Oboirien, BO

2012-11-01

Full Text Available In this study, the textural properties of chars generated from a vitrinite, high ash coal in a fluidised bed gasifier under air-blown, oxygen-blown and oxygen-enriched conditions were determined by detailed petrographic analysis. The char samples...

Thickness related textural properties of retinal nerve fiber layer in color fundus images.

Science.gov (United States)

Odstrcilik, Jan; Kolar, Radim; Tornow, Ralf-Peter; Jan, Jiri; Budai, Attila; Mayer, Markus; Vodakova, Martina; Laemmer, Robert; Lamos, Martin; Kuna, Zdenek; Gazarek, Jiri; Kubena, Tomas; Cernosek, Pavel; Ronzhina, Marina

2014-09-01

Images of ocular fundus are routinely utilized in ophthalmology. Since an examination using fundus camera is relatively fast and cheap procedure, it can be used as a proper diagnostic tool for screening of retinal diseases such as the glaucoma. One of the glaucoma symptoms is progressive atrophy of the retinal nerve fiber layer (RNFL) resulting in variations of the RNFL thickness. Here, we introduce a novel approach to capture these variations using computer-aided analysis of the RNFL textural appearance in standard and easily available color fundus images. The proposed method uses the features based on Gaussian Markov random fields and local binary patterns, together with various regression models for prediction of the RNFL thickness. The approach allows description of the changes in RNFL texture, directly reflecting variations in the RNFL thickness. Evaluation of the method is carried out on 16 normal ("healthy") and 8 glaucomatous eyes. We achieved significant correlation (normals: ρ=0.72±0.14; p≪0.05, glaucomatous: ρ=0.58±0.10; p≪0.05) between values of the model predicted output and the RNFL thickness measured by optical coherence tomography, which is currently regarded as a standard glaucoma assessment device. The evaluation thus revealed good applicability of the proposed approach to measure possible RNFL thinning. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Modelling patterns of pollinator species richness and diversity using satellite image texture.

Directory of Open Access Journals (Sweden)

Sylvia Hofmann

Full Text Available Assessing species richness and diversity on the basis of standardised field sampling effort represents a cost- and time-consuming method. Satellite remote sensing (RS can help overcome these limitations because it facilitates the collection of larger amounts of spatial data using cost-effective techniques. RS information is hence increasingly analysed to model biodiversity across space and time. Here, we focus on image texture measures as a proxy for spatial habitat heterogeneity, which has been recognized as an important determinant of species distributions and diversity. Using bee monitoring data of four years (2010-2013 from six 4 × 4 km field sites across Central Germany and a multimodel inference approach we test the ability of texture features derived from Landsat-TM imagery to model local pollinator biodiversity. Textures were shown to reflect patterns of bee diversity and species richness to some extent, with the first-order entropy texture and terrain roughness being the most relevant indicators. However, the texture measurements accounted for only 3-5% of up to 60% of the variability that was explained by our final models, although the results are largely consistent across different species groups (bumble bees, solitary bees. While our findings provide indications in support of the applicability of satellite imagery textures for modeling patterns of bee biodiversity, they are inconsistent with the high predictive power of texture metrics reported in previous studies for avian biodiversity. We assume that our texture data captured mainly heterogeneity resulting from landscape configuration, which might be functionally less important for wild bees than compositional diversity of plant communities. Our study also highlights the substantial variability among taxa in the applicability of texture metrics for modelling biodiversity.

Modelling patterns of pollinator species richness and diversity using satellite image texture.

Science.gov (United States)

Hofmann, Sylvia; Everaars, Jeroen; Schweiger, Oliver; Frenzel, Mark; Bannehr, Lutz; Cord, Anna F

2017-01-01

Assessing species richness and diversity on the basis of standardised field sampling effort represents a cost- and time-consuming method. Satellite remote sensing (RS) can help overcome these limitations because it facilitates the collection of larger amounts of spatial data using cost-effective techniques. RS information is hence increasingly analysed to model biodiversity across space and time. Here, we focus on image texture measures as a proxy for spatial habitat heterogeneity, which has been recognized as an important determinant of species distributions and diversity. Using bee monitoring data of four years (2010-2013) from six 4 × 4 km field sites across Central Germany and a multimodel inference approach we test the ability of texture features derived from Landsat-TM imagery to model local pollinator biodiversity. Textures were shown to reflect patterns of bee diversity and species richness to some extent, with the first-order entropy texture and terrain roughness being the most relevant indicators. However, the texture measurements accounted for only 3-5% of up to 60% of the variability that was explained by our final models, although the results are largely consistent across different species groups (bumble bees, solitary bees). While our findings provide indications in support of the applicability of satellite imagery textures for modeling patterns of bee biodiversity, they are inconsistent with the high predictive power of texture metrics reported in previous studies for avian biodiversity. We assume that our texture data captured mainly heterogeneity resulting from landscape configuration, which might be functionally less important for wild bees than compositional diversity of plant communities. Our study also highlights the substantial variability among taxa in the applicability of texture metrics for modelling biodiversity.

Temporal resolution of orientation-defined texture segregation: a VEP study.

Science.gov (United States)

Lachapelle, Julie; McKerral, Michelle; Jauffret, Colin; Bach, Michael

2008-09-01

Orientation is one of the visual dimensions that subserve figure-ground discrimination. A spatial gradient in orientation leads to "texture segregation", which is thought to be concurrent parallel processing across the visual field, without scanning. In the visual-evoked potential (VEP) a component can be isolated which is related to texture segregation ("tsVEP"). Our objective was to evaluate the temporal frequency dependence of the tsVEP to compare processing speed of low-level features (e.g., orientation, using the VEP, here denoted llVEP) with texture segregation because of a recent literature controversy in that regard. Visual-evoked potentials (VEPs) were recorded in seven normal adults. Oriented line segments of 0.1 degrees x 0.8 degrees at 100% contrast were presented in four different arrangements: either oriented in parallel for two homogeneous stimuli (from which were obtained the low-level VEP (llVEP)) or with a 90 degrees orientation gradient for two textured ones (from which were obtained the texture VEP). The orientation texture condition was presented at eight different temporal frequencies ranging from 7.5 to 45 Hz. Fourier analysis was used to isolate low-level components at the pattern-change frequency and texture-segregation components at half that frequency. For all subjects, there was lower high-cutoff frequency for tsVEP than for llVEPs, on average 12 Hz vs. 17 Hz (P = 0.017). The results suggest that the processing of feature gradients to extract texture segregation requires additional processing time, resulting in a lower fusion frequency.

Annealing texture of rolled nickel alloys

International Nuclear Information System (INIS)

Meshchaninov, I.V.; Khayutin, S.G.

1976-01-01

A texture of pure nickel and binary alloys after the 95% rolling and annealing has been studied. Insoluble additives (Mg, Zr) slacken the cubic texture in nickel and neral slackening of the texture (Zr). In the case of alloying with silicium (up to 2%) the texture practically coinsides with that of a technical-grade nickel. The remaining soluble additives either do not change the texture of pure nickel (C, Nb) or enhance the sharpness and intensity of the cubic compontnt (Al, Cu, Mn, Cr, Mo, W, Co -at their content 0.5 to 2.0%). A model is proposed by which variation of the annealing texture upon alloying is caused by dissimilar effect of the alloying elements on the mobility of high- and low-angle grain boundaries

Hierarchical Multiple Markov Chain Model for Unsupervised Texture Segmentation

Czech Academy of Sciences Publication Activity Database

Scarpa, G.; Gaetano, R.; Haindl, Michal; Zerubia, J.

2009-01-01

Roč. 18, č. 8 (2009), s. 1830-1843 ISSN 1057-7149 R&D Projects: GA ČR GA102/08/0593 EU Projects: European Commission(XE) 507752 - MUSCLE Institutional research plan: CEZ:AV0Z10750506 Keywords : Classification * texture analysis * segmentation * hierarchical image models * Markov process Subject RIV: BD - Theory of Information Impact factor: 2.848, year: 2009 http://library.utia.cas.cz/separaty/2009/RO/haindl-hierarchical multiple markov chain model for unsupervised texture segmentation.pdf

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

Directory of Open Access Journals (Sweden)

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.

Idiopathic Pulmonary Fibrosis: Data-driven Textural Analysis of Extent of Fibrosis at Baseline and 15-Month Follow-up.

Science.gov (United States)

Humphries, Stephen M; Yagihashi, Kunihiro; Huckleberry, Jason; Rho, Byung-Hak; Schroeder, Joyce D; Strand, Matthew; Schwarz, Marvin I; Flaherty, Kevin R; Kazerooni, Ella A; van Beek, Edwin J R; Lynch, David A

2017-10-01

Purpose To evaluate associations between pulmonary function and both quantitative analysis and visual assessment of thin-section computed tomography (CT) images at baseline and at 15-month follow-up in subjects with idiopathic pulmonary fibrosis (IPF). Materials and Methods This retrospective analysis of preexisting anonymized data, collected prospectively between 2007 and 2013 in a HIPAA-compliant study, was exempt from additional institutional review board approval. The extent of lung fibrosis at baseline inspiratory chest CT in 280 subjects enrolled in the IPF Network was evaluated. Visual analysis was performed by using a semiquantitative scoring system. Computer-based quantitative analysis included CT histogram-based measurements and a data-driven textural analysis (DTA). Follow-up CT images in 72 of these subjects were also analyzed. Univariate comparisons were performed by using Spearman rank correlation. Multivariate and longitudinal analyses were performed by using a linear mixed model approach, in which models were compared by using asymptotic χ 2 tests. Results At baseline, all CT-derived measures showed moderate significant correlation (P pulmonary function. At follow-up CT, changes in DTA scores showed significant correlation with changes in both forced vital capacity percentage predicted (ρ = -0.41, P pulmonary function (P fibrosis at CT yields an index of severity that correlates with visual assessment and functional change in subjects with IPF. © RSNA, 2017.

Laser surface texturing of tool steel: textured surfaces quality evaluation

Science.gov (United States)

Šugár, Peter; Šugárová, Jana; Frnčík, Martin

2016-05-01

In this experimental investigation the laser surface texturing of tool steel of type 90MnCrV8 has been conducted. The 5-axis highly dynamic laser precision machining centre Lasertec 80 Shape equipped with the nano-second pulsed ytterbium fibre laser and CNC system Siemens 840 D was used. The planar and spherical surfaces first prepared by turning have been textured. The regular array of spherical and ellipsoidal dimples with a different dimensions and different surface density has been created. Laser surface texturing has been realized under different combinations of process parameters: pulse frequency, pulse energy and laser beam scanning speed. The morphological characterization of ablated surfaces has been performed using scanning electron microscopy (SEM) technique. The results show limited possibility of ns pulse fibre laser application to generate different surface structures for tribological modification of metallic materials. These structures were obtained by varying the processing conditions between surface ablation, to surface remelting. In all cases the areas of molten material and re-cast layers were observed on the bottom and walls of the dimples. Beside the influence of laser beam parameters on the machined surface quality during laser machining of regular hemispherical and elipsoidal dimple texture on parabolic and hemispherical surfaces has been studied.

Semi-quantitative evaluation of texture components and anisotropy of the yield strength in 2524 T3 alloy sheets

International Nuclear Information System (INIS)

Shen, Fanghua; Yi, Danqing; Wang, Bin; Liu, Huiqun; Jiang, Yong; Tang, Cong; Jiang, Bo

2016-01-01

Decreasing the anisotropy of 2524 alloys is a key factor for their use in applications such as high-performance inertial components or space robots. Studying the interaction between sheet textures and anisotropy is a key factor to overcome this problem. In this study, the semi-quantitative approach to estimate the relation between texture and in-plane anisotropy (IPA) of yield strength has been developed. The intensity ratio between Cube and Brass texture components (F CGB ) was used as an effective variable for this purpose. This approach has been tested in 2524 T3 aluminum alloy sheets, which were investigated using X-Ray diffraction, scanning electron microscopy, optical microscopy and tensile tests. The results show that F CGB decreased with an increase in cold reduction. The 2524 T3 sheet, dominated by Cube texture grains, possesses the lowest in-plane anisotropy for the yield strength of all texture components investigated. The alloy sheet dominated by Brass texture exhibits the highest anisotropy, while the Goss texture-led sheets fall in between them. These results agree with the trends seen in the factor F CGB , suggesting that is suited to evaluate the anisotropy of yield strength in 2524 T3 alloy sheets semi-quantitatively.

Semi-quantitative evaluation of texture components and anisotropy of the yield strength in 2524 T3 alloy sheets

Energy Technology Data Exchange (ETDEWEB)

Shen, Fanghua [School of Materials Science and Engineering, Central South University, Changsha 410083 (China); Yi, Danqing, E-mail: yioffice@csu.edu.cn [School of Materials Science and Engineering, Central South University, Changsha 410083 (China); Light Alloy Research Institute, Central South University, Changsha, Hunan 410083 (China); National Collaborative Innovation Center of Advanced Nonferrous Structural Materials and Manufacturing, Central South University, Changsha 410083 (China); Wang, Bin; Liu, Huiqun; Jiang, Yong; Tang, Cong; Jiang, Bo [School of Materials Science and Engineering, Central South University, Changsha 410083 (China)

2016-10-15

Decreasing the anisotropy of 2524 alloys is a key factor for their use in applications such as high-performance inertial components or space robots. Studying the interaction between sheet textures and anisotropy is a key factor to overcome this problem. In this study, the semi-quantitative approach to estimate the relation between texture and in-plane anisotropy (IPA) of yield strength has been developed. The intensity ratio between Cube and Brass texture components (F{sub CGB}) was used as an effective variable for this purpose. This approach has been tested in 2524 T3 aluminum alloy sheets, which were investigated using X-Ray diffraction, scanning electron microscopy, optical microscopy and tensile tests. The results show that F{sub CGB} decreased with an increase in cold reduction. The 2524 T3 sheet, dominated by Cube texture grains, possesses the lowest in-plane anisotropy for the yield strength of all texture components investigated. The alloy sheet dominated by Brass texture exhibits the highest anisotropy, while the Goss texture-led sheets fall in between them. These results agree with the trends seen in the factor F{sub CGB}, suggesting that is suited to evaluate the anisotropy of yield strength in 2524 T3 alloy sheets semi-quantitatively.

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)

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

Directory of Open Access Journals (Sweden)

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.

Three-dimensional textural features of conventional MRI improve diagnostic classification of childhood brain tumours.

Science.gov (United States)

Fetit, Ahmed E; Novak, Jan; Peet, Andrew C; Arvanitits, Theodoros N

2015-09-01

The aim of this study was to assess the efficacy of three-dimensional texture analysis (3D TA) of conventional MR images for the classification of childhood brain tumours in a quantitative manner. The dataset comprised pre-contrast T1 - and T2-weighted MRI series obtained from 48 children diagnosed with brain tumours (medulloblastoma, pilocytic astrocytoma and ependymoma). 3D and 2D TA were carried out on the images using first-, second- and higher order statistical methods. Six supervised classification algorithms were trained with the most influential 3D and 2D textural features, and their performances in the classification of tumour types, using the two feature sets, were compared. Model validation was carried out using the leave-one-out cross-validation (LOOCV) approach, as well as stratified 10-fold cross-validation, in order to provide additional reassurance. McNemar's test was used to test the statistical significance of any improvements demonstrated by 3D-trained classifiers. Supervised learning models trained with 3D textural features showed improved classification performances to those trained with conventional 2D features. For instance, a neural network classifier showed 12% improvement in area under the receiver operator characteristics curve (AUC) and 19% in overall classification accuracy. These improvements were statistically significant for four of the tested classifiers, as per McNemar's tests. This study shows that 3D textural features extracted from conventional T1 - and T2-weighted images can improve the diagnostic classification of childhood brain tumours. Long-term benefits of accurate, yet non-invasive, diagnostic aids include a reduction in surgical procedures, improvement in surgical and therapy planning, and support of discussions with patients' families. It remains necessary, however, to extend the analysis to a multicentre cohort in order to assess the scalability of the techniques used. Copyright © 2015 John Wiley & Sons, Ltd.

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

Precision of quantitative computed tomography texture analysis using image filtering: A phantom study for scanner variability.

Science.gov (United States)

Yasaka, Koichiro; Akai, Hiroyuki; Mackin, Dennis; Court, Laurence; Moros, Eduardo; Ohtomo, Kuni; Kiryu, Shigeru

2017-05-01

Quantitative computed tomography (CT) texture analyses for images with and without filtration are gaining attention to capture the heterogeneity of tumors. The aim of this study was to investigate how quantitative texture parameters using image filtering vary among different computed tomography (CT) scanners using a phantom developed for radiomics studies.A phantom, consisting of 10 different cartridges with various textures, was scanned under 6 different scanning protocols using four CT scanners from four different vendors. CT texture analyses were performed for both unfiltered images and filtered images (using a Laplacian of Gaussian spatial band-pass filter) featuring fine, medium, and coarse textures. Forty-five regions of interest were placed for each cartridge (x) in a specific scan image set (y), and the average of the texture values (T(x,y)) was calculated. The interquartile range (IQR) of T(x,y) among the 6 scans was calculated for a specific cartridge (IQR(x)), while the IQR of T(x,y) among the 10 cartridges was calculated for a specific scan (IQR(y)), and the median IQR(y) was then calculated for the 6 scans (as the control IQR, IQRc). The median of their quotient (IQR(x)/IQRc) among the 10 cartridges was defined as the variability index (VI).The VI was relatively small for the mean in unfiltered images (0.011) and for standard deviation (0.020-0.044) and entropy (0.040-0.044) in filtered images. Skewness and kurtosis in filtered images featuring medium and coarse textures were relatively variable across different CT scanners, with VIs of 0.638-0.692 and 0.430-0.437, respectively.Various quantitative CT texture parameters are robust and variable among different scanners, and the behavior of these parameters should be taken into consideration.

Fabrication of friction-reducing texture surface by selective laser melting of ink-printed (SLM-IP) copper (Cu) nanoparticles(NPs)

Science.gov (United States)

Wang, Xinjian; Liu, Junyan; Wang, Yang; Fu, Yanan

2017-02-01

This paper reports a process of selective laser melting of ink-printed (SLM-IP) copper (Cu) nanoparticles(NPs) for the fabrication of full dense Cu friction-reducing texture on the metallic surface in ambient condition. This technique synthesizes pure Cu by chemical reduction route using an organic solvent during laser melting in the atmosphere environment, and provides a flexible additive manufacture approach to form complex friction-reduction texture on the metallic surface. Microtextures of ring and disc arrays have been fabricated on the stainless steel surface by SLM-IP Cu NPs. The friction coefficient has been measured under the lubricating condition of the oil. Disc texture surface (DTS) has a relatively low friction coefficient compared with ring texture surface (RTS), Cu film surface (Cu-FS) and the untreated substrate. The study suggests a further research on SLM-IP approach for complex microstructure or texture manufacturing, possibly realizing its advantage of flexibility.

Mechanical properties of highly textured Cu/Ni multilayers

International Nuclear Information System (INIS)

Liu, Y.; Bufford, D.; Wang, H.; Sun, C.; Zhang, X.

2011-01-01

We report on the synthesis of highly (1 1 1) and (1 0 0) textured Cu/Ni multilayers with individual layer thicknesses, h, varying from 1 to 200 nm. When, h, decreases to 5 nm or less, X-ray diffraction spectra show epitaxial growth of Cu/Ni multilayers. High resolution transmission electron microscopy studies show the coexistence of nanotwins and coherent layer interfaces in highly (1 1 1) textured Cu/Ni multilayers with smaller h. Hardnesses of multilayer films increase with decreasing h, approach a maximum at h of a few nanometers, and show softening thereafter at smaller h. The influence of layer interfaces as well as twin interfaces on strengthening mechanisms of multilayers and the formation of twins in Ni in multilayers are discussed.

Public and Private Partnership: A Strategy to Repair Old Texture

Directory of Open Access Journals (Sweden)

Mahdieh Nakhaei

2017-02-01

Full Text Available Todays, due to high construction costs and lack of economic potential of owners of old textures, public and private partnership is one of the restoration methods of these textures. Public-private partnership in the investment and implementation of worn and old textures’ restoration with guidance, support and supervision of governmental and public pillars is considered as a master key in restoration of old textures. This study aims at examining the effect of public and private partnership on restoration of old textures as well as providing strategies for strengthening and expanding this type of partnership. This article, based on descriptive-analytical approach, initially analyzes the existing problems and empowers the sections related to the rehabilitation and modernization of the textures. Then, through public and private partnership dealing with features such as shortening project times, reducing the project's financial problems, having financial–technical power, adopting equal rights for partners, and using flexible planning. Further, according to the findings of this study, in the case of legal infrastructures for public-private partnership, compliance of urbanism criteria with major goals of urban textures’ modernization, adequacy of facilities and incentive packages, the cooperation of owners, an increase in the supervision of the relevant institutions on partnership and the use of local experts and investors, the success of this partnership and restoration may be stably guaranteed.

Bas-relief map using texture analysis with application to live enhancement of ultrasound images.

Science.gov (United States)

Du, Huarui; Ma, Rui; Wang, Xiaoying; Zhang, Jue; Fang, Jing

2015-05-01

For ultrasound imaging, speckle is one of the most important factors in the degradation of contrast resolution because it masks meaningful texture and has the potential to interfere with diagnosis. It is expected that researchers would explore appropriate ways to reduce the speckle noise, to find the edges of structures and enhance weak borders between different organs in ultrasound imaging. Inspired by the principle of differential interference contrast microscopy, a "bas-relief map" is proposed that depicts the texture structure of ultrasound images. Based on a bas-relief map, an adaptive bas-relief filter was developed for ultrafast despeckling. Subsequently, an edge map was introduced to enhance the edges of images in real time. The holistic bas-relief map approach has been used experimentally with synthetic phantoms and digital ultrasound B-scan images of liver, kidney and gallbladder. Based on the visual inspection and the performance metrics of the despeckled images, it was found that the bas-relief map approach is capable of effectively reducing the speckle while significantly enhancing contrast and tissue boundaries for ultrasonic images, and its speckle reduction ability is comparable to that of Kuan, Lee and Frost filters. Meanwhile, the proposed technique could preserve more intra-region details compared with the popular speckle reducing anisotropic diffusion technique and more effectively enhance edges. In addition, the adaptive bas-relief filter was much less time consuming than the Kuan, Lee and Frost filter and speckle reducing anisotropic diffusion techniques. The bas-relief map strategy is effective for speckle reduction and live enhancement of ultrasound images, and can provide a valuable tool for clinical diagnosis. Copyright © 2015 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

THERMAL TEXTURE GENERATION AND 3D MODEL RECONSTRUCTION USING SFM AND GAN

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V. V. Kniaz

2018-05-01

Full Text Available Realistic 3D models with textures representing thermal emission of the object are widely used in such fields as dynamic scene analysis, autonomous driving, and video surveillance. Structure from Motion (SfM methods provide a robust approach for the generation of textured 3D models in the visible range. Still, automatic generation of 3D models from the infrared imagery is challenging due to an absence of the feature points and low sensor resolution. Recent advances in Generative Adversarial Networks (GAN have proved that they can perform complex image-to-image transformations such as a transformation of day to night and generation of imagery in a different spectral range. In this paper, we propose a novel method for generation of realistic 3D models with thermal textures using the SfM pipeline and GAN. The proposed method uses visible range images as an input. The images are processed in two ways. Firstly, they are used for point matching and dense point cloud generation. Secondly, the images are fed into a GAN that performs the transformation from the visible range to the thermal range. We evaluate the proposed method using real infrared imagery captured with a FLIR ONE PRO camera. We generated a dataset with 2000 pairs of real images captured in thermal and visible range. The dataset is used to train the GAN network and to generate 3D models using SfM. The evaluation of the generated 3D models and infrared textures proved that they are similar to the ground truth model in both thermal emissivity and geometrical shape.

A “Tuned” Mask Learnt Approach Based on Gravitational Search Algorithm

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Youchuan Wan

2016-01-01

Full Text Available Texture image classification is an important topic in many applications in machine vision and image analysis. Texture feature extracted from the original texture image by using “Tuned” mask is one of the simplest and most effective methods. However, hill climbing based training methods could not acquire the satisfying mask at a time; on the other hand, some commonly used evolutionary algorithms like genetic algorithm (GA and particle swarm optimization (PSO easily fall into the local optimum. A novel approach for texture image classification exemplified with recognition of residential area is detailed in the paper. In the proposed approach, “Tuned” mask is viewed as a constrained optimization problem and the optimal “Tuned” mask is acquired by maximizing the texture energy via a newly proposed gravitational search algorithm (GSA. The optimal “Tuned” mask is achieved through the convergence of GSA. The proposed approach has been, respectively, tested on some public texture and remote sensing images. The results are then compared with that of GA, PSO, honey-bee mating optimization (HBMO, and artificial immune algorithm (AIA. Moreover, feature extracted by Gabor wavelet is also utilized to make a further comparison. Experimental results show that the proposed method is robust and adaptive and exhibits better performance than other methods involved in the paper in terms of fitness value and classification accuracy.

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.

Analysis of through-thickness heterogeneities of microstructure and texture in nickel after accumulative roll bonding

DEFF Research Database (Denmark)

Zhang, Yubin; Mishin, Oleg; Godfrey, A.

2014-01-01

with the summed fraction of the rolling texture components. The observed microstructural and textural variations are discussed and compared with literature data, taking into account the influence of large-draught rolling and lubrication on the distribution of strain imposed during the ARB process....