Changes of the water-holding capacity and microstructure of panga and tilapia surimi gels using different stabilizers and processing methods.

PubMed

Filomena-Ambrosio, Annamaria; Quintanilla-Carvajal, María Ximena; Ana-Puig; Hernando, Isabel; Hernández-Carrión, María; Sotelo-Díaz, Indira

2016-01-01

Surimi gel is a food product traditionally manufactured from marine species; it has functional features including a specific texture and a high protein concentration. The objective of this study was to evaluate and compare the effect of the ultrasound extraction protein method and different stabilizers on the water-holding capacity (WHC), texture, and microstructure of surimi from panga and tilapia to potentially increase the value of these species. For this purpose, WHC was determined and texture profile analysis, scanning electron microscopy, and texture image analysis were carried out. The results showed that the ultrasound method and the sodium citrate can be used to obtain surimi gels from panga and tilapia with optimal textural properties such as the hardness and chewiness. Moreover, image analysis is recommended as a quantitative and non-invasive technique to evaluate the microstructure and texture image properties of surimis prepared using different processing methods and stabilizers. © The Author(s) 2015.

Texture analysis of Napoleonic War Era copper bolts

NASA Astrophysics Data System (ADS)

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.

Development of analysis techniques for remote sensing of vegetation resources

NASA Technical Reports Server (NTRS)

Draeger, W. C.

1972-01-01

Various data handling and analysis techniques are summarized for evaluation of ERTS-A and supporting high flight imagery. These evaluations are concerned with remote sensors applied to wildland and agricultural vegetation resource inventory problems. Monitoring California's annual grassland, automatic texture analysis, agricultural ground data collection techniques, and spectral measurements are included.

Scanning electron microscopy combined with image processing technique: Analysis of microstructure, texture and tenderness in Semitendinous and Gluteus Medius bovine muscles.

PubMed

Pieniazek, Facundo; Messina, Valeria

2016-11-01

In this study the effect of freeze drying on the microstructure, texture, and tenderness of Semitendinous and Gluteus Medius bovine muscles were analyzed applying Scanning Electron Microscopy combined with image analysis. Samples were analyzed by Scanning Electron Microscopy at different magnifications (250, 500, and 1,000×). Texture parameters were analyzed by Texture analyzer and by image analysis. Tenderness by Warner-Bratzler shear force. Significant differences (p < 0.05) were obtained for image and instrumental texture features. A linear trend with a linear correlation was applied for instrumental and image features. Image texture features calculated from Gray Level Co-occurrence Matrix (homogeneity, contrast, entropy, correlation and energy) at 1,000× in both muscles had high correlations with instrumental features (chewiness, hardness, cohesiveness, and springiness). Tenderness showed a positive correlation in both muscles with image features (energy and homogeneity). Combing Scanning Electron Microscopy with image analysis can be a useful tool to analyze quality parameters in meat.Summary SCANNING 38:727-734, 2016. © 2016 Wiley Periodicals, Inc. © Wiley Periodicals, Inc.

Investigation of quartz grain surface textures by atomic force microscopy for forensic analysis.

PubMed

Konopinski, D I; Hudziak, S; Morgan, R M; Bull, P A; Kenyon, A J

2012-11-30

This paper presents a study of quartz sand grain surface textures using atomic force microscopy (AFM) to image the surface. Until now scanning electron microscopy (SEM) has provided the primary technique used in the forensic surface texture analysis of quartz sand grains as a means of establishing the provenance of the grains for forensic reconstructions. The ability to independently corroborate the grain type classifications is desirable and provides additional weight to the findings of SEM analysis of the textures of quartz grains identified in forensic soil/sediment samples. AFM offers a quantitative means of analysis that complements SEM examination, and is a non-destructive technique that requires no sample preparation prior to scanning. It therefore has great potential to be used for forensic analysis where sample preservation is highly valuable. By taking quantitative topography scans, it is possible to produce 3D representations of microscopic surface textures and diagnostic features for examination. Furthermore, various empirical measures can be obtained from analysing the topography scans, including arithmetic average roughness, root-mean-square surface roughness, skewness, kurtosis, and multiple gaussian fits to height distributions. These empirical measures, combined with qualitative examination of the surfaces can help to discriminate between grain types and provide independent analysis that can corroborate the morphological grain typing based on the surface textures assigned using SEM. Furthermore, the findings from this study also demonstrate that quartz sand grain surfaces exhibit a statistically self-similar fractal nature that remains unchanged across scales. This indicates the potential for a further quantitative measure that could be utilised in the discrimination of quartz grains based on their provenance for forensic investigations. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

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?

PubMed

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.

Textured silicon nitride: processing and anisotropic properties

PubMed Central

Zhu, Xinwen; Sakka, Yoshio

2008-01-01

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 Si3N4 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 α-Sialon using the same methods as those used for textured β-Si3N4 and β-Sialon. PMID:27877995

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huber, M. B.; Carballido-Gamio, J.; Fritscher, K.

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 variousmore » 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}=0.61 (MF and MG features, p<0.01) and were partially independent of BMD. The correlations were dependent on the choice of the ROI and the texture measure. The best predictive multiregression model for failure load R{sub adj}{sup 2}=0.86 (p<0.001) included a set of recently developed texture methods (MF and SIM) but excluded bone mineral density and commonly used texture measures. Conclusions: The results suggest that texture information contained in trabecular bone structure visualized on radiographs may predict whether an implant anchorage can be used and may determine the local bone quality from preoperative radiographs.« less

Some distinguishing characteristics of contour and texture phenomena in images

NASA Technical Reports Server (NTRS)

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.

Photomorphic analysis techniques: An interim spatial analysis using satellite remote sensor imagery and historical data

NASA Technical Reports Server (NTRS)

Keuper, H. R.; Peplies, R. W.; Gillooly, R. P.

1977-01-01

The use of machine scanning and/or computer-based techniques to provide greater objectivity in the photomorphic approach was investigated. Photomorphic analysis and its application in regional planning are discussed. Topics included: delineation of photomorphic regions; inadequacies of existing classification systems; tonal and textural characteristics and signature analysis techniques; pattern recognition and Fourier transform analysis; and optical experiments. A bibliography is included.

Can texture analysis of tooth microwear detect within guild niche partitioning in extinct species?

NASA Astrophysics Data System (ADS)

Purnell, Mark; Nedza, Christopher; Rychlik, Leszek

2017-04-01

Recent work shows that tooth microwear analysis can be applied further back in time and deeper into the phylogenetic history of vertebrate clades than previously thought (e.g. niche partitioning in early Jurassic insectivorous mammals; Gill et al., 2014, Nature). Furthermore, quantitative approaches to analysis based on parameterization of surface roughness are increasing the robustness and repeatability of this widely used dietary proxy. Discriminating between taxa within dietary guilds has the potential to significantly increase our ability to determine resource use and partitioning in fossil vertebrates, but how sensitive is the technique? To address this question we analysed tooth microwear texture in sympatric populations of shrew species (Neomys fodiens, Neomys anomalus, Sorex araneus, Sorex minutus) from BiaŁ owieza Forest, Poland. These populations are known to exhibit varying degrees of niche partitioning (Churchfield & Rychlik, 2006, J. Zool.) with greatest overlap between the Neomys species. Sorex araneus also exhibits some niche overlap with N. anomalus, while S. minutus is the most specialised. Multivariate analysis based only on tooth microwear textures recovers the same pattern of niche partitioning. Our results also suggest that tooth textures track seasonal differences in diet. Projecting data from fossils into the multivariate dietary space defined using microwear from extant taxa demonstrates that the technique is capable of subtle dietary discrimination in extinct insectivores.

Texture functions in image analysis: A computationally efficient solution

NASA Technical Reports Server (NTRS)

Cox, S. C.; Rose, J. F.

1983-01-01

A computationally efficient means for calculating texture measurements from digital images by use of the co-occurrence technique is presented. The calculation of the statistical descriptors of image texture and a solution that circumvents the need for calculating and storing a co-occurrence matrix are discussed. The results show that existing efficient algorithms for calculating sums, sums of squares, and cross products can be used to compute complex co-occurrence relationships directly from the digital image input.

Comparison of Texture Analysis Techniques in Both Frequency and Spatial Domains for Cloud Feature Extraction

DTIC Science & Technology

1992-01-01

entropy , energy. variance, skewness, and object. It can also be applied to an image of a phenomenon. It kurtosis. These parameters are then used as...statistic. The co-occurrence matrix method is used in this study to derive texture values of entropy . Limogeneity. energy (similar to the GLDV angular...from working with the co-occurrence matrix method. Seven convolution sizes were chosen to derive the texture values of entropy , local homogeneity, and

Clustering document fragments using background color and texture information

NASA Astrophysics Data System (ADS)

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.

Texture analysis of tissues in Gleason grading of prostate cancer

NASA Astrophysics Data System (ADS)

Alexandratou, Eleni; Yova, Dido; Gorpas, Dimitris; Maragos, Petros; Agrogiannis, George; Kavantzas, Nikolaos

2008-02-01

Prostate cancer is a common malignancy among maturing men and the second leading cause of cancer death in USA. Histopathological grading of prostate cancer is based on tissue structural abnormalities. Gleason grading system is the gold standard and is based on the organization features of prostatic glands. Although Gleason score has contributed on cancer prognosis and on treatment planning, its accuracy is about 58%, with this percentage to be lower in GG2, GG3 and GG5 grading. On the other hand it is strongly affected by "inter- and intra observer variations", making the whole process very subjective. Therefore, there is need for the development of grading tools based on imaging and computer vision techniques for a more accurate prostate cancer prognosis. The aim of this paper is the development of a novel method for objective grading of biopsy specimen in order to support histopathological prognosis of the tumor. This new method is based on texture analysis techniques, and particularly on Gray Level Co-occurrence Matrix (GLCM) that estimates image properties related to second order statistics. Histopathological images of prostate cancer, from Gleason grade2 to Gleason grade 5, were acquired and subjected to image texture analysis. Thirteen texture characteristics were calculated from this matrix as they were proposed by Haralick. Using stepwise variable selection, a subset of four characteristics were selected and used for the description and classification of each image field. The selected characteristics profile was used for grading the specimen with the multiparameter statistical method of multiple logistic discrimination analysis. The subset of these characteristics provided 87% correct grading of the specimens. The addition of any of the remaining characteristics did not improve significantly the diagnostic ability of the method. This study demonstrated that texture analysis techniques could provide valuable grading decision support to the pathologists, concerning prostate cancer prognosis.

Acquiring 3-D information about thick objects from differential interference contrast images using texture extraction

NASA Astrophysics Data System (ADS)

Sierra, Heidy; Brooks, Dana; Dimarzio, Charles

2010-07-01

The extraction of 3-D morphological information about thick objects is explored in this work. We extract this information from 3-D differential interference contrast (DIC) images by applying a texture detection method. Texture extraction methods have been successfully used in different applications to study biological samples. A 3-D texture image is obtained by applying a local entropy-based texture extraction method. The use of this method to detect regions of blastocyst mouse embryos that are used in assisted reproduction techniques such as in vitro fertilization is presented as an example. Results demonstrate the potential of using texture detection methods to improve morphological analysis of thick samples, which is relevant to many biomedical and biological studies. Fluorescence and optical quadrature microscope phase images are used for validation.

3D Texture Features Mining for MRI Brain Tumor Identification

NASA Astrophysics Data System (ADS)

Rahim, Mohd Shafry Mohd; Saba, Tanzila; Nayer, Fatima; Syed, Afraz Zahra

2014-03-01

Medical image segmentation is a process to extract region of interest and to divide an image into its individual meaningful, homogeneous components. Actually, these components will have a strong relationship with the objects of interest in an image. For computer-aided diagnosis and therapy process, medical image segmentation is an initial mandatory step. Medical image segmentation is a sophisticated and challenging task because of the sophisticated nature of the medical images. Indeed, successful medical image analysis heavily dependent on the segmentation accuracy. Texture is one of the major features to identify region of interests in an image or to classify an object. 2D textures features yields poor classification results. Hence, this paper represents 3D features extraction using texture analysis and SVM as segmentation technique in the testing methodologies.

Texture Feature Extraction and Classification for Iris Diagnosis

NASA Astrophysics Data System (ADS)

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.

Micromechanical Characterization and Texture Analysis of Direct Cast Titanium Alloys Strips

NASA Technical Reports Server (NTRS)

2000-01-01

This research was conducted to determine a post-processing technique to optimize mechanical and material properties of a number of Titanium based alloys and aluminides processed via Melt Overflow Solidification Technique (MORST). This technique was developed by NASA for the development of thin sheet titanium and titanium aluminides used in high temperature applications. The materials investigated in this study included conventional titanium alloy strips and foils, Ti-1100, Ti-24Al-11Nb (Alpha-2), and Ti-48Al-2Ta (Gamma). The methodology used included micro-characterization, heat-treatment, mechanical processing and mechanical testing. Characterization techniques included optical, electron microscopy, and x-ray texture analysis. The processing included heat-treatment and mechanical deformation through cold rolling. The initial as-cast materials were evaluated for their microstructure and mechanical properties. Different heat-treatment and rolling steps were chosen to process these materials. The properties were evaluated further and a processing relationship was established in order to obtain an optimum processing condition. The results showed that the as-cast material exhibited a Widmanstatten (fine grain) microstructure that developed into a microstructure with larger grains through processing steps. The texture intensity showed little change for all processing performed in this investigation.

BCC skin cancer diagnosis based on texture analysis techniques

NASA Astrophysics Data System (ADS)

Chuang, Shao-Hui; Sun, Xiaoyan; Chang, Wen-Yu; Chen, Gwo-Shing; Huang, Adam; Li, Jiang; McKenzie, Frederic D.

2011-03-01

In this paper, we present a texture analysis based method for diagnosing the Basal Cell Carcinoma (BCC) skin cancer using optical images taken from the suspicious skin regions. We first extracted the Run Length Matrix and Haralick texture features from the images and used a feature selection algorithm to identify the most effective feature set for the diagnosis. We then utilized a Multi-Layer Perceptron (MLP) classifier to classify the images to BCC or normal cases. Experiments showed that detecting BCC cancer based on optical images is feasible. The best sensitivity and specificity we achieved on our data set were 94% and 95%, respectively.

Research for Key Techniques of Geophysical Recognition System of Hydrocarbon-induced Magnetic Anomalies Based on Hydrocarbon Seepage Theory

NASA Astrophysics Data System (ADS)

Zhang, L.; Hao, T.; Zhao, B.

2009-12-01

Hydrocarbon seepage effects can cause magnetic alteration zones in near surface, and the magnetic anomalies induced by the alteration zones can thus be used to locate oil-gas potential regions. In order to reduce the inaccuracy and multi-resolution of the hydrocarbon anomalies recognized only by magnetic data, and to meet the requirement of integrated management and sythetic analysis of multi-source geoscientfic data, it is necessary to construct a recognition system that integrates the functions of data management, real-time processing, synthetic evaluation, and geologic mapping. In this paper research for the key techniques of the system is discussed. Image processing methods can be applied to potential field images so as to make it easier for visual interpretation and geological understanding. For gravity or magnetic images, the anomalies with identical frequency-domain characteristics but different spatial distribution will reflect differently in texture and relevant textural statistics. Texture is a description of structural arrangements and spatial variation of a dataset or an image, and has been applied in many research fields. Textural analysis is a procedure that extracts textural features by image processing methods and thus obtains a quantitative or qualitative description of texture. When the two kinds of anomalies have no distinct difference in amplitude or overlap in frequency spectrum, they may be distinguishable due to their texture, which can be considered as textural contrast. Therefore, for the recognition system we propose a new “magnetic spots” recognition method based on image processing techniques. The method can be divided into 3 major steps: firstly, separate local anomalies caused by shallow, relatively small sources from the total magnetic field, and then pre-process the local magnetic anomaly data by image processing methods such that magnetic anomalies can be expressed as points, lines and polygons with spatial correlation, which includes histogram-equalization based image display, object recognition and extraction; then, mine the spatial characteristics and correlations of the magnetic anomalies using textural statistics and analysis, and study the features of known anomalous objects (closures, hydrocarbon-bearing structures, igneous rocks, etc.) in the same research area; finally, classify the anomalies, cluster them according to their similarity, and predict hydrocarbon induced “magnetic spots” combined with geologic, drilling and rock core data. The system uses the ArcGIS as the secondary development platform, inherits the basic functions of the ArcGIS, and develops two main sepecial functional modules, the module for conventional potential-field data processing methods and the module for feature extraction and enhancement based on image processing and analysis techniques. The system can be applied to realize the geophysical detection and recognition of near-surface hydrocarbon seepage anomalies, provide technical support for locating oil-gas potential regions, and promote geophysical data processing and interpretation to advance more efficiently.

Quantitative analysis on collagen of dermatofibrosarcoma protuberans skin by second harmonic generation microscopy.

PubMed

Wu, Shulian; Huang, Yudian; Li, Hui; Wang, Yunxia; Zhang, Xiaoman

2015-01-01

Dermatofibrosarcoma protuberans (DFSP) is a skin cancer usually mistaken as other benign tumors. Abnormal DFSP resection results in tumor recurrence. Quantitative characterization of collagen alteration on the skin tumor is essential for developing a diagnostic technique. In this study, second harmonic generation (SHG) microscopy was performed to obtain images of the human DFSP skin and normal skin. Subsequently, structure and texture analysis methods were applied to determine the differences in skin texture characteristics between the two skin types, and the link between collagen alteration and tumor was established. Results suggest that combining SHG microscopy and texture analysis methods is a feasible and effective method to describe the characteristics of skin tumor like DFSP. © Wiley Periodicals, Inc.

Rock classification based on resistivity patterns in electrical borehole wall images

NASA Astrophysics Data System (ADS)

Linek, Margarete; Jungmann, Matthias; Berlage, Thomas; Pechnig, Renate; Clauser, Christoph

2007-06-01

Electrical borehole wall images represent grey-level-coded micro-resistivity measurements at the borehole wall. Different scientific methods have been implemented to transform image data into quantitative log curves. We introduce a pattern recognition technique applying texture analysis, which uses second-order statistics based on studying the occurrence of pixel pairs. We calculate so-called Haralick texture features such as contrast, energy, entropy and homogeneity. The supervised classification method is used for assigning characteristic texture features to different rock classes and assessing the discriminative power of these image features. We use classifiers obtained from training intervals to characterize the entire image data set recovered in ODP hole 1203A. This yields a synthetic lithology profile based on computed texture data. We show that Haralick features accurately classify 89.9% of the training intervals. We obtained misclassification for vesicular basaltic rocks. Hence, further image analysis tools are used to improve the classification reliability. We decompose the 2D image signal by the application of wavelet transformation in order to enhance image objects horizontally, diagonally and vertically. The resulting filtered images are used for further texture analysis. This combined classification based on Haralick features and wavelet transformation improved our classification up to a level of 98%. The application of wavelet transformation increases the consistency between standard logging profiles and texture-derived lithology. Texture analysis of borehole wall images offers the potential to facilitate objective analysis of multiple boreholes with the same lithology.

In-situ laser ultrasonic measurement of the hcp to bcc transformation in commercially pure titanium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shinbine, A., E-mail: alyssa.shinbine@gmail.com; Garcin, T.; Sinclair, C.

2016-07-15

Using a novel in-situ laser ultrasonic technique, the evolution of longitudinal velocity was used to measure the α − β transformation during cyclic heating and cooling in commercially pure titanium. In order to quantify the transformation kinetics, it is shown that changes in texture can not be ignored. This is particularly important in the case of titanium where significant grain growth occurs in the β-phase leading to the ultrasonic wave sampling a decreasing number of grains on each thermal treatment cycle. Electron backscatter diffraction measurements made postmortem in the region where the ultrasonic pulse traveled were used to obtain anmore » estimate of such local texture and grain size changes. An analysis technique for including the anisotropy of wave velocity depending on local texture is presented and shown to give self consistent results for the transformation kinetics. - Highlights: • Laser ultrasound and EBSD interpret the hcp/bcc phase transformation in cp-Ti. • Grain growth and texture produced variation in velocity during similar treatments. • Texture was deconvoluted from phase addition to obtain transformation kinetics.« less

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Pneumothorax detection in chest radiographs using local and global texture signatures

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ahmed, M.M.Z., E-mail: mohamed_ahmed4@s-petrol.suez.edu.eg; Department of Metallurgical and Materials Engineering, Suez Canal University, Suez 43721; Wynne, B.P.

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.more » 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.« less

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

PubMed

Baldissin, Maurício Martins; Souza, Edna Marina de

2013-12-01

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.

Automatic small bowel tumor diagnosis by using multi-scale wavelet-based analysis in wireless capsule endoscopy images.

PubMed

Barbosa, Daniel C; Roupar, Dalila B; Ramos, Jaime C; Tavares, Adriano C; Lima, Carlos S

2012-01-11

Wireless capsule endoscopy has been introduced as an innovative, non-invasive diagnostic technique for evaluation of the gastrointestinal tract, reaching places where conventional endoscopy is unable to. However, the output of this technique is an 8 hours video, whose analysis by the expert physician is very time consuming. Thus, a computer assisted diagnosis tool to help the physicians to evaluate CE exams faster and more accurately is an important technical challenge and an excellent economical opportunity. The set of features proposed in this paper to code textural information is based on statistical modeling of second order textural measures extracted from co-occurrence matrices. To cope with both joint and marginal non-Gaussianity of second order textural measures, higher order moments are used. These statistical moments are taken from the two-dimensional color-scale feature space, where two different scales are considered. Second and higher order moments of textural measures are computed from the co-occurrence matrices computed from images synthesized by the inverse wavelet transform of the wavelet transform containing only the selected scales for the three color channels. The dimensionality of the data is reduced by using Principal Component Analysis. The proposed textural features are then used as the input of a classifier based on artificial neural networks. Classification performances of 93.1% specificity and 93.9% sensitivity are achieved on real data. These promising results open the path towards a deeper study regarding the applicability of this algorithm in computer aided diagnosis systems to assist physicians in their clinical practice.

Capturing the Surface Texture and Shape of Pollen: A Comparison of Microscopy Techniques

PubMed Central

Sivaguru, Mayandi; Mander, Luke; Fried, Glenn; Punyasena, Surangi W.

2012-01-01

Research on the comparative morphology of pollen grains depends crucially on the application of appropriate microscopy techniques. Information on the performance of microscopy techniques can be used to inform that choice. We compared the ability of several microscopy techniques to provide information on the shape and surface texture of three pollen types with differing morphologies. These techniques are: widefield, apotome, confocal and two-photon microscopy (reflected light techniques), and brightfield and differential interference contrast microscopy (DIC) (transmitted light techniques). We also provide a first view of pollen using super-resolution microscopy. The three pollen types used to contrast the performance of each technique are: Croton hirtus (Euphorbiaceae), Mabea occidentalis (Euphorbiaceae) and Agropyron repens (Poaceae). No single microscopy technique provided an adequate picture of both the shape and surface texture of any of the three pollen types investigated here. The wavelength of incident light, photon-collection ability of the optical technique, signal-to-noise ratio, and the thickness and light absorption characteristics of the exine profoundly affect the recovery of morphological information by a given optical microscopy technique. Reflected light techniques, particularly confocal and two-photon microscopy, best capture pollen shape but provide limited information on very fine surface texture. In contrast, transmitted light techniques, particularly differential interference contrast microscopy, can resolve very fine surface texture but provide limited information on shape. Texture comprising sculptural elements that are spaced near the diffraction limit of light (∼250 nm; NDL) presents an acute challenge to optical microscopy. Super-resolution structured illumination microscopy provides data on the NDL texture of A. repens that is more comparable to textural data from scanning electron microscopy than any other optical microscopy technique investigated here. Maximizing the recovery of morphological information from pollen grains should lead to more robust classifications, and an increase in the taxonomic precision with which ancient vegetation can be reconstructed. PMID:22720050

Proceedings of the Second Annual Symposium on Mathematical Pattern Recognition and Image Analysis Program

NASA Technical Reports Server (NTRS)

Guseman, L. F., Jr. (Principal Investigator)

1984-01-01

Several papers addressing image analysis and pattern recognition techniques for satellite imagery are presented. Texture classification, image rectification and registration, spatial parameter estimation, and surface fitting are discussed.

Power spectral ensity of markov texture fields

NASA Technical Reports Server (NTRS)

Shanmugan, K. S.; Holtzman, J. C.

1984-01-01

Texture is an important image characteristic. A variety of spatial domain techniques were proposed for extracting and utilizing textural features for segmenting and classifying images. for the most part, these spatial domain techniques are ad hos in nature. A markov random field model for image texture is discussed. A frequency domain description of image texture is derived in terms of the power spectral density. This model is used for designing optimum frequency domain filters for enhancing, restoring and segmenting images based on their textural properties.

Singular spectrum decomposition of Bouligand-Minkowski fractal descriptors: an application to the classification of texture Images

NASA Astrophysics Data System (ADS)

Florindo, João. Batista

2018-04-01

This work proposes the use of Singular Spectrum Analysis (SSA) for the classification of texture images, more specifically, to enhance the performance of the Bouligand-Minkowski fractal descriptors in this task. Fractal descriptors are known to be a powerful approach to model and particularly identify complex patterns in natural images. Nevertheless, the multiscale analysis involved in those descriptors makes them highly correlated. Although other attempts to address this point was proposed in the literature, none of them investigated the relation between the fractal correlation and the well-established analysis employed in time series. And SSA is one of the most powerful techniques for this purpose. The proposed method was employed for the classification of benchmark texture images and the results were compared with other state-of-the-art classifiers, confirming the potential of this analysis in image classification.

Advecting Procedural Textures for 2D Flow Animation

NASA Technical Reports Server (NTRS)

Kao, David; Pang, Alex; Moran, Pat (Technical Monitor)

2001-01-01

This paper proposes the use of specially generated 3D procedural textures for visualizing steady state 2D flow fields. We use the flow field to advect and animate the texture over time. However, using standard texture advection techniques and arbitrary textures will introduce some undesirable effects such as: (a) expanding texture from a critical source point, (b) streaking pattern from the boundary of the flowfield, (c) crowding of advected textures near an attracting spiral or sink, and (d) absent or lack of textures in some regions of the flow. This paper proposes a number of strategies to solve these problems. We demonstrate how the technique works using both synthetic data and computational fluid dynamics data.

X-ray diffraction analysis of residual stresses in textured ZnO thin films

NASA Astrophysics Data System (ADS)

Dobročka, E.; Novák, P.; Búc, D.; Harmatha, L.; Murín, J.

2017-02-01

Residual stresses are commonly generated in thin films during the deposition process and can influence the film properties. Among a number of techniques developed for stress analysis, X-ray diffraction methods, especially the grazing incidence set-up, are of special importance due to their capability to analyze the stresses in very thin layers as well as to investigate the depth variation of the stresses. In this contribution a method combining multiple {hkl} and multiple χ modes of X-ray diffraction stress analysis in grazing incidence set-up is used for the measurement of residual stress in strongly textured ZnO thin films. The method improves the precision of the stress evaluation in textured samples. Because the measurements are performed at very low incidence angles, the effect of refraction of X-rays on the measured stress is analyzed in details for the general case of non-coplanar geometry. It is shown that this effect cannot be neglected if the angle of incidence approaches the critical angle. The X-ray stress factors are calculated for hexagonal fiber-textured ZnO for the Reuss model of grain-interaction and the effect of texture on the stress factors is analyzed. The texture in the layer is modelled by Gaussian distribution function. Numerical results indicate that in the process of stress evaluation the Reuss model can be replaced by much simpler crystallite group method if the standard deviation of Gaussian describing the texture is less than 6°. The results can be adapted for fiber-textured films of various hexagonal materials.

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

NASA Astrophysics Data System (ADS)

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 < 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.

Use of feature extraction techniques for the texture and context information in ERTS imagery: Spectral and textural processing of ERTS imagery. [classification of Kansas land use

NASA Technical Reports Server (NTRS)

Haralick, R. H. (Principal Investigator); Bosley, R. J.

1974-01-01

The author has identified the following significant results. A procedure was developed to extract cross-band textural features from ERTS MSS imagery. Evolving from a single image texture extraction procedure which uses spatial dependence matrices to measure relative co-occurrence of nearest neighbor grey tones, the cross-band texture procedure uses the distribution of neighboring grey tone N-tuple differences to measure the spatial interrelationships, or co-occurrences, of the grey tone N-tuples present in a texture pattern. In both procedures, texture is characterized in such a way as to be invariant under linear grey tone transformations. However, the cross-band procedure complements the single image procedure by extracting texture information and spectral information contained in ERTS multi-images. Classification experiments show that when used alone, without spectral processing, the cross-band texture procedure extracts more information than the single image texture analysis. Results show an improvement in average correct classification from 86.2% to 88.8% for ERTS image no. 1021-16333 with the cross-band texture procedure. However, when used together with spectral features, the single image texture plus spectral features perform better than the cross-band texture plus spectral features, with an average correct classification of 93.8% and 91.6%, respectively.

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

PubMed Central

Li, Dali; Zou, Jiaojuan; Xie, Ruizhen; Wang, Zhihua; Tang, Bin

2018-01-01

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. PMID:29587358

Effect of fat types on the structural and textural properties of dough and semi-sweet biscuit.

PubMed

Mamat, Hasmadi; Hill, Sandra E

2014-09-01

Fat is an important ingredient in baking products and it plays many roles in providing desirable textural properties of baking products, particularly biscuit. In this study, the effect of fat types on dough rheological properties and quality of semi-sweet biscuit (rich tea type) were investigated using various techniques. Texture profile and extensibility analysis were used to study the dough rheology, while three-point bend test and scanning electron microscopy were used to analyse the textural characteristics of final product. TPA results showed that the type of fat significantly influenced dough textural properties. Biscuit produced with higher solid fat oil showed higher breaking force but this was not significantly different when evaluated by sensory panel. Scanning electron microscopy showed that biscuit produced with palm mid-fraction had an open internal microstructure and heterogeneous air cells as compared to other samples.

Texture feature extraction based on a uniformity estimation method for local brightness and structure in chest CT images.

PubMed

Peng, Shao-Hu; Kim, Deok-Hwan; Lee, Seok-Lyong; Lim, Myung-Kwan

2010-01-01

Texture feature is one of most important feature analysis methods in the computer-aided diagnosis (CAD) systems for disease diagnosis. In this paper, we propose a Uniformity Estimation Method (UEM) for local brightness and structure to detect the pathological change in the chest CT images. Based on the characteristics of the chest CT images, we extract texture features by proposing an extension of rotation invariant LBP (ELBP(riu4)) and the gradient orientation difference so as to represent a uniform pattern of the brightness and structure in the image. The utilization of the ELBP(riu4) and the gradient orientation difference allows us to extract rotation invariant texture features in multiple directions. Beyond this, we propose to employ the integral image technique to speed up the texture feature computation of the spatial gray level dependent method (SGLDM). Copyright © 2010 Elsevier Ltd. All rights reserved.

Characterization of Urban Landscape Using Super-Resolution UAS Data, Multiple Textural Scales and Data-Mining Techniques

NASA Astrophysics Data System (ADS)

Voss, M.; Blundell, B.

2015-12-01

Characterization of urban environments is a high priority for the U.S. Army as battlespaces have transitioned from the predominantly open spaces of the 20th century to urban areas where soldiers have reduced situational awareness due to the diversity and density of their surroundings. Creating high-resolution urban terrain geospatial information will improve mission planning and soldier effectiveness. In this effort, super-resolution true-color imagery was collected with an Altivan NOVA unmanned aerial system over the Muscatatuck Urban Training Center near Butlerville, Indiana on September 16, 2014. Multispectral texture analysis using different algorithms was conducted for urban surface characterization at a variety of scales. Training samples extracted from the true-color and texture images. These data were processed using a variety of meta-algorithms with a decision tree classifier to create a high-resolution urban features map. In addition to improving accuracy over traditional image classification methods, this technique allowed the determination of the most significant textural scales in creating urban terrain maps for tactical exploitation.

Statistical analysis of texture in trunk images for biometric identification of tree species.

PubMed

Bressane, Adriano; Roveda, José A F; Martins, Antônio C G

2015-04-01

The identification of tree species is a key step for sustainable management plans of forest resources, as well as for several other applications that are based on such surveys. However, the present available techniques are dependent on the presence of tree structures, such as flowers, fruits, and leaves, limiting the identification process to certain periods of the year. Therefore, this article introduces a study on the application of statistical parameters for texture classification of tree trunk images. For that, 540 samples from five Brazilian native deciduous species were acquired and measures of entropy, uniformity, smoothness, asymmetry (third moment), mean, and standard deviation were obtained from the presented textures. Using a decision tree, a biometric species identification system was constructed and resulted to a 0.84 average precision rate for species classification with 0.83accuracy and 0.79 agreement. Thus, it can be considered that the use of texture presented in trunk images can represent an important advance in tree identification, since the limitations of the current techniques can be overcome.

Computerized multiple image analysis on mammograms: performance improvement of nipple identification for registration of multiple views using texture convergence analyses

NASA Astrophysics Data System (ADS)

Zhou, Chuan; Chan, Heang-Ping; Sahiner, Berkman; Hadjiiski, Lubomir M.; Paramagul, Chintana

2004-05-01

Automated registration of multiple mammograms for CAD depends on accurate nipple identification. We developed two new image analysis techniques based on geometric and texture convergence analyses to improve the performance of our previously developed nipple identification method. A gradient-based algorithm is used to automatically track the breast boundary. The nipple search region along the boundary is then defined by geometric convergence analysis of the breast shape. Three nipple candidates are identified by detecting the changes along the gray level profiles inside and outside the boundary and the changes in the boundary direction. A texture orientation-field analysis method is developed to estimate the fourth nipple candidate based on the convergence of the tissue texture pattern towards the nipple. The final nipple location is determined from the four nipple candidates by a confidence analysis. Our training and test data sets consisted of 419 and 368 randomly selected mammograms, respectively. The nipple location identified on each image by an experienced radiologist was used as the ground truth. For 118 of the training and 70 of the test images, the radiologist could not positively identify the nipple, but provided an estimate of its location. These were referred to as invisible nipple images. In the training data set, 89.37% (269/301) of the visible nipples and 81.36% (96/118) of the invisible nipples could be detected within 1 cm of the truth. In the test data set, 92.28% (275/298) of the visible nipples and 67.14% (47/70) of the invisible nipples were identified within 1 cm of the truth. In comparison, our previous nipple identification method without using the two convergence analysis techniques detected 82.39% (248/301), 77.12% (91/118), 89.93% (268/298) and 54.29% (38/70) of the nipples within 1 cm of the truth for the visible and invisible nipples in the training and test sets, respectively. The results indicate that the nipple on mammograms can be detected accurately. This will be an important step towards automatic multiple image analysis for CAD techniques.

Remote sensing science for the Nineties; Proceedings of IGARSS '90 - 10th Annual International Geoscience and Remote Sensing Symposium, University of Maryland, College Park, May 20-24, 1990. Vols. 1, 2, & 3

NASA Technical Reports Server (NTRS)

1990-01-01

Various papers on remote sensing (RS) for the nineties are presented. The general topics addressed include: subsurface methods, radar scattering, oceanography, microwave models, atmospheric correction, passive microwave systems, RS in tropical forests, moderate resolution land analysis, SAR geometry and SNR improvement, image analysis, inversion and signal processing for geoscience, surface scattering, rain measurements, sensor calibration, wind measurements, terrestrial ecology, agriculture, geometric registration, subsurface sediment geology, radar modulation mechanisms, radar ocean scattering, SAR calibration, airborne radar systems, water vapor retrieval, forest ecosystem dynamics, land analysis, multisensor data fusion. Also considered are: geologic RS, RS sensor optical measurements, RS of snow, temperature retrieval, vegetation structure, global change, artificial intelligence, SAR processing techniques, geologic RS field experiment, stochastic modeling, topography and Digital Elevation model, SAR ocean waves, spaceborne lidar and optical, sea ice field measurements, millimeter waves, advanced spectroscopy, spatial analysis and data compression, SAR polarimetry techniques. Also discussed are: plant canopy modeling, optical RS techniques, optical and IR oceanography, soil moisture, sea ice back scattering, lightning cloud measurements, spatial textural analysis, SAR systems and techniques, active microwave sensing, lidar and optical, radar scatterometry, RS of estuaries, vegetation modeling, RS systems, EOS/SAR Alaska, applications for developing countries, SAR speckle and texture.

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

PubMed

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.

Relation between textured surface and diffuse reflectance of Cu films

NASA Astrophysics Data System (ADS)

Shukla, Gaurav; Angappane, S.

2018-04-01

Cu nanostructures namely chevron, slanted and vertical posts deposited on Si substrate by glancing angle deposition (GLAD) technique using DC magnetron sputtering are studied to understand the optical reflectance properties of various textures. The X-ray diffraction analysis confirmed the crystalline nature of the different structures of deposited Cu films. The FESEM images confirmed the formation of chevron, slanted and vertical posts. From the optical reflectance spectra, we found that the reflectance is more for chevron than vertical and slanted posts which have almost the same reflectance over the entire wavelength. The films with chevron texture would find various applications, like, light detector, light trapping, sensors etc.

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

NASA Astrophysics Data System (ADS)

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.

The Wear Behavior of Textured Steel Sliding against Polymers

PubMed Central

Wang, Meiling; Zhang, Changtao; Wang, Xiaolei

2017-01-01

Artificially fabricated surface textures can significantly improve the friction and wear resistance of a tribological contact. Recently, this surface texturing technique has been applied to polymer materials to improve their tribological performance. However, the wear behavior of textured tribo-pairs made of steel and polymer materials has been less thoroughly investigated and is not well understood; thus, it needs further research. The aim of this study is to investigate the wear properties of tribological contacts made of textured stainless steel against polymer surfaces. Three polymer materials were selected in this study, namely, ultrahigh molecular weight polyethylene (UHMWPE), polyoxymethylene (POM) and (polyetheretherketone) PEEK. Wear tests were operated through a ring-on-plane mode. The results revealed that the texture features and material properties affected the wear rates and friction coefficients of the textured tribo-pairs. In general, PEEK/textured steel achieved the lowest wear rate among the three types of tribo-pairs investigated. Energy dispersive x-ray spectroscopy (EDX) analysis revealed that the elements of C and O on the contacting counterfaces varied with texture features and indicated different wear behavior. Experimental and simulated results showed differences in the stress distribution around the dimple edge, which may influence wear performance. Wear debris with different surface morphologies were found for tribo-pairs with varying texture features. This study has increased the understanding of the wear behavior of tribo-pairs between textured stainless steel and polymer materials. PMID:28772688

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

PubMed Central

Qadri, Salman; Khan, Dost Muhammad; Ahmad, Farooq; Qadri, Syed Furqan; Babar, Masroor Ellahi; Shahid, Muhammad; Ul-Rehman, Muzammil; Razzaq, Abdul; Shah Muhammad, Syed; Fahad, Muhammad; Ahmad, Sarfraz; Pervez, Muhammad Tariq; Naveed, Nasir; Aslam, Naeem; Jamil, Mutiullah; Rehmani, Ejaz Ahmad; Ahmad, Nazir; Akhtar Khan, Naeem

2016-01-01

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. PMID:27376088

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

PubMed Central

Bayır, Şafak

2016-01-01

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. PMID:27110272

Histogram contrast analysis and the visual segregation of IID textures.

PubMed

Chubb, C; Econopouly, J; Landy, M S

1994-09-01

A new psychophysical methodology is introduced, histogram contrast analysis, that allows one to measure stimulus transformations, f, used by the visual system to draw distinctions between different image regions. The method involves the discrimination of images constructed by selecting texture micropatterns randomly and independently (across locations) on the basis of a given micropattern histogram. Different components of f are measured by use of different component functions to modulate the micropattern histogram until the resulting textures are discriminable. When no discrimination threshold can be obtained for a given modulating component function, a second titration technique may be used to measure the contribution of that component to f. The method includes several strong tests of its own assumptions. An example is given of the method applied to visual textures composed of small, uniform squares with randomly chosen gray levels. In particular, for a fixed mean gray level mu and a fixed gray-level variance sigma 2, histogram contrast analysis is used to establish that the class S of all textures composed of small squares with jointly independent, identically distributed gray levels with mean mu and variance sigma 2 is perceptually elementary in the following sense: there exists a single, real-valued function f S of gray level, such that two textures I and J in S are discriminable only if the average value of f S applied to the gray levels in I is significantly different from the average value of f S applied to the gray levels in J. Finally, histogram contrast analysis is used to obtain a seventh-order polynomial approximation of f S.

Topological image texture analysis for quality assessment

NASA Astrophysics Data System (ADS)

Asaad, Aras T.; Rashid, Rasber Dh.; Jassim, Sabah A.

2017-05-01

Image quality is a major factor influencing pattern recognition accuracy and help detect image tampering for forensics. We are concerned with investigating topological image texture analysis techniques to assess different type of degradation. We use Local Binary Pattern (LBP) as a texture feature descriptor. For any image construct simplicial complexes for selected groups of uniform LBP bins and calculate persistent homology invariants (e.g. number of connected components). We investigated image quality discriminating characteristics of these simplicial complexes by computing these models for a large dataset of face images that are affected by the presence of shadows as a result of variation in illumination conditions. Our tests demonstrate that for specific uniform LBP patterns, the number of connected component not only distinguish between different levels of shadow effects but also help detect the infected regions as well.

General Analytical Schemes for the Characterization of Pectin-Based Edible Gelled Systems

PubMed Central

Haghighi, Maryam; Rezaei, Karamatollah

2012-01-01

Pectin-based gelled systems have gained increasing attention for the design of newly developed food products. For this reason, the characterization of such formulas is a necessity in order to present scientific data and to introduce an appropriate finished product to the industry. Various analytical techniques are available for the evaluation of the systems formulated on the basis of pectin and the designed gel. In this paper, general analytical approaches for the characterization of pectin-based gelled systems were categorized into several subsections including physicochemical analysis, visual observation, textural/rheological measurement, microstructural image characterization, and psychorheological evaluation. Three-dimensional trials to assess correlations among microstructure, texture, and taste were also discussed. Practical examples of advanced objective techniques including experimental setups for small and large deformation rheological measurements and microstructural image analysis were presented in more details. PMID:22645484

Effect of Microstructure on the Mechanical Properties of Extruded Magnesium and a Magnesium Alloy

NASA Astrophysics Data System (ADS)

McGhee, Paul

The main objective of this research was to investigate the relationship between the fatigue behavior and crystallographic texture evolution of magnesium (Mg) alloys with a range of microalloying element content processed under various extrusion conditions. Several Mg alloys were processed under a range of extrusion temperatures, extrusion ratios, and alloying content and tested under monotonic and cyclic fatigue loading conditions: fully-reversed condition tested at strain amplitudes of 0.15% - 1.00% in strain-control mode. After fatigue testing, Mg microstructural analysis was performed using SEM, TEM, optical microscopy, and X-ray diffraction techniques. Microstructural observations revealed significant grain refinement through a combination of zirconium (Zr) addition and hot-extrusion, producing fine equiaxed grain structure with grain sizes ranging between 1-5 microm. Texture analysis and partial compression testing results showed that the initial texture of the extruded alloy gradually evolved upon compressive loading along the c-axes inducing extension twinning creating a strong basal texture along the extrusion direction. Full tensile and compression testing at room temperature showed that the combination of hot extrusion and Zr addition can further refine the grains of the Mg alloys microstructure and enhance the texture while simultaneously enhancing the mechanical properties.

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

PubMed

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 < 0.05) and had good interobserver agreement. An optimal feature subset including 11 features was further selected by the SVM-RFE method. The SVM-RFE+SMOTE classifier achieved the best performance in discriminating between small AMLwvf and RCC, with the highest accuracy, sensitivity, specificity and AUC of 93.9 %, 87.8 %, 100 % and 0.955, respectively. Machine learning analysis of CT texture features can facilitate the accurate differentiation of small AMLwvf from RCC. • 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.

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

PubMed

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

2017-07-11

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

RIS4E at Kilauea's December 1974 Flow: Lava Flow Texture LiDAR Signatures

NASA Astrophysics Data System (ADS)

Whelley, P.; Garry, W. B.; Scheidt, S. P.; Bleacher, J. E.; Hamilton, C.

2015-12-01

High-resolution point clouds and digital terrain models (DTMs) are used to investigate lava textures on the Big Island of Hawaii. Lava texture (e.g., ´áā and pāhoehoe) depends significantly on eruption conditions, and it is therefore instructive, if accurately determined. In places where field investigations are prohibitive (e.g., on other planets and remote regions of Earth) lava texture must be assessed from remote sensing data. A reliable method for doing so remains elusive. The December 1974 flow from Kilauea, in the Kau desert, presents an excellent field site to develop techniques for identifying lava texture. The eruption is young and the textures are well preserved. We present results comparing properties of lava textures observed in Terrestrial Laser Scanning (TLS) data. The authors collected the TLS data during May 2014 and June 2015 field seasons. Scans are a quantitative representation of what a geologist, or robotic system, sees "on the ground" and provides "ground truth" for airborne or orbital remote sensing analysis by enabling key parameters of lava morphology to be quantified. While individual scans have a heterogeneous point density, multiple scans are merged such that sub-cm lava textures can be quantified. Results indicate that TLS-derived surface roughness (i.e., de-trended RMS roughness) is useful for differentiating lava textures and assists volcanologic interpretations. As many lava types are quite rough, it is not simply roughness that is the most advantageous parameter for differentiating lava textures; rather co-occurrence patterns in surface roughness are used. Gradually forming textures (e.g., pāhoehoe) are elevated in statistics that measure smoothness (e.g., homogeneity) while lava with disrupted crusts (e.g., slabby and platy flow) have more random distributions of roughness (i.e., high entropy). A similar technique will be used to analyze high-resolution DTMs of martian lava flows using High Resolution Imaging Science Experiment DTMs. This work will lead to faster and more reliable volcanic mapping efforts for planetary exploration as well as terrestrial geohazards.

Segmentation of radiologic images with self-organizing maps: the segmentation problem transformed into a classification task

NASA Astrophysics Data System (ADS)

Pelikan, Erich; Vogelsang, Frank; Tolxdorff, Thomas

1996-04-01

The texture-based segmentation of x-ray images of focal bone lesions using topological maps is introduced. Texture characteristics are described by image-point correlation of feature images to feature vectors. For the segmentation, the topological map is labeled using an improved labeling strategy. Results of the technique are demonstrated on original and synthetic x-ray images and quantified with the aid of quality measures. In addition, a classifier-specific contribution analysis is applied for assessing the feature space.

Assessing clutter reduction in parallel coordinates using image processing techniques

NASA Astrophysics Data System (ADS)

Alhamaydh, Heba; Alzoubi, Hussein; Almasaeid, Hisham

2018-01-01

Information visualization has appeared as an important research field for multidimensional data and correlation analysis in recent years. Parallel coordinates (PCs) are one of the popular techniques to visual high-dimensional data. A problem with the PCs technique is that it suffers from crowding, a clutter which hides important data and obfuscates the information. Earlier research has been conducted to reduce clutter without loss in data content. We introduce the use of image processing techniques as an approach for assessing the performance of clutter reduction techniques in PC. We use histogram analysis as our first measure, where the mean feature of the color histograms of the possible alternative orderings of coordinates for the PC images is calculated and compared. The second measure is the extracted contrast feature from the texture of PC images based on gray-level co-occurrence matrices. The results show that the best PC image is the one that has the minimal mean value of the color histogram feature and the maximal contrast value of the texture feature. In addition to its simplicity, the proposed assessment method has the advantage of objectively assessing alternative ordering of PC visualization.

Cellular automata rule characterization and classification using texture descriptors

NASA Astrophysics Data System (ADS)

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-based characterization of subskin features by specified laser speckle effects at λ = 650 nm region for more accurate parametric 'skin age' modelling.

PubMed

Orun, A B; Seker, H; Uslan, V; Goodyer, E; Smith, G

2017-06-01

The textural structure of 'skin age'-related subskin components enables us to identify and analyse their unique characteristics, thus making substantial progress towards establishing an accurate skin age model. This is achieved by a two-stage process. First by the application of textural analysis using laser speckle imaging, which is sensitive to textural effects within the λ = 650 nm spectral band region. In the second stage, a Bayesian inference method is used to select attributes from which a predictive model is built. This technique enables us to contrast different skin age models, such as the laser speckle effect against the more widely used normal light (LED) imaging method, whereby it is shown that our laser speckle-based technique yields better results. The method introduced here is non-invasive, low cost and capable of operating in real time; having the potential to compete against high-cost instrumentation such as confocal microscopy or similar imaging devices used for skin age identification purposes. © 2016 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Automated texture-based identification of ovarian cancer in confocal microendoscope images

NASA Astrophysics Data System (ADS)

Srivastava, Saurabh; Rodriguez, Jeffrey J.; Rouse, Andrew R.; Brewer, Molly A.; Gmitro, Arthur F.

2005-03-01

The fluorescence confocal microendoscope provides high-resolution, in-vivo imaging of cellular pathology during optical biopsy. There are indications that the examination of human ovaries with this instrument has diagnostic implications for the early detection of ovarian cancer. The purpose of this study was to develop a computer-aided system to facilitate the identification of ovarian cancer from digital images captured with the confocal microendoscope system. To achieve this goal, we modeled the cellular-level structure present in these images as texture and extracted features based on first-order statistics, spatial gray-level dependence matrices, and spatial-frequency content. Selection of the best features for classification was performed using traditional feature selection techniques including stepwise discriminant analysis, forward sequential search, a non-parametric method, principal component analysis, and a heuristic technique that combines the results of these methods. The best set of features selected was used for classification, and performance of various machine classifiers was compared by analyzing the areas under their receiver operating characteristic curves. The results show that it is possible to automatically identify patients with ovarian cancer based on texture features extracted from confocal microendoscope images and that the machine performance is superior to that of the human observer.

Noninvasive Classification of Hepatic Fibrosis Based on Texture Parameters From Double Contrast-Enhanced Magnetic Resonance Images

PubMed Central

Bahl, Gautam; Cruite, Irene; Wolfson, Tanya; Gamst, Anthony C.; Collins, Julie M.; Chavez, Alyssa D.; Barakat, Fatma; Hassanein, Tarek; Sirlin, Claude B.

2016-01-01

Purpose To demonstrate a proof of concept that quantitative texture feature analysis of double contrast-enhanced magnetic resonance imaging (MRI) can classify fibrosis noninvasively, using histology as a reference standard. Materials and Methods A Health Insurance Portability and Accountability Act (HIPAA)-compliant Institutional Review Board (IRB)-approved retrospective study of 68 patients with diffuse liver disease was performed at a tertiary liver center. All patients underwent double contrast-enhanced MRI, with histopathology-based staging of fibrosis obtained within 12 months of imaging. The MaZda software program was used to compute 279 texture parameters for each image. A statistical regularization technique, generalized linear model (GLM)-path, was used to develop a model based on texture features for dichotomous classification of fibrosis category (F ≤2 vs. F ≥3) of the 68 patients, with histology as the reference standard. The model's performance was assessed and cross-validated. There was no additional validation performed on an independent cohort. Results Cross-validated sensitivity, specificity, and total accuracy of the texture feature model in classifying fibrosis were 91.9%, 83.9%, and 88.2%, respectively. Conclusion This study shows proof of concept that accurate, noninvasive classification of liver fibrosis is possible by applying quantitative texture analysis to double contrast-enhanced MRI. Further studies are needed in independent cohorts of subjects. PMID:22851409

A novel approach to assess temporal sensory perception of muscle foods: application of a time-intensity technique to diverse Iberian meat products.

PubMed

Lorido, Laura; Estévez, Mario; Ventanas, Sonia

2014-01-01

Although dynamic sensory techniques such as time-intensity (TI) have been applied to certain meat products, existing knowledge regarding the temporal sensory perception of muscle foods is still limited. The objective of the present study was to apply TI to the flavour and texture perception of three different Iberian meat products: liver pâté, dry-cured sausages ("salchichon") and dry-cured loin. Moreover, the advantages of using dynamic versus static sensory techniques were explored by subjecting the same products to a quantitative descriptive analysis (QDA). TI was a suitable technique to assess the impact of composition and structure of the three meat products on flavour and texture perception from a dynamic perspective. TI parameters extracted from the TI-curves and related to temporal perception enabled the detection of clear differences in sensory temporal perception between the meat products and provided additional insight on sensory perception compared to the conventional static sensory technique (QDA). © 2013.

Tissue classification for laparoscopic image understanding based on multispectral texture analysis

NASA Astrophysics Data System (ADS)

Zhang, Yan; Wirkert, Sebastian J.; Iszatt, Justin; Kenngott, Hannes; Wagner, Martin; Mayer, Benjamin; Stock, Christian; Clancy, Neil T.; Elson, Daniel S.; Maier-Hein, Lena

2016-03-01

Intra-operative tissue classification is one of the prerequisites for providing context-aware visualization in computer-assisted minimally invasive surgeries. As many anatomical structures are difficult to differentiate in conventional RGB medical images, we propose a classification method based on multispectral image patches. In a comprehensive ex vivo study we show (1) that multispectral imaging data is superior to RGB data for organ tissue classification when used in conjunction with widely applied feature descriptors and (2) that combining the tissue texture with the reflectance spectrum improves the classification performance. Multispectral tissue analysis could thus evolve as a key enabling technique in computer-assisted laparoscopy.

Automatic brain tumor detection in MRI: methodology and statistical validation

NASA Astrophysics Data System (ADS)

Iftekharuddin, Khan M.; Islam, Mohammad A.; Shaik, Jahangheer; Parra, Carlos; Ogg, Robert

2005-04-01

Automated brain tumor segmentation and detection are immensely important in medical diagnostics because it provides information associated to anatomical structures as well as potential abnormal tissue necessary to delineate appropriate surgical planning. In this work, we propose a novel automated brain tumor segmentation technique based on multiresolution texture information that combines fractal Brownian motion (fBm) and wavelet multiresolution analysis. Our wavelet-fractal technique combines the excellent multiresolution localization property of wavelets to texture extraction of fractal. We prove the efficacy of our technique by successfully segmenting pediatric brain MR images (MRIs) from St. Jude Children"s Research Hospital. We use self-organizing map (SOM) as our clustering tool wherein we exploit both pixel intensity and multiresolution texture features to obtain segmented tumor. Our test results show that our technique successfully segments abnormal brain tissues in a set of T1 images. In the next step, we design a classifier using Feed-Forward (FF) neural network to statistically validate the presence of tumor in MRI using both the multiresolution texture and the pixel intensity features. We estimate the corresponding receiver operating curve (ROC) based on the findings of true positive fractions and false positive fractions estimated from our classifier at different threshold values. An ROC, which can be considered as a gold standard to prove the competence of a classifier, is obtained to ascertain the sensitivity and specificity of our classifier. We observe that at threshold 0.4 we achieve true positive value of 1.0 (100%) sacrificing only 0.16 (16%) false positive value for the set of 50 T1 MRI analyzed in this experiment.

The scale invariant generator technique for quantifying anisotropic scale invariance

NASA Astrophysics Data System (ADS)

Lewis, G. M.; Lovejoy, S.; Schertzer, D.; Pecknold, S.

1999-11-01

Scale invariance is rapidly becoming a new paradigm for geophysics. However, little attention has been paid to the anisotropy that is invariably present in geophysical fields in the form of differential stratification and rotation, texture and morphology. In order to account for scaling anisotropy, the formalism of generalized scale invariance (GSI) was developed. Until now there has existed only a single fairly ad hoc GSI analysis technique valid for studying differential rotation. In this paper, we use a two-dimensional representation of the linear approximation to generalized scale invariance, to obtain a much improved technique for quantifying anisotropic scale invariance called the scale invariant generator technique (SIG). The accuracy of the technique is tested using anisotropic multifractal simulations and error estimates are provided for the geophysically relevant range of parameters. It is found that the technique yields reasonable estimates for simulations with a diversity of anisotropic and statistical characteristics. The scale invariant generator technique can profitably be applied to the scale invariant study of vertical/horizontal and space/time cross-sections of geophysical fields as well as to the study of the texture/morphology of fields.

Detection of pigment network in dermatoscopy images using texture analysis

PubMed Central

Anantha, Murali; Moss, Randy H.; Stoecker, William V.

2011-01-01

Dermatoscopy, also known as dermoscopy or epiluminescence microscopy (ELM), is a non-invasive, in vivo technique, which permits visualization of features of pigmented melanocytic neoplasms that are not discernable by examination with the naked eye. ELM offers a completely new range of visual features. One such prominent feature is the pigment network. Two texture-based algorithms are developed for the detection of pigment network. These methods are applicable to various texture patterns in dermatoscopy images, including patterns that lack fine lines such as cobblestone, follicular, or thickened network patterns. Two texture algorithms, Laws energy masks and the neighborhood gray-level dependence matrix (NGLDM) large number emphasis, were optimized on a set of 155 dermatoscopy images and compared. Results suggest superiority of Laws energy masks for pigment network detection in dermatoscopy images. For both methods, a texel width of 10 pixels or approximately 0.22 mm is found for dermatoscopy images. PMID:15249068

Uncertainty in Pedotransfer Functions from Soil Survey Data

NASA Astrophysics Data System (ADS)

Pachepsky, Y. A.; Rawls, W. J.

2002-05-01

Pedotransfer functions (PTFs) are empirical relationships between hard-to-get soil parameters, i.e. hydraulic properties, and more easily obtainable basic soil properties, such as texture. Use of PTFs in large-scale projects and pilot studies relies on data of soil survey that provides soil basic data as a categorical information. Unlike numerical variables, categorical data cannot be directly used in statistical regressions or neural networks to develop PTFs. Objectives of this work were (a) to find and test techniques to develop PTFs for soil water retention and saturated hydraulic conductivity with soil categorical data as inputs, (b) to evaluate sources of uncertainty in results of such PTFs and to research opportunities of mitigating the uncertainty. We used a subset of about 12,000 samples from the US National Soil characterization database to estimate water retention, and the data set for circa 1000 hydraulic conductivity measurements done in the US. Regression trees and polynomial neural networks based on dummy coding were the techniques tried for the PTF development. The jackknife validation was used to prevent the over-parameterization. Both techniques were equally efficient in developing PTFs, but regression trees gave much more transparent results. Textural class was the leading predictor with RMSE values of about 6.5 and 4.1 vol.% for water retention at -33 and -1500 kPa, respectively. The RMSE values decreased 10% when the laboratory textural analysis was used to establish the textural class. Textural class in the field was determined correctly only in 41% of all cases. To mitigate this source of error, we added slopes, position on the slope classes, and land surface shape classes to the list of PTF inputs. Regression trees generated topotextural groups that encompassed several textural classes. Using topographic variables and soil horizon appeared to be the way to make up for errors made in field determination of texture. Adding field descriptors of soil structure to the field-determined textural class gave similar results. No large improvement was achieved probably because textural class, topographic descriptors and structure descriptors were correlated predictors in many cases. Both median values and uncertainty of the saturated hydraulic conductivity had a power-law decrease as clay content increased. Defining two classes of bulk density helped to estimate hydraulic conductivity within textural classes. We conclude that categorical field soil survey data can be used in PTF-based estimating soil water retention and saturated hydraulic conductivity with quantified uncertainty

Automated retrieval of forest structure variables based on multi-scale texture analysis of VHR satellite imagery

NASA Astrophysics Data System (ADS)

Beguet, Benoit; Guyon, Dominique; Boukir, Samia; Chehata, Nesrine

2014-10-01

The main goal of this study is to design a method to describe the structure of forest stands from Very High Resolution satellite imagery, relying on some typical variables such as crown diameter, tree height, trunk diameter, tree density and tree spacing. The emphasis is placed on the automatization of the process of identification of the most relevant image features for the forest structure retrieval task, exploiting both spectral and spatial information. Our approach is based on linear regressions between the forest structure variables to be estimated and various spectral and Haralick's texture features. The main drawback of this well-known texture representation is the underlying parameters which are extremely difficult to set due to the spatial complexity of the forest structure. To tackle this major issue, an automated feature selection process is proposed which is based on statistical modeling, exploring a wide range of parameter values. It provides texture measures of diverse spatial parameters hence implicitly inducing a multi-scale texture analysis. A new feature selection technique, we called Random PRiF, is proposed. It relies on random sampling in feature space, carefully addresses the multicollinearity issue in multiple-linear regression while ensuring accurate prediction of forest variables. Our automated forest variable estimation scheme was tested on Quickbird and Pléiades panchromatic and multispectral images, acquired at different periods on the maritime pine stands of two sites in South-Western France. It outperforms two well-established variable subset selection techniques. It has been successfully applied to identify the best texture features in modeling the five considered forest structure variables. The RMSE of all predicted forest variables is improved by combining multispectral and panchromatic texture features, with various parameterizations, highlighting the potential of a multi-resolution approach for retrieving forest structure variables from VHR satellite images. Thus an average prediction error of ˜ 1.1 m is expected on crown diameter, ˜ 0.9 m on tree spacing, ˜ 3 m on height and ˜ 0.06 m on diameter at breast height.

Hyperspectral remote sensing exploration of carbonatite - an example from Epembe, Kunene region, Namibia

NASA Astrophysics Data System (ADS)

Zimmermann, Robert; Brandmeier, Melanie; Andreani, Louis; Gloaguen, Richard

2015-04-01

Remote sensing data can provide valuable information about ore deposits and their alteration zones at surface level. High spectral and spatial resolution of the data is essential for detailed mapping of mineral abundances and related structures. Carbonatites are well known for hosting economic enrichments in REE, Ta, Nb and P (Jones et al. 2013). These make them a preferential target for exploration for those critical elements. In this study we show how combining geomorphic, textural and spectral data improves classification result. We selected a site with a well-known occurrence in northern Namibia: the Epembe dyke. For analysis LANDSAT 8, SRTM and airborne hyperspectral (HyMap) data were chosen. The overlapping data allows a multi-scale and multi-resolution approach. Results from data analysis were validated during fieldwork in 2014. Data was corrected for atmospherical and geometrical effects. Image classification, mineral mapping and tectonic geomorphology allow a refinement of the geological map by lithological mapping in a second step. Detailed mineral abundance maps were computed using spectral unmixing techniques. These techniques are well suited to map abundances of carbonate minerals, but not to discriminate the carbonatite itself from surrounding rocks with similar spectral signatures. Thus, geometric indices were calculated using tectonic geomorphology and textures. For this purpose the TecDEM-toolbox (SHAHZAD & GLOAGUEN 2011) was applied to the SRTM-data for geomorphic analysis. Textural indices (e.g. uniformity, entropy, angular second moment) were derived from HyMap and SRTM by a grey-level co-occurrence matrix (CLAUSI 2002). The carbonatite in the study area is ridge-forming and shows a narrow linear feature in the textural bands. Spectral and geometric information were combined using kohonen Self-Organizing Maps (SOM) for unsupervised clustering. The resulting class spectra were visually compared and interpreted. Classes with similar signatures were merged according to geological context. The major conclusions are: 1. Carbonate minerals can be mapped using spectral unmixing techniques. 2. Carbonatites are associated with specific geometric pattern 3. The combination of spectral and geometric information improves classification result and reduces misclassification. References Clausi, D. A. (2002): An analysis of co-occurrence texture statistics as a function of grey-level quantization. - Canadian Journal of Remote Sensing, 28 (1), 45-62 Jones, A. P., Genge, M. and Carmody, L (2013): Carbonate Melts and Carbonatites. - Reviews in Mineralogy & Geochemistry, 75, 289-322 Shahzad, F. & Gloaguen, R. (2011): TecDEM: A MATLAB based toolbox for tectonic geomorphology, Part 2: Surface dynamics and basin analysis. - Computers and Geosciences, 37 (2), 261-271

Relevance of 2D radiographic texture analysis for the assessment of 3D bone micro-architecture

DOE Office of Scientific and Technical Information (OSTI.GOV)

Apostol, Lian; Boudousq, Vincent; Basset, Oliver

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 regard to fracture risk. 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. Thirty-three calcaneus and femoral neck bone samples including the cortical shells (diameter: 14 mm, height: 30-40 mm) were imaged using 3D-synchrotron x-ray micro-CT at the ESRF. The 3D reconstructed images with a cubic voxel size of 15 {mu}m were further usedmore » for two purposes: (1) quantification of three-dimensional trabecular bone micro-architecture (2) simulation of realistic x-ray radiographs under different acquisition conditions. The simulated x-ray radiographs were then analyzed using a large variety of texture analysis methods (co-occurrence, spectral density, fractal, morphology, etc.). The range of micro-architecture parameters was in agreement with previous studies and rather large, suggesting that the population was representative. More than 350 texture parameters were tested. A small number of them were selected based on their correlation to micro-architectural morphometric parameters. Using this subset of texture parameters, multiple regression allowed one to predict up to 93% of the variance of micro-architecture parameters using three texture features. 2D texture features predicting 3D micro-architecture parameters other than BV/TV were identified. The methodology proposed for evaluating the relationships between 3D micro-architecture and 2D texture parameters may also be used for optimizing the conditions for radiographic imaging. Further work will include the application of the method to physical radiographs. In the future, this approach could be used in combination with DXA to refine osteoporosis diagnosis.« less

A comparative study of new and current methods for dental micro-CT image denoising

PubMed Central

Lashgari, Mojtaba; Qin, Jie; Swain, Michael

2016-01-01

Objectives: The aim of the current study was to evaluate the application of two advanced noise-reduction algorithms for dental micro-CT images and to implement a comparative analysis of the performance of new and current denoising algorithms. Methods: Denoising was performed using gaussian and median filters as the current filtering approaches and the block-matching and three-dimensional (BM3D) method and total variation method as the proposed new filtering techniques. The performance of the denoising methods was evaluated quantitatively using contrast-to-noise ratio (CNR), edge preserving index (EPI) and blurring indexes, as well as qualitatively using the double-stimulus continuous quality scale procedure. Results: The BM3D method had the best performance with regard to preservation of fine textural features (CNREdge), non-blurring of the whole image (blurring index), the clinical visual score in images with very fine features and the overall visual score for all types of images. On the other hand, the total variation method provided the best results with regard to smoothing of images in texture-free areas (CNRTex-free) and in preserving the edges and borders of image features (EPI). Conclusions: The BM3D method is the most reliable technique for denoising dental micro-CT images with very fine textural details, such as shallow enamel lesions, in which the preservation of the texture and fine features is of the greatest importance. On the other hand, the total variation method is the technique of choice for denoising images without very fine textural details in which the clinician or researcher is interested mainly in anatomical features and structural measurements. PMID:26764583

Skin image retrieval using Gabor wavelet texture feature.

PubMed

Ou, X; Pan, W; Zhang, X; Xiao, P

2016-12-01

Skin imaging plays a key role in many clinical studies. We have used many skin imaging techniques, including the recently developed capacitive contact skin imaging based on fingerprint sensors. The aim of this study was to develop an effective skin image retrieval technique using Gabor wavelet transform, which can be used on different types of skin images, but with a special focus on skin capacitive contact images. Content-based image retrieval (CBIR) is a useful technology to retrieve stored images from database by supplying query images. In a typical CBIR, images are retrieved based on colour, shape, texture, etc. In this study, texture feature is used for retrieving skin images, and Gabor wavelet transform is used for texture feature description and extraction. The results show that the Gabor wavelet texture features can work efficiently on different types of skin images. Although Gabor wavelet transform is slower compared with other image retrieval techniques, such as principal component analysis (PCA) and grey-level co-occurrence matrix (GLCM), Gabor wavelet transform is the best for retrieving skin capacitive contact images and facial images with different orientations. Gabor wavelet transform can also work well on facial images with different expressions and skin cancer/disease images. We have developed an effective skin image retrieval method based on Gabor wavelet transform, that it is useful for retrieving different types of images, namely digital colour face images, digital colour skin cancer and skin disease images, and particularly greyscale skin capacitive contact images. Gabor wavelet transform can also be potentially useful for face recognition (with different orientation and expressions) and skin cancer/disease diagnosis. © 2016 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

Real-time Supervised Detection of Pink Areas in Dermoscopic Images of Melanoma: Importance of Color Shades, Texture and Location

PubMed Central

Kaur, Ravneet; Albano, Peter P.; Cole, Justin G.; Hagerty, Jason; LeAnder, Robert W.; Moss, Randy H.; Stoecker, William V.

2015-01-01

Background/Purpose Early detection of malignant melanoma is an important public health challenge. In the USA, dermatologists are seeing more melanomas at an early stage, before classic melanoma features have become apparent. Pink color is a feature of these early melanomas. If rapid and accurate automatic detection of pink color in these melanomas could be accomplished, there could be significant public health benefits. Methods Detection of three shades of pink (light pink, dark pink, and orange pink) was accomplished using color analysis techniques in five color planes (red, green, blue, hue and saturation). Color shade analysis was performed using a logistic regression model trained with an image set of 60 dermoscopic images of melanoma that contained pink areas. Detected pink shade areas were further analyzed with regard to the location within the lesion, average color parameters over the detected areas, and histogram texture features. Results Logistic regression analysis of a separate set of 128 melanomas and 128 benign images resulted in up to 87.9% accuracy in discriminating melanoma from benign lesions measured using area under the receiver operating characteristic curve. The accuracy in this model decreased when parameters for individual shades, texture, or shade location within the lesion were omitted. Conclusion Texture, color, and lesion location analysis applied to multiple shades of pink can assist in melanoma detection. When any of these three details: color location, shade analysis, or texture analysis were omitted from the model, accuracy in separating melanoma from benign lesions was lowered. Separation of colors into shades and further details that enhance the characterization of these color shades are needed for optimal discrimination of melanoma from benign lesions. PMID:25809473

Real-time supervised detection of pink areas in dermoscopic images of melanoma: importance of color shades, texture and location.

PubMed

Kaur, R; Albano, P P; Cole, J G; Hagerty, J; LeAnder, R W; Moss, R H; Stoecker, W V

2015-11-01

Early detection of malignant melanoma is an important public health challenge. In the USA, dermatologists are seeing more melanomas at an early stage, before classic melanoma features have become apparent. Pink color is a feature of these early melanomas. If rapid and accurate automatic detection of pink color in these melanomas could be accomplished, there could be significant public health benefits. Detection of three shades of pink (light pink, dark pink, and orange pink) was accomplished using color analysis techniques in five color planes (red, green, blue, hue, and saturation). Color shade analysis was performed using a logistic regression model trained with an image set of 60 dermoscopic images of melanoma that contained pink areas. Detected pink shade areas were further analyzed with regard to the location within the lesion, average color parameters over the detected areas, and histogram texture features. Logistic regression analysis of a separate set of 128 melanomas and 128 benign images resulted in up to 87.9% accuracy in discriminating melanoma from benign lesions measured using area under the receiver operating characteristic curve. The accuracy in this model decreased when parameters for individual shades, texture, or shade location within the lesion were omitted. Texture, color, and lesion location analysis applied to multiple shades of pink can assist in melanoma detection. When any of these three details: color location, shade analysis, or texture analysis were omitted from the model, accuracy in separating melanoma from benign lesions was lowered. Separation of colors into shades and further details that enhance the characterization of these color shades are needed for optimal discrimination of melanoma from benign lesions. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Super-hydrophobic, highly adhesive, polydimethylsiloxane (PDMS) surfaces.

PubMed

Stanton, Morgan M; Ducker, Robert E; MacDonald, John C; Lambert, Christopher R; McGimpsey, W Grant

2012-02-01

Super-hydrophobic surfaces have been fabricated by casting polydimethylsiloxane (PDMS) on a textured substrate of known surface topography, and were characterized using contact angle, atomic force microscopy, surface free energy calculations, and adhesion measurements. The resulting PDMS has a micro-textured surface with a static contact angle of 153.5° and a hysteresis of 27° when using de-ionized water. Unlike many super-hydrophobic materials, the textured PDMS is highly adhesive, allowing water drops as large as 25.0 μL to be inverted. This high adhesion, super-hydrophobic behavior is an illustration of the "petal effect". This rapid, reproducible technique has promising applications in transport and analysis of microvolume samples. Copyright © 2011 Elsevier Inc. All rights reserved.

Assessment of visual landscape quality using IKONOS imagery.

PubMed

Ozkan, Ulas Yunus

2014-07-01

The assessment of visual landscape quality is of importance to the management of urban woodlands. Satellite remote sensing may be used for this purpose as a substitute for traditional survey techniques that are both labour-intensive and time-consuming. This study examines the association between the quality of the perceived visual landscape in urban woodlands and texture measures extracted from IKONOS satellite data, which features 4-m spatial resolution and four spectral bands. The study was conducted in the woodlands of Istanbul (the most important element of urban mosaic) lying along both shores of the Bosporus Strait. The visual quality assessment applied in this study is based on the perceptual approach and was performed via a survey of expressed preferences. For this purpose, representative photographs of real scenery were used to elicit observers' preferences. A slide show comprising 33 images was presented to a group of 153 volunteers (all undergraduate students), and they were asked to rate the visual quality of each on a 10-point scale (1 for very low visual quality, 10 for very high). Average visual quality scores were calculated for landscape. Texture measures were acquired using the two methods: pixel-based and object-based. Pixel-based texture measures were extracted from the first principle component (PC1) image. Object-based texture measures were extracted by using the original four bands. The association between image texture measures and perceived visual landscape quality was tested via Pearson's correlation coefficient. The analysis found a strong linear association between image texture measures and visual quality. The highest correlation coefficient was calculated between standard deviation of gray levels (SDGL) (one of the pixel-based texture measures) and visual quality (r = 0.82, P < 0.05). The results showed that perceived visual quality of urban woodland landscapes can be estimated by using texture measures extracted from satellite data in combination with appropriate modelling techniques.

Time-series analysis of lung texture on bone-suppressed dynamic chest radiograph for the evaluation of pulmonary function: a preliminary study

NASA Astrophysics Data System (ADS)

Tanaka, Rie; Matsuda, Hiroaki; Sanada, Shigeru

2017-03-01

The density of lung tissue changes as demonstrated on imagery is dependent on the relative increases and decreases in the volume of air and lung vessels per unit volume of lung. Therefore, a time-series analysis of lung texture can be used to evaluate relative pulmonary function. This study was performed to assess a time-series analysis of lung texture on dynamic chest radiographs during respiration, and to demonstrate its usefulness in the diagnosis of pulmonary impairments. Sequential chest radiographs of 30 patients were obtained using a dynamic flat-panel detector (FPD; 100 kV, 0.2 mAs/pulse, 15 frames/s, SID = 2.0 m; Prototype, Konica Minolta). Imaging was performed during respiration, and 210 images were obtained over 14 seconds. Commercial bone suppression image-processing software (Clear Read Bone Suppression; Riverain Technologies, Miamisburg, Ohio, USA) was applied to the sequential chest radiographs to create corresponding bone suppression images. Average pixel values, standard deviation (SD), kurtosis, and skewness were calculated based on a density histogram analysis in lung regions. Regions of interest (ROIs) were manually located in the lungs, and the same ROIs were traced by the template matching technique during respiration. Average pixel value effectively differentiated regions with ventilatory defects and normal lung tissue. The average pixel values in normal areas changed dynamically in synchronization with the respiratory phase, whereas those in regions of ventilatory defects indicated reduced variations in pixel value. There were no significant differences between ventilatory defects and normal lung tissue in the other parameters. We confirmed that time-series analysis of lung texture was useful for the evaluation of pulmonary function in dynamic chest radiography during respiration. Pulmonary impairments were detected as reduced changes in pixel value. This technique is a simple, cost-effective diagnostic tool for the evaluation of regional pulmonary function.

ComDim for explorative multi-block data analysis of Cantal-type cheeses: Effects of salts, gentle heating and ripening.

PubMed

Loudiyi, M; Rutledge, D N; Aït-Kaddour, A

2018-10-30

Common Dimension (ComDim) chemometrics method for multi-block data analysis was employed to evaluate the impact of different added salts and ripening times on physicochemical, color, dynamic low amplitude oscillatory rheology, texture profile, and molecular structure (fluorescence and MIR spectroscopies) of five Cantal-type cheeses. Firstly, Independent Components Analysis (ICA) was applied separately on fluorescence and MIR spectra in order to extract the relevant signal source and the associated proportions related to molecular structure characteristics. ComDim was then applied on the 31 data tables corresponding to the proportion of ICA signals obtained for spectral methods and the global analysis of cheeses by the other techniques. The ComDim results indicated that generally cheeses made with 50% NaCl or with 75:25% NaCl/KCl exhibit the equivalent characteristics in structural, textural, meltability and color properties. The proposed methodology demonstrates the applicability of ComDim for the characterization of samples when different techniques describe the same samples. Copyright © 2018 Elsevier Ltd. All rights reserved.

On Animating 2D Velocity Fields

NASA Technical Reports Server (NTRS)

Kao, David; Pang, Alex; Yan, Jerry (Technical Monitor)

2001-01-01

A velocity field, even one that represents a steady state flow, implies a dynamical system. Animated velocity fields is an important tool in understanding such complex phenomena. This paper looks at a number of techniques that animate velocity fields and propose two new alternatives. These are texture advection and streamline cycling. The common theme among these techniques is the use of advection on some texture to generate a realistic animation of the velocity field. Texture synthesis and selection for these methods are presented. Strengths and weaknesses of the techniques are also discussed in conjunctions with several examples.

On Animating 2D Velocity Fields

NASA Technical Reports Server (NTRS)

Kao, David; Pang, Alex

2000-01-01

A velocity field. even one that represents a steady state flow implies a dynamical system. Animated velocity fields is an important tool in understanding such complex phenomena. This paper looks at a number of techniques that animate velocity fields and propose two new alternatives, These are texture advection and streamline cycling. The common theme among these techniques is the use of advection on some texture to generate a realistic animation of the velocity field. Texture synthesis and selection for these methods are presented. Strengths and weaknesses of the techniques are also discussed in conjunction with several examples.

Investigation of the microstructure and mineralogical composition of urinary calculi fragments by synchrotron radiation X-ray microtomography: a feasibility study.

PubMed

Kaiser, Jozef; Holá, Markéta; Galiová, Michaela; Novotný, Karel; Kanický, Viktor; Martinec, Petr; Sčučka, Jiří; Brun, Francesco; Sodini, Nicola; Tromba, Giuliana; Mancini, Lucia; Kořistková, Tamara

2011-08-01

The outcomes from the feasibility study on utilization of synchrotron radiation X-ray microtomography (SR-μCT) to investigate the texture and the quantitative mineralogical composition of selected calcium oxalate-based urinary calculi fragments are presented. The comparison of the results obtained by SR-μCT analysis with those derived from current standard analytical approaches is provided. SR-μCT is proved as a potential effective technique for determination of texture, 3D microstructure, and composition of kidney stones.

Defect Detection in Textures through the Use of Entropy as a Means for Automatically Selecting the Wavelet Decomposition Level.

PubMed

Navarro, Pedro J; Fernández-Isla, Carlos; Alcover, Pedro María; Suardíaz, Juan

2016-07-27

This paper presents a robust method for defect detection in textures, entropy-based automatic selection of the wavelet decomposition level (EADL), based on a wavelet reconstruction scheme, for detecting defects in a wide variety of structural and statistical textures. Two main features are presented. One of the new features is an original use of the normalized absolute function value (NABS) calculated from the wavelet coefficients derived at various different decomposition levels in order to identify textures where the defect can be isolated by eliminating the texture pattern in the first decomposition level. The second is the use of Shannon's entropy, calculated over detail subimages, for automatic selection of the band for image reconstruction, which, unlike other techniques, such as those based on the co-occurrence matrix or on energy calculation, provides a lower decomposition level, thus avoiding excessive degradation of the image, allowing a more accurate defect segmentation. A metric analysis of the results of the proposed method with nine different thresholding algorithms determined that selecting the appropriate thresholding method is important to achieve optimum performance in defect detection. As a consequence, several different thresholding algorithms depending on the type of texture are proposed.

Efficient optical analysis of surface texture combinations for silicon solar cells

NASA Astrophysics Data System (ADS)

Tucher, Nico; Eisenlohr, Johannes; Kiefel, Peter; Gebrewold, Habtamu; Höhn, Oliver; Hauser, Hubert; Müller, Claas; Goldschmidt, Jan Christoph; Bläsi, Benedikt

2016-04-01

Surface textures can significantly improve anti-reflective and light trapping properties of silicon solar cells. Combining standard pyramidal front side textures with scattering or diffractive rear side textures has the potential to further increase the light path length inside the silicon and thereby increase the solar cell efficiency. In this work we introduce the OPTOS (Optical Properties of Textured Optical Sheets) simulation formalism and apply it to the modelling of silicon solar cells with different surface textures at front and rear side. OPTOS is a matrix-based method that allows for the computationally-efficient calculation of non-coherent light propagation within textured solar cells, featuring multiple textures that may operate in different optical regimes. After calculating redistribution matrices for each individual surface texture with the most appropriate technique, optical properties like angle dependent reflectance, transmittance or absorptance can be determined via matrix multiplications. Using OPTOS, we demonstrate for example that the integration of a diffractive grating at the rear side of solar cells with random pyramids at the front results in an absorptance gain that corresponds to a photocurrent density enhancement of 0.73 mA/cm2 for a 250 μm thick cell. The re-usability of matrices enables the investigation of different solar cell thicknesses within minutes. For thicknesses down to 50 μm the simulated gain increases up to 1.22 mA/cm2. The OPTOS formalism is furthermore not restricted with respect to the number of textured interfaces. By combining two or more textured sheets to effective interfaces, it is possible to optically model a complete photovoltaic module including EVA and potentially textured glass layers with one calculation tool.

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

PubMed

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.

Enhanced Line Integral Convolution with Flow Feature Detection

NASA Technical Reports Server (NTRS)

Lane, David; Okada, Arthur

1996-01-01

The Line Integral Convolution (LIC) method, which blurs white noise textures along a vector field, is an effective way to visualize overall flow patterns in a 2D domain. The method produces a flow texture image based on the input velocity field defined in the domain. Because of the nature of the algorithm, the texture image tends to be blurry. This sometimes makes it difficult to identify boundaries where flow separation and reattachments occur. We present techniques to enhance LIC texture images and use colored texture images to highlight flow separation and reattachment boundaries. Our techniques have been applied to several flow fields defined in 3D curvilinear multi-block grids and scientists have found the results to be very useful.

Research in interactive scene analysis

NASA Technical Reports Server (NTRS)

Tenenbaum, J. M.; Barrow, H. G.; Weyl, S. A.

1976-01-01

Cooperative (man-machine) scene analysis techniques were developed whereby humans can provide a computer with guidance when completely automated processing is infeasible. An interactive approach promises significant near-term payoffs in analyzing various types of high volume satellite imagery, as well as vehicle-based imagery used in robot planetary exploration. This report summarizes the work accomplished over the duration of the project and describes in detail three major accomplishments: (1) the interactive design of texture classifiers; (2) a new approach for integrating the segmentation and interpretation phases of scene analysis; and (3) the application of interactive scene analysis techniques to cartography.

Content-based image retrieval for interstitial lung diseases using classification confidence

NASA Astrophysics Data System (ADS)

Dash, Jatindra Kumar; Mukhopadhyay, Sudipta; Prabhakar, Nidhi; Garg, Mandeep; Khandelwal, Niranjan

2013-02-01

Content Based Image Retrieval (CBIR) system could exploit the wealth of High-Resolution Computed Tomography (HRCT) data stored in the archive by finding similar images to assist radiologists for self learning and differential diagnosis of Interstitial Lung Diseases (ILDs). HRCT findings of ILDs are classified into several categories (e.g. consolidation, emphysema, ground glass, nodular etc.) based on their texture like appearances. Therefore, analysis of ILDs is considered as a texture analysis problem. Many approaches have been proposed for CBIR of lung images using texture as primitive visual content. This paper presents a new approach to CBIR for ILDs. The proposed approach makes use of a trained neural network (NN) to find the output class label of query image. The degree of confidence of the NN classifier is analyzed using Naive Bayes classifier that dynamically takes a decision on the size of the search space to be used for retrieval. The proposed approach is compared with three simple distance based and one classifier based texture retrieval approaches. Experimental results show that the proposed technique achieved highest average percentage precision of 92.60% with lowest standard deviation of 20.82%.

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

NASA Astrophysics Data System (ADS)

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 <001> 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 electromechanical coupling (k 33) of 81 vol% textured PMN-28PT (k33 = 0.79) was a significant fraction of single crystal (k33 = 0.91) and was higher than a commercial PMN-PT ceramic (k33 ˜ 0.74). The nonlinearity of the dielectric and piezoelectric response were investigated in textured ceramics and single crystal PMN-28PT using the Rayleigh approach. The reversible piezoelectric coefficient was found to increase significantly and the hysteretic contribution to the piezoelectric coefficient decreased significantly with an increase in texture volume. This indicates that increasing the texture volume decreases the non-180° domain wall contribution to the piezoelectric response in PMN-28PT. Finally, 81 vol% textured ceramics were also integrated into a Navy SONAR transducer design. In-water characterization of the transducers showed higher source levels, higher in-water coupling, higher acoustic intensity, and more bandwidth for the 81 vol% textured PMN-28PT tonpilz single elements compared to the ceramic PMN-28PT tonpilz element. In addition, an 81 vol% textured PMN-28PT tonpilz element showed large scale linearity in sound pressure levels as a function of drive level under high drive conditions (up to 2.33 kV/cm). The maximum electromechanical coupling obtained by the 81 vol% textured PMN-28PT transducer under high drive conditions was keff = 0.69. However, the resonance frequency shifted significantly during high drive tests (Deltafs = -19% at 3.7 kV/cm), evidence of a "soft" characteristic of the 81 vol% textured PMN-28PT, possibly caused by Sr2+ from the template particles. The results suggest there are limitations on the preload compressive stress (and thus drive level) for these textured ceramics, but this could be addressed with compositional modifications. The dielectric, piezoelectric and electromechanical properties have been significantly improved in textured PMN-PT ceramics of this study. Furthermore, scale-up in processing for incorporation into devices of highly textured ceramics with reproducible texture (and hence narrow properties distribution) was achieved in these materials. SONAR applications could benefit from textured ceramic parts because of their ease of processing, compositional homogeneity and potentially lower cost. (Abstract shortened by UMI.)

Performance Analysis of the SIFT Operator for Automatic Feature Extraction and Matching in Photogrammetric Applications.

PubMed

Lingua, Andrea; Marenchino, Davide; Nex, Francesco

2009-01-01

In the photogrammetry field, interest in region detectors, which are widely used in Computer Vision, is quickly increasing due to the availability of new techniques. Images acquired by Mobile Mapping Technology, Oblique Photogrammetric Cameras or Unmanned Aerial Vehicles do not observe normal acquisition conditions. Feature extraction and matching techniques, which are traditionally used in photogrammetry, are usually inefficient for these applications as they are unable to provide reliable results under extreme geometrical conditions (convergent taking geometry, strong affine transformations, etc.) and for bad-textured images. A performance analysis of the SIFT technique in aerial and close-range photogrammetric applications is presented in this paper. The goal is to establish the suitability of the SIFT technique for automatic tie point extraction and approximate DSM (Digital Surface Model) generation. First, the performances of the SIFT operator have been compared with those provided by feature extraction and matching techniques used in photogrammetry. All these techniques have been implemented by the authors and validated on aerial and terrestrial images. Moreover, an auto-adaptive version of the SIFT operator has been developed, in order to improve the performances of the SIFT detector in relation to the texture of the images. The Auto-Adaptive SIFT operator (A(2) SIFT) has been validated on several aerial images, with particular attention to large scale aerial images acquired using mini-UAV systems.

Quantitative evaluation of skeletal muscle defects in second harmonic generation images.

PubMed

Liu, Wenhua; Raben, Nina; Ralston, Evelyn

2013-02-01

Skeletal muscle pathologies cause irregularities in the normally periodic organization of the myofibrils. Objective grading of muscle morphology is necessary to assess muscle health, compare biopsies, and evaluate treatments and the evolution of disease. To facilitate such quantitation, we have developed a fast, sensitive, automatic imaging analysis software. It detects major and minor morphological changes by combining texture features and Fourier transform (FT) techniques. We apply this tool to second harmonic generation (SHG) images of muscle fibers which visualize the repeating myosin bands. Texture features are then calculated by using a Haralick gray-level cooccurrence matrix in MATLAB. Two scores are retrieved from the texture correlation plot by using FT and curve-fitting methods. The sensitivity of the technique was tested on SHG images of human adult and infant muscle biopsies and of mouse muscle samples. The scores are strongly correlated to muscle fiber condition. We named the software MARS (muscle assessment and rating scores). It is executed automatically and is highly sensitive even to subtle defects. We propose MARS as a powerful and unbiased tool to assess muscle health.

Quantitative evaluation of skeletal muscle defects in second harmonic generation images

NASA Astrophysics Data System (ADS)

Liu, Wenhua; Raben, Nina; Ralston, Evelyn

2013-02-01

Skeletal muscle pathologies cause irregularities in the normally periodic organization of the myofibrils. Objective grading of muscle morphology is necessary to assess muscle health, compare biopsies, and evaluate treatments and the evolution of disease. To facilitate such quantitation, we have developed a fast, sensitive, automatic imaging analysis software. It detects major and minor morphological changes by combining texture features and Fourier transform (FT) techniques. We apply this tool to second harmonic generation (SHG) images of muscle fibers which visualize the repeating myosin bands. Texture features are then calculated by using a Haralick gray-level cooccurrence matrix in MATLAB. Two scores are retrieved from the texture correlation plot by using FT and curve-fitting methods. The sensitivity of the technique was tested on SHG images of human adult and infant muscle biopsies and of mouse muscle samples. The scores are strongly correlated to muscle fiber condition. We named the software MARS (muscle assessment and rating scores). It is executed automatically and is highly sensitive even to subtle defects. We propose MARS as a powerful and unbiased tool to assess muscle health.

Advanced Ecosystem Mapping Techniques for Large Arctic Study Domains Using Calibrated High-Resolution Imagery

NASA Astrophysics Data System (ADS)

Macander, M. J.; Frost, G. V., Jr.

2015-12-01

Regional-scale mapping of vegetation and other ecosystem properties has traditionally relied on medium-resolution remote sensing such as Landsat (30 m) and MODIS (250 m). Yet, the burgeoning availability of high-resolution (<=2 m) imagery and ongoing advances in computing power and analysis tools raises the prospect of performing ecosystem mapping at fine spatial scales over large study domains. Here we demonstrate cutting-edge mapping approaches over a ~35,000 km² study area on Alaska's North Slope using calibrated and atmospherically-corrected mosaics of high-resolution WorldView-2 and GeoEye-1 imagery: (1) an a priori spectral approach incorporating the Satellite Imagery Automatic Mapper (SIAM) algorithms; (2) image segmentation techniques; and (3) texture metrics. The SIAM spectral approach classifies radiometrically-calibrated imagery to general vegetation density categories and non-vegetated classes. The SIAM classes were developed globally and their applicability in arctic tundra environments has not been previously evaluated. Image segmentation, or object-based image analysis, automatically partitions high-resolution imagery into homogeneous image regions that can then be analyzed based on spectral, textural, and contextual information. We applied eCognition software to delineate waterbodies and vegetation classes, in combination with other techniques. Texture metrics were evaluated to determine the feasibility of using high-resolution imagery to algorithmically characterize periglacial surface forms (e.g., ice-wedge polygons), which are an important physical characteristic of permafrost-dominated regions but which cannot be distinguished by medium-resolution remote sensing. These advanced mapping techniques provide products which can provide essential information supporting a broad range of ecosystem science and land-use planning applications in northern Alaska and elsewhere in the circumpolar Arctic.

Despeckle filtering software toolbox for ultrasound imaging of the common carotid artery.

PubMed

Loizou, Christos P; Theofanous, Charoula; Pantziaris, Marios; Kasparis, Takis

2014-04-01

Ultrasound imaging of the common carotid artery (CCA) is a non-invasive tool used in medicine to assess the severity of atherosclerosis and monitor its progression through time. It is also used in border detection and texture characterization of the atherosclerotic carotid plaque in the CCA, the identification and measurement of the intima-media thickness (IMT) and the lumen diameter that all are very important in the assessment of cardiovascular disease (CVD). Visual perception, however, is hindered by speckle, a multiplicative noise, that degrades the quality of ultrasound B-mode imaging. Noise reduction is therefore essential for improving the visual observation quality or as a pre-processing step for further automated analysis, such as image segmentation of the IMT and the atherosclerotic carotid plaque in ultrasound images. In order to facilitate this preprocessing step, we have developed in MATLAB(®) a unified toolbox that integrates image despeckle filtering (IDF), texture analysis and image quality evaluation techniques to automate the pre-processing and complement the disease evaluation in ultrasound CCA images. The proposed software, is based on a graphical user interface (GUI) and incorporates image normalization, 10 different despeckle filtering techniques (DsFlsmv, DsFwiener, DsFlsminsc, DsFkuwahara, DsFgf, DsFmedian, DsFhmedian, DsFad, DsFnldif, DsFsrad), image intensity normalization, 65 texture features, 15 quantitative image quality metrics and objective image quality evaluation. The software is publicly available in an executable form, which can be downloaded from http://www.cs.ucy.ac.cy/medinfo/. It was validated on 100 ultrasound images of the CCA, by comparing its results with quantitative visual analysis performed by a medical expert. It was observed that the despeckle filters DsFlsmv, and DsFhmedian improved image quality perception (based on the expert's assessment and the image texture and quality metrics). It is anticipated that the system could help the physician in the assessment of cardiovascular image analysis. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Texture- and deformability-based surface recognition by tactile image analysis.

PubMed

Khasnobish, Anwesha; Pal, Monalisa; Tibarewala, D N; Konar, Amit; Pal, Kunal

2016-08-01

Deformability and texture are two unique object characteristics which are essential for appropriate surface recognition by tactile exploration. Tactile sensation is required to be incorporated in artificial arms for rehabilitative and other human-computer interface applications to achieve efficient and human-like manoeuvring. To accomplish the same, surface recognition by tactile data analysis is one of the prerequisites. The aim of this work is to develop effective technique for identification of various surfaces based on deformability and texture by analysing tactile images which are obtained during dynamic exploration of the item by artificial arms whose gripper is fitted with tactile sensors. Tactile data have been acquired, while human beings as well as a robot hand fitted with tactile sensors explored the objects. The tactile images are pre-processed, and relevant features are extracted from the tactile images. These features are provided as input to the variants of support vector machine (SVM), linear discriminant analysis and k-nearest neighbour (kNN) for classification. Based on deformability, six household surfaces are recognized from their corresponding tactile images. Moreover, based on texture five surfaces of daily use are classified. The method adopted in the former two cases has also been applied for deformability- and texture-based recognition of four biomembranes, i.e. membranes prepared from biomaterials which can be used for various applications such as drug delivery and implants. Linear SVM performed best for recognizing surface deformability with an accuracy of 83 % in 82.60 ms, whereas kNN classifier recognizes surfaces of daily use having different textures with an accuracy of 89 % in 54.25 ms and SVM with radial basis function kernel recognizes biomembranes with an accuracy of 78 % in 53.35 ms. The classifiers are observed to generalize well on the unseen test datasets with very high performance to achieve efficient material recognition based on its deformability and texture.

Germinal center texture entropy as possible indicator of humoral immune response: immunophysiology viewpoint.

PubMed

Pantic, Igor; Pantic, Senka

2012-10-01

In this article, we present the results indicating that spleen germinal center (GC) texture entropy determined by gray-level co-occurrence matrix (GLCM) method is related to humoral immune response. Spleen tissue was obtained from eight outbred male short-haired guinea pigs previously immunized by sheep red blood cells (SRBC). A total of 312 images from 39 germinal centers (156 GC light zone images and 156 GC dark zone images) were acquired and analyzed by GLCM method. Angular second moment, contrast, correlation, entropy, and inverse difference moment were calculated for each image. Humoral immune response to SRBC was measured using T cell-dependent antibody response (TDAR) assay. Statistically highly significant negative correlation was detected between light zone entropy and the number of TDAR plaque-forming cells (r (s) = -0.86, p < 0.01). The entropy decreased as the plaque-forming cells increased and vice versa. A statistically significant negative correlation was also detected between dark zone entropy values and the number of plaque-forming cells (r (s) = -0.69, p < 0.05). Germinal center texture entropy may be a powerful indicator of humoral immune response. This study is one of the first to point out the potential scientific value of GLCM image texture analysis in lymphoid tissue cytoarchitecture evaluation. Lymphoid tissue texture analysis could become an important and affordable addition to the conventional immunophysiology techniques.

Confocal laser scanning microscopy and area-scale analysis used to quantify enamel surface textural changes from citric acid demineralization and salivary remineralization in vitro.

PubMed

Austin, R S; Giusca, C L; Macaulay, G; Moazzez, R; Bartlett, D W

2016-02-01

This paper investigates the application of confocal laser scanning microscopy to determine the effect of acid-mediated erosive enamel wear on the micro-texture of polished human enamel in vitro. Twenty polished enamel samples were prepared and subjected to a citric acid erosion and pooled human saliva remineralization model. Enamel surface microhardness was measured using a Knoop hardness tester, which confirmed that an early enamel erosion lesion was formed which was then subsequently completely remineralized. A confocal laser scanning microscope was used to capture high-resolution images of the enamel surfaces undergoing demineralization and remineralization. Area-scale analysis was used to identify the optimal feature size following which the surface texture was determined using the 3D (areal) texture parameter Sa. The Sa successfully characterized the enamel erosion and remineralization for the polished enamel samples (P<0.001). Areal surface texture characterization of the surface events occurring during enamel demineralization and remineralization requires optical imaging instrumentation with lateral resolution <2.5 μm, applied in combination with appropriate filtering in order to remove unwanted waviness and roughness. These techniques will facilitate the development of novel methods for measuring early enamel erosion lesions in natural enamel surfaces in vivo. Copyright © 2015 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.

Texturing of concrete pavements : final report.

DOT National Transportation Integrated Search

1979-08-01

During the month of June, 1973, the plastic concrete surface of a section of Interstate 10 in the Baton Rouge area was textured using several different texturing techniques, such as burlap drag, brooms and metal tines. The purpose of this experimenta...

Flow Charts: Visualization of Vector Fields on Arbitrary Surfaces

PubMed Central

Li, Guo-Shi; Tricoche, Xavier; Weiskopf, Daniel; Hansen, Charles

2009-01-01

We introduce a novel flow visualization method called Flow Charts, which uses a texture atlas approach for the visualization of flows defined over curved surfaces. In this scheme, the surface and its associated flow are segmented into overlapping patches, which are then parameterized and packed in the texture domain. This scheme allows accurate particle advection across multiple charts in the texture domain, providing a flexible framework that supports various flow visualization techniques. The use of surface parameterization enables flow visualization techniques requiring the global view of the surface over long time spans, such as Unsteady Flow LIC (UFLIC), particle-based Unsteady Flow Advection Convolution (UFAC), or dye advection. It also prevents visual artifacts normally associated with view-dependent methods. Represented as textures, Flow Charts can be naturally integrated into hardware accelerated flow visualization techniques for interactive performance. PMID:18599918

Microprobe monazite geochronology: new techniques for dating deformation and metamorphism

NASA Astrophysics Data System (ADS)

Williams, M.; Jercinovic, M.; Goncalves, P.; Mahan, K.

2003-04-01

High-resolution compositional mapping, age mapping, and precise dating of monazite on the electron microprobe are powerful additions to microstructural and petrologic analysis and important tools for tectonic studies. The in-situ nature and high spatial resolution of the technique offer an entirely new level of structurally and texturally specific geochronologic data that can be used to put absolute time constraints on P-T-D paths, constrain the rates of sedimentary, metamorphic, and deformational processes, and provide new links between metamorphism and deformation. New analytical techniques (including background modeling, sample preparation, and interference analysis) have significantly improved the precision and accuracy of the technique and new mapping and image analysis techniques have increased the efficiency and strengthened the correlation with fabrics and textures. Microprobe geochronology is particularly applicable to three persistent microstructural-microtextural problem areas: (1) constraining the chronology of metamorphic assemblages; (2) constraining the timing of deformational fabrics; and (3) interpreting other geochronological results. In addition, authigenic monazite can be used to date sedimentary basins, and detrital monazite can fingerprint sedimentary source areas, both critical for tectonic analysis. Although some monazite generations can be directly tied to metamorphism or deformation, at present, the most common constraints rely on monazite inclusion relations in porphyroblasts that, in turn, can be tied to the deformation and/or metamorphic history. Examples will be presented from deep-crustal rocks of northern Saskatchewan and from mid-crustal rocks from the southwestern USA. Microprobe monazite geochronology has been used in both regions to deconvolute overprinting deformation and metamorphic events and to clarify the interpretation of other geochronologic data. Microprobe mapping and dating are powerful companions to mass spectroscopic dating techniques. They allow geochronology to be incorporated into the microstructural analytical process, resulting in a new level of integration of time (t) into P-T-D histories.

Elasticity study of textured barium strontium titanate thin films by X-ray diffraction and laser acoustic waves

NASA Astrophysics Data System (ADS)

Chaabani, Anouar; Njeh, Anouar; Donner, Wolfgang; Klein, Andreas; Hédi Ben Ghozlen, Mohamed

2017-05-01

Ba0.65Sr0.35TiO3 (BST) thin films of 300 nm were deposited on Pt(111)/TiO2/SiO2/Si(001) substrates by radio frequency magnetron sputtering. Two thin films with different (111) and (001) fiber textures were prepared. X-ray diffraction was applied to measure texture. The raw pole figure data were further processed using the MTEX quantitative texture analysis software for plotting pole figures and calculating elastic constants and Young’s modulus from the orientation distribution function (ODF) for each type of textured fiber. The calculated elastic constants were used in the theoretical studies of surface acoustics waves (SAW) propagating in two types of multilayered BST systems. Theoretical dispersion curves were plotted by the application of the ordinary differential equation (ODE) and the stiffness matrix methods (SMM). A laser acoustic waves (LAW) technique was applied to generate surface acoustic waves (SAW) propagating in the BST films, and from a recursive process, the effective Young’s modulus are determined for the two samples. These methods are used to extract and compare elastic properties of two types of BST films, and quantify the influence of texture on the direction-dependent Young’s modulus.

Friction Stir Back Extrusion of Aluminium Alloys for Automotive Applications

NASA Astrophysics Data System (ADS)

Xu, Zeren

Since the invention of Friction Stir Welding in 1991 as a solid state joining technique, extensive scientific investigations have been carried out to understand fundamental aspects of material behaviors when processed by this technique, in order to optimize processing conditions as well as mechanical properties of the welds. Based on the basic principles of Friction Stir Welding, several derivatives have also been developed such as Friction Stir Processing, Friction Extrusion and Friction Stir Back Extrusion. Friction Stir Back Extrusion is a novel technique that is proposed recently and designed for fabricating tubes from lightweight alloys. Some preliminary results have been reported regarding microstructure and mechanical properties of Friction Stir Back Extrusion processed AZ31 magnesium alloy, however, systematic study and in-depth investigations are still needed to understand the materials behaviors and underlying mechanisms when subjected to Friction Stir Back Extrusion, especially for age-hardenable Al alloys. In the present study, Friction Stir Back Extrusion processed AA6063-T5 and AA7075-T6 alloys are analyzed with respect to grain structure evolution, micro-texture change, recrystallization mechanisms, precipitation sequence as well as mechanical properties. Optical Microscopy, Electron Backscatter Diffraction, Transmission Electron Microscopy, Vickers Hardness measurements and uniaxial tensile tests are carried out to characterize the microstructural change as well as micro and macro mechanical properties of the processed tubes. Special attention is paid to the micro-texture evolution across the entire tube and dynamic recrystallization mechanisms that are responsible for grain refinement. Significant grain refinement has been observed near the processing zone while the tube wall is characterized by inhomogeneous grain structure across the thickness for both alloys. Dissolution of existing precipitates is noticed under the thermal hysterias imposed by Friction Stir Back Extrusion process, resulting in decreased strength but improved elongation of the processed tubes; a post-process aging step can effectively restore the mechanical properties of the processed tubes by allowing for the reprecipitation of solute elements in the form of fine, dispersed precipitates. Texture analysis performed for AA6063 alloy suggests the dominance of simple shear type textures with clear transition from initial texture to stable B/ ?B components via intermediate types that are stable under moderate strain levels. In order to identify the texture components properly, rigid body rotations are applied to the existing coordinate system to align it to local shear reference frame. Surprisingly, for AA7075 tubes, and fibers are observed to be the dominant texture components in the transition region as well as thermomechanically affected zone while the processing zone is characterized by random texture. The underlying mechanisms responsible for the formation of random texture are discussed in Chapter 5 based on Electron Backscatter Diffraction analysis. Comparative discussions are also carried out for the recrystallization mechanisms that are responsible for grain structure evolution of both alloys. Continuous grain subdivision and reorientation is cited as the dominant mechanism for the recrystallization of AA6063 alloys, while dynamic recrystallization occurs mainly in the form of Geometric Dynamic Recrystallization and progressive subgrain rotations near grain boundaries in AA7075 alloys.

Classification of Weed Species Using Artificial Neural Networks Based on Color Leaf Texture Feature

NASA Astrophysics Data System (ADS)

Li, Zhichen; An, Qiu; Ji, Changying

The potential impact of herbicide utilization compel people to use new method of weed control. Selective herbicide application is optimal method to reduce herbicide usage while maintain weed control. The key of selective herbicide is how to discriminate weed exactly. The HIS color co-occurrence method (CCM) texture analysis techniques was used to extract four texture parameters: Angular second moment (ASM), Entropy(E), Inertia quadrature (IQ), and Inverse difference moment or local homogeneity (IDM).The weed species selected for studying were Arthraxon hispidus, Digitaria sanguinalis, Petunia, Cyperus, Alternanthera Philoxeroides and Corchoropsis psilocarpa. The software of neuroshell2 was used for designing the structure of the neural network, training and test the data. It was found that the 8-40-1 artificial neural network provided the best classification performance and was capable of classification accuracies of 78%.

Watermarking textures in video games

NASA Astrophysics Data System (ADS)

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.

Optimizing the sensory characteristics and acceptance of canned cat food: use of a human taste panel.

PubMed

Pickering, G J

2009-02-01

A methodology based on descriptive analysis techniques used in the evaluation of human food has been successfully refined to allow for a human taste panel to profile the flavour and texture of a range of cat food products (CFP) and their component parts. Included in this method is the development of evaluation protocols for homogeneous products and for binary samples containing both meat chunk (MC) and gravy/gel (GG) constituents. Using these techniques, 18 flavour attributes (sweet, sour/acid, tuna, herbal, spicy, soy, salty, cereal, caramel, chicken, methionine, vegetable, offaly, meaty, burnt flavour, prawn, rancid and bitter) and four texture dimensions (hardness, chewiness, grittiness and viscosity) were generated to describe the sensations elicited by 13 commercial pet food samples. These samples differed in intensity for 16 of the 18 flavour attributes, which allows for individual CFP flavour profiles to be developed. Principal components analysis (PCA) could successfully discriminate between samples within the PCA space and also reveal some groupings amongst them. While many flavour attributes were weakly correlated, a large number (describing both taste and retro-nasal aroma qualities) were required to adequately differentiate between samples, suggesting considerable complexity in the products assessed. For both MC and GG, differences between samples for each of the texture dimensions were also found. For MC, grittiness appears to be the most discriminating textural attribute, while for GG viscosity discriminates well between samples. Meat chunks and gravy/gels differed significantly from each other in both flavour and texture. Cat food products differed in their liking ratings, although no differences were found between homogeneous, MC and GG samples, and eight flavour attributes were correlated with overall liking scores. It is now necessary to determine the usefulness and limits of sensory data gathered from human panels in describing and predicting food acceptance and preference behaviours in cats. For instance, while the sense of taste in cats appears generally similar to that of other mammals, they lack a sweet taste receptor (Li et al., 2006), which may limit the applicability of sweetness ratings obtained from humans. Modification of existing techniques used with human food research, such as external preference mapping (Naes and Risvik, 1996) may be useful. Ultimately, this may facilitate more economical and efficient methods for optimizing cat food flavour and texture and predicting the effects of composition and processing changes on cat feeding behaviour. This will require collaboration between pet food manufacturers and nutritionists, animal behaviourists and human sensory scientists. The results of this preliminary study should assist in this process.

Wavelet-based image analysis system for soil texture analysis

NASA Astrophysics Data System (ADS)

Sun, Yun; Long, Zhiling; Jang, Ping-Rey; Plodinec, M. John

2003-05-01

Soil texture is defined as the relative proportion of clay, silt and sand found in a given soil sample. It is an important physical property of soil that affects such phenomena as plant growth and agricultural fertility. Traditional methods used to determine soil texture are either time consuming (hydrometer), or subjective and experience-demanding (field tactile evaluation). Considering that textural patterns observed at soil surfaces are uniquely associated with soil textures, we propose an innovative approach to soil texture analysis, in which wavelet frames-based features representing texture contents of soil images are extracted and categorized by applying a maximum likelihood criterion. The soil texture analysis system has been tested successfully with an accuracy of 91% in classifying soil samples into one of three general categories of soil textures. In comparison with the common methods, this wavelet-based image analysis approach is convenient, efficient, fast, and objective.

Computer-based quantitative computed tomography image analysis in idiopathic pulmonary fibrosis: A mini review.

PubMed

Ohkubo, Hirotsugu; Nakagawa, Hiroaki; Niimi, Akio

2018-01-01

Idiopathic pulmonary fibrosis (IPF) is the most common type of progressive idiopathic interstitial pneumonia in adults. Many computer-based image analysis methods of chest computed tomography (CT) used in patients with IPF include the mean CT value of the whole lungs, density histogram analysis, density mask technique, and texture classification methods. Most of these methods offer good assessment of pulmonary functions, disease progression, and mortality. Each method has merits that can be used in clinical practice. One of the texture classification methods is reported to be superior to visual CT scoring by radiologist for correlation with pulmonary function and prediction of mortality. In this mini review, we summarize the current literature on computer-based CT image analysis of IPF and discuss its limitations and several future directions. Copyright © 2017 The Japanese Respiratory Society. Published by Elsevier B.V. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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.

Comparison of two methods to explore consumer preferences for cottage cheese.

PubMed

Drake, S L; Lopetcharat, K; Drake, M A

2009-12-01

In the past 2 decades, total sales of cottage cheese have declined 17% despite increases in sales for low-fat cottage cheese. There are no recent published studies investigating consumer preferences for cottage cheese. This study was conducted to identify and define sensory characteristics of commercial cottage cheese and to compare 2 approaches for characterizing consumer preferences: traditional preference mapping and a new composite qualitative approach, qualitative multivariate analysis (QMA). A sensory language was identified to document the sensory properties (visual, flavor, and texture) of cottage cheeses. Twenty-six commercial cottage cheeses with variable fat contents (4, 2, 1, and 0% fat) were evaluated by trained panelists using the sensory language. Eight representative cottage cheeses were selected for consumer acceptance testing (n = 110) and QMA with consumer home usage testing (n = 12), followed by internal and external preference mapping to identify key drivers. Principal component analysis of descriptive data indicated that cottage cheeses were primarily differentiated by cooked, milkfat, diacetyl, and acetaldehyde flavors and salty taste, and by firmness, smoothness, tackiness, curd size, and adhesiveness texture attributes. Similar drivers of liking (diacetyl and milkfat flavors, smooth texture, and mouthcoating) were identified by both consumer research techniques. However, the QMA technique identified controversial distinctions among the cottage cheeses and the influence of brand and pricing. These results can be used by processors to promote cottage cheese sales.

Cool Polar Bears: Dabbing on the Texture

ERIC Educational Resources Information Center

O'Connell, Jean

2011-01-01

In this article, the author describes how her second-graders created their cool polar bears. The students used the elements of shape and texture to create the bears. They used Monet's technique of dabbing paint so as to give the bear some texture on his fur.

MPEG-4 ASP SoC receiver with novel image enhancement techniques for DAB networks

NASA Astrophysics Data System (ADS)

Barreto, D.; Quintana, A.; García, L.; Callicó, G. M.; Núñez, A.

2007-05-01

This paper presents a system for real-time video reception in low-power mobile devices using Digital Audio Broadcast (DAB) technology for transmission. A demo receiver terminal is designed into a FPGA platform using the Advanced Simple Profile (ASP) MPEG-4 standard for video decoding. In order to keep the demanding DAB requirements, the bandwidth of the encoded sequence must be drastically reduced. In this sense, prior to the MPEG-4 coding stage, a pre-processing stage is performed. It is firstly composed by a segmentation phase according to motion and texture based on the Principal Component Analysis (PCA) of the input video sequence, and secondly by a down-sampling phase, which depends on the segmentation results. As a result of the segmentation task, a set of texture and motion maps are obtained. These motion and texture maps are also included into the bit-stream as user data side-information and are therefore known to the receiver. For all bit-rates, the whole encoder/decoder system proposed in this paper exhibits higher image visual quality than the alternative encoding/decoding method, assuming equal image sizes. A complete analysis of both techniques has also been performed to provide the optimum motion and texture maps for the global system, which has been finally validated for a variety of video sequences. Additionally, an optimal HW/SW partition for the MPEG-4 decoder has been studied and implemented over a Programmable Logic Device with an embedded ARM9 processor. Simulation results show that a throughput of 15 QCIF frames per second can be achieved with low area and low power implementation.

Analysis of hyperspectral scattering images using locally linear embedding algorithm for apple mealiness classification

USDA-ARS?s Scientific Manuscript database

Hyperspectral scattering technique provides a means for assessing the structural and/or physical properties of apples. It could thus be useful for detection of apple mealiness, which is a symptom of physiological disorder, resulting in an undesirable texture and taste for apples and degrading their ...

Image statistics underlying natural texture selectivity of neurons in macaque V4

PubMed Central

Okazawa, Gouki; Tajima, Satohiro; Komatsu, Hidehiko

2015-01-01

Our daily visual experiences are inevitably linked to recognizing the rich variety of textures. However, how the brain encodes and differentiates a plethora of natural textures remains poorly understood. Here, we show that many neurons in macaque V4 selectively encode sparse combinations of higher-order image statistics to represent natural textures. We systematically explored neural selectivity in a high-dimensional texture space by combining texture synthesis and efficient-sampling techniques. This yielded parameterized models for individual texture-selective neurons. The models provided parsimonious but powerful predictors for each neuron’s preferred textures using a sparse combination of image statistics. As a whole population, the neuronal tuning was distributed in a way suitable for categorizing textures and quantitatively predicts human ability to discriminate textures. Together, we suggest that the collective representation of visual image statistics in V4 plays a key role in organizing the natural texture perception. PMID:25535362

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

PubMed

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.

Multi-Sectional Views Textural Based SVM for MS Lesion Segmentation in Multi-Channels MRIs

PubMed Central

Abdullah, Bassem A; Younis, Akmal A; John, Nigel M

2012-01-01

In this paper, a new technique is proposed for automatic segmentation of multiple sclerosis (MS) lesions from brain magnetic resonance imaging (MRI) data. The technique uses a trained support vector machine (SVM) to discriminate between the blocks in regions of MS lesions and the blocks in non-MS lesion regions mainly based on the textural features with aid of the other features. The classification is done on each of the axial, sagittal and coronal sectional brain view independently and the resultant segmentations are aggregated to provide more accurate output segmentation. The main contribution of the proposed technique described in this paper is the use of textural features to detect MS lesions in a fully automated approach that does not rely on manually delineating the MS lesions. In addition, the technique introduces the concept of the multi-sectional view segmentation to produce verified segmentation. The proposed textural-based SVM technique was evaluated using three simulated datasets and more than fifty real MRI datasets. The results were compared with state of the art methods. The obtained results indicate that the proposed method would be viable for use in clinical practice for the detection of MS lesions in MRI. PMID:22741026

Documentation of procedures for textural/spatial pattern recognition techniques

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Bryant, W. F.

1976-01-01

A C-130 aircraft was flown over the Sam Houston National Forest on March 21, 1973 at 10,000 feet altitude to collect multispectral scanner (MSS) data. Existing textural and spatial automatic processing techniques were used to classify the MSS imagery into specified timber categories. Several classification experiments were performed on this data using features selected from the spectral bands and a textural transform band. The results indicate that (1) spatial post-processing a classified image can cut the classification error to 1/2 or 1/3 of its initial value, (2) spatial post-processing the classified image using combined spectral and textural features produces a resulting image with less error than post-processing a classified image using only spectral features and (3) classification without spatial post processing using the combined spectral textural features tends to produce about the same error rate as a classification without spatial post processing using only spectral features.

Bayesian Fusion of Color and Texture Segmentations

NASA Technical Reports Server (NTRS)

Manduchi, Roberto

2000-01-01

In many applications one would like to use information from both color and texture features in order to segment an image. We propose a novel technique to combine "soft" segmentations computed for two or more features independently. Our algorithm merges models according to a mean entropy criterion, and allows to choose the appropriate number of classes for the final grouping. This technique also allows to improve the quality of supervised classification based on one feature (e.g. color) by merging information from unsupervised segmentation based on another feature (e.g., texture.)

3D Flow Visualization Using Texture Advection

NASA Technical Reports Server (NTRS)

Kao, David; Zhang, Bing; Kim, Kwansik; Pang, Alex; Moran, Pat (Technical Monitor)

2001-01-01

Texture advection is an effective tool for animating and investigating 2D flows. In this paper, we discuss how this technique can be extended to 3D flows. In particular, we examine the use of 3D and 4D textures on 3D synthetic and computational fluid dynamics flow fields.

Staging Liver Fibrosis with Statistical Observers

NASA Astrophysics Data System (ADS)

Brand, Jonathan Frieman

Chronic liver disease is a worldwide health problem, and hepatic fibrosis (HF) is one of the hallmarks of the disease. Pathology diagnosis of HF is based on textural change in the liver as a lobular collagen network that develops within portal triads. The scale of collagen lobules is characteristically on order of 1mm, which close to the resolution limit of in vivo Gd-enhanced MRI. In this work the methods to collect training and testing images for a Hotelling observer are covered. An observer based on local texture analysis is trained and tested using wet-tissue phantoms. The technique is used to optimize the MRI sequence based on task performance. The final method developed is a two stage model observer to classify fibrotic and healthy tissue in both phantoms and in vivo MRI images. The first stage observer tests for the presence of local texture. Test statistics from the first observer are used to train the second stage observer to globally sample the local observer results. A decision of the disease class is made for an entire MRI image slice using test statistics collected from the second observer. The techniques are tested on wet-tissue phantoms and in vivo clinical patient data.

Revisiting elastic anisotropy of biotite gneiss from the Outokumpu scientific drill hole based on new texture measurements and texture-based velocity calculations

NASA Astrophysics Data System (ADS)

Wenk, H.-R.; Vasin, R. N.; Kern, H.; Matthies, S.; Vogel, S. C.; Ivankina, T. I.

2012-10-01

A sample of biotite gneiss from the Outokumpu deep drilling project in Finland was investigated by Kern et al. (2008) for crystal preferred orientation and elastic anisotropy. Considerable differences between measured acoustic velocities and velocities calculated on the basis of texture patterns were observed. Measured P-wave anisotropy was 15.1% versus a Voigt average yielding 7.9%. Here we investigate the same sample with different methods and using different averaging techniques. Analyzing time-of-flight neutron diffraction data from Dubna-SKAT and LANSCE-HIPPO diffractometers with the Rietveld technique, much stronger preferred orientation for biotite is determined, compared to conventional pole-figure analysis reported previously. The comparison reveals important differences: HIPPO has much better counting statistics but pole figure coverage is poor. SKAT has better angular resolution. Using the new preferred orientation data and applying a self-consistent averaging method that takes grain shapes into account, close agreement of calculated and measured P-wave velocities is observed (12.6%). This is further improved by adding 0.1 vol.% flat micropores parallel to the biotite platelets in the simulation (14.9%).

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

PubMed

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 < 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.

Early diagnosis of osteoporosis using radiogrammetry and texture analysis from hand and wrist radiographs in Indian population.

PubMed

Areeckal, A S; Jayasheelan, N; Kamath, J; Zawadynski, S; Kocher, M; David S, S

2018-03-01

We propose an automated low cost tool for early diagnosis of onset of osteoporosis using cortical radiogrammetry and cancellous texture analysis from hand and wrist radiographs. The trained classifier model gives a good performance accuracy in classifying between healthy and low bone mass subjects. We propose a low cost automated diagnostic tool for early diagnosis of reduction in bone mass using cortical radiogrammetry and cancellous texture analysis of hand and wrist radiographs. Reduction in bone mass could lead to osteoporosis, a disease observed to be increasingly occurring at a younger age in recent times. Dual X-ray absorptiometry (DXA), currently used in clinical practice, is expensive and available only in urban areas in India. Therefore, there is a need to develop a low cost diagnostic tool in order to facilitate large-scale screening of people for early diagnosis of osteoporosis at primary health centers. Cortical radiogrammetry from third metacarpal bone shaft and cancellous texture analysis from distal radius are used to detect low bone mass. Cortical bone indices and cancellous features using Gray Level Run Length Matrices and Laws' masks are extracted. A neural network classifier is trained using these features to classify healthy subjects and subjects having low bone mass. In our pilot study, the proposed segmentation method shows 89.9 and 93.5% accuracy in detecting third metacarpal bone shaft and distal radius ROI, respectively. The trained classifier shows training accuracy of 94.3% and test accuracy of 88.5%. An automated diagnostic technique for early diagnosis of onset of osteoporosis is developed using cortical radiogrammetric measurements and cancellous texture analysis of hand and wrist radiographs. The work shows that a combination of cortical and cancellous features improves the diagnostic ability and is a promising low cost tool for early diagnosis of increased risk of osteoporosis.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fang, Y; Huang, H; Su, T

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

A software tool for automatic classification and segmentation of 2D/3D medical images

NASA Astrophysics Data System (ADS)

Strzelecki, Michal; Szczypinski, Piotr; Materka, Andrzej; Klepaczko, Artur

2013-02-01

Modern medical diagnosis utilizes techniques of visualization of human internal organs (CT, MRI) or of its metabolism (PET). However, evaluation of acquired images made by human experts is usually subjective and qualitative only. Quantitative analysis of MR data, including tissue classification and segmentation, is necessary to perform e.g. attenuation compensation, motion detection, and correction of partial volume effect in PET images, acquired with PET/MR scanners. This article presents briefly a MaZda software package, which supports 2D and 3D medical image analysis aiming at quantification of image texture. MaZda implements procedures for evaluation, selection and extraction of highly discriminative texture attributes combined with various classification, visualization and segmentation tools. Examples of MaZda application in medical studies are also provided.

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

PubMed

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.

Electron Backscatter Diffraction Analysis of Joints Between AISI 316L Austenitic/UNS S32750 Dual-Phase Stainless Steel

NASA Astrophysics Data System (ADS)

Shamanian, Morteza; Mohammadnezhad, Mahyar; Amini, Mahdi; Zabolian, Azam; Szpunar, Jerzy A.

2015-08-01

Stainless steels are among the most economical and highly practicable materials widely used in industrial areas due to their mechanical and corrosion resistances. In this study, a dissimilar weld joint consisting of an AISI 316L austenitic stainless steel (ASS) and a UNS S32750 dual-phase stainless steel was obtained under optimized welding conditions by gas tungsten arc welding technique using AWS A5.4:ER2594 filler metal. The effect of welding on the evolution of the microstructure, crystallographic texture, and micro-hardness distribution was also studied. The weld metal (WM) was found to be dual-phased; the microstructure is obtained by a fully ferritic solidification mode followed by austenite precipitation at both ferrite boundaries and ferrite grains through solid-state transformation. It is found that welding process can affect the ferrite content and grain growth phenomenon. The strong textures were found in the base metals for both steels. The AISI 316L ASS texture is composed of strong cube component. In the UNS S32750 dual-phase stainless steel, an important difference between the two phases can be seen in the texture evolution. Austenite phase is composed of a major cube component, whereas the ferrite texture mainly contains a major rotated cube component. The texture of the ferrite is stronger than that of austenite. In the WM, Kurdjumov-Sachs crystallographic orientation relationship is found in the solidification microstructure. The analysis of the Kernel average misorientation distribution shows that the residual strain is more concentrated in the austenite phase than in the other phase. The welding resulted in a significant hardness increase in the WM compared to initial ASS.

The new materials science diffractometer STRESS-SPEC at FRM-II

NASA Astrophysics Data System (ADS)

Hofmann, M.; Schneider, R.; Seidl, G. A.; Rebelo-Kornmeier, J.; Wimpory, R. C.; Garbe, U.; Brokmeier, H.-G.

2006-11-01

In response to the development of new materials and the application of materials and components in new technologies the direct measurement, calculation and evaluation of textures and residual stresses has gained worldwide significance in recent years. In order to cater for the development of these analytical techniques the Materials Science Diffractometer STRESS-SPEC at FRM-II is designed to be equally applied to texture or residual stress analysis by virtue of its flexible configuration and the high neutron flux at the sample position. The instrument is now available for routine operation and here we present details of first experiments and instrument performance.

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

PubMed Central

Colgan, Niall; Ganeshan, Balaji; Harrison, Ian F.; Ismail, Ozama; Holmes, Holly E.; Wells, Jack A.; Powell, Nick M.; O'Callaghan, James M.; O'Neill, Michael J.; Murray, Tracey K.; Ahmed, Zeshan; Collins, Emily C.; Johnson, Ross A.; Groves, Ashley; Lythgoe, Mark F.

2017-01-01

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 routinely acquired structural MR images. PMID:29163005

Adaptive texture filtering for defect inspection in ultrasound images

NASA Astrophysics Data System (ADS)

Zmola, Carl; Segal, Andrew C.; Lovewell, Brian; Nash, Charles

1993-05-01

The use of ultrasonic imaging to analyze defects and characterize materials is critical in the development of non-destructive testing and non-destructive evaluation (NDT/NDE) tools for manufacturing. To develop better quality control and reliability in the manufacturing environment advanced image processing techniques are useful. For example, through the use of texture filtering on ultrasound images, we have been able to filter characteristic textures from highly-textured C-scan images of materials. The materials have highly regular characteristic textures which are of the same resolution and dynamic range as other important features within the image. By applying texture filters and adaptively modifying their filter response, we have examined a family of filters for removing these textures.

Impact of fruit texture on the release and perception of aroma compounds during in vivo consumption using fresh and processed mango fruits.

PubMed

Bonneau, Adeline; Boulanger, Renaud; Lebrun, Marc; Maraval, Isabelle; Valette, Jérémy; Guichard, Élisabeth; Gunata, Ziya

2018-01-15

Two fresh (fresh cubic pieces, fresh puree) and two dried (dried cubic pieces, dried powder) products were prepared from a homogenous mango fruit batch to obtain four samples differing in texture. The aromatic profiles were determined by SAFE extraction technique and GC-MS analysis. VOCs released during consumption were trapped by a retronasal aroma-trapping device (RATD) and analysed by GC-MS. Twenty-one terpenes and one ester were identified from the exhaled nose-space. They were amongst the major mango volatile compounds, 10 of which were already reported as being potential key flavour compounds in mango. The in vivo release of aroma compounds was affected by the matrix texture. The intact samples (fresh and dried cubic pieces) released significantly more aroma compounds than disintegrated samples (fresh puree, dried powder). The sensory descriptive analysis findings were in close agreement with the in vivo aroma release data regarding fresh products, in contrast to the dried products. Copyright © 2017 Elsevier Ltd. All rights reserved.

Fast determination of the current loss mechanisms in textured crystalline Si-based solar cells

NASA Astrophysics Data System (ADS)

Nakane, Akihiro; Fujimoto, Shohei; Fujiwara, Hiroyuki

2017-11-01

A quite general device analysis method that allows the direct evaluation of optical and recombination losses in crystalline silicon (c-Si)-based solar cells has been developed. By applying this technique, the current loss mechanisms of the state-of-the-art solar cells with ˜20% efficiencies have been revealed. In the established method, the optical and electrical losses are characterized from the analysis of an experimental external quantum efficiency (EQE) spectrum with very low computational cost. In particular, we have performed the EQE analyses of textured c-Si solar cells by employing the experimental reflectance spectra obtained directly from the actual devices while using flat optical models without any fitting parameters. We find that the developed method provides almost perfect fitting to EQE spectra reported for various textured c-Si solar cells, including c-Si heterojunction solar cells, a dopant-free c-Si solar cell with a MoOx layer, and an n-type passivated emitter with rear locally diffused solar cell. The modeling of the recombination loss further allows the extraction of the minority carrier diffusion length and surface recombination velocity from the EQE analysis. Based on the EQE analysis results, the current loss mechanisms in different types of c-Si solar cells are discussed.

A Hydrodynamic Instability Is Used to Create Aesthetically Appealing Patterns in Painting

PubMed Central

Zetina, Sandra; Godínez, Francisco A.; Zenit, Roberto

2015-01-01

Painters often acquire a deep empirical knowledge of the way in which paints and inks behave. Through experimentation and practice, they can control the way in which fluids move and deform to create textures and images. David Alfaro Siqueiros, a recognized Mexican muralist, invented an accidental painting technique to create new and unexpected textures. By pouring layers of paint of different colors on a horizontal surface, the paints infiltrate into each other creating patterns of aesthetic value. In this investigation, we reproduce the technique in a controlled manner. We found that for the correct color combination, the dual viscous layer becomes Rayleigh-Taylor unstable: the density mismatch of the two color paints drives the formation of a spotted pattern. Experiments and a linear instability analysis were conducted to understand the properties of the process. We also argue that this flow configuration can be used to study the linear properties of this instability. PMID:25942586

Nonlinear histogram binning for quantitative analysis of lung tissue fibrosis in high-resolution CT data

NASA Astrophysics Data System (ADS)

Zavaletta, Vanessa A.; Bartholmai, Brian J.; Robb, Richard A.

2007-03-01

Diffuse lung diseases, such as idiopathic pulmonary fibrosis (IPF), can be characterized and quantified by analysis of volumetric high resolution CT scans of the lungs. These data sets typically have dimensions of 512 x 512 x 400. It is too subjective and labor intensive for a radiologist to analyze each slice and quantify regional abnormalities manually. Thus, computer aided techniques are necessary, particularly texture analysis techniques which classify various lung tissue types. Second and higher order statistics which relate the spatial variation of the intensity values are good discriminatory features for various textures. The intensity values in lung CT scans range between [-1024, 1024]. Calculation of second order statistics on this range is too computationally intensive so the data is typically binned between 16 or 32 gray levels. There are more effective ways of binning the gray level range to improve classification. An optimal and very efficient way to nonlinearly bin the histogram is to use a dynamic programming algorithm. The objective of this paper is to show that nonlinear binning using dynamic programming is computationally efficient and improves the discriminatory power of the second and higher order statistics for more accurate quantification of diffuse lung disease.

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

PubMed

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.

Bag-of-features approach for improvement of lung tissue classification in diffuse lung disease

NASA Astrophysics Data System (ADS)

Kato, Noriji; Fukui, Motofumi; Isozaki, Takashi

2009-02-01

Many automated techniques have been proposed to classify diffuse lung disease patterns. Most of the techniques utilize texture analysis approaches with second and higher order statistics, and show successful classification result among various lung tissue patterns. However, the approaches do not work well for the patterns with inhomogeneous texture distribution within a region of interest (ROI), such as reticular and honeycombing patterns, because the statistics can only capture averaged feature over the ROI. In this work, we have introduced the bag-of-features approach to overcome this difficulty. In the approach, texture images are represented as histograms or distributions of a few basic primitives, which are obtained by clustering local image features. The intensity descriptor and the Scale Invariant Feature Transformation (SIFT) descriptor are utilized to extract the local features, which have significant discriminatory power due to their specificity to a particular image class. In contrast, the drawback of the local features is lack of invariance under translation and rotation. We improved the invariance by sampling many local regions so that the distribution of the local features is unchanged. We evaluated the performance of our system in the classification task with 5 image classes (ground glass, reticular, honeycombing, emphysema, and normal) using 1109 ROIs from 211 patients. Our system achieved high classification accuracy of 92.8%, which is superior to that of the conventional system with the gray level co-occurrence matrix (GLCM) feature especially for inhomogeneous texture patterns.

Texture analysis applied to second harmonic generation image data for disease classification and development of a multi-view second harmonic generation imaging platform

NASA Astrophysics Data System (ADS)

Wen, Lianggong

Many diseases, e.g. ovarian cancer, breast cancer and pulmonary fibrosis, are commonly associated with drastic alterations in surrounding connective tissue, and changes in the extracellular matrix (ECM) are associated with the vast majority of cellular processes in disease progression and carcinogenesis: cell differentiation, proliferation, biosynthetic ability, polarity, and motility. We use second harmonic generation (SHG) microscopy for imaging the ECM because it is a non-invasive, non-linear laser scanning technique with high sensitivity and specificity for visualizing fibrillar collagen. In this thesis, we are interested in developing imaging techniques to understand how the ECM, especially the collagen architecture, is remodeled in diseases. To quantitate remodeling, we implement a 3D texture analysis to delineate the collagen fibrillar morphology observed in SHG microscopy images of human normal and high grade malignant ovarian tissues. In the learning stage, a dictionary of "textons"---frequently occurring texture features that are identified by measuring the image response to a filter bank of various shapes, sizes, and orientations---is created. By calculating a representative model based on the texton distribution for each tissue type using a training set of respective mages, we then perform classification between normal and high grade malignant ovarian tissues classification based on the area under receiver operating characteristic curves (true positives versus false positives). The local analysis algorithm is a more general method to probe rapidly changing fibrillar morphologies than global analyses such as FFT. It is also more versatile than other texture approaches as the filter bank can be highly tailored to specific applications (e.g., different disease states) by creating customized libraries based on common image features. Further, we describe the development of a multi-view 3D SHG imaging platform. Unlike fluorescence microscopy, SHG excites intrinsic characteristics of collagen, bypassing the need for additional primary and secondary imaging labels. However, single view image collection from endogenous SHG contrast of collagen molecules is not "a true 3D technique", because collagen fibers oriented along the plane of the lasers used to excite them are invisible to the excitation The loss of information means that researchers cannot resolve the 3D structure of the ECM using this technique. We are developing a new, multi-view approach that involves rotation of agarose embedded sample in FEP tubing, so that the excitation beam path travels to from multiple angles, to reveal new insight in understanding the 3D collagen structure and its role in normal and diseased tissue.

Quantification of Reflection Patterns in Ground-Penetrating Radar Data

NASA Astrophysics Data System (ADS)

Moysey, S.; Knight, R. J.; Jol, H. M.; Allen-King, R. M.; Gaylord, D. R.

2005-12-01

Radar facies analysis provides a way of interpreting the large-scale structure of the subsurface from ground-penetrating radar (GPR) data. Radar facies are often distinguished from each other by the presence of patterns, such as flat-lying, dipping, or chaotic reflections, in different regions of a radar image. When these patterns can be associated with radar facies in a repeated and predictable manner we refer to them as `radar textures'. While it is often possible to qualitatively differentiate between radar textures visually, pattern recognition tools, like neural networks, require a quantitative measure to discriminate between them. We investigate whether currently available tools, such as instantaneous attributes or metrics adapted from standard texture analysis techniques, can be used to improve the classification of radar facies. To this end, we use a neural network to perform cross-validation tests that assess the efficacy of different textural measures for classifying radar facies in GPR data collected from the William River delta, Saskatchewan, Canada. We found that the highest classification accuracies (>93%) were obtained for measures of texture that preserve information about the spatial arrangement of reflections in the radar image, e.g., spatial covariance. Lower accuracy (87%) was obtained for classifications based directly on windows of amplitude data extracted from the radar image. Measures that did not account for the spatial arrangement of reflections in the image, e.g., instantaneous attributes and amplitude variance, yielded classification accuracies of less than 65%. Optimal classifications were obtained for textural measures that extracted sufficient information from the radar data to discriminate between radar facies but were insensitive to other facies specific characteristics. For example, the rotationally invariant Fourier-Mellin transform delivered better classification results than the spatial covariance because dip angle of the reflections, but not dip direction, was an important discriminator between radar facies at the William River delta. To extend the use of radar texture beyond the identification of radar facies to sedimentary facies we are investigating how sedimentary features are encoded in GPR data at Borden, Ontario, Canada. At this site, we have collected extensive sedimentary and hydrologic data over the area imaged by GPR. Analysis of this data coupled with synthetic modeling of the radar signal has allowed us to develop insight into the generation of radar texture in complex geologic environments.

Combined elemental and microstructural analysis of genuine and fake copper-alloy coins

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bartoli, L; Agresti, J; Mascalchi, M

2011-07-31

Innovative noninvasive material analysis techniques are applied to determine archaeometallurgical characteristics of copper-alloy coins from Florence's National Museum of Archaeology. Three supposedly authentic Roman coins and three hypothetically fraudolent imitations are thoroughly investigated using laser-induced plasma spectroscopy and time of flight neutron diffraction along with 3D videomicroscopy and electron microscopy. Material analyses are aimed at collecting data allowing for objective discrimination between genuine Roman productions and late fakes. The results show the mentioned techniques provide quantitative compositional and textural data, which are strictly related to the manufacturing processes and aging of copper alloys. (laser applications)

2D virtual texture on 3D real object with coded structured light

NASA Astrophysics Data System (ADS)

Molinier, Thierry; Fofi, David; Salvi, Joaquim; Gorria, Patrick

2008-02-01

Augmented reality is used to improve color segmentation on human body or on precious no touch artifacts. We propose a technique to project a synthesized texture on real object without contact. Our technique can be used in medical or archaeological application. By projecting a suitable set of light patterns onto the surface of a 3D real object and by capturing images with a camera, a large number of correspondences can be found and the 3D points can be reconstructed. We aim to determine these points of correspondence between cameras and projector from a scene without explicit points and normals. We then project an adjusted texture onto the real object surface. We propose a global and automatic method to virtually texture a 3D real object.

Classification of fresh and frozen-thawed pork muscles using visible and near infrared hyperspectral imaging and textural analysis.

PubMed

Pu, Hongbin; Sun, Da-Wen; Ma, Ji; Cheng, Jun-Hu

2015-01-01

The potential of visible and near infrared hyperspectral imaging was investigated as a rapid and nondestructive technique for classifying fresh and frozen-thawed meats by integrating critical spectral and image features extracted from hyperspectral images in the region of 400-1000 nm. Six feature wavelengths (400, 446, 477, 516, 592 and 686 nm) were identified using uninformative variable elimination and successive projections algorithm. Image textural features of the principal component images from hyperspectral images were obtained using histogram statistics (HS), gray level co-occurrence matrix (GLCM) and gray level-gradient co-occurrence matrix (GLGCM). By these spectral and textural features, probabilistic neural network (PNN) models for classification of fresh and frozen-thawed pork meats were established. Compared with the models using the optimum wavelengths only, optimum wavelengths with HS image features, and optimum wavelengths with GLCM image features, the model integrating optimum wavelengths with GLGCM gave the highest classification rate of 93.14% and 90.91% for calibration and validation sets, respectively. Results indicated that the classification accuracy can be improved by combining spectral features with textural features and the fusion of critical spectral and textural features had better potential than single spectral extraction in classifying fresh and frozen-thawed pork meat. Copyright © 2014 Elsevier Ltd. All rights reserved.

Compositional and Textural Analysis of Maar-Diatreme Volcanic Deposits at Hopi Buttes Volcanic Field (AZ) Using GigaPan Panoramic and Thermal Infrared Imagery

NASA Astrophysics Data System (ADS)

Lee, R.; Graettinger, A. H.; Weinell, M.; Hughes, C. G.

2016-12-01

Basaltic maar-diatreme volcanoes are produced when rising magma interacts with groundwater and produces a maar crater at the ground surface. This crater is underlain by a diatreme, a downward-tapering conical structure filled with a mixture of fragments of intruded magma, fractured host rock, and clasts recycled through repeated discrete subsurface explosions. The debris of the diatreme records the mixing processes caused by subsurface explosions and is the source for ejected material that forms maar tephra rings. Determining the variable depths and lateral locations of these explosions and how energy is dissipated in the subsurface is critical to understanding how maar-diatreme eruptions progress. The Hopi Buttes Volcanic Field (HBVF) in the Navajo Nation, Arizona, USA, contains several diatremes and incised tephra rings with heterolithic clasts 10 mm - 10 m in size, and are well-exposed near-vertical to vertical outcrops. Our ability to measure the length scales and distribution of textures produced by subsurface explosions in these diatremes is limited by the physical accessibility of the exposures, due to both the verticality of the outcrops and the cultural sensitivity of the site. Quantifying the number and locations of explosions is dependent on our ability to investigate the full diatreme outcrop, and not just what can be accessed through traditional field observations. We present a novel field and computer-based technique for both quantitatively and qualitatively characterizing the composition and texture of maar-diatreme deposits in vertical outcrops. This technique uses a combination of field-collected multispectral thermal infrared (TIR) image data and visible wavelength GigaPan imagery to characterize the compositional and textural variations over a whole outcrop. To increase the spatial and spectral resolution of the TIR data, a super-resolution technique will be applied. The technique provides a simple and efficient method to augment the study of the maar-diatreme deposits at HBVF. In addition to contributing to a better understanding of the formation processes of maar-diatreme deposits around the world, the technique also shows great promise for studies involving other types of large outcrops and geologic structures.

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Ion beam texturing

NASA Technical Reports Server (NTRS)

Hudson, W. R.

1976-01-01

A microscopic surface texture is created by sputter etching a surface while simultaneously sputter depositing a lower sputter yield material onto the surface. A xenon ion beam source has been used to perform this texturing process on samples as large as three centimeters in diameter. Ion beam textured surface structures have been characterized with SEM photomicrographs for a large number of materials including Cu, Al, Si, Ti, Ni, Fe, Stainless steel, Au, and Ag. Surfaces have been textured using a variety of low sputter yield materials - Ta, Mo, Nb, and Ti. The initial stages of the texture creation have been documented, and the technique of ion beam sputter removal of any remaining deposited material has been studied. A number of other texturing parameters have been studied such as the variation of the texture with ion beam power, surface temperature, and the rate of texture growth with sputter etching time.

Near-infrared spectral image analysis of pork marbling based on Gabor filter and wide line detector techniques.

PubMed

Huang, Hui; Liu, Li; Ngadi, Michael O; Gariépy, Claude; Prasher, Shiv O

2014-01-01

Marbling is an important quality attribute of pork. Detection of pork marbling usually involves subjective scoring, which raises the efficiency costs to the processor. In this study, the ability to predict pork marbling using near-infrared (NIR) hyperspectral imaging (900-1700 nm) and the proper image processing techniques were studied. Near-infrared images were collected from pork after marbling evaluation according to current standard chart from the National Pork Producers Council. Image analysis techniques-Gabor filter, wide line detector, and spectral averaging-were applied to extract texture, line, and spectral features, respectively, from NIR images of pork. Samples were grouped into calibration and validation sets. Wavelength selection was performed on calibration set by stepwise regression procedure. Prediction models of pork marbling scores were built using multiple linear regressions based on derivatives of mean spectra and line features at key wavelengths. The results showed that the derivatives of both texture and spectral features produced good results, with correlation coefficients of validation of 0.90 and 0.86, respectively, using wavelengths of 961, 1186, and 1220 nm. The results revealed the great potential of the Gabor filter for analyzing NIR images of pork for the effective and efficient objective evaluation of pork marbling.

Characterization of crystallographic properties of thin films using X-ray diffraction

NASA Astrophysics Data System (ADS)

Zoo, Yeongseok

2007-12-01

Silver (Ag) has been recognized as one of promising candidates in Ultra-Large Scale Integrated (ULSI) applications in that it has the lowest bulk electrical resistivity of all pure metals and higher electromigration resistance than other interconnect materials. However, low thermal stability on Silicon Dioxide (Si02) at high temperatures (e.g., agglomeration) is considered a drawback for the Ag metallization scheme. Moreover, if a thin film is attached on a substrate, its properties may differ significantly from that of the bulk, since the properties of thin films can be significantly affected by the substrate. In this study, the Coefficient of Thermal Expansion (CTE) and texture evolution of Ag thin films on different substrates were characterized using various analytical techniques. The experimental results showed that the CTE of the Ag thin film was significantly affected by underlying substrate and the surface roughness of substrate. To investigate the alloying effect for Ag meatallization, small amounts of Copper (Cu) were added and characterized using theta-2theta X-ray Diffraction (XRD) scan and pole figure analysis. These XRD techniques are useful for investigating the primary texture of a metal film, (111) in this study, which (111) is the notation of a specific plane in the orthogonal coordinate system. They revealed that the (111) textures of Ag and Ag(Cu) thin films were enhanced with increasing temperature. Comparison of texture profiles between Ag and Ag(Cu) thin films showed that Cu additions enhanced (111) texture in Ag thin films. Accordingly, the texture enhancement in Ag thin films by Cu addition was discussed. Strained Silicon-On-Insulator (SSOI) is being considered as a potential substrate for Complementary Metal-Oxide-Semiconductor (CMOS) technology since the induced strain results in a significant improvement in device performance. High resolution X-ray diffraction (XRD) techniques were used to characterize the perpendicular and parallel strains in SSOI layers. XRD diffraction profiles generated from the crystalline SSOI layer provided a direct measurement of the layer's strain components. In addition, it has demonstrated that the rotational misalignment between the layer and the substrate can be incorporated within the biaxial strain equations for epitaxial layers. Based on these results, the strain behavior of the SSOI layer and the relation between strained Si and SiO2 layers are discussed for annealed samples.

Intelligent estimation of spatially distributed soil physical properties

USGS Publications Warehouse

Iwashita, F.; Friedel, M.J.; Ribeiro, G.F.; Fraser, Stephen J.

2012-01-01

Spatial analysis of soil samples is often times not possible when measurements are limited in number or clustered. To obviate potential problems, we propose a new approach based on the self-organizing map (SOM) technique. This approach exploits underlying nonlinear relation of the steady-state geomorphic concave-convex nature of hillslopes (from hilltop to bottom of the valley) to spatially limited soil textural data. The topographic features are extracted from Shuttle Radar Topographic Mission elevation data; whereas soil textural (clay, silt, and sand) and hydraulic data were collected in 29 spatially random locations (50 to 75. cm depth). In contrast to traditional principal component analysis, the SOM identifies relations among relief features, such as, slope, horizontal curvature and vertical curvature. Stochastic cross-validation indicates that the SOM is unbiased and provides a way to measure the magnitude of prediction uncertainty for all variables. The SOM cross-component plots of the soil texture reveals higher clay proportions at concave areas with convergent hydrological flux and lower proportions for convex areas with divergent flux. The sand ratio has an opposite pattern with higher values near the ridge and lower values near the valley. Silt has a trend similar to sand, although less pronounced. The relation between soil texture and concave-convex hillslope features reveals that subsurface weathering and transport is an important process that changed from loss-to-gain at the rectilinear hillslope point. These results illustrate that the SOM can be used to capture and predict nonlinear hillslope relations among relief, soil texture, and hydraulic conductivity data. ?? 2011 Elsevier B.V.

Automated analysis and classification of melanocytic tumor on skin whole slide images.

PubMed

Xu, Hongming; Lu, Cheng; Berendt, Richard; Jha, Naresh; Mandal, Mrinal

2018-06-01

This paper presents a computer-aided technique for automated analysis and classification of melanocytic tumor on skin whole slide biopsy images. The proposed technique consists of four main modules. First, skin epidermis and dermis regions are segmented by a multi-resolution framework. Next, epidermis analysis is performed, where a set of epidermis features reflecting nuclear morphologies and spatial distributions is computed. In parallel with epidermis analysis, dermis analysis is also performed, where dermal cell nuclei are segmented and a set of textural and cytological features are computed. Finally, the skin melanocytic image is classified into different categories such as melanoma, nevus or normal tissue by using a multi-class support vector machine (mSVM) with extracted epidermis and dermis features. Experimental results on 66 skin whole slide images indicate that the proposed technique achieves more than 95% classification accuracy, which suggests that the technique has the potential to be used for assisting pathologists on skin biopsy image analysis and classification. Copyright © 2018 Elsevier Ltd. All rights reserved.

Description of textures by a structural analysis.

PubMed

Tomita, F; Shirai, Y; Tsuji, S

1982-02-01

A structural analysis system for describing natural textures is introduced. The analyzer automatically extracts the texture elements in an input image, measures their properties, classifies them into some distinctive classes (one ``ground'' class and some ``figure'' classes), and computes the distributions of the gray level, the shape, and the placement of the texture elements in each class. These descriptions are used for classification of texture images. An analysis-by-synthesis method for evaluating texture analyzers is also presented. We propose a synthesizer which generates a texture image based on the descriptions. By comparing the reconstructed image with the original one, we can see what information is preserved and what is lost in the descriptions.

Crystallography of refractory metal nuggets in carbonaceous chondrites: A transmission Kikuchi diffraction approach

NASA Astrophysics Data System (ADS)

Daly, Luke; Bland, Phil A.; Dyl, Kathryn A.; Forman, Lucy V.; Saxey, David W.; Reddy, Steven M.; Fougerouse, Denis; Rickard, William D. A.; Trimby, Patrick W.; Moody, Steve; Yang, Limei; Liu, Hongwei; Ringer, Simon P.; Saunders, Martin; Piazolo, Sandra

2017-11-01

Transmission Kikuchi diffraction (TKD) is a relatively new technique that is currently being developed for geological sample analysis. This technique utilises the transmission capabilities of a scanning electron microscope (SEM) to rapidly and accurately map the crystallographic and geochemical features of an electron transparent sample. TKD uses a similar methodology to traditional electron backscatter diffraction (EBSD), but is capable of achieving a much higher spatial resolution (5-10 nm) (Trimby, 2012; Trimby et al., 2014). Here we apply TKD to refractory metal nuggets (RMNs) which are micrometre to sub-micrometre metal alloys composed of highly siderophile elements (HSEs) found in primitive carbonaceous chondrite meteorites. TKD allows us to analyse RMNs in situ, enabling the characterisation of nanometre-scale variations in chemistry and crystallography, whilst preserving their spatial and crystallographic context. This provides a complete representation of each RMN, permitting detailed interpretation of their formation history. We present TKD analysis of five transmission electron microscopy (TEM) lamellae containing RMNs coupled with EBSD and TEM analyses. These analyses revealed textures and relationships not previously observed in RMNs. These textures indicate some RMNs experienced annealing, forming twins. Some RMNs also acted as nucleation centres, and formed immiscible metal-silicate fluids. In fact, each RMN analysed in this study had different crystallographic textures. These RMNs also had heterogeneous compositions, even between RMNs contained within the same inclusion, host phase and even separated by only a few nanometres. Some RMNs are also affected by secondary processes at low temperature causing exsolution of molybdenite. However, most RMNs had crystallographic textures indicating that the RMN formed prior to their host inclusion. TKD analyses reveal most RMNs have been affected by processing in the protoplanetary disk. Despite this alteration, RMNs still preserve primary crystallographic textures and heterogeneous chemical signatures. This heterogeneity in crystallographic relationships, which mostly suggest that RMNs pre-date their host, is consistent with the idea that there is not a dominant RMN forming process. Each RMN has experienced a complex history, supporting the suggestion of Daly et al. (2017), that RMNs may preserve a diverse pre-solar chemical signature inherited from the Giant Molecular Cloud.

Volumetric characterization of human patellar cartilage matrix on phase contrast x-ray computed tomography

NASA Astrophysics Data System (ADS)

Abidin, Anas Z.; Nagarajan, Mahesh B.; Checefsky, Walter A.; Coan, Paola; Diemoz, Paul C.; Hobbs, Susan K.; Huber, Markus B.; Wismüller, Axel

2015-03-01

Phase contrast X-ray computed tomography (PCI-CT) has recently emerged as a novel imaging technique that allows visualization of cartilage soft tissue, subsequent examination of chondrocyte patterns, and their correlation to osteoarthritis. Previous studies have shown that 2D texture features are effective at distinguishing between healthy and osteoarthritic regions of interest annotated in the radial zone of cartilage matrix on PCI-CT images. In this study, we further extend the texture analysis to 3D and investigate the ability of volumetric texture features at characterizing chondrocyte patterns in the cartilage matrix for purposes of classification. Here, we extracted volumetric texture features derived from Minkowski Functionals and gray-level co-occurrence matrices (GLCM) from 496 volumes of interest (VOI) annotated on PCI-CT images of human patellar cartilage specimens. The extracted features were then used in a machine-learning task involving support vector regression to classify ROIs as healthy or osteoarthritic. Classification performance was evaluated using the area under the receiver operating characteristic (ROC) curve (AUC). The best classification performance was observed with GLCM features correlation (AUC = 0.83 +/- 0.06) and homogeneity (AUC = 0.82 +/- 0.07), which significantly outperformed all Minkowski Functionals (p < 0.05). These results suggest that such quantitative analysis of chondrocyte patterns in human patellar cartilage matrix involving GLCM-derived statistical features can distinguish between healthy and osteoarthritic tissue with high accuracy.

The relationships between residual stress relaxation and texture development in AZ31 Mg alloys via the vibratory stress relief technique

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Jia-Siang, E-mail: andy304312003@yahoo.com.tw; Hsieh, Chih-Chun, E-mail: jeromehsieh@gmail.com; Lai, Hsuan-Han, E-mail: g099066020@mail.nchu.edu.tw

2015-01-15

A systematic study of residual stress relaxation and the texture evolution of cold-rolled AZ31 Mg alloys using the vibratory stress relief technique with a simple cantilever beam vibration system was performed using a high-resolution X-ray diffractometer and a portable X-ray residual stress analyzer. The effects of vibrational stress excitation on the surface residual stress distribution and on the texture of pole figures (0002) occurring during the vibratory stress relief were examined. Compared with the effects corresponding to the same alloy under non-vibration condition, it can be observed that the uniform surface residual stress distribution and relaxation of the compressive residualmore » stress in the stress concentration zone were observed rather than all of the residual stresses being eliminated. Furthermore, with an increase in the vibrational aging time, the compressive residual stress, texture density, and (0002) preferred orientation increased first and then decreased. It should be underlined that the vibratory stress relief process for the vibrational aging time of more than 10 min is able to weaken the strong basal textures of AZ31 Mg alloys, which is valuable for enhancement of their formability and is responsible for an almost perfect 3D-Debye–Scherrer ring. - Highlights: • 3D-Debye ring about VSR technique is not discussed in the existing literature. • A newly developed VSR method is suitable for small or thin workpieces. • The cosα method accurately and effectively determines the residual stresses. • The VSR technique is valuable for enhancement of their formability. • The texture and preferred orientation change with the vibrational aging time.« less

Textural and Mineralogical Analysis of Volcanic Rocks by µ-XRF Mapping.

PubMed

Germinario, Luigi; Cossio, Roberto; Maritan, Lara; Borghi, Alessandro; Mazzoli, Claudio

2016-06-01

In this study, µ-XRF was applied as a novel surface technique for quick acquisition of elemental X-ray maps of rocks, image analysis of which provides quantitative information on texture and rock-forming minerals. Bench-top µ-XRF is cost-effective, fast, and non-destructive, can be applied to both large (up to a few tens of cm) and fragile samples, and yields major and trace element analysis with good sensitivity. Here, X-ray mapping was performed with a resolution of 103.5 µm and spot size of 30 µm over sample areas of about 5×4 cm of Euganean trachyte, a volcanic porphyritic rock from the Euganean Hills (NE Italy) traditionally used in cultural heritage. The relative abundance of phenocrysts and groundmass, as well as the size and shape of the various mineral phases, were obtained from image analysis of the elemental maps. The quantified petrographic features allowed identification of various extraction sites, revealing an objective method for archaeometric provenance studies exploiting µ-XRF imaging.

Material characterization and defect inspection in ultrasound images

NASA Astrophysics Data System (ADS)

Zmola, Carl; Segal, Andrew C.; Lovewell, Brian; Mahdavieh, Jacob; Ross, Joseph; Nash, Charles

1992-08-01

The use of ultrasonic imaging to analyze defects and characterize materials is critical in the development of non-destructive testing and non-destructive evaluation (NDT/NDE) tools for manufacturing. To develop better quality control and reliability in the manufacturing environment advanced image processing techniques are useful. For example, through the use of texture filtering on ultrasound images, we have been able to filter characteristic textures from highly textured C-scan images of materials. The materials have highly regular characteristic textures which are of the same resolution and dynamic range as other important features within the image. By applying texture filters and adaptively modifying their filter response, we have examined a family of filters for removing these textures.

POWTEX Neutron Diffractometer at FRM II - New Perspectives in Rock Deformation and Recrystallisation Analysis

NASA Astrophysics Data System (ADS)

Walter, J. M.; Stipp, M.; Ullemeyer, K.; Klein, H.; Leiss, B.; Hansen, B.; Kuhs, W. F.

2011-12-01

Neutron diffraction has become a routine method in Geoscience for the quantitative analysis of crystallographic preferred orientations (CPOs) and for (experimental) powder diffraction. Quantitative texture analysis is a common tool for the investigation of fabric development in mono- and polyphase rocks, their deformation histories and kinematics. Furthermore the quantitative characterization of anisotropic physical properties by bulk texture measurements can be achieved due to the high penetration capabilities of neutrons. To cope with increasing needs for beam time at neutron diffraction facilities with the corresponding technical characteristics and equipment, POWTEX (POWder and TEXture Diffractometer) is designed as a high-intensity diffractometer at the neutron research reactor FRM II in Garching, Germany by groups from the RWTH Aachen, Forschungszentrum Jülich and the University of Göttingen. Complementary to existing neutron diffractometers (SKAT at Dubna, Russia; GEM at ISIS, UK; HIPPO at Los Alamos, USA; D20 at ILL, France; and the local STRESS-SPEC and SPODI at FRM II) the layout of POWTEX is focused on fast (texture) measurements for either time-resolved experiments or the measurement of larger sample series as necessary for the study of large scale geological structures. By utilizing a range of neutron wavelengths simultaneously (TOF-technique), a high flux (~1 x 107 n/cm2s) and a high detector coverage ( 9.8 sr) effective texture measurements without sample tilting and rotation are possible. Furthermore the instrument and the angular detector resolution is sufficient for strong recrystallisation textures as well as weak textures of polyphase rocks. Thereby large sample environments will be implemented at POWTEX allowing in-situ time-resolved texture measurements during deformation experiments on rocksalt, ice and other materials. Furthermore a furnace for 3D-recrystallisation analysis of single grains will be realized complementary to the furnace that already exists for fine grained materials at the synchrotron beamline BW5 at HASYLAB, Germany (e.g. Klein et al. 2009). The in-situ triaxial deformation apparatus is operated by a uniaxial spindle drive with a maximum axial load of 200 kN, which will be redesigned to minimize shadowing effects on the detector. The HT experiments will be carried out in uniaxial compression or extension and an upgrade to triaxial deformation conditions is envisaged. The load frame can alternatively be used for ice deformation by inserting a cryostat cell for temperatures down to 77 K with a triaxial apparatus allowing also simple shear experiments on ice. Strain rates range between 10-8 and 10-3 s-1 reaching to at least 50 % axial strain. The furnace for the recrystallization analysis will be a mirror furnace with temperatures up to 1500° C, which will be rotatable around a vertical axis to obtain the required stereologic orientation information.

Ethyl 7-hydroxycoumarin-3-carboxylate derivatives: Synthesis, characterization and effect of liquid crystal properties

NASA Astrophysics Data System (ADS)

Srinivasa, H. T.; Palakshamurthy, B. S.; Mohammad, AbdulKarim-Talaq

2018-03-01

Two sets of new ethyl 7-hydroxycoumarin-3-carboxylate derivatives were synthesized and characterized to study the liquid crystalline properties. Chemical structures were confirmed by IR, NMR, CHN analysis techniques. Mesomarphic properties were accomplished by DSC, POM and X-ray studies. Density functional theory calculations and photophysical studies also performed. In the first set, smaller homologues of alkoxybenzoic acid derivatives exhibit monotropic smectic A (SmA) and higher homologous exhibit enantiotropic smectic A mesophase. The second set alkyl biphenyl derivatives exhibit stable SmA and nematic (N) mesophases. The well defined focal conic texture for SmA and threaded texture for nematic mesophases have been observed.

Beam modulation: A novel ToF-technique for high resolution diffraction at the Beamline for European Materials Engineering Research (BEER)

NASA Astrophysics Data System (ADS)

Rouijaa, M.; Kampmann, R.; Šaroun, J.; Fenske, J.; Beran, P.; Müller, M.; Lukáš, P.; Schreyer, A.

2018-05-01

The Beamline for European Materials Engineering Research (BEER) is under construction at the European Spallation Source (ESS) in Lund, Sweden. A basic requirement on BEER is to make best use of the long ESS pulse (2.86 ms) for engineering investigations. High-resolution diffraction, however, demands timing resolution up to 0.1% corresponding to a pulse length down to about 70 μs for the case of thermal neutrons (λ ∼ 1.8 Å). Such timing resolution can be achieved by pulse shaping techniques cutting a short section out of the long pulse, and thus paying for resolution by strong loss of intensity. In contrast to this, BEER proposes a novel operation mode called pulse modulation technique based on a new chopper design, which extracts several short pulses out of the long ESS pulse, and hence leads to a remarkable gain of intensity compared to nowadays existing conventional pulse shaping techniques. The potential of the new technique can be used with full advantage for investigating strains and textures of highly symmetric materials. Due to its instrument design and the high brilliance of the ESS pulse, BEER is expected to become the European flagship for engineering research for strain mapping and texture analysis.

Plasma-surface modification vs air oxidation on carbon obtained from peach stone: Textural and chemical changes and the efficiency as adsorbents

NASA Astrophysics Data System (ADS)

De Velasco Maldonado, Paola S.; Hernández-Montoya, Virginia; Montes-Morán, Miguel A.

2016-10-01

Carbons were prepared from peach stones (Prunus persica) using different carbonization temperatures (600, 800 and 1000 °C). A selected sample was modified by oxidation using conventional oxidation techniques (thermal treatment in air atmosphere) and with cold oxygen plasma oxidation, under different conditions. Samples were characterized using elemental analysis, FT-IR spectroscopy, nitrogen adsorption isotherms at -196 °C, SEM/EDX analysis, potentiometric titration and XPS analysis. Carbons with and without oxidation were employed in the adsorption of Pb2+ in aqueous solution. Results obtained indicated that the materials with high contents of acidic oxygen groups were more efficient in the removal of Pb2+, values as high as approx. 40 mg g-1 being obtained for the best performing carbon. Textural properties of the original, un-oxidized carbon were significantly altered only after oxidation under air atmosphere at 450 °C. On the other hand, the samples oxidized with plasma show little changes in the textural parameters and a slight increase in the specific surface was observed for the sample treated at high RF power (100 W). Additionally, a significant increment of the oxygen content was observed for the plasma oxidized samples, as measured by XPS.

The Development of Luminance- and Texture-Defined Form Perception during the School-Aged Years

ERIC Educational Resources Information Center

Bertone, Armando; Hanck, Julie; Guy, Jacalyn; Cornish, Kim

2010-01-01

The objective of the present study was to assess the development of luminance- and texture-defined static form perception in school-aged children. This was done using an adapted Landolt-C technique where C-optotypes were defined by either luminance or texture information, the latter necessitating extra-striate neural processing to be perceived.…

Use of feature extraction techniques for the texture and context information in ERTS imagery. [discrimination of land use categories in Kansas from MSS textural-spectral features

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Kelly, G. L. (Principal Investigator); Bosley, R. J.

1973-01-01

The author has identified the following significant results. The land use category of subimage regions over Kansas within an MSS image can be identified with an accuracy of about 70% using the textural-spectral features of the multi-images from the four MSS bands.

Ion beam sputter modification of the surface morphology of biological implants

NASA Technical Reports Server (NTRS)

Weigand, A. J.; Banks, B. A.

1976-01-01

The surface chemistry and texture of materials used for biological implants may significantly influence their performance and biocompatibility. Recent interest in the microscopic control of implant surface texture has led to the evaluation of ion beam sputtering as a potentially useful surface roughening technique. Ion sources, similar to electron bombardment ion thrusters designed for propulsive applications, are used to roughen the surfaces of various biocompatible alloys or polymer materials. These materials are typically used for dental implants, orthopedic prostheses, vascular prostheses, and artificial heart components. Masking techniques and resulting surface textures are described along with progress concerning evaluation of the biological response to the ion beam sputtered surfaces.

Ion-beam-sputter modification of the surface morphology of biological implants

NASA Technical Reports Server (NTRS)

Weigand, A. J.; Banks, B. A.

1977-01-01

The surface chemistry and texture of materials used for biological implants may significantly influence their performance and biocompatibility. Recent interest in the microscopic control of implant surface texture has led to the evaluation of ion-beam sputtering as a potentially useful surface roughening technique. Ion sources, similar to electron-bombardment ion thrusters designed for propulsive applications, are used to roughen the surfaces of various biocompatible alloys or polymer materials. These materials are typically used for dental implants, orthopedic prostheses, vascular prostheses, and artificial heart components. Masking techniques and resulting surface textures are described along with progress concerning evaluation of the biological response to the ion-beam-sputtered surfaces.

Efficient iris texture analysis method based on Gabor ordinal measures

NASA Astrophysics Data System (ADS)

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.

Stress-relaxation heat treatment in FeSiBNb amorphous alloy: Thermal, microstructure, nanomechanical and magnetic texture measurements

NASA Astrophysics Data System (ADS)

Lashgari, H. R.; Cadogan, J. M.; Kong, C.; Tang, C.; Doherty, C.; Chu, D.; Li, S.

2018-06-01

In the present study, the effect of stress-relaxation treatment (Tstress-relaxation < Tglass transition) on the magnetic texture, nanomechanical properties, and variation of free-volume in FeSiBNb amorphous alloy was investigated using Mössbauer spectroscopy, nanoindentation, dynamic mechanical analysis (DMA), and positron annihilation lifetime spectroscopy (PALS) techniques. It was shown that stress-relaxation treatment slightly improved the magnetic texture by 6% at T ≪Tg due to small-scale displacement of atoms whereas the magnetic texture was deteriorated due to thermal treatment at temperatures around the glass transition point (large-scale displacement of atoms). According to nanoindentation results, the hardness (H) and reduced modulus (Er) of the amorphous ribbon increased by 15% and 13%, respectively, after stress-relaxation treatment at 716 K for 5 min. Increasing the stress-relaxation time from 5 min to 60 min at 716 K resulted in decreases in the hardness and reduced modulus which are attributed to the increase of free-volume defects (increase of τ2 lifetime measured by PALS). Transmission electron microscopy (TEM) showed the formation of extremely fine embryos of α-Fe (3-5 nm in size) after stress-relaxation treatment.

Microstructural change in electroformed copper liners of shaped charges upon plastic deformation at ultra-high strain rate

NASA Astrophysics Data System (ADS)

Tian, W. H.; Hu, S. L.; Fan, A. L.; Wang, Z.

2002-01-01

Transmission electron microscopy (TEM) observations were carried out for examining the as-formed and post-deformed microstructures in a variety of electroformed copper liners of shaped charges. The deformation was carried out at an ultra-high strain rate. Specifically, the electron backscattering Kikuchi pattern (EBSP) technique was utilized to examine the micro-texture of these materials. TEM observations revealed that these electroformed copper liners of shaped charges have a grain size of about 1-3 mum, EBSP analysis demonstrated that the as-grown copper liners of shaped charges exhibit a l 10) fiber micro-texture which is parallel to the normal direction of the surface of the liners of shaped charges. Having undergone plastic deformation at ultra-high strain rate (10(7) s(-1)), the specimens which were recovered from the copper slugs were found to have grain size of the same order as that before deformation. EBSP analysis revealed that the (110) fiber texture existed in the as-formed copper liners disappears in the course of deformation. TEM examination results indicate that dynamic recovery and recrystallization play a significant role in this deformation process.

Impact-shocked zircons: discovery of shock-induced textures reflecting increasing degrees of shock metamorphism

USGS Publications Warehouse

Bohor, B.F.; Betterton, W.J.; Krogh, T.E.

1993-01-01

Textural effects specifically characteristic of shock metamorphism in zircons from impact environments have not been reported previously. However, planar deformation features (PDF) due to shock metamorphism are well documented in quartz and other mineral grains from these same environments. An etching technique was developed that allows SEM visualization of PDF and other probable shock-induced textural features, such as granular (polycrystalline) texture, in zircons from a variety of impact shock environments. These textural features in shocked zircons from K/T boundary distal ejecta form a series related to increasing degrees of shock that should correlate with proportionate resetting of the UPb isotopic system. ?? 1993.

Shape from texture: an evaluation of visual cues

NASA Astrophysics Data System (ADS)

Mueller, Wolfgang; Hildebrand, Axel

1994-05-01

In this paper an integrated approach is presented to understand and control the influence of texture on shape perception. Following Gibson's hypotheses, which states that texture is a mathematically and psychological sufficient stimulus for surface perception, we evaluate different perceptual cues. Starting out from a perception-based texture classification introduced by Tamura et al., we build up a uniform sampled parameter space. For the synthesis of some of our textures we use the texture description language HiLDTe. To acquire the desired texture specification we take advantage of a genetic algorithm. Employing these textures we practice a number of psychological tests to evaluate the significance of the different texture features. A comprehension of the results derived from the psychological tests is done to constitute new shape analyzing techniques. Since the vanishing point seems to be an important visual cue we introduce the Hough transform. A prospective of future work within the field of visual computing is provided within the final section.

Parenchymal Texture Analysis in Digital Breast Tomosynthesis for Breast Cancer Risk Estimation: A Preliminary Study

PubMed Central

Kontos, Despina; Bakic, Predrag R.; Carton, Ann-Katherine; Troxel, Andrea B.; Conant, Emily F.; Maidment, Andrew D.A.

2009-01-01

Rationale and Objectives Studies have demonstrated a relationship between mammographic parenchymal texture and breast cancer risk. Although promising, texture analysis in mammograms is limited by tissue superimposition. Digital breast tomosynthesis (DBT) is a novel tomographic x-ray breast imaging modality that alleviates the effect of tissue superimposition, offering superior parenchymal texture visualization compared to mammography. Our study investigates the potential advantages of DBT parenchymal texture analysis for breast cancer risk estimation. Materials and Methods DBT and digital mammography (DM) images of 39 women were analyzed. Texture features, shown in studies with mammograms to correlate with cancer risk, were computed from the retroareolar breast region. We compared the relative performance of DBT and DM texture features in correlating with two measures of breast cancer risk: (i) the Gail and Claus risk estimates, and (ii) mammographic breast density. Linear regression was performed to model the association between texture features and increasing levels of risk. Results No significant correlation was detected between parenchymal texture and the Gail and Claus risk estimates. Significant correlations were observed between texture features and breast density. Overall, the DBT texture features demonstrated stronger correlations with breast percent density (PD) than DM (p ≤0.05). When dividing our study population in groups of increasing breast PD, the DBT texture features appeared to be more discriminative, having regression lines with overall lower p-values, steeper slopes, and higher R2 estimates. Conclusion Although preliminary, our results suggest that DBT parenchymal texture analysis could provide more accurate characterization of breast density patterns, which could ultimately improve breast cancer risk estimation. PMID:19201357

Automated video-based assessment of surgical skills for training and evaluation in medical schools.

PubMed

Zia, Aneeq; Sharma, Yachna; Bettadapura, Vinay; Sarin, Eric L; Ploetz, Thomas; Clements, Mark A; Essa, Irfan

2016-09-01

Routine evaluation of basic surgical skills in medical schools requires considerable time and effort from supervising faculty. For each surgical trainee, a supervisor has to observe the trainees in person. Alternatively, supervisors may use training videos, which reduces some of the logistical overhead. All these approaches however are still incredibly time consuming and involve human bias. In this paper, we present an automated system for surgical skills assessment by analyzing video data of surgical activities. We compare different techniques for video-based surgical skill evaluation. We use techniques that capture the motion information at a coarser granularity using symbols or words, extract motion dynamics using textural patterns in a frame kernel matrix, and analyze fine-grained motion information using frequency analysis. We were successfully able to classify surgeons into different skill levels with high accuracy. Our results indicate that fine-grained analysis of motion dynamics via frequency analysis is most effective in capturing the skill relevant information in surgical videos. Our evaluations show that frequency features perform better than motion texture features, which in-turn perform better than symbol-/word-based features. Put succinctly, skill classification accuracy is positively correlated with motion granularity as demonstrated by our results on two challenging video datasets.

Ultrastructural characterization and Fourier analysis of fiber cell cytoplasm in the hyperbaric oxygen treated guinea pig lens opacification model.

PubMed

Freel, Christopher D; Gilliland, Kurt O; Mekeel, Harold E; Giblin, Frank J; Costello, M Joseph

2003-04-01

The structural characteristics of differentiated fiber cells in control and hyperbaric oxygen (HBO)-treated guinea pig lenses were examined by transmission electron microscopy (TEM). Emphasis was placed on cell damage, membrane integrity, and cytoplasmic texture. Given the faint gross opacities observed in HBO-treated lenses in previous studies, it was hypothesized that subtle but significant morphological differences due to oxidative damage exist between control and treated animals. Experimental animals received either 70 or 85 treatments with HBO (2.5 atm of 100% O(2) for 2.5 hr, 3 times per week for 5-7 months). All specimens were obtained within 24 hr of death. Freshly cut Vibratome lens sections were fixed and processed for low and high-magnification thin-section TEM analysis. Cytoplasmic texture was analyzed using Fourier and autocorrelation image processing techniques. Low-magnification analysis revealed relatively insignificant differences in general appearance between the fiber cells of the inner fetal and embryonic nuclei in control and HBO-treated guinea pigs. Both groups demonstrated cells of similar morphology with equivalent membrane complexity and homogeneous cytoplasmic texture. Evidence of any major cellular damage or extracellular space debris was not obvious. High-magnification analysis of the cytoplasm of the treated lenses exhibited a mild, yet detectable increase in texture compared with controls and was confirmed by Fourier analysis. Cytoplasmic texture increased in complexity with additional treatments. The absence of major cellular damage in the lenses of HBO-treated animals suggests a less conspicuous source of light scattering. The small changes in cytoplasmic organization observed between treated and control animals may entirely account for the increase in nuclear light scattering observed by slit lamp. The results obtained with this guinea pig/HBO model parallel many of the morphological data associated with human nuclear cataracts. The high-angle scattering observed in the lens of the HBO-treated guinea pig may represent the type of cytoplasmic reorganization that occurs with mild oxidation, effectively making it a valuable model for human lens aging.

MRI texture analysis (MRTA) of T2-weighted images in Crohn's disease may provide information on histological and MRI disease activity in patients undergoing ileal resection.

PubMed

Makanyanga, Jesica; Ganeshan, Balaji; Rodriguez-Justo, Manuel; Bhatnagar, Gauraang; Groves, Ashley; Halligan, Steve; Miles, Ken; Taylor, Stuart A

2017-02-01

To associate MRI textural analysis (MRTA) with MRI and histological Crohn's disease (CD) activity. Sixteen patients (mean age 39.5 years, 9 male) undergoing MR enterography before ileal resection were retrospectively analysed. Thirty-six small (≤3 mm) ROIs were placed on T2-weighted images and location-matched histological acute inflammatory scores (AIS) measured. MRI activity (mural thickness, T2 signal, T1 enhancement) (CDA) was scored in large ROIs. MRTA features (mean, standard deviation, mean of positive pixels (MPP), entropy, kurtosis, skewness) were extracted using a filtration histogram technique. Spatial scale filtration (SSF) ranged from 2 to 5 mm. Regression (linear/logistic) tested associations between MRTA and AIS (small ROIs), and CDA/constituent parameters (large ROIs). Skewness (SSF = 2 mm) was associated with AIS [regression coefficient (rc) 4.27, p = 0.02]. Of 120 large ROI analyses (for each MRI, MRTA feature and SSF), 15 were significant. Entropy (SSF = 2, 3 mm) and kurtosis (SSF = 3 mm) were associated with CDA (rc 0.9, 1.0, -0.45, p = 0.006-0.01). Entropy and mean (SSF = 2-4 mm) were associated with T2 signal [odds ratio (OR) 2.32-3.16, p = 0.02-0.004], [OR 1.22-1.28, p = 0.03-0.04]. MPP (SSF = 2 mm) was associated with mural thickness (OR 0.91, p = 0.04). Kurtosis (SSF = 3 mm), standard deviation (SSF = 5 mm) were associated with decreased T1 enhancement (OR 0.59, 0.42, p = 0.004, 0.007). MRTA features may be associated with CD activity. • MR texture analysis features may be associated with Crohn's disease histological activity. • Texture analysis features may correlate with MR-dependent Crohn's disease activity scores. • The utility of MR texture analysis in Crohn's disease merits further investigation.

Compositional and textural information from the dual inversion of visible, near and thermal infrared remotely sensed data

NASA Technical Reports Server (NTRS)

Brackett, Robert A.; Arvidson, Raymond E.

1993-01-01

A technique is presented that allows extraction of compositional and textural information from visible, near and thermal infrared remotely sensed data. Using a library of both emissivity and reflectance spectra, endmember abundances and endmember thermal inertias are extracted from AVIRIS (Airborne Visible and Infrared Imaging Spectrometer) and TIMS (Thermal Infrared Mapping Spectrometer) data over Lunar Crater Volcanic Field, Nevada, using a dual inversion. The inversion technique is motivated by upcoming Mars Observer data and the need for separation of composition and texture parameters from sub pixel mixtures of bedrock and dust. The model employed offers the opportunity to extract compositional and textural information for a variety of endmembers within a given pixel. Geologic inferences concerning grain size, abundance, and source of endmembers can be made directly from the inverted data. These parameters are of direct relevance to Mars exploration, both for Mars Observer and for follow-on missions.

Photogrammetry of the three-dimensional shape and texture of a nanoscale particle using scanning electron microscopy and free software.

PubMed

Gontard, Lionel C; Schierholz, Roland; Yu, Shicheng; Cintas, Jesús; Dunin-Borkowski, Rafal E

2016-10-01

We apply photogrammetry in a scanning electron microscope (SEM) to study the three-dimensional shape and surface texture of a nanoscale LiTi2(PO4)3 particle. We highlight the fact that the technique can be applied non-invasively in any SEM using free software (freeware) and does not require special sample preparation. Three-dimensional information is obtained in the form of a surface mesh, with the texture of the sample stored as a separate two-dimensional image (referred to as a UV Map). The mesh can be used to measure parameters such as surface area, volume, moment of inertia and center of mass, while the UV map can be used to study the surface texture using conventional image processing techniques. We also illustrate the use of 3D printing to visualize the reconstructed model. Copyright © 2016 Elsevier B.V. All rights reserved.

Multi-texture local ternary pattern for face recognition

NASA Astrophysics Data System (ADS)

Essa, Almabrok; Asari, Vijayan

2017-05-01

In imagery and pattern analysis domain a variety of descriptors have been proposed and employed for different computer vision applications like face detection and recognition. Many of them are affected under different conditions during the image acquisition process such as variations in illumination and presence of noise, because they totally rely on the image intensity values to encode the image information. To overcome these problems, a novel technique named Multi-Texture Local Ternary Pattern (MTLTP) is proposed in this paper. MTLTP combines the edges and corners based on the local ternary pattern strategy to extract the local texture features of the input image. Then returns a spatial histogram feature vector which is the descriptor for each image that we use to recognize a human being. Experimental results using a k-nearest neighbors classifier (k-NN) on two publicly available datasets justify our algorithm for efficient face recognition in the presence of extreme variations of illumination/lighting environments and slight variation of pose conditions.

A Clinical Decision Support System Using Ultrasound Textures and Radiologic Features to Distinguish Metastasis From Tumor-Free Cervical Lymph Nodes in Patients With Papillary Thyroid Carcinoma.

PubMed

Abbasian Ardakani, Ali; Reiazi, Reza; Mohammadi, Afshin

2018-03-30

This study investigated the potential of a clinical decision support approach for the classification of metastatic and tumor-free cervical lymph nodes (LNs) in papillary thyroid carcinoma on the basis of radiologic and textural analysis through ultrasound (US) imaging. In this research, 170 metastatic and 170 tumor-free LNs were examined by the proposed clinical decision support method. To discover the difference between the groups, US imaging was used for the extraction of radiologic and textural features. The radiologic features in the B-mode scans included the echogenicity, margin, shape, and presence of microcalcification. To extract the textural features, a wavelet transform was applied. A support vector machine classifier was used to classify the LNs. In the training set data, a combination of radiologic and textural features represented the best performance with sensitivity, specificity, accuracy, and area under the curve (AUC) values of 97.14%, 98.57%, 97.86%, and 0.994, respectively, whereas the classification based on radiologic and textural features alone yielded lower performance, with AUCs of 0.964 and 0.922. On testing the data set, the proposed model could classify the tumor-free and metastatic LNs with an AUC of 0.952, which corresponded to sensitivity, specificity, and accuracy of 93.33%, 96.66%, and 95.00%. The clinical decision support method based on textural and radiologic features has the potential to characterize LNs via 2-dimensional US. Therefore, it can be used as a supplementary technique in daily clinical practice to improve radiologists' understanding of conventional US imaging for characterizing LNs. © 2018 by the American Institute of Ultrasound in Medicine.

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

PubMed

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 <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. • 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.

A Fourier-based textural feature extraction procedure

NASA Technical Reports Server (NTRS)

Stromberg, W. D.; Farr, T. G.

1986-01-01

A procedure is presented to discriminate and characterize regions of uniform image texture. The procedure utilizes textural features consisting of pixel-by-pixel estimates of the relative emphases of annular regions of the Fourier transform. The utility and derivation of the features are described through presentation of a theoretical justification of the concept followed by a heuristic extension to a real environment. Two examples are provided that validate the technique on synthetic images and demonstrate its applicability to the discrimination of geologic texture in a radar image of a tropical vegetated area.

Gabor filter for the segmentation of skin lesions from ultrasonographic images

NASA Astrophysics Data System (ADS)

Petrella, Lorena I.; Gómez, W.; Alvarenga, André V.; Pereira, Wagner C. A.

2012-05-01

The present work applies Gabor filters bank for texture analysis of skin lesions images, obtained by ultrasound biomicroscopy. The regions affected by the lesions were differentiated from surrounding tissue in all the analyzed cases; however the accuracy of the traced borders showed some limitations in part of the images. Future steps are being contemplated, attempting to enhance the technique performance.

Analysis and interpretation of diffraction data from complex, anisotropic materials

NASA Astrophysics Data System (ADS)

Tutuncu, Goknur

Most materials are elastically anisotropic and exhibit additional anisotropy beyond elastic deformation. For instance, in ferroelectric materials the main inelastic deformation mode is via domains, which are highly anisotropic crystallographic features. To quantify this anisotropy of ferroelectrics, advanced X-ray and neutron diffraction methods were employed. Extensive sets of data were collected from tetragonal BaTiO3, PZT and other ferroelectric ceramics. Data analysis was challenging due to the complex constitutive behavior of these materials. To quantify the elastic strain and texture evolution in ferroelectrics under loading, a number of data analysis techniques such as the single peak and Rietveld methods were used and their advantages and disadvantages compared. It was observed that the single peak analysis fails at low peak intensities especially after domain switching while the Rietveld method does not account for lattice strain anisotropy although it overcomes the low intensity problem via whole pattern analysis. To better account for strain anisotropy the constant stress (Reuss) approximation was employed within the Rietveld method and new formulations to estimate lattice strain were proposed. Along the way, new approaches for handling highly anisotropic lattice strain data were also developed and applied. All of the ceramics studied exhibited significant changes in their crystallographic texture after loading indicating non-180° domain switching. For a full interpretation of domain switching the spherical harmonics method was employed in Rietveld. A procedure for simultaneous refinement of multiple data sets was established for a complete texture analysis. To further interpret diffraction data, a solid mechanics model based on the self-consistent approach was used in calculating lattice strain and texture evolution during the loading of a polycrystalline ferroelectric. The model estimates both the macroscopic average response of a specimen and its hkl-dependent lattice strains for different reflections. It also tracks the number of grains (or domains) contributing to each reflection and allows for domain switching. The agreement between the model and experimental data was found to be satisfactory.

POWTEX Neutron Diffractometer at FRM II - New Perspectives for In-Situ Rock Deformation Analysis

NASA Astrophysics Data System (ADS)

Walter, J. M.; Stipp, M.; Ullemeyer, K.; Klein, H.; Leiss, B.; Hansen, B. T.; Kuhs, W. F.

2012-04-01

In Geoscience quantitative texture analysis here defined as the quantitative analysis of the crystallographic preferred orientation (CPO), is a common tool for the investigation of fabric development in mono- and polyphase rocks, their deformation histories and kinematics. Bulk texture measurements also allow the quantitative characterisation of the anisotropic physical properties of rock materials. A routine tool to measure bulk sample volumes is neutron texture diffraction, as neutrons have large penetration capabilities of several cm in geological sample materials. The new POWTEX (POWder and TEXture) Diffractometer at the neutron research reactor FRM II in Garching, Germany is designed as a high-intensity diffractometer by groups from the RWTH Aachen, Forschungszentrum Jülich and the University of Göttingen. Complementary to existing neutron diffractometers (SKAT at Dubna, Russia; GEM at ISIS, UK; HIPPO at Los Alamos, USA; D20 at ILL, France; and the local STRESS-SPEC and SPODI at FRM II) the layout of POWTEX is focused on fast time-resolved experiments and the measurement of larger sample series as necessary for the study of large scale geological structures. POWTEX is a dedicated beam line for geoscientific research. Effective texture measurements without sample tilting and rotation are possible firstly by utilizing a range of neutron wavelengths simultaneously (Time-of-Flight technique) and secondly by the high detector coverage (9.8 sr) and a high flux (~1 - 107 n/cm2s) at the sample. Furthermore the instrument and the angular detector resolution is designed also for strong recrystallisation textures as well as for weak textures of polyphase rocks. These instrument characteristics allow in-situ time-resolved texture measurements during deformation experiments on rocksalt, ice and other materials as large sample environments will be implemented at POWTEX. The in-situ deformation apparatus is operated by a uniaxial spindle drive with a maximum axial load of 250 kN, which will be redesigned to minimize shadowing effects inside the cylindrical detector. The HT deformatione experiments will be carried out in uniaxial compression or extension and an upgrade to triaxial deformation conditions is envisaged. The load frame can alternatively be used for ice deformation by inserting a cryostat cell for temperatures down to 77 K with a triaxial apparatus allowing also simple shear experiments on ice. Strain rates range between 10-8 and 10-3 s-1 reaching to at least 50 % axial strain. The deformation apparatus is designed for continuous long-term deformation experiments and can be exchanged between in-situ and ex-situ placements during continuous operation inside and outside the neutron detector.

Structural coloration of metallic surfaces with micro/nano-structures induced by elliptical vibration texturing

NASA Astrophysics Data System (ADS)

Yang, Yang; Pan, Yayue; Guo, Ping

2017-04-01

Creating orderly periodic micro/nano-structures on metallic surfaces, or structural coloration, for control of surface apparent color and optical reflectivity has been an exciting research topic over the years. The direct applications of structural coloration include color marking, display devices, and invisibility cloak. This paper presents an efficient method to colorize metallic surfaces with periodic micro/nano-gratings using elliptical vibration texturing. When the tool vibration is coupled with a constant cutting velocity, controlled periodic ripples can be generated due to the overlapping tool trajectory. These periodic ripples with a wavelength near visible spectrum can act as micro-gratings to introduce iridescent colors. The proposed technique also provides a flexible method for color marking of metallic surfaces with arbitrary patterns and images by precise control of the spacing distance and orientation of induced micro/nano-ripples. Theoretical analysis and experimental results are given to demonstrate structural coloration of metals by a direct mechanical machining technique.

Study of CT image texture using deep learning techniques

NASA Astrophysics Data System (ADS)

Dutta, Sandeep; Fan, Jiahua; Chevalier, David

2018-03-01

For CT imaging, reduction of radiation dose while improving or maintaining image quality (IQ) is currently a very active research and development topic. Iterative Reconstruction (IR) approaches have been suggested to be able to offer better IQ to dose ratio compared to the conventional Filtered Back Projection (FBP) reconstruction. However, it has been widely reported that often CT image texture from IR is different compared to that from FBP. Researchers have proposed different figure of metrics to quantitate the texture from different reconstruction methods. But there is still a lack of practical and robust method in the field for texture description. This work applied deep learning method for CT image texture study. Multiple dose scans of a 20cm diameter cylindrical water phantom was performed on Revolution CT scanner (GE Healthcare, Waukesha) and the images were reconstructed with FBP and four different IR reconstruction settings. The training images generated were randomly allotted (80:20) to a training and validation set. An independent test set of 256-512 images/class were collected with the same scan and reconstruction settings. Multiple deep learning (DL) networks with Convolution, RELU activation, max-pooling, fully-connected, global average pooling and softmax activation layers were investigated. Impact of different image patch size for training was investigated. Original pixel data as well as normalized image data were evaluated. DL models were reliably able to classify CT image texture with accuracy up to 99%. Results show that the deep learning techniques suggest that CT IR techniques may help lower the radiation dose compared to FBP.

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

NASA Astrophysics Data System (ADS)

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, including texture movie animations, are used from both plutonic and volcanic systems to highlight the roll of this approach towards a goal of true 3D textural analysis.

A spherical harmonic approach for the determination of HCP texture from ultrasound: A solution to the inverse problem

NASA Astrophysics Data System (ADS)

Lan, Bo; Lowe, Michael J. S.; Dunne, Fionn P. E.

2015-10-01

A new spherical convolution approach has been presented which couples HCP single crystal wave speed (the kernel function) with polycrystal c-axis pole distribution function to give the resultant polycrystal wave speed response. The three functions have been expressed as spherical harmonic expansions thus enabling application of the de-convolution technique to enable any one of the three to be determined from knowledge of the other two. Hence, the forward problem of determination of polycrystal wave speed from knowledge of single crystal wave speed response and the polycrystal pole distribution has been solved for a broad range of experimentally representative HCP polycrystal textures. The technique provides near-perfect representation of the sensitivity of wave speed to polycrystal texture as well as quantitative prediction of polycrystal wave speed. More importantly, a solution to the inverse problem is presented in which texture, as a c-axis distribution function, is determined from knowledge of the kernel function and the polycrystal wave speed response. It has also been explained why it has been widely reported in the literature that only texture coefficients up to 4th degree may be obtained from ultrasonic measurements. Finally, the de-convolution approach presented provides the potential for the measurement of polycrystal texture from ultrasonic wave speed measurements.

Texture classification of normal tissues in computed tomography using Gabor filters

NASA Astrophysics Data System (ADS)

Dettori, Lucia; Bashir, Alia; Hasemann, Julie

2007-03-01

The research presented in this article is aimed at developing an automated imaging system for classification of normal tissues in medical images obtained from Computed Tomography (CT) scans. Texture features based on a bank of Gabor filters are used to classify the following tissues of interests: liver, spleen, kidney, aorta, trabecular bone, lung, muscle, IP fat, and SQ fat. The approach consists of three steps: convolution of the regions of interest with a bank of 32 Gabor filters (4 frequencies and 8 orientations), extraction of two Gabor texture features per filter (mean and standard deviation), and creation of a Classification and Regression Tree-based classifier that automatically identifies the various tissues. The data set used consists of approximately 1000 DIACOM images from normal chest and abdominal CT scans of five patients. The regions of interest were labeled by expert radiologists. Optimal trees were generated using two techniques: 10-fold cross-validation and splitting of the data set into a training and a testing set. In both cases, perfect classification rules were obtained provided enough images were available for training (~65%). All performance measures (sensitivity, specificity, precision, and accuracy) for all regions of interest were at 100%. This significantly improves previous results that used Wavelet, Ridgelet, and Curvelet texture features, yielding accuracy values in the 85%-98% range The Gabor filters' ability to isolate features at different frequencies and orientations allows for a multi-resolution analysis of texture essential when dealing with, at times, very subtle differences in the texture of tissues in CT scans.

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

PubMed

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

2015-09-01

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

Impact-shocked zircons: Discovery of shock-induced textures reflecting increasing degrees of shock metamorphism

NASA Technical Reports Server (NTRS)

Bohor, B. F.; Betterton, W. J.; Krogh, T. E.

1993-01-01

Textural effects specifically characteristic of shock metamorphism in zircons from impact environments have not been reported previously. However, planar deformation features (PDF) due to shock metamorphism are well documented in quartz and other mineral grains from these same environments. An etching technique was developed that allows scanning electron microscope (SEM) visualization of PDF and other probable shock-induced textural features, such as granular (polycrystalline) texture, in zircons from a variety of impact shock environments. These textural features in shocked zircons from K/T boundary distal ejecta form a series related to increasing degrees of shock that should correlate with proportionate resetting of the U-Pb isotopic system.

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

NASA Astrophysics Data System (ADS)

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.

Texturing of concrete pavements : interim report No. 2.

DOT National Transportation Integrated Search

1976-09-01

The purpose of this research study is to document and evaluate the findings of the Category II experimental concrete texturing project. Under this plan of experimental study, several texting techniques were tried and will be compared in order to dete...

Texture analysis of apparent diffusion coefficient maps for treatment response assessment in prostate cancer bone metastases-A pilot study.

PubMed

Reischauer, Carolin; Patzwahl, René; Koh, Dow-Mu; Froehlich, Johannes M; Gutzeit, Andreas

2018-04-01

To evaluate whole-lesion volumetric texture analysis of apparent diffusion coefficient (ADC) maps for assessing treatment response in prostate cancer bone metastases. Texture analysis is performed in 12 treatment-naïve patients with 34 metastases before treatment and at one, two, and three months after the initiation of androgen deprivation therapy. Four first-order and 19 second-order statistical texture features are computed on the ADC maps in each lesion at every time point. Repeatability, inter-patient variability, and changes in the feature values under therapy are investigated. Spearman rank's correlation coefficients are calculated across time to demonstrate the relationship between the texture features and the serum prostate specific antigen (PSA) levels. With few exceptions, the texture features exhibited moderate to high precision. At the same time, Friedman's tests revealed that all first-order and second-order statistical texture features changed significantly in response to therapy. Thereby, the majority of texture features showed significant changes in their values at all post-treatment time points relative to baseline. Bivariate analysis detected significant correlations between the great majority of texture features and the serum PSA levels. Thereby, three first-order and six second-order statistical features showed strong correlations with the serum PSA levels across time. The findings in the present work indicate that whole-tumor volumetric texture analysis may be utilized for response assessment in prostate cancer bone metastases. The approach may be used as a complementary measure for treatment monitoring in conjunction with averaged ADC values. Copyright © 2018 Elsevier B.V. All rights reserved.

Breast cancer detection in rotational thermography images using texture features

NASA Astrophysics Data System (ADS)

Francis, Sheeja V.; Sasikala, M.; Bhavani Bharathi, G.; Jaipurkar, Sandeep D.

2014-11-01

Breast cancer is a major cause of mortality in young women in the developing countries. Early diagnosis is the key to improve survival rate in cancer patients. Breast thermography is a diagnostic procedure that non-invasively images the infrared emissions from breast surface to aid in the early detection of breast cancer. Due to limitations in imaging protocol, abnormality detection by conventional breast thermography, is often a challenging task. Rotational thermography is a novel technique developed in order to overcome the limitations of conventional breast thermography. This paper evaluates this technique's potential for automatic detection of breast abnormality, from the perspective of cold challenge. Texture features are extracted in the spatial domain, from rotational thermogram series, prior to and post the application of cold challenge. These features are fed to a support vector machine for automatic classification of normal and malignant breasts, resulting in a classification accuracy of 83.3%. Feature reduction has been performed by principal component analysis. As a novel attempt, the ability of this technique to locate the abnormality has been studied. The results of the study indicate that rotational thermography holds great potential as a screening tool for breast cancer detection.

The use of morphological characteristics and texture analysis in the identification of tissue composition in prostatic neoplasia.

PubMed

Diamond, James; Anderson, Neil H; Bartels, Peter H; Montironi, Rodolfo; Hamilton, Peter W

2004-09-01

Quantitative examination of prostate histology offers clues in the diagnostic classification of lesions and in the prediction of response to treatment and prognosis. To facilitate the collection of quantitative data, the development of machine vision systems is necessary. This study explored the use of imaging for identifying tissue abnormalities in prostate histology. Medium-power histological scenes were recorded from whole-mount radical prostatectomy sections at x 40 objective magnification and assessed by a pathologist as exhibiting stroma, normal tissue (nonneoplastic epithelial component), or prostatic carcinoma (PCa). A machine vision system was developed that divided the scenes into subregions of 100 x 100 pixels and subjected each to image-processing techniques. Analysis of morphological characteristics allowed the identification of normal tissue. Analysis of image texture demonstrated that Haralick feature 4 was the most suitable for discriminating stroma from PCa. Using these morphological and texture measurements, it was possible to define a classification scheme for each subregion. The machine vision system is designed to integrate these classification rules and generate digital maps of tissue composition from the classification of subregions; 79.3% of subregions were correctly classified. Established classification rates have demonstrated the validity of the methodology on small scenes; a logical extension was to apply the methodology to whole slide images via scanning technology. The machine vision system is capable of classifying these images. The machine vision system developed in this project facilitates the exploration of morphological and texture characteristics in quantifying tissue composition. It also illustrates the potential of quantitative methods to provide highly discriminatory information in the automated identification of prostatic lesions using computer vision.

Segmentation Approach Towards Phase-Contrast Microscopic Images of Activated Sludge to Monitor the Wastewater Treatment.

PubMed

Khan, Muhammad Burhan; Nisar, Humaira; Ng, Choon Aun; Yeap, Kim Ho; Lai, Koon Chun

2017-12-01

Image processing and analysis is an effective tool for monitoring and fault diagnosis of activated sludge (AS) wastewater treatment plants. The AS image comprise of flocs (microbial aggregates) and filamentous bacteria. In this paper, nine different approaches are proposed for image segmentation of phase-contrast microscopic (PCM) images of AS samples. The proposed strategies are assessed for their effectiveness from the perspective of microscopic artifacts associated with PCM. The first approach uses an algorithm that is based on the idea that different color space representation of images other than red-green-blue may have better contrast. The second uses an edge detection approach. The third strategy, employs a clustering algorithm for the segmentation and the fourth applies local adaptive thresholding. The fifth technique is based on texture-based segmentation and the sixth uses watershed algorithm. The seventh adopts a split-and-merge approach. The eighth employs Kittler's thresholding. Finally, the ninth uses a top-hat and bottom-hat filtering-based technique. The approaches are assessed, and analyzed critically with reference to the artifacts of PCM. Gold approximations of ground truth images are prepared to assess the segmentations. Overall, the edge detection-based approach exhibits the best results in terms of accuracy, and the texture-based algorithm in terms of false negative ratio. The respective scenarios are explained for suitability of edge detection and texture-based algorithms.

Texture generation for use in synthetic infrared scenes

NASA Astrophysics Data System (ADS)

Ota, Clem Z.; Rollins, John M.; Bleiweiss, Max P.

1996-06-01

In the process of creating synthetic scenes for use in simulations/visualizations, texture is used as a surrogate to 'high' spatial definition. For example, if one were to measure the location of every blade of grass and all of the characteristics of each blade of grass in a lawn, then in the process of composing a scene of the lawn, it would be expected that the result would appear 'real;' however, because this process is excruciatingly laborious, various techniques have been devised to place the required details in the scene through the use of texturing. Experience gained during the recent Smart Weapons Operability Enhancement Joint Test and Evaluation (SWOE JT&E) has shown the need for higher fidelity texturing algorithms and a better parameterization of those that are in use. In this study, four aspects of the problem have been analyzed: texture extraction, texture insertion, texture metrics, and texture creation algorithms. The results of extracting real texture from an image, measuring it with a variety of metrics, and generating similar texture with three different algorithms is presented. These same metrics can be used to define clutter and to make comparisons between 'real' and synthetic (or artificial) scenes in an objective manner.

Conjoint representation of texture ensemble and location in the parahippocampal place area.

PubMed

Park, Jeongho; Park, Soojin

2017-04-01

Texture provides crucial information about the category or identity of a scene. Nonetheless, not much is known about how the texture information in a scene is represented in the brain. Previous studies have shown that the parahippocampal place area (PPA), a scene-selective part of visual cortex, responds to simple patches of texture ensemble. However, in natural scenes textures exist in spatial context within a scene. Here we tested two hypotheses that make different predictions on how textures within a scene context are represented in the PPA. The Texture-Only hypothesis suggests that the PPA represents texture ensemble (i.e., the kind of texture) as is, irrespective of its location in the scene. On the other hand, the Texture and Location hypothesis suggests that the PPA represents texture and its location within a scene (e.g., ceiling or wall) conjointly. We tested these two hypotheses across two experiments, using different but complementary methods. In experiment 1 , by using multivoxel pattern analysis (MVPA) and representational similarity analysis, we found that the representational similarity of the PPA activation patterns was significantly explained by the Texture-Only hypothesis but not by the Texture and Location hypothesis. In experiment 2 , using a repetition suppression paradigm, we found no repetition suppression for scenes that had the same texture ensemble but differed in location (supporting the Texture and Location hypothesis). On the basis of these results, we propose a framework that reconciles contrasting results from MVPA and repetition suppression and draw conclusions about how texture is represented in the PPA. NEW & NOTEWORTHY This study investigates how the parahippocampal place area (PPA) represents texture information within a scene context. We claim that texture is represented in the PPA at multiple levels: the texture ensemble information at the across-voxel level and the conjoint information of texture and its location at the within-voxel level. The study proposes a working hypothesis that reconciles contrasting results from multivoxel pattern analysis and repetition suppression, suggesting that the methods are complementary to each other but not necessarily interchangeable. Copyright © 2017 the American Physiological Society.

Functionalization of Ti99.2 substrates surface by hybrid treatment investigated with spectroscopic methods

NASA Astrophysics Data System (ADS)

Jasinski, Jaroslaw Jan; Lubas, Malgorzata; Kurpaska, Lukasz; Napadlek, Wojciech; Sitarz, Maciej

2018-07-01

The article presents spectroscopic investigation of Ti 99.2 based functional substrates formed by hybrid oxidation process. Surface treatments were performed by combining methods of fluidized bed atmospheric diffusion treatment (FADT) with physical vapor deposition (PVD) - magnetron sputtering and laser surface texturing (LST) treatments. The processes were implemented to form a titanium diffusive layer saturated with oxygen in the substrate and a tight homogeneous oxide coating on Ti surface deposited with magnetron sputtering or laser texturing technique. The hybrid treatment was realized in Al2O3 fluidized bed reactor with air atmosphere, at 640 °C for 8 h and 12 h. At the same time, magnetron sputtering with the use of TiO2 target at a pressure of 3 × 102 mbar and laser surface texturing treatment with Nd:YAG λ = 1064 nm was performed. In order to investigate the effects of hybrid oxidation, microscopic (AFM, CLSM, SEM/SEM-EDX), spectroscopic (RS) and X-ray investigations (GID-XRD) were performed. Applied hybrid technique made possible to combine the effects of the generated layers and to reduce the stresses in the area of the PVD coating/oxidized Ti substrate interface. Furthermore, Raman spectroscopy results obtained at oxide layers manufactured with different variants of oxidation allowed detailed analysis of the created oxides. The coatings have shown structure with a Tiα(O) diffusion zone, a TiO2 rutile and anatase oxide zone deposited and textured on the substrate. Phase composition and morphology of these oxides is essential for the osseointegration process i.e. intensity of hydroxyapatite growing on the implant surface. Performed processes influenced the surface roughness parameter and cause the increase of substrate functional properties, which are important for biomedical applications.

Cascaded Amplitude Modulations in Sound Texture Perception.

PubMed

McWalter, Richard; Dau, Torsten

2017-01-01

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.

Cest Analysis: Automated Change Detection from Very-High Remote Sensing Images

NASA Astrophysics Data System (ADS)

Ehlers, M.; Klonus, S.; Jarmer, T.; Sofina, N.; Michel, U.; Reinartz, P.; Sirmacek, B.

2012-08-01

A fast detection, visualization and assessment of change in areas of crisis or catastrophes are important requirements for coordination and planning of help. Through the availability of new satellites and/or airborne sensors with very high spatial resolutions (e.g., WorldView, GeoEye) new remote sensing data are available for a better detection, delineation and visualization of change. For automated change detection, a large number of algorithms has been proposed and developed. From previous studies, however, it is evident that to-date no single algorithm has the potential for being a reliable change detector for all possible scenarios. This paper introduces the Combined Edge Segment Texture (CEST) analysis, a decision-tree based cooperative suite of algorithms for automated change detection that is especially designed for the generation of new satellites with very high spatial resolution. The method incorporates frequency based filtering, texture analysis, and image segmentation techniques. For the frequency analysis, different band pass filters can be applied to identify the relevant frequency information for change detection. After transforming the multitemporal images via a fast Fourier transform (FFT) and applying the most suitable band pass filter, different methods are available to extract changed structures: differencing and correlation in the frequency domain and correlation and edge detection in the spatial domain. Best results are obtained using edge extraction. For the texture analysis, different 'Haralick' parameters can be calculated (e.g., energy, correlation, contrast, inverse distance moment) with 'energy' so far providing the most accurate results. These algorithms are combined with a prior segmentation of the image data as well as with morphological operations for a final binary change result. A rule-based combination (CEST) of the change algorithms is applied to calculate the probability of change for a particular location. CEST was tested with high-resolution satellite images of the crisis areas of Darfur (Sudan). CEST results are compared with a number of standard algorithms for automated change detection such as image difference, image ratioe, principal component analysis, delta cue technique and post classification change detection. The new combined method shows superior results averaging between 45% and 15% improvement in accuracy.

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

NASA Astrophysics Data System (ADS)

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.

Texture Analysis of Poly-Adenylated mRNA Staining Following Global Brain Ischemia and Reperfusion

PubMed Central

Szymanski, Jeffrey J.; Jamison, Jill T.; DeGracia, Donald J.

2011-01-01

Texture analysis provides a means to quantify complex changes in microscope images. We previously showed that cytoplasmic poly-adenylated mRNAs form mRNA granules in post-ischemic neurons and that these granules correlated with protein synthesis inhibition and hence cell death. Here we utilized the texture analysis software MaZda to quantify mRNA granules in photomicrographs of the pyramidal cell layer of rat hippocampal region CA3 around 1 hour of reperfusion after 10 min of normothermic global cerebral ischemia. At 1 hour reperfusion, we observed variations in the texture of mRNA granules amongst samples that were readily quantified by texture analysis. Individual sample variation was consistent with the interpretation that animal-to-animal variations in mRNA granules reflected the time-course of mRNA granule formation. We also used texture analysis to quantify the effect of cycloheximide, given either before or after brain ischemia, on mRNA granules. If administered before ischemia, cycloheximide inhibited mRNA granule formation, but if administered after ischemia did not prevent mRNA granulation, indicating mRNA granule formation is dependent on dissociation of polysomes. We conclude that texture analysis is an effective means for quantifying the complex morphological changes induced in neurons by brain ischemia and reperfusion. PMID:21477879

Comparison of existing digital image analysis systems for the analysis of Thematic Mapper data

NASA Technical Reports Server (NTRS)

Likens, W. C.; Wrigley, R. C.

1984-01-01

Most existing image analysis systems were designed with the Landsat Multi-Spectral Scanner in mind, leaving open the question of whether or not these systems could adequately process Thematic Mapper data. In this report, both hardware and software systems have been evaluated for compatibility with TM data. Lack of spectral analysis capability was not found to be a problem, though techniques for spatial filtering and texture varied. Computer processing speed and data storage of currently existing mini-computer based systems may be less than adequate. Upgrading to more powerful hardware may be required for many TM applications.

A manual for inexpensive methods of analyzing and utilizing remote sensor data

NASA Technical Reports Server (NTRS)

Elifrits, C. D.; Barr, D. J.

1978-01-01

Instructions are provided for inexpensive methods of using remote sensor data to assist in the completion of the need to observe the earth's surface. When possible, relative costs were included. Equipment need for analysis of remote sensor data is described, and methods of use of these equipment items are included, as well as advantages and disadvantages of the use of individual items. Interpretation and analysis of stereo photos and the interpretation of typical patterns such as tone and texture, landcover, drainage, and erosional form are described. Similar treatment is given to monoscopic image interpretation, including LANDSAT MSS data. Enhancement techniques are detailed with respect to their application and simple techniques of creating an enhanced data item. Techniques described include additive and subtractive (Diazo processes) color techniques and enlargement of photos or images. Applications of these processes, including mappings of land resources, engineering soils, geology, water resources, environmental conditions, and crops and/or vegetation, are outlined.

Development of low friction snake-inspired deterministic textured surfaces

NASA Astrophysics Data System (ADS)

Cuervo, P.; López, D. A.; Cano, J. P.; Sánchez, J. C.; Rudas, S.; Estupiñán, H.; Toro, A.; Abdel-Aal, H. A.

2016-06-01

The use of surface texturization to reduce friction in sliding interfaces has proved successful in some tribological applications. However, it is still difficult to achieve robust surface texturing with controlled designer-functionalities. This is because the current existing gap between enabling texturization technologies and surface design paradigms. Surface engineering, however, is advanced in natural surface constructs especially within legless reptiles. Many intriguing features facilitate the tribology of such animals so that it is feasible to discover the essence of their surface construction. In this work, we report on the tribological behavior of a novel class of surfaces of which the spatial dimensions of the textural patterns originate from micro-scale features present within the ventral scales of pre-selected snake species. Mask lithography was used to produce implement elliptical texturizing patterns on the surface of titanium alloy (Ti6Al4V) pins. To study the tribological behavior of the texturized pins, pin-on-disc tests were carried out with the pins sliding against ultra-high molecular weight polyethylene discs with no lubrication. For comparison, two non-texturized samples were also tested under the same conditions. The results show the feasibility of the texturization technique based on the coefficient of friction of the textured surfaces to be consistently lower than that of the non-texturized samples.

Pore network quantification of sandstones under experimental CO2 injection using image analysis

NASA Astrophysics Data System (ADS)

Berrezueta, Edgar; González-Menéndez, Luís; Ordóñez-Casado, Berta; Olaya, Peter

2015-04-01

Automated-image identification and quantification of minerals, pores and textures together with petrographic analysis can be applied to improve pore system characterization in sedimentary rocks. Our case study is focused on the application of these techniques to study the evolution of rock pore network subjected to super critical CO2-injection. We have proposed a Digital Image Analysis (DIA) protocol that guarantees measurement reproducibility and reliability. This can be summarized in the following stages: (i) detailed description of mineralogy and texture (before and after CO2-injection) by optical and scanning electron microscopy (SEM) techniques using thin sections; (ii) adjustment and calibration of DIA tools; (iii) data acquisition protocol based on image capture with different polarization conditions (synchronized movement of polarizers); (iv) study and quantification by DIA that allow (a) identification and isolation of pixels that belong to the same category: minerals vs. pores in each sample and (b) measurement of changes in pore network, after the samples have been exposed to new conditions (in our case: SC-CO2-injection). Finally, interpretation of the petrography and the measured data by an automated approach were done. In our applied study, the DIA results highlight the changes observed by SEM and microscopic techniques, which consisted in a porosity increase when CO2 treatment occurs. Other additional changes were minor: variations in the roughness and roundness of pore edges, and pore aspect ratio, shown in the bigger pore population. Additionally, statistic tests of pore parameters measured were applied to verify that the differences observed between samples before and after CO2-injection were significant.

Buffer layers on biaxially textured metal substrates

DOEpatents

Shoup, Shara S.; Paranthamam, Mariappan; Beach, David B.; Kroeger, Donald M.; Goyal, Amit

2001-01-01

A method is disclosed for forming a biaxially textured buffer layer on a biaxially oriented metal substrate by using a sol-gel coating technique followed by pyrolyzing/annealing in a reducing atmosphere. This method is advantageous for providing substrates for depositing electronically active materials thereon.

Ultrafast laser direct hard-mask writing for high efficiency c-Si texture designs

NASA Astrophysics Data System (ADS)

Kumar, Kitty; Lee, Kenneth K. C.; Nogami, Jun; Herman, Peter R.; Kherani, Nazir P.

2013-03-01

This study reports a high-resolution hard-mask laser writing technique to facilitate the selective etching of crystalline silicon (c-Si) into an inverted-pyramidal texture with feature size and periodicity on the order of the wavelength which, thus, provides for both anti-reflection and effective light-trapping of infrared and visible light. The process also enables engineered positional placement of the inverted-pyramid thereby providing another parameter for optimal design of an optically efficient pattern. The proposed technique, a non-cleanroom process, is scalable for large area micro-fabrication of high-efficiency thin c-Si photovoltaics. Optical wave simulations suggest the fabricated textured surface with 1.3 μm inverted-pyramids and a single anti-reflective coating increases the relative energy conversion efficiency by 11% compared to the PERL-cell texture with 9 μm inverted pyramids on a 400 μm thick wafer. This efficiency gain is anticipated to improve further for thinner wafers due to enhanced diffractive light trapping effects.

Deposition of highly textured AlN thin films by reactive high power impulse magnetron sputtering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Moreira, Milena A.; Törndahl, Tobias; Katardjiev, Ilia

2015-03-15

Aluminum nitride thin films were deposited by reactive high power impulse magnetron sputtering (HiPIMS) and pulsed direct-current on Si (100) and textured Mo substrates, where the same deposition conditions were used for both techniques. The films were characterized by x-ray diffraction and atomic force microscopy. The results show a pronounced improvement in the AlN crystalline texture for all films deposited by HiPIMS on Si. Already at room temperature, the HiPIMS films exhibited a strong preferred (002) orientation and at 400 °C, no contributions from other orientations were detected. Despite the low film thickness of only 200 nm, an ω-scan full width atmore » half maximum value of 5.1° was achieved on Si. The results are attributed to the high ionization of sputtered material achieved in HiPIMS. On textured Mo, there was no significant difference between the deposition techniques.« less

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

PubMed

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.

Classification of mass and normal breast tissue: A convolution neural network classifier with spatial domain and texture images

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sahiner, B.; Chan, H.P.; Petrick, N.

1996-10-01

The authors investigated the classification of regions of interest (ROI`s) on mammograms as either mass or normal tissue using a convolution neural network (CNN). A CNN is a back-propagation neural network with two-dimensional (2-D) weight kernels that operate on images. A generalized, fast and stable implementation of the CNN was developed. The input images to the CNN were obtained form the ROI`s using two techniques. The first technique employed averaging and subsampling. The second technique employed texture feature extraction methods applied to small subregions inside the ROI. Features computed over different subregions were arranged as texture images, which were subsequentlymore » used as CNN inputs. The effects of CNN architecture and texture feature parameters on classification accuracy were studied. Receiver operating characteristic (ROC) methodology was used to evaluate the classification accuracy. A data set consisting of 168 ROI`s containing biopsy-proven masses and 504 ROI`s containing normal breast tissue was extracted from 168 mammograms by radiologists experienced in mammography. This data set was used for training and testing the CNN. With the best combination of CNN architecture and texture feature parameters, the area under the test ROC curve reached 0.87, which corresponded to a true-positive fraction of 90% at a false positive fraction of 31%. The results demonstrate the feasibility of using a CNN for classification of masses and normal tissue on mammograms.« less

Adaptation of mastication mechanics and eating behaviour to small differences in food texture.

PubMed

Le Révérend, Benjamin; Saucy, Françoise; Moser, Mireille; Loret, Chrystel

2016-10-15

Eating behaviour is significantly modified with the consumption of soft or hard textures. However, it is of interest to describe how adaptive is mastication to a narrow range of texture. ElectroMyoGraphy (EMG) and Kinematics of Jaw Movements (KJM) techniques were used simultaneously to follow mastication muscle activity and jaw motion during mastication of seven cereal products. We show that parameters such as the time of chewing activity, the number of chewing cycles, the chewing muscle EMG activity and the volume occupied for each chewing cycle are amongst others significantly different depending on products tested, even though the textural product space investigated is quite narrow (cereal finger foods). In addition, through a time/chewing cycle dependent analysis of the chewing patterns, we demonstrate that different foods follow different breakdown pathways during oral processing, depending on their initial structural properties, as dictated by their formulation and manufacturing process. In particular, we show that mastication behaviour of cereal foods can be partly classified based on the process that is used to generate product internal structure (e.g. baking vs extrusion). To the best of our knowledge, such time dependent analyses have not yet been reported. Those results suggest that it is possible to influence the chewing behaviour by modifying food textures within the same "food family". This opens new possibilities to design foods for specific populations that cannot accomplish specific oral processing tasks. Copyright © 2016. Published by Elsevier Inc.

Music Structure Analysis from Acoustic Signals

NASA Astrophysics Data System (ADS)

Dannenberg, Roger B.; Goto, Masataka

Music is full of structure, including sections, sequences of distinct musical textures, and the repetition of phrases or entire sections. The analysis of music audio relies upon feature vectors that convey information about music texture or pitch content. Texture generally refers to the average spectral shape and statistical fluctuation, often reflecting the set of sounding instruments, e.g., strings, vocal, or drums. Pitch content reflects melody and harmony, which is often independent of texture. Structure is found in several ways. Segment boundaries can be detected by observing marked changes in locally averaged texture.

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

NASA Astrophysics Data System (ADS)

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.

Visualization and Quantitative Analysis of Crack-Tip Plastic Zone in Pure Nickel

NASA Astrophysics Data System (ADS)

Kelton, Randall; Sola, Jalal Fathi; Meletis, Efstathios I.; Huang, Haiying

2018-05-01

Changes in surface morphology have long been thought to be associated with crack propagation in metallic materials. We have studied areal surface texture changes around crack tips in an attempt to understand the correlations between surface texture changes and crack growth behavior. Detailed profiling of the fatigue sample surface was carried out at short fatigue intervals. An image processing algorithm was developed to calculate the surface texture changes. Quantitative analysis of the crack-tip plastic zone, crack-arrested sites near triple points, and large surface texture changes associated with crack release from arrested locations was carried out. The results indicate that surface texture imaging enables visualization of the development of plastic deformation around a crack tip. Quantitative analysis of the surface texture changes reveals the effects of local microstructures on the crack growth behavior.

Inter- and intraspecific diversity in Cistus L. (Cistaceae) seeds, analysed with computer vision techniques.

PubMed

Lo Bianco, M; Grillo, O; Cañadas, E; Venora, G; Bacchetta, G

2017-03-01

This work aims to discriminate among different species of the genus Cistus, using seed parameters and following the scientific plant names included as accepted in The Plant List. Also, the intraspecific phenotypic differentiation of C. creticus, through comparison with three subspecies (C. creticus subsp. creticus, C. c. subsp. eriocephalus and C. c. subsp. corsicus), as well as the interpopulation variability among five C. creticus subsp. eriocephalus populations was evaluated. Seed mean weight and 137 morphocolorimetric quantitative variables, describing shape, size, colour and textural seed traits, were measured using image analysis techniques. Measured data were analysed applying step-wise linear discriminant analysis. An overall cross-validated classification performance of 80.6% was recorded at species level. With regard to C. creticus, as case study, percentages of correct discrimination of 96.7% and 99.6% were achieved at intraspecific and interpopulation levels, respectively. In this classification model, the relevance of the colorimetric and textural descriptive features was highlighted, as well as the seed mean weight, which was the most discriminant feature at specific and intraspecific level. These achievements proved the ability of the image analysis system as highly diagnostic for systematic purposes and confirm that seeds in the genus Cistus have important diagnostic value. © 2016 German Botanical Society and The Royal Botanical Society of the Netherlands.

Embedded wavelet packet transform technique for texture compression

NASA Astrophysics Data System (ADS)

Li, Jin; Cheng, Po-Yuen; Kuo, C.-C. Jay

1995-09-01

A highly efficient texture compression scheme is proposed in this research. With this scheme, energy compaction of texture images is first achieved by the wavelet packet transform, and an embedding approach is then adopted for the coding of the wavelet packet transform coefficients. By comparing the proposed algorithm with the JPEG standard, FBI wavelet/scalar quantization standard and the EZW scheme with extensive experimental results, we observe a significant improvement in the rate-distortion performance and visual quality.

Evaluation of Wear on Macro-Surface Textures Generated by ns Fiber Laser

NASA Astrophysics Data System (ADS)

Harish, V.; Soundarapandian, S.; Vijayaraghavan, L.; Bharatish, A.

2018-03-01

The demand for improved performance and long term reliability of mechanical systems dictate the use of advanced materials and surface engineering techniques. A small change in the surface topography can lead to substantial improvements in the tribological behaviour of the contact surfaces. One way of altering the surface topography is by surface texturing by introducing dimples or channels on the surfaces. Surface texturing is already a successful technique which finds a wide area of applications ranging from heavy industries to small scale devices. This paper reports the effect of macro texture shapes generated using a nanosecond fiber laser on wear of high carbon chromium steel used in large size bearings having rolling contacts. Circular and square shaped dimples were generated on the surface to assess the effect of sliding velocities on friction coefficient. Graphite was used as solid lubricant to minimise the effect of wear on textured surfaces. The laser parameters such as power, scan speed and passes were optimised to obtain macro circular and square dimples which was characterised using a laser confocal microscope. The friction coefficients of the circular and square dimples were observed to lie in the same range due to minimum wear on the surface. On the contrary, at medium and higher sliding velocities, square dimples exhibited lower friction coefficient values compared to circular dimples. The morphology of textured specimen was characterised using Scanning Electron Microscope.

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

PubMed

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.

Semantic segmentation of 3D textured meshes for urban scene analysis

NASA Astrophysics Data System (ADS)

Rouhani, Mohammad; Lafarge, Florent; Alliez, Pierre

2017-01-01

Classifying 3D measurement data has become a core problem in photogrammetry and 3D computer vision, since the rise of modern multiview geometry techniques, combined with affordable range sensors. We introduce a Markov Random Field-based approach for segmenting textured meshes generated via multi-view stereo into urban classes of interest. The input mesh is first partitioned into small clusters, referred to as superfacets, from which geometric and photometric features are computed. A random forest is then trained to predict the class of each superfacet as well as its similarity with the neighboring superfacets. Similarity is used to assign the weights of the Markov Random Field pairwise-potential and to account for contextual information between the classes. The experimental results illustrate the efficacy and accuracy of the proposed framework.

Separation of specular and diffuse components using tensor voting in color images.

PubMed

Nguyen, Tam; Vo, Quang Nhat; Yang, Hyung-Jeong; Kim, Soo-Hyung; Lee, Guee-Sang

2014-11-20

Most methods for the detection and removal of specular reflections suffer from nonuniform highlight regions and/or nonconverged artifacts induced by discontinuities in the surface colors, especially when dealing with highly textured, multicolored images. In this paper, a novel noniterative and predefined constraint-free method based on tensor voting is proposed to detect and remove the highlight components of a single color image. The distribution of diffuse and specular pixels in the original image is determined using tensors' saliency analysis, instead of comparing color information among neighbor pixels. The achieved diffuse reflectance distribution is used to remove specularity components. The proposed method is evaluated quantitatively and qualitatively over a dataset of highly textured, multicolor images. The experimental results show that our result outperforms other state-of-the-art techniques.

Effect of surface texture by ion beam sputtering on implant biocompatibility and soft tissue attachment

NASA Technical Reports Server (NTRS)

Gibbons, D. F.

1977-01-01

The objectives in this report were to use the ion beam sputtering technique to produce surface textures on polymers, metals, and ceramics. The morphology of the texture was altered by varying both the width and depth of the square pits which were formed by ion beam erosion. The width of the ribs separating the pits were defined by the mask used to produce the texture. The area of the surface containing pits varies as the width was changed. The biological parameters used to evaluate the biological response to the texture were: (1) fibrous capsule and inflammatory response in subcutaneous soft tissue; (2) strength of the mechanical attachment of the textured surface by the soft tissue; and (3) morphology of the epidermal layer interfacing the textured surface of percutaneous connectors. Because the sputter yield on teflon ribs was approximately an order of magnitude larger than any other material the majority of the measurements presented in the report were obtained with teflon.

Ultrasonic imaging of textured alumina

NASA Technical Reports Server (NTRS)

Stang, David B.; Salem, Jonathan A.; Generazio, Edward R.

1989-01-01

Ultrasonic images representing the bulk attenuation and velocity of a set of alumina samples were obtained by a pulse-echo contact scanning technique. The samples were taken from larger bodies that were chemically similar but were processed by extrusion or isostatic processing. The crack growth resistance and fracture toughness of the larger bodies were found to vary with processing method and test orientation. The results presented here demonstrate that differences in texture that contribute to variations in structural performance can be revealed by analytic ultrasonic techniques.

ATR applications of minimax entropy models of texture and shape

NASA Astrophysics Data System (ADS)

Zhu, Song-Chun; Yuille, Alan L.; Lanterman, Aaron D.

2001-10-01

Concepts from information theory have recently found favor in both the mainstream computer vision community and the military automatic target recognition community. In the computer vision literature, the principles of minimax entropy learning theory have been used to generate rich probabilitistic models of texture and shape. In addition, the method of types and large deviation theory has permitted the difficulty of various texture and shape recognition tasks to be characterized by 'order parameters' that determine how fundamentally vexing a task is, independent of the particular algorithm used. These information-theoretic techniques have been demonstrated using traditional visual imagery in applications such as simulating cheetah skin textures and such as finding roads in aerial imagery. We discuss their application to problems in the specific application domain of automatic target recognition using infrared imagery. We also review recent theoretical and algorithmic developments which permit learning minimax entropy texture models for infrared textures in reasonable timeframes.

Objective measurement of bread crumb texture

NASA Astrophysics Data System (ADS)

Wang, Jian; Coles, Graeme D.

1995-01-01

Evaluation of bread crumb texture plays an important role in judging bread quality. This paper discusses the application of image analysis methods to the objective measurement of the visual texture of bread crumb. The application of Fast Fourier Transform and mathematical morphology methods have been discussed by the authors in their previous work, and a commercial bread texture measurement system has been developed. Based on the nature of bread crumb texture, we compare the advantages and disadvantages of the two methods, and a third method based on features derived directly from statistics of edge density in local windows of the bread image. The analysis of various methods and experimental results provides an insight into the characteristics of the bread texture image and interconnection between texture measurement algorithms. The usefulness of the application of general stochastic process modelling of texture is thus revealed; it leads to more reliable and accurate evaluation of bread crumb texture. During the development of these methods, we also gained useful insights into how subjective judges form opinions about bread visual texture. These are discussed here.

Temporal changes of flavour and texture in cooked bologna type sausages as affected by fat and salt content.

PubMed

Ventanas, Sonia; Puolanne, Eero; Tuorila, Hely

2010-07-01

Temporal changes of flavour (mushroom-like and saltiness) and texture (juiciness) in cooked bologna type sausages with different fat and salt content and containing selected volatile compounds (100 mg kg(-1) of 1-octen-3-ol and 200 mg kg(-1) of 2,6-dimethylpyrazine) were evaluated using time-intensity (TI) method. Preceding the TI study, descriptive profiles of sausages were determined. Release of volatiles was analysed by solid-phase microextraction coupled to gas chromatography-mass spectrometry (SPME-GC-MS) and an instrumental texture analysis was also performed. Chromatographic results obtained for 1-octen-3-ol were strongly correlated with the intensity perception of the linked odour and flavour (mushroom). Modifications of sausages matrix in terms of fat and salt content differently affected the dynamic perception of mushroom flavour, saltiness and juiciness. NaCl contributed to increasing release of 1-octen-3-ol (salting-out effect) confirmed by SPME analysis as well as the intensity and duration of the related flavour (mushroom) evaluated by TI. Similarly, NaCl increased the temporal perception of both saltines and juiciness of sausages. Increase in fat content led to a higher retention of 1-octen-3-ol (lipophilic compound) and thus to a less intense and shorter duration of mushroom flavour. Moreover, fat contributed to a more intense and a longer juiciness of sausages. These results highlight the feasibility of TI technique to evaluate changes in the temporal flavour and texture perception of sausages caused by modification of matrix composition. Copyright 2010 Elsevier Ltd. All rights reserved.

Doping profile measurement on textured silicon surface

NASA Astrophysics Data System (ADS)

Essa, Zahi; Taleb, Nadjib; Sermage, Bernard; Broussillou, Cédric; Bazer-Bachi, Barbara; Quillec, Maurice

2018-04-01

In crystalline silicon solar cells, the front surface is textured in order to lower the reflection of the incident light and increase the efficiency of the cell. This texturing whose dimensions are a few micrometers wide and high, often makes it difficult to determine the doping profile measurement. We have measured by secondary ion mass spectrometry (SIMS) and electrochemical capacitance voltage profiling the doping profile of implanted phosphorus in alkaline textured and in polished monocrystalline silicon wafers. The paper shows that SIMS gives accurate results provided the primary ion impact angle is small enough. Moreover, the comparison between these two techniques gives an estimation of the concentration of electrically inactive phosphorus atoms.

Cascaded Amplitude Modulations in Sound Texture Perception

PubMed Central

McWalter, Richard; Dau, Torsten

2017-01-01

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. PMID:28955191

Benign-malignant mass classification in mammogram using edge weighted local texture features

NASA Astrophysics Data System (ADS)

Rabidas, Rinku; Midya, Abhishek; Sadhu, Anup; Chakraborty, Jayasree

2016-03-01

This paper introduces novel Discriminative Robust Local Binary Pattern (DRLBP) and Discriminative Robust Local Ternary Pattern (DRLTP) for the classification of mammographic masses as benign or malignant. Mass is one of the common, however, challenging evidence of breast cancer in mammography and diagnosis of masses is a difficult task. Since DRLBP and DRLTP overcome the drawbacks of Local Binary Pattern (LBP) and Local Ternary Pattern (LTP) by discriminating a brighter object against the dark background and vice-versa, in addition to the preservation of the edge information along with the texture information, several edge-preserving texture features are extracted, in this study, from DRLBP and DRLTP. Finally, a Fisher Linear Discriminant Analysis method is incorporated with discriminating features, selected by stepwise logistic regression method, for the classification of benign and malignant masses. The performance characteristics of DRLBP and DRLTP features are evaluated using a ten-fold cross-validation technique with 58 masses from the mini-MIAS database, and the best result is observed with DRLBP having an area under the receiver operating characteristic curve of 0.982.

Mining textural knowledge in biological images: Applications, methods and trends.

PubMed

Di Cataldo, Santa; Ficarra, Elisa

2017-01-01

Texture analysis is a major task in many areas of computer vision and pattern recognition, including biological imaging. Indeed, visual textures can be exploited to distinguish specific tissues or cells in a biological sample, to highlight chemical reactions between molecules, as well as to detect subcellular patterns that can be evidence of certain pathologies. This makes automated texture analysis fundamental in many applications of biomedicine, such as the accurate detection and grading of multiple types of cancer, the differential diagnosis of autoimmune diseases, or the study of physiological processes. Due to their specific characteristics and challenges, the design of texture analysis systems for biological images has attracted ever-growing attention in the last few years. In this paper, we perform a critical review of this important topic. First, we provide a general definition of texture analysis and discuss its role in the context of bioimaging, with examples of applications from the recent literature. Then, we review the main approaches to automated texture analysis, with special attention to the methods of feature extraction and encoding that can be successfully applied to microscopy images of cells or tissues. Our aim is to provide an overview of the state of the art, as well as a glimpse into the latest and future trends of research in this area.

Inferring pterosaur diets through quantitative 3D textural analysis of tooth microwear in extant analogues

NASA Astrophysics Data System (ADS)

Bestwick, Jordan; Unwin, David; Butler, Richard; Henderson, Don; Purnell, Mark

2017-04-01

Pterosaurs (Pterosauria) were a successful group of Mesozoic flying reptiles. For 150 million years they were integral components of terrestrial and coastal ecosystems, yet their feeding ecology remains poorly constrained. Postulated pterosaur diets include insectivory, piscivory and/or carnivory, but many dietary hypotheses are speculative and/or based on little evidence, highlighting the need for alternative approaches to provide robust data. One method involves quantitative analysis of the micron-scale 3D textures of worn pterosaur tooth surfaces - dental microwear texture analysis. Microwear is produced as scratches and chips generated by food items create characteristic tooth surface textures. Microwear analysis has never been applied to pterosaurs, but we might expect microwear textures to differ between pterosaurs with different diets. An important step in investigating pterosaur microwear is to examine microwear from extant organisms with known diets to provide a comparative data set. This has been achieved through analysis of non-occlusal microwear textures in extant bats, crocodilians and monitor lizards, clades within which species exhibit insectivorous, piscivorous and carnivorous diets. The results - the first test of the hypothesis that non-occlusal microwear textures in these extant clades vary with diet - provide the context for the first robust quantitative tests of pterosaur diets.

Multiresolution texture models for brain tumor segmentation in MRI.

PubMed

Iftekharuddin, Khan M; Ahmed, Shaheen; Hossen, Jakir

2011-01-01

In this study we discuss different types of texture features such as Fractal Dimension (FD) and Multifractional Brownian Motion (mBm) for estimating random structures and varying appearance of brain tissues and tumors in magnetic resonance images (MRI). We use different selection techniques including KullBack - Leibler Divergence (KLD) for ranking different texture and intensity features. We then exploit graph cut, self organizing maps (SOM) and expectation maximization (EM) techniques to fuse selected features for brain tumors segmentation in multimodality T1, T2, and FLAIR MRI. We use different similarity metrics to evaluate quality and robustness of these selected features for tumor segmentation in MRI for real pediatric patients. We also demonstrate a non-patient-specific automated tumor prediction scheme by using improved AdaBoost classification based on these image features.

Optimizing morphology through blood cell image analysis.

PubMed

Merino, A; Puigví, L; Boldú, L; Alférez, S; Rodellar, J

2018-05-01

Morphological review of the peripheral blood smear is still a crucial diagnostic aid as it provides relevant information related to the diagnosis and is important for selection of additional techniques. Nevertheless, the distinctive cytological characteristics of the blood cells are subjective and influenced by the reviewer's interpretation and, because of that, translating subjective morphological examination into objective parameters is a challenge. The use of digital microscopy systems has been extended in the clinical laboratories. As automatic analyzers have some limitations for abnormal or neoplastic cell detection, it is interesting to identify quantitative features through digital image analysis for morphological characteristics of different cells. Three main classes of features are used as follows: geometric, color, and texture. Geometric parameters (nucleus/cytoplasmic ratio, cellular area, nucleus perimeter, cytoplasmic profile, RBC proximity, and others) are familiar to pathologists, as they are related to the visual cell patterns. Different color spaces can be used to investigate the rich amount of information that color may offer to describe abnormal lymphoid or blast cells. Texture is related to spatial patterns of color or intensities, which can be visually detected and quantitatively represented using statistical tools. This study reviews current and new quantitative features, which can contribute to optimize morphology through blood cell digital image processing techniques. © 2018 John Wiley & Sons Ltd.

A Bio Medical Waste Identification and Classification Algorithm Using Mltrp and Rvm.

PubMed

Achuthan, Aravindan; Ayyallu Madangopal, Vasumathi

2016-10-01

We aimed to extract the histogram features for text analysis and, to classify the types of Bio Medical Waste (BMW) for garbage disposal and management. The given BMW was preprocessed by using the median filtering technique that efficiently reduced the noise in the image. After that, the histogram features of the filtered image were extracted with the help of proposed Modified Local Tetra Pattern (MLTrP) technique. Finally, the Relevance Vector Machine (RVM) was used to classify the BMW into human body parts, plastics, cotton and liquids. The BMW image was collected from the garbage image dataset for analysis. The performance of the proposed BMW identification and classification system was evaluated in terms of sensitivity, specificity, classification rate and accuracy with the help of MATLAB. When compared to the existing techniques, the proposed techniques provided the better results. This work proposes a new texture analysis and classification technique for BMW management and disposal. It can be used in many real time applications such as hospital and healthcare management systems for proper BMW disposal.

SU-E-E-16: The Application of Texture Analysis for Differentiation of Central Cancer From Atelectasis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, M; Fan, T; Duan, J

2015-06-15

Purpose: Prospectively assess the potential utility of texture analysis for differentiation of central cancer from atelectasis. Methods: 0 consecutive central lung cancer patients who were referred for CT imaging and PET-CT were enrolled. Radiotherapy doctor delineate the tumor and atelectasis according to the fusion imaging based on CT image and PET-CT image. The texture parameters (such as energy, correlation, sum average, difference average, difference entropy), were obtained respectively to quantitatively discriminate tumor and atelectasis based on gray level co-occurrence matrix (GLCM) Results: The texture analysis results showed that the parameters of correlation and sum average had an obviously statistical significance(P<0.05).more » Conclusion: the results of this study indicate that texture analysis may be useful for the differentiation of central lung cancer and atelectasis.« less

Sol-gel deposition of buffer layers on biaxially textured metal substances

DOEpatents

Shoup, Shara S.; Paranthamam, Mariappan; Beach, David B.; Kroeger, Donald M.; Goyal, Amit

2000-01-01

A method is disclosed for forming a biaxially textured buffer layer on a biaxially oriented metal substrate by using a sol-gel coating technique followed by pyrolyzing/annealing in a reducing atmosphere. This method is advantageous for providing substrates for depositing electronically active materials thereon.

Structural analysis of natural textures.

PubMed

Vilnrotter, F M; Nevatia, R; Price, K E

1986-01-01

Many textures can be described structurally, in terms of the individual textural elements and their spatial relationships. This paper describes a system to generate useful descriptions of natural textures in these terms. The basic approach is to determine an initial, partial description of the elements using edge features. This description controls the extraction of the texture elements. The elements are grouped by type, and spatial relationships between elements are computed. The descriptions are shown to be useful for recognition of the textures, and for reconstruction of periodic textures.

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

PubMed

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.

Texture analysis at neutron diffractometer STRESS-SPEC

NASA Astrophysics Data System (ADS)

Brokmeier, H.-G.; Gan, W. M.; Randau, C.; Völler, M.; Rebelo-Kornmeier, J.; Hofmann, M.

2011-06-01

In response to the development of new materials and the application of materials and components in advanced technologies, non-destructive measurement methods of textures and residual stresses have gained worldwide significance in recent years. The materials science neutron diffractometer STRESS-SPEC at FRM II (Garching, Germany) is designed to be applied equally to texture and residual stress analyses by virtue of its very flexible configuration. Due to the high penetration capabilities of neutrons and the high neutron flux of STRESS-SPEC it allows a combined analysis of global texture, local texture, strain pole figure and FWHM pole figure in a wide variety of materials including metals, alloys, composites, ceramics and geological materials. Especially, the analysis of texture gradients in bulk materials using neutron diffraction has advantages over laboratory X-rays and EBSD for many scientific cases. Moreover, neutron diffraction is favourable for coarse-grained materials, where bulk information averaged over texture inhomogeneities is needed, and also stands out due to easy sample preparation. In future, the newly developed robot system for STRESS-SPEC will allow much more flexibility than an Eulerian cradle as on standard instruments. Five recent measurements are shown to demonstrate the wide range of possible texture applications at STRESS-SPEC diffractometer.

Recreational-Grade Sidescan Sonar: Transforming a Low-Cost Leisure Gadget into a High Resolution Riverbed Remote Sensing Tool

NASA Astrophysics Data System (ADS)

Hamill, D. D.; Buscombe, D.; Wheaton, J. M.; Wilcock, P. R.

2016-12-01

The size and spatial organization of bed material, bed texture, is a fundamental physical attribute of lotic ecosystems. Traditional methods to map bed texture (such as physical samples and underwater video) are limited by low spatial coverage, and poor precision in positioning. Recreational grade sidescan sonar systems now offer the possibility of imaging submerged riverbed sediments at coverages and resolutions sufficient to identify subtle changes in bed texture, in any navigable body of water, with minimal cost, expertise in sonar, or logistical effort, thereby facilitating the democratization of acoustic imaging of benthic environments, to support ecohydrological studies in shallow water, not subject to the rigors of hydrographic standards, nor the preserve of hydroacoustic expertise and proprietary hydrographic industry software. We investigate the possibility of using recreational grade sidescan sonar for sedimentary change detection using a case study of repeat sidescan imaging of mixed sand-gravel-rock riverbeds in a debris-fan dominated canyon river, at a coverage and resolution that meets the objectives of studies of the effects of changing bed substrates on salmonid spawning. A repeat substrate mapping analysis on data collected between 2012 and 2015 on the Colorado River in Glen, Marble, and Grand Canyons will be presented. A detailed method has been developed to interpret and analyze non-survey-grade sidescan sonar data, encoded within an open source software tool developed by the authors. An automated technique to quantify bed texture directly from sidescan sonar imagery is tested against bed sediment observations from underwater video and multibeam sonar. Predictive relationships between known bed sediment observations and bed texture metrics could provide an objective means to quantify bed textures and to relate changes in bed texture to biological components of an aquatic ecosystem, at high temporal frequency, and with minimal logistical effort and cost.

Automated Texture Classification of the Mawrth Vallis Landing Site Region

NASA Astrophysics Data System (ADS)

Parente, M.; Bayley, L.; Hunkins, L.; McKeown, N. K.; Bishop, J. L.

2009-12-01

Supervised classification techniques have been developed to discriminate geomorphologic units in HiRISE images of Mawrth Vallis on Mars, one of the MSL candidate landing sites. A variety of clay minerals that indicate water was once present have been identified in the ancient bedrock at Mawrth Vallis [1-7]. These clay-rich rocks exhibit distinct surface textures in HiRISE images, where the nontronite-bearing unit consists of two primary textures: 2-5 m irregular inverted polygons and irregular parallel fracture sets ([8,13], Fig. b-c). In contrast, the montmorillonite-bearing unit consists of 0.5-1.5 m regular polygons ([8,13], Fig. e). We also characterized dunes (Fig. d), and the spectrally unremarkable caprock unit (Fig. a). Classification of these textures was performed by extracting discriminatory features from gray-level run length matrices (GLRLMs) [9], gray-level co-occurrence matrices (GLCMs) [10], and semivariograms [11] calculated for small blocks of data in HiRISE images. Preliminary results using an algorithm containing eight of these classification features produced a texture classification technique that is 85 percent accurate. The discriminant analysis (e.g. [12]) classifier we used modeled a linear discriminant function for each class based on the training feature vectors for that class. The test vector with the largest value for its discriminant function was then assigned to each class. We assumed linear functions were acceptable for small training sets and we performed automated selection in order to identify the most discriminative features for the textures in Mawrth Vallis. Continued efforts are underway to test and refine this procedure in order to optimize texture recognition on a broader collection of textures, representing additional surface components from Mawrth Vallis and other landing sites on Mars. [1] Bibring, J.-P., et al. (2005) Science, 307, 1576-1581. [2] Poulet, F., et al. (2005) Nature, 438, 632-627. [3] Bishop, J. L., et al. (2008) Science, 321, 830-833. [4] Wray, J. J., et al. (2008) GRL, 35, L12202. [5] Loizeau, D., et al. (2009) Icarus, (in press). [6] McKeown, N. K., et al. (2009) JGR- Planets, (in press). [7] Noe Dobrea, E. Z., et al. (2009) JGR- Planets, (in revision). [8] McKeown, N. K. et al. (2009) LPSC abs. #2433. [9] Galloway, M. M., (1975),Computer Graphics and Image Processing 4, 172-179. [10] Haralick, R. M., (1973) IEEE Trans. on Systems, Man and Cybernetics 3, 610-621. [11] Curran, P. J., Remote Sensing of Environment 24, 493-507, 1988. [12] Hastie T., et al. (2005), The elements of statistical learning. Springer. [13] McKeown, N. K., et al. (2009) AGU

Fractal-Based Image Analysis In Radiological Applications

NASA Astrophysics Data System (ADS)

Dellepiane, S.; Serpico, S. B.; Vernazza, G.; Viviani, R.

1987-10-01

We present some preliminary results of a study aimed to assess the actual effectiveness of fractal theory and to define its limitations in the area of medical image analysis for texture description, in particular, in radiological applications. A general analysis to select appropriate parameters (mask size, tolerance on fractal dimension estimation, etc.) has been performed on synthetically generated images of known fractal dimensions. Moreover, we analyzed some radiological images of human organs in which pathological areas can be observed. Input images were subdivided into blocks of 6x6 pixels; then, for each block, the fractal dimension was computed in order to create fractal images whose intensity was related to the D value, i.e., texture behaviour. Results revealed that the fractal images could point out the differences between normal and pathological tissues. By applying histogram-splitting segmentation to the fractal images, pathological areas were isolated. Two different techniques (i.e., the method developed by Pentland and the "blanket" method) were employed to obtain fractal dimension values, and the results were compared; in both cases, the appropriateness of the fractal description of the original images was verified.

An analysis of texture, timbre, and rhythm in relation to form in Magnus Lindberg's "Gran Duo"

NASA Astrophysics Data System (ADS)

Wolfe, Brian Thomas

Gran Duo (1999-2000) by Magnus Lindberg (b. 1958) is the result of a commission by Sir Simon Rattle, former conductor of the City of Birmingham (England) Symphony Orchestra, and the Royal Festival Hall to commemorate the third millennium. Composed for twenty-four woodwinds and brass, Lindberg divides the woodwind and brass families into eight characters that serve as participants in an attentive twenty-minute conversation. The document includes biographical information about the composition to further understand Lindberg's writing style. The composer's use of computer-assisted composition techniques inspires an alternative structural analysis of Gran Duo. Spectral graphs provide a supplementary tool for score study assisting with the verification of formal structural elements. A tempo chart allows the conductor to easily identify form and tempo relationships between each of the nineteen sections throughout the five-movement composition. In order to reveal character areas and their relation to the structure of the work, the analysis of texture, timbre, and rhythm reveal the formal structure of the composition, which reflects a conversation between the brass and woodwinds in this setting for wind instruments.

Using Color, Texture and Object-Based Image Analysis of Multi-Temporal Camera Data to Monitor Soil Aggregate Breakdown

PubMed Central

Ymeti, Irena; van der Werff, Harald; Shrestha, Dhruba Pikha; Jetten, Victor G.; Lievens, Caroline; van der Meer, Freek

2017-01-01

Remote sensing has shown its potential to assess soil properties and is a fast and non-destructive method for monitoring soil surface changes. In this paper, we monitor soil aggregate breakdown under natural conditions. From November 2014 to February 2015, images and weather data were collected on a daily basis from five soils susceptible to detachment (Silty Loam with various organic matter content, Loam and Sandy Loam). Three techniques that vary in image processing complexity and user interaction were tested for the ability of monitoring aggregate breakdown. Considering that the soil surface roughness causes shadow cast, the blue/red band ratio is utilized to observe the soil aggregate changes. Dealing with images with high spatial resolution, image texture entropy, which reflects the process of soil aggregate breakdown, is used. In addition, the Huang thresholding technique, which allows estimation of the image area occupied by soil aggregate, is performed. Our results show that all three techniques indicate soil aggregate breakdown over time. The shadow ratio shows a gradual change over time with no details related to weather conditions. Both the entropy and the Huang thresholding technique show variations of soil aggregate breakdown responding to weather conditions. Using data obtained with a regular camera, we found that freezing–thawing cycles are the cause of soil aggregate breakdown. PMID:28556803

Using Color, Texture and Object-Based Image Analysis of Multi-Temporal Camera Data to Monitor Soil Aggregate Breakdown.

PubMed

Ymeti, Irena; van der Werff, Harald; Shrestha, Dhruba Pikha; Jetten, Victor G; Lievens, Caroline; van der Meer, Freek

2017-05-30

Remote sensing has shown its potential to assess soil properties and is a fast and non-destructive method for monitoring soil surface changes. In this paper, we monitor soil aggregate breakdown under natural conditions. From November 2014 to February 2015, images and weather data were collected on a daily basis from five soils susceptible to detachment (Silty Loam with various organic matter content, Loam and Sandy Loam). Three techniques that vary in image processing complexity and user interaction were tested for the ability of monitoring aggregate breakdown. Considering that the soil surface roughness causes shadow cast, the blue/red band ratio is utilized to observe the soil aggregate changes. Dealing with images with high spatial resolution, image texture entropy, which reflects the process of soil aggregate breakdown, is used. In addition, the Huang thresholding technique, which allows estimation of the image area occupied by soil aggregate, is performed. Our results show that all three techniques indicate soil aggregate breakdown over time. The shadow ratio shows a gradual change over time with no details related to weather conditions. Both the entropy and the Huang thresholding technique show variations of soil aggregate breakdown responding to weather conditions. Using data obtained with a regular camera, we found that freezing-thawing cycles are the cause of soil aggregate breakdown.

Predicting neo-adjuvant chemotherapy response and progression-free survival of locally advanced breast cancer using textural features of intratumoral heterogeneity on F-18 FDG PET/CT and diffusion-weighted MR imaging.

PubMed

Yoon, Hai-Jeon; Kim, Yemi; Chung, Jin; Kim, Bom Sahn

2018-03-30

Predicting response to neo-adjuvant chemotherapy (NAC) and survival in locally advanced breast cancer (LABC) is important. This study investigated the prognostic value of tumor heterogeneity evaluated with textural analysis through F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) and diffusion-weighted imaging (DWI). We enrolled 83 patients with LABC who had completed NAC and curative surgery. Tumor texture indices from pretreatment FDG PET and DWI were extracted from histogram analysis and 7 different parent matrices: co-occurrence matrix, the voxel-alignment matrix, neighborhood intensity difference matrix, intensity size-zone matrix (ISZM), normalized gray-level co-occurrence matrix (NGLCM), neighboring gray-level dependence matrix (NGLDM), and texture spectrum matrix. The predictive values of textural features were tested regarding both pathologic NAC response and progression-free survival. Among 83 patients, 46 were pathologic responders, while 37 were nonresponders. The PET texture indices from 7 parent matrices, DWI texture indices from histogram, and 1 parent matrix (NGLCM) showed significant differences according to NAC response. On multivariable analysis, number nonuniformity of PET extracted from the NGLDM was an independent predictor of pathologic response (P = .009). During a median follow-up period of 17.3 months, 14 patients experienced recurrence. High-intensity zone emphasis (HIZE) and high-intensity short-zone emphasis (HISZE) from PET extracted from ISZM were significant textural predictors (P = .011 and P = .033). On Cox regression analysis, only HIZE was a significant predictor of recurrence (P = .027), while HISZE showed borderline significance (P = .107). Tumor texture indices are useful for NAC response prediction in LABC. Moreover, PET texture indices can help to predict disease recurrence. © 2018 Wiley Periodicals, Inc.

A three dimensional scaffold with precise micro-architecture and surface micro-textures

PubMed Central

Mata, Alvaro; Kim, Eun Jung; Boehm, Cynthia A.; Fleischman, Aaron J.; Muschler, George F.; Roy, Shuvo

2013-01-01

A three-dimensional (3D) structure comprising precisely defined microarchitecture and surface micro-textures, designed to present specific physical cues to cells and tissues, may provide an efficient scaffold in a variety of tissue engineering and regenerative medicine applications. We report a fabrication technique based on microfabrication and soft lithography that permits for the development of 3D scaffolds with both precisely engineered architecture and tailored surface topography. The scaffold fabrication technique consists of three key steps starting with microfabrication of a mold using an epoxy-based photoresist (SU-8), followed by dual-sided molding of a single layer of polydimethylsiloxane (PDMS) using a mechanical jig for precise motion control; and finally, alignment, stacking, and adhesion of multiple PDMS layers to achieve a 3D structure. This technique was used to produce 3D Texture and 3D Smooth PDMS scaffolds, where the surface topography comprised 10 μm-diameter/height posts and smooth surfaces, respectively. The potential utility of the 3D microfabricated scaffolds, and the role of surface topography, were subsequently investigated in vitro with a combined heterogeneous population of adult human stem cells and their resultant progenitor cells, collectively termed connective tissue progenitors (CTPs), under conditions promoting the osteoblastic phenotype. Examination of bone-marrow derived CTPs cultured on the 3D Texture scaffold for 9 days revealed cell growth in three dimensions and increased cell numbers compared to those on the 3D Smooth scaffold. Furthermore, expression of alkaline phosphatase mRNA was higher on the 3D Texture scaffold, while osteocalcin mRNA expression was comparable for both types of scaffolds. PMID:19524292

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

MRI Texture Analysis of Background Parenchymal Enhancement of the Breast

PubMed Central

Woo, Jun; Amano, Maki; Yanagisawa, Fumi; Yamamoto, Hiroshi; Tani, Mayumi

2017-01-01

Purpose The purpose of this study was to determine texture parameters reflecting the background parenchymal enhancement (BPE) of the breast, which were acquired using texture analysis (TA). Methods We investigated 52 breasts of the 26 subjects who underwent dynamic contrast-enhanced MRI. One experienced reader scored BPE visually (i.e., minimal, mild, moderate, and marked). TA, including 12 texture parameters, was performed to distinguish the BPE scores quantitatively. Relationships between the visual BPE scores and texture parameters were evaluated using analysis of variance and receiver operating characteristic analysis. Results The variance and skewness of signal intensity were useful for differentiating between moderate and mild or minimal BPE or between mild and minimal BPE, respectively, with the cutoff value of 356.7 for variance and that of 0.21 for skewness. Some TA features could be useful for defining breast lesions from the BPE. Conclusion TA may be useful for quantifying the BPE of the breast. PMID:28812015

Structural texture similarity metrics for image analysis and retrieval.

PubMed

Zujovic, Jana; Pappas, Thrasyvoulos N; Neuhoff, David L

2013-07-01

We develop new metrics for texture similarity that accounts for human visual perception and the stochastic nature of textures. The metrics rely entirely on local image statistics and allow substantial point-by-point deviations between textures that according to human judgment are essentially identical. The proposed metrics extend the ideas of structural similarity and are guided by research in texture analysis-synthesis. They are implemented using a steerable filter decomposition and incorporate a concise set of subband statistics, computed globally or in sliding windows. We conduct systematic tests to investigate metric performance in the context of "known-item search," the retrieval of textures that are "identical" to the query texture. This eliminates the need for cumbersome subjective tests, thus enabling comparisons with human performance on a large database. Our experimental results indicate that the proposed metrics outperform peak signal-to-noise ratio (PSNR), structural similarity metric (SSIM) and its variations, as well as state-of-the-art texture classification metrics, using standard statistical measures.

Acoustoelastic effect of textured (Ba,Sr)TiO{sub 3} thin films under an initial mechanical stress

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kamel, Marwa; Mseddi, Souhir; Njeh, Anouar

Acoustoelastic (AE) analysis of initial stresses plays an important role as a nondestructive tool in current engineering. Two textured BST (Ba{sub 0.65}Sr{sub 0.35}TiO{sub 3}) thin films, with different substrate to target distance, were grown on Pt(111)/TiO{sub 2}/SiO{sub 2}/Si(001) substrate by rf-magnetron sputtering deposition techniques. A conventional “sin{sup 2} ψ” method to determine residual stress and strain in BST films by X-ray diffraction is applied. A laser acoustic waves (LA-waves) technique is used to generate surface acoustic waves (SAW) propagating in both samples. Young's modulus E and Poisson ratio ν of BST films in different propagation directions are derived from the measuredmore » dispersion curves. Estimation of effective second-order elastic constants of BST thin films in stressed states is served in SAW study. This paper presents an original investigation of AE effect in prestressed Ba{sub 0.65}Sr{sub 0.35}TiO{sub 3} films, where the effective elastic constants and the effect of texture on second and third order elastic tensor are considered and used. The propagation behavior of Rayleigh and Love waves in BST thin films under residual stress is explored and discussed. The guiding velocities affected by residual stresses, reveal some shifts which do not exceed four percent mainly in the low frequency range.« less

Texture Modification of the Shuttle Landing Facility Runway at Kennedy Space Center

NASA Technical Reports Server (NTRS)

Daugherty, Robert H.; Yager, Thomas J.

1997-01-01

This paper describes the test procedures and the criteria used in selecting an effective runway-surface-texture modification at the Kennedy Space Center (KSC) Shuttle Landing Facility (SLF) to reduce Orbiter tire wear. The new runway surface may ultimately result in an increase of allowable crosswinds for launch and landing operations. The modification allows launch and landing operations in 20-knot crosswinds, if desired. This 5-knot increase over the previous 15-knot limit drastically increases landing safety and the ability to make on-time launches to support missions in which Space Station rendezvous are planned. The paper presents the results of an initial (1988) texture modification to reduce tire spin-up wear and then describes a series of tests that use an instrumented ground-test vehicle to compare tire friction and wear characteristics, at small scale, of proposed texture modifications placed into the SLF runway surface itself. Based on these tests, three candidate surfaces were chosen to be tested at full-scale by using a highly modified and instrumented transport aircraft capable of duplicating full Orbiter landing profiles. The full-scale Orbiter tire testing revealed that tire wear could be reduced approximately by half with either of two candidates. The texture-modification technique using a Humble Equipment Company Skidabrader(trademark) shotpeening machine proved to be highly effective, and the entire SLF runway surface was modified in September 1994. The extensive testing and evaluation effort that preceded the selection of this particular surface-texture-modification technique is described herein.

Comparison of low-contrast detectability between two CT reconstruction algorithms using voxel-based 3D printed textured phantoms.

PubMed

Solomon, Justin; Ba, Alexandre; Bochud, François; Samei, Ehsan

2016-12-01

To use novel voxel-based 3D printed textured phantoms in order to compare low-contrast detectability between two reconstruction algorithms, FBP (filtered-backprojection) and SAFIRE (sinogram affirmed iterative reconstruction) and determine what impact background texture (i.e., anatomical noise) has on estimating the dose reduction potential of SAFIRE. Liver volumes were segmented from 23 abdominal CT cases. The volumes were characterized in terms of texture features from gray-level co-occurrence and run-length matrices. Using a 3D clustered lumpy background (CLB) model, a fitting technique based on a genetic optimization algorithm was used to find CLB textures that were reflective of the liver textures, accounting for CT system factors of spatial blurring and noise. With the modeled background texture as a guide, four cylindrical phantoms (Textures A-C and uniform, 165 mm in diameter, and 30 mm height) were designed, each containing 20 low-contrast spherical signals (6 mm diameter at nominal contrast levels of ∼3.2, 5.2, 7.2, 10, and 14 HU with four repeats per signal). The phantoms were voxelized and input into a commercial multimaterial 3D printer (Object Connex 350), with custom software for voxel-based printing (using principles of digital dithering). Images of the textured phantoms and a corresponding uniform phantom were acquired at six radiation dose levels (SOMATOM Flash, Siemens Healthcare) and observer model detection performance (detectability index of a multislice channelized Hotelling observer) was estimated for each condition (5 contrasts × 6 doses × 2 reconstructions × 4 backgrounds = 240 total conditions). A multivariate generalized regression analysis was performed (linear terms, no interactions, random error term, log link function) to assess whether dose, reconstruction algorithm, signal contrast, and background type have statistically significant effects on detectability. Also, fitted curves of detectability (averaged across contrast levels) as a function of dose were constructed for each reconstruction algorithm and background texture. FBP and SAFIRE were compared for each background type to determine the improvement in detectability at a given dose, and the reduced dose at which SAFIRE had equivalent performance compared to FBP at 100% dose. Detectability increased with increasing radiation dose (P = 2.7 × 10 -59 ) and contrast level (P = 2.2 × 10 -86 ) and was higher in the uniform phantom compared to the textured phantoms (P = 6.9 × 10 -51 ). Overall, SAFIRE had higher d' compared to FBP (P = 0.02). The estimated dose reduction potential of SAFIRE was found to be 8%, 10%, 27%, and 8% for Texture-A, Texture-B, Texture-C and uniform phantoms. In all background types, detectability was higher with SAFIRE compared to FBP. However, the relative improvement observed from SAFIRE was highly dependent on the complexity of the background texture. Iterative algorithms such as SAFIRE should be assessed in the most realistic context possible.

Comparative analysis of classification based algorithms for diabetes diagnosis using iris images.

PubMed

Samant, Piyush; Agarwal, Ravinder

2018-01-01

Photo-diagnosis is always an intriguing area for the researchers, with the advancement of image processing and computer machine vision techniques it have become more reliable and popular in recent years. The objective of this paper is to study the change in the features of iris, particularly irregularities in the pigmentation of certain areas of the iris with respect to diabetic health of an individual. Apart from the point that iris recognition concentrates on the overall structure of the iris, diagnostic techniques emphasises the local variations in the particular area of iris. Pre-image processing techniques have been applied to extract iris and thereafter, region of interest from the extracted iris have been cropped out. In order to observe the changes in the tissue pigmentation of region of interest, statistical, texture textural and wavelet features have been extracted. At the end, a comparison of accuracies of five different classifiers has been presented to classify two subject groups of diabetic and non-diabetic. Best classification accuracy has been calculated as 89.66% by the random forest classifier. Results have been shown the effectiveness and diagnostic significance of the proposed methodology. Presented piece of work offers a novel systemic perspective of non-invasive and automatic diabetic diagnosis.

Statistical ultrasonics: the influence of Robert F. Wagner

NASA Astrophysics Data System (ADS)

Insana, Michael F.

2009-02-01

An important ongoing question for higher education is how to successfully mentor the next generation of scientists and engineers. It has been my privilege to have been mentored by one of the best, Dr Robert F. Wagner and his colleagues at the CDRH/FDA during the mid 1980s. Bob introduced many of us in medical ultrasonics to statistical imaging techniques. These ideas continue to broadly influence studies on adaptive aperture management (beamforming, speckle suppression, compounding), tissue characterization (texture features, Rayleigh/Rician statistics, scatterer size and number density estimators), and fundamental questions about how limitations of the human eye-brain system for extracting information from textured images can motivate image processing. He adapted the classical techniques of signal detection theory to coherent imaging systems that, for the first time in ultrasonics, related common engineering metrics for image quality to task-based clinical performance. This talk summarizes my wonderfully-exciting three years with Bob as I watched him explore topics in statistical image analysis that formed a rational basis for many of the signal processing techniques used in commercial systems today. It is a story of an exciting time in medical ultrasonics, and of how a sparkling personality guided and motivated the development of junior scientists who flocked around him in admiration and amazement.

Fast Image Texture Classification Using Decision Trees

NASA Technical Reports Server (NTRS)

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.

Surface Texture-Induced Enhancement of Optical and Photoelectrochemical Activity of Cu2ZnSnS4 Photocathodes

NASA Astrophysics Data System (ADS)

Sarswat, Prashant K.; Deka, Nipon; Jagan Mohan Rao, S.; Free, Michael L.; Kumar, Gagan

2017-08-01

The objective of this work is to understand and improve the photocatalytic activity of Cu2ZnSnS4 (CZTS) through postgrowth modification techniques to create surface textures. This objective can be achieved using a combination of solvents, etching agents, and anodization techniques. One of the most effective surface treatments for enhancing the surface properties of photovoltaic materials is formation of nanoscale flakes, although other surface modifications were also evaluated. The superior performance of textured films can be attributed to enhanced surface area of absorber material exposed to electrolyte, ZnS deficiency, and high catalytic activity due to reduced charge-transfer resistance. Fine-tuning of ion flux and electrolyte stoichiometry can be used to create a controlled growth algorithm for CZTS thin films. The resulting information can be utilized to optimize film properties. The utility of nanostructured or engineered surfaces was evaluated using photoelectrochemical measurements. Finite-difference time-domain (FDTD)-assisted simulations were conducted for selected texturing, revealing enhanced surface area of absorbing medium that ultimately resulted in greater power loss of light in the medium.

Topographic modelling of haptic properties of tissue products

NASA Astrophysics Data System (ADS)

Rosen, B.-G.; Fall, A.; Rosen, S.; Farbrot, A.; Bergström, P.

2014-03-01

The way a product or material feels when touched, haptics, has been shown to be a property that plays an important role when consumers determine the quality of products For tissue products in constant touch with the skin, softness" becomes a primary quality parameter. In the present work, the relationship between topography and the feeling of the surface has been investigated for commercial tissues with varying degree of texture from the low textured crepe tissue to the highly textured embossed- and air-dried tissue products. A trained sensory panel at was used to grade perceived haptic "roughness". The technique used to characterize the topography was Digital light projection (DLP) technique, By the use of multivariate statistics, strong correlations between perceived roughness and topography were found with predictability of above 90 percent even though highly textured products were included. Characterization was made using areal ISO 25178-2 topography parameters in combination with non-contacting topography measurement. The best prediction ability was obtained when combining haptic properties with the topography parameters auto-correlation length (Sal), peak material volume (Vmp), core roughness depth (Sk) and the maximum height of the surface (Sz).

Theory of Image Analysis and Recognition.

DTIC Science & Technology

1983-01-24

Stanley M. Dunn, "Texture Classification with Change Point Statistics," TR- 1082 , July 1981. 97. R. Chellappa, "Synthesis of Textures Using Simultane...July 1981. 96. Stanley M. Dunn, "Texture Classification with Change Point Statistics," TR- 1082 , July 1981. * 97. R. Chellappa, "Synthesis of Textures

Metal catalyst technique for texturing silicon solar cells

DOEpatents

Ruby, Douglas S.; Zaidi, Saleem H.

2001-01-01

Textured silicon solar cells and techniques for their manufacture utilizing metal sources to catalyze formation of randomly distributed surface features such as nanoscale pyramidal and columnar structures. These structures include dimensions smaller than the wavelength of incident light, thereby resulting in a highly effective anti-reflective surface. According to the invention, metal sources present in a reactive ion etching chamber permit impurities (e.g. metal particles) to be introduced into a reactive ion etch plasma resulting in deposition of micro-masks on the surface of a substrate to be etched. Separate embodiments are disclosed including one in which the metal source includes one or more metal-coated substrates strategically positioned relative to the surface to be textured, and another in which the walls of the reaction chamber are pre-conditioned with a thin coating of metal catalyst material.

Prediction of canned black bean texture (Phaseolus vulgaris L.) from intact dry seeds using visible/near infrared spectroscopy and hyperspectral imaging data.

PubMed

Mendoza, Fernando A; Cichy, Karen A; Sprague, Christy; Goffnett, Amanda; Lu, Renfu; Kelly, James D

2018-01-01

Texture is a major quality parameter for the acceptability of canned whole beans. Prior knowledge of this quality trait before processing would be useful to guide variety development by bean breeders and optimize handling protocols by processors. The objective of this study was to evaluate and compare the predictive power of visible and near infrared reflectance spectroscopy (visible/NIRS, 400-2498 nm) and hyperspectral imaging (HYPERS, 400-1000 nm) techniques for predicting texture of canned black beans from intact dry seeds. Black beans were grown in Michigan (USA) over three field seasons. The samples exhibited phenotypic variability for canned bean texture due to genetic variability and processing practice. Spectral preprocessing methods (i.e. smoothing, first and second derivatives, continuous wavelet transform, and two-band ratios), coupled with a feature selection method, were tested for optimizing the prediction accuracy in both techniques based on partial least squares regression (PLSR) models. Visible/NIRS and HYPERS were effective in predicting texture of canned beans using intact dry seeds, as indicated by their correlation coefficients for prediction (R pred ) and standard errors of prediction (SEP). Visible/NIRS was superior (R pred = 0.546-0.923, SEP = 7.5-1.9 kg 100 g -1 ) to HYPERS (R pred = 0.401-0.883, SEP = 7.6-2.4 kg 100 g -1 ), which is likely due to the wider wavelength range collected in visible/NIRS. However, a significant improvement was reached in both techniques when the two-band ratios preprocessing method was applied to the data, reducing SEP by at least 10.4% and 16.2% for visible/NIRS and HYPERS, respectively. Moreover, results from using the combination of the three-season data sets based on the two-band ratios showed that visible/NIRS (R pred = 0.886, SEP = 4.0 kg 100 g -1 ) and HYPERS (R pred = 0.844, SEP = 4.6 kg 100 g -1 ) models were consistently successful in predicting texture over a wide range of measurements. Visible/NIRS and HYPERS have great potential for predicting the texture of canned beans; the robustness of the models is impacted by genotypic diversity, planting year and phenotypic variability for canned bean texture used for model building, and hence, robust models can be built based on data sets with high phenotypic diversity in textural properties, and periodically maintained and updated with new data. © 2017 Society of Chemical Industry. © 2017 Society of Chemical Industry.

Performance of two-lobe hole-entry hybrid journal bearing system under the combined influence of textured surface and couple stress lubricant

NASA Astrophysics Data System (ADS)

Khatri, Chandra B.; Sharma, Satish C.

2018-02-01

Textured surface in journal bearings is becoming an important area of investigation during the last few years. Surface textures have the shapes of micro-dimple with a small diameter and depth having order of magnitude of bearing clearance. This paper presents the influence of couple stress lubricant on the circular and non-circular hole-entry hybrid journal bearing system and reports the comparative study between the textured and non-textured circular/non-circular hybrid journal bearing system. The governing Reynolds equation has been modified for the couple stress lubricant flow in the clearance of bearing and journal. The FEM technique has been applied to solve the modified Reynolds equation together with restrictor flow equation. The numerically simulated results indicate that the influence of couple stress lubricant is significantly more in textured journal bearing than that of non-textured journal bearing. Further, it has been observed that the textured two-lobe (δ = 1.1) hybrid journal bearing lubricated with couple stress lubricant provides larger values of fluid film stiffness coefficients and stability threshold speed against other bearings studied in the present paper.

Quantitative Analysis of the Cervical Texture by Ultrasound and Correlation with Gestational Age.

PubMed

Baños, Núria; Perez-Moreno, Alvaro; Migliorelli, Federico; Triginer, Laura; Cobo, Teresa; Bonet-Carne, Elisenda; Gratacos, Eduard; Palacio, Montse

2017-01-01

Quantitative texture analysis has been proposed to extract robust features from the ultrasound image to detect subtle changes in the textures of the images. The aim of this study was to evaluate the feasibility of quantitative cervical texture analysis to assess cervical tissue changes throughout pregnancy. This was a cross-sectional study including singleton pregnancies between 20.0 and 41.6 weeks of gestation from women who delivered at term. Cervical length was measured, and a selected region of interest in the cervix was delineated. A model to predict gestational age based on features extracted from cervical images was developed following three steps: data splitting, feature transformation, and regression model computation. Seven hundred images, 30 per gestational week, were included for analysis. There was a strong correlation between the gestational age at which the images were obtained and the estimated gestational age by quantitative analysis of the cervical texture (R = 0.88). This study provides evidence that quantitative analysis of cervical texture can extract features from cervical ultrasound images which correlate with gestational age. Further research is needed to evaluate its applicability as a biomarker of the risk of spontaneous preterm birth, as well as its role in cervical assessment in other clinical situations in which cervical evaluation might be relevant. © 2016 S. Karger AG, Basel.

Microstructural and Textural Differences Induced by Water and Furnace Cooling in Commercially Pure Zr Annealed in the α + β Region

NASA Astrophysics Data System (ADS)

Chai, Linjiang; Wang, Tingting; Ren, Yi; Song, Bo; Guo, Ning; Chen, Liangyu

2018-07-01

In this work, a commercially pure Zr sheet with a typical bimodal basal texture was annealed in an α + β region and then subjected to different coolings (in water and furnace). Microstructures and textures of both the as-received and the heat-treated specimens were investigated by electron channeling contrast imaging and electron backscatter diffraction techniques. Results show that a duplex microstructure consisting of untransformed bulk α grains and twinned martensitic plates is produced in the water-cooled specimen, which possesses a weakened texture compared to the initial one. For the specimen cooled in furnace, however, a uniform microstructure fully comprised of coarser equiaxed grains with a strengthened texture is obtained. Analyses reveal that the rapid cooling in water could suppress variant selection behaviors during β → α transformation and allow α plates with scattered orientations to be nucleated inside β phases, contributing to the weakened texture. In contrast, during slow cooling in furnace, β boundaries would act as preferred nucleation sites of α embryos, resulting in a strong variant selection that accounts for the intensified texture.

Microstructural and Textural Differences Induced by Water and Furnace Cooling in Commercially Pure Zr Annealed in the α + β Region

NASA Astrophysics Data System (ADS)

Chai, Linjiang; Wang, Tingting; Ren, Yi; Song, Bo; Guo, Ning; Chen, Liangyu

2018-03-01

In this work, a commercially pure Zr sheet with a typical bimodal basal texture was annealed in an α + β region and then subjected to different coolings (in water and furnace). Microstructures and textures of both the as-received and the heat-treated specimens were investigated by electron channeling contrast imaging and electron backscatter diffraction techniques. Results show that a duplex microstructure consisting of untransformed bulk α grains and twinned martensitic plates is produced in the water-cooled specimen, which possesses a weakened texture compared to the initial one. For the specimen cooled in furnace, however, a uniform microstructure fully comprised of coarser equiaxed grains with a strengthened texture is obtained. Analyses reveal that the rapid cooling in water could suppress variant selection behaviors during β → α transformation and allow α plates with scattered orientations to be nucleated inside β phases, contributing to the weakened texture. In contrast, during slow cooling in furnace, β boundaries would act as preferred nucleation sites of α embryos, resulting in a strong variant selection that accounts for the intensified texture.

CFS-SMO based classification of breast density using multiple texture models.

PubMed

Sharma, Vipul; Singh, Sukhwinder

2014-06-01

It is highly acknowledged in the medical profession that density of breast tissue is a major cause for the growth of breast cancer. Increased breast density was found to be linked with an increased risk of breast cancer growth, as high density makes it difficult for radiologists to see an abnormality which leads to false negative results. Therefore, there is need for the development of highly efficient techniques for breast tissue classification based on density. This paper presents a hybrid scheme for classification of fatty and dense mammograms using correlation-based feature selection (CFS) and sequential minimal optimization (SMO). In this work, texture analysis is done on a region of interest selected from the mammogram. Various texture models have been used to quantify the texture of parenchymal patterns of breast. To reduce the dimensionality and to identify the features which differentiate between breast tissue densities, CFS is used. Finally, classification is performed using SMO. The performance is evaluated using 322 images of mini-MIAS database. Highest accuracy of 96.46% is obtained for two-class problem (fatty and dense) using proposed approach. Performance of selected features by CFS is also evaluated by Naïve Bayes, Multilayer Perceptron, RBF Network, J48 and kNN classifier. The proposed CFS-SMO method outperforms all other classifiers giving a sensitivity of 100%. This makes it suitable to be taken as a second opinion in classifying breast tissue density.

Fabrication and properties of radially <001>C textured PMN-PT cylinders for transducer applications

NASA Astrophysics Data System (ADS)

Poterala, Stephen F.; Meyer, Richard J.; Messing, Gary L.

2012-07-01

<001>C Textured PMN-PT ceramics have electromechanical properties (d33 = 850-1050 pm/V, k33 = 0.79-0.83) between those of conventional PZT ceramics and relaxor PMN-PT crystals. In this work, we tailor crystallographic orientation in textured PMN-PT ceramics for transducer designs with non-planar poling surfaces. Specifically, omni-directional cylindrical transducer elements were fabricated using monolithic, radially <001>C textured and poled PMN-PT ceramic. Texture was produced by templated grain growth using NBT-PT templates, which were oriented radially by wrapping green ceramic tapes around a cylindrical mandrel. Finished transducer elements measure ˜5 cm in diameter by ˜2.5 cm in height and demonstrate scalability of textured ceramic fabrication techniques. The fabricated cylinders are ˜50 vol. % textured and show high 31-mode electromechanical properties compared to PZT ceramics (d31 = -259 pm/V, k31 = 0.43, ɛT33 = 3000, and Qm = 350). Frequency bandwidth is related to the square of the hoop mode coupling coefficient kh2, which is ˜60% higher in textured PMN-PT cylinders compared to PZT 5H. Finite element simulations show that this parameter may be further increased by improving texture quality to ≥90 vol. %. Radially textured PMN-PT may thus improve performance in omni-directional cylindrical transducers while avoiding the need for segmented single crystal designs.

Method: automatic segmentation of mitochondria utilizing patch classification, contour pair classification, and automatically seeded level sets

PubMed Central

2012-01-01

Background While progress has been made to develop automatic segmentation techniques for mitochondria, there remains a need for more accurate and robust techniques to delineate mitochondria in serial blockface scanning electron microscopic data. Previously developed texture based methods are limited for solving this problem because texture alone is often not sufficient to identify mitochondria. This paper presents a new three-step method, the Cytoseg process, for automated segmentation of mitochondria contained in 3D electron microscopic volumes generated through serial block face scanning electron microscopic imaging. The method consists of three steps. The first is a random forest patch classification step operating directly on 2D image patches. The second step consists of contour-pair classification. At the final step, we introduce a method to automatically seed a level set operation with output from previous steps. Results We report accuracy of the Cytoseg process on three types of tissue and compare it to a previous method based on Radon-Like Features. At step 1, we show that the patch classifier identifies mitochondria texture but creates many false positive pixels. At step 2, our contour processing step produces contours and then filters them with a second classification step, helping to improve overall accuracy. We show that our final level set operation, which is automatically seeded with output from previous steps, helps to smooth the results. Overall, our results show that use of contour pair classification and level set operations improve segmentation accuracy beyond patch classification alone. We show that the Cytoseg process performs well compared to another modern technique based on Radon-Like Features. Conclusions We demonstrated that texture based methods for mitochondria segmentation can be enhanced with multiple steps that form an image processing pipeline. While we used a random-forest based patch classifier to recognize texture, it would be possible to replace this with other texture identifiers, and we plan to explore this in future work. PMID:22321695

Synthèse bibliographique : micro-texturation et microinjection de thermoplastiques

NASA Astrophysics Data System (ADS)

Vera, Julie; Brulez, Anne-Catherine; Contraires, Elise; Larochette, Mathieu; Valette, Stéphane; Benayoun, Stéphane

2017-12-01

La fonctionnalisation de surface des matériaux et notamment des polymères fait l'objet de recherches intenses dans de nombreux secteurs tels que l'industrie du biomédical ou du transport afin de conférer aux pièces des propriétés spécifiques comme l'antibuée, la réduction du frottement ou le dégivrage… Dans le cas d'une production en grande série de pièces polymères fonctionnalisées, il est préférable, pour des questions de coûts, de générer des textures, au moyen d'une technique de reproduction d'empreinte comme l'injection plastique. Toutefois les fonctions requises nécessitent parfois la reproduction de dimensions microniques voire submicroniques poussant à ses limites la maîtrise du procédé conventionnel, avec les caractéristiques de l'injection de micro-pièces, mais aussi des spécificités propres à la micro-texturation. L'objet de cette revue bibliographique est de couvrir le large spectre des problèmes techniques et scientifiques associés à la micro-texturation des pièces plastiques. Les techniques d'usinage de ces micro-motifs sur les outillages et le rôle des revêtements est particulièrement décrit ainsi que le besoin de mettre en œuvre des approches spécifiques de caractérisation topographique des textures. L'influence des paramètres du procédé d'injection est aussi discutée, soulignant la nécessité d'appréhender la micro-texturation des pièces plastiques avec une nouvelle grille de lecture de la microinjection.

Electric Arc and Electrochemical Surface Texturing Technologies

NASA Technical Reports Server (NTRS)

Banks, Bruce A.; Rutledge, Sharon K.; Snyder, Scott A.

1997-01-01

Surface texturing of conductive materials can readily be accomplished by means of a moving electric arc which produces a plasma from the environmental gases as well as from the vaporized substrate and arc electrode materials. As the arc is forced to move across the substrate surface, a condensate from the plasma re-deposits an extremely rough surface which is intimately mixed and attached to the substrate material. The arc textured surfaces produce greatly enhanced thermal emittance and hold potential for use as high temperature radiator surfaces in space, as well as in systems which use radiative heat dissipation such as computer assisted tomography (CAT) scan systems. Electrochemical texturing of titanium alloys can be accomplished by using sodium chloride solutions along with ultrasonic agitation to produce a random distribution of craters on the surface. The crater size and density can be controlled to produce surface craters appropriately sized for direct bone in-growth of orthopaedic implants. Electric arc texturing and electrochemical texturing techniques, surface properties and potential applications will be presented.

Extraction of texture features with a multiresolution neural network

NASA Astrophysics Data System (ADS)

Lepage, Richard; Laurendeau, Denis; Gagnon, Roger A.

1992-09-01

Texture is an important surface characteristic. Many industrial materials such as wood, textile, or paper are best characterized by their texture. Detection of defaults occurring on such materials or classification for quality control anD matching can be carried out through careful texture analysis. A system for the classification of pieces of wood used in the furniture industry is proposed. This paper is concerned with a neural network implementation of the features extraction and classification components of the proposed system. Texture appears differently depending at which spatial scale it is observed. A complete description of a texture thus implies an analysis at several spatial scales. We propose a compact pyramidal representation of the input image for multiresolution analysis. The feature extraction system is implemented on a multilayer artificial neural network. Each level of the pyramid, which is a representation of the input image at a given spatial resolution scale, is mapped into a layer of the neural network. A full resolution texture image is input at the base of the pyramid and a representation of the texture image at multiple resolutions is generated by the feedforward pyramid structure of the neural network. The receptive field of each neuron at a given pyramid level is preprogrammed as a discrete Gaussian low-pass filter. Meaningful characteristics of the textured image must be extracted if a good resolving power of the classifier must be achieved. Local dominant orientation is the principal feature which is extracted from the textured image. Local edge orientation is computed with a Sobel mask at four orientation angles (multiple of (pi) /4). The resulting intrinsic image, that is, the local dominant orientation image, is fed to the texture classification neural network. The classification network is a three-layer feedforward back-propagation neural network.

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

PubMed

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.

Non-destructive analysis of sensory traits of dry-cured loins by MRI-computer vision techniques and data mining.

PubMed

Caballero, Daniel; Antequera, Teresa; Caro, Andrés; Ávila, María Del Mar; G Rodríguez, Pablo; Perez-Palacios, Trinidad

2017-07-01

Magnetic resonance imaging (MRI) combined with computer vision techniques have been proposed as an alternative or complementary technique to determine the quality parameters of food in a non-destructive way. The aim of this work was to analyze the sensory attributes of dry-cured loins using this technique. For that, different MRI acquisition sequences (spin echo, gradient echo and turbo 3D), algorithms for MRI analysis (GLCM, NGLDM, GLRLM and GLCM-NGLDM-GLRLM) and predictive data mining techniques (multiple linear regression and isotonic regression) were tested. The correlation coefficient (R) and mean absolute error (MAE) were used to validate the prediction results. The combination of spin echo, GLCM and isotonic regression produced the most accurate results. In addition, the MRI data from dry-cured loins seems to be more suitable than the data from fresh loins. The application of predictive data mining techniques on computational texture features from the MRI data of loins enables the determination of the sensory traits of dry-cured loins in a non-destructive way. © 2016 Society of Chemical Industry. © 2016 Society of Chemical Industry.

Texture operator for snow particle classification into snowflake and graupel

NASA Astrophysics Data System (ADS)

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 additionally reduce the length of the feature vectors. The improvement of the correct classification efficiency for up to 100% is possible for methods: min-max histogram, texture operator built from structure achieved in a middle stage of co-occurrence matrix calculation, texture operator built from a structure achieved in a middle stage of grey-tone difference matrix creation, and texture operator based on a histogram, when the feature vector stores 99% of initial information.

Paraboloid Structured Silicon Surface for Enhanced Light Absorption: Experimental and Simulative Investigations

NASA Astrophysics Data System (ADS)

Khan, Firoz; Baek, Seong-Ho; Kaur, Jasmeet; Fareed, Imran; Mobin, Abdul; Kim, Jae Hyun

2015-09-01

In this paper, we present an optical model that simulates the light trapping and scattering effects of a paraboloid texture surface first time. This model was experimentally verified by measuring the reflectance values of the periodically textured silicon (Si) surface with the shape of a paraboloid under different conditions. A paraboloid texture surface was obtained by electrochemical etching Si in the solution of hydrofluoric acid, dimethylsulfoxide (DMSO), and deionized (DI) water. The paraboloid texture surface has the advantage of giving a lower reflectance value than the hemispherical, random pyramidal, and regular pyramidal texture surfaces. In the case of parabola, the light can be concentrated in the direction of the Si surface compared to the hemispherical, random pyramidal, and regular pyramidal textured surfaces. Furthermore, in a paraboloid textured surface, there can be a maximum value of 4 or even more by anisotropic etching duration compared to the hemispherical or pyramidal textured surfaces which have a maximum h/ D (depth and diameter of the texture) value of 0.5. The reflectance values were found to be strongly dependent on the h/ D ratio of the texture surface. The measured reflectance values were well matched with the simulated ones. The minimum reflectance value of ~4 % was obtained at a wavelength of 600 nm for an h/ D ratio of 3.75. The simulation results showed that the reflectance value for the h/ D ratio can be reduced to ~0.5 % by reducing the separations among the textures. This periodic paraboloidal structure can be applied to the surface texturing technique by substituting with a conventional pyramid textured surface or moth-eye antireflection coating.

Evaluation of Yogurt Microstructure Using Confocal Laser Scanning Microscopy and Image Analysis.

PubMed

Skytte, Jacob L; Ghita, Ovidiu; Whelan, Paul F; Andersen, Ulf; Møller, Flemming; Dahl, Anders B; Larsen, Rasmus

2015-06-01

The microstructure of protein networks in yogurts defines important physical properties of the yogurt and hereby partly its quality. Imaging this protein network using confocal scanning laser microscopy (CSLM) has shown good results, and CSLM has become a standard measuring technique for fermented dairy products. When studying such networks, hundreds of images can be obtained, and here image analysis methods are essential for using the images in statistical analysis. Previously, methods including gray level co-occurrence matrix analysis and fractal analysis have been used with success. However, a range of other image texture characterization methods exists. These methods describe an image by a frequency distribution of predefined image features (denoted textons). Our contribution is an investigation of the choice of image analysis methods by performing a comparative study of 7 major approaches to image texture description. Here, CSLM images from a yogurt fermentation study are investigated, where production factors including fat content, protein content, heat treatment, and incubation temperature are varied. The descriptors are evaluated through nearest neighbor classification, variance analysis, and cluster analysis. Our investigation suggests that the texton-based descriptors provide a fuller description of the images compared to gray-level co-occurrence matrix descriptors and fractal analysis, while still being as applicable and in some cases as easy to tune. © 2015 Institute of Food Technologists®

The promise and limits of PET texture analysis.

PubMed

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 T1-Weighted and Fluid-Attenuated Inversion Recovery Images Detects Abnormalities That Correlate With Cognitive Decline in Small Vessel Disease.

PubMed

Tozer, Daniel J; Zeestraten, Eva; Lawrence, Andrew J; Barrick, Thomas R; Markus, Hugh S

2018-06-04

Magnetic resonance imaging may be useful to assess disease severity in cerebral small vessel disease (SVD), identify those individuals who are most likely to progress to dementia, monitor disease progression, and act as surrogate markers to test new therapies. Texture analysis extracts information on the relationship between signal intensities of neighboring voxels. A potential advantage over techniques, such as diffusion tensor imaging, is that it can be used on clinically obtained magnetic resonance sequences. We determined whether texture parameters (TP) were abnormal in SVD, correlated with cognitive impairment, predicted cognitive decline, or conversion to dementia. In the prospective SCANS study (St George's Cognition and Neuroimaging in Stroke), we assessed TP in 121 individuals with symptomatic SVD at baseline, 99 of whom attended annual cognitive testing for 5 years. Conversion to dementia was recorded for all subjects during the 5-year period. Texture analysis was performed on fluid-attenuated inversion recovery and T1-weighted images. The TP obtained from the SVD cohort were cross-sectionally compared with 54 age-matched controls scanned on the same magnetic resonance imaging system. There were highly significant differences in several TP between SVD cases and controls. Within the SVD population, TP were highly correlated to other magnetic resonance imaging parameters (brain volume, white matter lesion volume, lacune count). TP correlated with executive function and global function at baseline and predicted conversion to dementia, after controlling for age, sex, premorbid intelligence quotient, and magnetic resonance parameters. TP, which can be obtained from routine clinical images, are abnormal in SVD, and the degree of abnormality correlates with executive dysfunction and global cognition at baseline and decline during 5 years. TP may be useful to assess disease severity in clinically collected data. This needs testing in data clinically acquired across multiple sites. © 2018 The Authors.

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

NASA Astrophysics Data System (ADS)

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.

Texturing of high T(sub c) superconducting polycrystalline fibers/wires by laser-driven directional solidification in an thermal gradient

NASA Technical Reports Server (NTRS)

Varshney, Usha; Eichelberger, B. Davis, III

1995-01-01

This paper summarizes the technique of laser-driven directional solidification in a controlled thermal gradient of yttria stabilized zirconia core coated Y-Ba-Cu-O materials to produce textured high T(sub c) superconducting polycrystalline fibers/wires with improved critical current densities in the extended range of magnetic fields at temperatures greater than 77 K. The approach involves laser heating to minimize phase segregation by heating very rapidly through the two-phase incongruent melt region to the single phase melt region and directionally solidifying in a controlled thermal gradient to achieve highly textured grains in the fiber axis direction. The technique offers a higher grain growth rate and a lower thermal budget compared with a conventional thermal gradient and is amenable as a continuous process for improving the J(sub c) of high T(sub c) superconducting polycrystalline fibers/wires. The technique has the advantage of suppressing weak-link behavior by orientation of crystals, formation of dense structures with enhanced connectivity, formation of fewer and cleaner grain boundaries, and minimization of phase segregation in the incongruent melt region.

Crystallographic texture in pulsed laser deposited hydroxyapatite bioceramic coatings

PubMed Central

Kim, Hyunbin; Camata, Renato P.; Lee, Sukbin; Rohrer, Gregory S.; Rollett, Anthony D.; Vohra, Yogesh K.

2008-01-01

The orientation texture of pulsed laser deposited hydroxyapatite coatings was studied by X-ray diffraction techniques. Increasing the laser energy density of the KrF excimer laser used in the deposition process from 5 to 7 J/cm2 increases the tendency for the c-axes of the hydroxyapatite grains to be aligned perpendicular to the substrate. This preferred orientation is most pronounced when the incidence direction of the plume is normal to the substrate. Orientation texture of the hydroxyapatite grains in the coatings is associated with the highly directional and energetic nature of the ablation plume. Anisotropic stresses, transport of hydroxyl groups and dehydroxylation effects during deposition all seem to play important roles in the texture development. PMID:18563207

Study on cavitation effect of mechanical seals with laser-textured porous surface

NASA Astrophysics Data System (ADS)

Liu, T.; Chen, H. l.; Liu, Y. H.; Wang, Q.; Liu, Z. B.; Hou, D. H.

2012-11-01

Study on the mechanisms underlying generation of hydrodynamic pressure effect associated with laser-textured porous surface on mechanical seal, is the key to seal and lubricant properties. The theory model of mechanical seals with laser-textured porous surface (LES-MS) based on cavitation model was established. The LST-MS was calculated and analyzed by using Fluent software with full cavitation model and non-cavitation model and film thickness was predicted by the dynamic mesh technique. The results indicate that the effect of hydrodynamic pressure and cavitation are the important reasons to generate liquid film opening force on LST-MS; Cavitation effect can enhance hydrodynamic pressure effect of LST-MS; The thickness of liquid film could be well predicted with the method of dynamic mesh technique on Fluent and it becomes larger as the increasing of shaft speed and the decreasing of pressure.

Measurement of Vibrated Bulk Density of Coke Particle Blends Using Image Texture Analysis

NASA Astrophysics Data System (ADS)

Azari, Kamran; Bogoya-Forero, Wilinthon; Duchesne, Carl; Tessier, Jayson

2017-09-01

A rapid and nondestructive machine vision sensor was developed for predicting the vibrated bulk density (VBD) of petroleum coke particles based on image texture analysis. It could be used for making corrective adjustments to a paste plant operation to reduce green anode variability (e.g., changes in binder demand). Wavelet texture analysis (WTA) and gray level co-occurrence matrix (GLCM) algorithms were used jointly for extracting the surface textural features of coke aggregates from images. These were correlated with the VBD using partial least-squares (PLS) regression. Coke samples of several sizes and from different sources were used to test the sensor. Variations in the coke surface texture introduced by coke size and source allowed for making good predictions of the VBD of individual coke samples and mixtures of them (blends involving two sources and different sizes). Promising results were also obtained for coke blends collected from an industrial-baked carbon anode manufacturer.

Kansas environmental and resource study: A Great Plains model, tasks 1-6

NASA Technical Reports Server (NTRS)

Haralick, R. M.; Kanemasu, E. T.; Morain, S. A.; Yarger, H. L. (Principal Investigator); Ulaby, F. T.; Shanmugam, K. S.; Williams, D. L.; Mccauley, J. R.; Mcnaughton, J. L.

1972-01-01

There are no author identified significant results in this report. Environmental and resources investigations in Kansas utilizing ERTS-1 imagery are summarized for the following areas: (1) use of feature extraction techniqued for texture context information in ERTS imagery; (2) interpretation and automatic image enhancement; (3) water use, production, and disease detection and predictions for wheat; (4) ERTS-1 agricultural statistics; (5) monitoring fresh water resources; and (6) ground pattern analysis in the Great Plains.

Visualization techniques for tongue analysis in traditional Chinese medicine

NASA Astrophysics Data System (ADS)

Pham, Binh L.; Cai, Yang

2004-05-01

Visual inspection of the tongue has been an important diagnostic method of Traditional Chinese Medicine (TCM). Clinic data have shown significant connections between various viscera cancers and abnormalities in the tongue and the tongue coating. Visual inspection of the tongue is simple and inexpensive, but the current practice in TCM is mainly experience-based and the quality of the visual inspection varies between individuals. The computerized inspection method provides quantitative models to evaluate color, texture and surface features on the tongue. In this paper, we investigate visualization techniques and processes to allow interactive data analysis with the aim to merge computerized measurements with human expert's diagnostic variables based on five-scale diagnostic conditions: Healthy (H), History Cancers (HC), History of Polyps (HP), Polyps (P) and Colon Cancer (C).

A subjective study and an objective metric to quantify the granularity level of textures

NASA Astrophysics Data System (ADS)

Subedar, Mahesh M.; Karam, Lina J.

2015-03-01

Texture granularity is an important visual characteristic that is useful in a variety of applications, including analysis, recognition, and compression, to name a few. A texture granularity measure can be used to quantify the perceived level of texture granularity. The granularity level of the textures is influenced by the size of the texture primitives. A primitive is defined as the smallest recognizable repetitive object in the texture. If the texture has large primitives then the perceived granularity level tends to be lower as compared to a texture with smaller primitives. In this work we are presenting a texture granularity database referred as GranTEX which consists of 30 textures with varying levels of primitive sizes and granularity levels. The GranTEX database consists of both natural and man-made textures. A subjective study is conducted to measure the perceived granularity level of textures present in the GranTEX database. An objective metric that automatically measures the perceived granularity level of textures is also presented as part of this work. It is shown that the proposed granularity metric correlates well with the subjective granularity scores.

Quantitative phase and texture angularity analysis of brain white matter lesions in multiple sclerosis

NASA Astrophysics Data System (ADS)

Baxandall, Shalese; Sharma, Shrushrita; Zhai, Peng; Pridham, Glen; Zhang, Yunyan

2018-03-01

Structural changes to nerve fiber tracts are extremely common in neurological diseases such as multiple sclerosis (MS). Accurate quantification is vital. However, while nerve fiber damage is often seen as multi-focal lesions in magnetic resonance imaging (MRI), measurement through visual perception is limited. Our goal was to characterize the texture pattern of the lesions in MRI and determine how texture orientation metrics relate to lesion structure using two new methods: phase congruency and multi-resolution spatial-frequency analysis. The former aims to optimize the detection of the `edges and corners' of a structure, and the latter evaluates both the radial and angular distributions of image texture associated with the various forming scales of a structure. The radial texture spectra were previously confirmed to measure the severity of nerve fiber damage, and were thus included for validation. All measures were also done in the control brain white matter for comparison. Using clinical images of MS patients, we found that both phase congruency and weighted mean phase detected invisible lesion patterns and were significantly greater in lesions, suggesting higher structure complexity, than the control tissue. Similarly, multi-angular spatial-frequency analysis detected much higher texture across the whole frequency spectrum in lesions than the control areas. Such angular complexity was consistent with findings from radial texture. Analysis of the phase and texture alignment may prove to be a useful new approach for assessing invisible changes in lesions using clinical MRI and thereby lead to improved management of patients with MS and similar disorders.

Multifunctional Textured Surfaces with Enhanced Friction and Hydrophobic Behaviors Produced by Fiber Debonding and Pullout.

PubMed

Rizvi, Reza; Anwer, Ali; Fernie, Geoff; Dutta, Tilak; Naguib, Hani

2016-11-02

Fiber debonding and pullout are well-understood processes that occur during damage and failure events in composite materials. In this study, we show how these mechanisms, under controlled conditions, can be used to produce multifunctional textured surfaces. A two-step process consisting of (1) achieving longitudinal fiber alignment followed by (2) cutting, rearranging, and joining is used to produce the textured surfaces. This process employs common composite manufacturing techniques and uses no reactive chemicals or wet handling, making it suitable for scalability. This uniform textured surface is due to the fiber debonding and pullout occurring during the cutting process. Using well-established fracture mechanics principles for composite materials, we demonstrate how different material parameters such as fiber geometry, fiber and matrix stiffness and strength, and interface behavior can be used to achieve multifunctional textured surfaces. The resulting textured surfaces show very high friction coefficients on wet ice (9× improvement), indicating their promising potential as materials for ice traction/tribology. Furthermore, the texturing enhances the surface's hydrophobicity as indicated by an increase in the contact angle of water by 30%. The substantial improvements to surface tribology and hydrophobicity make fiber debonding and pullout an effective, simple, and scalable method of producing multifunctional textured surfaces.

Detecting perceptual groupings in textures by continuity considerations

NASA Technical Reports Server (NTRS)

Greene, Richard J.

1990-01-01

A generalization is presented for the second derivative of a Gaussian D(sup 2)G operator to apply to problems of perceptual organization involving textures. Extensions to other problems of perceptual organization are evident and a new research direction can be established. The technique presented is theoretically pleasing since it has the potential of unifying the entire area of image segmentation under the mathematical notion of continuity and presents a single algorithm to form perceptual groupings where many algorithms existed previously. The eventual impact on both the approach and technique of image processing segmentation operations could be significant.

Bone texture analysis on dental radiographic images: results with several angulated radiographs on the same region of interest

NASA Astrophysics Data System (ADS)

Amouriq, Yves; Guedon, Jeanpierre; Normand, Nicolas; Arlicot, Aurore; Benhdech, Yassine; Weiss, Pierre

2011-03-01

Bone microarchitecture is the predictor of bone quality or bone disease. It can only be measured on a bone biopsy, which is invasive and not available for all clinical situations. Texture analysis on radiographs is a common way to investigate bone microarchitecture. But relationship between three-dimension histomorphometric parameters and two-dimension texture parameters is not always well known, with poor results. The aim of this study is to performed angulated radiographs of the same region of interest and see if a better relationship between texture analysis on several radiographs and histomorphometric parameters can be developed. Computed radiography images of dog (Beagle) mandible section in molar regions were compared with high-resolution micro-CT (Computed-Tomograph) volumes. Four radiographs with 27° angle (up, down, left, right, using Rinn ring and customized arm positioning system) were performed from initial radiograph position. Bone texture parameters were calculated on all images. Texture parameters were also computed from new images obtained by difference between angulated images. Results of fractal values in different trabecular areas give some caracterisation of bone microarchitecture.

A comparison between Warner-Bratzler shear force measurement and texture profile analysis of meat and meat products: a review

NASA Astrophysics Data System (ADS)

Novaković, S.; Tomašević, I.

2017-09-01

Texture is one of the most important characteristics of meat and we can explain it as the human physiological-psychological awareness of a number of rheological and other properties of foods and their relations. In this paper, we discuss instrumental measurement of texture by Warner-Bratzler shear force (WBSF) and texture profile analysis (TPA). The conditions for using the device are detailed in WBSF measurements, and the influence of different parameters on the execution of the method and final results are shown. After that, the main disadvantages are reflected in the non-standardized method. Also, we introduce basic texture parameters which connect and separate TPA and WBSF methods and mention contemporary methods with their main advantage.

When is a soil remediated? Comparison of biopiled and windrowed soils contaminated with bunker-fuel in a full-scale trial.

PubMed

Coulon, Frédéric; Al Awadi, Mohammed; Cowie, William; Mardlin, David; Pollard, Simon; Cunningham, Colin; Risdon, Graeme; Arthur, Paul; Semple, Kirk T; Paton, Graeme I

2010-10-01

A six month field scale study was carried out to compare windrow turning and biopile techniques for the remediation of soil contaminated with bunker C fuel oil. End-point clean-up targets were defined by human risk assessment and ecotoxicological hazard assessment approaches. Replicate windrows and biopiles were amended with either nutrients and inocula, nutrients alone or no amendment. In addition to fractionated hydrocarbon analysis, culturable microbial characterisation and soil ecotoxicological assays were performed. This particular soil, heavy in texture and historically contaminated with bunker fuel was more effectively remediated by windrowing, but coarser textures may be more amendable to biopiling. This trial reveals the benefit of developing risk and hazard based approaches in defining end-point bioremediation of heavy hydrocarbons when engineered biopile or windrow are proposed as treatment option. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Scale invariant texture descriptors for classifying celiac disease

PubMed Central

Hegenbart, Sebastian; Uhl, Andreas; Vécsei, Andreas; Wimmer, Georg

2013-01-01

Scale invariant texture recognition methods are applied for the computer assisted diagnosis of celiac disease. In particular, emphasis is given to techniques enhancing the scale invariance of multi-scale and multi-orientation wavelet transforms and methods based on fractal analysis. After fine-tuning to specific properties of our celiac disease imagery database, which consists of endoscopic images of the duodenum, some scale invariant (and often even viewpoint invariant) methods provide classification results improving the current state of the art. However, not each of the investigated scale invariant methods is applicable successfully to our dataset. Therefore, the scale invariance of the employed approaches is explicitly assessed and it is found that many of the analyzed methods are not as scale invariant as they theoretically should be. Results imply that scale invariance is not a key-feature required for successful classification of our celiac disease dataset. PMID:23481171

The effectiveness of texture analysis for mapping forest land using the panchromatic bands of Landsat 7, SPOT, and IRS imagery

Treesearch

Michael L. Hoppus; Rachel I. Riemann; Andrew J. Lister; Mark V. Finco

2002-01-01

The panchromatic bands of Landsat 7, SPOT, and IRS satellite imagery provide an opportunity to evaluate the effectiveness of texture analysis of satellite imagery for mapping of land use/cover, especially forest cover. A variety of texture algorithms, including standard deviation, Ryherd-Woodcock minimum variance adaptive window, low pass etc., were applied to moving...

A Community Database of Quartz Microstructures: Can we make measurements that constrain rheology?

NASA Astrophysics Data System (ADS)

Toy, Virginia; Peternell, Mark; Morales, Luiz; Kilian, Ruediger

2014-05-01

Rheology can be explored by performing deformation experiments, and by examining resultant microstructures and textures as links to naturally deformed rocks. Certain deformation processes are assumed to result in certain microstructures or textures, of which some might be uniquely indicative, while most cannot be unequivocally used to interpret the deformation mechanism and hence rheology. Despite our lack of a sufficient understanding of microstructure and texture forming processes, huge advances in texture measurements and quantification of microstructural parameters have been made. Unfortunately, there are neither standard procedures nor a common consensus on interpretation of many parameters (e.g. texture, grain size, shape preferred orientation). Textures (crystallographic preferred orientations) have been extensively correlated to the interpretation of deformation mechanisms. For example the strength of textures can be measured either from the orientation distribution function (e.g. the J-index (Bunge, 1983) or texture entropy (Hielscher et al., 2007) or via the intensity of polefigures. However, there are various ways to identify a representative volume, to measure, to process the data and to calculate an odf and texture descriptors, which restricts their use as a comparative and diagnostic measurement. Microstructural parameters such as grain size, grain shape descriptors and fabric descriptors are similarly used to deduce and quantify deformation mechanisms. However there is very little consensus on how to measure and calculate some of these very important parameters, e.g. grain size which makes comparison of a vast amount of precious data in the literature very difficult. We propose establishing a community database of a standard set of such measurements, made using typical samples of different types of quartz rocks through standard methods of microstructural and texture quantification. We invite suggestions and discussion from the community about the worth of proposed parameters, methodology and usefulness and willingness to contribute to a database with free access of the community. We further invite institutions to participate on a benchmark analysis of a set of 'standard' thin sections. Bunge, H.J. 1983, Texture Analysis in Materials Science: mathematical methods. Butterworth-Heinemann, 593pp. Hielscher, R., Schaeben, H., Chateigner, D., 2007, On the entropy to texture index relationship in quantitative texture analysis: Journal of Applied Crystallography 40, 371-375.

Textural states of a hot-worked MA2-1 magnesium alloy

NASA Astrophysics Data System (ADS)

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.

Multi Texture Analysis of Colorectal Cancer Continuum Using Multispectral Imagery

PubMed Central

Chaddad, Ahmad; Desrosiers, Christian; Bouridane, Ahmed; Toews, Matthew; Hassan, Lama; Tanougast, Camel

2016-01-01

Purpose This paper proposes to characterize the continuum of colorectal cancer (CRC) using multiple texture features extracted from multispectral optical microscopy images. Three types of pathological tissues (PT) are considered: benign hyperplasia, intraepithelial neoplasia and carcinoma. Materials and Methods In the proposed approach, the region of interest containing PT is first extracted from multispectral images using active contour segmentation. This region is then encoded using texture features based on the Laplacian-of-Gaussian (LoG) filter, discrete wavelets (DW) and gray level co-occurrence matrices (GLCM). To assess the significance of textural differences between PT types, a statistical analysis based on the Kruskal-Wallis test is performed. The usefulness of texture features is then evaluated quantitatively in terms of their ability to predict PT types using various classifier models. Results Preliminary results show significant texture differences between PT types, for all texture features (p-value < 0.01). Individually, GLCM texture features outperform LoG and DW features in terms of PT type prediction. However, a higher performance can be achieved by combining all texture features, resulting in a mean classification accuracy of 98.92%, sensitivity of 98.12%, and specificity of 99.67%. Conclusions These results demonstrate the efficiency and effectiveness of combining multiple texture features for characterizing the continuum of CRC and discriminating between pathological tissues in multispectral images. PMID:26901134

Neural net classification of liver ultrasonogram for quantitative evaluation of diffuse liver disease

NASA Astrophysics Data System (ADS)

Lee, Dong Hyuk; Kim, JongHyo; Kim, Hee C.; Lee, Yong W.; Min, Byong Goo

1997-04-01

There have been a number of studies on the quantitative evaluation of diffuse liver disease by using texture analysis technique. However, the previous studies have been focused on the classification between only normal and abnormal pattern based on textural properties, resulting in lack of clinically useful information about the progressive status of liver disease. Considering our collaborative research experience with clinical experts, we judged that not only texture information but also several shape properties are necessary in order to successfully classify between various states of disease with liver ultrasonogram. Nine image parameters were selected experimentally. One of these was texture parameter and others were shape parameters measured as length, area and curvature. We have developed a neural-net algorithm that classifies liver ultrasonogram into 9 categories of liver disease: 3 main category and 3 sub-steps for each. Nine parameters were collected semi- automatically from the user by using graphical user interface tool, and then processed to give a grade for each parameter. Classifying algorithm consists of two steps. At the first step, each parameter was graded into pre-defined levels using neural network. in the next step, neural network classifier determined disease status using graded nine parameters. We implemented a PC based computer-assist diagnosis workstation and installed it in radiology department of Seoul National University Hospital. Using this workstation we collected 662 cases during 6 months. Some of these were used for training and others were used for evaluating accuracy of the developed algorithm. As a conclusion, a liver ultrasonogram classifying algorithm was developed using both texture and shape parameters and neural network classifier. Preliminary results indicate that the proposed algorithm is useful for evaluation of diffuse liver disease.

Multi-scale textural feature extraction and particle swarm optimization based model selection for false positive reduction in mammography.

PubMed

Zyout, Imad; Czajkowska, Joanna; Grzegorzek, Marcin

2015-12-01

The high number of false positives and the resulting number of avoidable breast biopsies are the major problems faced by current mammography Computer Aided Detection (CAD) systems. False positive reduction is not only a requirement for mass but also for calcification CAD systems which are currently deployed for clinical use. This paper tackles two problems related to reducing the number of false positives in the detection of all lesions and masses, respectively. Firstly, textural patterns of breast tissue have been analyzed using several multi-scale textural descriptors based on wavelet and gray level co-occurrence matrix. The second problem addressed in this paper is the parameter selection and performance optimization. For this, we adopt a model selection procedure based on Particle Swarm Optimization (PSO) for selecting the most discriminative textural features and for strengthening the generalization capacity of the supervised learning stage based on a Support Vector Machine (SVM) classifier. For evaluating the proposed methods, two sets of suspicious mammogram regions have been used. The first one, obtained from Digital Database for Screening Mammography (DDSM), contains 1494 regions (1000 normal and 494 abnormal samples). The second set of suspicious regions was obtained from database of Mammographic Image Analysis Society (mini-MIAS) and contains 315 (207 normal and 108 abnormal) samples. Results from both datasets demonstrate the efficiency of using PSO based model selection for optimizing both classifier hyper-parameters and parameters, respectively. Furthermore, the obtained results indicate the promising performance of the proposed textural features and more specifically, those based on co-occurrence matrix of wavelet image representation technique. Copyright © 2015 Elsevier Ltd. All rights reserved.

Instrumental texture characteristics of broiler pectoralis major with the wooden breast condition.

PubMed

Chatterjee, D; Zhuang, H; Bowker, B C; Rincon, A M; Sanchez-Brambila, G

2016-10-01

The objective was to characterize texture properties of raw and cooked broiler fillets (Pectoralis major) with the wooden breast condition (WBC) using the instrumental texture techniques of Meullenet-Owens Razor Shear (MORS) and Texture Profile Analysis (TPA). Deboned (3 h postmortem) broiler fillets were collected from a commercial plant and categorized as normal, moderate, or severe WBC based on the incidence and severity of diffuse hardened areas throughout fillets and the degree of palpable hardness. The fillets were then either stored at 4°C overnight or in a -20°C freezer. The MORS and TPA of the raw samples were determined at 24 h postmortem for fresh samples and after thawing overnight for frozen samples. The same measurements were also taken after the samples were cooked to 78°C. Regardless of freshness (fresh vs. frozen-thawed), cooking (raw vs. cooked), and degree of WBC, both MORS force and energy of the WBC samples were higher than that of the normal samples (P < 0.05). For TPA adhesiveness and resilience, there were no differences between normal and WBC samples (P > 0.05). However, average TPA hardness and chewiness measurements of the fillets with WBC were higher than the normal fillets (P < 0.05). Regardless of texture measurement, there were no interactions between freshness and the wooden condition or no differences between moderate and severe WBC fillets (P > 0.05). These results demonstrate that there are significant differences in instrumental texture properties between normal fillets and those exhibiting the WBC. The WBC fillets required more force to cut through, harder, and chewier than normal breast muscles. These results suggest that cooked WBC meat would likely be tougher than cooked normal meat. Published by Oxford University Press on behalf of Poultry Science Association 2016. This work is written by (a) US Government employee(s) and is in the public domain in the US.

The simulation of the half-dry stroke based on the force feedback technology

NASA Astrophysics Data System (ADS)

Guo, Chao; Hou, Zeng-xuan; Zheng, Shuan-zhu; Yang, Guang-qing

2017-02-01

A novel stroke simulation method of the Half-dry style of Chinese calligraphy based on the force feedback technology is proposed for the virtual painting. Firstly, according to the deformation of the brush when the force is exerted on it, the brush footprint between the brush and paper is calculated. The complete brush stroke is obtained by superimposing brush footprints along the painting direction, and the dynamic painting of the brush stroke is implemented. Then, we establish the half-dry texture databases and propose the concept of half-dry value by researching the main factors that affect the effects of the half-dry stroke. In the virtual painting, the half-dry texture is mapped into the stroke in real time according to the half-dry value and painting technique. A technique of texture blending based on the KM model is applied to avoid the seams while texture mapping. The proposed method has been successfully applied to the virtual painting system based on the force feedback technology. In this system, users can implement the painting in real time with a Phantom Desktop haptic device, which can effectively enhance reality to users.

Enhanced electrical properties of textured NBBT ceramics derived from the screen printing technique.

PubMed

Wu, Mengjia; Wang, Youliang; Wang, Dong; Li, Yongxiang

2011-10-01

(001)(pc)-oriented (Na(0.5)Bi(0.5))(0.94)Ba(0.06)TiO(3) (NBBT) lead-free piezoelectric ceramics were fabricated by the screen printing technique using Na(0.5)Bi(0.5)TiO(3) (NBT) templates. The plate-like NBT template particles were synthesized from bismuth layer-structured ferroelectric Bi(4)Ti(3)O(12) (BiT) precursors by the topochemical method. The screen printed NBBT ceramics with 20 wt% NBT templates contained a large fraction of grains aligned with their c-axis normal to the sample surface, giving a Lotgering factor of 0.486. The dielectric and ferroelectric properties of textured NBBT ceramics were anisotropic. Compared with the non-textured NBBT ceramics, the dielectric, ferroelectric, and piezoelectric properties of the textured NBBT ceramics were improved, giving a dielectric constant ϵ(T)(33)/ϵ(0) of 910, a remnant polarization P(r) of 29.2 μC/cm(2), a coercive field E(c) of 23.5 kV/cm, a piezoelectric coefficient d(33) of 180 pC/N, and a thickness-mode electromechanical coupling coefficient k(t) of 0.485.

The effects of the physical and chemical properties of soils on the spectral reflectance of soils

NASA Technical Reports Server (NTRS)

Montgomery, O. L.; Baumgardner, M. F.

1974-01-01

The effects of organic matter, free iron oxides, texture, moisture content, and cation exchange capacity on the spectral reflectance of soils were investigated along with techniques for differentiating soil orders by computer analysis of multispectral data. By collecting soil samples of benchmark soils from the different climatic regions within the United States and using the extended wavelength field spectroradiometer to obtain reflectance values and curves for each sample, average curves were constructed for each soil order. Results indicate that multispectral analysis may be a valuable tool for delineating and quantifying differences between soils.

Nanoscale silver-assisted wet etching of crystalline silicon for anti-reflection surface textures.

PubMed

Li, Rui; Wang, Shuling; Chuwongin, Santhad; Zhou, Weidong

2013-01-01

We report here an electro-less metal-assisted chemical etching (MacEtch) process as light management surface-texturing technique for single crystalline Si photovoltaics. Random Silver nanostructures were formed on top of the Si surface based on the thin film evaporation and annealing process. Significant reflection reduction was obtained from the fabricated Si sample, with approximately 2% reflection over a wide spectra range (300 to 1050 nm). The work demonstrates the potential of MacEtch process for anti-reflection surface texture fabrication of large area, high efficiency, and low cost thin film solar cell.

Adaptation of ion beam technology to microfabrication of solid state devices and transducers

NASA Technical Reports Server (NTRS)

Topich, J. A.

1977-01-01

It was found that ion beam texturing of silicon surfaces can be used to increase the effective surface area of MOS capacitors. There is, however, a problem with low dielectric breakdown. Preliminary work was begun on the fabrication of ion implanted resistors on textured surfaces and the potential improvement of wire bond strength by bonding to a textured surface. In the area of ion beam sputtering, the techniques for sputtering PVC were developed. A PVC target containing valinomycin was used to sputter an ion selective membrane on a field effect transistor to form a potassium ion sensor.

Infrared Radiation Filament And Metnod Of Manufacture

DOEpatents

Johnson, Edward A.

1998-11-17

An improved IR radiation source is provided by the invention. A radiation filament has a textured surface produced by seeded ion bombardment of a metal foil which is cut to a serpentine shape and mounted in a windowed housing. Specific ion bombardment texturing techniques tune the surface to maximize emissions in the desired wavelength range and to limit emissions outside that narrow range, particularly at longer wavelengths. A combination of filament surface texture, thickness, material, shape and power circuit feedback control produce wavelength controlled and efficient radiation at much lower power requirements than devices of the prior art.

Can Infrared Spectroscopy Be Used to Measure Change in Potassium Nitrate Concentration as a Proxy for Soil Particle Movement?

PubMed Central

Luleva, Mila Ivanova; van der Werff, Harald; Jetten, Victor; van der Meer, Freek

2011-01-01

Displacement of soil particles caused by erosion influences soil condition and fertility. To date, the cesium 137 isotope (137Cs) technique is most commonly used for soil particle tracing. However when large areas are considered, the expensive soil sampling and analysis present an obstacle. Infrared spectral measurements would provide a solution, however the small concentrations of the isotope do not influence the spectral signal sufficiently. Potassium (K) has similar electrical, chemical and physical properties as Cs. Our hypothesis is that it can be used as possible replacement in soil particle tracing. Soils differing in texture were sampled for the study. Laboratory soil chemical analyses and spectral sensitivity analyses were carried out to identify the wavelength range related to K concentration. Different concentrations of K fertilizer were added to soils with varying texture properties in order to establish spectral characteristics of the absorption feature associated with the element. Changes in position of absorption feature center were observed at wavelengths between 2,450 and 2,470 nm, depending on the amount of fertilizer applied. Other absorption feature parameters (absorption band depth, width and area) were also found to change with K concentration with coefficient of determination between 0.85 and 0.99. Tracing soil particles using K fertilizer and infrared spectral response is considered suitable for soils with sandy and sandy silt texture. It is a new approach that can potentially grow to a technique for rapid monitoring of soil particle movement over large areas. PMID:22163843

Crop identification of SAR data using digital textural analysis

NASA Technical Reports Server (NTRS)

Nuesch, D. R.

1983-01-01

After preprocessing SEASAT SAR data which included slant to ground range transformation, registration to LANDSAT MSS data and appropriate filtering of the raw SAR data to minimize coherent speckle, textural features were developed based upon the spatial gray level dependence method (SGLDM) to compute entropy and inertia as textural measures. It is indicated that the consideration of texture features are very important in SAR data analysis. The SEASAT SAR data are useful for the improvement of field boundary definitions and for an earlier season estimate of corn and soybean area location than is supported by LANDSAT alone.

Automatic age and gender classification using supervised appearance model

NASA Astrophysics Data System (ADS)

Bukar, Ali Maina; Ugail, Hassan; Connah, David

2016-11-01

Age and gender classification are two important problems that recently gained popularity in the research community, due to their wide range of applications. Research has shown that both age and gender information are encoded in the face shape and texture, hence the active appearance model (AAM), a statistical model that captures shape and texture variations, has been one of the most widely used feature extraction techniques for the aforementioned problems. However, AAM suffers from some drawbacks, especially when used for classification. This is primarily because principal component analysis (PCA), which is at the core of the model, works in an unsupervised manner, i.e., PCA dimensionality reduction does not take into account how the predictor variables relate to the response (class labels). Rather, it explores only the underlying structure of the predictor variables, thus, it is no surprise if PCA discards valuable parts of the data that represent discriminatory features. Toward this end, we propose a supervised appearance model (sAM) that improves on AAM by replacing PCA with partial least-squares regression. This feature extraction technique is then used for the problems of age and gender classification. Our experiments show that sAM has better predictive power than the conventional AAM.

Utility of texture analysis for quantifying hepatic fibrosis on proton density MRI.

PubMed

Yu, HeiShun; Buch, Karen; Li, Baojun; O'Brien, Michael; Soto, Jorge; Jara, Hernan; Anderson, Stephan W

2015-11-01

To evaluate the potential utility of texture analysis of proton density maps for quantifying hepatic fibrosis in a murine model of hepatic fibrosis. Following Institutional Animal Care and Use Committee (IACUC) approval, a dietary model of hepatic fibrosis was used and 15 ex vivo murine liver tissues were examined. All images were acquired using a 30 mm bore 11.7T magnetic resonance imaging (MRI) scanner with a multiecho spin-echo sequence. A texture analysis was employed extracting multiple texture features including histogram-based, gray-level co-occurrence matrix-based (GLCM), gray-level run-length-based features (GLRL), gray level gradient matrix (GLGM), and Laws' features. Texture features were correlated with histopathologic and digital image analysis of hepatic fibrosis. Histogram features demonstrated very weak to moderate correlations (r = -0.29 to 0.51) with hepatic fibrosis. GLCM features correlation and contrast demonstrated moderate-to-strong correlations (r = -0.71 and 0.59, respectively) with hepatic fibrosis. Moderate correlations were seen between hepatic fibrosis and the GLRL feature short run low gray-level emphasis (SRLGE) (r = -0. 51). GLGM features demonstrate very weak to weak correlations with hepatic fibrosis (r = -0.27 to 0.09). Moderate correlations were seen between hepatic fibrosis and Laws' features L6 and L7 (r = 0.58). This study demonstrates the utility of texture analysis applied to proton density MRI in a murine liver fibrosis model and validates the potential utility of texture-based features for the noninvasive, quantitative assessment of hepatic fibrosis. © 2015 Wiley Periodicals, Inc.

Pectin engineering to modify product quality in potato.

PubMed

Ross, Heather A; Morris, Wayne L; Ducreux, Laurence J M; Hancock, Robert D; Verrall, Susan R; Morris, Jenny A; Tucker, Gregory A; Stewart, Derek; Hedley, Pete E; McDougall, Gordon J; Taylor, Mark A

2011-10-01

Although processed potato tuber texture is an important trait that influences consumer preference, a detailed understanding of tuber textural properties at the molecular level is lacking. Previous work has identified tuber pectin methyl esterase (PME) activity as a potential factor impacting on textural properties, and the expression of a gene encoding an isoform of PME (PEST1) was associated with cooked tuber textural properties. In this study, a transgenic approach was undertaken to investigate further the impact of the PEST1 gene. Antisense and over-expressing potato lines were generated. In over-expressing lines, tuber PME activity was enhanced by up to 2.3-fold; whereas in antisense lines, PME activity was decreased by up to 62%. PME isoform analysis indicated that the PEST1 gene encoded one isoform of PME. Analysis of cell walls from tubers from the over-expressing lines indicated that the changes in PME activity resulted in a decrease in pectin methylation. Analysis of processed tuber texture demonstrated that the reduced level of pectin methylation in the over-expressing transgenic lines was associated with a firmer processed texture. Thus, there is a clear link between PME activity, pectin methylation and processed tuber textural properties. © 2011 The Authors. Plant Biotechnology Journal © 2011 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd.

New durum wheat with soft kernel texture: end-use quality analysis of the Hardness locus in Triticum turgidum ssp. durum

USDA-ARS?s Scientific Manuscript database

Wheat kernel texture dictates U.S. wheat market class. Durum wheat has limited demand and culinary end-uses compared to bread wheat because of its extremely hard kernel texture which precludes conventional milling. ‘Soft Svevo’, a new durum cultivar with soft kernel texture comparable to a soft whit...

Ability of LANDSAT-8 Oli Derived Texture Metrics in Estimating Aboveground Carbon Stocks of Coppice Oak Forests

NASA Astrophysics Data System (ADS)

Safari, A.; Sohrabi, H.

2016-06-01

The role of forests as a reservoir for carbon has prompted the need for timely and reliable estimation of aboveground carbon stocks. Since measurement of aboveground carbon stocks of forests is a destructive, costly and time-consuming activity, aerial and satellite remote sensing techniques have gained many attentions in this field. Despite the fact that using aerial data for predicting aboveground carbon stocks has been proved as a highly accurate method, there are challenges related to high acquisition costs, small area coverage, and limited availability of these data. These challenges are more critical for non-commercial forests located in low-income countries. Landsat program provides repetitive acquisition of high-resolution multispectral data, which are freely available. The aim of this study was to assess the potential of multispectral Landsat 8 Operational Land Imager (OLI) derived texture metrics in quantifying aboveground carbon stocks of coppice Oak forests in Zagros Mountains, Iran. We used four different window sizes (3×3, 5×5, 7×7, and 9×9), and four different offsets ([0,1], [1,1], [1,0], and [1,-1]) to derive nine texture metrics (angular second moment, contrast, correlation, dissimilar, entropy, homogeneity, inverse difference, mean, and variance) from four bands (blue, green, red, and infrared). Totally, 124 sample plots in two different forests were measured and carbon was calculated using species-specific allometric models. Stepwise regression analysis was applied to estimate biomass from derived metrics. Results showed that, in general, larger size of window for deriving texture metrics resulted models with better fitting parameters. In addition, the correlation of the spectral bands for deriving texture metrics in regression models was ranked as b4>b3>b2>b5. The best offset was [1,-1]. Amongst the different metrics, mean and entropy were entered in most of the regression models. Overall, different models based on derived texture metrics were able to explain about half of the variation in aboveground carbon stocks. These results demonstrated that Landsat 8 derived texture metrics can be applied for mapping aboveground carbon stocks of coppice Oak Forests in large areas.

Optical coherence tomography assessment of vessel wall degradation in thoracic aortic aneurysms

NASA Astrophysics Data System (ADS)

Real, Eusebio; Eguizabal, Alma; Pontón, Alejandro; Díez, Marta Calvo; Fernando Val-Bernal, José; Mayorga, Marta; Revuelta, José M.; López-Higuera, José M.; Conde, Olga M.

2013-12-01

Optical coherence tomography images of human thoracic aorta from aneurysms reveal elastin disorders and smooth muscle cell alterations when visualizing the media layer of the aortic wall. These disorders can be employed as indicators for wall degradation and, therefore, become a hallmark for diagnosis of risk of aneurysm under intraoperative conditions. Two approaches are followed to evaluate this risk: the analysis of the reflectivity decay along the penetration depth and the textural analysis of a two-dimensional spatial distribution of the aortic wall backscattering. Both techniques require preprocessing stages for the identification of the air-sample interface and for the segmentation of the media layer. Results show that the alterations in the media layer of the aortic wall are better highlighted when the textural approach is considered and also agree with a semiquantitative histopathological grading that assesses the degree of wall degradation. The correlation of the co-occurrence matrix attains a sensitivity of 0.906 and specificity of 0.864 when aneurysm automatic diagnosis is evaluated with a receiver operating characteristic curve.

High compression image and image sequence coding

NASA Technical Reports Server (NTRS)

Kunt, Murat

1989-01-01

The digital representation of an image requires a very large number of bits. This number is even larger for an image sequence. The goal of image coding is to reduce this number, as much as possible, and reconstruct a faithful duplicate of the original picture or image sequence. Early efforts in image coding, solely guided by information theory, led to a plethora of methods. The compression ratio reached a plateau around 10:1 a couple of years ago. Recent progress in the study of the brain mechanism of vision and scene analysis has opened new vistas in picture coding. Directional sensitivity of the neurones in the visual pathway combined with the separate processing of contours and textures has led to a new class of coding methods capable of achieving compression ratios as high as 100:1 for images and around 300:1 for image sequences. Recent progress on some of the main avenues of object-based methods is presented. These second generation techniques make use of contour-texture modeling, new results in neurophysiology and psychophysics and scene analysis.

Retaining {1 0 0} texture from initial columnar grains in 6.5 wt% Si electrical steels

NASA Astrophysics Data System (ADS)

Liang, Ruiyang; Yang, Ping; Mao, Weimin

2017-11-01

6.5 wt% Si electrical steel is a superior soft magnetic material with excellent magnetic properties which highly depends on texture. In this study, based on the heredity of 〈0 0 1〉 orientation in columnar grains, columnar grains are used as the initial material to prepare non-oriented 6.5 wt% Si electrical steel with excellent magnetic properties. EBSD and XRD techniques are adopted to explore the structure and texture evolution during hot rolling, warm rolling, cold rolling and annealing. The results show that, due to the heredity of "structure and texture" from the initial strong {1 0 0} columnar grains, annealed sheet with {1 0 0}〈0 0 1〉 texture had better magnetic properties, which can be used as non-oriented high-silicon electrical steel. Both preferred cube grain nucleation in deformed {1 1 3}〈3 6 1〉 grains in subsurface and coarse {1 0 0}〈0 0 1〉 deformed grains in center layer show the effect of initial columnar grains with {1 0 0} texture.

SU-F-R-18: Updates to the Computational Environment for Radiological Research for Image Analysis

DOE Office of Scientific and Technical Information (OSTI.GOV)

Apte, Aditya P.; Deasy, Joseph O.

2016-06-15

Purpose: To present new tools in CERR for Texture Analysis and Visualization. Method: (1) Quantitative Image Analysis: We added the ability to compute Haralick texture features based on local neighbourhood. The Texture features depend on many parameters used in their derivation. For example: (a) directionality, (b) quantization of image, (c) patch-size for the neighborhood, (d) handling of the edge voxels within the region of interest, (e) Averaging co-occurance matrix vs texture features for different directions etc. A graphical user interface was built to set these parameters and then visualize their impact on the resulting texture maps. The entire functionality wasmore » written in Matlab. Array indexing was used to speed up the texture calculation. The computation speed is very competitive with the ITK library. Moreover, our implementation works with multiple CPUs and the computation time can be further reduced by using multiple processor threads. In order to reduce the Haralick texture maps into scalar features, we propose the use of Texture Volume Histograms. This lets users make use of the entire distribution of texture values within the region of interest rather than using just the mean and the standard deviations. (2) Qualitative/Visualization tools: The derived texture maps are stored as a new scan (derived) within CERR’s planC data structure. A display that compares various scans was built to show the raw image and the derived texture maps side-by-side. These images are positionally linked and can be navigated together. CERR’s graphics handling was updated and sped-up to be compatible with the newer Matlab versions. As a result, the users can use (a) different window levels and colormaps for different viewports, (b) click-and-drag or use mouse scroll-wheel to navigate slices. Results: The new features and updates are available via https://www.github.com/adityaapte/cerr . Conclusion: Features added to CERR increase its utility in Radiomics and Outcomes modeling.« less

Investigations on the change of texture of plant cells due to preservative treatments by digital holographic microscopy

NASA Astrophysics Data System (ADS)

Vora, Priyanka; Anand, Arun

2014-10-01

Texture change is observed in preserved fruits and vegetables. Responsible factors for texture change during preservative treatments are cell morphology, cell wall structure, cell turger, water content and some biochemical components, and also the environmental conditions. Digital Holographic microscopy (DHM) is a quantitative phase contrast imaging technique, which provides three dimensional optical thickness profiles of transparent specimen. Using DHM the morphology of plant cells preserved by refrigeration or stored in vinegar or in sodium chloride can be obtained. This information about the spatio-temporal evolution of optical volume and thickness can be an important tool in area of food processing. Also from the three dimensional images, the texture of the cell can be retrieved and can be investigated under varying conditions.

Effect of slice thickness on brain magnetic resonance image texture analysis

PubMed Central

2010-01-01

Background The accuracy of texture analysis in clinical evaluation of magnetic resonance images depends considerably on imaging arrangements and various image quality parameters. In this paper, we study the effect of slice thickness on brain tissue texture analysis using a statistical approach and classification of T1-weighted images of clinically confirmed multiple sclerosis patients. Methods We averaged the intensities of three consecutive 1-mm slices to simulate 3-mm slices. Two hundred sixty-four texture parameters were calculated for both the original and the averaged slices. Wilcoxon's signed ranks test was used to find differences between the regions of interest representing white matter and multiple sclerosis plaques. Linear and nonlinear discriminant analyses were applied with several separate training and test sets to determine the actual classification accuracy. Results Only moderate differences in distributions of the texture parameter value for 1-mm and simulated 3-mm-thick slices were found. Our study also showed that white matter areas are well separable from multiple sclerosis plaques even if the slice thickness differs between training and test sets. Conclusions Three-millimeter-thick magnetic resonance image slices acquired with a 1.5 T clinical magnetic resonance scanner seem to be sufficient for texture analysis of multiple sclerosis plaques and white matter tissue. PMID:20955567

Local binary pattern texture-based classification of solid masses in ultrasound breast images

NASA Astrophysics Data System (ADS)

Matsumoto, Monica M. S.; Sehgal, Chandra M.; Udupa, Jayaram K.

2012-03-01

Breast cancer is one of the leading causes of cancer mortality among women. Ultrasound examination can be used to assess breast masses, complementarily to mammography. Ultrasound images reveal tissue information in its echoic patterns. Therefore, pattern recognition techniques can facilitate classification of lesions and thereby reduce the number of unnecessary biopsies. Our hypothesis was that image texture features on the boundary of a lesion and its vicinity can be used to classify masses. We have used intensity-independent and rotation-invariant texture features, known as Local Binary Patterns (LBP). The classifier selected was K-nearest neighbors. Our breast ultrasound image database consisted of 100 patient images (50 benign and 50 malignant cases). The determination of whether the mass was benign or malignant was done through biopsy and pathology assessment. The training set consisted of sixty images, randomly chosen from the database of 100 patients. The testing set consisted of forty images to be classified. The results with a multi-fold cross validation of 100 iterations produced a robust evaluation. The highest performance was observed for feature LBP with 24 symmetrically distributed neighbors over a circle of radius 3 (LBP24,3) with an accuracy rate of 81.0%. We also investigated an approach with a score of malignancy assigned to the images in the test set. This approach provided an ROC curve with Az of 0.803. The analysis of texture features over the boundary of solid masses showed promise for malignancy classification in ultrasound breast images.

Mapping Topological Magnetization and Magnetic Skyrmions

NASA Astrophysics Data System (ADS)

Chess, Jordan J.

A 2014 study by the US Department of Energy conducted at Lawrence Berkeley National Laboratory estimated that U.S. data centers consumed 70 billion kWh of electricity. This represents about 1.8% of the total U.S. electricity consumption. Putting this in perspective 70 billion kWh of electricity is the equivalent of roughly 8 big nuclear reactors, or around double the nation's solar panel output. Developing new memory technologies capable of reducing this power consumption would be greatly beneficial as our demand for connectivity increases in the future. One newly emerging candidate for an information carrier in low power memory devices is the magnetic skyrmion. This magnetic texture is characterized by its specific non-trivial topology, giving it particle-like characteristics. Recent experimental work has shown that these skyrmions can be stabilized at room temperature and moved with extremely low electrical current densities. This rapidly developing field requires new measurement techniques capable of determining the topology of these textures at greater speed than previous approaches. In this dissertation, I give a brief introduction to the magnetic structures found in Fe/Gd multilayered systems. I then present newly developed techniques that streamline the analysis of Lorentz Transmission Electron Microscopy (LTEM) data. These techniques are then applied to further the understanding of the magnetic properties of these Fe/Gd based multilayered systems. This dissertation includes previously published and unpublished co-authored material.

Interior car noise created by textured pavement surfaces : final report.

DOT National Transportation Integrated Search

1975-01-01

Because of widespread concern about the effect of textured pavement surfaces on interior car noise, sound pressure levels (SPL) were measured inside a test vehicle as it traversed 21 pavements with various textures. A linear regression analysis run o...

Textural changes of FER-A peridotite in time series piston-cylinder experiments at 1.0 GPa, 1300°C

NASA Astrophysics Data System (ADS)

Schwab, B. E.; Mercer, C. N.; Johnston, A.

2012-12-01

A series of eight 1.0 GPa, 1300°C partial melting experiments were performed using FER-A peridotite starting material to investigate potential textural changes in the residual crystalline phases over time. Powdered peridotite with a layer of vitreous carbon spheres as a melt sink were sealed in graphite-lined Pt capsules and run in CaF2 furnace assemblies in 1.27cm piston-cylinder apparatus at the University of Oregon. Run durations ranged from 4 to 128 hours. Experimental charges were mounted in epoxy, cut, and polished for analysis. In a first attempt to quantify the mineral textures, individual 500x BSE images were collected from selected, representative locations on each of the experimental charges using the FEI Quanta 250 ESEM at Humboldt State University. Noran System Seven (NSS) EDS system was used to collect x-ray maps (spectral images) to aid in identification of phases. A combination of image analysis techniques within NSS and ImageJ software are being used to process the images and quantify the mineral textures observed. The goals are to quantify the size, shape, and abundance of residual olivine (ol), orthopyroxene (opx), clinopyroxene (cpx), and spinel crystals within the selected sample areas of the run products. Additional work will be done to compare the results of the selected areas with larger (lower magnification) images acquired using the same techniques. Preliminary results indicate that measurements of average grain area, minimum grain area, and average, maximum, and minimum grain perimeter show the greatest change (generally decreasing) in measurements for ol, opx, and cpx between the shortest-duration, 4-hour, experiment and the subsequent, 8-hour, experiment. The largest relative change in nearly all of these measurements appears to be for cpx. After the initial decrease, preliminary measurements remain relatively constant for ol, opx, and cpx, respectively, in experiments from 8 to 128 hours in duration. In contrast, measured parameters of spinel grains increase from the 4-hour to 8-hour experiment and continue to fluctuate over the time interval investigated. Spinel also represents the smallest number of individual grains (average n = 25) in any experiment. Average aspect ratios for all minerals remain relatively constant (~1.5-2) throughout the time series. Additional measurements and refinements are underway.

Constraints on the timing of multiple thermal events and re-equilibration recorded by high-U zircon and xenotime: Case study of pegmatite from Piława Górna (Góry Sowie Block, SW Poland)

NASA Astrophysics Data System (ADS)

Budzyń, Bartosz; Sláma, Jiří; Kozub-Budzyń, Gabriela A.; Konečný, Patrik; Holický, Ivan; Rzepa, Grzegorz; Jastrzębski, Mirosław

2018-06-01

The application of zircon and xenotime geochronometers requires knowledge of their potential and limitations related to possible disturbance of the age record. The alteration of the intergrown zircon and xenotime in pegmatite from the Góry Sowie Block (SW Poland) was studied using the electron microprobe analysis, X-ray WDS compositional mapping, micro-Raman analysis, and LA-ICP-MS U-Pb dating of zircon and xenotime, as well as the U-Th-total Pb dating of uraninite. These microanalytical techniques were applied to understand the formation mechanisms of the secondary textures related to post-magmatic processes in the zircon and xenotime intergrowth, and to constrain their timing. Textural and compositional features combined with U-Pb data indicate that the pegmatite-related crystallization of the zircon and xenotime intergrowth occurred ca. 2.09 Ga (2086 ± 35 Ma for zircon and 2093 ± 52 Ma for xenotime), followed by the re-equilibration of zircon and xenotime ca. 370 Ma (373 ± 18 Ma and 368 ± 6 Ma, respectively) during the formation of the younger pegmatite. The zircon and xenotime were most likely derived from Precambrian basement rocks and emplaced in the pegmatite as a restite. The zircon preserved textures related to diffusion-reaction processes that affected its high-U core (up to ca. 9.6 wt% UO2), which underwent further metamictization and amorphization due to self-radiation damage. The zircon rim and xenotime were affected by coupled dissolution-reprecipitation processes that resulted in patchy zoning, age disturbance and sponge-like textures. Xenotime was also partially replaced by fluorapatite or hingganite-(Y) and Y-enriched allanite-(Ce). The termination of the low-temperature alteration was constrained by the U-Th-total Pb age of the uraninite inclusions that crystallized in zircon at 281 ± 2 Ma, which is consistent with the age of 278 ± 15 Ma obtained from the youngest cluster of U-Pb ages in the re-equilibrated high-U zircon domains. This study demonstrates the importance of the careful examination of compositional, microtextural and geochronological data obtained using microanalytical techniques to reconstruct the complex thermal histories recorded by accessory minerals.

Oil Spill Detection and Tracking Using Lipschitz Regularity and Multiscale Techniques in Synthetic Aperture Radar Imagery

NASA Astrophysics Data System (ADS)

Ajadi, O. A.; Meyer, F. J.

2014-12-01

Automatic oil spill detection and tracking from Synthetic Aperture Radar (SAR) images is a difficult task, due in large part to the inhomogeneous properties of the sea surface, the high level of speckle inherent in SAR data, the complexity and the highly non-Gaussian nature of amplitude information, and the low temporal sampling that is often achieved with SAR systems. This research presents a promising new oil spill detection and tracking method that is based on time series of SAR images. Through the combination of a number of advanced image processing techniques, the develop approach is able to mitigate some of these previously mentioned limitations of SAR-based oil-spill detection and enables fully automatic spill detection and tracking across a wide range of spatial scales. The method combines an initial automatic texture analysis with a consecutive change detection approach based on multi-scale image decomposition. The first step of the approach, a texture transformation of the original SAR images, is performed in order to normalize the ocean background and enhance the contrast between oil-covered and oil-free ocean surfaces. The Lipschitz regularity (LR), a local texture parameter, is used here due to its proven ability to normalize the reflectivity properties of ocean water and maximize the visibly of oil in water. To calculate LR, the images are decomposed using two-dimensional continuous wavelet transform (2D-CWT), and transformed into Holder space to measure LR. After texture transformation, the now normalized images are inserted into our multi-temporal change detection algorithm. The multi-temporal change detection approach is a two-step procedure including (1) data enhancement and filtering and (2) multi-scale automatic change detection. The performance of the developed approach is demonstrated by an application to oil spill areas in the Gulf of Mexico. In this example, areas affected by oil spills were identified from a series of ALOS PALSAR images acquired in 2010. The comparison showed exceptional performance of our method. This method can be applied to emergency management and decision support systems with a need for real-time data, and it shows great potential for rapid data analysis in other areas, including volcano detection, flood boundaries, forest health, and wildfires.

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

PubMed

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.

The neutron texture diffractometer at the China Advanced Research Reactor

NASA Astrophysics Data System (ADS)

Li, Mei-Juan; Liu, Xiao-Long; Liu, Yun-Tao; Tian, Geng-Fang; Gao, Jian-Bo; Yu, Zhou-Xiang; Li, Yu-Qing; Wu, Li-Qi; Yang, Lin-Feng; Sun, Kai; Wang, Hong-Li; Santisteban, J. r.; Chen, Dong-Feng

2016-03-01

The first neutron texture diffractometer in China has been built at the China Advanced Research Reactor, due to strong demand for texture measurement with neutrons from the domestic user community. This neutron texture diffractometer has high neutron intensity, moderate resolution and is mainly applied to study texture in commonly used industrial materials and engineering components. In this paper, the design and characteristics of this instrument are described. The results for calibration with neutrons and quantitative texture analysis of zirconium alloy plate are presented. The comparison of texture measurements with the results obtained in HIPPO at LANSCE and Kowari at ANSTO illustrates the reliability of the texture diffractometer. Supported by National Nature Science Foundation of China (11105231, 11205248, 51327902) and International Atomic Energy Agency-TC program (CPR0012)

Novel Texture-based Probabilistic Object Recognition and Tracking Techniques for Food Intake Analysis and Traffic Monitoring

DTIC Science & Technology

2015-10-02

ratio or physical layout than the training sample, or new vs old bananas . For our system, this is similar the multimodal case mentioned above; however...different modes. Foods with multiple “types” such as green, yellow, and brown bananas are seamlessly handled as well. Secondly, with hundreds or thousands...Recognition and Classification of Food Grains, Fruits and Flowers Using Machine Vision. INTERNATIONAL JOURNAL OF FOOD ENGINEERING, 5(4), 2009. [155] T. E

SU-E-I-91: Quantitative Assessment of Early Hepatocellular Carcinoma and Cavernous Hemangioma of Live Using In-Line Phase-Contrast X-Ray Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Duan, J

Purpose: To investigate the potential utility of in-line phase-contrast imaging (ILPCI) technique with synchrotron radiation in detecting early hepatocellular carcinoma and cavernous hemangioma of live using in vitro model system. Methods: Without contrast agents, three typical early hepatocellular carcinoma specimens and three typical cavernous hemangioma of live specimens were imaged using ILPCI. To quantitatively discriminate early hepatocellular carcinoma tissues and cavernous hemangioma tissues, the projection images texture feature based on gray level co-occurrence matrix (GLCM) were extracted. The texture parameters of energy, inertia, entropy, correlation, sum average, sum entropy, difference average, difference entropy and inverse difference moment, were obtained respectively.more » Results: In the ILPCI planar images of early hepatocellular carcinoma specimens, vessel trees were clearly visualized on the micrometer scale. Obvious distortion deformation was presented, and the vessel mostly appeared as a ‘dry stick’. Liver textures appeared not regularly. In the ILPCI planar images of cavernous hemangioma of live specimens, typical vessels had not been found compared with the early hepatocellular carcinoma planar images. The planar images of cavernous hemangioma of live specimens clearly displayed the dilated hepatic sinusoids with the diameter of less than 100 microns, but all of them were overlapped with each other. The texture parameters of energy, inertia, entropy, correlation, sum average, sum entropy, and difference average, showed a statistically significant between the two types specimens image (P<0.01), except the texture parameters of difference entropy and inverse difference moment(P>0.01). Conclusion: The results indicate that there are obvious changes in morphological levels including vessel structures and liver textures. The study proves that this imaging technique has a potential value in evaluating early hepatocellular carcinoma and cavernous hemangioma of live.« less

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

PubMed

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.

Reliable Classification of Geologic Surfaces Using Texture Analysis

NASA Astrophysics Data System (ADS)

Foil, G.; Howarth, D.; Abbey, W. J.; Bekker, D. L.; Castano, R.; Thompson, D. R.; Wagstaff, K.

2012-12-01

Communication delays and bandwidth constraints are major obstacles for remote exploration spacecraft. Due to such restrictions, spacecraft could make use of onboard science data analysis to maximize scientific gain, through capabilities such as the generation of bandwidth-efficient representative maps of scenes, autonomous instrument targeting to exploit targets of opportunity between communications, and downlink prioritization to ensure fast delivery of tactically-important data. Of particular importance to remote exploration is the precision of such methods and their ability to reliably reproduce consistent results in novel environments. Spacecraft resources are highly oversubscribed, so any onboard data analysis must provide a high degree of confidence in its assessment. The TextureCam project is constructing a "smart camera" that can analyze surface images to autonomously identify scientifically interesting targets and direct narrow field-of-view instruments. The TextureCam instrument incorporates onboard scene interpretation and mapping to assist these autonomous science activities. Computer vision algorithms map scenes such as those encountered during rover traverses. The approach, based on a machine learning strategy, trains a statistical model to recognize different geologic surface types and then classifies every pixel in a new scene according to these categories. We describe three methods for increasing the precision of the TextureCam instrument. The first uses ancillary data to segment challenging scenes into smaller regions having homogeneous properties. These subproblems are individually easier to solve, preventing uncertainty in one region from contaminating those that can be confidently classified. The second involves a Bayesian approach that maximizes the likelihood of correct classifications by abstaining from ambiguous ones. We evaluate these two techniques on a set of images acquired during field expeditions in the Mojave Desert. Finally, the algorithm was expanded to perform robust texture classification across a wide range of lighting conditions. We characterize both the increase in precision achieved using different input data representations as well as the range of conditions under which reliable performance can be achieved. An ensemble learning approach is used to increase performance by leveraging the illumination-dependent statistics of an image. Our results show that the three algorithmic modifications lead to a significant increase in classification performance as well as an increase in precision using an adjustable and human-understandable metric of confidence.

Prediction of survival with multi-scale radiomic analysis in glioblastoma patients.

PubMed

Chaddad, Ahmad; Sabri, Siham; Niazi, Tamim; Abdulkarim, Bassam

2018-06-19

We propose a multiscale texture features based on Laplacian-of Gaussian (LoG) filter to predict progression free (PFS) and overall survival (OS) in patients newly diagnosed with glioblastoma (GBM). Experiments use the extracted features derived from 40 patients of GBM with T1-weighted imaging (T1-WI) and Fluid-attenuated inversion recovery (FLAIR) images that were segmented manually into areas of active tumor, necrosis, and edema. Multiscale texture features were extracted locally from each of these areas of interest using a LoG filter and the relation between features to OS and PFS was investigated using univariate (i.e., Spearman's rank correlation coefficient, log-rank test and Kaplan-Meier estimator) and multivariate analyses (i.e., Random Forest classifier). Three and seven features were statistically correlated with PFS and OS, respectively, with absolute correlation values between 0.32 and 0.36 and p < 0.05. Three features derived from active tumor regions only were associated with OS (p < 0.05) with hazard ratios (HR) of 2.9, 3, and 3.24, respectively. Combined features showed an AUC value of 85.37 and 85.54% for predicting the PFS and OS of GBM patients, respectively, using the random forest (RF) classifier. We presented a multiscale texture features to characterize the GBM regions and predict he PFS and OS. The efficiency achievable suggests that this technique can be developed into a GBM MR analysis system suitable for clinical use after a thorough validation involving more patients. Graphical abstract Scheme of the proposed model for characterizing the heterogeneity of GBM regions and predicting the overall survival and progression free survival of GBM patients. (1) Acquisition of pretreatment MRI images; (2) Affine registration of T1-WI image with its corresponding FLAIR images, and GBM subtype (phenotypes) labelling; (3) Extraction of nine texture features from the three texture scales fine, medium, and coarse derived from each of GBM regions; (4) Comparing heterogeneity between GBM regions by ANOVA test; Survival analysis using Univariate (Spearman rank correlation between features and survival (i.e., PFS and OS) based on each of the GBM regions, Kaplan-Meier estimator and log-rank test to predict the PFS and OS of patient groups that grouped based on median of feature), and multivariate (random forest model) for predicting the PFS and OS of patients groups that grouped based on median of PFS and OS.

Identifying prognostic intratumor heterogeneity using pre- and post-radiotherapy 18F-FDG PET images for pancreatic cancer patients.

PubMed

Yue, Yong; Osipov, Arsen; Fraass, Benedick; Sandler, Howard; Zhang, Xiao; Nissen, Nicholas; Hendifar, Andrew; Tuli, Richard

2017-02-01

To stratify risks of pancreatic adenocarcinoma (PA) patients using pre- and post-radiotherapy (RT) PET/CT images, and to assess the prognostic value of texture variations in predicting therapy response of patients. Twenty-six PA patients treated with RT from 2011-2013 with pre- and post-treatment 18F-FDG-PET/CT scans were identified. Tumor locoregional texture was calculated using 3D kernel-based approach, and texture variations were identified by fitting discrepancies of texture maps of pre- and post-treatment images. A total of 48 texture and clinical variables were identified and evaluated for association with overall survival (OS). The prognostic heterogeneity features were selected using lasso/elastic net regression, and further were evaluated by multivariate Cox analysis. Median age was 69 y (range, 46-86 y). The texture map and temporal variations between pre- and post-treatment were well characterized by histograms and statistical fitting. The lasso analysis identified seven predictors (age, node stage, post-RT SUVmax, variations of homogeneity, variance, sum mean, and cluster tendency). The multivariate Cox analysis identified five significant variables: age, node stage, variations of homogeneity, variance, and cluster tendency (with P=0.020, 0.040, 0.065, 0.078, and 0.081, respectively). The patients were stratified into two groups based on the risk score of multivariate analysis with log-rank P=0.001: a low risk group (n=11) with a longer mean OS (29.3 months) and higher texture variation (>30%), and a high risk group (n=15) with a shorter mean OS (17.7 months) and lower texture variation (<15%). Locoregional metabolic texture response provides a feasible approach for evaluating and predicting clinical outcomes following treatment of PA with RT. The proposed method can be used to stratify patient risk and help select appropriate treatment strategies for individual patients toward implementing response-driven adaptive RT.

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

PubMed

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.

Bridges between multiple-point geostatistics and texture synthesis: Review and guidelines for future research

NASA Astrophysics Data System (ADS)

Mariethoz, Gregoire; Lefebvre, Sylvain

2014-05-01

Multiple-Point Simulations (MPS) is a family of geostatistical tools that has received a lot of attention in recent years for the characterization of spatial phenomena in geosciences. It relies on the definition of training images to represent a given type of spatial variability, or texture. We show that the algorithmic tools used are similar in many ways to techniques developed in computer graphics, where there is a need to generate large amounts of realistic textures for applications such as video games and animated movies. Similarly to MPS, these texture synthesis methods use training images, or exemplars, to generate realistic-looking graphical textures. Both domains of multiple-point geostatistics and example-based texture synthesis present similarities in their historic development and share similar concepts. These disciplines have however remained separated, and as a result significant algorithmic innovations in each discipline have not been universally adopted. Texture synthesis algorithms present drastically increased computational efficiency, patterns reproduction and user control. At the same time, MPS developed ways to condition models to spatial data and to produce 3D stochastic realizations, which have not been thoroughly investigated in the field of texture synthesis. In this paper we review the possible links between these disciplines and show the potential and limitations of using concepts and approaches from texture synthesis in MPS. We also provide guidelines on how recent developments could benefit both fields of research, and what challenges remain open.

Texture analysis of aeromagnetic data for enhancing geologic features using co-occurrence matrices in Elallaqi area, South Eastern Desert of Egypt

NASA Astrophysics Data System (ADS)

Eldosouky, Ahmed M.; Elkhateeb, Sayed O.

2018-06-01

Enhancement of aeromagnetic data for qualitative purposes depends on the variations of texture and amplitude to outline various geologic features within the data. The texture of aeromagnetic data consists continuity of adjacent anomalies, size, and pattern. Variations in geology, or particularly rock magnetization, in a study area cause fluctuations in texture. In the present study, the anomalous features of Elallaqi area were extracted from aeromagnetic data. In order to delineate textures from the aeromagnetic data, the Red, Green, and Blue Co-occurrence Matrices (RGBCM) were applied to the reduced to the pole (RTP) grid of Elallaqi district in the South Eastern Desert of Egypt. The RGBCM are fashioned of sets of spatial analytical parameters that transform magnetic data into texture forms. Six texture features (parameters), i.e. Correlation, Contrast, Entropy, Homogeneity, Second Moment, and Variance, of RGB Co-occurrence Matrices (RGBCM) are used for analyzing the texture of the RTP grid in this study. These six RGBCM texture characteristics were mixed into a single image using principal component analysis. The calculated texture images present geologic characteristics and structures with much greater sidelong resolution than the original RTP grid. The estimated texture images enabled us to distinguish multiple geologic regions and structures within Elallaqi area including geologic terranes, lithologic boundaries, cracks, and faults. The faults of RGBCM maps were more represented than those of magnetic derivatives providing enhancement of the fine structures of Elallaqi area like the NE direction which scattered WNW metavolcanics and metasediments trending in the northwestern division of Elallaqi area.

A Systematic Evaluation of Food Textures to Decrease Packing and Increase Oral Intake in Children with Pediatric Feeding Disorders

ERIC Educational Resources Information Center

Patel, Meeta R.; Piazza, Cathleen C.; Layer, Stacy A.; Coleman, Russell; Swartzwelder, Dana M.

2005-01-01

This study examined packing (pocketing or holding accepted food in the mouth) in 3 children who were failing to thrive or had inadequate weight gain due to insufficient caloric intake. The results of an analysis of texture indicated that total grams consumed were higher when lower textured foods were presented than when higher textured foods were…

New durum wheat with soft kernel texture: milling performance and end-use quality analysis of the Hardness locus in Triticum turgidum ssp. durum

USDA-ARS?s Scientific Manuscript database

Wheat kernel texture dictates U.S. wheat market class. Durum wheat has limited demand and culinary end-uses compared to bread wheat because of its extremely hard kernel texture which preclude conventional milling. ‘Soft Svevo’, a new durum cultivar with soft kernel texture comparable to a soft white...

Mining hidden data to predict patient prognosis: texture feature extraction and machine learning in mammography

NASA Astrophysics Data System (ADS)

Leighs, J. A.; Halling-Brown, M. D.; Patel, M. N.

2018-03-01

The UK currently has a national breast cancer-screening program and images are routinely collected from a number of screening sites, representing a wealth of invaluable data that is currently under-used. Radiologists evaluate screening images manually and recall suspicious cases for further analysis such as biopsy. Histological testing of biopsy samples confirms the malignancy of the tumour, along with other diagnostic and prognostic characteristics such as disease grade. Machine learning is becoming increasingly popular for clinical image classification problems, as it is capable of discovering patterns in data otherwise invisible. This is particularly true when applied to medical imaging features; however clinical datasets are often relatively small. A texture feature extraction toolkit has been developed to mine a wide range of features from medical images such as mammograms. This study analysed a dataset of 1,366 radiologist-marked, biopsy-proven malignant lesions obtained from the OPTIMAM Medical Image Database (OMI-DB). Exploratory data analysis methods were employed to better understand extracted features. Machine learning techniques including Classification and Regression Trees (CART), ensemble methods (e.g. random forests), and logistic regression were applied to the data to predict the disease grade of the analysed lesions. Prediction scores of up to 83% were achieved; sensitivity and specificity of the models trained have been discussed to put the results into a clinical context. The results show promise in the ability to predict prognostic indicators from the texture features extracted and thus enable prioritisation of care for patients at greatest risk.

Differentiation of pre-ablation and post-ablation late gadolinium-enhanced cardiac MRI scans of longstanding persistent atrial fibrillation patients

NASA Astrophysics Data System (ADS)

Yang, Guang; Zhuang, Xiahai; Khan, Habib; Haldar, Shouvik; Nyktari, Eva; Li, Lei; Ye, Xujiong; Slabaugh, Greg; Wong, Tom; Mohiaddin, Raad; Keegan, Jennifer; Firmin, David

2017-03-01

Late Gadolinium-Enhanced Cardiac MRI (LGE CMRI) is an emerging non-invasive technique to image and quantify preablation native and post-ablation atrial scarring. Previous studies have reported that enhanced image intensities of the atrial scarring in the LGE CMRI inversely correlate with the left atrial endocardial voltage invasively obtained by electro-anatomical mapping. However, the reported reproducibility of using LGE CMRI to identify and quantify atrial scarring is variable. This may be due to two reasons: first, delineation of the left atrium (LA) and pulmonary veins (PVs) anatomy generally relies on manual operation that is highly subjective, and this could substantially affect the subsequent atrial scarring segmentation; second, simple intensity based image features may not be good enough to detect subtle changes in atrial scarring. In this study, we hypothesized that texture analysis can provide reliable image features for the LGE CMRI images subject to accurate and objective delineation of the heart anatomy based on a fully-automated whole heart segmentation (WHS) method. We tested the extracted texture features to differentiate between pre-ablation and post-ablation LGE CMRI studies in longstanding persistent atrial fibrillation patients. These patients often have extensive native scarring and differentiation from post-ablation scarring can be difficult. Quantification results showed that our method is capable of solving this classification task, and we can envisage further deployment of this texture analysis based method for other clinical problems using LGE CMRI.

Variogram methods for texture classification of atherosclerotic plaque ultrasound images

NASA Astrophysics Data System (ADS)

Jeromin, Oliver M.; Pattichis, Marios S.; Pattichis, Constantinos; Kyriacou, Efthyvoulos; Nicolaides, Andrew

2006-03-01

Stroke is the third leading cause of death in the western world and the major cause of disability in adults. The type and stenosis of extracranial carotid artery disease is often responsible for ischemic strokes, transient ischemic attacks (TIAs) or amaurosis fugax (AF). The identification and grading of stenosis can be done using gray scale ultrasound scans. The appearance of B-scan pictures containing various granular structures makes the use of texture analysis techniques suitable for computer assisted tissue characterization purposes. The objective of this study is to investigate the usefulness of variogram analysis in the assessment of ultrasound plague morphology. The variogram estimates the variance of random fields, from arbitrary samples in space. We explore stationary random field models based on the variogram, which can be applied in ultrasound plaque imaging leading to a Computer Aided Diagnosis (CAD) system for the early detection of symptomatic atherosclerotic plaques. Non-parametric tests on the variogram coefficients show that the cofficients coming from symptomatic versus asymptomatic plaques come from distinct distributions. Furthermore, we show significant improvement in class separation, when a log point-transformation is applied to the images, prior to variogram estimation. Model fitting using least squares is explored for anisotropic variograms along specific directions. Comparative classification results, show that variogram coefficients can be used for the early detection of symptomatic cases, and also exhibit the largest class distances between symptomatic and asymptomatic plaque images, as compared to over 60 other texture features, used in the literature.

Texture segmentation by genetic programming.

PubMed

Song, Andy; Ciesielski, Vic

2008-01-01

This paper describes a texture segmentation method using genetic programming (GP), which is one of the most powerful evolutionary computation algorithms. By choosing an appropriate representation texture, classifiers can be evolved without computing texture features. Due to the absence of time-consuming feature extraction, the evolved classifiers enable the development of the proposed texture segmentation algorithm. This GP based method can achieve a segmentation speed that is significantly higher than that of conventional methods. This method does not require a human expert to manually construct models for texture feature extraction. In an analysis of the evolved classifiers, it can be seen that these GP classifiers are not arbitrary. Certain textural regularities are captured by these classifiers to discriminate different textures. GP has been shown in this study as a feasible and a powerful approach for texture classification and segmentation, which are generally considered as complex vision tasks.

An investigation of density measurement method for yarn-dyed woven fabrics based on dual-side fusion technique

NASA Astrophysics Data System (ADS)

Zhang, Rui; Xin, Binjie

2016-08-01

Yarn density is always considered as the fundamental structural parameter used for the quality evaluation of woven fabrics. The conventional yarn density measurement method is based on one-side analysis. In this paper, a novel density measurement method is developed for yarn-dyed woven fabrics based on a dual-side fusion technique. Firstly, a lab-used dual-side imaging system is established to acquire both face-side and back-side images of woven fabric and the affine transform is used for the alignment and fusion of the dual-side images. Then, the color images of the woven fabrics are transferred from the RGB to the CIE-Lab color space, and the intensity information of the image extracted from the L component is used for texture fusion and analysis. Subsequently, three image fusion methods are developed and utilized to merge the dual-side images: the weighted average method, wavelet transform method and Laplacian pyramid blending method. The fusion efficacy of each method is evaluated by three evaluation indicators and the best of them is selected to do the reconstruction of the complete fabric texture. Finally, the yarn density of the fused image is measured based on the fast Fourier transform, and the yarn alignment image could be reconstructed using the inverse fast Fourier transform. Our experimental results show that the accuracy of density measurement by using the proposed method is close to 99.44% compared with the traditional method and the robustness of this new proposed method is better than that of conventional analysis methods.

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

NASA Astrophysics Data System (ADS)

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.

Parenchymal texture measures weighted by breast anatomy: preliminary optimization in a case-control study

NASA Astrophysics Data System (ADS)

Gastounioti, Aimilia; Keller, Brad M.; Hsieh, Meng-Kang; Conant, Emily F.; Kontos, Despina

2016-03-01

Growing evidence suggests that quantitative descriptors of the parenchymal texture patterns hold a valuable role in assessing an individual woman's risk for breast cancer. In this work, we assess the hypothesis that breast cancer risk factors are not uniformly expressed in the breast parenchymal tissue and, therefore, breast-anatomy-weighted parenchymal texture descriptors, where different breasts ROIs have non uniform contributions, may enhance breast cancer risk assessment. To this end, we introduce an automated breast-anatomy-driven methodology which generates a breast atlas, which is then used to produce a weight map that reinforces the contributions of the central and upper-outer breast areas. We incorporate this methodology to our previously validated lattice-based strategy for parenchymal texture analysis. In the framework of a pilot case-control study, including digital mammograms from 424 women, our proposed breast-anatomy-weighted texture descriptors are optimized and evaluated against non weighted texture features, using regression analysis with leave-one-out cross validation. The classification performance is assessed in terms of the area under the curve (AUC) of the receiver operating characteristic. The collective discriminatory capacity of the weighted texture features was maximized (AUC=0.87) when the central breast area was considered more important than the upperouter area, with significant performance improvement (DeLong's test, p-value<0.05) against the non-weighted texture features (AUC=0.82). Our results suggest that breast-anatomy-driven methodologies have the potential to further upgrade the promising role of parenchymal texture analysis in breast cancer risk assessment and may serve as a reference in the design of future studies towards image-driven personalized recommendations regarding women's cancer risk evaluation.

Frictional Behavior of Micro/nanotextured Surfaces Investigated by Atomic Force Microscope: a Review

NASA Astrophysics Data System (ADS)

Zhang, Xiaoliang; Jia, Junhong

2015-08-01

Tribological issues between friction pair are fundamental problems for minimized devices because of their higher surface-to-volume ratio. Micro/nanotexturing is an effective technique to reduce actual contact area between contact pair at the nanoscale. Micro/nanotexture made a great impact on the frictional behavior of textured surfaces. This paper summarizes the recent advancements in the field of frictional behavior of micro/nanotextured surfaces, which are based on solid surface contact in atmosphere environment, especially focusing on the factors influencing the frictional behavior: Surface property, texturing density, texturing height, texturing structure and size of contact pair (atomic force microscope (AFM) tip) and texturing structures. Summarizing the effects of these factors on the frictional behavior is helpful for the understanding and designing of the surfaces in sliding micro/nanoelectromechanical systems (MEMS/NEMS). Controlling and reducing the friction force in moving mechanical systems is very important for the performance and reliability of nanosystems, which contribute to a sustainable future.

Texture and microstructure evolution in single-phase Ti{sub x}Ta{sub 1-x}N alloys of rocksalt structure

DOE Office of Scientific and Technical Information (OSTI.GOV)

Koutsokeras, L. E.; Department of Materials Science and Engineering, University of Ioannina, GR-45100 Ioannina; Abadias, G.

2011-08-15

The mechanisms controlling the structural and morphological features (texture and microstructure) of ternary transition metal nitride thin films of the Ti{sub x}Ta{sub 1-x}N system, grown by various physical vapor deposition techniques, are reported. Films deposited by pulsed laser deposition, dual cathode magnetron sputtering, and dual ion beam sputtering have been investigated by means of x-ray diffraction in various geometries and scanning electron microscopy. We studied the effects of composition, energetic, and kinetics in the evolution of the microstructure and texture of the films. We obtain films with single and mixed texture as well as films with columnar ''zone-T'' and globularmore » type morphology. The results have shown that the texture evolution of ternary transition metal nitrides as well as the microstructural features of such films can be well understood in the framework of the kinetic mechanisms proposed for their binary counterparts, thus giving these mechanisms a global application.« less

Surface wettability of silicon substrates enhanced by laser ablation

NASA Astrophysics Data System (ADS)

Tseng, Shih-Feng; Hsiao, Wen-Tse; Chen, Ming-Fei; Huang, Kuo-Cheng; Hsiao, Sheng-Yi; Lin, Yung-Sheng; Chou, Chang-Pin

2010-11-01

Laser-ablation techniques have been widely applied for removing material from a solid surface using a laser-beam irradiating apparatus. This paper presents a surface-texturing technique to create rough patterns on a silicon substrate using a pulsed Nd:YAG laser system. The different degrees of microstructure and surface roughness were adjusted by the laser fluence and laser pulse duration. A scanning electron microscope (SEM) and a 3D confocal laser-scanning microscope are used to measure the surface micrograph and roughness of the patterns, respectively. The contact angle variations between droplets on the textured surface were measured using an FTA 188 video contact angle analyzer. The results indicate that increasing the values of laser fluence and laser pulse duration pushes more molten slag piled around these patterns to create micro-sized craters and leads to an increase in the crater height and surface roughness. A typical example of a droplet on a laser-textured surface shows that the droplet spreads very quickly and almost disappears within 0.5167 s, compared to a contact angle of 47.9° on an untextured surface. This processing technique can also be applied to fabricating Si solar panels to increase the absorption efficiency of light.

Multiresolution Local Binary Pattern texture analysis for false positive reduction in computerized detection of breast masses on mammograms

NASA Astrophysics Data System (ADS)

Choi, Jae Young; Kim, Dae Hoe; Choi, Seon Hyeong; Ro, Yong Man

2012-03-01

We investigated the feasibility of using multiresolution Local Binary Pattern (LBP) texture analysis to reduce falsepositive (FP) detection in a computerized mass detection framework. A new and novel approach for extracting LBP features is devised to differentiate masses and normal breast tissue on mammograms. In particular, to characterize the LBP texture patterns of the boundaries of masses, as well as to preserve the spatial structure pattern of the masses, two individual LBP texture patterns are then extracted from the core region and the ribbon region of pixels of the respective ROI regions, respectively. These two texture patterns are combined to produce the so-called multiresolution LBP feature of a given ROI. The proposed LBP texture analysis of the information in mass core region and its margin has clearly proven to be significant and is not sensitive to the precise location of the boundaries of masses. In this study, 89 mammograms were collected from the public MAIS database (DB). To perform a more realistic assessment of FP reduction process, the LBP texture analysis was applied directly to a total of 1,693 regions of interest (ROIs) automatically segmented by computer algorithm. Support Vector Machine (SVM) was applied for the classification of mass ROIs from ROIs containing normal tissue. Receiver Operating Characteristic (ROC) analysis was conducted to evaluate the classification accuracy and its improvement using multiresolution LBP features. With multiresolution LBP features, the classifier achieved an average area under the ROC curve, , z A of 0.956 during testing. In addition, the proposed LBP features outperform other state-of-the-arts features designed for false positive reduction.

Cortical mechanisms for the segregation and representation of acoustic textures.

PubMed

Overath, Tobias; Kumar, Sukhbinder; Stewart, Lauren; von Kriegstein, Katharina; Cusack, Rhodri; Rees, Adrian; Griffiths, Timothy D

2010-02-10

Auditory object analysis requires two fundamental perceptual processes: the definition of the boundaries between objects, and the abstraction and maintenance of an object's characteristic features. Although it is intuitive to assume that the detection of the discontinuities at an object's boundaries precedes the subsequent precise representation of the object, the specific underlying cortical mechanisms for segregating and representing auditory objects within the auditory scene are unknown. We investigated the cortical bases of these two processes for one type of auditory object, an "acoustic texture," composed of multiple frequency-modulated ramps. In these stimuli, we independently manipulated the statistical rules governing (1) the frequency-time space within individual textures (comprising ramps with a given spectrotemporal coherence) and (2) the boundaries between textures (adjacent textures with different spectrotemporal coherences). Using functional magnetic resonance imaging, we show mechanisms defining boundaries between textures with different coherences in primary and association auditory cortices, whereas texture coherence is represented only in association cortex. Furthermore, participants' superior detection of boundaries across which texture coherence increased (as opposed to decreased) was reflected in a greater neural response in auditory association cortex at these boundaries. The results suggest a hierarchical mechanism for processing acoustic textures that is relevant to auditory object analysis: boundaries between objects are first detected as a change in statistical rules over frequency-time space, before a representation that corresponds to the characteristics of the perceived object is formed.

Knee cartilage segmentation using active shape models and local binary patterns

NASA Astrophysics Data System (ADS)

González, Germán.; Escalante-Ramírez, Boris

2014-05-01

Segmentation of knee cartilage has been useful for opportune diagnosis and treatment of osteoarthritis (OA). This paper presents a semiautomatic segmentation technique based on Active Shape Models (ASM) combined with Local Binary Patterns (LBP) and its approaches to describe the surrounding texture of femoral cartilage. The proposed technique is tested on a 16-image database of different patients and it is validated through Leave- One-Out method. We compare different segmentation techniques: ASM-LBP, ASM-medianLBP, and ASM proposed by Cootes. The ASM-LBP approaches are tested with different ratios to decide which of them describes the cartilage texture better. The results show that ASM-medianLBP has better performance than ASM-LBP and ASM. Furthermore, we add a routine which improves the robustness versus two principal problems: oversegmentation and initialization.

Automated quantitative micro-mineralogical characterization for environmental applications

USGS Publications Warehouse

Smith, Kathleen S.; Hoal, K.O.; Walton-Day, Katherine; Stammer, J.G.; Pietersen, K.

2013-01-01

Characterization of ore and waste-rock material using automated quantitative micro-mineralogical techniques (e.g., QEMSCAN® and MLA) has the potential to complement traditional acid-base accounting and humidity cell techniques when predicting acid generation and metal release. These characterization techniques, which most commonly are used for metallurgical, mineral-processing, and geometallurgical applications, can be broadly applied throughout the mine-life cycle to include numerous environmental applications. Critical insights into mineral liberation, mineral associations, particle size, particle texture, and mineralogical residence phase(s) of environmentally important elements can be used to anticipate potential environmental challenges. Resources spent on initial characterization result in lower uncertainties of potential environmental impacts and possible cost savings associated with remediation and closure. Examples illustrate mineralogical and textural characterization of fluvial tailings material from the upper Arkansas River in Colorado.

Combining multiple features for color texture classification

NASA Astrophysics Data System (ADS)

Cusano, Claudio; Napoletano, Paolo; Schettini, Raimondo

2016-11-01

The analysis of color and texture has a long history in image analysis and computer vision. These two properties are often considered as independent, even though they are strongly related in images of natural objects and materials. Correlation between color and texture information is especially relevant in the case of variable illumination, a condition that has a crucial impact on the effectiveness of most visual descriptors. We propose an ensemble of hand-crafted image descriptors designed to capture different aspects of color textures. We show that the use of these descriptors in a multiple classifiers framework makes it possible to achieve a very high classification accuracy in classifying texture images acquired under different lighting conditions. A powerful alternative to hand-crafted descriptors is represented by features obtained with deep learning methods. We also show how the proposed combining strategy hand-crafted and convolutional neural networks features can be used together to further improve the classification accuracy. Experimental results on a food database (raw food texture) demonstrate the effectiveness of the proposed strategy.

Coastal modification of a scene employing multispectral images and vector operators.

PubMed

Lira, Jorge

2017-05-01

Changes in sea level, wind patterns, sea current patterns, and tide patterns have produced morphologic transformations in the coastline area of Tamaulipas Sate in North East Mexico. Such changes generated a modification of the coastline and variations of the texture-relief and texture of the continental area of Tamaulipas. Two high-resolution multispectral satellite Satellites Pour l'Observation de la Terre images were employed to quantify the morphologic change of such continental area. The images cover a time span close to 10 years. A variant of the principal component analysis was used to delineate the modification of the land-water line. To quantify changes in texture-relief and texture, principal component analysis was applied to the multispectral images. The first principal components of each image were modeled as a discrete bidimensional vector field. The divergence and Laplacian vector operators were applied to the discrete vector field. The divergence provided the change of texture, while the Laplacian produced the change of texture-relief in the area of study.

Cloud cover analysis with Arctic Advanced Very High Resolution Radiometer data. II - Classification with spectral and textural measures

NASA Technical Reports Server (NTRS)

Key, J.

1990-01-01

The spectral and textural characteristics of polar clouds and surfaces for a 7-day summer series of AVHRR data in two Arctic locations are examined, and the results used in the development of a cloud classification procedure for polar satellite data. Since spatial coherence and texture sensitivity tests indicate that a joint spectral-textural analysis based on the same cell size is inappropriate, cloud detection with AVHRR data and surface identification with passive microwave data are first done on the pixel level as described by Key and Barry (1989). Next, cloud patterns within 250-sq-km regions are described, then the spectral and local textural characteristics of cloud patterns in the image are determined and each cloud pixel is classified by statistical methods. Results indicate that both spectral and textural features can be utilized in the classification of cloudy pixels, although spectral features are most useful for the discrimination between cloud classes.

Direct Volume Rendering with Shading via Three-Dimensional Textures

NASA Technical Reports Server (NTRS)

VanGelder, Allen; Kim, Kwansik

1996-01-01

A new and easy-to-implement method for direct volume rendering that uses 3D texture maps for acceleration, and incorporates directional lighting, is described. The implementation, called Voltx, produces high-quality images at nearly interactive speeds on workstations with hardware support for three-dimensional texture maps. Previously reported methods did not incorporate a light model, and did not address issues of multiple texture maps for large volumes. Our research shows that these extensions impact performance by about a factor of ten. Voltx supports orthographic, perspective, and stereo views. This paper describes the theory and implementation of this technique, and compares it to the shear-warp factorization approach. A rectilinear data set is converted into a three-dimensional texture map containing color and opacity information. Quantized normal vectors and a lookup table provide efficiency. A new tesselation of the sphere is described, which serves as the basis for normal-vector quantization. A new gradient-based shading criterion is described, in which the gradient magnitude is interpreted in the context of the field-data value and the material classification parameters, and not in isolation. In the rendering phase, the texture map is applied to a stack of parallel planes, which effectively cut the texture into many slabs. The slabs are composited to form an image.

Classification and recognition of texture collagen obtaining by multiphoton microscope with neural network analysis

NASA Astrophysics Data System (ADS)

Wu, Shulian; Peng, Yuanyuan; Hu, Liangjun; Zhang, Xiaoman; Li, Hui

2016-01-01

Second harmonic generation microscopy (SHGM) was used to monitor the process of chronological aging skin in vivo. The collagen structures of mice model with different ages were obtained using SHGM. Then, texture feature with contrast, correlation and entropy were extracted and analysed using the grey level co-occurrence matrix. At last, the neural network tool of Matlab was applied to train the texture of collagen in different statues during the aging process. And the simulation of mice collagen texture was carried out. The results indicated that the classification accuracy reach 85%. Results demonstrated that the proposed approach effectively detected the target object in the collagen texture image during the chronological aging process and the analysis tool based on neural network applied the skin of classification and feature extraction method is feasible.

Detection of small bowel tumors in capsule endoscopy frames using texture analysis based on the discrete wavelet transform.

PubMed

Barbosa, Daniel J C; Ramos, Jaime; Lima, Carlos S

2008-01-01

Capsule endoscopy is an important tool to diagnose tumor lesions in the small bowel. The capsule endoscopic images possess vital information expressed by color and texture. This paper presents an approach based in the textural analysis of the different color channels, using the wavelet transform to select the bands with the most significant texture information. A new image is then synthesized from the selected wavelet bands, trough the inverse wavelet transform. The features of each image are based on second-order textural information, and they are used in a classification scheme using a multilayer perceptron neural network. The proposed methodology has been applied in real data taken from capsule endoscopic exams and reached 98.7% sensibility and 96.6% specificity. These results support the feasibility of the proposed algorithm.

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

PubMed

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

2018-05-14

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

Optical coherence tomography for the structural changes detection in aging skin

NASA Astrophysics Data System (ADS)

Cheng, Chih-Ming; Chang, Yu-Fen; Chiang, Hung-Chih; Chang, Chir-Weei

2018-01-01

Optical coherence tomography (OCT) technique is an extremely powerful tool to detect numerous ophthalmological disorders, such as retinal disorder, and can be applied on other fields. Thus, many OCT systems are developed. For assessment of the skin textures, a cross-sectional (B-scan) spectra domain OCT system is better than an en-face one. However, this kind of commercial OCT system is not available. We designed a brand-new probe of commercial OCT system for evaluating skin texture without destroying the original instrument and it can be restored in 5 minutes. This modification of OCT system retains the advantages of commercial instrument, such as reliable, stable, and safe. Furthermore, the structural changes in aging skin are easily obtained by means of our probe, including larger pores, thinning of the dermis, collagen volume loss, vessel atrophy and flattening of dermal-epidermal junction. We can use this OCT technique in the field of cosmetic medicine such as detecting the skin textures and skin care product effect followup.

Performance analysis of improved methodology for incorporation of spatial/spectral variability in synthetic hyperspectral imagery

NASA Astrophysics Data System (ADS)

Scanlan, Neil W.; Schott, John R.; Brown, Scott D.

2004-01-01

Synthetic imagery has traditionally been used to support sensor design by enabling design engineers to pre-evaluate image products during the design and development stages. Increasingly exploitation analysts are looking to synthetic imagery as a way to develop and test exploitation algorithms before image data are available from new sensors. Even when sensors are available, synthetic imagery can significantly aid in algorithm development by providing a wide range of "ground truthed" images with varying illumination, atmospheric, viewing and scene conditions. One limitation of synthetic data is that the background variability is often too bland. It does not exhibit the spatial and spectral variability present in real data. In this work, four fundamentally different texture modeling algorithms will first be implemented as necessary into the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model environment. Two of the models to be tested are variants of a statistical Z-Score selection model, while the remaining two involve a texture synthesis and a spectral end-member fractional abundance map approach, respectively. A detailed comparative performance analysis of each model will then be carried out on several texturally significant regions of the resultant synthetic hyperspectral imagery. The quantitative assessment of each model will utilize a set of three peformance metrics that have been derived from spatial Gray Level Co-Occurrence Matrix (GLCM) analysis, hyperspectral Signal-to-Clutter Ratio (SCR) measures, and a new concept termed the Spectral Co-Occurrence Matrix (SCM) metric which permits the simultaneous measurement of spatial and spectral texture. Previous research efforts on the validation and performance analysis of texture characterization models have been largely qualitative in nature based on conducting visual inspections of synthetic textures in order to judge the degree of similarity to the original sample texture imagery. The quantitative measures used in this study will in combination attempt to determine which texture characterization models best capture the correct statistical and radiometric attributes of the corresponding real image textures in both the spatial and spectral domains. The motivation for this work is to refine our understanding of the complexities of texture phenomena so that an optimal texture characterization model that can accurately account for these complexities can be eventually implemented into a synthetic image generation (SIG) model. Further, conclusions will be drawn regarding which of the candidate texture models are able to achieve realistic levels of spatial and spectral clutter, thereby permitting more effective and robust testing of hyperspectral algorithms in synthetic imagery.

Performance analysis of improved methodology for incorporation of spatial/spectral variability in synthetic hyperspectral imagery

NASA Astrophysics Data System (ADS)

Scanlan, Neil W.; Schott, John R.; Brown, Scott D.

2003-12-01

Synthetic imagery has traditionally been used to support sensor design by enabling design engineers to pre-evaluate image products during the design and development stages. Increasingly exploitation analysts are looking to synthetic imagery as a way to develop and test exploitation algorithms before image data are available from new sensors. Even when sensors are available, synthetic imagery can significantly aid in algorithm development by providing a wide range of "ground truthed" images with varying illumination, atmospheric, viewing and scene conditions. One limitation of synthetic data is that the background variability is often too bland. It does not exhibit the spatial and spectral variability present in real data. In this work, four fundamentally different texture modeling algorithms will first be implemented as necessary into the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model environment. Two of the models to be tested are variants of a statistical Z-Score selection model, while the remaining two involve a texture synthesis and a spectral end-member fractional abundance map approach, respectively. A detailed comparative performance analysis of each model will then be carried out on several texturally significant regions of the resultant synthetic hyperspectral imagery. The quantitative assessment of each model will utilize a set of three peformance metrics that have been derived from spatial Gray Level Co-Occurrence Matrix (GLCM) analysis, hyperspectral Signal-to-Clutter Ratio (SCR) measures, and a new concept termed the Spectral Co-Occurrence Matrix (SCM) metric which permits the simultaneous measurement of spatial and spectral texture. Previous research efforts on the validation and performance analysis of texture characterization models have been largely qualitative in nature based on conducting visual inspections of synthetic textures in order to judge the degree of similarity to the original sample texture imagery. The quantitative measures used in this study will in combination attempt to determine which texture characterization models best capture the correct statistical and radiometric attributes of the corresponding real image textures in both the spatial and spectral domains. The motivation for this work is to refine our understanding of the complexities of texture phenomena so that an optimal texture characterization model that can accurately account for these complexities can be eventually implemented into a synthetic image generation (SIG) model. Further, conclusions will be drawn regarding which of the candidate texture models are able to achieve realistic levels of spatial and spectral clutter, thereby permitting more effective and robust testing of hyperspectral algorithms in synthetic imagery.

Phase Transition and Texture Evolution in the Ni-Mn-Ga Ferromagnetic Shape-Memory Alloys Studied by a Neutron Diffraction Technique

NASA Astrophysics Data System (ADS)

Nie, Z. H.; Wang, Y. D.; Wang, G. Y.; Richardson, J. W.; Wang, G.; Liu, Y. D.; Liaw, P. K.; Zuo, L.

2008-12-01

The phase transition and influence of the applied stress on the texture evolution in the as-cast Ni-Mn-Ga ferromagnetic shape-memory alloys were studied by the time-of-flight (TOF) neutron diffraction technique. The neutron diffraction experiments were performed on the General Purpose Powder Diffractometer (Argonne National Laboratory). Inverse pole figures were determined from the neutron data for characterizing the orientation distributions and variant selections of polycrystalline Ni-Mn-Ga alloys subjected to different uniaxial compression deformations. Texture analyses reveal that the initial texture for the parent phase in the as-cast specimen was composed of {left\\{ {{text{001}}} right\\}}{left< {{text{100}}} rightrangle } , {left\\{ {{text{001}}} right\\}}{left< {{text{110}}} rightrangle } , {left\\{ {{text{011}}} right\\}}{left< {{text{100}}} rightrangle } , and {left\\{ {{text{011}}} right\\}}{left< {{text{110}}} rightrangle } , which was weakened after the compression deformation. Moreover, a strong preferred selection of martensitic-twin variants ( {left\\{ {{text{110}}} right\\}}{left< {{text{001}}} rightrangle } and {left\\{ {{text{100}}} right\\}}{left< {{text{001}}} rightrangle } ) was observed in the transformed martensite after a compression stress applied on the parent phase along the cyclindrical axis of the specimens. The preferred selection of variants can be well explained by considering the grain/variant-orientation-dependent Bain-distortion energy.

Electrostatic-Force-Assisted Dispensing Printing to Construct High-Aspect-Ratio of 0.79 Electrodes on a Textured Surface with Improved Adhesion and Contact Resistivity

PubMed Central

Shin, Dong-Youn; Yoo, Sung-Soo; Song, Hee-eun; Tak, Hyowon; Byun, Doyoung

2015-01-01

As a novel route to construct fine and abnormally high-aspect-ratio electrodes with excellent adhesion and reduced contact resistivity on a textured surface, an electrostatic-force-assisted dispensing printing technique is reported and compared with conventional dispensing and electrohydrodynamic jet printing techniques. The electrostatic force applied between a silver paste and the textured surface of a crystalline silicon solar cell wafer significantly improves the physical adhesion of the electrodes, whereas those fabricated using a conventional dispensing printing technique peel off with a silver paste containing 2 wt% of a fluorosurfactant. Moreover, the contact resistivity and dimensionless deviation of total resistance are significantly reduced from 2.19 ± 1.53 mΩ·cm2 to 0.98 ± 0.92 mΩ·cm2 and from 0.10 to 0.03, respectively. By utilizing electrodes with an abnormally high-aspect-ratio of 0.79 (the measured thickness and width are 30.4 μm and 38.3 μm, respectively), the cell efficiency is 17.2% on a polycrystalline silicon solar cell with an emitter sheet resistance of 60 Ω/sq. This cell efficiency is considerably higher than previously reported values obtained using a conventional electrohydrodynamic jet printing technique, by +0.48–3.5%p. PMID:26576857

A novel tensile test method to assess texture and gaping in salmon fillets.

PubMed

Ashton, Thomas J; Michie, Ian; Johnston, Ian A

2010-05-01

A new tensile strength method was developed to quantify the force required to tear a standardized block of Atlantic salmon muscle with the aim of identifying those samples more prone to factory downgrading as a result of softness and fillet gaping. The new method effectively overcomes problems of sample attachment encountered with previous tensile strength tests. The repeatability and sensitivity and predictability of the new technique were evaluated against other common instrumental texture measurement methods. The relationship between sensory assessments of firmness and parameters from the instrumental texture methods was also determined. Data from the new method were shown to have the strongest correlations with gaping severity (r =-0.514, P < 0.001) and the highest level of repeatability of data when analyzing cold-smoked samples. The Warner Bratzler shear method gave the most repeatable data from fresh samples and had the highest correlations between fresh and smoked product from the same fish (r = 0.811, P < 0.001). A hierarchical cluster analysis placed the tensile test in the top cluster, alongside the Warner Bratzler method, demonstrating that it also yields adequate data with respect to these tests. None of the tested sensory analysis attributes showed significant relationships to mechanical tests except fillet firmness, with correlations (r) of 0.42 for cylinder probe maximum force (P = 0.005) and 0.31 for tensile work (P = 0.04). It was concluded that the tensile test method developed provides an important addition to the available tools for mechanical analysis of salmon quality, particularly with respect to the prediction of gaping during factory processing, which is a serious commercial problem. A novel, reliable method of measuring flesh tensile strength in salmon, provides data of relevance to gaping.

Radiogenomics to characterize regional genetic heterogeneity in glioblastoma

PubMed Central

Hu, Leland S.; Ning, Shuluo; Eschbacher, Jennifer M.; Baxter, Leslie C.; Gaw, Nathan; Ranjbar, Sara; Plasencia, Jonathan; Dueck, Amylou C.; Peng, Sen; Smith, Kris A.; Nakaji, Peter; Karis, John P.; Quarles, C. Chad; Wu, Teresa; Loftus, Joseph C.; Jenkins, Robert B.; Sicotte, Hugues; Kollmeyer, Thomas M.; O'Neill, Brian P.; Elmquist, William; Hoxworth, Joseph M.; Frakes, David; Sarkaria, Jann; Swanson, Kristin R.; Tran, Nhan L.; Li, Jing; Mitchell, J. Ross

2017-01-01

Background Glioblastoma (GBM) exhibits profound intratumoral genetic heterogeneity. Each tumor comprises multiple genetically distinct clonal populations with different therapeutic sensitivities. This has implications for targeted therapy and genetically informed paradigms. Contrast-enhanced (CE)-MRI and conventional sampling techniques have failed to resolve this heterogeneity, particularly for nonenhancing tumor populations. This study explores the feasibility of using multiparametric MRI and texture analysis to characterize regional genetic heterogeneity throughout MRI-enhancing and nonenhancing tumor segments. Methods We collected multiple image-guided biopsies from primary GBM patients throughout regions of enhancement (ENH) and nonenhancing parenchyma (so called brain-around-tumor, [BAT]). For each biopsy, we analyzed DNA copy number variants for core GBM driver genes reported by The Cancer Genome Atlas. We co-registered biopsy locations with MRI and texture maps to correlate regional genetic status with spatially matched imaging measurements. We also built multivariate predictive decision-tree models for each GBM driver gene and validated accuracies using leave-one-out-cross-validation (LOOCV). Results We collected 48 biopsies (13 tumors) and identified significant imaging correlations (univariate analysis) for 6 driver genes: EGFR, PDGFRA, PTEN, CDKN2A, RB1, and TP53. Predictive model accuracies (on LOOCV) varied by driver gene of interest. Highest accuracies were observed for PDGFRA (77.1%), EGFR (75%), CDKN2A (87.5%), and RB1 (87.5%), while lowest accuracy was observed in TP53 (37.5%). Models for 4 driver genes (EGFR, RB1, CDKN2A, and PTEN) showed higher accuracy in BAT samples (n = 16) compared with those from ENH segments (n = 32). Conclusion MRI and texture analysis can help characterize regional genetic heterogeneity, which offers potential diagnostic value under the paradigm of individualized oncology. PMID:27502248

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

PubMed

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.

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

PubMed Central

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. PMID:28973006

Directional analysis and filtering for dust storm detection in NOAA-AVHRR imagery

NASA Astrophysics Data System (ADS)

Janugani, S.; Jayaram, V.; Cabrera, S. D.; Rosiles, J. G.; Gill, T. E.; Rivera Rivera, N.

2009-05-01

In this paper, we propose spatio-spectral processing techniques for the detection of dust storms and automatically finding its transport direction in 5-band NOAA-AVHRR imagery. Previous methods that use simple band math analysis have produced promising results but have drawbacks in producing consistent results when low signal to noise ratio (SNR) images are used. Moreover, in seeking to automate the dust storm detection, the presence of clouds in the vicinity of the dust storm creates a challenge in being able to distinguish these two types of image texture. This paper not only addresses the detection of the dust storm in the imagery, it also attempts to find the transport direction and the location of the sources of the dust storm. We propose a spatio-spectral processing approach with two components: visualization and automation. Both approaches are based on digital image processing techniques including directional analysis and filtering. The visualization technique is intended to enhance the image in order to locate the dust sources. The automation technique is proposed to detect the transport direction of the dust storm. These techniques can be used in a system to provide timely warnings of dust storms or hazard assessments for transportation, aviation, environmental safety, and public health.

Spectral dependence of texture features integrated with hyperspectral data for area target classification improvement

NASA Astrophysics Data System (ADS)

Bangs, Corey F.; Kruse, Fred A.; Olsen, Chris R.

2013-05-01

Hyperspectral data were assessed to determine the effect of integrating spectral data and extracted texture feature data on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were used from the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) portions of the electromagnetic spectrum. Haralick texture features (contrast, entropy, and correlation) were extracted from the average gray-level image for each of the four spectral ranges studied. A maximum likelihood classifier was trained using a set of ground truth regions of interest (ROIs) and applied separately to the spectral data, texture data, and a fused dataset containing both. Classification accuracy was measured by comparison of results to a separate verification set of test ROIs. Analysis indicates that the spectral range (source of the gray-level image) used to extract the texture feature data has a significant effect on the classification accuracy. This result applies to texture-only classifications as well as the classification of integrated spectral data and texture feature data sets. Overall classification improvement for the integrated data sets was near 1%. Individual improvement for integrated spectral and texture classification of the "Urban" class showed approximately 9% accuracy increase over spectral-only classification. Texture-only classification accuracy was highest for the "Dirt Path" class at approximately 92% for the spectral range from 947 to 1343nm. This research demonstrates the effectiveness of texture feature data for more accurate analysis of hyperspectral data and the importance of selecting the correct spectral range to be used for the gray-level image source to extract these features.

Advanced light-scattering materials: Double-textured ZnO:B films grown by LP-MOCVD

NASA Astrophysics Data System (ADS)

Addonizio, M. L.; Spadoni, A.; Antonaia, A.

2013-12-01

Double-textured ZnO:B layers with enhanced optical scattering in both short and long wavelength regions have been successfully fabricated using MOCVD technique through a three step process. Growth of double-textured structures has been induced by wet etching on polycrystalline ZnO surface. Our double-layer structure consists of a first ZnO:B layer wet etched and subsequently used as substrate for a second ZnO:B layer deposition. Polycrystalline ZnO:B layers were etched by utilizing diluted solutions of fluoridic acid (HF), chloridric acid (HCl) and phosphoric acid (H3PO4) and their effect on surface morphology modification was systematically investigated. The morphology of the second deposited ZnO layer strongly depended on the surface properties of the etched ZnO first layer. Growth of cauliflower-like texture was induced by protrusions presence on the HCl etched surface. Optimized double-layer structure shows a cauliflower-like double texture with higher RMS roughness and increased spectral haze values in both short and long wavelength regions, compared to conventional pyramidal-like single texture. Furthermore, this highly scattering structure preserves excellent optical and electrical properties.

Texture Feature Analysis for Different Resolution Level of Kidney Ultrasound Images

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

Down syndrome detection from facial photographs using machine learning techniques

NASA Astrophysics Data System (ADS)

Zhao, Qian; Rosenbaum, Kenneth; Sze, Raymond; Zand, Dina; Summar, Marshall; Linguraru, Marius George

2013-02-01

Down syndrome is the most commonly occurring chromosomal condition; one in every 691 babies in United States is born with it. Patients with Down syndrome have an increased risk for heart defects, respiratory and hearing problems and the early detection of the syndrome is fundamental for managing the disease. Clinically, facial appearance is an important indicator in diagnosing Down syndrome and it paves the way for computer-aided diagnosis based on facial image analysis. In this study, we propose a novel method to detect Down syndrome using photography for computer-assisted image-based facial dysmorphology. Geometric features based on facial anatomical landmarks, local texture features based on the Contourlet transform and local binary pattern are investigated to represent facial characteristics. Then a support vector machine classifier is used to discriminate normal and abnormal cases; accuracy, precision and recall are used to evaluate the method. The comparison among the geometric, local texture and combined features was performed using the leave-one-out validation. Our method achieved 97.92% accuracy with high precision and recall for the combined features; the detection results were higher than using only geometric or texture features. The promising results indicate that our method has the potential for automated assessment for Down syndrome from simple, noninvasive imaging data.

Diagnostic features of Alzheimer's disease extracted from PET sinograms

NASA Astrophysics Data System (ADS)

Sayeed, A.; Petrou, M.; Spyrou, N.; Kadyrov, A.; Spinks, T.

2002-01-01

Texture analysis of positron emission tomography (PET) images of the brain is a very difficult task, due to the poor signal to noise ratio. As a consequence, very few techniques can be implemented successfully. We use a new global analysis technique known as the Trace transform triple features. This technique can be applied directly to the raw sinograms to distinguish patients with Alzheimer's disease (AD) from normal volunteers. FDG-PET images of 18 AD and 10 normal controls obtained from the same CTI ECAT-953 scanner were used in this study. The Trace transform triple feature technique was used to extract features that were invariant to scaling, translation and rotation, referred to as invariant features, as well as features that were sensitive to rotation but invariant to scaling and translation, referred to as sensitive features in this study. The features were used to classify the groups using discriminant function analysis. Cross-validation tests using stepwise discriminant function analysis showed that combining both sensitive and invariant features produced the best results, when compared with the clinical diagnosis. Selecting the five best features produces an overall accuracy of 93% with sensitivity of 94% and specificity of 90%. This is comparable with the classification accuracy achieved by Kippenhan et al (1992), using regional metabolic activity.

The effect of texture on the shaft surface on the sealing performance of radial lip seals

NASA Astrophysics Data System (ADS)

Guo, Fei; Jia, XiaoHong; Gao, Zhi; Wang, YuMing

2014-07-01

On the basis of elastohydrodynamic model, the present study numerically analyzes the effect of various microdimple texture shapes, namely, circular, square, oriented isosceles triangular, on the pumping rate and the friction torque of radial lip seals, and determines the microdimple texture shape that can produce positive pumping rate. The area ratio, depth and shape dimension of a single texture are the most important geometric parameters which influence the tribological performance. According to the selected texture shape, parameter analysis is conducted to determine the optimal combination for the above three parameters. Simultaneously, the simulated performances of radial lip seal with texture on the shaft surface are compared with those of the conventional lip seal without any texture on the shaft surface.

Early classification of Alzheimer's disease using hippocampal texture from structural MRI

NASA Astrophysics Data System (ADS)

Zhao, Kun; Ding, Yanhui; Wang, Pan; Dou, Xuejiao; Zhou, Bo; Yao, Hongxiang; An, Ningyu; Zhang, Yongxin; Zhang, Xi; Liu, Yong

2017-03-01

Convergent evidence has been collected to support that Alzheimer's disease (AD) is associated with reduction in hippocampal volume based on anatomical magnetic resonance imaging (MRI) and impaired functional connectivity based on functional MRI. Radiomics texture analysis has been previously successfully used to identify MRI biomarkers of several diseases, including AD, mild cognitive impairment and multiple sclerosis. In this study, our goal was to determine if MRI hippocampal textures, including the intensity, shape, texture and wavelet features, could be served as an MRI biomarker of AD. For this purpose, the texture marker was trained and evaluated from MRI data of 48 AD and 39 normal samples. The result highlights the presence of hippocampal texture abnormalities in AD, and the possibility that texture may serve as a neuroimaging biomarker for AD.

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

PubMed

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.

[The choice of color in fixed prosthetics: what steps should be followed for a reliable outcome?].

PubMed

Vanheusden, Alain; Mainjot, Amélie

2004-01-01

The creation of a perfectly-matched esthetic fixed restoration is undeniably one of the most difficult challenges in modern dentistry. The final outcome depends on several essential steps: the use of an appropriate light source, the accurate analysis and correct evaluation of patient's teeth parameters (morphology, colour, surface texture,...), the clear and precise transmission of this data to the laboratory and the sound interpretation of it by a dental technician who masters esthetic prosthetic techniques perfectly. The purpose of this paper was to give a reproducible clinical method to the practitioner in order to achieve a reliable dental colorimetric analysis.

Computer Graphics Meets Image Fusion: the Power of Texture Baking to Simultaneously Visualise 3d Surface Features and Colour

NASA Astrophysics Data System (ADS)

Verhoeven, G. J.

2017-08-01

Since a few years, structure-from-motion and multi-view stereo pipelines have become omnipresent in the cultural heritage domain. The fact that such Image-Based Modelling (IBM) approaches are capable of providing a photo-realistic texture along the threedimensional (3D) digital surface geometry is often considered a unique selling point, certainly for those cases that aim for a visually pleasing result. However, this texture can very often also obscure the underlying geometrical details of the surface, making it very hard to assess the morphological features of the digitised artefact or scene. Instead of constantly switching between the textured and untextured version of the 3D surface model, this paper presents a new method to generate a morphology-enhanced colour texture for the 3D polymesh. The presented approach tries to overcome this switching between objects visualisations by fusing the original colour texture data with a specific depiction of the surface normals. Whether applied to the original 3D surface model or a lowresolution derivative, this newly generated texture does not solely convey the colours in a proper way but also enhances the smalland large-scale spatial and morphological features that are hard or impossible to perceive in the original textured model. In addition, the technique is very useful for low-end 3D viewers, since no additional memory and computing capacity are needed to convey relief details properly. Apart from simple visualisation purposes, the textured 3D models are now also better suited for on-surface interpretative mapping and the generation of line drawings.

Low temperature texture development in Nd2Fe14B/α-Fe nanocomposite magnets via equal channel angular pressing

NASA Astrophysics Data System (ADS)

Besley, L.; Garitaonandia, J. S.; Molotnikov, A.; Kishimoto, H.; Kato, A.; Davies, C.; Suzuki, K.

2018-05-01

While suitable texture has been developed in Nd2Fe14B/α-Fe nanocomposites via thermomechanical processing methods such as die upsetting by incorporating low melting point eutectic Nd-Cu additives, significant grain coarsening occurs during this process due to the high temperature and long timescales involved, resulting in a loss of exchange coupling. Equal channel angular pressing (ECAP) is a severe plastic deformation technique which has been successfully used to produce a suitable texture in single-phase Nd2Fe14B at temperatures on the order of 500°C while preserving grain sizes on the order of 20-30nm. We investigate the development of texture in a commercial Nd2Fe14B/α-Fe nanocomposite alloy with added Nd90Cu10 produced via ECAP and then characterise it using texture x-ray diffraction and magnetic measurements. It is found that initial texture can be developed in this nanocomposite system at T = 520°C via ECAP. The average grain size of Nd2Fe14B as measured via X-ray diffraction after ECAP remains below 50nm with a developed texture. The effect of varying the amount of Nd90Cu10 additive is also investigated. It is found that with decreasing Nd90Cu10, the degree of texture is reduced while the volume fraction of α-Fe increases. This work demonstrates the development of texture in nanocomposite Nd2Fe14B/α-Fe with Nd-Cu additives whilst maintaining a grain size of approximately 50nm.

Prediction of neonatal respiratory morbidity by quantitative ultrasound lung texture analysis: a multicenter study.

PubMed

Palacio, Montse; Bonet-Carne, Elisenda; Cobo, Teresa; Perez-Moreno, Alvaro; Sabrià, Joan; Richter, Jute; Kacerovsky, Marian; Jacobsson, Bo; García-Posada, Raúl A; Bugatto, Fernando; Santisteve, Ramon; Vives, Àngels; Parra-Cordero, Mauro; Hernandez-Andrade, Edgar; Bartha, José Luis; Carretero-Lucena, Pilar; Tan, Kai Lit; Cruz-Martínez, Rogelio; Burke, Minke; Vavilala, Suseela; Iruretagoyena, Igor; Delgado, Juan Luis; Schenone, Mauro; Vilanova, Josep; Botet, Francesc; Yeo, George S H; Hyett, Jon; Deprest, Jan; Romero, Roberto; Gratacos, Eduard

2017-08-01

Prediction of neonatal respiratory morbidity may be useful to plan delivery in complicated pregnancies. The limited predictive performance of the current diagnostic tests together with the risks of an invasive procedure restricts the use of fetal lung maturity assessment. The objective of the study was to evaluate the performance of quantitative ultrasound texture analysis of the fetal lung (quantusFLM) to predict neonatal respiratory morbidity in preterm and early-term (<39.0 weeks) deliveries. This was a prospective multicenter study conducted in 20 centers worldwide. Fetal lung ultrasound images were obtained at 25.0-38.6 weeks of gestation within 48 hours of delivery, stored in Digital Imaging and Communication in Medicine format, and analyzed with quantusFLM. Physicians were blinded to the analysis. At delivery, perinatal outcomes and the occurrence of neonatal respiratory morbidity, defined as either respiratory distress syndrome or transient tachypnea of the newborn, were registered. The performance of the ultrasound texture analysis test to predict neonatal respiratory morbidity was evaluated. A total of 883 images were collected, but 17.3% were discarded because of poor image quality or exclusion criteria, leaving 730 observations for the final analysis. The prevalence of neonatal respiratory morbidity was 13.8% (101 of 730). The quantusFLM predicted neonatal respiratory morbidity with a sensitivity, specificity, positive and negative predictive values of 74.3% (75 of 101), 88.6% (557 of 629), 51.0% (75 of 147), and 95.5% (557 of 583), respectively. Accuracy was 86.5% (632 of 730) and positive and negative likelihood ratios were 6.5 and 0.3, respectively. The quantusFLM predicted neonatal respiratory morbidity with an accuracy similar to that previously reported for other tests with the advantage of being a noninvasive technique. Copyright © 2017. Published by Elsevier Inc.

The use of an ion-beam source to alter the surface morphology of biological implant materials

NASA Technical Reports Server (NTRS)

Weigand, A. J.

1978-01-01

An electron bombardment, ion thruster was used as a neutralized-ion beam sputtering source to texture the surfaces of biological implant materials. Scanning electron microscopy was used to determine surface morphology changes of all materials after ion-texturing. Electron spectroscopy for chemical analysis was used to determine the effects of ion texturing on the surface chemical composition of some polymers. Liquid contact angle data were obtained for ion textured and untextured polymer samples. Results of tensile and fatigue tests of ion-textured metal alloys are presented. Preliminary data of tissue response to ion textured surfaces of some metals, polytetrafluoroethylene, alumina, and segmented polyurethane were obtained.

A novel content-based active contour model for brain tumor segmentation.

PubMed

Sachdeva, Jainy; Kumar, Vinod; Gupta, Indra; Khandelwal, Niranjan; Ahuja, Chirag Kamal

2012-06-01

Brain tumor segmentation is a crucial step in surgical and treatment planning. Intensity-based active contour models such as gradient vector flow (GVF), magneto static active contour (MAC) and fluid vector flow (FVF) have been proposed to segment homogeneous objects/tumors in medical images. In this study, extensive experiments are done to analyze the performance of intensity-based techniques for homogeneous tumors on brain magnetic resonance (MR) images. The analysis shows that the state-of-art methods fail to segment homogeneous tumors against similar background or when these tumors show partial diversity toward the background. They also have preconvergence problem in case of false edges/saddle points. However, the presence of weak edges and diffused edges (due to edema around the tumor) leads to oversegmentation by intensity-based techniques. Therefore, the proposed method content-based active contour (CBAC) uses both intensity and texture information present within the active contour to overcome above-stated problems capturing large range in an image. It also proposes a novel use of Gray-Level Co-occurrence Matrix to define texture space for tumor segmentation. The effectiveness of this method is tested on two different real data sets (55 patients - more than 600 images) containing five different types of homogeneous, heterogeneous, diffused tumors and synthetic images (non-MR benchmark images). Remarkable results are obtained in segmenting homogeneous tumors of uniform intensity, complex content heterogeneous, diffused tumors on MR images (T1-weighted, postcontrast T1-weighted and T2-weighted) and synthetic images (non-MR benchmark images of varying intensity, texture, noise content and false edges). Further, tumor volume is efficiently extracted from 2-dimensional slices and is named as 2.5-dimensional segmentation. Copyright © 2012 Elsevier Inc. All rights reserved.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Solla, E.L., E-mail: esolla@uvigo.es

Herein, we report on the micro- and nanostructure of the calcium phosphate coating produced by pulsed laser deposition (PLD), using focused ion beam (FIB) lamella sample preparation and transmission electron microscopy (TEM) as the characterization technique. The initial selected area electron diffraction (SAED) data demonstrated the presence of hydroxyapatite (HA) over any other possible calcium phosphate crystalline structure and the polycrystalline nature of the coating. Moreover, the SAED analyses showed clear textured ring patterns coherent with the presence of a preferred orientation in the HA nano-crystal growth. The SAED data also indicated that the coating appears to be textured inmore » the 〈002〉 crystalline direction. Dark-field images obtained using 002 as the working reflection showed a clear oriented crystal growth in columns, from bottom to top. These columns have a peculiar arrangement of nano-crystals since, in some cases, the preferred orientation appears to start at a certain distance from the substrate. Direct d-spacing measurements on high-resolution TEM images provided further proof of the presence of an HA nano-crystal structure. The reported data may be of interest in the future to adjust the microstructure of the HA coatings. - Highlights: •The FIB lift-out technique allows a very site-specific sample preparation method for HRTEM analysis. •It also permits a fast assessment of the HA coating thickness and elemental composition (EDS). •The coatings exhibit a nano-crystalline nature, with a texturing effect along the 002 planes. •PLD is suitable for the production of crystalline c-axis oriented hydroxyapatite coatings. •The crystalline HA phase in the PLD coating is very similar to the present in bone.« less

Mineralogy, morphology, and textural relationships in coatings on quartz grains in sediments in a quartz-sand aquifer

USGS Publications Warehouse

Zhang, Shouliang; Kent, Douglas B.; Elbert, David C.; Shi, Zhi; Davis, James A.; Veblen, David R.

2011-01-01

Mineralogical studies of coatings on quartz grains and bulk sediments from an aquifer on Western Cape Cod, Massachusetts, USA were carried out using a variety of transmission electron microscopy (TEM) techniques. Previous studies demonstrated that coatings on quartz grains control the adsorption properties of these sediments. Samples for TEM characterization were made by a gentle mechanical grinding method and focused ion beam (FIB) milling. The former method can make abundant electron-transparent coating assemblages for comprehensive and quantitative X-ray analysis and the latter technique protects the coating texture from being destroyed. Characterization of the samples from both a pristine area and an area heavily impacted by wastewater discharge shows similar coating textures and chemical compositions. Major constituents of the coating include Al-substituted goethite and illite/chlorite clays. Goethite is aggregated into well-crystallized domains through oriented attachment resulting in increased porosity. Illite/chlorite clays with various chemical compositions were observed to be mixed with goethite aggregates and aligned sub-parallel to the associated quartz surface. The uniform spatial distribution of wastewater-derived phosphorus throughout the coating from the wastewater-contaminated site suggests that all of the coating constituents, including those adjacent to the quartz surface, are accessible to groundwater solutes. Both TEM characterization and chemical extraction results indicate there is a significantly greater amount of amorphous iron oxide in samples from wastewater discharge area compared to those from the pristine region, which might reflect the impact of redox cycling of iron under the wastewater-discharge area. Coating compositions are consistent with the moderate metal and oxy-metalloid adsorption capacities, low but significant cation exchange capacities, and control of iron(III) solubility by goethite observed in reactive transport experimental and modeling studies conducted at the site.

Aesthetic perception of visual textures: a holistic exploration using texture analysis, psychological experiment, and perception modeling.

PubMed

Liu, Jianli; Lughofer, Edwin; Zeng, Xianyi

2015-01-01

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 non-linear 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.

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

PubMed

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

2018-04-01

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

Decoupling of superposed textures in an electrically biased piezoceramic with a 100 preferred orientation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fancher, Chris M.; Blendell, John E.; Bowman, Keith J.

2017-02-07

A method leveraging Rietveld full-pattern texture analysis to decouple induced domain texture from a preferred grain orientation is presented in this paper. The proposed method is demonstrated by determining the induced domain texture in a polar polymorph of 100 oriented 0.91Bi 1/2Na 1/2TiO 3-0.07BaTiO 3-0.02K 0.5Na 0.5NbO 3. Domain textures determined using the present method are compared with results obtained via single peak fitting. Texture determined using single peak fitting estimated more domain alignment than that determined using the Rietveld based method. These results suggest that the combination of grain texture and phase transitions can lead to single peak fittingmore » under or over estimating domain texture. Finally, while demonstrated for a bulk piezoelectric, the proposed method can be applied to quantify domain textures in multi-component systems and thin films.« less

Texture in steel plates revealed by laser ultrasonic surface acoustic waves velocity dispersion analysis.

PubMed

Yin, Anmin; Wang, Xiaochen; Glorieux, Christ; Yang, Quan; Dong, Feng; He, Fei; Wang, Yanlong; Sermeus, Jan; Van der Donck, Tom; Shu, Xuedao

2017-07-01

A photoacoustic, laser ultrasonics based approach in an Impulsive Stimulated Scattering (ISS) implementation was used to investigate the texture in polycrystalline metal plates. The angular dependence of the 'polycrystalline' surface acoustic wave (SAW) velocity measured along regions containing many grains was experimentally determined and compared with simulated results that were based on the angular dependence of the 'single grain' SAW velocity within single grains and the grain orientation distribution. The polycrystalline SAW velocities turn out to vary with texture. The SAW velocities and their angular variations for {110} texture were found to be larger than that the ones for {111} texture or the strong γ fiber texture. The SAW velocities for {001} texture were larger than for {111} texture, but with almost the same angular dependence. The results infer the feasibility to apply angular SAW angular dispersion measurements by laser ultrasonics for on-line texture monitoring. Copyright © 2017 Elsevier B.V. All rights reserved.

Combined radiogrammetry and texture analysis for early diagnosis of osteoporosis using Indian and Swiss data.

PubMed

Areeckal, Anu Shaju; Kamath, Jagannath; Zawadynski, Sophie; Kocher, Michel; S, Sumam David

2018-05-26

Osteoporosis is a bone disorder characterized by bone loss and decreased bone strength. The most widely used technique for detection of osteoporosis is the measurement of bone mineral density (BMD) using dual energy X-ray absorptiometry (DXA). But DXA scans are expensive and not widely available in low-income economies. In this paper, we propose a low cost pre-screening tool for the detection of low bone mass, using cortical radiogrammetry of third metacarpal bone and trabecular texture analysis of distal radius from hand and wrist radiographs. An automatic segmentation algorithm to automatically locate and segment the third metacarpal bone and distal radius region of interest (ROI) is proposed. Cortical measurements such as combined cortical thickness (CCT), cortical area (CA), percent cortical area (PCA) and Barnett Nordin index (BNI) were taken from the shaft of third metacarpal bone. Texture analysis of trabecular network at the distal radius was performed using features obtained from histogram, gray level Co-occurrence matrix (GLCM) and morphological gradient method (MGM). The significant cortical and texture features were selected using independent sample t-test and used to train classifiers to classify healthy subjects and people with low bone mass. The proposed pre-screening tool was validated on two ethnic groups, Indian sample population and Swiss sample population. Data of 134 subjects from Indian sample population and 65 subjects from Swiss sample population were analysed. The proposed automatic segmentation approach shows a detection accuracy of 86% in detecting the third metacarpal bone shaft and 90% in accurately locating the distal radius ROI. Comparison of the automatic radiogrammetry to the ground truth provided by experts show a mean absolute error of 0.04 mm for cortical width of healthy group, 0.12 mm for cortical width of low bone mass group, 0.22 mm for medullary width of healthy group, and 0.26 mm for medullary width of low bone mass group. Independent sample t-test was used to select the most discriminant features, to be used as input for training the classifiers. Pearson correlation analysis of the extracted features with DXA-BMD of lumbar spine (DXA-LS) shows significantly high correlation values. Classifiers were trained with the most significant features in the Indian and Swiss sample data. Weighted KNN classifier shows the best test accuracy of 78% for Indian sample data and 100% for Swiss sample data. Hence, combined automatic radiogrammetry and texture analysis is shown to be an effective low cost pre-screening tool for early diagnosis of osteoporosis. Copyright © 2018 Elsevier Ltd. All rights reserved.

The analysis of image feature robustness using cometcloud

PubMed Central

Qi, Xin; Kim, Hyunjoo; Xing, Fuyong; Parashar, Manish; Foran, David J.; Yang, Lin

2012-01-01

The robustness of image features is a very important consideration in quantitative image analysis. The objective of this paper is to investigate the robustness of a range of image texture features using hematoxylin stained breast tissue microarray slides which are assessed while simulating different imaging challenges including out of focus, changes in magnification and variations in illumination, noise, compression, distortion, and rotation. We employed five texture analysis methods and tested them while introducing all of the challenges listed above. The texture features that were evaluated include co-occurrence matrix, center-symmetric auto-correlation, texture feature coding method, local binary pattern, and texton. Due to the independence of each transformation and texture descriptor, a network structured combination was proposed and deployed on the Rutgers private cloud. The experiments utilized 20 randomly selected tissue microarray cores. All the combinations of the image transformations and deformations are calculated, and the whole feature extraction procedure was completed in 70 minutes using a cloud equipped with 20 nodes. Center-symmetric auto-correlation outperforms all the other four texture descriptors but also requires the longest computational time. It is roughly 10 times slower than local binary pattern and texton. From a speed perspective, both the local binary pattern and texton features provided excellent performance for classification and content-based image retrieval. PMID:23248759

Texture analysis of high-resolution FLAIR images for TLE

NASA Astrophysics Data System (ADS)

Jafari-Khouzani, Kourosh; Soltanian-Zadeh, Hamid; Elisevich, Kost

2005-04-01

This paper presents a study of the texture information of high-resolution FLAIR images of the brain with the aim of determining the abnormality and consequently the candidacy of the hippocampus for temporal lobe epilepsy (TLE) surgery. Intensity and volume features of the hippocampus from FLAIR images of the brain have been previously shown to be useful in detecting the abnormal hippocampus in TLE. However, the small size of the hippocampus may limit the texture information. High-resolution FLAIR images show more details of the abnormal intensity variations of the hippocampi and therefore are more suitable for texture analysis. We study and compare the low and high-resolution FLAIR images of six epileptic patients. The hippocampi are segmented manually by an expert from T1-weighted MR images. Then the segmented regions are mapped on the corresponding FLAIR images for texture analysis. The 2-D wavelet transforms of the hippocampi are employed for feature extraction. We compare the ability of the texture features from regular and high-resolution FLAIR images to distinguish normal and abnormal hippocampi. Intracranial EEG results as well as surgery outcome are used as gold standard. The results show that the intensity variations of the hippocampus are related to the abnormalities in the TLE.

Three-dimensional ultrasound-based texture analysis of the effect of atorvastatin on carotid atherosclerosis

NASA Astrophysics Data System (ADS)

Awad, Joseph; Krasinski, Adam; Spence, David; Parraga, Grace; Fenster, Aaron

2010-03-01

Carotid atherosclerosis is the major cause of ischemic stroke, a leading cause of death and disability. This is driving the development of image analysis methods to quantitatively evaluate local arterial effects of potential treatments of carotid disease. Here we investigate the use of novel texture analysis tools to detect potential changes in the carotid arteries after statin therapy. Three-dimensional (3D) carotid ultrasound images were acquired from the left and right carotid arteries of 35 subjects (16 treated with 80 mg atorvastatin and 19 treated with placebo) at baseline and after 3 months of treatment. Two-hundred and seventy texture features were extracted from 3D ultrasound carotid artery images. These images previously had their vessel walls (VW) manually segmented. Highly ranked individual texture features were selected and compared to the VW volume (VWV) change using 3 measures: distance between classes, Wilcoxon rank sum test, and accuracy of the classifiers. Six classifiers were used. Using texture feature (L7R7) increases the average accuracy and area under the ROC curve to 74.4% and 0.72 respectively compared to 57.2% and 0.61 using VWV change. Thus, the results demonstrate that texture features are more sensitive in detecting drug effects on the carotid vessel wall than VWV change.

Classification of pulmonary nodules in lung CT images using shape and texture features

NASA Astrophysics Data System (ADS)

Dhara, Ashis Kumar; Mukhopadhyay, Sudipta; Dutta, Anirvan; Garg, Mandeep; Khandelwal, Niranjan; Kumar, Prafulla

2016-03-01

Differentiation of malignant and benign pulmonary nodules is important for prognosis of lung cancer. In this paper, benign and malignant nodules are classified using support vector machine. Several shape-based and texture-based features are used to represent the pulmonary nodules in the feature space. A semi-automated technique is used for nodule segmentation. Relevant features are selected for efficient representation of nodules in the feature space. The proposed scheme and the competing technique are evaluated on a data set of 542 nodules of Lung Image Database Consortium and Image Database Resource Initiative. The nodules with composite rank of malignancy "1","2" are considered as benign and "4","5" are considered as malignant. Area under the receiver operating characteristics curve is 0:9465 for the proposed method. The proposed method outperforms the competing technique.

Textural signatures for wetland vegetation

NASA Technical Reports Server (NTRS)

Whitman, R. I.; Marcellus, K. L.

1973-01-01

This investigation indicates that unique textural signatures do exist for specific wetland communities at certain times in the growing season. When photographs with the proper resolution are obtained, the textural features can identify the spectral features of the vegetation community seen with lower resolution mapping data. The development of a matrix of optimum textural signatures is the goal of this research. Seasonal variations of spectral and textural features are particularly important when performing a vegetations analysis of fresh water marshes. This matrix will aid in flight planning, since expected seasonal variations and resolution requirements can be established prior to a given flight mission.

Efficient Data Mining for Local Binary Pattern in Texture Image Analysis

PubMed Central

Kwak, Jin Tae; Xu, Sheng; Wood, Bradford J.

2015-01-01

Local binary pattern (LBP) is a simple gray scale descriptor to characterize the local distribution of the grey levels in an image. Multi-resolution LBP and/or combinations of the LBPs have shown to be effective in texture image analysis. However, it is unclear what resolutions or combinations to choose for texture analysis. Examining all the possible cases is impractical and intractable due to the exponential growth in a feature space. This limits the accuracy and time- and space-efficiency of LBP. Here, we propose a data mining approach for LBP, which efficiently explores a high-dimensional feature space and finds a relatively smaller number of discriminative features. The features can be any combinations of LBPs. These may not be achievable with conventional approaches. Hence, our approach not only fully utilizes the capability of LBP but also maintains the low computational complexity. We incorporated three different descriptors (LBP, local contrast measure, and local directional derivative measure) with three spatial resolutions and evaluated our approach using two comprehensive texture databases. The results demonstrated the effectiveness and robustness of our approach to different experimental designs and texture images. PMID:25767332

Color and texture associations in voice-induced synesthesia

PubMed Central

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

Fingerprint recognition of alien invasive weeds based on the texture character and machine learning

NASA Astrophysics Data System (ADS)

Yu, Jia-Jia; Li, Xiao-Li; He, Yong; Xu, Zheng-Hao

2008-11-01

Multi-spectral imaging technique based on texture analysis and machine learning was proposed to discriminate alien invasive weeds with similar outline but different categories. The objectives of this study were to investigate the feasibility of using Multi-spectral imaging, especially the near-infrared (NIR) channel (800 nm+/-10 nm) to find the weeds' fingerprints, and validate the performance with specific eigenvalues by co-occurrence matrix. Veronica polita Pries, Veronica persica Poir, longtube ground ivy, Laminum amplexicaule Linn. were selected in this study, which perform different effect in field, and are alien invasive species in China. 307 weed leaves' images were randomly selected for the calibration set, while the remaining 207 samples for the prediction set. All images were pretreated by Wallis filter to adjust the noise by uneven lighting. Gray level co-occurrence matrix was applied to extract the texture character, which shows density, randomness correlation, contrast and homogeneity of texture with different algorithms. Three channels (green channel by 550 nm+/-10 nm, red channel by 650 nm+/-10 nm and NIR channel by 800 nm+/-10 nm) were respectively calculated to get the eigenvalues.Least-squares support vector machines (LS-SVM) was applied to discriminate the categories of weeds by the eigenvalues from co-occurrence matrix. Finally, recognition ratio of 83.35% by NIR channel was obtained, better than the results by green channel (76.67%) and red channel (69.46%). The prediction results of 81.35% indicated that the selected eigenvalues reflected the main characteristics of weeds' fingerprint based on multi-spectral (especially by NIR channel) and LS-SVM model.

Coregistered FDG PET/CT-based textural characterization of head and neck cancer for radiation treatment planning.

PubMed

Yu, Huan; Caldwell, Curtis; Mah, Katherine; Mozeg, Daniel

2009-03-01

Coregistered fluoro-deoxy-glucose (FDG) positron emission tomography/computed tomography (PET/CT) has shown potential to improve the accuracy of radiation targeting of head and neck cancer (HNC) when compared to the use of CT simulation alone. The objective of this study was to identify textural features useful in distinguishing tumor from normal tissue in head and neck via quantitative texture analysis of coregistered 18F-FDG PET and CT images. Abnormal and typical normal tissues were manually segmented from PET/CT images of 20 patients with HNC and 20 patients with lung cancer. Texture features including some derived from spatial grey-level dependence matrices (SGLDM) and neighborhood gray-tone-difference matrices (NGTDM) were selected for characterization of these segmented regions of interest (ROIs). Both K nearest neighbors (KNNs) and decision tree (DT)-based KNN classifiers were employed to discriminate images of abnormal and normal tissues. The area under the curve (AZ) of receiver operating characteristics (ROC) was used to evaluate the discrimination performance of features in comparison to an expert observer. The leave-one-out and bootstrap techniques were used to validate the results. The AZ of DT-based KNN classifier was 0.95. Sensitivity and specificity for normal and abnormal tissue classification were 89% and 99%, respectively. In summary, NGTDM features such as PET Coarseness, PET Contrast, and CT Coarseness extracted from FDG PET/CT images provided good discrimination performance. The clinical use of such features may lead to improvement in the accuracy of radiation targeting of HNC.

Investigating the chemical mist deposition technique for poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) on textured crystalline-silicon for organic/crystalline-silicon heterojunction solar cells

NASA Astrophysics Data System (ADS)

Hossain, Jaker; Ohki, Tatsuya; Ichikawa, Koki; Fujiyama, Kazuhiko; Ueno, Keiji; Fujii, Yasuhiko; Hanajiri, Tatsuro; Shirai, Hajime

2016-03-01

Chemical mist deposition (CMD) of poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS) was investigated in terms of cavitation frequency f, solvent, flow rate of nitrogen, substrate temperature Ts, and substrate dc bias Vs as variables for efficient PEDOT:PSS/crystalline silicon (c-Si) heterojunction solar cells. The high-speed-camera and differential mobility analysis characterizations revealed that the average size and flux of PEDOT:PSS mist depend on f, type of solvent, and Vs. Film deposition occurred when positive Vs was applied to the c-Si substrate at Ts of 30-40 °C, whereas no deposition of films occurred with negative Vs, implying that the film is deposited mainly from negatively charged mist. The uniform deposition of PEDOT:PSS films occurred on textured c-Si(100) substrates by adjusting Ts and Vs. The adhesion of CMD PEDOT:PSS film to c-Si was greatly enhanced by applying substrate dc bias Vs compared with that of spin-coated film. The CMD PEDOT:PSS/c-Si heterojunction solar cell devices on textured c-Si(100) in 2 × 2 cm2 exhibited a power conversion efficiency η of 11.0% with better uniformity of the solar cell parameters. Furthermore, η was increased to 12.5% by adding an AR coating layer of molybdenum oxide MoOx formed by CMD. These findings suggest that CMD with negatively charged mist has great potential for the uniform deposition of organic and inorganic materials on textured c-Si substrates by suitably adjusting Ts and Vs.

Correlation between 99Tcm-HMPAO-SPECT brain image and a history of decompression illness or extent of diving experience in commercial divers.

PubMed Central

Shields, T G; Duff, P M; Evans, S A; Gemmell, H G; Sharp, P F; Smith, F W; Staff, R T; Wilcock, S E

1997-01-01

OBJECTIVES: To explore the use of 99technetiumm-hexamethyl propylene amine oxime single photon computed tomography (HMPAO-SPECT) of the brain as a means of detecting nervous tissue damage in divers and to determine if there is any correlation between brain image and a diver's history of diving or decompression illness (DCI). METHODS: 28 commercial divers with a history of DCI, 26 divers with no history of DCI, and 19 non-diving controls were examined with brain HMPAO-SPECT. Results were classified by observer assessment as normal (I) or as a pattern variants (II-V). The brain images of a subgroup of these divers (n = 44) and the controls (n = 17) were further analysed with a first order texture analysis technique based on a grey level histogram. RESULTS: 15 of 54 commercial divers (28%) were visually assessed as having HMPAO-SPECT images outside normal limits compared with 15.8% in appropriately identified non-diver control subjects. 18% of divers with a history of DCI were classified as having a pattern different from the normal image compared with 38% with no history of DCI. No association was established between the presence of a pattern variant from the normal image and history of DCI, diving, or other previous possible neurological insult. On texture analysis of the brain images, divers had a significantly lower mean grey level (MGL) than non-divers. Divers with a history of DCI (n = 22) had a significantly lower MGL when compared with divers with no history of DCI (n = 22). Divers with > 14 years professional diving or > 100 decompression days a year had a significantly lower MGL value. CONCLUSIONS: Observer assessment of HMPAO-SPECT brain images can lead to disparity in results. Texture analysis of the brain images supplies both an objective and consistent method of measurement. A significant correlation was found between a low measure of MGL and a history of DCI. There was also an indication that diving itself had an effect on texture measurement, implying that it had caused subclinical nervous tissue damage. PMID:9166130

Employing wavelet-based texture features in ammunition classification

NASA Astrophysics Data System (ADS)

Borzino, Ángelo M. C. R.; Maher, Robert C.; Apolinário, José A.; de Campos, Marcello L. R.

2017-05-01

Pattern recognition, a branch of machine learning, involves classification of information in images, sounds, and other digital representations. This paper uses pattern recognition to identify which kind of ammunition was used when a bullet was fired based on a carefully constructed set of gunshot sound recordings. To do this task, we show that texture features obtained from the wavelet transform of a component of the gunshot signal, treated as an image, and quantized in gray levels, are good ammunition discriminators. We test the technique with eight different calibers and achieve a classification rate better than 95%. We also compare the performance of the proposed method with results obtained by standard temporal and spectrographic techniques

Spatially resolved texture and microstructure evolution of additively manufactured and gas gun deformed 304L stainless steel investigated by neutron diffraction and electron backscatter diffraction

DOE PAGES

Takajo, Shigehiro; Brown, Donald William; Clausen, Bjorn; ...

2018-04-30

In this study, we report the characterization of a 304L stainless steel cylindrical projectile produced by additive manufacturing. The projectile was compressively deformed using a Taylor Anvil Gas Gun, leading to a huge strain gradient along the axis of the deformed cylinder. Spatially resolved neutron diffraction measurements on the HIgh Pressure Preferred Orientation time-of-flight diffractometer (HIPPO) and Spectrometer for Materials Research at Temperature and Stress diffractometer (SMARTS) beamlines at the Los Alamos Neutron Science CEnter (LANSCE) with Rietveld and single-peak analysis were used to quantitatively evaluate the volume fractions of the α, γ, and ε phases as well as residualmore » strain and texture. The texture of the γ phase is consistent with uniaxial compression, while the α texture can be explained by the Kurdjumov–Sachs relationship from the γ texture after deformation. This indicates that the material first deformed in the γ phase and subsequently transformed at larger strains. The ε phase was only found in volumes close to the undeformed material with a texture connected to the γ texture by the Shoji–Nishiyama orientation relationship. This allows us to conclude that the ε phase occurs as an intermediate phase at lower strain, and is superseded by the α phase when strain increases further. We found a proportionality between the root-mean-squared microstrain of the γ phase, dominated by the dislocation density, with the α volume fraction, consistent with strain-induced martensite α formation. In conclusion, knowledge of the sample volume with the ε phase from the neutron diffraction analysis allowed us to identify the ε phase by electron back scatter diffraction analysis, complementing the neutron diffraction analysis with characterization on the grain level.« less

Spatially resolved texture and microstructure evolution of additively manufactured and gas gun deformed 304L stainless steel investigated by neutron diffraction and electron backscatter diffraction

DOE Office of Scientific and Technical Information (OSTI.GOV)

Takajo, Shigehiro; Brown, Donald William; Clausen, Bjorn

In this study, we report the characterization of a 304L stainless steel cylindrical projectile produced by additive manufacturing. The projectile was compressively deformed using a Taylor Anvil Gas Gun, leading to a huge strain gradient along the axis of the deformed cylinder. Spatially resolved neutron diffraction measurements on the HIgh Pressure Preferred Orientation time-of-flight diffractometer (HIPPO) and Spectrometer for Materials Research at Temperature and Stress diffractometer (SMARTS) beamlines at the Los Alamos Neutron Science CEnter (LANSCE) with Rietveld and single-peak analysis were used to quantitatively evaluate the volume fractions of the α, γ, and ε phases as well as residualmore » strain and texture. The texture of the γ phase is consistent with uniaxial compression, while the α texture can be explained by the Kurdjumov–Sachs relationship from the γ texture after deformation. This indicates that the material first deformed in the γ phase and subsequently transformed at larger strains. The ε phase was only found in volumes close to the undeformed material with a texture connected to the γ texture by the Shoji–Nishiyama orientation relationship. This allows us to conclude that the ε phase occurs as an intermediate phase at lower strain, and is superseded by the α phase when strain increases further. We found a proportionality between the root-mean-squared microstrain of the γ phase, dominated by the dislocation density, with the α volume fraction, consistent with strain-induced martensite α formation. In conclusion, knowledge of the sample volume with the ε phase from the neutron diffraction analysis allowed us to identify the ε phase by electron back scatter diffraction analysis, complementing the neutron diffraction analysis with characterization on the grain level.« less

Domain Engineered Magnetoelectric Thin Films for High Sensitivity Resonant Magnetic Field Sensors

DTIC Science & Technology

2011-12-01

synthesis and texture analysis Sol-gel deposition and RF sputtering process was developed for deposition of PZT on Pt/Ti/Si02/Si (hereafter...well textured (i.e. with preferred crystalline orientation). To texture and obtain crack-free thick PZT RF films, we employed pre- treated substrates...and post-deposition annealing. One pre-treatment was the use of seed layer of textured PZT sol-gel thin film of thickness 65-85nm [1]. • Oean

Textural features for radar image analysis

NASA Technical Reports Server (NTRS)

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.

BRAIN TUMOR SEGMENTATION WITH SYMMETRIC TEXTURE AND SYMMETRIC INTENSITY-BASED DECISION FORESTS.

PubMed

Bianchi, Anthony; Miller, James V; Tan, Ek Tsoon; Montillo, Albert

2013-04-01

Accurate automated segmentation of brain tumors in MR images is challenging due to overlapping tissue intensity distributions and amorphous tumor shape. However, a clinically viable solution providing precise quantification of tumor and edema volume would enable better pre-operative planning, treatment monitoring and drug development. Our contributions are threefold. First, we design efficient gradient and LBPTOP based texture features which improve classification accuracy over standard intensity features. Second, we extend our texture and intensity features to symmetric texture and symmetric intensity which further improve the accuracy for all tissue classes. Third, we demonstrate further accuracy enhancement by extending our long range features from 100mm to a full 200mm. We assess our brain segmentation technique on 20 patients in the BraTS 2012 dataset. Impact from each contribution is measured and the combination of all the features is shown to yield state-of-the-art accuracy and speed.

Investigation of rail wheel steel crystallographic texture changes due to modification and thermomechanical treatment

NASA Astrophysics Data System (ADS)

Lychagina, T.; Nikolayev, D.; Sanin, A.; Tatarko, J.; Ullemeyer, K.

2015-04-01

In this work crystallographic texture for a set of rail wheel steel samples with different regimes of thermo-mechanical treatment and with and without modification by system Al-Mg-Si- Fe-C-Ca-Ti-Ce was measured by neutron diffraction. The texture measurements were carried out by using time-of-flight technique at SKAT diffractometer situated at IBR-2 reactor (Dubna, JINR, Russia). The three complete pole figures (110), (200), (211) of α-Fe phase in 5°×5°grid were extracted from a set of 1368 spectra measured for each sample. The samples were cut from rail wheel rim and from transitional zone (between rail wheel hub and wheel disk). It was concluded that the steel modification and some changes in the heat treatment modes of the rail wheels from the experimental (modified) and the conventional (non-modified) steel lead to reorientation of texture component.

Texture-dependent motion signals in primate middle temporal area

PubMed Central

Gharaei, Saba; Tailby, Chris; Solomon, Selina S; Solomon, Samuel G

2013-01-01

Neurons in the middle temporal (MT) area of primate cortex provide an important stage in the analysis of visual motion. For simple stimuli such as bars and plaids some neurons in area MT – pattern cells – seem to signal motion independent of contour orientation, but many neurons – component cells – do not. Why area MT supports both types of receptive field is unclear. To address this we made extracellular recordings from single units in area MT of anaesthetised marmoset monkeys and examined responses to two-dimensional images with a large range of orientations and spatial frequencies. Component and pattern cell response remained distinct during presentation of these complex spatial textures. Direction tuning curves were sharpest in component cells when a texture contained a narrow range of orientations, but were similar across all neurons for textures containing all orientations. Response magnitude of pattern cells, but not component cells, increased with the spatial bandwidth of the texture. In addition, response variability in all neurons was reduced when the stimulus was rich in spatial texture. Fisher information analysis showed that component cells provide more informative responses than pattern cells when a texture contains a narrow range of orientations, but pattern cells had more informative responses for broadband textures. Component cells and pattern cells may therefore coexist because they provide complementary and parallel motion signals. PMID:24000175

Rough-Fuzzy Clustering and Unsupervised Feature Selection for Wavelet Based MR Image Segmentation

PubMed Central

Maji, Pradipta; Roy, Shaswati

2015-01-01

Image segmentation is an indispensable process in the visualization of human tissues, particularly during clinical analysis of brain magnetic resonance (MR) images. For many human experts, manual segmentation is a difficult and time consuming task, which makes an automated brain MR image segmentation method desirable. In this regard, this paper presents a new segmentation method for brain MR images, integrating judiciously the merits of rough-fuzzy computing and multiresolution image analysis technique. The proposed method assumes that the major brain tissues, namely, gray matter, white matter, and cerebrospinal fluid from the MR images are considered to have different textural properties. The dyadic wavelet analysis is used to extract the scale-space feature vector for each pixel, while the rough-fuzzy clustering is used to address the uncertainty problem of brain MR image segmentation. An unsupervised feature selection method is introduced, based on maximum relevance-maximum significance criterion, to select relevant and significant textural features for segmentation problem, while the mathematical morphology based skull stripping preprocessing step is proposed to remove the non-cerebral tissues like skull. The performance of the proposed method, along with a comparison with related approaches, is demonstrated on a set of synthetic and real brain MR images using standard validity indices. PMID:25848961

Investigation of the Influence of Shapes-Texture on Surface Deformation of UHMWPE as a Bearing Material in Static Normal Load and Rolling Contact

NASA Astrophysics Data System (ADS)

Lestari, W. D.; Ismail, R.; Jamari, J.; Bayuseno, A. P.

2017-05-01

Surface texture is a common method for improving wear properties of a tribo-pair of soft and hard bearing material. The reduction of wear rates on the contacting surface material is becoming important issues. In the present study, analysis of the contact pressure on the flat surface of UHMWPE (Ultra High Molecular Weight Polyethylene) under the static- and rolling motion with the surface of steel ball used the 3D finite element method (FEM) (the ABAQUS software version 6.12). Five shaped-texture models (square, circle, ellipse, triangle, and chevron) were presented on the flat surface for analysis. The normal load of 17, 30 and 50 N was deliberately set-up for static and rolling contact analysis. The contact pressure was determined to predict the wear behavior of the shaped-texture on the flat surface of UHMWPE. The results have shown that the static normal load yielded the lowest von-Mises stress distribution on the shaped-texture of the ellipse for all values applied a load, while the square shape experienced the highest stress distribution. Under rolling contact, however, the increasing load yielded the increasing von Mises stress distribution for the texture with a triangle shape. Moreover, the texture shapes for circle, ellipse, and chevron respectively, may undergo the lowest stress distribution for all load. The wear calculation provided that the circle and square shape may undergo the highest wear rates. Obviously, the surface texture of circle, ellipse, and chevron may experience the lowest wear rates and is potential for use in the surface engineering of bearing materials.

Breast Implant-Associated Anaplastic Large Cell Lymphoma in Australia and New Zealand: High-Surface-Area Textured Implants Are Associated with Increased Risk.

PubMed

Loch-Wilkinson, Anna; Beath, Kenneth J; Knight, Robert John William; Wessels, William Louis Fick; Magnusson, Mark; Papadopoulos, Tim; Connell, Tony; Lofts, Julian; Locke, Michelle; Hopper, Ingrid; Cooter, Rodney; Vickery, Karen; Joshi, Preeti Avinash; Prince, H Miles; Deva, Anand K

2017-10-01

The association between breast implants and breast implant-associated anaplastic large cell lymphoma (ALCL) has been confirmed. Implant-related risk has been difficult to estimate to date due to incomplete datasets. All cases in Australia and New Zealand were identified and analyzed. Textured implants reported in this group were subjected to surface area analysis. Sales data from three leading breast implant manufacturers (i.e., Mentor, Allergan, and Silimed) dating back to 1999 were secured to estimate implant-specific risk. Fifty-five cases of breast implant-associated ALCL were diagnosed in Australia and New Zealand between 2007 and 2016. The mean age of patients was 47.1 years and the mean time of implant exposure was 7.46 years. There were four deaths in the series related to mass and/or metastatic presentation. All patients were exposed to textured implants. Surface area analysis confirmed that higher surface area was associated with 64 of the 75 implants used (85.3 percent). Biocell salt loss textured (Allergan, Inamed, and McGhan) implants accounted for 58.7 percent of the implants used in this series. Comparative analysis showed the risk of developing breast implant-associated ALCL to be 14.11 times higher with Biocell textured implants and 10.84 higher with polyurethane (Silimed) textured implants compared with Siltex textured implants. This study has calculated implant-specific risk of breast implant-associated ALCL. Higher-surface-area textured implants have been shown to significantly increase the risk of breast implant-associated ALCL in Australia and New Zealand. The authors present a unifying hypothesis to explain these observations.

JView Visualization for Next Generation Air Transportation System

DTIC Science & Technology

2011-01-01

hardware graphics acceleration. JView relies on concrete Object Oriented Design (OOD) and programming techniques to provide a robust and venue non...visibility priority of a texture set. A good example of this is you have translucent images that should always be visible over the other textures...elements present in the scene. • Capture Alpha. Allows the alpha color channel ( translucency ) to be saved when capturing images or movies of a 3D scene

Texture classification of lung computed tomography images

NASA Astrophysics Data System (ADS)

Pheng, Hang See; Shamsuddin, Siti M.

2013-03-01

Current development of algorithms in computer-aided diagnosis (CAD) scheme is growing rapidly to assist the radiologist in medical image interpretation. Texture analysis of computed tomography (CT) scans is one of important preliminary stage in the computerized detection system and classification for lung cancer. Among different types of images features analysis, Haralick texture with variety of statistical measures has been used widely in image texture description. The extraction of texture feature values is essential to be used by a CAD especially in classification of the normal and abnormal tissue on the cross sectional CT images. This paper aims to compare experimental results using texture extraction and different machine leaning methods in the classification normal and abnormal tissues through lung CT images. The machine learning methods involve in this assessment are Artificial Immune Recognition System (AIRS), Naive Bayes, Decision Tree (J48) and Backpropagation Neural Network. AIRS is found to provide high accuracy (99.2%) and sensitivity (98.0%) in the assessment. For experiments and testing purpose, publicly available datasets in the Reference Image Database to Evaluate Therapy Response (RIDER) are used as study cases.

New constraints on deformation processes in serpentinite from sub-micron Raman Spectroscopy and TEM

NASA Astrophysics Data System (ADS)

Smith, S. A. F.; Tarling, M.; Rooney, J. S.; Gordon, K. C.; Viti, C.

2017-12-01

Extensive work has been performed to characterize the mineralogical and mechanical properties of the various serpentine minerals (i.e. antigorite, lizardite, chrysotile, polyhedral and polygonal serpentine). However, correct identification of serpentine minerals is often difficult or impossible using conventional analytical techniques such as optical- and SEM-based microscopy, X-ray diffraction and infrared spectroscopy. Transmission Electron Microscopy (TEM) is the best analytical technique to identify the serpentine minerals, but TEM requires complex sample preparation and typically results in very small analysis areas. Sub-micron confocal Raman spectroscopy mapping of polished thin sections provides a quick and relatively inexpensive way of unambiguously distinguishing the main serpentine minerals within their in-situ microstructural context. The combination of high spatial resolution (with a diffraction-limited system, 366 nm), large-area coverage (up to hundreds of microns in each dimension) and ability to map directly on thin sections allows intricate fault rock textures to be imaged at a sample-scale, which can then form the target of more focused TEM work. The potential of sub-micron Raman Spectroscopy + TEM is illustrated by examining sub-micron-scale mineral intergrowths and deformation textures in scaly serpentinites (e.g. dissolution seams, mineral growth in pressure shadows), serpentinite crack-seal veins and polished fault slip surfaces from a serpentinite-bearing mélange in New Zealand. The microstructural information provided by these techniques has yielded new insights into coseismic dehydration and amorphization processes and the interplay between creep and localised rupture in serpentinite shear zones.

Surface defect detection in tiling Industries using digital image processing methods: analysis and evaluation.

PubMed

Karimi, Mohammad H; Asemani, Davud

2014-05-01

Ceramic and tile industries should indispensably include a grading stage to quantify the quality of products. Actually, human control systems are often used for grading purposes. An automatic grading system is essential to enhance the quality control and marketing of the products. Since there generally exist six different types of defects originating from various stages of tile manufacturing lines with distinct textures and morphologies, many image processing techniques have been proposed for defect detection. In this paper, a survey has been made on the pattern recognition and image processing algorithms which have been used to detect surface defects. Each method appears to be limited for detecting some subgroup of defects. The detection techniques may be divided into three main groups: statistical pattern recognition, feature vector extraction and texture/image classification. The methods such as wavelet transform, filtering, morphology and contourlet transform are more effective for pre-processing tasks. Others including statistical methods, neural networks and model-based algorithms can be applied to extract the surface defects. Although, statistical methods are often appropriate for identification of large defects such as Spots, but techniques such as wavelet processing provide an acceptable response for detection of small defects such as Pinhole. A thorough survey is made in this paper on the existing algorithms in each subgroup. Also, the evaluation parameters are discussed including supervised and unsupervised parameters. Using various performance parameters, different defect detection algorithms are compared and evaluated. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

Changing the texture of footwear can alter gait patterns.

PubMed

Nurse, Matthew A; Hulliger, Manuel; Wakeling, James M; Nigg, Benno M; Stefanyshyn, Darren J

2005-10-01

The foot provides an important source of afferent feedback for balance and locomotion. Sensory feedback from the feet can be altered by standing or walking on different surfaces. The purpose was to determine the effects of textured footwear on lower extremity muscle activity, limb kinematics, and joint kinetics while walking. Three-dimensional kinematics and kinetics, as well as muscle EMG, were collected as subjects walked with a smooth and textured shoe insert. Muscle activity was analyzed using a wavelet technique. The textured shoe insert caused a significant reduction in both soleus and tibialis anterior intensity during periods when these muscles are most active. Furthermore, the changes in muscle activity were only seen in the low frequency content of the EMG signal. The foot was significantly more plantar flexed at heel strike with the textured inserts. Small changes were also seen in vertical ground reaction forces and joint moments. It was assumed that the changes in gait patterns were due to a change in sensory feedback caused by the textured shoe insert. The possibilities of altered sensory feedback with footwear are discussed. Sensory feedback from the feet may affect specific motor unit pools during different activities. Changing the texture, without changing the geometry, of a shoe insert can alter muscle activity during walking. This may be useful in the prescription of footwear interventions and suggests that footwear may have sensory as well as mechanical effects.

Time-frequency feature representation using multi-resolution texture analysis and acoustic activity detector for real-life speech emotion recognition.

PubMed

Wang, Kun-Ching

2015-01-14

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.

Principles of Metamorphic Petrology

NASA Astrophysics Data System (ADS)

Williams, Michael L.

2009-05-01

The field of metamorphic petrology has seen spectacular advances in the past decade, including new X-ray mapping techniques for characterizing metamorphic rocks and minerals, new internally consistent thermobarometers, new software for constructing and viewing phase diagrams, new methods to date metamorphic processes, and perhaps most significant, revised petrologic databases and the ability to calculate accurate phase diagrams and pseudosections. These tools and techniques provide new power and resolution for constraining pressure-temperature (P-T) histories and tectonic events. Two books have been fundamental for empowering petrologists and structural geologists during the past decade. Frank Spear's Metamorphic Phase Equilibria and Pressure-Temperature-Time Paths, published in 1993, builds on his seminal papers to provide a quantitative framework for P-T path analysis. Spear's book lays the foundation for modern quantitative metamorphic analysis. Cees Passchier and Rudolph Trouw's Microtectonics, published in 2005, with its superb photos and figures, provides the tools and the theory for interpreting deformation textures and inferring deformation processes.

Mammographic parenchymal texture as an imaging marker of hormonal activity: a comparative study between pre- and post-menopausal women

NASA Astrophysics Data System (ADS)

Daye, Dania; Bobo, Ezra; Baumann, Bethany; Ioannou, Antonios; Conant, Emily F.; Maidment, Andrew D. A.; Kontos, Despina

2011-03-01

Mammographic parenchymal texture patterns have been shown to be related to breast cancer risk. Yet, little is known about the biological basis underlying this association. Here, we investigate the potential of mammographic parenchymal texture patterns as an inherent phenotypic imaging marker of endogenous hormonal exposure of the breast tissue. Digital mammographic (DM) images in the cranio-caudal (CC) view of the unaffected breast from 138 women diagnosed with unilateral breast cancer were retrospectively analyzed. Menopause status was used as a surrogate marker of endogenous hormonal activity. Retroareolar 2.5cm2 ROIs were segmented from the post-processed DM images using an automated algorithm. Parenchymal texture features of skewness, coarseness, contrast, energy, homogeneity, grey-level spatial correlation, and fractal dimension were computed. Receiver operating characteristic (ROC) curve analysis was performed to evaluate feature classification performance in distinguishing between 72 pre- and 66 post-menopausal women. Logistic regression was performed to assess the independent effect of each texture feature in predicting menopause status. ROC analysis showed that texture features have inherent capacity to distinguish between pre- and post-menopausal statuses (AUC>0.5, p<0.05). Logistic regression including all texture features yielded an ROC curve with an AUC of 0.76. Addition of age at menarche, ethnicity, contraception use and hormonal replacement therapy (HRT) use lead to a modest model improvement (AUC=0.78) while texture features maintained significant contribution (p<0.05). The observed differences in parenchymal texture features between pre- and post- menopausal women suggest that mammographic texture can potentially serve as a surrogate imaging marker of endogenous hormonal activity.

Mammographic phenotypes of breast cancer risk driven by breast anatomy

NASA Astrophysics Data System (ADS)

Gastounioti, Aimilia; Oustimov, Andrew; Hsieh, Meng-Kang; Pantalone, Lauren; Conant, Emily F.; Kontos, Despina

2017-03-01

Image-derived features of breast parenchymal texture patterns have emerged as promising risk factors for breast cancer, paving the way towards personalized recommendations regarding women's cancer risk evaluation and screening. The main steps to extract texture features of the breast parenchyma are the selection of regions of interest (ROIs) where texture analysis is performed, the texture feature calculation and the texture feature summarization in case of multiple ROIs. In this study, we incorporate breast anatomy in these three key steps by (a) introducing breast anatomical sampling for the definition of ROIs, (b) texture feature calculation aligned with the structure of the breast and (c) weighted texture feature summarization considering the spatial position and the underlying tissue composition of each ROI. We systematically optimize this novel framework for parenchymal tissue characterization in a case-control study with digital mammograms from 424 women. We also compare the proposed approach with a conventional methodology, not considering breast anatomy, recently shown to enhance the case-control discriminatory capacity of parenchymal texture analysis. The case-control classification performance is assessed using elastic-net regression with 5-fold cross validation, where the evaluation measure is the area under the curve (AUC) of the receiver operating characteristic. Upon optimization, the proposed breast-anatomy-driven approach demonstrated a promising case-control classification performance (AUC=0.87). In the same dataset, the performance of conventional texture characterization was found to be significantly lower (AUC=0.80, DeLong's test p-value<0.05). Our results suggest that breast anatomy may further leverage the associations of parenchymal texture features with breast cancer, and may therefore be a valuable addition in pipelines aiming to elucidate quantitative mammographic phenotypes of breast cancer risk.

Simulation of complex magnesium alloy texture using the axial component fit method with central normal distributions

NASA Astrophysics Data System (ADS)

Ivanova, T. M.; Serebryany, V. N.

2017-12-01

The component fit method in quantitative texture analysis assumes that the texture of the polycrystalline sample can be represented by a superposition of weighted standard distributions those are characterized by position in the orientation space, shape and sharpness of the scattering. The components of the peak and axial shapes are usually used. It is known that an axial texture develops in materials subjected to direct pressing. In this paper we considered the possibility of modelling a texture of a magnesium sample subjected to equal-channel angular pressing with axial components only. The results obtained make it possible to conclude that ECAP is also a process leading to the appearance of an axial texture in magnesium alloys.

The effect of plastic strain on the evolution of crystallographic texture in Zircaloy-2

NASA Astrophysics Data System (ADS)

Ballinger, R. G.; Lucas, G. E.; Pelloux, R. M.

1984-09-01

The evolution of crystallographic texture during plastic deformation was investigated in Zircaloy-2 using X-ray and metallographic techniques. Inverse pole figures, the resolved fraction of basal poles, and the volume fraction of twinned material, were determined as a function of plastic strain for several strain paths and initial textures at 298 K and 623 K. Incremental transverse platic strain ratios ( R) were mesured as a function of plastic strain. Texture rotation occurs early in the deformation process, after as little as 1.5% plastic strain. For compressive plastic strains, the resolved fraction of basal poles increases in the direction parallel to the strain axis. For tensile plastic strains, the resolved fraction of basal poles decreases in the direction parallel to the strain axis. The rate of change of the resolved fraction of basal poles with plastic strain is a function of the initial resolved fraction of basal poles. The texture rotation can be explained by considering the operation of the principal tensile twinning systems, {101¯2}<1¯011>.

Growth of self-textured Ga3+-substituted Li7La3Zr2O12 ceramics by solid state reaction and their significant enhancement in ionic conductivity

NASA Astrophysics Data System (ADS)

Qin, Shiying; Zhu, Xiaohong; Jiang, Yue; Ling, Ming'en; Hu, Zhiwei; Zhu, Jiliang

2018-03-01

A highly self-textured Ga2O3-substituted Li7La3Zr2O12 (LLZO-Ga) solid electrolyte with a nominal composition of Li6.55Ga0.15La3Zr2O12 is obtained by a simple and low-cost solid-state reaction technique, requiring no seed crystals to achieve grain orientation. The as-prepared self-textured LLZO-Ga shows a strong (420) preferred orientation with a high Lotgering factor of 0.91. Coherently, a terrace-shaped microstructure consisting of many parallel layers, indicating a two-dimensional-like growth mode, is clearly observed in the self-textured sample. As a result, the highly self-textured garnet-type lithium-ion conducting solid electrolyte of LLZO-Ga exhibits an extremely high ionic conductivity, reaching a state-of-the-art level of 2.06 × 10-3 S cm-1 at room temperature (25 °C) and thus shedding light on an important strategy for improving the structure and ionic conductivity of solid electrolytes.

Relationships Between the Phase Transformation Kinetics, Texture Evolution, and Microstructure Development in a 304L Stainless Steel Under Biaxial Loading Conditions: Synchrotron X-ray and Electron Backscatter Diffraction Studies

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cakmak, Ercan; Choo, Hahn; Kang, Jun-Yun

2015-02-11

The relationships between the martensitic phase transformation kinetics, texture evolution, and the microstructure development in the parent austenite phase were studied for a 304L stainless steel that exhibits the transformation-induced plasticity effect under biaxial loading conditions at ambient temperature. The applied loading paths included: pure torsion, simultaneous biaxial torsion/tension, simultaneous biaxial torsion/compression, and stepwise loading of tension followed by torsion (i.e., first loading by uniaxial tension and then by pure torsion in sequence). Synchrotron X-ray and electron backscatter diffraction techniques were used to measure the evolution of the phase fractions, textures, and microstructures as a function of the applied strains.more » The influence of loading character and path on the changes in martensitic phase transformation kinetics is discussed in the context of (1) texture-transformation relationship and the preferred transformation of grains belonging to certain texture components over the others, (2) effects of axial strains on shear band evolutions, and (3) volume changes associated with martensitic transformation.« less

Bilinear magnetoelectric resistance as a probe of three-dimensional spin texture in topological surface states

NASA Astrophysics Data System (ADS)

He, Pan; Zhang, Steven S.-L.; Zhu, Dapeng; Liu, Yang; Wang, Yi; Yu, Jiawei; Vignale, Giovanni; Yang, Hyunsoo

2018-05-01

Surface states of three-dimensional topological insulators exhibit the phenomenon of spin-momentum locking, whereby the orientation of an electron spin is determined by its momentum. Probing the spin texture of these states is of critical importance for the realization of topological insulator devices, but the main technique currently available is spin- and angle-resolved photoemission spectroscopy. Here we reveal a close link between the spin texture and a new kind of magnetoresistance, which depends on the relative orientation of the current with respect to the magnetic field as well as the crystallographic axes, and scales linearly with both the applied electric and magnetic fields. This bilinear magnetoelectric resistance can be used to map the spin texture of topological surface states by simple transport measurements. For a prototypical Bi2Se3 single layer, we can map both the in-plane and out-of-plane components of the spin texture (the latter arising from hexagonal warping). Theoretical calculations suggest that the bilinear magnetoelectric resistance originates from conversion of a non-equilibrium spin current into a charge current under application of the external magnetic field.

Texture and phase analysis of deformed SUS304 by using HIPPO

DOE Office of Scientific and Technical Information (OSTI.GOV)

Takajo, Shigehiro; Vogel, Sven C.

2016-11-15

These slides represent the author's research activity at Los Alamos National Laboratory (LANL), which is about texture and phase analysis of deformed SUS304 by using HIPPO. The following topics are covered: diffraction histogram at each sample position, diffraction histogram (all bank data averaged), possiblity of ε-phase, MAUD analysis with including ε-phase.

Methodology of remote sensing data interpretation and geological applications. [Brazil

NASA Technical Reports Server (NTRS)

Parada, N. D. J. (Principal Investigator); Veneziani, P.; Dosanjos, C. E.

1982-01-01

Elements of photointerpretation discussed include the analysis of photographic texture and structure as well as film tonality. The method used is based on conventional techniques developed for interpreting aerial black and white photographs. By defining the properties which characterize the form and individuality of dual images, homologous zones can be identified. Guy's logic method (1966) was adapted and used on functions of resolution, scale, and spectral characteristics of remotely sensed products. Applications of LANDSAT imagery are discussed for regional geological mapping, mineral exploration, hydrogeology, and geotechnical engineering in Brazil.

Influence of compression parameters on mechanical behavior of mozzarella cheese.

PubMed

Fogaça, Davi Novaes Ladeia; da Silva, William Soares; Rodrigues, Luciano Brito

2017-10-01

Studies on the interaction between direction and degree of compression in the Texture Profile Analysis (TPA) of cheeses are limited. For this reason the present study aimed to evaluate the mechanical properties of Mozzarella cheese by TPA at different compression degrees (65, 75, and 85%) and directions (axes X, Y, and Z). Data obtained were compared in order to identify possible interaction between both factors. Compression direction did not affect any mechanical variable, or rather, the cheese had an isotropic behavior for TPA. Compression degree had a significant influence (p < 0.05) on TPA responses, excepting for chewiness TPA (N), which remained constant. Data from texture profile were adjusted to models to explain the mechanical behavior according to the compression degree used in the test. The isotropic behavior observed may be result of differences in production method of Mozzarella cheese especially on stretching of cheese mass. Texture Profile Analysis (TPA) is a technique largely used to assess the mechanical properties of food, particularly cheese. The precise choice of the instrumental test configuration is essential for achieving results that represent the material analyzed. The method of manufacturing is another factor that may directly influence the mechanical properties of food. This can be seen, for instance, in stretched curd cheese, such as Mozzarella. Knowledge on such mechanical properties is highly relevant for food industries due to the mechanical resistance in piling, pressing, manufacture of packages, and food transport, or to melting features presented by the food at high temperatures in preparation of several foods, such as pizzas, snacks, sandwiches, and appetizers. © 2016 Wiley Periodicals, Inc.

SU-E-I-90: Characterizing Small Animal Lung Properties Using Speckle Observed with An In-Line X-Ray Phase Contrast Benchtop System

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garson, A; Gunsten, S; Guan, H

Purpose: We demonstrate a novel X-ray phase-contrast (XPC) method for lung imaging representing a paradigm shift in the way small animal functional imaging is performed. In our method, information regarding airway microstructure that is encoded within speckle texture of a single XPC radiograph is decoded to produce 2D parametric images that will spatially resolve changes in lung properties such as microstructure sizes and air volumes. Such information cannot be derived from conventional lung radiography or any other 2D imaging modality. By computing these images at different points within a breathing cycle, dynamic functional imaging will be readily achieved without themore » need for tomography. Methods: XPC mouse lung radiographs acquired in situ with an in-line X-ray phase contrast benchtop system. The lung air volume is varied and controlled with a small animal ventilator. XPC radiographs will be acquired for various lung air volume levels representing different phases of the respiratory cycle. Similar data will be acquired of microsphere-based lung phantoms containing hollow glass spheres with known distributions of diameters. Image texture analysis is applied to the data to investigate relationships between texture characteristics and airspace/microsphere physical properties. Results: Correlations between Fourier-based texture descriptors (FBTDs) and regional lung air volume indicate that the texture features in 2D radiographs reveal information on 3D properties of the lungs. For example, we find for a 350 × 350 πm2 lung ROI a linear relationship between injected air volume and FBTD value with slope and intercept of 8.9×10{sup 5} and 7.5, respectively. Conclusion: We demonstrate specific image texture measures related to lung speckle features are correlated with physical characteristics of refracting elements (i.e. lung air spaces). Furthermore, we present results indicating the feasibility of implementing the technique with a simple imaging system design, short exposures, and low dose which provides potential for widespread use in laboratory settings for in vivo studies. This research was supported in part by NSF Award CBET1263988.« less

Modelling submerged coastal environments: Remote sensing technologies, techniques, and comparative analysis

NASA Astrophysics Data System (ADS)

Dillon, Chris

Built upon remote sensing and GIS littoral zone characterization methodologies of the past decade, a series of loosely coupled models aimed to test, compare and synthesize multi-beam SONAR (MBES), Airborne LiDAR Bathymetry (ALB), and satellite based optical data sets in the Gulf of St. Lawrence, Canada, eco-region. Bathymetry and relative intensity metrics for the MBES and ALB data sets were run through a quantitative and qualitative comparison, which included outputs from the Benthic Terrain Modeller (BTM) tool. Substrate classification based on relative intensities of respective data sets and textural indices generated using grey level co-occurrence matrices (GLCM) were investigated. A spatial modelling framework built in ArcGIS(TM) for the derivation of bathymetric data sets from optical satellite imagery was also tested for proof of concept and validation. Where possible, efficiencies and semi-automation for repeatable testing was achieved using ArcGIS(TM) ModelBuilder. The findings from this study could assist future decision makers in the field of coastal management and hydrographic studies. Keywords: Seafloor terrain characterization, Benthic Terrain Modeller (BTM), Multi-beam SONAR, Airborne LiDAR Bathymetry, Satellite Derived Bathymetry, ArcGISTM ModelBuilder, Textural analysis, Substrate classification.

Coal liquefaction process streams characterization and evaluation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Mitchell, G.; Davis, A.; Burke, F.P.

1991-12-01

This study demonstrated the use of the gold tube carbonization technique and reflectance microscopy analysis for the examination of process-derived materials from direct coal liquefaction. The carbonization technique, which was applied to coal liquefaction distillation resids, yields information on the amounts of gas plus distillate, pyridine-soluble resid, and pyridine-insoluble material formed when a coal liquid sample is heated to 450{degree}C for one hour at 5000 psi in an inert atmosphere. The pyridine-insolubles then are examined by reflectance microscopy to determine the type, amount, and optical texture of isotropic and anisotropic carbon formed upon carbonization. Further development of these analytical methodsmore » as process development tools may be justified on the basis of these results.« less

The effect of added dimensionality on perceived image value

NASA Astrophysics Data System (ADS)

Farnand, Susan

2008-01-01

Texture is an important element of the world around us. It can convey information about the object at hand. Although embossing has been used in a limited way, to enhance the appearance of greeting cards and book covers for example, texture is something that printed material traditionally lacks. Recently, techniques have been developed that allow the incorporation of texture in printed material. Prints made using such processes are similar to traditional 2D prints but have added texture such that a reproduction of an oil painting can have the texture of oil paint on canvas or a picture of a lizard can actually have the texture of lizard skin. It seems intuitive that the added dimensionality would add to the perceived quality of the image, but to what degree? To examine the question of the impact of a third dimension on the perceived quality of printed images, a survey was conducted asking participants to determine the relative worth of sets of print products. Pairs of print products were created, where one print of each pair was 2D and the other was the same image with added texture. Using these print pairs, thirty people from the Rochester Institute of Technology community were surveyed. The participants were shown seven pairs of print products and asked to rate the relative value of each pair by apportioning a specified amount of money between the two items according to their perception of what each item was worth. The results indicated that the addition of a third dimension or texture to the printed images gave a clear boost to the perceived worth of the printed products. The rating results were 50% higher for the 3D products than the 2D products, with the participants apportioning approximately 60% of each dollar to the 3D product and 40% to the 2D product. About 80% of the time participants felt that the 3D items had at least some added value over their 2D counterparts, about 15% of the time, they felt the products were essentially equivalent in value and 4% of the time they rated the 3D product as having lower value than the 2D product. The comments of the participants indicated that they were clearly impressed with the 3D technology and their ratings indicated that they were might be willing to pay more for it, meaning advertisers and package designers will be interested in using this technology in their products. As 3D printing technology emerges it will add yet another dimension to the work of print quality analysis.

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

PubMed

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

2017-06-22

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

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nawrocki, J; Chino, J; Craciunescu, O

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% thresholdmore » 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 be used complimentary to SUV metrics, especially when using gradient based segmentation.« less

Characterization of microstructure and texture across dissimilar super duplex/austenitic stainless steel weldment joint by super duplex filler metal

DOE Office of Scientific and Technical Information (OSTI.GOV)

Eghlimi, Abbas, E-mail: a.eghlimi@ma.iut.ac.ir; Shamanian, Morteza; Eskandarian, Masoomeh

In the present paper, microstructural changes across an as-welded dissimilar austenitic/duplex stainless steel couple welded by a super duplex stainless steel filler metal using gas tungsten arc welding process is characterized with optical microscopy and electron back-scattered diffraction techniques. Accordingly, variations of microstructure, texture, and grain boundary character distribution of base metals, heat affected zones, and weld metal were investigated. The results showed that the weld metal, which was composed of Widmanstätten austenite side-plates and allotriomorphic grain boundary austenite morphologies, had the weakest texture and was dominated by low angle boundaries. The welding process increased the ferrite content but decreasedmore » the texture intensity at the heat affected zone of the super duplex stainless steel base metal. In addition, through partial ferritization, it changed the morphology of elongated grains of the rolled microstructure to twinned partially transformed austenite plateaus scattered between ferrite textured colonies. However, the texture of the austenitic stainless steel heat affected zone was strengthened via encouraging recrystallization and formation of annealing twins. At both interfaces, an increase in the special character coincident site lattice boundaries of the primary phase as well as a strong texture with <100> orientation, mainly of Goss component, was observed. - Graphical abstract: Display Omitted - Highlights: • Weld metal showed local orientation at microscale but random texture at macroscale. • Intensification of <100> orientated grains was observed adjacent to the fusion lines. • The austenite texture was weaker than that of the ferrite in all duplex regions. • Welding caused twinned partially transformed austenites to form at SDSS HAZ. • At both interfaces, the ratio of special CSL boundaries of the primary phase increased.« less

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

USDA-ARS?s Scientific Manuscript database

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...

Detection of Focal Cortical Dysplasia Lesions in MRI Using Textural Features

NASA Astrophysics Data System (ADS)

Loyek, Christian; Woermann, Friedrich G.; Nattkemper, Tim W.

Focal cortical dysplasia (FCD) is a frequent cause of medically refractory partial epilepsy. The visual identification of FCD lesions on magnetic resonance images (MRI) is a challenging task in standard radiological analysis. Quantitative image analysis which tries to assist in the diagnosis of FCD lesions is an active field of research. In this work we investigate the potential of different texture features, in order to explore to what extent they are suitable for detecting lesional tissue. As a result we can show first promising results based on segmentation and texture classification.

Preference evaluation of ground beef by untrained subjects with three levels of finely textured beef

PubMed Central

Depue, Sandra Molly; Neilson, Morgan Marie

2018-01-01

After receiving bad publicity in 2012 and being removed from many ground beef products, finely textured beef (referred to as ‘pink slime’ by some) is making a comeback. Some of its proponents argue that consumers prefer ground beef containing finely textured beef, but no objective scientific party has tested this claim—that is the purpose of the present study. Over 200 untrained subjects participated in a sensory analysis in which they tasted one ground beef sample with no finely textured beef, another with 15% finely textured beef (by weight), and another with more than 15%. Beef with 15% finely textured beef has an improved juiciness (p < 0.01) and tenderness (p < 0.01) quality. However, subjects rate the flavor-liking and overall likeability the same regardless of the finely textured beef content. Moreover, when the three beef types are consumed as part of a slider (small hamburger), subjects are indifferent to the level of finely textured beef. PMID:29342174

Field-Scale Evaluation of Infiltration Parameters From Soil Texture for Hydrologic Analysis

NASA Astrophysics Data System (ADS)

Springer, Everett P.; Cundy, Terrance W.

1987-02-01

Recent interest in predicting soil hydraulic properties from simple physical properties such as texture has major implications in the parameterization of physically based models of surface runoff. This study was undertaken to (1) compare, on a field scale, soil hydraulic parameters predicted from texture to those derived from field measurements and (2) compare simulated overland flow response using these two parameter sets. The parameters for the Green-Ampt infiltration equation were obtained from field measurements and using texture-based predictors for two agricultural fields, which were mapped as single soil units. Results of the analyses were that (1) the mean and variance of the field-based parameters were not preserved by the texture-based estimates, (2) spatial and cross correlations between parameters were induced by the texture-based estimation procedures, (3) the overland flow simulations using texture-based parameters were significantly different than those from field-based parameters, and (4) simulations using field-measured hydraulic conductivities and texture-based storage parameters were very close to simulations using only field-based parameters.

Computer-aided diagnosis of liver tumors on computed tomography images.

PubMed

Chang, Chin-Chen; Chen, Hong-Hao; Chang, Yeun-Chung; Yang, Ming-Yang; Lo, Chung-Ming; Ko, Wei-Chun; Lee, Yee-Fan; Liu, Kao-Lang; Chang, Ruey-Feng

2017-07-01

Liver cancer is the tenth most common cancer in the USA, and its incidence has been increasing for several decades. Early detection, diagnosis, and treatment of the disease are very important. Computed tomography (CT) is one of the most common and robust imaging techniques for the detection of liver cancer. CT scanners can provide multiple-phase sequential scans of the whole liver. In this study, we proposed a computer-aided diagnosis (CAD) system to diagnose liver cancer using the features of tumors obtained from multiphase CT images. A total of 71 histologically-proven liver tumors including 49 benign and 22 malignant lesions were evaluated with the proposed CAD system to evaluate its performance. Tumors were identified by the user and then segmented using a region growing algorithm. After tumor segmentation, three kinds of features were obtained for each tumor, including texture, shape, and kinetic curve. The texture was quantified using 3 dimensional (3-D) texture data of the tumor based on the grey level co-occurrence matrix (GLCM). Compactness, margin, and an elliptic model were used to describe the 3-D shape of the tumor. The kinetic curve was established from each phase of tumor and represented as variations in density between each phase. Backward elimination was used to select the best combination of features, and binary logistic regression analysis was used to classify the tumors with leave-one-out cross validation. The accuracy and sensitivity for the texture were 71.82% and 68.18%, respectively, which were better than for the shape and kinetic curve under closed specificity. Combining all of the features achieved the highest accuracy (58/71, 81.69%), sensitivity (18/22, 81.82%), and specificity (40/49, 81.63%). The Az value of combining all features was 0.8713. Combining texture, shape, and kinetic curve features may be able to differentiate benign from malignant tumors in the liver using our proposed CAD system. Copyright © 2017 Elsevier B.V. All rights reserved.

A prospective study of anti-aging topical therapies using a quantitative method of assessment.

PubMed

Rubino, Corrado; Farace, Francesco; Dessy, Luca A; Sanna, Marco P G; Mazzarello, Vittorio

2005-04-01

In the treatment of photoaged skin, glycolic acid works by removing superficial portions of the epidermis and stimulating dermis regeneration. Vitamins A, C, and E should stimulate collagen production and antioxidants should prevent free radical damage and skin aging. However, the effectiveness of different therapies has often relied on subjective methods of assessment. Histologic analysis has seldom been used because of the drawback of permanent scarring. In the literature, the use of a quantitative method for the assessment of facial rejuvenation has been described: the silicone replica technique. The authors' aim was to promote and recommend the use of this technique and, in particular, to test the effect of glycolic acid and multivitamin- and antioxidant-based products on skin texture. The authors performed a prospective, randomized, double-blind, controlled study on 30 women treated topically in the outer canthal region (crow's-feet area). Patients were divided into three groups (groups A, B, and C); each group consisted of five patients between the ages of 31 and 40 years and five patients between the ages of 41 and 50 years. Group A was treated by glycolic acid application, initially at home for 2 weeks, followed by a higher concentration administered in the office weekly for six applications. Group B was treated by topical application at home of a multivitamin product daily for 3 months. Group C was treated with a cream base (placebo) for 3 months and represented the control group. Skin areas under treatment were photographed and reproduced by the silicone replica technique at baseline and at the end of treatment. This technique reproduces exactly the skin's texture. Digital images were obtained from skin replicas and analyzed by specific software for different parameters: roughness, microsulcus number, and width. Pretreatment and posttreatment values were compared using the Wilcoxon signed-rank test. In group A, microsulcus number and width were statistically decreased, but roughness was not. In groups B and C, parameters were not statistically modified. The silicone replica technique allowed a quantitative analysis of results obtained with different topical therapies. In particular, it confirmed the efficacy of glycolic acid in skin rejuvenation.

Experimental Study on the Perception Characteristics of Haptic Texture by Multidimensional Scaling.

PubMed

Wu, Juan; Li, Na; Liu, Wei; Song, Guangming; Zhang, Jun

2015-01-01

Recent works regarding real texture perception demonstrate that physical factors such as stiffness and spatial period play a fundamental role in texture perception. This research used a multidimensional scaling (MDS) analysis to further characterize and quantify the effects of the simulation parameters on haptic texture rendering and perception. In a pilot experiment, 12 haptic texture samples were generated by using a 3-degrees-of-freedom (3-DOF) force-feedback device with varying spatial period, height, and stiffness coefficient parameter values. The subjects' perceptions of the virtual textures indicate that roughness, denseness, flatness and hardness are distinguishing characteristics of texture. In the main experiment, 19 participants rated the dissimilarities of the textures and estimated the magnitudes of their characteristics. The MDS method was used to recover the underlying perceptual space and reveal the significance of the space from the recorded data. The physical parameters and their combinations have significant effects on the perceptual characteristics. A regression model was used to quantitatively analyze the parameters and their effects on the perceptual characteristics. This paper is to illustrate that haptic texture perception based on force feedback can be modeled in two- or three-dimensional space and provide suggestions on improving perception-based haptic texture rendering.

Ribbon Growth of Single Crystal GaAs for Solar Cell Application.

DTIC Science & Technology

1981-11-01

Entered) 20. Abstract (Cont.) 7growth techniques, dendrite seeds, and melt chemistry were optimized during the course of the program; however...Faceted Web. 10 Crystal Grown From a Melt Doped With 1.0 Atomic% Ge. 17 The Ge-Doped Crystals Grew at Low Undercooling and Contained Flatter Textured-Web...Ge Melt Doping. The 18 Textured-Web Sections Were the Widest Achieved at Small Undercooling, ɝ.0°C. 12 Radiation Exchange Between the Melt Surface

Scalable fabrication of strongly textured organic semiconductor micropatterns by capillary force lithography.

PubMed

Jo, Pil Sung; Vailionis, Arturas; Park, Young Min; Salleo, Alberto

2012-06-26

Strongly textured organic semiconductor micropatterns made of the small molecule dioctylbenzothienobenzothiophene (C(8)-BTBT) are fabricated by using a method based on capillary force lithography (CFL). This technique provides the C(8)-BTBT solution with nucleation sites for directional growth, and can be used as a scalable way to produce high quality crystalline arrays in desired regions of a substrate for OFET applications. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Comparison between different techniques applied to quartz CPO determination in granitoid mylonites

NASA Astrophysics Data System (ADS)

Fazio, Eugenio; Punturo, Rosalda; Cirrincione, Rosolino; Kern, Hartmut; Wenk, Hans-Rudolph; Pezzino, Antonino; Goswami, Shalini; Mamtani, Manish

2016-04-01

Since the second half of the last century, several techniques have been adopted to resolve the crystallographic preferred orientation (CPO) of major minerals constituting crustal and mantle rocks. To this aim, many efforts have been made to increase the accuracy of such analytical devices as well as to progressively reduce the time needed to perform microstructural analysis. It is worth noting that many of these microstructural studies deal with quartz CPO because of the wide occurrence of this mineral phase in crustal rocks as well as its quite simple chemical composition. In the present work, four different techniques were applied to define CPOs of dynamically recrystallized quartz domains from naturally deformed rocks collected from a ductile crustal scale shear zone in order to compare their advantages and limitation. The selected Alpine shear zone is located in the Aspromonte Massif (Calabrian Peloritani Orogen, southern Italy) representing granitoid lithotypes. The adopted methods span from "classical" universal stage (US), to image analysis technique (CIP), electron back-scattered diffraction (EBSD), and time of flight neutron diffraction (TOF). When compared, bulk texture pole figures obtained by means of these different techniques show a good correlation. Advances in analytical techniques used for microstructural investigations are outlined by discussing results of quartz CPO that are presented in this study.

Textured digital elevation model formation from low-cost UAV LADAR/digital image data

NASA Astrophysics Data System (ADS)

Bybee, Taylor C.; Budge, Scott E.

2015-05-01

Textured digital elevation models (TDEMs) have valuable use in precision agriculture, situational awareness, and disaster response. However, scientific-quality models are expensive to obtain using conventional aircraft-based methods. The cost of creating an accurate textured terrain model can be reduced by using a low-cost (<$20k) UAV system fitted with ladar and electro-optical (EO) sensors. A texel camera fuses calibrated ladar and EO data upon simultaneous capture, creating a texel image. This eliminates the problem of fusing the data in a post-processing step and enables both 2D- and 3D-image registration techniques to be used. This paper describes formation of TDEMs using simulated data from a small UAV gathering swaths of texel images of the terrain below. Being a low-cost UAV, only a coarse knowledge of position and attitude is known, and thus both 2D- and 3D-image registration techniques must be used to register adjacent swaths of texel imagery to create a TDEM. The process of creating an aggregate texel image (a TDEM) from many smaller texel image swaths is described. The algorithm is seeded with the rough estimate of position and attitude of each capture. Details such as the required amount of texel image overlap, registration models, simulated flight patterns (level and turbulent), and texture image formation are presented. In addition, examples of such TDEMs are shown and analyzed for accuracy.

Rapid extraction of image texture by co-occurrence using a hybrid data structure

NASA Astrophysics Data System (ADS)

Clausi, David A.; Zhao, Yongping

2002-07-01

Calculation of co-occurrence probabilities is a popular method for determining texture features within remotely sensed digital imagery. Typically, the co-occurrence features are calculated by using a grey level co-occurrence matrix (GLCM) to store the co-occurring probabilities. Statistics are applied to the probabilities in the GLCM to generate the texture features. This method is computationally intensive since the matrix is usually sparse leading to many unnecessary calculations involving zero probabilities when applying the statistics. An improvement on the GLCM method is to utilize a grey level co-occurrence linked list (GLCLL) to store only the non-zero co-occurring probabilities. The GLCLL suffers since, to achieve preferred computational speeds, the list should be sorted. An improvement on the GLCLL is to utilize a grey level co-occurrence hybrid structure (GLCHS) based on an integrated hash table and linked list approach. Texture features obtained using this technique are identical to those obtained using the GLCM and GLCLL. The GLCHS method is implemented using the C language in a Unix environment. Based on a Brodatz test image, the GLCHS method is demonstrated to be a superior technique when compared across various window sizes and grey level quantizations. The GLCHS method required, on average, 33.4% ( σ=3.08%) of the computational time required by the GLCLL. Significant computational gains are made using the GLCHS method.

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

PubMed

Valdés Hernández, Maria Del C; González-Castro, Victor; Chappell, Francesca M; Sakka, Eleni; Makin, Stephen; Armitage, Paul A; Nailon, William H; Wardlaw, Joanna M

2017-01-01

We evaluate the alternative use of texture analysis for evaluating the role of blood-brain barrier (BBB) in small vessel disease (SVD). We 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. Textural "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. A 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.

Texture of cellulose microfibrils of root hair cell walls of Arabidopsis thaliana, Medicago truncatula, and Vicia sativa.

PubMed

Akkerman, M; Franssen-Verheijen, M A W; Immerzeel, P; Hollander, L D E N; Schel, J H N; Emons, A M C

2012-07-01

Cellulose is the most abundant biopolymer on earth, and has qualities that make it suitable for biofuel. There are new tools for the visualisation of the cellulose synthase complexes in living cells, but those do not show their product, the cellulose microfibrils (CMFs). In this study we report the characteristics of cell wall textures, i.e. the architectures of the CMFs in the wall, of root hairs of Arabidopsis thaliana, Medicago truncatula and Vicia sativa and compare the different techniques we used to study them. Root hairs of these species have a random primary cell wall deposited at the root hair tip, which covers the outside of the growing and fully grown hair. The secondary wall starts between 10 (Arabidopsis) and 40 (Vicia) μm from the hair tip and the CMFs make a small angle, Z as well as S direction, with the long axis of the root hair. CMFs are 3-4 nm wide in thin sections, indicating that single cellulose synthase complexes make them. Thin sections after extraction of cell wall matrix, leaving only the CMFs, reveal the type of wall texture and the orientation and width of CMFs, but CMF density within a lamella cannot be quantified, and CMF length is always underestimated by this technique. Field emission scanning electron microscopy and surface preparations for transmission electron microscopy reveal the type of wall texture and the orientation of individual CMFs. Only when the orientation of CMFs in subsequent deposited lamellae is different, their density per lamella can be determined. It is impossible to measure CMF length with any of the EM techniques. © 2012 The Authors Journal of Microscopy © 2012 Royal Microscopical Society.

Effects of high temperature and film thicknesses on the texture evolution in Ag thin films

NASA Astrophysics Data System (ADS)

Eshaghi, F.; Zolanvari, A.

2017-04-01

In situ high-temperature X-ray diffraction techniques were used to study the effect of high temperatures (up to 600°C) on the texture evolution in silver thin films. Ag thin films with different thicknesses of 40, 80, 120 and 160nm were sputtered on the Si(100) substrates at room temperature. Then, microstructure of thin films was determined using X-ray diffraction. To investigate the influence of temperature on the texture development in the Ag thin films with different thicknesses, (111), (200) and (220) pole figures were evaluated and orientation distribution functions were calculated. Minimizing the total energy of the system which is affected by competition between surface and elastic strain energy was a key factor in the as-deposited and post annealed thin films. Since sputtering depositions was performed at room temperature and at the same thermodynamic conditions, the competition growth caused the formation of the {122} < uvw \\rangle weak fiber texture in as-deposited Ag thin films. It was significantly observed that the post annealed Ag thin films showed {111} < uvw \\rangle orientations as their preferred orientations, but their preferred fiber texture varied with the thickness of thin films. Increasing thin film thickness from 40nm to 160nm led to decreasing the intensity of the {111} < uvw \\rangle fiber texture.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, B; Yu, H; Jara, H

Purpose: To compare enhanced Laws texture derived from parametric proton density (PD) maps to other MRI-based surrogate markers (T2, PD, ADC) in assessing degrees of liver fibrosis in a murine model of hepatic fibrosis using 11.7T scanner. Methods: This animal study was IACUC approved. Fourteen mice were divided into control (n=1) and experimental (n=13). The latter were fed a DDC-supplemented diet to induce hepatic fibrosis. Liver specimens were imaged using an 11.7T scanner; the parametric PD, T2, and ADC maps were generated from spin-echo pulsed field gradient and multi-echo spin-echo acquisitions. Enhanced Laws texture analysis was applied to the PDmore » maps: first, hepatic blood vessels and liver margins were segmented/removed using an automated dual-clustering algorithm; secondly, an optimal thresholding algorithm was applied to reduce the partial volume artifact; next, mean and stdev were corrected to minimize grayscale variation across images; finally, Laws texture was extracted. Degrees of fibrosis was assessed by an experienced pathologist and digital image analysis (%Area Fibrosis). Scatterplots comparing enhanced Laws texture, T2, PD, and ADC values to degrees of fibrosis were generated and correlation coefficients were calculated. Unenhanced Laws texture was also compared to assess the effectiveness of the proposed enhancements. Results: Hepatic fibrosis and the enhanced Laws texture were strongly correlated with higher %Area Fibrosis associated with higher Laws texture (r=0.89). Only a moderate correlation was detected between %Area Fibrosis and unenhanced Laws texture (r=0.70). Strong correlation also existed between ADC and %Area Fibrosis (r=0.86). Moderate correlations were seen between %Area Fibrosis and PD (r=0.65) and T2 (r=0.66). Conclusions: Higher degrees of hepatic fibrosis are associated with increased Laws texture. The proposed enhancements improve the accuracy of Laws texture. Enhanced Laws texture features are more accurate than PD and T2 in assessing fibrosis, and can potentially serve as an accurate surrogate marker for hepatic fibrosis.« less

Genome-wide association study unravels the genetic control of the apple volatilome and its interplay with fruit texture.

PubMed

Farneti, Brian; Di Guardo, Mario; Khomenko, Iuliia; Cappellin, Luca; Biasioli, Franco; Velasco, Riccardo; Costa, Fabrizio

2017-03-01

Fruit quality represents a fundamental factor guiding consumers' preferences. Among apple quality traits, volatile organic compounds and texture features play a major role. Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS), coupled with an artificial chewing device, was used to profile the entire apple volatilome of 162 apple accessions, while the fruit texture was dissected with a TAXT-AED texture analyzer. The array of volatile compounds was classed into seven major groups and used in a genome-wide association analysis carried out with 9142 single nucleotide polymorphisms (SNPs). Marker-trait associations were identified on seven chromosomes co-locating with important candidate genes for aroma, such as MdAAT1 and MdIGS. The integration of volatilome and fruit texture data conducted with a multiple factor analysis unraveled contrasting behavior, underlying opposite regulation of the two fruit quality aspects. The association analysis using the first two principal components identified two QTLs located on chromosomes 10 and 2, respectively. The distinction of the apple accessions on the basis of the allelic configuration of two functional markers, MdPG1 and MdACO1, shed light on the type of interplay existing between fruit texture and the production of volatile organic compounds. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Extracting Information about the Rotator Cuff from Magnetic Resonance Images Using Deterministic and Random Techniques

PubMed Central

De Los Ríos, F. A.; Paluszny, M.

2015-01-01

We consider some methods to extract information about the rotator cuff based on magnetic resonance images; the study aims to define an alternative method of display that might facilitate the detection of partial tears in the supraspinatus tendon. Specifically, we are going to use families of ellipsoidal triangular patches to cover the humerus head near the affected area. These patches are going to be textured and displayed with the information of the magnetic resonance images using the trilinear interpolation technique. For the generation of points to texture each patch, we propose a new method that guarantees the uniform distribution of its points using a random statistical method. Its computational cost, defined as the average computing time to generate a fixed number of points, is significantly lower as compared with deterministic and other standard statistical techniques. PMID:25650281

Microstructural and micromechanical characterization of IN718 theta shaped specimens built with electron beam melting

DOE PAGES

Cakmak, Ercan; Kirka, Michael M.; Watkins, Thomas R.; ...

2016-02-23

Theta-shaped specimens were additively manufactured out of Inconel 718 powders using an electron beam melting technique, as a model complex load bearing structure. We employed two different build strategies; producing two sets of specimens. Microstructural and micro-mechanical characterizations were performed using electron back-scatter, synchrotron x-ray and in-situ neutron diffraction techniques. In particular, the cross-members of the specimens were the focus of the synchrotron x-ray and in-situ neutron diffraction measurements. The build strategies employed resulted in the formation of distinct microstructures and crystallographic textures, signifying the importance of build-parameter manipulation for microstructural optimization. Large strain anisotropy of the different lattice planesmore » was observed during in-situ loading. Texture was concluded to have a distinct effect upon both the axial and transverse strain responses of the cross-members. In particular, the (200), (220) and (420) transverse lattice strains all showed unexpected overlapping trends in both builds. This was related to the strong {200} textures along the build/loading direction, providing agreement between the experimental and calculated results.« less

Autonomous selection of PDE inpainting techniques vs. exemplar inpainting techniques for void fill of high resolution digital surface models

NASA Astrophysics Data System (ADS)

Rahmes, Mark; Yates, J. Harlan; Allen, Josef DeVaughn; Kelley, Patrick

2007-04-01

High resolution Digital Surface Models (DSMs) may contain voids (missing data) due to the data collection process used to obtain the DSM, inclement weather conditions, low returns, system errors/malfunctions for various collection platforms, and other factors. DSM voids are also created during bare earth processing where culture and vegetation features have been extracted. The Harris LiteSite TM Toolkit handles these void regions in DSMs via two novel techniques. We use both partial differential equations (PDEs) and exemplar based inpainting techniques to accurately fill voids. The PDE technique has its origin in fluid dynamics and heat equations (a particular subset of partial differential equations). The exemplar technique has its origin in texture analysis and image processing. Each technique is optimally suited for different input conditions. The PDE technique works better where the area to be void filled does not have disproportionately high frequency data in the neighborhood of the boundary of the void. Conversely, the exemplar based technique is better suited for high frequency areas. Both are autonomous with respect to detecting and repairing void regions. We describe a cohesive autonomous solution that dynamically selects the best technique as each void is being repaired.

Image segmentation using association rule features.

PubMed

Rushing, John A; Ranganath, Heggere; Hinke, Thomas H; Graves, Sara J

2002-01-01

A new type of texture feature based on association rules is described. Association rules have been used in applications such as market basket analysis to capture relationships present among items in large data sets. It is shown that association rules can be adapted to capture frequently occurring local structures in images. The frequency of occurrence of these structures can be used to characterize texture. Methods for segmentation of textured images based on association rule features are described. Simulation results using images consisting of man made and natural textures show that association rule features perform well compared to other widely used texture features. Association rule features are used to detect cumulus cloud fields in GOES satellite images and are found to achieve higher accuracy than other statistical texture features for this problem.

The Effects of Bolus Volume and Texture on Pharyngeal Pressure Events Using High-resolution Manometry and Its Comparison with Videofluoroscopic Swallowing Study

PubMed Central

Ryu, Ju Seok; Park, Donghwi; Oh, Yoongul; Lee, Seok Tae; Kang, Jin Young

2016-01-01

Background/Aims The purpose of this study was to develop new parameters of high-resolution manometry (HRM) and to applicate these to quantify the effect of bolus volume and texture on pharyngeal swallowing. Methods Ten healthy subjects prospectively swallowed dry, thin fluid 2 mL, thin fluid 5 mL, thin fluid 10 mL, and drinking twice to compare effects of bolus volume. To compare effect of texture, subjects swallowed thin fluid 5 mL, yogurt 5 mL, and bread twice. A 32-sensor HRM catheter and BioVIEW ANALYSIS software were used for data collection and analysis. HRM data were synchronized with kinematic analysis of videofluoroscopic swallowing study (VFSS) using epiglottis tilting. Results Linear correlation analysis for volume showed significant correlation for area of velopharynx, duration of velopharynx, pre-upper esophageal sphincter (UES) maximal pressure, minimal UES pressure, UES activity time, and nadir UES duration. In the correlation with texture, all parameters were not significantly different. The contraction of the velopharynx was faster than laryngeal elevation. The durations of UES relaxation was shorter in the kinematic analysis than HRM. Conclusions The bolus volume was shown to have significant effect on pharyngeal pressure and timing, but the texture did not show any effect on pharyngeal swallowing. The parameters of HRM were more sensitive than those of kinematic analysis. As the parameters of HRM are based on precise anatomic structure and the kinematic analysis reflects the actions of multiple anatomic structures, HRM and VFSS should be used according to their purposes. PMID:26598598

Mobile robots traversability awareness based on terrain visual sensory data fusion

NASA Astrophysics Data System (ADS)

Shirkhodaie, Amir

2007-04-01

In this paper, we have presented methods that significantly improve the robot awareness of its terrain traversability conditions. The terrain traversability awareness is achieved by association of terrain image appearances from different poses and fusion of extracted information from multimodality imaging and range sensor data for localization and clustering environment landmarks. Initially, we describe methods for extraction of salient features of the terrain for the purpose of landmarks registration from two or more images taken from different via points along the trajectory path of the robot. The method of image registration is applied as a means of overlaying (two or more) of the same terrain scene at different viewpoints. The registration geometrically aligns salient landmarks of two images (the reference and sensed images). A Similarity matching techniques is proposed for matching the terrain salient landmarks. Secondly, we present three terrain classifier models based on rule-based, supervised neural network, and fuzzy logic for classification of terrain condition under uncertainty and mapping the robot's terrain perception to apt traversability measures. This paper addresses the technical challenges and navigational skill requirements of mobile robots for traversability path planning in natural terrain environments similar to Mars surface terrains. We have described different methods for detection of salient terrain features based on imaging texture analysis techniques. We have also presented three competing techniques for terrain traversability assessment of mobile robots navigating in unstructured natural terrain environments. These three techniques include: a rule-based terrain classifier, a neural network-based terrain classifier, and a fuzzy-logic terrain classifier. Each proposed terrain classifier divides a region of natural terrain into finite sub-terrain regions and classifies terrain condition exclusively within each sub-terrain region based on terrain spatial and textural cues.

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

PubMed Central

Wang, Kun-Ching

2015-01-01

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. PMID:25594590

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

PubMed

Hu, Leland S; Ning, Shuluo; Eschbacher, Jennifer M; Gaw, Nathan; Dueck, Amylou C; Smith, Kris A; Nakaji, Peter; Plasencia, Jonathan; Ranjbar, Sara; Price, Stephen J; Tran, Nhan; Loftus, Joseph; Jenkins, Robert; O'Neill, Brian P; Elmquist, William; Baxter, Leslie C; Gao, Fei; Frakes, David; Karis, John P; Zwart, Christine; Swanson, Kristin R; Sarkaria, Jann; Wu, Teresa; Mitchell, J Ross; Li, Jing

2015-01-01

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.

The application of tribology in assessing texture perception of oral liquid medicines.

PubMed

Batchelor, Hannah; Venables, Rebecca; Marriott, John; Mills, Tom

2015-02-20

The palatability of medicines is likely to have a significant impact on patient adherence and consequently, on the safety and efficacy of a medicinal product. Palatability encompasses properties of medicines not limited to taste including swallowability (e.g. size, shape, texture). However, there has been limited work undertaken to measure the texture of medicines and how this may affect palatability and subsequent adherence. Tribology offers an understanding of oral processes and can allow physical properties of materials to be linked to "mouthfeel". This paper describes a preliminary application of tribology to oral liquid medicines and demonstrates that this technique is useful in the development of future oral liquid medicines. Copyright © 2015 Elsevier B.V. All rights reserved.

Potential Performance Criteria for Combat Ration Packs - Texture Profile Analysis

DTIC Science & Technology

2014-11-01

12 3.3.1 Apricot & coconut muesli bar...Figure 5 Texture vs aw of canned puddings stored at 30 °C for up to 730 days. 3.3 Muesli Bar The three muesli bars (apricot and coconut , tropical...Apricot & coconut muesli bar No significant changes were observed during storage for texture attributes, except at 40 °C for break strength and

Origin of texture development in orthorhombic uranium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zecevic, Miroslav; Knezevic, Marko; Beyerlein, Irene Jane

We study texture evolution of alpha-uranium (α-U) during plane strain compression and uniaxial compression to high strains at different temperatures. We combine a multiscale polycrystal constitutive model and detailed analysis of texture data to uncover the slip and twinning modes responsible for the formation of individual texture components. The analysis indicates that during plane strain compression, floor slip (001)[100] results in the formation of two pronounced {001}{001} texture peaks tilted 10–15° away from the normal toward the rolling direction. During both high-temperature (573 K) through-thickness compression and plane strain compression, the active slip modes are floor slip (001)[100] and chimneymore » slip 1/2{110} <11¯0> with slightly different ratios. {130} <31¯0> deformation twinning is profuse during rolling and in-plane compression and decreases with increasing temperature, but is not as active for through-thickness compression. Lastly, we comment on some similarities between rolling textures of α-U, which has a c/a ratio of 1.734, and those that develop in hexagonal close packed metals with similarly high c/a ratios like Zn (1.856) and Cd (1.885) and are dominated by basal slip.« less

Origin of texture development in orthorhombic uranium

DOE PAGES

Zecevic, Miroslav; Knezevic, Marko; Beyerlein, Irene Jane; ...

2016-04-09

We study texture evolution of alpha-uranium (α-U) during plane strain compression and uniaxial compression to high strains at different temperatures. We combine a multiscale polycrystal constitutive model and detailed analysis of texture data to uncover the slip and twinning modes responsible for the formation of individual texture components. The analysis indicates that during plane strain compression, floor slip (001)[100] results in the formation of two pronounced {001}{001} texture peaks tilted 10–15° away from the normal toward the rolling direction. During both high-temperature (573 K) through-thickness compression and plane strain compression, the active slip modes are floor slip (001)[100] and chimneymore » slip 1/2{110} <11¯0> with slightly different ratios. {130} <31¯0> deformation twinning is profuse during rolling and in-plane compression and decreases with increasing temperature, but is not as active for through-thickness compression. Lastly, we comment on some similarities between rolling textures of α-U, which has a c/a ratio of 1.734, and those that develop in hexagonal close packed metals with similarly high c/a ratios like Zn (1.856) and Cd (1.885) and are dominated by basal slip.« less

Multi-Scale Fractal Analysis of Image Texture and Pattern

NASA Technical Reports Server (NTRS)

Emerson, Charles W.

1998-01-01

Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely independent of scale. Self-similarity is defined as a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. An ideal fractal (or monofractal) curve or surface has a constant dimension over all scales, although it may not be an integer value. This is in contrast to Euclidean or topological dimensions, where discrete one, two, and three dimensions describe curves, planes, and volumes. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution. However, most geographical phenomena are not strictly self-similar at all scales, but they can often be modeled by a stochastic fractal in which the scaling and self-similarity properties of the fractal have inexact patterns that can be described by statistics. Stochastic fractal sets relax the monofractal self-similarity assumption and measure many scales and resolutions in order to represent the varying form of a phenomenon as a function of local variables across space. In image interpretation, pattern is defined as the overall spatial form of related features, and the repetition of certain forms is a characteristic pattern found in many cultural objects and some natural features. Texture is the visual impression of coarseness or smoothness caused by the variability or uniformity of image tone or color. A potential use of fractals concerns the analysis of image texture. In these situations it is commonly observed that the degree of roughness or inexactness in an image or surface is a function of scale and not of experimental technique. The fractal dimension of remote sensing data could yield quantitative insight on the spatial complexity and information content contained within these data. A software package known as the Image Characterization and Modeling System (ICAMS) was used to explore how fractal dimension is related to surface texture and pattern. The ICAMS software was verified using simulated images of ideal fractal surfaces with specified dimensions. The fractal dimension for areas of homogeneous land cover in the vicinity of Huntsville, Alabama was measured to investigate the relationship between texture and resolution for different land covers.

Document reconstruction by layout analysis of snippets

NASA Astrophysics Data System (ADS)

Kleber, Florian; Diem, Markus; Sablatnig, Robert

2010-02-01

Document analysis is done to analyze entire forms (e.g. intelligent form analysis, table detection) or to describe the layout/structure of a document. Also skew detection of scanned documents is performed to support OCR algorithms that are sensitive to skew. In this paper document analysis is applied to snippets of torn documents to calculate features for the reconstruction. Documents can either be destroyed by the intention to make the printed content unavailable (e.g. tax fraud investigation, business crime) or due to time induced degeneration of ancient documents (e.g. bad storage conditions). Current reconstruction methods for manually torn documents deal with the shape, inpainting and texture synthesis techniques. In this paper the possibility of document analysis techniques of snippets to support the matching algorithm by considering additional features are shown. This implies a rotational analysis, a color analysis and a line detection. As a future work it is planned to extend the feature set with the paper type (blank, checked, lined), the type of the writing (handwritten vs. machine printed) and the text layout of a snippet (text size, line spacing). Preliminary results show that these pre-processing steps can be performed reliably on a real dataset consisting of 690 snippets.

Fractal lacunarity of trabecular bone and magnetic resonance imaging: New perspectives for osteoporotic fracture risk assessment

PubMed Central

Zaia, Annamaria

2015-01-01

Osteoporosis represents one major health condition for our growing elderly population. It accounts for severe morbidity and increased mortality in postmenopausal women and it is becoming an emerging health concern even in aging men. Screening of the population at risk for bone degeneration and treatment assessment of osteoporotic patients to prevent bone fragility fractures represent useful tools to improve quality of life in the elderly and to lighten the related socio-economic impact. Bone mineral density (BMD) estimate by means of dual-energy X-ray absorptiometry is normally used in clinical practice for osteoporosis diagnosis. Nevertheless, BMD alone does not represent a good predictor of fracture risk. From a clinical point of view, bone microarchitecture seems to be an intriguing aspect to characterize bone alteration patterns in aging and pathology. The widening into clinical practice of medical imaging techniques and the impressive advances in information technologies together with enhanced capacity of power calculation have promoted proliferation of new methods to assess changes of trabecular bone architecture (TBA) during aging and osteoporosis. Magnetic resonance imaging (MRI) has recently arisen as a useful tool to measure bone structure in vivo. In particular, high-resolution MRI techniques have introduced new perspectives for TBA characterization by non-invasive non-ionizing methods. However, texture analysis methods have not found favor with clinicians as they produce quite a few parameters whose interpretation is difficult. The introduction in biomedical field of paradigms, such as theory of complexity, chaos, and fractals, suggests new approaches and provides innovative tools to develop computerized methods that, by producing a limited number of parameters sensitive to pathology onset and progression, would speed up their application into clinical practice. Complexity of living beings and fractality of several physio-anatomic structures suggest fractal analysis as a promising approach to quantify morpho-functional changes in both aging and pathology. In this particular context, fractal lacunarity seems to be the proper tool to characterize TBA texture as it is able to describe both discontinuity of bone network and sizes of bone marrow spaces, whose changes are an index of bone fracture risk. In this paper, an original method of MRI texture analysis, based on TBA fractal lacunarity is described and discussed in the light of new perspectives for early diagnosis of osteoporotic fractures. PMID:25793162

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nawrocki, J; Chino, J; Das, S

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. Eachmore » 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 features showed significant changes during treatment independent of reconstruction effects.« less

Homomorphic filtering textural analysis technique to reduce multiplicative noise in the 11Oba nano-doped liquid crystalline compounds

NASA Astrophysics Data System (ADS)

Madhav, B. T. P.; Pardhasaradhi, P.; Manepalli, R. K. N. R.; Pisipati, V. G. K. M.

2015-07-01

The compound undecyloxy benzoic acid (11Oba) exhibits nematic and smectic-C phases while a nano-doped undecyloxy benzoic acid with ZnO exhibits the same nematic and smectic-C phases with reduced clearing temperature as expected. The doping is done with 0.5% and 1% ZnO molecules. The clearing temperatures are reduced by approximately 4 ° and 6 °, respectively (differential scanning calorimeter data). While collecting the images from a polarizing microscope connected with hot stage and camera, the illumination and reflectance combined multiplicatively and the image quality was reduced to identify the exact phase in the compound. A novel technique of homomorphic filtering is used in this manuscript through which multiplicative noise components of the image are separated linearly in the frequency domain. This technique provides a frequency domain procedure to improve the appearance of an image by gray level range compression and contrast enhancement.

Computer-aided assessment of pulmonary disease in novel swine-origin H1N1 influenza on CT

NASA Astrophysics Data System (ADS)

Yao, Jianhua; Dwyer, Andrew J.; Summers, Ronald M.; Mollura, Daniel J.

2011-03-01

The 2009 pandemic is a global outbreak of novel H1N1 influenza. Radiologic images can be used to assess the presence and severity of pulmonary infection. We develop a computer-aided assessment system to analyze the CT images from Swine-Origin Influenza A virus (S-OIV) novel H1N1 cases. The technique is based on the analysis of lung texture patterns and classification using a support vector machine (SVM). Pixel-wise tissue classification is computed from the SVM value. The method was validated on four H1N1 cases and ten normal cases. We demonstrated that the technique can detect regions of pulmonary abnormality in novel H1N1 patients and differentiate these regions from visually normal lung (area under the ROC curve is 0.993). This technique can also be applied to differentiate regions infected by different pulmonary diseases.

Microstructure, texture evolution and magnetic properties of strip-casting non-oriented 6.5 wt.% Si electrical steel doped with cerium

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Hao-Ze, E-mail: lhzqq83@163.com; Liu, Hai-Tao; Liu, Zhen-Yu, E-mail: zyliu@mail.neu.edu.cn

A 0.3 mm thick non-oriented 6.5 wt.% Si electrical steel sheet doped with cerium is produced by twin-roll strip casting, hot rolling, warm rolling and annealing. A detailed study of the cerium precipitates in the as-cast strip, microstructure and texture evolution at different processing stages is carried out by electron probe micro-analysis, optical microscopy, X-ray diffraction and electron backscattered diffraction analysis. Grain interior distributing precipitates identified as Ce-oxides, Ce-oxysulfides and Ce-phosphides, and boundary distributing Ce-oxides and Ce-phosphides are observed in the as-cast strip. The initial as-cast strip is characterized by a much finer solidification microstructure and dominated by obvious //ND texture through the strip thickness. After hot and warm rolling, inhomogeneous microstructure containing large amounts of in-grain shear bands is characterized by mixed < 110 >//RD and < 111 >//ND textures. The texture of the annealed sheet with a relatively large average grain size is far more optimized by the domination of the beneficial cube, rotated cube, (001)< 120 > to (001)< 130 > and Goss texture components, and the elimination of the detrimental γ-fiber texture, leading to a superior magnetic induction and improved iron loss. - Highlights: • An Fe–6.5 wt.% Si as-cast strip doped with cerium was produced. • A thin warm rolled sheet with limited edge cracks was obtained. • Microstructure and texture evolution at each stage were investigated. • Strong λ-fiber and Goss recrystallization textures were formed. • The magnetic properties of the annealed sheet were significantly improved.« less

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

Diet of upper paleolithic modern humans: evidence from microwear texture analysis.

PubMed

El Zaatari, Sireen; Hublin, Jean-Jacques

2014-04-01

This article presents the results of the occlusal molar microwear texture analysis of 32 adult Upper Paleolithic modern humans from a total of 21 European sites dating to marine isotope stages 3 and 2. The occlusal molar microwear textures of these specimens were analyzed with the aim of examining the effects of the climatic, as well as the cultural, changes on the diets of the Upper Paleolithic modern humans. The results of this analysis do not reveal any environmentally driven dietary shifts for the Upper Paleolithic hominins indicating that the climatic and their associated paleoecological changes did not force these humans to significantly alter their diets in order to survive. However, the microwear texture analysis does detect culturally related changes in the Upper Paleolithic humans' diets. Specifically, significant differences in diet were found between the earlier Upper Paleolithic individuals, i.e., those belonging to the Aurignacian and Gravettian contexts, and the later Magdalenian ones, such that the diet of the latter group was more varied and included more abrasive foods compared with those of the former. Copyright © 2014 Wiley Periodicals, Inc.

3D Texture Analysis in Renal Cell Carcinoma Tissue Image Grading

PubMed Central

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

Quantitative three-dimensional microtextural analyses of tooth wear as a tool for dietary discrimination in fishes

PubMed Central

Purnell, Mark; Seehausen, Ole; Galis, Frietson

2012-01-01

Resource polymorphisms and competition for resources are significant factors in speciation. Many examples come from fishes, and cichlids are of particular importance because of their role as model organisms at the interface of ecology, development, genetics and evolution. However, analysis of trophic resource use in fishes can be difficult and time-consuming, and for fossil fish species it is particularly problematic. Here, we present evidence from cichlids that analysis of tooth microwear based on high-resolution (sub-micrometre scale) three-dimensional data and new ISO standards for quantification of surface textures provides a powerful tool for dietary discrimination and investigation of trophic resource exploitation. Our results suggest that three-dimensional approaches to analysis offer significant advantages over two-dimensional operator-scored methods of microwear analysis, including applicability to rough tooth surfaces that lack distinct scratches and pits. Tooth microwear textures develop over a longer period of time than is represented by stomach contents, and analyses based on textures are less prone to biases introduced by opportunistic feeding. They are more sensitive to subtle dietary differences than isotopic analysis. Quantitative textural analysis of tooth microwear has a useful role to play, complementing existing approaches, in trophic analysis of fishes—both extant and extinct. PMID:22491979

Entropy-Based Adaptive Nuclear Texture Features are Independent Prognostic Markers in a Total Population of Uterine Sarcomas

PubMed Central

Nielsen, Birgitte; Hveem, Tarjei Sveinsgjerd; Kildal, Wanja; Abeler, Vera M; Kristensen, Gunnar B; Albregtsen, Fritz; Danielsen, Håvard E; Rohde, Gustavo K

2015-01-01

Nuclear texture analysis measures the spatial arrangement of the pixel gray levels in a digitized microscopic nuclear image and is a promising quantitative tool for prognosis of cancer. The aim of this study was to evaluate the prognostic value of entropy-based adaptive nuclear texture features in a total population of 354 uterine sarcomas. Isolated nuclei (monolayers) were prepared from 50 µm tissue sections and stained with Feulgen-Schiff. Local gray level entropy was measured within small windows of each nuclear image and stored in gray level entropy matrices, and two superior adaptive texture features were calculated from each matrix. The 5-year crude survival was significantly higher (P < 0.001) for patients with high texture feature values (72%) than for patients with low feature values (36%). When combining DNA ploidy classification (diploid/nondiploid) and texture (high/low feature value), the patients could be stratified into three risk groups with 5-year crude survival of 77, 57, and 34% (Hazard Ratios (HR) of 1, 2.3, and 4.1, P < 0.001). Entropy-based adaptive nuclear texture was an independent prognostic marker for crude survival in multivariate analysis including relevant clinicopathological features (HR = 2.1, P = 0.001), and should therefore be considered as a potential prognostic marker in uterine sarcomas. © The Authors. Published 2014 International Society for Advancement of Cytometry PMID:25483227

Surface scaling analysis of textured MgO thin films fabricated by energetic particle self-assisted deposition

NASA Astrophysics Data System (ADS)

Feng, Feng; Zhang, Xiangsong; Qu, Timing; Liu, Binbin; Huang, Junlong; Li, Jun; Xiao, Shaozhu; Han, Zhenghe; Feng, Pingfa

2018-04-01

In the fabrication of a high-temperature superconducting coated conductor, the surface roughness and texture of buffer layers can significantly affect the epitaxially grown superconductor layer. A biaxially textured MgO buffer layer fabricated by ion beam assisted deposition (IBAD) is widely used in the coated conductor manufacture due to its low thickness requirement. In our previous study, a new method called energetic particle self-assisted deposition (EPSAD), which employed only a sputtering deposition apparatus without an ion source, was proposed for fabricating biaxially textured MgO films on non-textured substrates. In this study, our aim was to investigate the deposition mechanism of EPSAD-MgO thin films. The behavior of the surface roughness (evaluated by Rq) was studied using atomic force microscopy (AFM) measurements with three scan scales, while the in-plane and out-of-plane textures were measured using X-ray diffraction (XRD). It was found that the variations of surface roughness and textures along with the increase in the thickness of EPSAD-MgO samples were very similar to those of IBAD-MgO reported in the literature, revealing the similarity of their deposition mechanisms. Moreover, fractal geometry was utilized to conduct the scaling analysis of EPSAD-MgO film's surface. Different scaling behaviors were found in two scale ranges, and the indications of the fractal properties in different scale ranges were discussed.

Transition from Round to Shaped Implants in Immediate Breast Reconstruction: Our Preferred Approach and Clinical Outcomes.

PubMed

Imahiyerobo, Thomas A; Small, Kevin H; Sackeyfio, Robyn; Hoffman, Hannah; Talmor, Mia

2017-04-01

Smooth, round, silicone implants predominate device-based breast reconstruction in the USA; despite their prevalence, complications can include bottoming out, superior contour deformity, rippling, and/or lateral malposition. This complication profile increases the need for revision surgery and subsequent patient dissatisfaction. With the resurgence of shaped, textured, silicone implants in the USA, we report the senior author's success with these devices and outline a strategy to optimize outcomes in breast reconstruction surgery. A retrospective chart review was conducted on a prospectively collected IRB-approved database of nipple-sparing mastectomies (NSMs) with immediate breast reconstruction with smooth, round, silicone implants (Group A) in 2011 in comparison to textured, shaped, silicone implants (Group B) in 2012. Changes in operative technique were highlighted and extrapolated. Outcomes were reviewed. In Group A, 128 NSMs were performed in 76 patients. In Group B, 109 NSMs were performed in 59 patients. Thirteen percent of patients in Group A had direct to implant reconstruction as compared with 21% in Group B. Patients with textured, shaped implants were more likely to have acellular dermal matrix (61 vs 34%, p < 0.0001) than those with smooth, round implants. Patients who had smooth, round implants were more likely to have postoperative nipple malposition (18 vs 0%, p < 0.0001,) and rippling (29 vs 0%, p < 0.0001.) Patients with textured, shaped implants had fewer operative revision reconstructions as compared with those with smooth, round implants (36.71 vs 12.8%, p < 0.0001) Based on these results, our technique has evolved and has eight key technical modifications. With a few adaptations in surgical technique, the transition to textured, shaped, silicone devices for breast reconstruction can be seamless with superior breast contour and reduced complications/revision rates. This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .