Early detection of chemotherapy-refractory patients by monitoring textural alterations in diffuse optical spectroscopic images.

PubMed

Sadeghi-Naini, Ali; Vorauer, Eric; Chin, Lee; Falou, Omar; Tran, William T; Wright, Frances C; Gandhi, Sonal; Yaffe, Martin J; Czarnota, Gregory J

2015-11-01

Changes in textural characteristics of diffuse optical spectroscopic (DOS) functional images, accompanied by alterations in their mean values, are demonstrated here for the first time as early surrogates of ultimate treatment response in locally advanced breast cancer (LABC) patients receiving neoadjuvant chemotherapy (NAC). NAC, as a standard component of treatment for LABC patient, induces measurable heterogeneous changes in tumor metabolism which were evaluated using DOS-based metabolic maps. This study characterizes such inhomogeneous nature of response development, by determining alterations in textural properties of DOS images apparent at early stages of therapy, followed later by gross changes in mean values of these functional metabolic maps. Twelve LABC patients undergoing NAC were scanned before and at four times after treatment initiation, and tomographic DOS images were reconstructed at each time. Ultimate responses of patients were determined clinically and pathologically, based on a reduction in tumor size and assessment of residual tumor cellularity. The mean-value parameters and textural features were extracted from volumetric DOS images for several functional and metabolic parameters prior to the treatment initiation. Changes in these DOS-based biomarkers were also monitored over the course of treatment. The measured biomarkers were applied to differentiate patient responses noninvasively and compared to clinical and pathologic responses. Responding and nonresponding patients demonstrated different changes in DOS-based textural and mean-value parameters during chemotherapy. Whereas none of the biomarkers measured prior the start of therapy demonstrated a significant difference between the two patient populations, statistically significant differences were observed at week one after treatment initiation using the relative change in contrast/homogeneity of seven functional maps (0.001

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.

Dysphagia in Amyotrophic Lateral Sclerosis: Relationships between disease progression and Fiberoptic Endoscopic Evaluation of Swallowing.

PubMed

Fattori, Bruno; Siciliano, Gabriele; Mancini, Valentina; Bastiani, Luca; Bongioanni, Paolo; Caldarazzo Ienco, Elena; Barillari, Maria R; Romeo, Salvatore O; Nacci, Andrea

2017-06-01

Our aim was to evaluate the relationship between the disease severity of Amyotrophic Lateral Sclerosis (ALS) and the following parameters of Fiberoptic Endoscopic Evaluation of Swallowing (FEES): premature spillage, post-swallowing residue and aspiration. We studied 202 patients (95 women and 107 men) with ALS; of these, 136 had spinal and 66 had bulbar onset. They were analyzed according to the Amyotrophic Lateral Sclerosis Functioning Rating Scale (ALSFRS) and the b-ALSFRS subscale (bulbar scale). All subjects underwent FEES. Post-swallowing residue was classified into four classes (0-3); premature spillage and aspiration were considered either present or absent. Spearman's correlation test showed a highly significant correlation (p<0.0001) between the value of ALSFRS and b-ALSFRS and the FEES parameters as the following: disease severity and dysphagia severity are closely related, both in spinal and bulbar onset, no matter what bolus texture was used. Spearman's Rho was more significant for post-swallowing residue, ≤-0.500 with all three consistencies (p<0.0001) in spinal onset and -0.520 only with liquid bolus (p<0.0001) in bulbar onset. Independent T-Test revealed a significant difference (p<0.0001) between the mean ALSFRS and b-ALSFRS scores and the presence/absence of aspiration. For the premature spillage in spinal onset (ALSFRS), we found a statistically significant difference for all three bolus textures (p<0.0001). Analysis of variance for the post-swallowing residue in spinal onset (ALSFRS) revealed a statistically significant difference (p<0.0001) for most of the comparisons between groups for all three textures. For the premature spillage in bulbar onset (b-ALSFRS), we found a statistically significant difference for all three textures (p<0.0001). Analysis of variance for the post-swallowing residue in bulbar onset (b-ALSFRS) showed a statistically significant difference (p<0.0001) for most of the comparisons between groups for all three textures. Kruskal-Wallis test showed a highly significant association between the classes of severity in bulbar forms and all the FEES parameters, no matter what type of bolus was administered (p<0.0001), whereas a significant correlation in spinal forms only for post-swallowing residue with solid (p=0.026) and semisolid (p=0.031) boluses. There is a highly significant relationship as the following between the FEES parameters and the disease severity assessed via ALSFRS and b-ALSFRS: classes of greater severity entail a greater deterioration of FEES parameters. FEES can be considered a good indicator of the dysphagia severity and a useful test for the follow-up of dysphagia in patients with ALS, whether of spinal or bulbar onset. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Intercomparison of textural parameters of intertidal sediments generated by different statistical procedures, and implications for a unifying descriptive nomenclature

NASA Astrophysics Data System (ADS)

Fan, Daidu; Tu, Junbiao; Cai, Guofu; Shang, Shuai

2015-06-01

Grain-size analysis is a basic routine in sedimentology and related fields, but diverse methods of sample collection, processing and statistical analysis often make direct comparisons and interpretations difficult or even impossible. In this paper, 586 published grain-size datasets from the Qiantang Estuary (East China Sea) sampled and analyzed by the same procedures were merged and their textural parameters calculated by a percentile and two moment methods. The aim was to explore which of the statistical procedures performed best in the discrimination of three distinct sedimentary units on the tidal flats of the middle Qiantang Estuary. A Gaussian curve-fitting method served to simulate mixtures of two normal populations having different modal sizes, sorting values and size distributions, enabling a better understanding of the impact of finer tail components on textural parameters, as well as the proposal of a unifying descriptive nomenclature. The results show that percentile and moment procedures yield almost identical results for mean grain size, and that sorting values are also highly correlated. However, more complex relationships exist between percentile and moment skewness (kurtosis), changing from positive to negative correlations when the proportions of the finer populations decrease below 35% (10%). This change results from the overweighting of tail components in moment statistics, which stands in sharp contrast to the underweighting or complete amputation of small tail components by the percentile procedure. Intercomparisons of bivariate plots suggest an advantage of the Friedman & Johnson moment procedure over the McManus moment method in terms of the description of grain-size distributions, and over the percentile method by virtue of a greater sensitivity to small variations in tail components. The textural parameter scalings of Folk & Ward were translated into their Friedman & Johnson moment counterparts by application of mathematical functions derived by regression analysis of measured and modeled grain-size data, or by determining the abscissa values of intersections between auxiliary lines running parallel to the x-axis and vertical lines corresponding to the descriptive percentile limits along the ordinate of representative bivariate plots. Twofold limits were extrapolated for the moment statistics in relation to single descriptive terms in the cases of skewness and kurtosis by considering both positive and negative correlations between percentile and moment statistics. The extrapolated descriptive scalings were further validated by examining entire size-frequency distributions simulated by mixing two normal populations of designated modal size and sorting values, but varying in mixing ratios. These were found to match well in most of the proposed scalings, although platykurtic and very platykurtic categories were questionable when the proportion of the finer population was below 5%. Irrespective of the statistical procedure, descriptive nomenclatures should therefore be cautiously used when tail components contribute less than 5% to grain-size distributions.

Estimation of trabecular bone parameters in children from multisequence MRI using texture-based regression

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

Lekadir, Karim, E-mail: karim.lekadir@upf.edu; Hoogendoorn, Corné; Armitage, Paul

Purpose: This paper presents a statistical approach for the prediction of trabecular bone parameters from low-resolution multisequence magnetic resonance imaging (MRI) in children, thus addressing the limitations of high-resolution modalities such as HR-pQCT, including the significant exposure of young patients to radiation and the limited applicability of such modalities to peripheral bones in vivo. Methods: A statistical predictive model is constructed from a database of MRI and HR-pQCT datasets, to relate the low-resolution MRI appearance in the cancellous bone to the trabecular parameters extracted from the high-resolution images. The description of the MRI appearance is achieved between subjects by usingmore » a collection of feature descriptors, which describe the texture properties inside the cancellous bone, and which are invariant to the geometry and size of the trabecular areas. The predictive model is built by fitting to the training data a nonlinear partial least square regression between the input MRI features and the output trabecular parameters. Results: Detailed validation based on a sample of 96 datasets shows correlations >0.7 between the trabecular parameters predicted from low-resolution multisequence MRI based on the proposed statistical model and the values extracted from high-resolution HRp-QCT. Conclusions: The obtained results indicate the promise of the proposed predictive technique for the estimation of trabecular parameters in children from multisequence MRI, thus reducing the need for high-resolution radiation-based scans for a fragile population that is under development and growth.« less

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.

Low-level contrast statistics are diagnostic of invariance of natural textures

PubMed Central

Groen, Iris I. A.; Ghebreab, Sennay; Lamme, Victor A. F.; Scholte, H. Steven

2012-01-01

Texture may provide important clues for real world object and scene perception. To be reliable, these clues should ideally be invariant to common viewing variations such as changes in illumination and orientation. In a large image database of natural materials, we found textures with low-level contrast statistics that varied substantially under viewing variations, as well as textures that remained relatively constant. This led us to ask whether textures with constant contrast statistics give rise to more invariant representations compared to other textures. To test this, we selected natural texture images with either high (HV) or low (LV) variance in contrast statistics and presented these to human observers. In two distinct behavioral categorization paradigms, participants more often judged HV textures as “different” compared to LV textures, showing that textures with constant contrast statistics are perceived as being more invariant. In a separate electroencephalogram (EEG) experiment, evoked responses to single texture images (single-image ERPs) were collected. The results show that differences in contrast statistics correlated with both early and late differences in occipital ERP amplitude between individual images. Importantly, ERP differences between images of HV textures were mainly driven by illumination angle, which was not the case for LV images: there, differences were completely driven by texture membership. These converging neural and behavioral results imply that some natural textures are surprisingly invariant to illumination changes and that low-level contrast statistics are diagnostic of the extent of this invariance. PMID:22701419

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

Association between pathology and texture features of multi parametric MRI of the prostate

NASA Astrophysics Data System (ADS)

Kuess, Peter; Andrzejewski, Piotr; Nilsson, David; Georg, Petra; Knoth, Johannes; Susani, Martin; Trygg, Johan; Helbich, Thomas H.; Polanec, Stephan H.; Georg, Dietmar; Nyholm, Tufve

2017-10-01

The role of multi-parametric (mp)MRI in the diagnosis and treatment of prostate cancer has increased considerably. An alternative to visual inspection of mpMRI is the evaluation using histogram-based (first order statistics) parameters and textural features (second order statistics). The aims of the present work were to investigate the relationship between benign and malignant sub-volumes of the prostate and textures obtained from mpMR images. The performance of tumor prediction was investigated based on the combination of histogram-based and textural parameters. Subsequently, the relative importance of mpMR images was assessed and the benefit of additional imaging analyzed. Finally, sub-structures based on the PI-RADS classification were investigated as potential regions to automatically detect maligned lesions. Twenty-five patients who received mpMRI prior to radical prostatectomy were included in the study. The imaging protocol included T2, DWI, and DCE. Delineation of tumor regions was performed based on pathological information. First and second order statistics were derived from each structure and for all image modalities. The resulting data were processed with multivariate analysis, using PCA (principal component analysis) and OPLS-DA (orthogonal partial least squares discriminant analysis) for separation of malignant and healthy tissue. PCA showed a clear difference between tumor and healthy regions in the peripheral zone for all investigated images. The predictive ability of the OPLS-DA models increased for all image modalities when first and second order statistics were combined. The predictive value reached a plateau after adding ADC and T2, and did not increase further with the addition of other image information. The present study indicates a distinct difference in the signatures between malign and benign prostate tissue. This is an absolute prerequisite for automatic tumor segmentation, but only the first step in that direction. For the specific identified signature, DCE did not add complementary information to T2 and ADC maps.

Cloud field classification based on textural features

NASA Technical Reports Server (NTRS)

Sengupta, Sailes Kumar

1989-01-01

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

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

Caracterisation des occupations du sol en milieu urbain par imagerie radar

NASA Astrophysics Data System (ADS)

Codjia, Claude

This study aims to test the relevance of medium and high-resolution SAR images on the characterization of the types of land use in urban areas. To this end, we have relied on textural approaches based on second-order statistics. Specifically, we look for texture parameters most relevant for discriminating urban objects. We have used in this regard Radarsat-1 in fine polarization mode and Radarsat-2 HH fine mode in dual and quad polarization and ultrafine mode HH polarization. The land uses sought were dense building, medium density building, low density building, industrial and institutional buildings, low density vegetation, dense vegetation and water. We have identified nine texture parameters for analysis, grouped into families according to their mathematical definitions in a first step. The parameters of similarity / dissimilarity include Homogeneity, Contrast, the Differential Inverse Moment and Dissimilarity. The parameters of disorder are Entropy and the Second Angular Momentum. The Standard Deviation and Correlation are the dispersion parameters and the Average is a separate family. It is clear from experience that certain combinations of texture parameters from different family used in classifications yield good results while others produce kappa of very little interest. Furthermore, we realize that if the use of several texture parameters improves classifications, its performance ceils from three parameters. The calculation of correlations between the textures and their principal axes confirm the results. Despite the good performance of this approach based on the complementarity of texture parameters, systematic errors due to the cardinal effects remain on classifications. To overcome this problem, a radiometric compensation model was developed based on the radar cross section (SER). A radar simulation from the digital surface model of the environment allowed us to extract the building backscatter zones and to analyze the related backscatter. Thus, we were able to devise a strategy of compensation of cardinal effects solely based on the responses of the objects according to their orientation from the plane of illumination through the radar's beam. It appeared that a compensation algorithm based on the radar cross section was appropriate. Some examples of the application of this algorithm on HH polarized RADARSAT-2 images are presented as well. Application of this algorithm will allow considerable gains with regard to certain forms of automation (classification and segmentation) at the level of radar imagery thus generating a higher level of quality in regard to visual interpretation. Application of this algorithm on RADARSAT-1 and RADARSAT-2 images with HH, HV, VH, and VV polarisations helped make considerable gains and eliminate most of the classification errors due to the cardinal effects.

Effects of long-term stimulation of textured insoles on postural control in health elderly.

PubMed

Annino, Giuseppe; Palazzo, Francesco; Alwardat, Mohammad S; Manzi, Vincenzo; Lebone, Pietro; Tancredi, Virginia; Sinibaldi Salimei, Paola; Caronti, Alfio; Panzarino, Michele; Padua, Elvira

2018-04-01

The aim of this study was to confirm the effects of long term (chronic) stimulating surface (textured insole) on body balance of elderly people. Twenty-four healthy elderly individuals were randomly distributed in two groups: control and experimental (67.75±6.04 years, 74.55±12.14 kg, 163.7±8.55 cm, 27.75±3.04 kg/m2). Over one month, control group (CG) used smooth insoles and the experimental group (ExG) used textured insoles every day. Velocity net (Vnet), anteroposterior (VA/P), mediolateral (VM/L) and sway path of CoP were assessed in different eye conditions before and after the experimental procedure. A mixed between-within subject ANOVA was conducted to assess the impact of soft and textured insoles and two visual conditions (vision vs. no vision) across two time periods (α≤0.05). The results showed any statistical difference between groups in each parameter assessed in this study. CoP, Vnet and VM/L in the experimental group showed a statistically significant effect of textured insoles only without vision (CoP: P=0.002; η2=0.35), Vnet P=0.02; η2=0.24, VM/L P=0.04; η2=0.177) whereas VA/P showed no statistically significant effect in the same group and condition. There was no significant effect in Vnet, VA/P, VM/L and COP in control group that used smooth insole for both eye conditions. The results confirm that postural stability improved in healthy elderly individuals, increasing somatosensory information's from feet plantar mechanoreceptors. Long term stimulation with textured insoles decreased CoP, Vnet and VM/L with eyes closed.

Resolving structural influences on water-retention properties of alluvial deposits

USGS Publications Warehouse

Winfield, K.A.; Nimmo, J.R.; Izbicki, J.A.; Martin, P.M.

2006-01-01

With the goal of improving property-transfer model (PTM) predictions of unsaturated hydraulic properties, we investigated the influence of sedimentary structure, defined as particle arrangement during deposition, on laboratory-measured water retention (water content vs. potential [??(??)]) of 10 undisturbed core samples from alluvial deposits in the western Mojave Desert, California. The samples were classified as having fluvial or debris-flow structure based on observed stratification and measured spread of particle-size distribution. The ??(??) data were fit with the Rossi-Nimmo junction model, representing water retention with three parameters: the maximum water content (??max), the ??-scaling parameter (??o), and the shape parameter (??). We examined trends between these hydraulic parameters and bulk physical properties, both textural - geometric mean, Mg, and geometric standard deviation, ??g, of particle diameter - and structural - bulk density, ??b, the fraction of unfilled pore space at natural saturation, Ae, and porosity-based randomness index, ??s, defined as the excess of total porosity over 0.3. Structural parameters ??s and Ae were greater for fluvial samples, indicating greater structural pore space and a possibly broader pore-size distribution associated with a more systematic arrangement of particles. Multiple linear regression analysis and Mallow's Cp statistic identified combinations of textural and structural parameters for the most useful predictive models: for ??max, including Ae, ??s, and ??g, and for both ??o and ??, including only textural parameters, although use of Ae can somewhat improve ??o predictions. Textural properties can explain most of the sample-to-sample variation in ??(??) independent of deposit type, but inclusion of the simple structural indicators Ae and ??s can improve PTM predictions, especially for the wettest part of the ??(??) curve. ?? Soil Science Society of America.

Structure-guided statistical textural distinctiveness for salient region detection in natural images.

PubMed

Scharfenberger, Christian; Wong, Alexander; Clausi, David A

2015-01-01

We propose a simple yet effective structure-guided statistical textural distinctiveness approach to salient region detection. Our method uses a multilayer approach to analyze the structural and textural characteristics of natural images as important features for salient region detection from a scale point of view. To represent the structural characteristics, we abstract the image using structured image elements and extract rotational-invariant neighborhood-based textural representations to characterize each element by an individual texture pattern. We then learn a set of representative texture atoms for sparse texture modeling and construct a statistical textural distinctiveness matrix to determine the distinctiveness between all representative texture atom pairs in each layer. Finally, we determine saliency maps for each layer based on the occurrence probability of the texture atoms and their respective statistical textural distinctiveness and fuse them to compute a final saliency map. Experimental results using four public data sets and a variety of performance evaluation metrics show that our approach provides promising results when compared with existing salient region detection approaches.

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.

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

PubMed Central

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

2015-01-01

Abstract. Image heterogeneity metrics such as textural features are an active area of research for evaluating clinical outcomes with positron emission tomography (PET) imaging and other modalities. However, the effects of stochastic image acquisition noise on these metrics are poorly understood. We performed a simulation study by generating 50 statistically independent PET images of the NEMA IQ phantom with realistic noise and resolution properties. Heterogeneity metrics based on gray-level intensity histograms, co-occurrence matrices, neighborhood difference matrices, and zone size matrices were evaluated within regions of interest surrounding the lesions. The impact of stochastic variability was evaluated with percent difference from the mean of the 50 realizations, coefficient of variation and estimated sample size for clinical trials. Additionally, sensitivity studies were performed to simulate the effects of patient size and image reconstruction method on the quantitative performance of these metrics. Complex trends in variability were revealed as a function of textural feature, lesion size, patient size, and reconstruction parameters. In conclusion, the sensitivity of PET textural features to normal stochastic image variation and imaging parameters can be large and is feature-dependent. Standards are needed to ensure that prospective studies that incorporate textural features are properly designed to measure true effects that may impact clinical outcomes. PMID:26251842

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

PubMed

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

2015-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

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

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

PubMed

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

1987-06-01

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

Different Manhattan project: automatic statistical model generation

NASA Astrophysics Data System (ADS)

Yap, Chee Keng; Biermann, Henning; Hertzmann, Aaron; Li, Chen; Meyer, Jon; Pao, Hsing-Kuo; Paxia, Salvatore

2002-03-01

We address the automatic generation of large geometric models. This is important in visualization for several reasons. First, many applications need access to large but interesting data models. Second, we often need such data sets with particular characteristics (e.g., urban models, park and recreation landscape). Thus we need the ability to generate models with different parameters. We propose a new approach for generating such models. It is based on a top-down propagation of statistical parameters. We illustrate the method in the generation of a statistical model of Manhattan. But the method is generally applicable in the generation of models of large geographical regions. Our work is related to the literature on generating complex natural scenes (smoke, forests, etc) based on procedural descriptions. The difference in our approach stems from three characteristics: modeling with statistical parameters, integration of ground truth (actual map data), and a library-based approach for texture mapping.

A Study of Feature Extraction Using Divergence Analysis of Texture Features

NASA Technical Reports Server (NTRS)

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

1982-01-01

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

Computerized morphometry as an aid in distinguishing recurrent versus nonrecurrent meningiomas.

PubMed

Noy, Shawna; Vlodavsky, Euvgeni; Klorin, Geula; Drumea, Karen; Ben Izhak, Ofer; Shor, Eli; Sabo, Edmond

2011-06-01

To use novel digital and morphometric methods to identify variables able to better predict the recurrence of intracranial meningiomas. Histologic images from 30 previously diagnosed meningioma tumors that recurred over 10 years of follow-up were consecutively selected from the Rambam Pathology Archives. Images were captured and morphometrically analyzed. Novel algorithms of digital pattern recognition using Fourier transformation and fractal and nuclear texture analyses were applied to evaluate the overall growth pattern complexity of the tumors, as well as the chromatin texture of individual tumor nuclei. The extracted parameters were then correlated with patient prognosis. Kaplan-Meier analyses revealed statistically significant associations between tumor morphometric parameters and recurrence times. Tumors with less nuclear orientation, more nuclear density, higher fractal dimension, and less regular chromatin textures tended to recur faster than those with a higher degree of nuclear order, less pattern complexity, lower density, and more homogeneous chromatin nuclear textures (p < 0.01). To our knowledge, these digital morphometric methods were used for the first time to accurately predict tumor recurrence in patients with intracranial meningiomas. The use of these methods may bring additional valuable information to the clinician regarding the optimal management of these patients.

Compressed Sensing (CS) Imaging with Wide FOV and Dynamic Magnification

DTIC Science & Technology

2011-03-14

Digital Micromirror Device (DMD) to implement the CS measurement patterns. The core component of the DMD is a 768(V)?1024(H) aluminum micromirror array...image has different curves and textures, thus has different statistical model parameters. The sampling 19 Table 2: Reconstruction of images in

Quantification of Valleys of Randomly Textured Substrates as a Function of Opening Angle: Correlation to the Defect Density in Intrinsic nc-Si:H.

PubMed

Kim, Do Yun; Hänni, Simon; Schüttauf, Jan-Willem; van Swaaij, René A C M M; Zeman, Miro

2016-08-17

Optical and electrical properties of hydrogenated nanocrystalline silicon (nc-Si:H) solar cells are strongly influenced by the morphology of underlying substrates. By texturing the substrates, the photogenerated current of nc-Si:H solar cells can increase due to enhanced light scattering. These textured substrates are, however, often incompatible with defect-less nc-Si:H growth resulting in lower Voc and FF. In this study we investigate the correlation between the substrate morphology, the nc-Si:H solar-cell performance, and the defect density in the intrinsic layer of the solar cells (i-nc-Si:H). Statistical surface parameters representing the substrate morphology do not show a strong correlation with the solar-cell parameters. Thus, we first quantify the line density of potentially defective valleys of randomly textured ZnO substrates where the opening angle is smaller than 130° (ρ<130). This ρ<130 is subsequently compared with the solar-cell performance and the defect density of i-nc-Si:H (ρdefect), which is obtained by fitting external photovoltaic parameters from experimental results and simulations. We confirm that when ρ<130 increases the Voc and FF significantly drops. It is also observed that ρdefect increases following a power law dependence of ρ<130. This result is attributed to more frequently formed defective regions for substrates having higher ρ<130.

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

NASA Astrophysics Data System (ADS)

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

2001-07-01

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

Sound texture perception via statistics of the auditory periphery: Evidence from sound synthesis

PubMed Central

McDermott, Josh H.; Simoncelli, Eero P.

2014-01-01

Rainstorms, insect swarms, and galloping horses produce “sound textures” – the collective result of many similar acoustic events. Sound textures are distinguished by temporal homogeneity, suggesting they could be recognized with time-averaged statistics. To test this hypothesis, we processed real-world textures with an auditory model containing filters tuned for sound frequencies and their modulations, and measured statistics of the resulting decomposition. We then assessed the realism and recognizability of novel sounds synthesized to have matching statistics. Statistics of individual frequency channels, capturing spectral power and sparsity, generally failed to produce compelling synthetic textures. However, combining them with correlations between channels produced identifiable and natural-sounding textures. Synthesis quality declined if statistics were computed from biologically implausible auditory models. The results suggest that sound texture perception is mediated by relatively simple statistics of early auditory representations, presumably computed by downstream neural populations. The synthesis methodology offers a powerful tool for their further investigation. PMID:21903084

Respiration-Averaged CT for Attenuation Correction of PET Images – Impact on PET Texture Features in Non-Small Cell Lung Cancer Patients

PubMed Central

Cheng, Nai-Ming; Fang, Yu-Hua Dean; Tsan, Din-Li

2016-01-01

Purpose We compared attenuation correction of PET images with helical CT (PET/HCT) and respiration-averaged CT (PET/ACT) in patients with non-small-cell lung cancer (NSCLC) with the goal of investigating the impact of respiration-averaged CT on 18F FDG PET texture parameters. Materials and Methods A total of 56 patients were enrolled. Tumors were segmented on pretreatment PET images using the adaptive threshold. Twelve different texture parameters were computed: standard uptake value (SUV) entropy, uniformity, entropy, dissimilarity, homogeneity, coarseness, busyness, contrast, complexity, grey-level nonuniformity, zone-size nonuniformity, and high grey-level large zone emphasis. Comparisons of PET/HCT and PET/ACT were performed using Wilcoxon signed-rank tests, intraclass correlation coefficients, and Bland-Altman analysis. Receiver operating characteristic (ROC) curves as well as univariate and multivariate Cox regression analyses were used to identify the parameters significantly associated with disease-specific survival (DSS). A fixed threshold at 45% of the maximum SUV (T45) was used for validation. Results SUV maximum and total lesion glycolysis (TLG) were significantly higher in PET/ACT. However, texture parameters obtained with PET/ACT and PET/HCT showed a high degree of agreement. The lowest levels of variation between the two modalities were observed for SUV entropy (9.7%) and entropy (9.8%). SUV entropy, entropy, and coarseness from both PET/ACT and PET/HCT were significantly associated with DSS. Validation analyses using T45 confirmed the usefulness of SUV entropy and entropy in both PET/HCT and PET/ACT for the prediction of DSS, but only coarseness from PET/ACT achieved the statistical significance threshold. Conclusions Our results indicate that 1) texture parameters from PET/ACT are clinically useful in the prediction of survival in NSCLC patients and 2) SUV entropy and entropy are robust to attenuation correction methods. PMID:26930211

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.

Randomized clinical trial of two resin-modified glass ionomer materials: 1-year results.

PubMed

Perdigão, J; Dutra-Corrêa, M; Saraceni, S H C; Ciaramicoli, M T; Kiyan, V H

2012-01-01

With institutional review board approval, 33 patients who needed restoration of noncarious cervical lesions (NCCL) were enrolled in this study. A total of 92 NCCL were selected and randomly assigned to three groups: (1) Ambar (FGM), a two-step etch-and-rinse adhesive (control), combined with the nanofilled composite resin Filtek Supreme Plus (FSP; 3M ESPE); (2) Fuji II LC (GC America), a traditional resin-modified glass ionomer (RMGIC) restorative material; (3) Ketac Nano (3M ESPE), a nanofilled RMGIC restorative material. Restorations were evaluated at six months and one year using modified United States Public Health Service parameters. At six months after initial placement, 84 restorations (a 91.3% recall rate) were evaluated. At one year, 78 restorations (a 84.8% recall rate) were available for evaluation. The six month and one year overall retention rates were 93.1% and 92.6%, respectively, for Ambar/FSP; 100% and 100%, respectively, for Fuji II LC; and 100% and 100%, respectively, for Ketac Nano with no statistical difference between any pair of groups at each recall. Sensitivity to air decreased for all three adhesive materials from the preoperative to the postoperative stage, but the difference was not statistically significant. For Ambar/FSP, there were no statistical differences for any of the parameters from baseline to six months and from baseline to one year. For Fuji II LC, surface texture worsened significantly from baseline to six months and from baseline to one year. For Ketac Nano, enamel marginal staining increased significantly from baseline to one year and from six months to one year. Marginal adaptation was statistically worse at one year compared with baseline only for Ketac Nano. When parameters were compared for materials at each recall, Ketac Nano resulted in significantly worse color match than any of the other two materials at any evaluation period. At one year, Ketac Nano resulted in significantly worse marginal adaptation than the other two materials and worse marginal staining than Fuji II LC. Surface texture was statistically worse for Fuji II LC compared with the other two materials at all evaluation periods. The one-year retention rate was statistically similar for the three adhesive materials. Nevertheless, enamel marginal deficiencies and color mismatch were more prevalent for Ketac Nano. Surface texture of Fuji II LC restorations deteriorated quickly.

Addressing scale dependence in roughness and morphometric statistics derived from point cloud data.

NASA Astrophysics Data System (ADS)

Buscombe, D.; Wheaton, J. M.; Hensleigh, J.; Grams, P. E.; Welcker, C. W.; Anderson, K.; Kaplinski, M. A.

2015-12-01

The heights of natural surfaces can be measured with such spatial density that almost the entire spectrum of physical roughness scales can be characterized, down to the morphological form and grain scales. With an ability to measure 'microtopography' comes a demand for analytical/computational tools for spatially explicit statistical characterization of surface roughness. Detrended standard deviation of surface heights is a popular means to create continuous maps of roughness from point cloud data, using moving windows and reporting window-centered statistics of variations from a trend surface. If 'roughness' is the statistical variation in the distribution of relief of a surface, then 'texture' is the frequency of change and spatial arrangement of roughness. The variance in surface height as a function of frequency obeys a power law. In consequence, roughness is dependent on the window size through which it is examined, which has a number of potential disadvantages: 1) the choice of window size becomes crucial, and obstructs comparisons between data; 2) if windows are large relative to multiple roughness scales, it is harder to discriminate between those scales; 3) if roughness is not scaled by the texture length scale, information on the spacing and clustering of roughness `elements' can be lost; and 4) such practice is not amenable to models describing the scattering of light and sound from rough natural surfaces. We discuss the relationship between roughness and texture. Some useful parameters which scale vertical roughness to characteristic horizontal length scales are suggested, with examples of bathymetric point clouds obtained using multibeam from two contrasting riverbeds, namely those of the Colorado River in Grand Canyon, and the Snake River in Hells Canyon. Such work, aside from automated texture characterization and texture segmentation, roughness and grain size calculation, might also be useful for feature detection and classification from point clouds.

Histological evaluation of capsules formed by silicon implants coated with polyurethane foam and with a textured surface in rats.

PubMed

Silva, Eduardo Nascimento; Ribas-Filho, Jurandir Marcondes; Czeczko, Nicolau Gregori; Pachnicki, Jan Pawel Andrade; Netto, Mário Rodrigues Montemor; Lipinski, Leandro Cavalcante; Noronha, Lucia de; Colman, Joelmir; Zeni, João Otavio; Carvalho, Caroline Aragão de

2016-12-01

To assess the capsules formed by silicone implants coated with polyurethane foam and with a textured surface. Sixty-four Wistar albinus rats were divided into two groups of 32 each using polyurethane foam and textured surface. The capsules around the implants were analyzed for 30, 50, 70 and 90 days. Were analyzed the following parameters: foreign body reaction, granulation tissue, presence of myofibroblasts, neoangiogenesis, presence of synovial metaplasia, capsular thickness, total area and collagen percentage of type I and III, in capsules formed around silicone implants in both groups. The foreign body reaction was only present in the four polyurethane subgroups. The formation of granulation tissue and the presence of myofibroblasts were higher in the four polyurethane subgroups. Regarding to neoangiogenesis and synovial metaplasia, there was no statistical difference between the groups. Polyurethane group presented (all subgroups) a greater capsule thickness, a smaller total area and collagen percentage of type I and a higher percentage area of type III, with statistical difference. The use of polyurethane-coated implants should be stimulated by the long-term results in a more stable capsule and a lower incidence of capsular contracture, despite developing a more intense and delayed inflammatory reaction in relation to implants with textured surface.

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

Ecological model of glittering texture

NASA Astrophysics Data System (ADS)

Vallet, Matthieu; Paille, Damien; Monot, Annie; Kemeny, Andras

2003-06-01

The perceptual effects of changes of texture luminance either between the eyes or over time have been studied in several experiments and have led to a better comprehension of phenomenons such as sieve effect, binocular and monocular lustre and rivaldepth. In this paper, we propose an ecological model of glittering texture and analyze glitter perception in terms of variations of texture luminance and animation frequency, in dynamic illumination conditions. Our approach is based on randomly oriented mirrors that are computed according to the specular term of Phong's image rendering formula. The sparkling effect is thus correlated to the relative movements of the resulting textured object, the light array and the observer's point of view. The perceptual effect obtained with this model depends on several parameters: mirrors' density, the Phong specular exponent and the statistical properties of the mirrors' normal vectors. The ability to independently set these properties offers a way to explore a characterization space of glitter. A rating procedure provided a first approximation of the numerical values that lead to the best feeling of typical sparkling surfaces such as metallic paint, granite or sea shore.

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.

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.

Effect of texturing on polarization switching dynamics in ferroelectric ceramics

NASA Astrophysics Data System (ADS)

Zhukov, Sergey; Genenko, Yuri A.; Koruza, Jurij; Schultheiß, Jan; von Seggern, Heinz; Sakamoto, Wataru; Ichikawa, Hiroki; Murata, Tatsuro; Hayashi, Koichiro; Yogo, Toshinobu

2016-01-01

Highly (100),(001)-oriented (Ba0.85Ca0.15)TiO3 (BCT) lead-free piezoelectric ceramics were fabricated by the reactive templated grain growth method using a mixture of plate-like CaTiO3 and BaTiO3 particles. Piezoelectric properties of the ceramics with a high degree of texture were found to be considerably enhanced compared with the BCT ceramics with a low degree of texture. With increasing the Lotgering factor from 26% up to 94%, the piezoelectric properties develop towards the properties of a single crystal. The dynamics of polarization switching was studied over a broad time domain of 8 orders of magnitude and was found to strongly depend on the degree of orientation of the ceramics. Samples with a high degree of texture exhibited 2-3 orders of magnitude faster polarization switching, as compared with the ones with a low degree of texture. This was rationalized by means of the Inhomogeneous Field Mechanism model as a result of the narrower statistical distribution of the local electric field values in textured media, which promotes a more coherent switching process. The extracted microscopic parameters of switching revealed a decrease of the critical nucleus energy in systems with a high degree of texture providing more favorable switching conditions related to the enhanced ferroelectric properties of the textured material.

Texture analysis on the fluence map to evaluate the degree of modulation for volumetric modulated arc therapy.

PubMed

Park, So-Yeon; Kim, Il Han; Ye, Sung-Joon; Carlson, Joel; Park, Jong Min

2014-11-01

Texture analysis on fluence maps was performed to evaluate the degree of modulation for volumetric modulated arc therapy (VMAT) plans. A total of six textural features including angular second moment, inverse difference moment, contrast, variance, correlation, and entropy were calculated for fluence maps generated from 20 prostate and 20 head and neck VMAT plans. For each of the textural features, particular displacement distances (d) of 1, 5, and 10 were adopted. To investigate the deliverability of each VMAT plan, gamma passing rates of pretreatment quality assurance, and differences in modulating parameters such as multileaf collimator (MLC) positions, gantry angles, and monitor units at each control point between VMAT plans and dynamic log files registered by the Linac control system during delivery were acquired. Furthermore, differences between the original VMAT plan and the plan reconstructed from the dynamic log files were also investigated. To test the performance of the textural features as indicators for the modulation degree of VMAT plans, Spearman's rank correlation coefficients (rs) with the plan deliverability were calculated. For comparison purposes, conventional modulation indices for VMAT including the modulation complexity score for VMAT, leaf travel modulation complexity score, and modulation index supporting station parameter optimized radiation therapy (MISPORT) were calculated, and their correlations were analyzed in the same way. There was no particular textural feature which always showed superior correlations with every type of plan deliverability. Considering the results comprehensively, contrast (d = 1) and variance (d = 1) generally showed considerable correlations with every type of plan deliverability. These textural features always showed higher correlations to the plan deliverability than did the conventional modulation indices, except in the case of modulating parameter differences. The rs values of contrast to the global gamma passing rates with criteria of 2%/2 mm, 2%/1 mm, and 1%/2 mm were 0.536, 0.473, and 0.718, respectively. The respective values for variance were 0.551, 0.481, and 0.688. In the case of local gamma passing rates, the rs values of contrast were 0.547, 0.578, and 0.620, respectively, and those of variance were 0.519, 0.527, and 0.569. All of the rs values in those cases were statistically significant (p < 0.003). In the cases of global and local gamma passing rates, MISPORT showed the highest correlations among the conventional modulation indices. For global passing rates, rs values of MISPORT were -0.420, -0.330, and -0.632, respectively, and those for local passing rates were -0.455, -0.490 and -0.502. The values of rs of contrast, variance, and MISPORT with the MLC errors were -0.863, -0.828, and 0.795, respectively, all with statistical significances (p < 0.001). The correlations with statistical significances between variance and dose-volumetric differences were observed more frequently than the others. The contrast (d = 1) and variance (d = 1) calculated from fluence maps of VMAT plans showed considerable correlations with the plan deliverability, indicating their potential use as indicators for assessing the degree of modulation of VMAT plans. Both contrast and variance consistently showed better performance than the conventional modulation indices for VMAT.

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.

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.

Texturing of polypropylene (PP) with nanosecond lasers

NASA Astrophysics Data System (ADS)

Riveiro, A.; Soto, R.; del Val, J.; Comesaña, R.; Boutinguiza, M.; Quintero, F.; Lusquiños, F.; Pou, J.

2016-06-01

Polypropylene (PP) is a biocompatible and biostable polymer, showing good mechanical properties that has been recently introduced in the biomedical field for bone repairing applications; however, its poor surface properties due to its low surface energy limit their use in biomedical applications. In this work, we have studied the topographical modification of polypropylene (PP) laser textured with Nd:YVO4 nanosecond lasers emitting at λ = 1064 nm, 532 nm, and 355 nm. First, optical response of this material under these laser wavelengths was determined. The application of an absorbing coating was also studied. The influence of the laser processing parameters on the surface modification of PP was investigated by means of statistically designed experiments. Processing maps to tailor the roughness, and wettability, the main parameters affecting cell adhesion characteristics of implants, were also determined. Microhardness measurements were performed to discern the impact of laser treatment on the final mechanical properties of PP.

Quantitative Analysis of the Effect of Iterative Reconstruction Using a Phantom: Determining the Appropriate Blending Percentage

PubMed Central

Kim, Hyun Gi; Lee, Young Han; Choi, Jin-Young; Park, Mi-Suk; Kim, Myeong-Jin; Kim, Ki Whang

2015-01-01

Purpose To investigate the optimal blending percentage of adaptive statistical iterative reconstruction (ASIR) in a reduced radiation dose while preserving a degree of image quality and texture that is similar to that of standard-dose computed tomography (CT). Materials and Methods The CT performance phantom was scanned with standard and dose reduction protocols including reduced mAs or kVp. Image quality parameters including noise, spatial, and low-contrast resolution, as well as image texture, were quantitatively evaluated after applying various blending percentages of ASIR. The optimal blending percentage of ASIR that preserved image quality and texture compared to standard dose CT was investigated in each radiation dose reduction protocol. Results As the percentage of ASIR increased, noise and spatial-resolution decreased, whereas low-contrast resolution increased. In the texture analysis, an increasing percentage of ASIR resulted in an increase of angular second moment, inverse difference moment, and correlation and in a decrease of contrast and entropy. The 20% and 40% dose reduction protocols with 20% and 40% ASIR blending, respectively, resulted in an optimal quality of images with preservation of the image texture. Conclusion Blending the 40% ASIR to the 40% reduced tube-current product can maximize radiation dose reduction and preserve adequate image quality and texture. PMID:25510772

Image informative maps for component-wise estimating parameters of signal-dependent noise

NASA Astrophysics Data System (ADS)

Uss, Mykhail L.; Vozel, Benoit; Lukin, Vladimir V.; Chehdi, Kacem

2013-01-01

We deal with the problem of blind parameter estimation of signal-dependent noise from mono-component image data. Multispectral or color images can be processed in a component-wise manner. The main results obtained rest on the assumption that the image texture and noise parameters estimation problems are interdependent. A two-dimensional fractal Brownian motion (fBm) model is used for locally describing image texture. A polynomial model is assumed for the purpose of describing the signal-dependent noise variance dependence on image intensity. Using the maximum likelihood approach, estimates of both fBm-model and noise parameters are obtained. It is demonstrated that Fisher information (FI) on noise parameters contained in an image is distributed nonuniformly over intensity coordinates (an image intensity range). It is also shown how to find the most informative intensities and the corresponding image areas for a given noisy image. The proposed estimator benefits from these detected areas to improve the estimation accuracy of signal-dependent noise parameters. Finally, the potential estimation accuracy (Cramér-Rao Lower Bound, or CRLB) of noise parameters is derived, providing confidence intervals of these estimates for a given image. In the experiment, the proposed and existing state-of-the-art noise variance estimators are compared for a large image database using CRLB-based statistical efficiency criteria.

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.

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.

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.

The Effect of Petrographic Characteristics on Engineering Properties of Conglomerates from Famenin Region, Northeast of Hamedan, Iran

NASA Astrophysics Data System (ADS)

Khanlari, G. R.; Heidari, M.; Noori, M.; Momeni, A.

2016-07-01

To assess relationship between engineering characteristics and petrographic features, conglomerates samples related to Qom formation from Famenin region in northeast of Hamedan province were studied. Samples were tested in laboratory to determine the uniaxial compressive strength, point load strength index, modulus of elasticity, porosity, dry and saturation densities. For determining petrographic features, textural and mineralogical parameters, thin sections of the samples were prepared and studied. The results show that the effect of textural characteristics on the engineering properties of conglomerates supposed to be more important than mineralogical composition. It also was concluded that the packing proximity, packing density, grain shape and mean grain size, cement and matrix frequency are as textural features that have a significant effect on the physical and mechanical properties of the studied conglomerates. In this study, predictive statistical relationships were developed to estimate the physical and mechanical properties of the rocks based on the results of petrographic features. Furthermore, multivariate linear regression was used in four different steps comprising various combinations of petrographical characteristics for each engineering parameters. Finally, the best equations with specific arrangement were suggested to estimate engineering properties of the Qom formation conglomerates.

Estimation of forest biomass using remote sensing

NASA Astrophysics Data System (ADS)

Sarker, Md. Latifur Rahman

Forest biomass estimation is essential for greenhouse gas inventories, terrestrial carbon accounting and climate change modelling studies. The availability of new SAR, (C-band RADARSAT-2 and L-band PALSAR) and optical sensors (SPOT-5 and AVNIR-2) has opened new possibilities for biomass estimation because these new SAR sensors can provide data with varying polarizations, incidence angles and fine spatial resolutions. 'Therefore, this study investigated the potential of two SAR sensors (RADARSAT-2 with C-band and PALSAR with L-band) and two optical sensors (SPOT-5 and AVNIR2) for the estimation of biomass in Hong Kong. Three common major processing steps were used for data processing, namely (i) spectral reflectance/intensity, (ii) texture measurements and (iii) polarization or band ratios of texture parameters. Simple linear and stepwise multiple regression models were developed to establish a relationship between the image parameters and the biomass of field plots. The results demonstrate the ineffectiveness of raw data. However, significant improvements in performance (r2) (RADARSAT-2=0.78; PALSAR=0.679; AVNIR-2=0.786; SPOT-5=0.854; AVNIR-2 + SPOT-5=0.911) were achieved using texture parameters of all sensors. The performances were further improved and very promising performances (r2) were obtained using the ratio of texture parameters (RADARSAT-2=0.91; PALSAR=0.823; PALSAR two-date=0.921; AVNIR-2=0.899; SPOT-5=0.916; AVNIR-2 + SPOT-5=0.939). These performances suggest four main contributions arising from this research, namely (i) biomass estimation can be significantly improved by using texture parameters, (ii) further improvements can be obtained using the ratio of texture parameters, (iii) multisensor texture parameters and their ratios have more potential than texture from a single sensor, and (iv) biomass can be accurately estimated far beyond the previously perceived saturation levels of SAR and optical data using texture parameters or the ratios of texture parameters. A further important contribution resulting from the fusion of SAR & optical images produced accuracies (r2) of 0.706 and 0.77 from the simple fusion, and the texture processing of the fused image, respectively. Although these performances were not as attractive as the performances obtained from the other four processing steps, the wavelet fusion procedure improved the saturation level of the optical (AVNIR-2) image very significantly after fusion with SAR, image. Keywords: biomass, climate change, SAR, optical, multisensors, RADARSAT-2, PALSAR, AVNIR-2, SPOT-5, texture measurement, ratio of texture parameters, wavelets, fusion, saturation

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.

Temporal evolution of soil moisture statistical fractal and controls by soil texture and regional groundwater flow

NASA Astrophysics Data System (ADS)

Ji, Xinye; Shen, Chaopeng; Riley, William J.

2015-12-01

Soil moisture statistical fractal is an important tool for downscaling remotely-sensed observations and has the potential to play a key role in multi-scale hydrologic modeling. The fractal was first introduced two decades ago, but relatively little is known regarding how its scaling exponents evolve in time in response to climatic forcings. Previous studies have neglected the process of moisture re-distribution due to regional groundwater flow. In this study we used a physically-based surface-subsurface processes model and numerical experiments to elucidate the patterns and controls of fractal temporal evolution in two U.S. Midwest basins. Groundwater flow was found to introduce large-scale spatial structure, thereby reducing the scaling exponents (τ), which has implications for the transferability of calibrated parameters to predict τ. However, the groundwater effects depend on complex interactions with other physical controls such as soil texture and land use. The fractal scaling exponents, while in general showing a seasonal mode that correlates with mean moisture content, display hysteresis after storm events that can be divided into three phases, consistent with literature findings: (a) wetting, (b) re-organizing, and (c) dry-down. Modeling experiments clearly show that the hysteresis is attributed to soil texture, whose "patchiness" is the primary contributing factor. We generalized phenomenological rules for the impacts of rainfall, soil texture, groundwater flow, and land use on τ evolution. Grid resolution has a mild influence on the results and there is a strong correlation between predictions of τ from different resolutions. Overall, our results suggest that groundwater flow should be given more consideration in studies of the soil moisture statistical fractal, especially in regions with a shallow water table.

SU-F-R-32: Evaluation of MRI Acquisition Parameter Variations On Texture Feature Extraction Using ACR Phantom

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

Xie, Y; Wang, J; Wang, C

Purpose: To investigate the sensitivity of classic texture features to variations of MRI acquisition parameters. Methods: This study was performed on American College of Radiology (ACR) MRI Accreditation Program Phantom. MR imaging was acquired on a GE 750 3T scanner with XRM explain gradient, employing a T1-weighted images (TR/TE=500/20ms) with the following parameters as the reference standard: number of signal average (NEX) = 1, matrix size = 256×256, flip angle = 90°, slice thickness = 5mm. The effect of the acquisition parameters on texture features with and without non-uniformity correction were investigated respectively, while all the other parameters were keptmore » as reference standard. Protocol parameters were set as follows: (a). NEX = 0.5, 2 and 4; (b).Phase encoding steps = 128, 160 and 192; (c). Matrix size = 128×128, 192×192 and 512×512. 32 classic texture features were generated using the classic gray level run length matrix (GLRLM) and gray level co-occurrence matrix (GLCOM) from each image data set. Normalized range ((maximum-minimum)/mean) was calculated to determine variation among the scans with different protocol parameters. Results: For different NEX, 31 out of 32 texture features’ range are within 10%. For different phase encoding steps, 31 out of 32 texture features’ range are within 10%. For different acquisition matrix size without non-uniformity correction, 14 out of 32 texture features’ range are within 10%; for different acquisition matrix size with non-uniformity correction, 16 out of 32 texture features’ range are within 10%. Conclusion: Initial results indicated that those texture features that range within 10% are less sensitive to variations in T1-weighted MRI acquisition parameters. This might suggest that certain texture features might be more reliable to be used as potential biomarkers in MR quantitative image analysis.« less

Constraints on texture zero and cofactor zero models for neutrino mass

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

Whisnant, K.; Liao, Jiajun; Marfatia, D.

2014-06-24

Imposing a texture or cofactor zero on the neutrino mass matrix reduces the number of independent parameters from nine to seven. Since five parameters have been measured, only two independent parameters would remain in such models. We find the allowed regions for single texture zero and single cofactor zero models. We also find strong similarities between single texture zero models with one mass hierarchy and single cofactor zero models with the opposite mass hierarchy. We show that this correspondence can be generalized to texture-zero and cofactor-zero models with the same homogeneous costraints on the elements and cofactors.

Statistical Approach To Extraction Of Texture In SAR

NASA Technical Reports Server (NTRS)

Rignot, Eric J.; Kwok, Ronald

1992-01-01

Improved statistical method of extraction of textural features in synthetic-aperture-radar (SAR) images takes account of effects of scheme used to sample raw SAR data, system noise, resolution of radar equipment, and speckle. Treatment of speckle incorporated into overall statistical treatment of speckle, system noise, and natural variations in texture. One computes speckle auto-correlation function from system transfer function that expresses effect of radar aperature and incorporates range and azimuth resolutions.

Texture analysis on the fluence map to evaluate the degree of modulation for volumetric modulated arc therapy

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

Park, So-Yeon; Institute of Radiation Medicine, Seoul National University Medical Research Center, Seoul 110-744; Biomedical Research Institute, Seoul National University College of Medicine, Seoul 110-744

Purpose: Texture analysis on fluence maps was performed to evaluate the degree of modulation for volumetric modulated arc therapy (VMAT) plans. Methods: A total of six textural features including angular second moment, inverse difference moment, contrast, variance, correlation, and entropy were calculated for fluence maps generated from 20 prostate and 20 head and neck VMAT plans. For each of the textural features, particular displacement distances (d) of 1, 5, and 10 were adopted. To investigate the deliverability of each VMAT plan, gamma passing rates of pretreatment quality assurance, and differences in modulating parameters such as multileaf collimator (MLC) positions, gantrymore » angles, and monitor units at each control point between VMAT plans and dynamic log files registered by the Linac control system during delivery were acquired. Furthermore, differences between the original VMAT plan and the plan reconstructed from the dynamic log files were also investigated. To test the performance of the textural features as indicators for the modulation degree of VMAT plans, Spearman’s rank correlation coefficients (r{sub s}) with the plan deliverability were calculated. For comparison purposes, conventional modulation indices for VMAT including the modulation complexity score for VMAT, leaf travel modulation complexity score, and modulation index supporting station parameter optimized radiation therapy (MI{sub SPORT}) were calculated, and their correlations were analyzed in the same way. Results: There was no particular textural feature which always showed superior correlations with every type of plan deliverability. Considering the results comprehensively, contrast (d = 1) and variance (d = 1) generally showed considerable correlations with every type of plan deliverability. These textural features always showed higher correlations to the plan deliverability than did the conventional modulation indices, except in the case of modulating parameter differences. The r{sub s} values of contrast to the global gamma passing rates with criteria of 2%/2 mm, 2%/1 mm, and 1%/2 mm were 0.536, 0.473, and 0.718, respectively. The respective values for variance were 0.551, 0.481, and 0.688. In the case of local gamma passing rates, the r{sub s} values of contrast were 0.547, 0.578, and 0.620, respectively, and those of variance were 0.519, 0.527, and 0.569. All of the r{sub s} values in those cases were statistically significant (p < 0.003). In the cases of global and local gamma passing rates, MI{sub SPORT} showed the highest correlations among the conventional modulation indices. For global passing rates, r{sub s} values of MI{sub SPORT} were −0.420, −0.330, and −0.632, respectively, and those for local passing rates were −0.455, −0.490 and −0.502. The values of r{sub s} of contrast, variance, and MI{sub SPORT} with the MLC errors were −0.863, −0.828, and 0.795, respectively, all with statistical significances (p < 0.001). The correlations with statistical significances between variance and dose-volumetric differences were observed more frequently than the others. Conclusions: The contrast (d = 1) and variance (d = 1) calculated from fluence maps of VMAT plans showed considerable correlations with the plan deliverability, indicating their potential use as indicators for assessing the degree of modulation of VMAT plans. Both contrast and variance consistently showed better performance than the conventional modulation indices for VMAT.« less

Patient-specific bronchoscopy visualization through BRDF estimation and disocclusion correction.

PubMed

Chung, Adrian J; Deligianni, Fani; Shah, Pallav; Wells, Athol; Yang, Guang-Zhong

2006-04-01

This paper presents an image-based method for virtual bronchoscope with photo-realistic rendering. The technique is based on recovering bidirectional reflectance distribution function (BRDF) parameters in an environment where the choice of viewing positions, directions, and illumination conditions are restricted. Video images of bronchoscopy examinations are combined with patient-specific three-dimensional (3-D) computed tomography data through two-dimensional (2-D)/3-D registration and shading model parameters are then recovered by exploiting the restricted lighting configurations imposed by the bronchoscope. With the proposed technique, the recovered BRDF is used to predict the expected shading intensity, allowing a texture map independent of lighting conditions to be extracted from each video frame. To correct for disocclusion artefacts, statistical texture synthesis was used to recreate the missing areas. New views not present in the original bronchoscopy video are rendered by evaluating the BRDF with different viewing and illumination parameters. This allows free navigation of the acquired 3-D model with enhanced photo-realism. To assess the practical value of the proposed technique, a detailed visual scoring that involves both real and rendered bronchoscope images is conducted.

Selecting relevant 3D image features of margin sharpness and texture for lung nodule retrieval.

PubMed

Ferreira, José Raniery; de Azevedo-Marques, Paulo Mazzoncini; Oliveira, Marcelo Costa

2017-03-01

Lung cancer is the leading cause of cancer-related deaths in the world. Its diagnosis is a challenge task to specialists due to several aspects on the classification of lung nodules. Therefore, it is important to integrate content-based image retrieval methods on the lung nodule classification process, since they are capable of retrieving similar cases from databases that were previously diagnosed. However, this mechanism depends on extracting relevant image features in order to obtain high efficiency. The goal of this paper is to perform the selection of 3D image features of margin sharpness and texture that can be relevant on the retrieval of similar cancerous and benign lung nodules. A total of 48 3D image attributes were extracted from the nodule volume. Border sharpness features were extracted from perpendicular lines drawn over the lesion boundary. Second-order texture features were extracted from a cooccurrence matrix. Relevant features were selected by a correlation-based method and a statistical significance analysis. Retrieval performance was assessed according to the nodule's potential malignancy on the 10 most similar cases and by the parameters of precision and recall. Statistical significant features reduced retrieval performance. Correlation-based method selected 2 margin sharpness attributes and 6 texture attributes and obtained higher precision compared to all 48 extracted features on similar nodule retrieval. Feature space dimensionality reduction of 83 % obtained higher retrieval performance and presented to be a computationaly low cost method of retrieving similar nodules for the diagnosis of lung cancer.

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

Summary statistics in auditory perception.

PubMed

McDermott, Josh H; Schemitsch, Michael; Simoncelli, Eero P

2013-04-01

Sensory signals are transduced at high resolution, but their structure must be stored in a more compact format. Here we provide evidence that the auditory system summarizes the temporal details of sounds using time-averaged statistics. We measured discrimination of 'sound textures' that were characterized by particular statistical properties, as normally result from the superposition of many acoustic features in auditory scenes. When listeners discriminated examples of different textures, performance improved with excerpt duration. In contrast, when listeners discriminated different examples of the same texture, performance declined with duration, a paradoxical result given that the information available for discrimination grows with duration. These results indicate that once these sounds are of moderate length, the brain's representation is limited to time-averaged statistics, which, for different examples of the same texture, converge to the same values with increasing duration. Such statistical representations produce good categorical discrimination, but limit the ability to discern temporal detail.

Textural feature calculated from segmental fluences as a modulation index for VMAT.

PubMed

Park, So-Yeon; Park, Jong Min; Kim, Jung-In; Kim, Hyoungnyoun; Kim, Il Han; Ye, Sung-Joon

2015-12-01

Textural features calculated from various segmental fluences of volumetric modulated arc therapy (VMAT) plans were optimized to enhance its performance to predict plan delivery accuracy. Twenty prostate and twenty head and neck VMAT plans were selected retrospectively. Fluences were generated for each VMAT plan by summations of segments at sequential groups of control points. The numbers of summed segments were 5, 10, 20, 45, 90, 178 and 356. For each fluence, we investigated 6 textural features: angular second moment, inverse difference moment, contrast, variance, correlation and entropy (particular displacement distances, d = 1, 5 and 10). Spearman's rank correlation coefficients (rs) were calculated between each textural feature and several different measures of VMAT delivery accuracy. The values of rs of contrast (d = 10) with 10 segments to both global and local gamma passing rates with 2%/2 mm were 0.666 (p <0.001) and 0.573 (p <0.001), respectively. It showed rs values of -0.895 (p <0.001) and 0.727 (p <0.001) to multi-leaf collimator positional errors and gantry angle errors during delivery, respectively. The number of statistically significant rs values (p <0.05) to the changes in dose-volumetric parameters during delivery was 14 among a total of 35 tested parameters. Contrast (d = 10) with 10 segments showed higher correlations to the VMAT delivery accuracy than did the conventional modulation indices. Copyright © 2015 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

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.

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.

Response evaluation of giant-cell tumor of bone treated by denosumab: Histogram and texture analysis of CT images.

PubMed

Yi, Jisook; Lee, Young Han; Kim, Sang Kyum; Kim, Seung Hyun; Song, Ho-Taek; Shin, Kyoo-Ho; Suh, Jin-Suck

2018-05-01

This study aimed to compare computed tomography (CT) features, including tumor size and textural and histogram measurements, of giant-cell tumors of bone (GCTBs) before and after denosumab treatment and determine their applicability in monitoring GCTB response to denosumab treatment. This retrospective study included eight patients (male, 3; female, 5; mean age, 33.4 years) diagnosed with GCTB, who had received treatment by denosumab and had undergone pre- and post-treatment non-contrast CT between January 2010 and December 2016. This study was approved by the institutional review board. Pre- and post-treatment size, histogram, and textural parameters of GCTBs were compared by the Wilcoxon signed-rank test. Pathological findings of five patients who underwent surgery after denosumab treatment were evaluated for assessment of treatment response. Relative to the baseline values, the tumor size had decreased, while the mean attenuation, standard deviation, entropy (all, P = 0.017), and skewness (P = 0.036) of the GCTBs had significantly increased post-treatment. Although the difference was statistically insignificant, the tumors also exhibited increased kurtosis, contrast, and inverse difference moment (P = 0.123, 0.327, and 0.575, respectively) post-treatment. Histologic findings revealed new bone formation and complete depletion or decrease in the number of osteoclast-like giant cells. The histogram and textural parameters of GCTBs changed significantly after denosumab treatment. Knowledge of the tendency towards increased mean attenuation and heterogeneity but increased local homogeneity in post-treatment CT histogram and textural features of GCTBs might aid in treatment planning and tumor response evaluation during denosumab treatment. Copyright © 2018. Published by Elsevier B.V.

Inferring Species Richness and Turnover by Statistical Multiresolution Texture Analysis of Satellite Imagery

PubMed Central

Convertino, Matteo; Mangoubi, Rami S.; Linkov, Igor; Lowry, Nathan C.; Desai, Mukund

2012-01-01

Background The quantification of species-richness and species-turnover is essential to effective monitoring of ecosystems. Wetland ecosystems are particularly in need of such monitoring due to their sensitivity to rainfall, water management and other external factors that affect hydrology, soil, and species patterns. A key challenge for environmental scientists is determining the linkage between natural and human stressors, and the effect of that linkage at the species level in space and time. We propose pixel intensity based Shannon entropy for estimating species-richness, and introduce a method based on statistical wavelet multiresolution texture analysis to quantitatively assess interseasonal and interannual species turnover. Methodology/Principal Findings We model satellite images of regions of interest as textures. We define a texture in an image as a spatial domain where the variations in pixel intensity across the image are both stochastic and multiscale. To compare two textures quantitatively, we first obtain a multiresolution wavelet decomposition of each. Either an appropriate probability density function (pdf) model for the coefficients at each subband is selected, and its parameters estimated, or, a non-parametric approach using histograms is adopted. We choose the former, where the wavelet coefficients of the multiresolution decomposition at each subband are modeled as samples from the generalized Gaussian pdf. We then obtain the joint pdf for the coefficients for all subbands, assuming independence across subbands; an approximation that simplifies the computational burden significantly without sacrificing the ability to statistically distinguish textures. We measure the difference between two textures' representative pdf's via the Kullback-Leibler divergence (KL). Species turnover, or diversity, is estimated using both this KL divergence and the difference in Shannon entropy. Additionally, we predict species richness, or diversity, based on the Shannon entropy of pixel intensity.To test our approach, we specifically use the green band of Landsat images for a water conservation area in the Florida Everglades. We validate our predictions against data of species occurrences for a twenty-eight years long period for both wet and dry seasons. Our method correctly predicts 73% of species richness. For species turnover, the newly proposed KL divergence prediction performance is near 100% accurate. This represents a significant improvement over the more conventional Shannon entropy difference, which provides 85% accuracy. Furthermore, we find that changes in soil and water patterns, as measured by fluctuations of the Shannon entropy for the red and blue bands respectively, are positively correlated with changes in vegetation. The fluctuations are smaller in the wet season when compared to the dry season. Conclusions/Significance Texture-based statistical multiresolution image analysis is a promising method for quantifying interseasonal differences and, consequently, the degree to which vegetation, soil, and water patterns vary. The proposed automated method for quantifying species richness and turnover can also provide analysis at higher spatial and temporal resolution than is currently obtainable from expensive monitoring campaigns, thus enabling more prompt, more cost effective inference and decision making support regarding anomalous variations in biodiversity. Additionally, a matrix-based visualization of the statistical multiresolution analysis is presented to facilitate both insight and quick recognition of anomalous data. PMID:23115629

High Power Picosecond Laser Surface Micro-texturing of H13 Tool Steel and Pattern Replication onto ABS Plastics via Injection Moulding

NASA Astrophysics Data System (ADS)

Otanocha, Omonigho B.; Li, Lin; Zhong, Shan; Liu, Zhu

2016-03-01

H13 tool steels are often used as dies and moulds for injection moulding of plastic components. Certain injection moulded components require micro-patterns on their surfaces in order to modify the physical properties of the components or for better mould release to reduce mould contamination. With these applications it is necessary to study micro-patterning to moulds and to ensure effective pattern transfer and replication onto the plastic component during moulding. In this paper, we report an investigation into high average powered (100 W) picosecond laser interactions with H13 tool steel during surface micro-patterning (texturing) and the subsequent pattern replication on ABS plastic material through injection moulding. Design of experiments and statistical modelling were used to understand the influences of laser pulse repetition rate, laser fluence, scanning velocity, and number of scans on the depth of cut, kerf width and heat affected zones (HAZ) size. The characteristics of the surface patterns are analysed. The process parameter interactions and significance of process parameters on the processing quality and efficiency are characterised. An optimum operating window is recommended. The transferred geometry is compared with the patterns generated on the dies. A discussion is made to explain the characteristics of laser texturing and pattern replication on plastics.

Mapping of bare soil surface parameters from TerraSAR-X radar images over a semi-arid region

NASA Astrophysics Data System (ADS)

Gorrab, A.; Zribi, M.; Baghdadi, N.; Lili Chabaane, Z.

2015-10-01

The goal of this paper is to analyze the sensitivity of X-band SAR (TerraSAR-X) signals as a function of different physical bare soil parameters (soil moisture, soil roughness), and to demonstrate that it is possible to estimate of both soil moisture and texture from the same experimental campaign, using a single radar signal configuration (one incidence angle, one polarization). Firstly, we analyzed statistically the relationships between X-band SAR (TerraSAR-X) backscattering signals function of soil moisture and different roughness parameters (the root mean square height Hrms, the Zs parameter and the Zg parameter) at HH polarization and for an incidence angle about 36°, over a semi-arid site in Tunisia (North Africa). Results have shown a high sensitivity of real radar data to the two soil parameters: roughness and moisture. A linear relationship is obtained between volumetric soil moisture and radar signal. A logarithmic correlation is observed between backscattering coefficient and all roughness parameters. The highest dynamic sensitivity is obtained with Zg parameter. Then, we proposed to retrieve of both soil moisture and texture using these multi-temporal X-band SAR images. Our approach is based on the change detection method and combines the seven radar images with different continuous thetaprobe measurements. To estimate soil moisture from X-band SAR data, we analyzed statistically the sensitivity between radar measurements and ground soil moisture derived from permanent thetaprobe stations. Our approaches are applied over bare soil class identified from an optical image SPOT / HRV acquired in the same period of measurements. Results have shown linear relationship for the radar signals as a function of volumetric soil moisture with high sensitivity about 0.21 dB/vol%. For estimation of change in soil moisture, we considered two options: (1) roughness variations during the three-month radar acquisition campaigns were not accounted for; (2) a simple correction for temporal variations in roughness was included. The results reveal a small improvement in the estimation of soil moisture when a correction for temporal variations in roughness is introduced. Finally, by considering the estimated temporal dynamics of soil moisture, a methodology is proposed for the retrieval of clay and sand content (expressed as percentages) in soil. Two empirical relationships were established between the mean moisture values retrieved from the seven acquired radar images and the two soil texture components over 36 test fields. Validation of the proposed approach was carried out over a second set of 34 fields, showing that highly accurate clay estimations can be achieved.

TU-F-12A-05: Sensitivity of Textural Features to 3D Vs. 4D FDG-PET/CT Imaging in NSCLC Patients

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

Yang, F; Nyflot, M; Bowen, S

2014-06-15

Purpose: Neighborhood Gray-level difference matrices (NGLDM) based texture parameters extracted from conventional (3D) 18F-FDG PET scans in patients with NSCLC have been previously shown to associate with response to chemoradiation and poorer patient outcome. However, the change in these parameters when utilizing respiratory-correlated (4D) FDG-PET scans has not yet been characterized for NSCLC. The Objectives: of this study was to assess the extent to which NGLDM-based texture parameters on 4D PET images vary with reference to values derived from 3D scans in NSCLC. Methods: Eight patients with newly diagnosed NSCLC treated with concomitant chemoradiotherapy were included in this study. 4Dmore » PET scans were reconstructed with OSEM-IR in 5 respiratory phase-binned images and corresponding CT data of each phase were employed for attenuation correction. NGLDM-based texture features, consisting of coarseness, contrast, busyness, complexity and strength, were evaluated for gross tumor volumes defined on 3D/4D PET scans by radiation oncologists. Variation of the obtained texture parameters over the respiratory cycle were examined with respect to values extracted from 3D scans. Results: Differences between texture parameters derived from 4D scans at different respiratory phases and those extracted from 3D scans ranged from −30% to 13% for coarseness, −12% to 40% for contrast, −5% to 50% for busyness, −7% to 38% for complexity, and −43% to 20% for strength. Furthermore, no evident correlations were observed between respiratory phase and 4D scan texture parameters. Conclusion: Results of the current study showed that NGLDM-based texture parameters varied considerably based on choice of 3D PET and 4D PET reconstruction of NSCLC patient images, indicating that standardized image acquisition and analysis protocols need to be established for clinical studies, especially multicenter clinical trials, intending to validate prognostic values of texture features for NSCLC.« less

Evaluation of efficacy of a bioresorbable membrane in the treatment of oral lichen planus

PubMed Central

Kapoor, Anoop; Sikri, Poonam; Grover, Vishakha; Malhotra, Ranjan; Sachdeva, Sonia

2014-01-01

Background: Gingival involvement is commonly seen in lichen planus, a chronic mucocutaneous inflammatory condition of the stratified squamous epithelia. It is often painful and may undergo malignant transformation and thus warrants early diagnosis and prompt treatment. The aim of this study is to evaluate the use of a bioresorbable membrane (Polyglactin 910) in the management of erosive lichen planus of gingiva. Materials and Methods: A split-mouth randomized controlled trial was carried out. Fifteen patients with identical bilateral lesions of lichen planus on gingiva were included in the study. Three parameters were selected for the clinical assessment of gingival lesions: Surface texture, color, and burning sensation. After complete oral prophylaxis, an excisional biopsy procedure was carried out for lesions on both sides, but on the experimental side, the biopsy procedure was combined with placement of the bioresorbable membrane. The statistical significance of intergroup differences in measurements was tested by using an independent sample t-test. A two-tailed P-value less than 0.05 was considered as statistically significant. Results: Intragroup comparisons revealed a statistically significant difference between mean value of grades at 6, 12, and 24 weeks in both groups for the surface texture, color, and burning sensation of gingiva, respectively. For intergroup comparison of change in surface texture, color, and burning sensation of gingiva between group A and group B, differences were statistically nonsignificant. Conclusion: Surgical management of the lesion accomplished significant improvement of lesion with no significant additional clinical benefits with the application of bioresorbable membrane. Worsening of baseline scores was not observed in any case at the end of the study. PMID:25097651

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.

Identification of low variability textural features for heterogeneity quantification of 18F-FDG PET/CT imaging.

PubMed

Cortes-Rodicio, J; Sanchez-Merino, G; Garcia-Fidalgo, M A; Tobalina-Larrea, I

To identify those textural features that are insensitive to both technical and biological factors in order to standardise heterogeneity studies on 18 F-FDG PET imaging. Two different studies were performed. First, nineteen series from a cylindrical phantom filled with different 18 F-FDG activity concentration were acquired and reconstructed using three different protocols. Seventy-two texture features were calculated inside a circular region of interest. The variability of each feature was obtained. Second, the data for 15 patients showing non-pathological liver were acquired. Anatomical and physiological features such as patient's weight, height, body mass index, metabolic active volume, blood glucose level, SUV and SUV standard deviation were also recorded. A liver covering region of interest was delineated and low variability textural features calculated in each patient. Finally, a multivariate Spearman's correlation analysis between biological factors and texture features was performed. Only eight texture features analysed show small variability (<5%) with activity concentration and reconstruction protocol making them suitable for heterogeneity quantification. On the other hand, there is a high statistically significant correlation between MAV and entropy (P<0.05). Entropy feature is, indeed, correlated (P<0.05) with all patient parameters, except body mass index. The textural features that are correlated with neither technical nor biological factors are run percentage, short-zone emphasis and intensity, making them suitable for quantifying functional changes or classifying patients. Other textural features are correlated with technical and biological factors and are, therefore, a source of errors if used for this purpose. Copyright © 2016 Elsevier España, S.L.U. y SEMNIM. All rights reserved.

Influence of Femtosecond Laser Parameters and Environment on Surface Texture Characteristics of Metals and Non-Metals - State of the Art

NASA Astrophysics Data System (ADS)

Bharatish, A.; Soundarapandian, S.

2018-04-01

Enhancing the surface functionality by ultrashort pulsed laser texturing has received the considerable attention from researchers in the past few decades. Femtosecond lasers are widely adopted since it provides high repeatability and reproducibility by minimizing the heat affected zone (HAZ) and other collateral damages to a great extent. The present paper reports some recent studies being made worldwide on femtosecond laser surface texturing of metals, ceramics, polymers, semiconductors, thinfilms and advanced nanocomposites. It presents the state of the art knowledge in femtosecond laser surface texturing and the potential of this technology to improve properties in terms of biological, tribological and wetting performance. Since the texture quality and functionality are enhanced by the proper selection of appropriate laser parameters and ambient conditions for individual application, reporting the influence of laser parameters on surface texture characteristics assume utmost importance.

Influence of Femtosecond Laser Parameters and Environment on Surface Texture Characteristics of Metals and Non-Metals - State of the Art

NASA Astrophysics Data System (ADS)

Bharatish, A.; Soundarapandian, S.

2018-06-01

Enhancing the surface functionality by ultrashort pulsed laser texturing has received the considerable attention from researchers in the past few decades. Femtosecond lasers are widely adopted since it provides high repeatability and reproducibility by minimizing the heat affected zone (HAZ) and other collateral damages to a great extent. The present paper reports some recent studies being made worldwide on femtosecond laser surface texturing of metals, ceramics, polymers, semiconductors, thinfilms and advanced nanocomposites. It presents the state of the art knowledge in femtosecond laser surface texturing and the potential of this technology to improve properties in terms of biological, tribological and wetting performance. Since the texture quality and functionality are enhanced by the proper selection of appropriate laser parameters and ambient conditions for individual application, reporting the influence of laser parameters on surface texture characteristics assume utmost importance.

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.

Physicochemical and sensory properties of fresh potato-based pasta (gnocchi).

PubMed

Alessandrini, Laura; Balestra, Federica; Romani, Santina; Rocculi, Pietro; Rosa, Marco Dalla

2010-01-01

This study dealt with the characterization and quality assessment of 3 kinds of potato-based pasta (gnocchi) made with steam-cooked, potato puree (water added to potato flakes), and reconstituted potatoes as main ingredients. The aim of the research was to evaluate the quality of the products in terms of physicochemical, textural, and sensory characteristics. Water content, water activity, color (L* and h°), and texture (texture profile analysis [TPA] and shearing test) were evaluated on both raw and cooked samples. In addition, on the recovered cooking water the loss of solid substances was determined and on the cooked gnocchi a sensory assessment was performed. Eight sensory attributes (yellowness, hardness, gumminess, adhesiveness, potato taste, sweet taste, flour taste, and sapidity) were investigated. Statistically significant differences among products were obtained, especially concerning textural properties. In fact, sample made with reconstituted potatoes and emulsifiers resulted the hardest (8.53 ± 1.22 N), the gummiest (2.90 ± 0.05 N), and the "chewiest" (2.90 ± 0.58 N) after cooking. Gnocchi made with potato puree or reconstituted potatoes significantly differed from the one produced with steam-cooked potatoes in terms of sensory properties (yellowness, hardness, flour taste, and sapidity). Pearson's correlation analysis between some textural instrumental and sensory parameters showed significant correlation coefficients (0.532 < r < 0.810). Score plot of principal component analysis (PCA) confirmed obtained results from physicochemical and sensory analyses, in terms of high discriminant capacity of colorimetric and textural characteristics. © 2010 Institute of Food Technologists®

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.

Relationship between the properties of raw and cooked spaghetti - new indices for pasta quality evaluation

NASA Astrophysics Data System (ADS)

Biernacka, Beata; Dziki, Dariusz; Różyło, Renata; Wójcik, Monika; Miś, Antoni; Romankiewicz, Daria; Krzysiak, Zbigniew

2018-04-01

The quality of pasta can be evaluated by measuring the characteristics which encompass the most important quality parameters, such as colour, cooking properties and texture. The aim of the study was to suggest new indices which can be used to evaluate the quality of pasta. For the tests, 15 samples of spaghetti (produced from either semolina or common wheat flour) were used. The bending test was performed for the determination of the strength properties of raw pasta, while the pasta colour parameters were evaluated via the Commission Internationale de l'Eclairage system. The pasta cooking test included the evaluation of optimum cooking time, weight increase index and cooking loss. The samples of cooked spaghetti were cut, and the parameters describing pasta texture were determined. Statistical analysis showed significant correlations (α = 0.05) between colour parameters (lightness and redness) and pasta ash content (R = -0.90 and 0.84, respectively). The mechanical properties of raw pasta correlated positively with pasta density. The strongest correlation was found between pasta density and flexural strength. The destruction force for raw spaghetti during the bending test correlated significantly and positively with the cutting force of the cooked pasta. The obtained correlations can be helpful in pasta quality evaluation.

Probing Majorana neutrino textures at DUNE

NASA Astrophysics Data System (ADS)

Bora, Kalpana; Borah, Debasish; Dutta, Debajyoti

2017-10-01

We study the possibility of probing different texture zero neutrino mass matrices at the long baseline neutrino experiment DUNE, particularly focusing on its sensitivity to the octant of atmospheric mixing angle θ23 and leptonic Dirac C P phase δcp. Assuming a diagonal charged lepton basis and Majorana nature of light neutrinos, we first classify the possible light neutrino mass matrices with one and two texture zeros and then numerically evaluate the parameter space which satisfies the texture zero conditions. Apart from using the latest global fit 3 σ values of neutrino oscillation parameters, we also use the latest bound on the sum of absolute neutrino masses (∑i |mi|) from the Planck mission data and the updated bound on effective neutrino mass Me e from neutrinoless double beta decay (0 ν β β ) experiments to find the allowed Majorana texture zero mass matrices. For the allowed texture zero mass matrices from all these constraints, we then feed the corresponding light neutrino parameter values satisfying the texture zero conditions into the numerical analysis in order to study the capability of DUNE to allow or exclude them once it starts taking data. We find that DUNE will be able to exclude some of these texture zero mass matrices which restrict (θ23-δcp) to a very specific range of values, depending on the values of the parameters that nature has chosen.

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.

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

Enamel surface topography analysis for diet discrimination. A methodology to enhance and select discriminative parameters

NASA Astrophysics Data System (ADS)

Francisco, Arthur; Blondel, Cécile; Brunetière, Noël; Ramdarshan, Anusha; Merceron, Gildas

2018-03-01

Tooth wear and, more specifically, dental microwear texture is a dietary proxy that has been used for years in vertebrate paleoecology and ecology. DMTA, dental microwear texture analysis, relies on a few parameters related to the surface complexity, anisotropy and heterogeneity of the enamel facets at the micrometric scale. Working with few but physically meaningful parameters helps in comparing published results and in defining levels for classification purposes. Other dental microwear approaches are based on ISO parameters and coupled with statistical tests to find the more relevant ones. The present study roughly utilizes most of the aforementioned parameters in their more or less modified form. But more than parameters, we here propose a new approach: instead of a single parameter characterizing the whole surface, we sample the surface and thus generate 9 derived parameters in order to broaden the parameter set. The identification of the most discriminative parameters is performed with an automated procedure which is an extended and refined version of the workflows encountered in some studies. The procedure in its initial form includes the most common tools, like the ANOVA and the correlation analysis, along with the required mathematical tests. The discrimination results show that a simplified form of the procedure is able to more efficiently identify the desired number of discriminative parameters. Also highlighted are some trends like the relevance of working with both height and spatial parameters, as well as the potential benefits of dimensionless surfaces. On a set of 45 surfaces issued from 45 specimens of three modern ruminants with differences in feeding preferences (grazing, leaf-browsing and fruit-eating), it is clearly shown that the level of wear discrimination is improved with the new methodology compared to the other ones.

Investigation into the Effects of Textural Properties on Cuttability Performance of a Chisel Tool

NASA Astrophysics Data System (ADS)

Tumac, Deniz; Copur, Hanifi; Balci, Cemal; Er, Selman; Avunduk, Emre

2018-04-01

The main objective of this study is to investigate the effect of textural properties of stones on cutting performance of a standard chisel tool. Therewithal, the relationships between textural properties and cutting performance parameters and physical and mechanical properties were statistically analyzed. For this purpose, physical and mechanical property tests and mineralogical and petrographic analyses were carried out on eighteen natural stone samples, which can be grouped into three fundamentally different geological origins, i.e., metamorphic, igneous, and sedimentary. Then, texture coefficient analyses were performed on the samples. To determine the cuttability of the stones; the samples were cut with a portable linear cutting machine using a standard chisel tool at different depths of cut in unrelieved (non-interactive) cutting mode. The average and maximum forces (normal and cutting) and specific energy were measured, and the obtained values were correlated with texture coefficient, packing weighting, and grain size. With reference to the relation between depth of cut and cutting performance of the chisel tool for three types of natural stone groups, specific energy decreases with increasing depth of cut, and cutting forces increase in proportion to the depth of cut. The same is observed for the relationship between packing weighting and both of specific energy and cutter forces. On the other hand, specific energy and the forces decrease while grain size increases. Based on the findings of the present study, texture coefficient has strong correlation with specific energy. Generally, the lower depth of cut values in cutting tests shows higher and more reliable correlations with texture coefficient than the increased depth of cut. The results of cutting tests show also that, at a lower depth of cut (less than 1.5 mm), even stronger correlations can be observed between texture coefficient and cutting performance. Experimental studies indicate that cutting performance of chisel tools can be predicted based on texture coefficients of the natural stones.

Role of morphometry in the cytological differentiation of benign and malignant thyroid lesions

PubMed Central

Khatri, Pallavi; Choudhury, Monisha; Jain, Manjula; Thomas, Shaji

2017-01-01

Context: Thyroid nodules represent a common problem, with an estimated prevalence of 4–7%. Although fine needle aspiration cytology (FNAC) has been accepted as a first line diagnostic test, the rate of false negative reports of malignancy is still high. Nuclear morphometry is the measurement of nuclear parameters by image analysis. Image analysis can merge the advantages of morphologic interpretation with those of quantitative data. Aims: To evaluate the nuclear morphometric parameters in fine needle aspirates of thyroid lesions and to study its role in differentiating benign from malignant thyroid lesions. Material and Methods: The study included 19 benign and 16 malignant thyroid lesions. Image analysis was performed on Giemsa-stained FNAC slides by Nikon NIS-Elements Advanced Research software (Version 4.00). Nuclear morphometric parameters analyzed included nuclear size, shape, texture, and density parameters. Statistical Analysis: Normally distributed continuous variables were compared using the unpaired t-test for two groups and analysis of variance was used for three or more groups. Tukey or Tamhane's T2 multiple comparison test was used to assess the differences between the individual groups. Categorical variables were analyzed using the chi square test. Results and Conclusion: Five out of the six nuclear size parameters as well as all the texture and density parameters studied were significant in distinguishing between benign and malignant thyroid lesions (P < 0.05). Cut-off values were derived to differentiate between benign and malignant cases. PMID:28182069

IDH mutation assessment of glioma using texture features of multimodal MR images

NASA Astrophysics Data System (ADS)

Zhang, Xi; Tian, Qiang; Wu, Yu-Xia; Xu, Xiao-Pan; Li, Bao-Juan; Liu, Yi-Xiong; Liu, Yang; Lu, Hong-Bing

2017-03-01

Purpose: To 1) find effective texture features from multimodal MRI that can distinguish IDH mutant and wild status, and 2) propose a radiomic strategy for preoperatively detecting IDH mutation patients with glioma. Materials and Methods: 152 patients with glioma were retrospectively included from the Cancer Genome Atlas. Corresponding T1-weighted image before- and post-contrast, T2-weighted image and fluid-attenuation inversion recovery image from the Cancer Imaging Archive were analyzed. Specific statistical tests were applied to analyze the different kind of baseline information of LrGG patients. Finally, 168 texture features were derived from multimodal MRI per patient. Then the support vector machine-based recursive feature elimination (SVM-RFE) and classification strategy was adopted to find the optimal feature subset and build the identification models for detecting the IDH mutation. Results: Among 152 patients, 92 and 60 were confirmed to be IDH-wild and mutant, respectively. Statistical analysis showed that the patients without IDH mutation was significant older than patients with IDH mutation (p<0.01), and the distribution of some histological subtypes was significant different between IDH wild and mutant groups (p<0.01). After SVM-RFE, 15 optimal features were determined for IDH mutation detection. The accuracy, sensitivity, specificity, and AUC after SVM-RFE and parameter optimization were 82.2%, 85.0%, 78.3%, and 0.841, respectively. Conclusion: This study presented a radiomic strategy for noninvasively discriminating IDH mutation of patients with glioma. It effectively incorporated kinds of texture features from multimodal MRI, and SVM-based classification strategy. Results suggested that features selected from SVM-RFE were more potential to identifying IDH mutation. The proposed radiomics strategy could facilitate the clinical decision making in patients with glioma.

Quantitative parameters of CT texture analysis as potential markersfor early prediction of spontaneous intracranial hemorrhage enlargement.

PubMed

Shen, Qijun; Shan, Yanna; Hu, Zhengyu; Chen, Wenhui; Yang, Bing; Han, Jing; Huang, Yanfang; Xu, Wen; Feng, Zhan

2018-04-30

To objectively quantify intracranial hematoma (ICH) enlargement by analysing the image texture of head CT scans and to provide objective and quantitative imaging parameters for predicting early hematoma enlargement. We retrospectively studied 108 ICH patients with baseline non-contrast computed tomography (NCCT) and 24-h follow-up CT available. Image data were assessed by a chief radiologist and a resident radiologist. Consistency analysis between observers was tested. The patients were divided into training set (75%) and validation set (25%) by stratified sampling. Patients in the training set were dichotomized according to 24-h hematoma expansion ≥ 33%. Using the Laplacian of Gaussian bandpass filter, we chose different anatomical spatial domains ranging from fine texture to coarse texture to obtain a series of derived parameters (mean grayscale intensity, variance, uniformity) in order to quantify and evaluate all data. The parameters were externally validated on validation set. Significant differences were found between the two groups of patients within variance at V 1.0 and in uniformity at U 1.0 , U 1.8 and U 2.5 . The intraclass correlation coefficients for the texture parameters were between 0.67 and 0.99. The area under the ROC curve between the two groups of ICH cases was between 0.77 and 0.92. The accuracy of validation set by CTTA was 0.59-0.85. NCCT texture analysis can objectively quantify the heterogeneity of ICH and independently predict early hematoma enlargement. • Heterogeneity is helpful in predicting ICH enlargement. • CTTA could play an important role in predicting early ICH enlargement. • After filtering, fine texture had the best diagnostic performance. • The histogram-based uniformity parameters can independently predict ICH enlargement. • CTTA is more objective, more comprehensive, more independently operable, than previous methods.

Enhancement of multimodality texture-based prediction models via optimization of PET and MR image acquisition protocols: a proof of concept

NASA Astrophysics Data System (ADS)

Vallières, Martin; Laberge, Sébastien; Diamant, André; El Naqa, Issam

2017-11-01

Texture-based radiomic models constructed from medical images have the potential to support cancer treatment management via personalized assessment of tumour aggressiveness. While the identification of stable texture features under varying imaging settings is crucial for the translation of radiomics analysis into routine clinical practice, we hypothesize in this work that a complementary optimization of image acquisition parameters prior to texture feature extraction could enhance the predictive performance of texture-based radiomic models. As a proof of concept, we evaluated the possibility of enhancing a model constructed for the early prediction of lung metastases in soft-tissue sarcomas by optimizing PET and MR image acquisition protocols via computerized simulations of image acquisitions with varying parameters. Simulated PET images from 30 STS patients were acquired by varying the extent of axial data combined per slice (‘span’). Simulated T 1-weighted and T 2-weighted MR images were acquired by varying the repetition time and echo time in a spin-echo pulse sequence, respectively. We analyzed the impact of the variations of PET and MR image acquisition parameters on individual textures, and we investigated how these variations could enhance the global response and the predictive properties of a texture-based model. Our results suggest that it is feasible to identify an optimal set of image acquisition parameters to improve prediction performance. The model constructed with textures extracted from simulated images acquired with a standard clinical set of acquisition parameters reached an average AUC of 0.84 +/- 0.01 in bootstrap testing experiments. In comparison, the model performance significantly increased using an optimal set of image acquisition parameters (p = 0.04 ), with an average AUC of 0.89 +/- 0.01 . Ultimately, specific acquisition protocols optimized to generate superior radiomics measurements for a given clinical problem could be developed and standardized via dedicated computer simulations and thereafter validated using clinical scanners.

Robust automatic line scratch detection in films.

PubMed

Newson, Alasdair; Almansa, Andrés; Gousseau, Yann; Pérez, Patrick

2014-03-01

Line scratch detection in old films is a particularly challenging problem due to the variable spatiotemporal characteristics of this defect. Some of the main problems include sensitivity to noise and texture, and false detections due to thin vertical structures belonging to the scene. We propose a robust and automatic algorithm for frame-by-frame line scratch detection in old films, as well as a temporal algorithm for the filtering of false detections. In the frame-by-frame algorithm, we relax some of the hypotheses used in previous algorithms in order to detect a wider variety of scratches. This step's robustness and lack of external parameters is ensured by the combined use of an a contrario methodology and local statistical estimation. In this manner, over-detection in textured or cluttered areas is greatly reduced. The temporal filtering algorithm eliminates false detections due to thin vertical structures by exploiting the coherence of their motion with that of the underlying scene. Experiments demonstrate the ability of the resulting detection procedure to deal with difficult situations, in particular in the presence of noise, texture, and slanted or partial scratches. Comparisons show significant advantages over previous work.

Automated diagnosis of epilepsy using CWT, HOS and texture parameters.

PubMed

Acharya, U Rajendra; Yanti, Ratna; Zheng, Jia Wei; Krishnan, M Muthu Rama; Tan, Jen Hong; Martis, Roshan Joy; Lim, Choo Min

2013-06-01

Epilepsy is a chronic brain disorder which manifests as recurrent seizures. Electroencephalogram (EEG) signals are generally analyzed to study the characteristics of epileptic seizures. In this work, we propose a method for the automated classification of EEG signals into normal, interictal and ictal classes using Continuous Wavelet Transform (CWT), Higher Order Spectra (HOS) and textures. First the CWT plot was obtained for the EEG signals and then the HOS and texture features were extracted from these plots. Then the statistically significant features were fed to four classifiers namely Decision Tree (DT), K-Nearest Neighbor (KNN), Probabilistic Neural Network (PNN) and Support Vector Machine (SVM) to select the best classifier. We observed that the SVM classifier with Radial Basis Function (RBF) kernel function yielded the best results with an average accuracy of 96%, average sensitivity of 96.9% and average specificity of 97% for 23.6 s duration of EEG data. Our proposed technique can be used as an automatic seizure monitoring software. It can also assist the doctors to cross check the efficacy of their prescribed drugs.

Sedimentary control of volcanic debris-avalanche structures and transformation into lahars

NASA Astrophysics Data System (ADS)

Bernard, Karine; van Wyk de Vries, Benjamin; Thouret, Jean-Claude; Roche, Olivier; Samaniego Eguiguren, Pablo

2017-04-01

Volcanic debris avalanche structures and related transformations into lahars have been extensively analysed in order to establish a sedimentary classification of the deposits. Textural and structural variations of eight debris-avalanche deposits (DADs) have been correlated with Shape Preferred Orientation of 30,000 clasts together with grain-size distributions and statistical parameters from 156 sieved matrix samples. Granular segregation patterns have been observed with structural fault controls: proximal granular-segregation structures of the Tutupaca DAD ridges in Peru, basal sheared bands along overthrust lateral levee (Mt. Dore, France), mixing and cataclasis of fault-controlled deposits in half-graben during lateral spreading of distal thrust lobe (Pichu-Pichu, Peru), neo-cataclasis at the frontal thrust lobe (Meager, Canada and Mt. Dore, France). A logarithmic regression characterises the % matrix vs. matrix/gravels showing proximal and primary cataclasis, hybrid DADs with polymodal matrix and mixed facies up to transformations into lahar (Misti, Mt Dore). The sequential fragmentation helps to distinguish DAD that belong to Andean and Cascade Volcanic arcs (Tutupaca and Misti, Peru; Meager, Canada) to the hybrid DADs, before distal transformation into lahars (Pichu-Pichu); and hydrovolcanic fragmentation characterises the transformed lahar deposits (Misti). The fractal values of 150 sieved samples range between 2.3 and 2.7, implying extensional fractures with granular disaggregation. Skewness vs. kurtosis values help to distinguish the proximal mass wasting deposits and the transformed deposits by dilution. The sorting vs. median values enable us to differentiate the hybrid DADs with the transformed deposits by dilution. The sedimentological statistical parameters with Shape Preferred Orientation analysis that have been correlated with textural and structural observations show textural fabrics resulting from kinematic processes: cataclasis, hybrid matrix facies and transformations. Inherited fractures from tectono-volcanic structures contribute to the particle size distributions of DAD and associated deposits such as pyroclastic and lahar deposits (Misti, Mt Dore, Tutupaca). The statistical results highlight granular structure and kinematic process of DAD transformations into lahars and associated deposits, which would contribute to understand the rheological process behind the excess DAD run-out and to test granular models for DAD transformations. Key words: volcanic debris-avalanche deposits, lahar transformation, structure, sedimentology, hazard

Automatic extraction of tree crowns from aerial imagery in urban environment

NASA Astrophysics Data System (ADS)

Liu, Jiahang; Li, Deren; Qin, Xunwen; Yang, Jianfeng

2006-10-01

Traditionally, field-based investigation is the main method to investigate greenbelt in urban environment, which is costly and low updating frequency. In higher resolution image, the imagery structure and texture of tree canopy has great similarity in statistics despite the great difference in configurations of tree canopy, and their surface structures and textures of tree crown are very different from the other types. In this paper, we present an automatic method to detect tree crowns using high resolution image in urban environment without any apriori knowledge. Our method catches unique structure and texture of tree crown surface, use variance and mathematical expectation of defined image window to position the candidate canopy blocks coarsely, then analysis their inner structure and texture to refine these candidate blocks. The possible spans of all the feature parameters used in our method automatically generate from the small number of samples, and HOLE and its distribution as an important characteristics are introduced into refining processing. Also the isotropy of candidate image block and holes' distribution is integrated in our method. After introduction the theory of our method, aerial imageries were used ( with a resolution about 0.3m ) to test our method, and the results indicate that our method is an effective approach to automatically detect tree crown in urban environment.

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

PubMed

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

2017-10-20

This study evaluated, for the first time, the efficacy of quantitative ultrasound (QUS) spectral parametric maps in conjunction with texture-analysis techniques to differentiate non-invasively benign versus malignant breast lesions. Ultrasound B-mode images and radiofrequency data were acquired from 78 patients with suspicious breast lesions. QUS spectral-analysis techniques were performed on radiofrequency data to generate parametric maps of mid-band fit, spectral slope, spectral intercept, spacing among scatterers, average scatterer diameter, and average acoustic concentration. Texture-analysis techniques were applied to determine imaging biomarkers consisting of mean, contrast, correlation, energy and homogeneity features of parametric maps. These biomarkers were utilized to classify benign versus malignant lesions with leave-one-patient-out cross-validation. Results were compared to histopathology findings from biopsy specimens and radiology reports on MR images to evaluate the accuracy of technique. Among the biomarkers investigated, one mean-value parameter and 14 textural features demonstrated statistically significant differences (p < 0.05) between the two lesion types. A hybrid biomarker developed using a stepwise feature selection method could classify the legions with a sensitivity of 96%, a specificity of 84%, and an AUC of 0.97. Findings from this study pave the way towards adapting novel QUS-based frameworks for breast cancer screening and rapid diagnosis in clinic.

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

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.

Textural features of dynamic contrast-enhanced MRI derived model-free and model-based parameter maps in glioma grading.

PubMed

Xie, Tian; Chen, Xiao; Fang, Jingqin; Kang, Houyi; Xue, Wei; Tong, Haipeng; Cao, Peng; Wang, Sumei; Yang, Yizeng; Zhang, Weiguo

2018-04-01

Presurgical glioma grading by dynamic contrast-enhanced MRI (DCE-MRI) has unresolved issues. The aim of this study was to investigate the ability of textural features derived from pharmacokinetic model-based or model-free parameter maps of DCE-MRI in discriminating between different grades of gliomas, and their correlation with pathological index. Retrospective. Forty-two adults with brain gliomas. 3.0T, including conventional anatomic sequences and DCE-MRI sequences (variable flip angle T1-weighted imaging and three-dimensional gradient echo volumetric imaging). Regions of interest on the cross-sectional images with maximal tumor lesion. Five commonly used textural features, including Energy, Entropy, Inertia, Correlation, and Inverse Difference Moment (IDM), were generated. All textural features of model-free parameters (initial area under curve [IAUC], maximal signal intensity [Max SI], maximal up-slope [Max Slope]) could effectively differentiate between grade II (n = 15), grade III (n = 13), and grade IV (n = 14) gliomas (P < 0.05). Two textural features, Entropy and IDM, of four DCE-MRI parameters, including Max SI, Max Slope (model-free parameters), vp (Extended Tofts), and vp (Patlak) could differentiate grade III and IV gliomas (P < 0.01) in four measurements. Both Entropy and IDM of Patlak-based K trans and vp could differentiate grade II (n = 15) from III (n = 13) gliomas (P < 0.01) in four measurements. No textural features of any DCE-MRI parameter maps could discriminate between subtypes of grade II and III gliomas (P < 0.05). Both Entropy and IDM of Extended Tofts- and Patlak-based vp showed highest area under curve in discriminating between grade III and IV gliomas. However, intraclass correlation coefficient (ICC) of these features revealed relatively lower inter-observer agreement. No significant correlation was found between microvascular density and textural features, compared with a moderate correlation found between cellular proliferation index and those features. Textural features of DCE-MRI parameter maps displayed a good ability in glioma grading. 3 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:1099-1111. © 2017 International Society for Magnetic Resonance in Medicine.

Experimental study of grain interactions on rolling texture development in face-centered cubic metals

NASA Astrophysics Data System (ADS)

Kumar Ray, Atish

There exists considerable debate in the texture community about whether grain interactions are a necessary factor to explain the development of deformation textures in polycrystalline metals. Computer simulations indicate that grain interactions play a significant role, while experimental evidence shows that the material type and starting orientation are more important in the development of texture and microstructure. A balanced review of the literature on face-centered cubic metals shows that the opposing viewpoints have developed due to the lack of any complete experimental study which considers both the intrinsic (material type and starting orientation) and extrinsic (grain interaction) factors. In this study, a novel method was developed to assemble ideally orientated crystalline aggregates in 99.99% aluminum (Al) or copper (Cu) to experimentally evaluate the effect of grain interactions on room temperature deformation texture. Ideal orientations relevant to face-centered cubic rolling textures, Cube {100} <001>, Goss {110} <001>, Brass {110} <11¯2> and Copper {112} <111¯> were paired in different combinations and deformed by plane strain compression to moderate strain levels of 1.0 to 1.5. Orientation dependent mechanical behavior was distinguishable from that of the neighbor-influenced behavior. In interacting crystals the constraint on the rolling direction shear strains (gammaXY , gammaXZ) was found to be most critical to show the effect of interactions via the evolution of local microstructure and microtexture. Interacting crystals with increasing deformations were observed to gradually rotate towards the S-component, {123} <634>. Apart from the average lattice reorientations, the interacting crystals also developed strong long-range orientation gradients inside the bulk of the crystal, which were identified as accumulating misorientations across the deformation boundaries. Based on a statistical procedure using quaternions, the orientation and interaction related heterogeneous deformations were characterized by three principal component vectors and their respective eigenvalues for both the orientation and misorientation distributions. For the case of a medium stacking fault energy metal like Cu, the texture and microstructure development depends wholly on the starting orientations. Microstructural instabilities in Cu are explained through a local slip clustering process, and the possible role of grain interactions on such instabilities is proposed. In contrast, the texture and microstructure development in a high stacking fault energy metal like Al is found to be dependent on the grain interactions. In general, orientation, grain interaction and material type were found to be key factors in the development of rolling textures in face-centered cubic metals and alloys. Moreso, in the texture development not any single parameter can be held responsible, rather, the interdependency of each of the three parameters must be considered. In this frame-work polycrystalline grains can be classified into four types according to their stability and susceptibility during deformation.

SU-E-I-85: Exploring the 18F-Fluorodeoxyglucose PET Characteristics in Staging of Esophageal Squamous Cell Carcinoma

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

Ma, C; Yin, Y

2014-06-01

Purpose: The aim of this study was to explore the characteristics derived from 18F-fluorodeoxyglucose (18F-FDG) PET image and assess its capacity in staging of esophageal squamous cell carcinoma (ESCC). Methods: 26 patients with newly diagnosed ESCC who underwent 18F-FDG PET scan were included in this study. Different image-derived indices including the standardized uptake value (SUV), gross tumor length, texture features and shape feature were considered. Taken the histopathologic examination as the gold standard, the extracted capacities of indices in staging of ESCC were assessed by Kruskal-Wallis test and Mann-Whitney test. Specificity and sensitivity for each of the studied parameters weremore » derived using receiver-operating characteristic curves. Results: 18F-FDG SUVmax and SUVmean showed statistically significant capability in AJCC and TNM stages. Texture features such as ENT and CORR were significant factors for N stages(p=0.040, p=0.029). Both FDG PET Longitudinal length and shape feature Eccentricity (EC) (p≤0.010) provided powerful stratification in the primary ESCC AJCC and TNM stages than SUV and texture features. Receiver-operating-characteristic curve analysis showed that tumor textural analysis can capability M stages with higher sensitivity than SUV measurement but lower in T and N stages. Conclusion: The 18F-FDG image-derived characteristics of SUV, textural features and shape feature allow for good stratification AJCC and TNM stage in ESCC patients.« less

Skin texture parameters of the dorsal hand in evaluating skin aging in China.

PubMed

Gao, Qian; Hu, Li-Wen; Wang, Yang; Xu, Wen-Ying; Ouyang, Nan-Ning; Dong, Guo-Qing; Shi, Song-Tian; Liu, Yang

2011-11-01

There are various non-invasive methods in skin morphology for assessing skin aging. The use of digital photography will make it easier and more convenient. In this study, we explored some skin texture parameters for evaluating skin aging using digital image processing. Two hundred and twenty-eight subjects who lived in Sanya, China, were involved. Individual sun exposure history and other factors influencing skin aging were collected by a questionnaire. Meanwhile, we took photos of their dorsal hands. Skin images were graded according to the Beagley-Gibson system. These skin images were also processed using image analysis software. Five skin texture parameters, Angle Num., Angle Max., Angle Diff., Distance and Grids, were produced in reference to the Beagley-Gibson system. All texture parameters were significantly associated with the Beagley-Gibson score. Among the parameters, the distance between primary lines (Distance) and the value of angle formed by intersection textures (Angle Max., Angle Diff.) were positively associated with the Beagley-Gibson score. However, there was a negative correlation between the number of grids (Grids), the number of angle (Angle Num.) and the Beagley-Gibson score. These texture parameters were also correlated with factors influencing skin aging such as sun exposure, age, smoking, drinking and body mass index. In multivariate analysis, Grids and Distance were mainly affected by age. But Angle Max. and Angle Diff. were mainly affected by sun exposure. It seemed that the skin surface morphologic parameters presented in our study reflect skin aging changes to some extent and could be used to describe skin aging using digital image processing. © 2011 John Wiley & Sons A/S.

Evidence Integration in Natural Acoustic Textures during Active and Passive Listening

PubMed Central

Rupp, Andre; Celikel, Tansu

2018-01-01

Abstract Many natural sounds can be well described on a statistical level, for example, wind, rain, or applause. Even though the spectro-temporal profile of these acoustic textures is highly dynamic, changes in their statistics are indicative of relevant changes in the environment. Here, we investigated the neural representation of change detection in natural textures in humans, and specifically addressed whether active task engagement is required for the neural representation of this change in statistics. Subjects listened to natural textures whose spectro-temporal statistics were modified at variable times by a variable amount. Subjects were instructed to either report the detection of changes (active) or to passively listen to the stimuli. A subset of passive subjects had performed the active task before (passive-aware vs passive-naive). Psychophysically, longer exposure to pre-change statistics was correlated with faster reaction times and better discrimination performance. EEG recordings revealed that the build-up rate and size of parieto-occipital (PO) potentials reflected change size and change time. Reduced effects were observed in the passive conditions. While P2 responses were comparable across conditions, slope and height of PO potentials scaled with task involvement. Neural source localization identified a parietal source as the main contributor of change-specific potentials, in addition to more limited contributions from auditory and frontal sources. In summary, the detection of statistical changes in natural acoustic textures is predominantly reflected in parietal locations both on the skull and source level. The scaling in magnitude across different levels of task involvement suggests a context-dependent degree of evidence integration. PMID:29662943

Evidence Integration in Natural Acoustic Textures during Active and Passive Listening.

PubMed

Górska, Urszula; Rupp, Andre; Boubenec, Yves; Celikel, Tansu; Englitz, Bernhard

2018-01-01

Many natural sounds can be well described on a statistical level, for example, wind, rain, or applause. Even though the spectro-temporal profile of these acoustic textures is highly dynamic, changes in their statistics are indicative of relevant changes in the environment. Here, we investigated the neural representation of change detection in natural textures in humans, and specifically addressed whether active task engagement is required for the neural representation of this change in statistics. Subjects listened to natural textures whose spectro-temporal statistics were modified at variable times by a variable amount. Subjects were instructed to either report the detection of changes (active) or to passively listen to the stimuli. A subset of passive subjects had performed the active task before (passive-aware vs passive-naive). Psychophysically, longer exposure to pre-change statistics was correlated with faster reaction times and better discrimination performance. EEG recordings revealed that the build-up rate and size of parieto-occipital (PO) potentials reflected change size and change time. Reduced effects were observed in the passive conditions. While P2 responses were comparable across conditions, slope and height of PO potentials scaled with task involvement. Neural source localization identified a parietal source as the main contributor of change-specific potentials, in addition to more limited contributions from auditory and frontal sources. In summary, the detection of statistical changes in natural acoustic textures is predominantly reflected in parietal locations both on the skull and source level. The scaling in magnitude across different levels of task involvement suggests a context-dependent degree of evidence integration.

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

PubMed

Neofytou, Marios S; Tanos, Vasilis; Pattichis, Marios S; Pattichis, Constantinos S; Kyriacou, Efthyvoulos C; Koutsouris, Dimitris D

2007-11-29

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

Texture as a basis for acoustic classification of substrate in the nearshore region

NASA Astrophysics Data System (ADS)

Dennison, A.; Wattrus, N. J.

2016-12-01

Segmentation and classification of substrate type from two locations in Lake Superior, are predicted using multivariate statistical processing of textural measures derived from shallow-water, high-resolution multibeam bathymetric data. During a multibeam sonar survey, both bathymetric and backscatter data are collected. It is well documented that the statistical characteristic of a sonar backscatter mosaic is dependent on substrate type. While classifying the bottom-type on the basis on backscatter alone can accurately predict and map bottom-type, it lacks the ability to resolve and capture fine textural details, an important factor in many habitat mapping studies. Statistical processing can capture the pertinent details about the bottom-type that are rich in textural information. Further multivariate statistical processing can then isolate characteristic features, and provide the basis for an accurate classification scheme. Preliminary results from an analysis of bathymetric data and ground-truth samples collected from the Amnicon River, Superior, Wisconsin, and the Lester River, Duluth, Minnesota, demonstrate the ability to process and develop a novel classification scheme of the bottom type in two geomorphologically distinct areas.

Alluvial substrate mapping by automated texture segmentation of recreational-grade side scan sonar imagery.

PubMed

Hamill, Daniel; Buscombe, Daniel; Wheaton, Joseph M

2018-01-01

Side scan sonar in low-cost 'fishfinder' systems has become popular in aquatic ecology and sedimentology for imaging submerged riverbed sediment at coverages and resolutions sufficient to relate bed texture to grain-size. Traditional methods to map bed texture (i.e. physical samples) are relatively high-cost and low spatial coverage compared to sonar, which can continuously image several kilometers of channel in a few hours. Towards a goal of automating the classification of bed habitat features, we investigate relationships between substrates and statistical descriptors of bed textures in side scan sonar echograms of alluvial deposits. We develop a method for automated segmentation of bed textures into between two to five grain-size classes. Second-order texture statistics are used in conjunction with a Gaussian Mixture Model to classify the heterogeneous bed into small homogeneous patches of sand, gravel, and boulders with an average accuracy of 80%, 49%, and 61%, respectively. Reach-averaged proportions of these sediment types were within 3% compared to similar maps derived from multibeam sonar.

Texture-based segmentation of temperate-zone woodland in panchromatic IKONOS imagery

NASA Astrophysics Data System (ADS)

Gagnon, Langis; Bugnet, Pierre; Cavayas, Francois

2003-08-01

We have performed a study to identify optimal texture parameters for woodland segmentation in a highly non-homogeneous urban area from a temperate-zone panchromatic IKONOS image. Texture images are produced with the sum- and difference-histograms depend on two parameters: window size f and displacement step p. The four texture features yielding the best discrimination between classes are the mean, contrast, correlation and standard deviation. The f-p combinations 17-1, 17-2, 35-1 and 35-2 are those which give the best performance, with an average classification rate of 90%.

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

A set of hypotheses on tribology of mammalian herbivore teeth

NASA Astrophysics Data System (ADS)

Kaiser, Thomas M.; Clauss, Marcus; Schulz-Kornas, Ellen

2016-03-01

Once erupted, mammal cheek teeth molars are continuously worn. Contact of molar surfaces with ingesta and with other teeth contribute to this wear. Microscopic wear features (dental surface texture) change continuously as new wear overprints old texture features. These features have been debated to indicate diet. The general assumption in relating occlusal textures to diet is that they are independent of masticatory movements and forces. If this assumption is not accepted, one needs to propose that occlusal textures comprise signals not only from the ‘last supper’ but also from masticatory events that represent ecological, species- or taxon-specific adaptations, and that occlusal textures therefore give a rather unspecific, somehow diet-related signal that is functionally inadequately understood. In order to test for mechanical mechanisms of wear, we created a hypothesis matrix that related sampled individuals with six tribological variables. Three variables represent mechanically relevant ingesta properties, and three represent animal-specific characteristics of the masticatory system. Three groups of mammal species (free ranging Cetartiodactyla and Perissodactyla, free ranging primates, and artificially fed rabbits) were investigated in terms of their 3D dental surface textures, which were quantified employing ten ISO 25178 surface texture parameters. We first formulated a set of specific predictions based on theoretical reflections on the effects of diet properties and animal characteristics, and subsequently performed discriminant analysis to test which parameters actually followed these predictions. We found that parameters Vvc, Vmc, Sp, Sq allowed the prediction of both, ingesta properties and properties of the masticatory system, if combined with other parameters. Sha, Sda and S5v had little predictive power in our dataset. Spd seemed rather unrelated to ingesta properties and made this parameter a suitable indicator of masticatory system properties.

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.

Variations in algorithm implementation among quantitative texture analysis software packages

NASA Astrophysics Data System (ADS)

Foy, Joseph J.; Mitta, Prerana; Nowosatka, Lauren R.; Mendel, Kayla R.; Li, Hui; Giger, Maryellen L.; Al-Hallaq, Hania; Armato, Samuel G.

2018-02-01

Open-source texture analysis software allows for the advancement of radiomics research. Variations in texture features, however, result from discrepancies in algorithm implementation. Anatomically matched regions of interest (ROIs) that captured normal breast parenchyma were placed in the magnetic resonance images (MRI) of 20 patients at two time points. Six first-order features and six gray-level co-occurrence matrix (GLCM) features were calculated for each ROI using four texture analysis packages. Features were extracted using package-specific default GLCM parameters and using GLCM parameters modified to yield the greatest consistency among packages. Relative change in the value of each feature between time points was calculated for each ROI. Distributions of relative feature value differences were compared across packages. Absolute agreement among feature values was quantified by the intra-class correlation coefficient. Among first-order features, significant differences were found for max, range, and mean, and only kurtosis showed poor agreement. All six second-order features showed significant differences using package-specific default GLCM parameters, and five second-order features showed poor agreement; with modified GLCM parameters, no significant differences among second-order features were found, and all second-order features showed poor agreement. While relative texture change discrepancies existed across packages, these differences were not significant when consistent parameters were used.

Texture classification using autoregressive filtering

NASA Technical Reports Server (NTRS)

Lawton, W. M.; Lee, M.

1984-01-01

A general theory of image texture models is proposed and its applicability to the problem of scene segmentation using texture classification is discussed. An algorithm, based on half-plane autoregressive filtering, which optimally utilizes second order statistics to discriminate between texture classes represented by arbitrary wide sense stationary random fields is described. Empirical results of applying this algorithm to natural and sysnthesized scenes are presented and future research is outlined.

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.

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.

Multi-scale radiomic analysis of sub-cortical regions in MRI related to autism, gender and age

NASA Astrophysics Data System (ADS)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2017-03-01

We propose using multi-scale image textures to investigate links between neuroanatomical regions and clinical variables in MRI. Texture features are derived at multiple scales of resolution based on the Laplacian-of-Gaussian (LoG) filter. Three quantifier functions (Average, Standard Deviation and Entropy) are used to summarize texture statistics within standard, automatically segmented neuroanatomical regions. Significance tests are performed to identify regional texture differences between ASD vs. TDC and male vs. female groups, as well as correlations with age (corrected p < 0.05). The open-access brain imaging data exchange (ABIDE) brain MRI dataset is used to evaluate texture features derived from 31 brain regions from 1112 subjects including 573 typically developing control (TDC, 99 females, 474 males) and 539 Autism spectrum disorder (ASD, 65 female and 474 male) subjects. Statistically significant texture differences between ASD vs. TDC groups are identified asymmetrically in the right hippocampus, left choroid-plexus and corpus callosum (CC), and symmetrically in the cerebellar white matter. Sex-related texture differences in TDC subjects are found in primarily in the left amygdala, left cerebellar white matter, and brain stem. Correlations between age and texture in TDC subjects are found in the thalamus-proper, caudate and pallidum, most exhibiting bilateral symmetry.

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.

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)

Texture and haptic cues in slant discrimination: reliability-based cue weighting without statistically optimal cue combination

NASA Astrophysics Data System (ADS)

Rosas, Pedro; Wagemans, Johan; Ernst, Marc O.; Wichmann, Felix A.

2005-05-01

A number of models of depth-cue combination suggest that the final depth percept results from a weighted average of independent depth estimates based on the different cues available. The weight of each cue in such an average is thought to depend on the reliability of each cue. In principle, such a depth estimation could be statistically optimal in the sense of producing the minimum-variance unbiased estimator that can be constructed from the available information. Here we test such models by using visual and haptic depth information. Different texture types produce differences in slant-discrimination performance, thus providing a means for testing a reliability-sensitive cue-combination model with texture as one of the cues to slant. Our results show that the weights for the cues were generally sensitive to their reliability but fell short of statistically optimal combination - we find reliability-based reweighting but not statistically optimal cue combination.

Identification of natural images and computer-generated graphics based on statistical and textural features.

PubMed

Peng, Fei; Li, Jiao-ting; Long, Min

2015-03-01

To discriminate the acquisition pipelines of digital images, a novel scheme for the identification of natural images and computer-generated graphics is proposed based on statistical and textural features. First, the differences between them are investigated from the view of statistics and texture, and 31 dimensions of feature are acquired for identification. Then, LIBSVM is used for the classification. Finally, the experimental results are presented. The results show that it can achieve an identification accuracy of 97.89% for computer-generated graphics, and an identification accuracy of 97.75% for natural images. The analyses also demonstrate the proposed method has excellent performance, compared with some existing methods based only on statistical features or other features. The method has a great potential to be implemented for the identification of natural images and computer-generated graphics. © 2014 American Academy of Forensic Sciences.

A research of selected textural features for detection of asbestos-cement roofing sheets using orthoimages

NASA Astrophysics Data System (ADS)

Książek, Judyta

2015-10-01

At present, there has been a great interest in the development of texture based image classification methods in many different areas. This study presents the results of research carried out to assess the usefulness of selected textural features for detection of asbestos-cement roofs in orthophotomap classification. Two different orthophotomaps of southern Poland (with ground resolution: 5 cm and 25 cm) were used. On both orthoimages representative samples for two classes: asbestos-cement roofing sheets and other roofing materials were selected. Estimation of texture analysis usefulness was conducted using machine learning methods based on decision trees (C5.0 algorithm). For this purpose, various sets of texture parameters were calculated in MaZda software. During the calculation of decision trees different numbers of texture parameters groups were considered. In order to obtain the best settings for decision trees models cross-validation was performed. Decision trees models with the lowest mean classification error were selected. The accuracy of the classification was held based on validation data sets, which were not used for the classification learning. For 5 cm ground resolution samples, the lowest mean classification error was 15.6%. The lowest mean classification error in the case of 25 cm ground resolution was 20.0%. The obtained results confirm potential usefulness of the texture parameter image processing for detection of asbestos-cement roofing sheets. In order to improve the accuracy another extended study should be considered in which additional textural features as well as spectral characteristics should be analyzed.

Characterization of Breast Implant Surfaces, Shapes, and Biomechanics: A Comparison of High Cohesive Anatomically Shaped Textured Silicone, Breast Implants from Three Different Manufacturers.

PubMed

Atlan, Michael; Bigerelle, Maxence; Larreta-garde, Véronique; Hindié, Mathilde; Hedén, Per

2016-02-01

Several companies offer anatomically shaped breast implants but differences among manufacturers are often misunderstood. The shell texture is a crucial parameter for anatomically shaped implants to prevent rotation and to decrease the risk of capsular contracture, even though concerns have recently been raised concerning the complications associated with textured breast implants. The aim of this study was to characterize differences in terms of texture, cell adhesion, shape, and stiffness between some commonly used anatomically shaped implants from three different manufacturers. Five commercially available anatomically shaped breast implants from 3 different manufacturers (Allergan, Mentor, and Sebbin) were used. Scanning electron microscopy, X-ray microtomography, and scanning mechanical microscopy were used to characterize the shell texture. Human fibroblast adhesion onto the shells was evaluated. 3D models of the implants were obtained using CT-scan acquisitions to analyze their shape. Implant stiffness was evaluated using a tractiometer. Major differences were observed in the topography of the textures of the shells, but this was not conveyed by a statistically significant fibroblast adhesion difference. However, fibroblasts adhered better on anatomically shaped textured implants than on smooth implants (p < 0.01). Our work pointed out differences in the Biocell® texture in comparison with older studies. The 3D analysis showed significant shape differences between the anatomically shaped implants of the 3 companies, despite similar dimensions. Implant stiffness was comparable among the 3 brands. Each texture had its specific topography, and this work is the first description of Sebbin anatomic breast implant texturation. Moreover, major discrepancies were found in the analysis of the Biocell® texture when comparing our results with previous reports. These differences may have clinical implications and are discussed. This study also highlighted major shape differences among breast implants from different manufacturers, which is quite counterintuitive. The clinical impact of these differences however needs further investigation. This journal requires that authors assign a level of evidence to each submission to which Evidence-Based Medicine rankings are applicable. This excludes Review Articles, Book Reviews, and manuscripts that concern Basic Science, Animal Studies, Cadaver Studies, and Experimental Studies. 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.

Spatial variation of corn canopy temperature as dependent upon soil texture and crop rooting characteristics

NASA Technical Reports Server (NTRS)

Choudhury, B. J.

1983-01-01

A soil plant atmosphere model for corn (Zea mays L.) together with the scaling theory for soil hydraulic heterogeneity are used to study the sensitivity of spatial variation of canopy temperature to field averaged soil texture and crop rooting characteristics. The soil plant atmosphere model explicitly solves a continuity equation for water flux resulting from root water uptake, changes in plant water storage and transpirational flux. Dynamical equations for root zone soil water potential and the plant water storage models the progressive drying of soil, and day time dehydration and night time hydration of the crop. The statistic of scaling parameter which describes the spatial variation of soil hydraulic conductivity and matric potential is assumed to be independent of soil texture class. The field averaged soil hydraulic characteristics are chosen to be representative of loamy sand and clay loam soils. Two rooting characteristics are chosen, one shallow and the other deep rooted. The simulation shows that the range of canopy temperatures in the clayey soil is less than 1K, but for the sandy soil the range is about 2.5 and 5.0 K, respectively, for the shallow and deep rooted crops.

Increasing the hydrophobicity degree of stonework by means of laser surface texturing: An application on Zimbabwe black granites

NASA Astrophysics Data System (ADS)

Chantada, A.; Penide, J.; Riveiro, A.; del Val, J.; Quintero, F.; Meixus, M.; Soto, R.; Lusquiños, F.; Pou, J.

2017-10-01

Tailoring the wetting characteristics of materials has gained much interest in applications related to surface cleaning in both industry and home. Zimbabwe black granite is a middle-to-fine-grained natural stone commonly used as countertops in kitchens and bathrooms. In this study, the laser texturing of Zimbabwe black granite surfaces is investigated with the aim to enhance its hydrophobic character, thus reducing the attachment of contaminants on the surface. Two laser sources (λ = 1064 and 532 nm) were used for this purpose. The treatment is based on the irradiation of the stone by a laser focused on the surface of the targeting sample. The influence of different laser processing parameters on the surface characteristics of granite (wettability, roughness, and chemistry) was statistically assessed. Most suitable laser processing parameters required to obtain the highest hydrophobicity degree were identified. It has been possible to identify the 532 nm laser wavelength as the most effective one to increase the hydrophobic degree of Zimbabwe black granite surface. The phenomenon governing wettability changes was found to be the surface roughness patterns, given the unaltered chemical surface composition after laser processing.

Alluvial substrate mapping by automated texture segmentation of recreational-grade side scan sonar imagery

PubMed Central

Buscombe, Daniel; Wheaton, Joseph M.

2018-01-01

Side scan sonar in low-cost ‘fishfinder’ systems has become popular in aquatic ecology and sedimentology for imaging submerged riverbed sediment at coverages and resolutions sufficient to relate bed texture to grain-size. Traditional methods to map bed texture (i.e. physical samples) are relatively high-cost and low spatial coverage compared to sonar, which can continuously image several kilometers of channel in a few hours. Towards a goal of automating the classification of bed habitat features, we investigate relationships between substrates and statistical descriptors of bed textures in side scan sonar echograms of alluvial deposits. We develop a method for automated segmentation of bed textures into between two to five grain-size classes. Second-order texture statistics are used in conjunction with a Gaussian Mixture Model to classify the heterogeneous bed into small homogeneous patches of sand, gravel, and boulders with an average accuracy of 80%, 49%, and 61%, respectively. Reach-averaged proportions of these sediment types were within 3% compared to similar maps derived from multibeam sonar. PMID:29538449

Impact of bimodal textural heterogeneity and connectivity on flow and transport through unsaturated mine waste rock

NASA Astrophysics Data System (ADS)

Appels, Willemijn M.; Ireson, Andrew M.; Barbour, S. Lee

2018-02-01

Mine waste rock dumps have highly variable flowpaths caused by contrasting textures and geometry of materials laid down during the 'plug dumping' process. Numerical experiments were conducted to investigate how these characteristics control unsaturated zone flow and transport. Hypothetical profiles of inner-lift structure were generated with multiple point statistics and populated with hydraulic parameters of a finer and coarser material. Early arrival of water and solutes at the bottom of the lifts was observed after spring snowmelt. The leaching efficiency, a measure of the proportion of a resident solute that is flushed out of the rock via infiltrating snowmelt or rainfall, was consistently high, but modified by the structure and texture of the lift. Under high rates of net percolation during snowmelt, preferential flow was generated in coarse textured part of the rock, and solutes in the fine textured parts of the rock remained stagnant. Under lower rates of net percolation during the summer and fall, finer materialswere flushed too, and the spatial variability of solute concentration in the lift was reduced. Layering of lifts leads to lower flow rates at depth, minimizing preferential flow and increased leaching of resident solutes. These findings highlight the limited role of large scale connected geometries on focusing flow and transport under dynamic surface net percolation conditions. As such, our findings agree with recent numerical results from soil studies with Gaussian connected geometries as well as recent experimental findings, emphasizing the dominant role of matrix flow and high leaching efficiency in large waste rock dumps.

Temporal and spatial evolution characteristics of gas-liquid two-phase flow pattern based on image texture spectrum descriptor

NASA Astrophysics Data System (ADS)

Zhou, Xi-Guo; Jin, Ning-De; Wang, Zhen-Ya; Zhang, Wen-Yin

2009-11-01

The dynamic image information of typical gas-liquid two-phase flow patterns in vertical upward pipe is captured by a highspeed dynamic camera. The texture spectrum descriptor is used to describe the texture characteristics of the processed images whose content is represented in the form of texture spectrum histogram, and four time-varying characteristic parameter indexes which represent image texture structure of different flow patterns are extracted. The study results show that the amplitude fluctuation of texture characteristic parameter indexes of bubble flow is lowest and shows very random complex dynamic behavior; the amplitude fluctuation of slug flow is higher and shows intermittent motion behavior between gas slug and liquid slug, and the amplitude fluctuation of churn flow is the highest and shows better periodicity; the amplitude fluctuation of bubble-slug flow is from low to high and oscillating frequence is higher than that of slug flow, and includes the features of both slug flow and bubble flow; the slug-churn flow loses the periodicity of slug flow and churn flow, and the amplitude fluctuation is high. The results indicate that the image texture characteristic parameter indexes of different flow pattern can reflect the flow characteristics of gas-liquid two-phase flow, which provides a new approach to understand the temporal and spatial evolution of flow pattern dynamics.

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.

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

Bagher-Ebadian, H; Chetty, I; Liu, C

Purpose: To examine the impact of image smoothing and noise on the robustness of textural information extracted from CBCT images for prediction of radiotherapy response for patients with head/neck (H/N) cancers. Methods: CBCT image datasets for 14 patients with H/N cancer treated with radiation (70 Gy in 35 fractions) were investigated. A deformable registration algorithm was used to fuse planning CT’s to CBCT’s. Tumor volume was automatically segmented on each CBCT image dataset. Local control at 1-year was used to classify 8 patients as responders (R), and 6 as non-responders (NR). A smoothing filter [2D Adaptive Weiner (2DAW) with 3more » different windows (ψ=3, 5, and 7)], and two noise models (Poisson and Gaussian, SNR=25) were implemented, and independently applied to CBCT images. Twenty-two textural features, describing the spatial arrangement of voxel intensities calculated from gray-level co-occurrence matrices, were extracted for all tumor volumes. Results: Relative to CBCT images without smoothing, none of 22 textural features extracted showed any significant differences when smoothing was applied (using the 2DAW with filtering parameters of ψ=3 and 5), in the responder and non-responder groups. When smoothing, 2DAW with ψ=7 was applied, one textural feature, Information Measure of Correlation, was significantly different relative to no smoothing. Only 4 features (Energy, Entropy, Homogeneity, and Maximum-Probability) were found to be statistically different between the R and NR groups (Table 1). These features remained statistically significant discriminators for R and NR groups in presence of noise and smoothing. Conclusion: This preliminary work suggests that textural classifiers for response prediction, extracted from H&N CBCT images, are robust to low-power noise and low-pass filtering. While other types of filters will alter the spatial frequencies differently, these results are promising. The current study is subject to Type II errors. A much larger cohort of patients is needed to confirm these results. This work was supported in part by a grant from Varian Medical Systems (Palo Alto, CA)« less

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.

Spatial prediction of soil texture in region Centre (France) from summary data

NASA Astrophysics Data System (ADS)

Dobarco, Mercedes Roman; Saby, Nicolas; Paroissien, Jean-Baptiste; Orton, Tom G.

2015-04-01

Soil texture is a key controlling factor of important soil functions like water and nutrient holding capacity, retention of pollutants, drainage, soil biodiversity, and C cycling. High resolution soil texture maps enhance our understanding of the spatial distribution of soil properties and provide valuable information for decision making and crop management, environmental protection, and hydrological planning. We predicted the soil texture of agricultural topsoils in the Region Centre (France) combining regression and area-to-point kriging. Soil texture data was collected from the French soil-test database (BDAT), which is populated with soil analysis performed by farmers' demand. To protect the anonymity of the farms the data was treated by commune. In a first step, summary statistics of environmental covariates by commune were used to develop prediction models with Cubist, boosted regression trees, and random forests. In a second step the residuals of each individual observation were summarized by commune and kriged following the method developed by Orton et al. (2012). This approach allowed to include non-linear relationships among covariates and soil texture while accounting for the uncertainty on areal means in the area-to-point kriging step. Independent validation of the models was done using data from the systematic soil monitoring network of French soils. Future work will compare the performance of these models with a non-stationary variance geostatistical model using the most important covariates and summary statistics of texture data. The results will inform on whether the later and statistically more-challenging approach improves significantly texture predictions or whether the more simple area-to-point regression kriging can offer satisfactory results. The application of area-to-point regression kriging at national level using BDAT data has the potential to improve soil texture predictions for agricultural topsoils, especially when combined with existing maps (i.e., model ensemble).

Differentiating malignant from benign breast tumors on acoustic radiation force impulse imaging using fuzzy-based neural networks with principle component analysis

NASA Astrophysics Data System (ADS)

Liu, Hsiao-Chuan; Chou, Yi-Hong; Tiu, Chui-Mei; Hsieh, Chi-Wen; Liu, Brent; Shung, K. Kirk

2017-03-01

Many modalities have been developed as screening tools for breast cancer. A new screening method called acoustic radiation force impulse (ARFI) imaging was created for distinguishing breast lesions based on localized tissue displacement. This displacement was quantitated by virtual touch tissue imaging (VTI). However, VTIs sometimes express reverse results to intensity information in clinical observation. In the study, a fuzzy-based neural network with principle component analysis (PCA) was proposed to differentiate texture patterns of malignant breast from benign tumors. Eighty VTIs were randomly retrospected. Thirty four patients were determined as BI-RADS category 2 or 3, and the rest of them were determined as BI-RADS category 4 or 5 by two leading radiologists. Morphological method and Boolean algebra were performed as the image preprocessing to acquire region of interests (ROIs) on VTIs. Twenty four quantitative parameters deriving from first-order statistics (FOS), fractal dimension and gray level co-occurrence matrix (GLCM) were utilized to analyze the texture pattern of breast tumors on VTIs. PCA was employed to reduce the dimension of features. Fuzzy-based neural network as a classifier to differentiate malignant from benign breast tumors. Independent samples test was used to examine the significance of the difference between benign and malignant breast tumors. The area Az under the receiver operator characteristic (ROC) curve, sensitivity, specificity and accuracy were calculated to evaluate the performance of the system. Most all of texture parameters present significant difference between malignant and benign tumors with p-value of less than 0.05 except the average of fractal dimension. For all features classified by fuzzy-based neural network, the sensitivity, specificity, accuracy and Az were 95.7%, 97.1%, 95% and 0.964, respectively. However, the sensitivity, specificity, accuracy and Az can be increased to 100%, 97.1%, 98.8% and 0.985, respectively if PCA was performed to reduce the dimension of features. Patterns of breast tumors on VTIs can effectively be recognized by quantitative texture parameters, and differentiated malignant from benign lesions by fuzzy-based neural network with PCA.

Human (Homo sapiens) facial attractiveness in relation to skin texture and color.

PubMed

Fink, B; Grammer, K; Thornhill, R

2001-03-01

The notion that surface texture may provide important information about the geometry of visible surfaces has attracted considerable attention for a long time. The present study shows that skin texture plays a significant role in the judgment of female facial beauty. Following research in clinical dermatology, the authors developed a computer program that implemented an algorithm based on co-occurrence matrices for the analysis of facial skin texture. Homogeneity and contrast features as well as color parameters were extracted out of stimulus faces. Attractiveness ratings of the images made by male participants relate positively to parameters of skin homogeneity. The authors propose that skin texture is a cue to fertility and health. In contrast to some previous studies, the authors found that dark skin, not light skin, was rated as most attractive.

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

PubMed

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

2017-05-01

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

Effect of divergent selection for intramuscular fat on sensory traits and instrumental texture in rabbit meat.

PubMed

Martínez-Álvaroi, M; Penalba, V; Blasco, A; Hernández, P

2016-12-01

Intramuscular fat (IMF) is one of the main parameters affecting meat quality. This work analyzes the effect of selection for IMF on sensory attributes and instrumental texture parameters in rabbit meat. A total of 115 rabbits after 6 generations of divergent selection for IMF were slaughtered at 9 or 13 wk (57 and 58 animals, respectively). For each animal, the left longissimus dorsi muscle (LD) was analyzed by near-infrared spectroscopy to measure IMF whereas the right LD was used for the sensory or instrumental texture analysis. Sensory attributes measured were rabbit odor, liver odor, rabbit flavor, liver flavor, aniseed flavor, hardness, juiciness, and fibrousness. The instrumental texture parameters maximum shear force, shear firmness, and total work to cut the sample were measured by a Warner-Bratzler shear test. The line selected for high IMF showed 58% greater IMF than the line selected for low IMF. This divergence affected firmness that was 9.9% greater in the low-IMF line, although no effect was found for the other instrumental texture traits. No effect of selection was observed in any odor or flavor, except for aniseed flavor, which was greater in the high-IMF line than in the low-IMF line. Age had an effect on IMF, instrumental texture parameters, and sensory attributes. Rabbits at 13 wk showed greater IMF and instrumental and sensory hardness and more intense odor and flavor and lower juiciness than rabbits at 9 wk.

Analyzing and improving surface texture by dual-rotation magnetorheological finishing

NASA Astrophysics Data System (ADS)

Wang, Yuyue; Zhang, Yun; Feng, Zhijing

2016-01-01

The main advantages of magnetorheological finishing (MRF) are its high convergence rate of surface error, the ability of polishing aspheric surfaces and nearly no subsurface damage. However, common MRF produces directional surface texture due to the constant flow direction of the magnetorheological (MR) polishing fluid. This paper studies the mechanism of surface texture formation by texture modeling. Dual-rotation magnetorheological finishing (DRMRF) is presented to suppress directional surface texture after analyzing the results of the texture model for common MRF. The results of the surface texture model for DRMRF and the proposed quantitative method based on mathematical statistics indicate the effective suppression of directional surface texture. An experimental setup is developed and experiments show directional surface texture and no directional surface texture in common MRF and DRMRF, respectively. As a result, the surface roughness of DRMRF is 0.578 nm (root-mean-square value) which is lower than 1.109 nm in common MRF.

Textural and viscoelastic properties of pork frankfurters containing canola-olive oils, rice bran, and walnut.

PubMed

Álvarez, D; Xiong, Y L; Castillo, M; Payne, F A; Garrido, M D

2012-09-01

Textural, rheological and microstructural properties of frankfurters made with 20% pork backfat, 20% canola or 20% canola-olive (3:1) oils, including rice bran (RB) and walnut extract (WE) as macronutrients (2.5%) were investigated. Textural parameters, including hardness, gumminess and rupture-force, were highly (P<0.05) influenced by the fat-oil composition. Addition of RB or WE in vegetable oil emulsions improved textural consistency (P<0.05). However, RB addition reduced gelling capacity, suggesting antagonistic interactions between fiber and oil droplets. Vegetable oil addition favored gel network formation, and, when combined with WE, showed the highest improvement of gel elasticity. These textural and gelling properties were corroborated by frankfurter micrographs, which revealed interactions between vegetable oils, RB, or WE with protein matrix and fat globules affecting these parameters. The results suggest that functional plant-derived ingredients can be valuable to the modification of frankfurter formulations for improved nutrition and as well as textural quality. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

PubMed

González-Tomás, L; Costell, E

2006-12-01

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

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

NASA Astrophysics Data System (ADS)

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

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

A procedure for classifying textural facies in gravel‐bed rivers

USGS Publications Warehouse

Buffington, John M.; Montgomery, David R.

1999-01-01

Textural patches (i.e., grain‐size facies) are commonly observed in gravel‐bed channels and are of significance for both physical and biological processes at subreach scales. We present a general framework for classifying textural patches that allows modification for particular study goals, while maintaining a basic degree of standardization. Textures are classified using a two‐tier system of ternary diagrams that identifies the relative abundance of major size classes and subcategories of the dominant size. An iterative procedure of visual identification and quantitative grain‐size measurement is used. A field test of our classification indicates that it affords reasonable statistical discrimination of median grain size and variance of bed‐surface textures. We also explore the compromise between classification simplicity and accuracy. We find that statistically meaningful textural discrimination requires use of both tiers of our classification. Furthermore, we find that simplified variants of the two‐tier scheme are less accurate but may be more practical for field studies which do not require a high level of textural discrimination or detailed description of grain‐size distributions. Facies maps provide a natural template for stratifying other physical and biological measurements and produce a retrievable and versatile database that can be used as a component of channel monitoring efforts.

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

Influence of extrusion-cooking parameters on some quality aspects of precooked pasta-like products.

PubMed

Wójtowicz, A; Mościcki, L

2009-06-01

The present article aims to evaluate some quality parameters and texture characteristics of precooked wheat pasta-like products. Using the methods for pasta and instant noodles the tested parameters were water absorption, starch gelatinization degree, cooking losses, and hardness. The texture profile was characterized using Zwick apparatus by cutting test with the head speed of 10 mm/min and expressed as hardness and firmness of hydrated products. SEM pictures were used to illustrate the internal structure of dry and cooked pasta-like products. Dough moisture content and process conditions influenced all tested quality parameters of the pasta-like products processed on a modified single screw extrusion-cooker TS-45 with L: D = 16: 1. Good organoleptical quality (notes higher than 4 in a 5-point scale) and firm texture were observed for common wheat flour pasta processed at 30% m.c. Hardness and firmness of hydrated products lowered with a longer hydration time in hot water. The firmest texture and low stickiness was observed for products with a highest starch gelatinization degree.

Optimization of VPSC Model Parameters for Two-Phase Titanium Alloys: Flow Stress Vs Orientation Distribution Function Metrics

NASA Astrophysics Data System (ADS)

Miller, V. M.; Semiatin, S. L.; Szczepanski, C.; Pilchak, A. L.

2018-06-01

The ability to predict the evolution of crystallographic texture during hot work of titanium alloys in the α + β temperature regime is greatly significant to numerous engineering disciplines; however, research efforts are complicated by the rapid changes in phase volume fractions and flow stresses with temperature in addition to topological considerations. The viscoplastic self-consistent (VPSC) polycrystal plasticity model is employed to simulate deformation in the two phase field. Newly developed parameter selection schemes utilizing automated optimization based on two different error metrics are considered. In the first optimization scheme, which is commonly used in the literature, the VPSC parameters are selected based on the quality of fit between experiment and simulated flow curves at six hot-working temperatures. Under the second newly developed scheme, parameters are selected to minimize the difference between the simulated and experimentally measured α textures after accounting for the β → α transformation upon cooling. It is demonstrated that both methods result in good qualitative matches for the experimental α phase texture, but texture-based optimization results in a substantially better quantitative orientation distribution function match.

TU-F-CAMPUS-J-04: Impact of Voxel Anisotropy On Statistic Texture Features of Oncologic PET: A Simulation Study

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

Yang, F; Byrd, D; Bowen, S

2015-06-15

Purpose: Texture metrics extracted from oncologic PET have been investigated with respect to their usefulness as definitive indicants for prognosis in a variety of cancer. Metric calculation is often based on cubic voxels. Most commonly used PET scanners, however, produce rectangular voxels, which may change texture metrics. The objective of this study was to examine the variability of PET texture feature metrics resulting from voxel anisotropy. Methods: Sinograms of NEMA NU-2 phantom for 18F-FDG were simulated using the ASIM simulation tool. The obtained projection data was reconstructed (3D-OSEM) on grids of cubic and rectangular voxels, producing PET images of resolutionmore » of 2.73x2.73x3.27mm3 and 3.27x3.27x3.27mm3, respectively. An interpolated dataset obtained from resampling the rectangular voxel data for isotropic voxel dimension (3.27mm) was also considered. For each image dataset, 28 texture parameters based on grey-level co-occurrence matrices (GLCOM), intensity histograms (GLIH), neighborhood difference matrices (GLNDM), and zone size matrices (GLZSM) were evaluated within lesions of diameter of 33, 28, 22, and 17mm. Results: In reference to the isotopic image data, texture features appearing on the rectangular voxel data varied with a range of -34-10% for GLCOM based, -31-39% for GLIH based, -80 -161% for GLNDM based, and −6–45% for GLZSM based while varied with a range of -35-23% for GLCOM based, -27-35% for GLIH based, -65-86% for GLNDM based, and -22 -18% for GLZSM based for the interpolated image data. For the anisotropic data, GLNDM-cplx exhibited the largest extent of variation (161%) while GLZSM-zp showed the least (<1%). As to the interpolated data, GLNDM-busy varied the most (86%) while GLIH-engy varied the least (<1%). Conclusion: Variability of texture appearance on oncologic PET with respect to voxel representation is substantial and feature-dependent. It necessitates consideration of standardized voxel representation for inter-institution studies attempting to validate prognostic values of PET texture features in cancer treatment.« less

Piezoelectric textured ceramics: Effective properties and application to ultrasonic transducers.

PubMed

Levassort, Franck; Pham Thi, Mai; Hemery, Henry; Marechal, Pierre; Tran-Huu-Hue, Louis-Pascal; Lethiecq, Marc

2006-12-22

Piezoelectric textured ceramics obtained by homo-template grain growth (HTGG) were recently demonstrated. A simple model with several assumptions has been used to calculate effective parameters of these new materials. Different connectivities have been simulated to show that spatial arrangements between the considered phases have little influence on the effective parameters, even through the 3-0 connectivity delivers the highest electromechanical thickness factor. A transducer based on a textured ceramic sample has been fabricated and characterised to show the efficiency of these piezoelectric materials. Finally, in a single element transducer configuration, simulation shows an improvement of 2 dB sensitivity for a transducer made with textured ceramic in comparison with a similar transducer design based on standard soft PZT (at equivalent bandwidths).

Assessing quality of citizen scientists’ soil texture estimates to evaluate land potential

USDA-ARS?s Scientific Manuscript database

Texture influences nearly all soil processes and is often the most measured parameter in soil science. Estimating soil texture is a universal and fundamental practice applied by resource scientists to classify and understand the behavior and management of soil systems. While trained soil scientist c...

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

NASA Astrophysics Data System (ADS)

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

1994-11-01

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

Texture Classification by Texton: Statistical versus Binary

PubMed Central

Guo, Zhenhua; Zhang, Zhongcheng; Li, Xiu; Li, Qin; You, Jane

2014-01-01

Using statistical textons for texture classification has shown great success recently. The maximal response 8 (Statistical_MR8), image patch (Statistical_Joint) and locally invariant fractal (Statistical_Fractal) are typical statistical texton algorithms and state-of-the-art texture classification methods. However, there are two limitations when using these methods. First, it needs a training stage to build a texton library, thus the recognition accuracy will be highly depended on the training samples; second, during feature extraction, local feature is assigned to a texton by searching for the nearest texton in the whole library, which is time consuming when the library size is big and the dimension of feature is high. To address the above two issues, in this paper, three binary texton counterpart methods were proposed, Binary_MR8, Binary_Joint, and Binary_Fractal. These methods do not require any training step but encode local feature into binary representation directly. The experimental results on the CUReT, UIUC and KTH-TIPS databases show that binary texton could get sound results with fast feature extraction, especially when the image size is not big and the quality of image is not poor. PMID:24520346

THE MEASUREMENT OF BONE QUALITY USING GRAY LEVEL CO-OCCURRENCE MATRIX TEXTURAL FEATURES.

PubMed

Shirvaikar, Mukul; Huang, Ning; Dong, Xuanliang Neil

2016-10-01

In this paper, statistical methods for the estimation of bone quality to predict the risk of fracture are reported. Bone mineral density and bone architecture properties are the main contributors of bone quality. Dual-energy X-ray Absorptiometry (DXA) is the traditional clinical measurement technique for bone mineral density, but does not include architectural information to enhance the prediction of bone fragility. Other modalities are not practical due to cost and access considerations. This study investigates statistical parameters based on the Gray Level Co-occurrence Matrix (GLCM) extracted from two-dimensional projection images and explores links with architectural properties and bone mechanics. Data analysis was conducted on Micro-CT images of 13 trabecular bones (with an in-plane spatial resolution of about 50μm). Ground truth data for bone volume fraction (BV/TV), bone strength and modulus were available based on complex 3D analysis and mechanical tests. Correlation between the statistical parameters and biomechanical test results was studied using regression analysis. The results showed Cluster-Shade was strongly correlated with the microarchitecture of the trabecular bone and related to mechanical properties. Once the principle thesis of utilizing second-order statistics is established, it can be extended to other modalities, providing cost and convenience advantages for patients and doctors.

THE MEASUREMENT OF BONE QUALITY USING GRAY LEVEL CO-OCCURRENCE MATRIX TEXTURAL FEATURES

PubMed Central

Shirvaikar, Mukul; Huang, Ning; Dong, Xuanliang Neil

2016-01-01

In this paper, statistical methods for the estimation of bone quality to predict the risk of fracture are reported. Bone mineral density and bone architecture properties are the main contributors of bone quality. Dual-energy X-ray Absorptiometry (DXA) is the traditional clinical measurement technique for bone mineral density, but does not include architectural information to enhance the prediction of bone fragility. Other modalities are not practical due to cost and access considerations. This study investigates statistical parameters based on the Gray Level Co-occurrence Matrix (GLCM) extracted from two-dimensional projection images and explores links with architectural properties and bone mechanics. Data analysis was conducted on Micro-CT images of 13 trabecular bones (with an in-plane spatial resolution of about 50μm). Ground truth data for bone volume fraction (BV/TV), bone strength and modulus were available based on complex 3D analysis and mechanical tests. Correlation between the statistical parameters and biomechanical test results was studied using regression analysis. The results showed Cluster-Shade was strongly correlated with the microarchitecture of the trabecular bone and related to mechanical properties. Once the principle thesis of utilizing second-order statistics is established, it can be extended to other modalities, providing cost and convenience advantages for patients and doctors. PMID:28042512

A Study on the Basic Criteria for Selecting Heterogeneity Parameters of F18-FDG PET Images.

PubMed

Forgacs, Attila; Pall Jonsson, Hermann; Dahlbom, Magnus; Daver, Freddie; D DiFranco, Matthew; Opposits, Gabor; K Krizsan, Aron; Garai, Ildiko; Czernin, Johannes; Varga, Jozsef; Tron, Lajos; Balkay, Laszlo

2016-01-01

Textural analysis might give new insights into the quantitative characterization of metabolically active tumors. More than thirty textural parameters have been investigated in former F18-FDG studies already. The purpose of the paper is to declare basic requirements as a selection strategy to identify the most appropriate heterogeneity parameters to measure textural features. Our predefined requirements were: a reliable heterogeneity parameter has to be volume independent, reproducible, and suitable for expressing quantitatively the degree of heterogeneity. Based on this criteria, we compared various suggested measures of homogeneity. A homogeneous cylindrical phantom was measured on three different PET/CT scanners using the commonly used protocol. In addition, a custom-made inhomogeneous tumor insert placed into the NEMA image quality phantom was imaged with a set of acquisition times and several different reconstruction protocols. PET data of 65 patients with proven lung lesions were retrospectively analyzed as well. Four heterogeneity parameters out of 27 were found as the most attractive ones to characterize the textural properties of metabolically active tumors in FDG PET images. These four parameters included Entropy, Contrast, Correlation, and Coefficient of Variation. These parameters were independent of delineated tumor volume (bigger than 25-30 ml), provided reproducible values (relative standard deviation< 10%), and showed high sensitivity to changes in heterogeneity. Phantom measurements are a viable way to test the reliability of heterogeneity parameters that would be of interest to nuclear imaging clinicians.

A Study on the Basic Criteria for Selecting Heterogeneity Parameters of F18-FDG PET Images

PubMed Central

Forgacs, Attila; Pall Jonsson, Hermann; Dahlbom, Magnus; Daver, Freddie; D. DiFranco, Matthew; Opposits, Gabor; K. Krizsan, Aron; Garai, Ildiko; Czernin, Johannes; Varga, Jozsef; Tron, Lajos; Balkay, Laszlo

2016-01-01

Textural analysis might give new insights into the quantitative characterization of metabolically active tumors. More than thirty textural parameters have been investigated in former F18-FDG studies already. The purpose of the paper is to declare basic requirements as a selection strategy to identify the most appropriate heterogeneity parameters to measure textural features. Our predefined requirements were: a reliable heterogeneity parameter has to be volume independent, reproducible, and suitable for expressing quantitatively the degree of heterogeneity. Based on this criteria, we compared various suggested measures of homogeneity. A homogeneous cylindrical phantom was measured on three different PET/CT scanners using the commonly used protocol. In addition, a custom-made inhomogeneous tumor insert placed into the NEMA image quality phantom was imaged with a set of acquisition times and several different reconstruction protocols. PET data of 65 patients with proven lung lesions were retrospectively analyzed as well. Four heterogeneity parameters out of 27 were found as the most attractive ones to characterize the textural properties of metabolically active tumors in FDG PET images. These four parameters included Entropy, Contrast, Correlation, and Coefficient of Variation. These parameters were independent of delineated tumor volume (bigger than 25–30 ml), provided reproducible values (relative standard deviation< 10%), and showed high sensitivity to changes in heterogeneity. Phantom measurements are a viable way to test the reliability of heterogeneity parameters that would be of interest to nuclear imaging clinicians. PMID:27736888

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.

Applications of optical coherence tomography in the non-contact assessment of automotive paints

NASA Astrophysics Data System (ADS)

Lawman, Samuel; Zhang, Jinke; Williams, Bryan M.; Zheng, Yalin; Shen, Yao-Chun

2017-06-01

The multiple layer paint systems on modern cars serve two end purposes, they firstly protect against corrosion and secondly give the desired visual appearance. To ensure consistent corrosion protection and appearance, suitable Quality Assurance (QA) measures on the final product are required. Various (layer thickness and consistency, layer composition, flake statistics, surface profile and layer dryness) parameters are of importance, each with specific techniques that can measure one or some of them but no technique that can measure all or most of them. Optical Coherence Tomography (OCT) is a 3D imaging technique with micrometre resolution. Since 2016, OCT measurements of layer thickness and consistency, layer composition fingerprint and flake statistics have been reported. In this paper we demonstrate two more novel applications of OCT to automotive paints. Firstly, we use OCT to quantify unwanted surface texture, which leads to an "orange peel" visual defect. This was done by measuring the surface profiles of automotive paints, with an unoptimised precision of 37 nm over lateral range of 7 mm, to quantify texture of less than 500 nm. Secondly, we demonstrate that OCT can measure how dry a coating layer is by measuring how fast it is still shrinking quasiinstantaneously, using Fourier phase sensitivity.

Connecting Majorana phases to the geometric parameters of the Majorana unitarity triangle in a neutrino mass matrix model

NASA Astrophysics Data System (ADS)

Verma, Surender; Bhardwaj, Shankita

2018-05-01

We have investigated a possible connection between the Majorana phases and geometric parameters of Majorana unitarity triangle (MT) in two-texture zero neutrino mass matrix. Such analytical relations can, also, be obtained for other theoretical models viz. hybrid textures, neutrino mass matrix with vanishing minors and have profound implications for geometric description of C P violation. As an example, we have considered the two-texture zero neutrino mass model to obtain a relation between Majorana phases and MT parameters that may be probed in various lepton number violating processes. In particular, we find that Majorana phases depend on only one of the three interior angles of the MT in each class of two-texture zero neutrino mass matrix. We have also constructed the MT for class A , B , and C neutrino mass matrices. Nonvanishing areas and nontrivial orientations of these Majorana unitarity triangles indicate nonzero C P violation as a generic feature of this class of mass models.

Sensory and instrumental texture measurements for assessing grape seed parameters during fruit development.

PubMed

Letaief, Hend; Maury, Chantal; Symoneaux, Ronan; Siret, René

2013-08-15

The evolution of the sensory and instrumental properties of grape seeds was investigated during berry development, with a focus on the effects of the harvest season and growing location. The sensory and instrumental texture analyses gave a consistent description of the ripening process. Moreover, the effect of maturation on the seed sensory descriptors was clearly influenced by the harvest season, and astringency was the most appropriate sensory attribute for the assessment of grape seed ripening. Except for seed cracking, which was positively correlated with fracturability (R = 0.69) and toughness (R = 0.68) in 2006, the compression parameters were generally not correlated with the sensory textural attributes but were more likely correlated with other sensory attributes such as astringency and vegetal aroma. The compression indices showed a logarithmic behaviour pattern during grape development, and seed stiffness was shown to be the most valuable textural index for parcel discrimination and identification of the optimal grape harvesting date. This research showed that both seed sensory attributes and instrumental texture properties are indicators of grape ripening. However, these properties could be affected by the harvest season and growing location. As no clear correlation was found between the seed sensory attributes and instrumental texture parameters, a revision of the sensory method available in the literature could be suggested. © 2013 Society of Chemical Industry.

Multiresolution texture analysis applied to road surface inspection

NASA Astrophysics Data System (ADS)

Paquis, Stephane; Legeay, Vincent; Konik, Hubert; Charrier, Jean

1999-03-01

Technological advances provide now the opportunity to automate the pavement distress assessment. This paper deals with an approach for achieving an automatic vision system for road surface classification. Road surfaces are composed of aggregates, which have a particular grain size distribution and a mortar matrix. From various physical properties and visual aspects, four road families are generated. We present here a tool using a pyramidal process with the assumption that regions or objects in an image rise up because of their uniform texture. Note that the aim is not to compute another statistical parameter but to include usual criteria in our method. In fact, the road surface classification uses a multiresolution cooccurrence matrix and a hierarchical process through an original intensity pyramid, where a father pixel takes the minimum gray level value of its directly linked children pixels. More precisely, only matrix diagonal is taken into account and analyzed along the pyramidal structure, which allows the classification to be made.

Comparative study on the performance of textural image features for active contour segmentation.

PubMed

Moraru, Luminita; Moldovanu, Simona

2012-07-01

We present a computerized method for the semi-automatic detection of contours in ultrasound images. The novelty of our study is the introduction of a fast and efficient image function relating to parametric active contour models. This new function is a combination of the gray-level information and first-order statistical features, called standard deviation parameters. In a comprehensive study, the developed algorithm and the efficiency of segmentation were first tested for synthetic images. Tests were also performed on breast and liver ultrasound images. The proposed method was compared with the watershed approach to show its efficiency. The performance of the segmentation was estimated using the area error rate. Using the standard deviation textural feature and a 5×5 kernel, our curve evolution was able to produce results close to the minimal area error rate (namely 8.88% for breast images and 10.82% for liver images). The image resolution was evaluated using the contrast-to-gradient method. The experiments showed promising segmentation results.

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.

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.

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.

Tailoring Spin Textures in Complex Oxide Micromagnets

DOE PAGES

Lee, Michael S.; Wynn, Thomas A.; Folven, Erik; ...

2016-09-12

Engineered topological spin textures with submicron dimensions in magnetic materials have emerged in recent years as the building blocks for various spin-based memory devices. Examples of these magnetic configurations include magnetic skyrmions, vortices, and domain walls. Here in this paper, we show the ability to control and characterize the evolution of spin textures in complex oxide micromagnets as a function of temperature through the delicate balance of fundamental materials parameters, micromagnet geometries, and epitaxial strain. These results demonstrate that in order to fully describe the observed spin textures, it is necessary to account for the spatial variation of the magneticmore » parameters within the micromagnet. This study provides the framework to accurately characterize such structures, leading to efficient design of spin-based memory devices based on complex oxide thin films.« less

A multiscale coupled finite-element and phase-field framework to modeling stressed grain growth in polycrystalline thin films

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

Jamshidian, M., E-mail: jamshidian@cc.iut.ac.ir; Institute of Structural Mechanics, Bauhaus-University Weimar, Marienstrasse 15, 99423 Weimar; Thamburaja, P., E-mail: prakash.thamburaja@gmail.com

A previously-developed finite-deformation- and crystal-elasticity-based constitutive theory for stressed grain growth in cubic polycrystalline bodies has been augmented to include a description of excess surface energy and grain-growth stagnation mechanisms through the use of surface effect state variables in a thermodynamically-consistent manner. The constitutive theory was also implemented into a multiscale coupled finite-element and phase-field computational framework. With the material parameters in the constitutive theory suitably calibrated, our three-dimensional numerical simulations show that the constitutive model is able to accurately predict the experimentally-determined evolution of crystallographic texture and grain size statistics in polycrystalline copper thin films deposited on polyimide substratemore » and annealed at high-homologous temperatures. In particular, our numerical analyses show that the broad texture transition observed in the annealing experiments of polycrystalline thin films is caused by grain growth stagnation mechanisms. - Graphical abstract: - Highlights: • Developing a theory for stressed grain growth in polycrystalline thin films. • Implementation into a multiscale coupled finite-element and phase-field framework. • Quantitative reproduction of the experimental grain growth data by simulations. • Revealing the cause of texture transition to be due to the stagnation mechanisms.« less

Carbon Dioxide Sealing Capacity: Textural or Compositional Controls?

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

Cranganu, Constantin; Soleymani, Hamidreza; Sadiqua, Soleymani

2013-11-30

This research project is aiming to assess the carbon dioxide sealing capacity of most common seal-rocks, such as shales and non-fractured limestones, by analyzing the role of textural and compositional parameters of those rocks. We hypothesize that sealing capacity is controlled by textural and/or compositional pa-rameters of caprocks. In this research, we seek to evaluate the importance of textural and compositional parameters affecting the sealing capacity of caprocks. The conceptu-al framework involves two testable end-member hypotheses concerning the sealing ca-pacity of carbon dioxide reservoir caprocks. Better understanding of the elements controlling sealing quality will advance our knowledge regarding the sealingmore » capacity of shales and carbonates. Due to relatively low permeability, shale and non-fractured carbonate units are considered relatively imper-meable formations which can retard reservoir fluid flow by forming high capillary pres-sure. Similarly, these unites can constitute reliable seals for carbon dioxide capture and sequestration purposes. This project is a part of the comprehensive project with the final aim of studying the caprock sealing properties and the relationship between microscopic and macroscopic characteristics of seal rocks in depleted gas fields of Oklahoma Pan-handle. Through this study we examined various seal rock characteristics to infer about their respective effects on sealing capacity in special case of replacing reservoir fluid with super critical carbon dioxide (scCO{sub 2}). To assess the effect of textural and compositional properties on scCO{sub 2} maximum reten-tion column height we collected 30 representative core samples in caprock formations in three counties (Cimarron, Texas, Beaver) in Oklahoma Panhandle. Core samples were collected from various seal formations (e.g., Cherokee, Keys, Morrowan) at different depths. We studied the compositional and textural properties of the core samples using several techniques. Mercury Injection Porosimetry (MIP), Scanning Electron Microsco-py SEM, and Sedigraph measurements are used to assess the pore-throat-size distribu-tion, sorting, texture, and grain size of the samples. Also, displacement pressure at 10% mercury saturation (Pd) and graphically derived threshold pressure (Pc) were deter-mined by MIP technique. SEM images were used for qualitative study of the minerals and pores texture of the core samples. Moreover, EDS (Energy Dispersive X-Ray Spec-trometer), BET specific surface area, and Total Organic Carbon (TOC) measurements were performed to study various parameters and their possible effects on sealing capaci-ty of the samples. We found that shales have the relatively higher average sealing threshold pressure (Pc) than carbonate and sandstone samples. Based on these observations, shale formations could be considered as a promising caprock in terms of retarding scCO{sub 2} flow and leak-age into above formations. We hypothesized that certain characteristics of shales (e.g., 3 fine pore size, pore size distribution, high specific surface area, and strong physical chemical interaction between wetting phase and mineral surface) make them an effi-cient caprock for sealing super critical CO{sub 2}. We found that the displacement pressure at 10% mercury saturation could not be the ultimate representative of the sealing capacity of the rock sample. On the other hand, we believe that graphical method, introduced by Cranganu (2004) is a better indicator of the true sealing capacity. Based on statistical analysis of our samples from Oklahoma Panhandle we assessed the effects of each group of properties (textural and compositional) on maximum supercriti-cal CO{sub 2} height that can be hold by the caprock. We conclude that there is a relatively strong positive relationship (+.40 to +.69) between supercritical CO{sub 2} column height based on Pc and hard/ soft mineral content index (ratio of minerals with Mohs hardness more than 5 over minerals with Mohs hardness less than 5) in both shales and limestone samples. Average median pore radius and porosity display a strong negative correlation with supercritical CO{sub 2} retention column height. Also, increasing bulk density is positive-ly correlated with the supercritical CO{sub 2} retention column height. One of the most im-portant factors affecting sealing capacity and consequently the height of supercritical CO{sub 2} column is sorting of the pore throats. We observed a strong positive correlation be-tween pore throat sorting and height of CO{sub 2} retention column, especially in shales. This correlation could not be observed in limestone samples. It suggests that the pore throat sorting is more controlling the sealing capacity in shales and shales with well sorted pore throats are the most reliable lithology as seal. We observed that Brunauer–Emmett–Teller (BET) surface area shows a very strong correlation with CO{sub 2} retention column height in limestone samples while BET surface area did not display significant correlation in shales. Pore structure based on SEM mi-crographs exhibits strong correlation with CO{sub 2} retention column height in limestones. Both intercrystalline and vuggy structures have negative correlations while intergranu-lar texture has positive correlation in limestone with respect to CO{sub 2} retention column height. Textural effects observed on SEM micrographs did not show statistically signifi-cant correlation with supercritical CO{sub 2} retention column height in shale samples. Finally, we showed that increasing hard/soft mineral index is strongly correlated with the displacement pressure in limestone samples. Vuggy texture displays a relatively strong and negative correlation with displacement pressure values at 10% mercury satu-ration in shale samples.« less

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

PubMed

Pyka, Thomas; Gempt, Jens; Hiob, Daniela; Ringel, Florian; Schlegel, Jürgen; Bette, Stefanie; Wester, Hans-Jürgen; Meyer, Bernhard; Förster, Stefan

2016-01-01

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

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.

Assessment of chronic kidney disease using skin texture as a key parameter: for South Indian population.

PubMed

Udhayarasu, Madhanlal; Ramakrishnan, Kalpana; Periasamy, Soundararajan

2017-12-01

Periodical monitoring of renal function, specifically for subjects with history of diabetic or hypertension would prevent them from entering into chronic kidney disease (CKD) condition. The recent increase in numbers may be due to food habits or lack of physical exercise, necessitates a rapid kidney function monitoring system. Presently, it is determined by evaluating glomerular filtration rate (GFR) that is mainly dependent on serum creatinine value and demographic parameters and ethnic value. Attempted here is to develop ethnic parameter based on skin texture for every individual. This value when used in GFR computation, the results are much agreeable with GFR obtained through standard modification of diet in renal disease and CKD epidemiology collaboration equations. Once correlation between CKD and skin texture is established, classification tool using artificial neural network is built to categorise CKD level based on demographic values and parameter obtained through skin texture (without using creatinine). This network when tested gives almost at par results with the network that is trained with demographic and creatinine values. The results of this Letter demonstrate the possibility of non-invasively determining kidney function and hence for making a device that would readily assess the kidney function even at home.

PET textural features stability and pattern discrimination power for radiomics analysis: An "ad-hoc" phantoms study.

PubMed

Presotto, L; Bettinardi, V; De Bernardi, E; Belli, M L; Cattaneo, G M; Broggi, S; Fiorino, C

2018-06-01

The analysis of PET images by textural features, also known as radiomics, shows promising results in tumor characterization. However, radiomic metrics (RMs) analysis is currently not standardized and the impact of the whole processing chain still needs deep investigation. We characterized the impact on RM values of: i) two discretization methods, ii) acquisition statistics, and iii) reconstruction algorithm. The influence of tumor volume and standardized-uptake-value (SUV) on RM was also investigated. The Chang-Gung-Image-Texture-Analysis (CGITA) software was used to calculate 39 RMs using phantom data. Thirty noise realizations were acquired to measure statistical effect size indicators for each RM. The parameter η 2 (fraction of variance explained by the nuisance factor) was used to assess the effect of categorical variables, considering η 2  < 20% and 20% < η 2  < 40% as representative of a "negligible" and a "small" dependence respectively. The Cohen's d was used as discriminatory power to quantify the separation of two distributions. We found the discretization method based on fixed-bin-number (FBN) to outperform the one based on fixed-bin-size in units of SUV (FBS), as the latter shows a higher SUV dependence, with 30 RMs showing η 2  > 20%. FBN was also less influenced by the acquisition and reconstruction setup:with FBN 37 RMs had η 2  < 40%, only 20 with FBS. Most RMs showed a good discriminatory power among heterogeneous PET signals (for FBN: 29 out of 39 RMs with d > 3). For RMs analysis, FBN should be preferred. A group of 21 RMs was suggested for PET radiomics analysis. Copyright © 2018 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

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

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

Huang, W; Tu, S

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

Physical-Mechanical characterization of cosmetic formulations and correlation between instrumental measurements and sensorial properties.

PubMed

Calixto, L S; Maia Campos, P M B G

2017-10-01

The correct choice of raw materials in the development of cosmetic formulations is essential for obtaining stable and pleasant skin care products. Therefore, rheological, texture and sensory analyses are important to understand the behaviour and stability of the formulations. In this context, the aim of this study was to develop cosmetic formulations containing or not (vehicle) UV filters and chicory root extract, to evaluate their stability as well as to characterize their physical and texture properties and correlate them with the sensory attributes. Four formulations containing organic UV filters and chicory extract, each alone or in combination, were developed and evaluated for 180 days with a cone and plate rheometer, a texture analyzer and consumer's sensorial analysis. Thus, the data obtained were correlated to observe the different influences. The developed formulations remained stable after 180 days regarding macroscopic aspects, organoleptic characteristics and pH values. The addition of the UV filters alone and in combination with the active substance resulted in significant increases in rheology properties, viscosity and consistency. The formulation with the active ingredient showed significant decreases in the texture parameters after 180 days, mainly due to its polysaccharide inulin. All formulations obtained high scores in sensorial parameters. A strong correlation was mainly found between spreadability and work of shear, and between the texture parameters. The raw materials strongly influenced the physical, texture and sensorial parameters. Finally, the UV filters showed a greater influence on the results of the formulations than the chicory root extract. In conclusion, the association of the mentioned methods allows the correct choice of ingredients and their combinations. © 2017 Society of Cosmetic Scientists and the Société Française de Cosmétologie.

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

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.

Hybrid texture generator

NASA Astrophysics Data System (ADS)

Miyata, Kazunori; Nakajima, Masayuki

1995-04-01

A method is given for synthesizing a texture by using the interface of a conventional drawing tool. The majority of conventional texture generation methods are based on the procedural approach, and can generate a variety of textures that are adequate for generating a realistic image. But it is hard for a user to imagine what kind of texture will be generated simply by looking at its parameters. Furthermore, it is difficult to design a new texture freely without a knowledge of all the procedures for texture generation. Our method offers a solution to these problems, and has the following four merits: First, a variety of textures can be obtained by combining a set of feature lines and attribute functions. Second, data definitions are flexible. Third, the user can preview a texture together with its feature lines. Fourth, people can design their own textures interactively and freely by using the interface of a conventional drawing tool. For users who want to build this texture generation method into their own programs, we also give the language specifications for generating a texture. This method can interactively provide a variety of textures, and can also be used for typographic design.

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.

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

PubMed

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

2012-05-01

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

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

PubMed Central

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

2012-01-01

18F-FDG PET measurement of standardized uptake values (SUV) is increasingly used for monitoring therapy response or predicting outcome. Alternative parameters computed through textural analysis were recently proposed to quantify the tumor tracer uptake heterogeneity as significant predictors of response. The primary objective of this study was the evaluation of the reproducibility of these heterogeneity measurements. Methods Double-baseline 18F-FDG PET scans of 16 patients acquired within a period of 4 days prior to any treatment were considered. A Bland-Altman analysis was carried out on six parameters based on histogram measurements and 17 heterogeneity parameters based on textural features obtained after discretization with values between 8 and 128. Results SUVmax and SUVmean reproducibility were similar to previously reported studies with a mean percentage difference of 4.7±19.5% and 5.5±21.2% respectively. By comparison better reproducibility was measured for some of the textural features describing tumor tracer local heterogeneity, such as entropy and homogeneity with a mean percentage difference of −2±5.4% and 1.8±11.5% respectively. Several of the tumor regional heterogeneity parameters such as the variability in the intensity and size of homogeneous tumor activity distribution regions had similar reproducibility to the SUV measurements with 95% confidence intervals of −22.5% to 3.1% and −1.1% to 23.5% respectively. These parameters were largely insensitive to the discretization range values. Conclusion Several of the parameters derived from textural analysis describing tumor tracer heterogeneity at local and regional scales had similar or better reproducibility as simple SUV measurements. These reproducibility results suggest that these FDG PET image derived parameters which have already been shown to have a predictive and prognostic value in certain cancer models, may be used within the context of therapy response monitoring or predicting patient outcome. PMID:22454484

Texture metric that predicts target detection performance

NASA Astrophysics Data System (ADS)

Culpepper, Joanne B.

2015-12-01

Two texture metrics based on gray level co-occurrence error (GLCE) are used to predict probability of detection and mean search time. The two texture metrics are local clutter metrics and are based on the statistics of GLCE probability distributions. The degree of correlation between various clutter metrics and the target detection performance of the nine military vehicles in complex natural scenes found in the Search_2 dataset are presented. Comparison is also made between four other common clutter metrics found in the literature: root sum of squares, Doyle, statistical variance, and target structure similarity. The experimental results show that the GLCE energy metric is a better predictor of target detection performance when searching for targets in natural scenes than the other clutter metrics studied.

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Modeling the microstructural changes during hot tandem rolling of AA5 XXX aluminum alloys: Part II. Textural evolution

NASA Astrophysics Data System (ADS)

Wells, M. A.; Samarasekera, I. V.; Brimacombe, J. K.; Hawbolt, E. B.; Lloyd, D. J.

1998-06-01

In Part II of this article, the experimental work undertaken to measure the effect of deformation parameters (temperature, strain, and strain rate) on the texture formation during hot deformation and the evolution during subsequent recrystallization is described. In addition, the isothermal kinetics of development of individual texture components were also determined. A neutron diffractometer was used to measure the texture in the as-hot-deformed aluminum samples, and the samples were then heat treated in a 400 °C salt bath for various lengths of time, with the texture being remeasured at various stages in the recrystallization process. Using data from the experimental program, the texture evolution during recrystallization was modeled by applying a modified form of the Avrami equation. Results indicated that, of the deformation parameters studied, textural development was most sensitive to the deformation temperature for both alloys. In addition, modeling results revealed that the Cu component ({112} <111>) was the first to recrystallize, typically followed by the S ({123} <634>) and Bs ({110} <112>) components. This is in agreement with earlier work which indicated that the Bs component was the hardest to recrystallize, possibly because it is able to deform on very few slip systems and, hence, the dislocation interaction may be low.

Characterisation of group behaviour surface texturing with multi-layers fitting method

NASA Astrophysics Data System (ADS)

Kang, Zhengyang; Fu, Yonghong; Ji, Jinghu; Wang, Hao

2016-07-01

Surface texturing was widely applied in improving the tribological properties of mechanical components, but study of measurement of this technology was still insufficient. This study proposed the multi-layers fitting (MLF) method to characterise the dimples array texture surface. Based on the synergistic effect among the dimples, the 3D morphology of texture surface was rebuilt by 2D stylus profiler in the MLF method. The feasible regions of texture patterns and sensitive parameters were confirmed by non-linear programming, and the processing software of MLF method was developed based on the Matlab®. The characterisation parameters system of dimples was defined mathematically, and the accuracy of MLF method was investigated by comparison experiment. The surface texture specimens were made by laser surface texturing technology, in which high consistency of dimples' size and distribution was achieved. Then, 2D profiles of different dimples were captured by employing Hommel-T1000 stylus profiler, and the data were further processed by MLF software to rebuild 3D morphology of single dimple. The experiment results indicated that the MLF characterisation results were similar to those of Wyko T1100, the white light interference microscope. It was also found that the stability of MLF characterisation results highly depended on the number of captured cross-sections.

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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.

Fracture discrimination by combined bone mineral density (BMD) and microarchitectural texture analysis.

PubMed

Touvier, J; Winzenrieth, R; Johansson, H; Roux, J P; Chaintreuil, J; Toumi, H; Jennane, R; Hans, D; Lespessailles, E

2015-04-01

The use of bone mineral density (BMD) for fracture discrimination may be improved by considering bone microarchitecture. Texture parameters such as trabecular bone score (TBS) or mean Hurst parameter (H) could help to find women who are at high risk of fracture in the non-osteoporotic group. The purpose of this study was to combine BMD and microarchitectural texture parameters (spine TBS and calcaneus H) for the detection of osteoporotic fractures. Two hundred and fifty five women had a lumbar spine (LS), total hip (TH), and femoral neck (FN) DXA. Additionally, texture analyses were performed with TBS on spine DXA and with H on calcaneus radiographs. Seventy-nine women had prevalent fragility fractures. The association with fracture was evaluated by multivariate logistic regressions. The diagnostic value of each parameter alone and together was evaluated by odds ratios (OR). The area under curve (AUC) of the receiver operating characteristics (ROC) were assessed in models including BMD, H, and TBS. Women were also classified above and under the lowest tertile of H or TBS according to their BMD status. Women with prevalent fracture were older and had lower TBS, H, LS-BMD, and TH-BMD than women without fracture. Age-adjusted ORs were 1.66, 1.70, and 1.93 for LS, FN, and TH-BMD, respectively. Both TBS and H remained significantly associated with fracture after adjustment for age and TH-BMD: OR 2.07 [1.43; 3.05] and 1.47 [1.04; 2.11], respectively. The addition of texture parameters in the multivariate models didn't show a significant improvement of the ROC-AUC. However, women with normal or osteopenic BMD in the lowest range of TBS or H had significantly more fractures than women above the TBS or the H threshold. We have shown the potential interest of texture parameters such as TBS and H in addition to BMD to discriminate patients with or without osteoporotic fractures. However, their clinical added values should be evaluated relative to other risk factors.

How far are rheological parameters from amplitude sweep tests predictable using common physicochemical soil properties?

NASA Astrophysics Data System (ADS)

Stoppe, N.; Horn, R.

2017-01-01

A basic understanding of soil behavior on the mesoscale resp. macroscale (i.e. soil aggregates resp. bulk soil) requires knowledge of the processes at the microscale (i.e. particle scale), therefore rheological investigations of natural soils receive growing attention. In the present research homogenized and sieved (< 2 mm) samples from Marshland soils of the riparian zone of the River Elbe (North Germany) were analyzed with a modular compact rheometer MCR 300 (Anton Paar, Ostfildern, Germany) with a profiled parallel-plate measuring system. Amplitude sweep tests (AST) with controlled shear deformation were conducted to investigate the viscoelastic properties of the studied soils under oszillatory stress. The gradual depletion of microstructural stiffness during AST cannot only be characterized by the well-known rheological parameters G, G″ and tan δ but also by the dimensionless area parameter integral z, which quantifies the elasticity of microstructure. To discover the physicochemical parameters, which influences the microstructural stiffness, statistical tests were used taking the combined effects of these parameters into account. Although the influence of the individual factors varies depending on soil texture, the physicochemical features significantly affecting soil micro structure were identified. Based on the determined statistical relationships between rheological and physicochemical parameters, pedotransfer functions (PTF) have been developed, which allow a mathematical estimation of the rheological target value integral z. Thus, stabilizing factors are: soil organic matter, concentration of Ca2+, content of CaCO3 and pedogenic iron oxides; whereas the concentration of Na+ and water content represent structurally unfavorable factors.

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.

Method of forming biaxially textured alloy substrates and devices thereon

DOEpatents

Goyal, Amit; Specht, Eliot D.; Kroeger, Donald M.; Paranthaman, Mariappan

2000-01-01

Specific alloys, in particular Ni-based alloys, that can be biaxially textured, with a well-developed, single component texture are disclosed. These alloys have a significantly reduced Curie point, which is very desirable from the point of view of superconductivity applications. The biaxially textured alloy substrates also possess greatly enhanced mechanical properties (yield strength, ultimate tensile strength) which are essential for most applications, in particular, superconductors. A method is disclosed for producing complex multicomponent alloys which have the ideal physical properties for specific applications, such as lattice parameter, degree of magnetism and mechanical strength, and which cannot be in textured form. In addition, a method for making ultra thin biaxially textured substrates with complex compositions is disclosed.

Cloud and surface textural features in polar regions

NASA Technical Reports Server (NTRS)

Welch, Ronald M.; Kuo, Kwo-Sen; Sengupta, Sailes K.

1990-01-01

The study examines the textural signatures of clouds, ice-covered mountains, solid and broken sea ice and floes, and open water. The textural features are computed from sum and difference histogram and gray-level difference vector statistics defined at various pixel displacement distances derived from Landsat multispectral scanner data. Polar cloudiness, snow-covered mountainous regions, solid sea ice, glaciers, and open water have distinguishable texture features. This suggests that textural measures can be successfully applied to the detection of clouds over snow-covered mountains, an ability of considerable importance for the modeling of snow-melt runoff. However, broken stratocumulus cloud decks and thin cirrus over broken sea ice remain difficult to distinguish texturally. It is concluded that even with high spatial resolution imagery, it may not be possible to distinguish broken stratocumulus and thin clouds from sea ice in the marginal ice zone using the visible channel textural features alone.

Effects of vacuum and modified atmosphere on textural parameters and structural proteins of cultured meagre (Argyrosomus regius) fillets.

PubMed

Sáez, María I; Martínez, Tomás F; Cárdenas, Salvador; Suárez, María D

2015-09-01

The influence of two preservation strategies (vacuum package and modified atmosphere package) on the post-mortem changes of textural parameters, pH, water holding capacity, sarcoplasmic and myofibrillar proteins, and collagen content of meagre (Argyrosomus regius) fillets was studied. Fillets were stored in a cold room in aerobic (control, C), vacuum (V) and modified atmosphere (MA) package. Samples were withdrawn at six sampling points throughout 15-day storage, and post-mortem changes were assessed. The textural parameters were significantly enhanced in V and MA compared to C. Both V and MA treatments reduced the intensity of a group of myofibrillar protein fractions (140-195 kDa) and increased insoluble collagen compared to C. Consequently, the post-mortem flesh softening in C was attributed to increased proteolysis in both intracellular and extracellular structural proteins. The preservation of the textural and biochemical characteristics of meagre fillets subjected to V and MA treatments makes these two treatments highly recommendable for the commercialization of meagre fillets. © The Author(s) 2014.

Texture measurement of shaped material by impulse acoustic microscopy

PubMed

Eyraud; Nadal; Gondard

2000-03-01

All the microstructural parameters involved in metallurgical processes are difficult to determine directly on a shaped material. The aim of this paper is to use an impulse line-focus acoustic microscope (LFAM) as a non-destructive alternative to X-ray diffraction for measuring texture of slightly anisotropic materials. We apply it to characterize the rolling and annealing texture for tantalum sheets.

An experimental bioactive dental ceramic for metal-ceramic restorations: Textural characteristics and investigation of the mechanical properties.

PubMed

Goudouri, Ourania-Menti; Kontonasaki, Eleana; Papadopoulou, Lambrini; Manda, Marianthi; Kavouras, Panagiotis; Triantafyllidis, Konstantinos S; Stefanidou, Maria; Koidis, Petros; Paraskevopoulos, Konstantinos M

2017-02-01

The aim of this study was the evaluation of the textural characteristics of an experimental sol-gel derived feldspathic dental ceramic, which has already been proven bioactive and the investigation of its flexural strength through Weibull Statistical Analysis. The null hypothesis was that the flexural strength of the experimental and the commercial dental ceramic would be of the same order, resulting in a dental ceramic with apatite forming ability and adequate mechanical integrity. Although the flexural strength of the experimental ceramics was not statistically significant different compared to the commercial one, the amount of blind pores due to processing was greater. The textural characteristics of the experimental ceramic were in accordance with the standard low porosity levels reported for dental ceramics used for fixed prosthetic restorations. Feldspathic dental ceramics with typical textural characteristics and advanced mechanical properties as well as enhanced apatite forming ability can be synthesized through the sol-gel method. Copyright © 2016 Elsevier Ltd. All rights reserved.

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.

High-resolution land cover classification using low resolution global data

NASA Astrophysics Data System (ADS)

Carlotto, Mark J.

2013-05-01

A fusion approach is described that combines texture features from high-resolution panchromatic imagery with land cover statistics derived from co-registered low-resolution global databases to obtain high-resolution land cover maps. The method does not require training data or any human intervention. We use an MxN Gabor filter bank consisting of M=16 oriented bandpass filters (0-180°) at N resolutions (3-24 meters/pixel). The size range of these spatial filters is consistent with the typical scale of manmade objects and patterns of cultural activity in imagery. Clustering reduces the complexity of the data by combining pixels that have similar texture into clusters (regions). Texture classification assigns a vector of class likelihoods to each cluster based on its textural properties. Classification is unsupervised and accomplished using a bank of texture anomaly detectors. Class likelihoods are modulated by land cover statistics derived from lower resolution global data over the scene. Preliminary results from a number of Quickbird scenes show our approach is able to classify general land cover features such as roads, built up area, forests, open areas, and bodies of water over a wide range of scenes.

Soil erosion model predictions using parent material/soil texture-based parameters compared to using site-specific parameters

Treesearch

R. B. Foltz; W. J. Elliot; N. S. Wagenbrenner

2011-01-01

Forested areas disturbed by access roads produce large amounts of sediment. One method to predict erosion and, hence, manage forest roads is the use of physically based soil erosion models. A perceived advantage of a physically based model is that it can be parameterized at one location and applied at another location with similar soil texture or geological parent...

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.

Relationship between Agronomic Parameters, Phenolic Composition of Grape Skin, and Texture Properties of Vitis vinifera L. cv. Tempranillo.

PubMed

García-Estévez, Ignacio; Andrés-García, Paula; Alcalde-Eon, Cristina; Giacosa, Simone; Rolle, Luca; Rivas-Gonzalo, Julián C; Quijada-Morín, Natalia; Escribano-Bailón, M Teresa

2015-09-09

The relationship between the agronomic parameters of grapevine and the phenolic composition of skin of Vitis vinifera L. cv. Tempranillo grapes was assessed. The physical and mechanical properties of berries and their skins were also determined and correlated to the chemical composition. Results showed a significant negative correlation between grapevine vigor-related parameters (such as leaf area and bunch weight) and anthocyanin composition, whereas the percentage (w/w) of seeds was negatively correlated with the amount of flavanols of grape skins. Texture properties of grape skins also showed an important relationship with chemical composition. Berry hardness showed a negative correlation with the coumaroyl-anthocyanin derivatives, but it was positively correlated to skin flavanic composition. Moreover, significant regressions with high coefficients of determination were found between phenolic composition and grapevine vigor-related and texture variables, thus pointing out that these parameters might be useful for estimating the phenolic composition of grape skins.

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.

Electromigration kinetics and critical current of Pb-free interconnects

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

Lu, Minhua; Rosenberg, Robert

2014-04-07

Electromigration kinetics of Pb-free solder bump interconnects have been studied using a single bump parameter sweep technique. By removing bump to bump variations in structure, texture, and composition, the single bump sweep technique has provided both activation energy and power exponents that reflect atomic migration and interface reactions with fewer samples, shorter stress time, and better statistics than standard failure testing procedures. Contact metallurgies based on Cu and Ni have been studied. Critical current, which corresponds to the Blech limit, was found to exist in the Ni metallurgy, but not in the Cu metallurgy. A temperature dependence of critical currentmore » was also observed.« less

Semantic attributes based texture generation

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Texture 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.

Method of forming biaxially textured alloy substrates and devices thereon

DOEpatents

Goyal, Amit; Specht, Eliot D.; Kroeger, Donald M.; Paranthaman, Mariappan

1999-01-01

Specific alloys, in particular Ni-based alloys, that can be biaxially textured, with a well-developed, single component texture are disclosed. These alloys have a significantly reduced Curie point, which is very desirable from the point of view of superconductivity applications. The biaxially textured alloy substrates also possess greatly enhanced mechanical properties (yield strength, ultimate tensile strength) which are essential for most applications, in particular, superconductors. A method is disclosed for producing complex multicomponent alloys which have the ideal physical properties for specific applications, such as lattice parameter, degree of magnetism and mechanical strength, and which cannot be fabricated in textured form. In addition, a method for making ultra thin biaxially textured substrates with complex compositions is disclosed.

A candidate gene based approach validates Md-PG1 as the main responsible for a QTL impacting fruit texture in apple (Malus x domestica Borkh).

PubMed

Longhi, Sara; Hamblin, Martha T; Trainotti, Livio; Peace, Cameron P; Velasco, Riccardo; Costa, Fabrizio

2013-03-04

Apple is a widely cultivated fruit crop for its quality properties and extended storability. Among the several quality factors, texture is the most important and appreciated, and within the apple variety panorama the cortex texture shows a broad range of variability. Anatomically these variations depend on degradation events occurring in both fruit primary cell wall and middle lamella. This physiological process is regulated by an enzymatic network generally encoded by large gene families, among which polygalacturonase is devoted to the depolymerization of pectin. In apple, Md-PG1, a key gene belonging to the polygalacturonase gene family, was mapped on chromosome 10 and co-localized within the statistical interval of a major hot spot QTL associated to several fruit texture sub-phenotypes. In this work, a QTL corresponding to the position of Md-PG1 was validated and new functional alleles associated to the fruit texture properties in 77 apple cultivars were discovered. 38 SNPs genotyped by gene full length resequencing and 2 SSR markers ad hoc targeted in the gene metacontig were employed. Out of this SNP set, eleven were used to define three significant haplotypes statistically associated to several texture components. The impact of Md-PG1 in the fruit cell wall disassembly was further confirmed by the cortex structure electron microscope scanning in two apple varieties characterized by opposite texture performance, such as 'Golden Delicious' and 'Granny Smith'. The results here presented step forward into the genetic dissection of fruit texture in apple. This new set of haplotypes, and microsatellite alleles, can represent a valuable toolbox for a more efficient parental selection as well as the identification of new apple accessions distinguished by superior fruit quality features.

Coupled crystal orientation-size effects on the strength of nano crystals

PubMed Central

Yuan, Rui; Beyerlein, Irene J.; Zhou, Caizhi

2016-01-01

We study the combined effects of grain size and texture on the strength of nanocrystalline copper (Cu) and nickel (Ni) using a crystal-plasticity based mechanics model. Within the model, slip occurs in discrete slip events exclusively by individual dislocations emitted statistically from the grain boundaries. We show that a Hall-Petch relationship emerges in both initially texture and non-textured materials and our values are in agreement with experimental measurements from numerous studies. We find that the Hall-Petch slope increases with texture strength, indicating that preferred orientations intensify the enhancements in strength that accompany grain size reductions. These findings reveal that texture is too influential to be neglected when analyzing and engineering grain size effects for increasing nanomaterial strength. PMID:27185364

Automatic Texture Reconstruction of 3d City Model from Oblique Images

NASA Astrophysics Data System (ADS)

Kang, Junhua; Deng, Fei; Li, Xinwei; Wan, Fang

2016-06-01

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

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

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.

Perturbed Yukawa textures in the minimal seesaw model

NASA Astrophysics Data System (ADS)

Rink, Thomas; Schmitz, Kai

2017-03-01

We revisit the minimal seesaw model, i.e., the type-I seesaw mechanism involving only two right-handed neutrinos. This model represents an important minimal benchmark scenario for future experimental updates on neutrino oscillations. It features four real parameters that cannot be fixed by the current data: two CP -violating phases, δ and σ, as well as one complex parameter, z, that is experimentally inaccessible at low energies. The parameter z controls the structure of the neutrino Yukawa matrix at high energies, which is why it may be regarded as a label or index for all UV completions of the minimal seesaw model. The fact that z encompasses only two real degrees of freedom allows us to systematically scan the minimal seesaw model over all of its possible UV completions. In doing so, we address the following question: suppose δ and σ should be measured at particular values in the future — to what extent is one then still able to realize approximate textures in the neutrino Yukawa matrix? Our analysis, thus, generalizes previous studies of the minimal seesaw model based on the assumption of exact texture zeros. In particular, our study allows us to assess the theoretical uncertainty inherent to the common texture ansatz. One of our main results is that a normal light-neutrino mass hierarchy is, in fact, still consistent with a two-zero Yukawa texture, provided that the two texture zeros receive corrections at the level of O (10%). While our numerical results pertain to the minimal seesaw model only, our general procedure appears to be applicable to other neutrino mass models as well.

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.

Prediction models for solitary pulmonary nodules based on curvelet textural features and clinical parameters.

PubMed

Wang, Jing-Jing; Wu, Hai-Feng; Sun, Tao; Li, Xia; Wang, Wei; Tao, Li-Xin; Huo, Da; Lv, Ping-Xin; He, Wen; Guo, Xiu-Hua

2013-01-01

Lung cancer, one of the leading causes of cancer-related deaths, usually appears as solitary pulmonary nodules (SPNs) which are hard to diagnose using the naked eye. In this paper, curvelet-based textural features and clinical parameters are used with three prediction models [a multilevel model, a least absolute shrinkage and selection operator (LASSO) regression method, and a support vector machine (SVM)] to improve the diagnosis of benign and malignant SPNs. Dimensionality reduction of the original curvelet-based textural features was achieved using principal component analysis. In addition, non-conditional logistical regression was used to find clinical predictors among demographic parameters and morphological features. The results showed that, combined with 11 clinical predictors, the accuracy rates using 12 principal components were higher than those using the original curvelet-based textural features. To evaluate the models, 10-fold cross validation and back substitution were applied. The results obtained, respectively, were 0.8549 and 0.9221 for the LASSO method, 0.9443 and 0.9831 for SVM, and 0.8722 and 0.9722 for the multilevel model. All in all, it was found that using curvelet-based textural features after dimensionality reduction and using clinical predictors, the highest accuracy rate was achieved with SVM. The method may be used as an auxiliary tool to differentiate between benign and malignant SPNs in CT images.

Texture of low-fat Iranian White cheese as influenced by gum tragacanth as a fat replacer.

PubMed

Rahimi, J; Khosrowshahi, A; Madadlou, A; Aziznia, S

2007-09-01

The effect of different concentrations of gum tragacanth on the textural characteristics of low-fat Iranian White cheese was studied during ripening. A batch of full-fat and 5 batches of low-fat Iranian White cheeses with different gum tragacanth concentrations (without gum or with 0.25, 0.5, 0.75, or 1 g of gum/kg of milk) were produced to study the effects of fat content reduction and gum concentration on the textural and functional properties of the product during ripening. Cheese samples were analyzed with respect to chemical, color, and sensory characteristics, rheological parameters (uniaxial compression and small-amplitude oscillatory shear), and microstructure. Reducing the fat content had an adverse effect on cheese yield, sensory characteristics, and the texture of Iranian White cheese, and it increased the instrumental hardness parameters (i.e., fracture stress, elastic modulus, storage modulus, and complex modulus). However, increasing the gum tragacanth concentration reduced the values of instrumental hardness parameters and increased the whiteness of cheese. Although when the gum concentration was increased, the low-fat cheese somewhat resembled its full-fat counterpart, the interaction of the gum concentration with ripening time caused visible undesirable effects on cheese characteristics by the sixth week of ripening. Cheeses with a high gum tragacanth concentration became very soft and their solid texture declined somewhat.

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

Effect of Duck Feet Gelatin on Physicochemical, Textural, and Sensory Properties of Low-fat Frankfurters

PubMed Central

2014-01-01

Duck feet gelatin (DFG) gel was added as a fat replacer to low-fat frankfurters and the effect of DFG on physicochemical, textural, and sensory characteristics of low-fat frankfurters was evaluated. DFG gel was prepared with a 20% duck feet gelatin concentration (w/w). Adding DFG decreased lightness and increased yellowness of the low-fat frankfurters (p<0.05). However, DFG did not affect redness of low-fat frankfurters (p>0.05). The statistical results indicated that adding DFG improved cooking yield of low-fat frankfurters (p<0.05). In addition, replacing pork back fat with DFG resulted in increased moisture content, protein content, and ash content of low-fat frankfurters, and the low-fat frankfurter formulated with 5% pork back fat and 15% DFG gel had the highest moisture content and lowest fat content (p<0.05). Adding of DFG increased all textural parameters including hardness, springiness, cohesiveness, chewiness, and gumminess of low-fat frankfurters (p<0.05). In terms of sensory properties, the low-fat frankfurter formulated with 5% pork back fat and 15% DFG gel showed similar satisfaction scores for the flavor, tenderness, juiciness, and overall acceptance when compared to the regular frankfurters (20% back fat). Therefore, our results suggest that DFG could be an effective novel source, as a fat replacer, for manufacturing of low-fat frankfurters. PMID:26761279

Effect of Duck Feet Gelatin on Physicochemical, Textural, and Sensory Properties of Low-fat Frankfurters.

PubMed

Yeo, Eui-Joo; Kim, Hyun-Wook; Hwang, Ko-Eun; Song, Dong-Heon; Kim, Yong-Jae; Ham, Youn-Kyung; He, Fu-Yi; Park, Jae-Hyun; Kim, Cheon-Jei

2014-01-01

Duck feet gelatin (DFG) gel was added as a fat replacer to low-fat frankfurters and the effect of DFG on physicochemical, textural, and sensory characteristics of low-fat frankfurters was evaluated. DFG gel was prepared with a 20% duck feet gelatin concentration (w/w). Adding DFG decreased lightness and increased yellowness of the low-fat frankfurters (p<0.05). However, DFG did not affect redness of low-fat frankfurters (p>0.05). The statistical results indicated that adding DFG improved cooking yield of low-fat frankfurters (p<0.05). In addition, replacing pork back fat with DFG resulted in increased moisture content, protein content, and ash content of low-fat frankfurters, and the low-fat frankfurter formulated with 5% pork back fat and 15% DFG gel had the highest moisture content and lowest fat content (p<0.05). Adding of DFG increased all textural parameters including hardness, springiness, cohesiveness, chewiness, and gumminess of low-fat frankfurters (p<0.05). In terms of sensory properties, the low-fat frankfurter formulated with 5% pork back fat and 15% DFG gel showed similar satisfaction scores for the flavor, tenderness, juiciness, and overall acceptance when compared to the regular frankfurters (20% back fat). Therefore, our results suggest that DFG could be an effective novel source, as a fat replacer, for manufacturing of low-fat frankfurters.

Texture analysis of pulmonary parenchyma in normal and emphysematous lung

NASA Astrophysics Data System (ADS)

Uppaluri, Renuka; Mitsa, Theophano; Hoffman, Eric A.; McLennan, Geoffrey; Sonka, Milan

1996-04-01

Tissue characterization using texture analysis is gaining increasing importance in medical imaging. We present a completely automated method for discriminating between normal and emphysematous regions from CT images. This method involves extracting seventeen features which are based on statistical, hybrid and fractal texture models. The best subset of features is derived from the training set using the divergence technique. A minimum distance classifier is used to classify the samples into one of the two classes--normal and emphysema. Sensitivity and specificity and accuracy values achieved were 80% or greater in most cases proving that texture analysis holds great promise in identifying emphysema.

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.

Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters.

PubMed

Galavis, Paulina E; Hollensen, Christian; Jallow, Ngoneh; Paliwal, Bhudatt; Jeraj, Robert

2010-10-01

Characterization of textural features (spatial distributions of image intensity levels) has been considered as a tool for automatic tumor segmentation. The purpose of this work is to study the variability of the textural features in PET images due to different acquisition modes and reconstruction parameters. Twenty patients with solid tumors underwent PET/CT scans on a GE Discovery VCT scanner, 45-60 minutes post-injection of 10 mCi of [(18)F]FDG. Scans were acquired in both 2D and 3D modes. For each acquisition the raw PET data was reconstructed using five different reconstruction parameters. Lesions were segmented on a default image using the threshold of 40% of maximum SUV. Fifty different texture features were calculated inside the tumors. The range of variations of the features were calculated with respect to the average value. Fifty textural features were classified based on the range of variation in three categories: small, intermediate and large variability. Features with small variability (range ≤ 5%) were entropy-first order, energy, maximal correlation coefficient (second order feature) and low-gray level run emphasis (high-order feature). The features with intermediate variability (10% ≤ range ≤ 25%) were entropy-GLCM, sum entropy, high gray level run emphsis, gray level non-uniformity, small number emphasis, and entropy-NGL. Forty remaining features presented large variations (range > 30%). Textural features such as entropy-first order, energy, maximal correlation coefficient, and low-gray level run emphasis exhibited small variations due to different acquisition modes and reconstruction parameters. Features with low level of variations are better candidates for reproducible tumor segmentation. Even though features such as contrast-NGTD, coarseness, homogeneity, and busyness have been previously used, our data indicated that these features presented large variations, therefore they could not be considered as a good candidates for tumor segmentation.

Variability of textural features in FDG PET images due to different acquisition modes and reconstruction parameters

PubMed Central

GALAVIS, PAULINA E.; HOLLENSEN, CHRISTIAN; JALLOW, NGONEH; PALIWAL, BHUDATT; JERAJ, ROBERT

2014-01-01

Background Characterization of textural features (spatial distributions of image intensity levels) has been considered as a tool for automatic tumor segmentation. The purpose of this work is to study the variability of the textural features in PET images due to different acquisition modes and reconstruction parameters. Material and methods Twenty patients with solid tumors underwent PET/CT scans on a GE Discovery VCT scanner, 45–60 minutes post-injection of 10 mCi of [18F]FDG. Scans were acquired in both 2D and 3D modes. For each acquisition the raw PET data was reconstructed using five different reconstruction parameters. Lesions were segmented on a default image using the threshold of 40% of maximum SUV. Fifty different texture features were calculated inside the tumors. The range of variations of the features were calculated with respect to the average value. Results Fifty textural features were classified based on the range of variation in three categories: small, intermediate and large variability. Features with small variability (range ≤ 5%) were entropy-first order, energy, maximal correlation coefficient (second order feature) and low-gray level run emphasis (high-order feature). The features with intermediate variability (10% ≤ range ≤ 25%) were entropy-GLCM, sum entropy, high gray level run emphsis, gray level non-uniformity, small number emphasis, and entropy-NGL. Forty remaining features presented large variations (range > 30%). Conclusion Textural features such as entropy-first order, energy, maximal correlation coefficient, and low-gray level run emphasis exhibited small variations due to different acquisition modes and reconstruction parameters. Features with low level of variations are better candidates for reproducible tumor segmentation. Even though features such as contrast-NGTD, coarseness, homogeneity, and busyness have been previously used, our data indicated that these features presented large variations, therefore they could not be considered as a good candidates for tumor segmentation. PMID:20831489

Nd:YOV4 laser surface texturing on DLC coating: Effect on morphology, adhesion, and dry wear behavior

NASA Astrophysics Data System (ADS)

Surfaro, Maria; Giorleo, Luca; Montesano, Lorenzo; Allegri, Gabriele; Ceretti, Elisabetta; La Vecchia, Giovina Marina

2018-05-01

The surface of structural components is usually subjected to higher stresses, greater wear or fatigue damage, and more direct environmental exposure than the inner parts. For this reason, the interest to improve superficial properties of items is constantly increasing in different fields as automotive, electronic, biomedical, etc. Different approaches can be used to achieve this goal: case hardening by means of superficial heat treatments like carburizing or nitriding, deposition of thin or thick coatings, roughness modification, etc. Between the available technologies to modify components surface, Laser Surface Texturing (LST) has already been recognized in the last decade as a process, which improves the tribological properties of various parts. Based on these considerations the aim of the present research work was to realize a controlled laser texture on a Diamond-like Carbon (DLC) thin coating (about 3 µm thick) without damaging both the coating itself and the substrate. In particular, the effect of laser process parameters as marking speed and loop cycle were investigated in terms of texture features modifications. Both qualitative and quantitative analyses of the texture were executed by using a scanning electron microscope and a laser probe system to select the proper laser parameters. Moreover, the effect of the selected texture on the DLC nanohardness, adhesion and wear behavior was pointed out.

Optimization of consolidation parameters of 18Cr-ODS ferritic steel through microstructural and microtexture characterization

NASA Astrophysics Data System (ADS)

Dash, Manmath Kumar; Mythili, R.; Dasgupta, Arup; Saroja, S.

2018-04-01

This paper reports the optimization of consolidation process based on the evolution of microstructure, microtexture and densification in 18%-Cr Oxide Dispersion Strengthened steel. The steel powder of composition Fe-18Cr-0.01C-2W-0.25Ti-0.35Y2O3 has been consolidated by cold isostatic pressing (CIP) for green compaction after mechanical milling. Sintering (1000-1250 °C) and hot isostatic pressing (HIP) at 1150 °C has been employed to achieve good densification on compacted CIP specimen. The effect of sintering temperatures on densification behavior was evaluated and sintering at 1150°C was identified to be optimum for achieving good compaction (92% density) and homogeneous polygonal microstructure with a uniform distribution of fine pores. In addition, HIP of CIP product at 1150°C was found to yield a more homogeneous microstructure as compared to sintered product with 97% density. A static/dynamic recrystallization associated with (1 1 1) texture is observed during consolidation process. A statistical comparison has been made based on frequency of grain boundary distribution and associated texture with its theoretical attributes.

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.

Experimental studies on the physico-mechanical properties of jet-grout columns in sandy and silty soils

NASA Astrophysics Data System (ADS)

Akin, Muge K.

2016-04-01

The term of ground improvement states to the modification of the engineering properties of soils. Jet-grouting is one of the grouting methods among various ground improvement techniques. During jet-grouting, different textures of columns can be obtained depending on the characteristics of surrounding subsoil as well as the adopted jet-grouting system for each site is variable. In addition to textural properties, strength and index parameters of jet-grout columns are highly affected by the adjacent soil. In this study, the physical and mechanical properties of jet-grout columns constructed at two different sites in silty and sandy soil conditions were determined by laboratory tests. A number of statistical relationships between physical and mechanical properties of soilcrete were established in this study in order to investigate the dependency of numerous variables. The relationship between qu and γd is more reliable for sandy soilcrete than that of silty columns considering the determination coefficients. Positive linear relationships between Vp and γd with significantly high determination coefficients were obtained for the jet-grout columns in silt and sand. The regression analyses indicate that the P-wave velocity is a very dominant parameter for the estimation of physical and mechanical properties of jet-grout columns and should be involved during the quality control of soilcrete material despite the intensive use of uniaxial compressive strength test. Besides, it is concluded that the dry unit weight of jet-grout column is a good indicator of the efficiency of employed operational parameters during jet-grouting.

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

PubMed

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

2014-02-01

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

Cold Gas-Sprayed Deposition of Metallic Coatings onto Ceramic Substrates Using Laser Surface Texturing Pre-treatment

NASA Astrophysics Data System (ADS)

Kromer, R.; Danlos, Y.; Costil, S.

2018-04-01

Cold spraying enables a variety of metals dense coatings onto metal surfaces. Supersonic gas jet accelerates particles which undergo with the substrate plastic deformation. Different bonding mechanisms can be created depending on the materials. The particle-substrate contact time, contact temperature and contact area upon impact are the parameters influencing physicochemical and mechanical bonds. The resultant bonding arose from plastic deformation of the particle and substrate and temperature increasing at the interface. The objective was to create specific topography to enable metallic particle adhesion onto ceramic substrates. Ceramic did not demonstrate deformation during the impact which minimized the intimate bonds. Laser surface texturing was hence used as prior surface treatment to create specific topography and to enable mechanical anchoring. Particle compressive states were necessary to build up coating. The coating deposition efficiency and adhesion strength were evaluated. Textured surface is required to obtain strong adhesion of metallic coatings onto ceramic substrates. Consequently, cold spray coating parameters depend on the target material and a methodology was established with particle parameters (diameters, velocities, temperatures) and particle/substrate properties to adapt the surface topography. Laser surface texturing is a promising tool to increase the cold spraying applications.

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

PubMed

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

2008-11-01

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

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.

The discrimination of sea ice types using SAR backscatter statistics

NASA Technical Reports Server (NTRS)

Shuchman, Robert A.; Wackerman, Christopher C.; Maffett, Andrew L.; Onstott, Robert G.; Sutherland, Laura L.

1989-01-01

X-band (HH) synthetic aperture radar (SAR) data of sea ice collected during the Marginal Ice Zone Experiment in March and April of 1987 was statistically analyzed with respect to discriminating open water, first-year ice, multiyear ice, and Odden. Odden are large expanses of nilas ice that rapidly form in the Greenland Sea and transform into pancake ice. A first-order statistical analysis indicated that mean versus variance can segment out open water and first-year ice, and skewness versus modified skewness can segment the Odden and multilayer categories. In additions to first-order statistics, a model has been generated for the distribution function of the SAR ice data. Segmentation of ice types was also attempted using textural measurements. In this case, the general co-occurency matrix was evaluated. The textural method did not generate better results than the first-order statistical approach.

Modulating Thin Film Transistor Characteristics by Texturing the Gate Metal.

PubMed

Nair, Aswathi; Bhattacharya, Prasenjit; Sambandan, Sanjiv

2017-12-20

The development of reliable, high performance integrated circuits based on thin film transistors (TFTs) is of interest for the development of flexible electronic circuits. In this work we illustrate the modulation of TFT transconductance via the texturing of the gate metal created by the addition of a conductive pattern on top of a planar gate. Texturing results in the semiconductor-insulator interface acquiring a non-planar geometry with local variations in the radius of curvature. This influences various TFT parameters such as the subthreshold slope, gate voltage at the onset of conduction, contact resistance and gate capacitance. Specific studies are performed on textures based on periodic striations oriented along different directions. Textured TFTs showed upto ±40% variation in transconductance depending on the texture orientation as compared to conventional planar gate TFTs. Analytical models are developed and compared with experiments. Gain boosting in common source amplifiers based on textured TFTs as compared to conventional TFTs is demonstrated.

Influence of additive laser manufacturing parameters on surface using density of partially melted particles

NASA Astrophysics Data System (ADS)

Rosa, Benoit; Brient, Antoine; Samper, Serge; Hascoët, Jean-Yves

2016-12-01

Mastering the additive laser manufacturing surface is a real challenge and would allow functional surfaces to be obtained without finishing. Direct Metal Deposition (DMD) surfaces are composed by directional and chaotic textures that are directly linked to the process principles. The aim of this work is to obtain surface topographies by mastering the operating process parameters. Based on experimental investigation, the influence of operating parameters on the surface finish has been modeled. Topography parameters and multi-scale analysis have been used in order to characterize the DMD obtained surfaces. This study also proposes a methodology to characterize DMD chaotic texture through topography filtering and 3D image treatment. In parallel, a new parameter is proposed: density of particles (D p). Finally, this study proposes a regression modeling between process parameters and density of particles parameter.

Texture-preserved penalized weighted least-squares reconstruction of low-dose CT image via image segmentation and high-order MRF modeling

NASA Astrophysics Data System (ADS)

Han, Hao; Zhang, Hao; Wei, Xinzhou; Moore, William; Liang, Zhengrong

2016-03-01

In this paper, we proposed a low-dose computed tomography (LdCT) image reconstruction method with the help of prior knowledge learning from previous high-quality or normal-dose CT (NdCT) scans. The well-established statistical penalized weighted least squares (PWLS) algorithm was adopted for image reconstruction, where the penalty term was formulated by a texture-based Gaussian Markov random field (gMRF) model. The NdCT scan was firstly segmented into different tissue types by a feature vector quantization (FVQ) approach. Then for each tissue type, a set of tissue-specific coefficients for the gMRF penalty was statistically learnt from the NdCT image via multiple-linear regression analysis. We also proposed a scheme to adaptively select the order of gMRF model for coefficients prediction. The tissue-specific gMRF patterns learnt from the NdCT image were finally used to form an adaptive MRF penalty for the PWLS reconstruction of LdCT image. The proposed texture-adaptive PWLS image reconstruction algorithm was shown to be more effective to preserve image textures than the conventional PWLS image reconstruction algorithm, and we further demonstrated the gain of high-order MRF modeling for texture-preserved LdCT PWLS image reconstruction.

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

Increase of Breakthrough Pressure of Cotton Fabric by Fluoropolymer/Fluoroposs Treatment

DTIC Science & Technology

2011-11-29

obtaining superhydrophobic and superolcophobic textured surfaces. Geometrical parameters based on these textures have been developed to model predicted...contact angles with liquids of varying surfaces tensions. One way of determining the robustness of the superhydrophobic state is to study the

Role of deformation temperature on the evolution and heterogeneity of texture during equal channel angular pressing of magnesium

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

Biswas, Somjeet, E-mail: somjeetbiswas@gmail.com; Department of Materials Engineering, Indian Institute of Science, Bangalore 560012; Laboratory of Excellence on Design of Alloy Metals for low-mAss Structures

Investigations on texture evolution and through-thickness texture heterogeneity during equal channel angular pressing (ECAP) of pure magnesium at 200 °C, 150 °C and room temperature (RT) was carried out by neutron, high energy synchrotron X-ray and electron back-scatter diffraction. Irrespective of the ECAP temperature, a distinctive basal (B) and pyramidal (C{sub 2}) II type of fibers forms. The texture differs in the bottom 1 mm portion, where the B-fiber is shifted ~ 55° due to negative shear attributed to friction. - Highlights: • ECAP of magnesium was carried out at 200 °C, 150 °C and room temperature. • Microstructure andmore » micro-texture evolution was examined using EBSD in FEG–SEM. • Bulk-texture was studied using neutron diffraction and compared with micro-texture. • Through thickness texture heterogeneity was observed by synchrotron radiation. • Changes in these parameters with respect to deformation temperature are discussed.« less

SU-F-R-20: Image Texture Features Correlate with Time to Local Failure in Lung SBRT Patients

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

Andrews, M; Abazeed, M; Woody, N

Purpose: To explore possible correlation between CT image-based texture and histogram features and time-to-local-failure in early stage non-small cell lung cancer (NSCLC) patients treated with stereotactic body radiotherapy (SBRT).Methods and Materials: From an IRB-approved lung SBRT registry for patients treated between 2009–2013 we selected 48 (20 male, 28 female) patients with local failure. Median patient age was 72.3±10.3 years. Mean time to local failure was 15 ± 7.1 months. Physician-contoured gross tumor volumes (GTV) on the planning CT images were processed and 3D gray-level co-occurrence matrix (GLCM) based texture and histogram features were calculated in Matlab. Data were exported tomore » R and a multiple linear regression model was used to examine the relationship between texture features and time-to-local-failure. Results: Multiple linear regression revealed that entropy (p=0.0233, multiple R2=0.60) from GLCM-based texture analysis and the standard deviation (p=0.0194, multiple R2=0.60) from the histogram-based features were statistically significantly correlated with the time-to-local-failure. Conclusion: Image-based texture analysis can be used to predict certain aspects of treatment outcomes of NSCLC patients treated with SBRT. We found entropy and standard deviation calculated for the GTV on the CT images displayed a statistically significant correlation with and time-to-local-failure in lung SBRT patients.« less

A perceptual space of local image statistics.

PubMed

Victor, Jonathan D; Thengone, Daniel J; Rizvi, Syed M; Conte, Mary M

2015-12-01

Local image statistics are important for visual analysis of textures, surfaces, and form. There are many kinds of local statistics, including those that capture luminance distributions, spatial contrast, oriented segments, and corners. While sensitivity to each of these kinds of statistics have been well-studied, much less is known about visual processing when multiple kinds of statistics are relevant, in large part because the dimensionality of the problem is high and different kinds of statistics interact. To approach this problem, we focused on binary images on a square lattice - a reduced set of stimuli which nevertheless taps many kinds of local statistics. In this 10-parameter space, we determined psychophysical thresholds to each kind of statistic (16 observers) and all of their pairwise combinations (4 observers). Sensitivities and isodiscrimination contours were consistent across observers. Isodiscrimination contours were elliptical, implying a quadratic interaction rule, which in turn determined ellipsoidal isodiscrimination surfaces in the full 10-dimensional space, and made predictions for sensitivities to complex combinations of statistics. These predictions, including the prediction of a combination of statistics that was metameric to random, were verified experimentally. Finally, check size had only a mild effect on sensitivities over the range from 2.8 to 14min, but sensitivities to second- and higher-order statistics was substantially lower at 1.4min. In sum, local image statistics form a perceptual space that is highly stereotyped across observers, in which different kinds of statistics interact according to simple rules. Copyright © 2015 Elsevier Ltd. All rights reserved.

A perceptual space of local image statistics

PubMed Central

Victor, Jonathan D.; Thengone, Daniel J.; Rizvi, Syed M.; Conte, Mary M.

2015-01-01

Local image statistics are important for visual analysis of textures, surfaces, and form. There are many kinds of local statistics, including those that capture luminance distributions, spatial contrast, oriented segments, and corners. While sensitivity to each of these kinds of statistics have been well-studied, much less is known about visual processing when multiple kinds of statistics are relevant, in large part because the dimensionality of the problem is high and different kinds of statistics interact. To approach this problem, we focused on binary images on a square lattice – a reduced set of stimuli which nevertheless taps many kinds of local statistics. In this 10-parameter space, we determined psychophysical thresholds to each kind of statistic (16 observers) and all of their pairwise combinations (4 observers). Sensitivities and isodiscrimination contours were consistent across observers. Isodiscrimination contours were elliptical, implying a quadratic interaction rule, which in turn determined ellipsoidal isodiscrimination surfaces in the full 10-dimensional space, and made predictions for sensitivities to complex combinations of statistics. These predictions, including the prediction of a combination of statistics that was metameric to random, were verified experimentally. Finally, check size had only a mild effect on sensitivities over the range from 2.8 to 14 min, but sensitivities to second- and higher-order statistics was substantially lower at 1.4 min. In sum, local image statistics forms a perceptual space that is highly stereotyped across observers, in which different kinds of statistics interact according to simple rules. PMID:26130606

MRI textures as outcome predictor for Gamma Knife radiosurgery on vestibular schwannoma

NASA Astrophysics Data System (ADS)

Langenhuizen, P. P. J. H.; Legters, M. J. W.; Zinger, S.; Verheul, H. B.; Leenstra, S.; de With, P. H. N.

2018-02-01

Vestibular schwannomas (VS) are benign brain tumors that can be treated with high-precision focused radiation with the Gamma Knife in order to stop tumor growth. Outcome prediction of Gamma Knife radiosurgery (GKRS) treatment can help in determining whether GKRS will be effective on an individual patient basis. However, at present, prognostic factors of tumor control after GKRS for VS are largely unknown, and only clinical factors, such as size of the tumor at treatment and pre-treatment growth rate of the tumor, have been considered thus far. This research aims at outcome prediction of GKRS by means of quantitative texture feature analysis on conventional MRI scans. We compute first-order statistics and features based on gray-level co- occurrence (GLCM) and run-length matrices (RLM), and employ support vector machines and decision trees for classification. In a clinical dataset, consisting of 20 tumors showing treatment failure and 20 tumors exhibiting treatment success, we have discovered that the second-order statistical metrics distilled from GLCM and RLM are suitable for describing texture, but are slightly outperformed by simple first-order statistics, like mean, standard deviation and median. The obtained prediction accuracy is about 85%, but a final choice of the best feature can only be made after performing more extensive analyses on larger datasets. In any case, this work provides suitable texture measures for successful prediction of GKRS treatment outcome for VS.

Multi-year encoding of daily rainfall and streamflow via the fractal-multifractal method

NASA Astrophysics Data System (ADS)

Puente, C. E.; Maskey, M.; Sivakumar, B.

2017-12-01

A deterministic geometric approach, the fractal-multifractal (FM) method, which has been proven to be faithful in encoding daily geophysical sets over a year, is used to describe records over multiple years at a time. Looking for FM parameter trends over longer periods, the present study shows FM descriptions of daily rainfall and streamflow gathered over five consecutive years optimizing deviations on accumulated sets. The results for 100 and 60 sets of five years for rainfall streamflow, respectively, near Sacramento, California illustrate that: (a) encoding of both types of data sets may be accomplished with relatively small errors; and (b) predicting the geometry of both variables appears to be possible, even five years ahead, training neural networks on the respective FM parameters. It is emphasized that the FM approach not only captures the accumulated sets over successive pentades but also preserves other statistical attributes including the overall "texture" of the records.

Three-dimensional positron emission tomography image texture analysis of esophageal squamous cell carcinoma: relationship between tumor 18F-fluorodeoxyglucose uptake heterogeneity, maximum standardized uptake value, and tumor stage.

PubMed

Dong, Xinzhe; Xing, Ligang; Wu, Peipei; Fu, Zheng; Wan, Honglin; Li, Dengwang; Yin, Yong; Sun, Xiaorong; Yu, Jinming

2013-01-01

To explore the relationship of a new PET image parameter, (18)F-fluorodeoxyglucose ((18)F-FDG) uptake heterogeneity assessed by texture analysis, with maximum standardized uptake value (SUV(max)) and tumor TNM staging. Forty consecutive patients with esophageal squamous cell carcinoma were enrolled. All patients underwent whole-body preoperative (18)F-FDG PET/CT. Heterogeneity of intratumoral (18)F-FDG uptake was assessed on the basis of the textural features (entropy and energy) of the three-dimensional images using MATLAB software. The correlations between the textural parameters and SUV(max), histological grade, tumor location, and TNM stage were analyzed. Tumors with higher SUV(max) were seen to be more heterogenous on (18)F-FDG uptake. Significant correlations were observed between T stage and SUV(max) (r(s)=0.390, P=0.013), entropy (rs=0.693, P<0.001), and energy (r(s)=-0.469, P=0.002). Correlations were also found between SUV(max), entropy, energy, and N stage (r(s)=0.326, P=0.04; r(s)=0.501, P=0.001; r(s)=-0.413, P=0.008). The American Joint Committee on Cancer stage correlated significantly with all metabolic parameters. The receiver-operating characteristic curve demonstrated an entropy of 4.699 as the optimal cutoff point for detecting tumors above stage II(b) with an areas under the ROC curve of 0.789 (P<0.001). This study provides initial evidence for the relationship between the new parameter of tumor uptake heterogeneity and the commonly used simplistic parameter of SUV and tumor stage. Our findings suggest a complementary role of these parameters in the staging and prognosis of esophageal squamous cell carcinoma.

Effect of high hydrostatic pressure on the color and texture parameters of refrigerated Caiman (Caiman crocodilus yacare) tail meat.

PubMed

Canto, A C V C S; Lima, B R C C; Cruz, A G; Lázaro, C A; Freitas, D G C; Faria, Jose A F; Torrezan, R; Freitas, M Q; Silva, T P J

2012-07-01

The effect of applying high hydrostatic pressure (HHP) on the instrumental parameters of color and texture and sensory characteristics of alligator meat were evaluated. Samples of alligator tail meat were sliced, vacuum-packed, pressurized and distributed into four groups: control, treated with 200 MPa/10 min, 300 MPa/10 min and 400 MPa/10 min, then stored at 4°C±1°C for 45 days. Instrumental color, texture profile and a sensory profiling using quantitative descriptive analysis were carried out on the 1st, 15th, 30th and 45th days of storage. HHP was shown to affect the color and texture of the product, and the sensory descriptors (p<0.05). The results suggest that high pressure is a promising technology for the processing of alligator meat, especially low pressures (200 MPa) which can have positive effects on the quality of the product. Copyright © 2012 Elsevier Ltd. All rights reserved.

Understanding the effect of watershed characteristic on the runoff using SCS curve number

NASA Astrophysics Data System (ADS)

Damayanti, Frieta; Schneider, Karl

2015-04-01

Runoff modeling is a key component in watershed management. The temporal course and amount of runoff is a complex function of a multitude of parameters such as climate, soil, topography, land use, and water management. Against the background of the current rapid environmental change, which is due to both i) man-made changes (e.g. urban development, land use change, water management) as well as ii) changes in the natural systems (e.g. climate change), understanding and predicting the impacts of these changes upon the runoff is very important and affects the wellbeing of many people living in the watershed. A main tool for predictions is hydrologic models. Particularly process based models are the method of choice to assess the impact of land use and climate change. However, many regions which experience large changes in the watersheds can be described as rather data poor, which limits the applicability of such models. This is particularly also true for the Telomoyo Watershed (545 km2) which is located in southern part of Central Java province. The average annual rainfall of the study area reaches 2971 mm. Irrigated paddy field are the dominating land use (35%), followed by built-up area and dry land agriculture. The only available soil map is the FAO soil digital map of the world, which provides rather general soil information. A field survey accompanied by a lab analysis 65 soil samples of was carried out to provide more detailed soil texture information. The soil texture map is a key input in the SCS method to define hydrological soil groups. In the frame of our study on 'Integrated Analysis on Flood Risk of Telomoyo Watershed in Response to the Climate and Land Use Change' funded by the German Academic Exchange service (DAAD) we analyzed the sensitivity of the modeled runoff upon the choice of the method to estimate the CN values using the SCS-CN method. The goal of this study is to analyze the impact of different data sources on the curve numbers and the estimated runoff. CN values were estimated using the field measurements of soil textures for different combinations of land use and topography. To transfer the local soil texture measurements to the watershed domain a statistical analysis using the frequency distribution of the measured soil textures is applied and used to derive the effective CN value for a given land use, topography and soil texture combination. Since the curve numbers change as a function of parameter combinations, the effect of different methods to estimate the curve number upon the runoff is analyzed and compared to the straight forward method of using the data from the FAO soil map.

Built-up Areas Extraction in High Resolution SAR Imagery based on the method of Multiple Feature Weighted Fusion

NASA Astrophysics Data System (ADS)

Liu, X.; Zhang, J. X.; Zhao, Z.; Ma, A. D.

2015-06-01

Synthetic aperture radar in the application of remote sensing technology is becoming more and more widely because of its all-time and all-weather operation, feature extraction research in high resolution SAR image has become a hot topic of concern. In particular, with the continuous improvement of airborne SAR image resolution, image texture information become more abundant. It's of great significance to classification and extraction. In this paper, a novel method for built-up areas extraction using both statistical and structural features is proposed according to the built-up texture features. First of all, statistical texture features and structural features are respectively extracted by classical method of gray level co-occurrence matrix and method of variogram function, and the direction information is considered in this process. Next, feature weights are calculated innovatively according to the Bhattacharyya distance. Then, all features are weighted fusion. At last, the fused image is classified with K-means classification method and the built-up areas are extracted after post classification process. The proposed method has been tested by domestic airborne P band polarization SAR images, at the same time, two groups of experiments based on the method of statistical texture and the method of structural texture were carried out respectively. On the basis of qualitative analysis, quantitative analysis based on the built-up area selected artificially is enforced, in the relatively simple experimentation area, detection rate is more than 90%, in the relatively complex experimentation area, detection rate is also higher than the other two methods. In the study-area, the results show that this method can effectively and accurately extract built-up areas in high resolution airborne SAR imagery.

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

PubMed

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

2018-03-01

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

Textural Analysis and Substrate Classification in the Nearshore Region of Lake Superior Using High-Resolution Multibeam Bathymetry

NASA Astrophysics Data System (ADS)

Dennison, Andrew G.

Classification of the seafloor substrate can be done with a variety of methods. These methods include Visual (dives, drop cameras); mechanical (cores, grab samples); acoustic (statistical analysis of echosounder returns). Acoustic methods offer a more powerful and efficient means of collecting useful information about the bottom type. Due to the nature of an acoustic survey, larger areas can be sampled, and by combining the collected data with visual and mechanical survey methods provide greater confidence in the classification of a mapped region. During a multibeam sonar survey, both bathymetric and backscatter data is collected. It is well documented that the statistical characteristic of a sonar backscatter mosaic is dependent on bottom type. While classifying the bottom-type on the basis on backscatter alone can accurately predict and map bottom-type, i.e a muddy area from a rocky area, it lacks the ability to resolve and capture fine textural details, an important factor in many habitat mapping studies. Statistical processing of high-resolution multibeam data can capture the pertinent details about the bottom-type that are rich in textural information. Further multivariate statistical processing can then isolate characteristic features, and provide the basis for an accurate classification scheme. The development of a new classification method is described here. It is based upon the analysis of textural features in conjunction with ground truth sampling. The processing and classification result of two geologically distinct areas in nearshore regions of Lake Superior; off the Lester River,MN and Amnicon River, WI are presented here, using the Minnesota Supercomputer Institute's Mesabi computing cluster for initial processing. Processed data is then calibrated using ground truth samples to conduct an accuracy assessment of the surveyed areas. From analysis of high-resolution bathymetry data collected at both survey sites is was possible to successfully calculate a series of measures that describe textural information about the lake floor. Further processing suggests that the features calculated capture a significant amount of statistical information about the lake floor terrain as well. Two sources of error, an anomalous heave and refraction error significantly deteriorated the quality of the processed data and resulting validate results. Ground truth samples used to validate the classification methods utilized for both survey sites, however, resulted in accuracy values ranging from 5 -30 percent at the Amnicon River, and between 60-70 percent for the Lester River. The final results suggest that this new processing methodology does adequately capture textural information about the lake floor and does provide an acceptable classification in the absence of significant data quality issues.

Analytical solution for haze values of aluminium-induced texture (AIT) glass superstrates for a-Si:H solar cells.

PubMed

Sahraei, Nasim; Forberich, Karen; Venkataraj, Selvaraj; Aberle, Armin G; Peters, Marius

2014-01-13

Light scattering at randomly textured interfaces is essential to improve the absorption of thin-film silicon solar cells. Aluminium-induced texture (AIT) glass provides suitable scattering for amorphous silicon (a-Si:H) solar cells. The scattering properties of textured surfaces are usually characterised by two properties: the angularly resolved intensity distribution and the haze. However, we find that the commonly used haze equations cannot accurately describe the experimentally observed spectral dependence of the haze of AIT glass. This is particularly the case for surface morphologies with a large rms roughness and small lateral feature sizes. In this paper we present an improved method for haze calculation, based on the power spectral density (PSD) function of the randomly textured surface. To better reproduce the measured haze characteristics, we suggest two improvements: i) inclusion of the average lateral feature size of the textured surface into the haze calculation, and ii) considering the opening angle of the haze measurement. We show that with these two improvements an accurate prediction of the haze of AIT glass is possible. Furthermore, we use the new equation to define optimum morphology parameters for AIT glass to be used for a-Si:H solar cell applications. The autocorrelation length is identified as the critical parameter. For the investigated a-Si:H solar cells, the optimum autocorrelation length is shown to be 320 nm.

The effect of pineapple core fiber on dough rheology and the quality of mantou.

PubMed

Shiau, Sy-Yu; Wu, Ming-Yin; Liu, Yao-Ling

2015-09-01

The consumption of dietary fiber offers the health benefit of lowering the risk of many chronic diseases. Pineapple core fiber (PCF) in this study was extracted and incorporated into dough and mantou (i.e., steamed bread). The effects of PCF substitution and fiber size on textural and rheological properties of dough and mantou were evaluated by a texture analyzer. The substitution of wheat flour by PCF resulted in a stiffer and less extensible dough with or without fermentation. The hardness and gumminess of mantou significantly increased as the PCF substitution increased from 0% to 15%, but the cohesiveness, specific volume, and elasticity significantly decreased with the fiber substitution. Ten percent PCF-enriched dough and mantou with various fiber sizes had similar rheological and textural properties, except for the k 1 and k 2 values. By sensory evaluation, 5% PCF-enriched mantou and the control bread had better acceptability in texture, color, odor, and overall acceptability, compared to mantous enriched with 10% or 15% PCF. Significant correlations existed between the rheological properties of dough and textural parameters of mantou and between the sensory quality and textural parameters of mantou. Therefore, we suggest that fiber-enriched mantou can be prepared with 5% PCF substitution to increase the intake of dietary fiber and maintain the quality of mantou. Copyright © 2014. Published by Elsevier B.V.

A candidate gene based approach validates Md-PG1 as the main responsible for a QTL impacting fruit texture in apple (Malus x domestica Borkh)

PubMed Central

2013-01-01

Background Apple is a widely cultivated fruit crop for its quality properties and extended storability. Among the several quality factors, texture is the most important and appreciated, and within the apple variety panorama the cortex texture shows a broad range of variability. Anatomically these variations depend on degradation events occurring in both fruit primary cell wall and middle lamella. This physiological process is regulated by an enzymatic network generally encoded by large gene families, among which polygalacturonase is devoted to the depolymerization of pectin. In apple, Md-PG1, a key gene belonging to the polygalacturonase gene family, was mapped on chromosome 10 and co-localized within the statistical interval of a major hot spot QTL associated to several fruit texture sub-phenotypes. Results In this work, a QTL corresponding to the position of Md-PG1 was validated and new functional alleles associated to the fruit texture properties in 77 apple cultivars were discovered. 38 SNPs genotyped by gene full length resequencing and 2 SSR markers ad hoc targeted in the gene metacontig were employed. Out of this SNP set, eleven were used to define three significant haplotypes statistically associated to several texture components. The impact of Md-PG1 in the fruit cell wall disassembly was further confirmed by the cortex structure electron microscope scanning in two apple varieties characterized by opposite texture performance, such as ‘Golden Delicious’ and ‘Granny Smith’. Conclusions The results here presented step forward into the genetic dissection of fruit texture in apple. This new set of haplotypes, and microsatellite alleles, can represent a valuable toolbox for a more efficient parental selection as well as the identification of new apple accessions distinguished by superior fruit quality features. PMID:23496960

Effects of morphology parameters on anti-icing performance in superhydrophobic surfaces

NASA Astrophysics Data System (ADS)

Nguyen, Thanh-Binh; Park, Seungchul; Lim, Hyuneui

2018-03-01

In this paper, we report the contributions of actual ice-substrate contact area and nanopillar height to passive anti-icing performance in terms of adhesion force and freezing time. Well-textured nanopillars with various parameters were fabricated via colloidal lithography and a dry etching process. The nanostructured quartz surface was coated with low-energy material to confer water-repellent properties. These superhydrophobic surfaces were investigated to determine the parameters essential for reducing adhesion strength and delaying freezing time. A well-textured surface with nanopillars of very small top diameter, regardless of height, could reduce adhesion force and delay freezing time in a subsequent de-icing process. Small top diameters of nanopillars also ensured the metastable Cassie-Baxter state based on energy barrier calculations. The results demonstrated the important role of areal fraction in anti-icing efficiency, and the negligible contribution of texture height. This insight into icing phenomena should lead to design of improved ice-phobic surfaces in the future.

A Study for Texture Feature Extraction of High-Resolution Satellite Images Based on a Direction Measure and Gray Level Co-Occurrence Matrix Fusion Algorithm

PubMed Central

Zhang, Xin; Cui, Jintian; Wang, Weisheng; Lin, Chao

2017-01-01

To address the problem of image texture feature extraction, a direction measure statistic that is based on the directionality of image texture is constructed, and a new method of texture feature extraction, which is based on the direction measure and a gray level co-occurrence matrix (GLCM) fusion algorithm, is proposed in this paper. This method applies the GLCM to extract the texture feature value of an image and integrates the weight factor that is introduced by the direction measure to obtain the final texture feature of an image. A set of classification experiments for the high-resolution remote sensing images were performed by using support vector machine (SVM) classifier with the direction measure and gray level co-occurrence matrix fusion algorithm. Both qualitative and quantitative approaches were applied to assess the classification results. The experimental results demonstrated that texture feature extraction based on the fusion algorithm achieved a better image recognition, and the accuracy of classification based on this method has been significantly improved. PMID:28640181

Texturing of continuous LOD meshes with the hierarchical texture atlas

NASA Astrophysics Data System (ADS)

Birkholz, Hermann

2006-02-01

For the rendering of detailed virtual environments, trade-offs have to be made between image quality and rendering time. An immersive experience of virtual reality always demands high frame-rates with the best reachable image qual-ity. Continuous Level of Detail (cLoD) triangle-meshes provide an continuous spectrum of detail for a triangle mesh that can be used to create view-dependent approximations of the environment in real-time. This enables the rendering with a constant number of triangles and thus with constant frame-rates. Normally the construction of such cLoD mesh representations leads to the loss of all texture information of the original mesh. To overcome this problem, a parameter domain can be created, in order to map the surface properties (colour, texture, normal) to it. This parameter domain can be used to map the surface properties back to arbitrary approximations of the original mesh. The parameter domain is often a simplified version of the mesh to be parameterised. This limits the reachable simplification to the domain mesh which has to map the surface of the original mesh with the least possible stretch. In this paper, a hierarchical domain mesh is presented, that scales between very coarse domain meshes and good property-mapping.

A Novel Microcharacterization Technique in the Measurement of Strain and Orientation Gradient in Advanced Materials

NASA Technical Reports Server (NTRS)

Garmestai, H.; Harris, K.; Lourenco, L.

1997-01-01

Representation of morphology and evolution of the microstructure during processing and their relation to properties requires proper experimental techniques. Residual strains, lattice distortion, and texture (micro-texture) at the interface and the matrix of a layered structure or a functionally gradient material and their variation are among parameters important in materials characterization but hard to measure with present experimental techniques. Current techniques available to measure changes in interred material parameters (residual stress, micro-texture, microplasticity) produce results which are either qualitative or unreliable. This problem becomes even more complicated in the case of a temperature variation. These parameters affect many of the mechanical properties of advanced materials including stress-strain relation, ductility, creep, and fatigue. A review of some novel experimental techniques using recent advances in electron microscopy is presented here to measure internal stress, (micro)texture, interracial strength and (sub)grain formation and realignment. Two of these techniques are combined in the chamber of an Environmental Scanning Electron Microscope to measure strain and orientation gradients in advanced materials. These techniques which include Backscattered Kikuchi Diffractometry (BKD) and Microscopic Strain Field Analysis are used to characterize metallic and intermetallic matrix composites and superplastic materials. These techniques are compared with the more conventional x-ray diffraction and indentation techniques.

Degradation kinetics of peroxidase enzyme, phenolic content, and physical and sensorial characteristics in broccoli (Brassica oleracea L. ssp. Italica) during blanching.

PubMed

Gonçalves, Elsa M; Pinheiro, Joaquina; Alegria, Carla; Abreu, Marta; Brandão, Teresa R S; Silva, Cristina L M

2009-06-24

The effects of water blanching treatment on peroxidase inactivation, total phenolic content, color parameters [-a*/b* and hue (h degrees*)], texture (maximum shear force), and sensory attributes (color and texture, evaluated by a trained panel) of broccoli (Brassica oleracea L. ssp. Italica) were studied at five temperatures (70, 75, 80, 85, and 90 degrees C). Experimental results showed that all studied broccoli quality parameters suffered significative changes due to blanching treatments. The vegetal total phenolic content showed a marked decline. Degradation on objective color and texture measurements and alterations in sensorial attributes were detected. Correlations between sensory and instrumental measurements have been found. Under the conditions 70 degrees C and 6.5 min or 90 degrees C and 0.4 min, 90% of the initial peroxidase activity was reduced. At these conditions, no significant alterations were detected by panelists, and a small amount of phenolic content was lost (ca. 16 and 10%, respectively). The peroxidase inactivation and phenolic content degradation were found to follow first-order reaction models. The zero-order reaction model showed a good fit to the broccoli color (-a*/b* and h degrees*), texture, and sensory parameters changes. The temperature effect was well-described by the Arrhenius law.

[Development of bakery products for greater adult consumption based on wheat and rice flour].

PubMed

Reyes Aguilar, María José; Palomo, Patricia de; Bressani, Ricardo

2004-09-01

The present investigation was developed as a contribution to Guatemalan's elderly food and nutrition. Its main objective was to evaluate the chemical, nutritional and sensory quality of bread prepared from the partial substitution of wheat flour with rice flour. Wheat flour substitutions with rice flour in the order of 15, 20, 30, 40, 50 and 60% were evaluated. Differences with the control (100% wheat bread) were found during the process of preparation, as well as texture, volume, height, weight and specific volume. Important effects in dough handling were noted specifically in the 40, 50 and 60% rice bread. Thus, a sandy texture was found in breads of higher rice levels. The bread protein quality increased with the level of substitution; however the protein quality difference between the wheat bread and the bread with 60% rice flour did not achieve statistical significance. Based on a statistical analysis of the physical properties the bread with 30 and 40% rice flour was selected, and through a preference test between these last two, the 30% rice flour bread was selected as the sample best suited to the present study's purposes. This bread was not different to wheat bread in many nutritional parameters, although in others it showed to be superior. Each serving size of bread has a weight of 80 grams (2 slices) that contributes adequate quantity of calories, protein and sodium, although a little less dietary fiber than 100% wheat bread.

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.

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.

On soil textural classifications and soil-texture-based estimations

NASA Astrophysics Data System (ADS)

Ángel Martín, Miguel; Pachepsky, Yakov A.; García-Gutiérrez, Carlos; Reyes, Miguel

2018-02-01

The soil texture representation with the standard textural fraction triplet sand-silt-clay is commonly used to estimate soil properties. The objective of this work was to test the hypothesis that other fraction sizes in the triplets may provide a better representation of soil texture for estimating some soil parameters. We estimated the cumulative particle size distribution and bulk density from an entropy-based representation of the textural triplet with experimental data for 6240 soil samples. The results supported the hypothesis. For example, simulated distributions were not significantly different from the original ones in 25 and 85 % of cases when the sand-silt-clay and very coarse+coarse + medium sand - fine + very fine sand - silt+clay were used, respectively. When the same standard and modified triplets were used to estimate the average bulk density, the coefficients of determination were 0.001 and 0.967, respectively. Overall, the textural triplet selection appears to be application and data specific.

3D Texture Analysis Reveals Imperceptible MRI Textural Alterations in the Thalamus and Putamen in Progressive Myoclonic Epilepsy Type 1, EPM1

PubMed Central

Suoranta, Sanna; Holli-Helenius, Kirsi; Koskenkorva, Päivi; Niskanen, Eini; Könönen, Mervi; Äikiä, Marja; Eskola, Hannu; Kälviäinen, Reetta; Vanninen, Ritva

2013-01-01

Progressive myoclonic epilepsy type 1 (EPM1) is an autosomal recessively inherited neurodegenerative disorder characterized by young onset age, myoclonus and tonic-clonic epileptic seizures. At the time of diagnosis, the visual assessment of the brain MRI is usually normal, with no major changes found later. Therefore, we utilized texture analysis (TA) to characterize and classify the underlying properties of the affected brain tissue by means of 3D texture features. Sixteen genetically verified patients with EPM1 and 16 healthy controls were included in the study. TA was performed upon 3D volumes of interest that were placed bilaterally in the thalamus, amygdala, hippocampus, caudate nucleus and putamen. Compared to the healthy controls, EPM1 patients had significant textural differences especially in the thalamus and right putamen. The most significantly differing texture features included parameters that measure the complexity and heterogeneity of the tissue, such as the co-occurrence matrix-based entropy and angular second moment, and also the run-length matrix-based parameters of gray-level non-uniformity, short run emphasis and long run emphasis. This study demonstrates the usability of 3D TA for extracting additional information from MR images. Textural alterations which suggest complex, coarse and heterogeneous appearance were found bilaterally in the thalamus, supporting the previous literature on thalamic pathology in EPM1. The observed putamenal involvement is a novel finding. Our results encourage further studies on the clinical applications, feasibility, reproducibility and reliability of 3D TA. PMID:23922849

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.

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.

Imaging Heterogeneity in Lung Cancer: Techniques, Applications, and Challenges.

PubMed

Bashir, Usman; Siddique, Muhammad Musib; Mclean, Emma; Goh, Vicky; Cook, Gary J

2016-09-01

Texture analysis involves the mathematic processing of medical images to derive sets of numeric quantities that measure heterogeneity. Studies on lung cancer have shown that texture analysis may have a role in characterizing tumors and predicting patient outcome. This article outlines the mathematic basis of and the most recent literature on texture analysis in lung cancer imaging. We also describe the challenges facing the clinical implementation of texture analysis. Texture analysis of lung cancer images has been applied successfully to FDG PET and CT scans. Different texture parameters have been shown to be predictive of the nature of disease and of patient outcome. In general, it appears that more heterogeneous tumors on imaging tend to be more aggressive and to be associated with poorer outcomes and that tumor heterogeneity on imaging decreases with treatment. Despite these promising results, there is a large variation in the reported data and strengths of association.

Characteristics of hierarchical micro/nano surface structure formation generated by picosecond laser processing in water and air

NASA Astrophysics Data System (ADS)

Rajab, Fatema H.; Whitehead, David; Liu, Zhu; Li, Lin

2017-12-01

Laser surface texturing or micro/nano surface structuring in the air has been extensively studied. However, until now, there are very few studies on the characteristics of laser-textured surfaces in water, and there was no reported work on picosecond laser surface micro/nano-structuring in water. In this work, the surface properties of picosecond laser surface texturing in water and air were analysed and compared. 316L stainless steel substrates were textured using a picosecond laser. The surface morphology and the chemical composition were characterised using Philips XL30 FEG-SEM, EDX and confocal laser microscopy. The wettability of the textured surfaces was determined using a contact angle analyser FTA 188. Results showed that a variety of hierarchical micro/nano surface patterns could be controlled by a suitable adjustment of laser parameters. Not only surface morphology but also remarkable differences in wettability, optical reflectivity and surface oxygen content were observed for different types of surface textures produced by laser surface texture in water and air. The possible mechanisms of the changes in the behaviour of laser-textured surfaces are discussed.

Steganalysis based on reducing the differences of image statistical characteristics

NASA Astrophysics Data System (ADS)

Wang, Ran; Niu, Shaozhang; Ping, Xijian; Zhang, Tao

2018-04-01

Compared with the process of embedding, the image contents make a more significant impact on the differences of image statistical characteristics. This makes the image steganalysis to be a classification problem with bigger withinclass scatter distances and smaller between-class scatter distances. As a result, the steganalysis features will be inseparate caused by the differences of image statistical characteristics. In this paper, a new steganalysis framework which can reduce the differences of image statistical characteristics caused by various content and processing methods is proposed. The given images are segmented to several sub-images according to the texture complexity. Steganalysis features are separately extracted from each subset with the same or close texture complexity to build a classifier. The final steganalysis result is figured out through a weighted fusing process. The theoretical analysis and experimental results can demonstrate the validity of the framework.

Automated Array Assembly Task In-depth Study of Silicon Wafer Surface Texturizing

NASA Technical Reports Server (NTRS)

Jones, G. T.; Chitre, S.; Rhee, S. S.; Allison, K. L.

1979-01-01

A low cost wafer surface texturizing process was studied. An investigation of low cost cleaning operations to clean residual wax and organics from the surface of silicon wafers was made. The feasibility of replacing dry nitrogen with clean dry air for drying silicon wafers was examined. The two stage texturizing process was studied for the purpose of characterizing relevant parameters in large volume applications. The effect of gettering solar cells on photovoltaic energy conversion efficiency is described.

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

TU-D-207B-03: Early Assessment of Response to Chemoradiotherapy Based On Textural Analysis of Pre and Mid-Treatment FDG-PET Image in Locally Advanced Head and Neck Cancer

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

Cui, Y; Pollom, E; Loo, B

Purpose: To evaluate whether tumor textural features extracted from both pre- and mid-treatment FDG-PET images predict early response to chemoradiotherapy in locally advanced head and neck cancer, and investigate whether they provide complementary value to conventional volume-based measurements. Methods: Ninety-four patients with locally advanced head and neck cancers were retrospectively studied. All patients received definitive chemoradiotherapy and underwent FDG-PET planning scans both before and during treatment. Within the primary tumor we extracted 6 textural features based on gray-level co-occurrence matrices (GLCM): entropy, dissimilarity, contrast, correlation, energy, and homogeneity. These image features were evaluated for their predictive power of treatment responsemore » to chemoradiotherapy in terms of local recurrence free survival (LRFS) and progression free survival (PFS). Logrank test were used to assess the statistical significance of the stratification between low- and high-risk groups. P-values were adjusted for multiple comparisons by the false discovery rate (FDR) method. Results: All six textural features extracted from pre-treatment PET images significantly differentiated low- and high-risk patient groups for LRFS (P=0.011–0.038) and PFS (P=0.029–0.034). On the other hand, none of the textural features on mid-treatment PET images was statistically significant in stratifying LRFS (P=0.212–0.445) or PFS (P=0.168–0.299). An imaging signature that combines textural feature (GLCM homogeneity) and metabolic tumor volume showed an improved performance for predicting LRFS (hazard ratio: 22.8, P<0.0001) and PFS (hazard ratio: 13.9, P=0.0005) in leave-one-out cross validation. Intra-tumor heterogeneity measured by textural features was significantly lower in mid-treatment PET images than in pre-treatment PET images (T-test: P<1.4e-6). Conclusion: Tumor textural features on pretreatment FDG-PET images are predictive for response to chemoradiotherapy in locally advanced head and neck cancer. The complementary information offered by textural features improves patient stratification and may potentially aid in personalized risk-adaptive therapy.« less

PCTO-SIM: Multiple-point geostatistical modeling using parallel conditional texture optimization

NASA Astrophysics Data System (ADS)

Pourfard, Mohammadreza; Abdollahifard, Mohammad J.; Faez, Karim; Motamedi, Sayed Ahmad; Hosseinian, Tahmineh

2017-05-01

Multiple-point Geostatistics is a well-known general statistical framework by which complex geological phenomena have been modeled efficiently. Pixel-based and patch-based are two major categories of these methods. In this paper, the optimization-based category is used which has a dual concept in texture synthesis as texture optimization. Our extended version of texture optimization uses the energy concept to model geological phenomena. While honoring the hard point, the minimization of our proposed cost function forces simulation grid pixels to be as similar as possible to training images. Our algorithm has a self-enrichment capability and creates a richer training database from a sparser one through mixing the information of all surrounding patches of the simulation nodes. Therefore, it preserves pattern continuity in both continuous and categorical variables very well. It also shows a fuzzy result in its every realization similar to the expected result of multi realizations of other statistical models. While the main core of most previous Multiple-point Geostatistics methods is sequential, the parallel main core of our algorithm enabled it to use GPU efficiently to reduce the CPU time. One new validation method for MPS has also been proposed in this paper.

Quantitative analysis and implications of drainage morphometry of the Agula watershed in the semi-arid northern Ethiopia

NASA Astrophysics Data System (ADS)

Fenta, Ayele Almaw; Yasuda, Hiroshi; Shimizu, Katsuyuki; Haregeweyn, Nigussie; Woldearegay, Kifle

2017-11-01

This study aimed at quantitative analysis of morphometric parameters of Agula watershed and its sub-watersheds using remote sensing data, geographic information system, and statistical methods. Morphometric parameters were evaluated from four perspectives: drainage network, watershed geometry, drainage texture, and relief characteristics. A sixth-order river drains Agula watershed and the drainage network is mainly dendritic type. The mean bifurcation ratio ( R b) was 4.46 and at sub-watershed scale, high R b values ( R b > 5) were observed which might be expected in regions of steeply sloping terrain. The longest flow path of Agula watershed is 48.5 km, with knickpoints along the main river which could be attributed to change of lithology and major faults which are common along the rift escarpments. The watershed has elongated shape suggesting low peak flows for longer duration and hence easier flood management. The drainage texture analysis revealed fine drainage which implies the dominance of impermeable soft rock with low resistance against erosion. High relief and steep slopes dominates, by which rough landforms (hills, breaks, and low mountains) make up 76% of the watershed. The S-shaped hypsometric curve with hypsometric integral of 0.4 suggests that Agula watershed is in equilibrium or mature stage of geomorphic evolution. At sub-watershed scale, the derived morphometric parameters were grouped into three clusters (low, moderate, and high) and considerable spatial variability was observed. The results of this study provide information on drainage morphometry that can help better understand the watershed characteristics and serve as a basis for improved planning, management, and decision making to ensure sustainable use of watershed resources.

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.

Revisiting the Robustness of PET-Based Textural Features in the Context of Multi-Centric Trials.

PubMed

Bailly, Clément; Bodet-Milin, Caroline; Couespel, Solène; Necib, Hatem; Kraeber-Bodéré, Françoise; Ansquer, Catherine; Carlier, Thomas

2016-01-01

This study aimed to investigate the variability of textural features (TF) as a function of acquisition and reconstruction parameters within the context of multi-centric trials. The robustness of 15 selected TFs were studied as a function of the number of iterations, the post-filtering level, input data noise, the reconstruction algorithm and the matrix size. A combination of several reconstruction and acquisition settings was devised to mimic multi-centric conditions. We retrospectively studied data from 26 patients enrolled in a diagnostic study that aimed to evaluate the performance of PET/CT 68Ga-DOTANOC in gastro-entero-pancreatic neuroendocrine tumors. Forty-one tumors were extracted and served as the database. The coefficient of variation (COV) or the absolute deviation (for the noise study) was derived and compared statistically with SUVmax and SUVmean results. The majority of investigated TFs can be used in a multi-centric context when each parameter is considered individually. The impact of voxel size and noise in the input data were predominant as only 4 TFs presented a high/intermediate robustness against SUV-based metrics (Entropy, Homogeneity, RP and ZP). When combining several reconstruction settings to mimic multi-centric conditions, most of the investigated TFs were robust enough against SUVmax except Correlation, Contrast, LGRE, LGZE and LZLGE. Considering previously published results on either reproducibility or sensitivity against delineation approach and our findings, it is feasible to consider Homogeneity, Entropy, Dissimilarity, HGRE, HGZE and ZP as relevant for being used in multi-centric trials.

The Development of Surface Roughness and Implications for Cellular Attachment in Biomedical Applications

NASA Technical Reports Server (NTRS)

Banks, Bruce; Miller, Sharon; deGroh, Kim; Chan, Amy; Sahota, Mandeep

2001-01-01

The application of a microscopic surface texture produced by ion beam sputter texturing to the surfaces of polymer implants has been shown to result in significant increases in cellular attachment compared to smooth surface implants in animal studies. A collaborative program between NASA Glenn Research Center and the Cleveland Clinic Foundation has been established to evaluate the potential for improving osteoblast attachment to surfaces that have been microscopically roughened by atomic oxygen texturing. The range of surface textures that are feasible depends upon both the texturing process and the duration of treatment. To determine whether surface texture saturates or continues to increase with treatment duration, an effort was conducted to examine the development of surface textures produced by various physical and chemical erosion processes. Both experimental tests and computational modeling were performed to explore the growth of surface texture with treatment time. Surface texturing by means of abrasive grit blasting of glass, stainless steel, and polymethylmethacry I ate surfaces was examined to measure the growth in roughness with grit blasting duration by surface profilometry measurements. Laboratory tests and computational modeling was also conducted to examine the development of texture on Aclar(R) (chlorotfifluoroethylene) and Kapton(R) polyimide, respectively. For the atomic oxygen texturing tests of Aclar(R), atomic force microscopy was used to measure the development of texture with atomic oxygen fluence. The results of all the testing and computational modeling support the premise that development of surface roughness obeys Poisson statistics. The results indicate that surface roughness does not saturate but increases as the square root of the treatment time.

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.

LITERATURE ABSTRACTS.

PubMed

1971-12-01

1. General Principles: 'Statistical Aspect of the Correlation Between Objective and Subjective Measurements of Meat Tenderness', by M. C. Gacula, Jr., J. B. Reaume, K. J. Morgan, and R. L. Luckett 1. General Principles: 'Texture of Semi-Solid Foods: Sensory and Physical Correlates', by W. F. Henry, M. H. Katz, F. J. Pilgrim, and A. T. May 2. Instrumentation and Methodology: 'Measurement of Bread Staling', by W. Morandini and L. Wassermann 2. Instrumentation and Methodology: 'Physical Considerations of the Methods of Consistency Measurement of Butter', by E. Knoop 2. Instrumentation and Methodology: 'Electronic Recording Mixers for the Baking Test', by P. W. Voisey, V. M. Bendelow and H. Miller 2. Instrumentation and Methodology: 'Measurement of the Consistency of Reconstituted Instant Potato Flakes', by P. W. Voisey and P. R. Dean 2. Instrumentation and Methodology: 'The Ottawa Electronic Recording Farinograph', by P. W. Voisey, H. Miller and P. L. Byrne 3. Objective Measurements: A. FOODS: 'The Rheological Properties of Corn Horny Endosperm', by J. R. Hamerle*, R. K. White**, and N. N. Mohsenin*** 3. Objective Measurements: 'Evaluation of Mechanical Properties of Comminuted Sausages by Construction and Analysis of Rheological Model', by St. Tyszkiewicz 3. Objective Measurements: 'Studies on Creep Compliance of Butter', by M. Chwiej 3. Objective Measurements: 'Heat-Induced Milk Gels. II. Preparation of Gels and Measurement of Firmness', by M. Kalab, P. W. Voisey and D. B. Emmons 3. Objective Measurements: 'Rheology of Fresh, Aged and Gamma-Irradiated Egg White', by M. A. Tung, J. F. Richards, B. C. Morrison and E. L. Watson 3. Objective Measurements: 'Retardation of Bread Staling - Practical Experiences', by W. Morandini and L. Wassermann 3. Objective Measurements: B. PHARMACEUTICALS: 'Influence of HLB on Certain Physicochemical Parameters of an O/W Emulsion', by M. Schrenzel 3. Objective Measurements: 'The Rheological Evaluation of Semisolids', by L. H. Block and P. P. Lamy 4. Factors Affecting Texture: 'Effects of Physical and Mechanical Treatments on the Tenderness of the Beef Longissimus', by G. C. Smith, T. C. Arango and Z. L. Carpenter 4. Factors Affecting Texture: 'Histological and Physical Changes in Carrots as Affected by Blanching, Cooking, Freezing, Freeze Drying and Compression', by A. R. Rahman, W. L. Henning and D. E. Westcott 4. Factors Affecting Texture: 'Effects of Physiological Maturity of Beef and Marbling of Rib Steaks on Eating Quality', by H. L. Norris, D. L. Harrison, L. L. Anderson, B. Van Welck and H. J. Tuma 4. Factors Affecting Texture: 'Effect of Ultimate pH Upon the Water-Holding Capacity and Tenderness of Mutton', by P. E. Bouton, P. V. Harris and W. R. Shorthose 4. Factors Affecting Texture: 'The Dilution Coefficient of Butter Serum and the Consistency of Butter', by E. Pijanowski, M. Chwiej, H. Hernik and M. Kurtowicz 4. Factors Affecting Texture: 'Moisture and pH Changes as Criteria of Freshness in Abalone and their Relationship to Texture of the Canned Product', by D. G. James and J. Olley 4. Factors Affecting Texture: 'Effect of Sucrose on Crispness of Explosion-Puffed Apple Pieces Exposed to High Humidities', by E. O. Strolle, J. Cording, Jr., P. E. McDowell, and R. K. Eskew 4. Factors Affecting Texture: 'Effect of Heat Treatment on Viscosity of Yolk', by P. K. Chang, W. D. Powrie and O. Fennema 4. Factors Affecting Texture: 'Protein Quality and Quantity: A Rheological Assessment of the Relative Importance in Breadmaking', by T. Webb, P. W. Heaps, and J. B. M. Coppock 4. Factors Affecting Texture: 'Bread Staling. 1. Experimental Study', by E. M. A. Willhoft 4. Factors Affecting Texture: 'Bread Staling. II. Theoretical Study', by E. M. A. Willhoft.

Effect of different temperature-time combinations on physicochemical, microbiological, textural and structural features of sous-vide cooked lamb loins.

PubMed

Roldán, Mar; Antequera, Teresa; Martín, Alberto; Mayoral, Ana Isabel; Ruiz, Jorge

2013-03-01

Lamb loins were subjected to sous-vide cooking at different combinations of temperature (60, 70, and 80 °C) and time (6, 12, and 24 h). Different physicochemical, histological and structural parameters were studied. Increasing cooking temperatures led to higher weight losses and lower moisture contents, whereas the effect of cooking time on these variables was limited. Samples cooked at 60 °C showed the highest lightness and redness, while increasing cooking temperature and cooking time produced higher yellowness values. Most textural variables in a texture profile analysis showed a marked interaction between cooking temperature and time. Samples cooked for 24h showed significantly lower values for most of the studied textural parameters for all the temperatures considered. Connective tissue granulation at 60 °C and gelation at 70 °C were observed in the SEM micrographs. The sous-vide cooking of lamb loins dramatically reduced microbial population even with the less intense heat treatment studied (60 °C-6 h). Copyright © 2012 Elsevier Ltd. All rights reserved.

Chemical, instrumental and sensory characteristics of cooked pork ham.

PubMed

Válková, V; Saláková, A; Buchtová, H; Tremlová, B

2007-12-01

Instrumental, chemical and sensory parameters of cooked pork ham were evaluated. Principal component analysis was carried out on the basis of the instrumental variables related to colour and texture. The four PCs account for almost 94% of the total variance in the data set. The PCA only separated 3 hams with a(∗)>10. Hardness was correlated with non-collagen muscle protein (P⩽0.01), gumminess (P⩽0.01) and ash (P⩽0.05). Sensory evaluated tenderness showed positive significant correlation with L(∗) (P⩽0.01). The most important colour parameter seems to be a(∗), which was negatively correlated with sensory evaluated parameter colour (P⩽0.01). The PCA performed on all parameters (sensory, chemical and textural) discriminated two groups of hams differing in non-collagen muscle protein content and hardness.

SU-F-R-54: CT-Texture Based Early Tumor Treatment Response Assessment During Radiation Therapy Delivery: Small Cell Versus Non-Small Cell Lung Cancers

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

Paul, J; Gore, E; Li, X

Purpose: Tumor treatment response may potentially be assessed during radiation therapy (RT) by analyzing changes in CT-textures. We investigated the different early RT-responses between small cell (SCLC) and non-small cell lung cancer (NSCLC) as assessed by CT-texture. Methods: Daily diagnostic-quality CT acquired during routine CT-guided RT using a CT-on-Rails for 13-NSCLC and 5-SCLC patients were analyzed. These patient had ages ranging from 45–78 and 38–63 years, respectively, for NSCLC and SCLC groups, and tumor-stages ranging from T2-T4, and were treated with either RT or chemotherapy and RT with 45–66Gy/ 20–34 fractions. Gross-tumor volume (GTV) contour was generated on each dailymore » CT by populating GTV contour from simulation to daily CTs with manual editing if necessary. CT-texture parameters, such as Hounsfield Unit (HU) histogram, mean HU, skewness, kurtosis, entropy, and short-run high-gray level emphasis (SRHGLE), were calculated in GTV from each daily CT-set using an in house software tool. Difference in changes of these texture parameters during RT between NSCLC and SCLC was analyzed and compared with GTV volume changes. Results: Radiation-induced changes in CT-texture were different between SCLC and NSCLC. Average changes from first to the last fractions for NSCLC and SCLC in GTV were 28±10(12–44) and 30±15(11–47) HU (mean HU reduction), 12.7% and 18.3% (entropy), 50% and 55% (SRHGLE), 19% and 22% (kurtosis), and 5.2% and 22% (skewness), respectively. Good correlation in kurtosis changes and GTV was seen (R{sup 2}=0.8923) for SCLC, but not for NSCLC (R{sup 2}=0.4748). SCLC had better correlations between GTV volume reduction and entropy (SCLC R{sup 2}=0.847; NSCLC R{sup 2}=0.6485), skewness (SCLC R{sup 2}=0.935; NSCLC R{sup 2}=0.7666), or SRHGLE (SCLC R{sup 2}=0.9619; NSCLC R{sup 2}=0.787). Conclusion: NSCLC and SCLC exhibited different early RT-responses as assessed by CT-texture changes during RT-delivery. The observed larger changes in various CT-texture parameters for SCLC indicate that SCLC may respond to RT more rapid than NSCLC.« less

Automatic measurement of skin textures of the dorsal hand in evaluating skin aging.

PubMed

Gao, Qian; Yu, Jiaming; Wang, Fang; Ge, Tiantian; Hu, Liwen; Liu, Yang

2013-05-01

Changes in skin textures have been used to evaluate skin aging in many studies. In our previous study, we built some skin texture parameters, which can be used to evaluate skin aging of human dorsal hand. However, it will take too much time and need to work arduously to get the information from digital skin image by manual work. So, we want to build a simple and effective method to automatically count some of those skin texture parameters by using digital image-processing technology. A total of 100 subjects aged 30 years and above were involved. Sun exposure history and demographic information were collected by using a questionnaire. The skin image of subjects' dorsal hand was obtained by using a portable skin detector. The number of grids, which is one of skin texture parameters built in our previous study, was measured manually and automatically. Automated image analysis program was developed by using Matlab 7.1 software. The number of grids counted automatically (NGA) was significantly correlated with the number of grids counted manually (NGM) (r = 0.9287, P < 0.0001). And in each age group, there were no significant differences between NGA and NGM. The NGA was negatively correlated with age and lifetime sun exposure, and decreased with increasing Beagley-Gibson score from 3 to 6. In addition, even after adjusting for NGA, the standard deviation of grid areas for each image was positively correlated with age, sun exposure, and Bealey-Gibson score. The method introduced in present study can be used to measure some skin aging parameters automatically and objectively. And it will save much time, reduce labor, and avoid measurement errors of deferent investigators when evaluating a great deal of skin images in a short time. © 2013 John Wiley & Sons A/S. Published by Blackwell Publishing Ltd.

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

Mateos, M-J; Brandan, M-E; Gastelum, A

Purpose: To evaluate the time evolution of texture parameters, based on the gray level co-occurrence matrix (GLCM), in subtracted images of 17 patients (10 malignant and 7 benign) subjected to contrast-enhanced digital mammography (CEDM). The goal is to determine the sensitivity of texture to iodine uptake at the lesion, and its correlation (or lack of) with mean-pixel-value (MPV). Methods: Acquisition of clinical images followed a single-energy CEDM protocol using Rh/Rh/48 kV plus external 0.5 cm Al from a Senographe DS unit. Prior to the iodine-based contrast medium (CM) administration a mask image was acquired; four CM images were obtained 1,more » 2, 3, and 5 minutes after CM injection. Temporal series were obtained by logarithmic subtraction of registered CM minus mask images.Regions of interest (ROI) for the lesion were drawn by a radiologist and the texture was analyzed. GLCM was evaluated at a 3 pixel distance, 0° angle, and 64 gray-levels. Pixels identified as registration errors were excluded from the computation. 17 texture parameters were chosen, classified according to similarity into 7 groups, and analyzed. Results: In all cases the texture parameters within a group have similar dynamic behavior. Two texture groups (associated to cluster and sum mean) show a strong correlation with MPV; their average correlation coefficient (ACC) is r{sup 2}=0.90. Other two groups (contrast, homogeneity) remain constant with time, that is, a low-sensitivity to CM uptake. Three groups (regularity, lacunarity and diagonal moment) are sensitive to CM uptake but less correlated with MPV; their ACC is r{sup 2}=0.78. Conclusion: This analysis has shown that, at least groups associated to regularity, lacunarity and diagonal moment offer dynamical information additional to the mean pixel value due to the presence of CM at the lesion. The next step will be the analysis in terms of the lesion pathology. Authors thank PAPIIT-IN105813 for support. Consejo Nacional de Ciencia Y Tecnologia, PAPIIT-IN105813.« less

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

PubMed

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

2017-06-01

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

Transfer of the nationwide Czech soil survey data to a foreign soil classification - generating input parameters for a process-based soil erosion modelling approach

NASA Astrophysics Data System (ADS)

Beitlerová, Hana; Hieke, Falk; Žížala, Daniel; Kapička, Jiří; Keiser, Andreas; Schmidt, Jürgen; Schindewolf, Marcus

2017-04-01

Process-based erosion modelling is a developing and adequate tool to assess, simulate and understand the complex mechanisms of soil loss due to surface runoff. While the current state of available models includes powerful approaches, a major drawback is given by complex parametrization. A major input parameter for the physically based soil loss and deposition model EROSION 3D is represented by soil texture. However, as the model has been developed in Germany it is dependent on the German soil classification. To exploit data generated during a massive nationwide soil survey campaign taking place in the 1960s across the entire Czech Republic, a transfer from the Czech to the German or at least international (e.g. WRB) system is mandatory. During the survey the internal differentiation of grain sizes was realized in a two fractions approach, separating texture into solely above and below 0.01 mm rather than into clayey, silty and sandy textures. Consequently, the Czech system applies a classification of seven different textures based on the respective percentage of large and small particles, while in Germany 31 groups are essential. The followed approach of matching Czech soil survey data to the German system focusses on semi-logarithmic interpolation of the cumulative soil texture curve additionally on a regression equation based on a recent database of 128 soil pits. Furthermore, for each of the seven Czech texture classes a group of typically suitable classes of the German system was derived. A GIS-based spatial analysis to test approaches of interpolation the soil texture was carried out. First results show promising matches and pave the way to a Czech model application of EROSION 3D.

Research of second harmonic generation images based on texture analysis

NASA Astrophysics Data System (ADS)

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

2014-09-01

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

Effect of phase composition on crystal texture formation in hot deformed nanocrystalline SmCo5 magnets

NASA Astrophysics Data System (ADS)

Ma, Qiang; Yue, Ming; Xu, Xiaochang; Zhang, Hongguo; Zhang, Dongtao; Zhang, Xuefeng; Zhang, Jiuxing

2018-05-01

In the present study, bulk anisotropic nanocrystalline SmCo5 magnets were prepared by hot press and subsequent hot deformation method. Effect of phase composition on texture and magnetic properties are presented, based on which the mechanism of plastic deformation and texture formation during the hot deformation process is discussed. The SmCo5 magnets were prepared by hot deformation, excessive Sm of 2.5 wt% and 10 wt% was added to compensate the weight loss due to Sm evaporation. Our analyses reveal that the phase composition is one of the most important parameters that determine the texture of SmCo5 magnets. It is therefore suggested that the existence of 2:17 phase and its phase transformation undermined the crystal texture formation as well as the magnetic properties of nanocrystalline SmCo5 magnets.

Prediction of Chemoresistance in Women Undergoing Neo-Adjuvant Chemotherapy for Locally Advanced Breast Cancer: Volumetric Analysis of First-Order Textural Features Extracted from Multiparametric MRI

PubMed Central

Losio, C.; Della Corte, A.; Venturini, E.; Ambrosi, A.; Panizza, P.; De Cobelli, F.

2018-01-01

Purpose To assess correlations between volumetric first-order texture parameters on baseline MRI and pathological response after neoadjuvant chemotherapy (NAC) for locally advanced breast cancer (BC). Materials and Methods 69 patients with locally advanced BC candidate to neoadjuvant chemotherapy underwent MRI within 4 weeks from the start of therapeutic regimen. T2, DWI, and DCE sequences were analyzed and maps were generated for Apparent Diffusion Coefficient (ADC), T2 signal intensity, and the following dynamic parameters: k-trans, peak enhancement, area under curve (AUC), time to maximal enhancement (TME), wash-in rate, and washout rate. Volumetric analysis of these parameters was performed, yielding a histogram analysis including first-order texture kinetics (percentiles, maximum value, minimum value, range, standard deviation, mean, median, mode, skewness, and kurtosis). Finally, correlations between these values and response to NAC (evaluated on the surgical specimen according to RECIST 1.1 criteria) were assessed. Results Out of 69 tumors, 33 (47.8%) achieved complete pathological response, 26 (37.7%) partial response, and 10 (14.5%) no response. Higher levels of AUCmax (p value = 0.0338), AUCrange (p value = 0.0311), and TME75 (p value = 0.0452) and lower levels of washout10 (p value = 0.0417), washout20 (p value = 0.0138), washout25 (p value = 0.0114), and washout30 (p value = 0.05) were predictive of noncomplete response. Conclusion Histogram-derived texture analysis of MRI images allows finding quantitative parameters predictive of nonresponse to NAC in women affected by locally advanced BC. PMID:29853811

Prediction of Chemoresistance in Women Undergoing Neo-Adjuvant Chemotherapy for Locally Advanced Breast Cancer: Volumetric Analysis of First-Order Textural Features Extracted from Multiparametric MRI.

PubMed

Panzeri, M M; Losio, C; Della Corte, A; Venturini, E; Ambrosi, A; Panizza, P; De Cobelli, F

2018-01-01

To assess correlations between volumetric first-order texture parameters on baseline MRI and pathological response after neoadjuvant chemotherapy (NAC) for locally advanced breast cancer (BC). 69 patients with locally advanced BC candidate to neoadjuvant chemotherapy underwent MRI within 4 weeks from the start of therapeutic regimen. T2, DWI, and DCE sequences were analyzed and maps were generated for Apparent Diffusion Coefficient (ADC), T2 signal intensity, and the following dynamic parameters: k -trans, peak enhancement, area under curve (AUC), time to maximal enhancement (TME), wash-in rate, and washout rate. Volumetric analysis of these parameters was performed, yielding a histogram analysis including first-order texture kinetics (percentiles, maximum value, minimum value, range, standard deviation, mean, median, mode, skewness, and kurtosis). Finally, correlations between these values and response to NAC (evaluated on the surgical specimen according to RECIST 1.1 criteria) were assessed. Out of 69 tumors, 33 (47.8%) achieved complete pathological response, 26 (37.7%) partial response, and 10 (14.5%) no response. Higher levels of AUCmax ( p value = 0.0338), AUCrange ( p value = 0.0311), and TME 75 ( p value = 0.0452) and lower levels of washout 10 ( p value = 0.0417), washout 20 ( p value = 0.0138), washout 25 ( p value = 0.0114), and washout 30 ( p value = 0.05) were predictive of noncomplete response. Histogram-derived texture analysis of MRI images allows finding quantitative parameters predictive of nonresponse to NAC in women affected by locally advanced BC.

Rehydration of freeze-dried and convective dried boletus edulis mushrooms: effect on some quality parameters.

PubMed

Hernando, I; Sanjuán, N; Pérez-Munuera, I; Mulet, A

2008-10-01

Quality of rehydrated products is a key aspect linked to rehydration conditions. To assess the effect of rehydration temperature on some quality parameters, experiments at 20 and 70 degrees C were performed with convective dried and freeze-dried Boletus edulis mushrooms. Rehydration characteristics (through Peleg's parameter, k(1), and equilibrium moisture, W(e)), texture (Kramer), and microstructure (Cryo-Scanning Electron Microscopy) were evaluated. Freeze-dried samples absorbed water more quickly and attained higher W(e) values than convective dried ones. Convective dehydrated samples rehydrated at 20 degrees C showed significantly lower textural values (11.9 +/- 3.3 N/g) than those rehydrated at 70 degrees C (15.7 +/- 1.2 N/g). For the freeze-dried Boletus edulis, the textural values also exhibited significant differences, being 8.2 +/- 1.3 and 10.5 +/- 2.3 N/g for 20 and 70 degrees C, respectively. Freeze-dried samples showed a porous structure that allows rehydration to take place mainly at the extracellular level. This explains the fact that, regardless of temperature, freeze-dried mushrooms absorbed water more quickly and reached higher W(e) values than convective dried ones. Whatever the dehydration technique used, rehydration at 70 degrees C produced a structural damage that hindered water absorption; consequently lower W(e) values and higher textural values were attained than when rehydrating at 20 degrees C.

Investigation of the Effects of Inulin and β-Glucan on the Physical and Sensory Properties of Low-Fat Beef Burgers Containing Vegetable Oils: Optimisation of the Formulation Using D-Optimal Mixture Design

PubMed Central

Afshari, Roya; Khaksar, Ramin; Mohammadifar, Mohammad Amin; Amiri, Zohre; Komeili, Rozita; Khaneghah, Amin Mousavi

2015-01-01

Summary In this study, the D-optimal mixture design methodology was applied to determine the optimised proportions of inulin, β-glucan and breadcrumbs in formulation of low-fat beef burgers containing pre-emulsified canola and olive oil blend. Also, the effect of each of the ingredients individually as well as their interactions on cooking characteristics, texture, colour and sensory properties of low-fat beef burgers were investigated. The results of this study revealed that the increase of inulin content in the formulations of burgers led to lower cooking yield, moisture retention and increased lightness, overall acceptability, mouldability and desired textural parameters. In contrast, incorporation of β-glucan increased the cooking yield, moisture retention and decreased lightness, overall acceptability, mouldability and desired textural parameters of burger patties. The interaction between inulin and β-glucan improved the cooking characteristics of the burgers without significantly negative effect on the colour or sensory properties. The results of the study clearly stated that the optimum mixture for the burger formulation consisted of (in g per 100 g): inulin 3.1, β-glucan 2.2 and breadcrumbs 2.7. The texture parameters and cooking characteristics were improved by using the mixture of inulin, β-glucan and breadcrumbs, without any negative effects on the sensory properties of the burgers. PMID:27904378

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

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

Ma, Fa-Jun, E-mail: Fajun.Ma@nus.edu.sg; Duttagupta, Shubham; Department of Electrical and Computer Engineering, National University of Singapore, 4 Engineering Drive 3, 117576

2014-11-14

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

Feature recognition and detection for ancient architecture based on machine vision

NASA Astrophysics Data System (ADS)

Zou, Zheng; Wang, Niannian; Zhao, Peng; Zhao, Xuefeng

2018-03-01

Ancient architecture has a very high historical and artistic value. The ancient buildings have a wide variety of textures and decorative paintings, which contain a lot of historical meaning. Therefore, the research and statistics work of these different compositional and decorative features play an important role in the subsequent research. However, until recently, the statistics of those components are mainly by artificial method, which consumes a lot of labor and time, inefficiently. At present, as the strong support of big data and GPU accelerated training, machine vision with deep learning as the core has been rapidly developed and widely used in many fields. This paper proposes an idea to recognize and detect the textures, decorations and other features of ancient building based on machine vision. First, classify a large number of surface textures images of ancient building components manually as a set of samples. Then, using the convolution neural network to train the samples in order to get a classification detector. Finally verify its precision.

Textural content in 3T MR: an image-based marker for Alzheimer's disease

NASA Astrophysics Data System (ADS)

Bharath Kumar, S. V.; Mullick, Rakesh; Patil, Uday

2005-04-01

In this paper, we propose a study, which investigates the first-order and second-order distributions of T2 images from a magnetic resonance (MR) scan for an age-matched data set of 24 Alzheimer's disease and 17 normal patients. The study is motivated by the desire to analyze the brain iron uptake in the hippocampus of Alzheimer's patients, which is captured by low T2 values. Since, excess iron deposition occurs locally in certain regions of the brain, we are motivated to investigate the spatial distribution of T2, which is captured by higher-order statistics. Based on the first-order and second-order distributions (involving gray level co-occurrence matrix) of T2, we show that the second-order statistics provide features with sensitivity >90% (at 80% specificity), which in turn capture the textural content in T2 data. Hence, we argue that different texture characteristics of T2 in the hippocampus for Alzheimer's and normal patients could be used as an early indicator of Alzheimer's disease.

Multifractal modeling, segmentation, prediction, and statistical validation of posterior fossa tumors

NASA Astrophysics Data System (ADS)

Islam, Atiq; Iftekharuddin, Khan M.; Ogg, Robert J.; Laningham, Fred H.; Sivakumar, Bhuvaneswari

2008-03-01

In this paper, we characterize the tumor texture in pediatric brain magnetic resonance images (MRIs) and exploit these features for automatic segmentation of posterior fossa (PF) tumors. We focus on PF tumor because of the prevalence of such tumor in pediatric patients. Due to varying appearance in MRI, we propose to model the tumor texture with a multi-fractal process, such as a multi-fractional Brownian motion (mBm). In mBm, the time-varying Holder exponent provides flexibility in modeling irregular tumor texture. We develop a detailed mathematical framework for mBm in two-dimension and propose a novel algorithm to estimate the multi-fractal structure of tissue texture in brain MRI based on wavelet coefficients. This wavelet based multi-fractal feature along with MR image intensity and a regular fractal feature obtained using our existing piecewise-triangular-prism-surface-area (PTPSA) method, are fused in segmenting PF tumor and non-tumor regions in brain T1, T2, and FLAIR MR images respectively. We also demonstrate a non-patient-specific automated tumor prediction scheme based on these image features. We experimentally show the tumor discriminating power of our novel multi-fractal texture along with intensity and fractal features in automated tumor segmentation and statistical prediction. To evaluate the performance of our tumor prediction scheme, we obtain ROCs and demonstrate how sharply the curves reach the specificity of 1.0 sacrificing minimal sensitivity. Experimental results show the effectiveness of our proposed techniques in automatic detection of PF tumors in pediatric MRIs.

SU-D-207B-07: Development of a CT-Radiomics Based Early Response Prediction Model During Delivery of Chemoradiation Therapy for Pancreatic Cancer

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

Klawikowski, S; Christian, J; Schott, D

Purpose: Pilot study developing a CT-texture based model for early assessment of treatment response during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Methods: Daily CT data acquired for 24 pancreatic head cancer patients using CT-on-rails, during the routine CT-guided CRT delivery with a radiation dose of 50.4 Gy in 28 fractions, were analyzed. The pancreas head was contoured on each daily CT. Texture analysis was performed within the pancreas head contour using a research tool (IBEX). Over 1300 texture metrics including: grey level co-occurrence, run-length, histogram, neighborhood intensity difference, and geometrical shape features were calculated for each dailymore » CT. Metric-trend information was established by finding the best fit of either a linear, quadratic, or exponential function for each metric value verses accumulated dose. Thus all the daily CT texture information was consolidated into a best-fit trend type for a given patient and texture metric. Linear correlation was performed between the patient histological response vector (good, medium, poor) and all combinations of 23 patient subgroups (statistical jackknife) determining which metrics were most correlated to response and repeatedly reliable across most patients. Control correlations against CT scanner, reconstruction kernel, and gated/nongated CT images were also calculated. Euclidean distance measure was used to group/sort patient vectors based on the data of these trend-response metrics. Results: We found four specific trend-metrics (Gray Level Coocurence Matrix311-1InverseDiffMomentNorm, Gray Level Coocurence Matrix311-1InverseDiffNorm, Gray Level Coocurence Matrix311-1 Homogeneity2, and Intensity Direct Local StdMean) that were highly correlated with patient response and repeatedly reliable. Our four trend-metric model successfully ordered our pilot response dataset (p=0.00070). We found no significant correlation to our control parameters: gating (p=0.7717), scanner (p=0.9741), and kernel (p=0.8586). Conclusion: We have successfully created a CT-texture based early treatment response prediction model using the CTs acquired during the delivery of chemoradiation therapy for pancreatic cancer. Future testing is required to validate the model with more patient data.« less

Directional motion of impacting drops on dual-textured surfaces.

PubMed

Vaikuntanathan, V; Sivakumar, D

2012-09-01

In this work, we analyze the directional movement of impacting liquid drops on dual-textured solid surfaces comprising two different surface morphologies: a textured surface and a smooth surface. The dynamics of liquid drops impacting onto the junction line between the two parts of the dual-textured surfaces is studied experimentally for varying drop impact velocity. The dual-textured surfaces used here featured a variation in their textures' geometrical parameters as well as their surface chemistry. Two types of liquid drop differing in their surface tension were used. The impact process develops a net horizontal drop velocity towards the higher-wettability surface portion and results in a bulk movement of the impacting drop liquid. The final distance moved by the impacting drop from the junction line decreases with increasing impacting drop Weber number We. A fully theoretical model, employing a balance of forces acting at the drop contact line as well as energy conservation, is formulated to determine the variation, with We, of net horizontal drop velocity and subsequent movement of the impacting drop on the dual-textured surfaces.

Effect of various binning methods and ROI sizes on the accuracy of the automatic classification system for differentiation between diffuse infiltrative lung diseases on the basis of texture features at HRCT

NASA Astrophysics Data System (ADS)

Kim, Namkug; Seo, Joon Beom; Sung, Yu Sub; Park, Bum-Woo; Lee, Youngjoo; Park, Seong Hoon; Lee, Young Kyung; Kang, Suk-Ho

2008-03-01

To find optimal binning, variable binning size linear binning (LB) and non-linear binning (NLB) methods were tested. In case of small binning size (Q <= 10), NLB shows significant better accuracy than the LB. K-means NLB (Q = 26) is statistically significant better than every LB. To find optimal binning method and ROI size of the automatic classification system for differentiation between diffuse infiltrative lung diseases on the basis of textural analysis at HRCT Six-hundred circular regions of interest (ROI) with 10, 20, and 30 pixel diameter, comprising of each 100 ROIs representing six regional disease patterns (normal, NL; ground-glass opacity, GGO; reticular opacity, RO; honeycombing, HC; emphysema, EMPH; and consolidation, CONS) were marked by an experienced radiologist from HRCT images. Histogram (mean) and co-occurrence matrix (mean and SD of angular second moment, contrast, correlation, entropy, and inverse difference momentum) features were employed to test binning and ROI effects. To find optimal binning, variable binning size LB (bin size Q: 4~30, 32, 64, 128, 144, 196, 256, 384) and NLB (Q: 4~30) methods (K-means, and Fuzzy C-means clustering) were tested. For automated classification, a SVM classifier was implemented. To assess cross-validation of the system, a five-folding method was used. Each test was repeatedly performed twenty times. Overall accuracies with every combination of variable ROIs, and binning sizes were statistically compared. In case of small binning size (Q <= 10), NLB shows significant better accuracy than the LB. K-means NLB (Q = 26) is statistically significant better than every LB. In case of 30x30 ROI size and most of binning size, the K-means method showed better than other NLB and LB methods. When optimal binning and other parameters were set, overall sensitivity of the classifier was 92.85%. The sensitivity and specificity of the system for each class were as follows: NL, 95%, 97.9%; GGO, 80%, 98.9%; RO 85%, 96.9%; HC, 94.7%, 97%; EMPH, 100%, 100%; and CONS, 100%, 100%, respectively. We determined the optimal binning method and ROI size of the automatic classification system for differentiation between diffuse infiltrative lung diseases on the basis of texture features at HRCT.

Application of TiN/TiO2 coatings on stainless steel: composition and mechanical reliability

NASA Astrophysics Data System (ADS)

Nikolova, M. P.; Genov, A.; Valkov, S.; Yankov, E.; Dechev, D.; Ivanov, N.; Bezdushnyi, R.; Petrov, P.

2018-03-01

The paper reports on the effect of the substrate temperature (350 °C, 380 °C and 420 °C) during reactive magnetron sputtering of a TiN film on the phase composition, texture and mechanical properties of TiN/TiO2 coatings on 304L stainless steel substrates. Pure Ti was used as a cathode source of Ti. The texture and unit cell parameters of both TiN and TiO2 phases of the coating are discussed in relation with the tribological properties and adhesion of the coating. The scratch tests performed showed that the nitride deposited at 380 °C, having the highest unit cell parameter and a predominant (111) texture, possessed the lowest friction coefficient (μ), tangential force and brittleness. The anatase-type TiO2 with predominant (101) pole density and increased c unit cell parameter showed the highest stability on the nitride deposited at 420 °C. The results indicated that the friction coefficient, tangential force and critical forces of fracture could be varied by controlling the coating deposition temperature.

Effect of Groove Surface Texture on Tribological Characteristics and Energy Consumption under High Temperature Friction.

PubMed

Wu, Wei; Chen, Guiming; Fan, Boxuan; Liu, Jianyou

2016-01-01

Energy consumption and tribological properties could be improved by proper design of surface texture in friction. However, some literature focused on investigating their performance under high temperature. In the study, different groove surface textures were fabricated on steels by a laser machine, and their tribological behaviors were experimentally studied with the employment of the friction and wear tester under distinct high temperature and other working conditions. The friction coefficient was recorded, and wear performance were characterized by double light interference microscope, scanning electron microscope (SEM) and x-ray energy dispersive spectrometry (EDS). Then, the performances of energy consumptions were carefully estimated. Results showed that friction coefficient, wear, and energy consumption could almost all be reduced by most textures under high temperature conditions, but to a different extent which depends on the experimental conditions and texture parameters. The main improvement mechanisms were analyzed, such as the hardness change, wear debris storage, thermal stress release and friction induced temperature reduction by the textures. Finally, a scattergram of the relatively reduced ratio of the energy consumption was drawn for different surface textures under four distinctive experimental conditions to illustrate the comprehensive energy consumption improving ability of textures, which was of benefit for the application of texture design.

Effect of Groove Surface Texture on Tribological Characteristics and Energy Consumption under High Temperature Friction

PubMed Central

Wu, Wei; Chen, Guiming; Fan, Boxuan; Liu, Jianyou

2016-01-01

Energy consumption and tribological properties could be improved by proper design of surface texture in friction. However, some literature focused on investigating their performance under high temperature. In the study, different groove surface textures were fabricated on steels by a laser machine, and their tribological behaviors were experimentally studied with the employment of the friction and wear tester under distinct high temperature and other working conditions. The friction coefficient was recorded, and wear performance were characterized by double light interference microscope, scanning electron microscope (SEM) and x-ray energy dispersive spectrometry (EDS). Then, the performances of energy consumptions were carefully estimated. Results showed that friction coefficient, wear, and energy consumption could almost all be reduced by most textures under high temperature conditions, but to a different extent which depends on the experimental conditions and texture parameters. The main improvement mechanisms were analyzed, such as the hardness change, wear debris storage, thermal stress release and friction induced temperature reduction by the textures. Finally, a scattergram of the relatively reduced ratio of the energy consumption was drawn for different surface textures under four distinctive experimental conditions to illustrate the comprehensive energy consumption improving ability of textures, which was of benefit for the application of texture design. PMID:27035658

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.

Relationship between the erosion properties of soils and other parameters

USDA-ARS?s Scientific Manuscript database

Soil parameters are essential for erosion process prediction and ultimately improved model development, especially as they relate to dam and levee failure. Soil parameters including soil texture and structure, soil classification, soil compaction, moisture content, and degree of saturation can play...

The use of higher-order statistics in rapid object categorization in natural scenes.

PubMed

Banno, Hayaki; Saiki, Jun

2015-02-04

We can rapidly and efficiently recognize many types of objects embedded in complex scenes. What information supports this object recognition is a fundamental question for understanding our visual processing. We investigated the eccentricity-dependent role of shape and statistical information for ultrarapid object categorization, using the higher-order statistics proposed by Portilla and Simoncelli (2000). Synthesized textures computed by their algorithms have the same higher-order statistics as the originals, while the global shapes were destroyed. We used the synthesized textures to manipulate the availability of shape information separately from the statistics. We hypothesized that shape makes a greater contribution to central vision than to peripheral vision and that statistics show the opposite pattern. Results did not show contributions clearly biased by eccentricity. Statistical information demonstrated a robust contribution not only in peripheral but also in central vision. For shape, the results supported the contribution in both central and peripheral vision. Further experiments revealed some interesting properties of the statistics. They are available for a limited time, attributable to the presence or absence of animals without shape, and predict how easily humans detect animals in original images. Our data suggest that when facing the time constraint of categorical processing, higher-order statistics underlie our significant performance for rapid categorization, irrespective of eccentricity. © 2015 ARVO.

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

PubMed

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

2016-10-01

Hepatic lipidosis is the most diffused hepatic disease in the lactating cow. A new methodology to estimate the degree of fatty infiltration of the liver in lactating cows by means of texture analysis of B-mode ultrasound images is proposed. B-mode ultrasonography of the liver was performed in 48 Holstein Friesian cows using standardized ultrasound parameters. Liver biopsies to determine the triacylglycerol content of the liver (TAGqa) were obtained from each animal. A large number of texture parameters were calculated on the ultrasound images by means of a free software. Based on the TAGqa content of the liver, 29 samples were classified as mild (TAGqa<50mg/g), 6 as moderate (50mg/g100mg/g) and 13 as severe (TAG>100mg/g) in steatosis. Stepwise linear regression analysis was performed to predict the TAGqa content of the liver (TAGpred) from the texture parameters calculated on the ultrasound images. A five-variable model was used to predict the TAG content from the ultrasound images. The regression model explained 83.4% of the variance. An area under the curve (AUC) of 0.949 was calculated for <50mg/g vs >50mg/g of TAGqa; using an optimal cut-off value of 72mg/g TAGpred had a sensitivity of 86.2% and a specificity of 84.2%. An AUC of 0.978 for <100mg/g vs >100mg/g of TAGqa was calculated; using an optimal cut-off value of 89mg/g, TAGpred sensitivity was 92.3% and specificity was 88.6%. Texture analysis of B-mode ultrasound images may therefore be used to accurately predict the TAG content of the liver in lactating cows. Copyright © 2016 Elsevier Ltd. All rights reserved.

Texture analysis of computed tomographic images in osteoporotic patients with sinus lift bone graft reconstruction.

PubMed

Marchand-Libouban, Hélène; Guillaume, Bernard; Bellaiche, Norbert; Chappard, Daniel

2013-05-01

Bone implants are now widely used to replace missing teeth. Bone grafting (sinus lift) is a very useful way to increase the bone volume of the maxilla in patients with bone atrophy. There is a 6- to 9-month delay for the receiver grafted site to heal before the implants can be placed. Computed tomography is a useful method to measure the amount of remaining bone before implantation and to evaluate the quality of the receiver bone at the end of the healing period. Texture analysis is a non-invasive method useful to characterize bone microarchitecture on X-ray images. Ten patients in which a sinus lift surgery was necessary before implantation were analyzed in the present study. All had a bone reconstruction with a combination of a biomaterial (beta tricalcium phosphate) and autograft bone harvested at the chin. Computed tomographic images were obtained before grafting (t0), at mid-interval (t1, 4.2 ± 0.7 months) and before implant placement (t2, 9.2 ± 0.6 months). Texture analysis was done with the run-length method. A significant increase of texture parameters at t1 reflected a gain of homogeneity due to the graft and the beginning of bone remodeling. At t2, some parameters remained high and corresponded to the persistence of bone trabeculae while the resorption of biomaterials was identified by other parameters which tended to return to pregraft values. Texture analysis identified changes during the healing of the receiver site. The method is known to correlate with microarchitectural changes in bone and could be a useful approach to characterized osseointegrated grafts.

Texture analysis of intermediate-advanced hepatocellular carcinoma: prognosis and patients' selection of transcatheter arterial chemoembolization and sorafenib

PubMed Central

Fu, Sirui; Chen, Shuting; Liang, Changhong; Liu, Zaiyi; Zhu, Yanjie; Li, Yong; Lu, Ligong

2017-01-01

Transcatheter arterial chemoembolization (TACE) and sorafenib combination treatment for unselected hepatocellular carcinoma (HCC) is controversial. We explored the potential of texture analysis for appropriate patient selection. There were 261 HCCs included (TACE group: n = 197; TACE plus sorafenib (TACE+Sorafenib) group n = 64). We applied a Gabor filter and wavelet transform with 3 band-width responses (filter 0, 1.0, and 1.5) to portal-phase computed tomography (CT) images of the TACE group. Twenty-one textural parameters per filter were extracted from the region of interests delineated around tumor outline. After testing survival correlations, the TACE group was subdivided according to parameter thresholds in receiver operating characteristic curves and compared to TACE+Sorafenib group survival. The Gabor-1-90 (filter 0) was most significantly correlated with TTP. The TACE group was accordingly divided into the TACE-1 (Gabor-1-90 ≤ 3.6190) and TACE-2 (Gabor-1-90 > 3.6190) subgroups; TTP was similar in the TACE-1 subgroup and TACE+Sorafenib group, but shorter in the TACE-2 subgroup. Only wavelet-3-D (filter 1.0) correlated with overall survival (OS), and was used for subgrouping. The TACE-5 (wavelet-3-D ≤ 12.2620) subgroup and the TACE+Sorafenib group showed similar OS, while the TACE-6 (wavelet-3-D > 12.2620) subgroup had shorter OS. Gabor-1-90 and wavelet-3-D were consistent. In dependent of tumor number or size, CT textural parameters are correlated with TTP and OS. Patients with lower Gabor-1-90 (filter 0) and wavelet-3-D (filter 1.0) should be treated with TACE and sorafenib. Texture analysis holds promise for appropriate selection of HCCs for this combination therapy. PMID:27911268

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.

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.

Effect of immersion chilling and air chilling on texture quality and cook yield of chicken breast tenderlion deboned for hours postmortem

USDA-ARS?s Scientific Manuscript database

Boneless chicken breast fillets (pectoralis major) and tenderloins (pectoralis minor) are common poultry products in retail markets and are used extensively by restaurants and food service. Texture quality of these products could be impacted by poultry processing methods and parameters. Effects of c...

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.

Inferring Species Richness and Turnover by Statistical Multiresolution Texture Analysis of Satellite Imagery

DTIC Science & Technology

2012-10-24

representative pdf’s via the Kullback - Leibler divergence (KL). Species turnover, or b diversity, is estimated using both this KL divergence and the...multiresolution analysis provides a means for estimating divergence between two textures, specifically the Kullback - Leibler divergence between the pair of ...and open challenges. Ecological Informatics 5: 318–329. 19. Ludovisi A, TaticchiM(2006) Investigating beta diversity by kullback - leibler information

Accuracy and variability of texture-based radiomics features of lung lesions across CT imaging conditions

NASA Astrophysics Data System (ADS)

Zheng, Yuese; Solomon, Justin; Choudhury, Kingshuk; Marin, Daniele; Samei, Ehsan

2017-03-01

Texture analysis for lung lesions is sensitive to changing imaging conditions but these effects are not well understood, in part, due to a lack of ground-truth phantoms with realistic textures. The purpose of this study was to explore the accuracy and variability of texture features across imaging conditions by comparing imaged texture features to voxel-based 3D printed textured lesions for which the true values are known. The seven features of interest were based on the Grey Level Co-Occurrence Matrix (GLCM). The lesion phantoms were designed with three shapes (spherical, lobulated, and spiculated), two textures (homogenous and heterogeneous), and two sizes (diameter < 1.5 cm and 1.5 cm < diameter < 3 cm), resulting in 24 lesions (with a second replica of each). The lesions were inserted into an anthropomorphic thorax phantom (Multipurpose Chest Phantom N1, Kyoto Kagaku) and imaged using a commercial CT system (GE Revolution) at three CTDI levels (0.67, 1.42, and 5.80 mGy), three reconstruction algorithms (FBP, IR-2, IR-4), four reconstruction kernel types (standard, soft, edge), and two slice thicknesses (0.6 mm and 5 mm). Another repeat scan was performed. Texture features from these images were extracted and compared to the ground truth feature values by percent relative error. The variability across imaging conditions was calculated by standard deviation across a certain imaging condition for all heterogeneous lesions. The results indicated that the acquisition method has a significant influence on the accuracy and variability of extracted features and as such, feature quantities are highly susceptible to imaging parameter choices. The most influential parameters were slice thickness and reconstruction kernels. Thin slice thickness and edge reconstruction kernel overall produced more accurate and more repeatable results. Some features (e.g., Contrast) were more accurately quantified under conditions that render higher spatial frequencies (e.g., thinner slice thickness and sharp kernels), while others (e.g., Homogeneity) showed more accurate quantification under conditions that render smoother images (e.g., higher dose and smoother kernels). Care should be exercised is relating texture features between cases of varied acquisition protocols, with need to cross calibration dependent on the feature of interest.

Textural features and SUV-based variables assessed by dual time point 18F-FDG PET/CT in locally advanced breast cancer.

PubMed

Garcia-Vicente, Ana María; Molina, David; Pérez-Beteta, Julián; Amo-Salas, Mariano; Martínez-González, Alicia; Bueno, Gloria; Tello-Galán, María Jesús; Soriano-Castrejón, Ángel

2017-12-01

To study the influence of dual time point 18F-FDG PET/CT in textural features and SUV-based variables and their relation among them. Fifty-six patients with locally advanced breast cancer (LABC) were prospectively included. All of them underwent a standard 18F-FDG PET/CT (PET-1) and a delayed acquisition (PET-2). After segmentation, SUV variables (SUVmax, SUVmean, and SUVpeak), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) were obtained. Eighteen three-dimensional (3D) textural measures were computed including: run-length matrices (RLM) features, co-occurrence matrices (CM) features, and energies. Differences between all PET-derived variables obtained in PET-1 and PET-2 were studied. Significant differences were found between the SUV-based parameters and MTV obtained in the dual time point PET/CT, with higher values of SUV-based variables and lower MTV in the PET-2 with respect to the PET-1. In relation with the textural parameters obtained in dual time point acquisition, significant differences were found for the short run emphasis, low gray-level run emphasis, short run high gray-level emphasis, run percentage, long run emphasis, gray-level non-uniformity, homogeneity, and dissimilarity. Textural variables showed relations with MTV and TLG. Significant differences of textural features were found in dual time point 18F-FDG PET/CT. Thus, a dynamic behavior of metabolic characteristics should be expected, with higher heterogeneity in delayed PET acquisition compared with the standard PET. A greater heterogeneity was found in bigger tumors.

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

PubMed

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

2017-09-01

To investigate the feasibility of using CT texture analysis (CTTA) to differentiate pheochromocytoma from lipid-poor adrenocortical adenoma (lp-ACA). Ninety-eight pheochromocytomas and 66 lp-ACAs were included in this retrospective study. CTTA was performed on unenhanced and enhanced images. Receiver operating characteristic (ROC) analysis was performed, and the area under the ROC curve (AUC) was calculated for texture parameters that were significantly different for the objective. Diagnostic accuracies were evaluated using the cutoff values of texture parameters with the highest AUCs. Compared to lp-ACAs, pheochromocytomas had significantly higher mean gray-level intensity (Mean), entropy, and mean of positive pixels (MPP), but lower skewness and kurtosis on unenhanced images (P < 0.001). On enhanced images, these texture-quantifiers followed a similar trend where Mean, entropy, and MPP were higher, but skewness and kurtosis were lower in pheochromocytomas. Standard deviation (SD) was also significantly higher in pheochromocytomas on enhanced images. Mean and MPP quantified from no filtration on unenhanced CT images yielded the highest AUC of 0.86 ± 0.03 (95% CI 0.81-0.91) at a cutoff value of 34.0 for Mean and MPP, respectively (sensitivity = 79.6%, specificity = 83.3%, accuracy = 81.1%). It was feasible to use CTTA to differentiate pheochromocytoma from lp-ACA.

Capillary rise in a textured channel

NASA Astrophysics Data System (ADS)

Beilharz, Daniel; Clanet, Christophe; Quere, David

2016-11-01

A wetting liquid can invade a textured material, for example a forest of micropillars. The driving and the viscous forces of this motion are determined by the texture parameters and the influence of shape, height and spacing of posts has been widely studied for the last decade. In this work, we build a channel with textured walls. Brought into contact with a reservoir of wetting liquid, we observe in some cases two advancing fronts. A first one ahead invading the forest of micropillars, and a second one behind filling the remaining gap. We study and model the conditions of existence and the dynamics of these two fronts as a function of the characteristics of both microstructure and gap of this elementary porous medium.

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.

Shear-Coupled Grain Growth and Texture Development in a Nanocrystalline Ni-Fe Alloy during Cold Rolling

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

Li, Li; Ungár, Tamás; Toth, Laszlo S.

The evolution of texture, grain size, grain shape, dislocation and twin density has been determined by synchrotron X-ray diffraction and line profile analysis in a nanocrystalline Ni- Fe alloy after cold rolling along different directions related to the initial fiber and the long axis of grains. The texture evolution has been simulated by the Taylor-type relaxed constraints viscoplastic polycrystal model. The simulations were based on the activity of partial dislocations in correlation with the experimental results of dislocation density determination. The concept of stress-induced shear-coupling is supported and strengthened by both the texture simulations and the experimentally determined evolution ofmore » the microstructure parameters. Grain-growth and texture evolution are shown to proceed by the shear-coupling mechanism supported by dislocation activity as long as the grain size is not smaller than about 20 nm.« less

Comparing the role of shape and texture on staging hepatic fibrosis from medical imaging

NASA Astrophysics Data System (ADS)

Zhang, Xuejun; Louie, Ryan; Liu, Brent J.; Gao, Xin; Tan, Xiaomin; Qu, Xianghe; Long, Liling

2016-03-01

The purpose of this study is to investigate the role of shape and texture in the classification of hepatic fibrosis by selecting the optimal parameters for a better Computer-aided diagnosis (CAD) system. 10 surface shape features are extracted from a standardized profile of liver; while15 texture features calculated from gray level co-occurrence matrix (GLCM) are extracted within an ROI in liver. Each combination of these input subsets is checked by using support vector machine (SVM) with leave-one-case-out method to differentiate fibrosis into two groups: normal or abnormal. The accurate rate value of all 10/15 types number of features is 66.83% by texture, while 85.74% by shape features, respectively. The irregularity of liver shape can demonstrate fibrotic grade efficiently and texture feature of CT image is not recommended to use with shape feature for interpretation of cirrhosis.

Textural properties of mango cultivars during ripening.

PubMed

Jha, Shyam Narayan; Jaiswal, Pranita; Narsaiah, Kairam; Kaur, Poonam Preet; Singh, Ashish Kumar; Kumar, Ramesh

2013-12-01

Firmness and toughness of fruit, peel and pulp of seven different mango cultivars were studied over a ripening period of ten days to investigate the effects of harvesting stages (early, mid and late) on fruit quality. Parameters were measured at equatorial region of fruits using TA-Hdi Texture Analyzer. The textural characteristics showed a rapid decline in their behaviour until mangoes got ripened and thereafter, the decline became almost constant indicating the completion of ripening. However, the rate of decline in textural properties was found to be cultivar specific. In general, the changes in textural attributes were found to be significantly influenced by ripening period and stage of harvesting, but firmness attributes (peel, fruit and pulp) of early harvested mangoes did not differ significantly from mid harvested mangoes, while peel, fruit and pulp firmness of late harvested mangoes were found to be significantly lower than early and mid harvested mangoes.

High-order statistics of weber local descriptors for image representation.

PubMed

Han, Xian-Hua; Chen, Yen-Wei; Xu, Gang

2015-06-01

Highly discriminant visual features play a key role in different image classification applications. This study aims to realize a method for extracting highly-discriminant features from images by exploring a robust local descriptor inspired by Weber's law. The investigated local descriptor is based on the fact that human perception for distinguishing a pattern depends not only on the absolute intensity of the stimulus but also on the relative variance of the stimulus. Therefore, we firstly transform the original stimulus (the images in our study) into a differential excitation-domain according to Weber's law, and then explore a local patch, called micro-Texton, in the transformed domain as Weber local descriptor (WLD). Furthermore, we propose to employ a parametric probability process to model the Weber local descriptors, and extract the higher-order statistics to the model parameters for image representation. The proposed strategy can adaptively characterize the WLD space using generative probability model, and then learn the parameters for better fitting the training space, which would lead to more discriminant representation for images. In order to validate the efficiency of the proposed strategy, we apply three different image classification applications including texture, food images and HEp-2 cell pattern recognition, which validates that our proposed strategy has advantages over the state-of-the-art approaches.

Multispectral imaging system based on light-emitting diodes for the detection of melanomas and basal cell carcinomas: a pilot study

NASA Astrophysics Data System (ADS)

Delpueyo, Xana; Vilaseca, Meritxell; Royo, Santiago; Ares, Miguel; Rey-Barroso, Laura; Sanabria, Ferran; Puig, Susana; Pellacani, Giovanni; Noguero, Fernando; Solomita, Giuseppe; Bosch, Thierry

2017-06-01

This article proposes a multispectral system that uses the analysis of the spatial distribution of color and spectral features to improve the detection of skin cancer lesions, specifically melanomas and basal cell carcinomas. The system consists of a digital camera and light-emitting diodes of eight different wavelengths (414 to 995 nm). The parameters based on spectral features of the lesions such as reflectance and color, as well as others empirically computed using reflectance values, were calculated pixel-by-pixel from the images obtained. Statistical descriptors were calculated for every segmented lesion [mean (x˜), standard deviation (σ), minimum, and maximum]; descriptors based on the first-order statistics of the histogram [entropy (Ep), energy (En), and third central moment (μ3)] were also obtained. The study analyzed 429 pigmented and nonpigmented lesions: 290 nevi and 139 malignant (95 melanomas and 44 basal cell carcinomas), which were split into training and validation sets. Fifteen parameters were found to provide the best sensitivity (87.2% melanomas and 100% basal cell carcinomas) and specificity (54.5%). The results suggest that the extraction of textural information can contribute to the diagnosis of melanomas and basal cell carcinomas as a supporting tool to dermoscopy and confocal microscopy.

Crystal surface analysis using matrix textural features classified by a probabilistic neural network

NASA Astrophysics Data System (ADS)

Sawyer, Curry R.; Quach, Viet; Nason, Donald; van den Berg, Lodewijk

1991-12-01

A system is under development in which surface quality of a growing bulk mercuric iodide crystal is monitored by video camera at regular intervals for early detection of growth irregularities. Mercuric iodide single crystals are employed in radiation detectors. A microcomputer system is used for image capture and processing. The digitized image is divided into multiple overlapping sub-images and features are extracted from each sub-image based on statistical measures of the gray tone distribution, according to the method of Haralick. Twenty parameters are derived from each sub-image and presented to a probabilistic neural network (PNN) for classification. This number of parameters was found to be optimal for the system. The PNN is a hierarchical, feed-forward network that can be rapidly reconfigured as additional training data become available. Training data is gathered by reviewing digital images of many crystals during their growth cycle and compiling two sets of images, those with and without irregularities.

Detection of Changes on and below the Surface in Epithelium Mucosal Tissue Structure using Scattered Light

NASA Astrophysics Data System (ADS)

Taslidere, Ezgi

The aim of this work is to answer the question of whether it is possible to detect changes on and below the surface in epithelium tissue structure using light reflected from the tissue over an area (2-D scan) illuminated by an optical sensor (fiber) emitting light at either one wavelength or with white light. Towards that end we model the 2-D reflected scans using a Stochastic Decomposition Method (SDM). The emphasis in this work is on the novelty of the proposed model and its theoretical pinning and foundation. The model is biologically motivated by the stochastic textural nature of the tissue. We model the textural content (which relates to tissue morphology) that manifests itself in the 2-D scans. Unlike previous works that analyze the scattered signal at one spot at various wavelengths, our method statistically analyzes 2-D scans of light scattering data over an area, and extracts from the data features (SDM parameters) that change with changes in the tissue morphology. The examination of an area rather than a spot not only leads to a more reliable calculation of the extracted parameters using single techniques (e.g. nuclear size distribution), but it also leads to the computation of additional information embedded in the spatial texture that our decomposition technique arrives at by modeling the hidden correlations that are obtained only by interrogating a wide sample area. To the best of our knowledge, this is the first attempt at modeling the scattered light over an area using a stochastic decomposition model that allows for the assessment of correlation and textural characteristics that otherwise could not be revealed when the analysis of the scattering signal is a function of wavelength or angle. We also come up with a segmentation technique to raise a flag on the fly when a transition occurs between different mucosal architectures on the surface. The segmentation is based on a novel difference metric for detecting an abrupt change in the parameters extracted from SDM. This has a great potential to enhance the endoscopist's ability to locate and identify abnormal mucosal architectures and help the endoscopist's decision making for when and where to take biopsies. Finally, this work presents a meaningful comparison between existing point spectroscopy methods and our method on tissue phantom data as well as in vitro biological tissues and shows scenarios where the two methods are complimentary and other scenarios where our method will be able to detect changes in tissue morphology whereas point spectroscopy will not. The method is tested on simulation, tissue phantom data and animal tissue data collected from rat and rabbit colons in-vitro and shows great promise.

Weighted recalibration of the Rosetta pedotransfer model with improved estimates of hydraulic parameter distributions and summary statistics (Rosetta3)

NASA Astrophysics Data System (ADS)

Zhang, Yonggen; Schaap, Marcel G.

2017-04-01

Pedotransfer functions (PTFs) have been widely used to predict soil hydraulic parameters in favor of expensive laboratory or field measurements. Rosetta (Schaap et al., 2001, denoted as Rosetta1) is one of many PTFs and is based on artificial neural network (ANN) analysis coupled with the bootstrap re-sampling method which allows the estimation of van Genuchten water retention parameters (van Genuchten, 1980, abbreviated here as VG), saturated hydraulic conductivity (Ks), and their uncertainties. In this study, we present an improved set of hierarchical pedotransfer functions (Rosetta3) that unify the water retention and Ks submodels into one. Parameter uncertainty of the fit of the VG curve to the original retention data is used in the ANN calibration procedure to reduce bias of parameters predicted by the new PTF. One thousand bootstrap replicas were used to calibrate the new models compared to 60 or 100 in Rosetta1, thus allowing the uni-variate and bi-variate probability distributions of predicted parameters to be quantified in greater detail. We determined the optimal weights for VG parameters and Ks, the optimal number of hidden nodes in ANN, and the number of bootstrap replicas required for statistically stable estimates. Results show that matric potential-dependent bias was reduced significantly while root mean square error (RMSE) for water content were reduced modestly; RMSE for Ks was increased by 0.9% (H3w) to 3.3% (H5w) in the new models on log scale of Ks compared with the Rosetta1 model. It was found that estimated distributions of parameters were mildly non-Gaussian and could instead be described rather well with heavy-tailed α-stable distributions. On the other hand, arithmetic means had only a small estimation bias for most textures when compared with the mean-like "shift" parameter of the α-stable distributions. Arithmetic means and (co-)variances are therefore still recommended as summary statistics of the estimated distributions. However, it may be necessary to parameterize the distributions in different ways if the new estimates are used in stochastic analyses of vadose zone flow and transport. Rosetta1 and Posetta3 were implemented in the python programming language, and the source code as well as additional documentation is available at: http://www.cals.arizona.edu/research/rosettav3.html.

Automated labelling of cancer textures in colorectal histopathology slides using quasi-supervised learning.

PubMed

Onder, Devrim; Sarioglu, Sulen; Karacali, Bilge

2013-04-01

Quasi-supervised learning is a statistical learning algorithm that contrasts two datasets by computing estimate for the posterior probability of each sample in either dataset. This method has not been applied to histopathological images before. The purpose of this study is to evaluate the performance of the method to identify colorectal tissues with or without adenocarcinoma. Light microscopic digital images from histopathological sections were obtained from 30 colorectal radical surgery materials including adenocarcinoma and non-neoplastic regions. The texture features were extracted by using local histograms and co-occurrence matrices. The quasi-supervised learning algorithm operates on two datasets, one containing samples of normal tissues labelled only indirectly, and the other containing an unlabeled collection of samples of both normal and cancer tissues. As such, the algorithm eliminates the need for manually labelled samples of normal and cancer tissues for conventional supervised learning and significantly reduces the expert intervention. Several texture feature vector datasets corresponding to different extraction parameters were tested within the proposed framework. The Independent Component Analysis dimensionality reduction approach was also identified as the one improving the labelling performance evaluated in this series. In this series, the proposed method was applied to the dataset of 22,080 vectors with reduced dimensionality 119 from 132. Regions containing cancer tissue could be identified accurately having false and true positive rates up to 19% and 88% respectively without using manually labelled ground-truth datasets in a quasi-supervised strategy. The resulting labelling performances were compared to that of a conventional powerful supervised classifier using manually labelled ground-truth data. The supervised classifier results were calculated as 3.5% and 95% for the same case. The results in this series in comparison with the benchmark classifier, suggest that quasi-supervised image texture labelling may be a useful method in the analysis and classification of pathological slides but further study is required to improve the results. Copyright © 2013 Elsevier Ltd. All rights reserved.

Development of an Engineering Soil Database

DTIC Science & Technology

2017-12-27

systems such as agricultural and geological soil classifications and soil parameters. Tier 3 Data were converted into equivalent USCS classification...14 2.7 U.S. Department of Agriculture (USDA) textural soil classification ............................ 16 2.7.1 Properties of USDA textural...Defense ERDC U.S. Army Engineer Research and Development Center ESDB European Soil Database FAO Food and Agriculture Organization (of the United

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

USDA-ARS?s Scientific Manuscript database

BACKGROUND: 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 evalua...

Using Parameters of Dynamic Pulse Function for 3d Modeling in LOD3 Based on Random Textures

NASA Astrophysics Data System (ADS)

Alizadehashrafi, B.

2015-12-01

The pulse function (PF) is a technique based on procedural preprocessing system to generate a computerized virtual photo of the façade with in a fixed size square(Alizadehashrafi et al., 2009, Musliman et al., 2010). Dynamic Pulse Function (DPF) is an enhanced version of PF which can create the final photo, proportional to real geometry. This can avoid distortion while projecting the computerized photo on the generated 3D model(Alizadehashrafi and Rahman, 2013). The challenging issue that might be handled for having 3D model in LoD3 rather than LOD2, is the final aim that have been achieved in this paper. In the technique based DPF the geometries of the windows and doors are saved in an XML file schema which does not have any connections with the 3D model in LoD2 and CityGML format. In this research the parameters of Dynamic Pulse Functions are utilized via Ruby programming language in SketchUp Trimble to generate (exact position and deepness) the windows and doors automatically in LoD3 based on the same concept of DPF. The advantage of this technique is automatic generation of huge number of similar geometries e.g. windows by utilizing parameters of DPF along with defining entities and window layers. In case of converting the SKP file to CityGML via FME software or CityGML plugins the 3D model contains the semantic database about the entities and window layers which can connect the CityGML to MySQL(Alizadehashrafi and Baig, 2014). The concept behind DPF, is to use logical operations to project the texture on the background image which is dynamically proportional to real geometry. The process of projection is based on two vertical and horizontal dynamic pulses starting from upper-left corner of the background wall in down and right directions respectively based on image coordinate system. The logical one/zero on the intersections of two vertical and horizontal dynamic pulses projects/does not project the texture on the background image. It is possible to define priority for each layer. For instance the priority of the door layer can be higher than window layer which means that window texture cannot be projected on the door layer. Orthogonal and rectified perpendicular symmetric photos of the 3D objects that are proportional to the real façade geometry must be utilized for the generation of the output frame for DPF. The DPF produces very high quality and small data size of output image files in quite smaller dimension compare with the photorealistic texturing method. The disadvantage of DPF is its preprocessing method to generate output image file rather than online processing to generate the texture within the 3D environment such as CityGML. Furthermore the result of DPF can be utilized for 3D model in LOD2 rather than LOD3. In the current work the random textures of the window layers are created based on parameters of DPF within Ruby console of SketchUp Trimble to generate the deeper geometries of the windows and their exact position on the façade automatically along with random textures to increase Level of Realism (LoR)(Scarpino, 2010). As the output frame in DPF is proportional to real geometry (height and width of the façade) it is possible to query the XML database and convert them to units such as meter automatically. In this technique, the perpendicular terrestrial photo from the façade is rectified by employing projective transformation based on the frame which is in constrain proportion to real geometry. The rectified photos which are not suitable for texturing but necessary for measuring, can be resized in constrain proportion to real geometry before measuring process. Height and width of windows, doors, horizontal and vertical distance between windows from upper left corner of the photo dimensions of doors and windows are parameters that should be measured to run the program as a plugins in SketchUp Trimble. The system can use these parameters and texture file names and file paths to create the façade semi-automatically. To avoid leaning geometry the textures of windows, doors and etc, should be cropped and rectified from perpendicular photos, so that they can be used in the program to create the whole façade along with its geometries. Texture enhancement should be done in advance such as removing disturbing objects, exposure setting, left-right up-down transformation, and so on. In fact, the quality, small data size, scale and semantic database for each façade are the prominent advantages of this method.

Investigation on improved infrared image detail enhancement algorithm based on adaptive histogram statistical stretching and gradient filtering

NASA Astrophysics Data System (ADS)

Zeng, Bangze; Zhu, Youpan; Li, Zemin; Hu, Dechao; Luo, Lin; Zhao, Deli; Huang, Juan

2014-11-01

Duo to infrared image with low contrast, big noise and unclear visual effect, target is very difficult to observed and identified. This paper presents an improved infrared image detail enhancement algorithm based on adaptive histogram statistical stretching and gradient filtering (AHSS-GF). Based on the fact that the human eyes are very sensitive to the edges and lines, the author proposed to extract the details and textures by using the gradient filtering. New histogram could be acquired by calculating the sum of original histogram based on fixed window. With the minimum value for cut-off point, author carried on histogram statistical stretching. After the proper weights given to the details and background, the detail-enhanced results could be acquired finally. The results indicate image contrast could be improved and the details and textures could be enhanced effectively as well.

Aural analysis of image texture via cepstral filtering and sonification

NASA Astrophysics Data System (ADS)

Rangayyan, Rangaraj M.; Martins, Antonio C. G.; Ruschioni, Ruggero A.

1996-03-01

Texture plays an important role in image analysis and understanding, with many applications in medical imaging and computer vision. However, analysis of texture by image processing is a rather difficult issue, with most techniques being oriented towards statistical analysis which may not have readily comprehensible perceptual correlates. We propose new methods for auditory display (AD) and sonification of (quasi-) periodic texture (where a basic texture element or `texton' is repeated over the image field) and random texture (which could be modeled as filtered or `spot' noise). Although the AD designed is not intended to be speech- like or musical, we draw analogies between the two types of texture mentioned above and voiced/unvoiced speech, and design a sonification algorithm which incorporates physical and perceptual concepts of texture and speech. More specifically, we present a method for AD of texture where the projections of the image at various angles (Radon transforms or integrals) are mapped to audible signals and played in sequence. In the case of random texture, the spectral envelopes of the projections are related to the filter spot characteristics, and convey the essential information for texture discrimination. In the case of periodic texture, the AD provides timber and pitch related to the texton and periodicity. In another procedure for sonification of periodic texture, we propose to first deconvolve the image using cepstral analysis to extract information about the texton and horizontal and vertical periodicities. The projections of individual textons at various angles are used to create a voiced-speech-like signal with each projection mapped to a basic wavelet, the horizontal period to pitch, and the vertical period to rhythm on a longer time scale. The sound pattern then consists of a serial, melody-like sonification of the patterns for each projection. We believe that our approaches provide the much-desired `natural' connection between the image data and the sounds generated. We have evaluated the sonification techniques with a number of synthetic textures. The sound patterns created have demonstrated the potential of the methods in distinguishing between different types of texture. We are investigating the application of these techniques to auditory analysis of texture in medical images such as magnetic resonance images.

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.

Revisiting the Robustness of PET-Based Textural Features in the Context of Multi-Centric Trials

PubMed Central

Bailly, Clément; Bodet-Milin, Caroline; Couespel, Solène; Necib, Hatem; Kraeber-Bodéré, Françoise; Ansquer, Catherine; Carlier, Thomas

2016-01-01

Purpose This study aimed to investigate the variability of textural features (TF) as a function of acquisition and reconstruction parameters within the context of multi-centric trials. Methods The robustness of 15 selected TFs were studied as a function of the number of iterations, the post-filtering level, input data noise, the reconstruction algorithm and the matrix size. A combination of several reconstruction and acquisition settings was devised to mimic multi-centric conditions. We retrospectively studied data from 26 patients enrolled in a diagnostic study that aimed to evaluate the performance of PET/CT 68Ga-DOTANOC in gastro-entero-pancreatic neuroendocrine tumors. Forty-one tumors were extracted and served as the database. The coefficient of variation (COV) or the absolute deviation (for the noise study) was derived and compared statistically with SUVmax and SUVmean results. Results The majority of investigated TFs can be used in a multi-centric context when each parameter is considered individually. The impact of voxel size and noise in the input data were predominant as only 4 TFs presented a high/intermediate robustness against SUV-based metrics (Entropy, Homogeneity, RP and ZP). When combining several reconstruction settings to mimic multi-centric conditions, most of the investigated TFs were robust enough against SUVmax except Correlation, Contrast, LGRE, LGZE and LZLGE. Conclusion Considering previously published results on either reproducibility or sensitivity against delineation approach and our findings, it is feasible to consider Homogeneity, Entropy, Dissimilarity, HGRE, HGZE and ZP as relevant for being used in multi-centric trials. PMID:27467882

Applying tribology to teeth of hoofed mammals.

PubMed

Schulz, Ellen; Calandra, Ivan; Kaiser, Thomas M

2010-01-01

Mammals inhabit all types of environments and have evolved chewing systems capable of processing a huge variety of structurally diverse food components. Surface textures of cheek teeth should thus reflect the mechanisms of wear as well as the functional traits involved. We employed surface textures parameters from ISO/DIS 25178 and scale-sensitive fractal analysis (SSFA) to quantify dental wear in herbivorous mammals at the level of an individual wear enamel facet. We evaluated cheek dentitions of two grazing ungulates: the Blue Wildebeest (Connochaetes taurinus) and the Grevy's Zebra (Equus grevyi). Both inhabit the east African grassland savanna habitat, but they belong to fundamentally different taxonomic units. We tested the hypothesis that the foregut fermenting wildebeest and the hindgut fermenting zebra show functional traits in their dentitions that relate to their specific mode of food-composition processing and digestion. In general, surface texture parameters from SSFA as well as ISO/DIS 25178 indicated that individual enamel ridges acting as crushing blades and individual wear facets of upper cheek teeth are significantly different in surface textures in the zebra when compared with the wildebeest. We interpreted the complexity and anisotropy signals to be clearly related to the brittle, dry grass component in the diet of the zebra, unlike the wildebeest, which ingests a more heterogeneous diet including fresh grass and herbs. Thus, SSFA and ISO parameters allow distinctions within the subtle dietary strategies that evolved in herbivorous ungulates with fundamentally different systematic affinities but which exploit a similar dietary niche. © 2010 Wiley Periodicals, Inc.

Laser gas assisted texturing and formation of nitride and oxynitride compounds on alumina surface: Surface response to environmental dust

NASA Astrophysics Data System (ADS)

Yilbas, B. S.; Ali, H.; Al-Sharafi, A.; Al-Aqeeli, N.

2018-03-01

Laser gas assisted texturing of alumina surface is carried out, and formation of nitride and oxynitride compounds in the surface vicinity is examined. The laser parameters are selected to create the surface topology consisting of micro/nano pillars with minimum defect sites including micro-cracks, voids and large size cavities. Morphological and hydrophobic characteristics of the textured surface are examined using the analytical tools. The characteristics of the environmental dust and its influence on the laser textured surface are studied while mimicking the local humid air ambient. Adhesion of the dry mud on the laser textured surface is assessed through the measurement of the tangential force, which is required to remove the dry mud from the surface. It is found that laser texturing gives rise to micro/nano pillars topology and the formation of AlN and AlON compounds in the surface vicinity. This, in turn, lowers the free energy of the textured surface and enhances the hydrophobicity of the surface. The liquid solution resulted from the dissolution of alkaline and alkaline earth metals of the dust particles in water condensate forms locally scattered liquid islands at the interface of mud and textured surface. The dried liquid solution at the interface increases the dry mud adhesion on the textured surface. Some dry mud residues remain on the textured surface after the dry mud is removed by a pressurized desalinated water jet.

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.

Early prediction of lung cancer recurrence after stereotactic radiotherapy using second order texture statistics

NASA Astrophysics Data System (ADS)

Mattonen, Sarah A.; Palma, David A.; Haasbeek, Cornelis J. A.; Senan, Suresh; Ward, Aaron D.

2014-03-01

Benign radiation-induced lung injury is a common finding following stereotactic ablative radiotherapy (SABR) for lung cancer, and is often difficult to differentiate from a recurring tumour due to the ablative doses and highly conformal treatment with SABR. Current approaches to treatment response assessment have shown limited ability to predict recurrence within 6 months of treatment. The purpose of our study was to evaluate the accuracy of second order texture statistics for prediction of eventual recurrence based on computed tomography (CT) images acquired within 6 months of treatment, and compare with the performance of first order appearance and lesion size measures. Consolidative and ground-glass opacity (GGO) regions were manually delineated on post-SABR CT images. Automatic consolidation expansion was also investigated to act as a surrogate for GGO position. The top features for prediction of recurrence were all texture features within the GGO and included energy, entropy, correlation, inertia, and first order texture (standard deviation of density). These predicted recurrence with 2-fold cross validation (CV) accuracies of 70-77% at 2- 5 months post-SABR, with energy, entropy, and first order texture having leave-one-out CV accuracies greater than 80%. Our results also suggest that automatic expansion of the consolidation region could eliminate the need for manual delineation, and produced reproducible results when compared to manually delineated GGO. If validated on a larger data set, this could lead to a clinically useful computer-aided diagnosis system for prediction of recurrence within 6 months of SABR and allow for early salvage therapy for patients with recurrence.

Computerized Liquid Crystal Phase Identification by Neural Networks Analysis of Polarizing Microscopy Textures

NASA Astrophysics Data System (ADS)

Karaszi, Zoltan; Konya, Andrew; Dragan, Feodor; Jakli, Antal; CPIP/LCI; CS Dept. of Kent State University Collaboration

Polarizing optical microscopy (POM) is traditionally the best-established method of studying liquid crystals, and using POM started already with Otto Lehman in 1890. An expert, who is familiar with the science of optics of anisotropic materials and typical textures of liquid crystals, can identify phases with relatively large confidence. However, for unambiguous identification usually other expensive and time-consuming experiments are needed. Replacement of the subjective and qualitative human eye-based liquid crystal texture analysis with quantitative computerized image analysis technique started only recently and were used to enhance the detection of smooth phase transitions, determine order parameter and birefringence of specific liquid crystal phases. We investigate if the computer can recognize and name the phase where the texture was taken. To judge the potential of reliable image recognition based on this procedure, we used 871 images of liquid crystal textures belonging to five main categories: Nematic, Smectic A, Smectic C, Cholesteric and Crystal, and used a Neural Network Clustering Technique included in the data mining software package in Java ``WEKA''. A neural network trained on a set of 827 LC textures classified the remaining 44 textures with 80% accuracy.

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

PubMed

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

2017-06-01

The quality of extruded snacks can be affected not only by processing conditions, but also by some factors like the concentration and type of ingredients incorporated in their formulation and the working conditions used. Although the process conditions have been established with measurable textural properties, sensory qualities have not been correlated with these responses in expanded extruded snacks made with added functional ingredients. Therefore, in this study the effect of adding textured soy flour (TSF) and whole wheat flour (WWF) to refined wheat flour in the production of extruded snacks and expanded with hot air was evaluated. A response surface design using two levels with five central points was applied to obtain the best combinations of functional ingredients added, holding the parameters of the extrusion process and moisture of treatments. Some texture characteristics and sensory analysis were used as response variables, such as, hardness, fracturability, toughness, crispness, granularity, and chewiness. Likewise, the rate of expansion was evaluated. The results showed that the level of substitution of WWF, especially levels of 15%, had a significant effect on the hardness perceived by the panelist during sensory evaluation. The TSF at concentrations of ≥15%, favored the fracturability and crispness of the samples. It was found that the best expansion index was with the combination of 5% TSF and 15% WWF. Although a correlation between instrumental and sensory tests carried out on the extruded snacks expanded was not found. The physical characteristics of the extruded snacks such as expansion, hardness, and density are important parameters in terms of consumer acceptability of the final product as well as their functional properties. In other words, the appearance and texture are two of the most important attributes that can be seen in snack foods. In particular, the texture can be measured by intrinsic tests: objective (instrumental) and subjective (sensory). That is because the instrumental analysis provides parameters such as firmness, brittleness, consistency, chewiness, among others, when subjected to different stress, strain, and strain rates at the snacks. Similarly, sensory analysis, allows us to see features that include mechanical attributes (concerning the reaction to the applied force), geometric attributes (concerning the shape, size, and orientation of the particles within the food), and attributes related to the perception of moisture or fat content. © 2016 Wiley Periodicals, Inc.

Textural features in pre-treatment [F18]-FDG-PET/CT are correlated with risk of local recurrence and disease-specific survival in early stage NSCLC patients receiving primary stereotactic radiation therapy.

PubMed

Pyka, Thomas; Bundschuh, Ralph A; Andratschke, Nicolaus; Mayer, Benedikt; Specht, Hanno M; Papp, Laszló; Zsótér, Norbert; Essler, Markus

2015-04-22

Textural features in FDG-PET have been shown to provide prognostic information in a variety of tumor entities. Here we evaluate their predictive value for recurrence and prognosis in NSCLC patients receiving primary stereotactic radiation therapy (SBRT). 45 patients with early stage NSCLC (T1 or T2 tumor, no lymph node or distant metastases) were included in this retrospective study and followed over a median of 21.4 months (range 3.1-71.1). All patients were considered non-operable due to concomitant disease and referred to SBRT as the primary treatment modality. Pre-treatment FDG-PET/CT scans were obtained from all patients. SUV and volume-based analysis as well as extraction of textural features based on neighborhood gray-tone difference matrices (NGTDM) and gray-level co-occurence matrices (GLCM) were performed using InterView Fusion™ (Mediso Inc., Budapest). The ability to predict local recurrence (LR), lymph node (LN) and distant metastases (DM) was measured using the receiver operating characteristic (ROC). Univariate and multivariate analysis of overall and disease-specific survival were executed. 7 out of 45 patients (16%) experienced LR, 11 (24%) LN and 11 (24%) DM. ROC revealed a significant correlation of several textural parameters with LR with an AUC value for entropy of 0.872. While there was also a significant correlation of LR with tumor size in the overall cohort, only texture was predictive when examining T1 (tumor diameter < = 3 cm) and T2 (>3 cm) subgroups. No correlation of the examined PET parameters with LN or DM was shown. In univariate survival analysis, both heterogeneity and tumor size were predictive for disease-specific survival, but only texture determined by entropy was determined as an independent factor in multivariate analysis (hazard ratio 7.48, p = .016). Overall survival was not significantly correlated to any examined parameter, most likely due to the high comorbidity in our cohort. Our study adds to the growing evidence that tumor heterogeneity as described by FDG-PET texture is associated with response to radiation therapy in NSCLC. The results may be helpful into identifying patients who might profit from an intensified treatment regime, but need to be verified in a prospective patient cohort before being incorporated into routine clinical practice.

Parameterization of Shape and Compactness in Object-based Image Classification Using Quickbird-2 Imagery

NASA Astrophysics Data System (ADS)

Tonbul, H.; Kavzoglu, T.

2016-12-01

In recent years, object based image analysis (OBIA) has spread out and become a widely accepted technique for the analysis of remotely sensed data. OBIA deals with grouping pixels into homogenous objects based on spectral, spatial and textural features of contiguous pixels in an image. The first stage of OBIA, named as image segmentation, is the most prominent part of object recognition. In this study, multiresolution segmentation, which is a region-based approach, was employed to construct image objects. In the application of multi-resolution, three parameters, namely shape, compactness and scale must be set by the analyst. Segmentation quality remarkably influences the fidelity of the thematic maps and accordingly the classification accuracy. Therefore, it is of great importance to search and set optimal values for the segmentation parameters. In the literature, main focus has been on the definition of scale parameter, assuming that the effect of shape and compactness parameters is limited in terms of achieved classification accuracy. The aim of this study is to deeply analyze the influence of shape/compactness parameters by varying their values while using the optimal scale parameter determined by the use of Estimation of Scale Parameter (ESP-2) approach. A pansharpened Qickbird-2 image covering Trabzon, Turkey was employed to investigate the objectives of the study. For this purpose, six different combinations of shape/compactness were utilized to make deductions on the behavior of shape and compactness parameters and optimal setting for all parameters as a whole. Objects were assigned to classes using nearest neighbor classifier in all segmentation observations and equal number of pixels was randomly selected to calculate accuracy metrics. The highest overall accuracy (92.3%) was achieved by setting the shape/compactness criteria to 0.3/0.3. The results of this study indicate that shape/compactness parameters can have significant effect on classification accuracy with 4% change in overall accuracy. Also, statistical significance of differences in accuracy was tested using the McNemar's test and found that the difference between poor and optimal setting of shape/compactness parameters was statistically significant, suggesting a search for optimal parameterization instead of default setting.

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.

Brownian motion curve-based textural classification and its application in cancer diagnosis.

PubMed

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

2011-06-01

To develop an automated diagnostic methodology based on textural features of the oral mucosal epithelium to discriminate normal and oral submucous fibrosis (OSF). A total of 83 normal and 29 OSF images from histopathologic sections of the oral mucosa are considered. The proposed diagnostic mechanism consists of two parts: feature extraction using Brownian motion curve (BMC) and design ofa suitable classifier. The discrimination ability of the features has been substantiated by statistical tests. An error back-propagation neural network (BPNN) is used to classify OSF vs. normal. In development of an automated oral cancer diagnostic module, BMC has played an important role in characterizing textural features of the oral images. Fisher's linear discriminant analysis yields 100% sensitivity and 85% specificity, whereas BPNN leads to 92.31% sensitivity and 100% specificity, respectively. In addition to intensity and morphology-based features, textural features are also very important, especially in histopathologic diagnosis of oral cancer. In view of this, a set of textural features are extracted using the BMC for the diagnosis of OSF. Finally, a textural classifier is designed using BPNN, which leads to a diagnostic performance with 96.43% accuracy. (Anal Quant

An adaptive tensor voting algorithm combined with texture spectrum

NASA Astrophysics Data System (ADS)

Wang, Gang; Su, Qing-tang; Lü, Gao-huan; Zhang, Xiao-feng; Liu, Yu-huan; He, An-zhi

2015-01-01

An adaptive tensor voting algorithm combined with texture spectrum is proposed. The image texture spectrum is used to get the adaptive scale parameter of voting field. Then the texture information modifies both the attenuation coefficient and the attenuation field so that we can use this algorithm to create more significant and correct structures in the original image according to the human visual perception. At the same time, the proposed method can improve the edge extraction quality, which includes decreasing the flocculent region efficiently and making image clear. In the experiment for extracting pavement cracks, the original pavement image is processed by the proposed method which is combined with the significant curve feature threshold procedure, and the resulted image displays the faint crack signals submerged in the complicated background efficiently and clearly.

Attaining insight into interactions between hydrologic model parameters and geophysical attributes for national-scale model parameter estimation

NASA Astrophysics Data System (ADS)

Mizukami, N.; Clark, M. P.; Newman, A. J.; Wood, A.; Gutmann, E. D.

2017-12-01

Estimating spatially distributed model parameters is a grand challenge for large domain hydrologic modeling, especially in the context of hydrologic model applications such as streamflow forecasting. Multi-scale Parameter Regionalization (MPR) is a promising technique that accounts for the effects of fine-scale geophysical attributes (e.g., soil texture, land cover, topography, climate) on model parameters and nonlinear scaling effects on model parameters. MPR computes model parameters with transfer functions (TFs) that relate geophysical attributes to model parameters at the native input data resolution and then scales them using scaling functions to the spatial resolution of the model implementation. One of the biggest challenges in the use of MPR is identification of TFs for each model parameter: both functional forms and geophysical predictors. TFs used to estimate the parameters of hydrologic models typically rely on previous studies or were derived in an ad-hoc, heuristic manner, potentially not utilizing maximum information content contained in the geophysical attributes for optimal parameter identification. Thus, it is necessary to first uncover relationships among geophysical attributes, model parameters, and hydrologic processes (i.e., hydrologic signatures) to obtain insight into which and to what extent geophysical attributes are related to model parameters. We perform multivariate statistical analysis on a large-sample catchment data set including various geophysical attributes as well as constrained VIC model parameters at 671 unimpaired basins over the CONUS. We first calibrate VIC model at each catchment to obtain constrained parameter sets. Additionally, parameter sets sampled during the calibration process are used for sensitivity analysis using various hydrologic signatures as objectives to understand the relationships among geophysical attributes, parameters, and hydrologic processes.

Comparison of model microbial allocation parameters in soils of varying texture

NASA Astrophysics Data System (ADS)

Hagerty, S. B.; Slessarev, E.; Schimel, J.

2017-12-01

The soil microbial community decomposes the majority of carbon (C) inputs to the soil. However, not all of this C is respired—rather, a substantial portion of the carbon processed by microbes may remain stored in the soil. The balance between C storage and respiration is controlled by microbial turnover rates and C allocation strategies. These microbial community properties may depend on soil texture, which has the potential to influence both the nature and the fate of microbial necromass and extracellular products. To evaluate the role of texture on microbial turnover and C allocation, we sampled four soils from the University of California's Hastings Reserve that varied in texture (one silt loam, two sandy loam, and on clay soil), but support similar grassland plant communities. We added 14C- glucose to the soil and measured the concentration of the label in the carbon dioxide (CO2), microbial biomass, and extractable C pools over 7 weeks. The labeled biomass turned over the slowest in the clay soil; the concentration of labeled biomass was more than 1.5 times the concentration of the other soils after 8 weeks. The clay soil also had the lowest mineralization rate of the label, and mineralization slowed after two weeks. In contrast, in the sandier soils mineralization rates were higher and did not plateau until 5 weeks into the incubation period. We fit the 14C data to a microbial allocation model and estimated microbial parameters; assimilation efficiency, exudation, and biomass specific respiration and turnover for each soil. We compare these parameters across the soil texture gradient to assess the extent to which models may need to account for variability in microbial C allocation across soils of different texture. Our results suggest that microbial C turns over more slowly in high-clay soils than in sandy soils, and that C lost from microbial biomass is retained at higher rates in high-clay soils. Accounting for these differences in microbial allocation and carbon stabilization could improve model representations of C cycling across a range of soil types.

Consequences of using different soil texture determination methodologies for soil physical quality and unsaturated zone time lag estimates

NASA Astrophysics Data System (ADS)

Fenton, O.; Vero, S.; Ibrahim, T. G.; Murphy, P. N. C.; Sherriff, S. C.; Ó hUallacháin, D.

2015-11-01

Elucidation of when the loss of pollutants, below the rooting zone in agricultural landscapes, affects water quality is important when assessing the efficacy of mitigation measures. Investigation of this inherent time lag (tT) is divided into unsaturated (tu) and saturated (ts) components. The duration of these components relative to each other differs depending on soil characteristics and the landscape position. The present field study focuses on tu estimation in a scenario where the saturated zone is likely to constitute a higher proportion of tT. In such instances, or where only initial breakthrough (IBT) or centre of mass (COM) is of interest, utilisation of site and depth specific "simple" textural class or actual sand-silt-clay percentages to generate soil water characteristic curves with associated soil hydraulic parameters is acceptable. With the same data it is also possible to estimate a soil physical quality (S) parameter for each soil layer which can be used to infer many other physical, chemical and biological quality indicators. In this study, hand texturing in the field was used to determine textural classes of a soil profile. Laboratory methods, including hydrometer, pipette and laser diffraction methods were used to determine actual sand-silt-clay percentages of sections of the same soil profile. Results showed that in terms of S, hand texturing resulted in a lower index value (inferring a degraded soil) than that of pipette, hydrometer and laser equivalents. There was no difference between S index values determined using the pipette, hydrometer and laser diffraction methods. The difference between the three laboratory methods on both the IBT and COM stages of tu were negligible, and in this instance were unlikely to affect either groundwater monitoring decisions, or to be of consequence from a policy perspective. When tu estimates are made over the full depth of the vadose zone, which may extend to several metres, errors resulting from the use of hydraulic parameters generated from hand texture data will be resultantly greater, and may lead to flawed predictions regarding the achievability of water policy targets. For this reason laboratory analysis, regardless of method, should be preferred to simple field assessments.

Effect of equal-channel angular pressing and annealing conditions on the texture, microstructure, and deformability of an MA2-1 alloy

NASA Astrophysics Data System (ADS)

Serebryany, V. N.; Ivanova, T. M.; Kopylov, V. I.; Dobatkin, S. V.; Pozdnyakova, N. N.; Pimenov, V. A.; Savelova, T. I.

2010-07-01

Equal-channel angular pressing (ECAP) of am MA2-1 alloy according to routes A and Bc is used to study the possibility of increasing the low-temperature deformability of the alloy due to grain refinement and a change in its texture. To separate the grain refinement effect from the effect of texture on the deformability of the alloy, samples after ECAP are subjected to recrystallization annealing that provides grain growth to the grain size characteristic of the initial state (IS) of the alloy. Upon ECAP, the average grain size is found to decrease to 2-2.4 μm and the initial sharp axial texture changes substantially (it decomposes into several scattered orientations). The type of orientations and the degree of their scattering depend on the type of ECAP routes. The detected change in the texture is accompanied by an increase in the deformability parameters (normal plastic anisotropy coefficient R, strain-hardening exponent n, relative uniform elongation δu) determined upon tensile tests at 20°C for the states of the alloy formed in the IS-4A-4Bc and IS-4Ao-4BcO sequences. The experimental values of R agree with the values calculated in terms of the Taylor model of plastic deformation in the Bishop-Hill approximation using quantitative texture data in the form of orientation distribution function coefficients with allowance for the activation of prismatic slip, especially for ECAP routes 4Bc and 4BcO. When the simulation results, the Hall-Petch relation, and the generalized Schmid factors are taken into account, a correlation is detected between the deformability parameter, the Hall-Petch coefficient, and the ratio of the critical shear stresses on prismatic and basal planes.

Texture analysis as a predictor of radiation-induced xerostomia in head and neck patients undergoing IMRT.

PubMed

Nardone, Valerio; Tini, Paolo; Nioche, Christophe; Mazzei, Maria Antonietta; Carfagno, Tommaso; Battaglia, Giuseppe; Pastina, Pierpaolo; Grassi, Roberta; Sebaste, Lucio; Pirtoli, Luigi

2018-06-01

Image texture analysis (TA) is a heterogeneity quantifying approach that cannot be appreciated by the naked eye, and early evidence suggests that TA has great potential in the field of oncology. The aim of this study is to evaluate parotid gland texture analysis (TA) combined with formal dosimetry as a factor for predicting severe late xerostomia in patients undergoing radiation therapy for head and neck cancers. We performed a retrospective analysis of patients treated at our Radiation Oncology Unit between January 2010 and December 2015, and selected the patients whose normal dose constraints for the parotid gland (mean dose < 26 Gy for the bilateral gland) could not be satisfied due to the presence of positive nodes close to the parotid glands. The parotid gland that showed the higher V30 was contoured on CT simulation and analysed with LifeX Software©. TA parameters included features of grey-level co-occurrence matrix (GLCM), neighbourhood grey-level dependence matrix (NGLDM), grey-level run length matrix (GLRLM), grey-level zone length matrix (GLZLM), sphericity, and indices from the grey-level histogram. We performed a univariate and multivariate analysis between all the texture parameters, the volume of the gland, the normal dose parameters (V30 and Mean Dose), and the development of severe chronic xerostomia. Seventy-eight patients were included and 25 (31%) developed chronic xerostomia. The TA parameters correlated with severe chronic xerostomia included V30 (OR 5.63), Dmean (OR 5.71), Kurtosis (OR 0.78), GLCM Correlation (OR 1.34), and RLNU (OR 2.12). The multivariate logistic regression showed a significant correlation between V30 (0.001), GLCM correlation (p: 0.026), RLNU (p: 0.011), and chronic xerostomia (p < 0.001, R2:0.664). Xerostomia represents an important cause of morbidity for head and neck cancer survivors after radiation therapy, and in certain cases normal dose constraints cannot be satisfied. Our results seem promising as texture analysis could enhance the normal dose constraints for the prediction of xerostomia.

Classification of endoscopic capsule images by using color wavelet features, higher order statistics and radial basis functions.

PubMed

Lima, C S; Barbosa, D; Ramos, J; Tavares, A; Monteiro, L; Carvalho, L

2008-01-01

This paper presents a system to support medical diagnosis and detection of abnormal lesions by processing capsule endoscopic images. Endoscopic images possess rich information expressed by texture. Texture information can be efficiently extracted from medium scales of the wavelet transform. The set of features proposed in this paper to code textural information is named color wavelet covariance (CWC). CWC coefficients are based on the covariances of second order textural measures, an optimum subset of them is proposed. Third and forth order moments are added to cope with distributions that tend to become non-Gaussian, especially in some pathological cases. The proposed approach is supported by a classifier based on radial basis functions procedure for the characterization of the image regions along the video frames. The whole methodology has been applied on real data containing 6 full endoscopic exams and reached 95% specificity and 93% sensitivity.

Anorexia Nervosa: Analysis of Trabecular Texture with CT

PubMed Central

Tabari, Azadeh; Torriani, Martin; Miller, Karen K.; Klibanski, Anne; Kalra, Mannudeep K.

2017-01-01

Purpose To determine indexes of skeletal integrity by using computed tomographic (CT) trabecular texture analysis of the lumbar spine in patients with anorexia nervosa and normal-weight control subjects and to determine body composition predictors of trabecular texture. Materials and Methods This cross-sectional study was approved by the institutional review board and compliant with HIPAA. Written informed consent was obtained. The study included 30 women with anorexia nervosa (mean age ± standard deviation, 26 years ± 6) and 30 normal-weight age-matched women (control group). All participants underwent low-dose single-section quantitative CT of the L4 vertebral body with use of a calibration phantom. Trabecular texture analysis was performed by using software. Skewness (asymmetry of gray-level pixel distribution), kurtosis (pointiness of pixel distribution), entropy (inhomogeneity of pixel distribution), and mean value of positive pixels (MPP) were assessed. Bone mineral density and abdominal fat and paraspinal muscle areas were quantified with quantitative CT. Women with anorexia nervosa and normal-weight control subjects were compared by using the Student t test. Linear regression analyses were performed to determine associations between trabecular texture and body composition. Results Women with anorexia nervosa had higher skewness and kurtosis, lower MPP (P < .001), and a trend toward lower entropy (P = .07) compared with control subjects. Bone mineral density, abdominal fat area, and paraspinal muscle area were inversely associated with skewness and kurtosis and positively associated with MPP and entropy. Texture parameters, but not bone mineral density, were associated with lowest lifetime weight and duration of amenorrhea in anorexia nervosa. Conclusion Patients with anorexia nervosa had increased skewness and kurtosis and decreased entropy and MPP compared with normal-weight control subjects. These parameters were associated with lowest lifetime weight and duration of amenorrhea, but there were no such associations with bone mineral density. These findings suggest that trabecular texture analysis might contribute information about bone health in anorexia nervosa that is independent of that provided with bone mineral density. © RSNA, 2016 PMID:27797678

Anorexia Nervosa: Analysis of Trabecular Texture with CT.

PubMed

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

2017-04-01

Purpose To determine indexes of skeletal integrity by using computed tomographic (CT) trabecular texture analysis of the lumbar spine in patients with anorexia nervosa and normal-weight control subjects and to determine body composition predictors of trabecular texture. Materials and Methods This cross-sectional study was approved by the institutional review board and compliant with HIPAA. Written informed consent was obtained. The study included 30 women with anorexia nervosa (mean age ± standard deviation, 26 years ± 6) and 30 normal-weight age-matched women (control group). All participants underwent low-dose single-section quantitative CT of the L4 vertebral body with use of a calibration phantom. Trabecular texture analysis was performed by using software. Skewness (asymmetry of gray-level pixel distribution), kurtosis (pointiness of pixel distribution), entropy (inhomogeneity of pixel distribution), and mean value of positive pixels (MPP) were assessed. Bone mineral density and abdominal fat and paraspinal muscle areas were quantified with quantitative CT. Women with anorexia nervosa and normal-weight control subjects were compared by using the Student t test. Linear regression analyses were performed to determine associations between trabecular texture and body composition. Results Women with anorexia nervosa had higher skewness and kurtosis, lower MPP (P < .001), and a trend toward lower entropy (P = .07) compared with control subjects. Bone mineral density, abdominal fat area, and paraspinal muscle area were inversely associated with skewness and kurtosis and positively associated with MPP and entropy. Texture parameters, but not bone mineral density, were associated with lowest lifetime weight and duration of amenorrhea in anorexia nervosa. Conclusion Patients with anorexia nervosa had increased skewness and kurtosis and decreased entropy and MPP compared with normal-weight control subjects. These parameters were associated with lowest lifetime weight and duration of amenorrhea, but there were no such associations with bone mineral density. These findings suggest that trabecular texture analysis might contribute information about bone health in anorexia nervosa that is independent of that provided with bone mineral density. © RSNA, 2016.

Comparison of energy and protein intakes of older people consuming a texture modified diet with a normal hospital diet.

PubMed

Wright, L; Cotter, D; Hickson, M; Frost, G

2005-06-01

There are very few studies looking at the energy and protein requirements of patients requiring texture modified diets. Dysphagia is the main indication for people to be recommended texture-modified diets. Older people post-stroke are the key group in the hospital setting who consume this type of diet. The diets can be of several consistencies ranging from pureed to soft textures. To compare the 24-hour dietary intake of older people consuming a texture modified diet in a clinical setting to older people consuming a normal hospital diet. Weighed food intakes and food record charts were used to quantify the patients' intakes, which were compared to their individual requirements. The oral intake of 55 patients was measured. Twenty-five of the patients surveyed were eating a normal diet and acted as controls for 30 patients who were prescribed a texture-modified diet. The results showed that the texture-modified group had significantly lower intakes of energy (3877 versus 6115 kJ, P < 0.0001) and protein (40 versus 60 g, P < 0.003) compared to consumption of the normal diet. The energy and protein deficit from estimated requirements was significantly greater in the texture-modified group (2549 versus 357 kJ, P < 0.0001; 6 versus 22 g, P = 0.013; respectively). These statistically significant results indicate that older people on texture-modified diets have a lower intake of energy and protein than those consuming a normal hospital diet and it is likely that other nutrients will be inadequate. All patients on texture-modified diets should be assessed by the dietitian for nutritional support. Evidence based strategies for improving overall nutrient intake should be identified.

The effect of addition of selected vegetables on the microbiological, textural and flavour profile properties of yoghurts.

PubMed

Najgebauer-Lejko, Dorota; Tabaszewska, Małgorzata; Grega, Tadeusz

2015-01-01

Vegetables, apart from having high nutritional value, also contain considerable amounts of dietary fibre and other components, which may affect physico-chemical properties of fermented milks, e.g. viscosity, texture, susceptibility to syneresis, flavour profile etc. The present work was established to study the effect of selected vegetables addition on the rheological, textural, microbiological and flavour profile parameters of yoghurts. The vegetable preparations (carrot, pumpkin, broccoli and red sweet pepper) were added (10% w/w) to the processed cow's milk fermented with DVS yoghurt culture. Texture profile analysis, determination of viscosity, susceptibility to syneresis and descriptive flavour evaluation were conducted at the 1st, 7th and 14th day after production. Additionally, microbiological studies were performed for 28 days, at 7-day intervals. The highest apparent viscosity and adhesiveness were obtained for the carrot yoghurt, whereas yoghurt with pumpkin was the least susceptible to syneresis. The other texture parameters were not affected by the addition of vegetables. Broccoli and red sweet pepper flavours were dominating in the fermented milks fortified with these vegetables, whereas carrot and pumpkin flavours were less distinctive. Yoghurt supplemented with red sweet pepper got the highest sensoric acceptability. The number of starter bacteria was not influenced by the vegetable additives, except for pumpkin yoghurt, which contained lower population of lactobacilli. Among all tested vegetables, carrot additive had the greatest potential to improve yoghurt structure, whereas red sweet pepper imparted the most acceptable flavour.

Ti6Al4V laser surface preparation and functionalization using hydroxyapatite for biomedical applications.

PubMed

Faria, D; Abreu, C S; Buciumeanu, M; Dourado, N; Carvalho, O; Silva, F S; Miranda, G

2018-05-01

This work presents a novel texture design for implants surface functionalization, through the creation of line-shaped textures on Ti6Al4V surfaces and subsequent sintering of hydroxyapatite (HAp) powder into the designated locations. HAp-rich locations were designed to avoid HAp detachment during insertion, thus guaranteeing an effective osseointegration. This process starts by creating textured lines using a Nd:YAG laser, filling these lines with HAp powder and sintering HAp using a CO 2 laser. The adhesion of HAp is known to be influenced by HAp sintering parameters, especially laser power and scanning speed and also by the textured lines manufacturing. Different laser parameters combinations were used to assess the sintering and adhesion of HAp to the textured lines. HAp adhesion was assessed by performing high energy ultrasonic cavitation tests and sliding tests mimicking an implant insertion, with Ti6Al4V/HAp specimens sliding against animal bone. The HAp content retained after these tests was measured and results showed that an excellent HAp sintering and adhesion was achieved when using a scan speed of 1 mm/s and laser power between 9 and 9.6 W. It is important to emphasize that results indicated that the HAp bioactivity was maintained when using these conditions, validating this functionalization process for the production of hip prosthesis with improved bioactivity. © 2017 Wiley Periodicals, Inc. J Biomed Mater Res Part B: Appl Biomater, 106B: 1534-1545, 2018. © 2017 Wiley Periodicals, Inc.

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

Topological characterization of antireflective and hydrophobic rough surfaces: are random process theory and fractal modeling applicable?

NASA Astrophysics Data System (ADS)

Borri, Claudia; Paggi, Marco

2015-02-01

The random process theory (RPT) has been widely applied to predict the joint probability distribution functions (PDFs) of asperity heights and curvatures of rough surfaces. A check of the predictions of RPT against the actual statistics of numerically generated random fractal surfaces and of real rough surfaces has been only partially undertaken. The present experimental and numerical study provides a deep critical comparison on this matter, providing some insight into the capabilities and limitations in applying RPT and fractal modeling to antireflective and hydrophobic rough surfaces, two important types of textured surfaces. A multi-resolution experimental campaign using a confocal profilometer with different lenses is carried out and a comprehensive software for the statistical description of rough surfaces is developed. It is found that the topology of the analyzed textured surfaces cannot be fully described according to RPT and fractal modeling. The following complexities emerge: (i) the presence of cut-offs or bi-fractality in the power-law power-spectral density (PSD) functions; (ii) a more pronounced shift of the PSD by changing resolution as compared to what was expected from fractal modeling; (iii) inaccuracy of the RPT in describing the joint PDFs of asperity heights and curvatures of textured surfaces; (iv) lack of resolution-invariance of joint PDFs of textured surfaces in case of special surface treatments, not accounted for by fractal modeling.

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.

SU-F-R-36: Validating Quantitative Radiomic Texture Features for Oncologic PET: A Digital Phantom Study

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

Yang, F; Yang, Y; Young, L

Purpose: Radiomic texture features derived from the oncologic PET have recently been brought under intense investigation within the context of patient stratification and treatment outcome prediction in a variety of cancer types; however, their validity has not yet been examined. This work is aimed to validate radiomic PET texture metrics through the use of realistic simulations in the ground truth setting. Methods: Simulation of FDG-PET was conducted by applying the Zubal phantom as an attenuation map to the SimSET software package that employs Monte Carlo techniques to model the physical process of emission imaging. A total of 15 irregularly-shaped lesionsmore » featuring heterogeneous activity distribution were simulated. For each simulated lesion, 28 texture features in relation to the intensity histograms (GLIH), grey-level co-occurrence matrices (GLCOM), neighborhood difference matrices (GLNDM), and zone size matrices (GLZSM) were evaluated and compared with their respective values extracted from the ground truth activity map. Results: In reference to the values from the ground truth images, texture parameters appearing on the simulated data varied with a range of 0.73–3026.2% for GLIH-based, 0.02–100.1% for GLCOM-based, 1.11–173.8% for GLNDM-based, and 0.35–66.3% for GLZSM-based. For majority of the examined texture metrics (16/28), their values on the simulated data differed significantly from those from the ground truth images (P-value ranges from <0.0001 to 0.04). Features not exhibiting significant difference comprised of GLIH-based standard deviation, GLCO-based energy and entropy, GLND-based coarseness and contrast, and GLZS-based low gray-level zone emphasis, high gray-level zone emphasis, short zone low gray-level emphasis, long zone low gray-level emphasis, long zone high gray-level emphasis, and zone size nonuniformity. Conclusion: The extent to which PET imaging disturbs texture appearance is feature-dependent and could be substantial. It is thus advised that use of PET texture parameters for predictive and prognostic measurements in oncologic setting awaits further systematic and critical evaluation.« less

Effect of Laser Powder Bed Fusion Parameters on the Microstructure and Texture Development in Superelastic Ti-18Zr-14Nb Alloy

NASA Astrophysics Data System (ADS)

Kreitcberg, A.; Brailovski, V.; Sheremetyev, V.; Prokoshkin, S.

2017-12-01

The effect of different laser powder bed fusion (L-PBF) parameters on the phase composition, microstructure, and crystallographic texture of Ti-18Zr-14Nb alloy was studied. Two levels of laser power, scanning speed, and hatching space were used, while the layer thickness was kept constant. The resulting volume energy density was ranged from 20 to 60 J/mm3, and the build rate, from 12 to 36 cm3/h. The manufactured coupons were analyzed by X-ray diffractometry, transmission, and scanning electron microscopy. It was found that the greater influence observed on the microstructure and texture development was caused by the value of laser power, while the lowest, by that of hatching space. Based on the results obtained, the processing optimization strategy aimed at improving the density, superelastic, and fatigue properties of the L-PBF manufactured Ti-18Zr-14Nb alloy was proposed.

High-Speed Friction Stir Welding of AA7075-T6 Sheet: Microstructure, Mechanical Properties, Micro-texture, and Thermal History

NASA Astrophysics Data System (ADS)

Zhang, Jingyi; Upadhyay, Piyush; Hovanski, Yuri; Field, David P.

2018-01-01

Friction stir welding (FSW) is a cost-effective and high-quality joining process for aluminum alloys (especially heat-treatable alloys) that is historically operated at lower joining speeds (up to hundreds of millimeters per minute). In this study, we present a microstructural analysis of friction stir welded AA7075-T6 blanks with high welding speeds up to 3 M/min. Textures, microstructures, mechanical properties, and weld quality are analyzed using TEM, EBSD, metallographic imaging, and Vickers hardness. The higher welding speed results in narrower, stronger heat-affected zones (HAZs) and also higher hardness in the nugget zones. The material flow direction in the nugget zone is found to be leaning towards the welding direction as the welding speed increases. Results are coupled with welding parameters and thermal history to aid in the understanding of the complex material flow and texture gradients within the welds in an effort to optimize welding parameters for high-speed processing.

Factors influencing perceived angular velocity

NASA Technical Reports Server (NTRS)

Kaiser, Mary K.; Calderone, Jack B.

1991-01-01

Angular velocity perception is examined for rotations both in depth and in the image plane and the influence of several object properties on this motion parameter is explored. Two major object properties are considered, namely, texture density which determines the rate of edge transitions for rotations in depth, i.e., the number of texture elements that pass an object's boundary per unit of time, and object size which determines the tangential linear velocities and 2D image velocities of texture elements for a given angular velocity. Results of experiments show that edge-transition rate biased angular velocity estimates only when edges were highly salient. Element velocities had an impact on perceived angular velocity; this bias was associated with 2D image velocity rather than 3D tangential velocity. Despite these biases judgements were most strongly determined by the true angular velocity. Sensitivity to this higher order motion parameter appeared to be good for rotations both in depth (y-axis) and parallel to the line of sight (z-axis).

Multiple optimization of chemical components and texture of purple maize expanded by IVDV treatment using the response surface methodology.

PubMed

Mrad, Rachelle; Debs, Espérance; Maroun, Richard G; Louka, Nicolas

2014-12-15

A new process, Intensification of Vaporization by Decompression to the Vacuum (IVDV), is proposed for texturizing purple maize. It consists in exposing humid kernels to high steam pressure followed by a decompression to the vacuum. Response surface methodology with three operating parameters (initial water content (W), steam pressure (P) and processing time (T)) was used to study the response parameters: Total Anthocyanins Content, Total Polyphenols Content, Free Radical Scavenging Activity, Expansion Ratio, Hardness and Work Done. P was the most important variable, followed by T. Pressure drop helped the release of bound phenolics arriving to their expulsion outside the cell. Combined with convenient T and W, it caused kernels expansion. Multiple optimization of expansion and chemical content showed that IVDV resulted in good texturization of maize while preserving the antioxidant compounds and activity. Optimal conditions were: W=29%, P=5 bar and T=37s. Copyright © 2014 Elsevier Ltd. All rights reserved.

Association between textural and morphological tumor indices on baseline PET-CT and early metabolic response on interim PET-CT in bulky malignant lymphomas.

PubMed

Ben Bouallègue, Fayçal; Tabaa, Yassine Al; Kafrouni, Marilyne; Cartron, Guillaume; Vauchot, Fabien; Mariano-Goulart, Denis

2017-09-01

We investigated whether metabolic, textural, and morphological tumoral indices evaluated on baseline PET-CT were predictive of early metabolic response on interim PET-CT in a cohort of patients with bulky Hodgkin and non-Hodgkin malignant lymphomas. This retrospective study included 57 patients referred for initial PET-CT examination. In-house dedicated software was used to delineate tumor contours using a fixed 30% threshold of SUV max and then to compute tumoral metabolic parameters (SUV max, mean, peak, standard deviation, skewness and kurtosis, metabolic tumoral volume (MTV), total lesion glycolysis, and area under the curve of the cumulative histogram), textural parameters (Moran's and Geary's indices, energy, entropy, contrast, correlation derived from the gray-level co-occurrence matrix, area under the curve of the power spectral density, auto-correlation distance, and granularity), and shape parameters (surface, asphericity, convexity, surfacic extension, and 2D and 3D fractal dimensions). Early metabolic response was assessed on interim PET-CT using the Deauville 5-point scale and patients were ranked according to the Lugano classification as complete or not complete metabolic responders. The impact of the segmentation method (alternate threshold at 41%) and image resolution (Gaussian postsmoothing of 3, 5, and 7 mm) was investigated. The association of the proposed parameters with early response was assessed in univariate and multivariate analyses. Their added predictive value was explored using supervised classification by support vector machines (SVM). We evaluated in leave-one-out cross-validation three SVMs admitting as input features (a) MTV, (b) MTV + histological type, and (c) MTV + histology + relevant texture/shape indices. Features associated with complete metabolic response were low MTV (P = 0.01), low TLG (P = 0.003), high power spectral density AUC (P = 0.007), high surfacic extension (P = 0.006), low 2D fractal dimension (P = 0.007), and low 3D fractal dimension (P = 0.003). The prognostic value of these metrics was optimal with the 30% segmentation threshold and overall was progressively altered with decreasing image resolution. In cross-validation, the SVM accounting for texture and shape achieved the highest predictive value with ROC AUC of 0.82 and 80% accuracy (compared with 0.68 and 61% for MTV, and 0.65 and 68% for MTV + histology). The combination of usual prognostic factors with appropriately chosen textural and shape parameters evaluated on baseline PET-CT improves the prediction of early metabolic response in bulky lymphoma. © 2017 American Association of Physicists in Medicine.

Analysis of microstructures and macrotextures for different apple cultivars based on parenchyma morphology.

PubMed

Hou, Jumin; Sun, Yonghai; Chen, Fangyuan; Yu, Libo; Mao, Qian; Wang, Lu; Guo, Xiaolei; Liu, Chao

2016-04-01

Fuji, Golden Delicious, and Jonagold parenchyma were imaged by confocal laser scanning microscopy to be extracted morphology characteristics, which were used to analyze the relationship with macrotexture of apples tested by penetration and compression. Before analyzing the relationship, the significantly different morphology parameters were reduced in dimensions by principal component analysis and were proved to be availably used for distinguishing the different apple cultivars. For compression results, cell did not absolutely determine the hardness in different apple cultivars, and the pore should also be taken into consideration. With the same size in cell feret diameter, the bigger the pore feret diameter was, the softer the apple became. If no difference existed in pore feret diameter size, the cultivar became harder with a narrower distribution in cell feret diameter. The texture parameters were compared with the roundness parameters in the same or inverse changing trends to explore the relationship. High correlations were found between the texture parameters (energy required in whole penetration (Wt), fracture force (Fp), crispness) and pore solidity (R(2)  > 0.924, P < 0.001). Compactness of parenchyma played an important role in fruit texture. This research could provide the comprehension about relationship between microstructure and macrotexture of apple cultivars and morphological values for modeling apple parenchyma, contributing to numerical simulation for constitutive relation of fruit. © 2016 Wiley Periodicals, Inc.

Anterior dental microwear textures show habitat-driven variability in Neandertal behavior.

PubMed

Krueger, Kristin L; Ungar, Peter S; Guatelli-Steinberg, Debbie; Hublin, Jean-Jacques; Pérez-Pérez, Alejandro; Trinkaus, Erik; Willman, John C

2017-04-01

The causes of Neandertal anterior tooth wear patterns, including labial rounding, labial scratches, and differential anterior-posterior wear, have been debated for decades. The most common explanation is the "stuff-and-cut" hypothesis, which describes Neandertals clamping down on a piece of meat and slicing a portion close to their lips. "Stuff-and-cut" has been accepted as a general aspect of Neandertal behavior without fully assessing its variability. This study analyzes anterior dental microwear textures across habitats, locations, and time intervals to discern possible variation in Neandertal anterior tooth-use behavior. Forty-five Neandertals from 24 sites were analyzed, represented by high-resolution replicas of permanent anterior teeth. The labial surface was scanned for antemortem microwear using a white-light confocal profiler. The resultant 3D-point clouds, representing 204 × 276 μm for each specimen, were uploaded into SSFA software packages for texture characterization. Statistical analyses, including MANOVAs, ANOVAs, and pairwise comparisons, were completed on ranked microwear data. Neandertal descriptive statistics were also compared to 10 bioarchaeological samples of known or inferred dietary and behavioral regimes. The Neandertal sample varied significantly by habitat, suggesting this factor was a principal driving force for differences in Neandertal anterior tooth-use behaviors. The Neandertals from open habitats showed significantly lower anisotropy and higher textural fill volume than those inhabiting more closed, forested environments. The texture signature from the open-habitat Neandertals was most similar to that of the Ipiutak and Nunavut, who used their anterior teeth for intense clamping and grasping behaviors related to hide preparation. Those in more closed habitats were most similar to the Arikara, who did not participate in non-dietary behaviors. These Neandertal individuals had a broad range of texture values consistent with non-dietary and dietary behaviors, suggesting they varied more in anterior tooth-use behaviors and exploited a wider variety of plant and animal resources than did those from open habitats. Copyright © 2017 Elsevier Ltd. All rights reserved.

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.

Atomic Oxygen Erosion Yield Dependence Upon Texture Development in Polymers

NASA Technical Reports Server (NTRS)

Banks, Bruce A.; Loftus, Ryan J.; Miller, Sharon K.

2016-01-01

The atomic oxygen erosion yield (volume of a polymer that is lost due to oxidation per incident atom) of polymers is typically assumed to be reasonably constant with increasing fluence. However polymers containing ash or inorganic pigments, tend to have erosion yields that decrease with fluence due to an increasing presence of protective particles on the polymer surface. This paper investigates two additional possible causes for erosion yields of polymers that are dependent upon atomic oxygen. These are the development of surface texture which can cause the erosion yield to change with fluence due to changes in the aspect ratio of the surface texture that develops and polymer specific atomic oxygen interaction parameters. The surface texture development under directed hyperthermal attack produces higher aspect ratio surface texture than isotropic thermal energy atomic oxygen attack. The fluence dependence of erosion yields is documented for low Kapton H (DuPont, Wilmington, DE) effective fluences for a variety of polymers under directed hyperthermal and isotropic thermal energy attack.

Influence of Laser Shock Texturing on W9 Steel Surface Friction Property

NASA Astrophysics Data System (ADS)

Fan, Yujie; Cui, Pengfei; Zhou, Jianzhong; Dai, Yibin; Guo, Erbin; Tang, Deye

2017-09-01

To improve surface friction property of high speed steel, micro-dent arrays on W9Mo3Cr4V surface were produced by laser shock processing. Friction test was conducted on smooth surface and texturing surface and effect of surface texturing density on friction property was studied. The results show that, under the same condition, friction coefficient of textured surface is lower than smooth surface with dent area density less than 6%, wear mass loss, width and depth of wear scar are smaller; Wear resistance of the surface is the best and the friction coefficient is the smallest when dent area density is 2.2%; Friction coefficient, wear mass loss, width and depth of wear scar increase correspondingly as density of dent area increases when dent area density is more than 2.2%. Abrasive wear and adhesive wear, oxidative wear appear in the wear process. Reasonable control of geometric parameters of surface texturing induced by laser shock processing is helpful to improve friction performance.

The formation of cosmic structure in a texture-seeded cold dark matter cosmogony

NASA Technical Reports Server (NTRS)

Gooding, Andrew K.; Park, Changbom; Spergel, David N.; Turok, Neil; Gott, Richard, III

1992-01-01

The growth of density fluctuations induced by global texture in an Omega = 1 cold dark matter (CDM) cosmogony is calculated. The resulting power spectra are in good agreement with each other, with more power on large scales than in the standard inflation plus CDM model. Calculation of related statistics (two-point correlation functions, mass variances, cosmic Mach number) indicates that the texture plus CDM model compares more favorably than standard CDM with observations of large-scale structure. Texture produces coherent velocity fields on large scales, as observed. Excessive small-scale velocity dispersions, and voids less empty than those observed may be remedied by including baryonic physics. The topology of the cosmic structure agrees well with observation. The non-Gaussian texture induced density fluctuations lead to earlier nonlinear object formation than in Gaussian models and may also be more compatible with recent evidence that the galaxy density field is non-Gaussian on large scales. On smaller scales the density field is strongly non-Gaussian, but this appears to be primarily due to nonlinear gravitational clustering. The velocity field on smaller scales is surprisingly Gaussian.

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

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

Masotti, Matteo; Lanconelli, Nico; Campanini, Renato

In this work, gray-scale invariant ranklet texture features are proposed for false positive reduction (FPR) in computer-aided detection (CAD) of breast masses. Two main considerations are at the basis of this proposal. First, false positive (FP) marks surviving our previous CAD system seem to be characterized by specific texture properties that can be used to discriminate them from masses. Second, our previous CAD system achieves invariance to linear/nonlinear monotonic gray-scale transformations by encoding regions of interest into ranklet images through the ranklet transform, an image transformation similar to the wavelet transform, yet dealing with pixels' ranks rather than with theirmore » gray-scale values. Therefore, the new FPR approach proposed herein defines a set of texture features which are calculated directly from the ranklet images corresponding to the regions of interest surviving our previous CAD system, hence, ranklet texture features; then, a support vector machine (SVM) classifier is used for discrimination. As a result of this approach, texture-based information is used to discriminate FP marks surviving our previous CAD system; at the same time, invariance to linear/nonlinear monotonic gray-scale transformations of the new CAD system is guaranteed, as ranklet texture features are calculated from ranklet images that have this property themselves by construction. To emphasize the gray-scale invariance of both the previous and new CAD systems, training and testing are carried out without any in-between parameters' adjustment on mammograms having different gray-scale dynamics; in particular, training is carried out on analog digitized mammograms taken from a publicly available digital database, whereas testing is performed on full-field digital mammograms taken from an in-house database. Free-response receiver operating characteristic (FROC) curve analysis of the two CAD systems demonstrates that the new approach achieves a higher reduction of FP marks when compared to the previous one. Specifically, at 60%, 65%, and 70% per-mammogram sensitivity, the new CAD system achieves 0.50, 0.68, and 0.92 FP marks per mammogram, whereas at 70%, 75%, and 80% per-case sensitivity it achieves 0.37, 0.48, and 0.71 FP marks per mammogram, respectively. Conversely, at the same sensitivities, the previous CAD system reached 0.71, 0.87, and 1.15 FP marks per mammogram, and 0.57, 0.73, and 0.92 FPs per mammogram. Also, statistical significance of the difference between the two per-mammogram and per-case FROC curves is demonstrated by the p-value<0.001 returned by jackknife FROC analysis performed on the two CAD systems.« less

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.

How visual attention is modified by disparities and textures changes?

NASA Astrophysics Data System (ADS)

Khaustova, Dar'ya; Fournier, Jérome; Wyckens, Emmanuel; Le Meur, Olivier

2013-03-01

The 3D image/video quality of experience is a multidimensional concept that depends on 2D image quality, depth quantity and visual comfort. The relationship between these parameters is not yet clearly defined. From this perspective, we aim to understand how texture complexity, depth quantity and visual comfort influence the way people observe 3D content in comparison with 2D. Six scenes with different structural parameters were generated using Blender software. For these six scenes, the following parameters were modified: texture complexity and the amount of depth changing the camera baseline and the convergence distance at the shooting side. Our study was conducted using an eye-tracker and a 3DTV display. During the eye-tracking experiment, each observer freely examined images with different depth levels and texture complexities. To avoid memory bias, we ensured that each observer had only seen scene content once. Collected fixation data were used to build saliency maps and to analyze differences between 2D and 3D conditions. Our results show that the introduction of disparity shortened saccade length; however fixation durations remained unaffected. An analysis of the saliency maps did not reveal any differences between 2D and 3D conditions for the viewing duration of 20 s. When the whole period was divided into smaller intervals, we found that for the first 4 s the introduced disparity was conducive to the section of saliency regions. However, this contribution is quite minimal if the correlation between saliency maps is analyzed. Nevertheless, we did not find that discomfort (comfort) had any influence on visual attention. We believe that existing metrics and methods are depth insensitive and do not reveal such differences. Based on the analysis of heat maps and paired t-tests of inter-observer visual congruency values we deduced that the selected areas of interest depend on texture complexities.

USCS and the USDA Soil Classification System: Development of a Mapping Scheme

DTIC Science & Technology

2015-03-01

important to human daily living. A variety of disciplines (geology, agriculture, engineering, etc.) require a sys- tematic categorization of soil, detailing...it is often important to also con- sider parameters that indicate soil strength. Two important properties used for engineering-related problems are...that many textural clas- sification systems were developed to meet specifics needs. In agriculture, textural classification is used to determine crop

Fuzzy recurrence plots

NASA Astrophysics Data System (ADS)

Pham, T. D.

2016-12-01

Recurrence plots display binary texture of time series from dynamical systems with single dots and line structures. Using fuzzy recurrence plots, recurrences of the phase-space states can be visualized as grayscale texture, which is more informative for pattern analysis. The proposed method replaces the crucial similarity threshold required by symmetrical recurrence plots with the number of cluster centers, where the estimate of the latter parameter is less critical than the estimate of the former.

Effect of magnetron sputtering parameters and stress state of W film precursors on WSe2 layer texture by rapid selenization.

PubMed

Li, Hongchao; Gao, Di; Xie, Senlin; Zou, Jianpeng

2016-11-04

Tungsten diselenide (WSe 2 ) film was obtained by rapid selenization of magnetron sputtered tungsten (W) film. To prevent WSe 2 film peeling off from the substrate during selenization, the W film was designed with a double-layer structure. The first layer was deposited at a high sputtering-gas pressure to form a loose structure, which can act as a buffer layer to release stresses caused by WSe 2 growth. The second layer was deposited naturally on the first layer to react with selenium vapour in the next step. The effect of the W film deposition parameters(such as sputtering time, sputtering-gas pressure and substrate bias voltage)on the texture and surface morphology of the WSe 2 film was studied. Shortening the sputtering time, increasing the sputtering-gas pressure or decreasing the substrate bias voltage can help synthesize WSe 2 films with more platelets embedded vertically in the matrix. The stress state of the W film influences the WSe 2 film texture. Based on the stress state of the W film, a model for growth of the WSe 2 films with different textures was proposed. The insertion direction of the van der Waals gap is a key factor for the anisotropic formation of WSe 2 film.

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

PubMed

Szakonyi, G; Zelkó, R

2013-05-20

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

Application of mid-infrared spectroscopy to the prediction of maturity and sensory texture attributes of cheddar cheese.

PubMed

Fagan, C C; O'Donnell, C P; O'Callaghan, D J; Downey, G; Sheehan, E M; Delahunty, C M; Everard, C; Guinee, T P; Howard, V

2007-04-01

The objective of this study was to determine the potential of mid-infrared spectroscopy in conjunction with partial least squares (PLS) regression to predict various quality parameters in cheddar cheese. Cheddar cheeses (n= 24) were manufactured and stored at 8 degrees C for 12 mo. Mid-infrared spectra (640 to 4000/cm) were recorded after 4, 6, 9, and 12 mo storage. At 4, 6, and 9 mo, the water-soluble nitrogen (WSN) content of the samples was determined and the samples were also evaluated for 11 sensory texture attributes using descriptive sensory analysis. The mid-infrared spectra were subjected to a number of pretreatments, and predictive models were developed for all parameters. Age was predicted using scatter-corrected, 1st derivative spectra with a root mean square error of cross-validation (RMSECV) of 1 mo, while WSN was predicted using 1st derivative spectra (RMSECV = 2.6%). The sensory texture attributes most successfully predicted were rubbery, crumbly, chewy, and massforming. These attributes were modeled using 2nd derivative spectra and had corresponding RMSECV values in the range of 2.5 to 4.2 on a scale of 0 to 100. It was concluded that mid-infrared spectroscopy has the potential to predict age, WSN, and several sensory texture attributes of cheddar cheese.

Effect of magnetron sputtering parameters and stress state of W film precursors on WSe2 layer texture by rapid selenization

PubMed Central

Li, Hongchao; Gao, Di; Xie, Senlin; Zou, Jianpeng

2016-01-01

Tungsten diselenide (WSe2) film was obtained by rapid selenization of magnetron sputtered tungsten (W) film. To prevent WSe2 film peeling off from the substrate during selenization, the W film was designed with a double-layer structure. The first layer was deposited at a high sputtering-gas pressure to form a loose structure, which can act as a buffer layer to release stresses caused by WSe2 growth. The second layer was deposited naturally on the first layer to react with selenium vapour in the next step. The effect of the W film deposition parameters(such as sputtering time, sputtering-gas pressure and substrate bias voltage)on the texture and surface morphology of the WSe2 film was studied. Shortening the sputtering time, increasing the sputtering-gas pressure or decreasing the substrate bias voltage can help synthesize WSe2 films with more platelets embedded vertically in the matrix. The stress state of the W film influences the WSe2 film texture. Based on the stress state of the W film, a model for growth of the WSe2 films with different textures was proposed. The insertion direction of the van der Waals gap is a key factor for the anisotropic formation of WSe2 film. PMID:27812031

An overview of impact of subsurface drainage project studies on salinity management in developing countries

NASA Astrophysics Data System (ADS)

Tiwari, Priyanka; Goel, Arun

2017-05-01

Subsurface drainage has been used for more than a century to keep water table at a desired level of salinity and waterlogging control. This paper has been focused on the impact assessment of pilot studies in India and some other countries from 1969 to 2014 . This review article may prove quite useful in deciding the installation of subsurface drainage project depending on main design parameters, such as drain depth and drain spacing, installation area and type of used outlet. A number of pilot studies have been taken up in past to solve the problems of soil salinity and waterlogging in India. The general guidelines that arise on the behalf of this review paper are to adapt drain depth >1.2 m and spacing depending on soil texture classification, i.e., 100-150 m for light-textured soils, 50-100 m for medium-textured soils and 30-50 m heavy-textured soils, for better result obtained from the problem areas in Indian soil and climatic conditions. An attempt has been made in the manner of literature survey to highlight the salient features of these studies, and it is hopeful to go a long way in selecting design parameters for subsurface drainage problems in the future with similar soil, water table and climatic conditions.

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

PubMed

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

2016-01-01

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

Wireless majorana fermions: from magnetic tunability to braiding (Conference Presentation)

NASA Astrophysics Data System (ADS)

Fatin, Geoffrey L.; Matos-Abiague, Alex; Scharf, Benedikt; Zutic, Igor

2016-10-01

In condensed-matter systems Majorana bound states (MBSs) are emergent quasiparticles with non-Abelian statistics and particle-antiparticle symmetry. While realizing the non-Abelian braiding statistics under exchange would provide both an ultimate proof for MBS existence and the key element for fault-tolerant topological quantum computing, even theoretical schemes imply a significant complexity to implement such braiding. Frequently examined 1D superconductor/semiconductor wires provide a prototypical example of how to produce MBSs, however braiding statistics are ill-defined in 1D and complex wire networks must be used. By placing an array of magnetic tunnel junctions (MTJs) above a 2D electron gas formed in a semiconductor quantum well grown on the surface of an s-wave superconductor, we have predicted the existence of highly tunable zero-energy MBSs and have proposed a novel scheme by which MBSs could be exchanged [1]. This scheme may then be used to demonstrate the states' non-Abelian statistics through braiding. The underlying magnetic textures produced by MTJ array provides a pseudo-helical texture which allows for highly-controllable topological phase transitions. By defining a local condition for topological nontriviality which takes into account the local rotation of magnetic texture, effective wire geometries support MBS formation and permit their controlled movement in 2D by altering the shape and orientation of such wires. This scheme then overcomes the requirement for a network of physical wires in order to exchange MBSs, allowing easier manipulation of such states. [1] G. L. Fatin, A. Matos-Abiague, B. Scharf, and I. Zutic, arXiv:1510.08182, preprint.

Compaction behavior and deformation mechanism of directly compressible textured mannitol in a rotary tablet press simulator.

PubMed

Tarlier, Nicolas; Soulairol, Ian; Bataille, Bernard; Baylac, Gilles; Ravel, Patrice; Nofrerias, Isaac; Lefèvre, Philippe; Sharkawi, Tahmer

2015-11-10

Textured mannitol powder is widely used as a pharmaceutical excipient for tablet compaction. In order to choose the right tableting parameters, it is necessary to understand its mechanical behavior during deformation under industrial tableting conditions. The aim of this study was to evaluate the mechanical behavior during deformation of a textured mannitol using a rotary tablet press simulator. Mean yield pressure (Py) obtained by Heckel modeling, Walker coefficients (W) and Stress Rate Sensitivity (SRS) were compared to reference excipients, known for either their plastic (microcrystalline cellulose) or fragmentary (lactose and dibasic calcium phosphate) deformation behavior. Py, W and SRS values showed that the studied textured mannitol has a fragmentary deformation mechanism. Furthermore, this mechanical behavior was not sensitive to lubrication, which is characteristic of fragmentary excipients. Copyright © 2015 Elsevier B.V. All rights reserved.

Evaporation dynamics of completely wetting drops on geometrically textured surfaces

NASA Astrophysics Data System (ADS)

Mekhitarian, Loucine; Sobac, Benjamin; Dehaeck, Sam; Haut, Benoît; Colinet, Pierre

2017-10-01

This study deals with the evaporation dynamics of completely wetting and highly volatile drops deposited on geometrically textured but chemically homogeneous surfaces. The texturation consists in a cylindrical pillars array with a square pitch. The triple line dynamics and the drop shape are characterized by an interferometric method. A parametric study is realized by varying the radius and the height of the pillars (at fixed interpillar distance), allowing to distinguish three types of dynamics: i) an evaporation-dominated regime with a receding triple line; ii) a spreading-dominated regime with an initially advancing triple line; iii) a cross-over region with strong pinning effects. The overall picture is in qualitative agreement with a mathematical model showing that the selected regime mostly depends on the value of a dimensionless parameter comparing the time scales for evaporation and spreading into the substrate texture.

Operational Mapping of Soil Moisture Using Synthetic Aperture Radar Data: Application to the Touch Basin (France)

PubMed Central

Baghdadi, Nicolas; Aubert, Maelle; Cerdan, Olivier; Franchistéguy, Laurent; Viel, Christian; Martin, Eric; Zribi, Mehrez; Desprats, Jean François

2007-01-01

Soil moisture is a key parameter in different environmental applications, such as hydrology and natural risk assessment. In this paper, surface soil moisture mapping was carried out over a basin in France using satellite synthetic aperture radar (SAR) images acquired in 2006 and 2007 by C-band (5.3 GHz) sensors. The comparison between soil moisture estimated from SAR data and in situ measurements shows good agreement, with a mapping accuracy better than 3%. This result shows that the monitoring of soil moisture from SAR images is possible in operational phase. Moreover, moistures simulated by the operational Météo-France ISBA soil-vegetation-atmosphere transfer model in the SIM-Safran-ISBA-Modcou chain were compared to radar moisture estimates to validate its pertinence. The difference between ISBA simulations and radar estimates fluctuates between 0.4 and 10% (RMSE). The comparison between ISBA and gravimetric measurements of the 12 March 2007 shows a RMSE of about 6%. Generally, these results are very encouraging. Results show also that the soil moisture estimated from SAR images is not correlated with the textural units defined in the European Soil Geographical Database (SGDBE) at 1:1000000 scale. However, dependence was observed between texture maps and ISBA moisture. This dependence is induced by the use of the texture map as an input parameter in the ISBA model. Even if this parameter is very important for soil moisture estimations, radar results shown that the textural map scale at 1:1000000 is not appropriate to differentiate moistures zones. PMID:28903238

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.

Theoretical Analysis of Spacing Parameters of Anisotropic 3D Surface Roughness

NASA Astrophysics Data System (ADS)

Rudzitis, J.; Bulaha, N.; Lungevics, J.; Linins, O.; Berzins, K.

2017-04-01

The authors of the research have analysed spacing parameters of anisotropic 3D surface roughness crosswise to machining (friction) traces RSm1 and lengthwise to machining (friction) traces RSm2. The main issue arises from the RSm2 values being limited by values of sampling length l in the measuring devices; however, on many occasions RSm2 values can exceed l values. Therefore, the mean spacing values of profile irregularities in the longitudinal direction in many cases are not reliable and they should be determined by another method. Theoretically, it is proved that anisotropic surface roughness anisotropy coefficient c=RSm1/RSm2 equals texture aspect ratio Str, which is determined by surface texture standard EN ISO 25178-2. This allows using parameter Str to determine mean spacing of profile irregularities and estimate roughness anisotropy.

Perceptual adaptation in the use of night vision goggles

NASA Technical Reports Server (NTRS)

Durgin, Frank H.; Proffitt, Dennis R.

1992-01-01

The image intensification (I sup 2) systems studied for this report were the biocular AN/PVS-7(NVG) and the binocular AN/AVS-6(ANVIS). Both are quite impressive for purposes of revealing the structure of the environment in a fairly straightforward way in extremely low-light conditions. But these systems represent an unusual viewing medium. The perceptual information available through I sup 2 systems is different in a variety of ways from the typical input of everyday vision, and extensive training and practice is required for optimal use. Using this sort of system involves a kind of perceptual skill learning, but is may also involve visual adaptations that are not simply an extension of normal vision. For example, the visual noise evident in the goggles in very low-light conditions results in unusual statistical properties in visual input. Because we had recently discovered a strong and enduring aftereffect of perceived texture density which seemed to be sensitive to precisely the sorts of statistical distortions introduced by I sup 2 systems, it occurred to use that visual noise of this sort might be a very adapting stimulus for texture density and produce an aftereffect that extended into normal vision once the goggles were removed. We have not found any experimental evidence that I sup 2 systems produce texture density aftereffects. The nature of the texture density aftereffect is briefly explained, followed by an accounting of our studies of I sup 2 systems and our most recent work on the texture density aftereffect. A test for spatial frequency adaptation after exposure to NVG's is also reported, as is a study of perceived depth from motion (motion parallax) while wearing the biocular goggles. We conclude with a summary of our findings.

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.

Characterization of difference of Gaussian filters in the detection of mammographic regions

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

Catarious, David M. Jr.; Baydush, Alan H.; Floyd, Carey E. Jr.

2006-11-15

In this article, we present a characterization of the effect of difference of Gaussians (DoG) filters in the detection of mammographic regions. DoG filters have been used previously in mammographic mass computer-aided detection (CAD) systems. As DoG filters are constructed from the subtraction of two bivariate Gaussian distributions, they require the specification of three parameters: the size of the filter template and the standard deviations of the constituent Gaussians. The influence of these three parameters in the detection of mammographic masses has not been characterized. In this work, we aim to determine how the parameters affect (1) the physical descriptorsmore » of the detected regions (2) the true and false positive rates, and (3) the classification performance of the individual descriptors. To this end, 30 DoG filters are created from the combination of three template sizes and four values for each of the Gaussians' standard deviations. The filters are used to detect regions in a study database of 181 craniocaudal-view mammograms extracted from the Digital Database for Screening Mammography. To describe the physical characteristics of the identified regions, morphological and textural features are extracted from each of the detected regions. Differences in the mean values of the features caused by altering the DoG parameters are examined through statistical and empirical comparisons. The parameters' effects on the true and false positive rate are determined by examining the mean malignant sensitivities and false positives per image (FPpI). Finally, the effect on the classification performance is described by examining the variation in FPpI at the point where 81% of the malignant masses in the study database are detected. Overall, the findings of the study indicate that increasing the standard deviations of the Gaussians used to construct a DoG filter results in a dramatic decrease in the number of regions identified at the expense of missing a small number of malignancies. The sharp reduction in the number of identified regions allowed the identification of textural differences between large and small mammographic regions. We find that the classification performances of the features that achieve the lowest average FPpI are influenced by all three of the parameters.« less

Characterization of coronary plaque regions in intravascular ultrasound images using a hybrid ensemble classifier.

PubMed

Hwang, Yoo Na; Lee, Ju Hwan; Kim, Ga Young; Shin, Eun Seok; Kim, Sung Min

2018-01-01

The purpose of this study was to propose a hybrid ensemble classifier to characterize coronary plaque regions in intravascular ultrasound (IVUS) images. Pixels were allocated to one of four tissues (fibrous tissue (FT), fibro-fatty tissue (FFT), necrotic core (NC), and dense calcium (DC)) through processes of border segmentation, feature extraction, feature selection, and classification. Grayscale IVUS images and their corresponding virtual histology images were acquired from 11 patients with known or suspected coronary artery disease using 20 MHz catheter. A total of 102 hybrid textural features including first order statistics (FOS), gray level co-occurrence matrix (GLCM), extended gray level run-length matrix (GLRLM), Laws, local binary pattern (LBP), intensity, and discrete wavelet features (DWF) were extracted from IVUS images. To select optimal feature sets, genetic algorithm was implemented. A hybrid ensemble classifier based on histogram and texture information was then used for plaque characterization in this study. The optimal feature set was used as input of this ensemble classifier. After tissue characterization, parameters including sensitivity, specificity, and accuracy were calculated to validate the proposed approach. A ten-fold cross validation approach was used to determine the statistical significance of the proposed method. Our experimental results showed that the proposed method had reliable performance for tissue characterization in IVUS images. The hybrid ensemble classification method outperformed other existing methods by achieving characterization accuracy of 81% for FFT and 75% for NC. In addition, this study showed that Laws features (SSV and SAV) were key indicators for coronary tissue characterization. The proposed method had high clinical applicability for image-based tissue characterization. Copyright © 2017 Elsevier B.V. All rights reserved.

Sensory and rapid instrumental methods as a combined tool for quality control of cooked ham.

PubMed

Barbieri, Sara; Soglia, Francesca; Palagano, Rosa; Tesini, Federica; Bendini, Alessandra; Petracci, Massimiliano; Cavani, Claudio; Gallina Toschi, Tullia

2016-11-01

In this preliminary investigation, different commercial categories of Italian cooked pork hams have been characterized using an integrated approach based on both sensory and fast instrumental measurements. For these purposes, Italian products belonging to different categories (cooked ham, "selected" cooked ham and "high quality" cooked ham) were evaluated by sensory descriptive analysis and by the application of rapid tools such as image analysis by an "electronic eye" and texture analyzer. The panel of trained assessors identified and evaluated 10 sensory descriptors able to define the quality of the products. Statistical analysis highlighted that sensory characteristics related to appearance and texture were the most significant in discriminating samples belonged to the highest (high quality cooked hams) and the lowest (cooked hams) quality of the product whereas the selected cooked hams, showed intermediate characteristics. In particular, high quality samples were characterized, above all, by the highest intensity of pink intensity, typical appearance and cohesiveness, and, at the same time, by the lowest intensity of juiciness; standard cooked ham samples showed the lowest intensity of all visual attributes and the highest value of juiciness, whereas the intermediate category (selected cooked ham) was not discriminated from the other. Also physical-rheological parameters measured by electronic eye and texture analyzer were effective in classifying samples. In particular, the PLS model built with data obtained from the electronic eye showed a satisfactory performance in terms of prediction of the pink intensity and presence of fat attributes evaluated during the sensory visual phase. This study can be considered a first application of this combined approach that could represent a suitable and fast method to verify if the meat product purchased by consumer match its description in terms of compliance with the claimed quality.

Self-Affinity and Lacunarity of Chromatin Texture in Benign and Malignant Breast Epithelial Cell Nuclei

NASA Astrophysics Data System (ADS)

Einstein, Andrew J.; Wu, Hai-Shan; Gil, Joan

1998-01-01

Methods are presented for characterizing the self-affinity and lacunarity of arbitrarily shaped images. Chromatin appearance in breast epithelial cell nuclei is shown to be statistically self-affine. Spectral and Minkowski dimensions are lesser in nuclei of malignant cases than in nuclei of benign cases, and lacunarity further quantifies morphologic differences such as chromatin clumping and nucleoli. Fractal texture features are used as the basis for an accurate cytologic diagnosis of breast cancer.

Manicouagan impact melt, Quebec. I - Stratigraphy, petrology, and chemistry

NASA Technical Reports Server (NTRS)

Floran, R. J.; Grieve, R. A. F.; Dence, M. R.; Phinney, W. C.; Warner, J. L.; Blanchard, D. P.; Simonds, C. H.

1978-01-01

A sheet of clast-laden impact melt 230 m thick and 55 km in diameter forms an annular plateau surrounding an uplift of shocked anorthosite within the moderately eroded Manicouagan structure. Three gradational units of the melt sheet are characterized with respect to grain size, inclusions, texture, and mineralogy. The melt rocks as a group are chemically homogeneous with a bulk composition similar to that of latite and with no statistically significant regional chemical variations. The melt is not completely chemically homogeneous as a local mafic variant represented by two samples with poikilitic texture was found. These poikilitic rocks texturally resemble some Apollo 17 impact melt rocks and are inferred to have had a similar origin and thermal history.

Intratumoral heterogeneity characterized by pretreatment PET in non-small cell lung cancer patients predicts progression-free survival on EGFR tyrosine kinase inhibitor

PubMed Central

Paeng, Jin Chul; Keam, Bhumsuk; Kim, Tae Min; Kim, Dong-Wan; Heo, Dae Seog

2018-01-01

Intratumoral heterogeneity has been suggested to be an important resistance mechanism leading to treatment failure. We hypothesized that radiologic images could be an alternative method for identification of tumor heterogeneity. We tested heterogeneity textural parameters on pretreatment FDG-PET/CT in order to assess the predictive value of target therapy. Recurred or metastatic non-small cell lung cancer (NSCLC) subjects with an activating EGFR mutation treated with either gefitinib or erlotinib were reviewed. An exploratory data set (n = 161) and a validation data set (n = 21) were evaluated, and eight parameters were selected for survival analysis. The optimal cutoff value was determined by the recursive partitioning method, and the predictive value was calculated using Harrell’s C-index. Univariate analysis revealed that all eight parameters showed an increased hazard ratio (HR) for progression-free survival (PFS). The highest HR was 6.41 (P<0.01) with co-occurrence (Co) entropy. Increased risk remained present after adjusting for initial stage, performance status (PS), and metabolic volume (MV) (aHR: 4.86, P<0.01). Textural parameters were found to have an incremental predictive value of early EGFR tyrosine kinase inhibitor (TKI) failure compared to that of the base model of the stage and PS (C-index 0.596 vs. 0.662, P = 0.02, by Co entropy). Heterogeneity textural parameters acquired from pretreatment FDG-PET/CT are highly predictive factors for PFS of EGFR TKI in EGFR-mutated NSCLC patients. These parameters are easily applicable to the identification of a subpopulation at increased risk of early EGFR TKI failure. Correlation to genomic alteration should be determined in future studies. PMID:29385152

Parenchymal texture analysis in digital mammography: robust texture feature identification and equivalence across devices.

PubMed

Keller, Brad M; Oustimov, Andrew; Wang, Yan; Chen, Jinbo; Acciavatti, Raymond J; Zheng, Yuanjie; Ray, Shonket; Gee, James C; Maidment, Andrew D A; Kontos, Despina

2015-04-01

An analytical framework is presented for evaluating the equivalence of parenchymal texture features across different full-field digital mammography (FFDM) systems using a physical breast phantom. Phantom images (FOR PROCESSING) are acquired from three FFDM systems using their automated exposure control setting. A panel of texture features, including gray-level histogram, co-occurrence, run length, and structural descriptors, are extracted. To identify features that are robust across imaging systems, a series of equivalence tests are performed on the feature distributions, in which the extent of their intersystem variation is compared to their intrasystem variation via the Hodges-Lehmann test statistic. Overall, histogram and structural features tend to be most robust across all systems, and certain features, such as edge enhancement, tend to be more robust to intergenerational differences between detectors of a single vendor than to intervendor differences. Texture features extracted from larger regions of interest (i.e., [Formula: see text]) and with a larger offset length (i.e., [Formula: see text]), when applicable, also appear to be more robust across imaging systems. This framework and observations from our experiments may benefit applications utilizing mammographic texture analysis on images acquired in multivendor settings, such as in multicenter studies of computer-aided detection and breast cancer risk assessment.

Perception of stochastic envelopes by normal-hearing and cochlear-implant listeners

PubMed Central

Gomersall, Philip A.; Turner, Richard E.; Baguley, David M.; Deeks, John M.; Gockel, Hedwig E.; Carlyon, Robert P.

2016-01-01

We assessed auditory sensitivity to three classes of temporal-envelope statistics (modulation depth, modulation rate, and comodulation) that are important for the perception of ‘sound textures’. The textures were generated by a probabilistic model that prescribes the temporal statistics of a selected number of modulation envelopes, superimposed onto noise carriers. Discrimination thresholds were measured for normal-hearing (NH) listeners and users of a MED-EL pulsar cochlear implant (CI), for separate manipulations of the average rate and modulation depth of the envelope in each frequency band of the stimulus, and of the co-modulation between bands. Normal-hearing (NH) listeners' discrimination of envelope rate was similar for baseline modulation rates of 5 and 34 Hz, and much poorer than previously reported for sinusoidally amplitude-modulated sounds. In contrast, discrimination of model parameters that controlled modulation depth was poorer at the lower baseline rate, consistent with the idea that, at the lower rate, subjects get fewer ‘looks’ at the relevant information when comparing stimuli differing in modulation depth. NH listeners could discriminate differences in co-modulation across bands; a multidimensional scaling study revealed that this was likely due to genuine across-frequency processing, rather than within-channel cues. CI users' discrimination performance was worse overall than for NH listeners, but showed a similar dependence on stimulus parameters. PMID:26706708

An incremental knowledge assimilation system (IKAS) for mine detection

NASA Astrophysics Data System (ADS)

Porway, Jake; Raju, Chaitanya; Varadarajan, Karthik Mahesh; Nguyen, Hieu; Yadegar, Joseph

2010-04-01

In this paper we present an adaptive incremental learning system for underwater mine detection and classification that utilizes statistical models of seabed texture and an adaptive nearest-neighbor classifier to identify varied underwater targets in many different environments. The first stage of processing uses our Background Adaptive ANomaly detector (BAAN), which identifies statistically likely target regions using Gabor filter responses over the image. Using this information, BAAN classifies the background type and updates its detection using background-specific parameters. To perform classification, a Fully Adaptive Nearest Neighbor (FAAN) determines the best label for each detection. FAAN uses an extremely fast version of Nearest Neighbor to find the most likely label for the target. The classifier perpetually assimilates new and relevant information into its existing knowledge database in an incremental fashion, allowing improved classification accuracy and capturing concept drift in the target classes. Experiments show that the system achieves >90% classification accuracy on underwater mine detection tasks performed on synthesized datasets provided by the Office of Naval Research. We have also demonstrated that the system can incrementally improve its detection accuracy by constantly learning from new samples.

Effects of processing parameters on immersion vacuum cooling time and physico-chemical properties of pork hams.

PubMed

Feng, Chao-Hui; Drummond, Liana; Zhang, Zhi-Hang; Sun, Da-Wen

2013-10-01

The effects of agitation (1002 rpm), different pressure reduction rates (60 and 100 mbar/min), as well as employing cold water with different initial temperatures (IWT: 7 and 20°C) on immersion vacuum cooling (IVC) of cooked pork hams were experimentally investigated. Final pork ham core temperature, cooling time, cooling loss, texture properties, colour and chemical composition were evaluated. The application for the first time of agitation during IVC substantially reduced the cooling time (47.39%) to 4.6°C, compared to IVC without agitation. For the different pressure drop rates, there was a trend that shorter IVC cooling times were achieved with lower cooling rate, although results were not statistically significant (P>0.05). For both IWTs tested, the same trend was observed: shorter cooling time and lower cooling loss were obtained under lower linear pressure drop rate of 60 mbar/min (not statistically significant, P>0.05). Compared to the reference cooling method (air blast cooling), IVC achieved higher cooling rates and better meat quality. Copyright © 2013 Elsevier Ltd. All rights reserved.

A Comparison of Land Surface Model Soil Hydraulic Properties Estimated by Inverse Modeling and Pedotransfer Functions

NASA Technical Reports Server (NTRS)

Gutmann, Ethan D.; Small, Eric E.

2007-01-01

Soil hydraulic properties (SHPs) regulate the movement of water in the soil. This in turn plays an important role in the water and energy cycles at the land surface. At present, SHPS are commonly defined by a simple pedotransfer function from soil texture class, but SHPs vary more within a texture class than between classes. To examine the impact of using soil texture class to predict SHPS, we run the Noah land surface model for a wide variety of measured SHPs. We find that across a range of vegetation cover (5 - 80% cover) and climates (250 - 900 mm mean annual precipitation), soil texture class only explains 5% of the variance expected from the real distribution of SHPs. We then show that modifying SHPs can drastically improve model performance. We compare two methods of estimating SHPs: (1) inverse method, and (2) soil texture class. Compared to texture class, inverse modeling reduces errors between measured and modeled latent heat flux from 88 to 28 w/m(exp 2). Additionally we find that with increasing vegetation cover the importance of SHPs decreases and that the van Genuchten m parameter becomes less important, while the saturated conductivity becomes more important.

Statistical process control applied to mechanized peanut sowing as a function of soil texture.

PubMed

Zerbato, Cristiano; Furlani, Carlos Eduardo Angeli; Ormond, Antonio Tassio Santana; Gírio, Lucas Augusto da Silva; Carneiro, Franciele Morlin; da Silva, Rouverson Pereira

2017-01-01

The successful establishment of agricultural crops depends on sowing quality, machinery performance, soil type and conditions, among other factors. This study evaluates the operational quality of mechanized peanut sowing in three soil types (sand, silt, and clay) with variable moisture contents. The experiment was conducted in three locations in the state of São Paulo, Brazil. The track-sampling scheme was used for 80 sampling locations of each soil type. Descriptive statistics and statistical process control (SPC) were used to evaluate the quality indicators of mechanized peanut sowing. The variables had normal distributions and were stable from the viewpoint of SPC. The best performance for peanut sowing density, normal spacing, and the initial seedling growing stand was found for clayey soil followed by sandy soil and then silty soil. Sandy or clayey soils displayed similar results regarding sowing depth, which was deeper than in the silty soil. Overall, the texture and the moisture of clayey soil provided the best operational performance for mechanized peanut sowing.

Statistical process control applied to mechanized peanut sowing as a function of soil texture

PubMed Central

Furlani, Carlos Eduardo Angeli; da Silva, Rouverson Pereira

2017-01-01

The successful establishment of agricultural crops depends on sowing quality, machinery performance, soil type and conditions, among other factors. This study evaluates the operational quality of mechanized peanut sowing in three soil types (sand, silt, and clay) with variable moisture contents. The experiment was conducted in three locations in the state of São Paulo, Brazil. The track-sampling scheme was used for 80 sampling locations of each soil type. Descriptive statistics and statistical process control (SPC) were used to evaluate the quality indicators of mechanized peanut sowing. The variables had normal distributions and were stable from the viewpoint of SPC. The best performance for peanut sowing density, normal spacing, and the initial seedling growing stand was found for clayey soil followed by sandy soil and then silty soil. Sandy or clayey soils displayed similar results regarding sowing depth, which was deeper than in the silty soil. Overall, the texture and the moisture of clayey soil provided the best operational performance for mechanized peanut sowing. PMID:28742095

Three-dimensional biofilm structure quantification.

PubMed

Beyenal, Haluk; Donovan, Conrad; Lewandowski, Zbigniew; Harkin, Gary

2004-12-01

Quantitative parameters describing biofilm physical structure have been extracted from three-dimensional confocal laser scanning microscopy images and used to compare biofilm structures, monitor biofilm development, and quantify environmental factors affecting biofilm structure. Researchers have previously used biovolume, volume to surface ratio, roughness coefficient, and mean and maximum thicknesses to compare biofilm structures. The selection of these parameters is dependent on the availability of software to perform calculations. We believe it is necessary to develop more comprehensive parameters to describe heterogeneous biofilm morphology in three dimensions. This research presents parameters describing three-dimensional biofilm heterogeneity, size, and morphology of biomass calculated from confocal laser scanning microscopy images. This study extends previous work which extracted quantitative parameters regarding morphological features from two-dimensional biofilm images to three-dimensional biofilm images. We describe two types of parameters: (1) textural parameters showing microscale heterogeneity of biofilms and (2) volumetric parameters describing size and morphology of biomass. The three-dimensional features presented are average (ADD) and maximum diffusion distances (MDD), fractal dimension, average run lengths (in X, Y and Z directions), aspect ratio, textural entropy, energy and homogeneity. We discuss the meaning of each parameter and present the calculations in detail. The developed algorithms, including automatic thresholding, are implemented in software as MATLAB programs which will be available at site prior to publication of the paper.

Geodiversity of landforms within morphoclimatic zones of the Earth

NASA Astrophysics Data System (ADS)

Zwoliński, Zbigniew; Gudowicz, Joanna

2016-04-01

The aim of the paper is trying to calculate and classify geomorphometric parameters and on the basis of their values describe geodiversity of landforms within morphoclimatic zones. Morphoclimatic zone classifications by Büdel (1963), Tricart, Cailleux (1965) and Hagedorn, Poser (1974) were evaluated. Zonal morphological and climatic variation of the Earth reflects the spatial distribution of the nature and intensity of the ancient and modern processes of erosion, denudation and accumulation. Therefore, can be observing variation of landforms within particular zones. Morphoclimatic zones we digitized to get polygon vector layers with consistent coverage for the whole world. Elevation data we obtained from the Shuttle Radar Topography Mission (SRTM Version 4). The coverage of elevation data are between 56° S and 60° N. In order to look at maps of morphoclimatic zones multiple parameters were calculated. Primary parameters consisted of relative heights, slope, plan and profile curvature. We used in the analysis also the secondary parameters i.e. Topographic Wetness Index and Convergence Index. Within the analyzed zones we also compared automatic landform classification methods based on Topographic Position Index, Hammond's classification, unsupervised nested-means algorithm and a three part geometric signature: slope gradient, local convexity, and surface texture. For the primary and secondary parameters descriptive statistics such as minimum, maximum, range, mean, standard deviation within each morphoclimatic zone were calculated. Then the parameter maps have been classified on the basis of the natural distribution of Jenks method (1967). Within each morphoclimatic zone, area percentage was calculated for the derived classes of parameters, as well as the percentage of surface forms generated on the basis of automatic classification methods. Iwahashi, Pike (2007) obtained terrain class values, as well as terrain series values for the entire world (see the first row in Table I). The table also contains newly calculated data for terrain classes and series, for average morphoclimatic zones according to the classifications of Büdel, Tricart, Cailleux and Hagedorn, Poser. Differences for the entire world data between the original Iwahashi, Pike data and the three classifications are relatively small and fall in the range of -3.1 to 2.4%. This means that at the scale of the entire world - regardless of the morphoclimatic zone classification method - the results are similar, despite the fact that glacial zones are not allowed for in the calculations. Extremely interesting information is provided by the analysis of data for the 16-fold terrain classes, which show significant differences in morphoclimatic zones according to different classifications (Table I). They show obvious differences in the morphological development of morphoclimatic zones, regardless of classification. Maps prepared for the primary and secondary geomorphometric parameters constitute the next series of results. Not all the parameters have proven to be fully useful for the characteristics and differentiation of morphoclimatic zones. However, in many cases the analysis of the special layout of these parameters allows discovering interesting morphogenetic observations. The unquestionable benefit of many geomorphometric parameters is the possibility to indicate the morphometric relief circumstances fostering the presence of geomorphological hazards such as flooding or landslides. The obtained preliminary data confirm the sense of the undertaken research problem. The possibility to use big data in the calculation of geomorphometric characteristics for selected classifications of morphoclimatic zones at the scale of the entire world opens new ways of interpreting the landforms. Budel's proposal (1963) should be considered the least useful of the three morphoclimatic classifications analysed. Generally, it may be assumed that the more complex the morphoclimatic classification, the better it adjusts to the spatial geomorphometric diversification of the topographic surface of the world. References Büdel, J., 1963. Klima-genetische Geomorphologie. Geographische Rundschau, 15:269-285. Hagedorn, J., Poser, H., 1974. Räumliche Ordnung der rezenten geomorphologischen Prozesse und Prozesskombinationen auf der Erde. Abh. Akad. Wiss. Göttingen, Math.-Physik. Kl. III/29, Göttingen: 426-439. Iwahashi, J., Pike, R., 2007. Automated classification of topography from DEMs by an unsupervised nested-means algorithm and three-part geometric signature. Geomorphology 86, 409-440. Jenks, G.F., 1967. The Data Model Concept in Statistical Mapping. International Yearbook of Cartography. 7:186-190. Tricart, J., Cailleux, A., 1965. Introduction à la géomorphologie climatique. Traité de géomorphologie, tome I, SEDES, París, 306 p. TABLE 1. TERRAIN CLASSES AND SERIES ACCORDING TO IWAHASHI AND PIKE (2007) FOR THREE MORPHOCLIMATIC CLASSICATIONS OF THE EARTH [%] Author Iwahashi, Pike (2007) Büdel (1963) Tricart, Cailleux (1965) Hagedorn, Poser (1974) 16-fold terrain classes 1 13.2 12.9 14.9 12.8 2 0.9 1.2 1.2 0.8 3 9.0 8.9 10.0 9.0 4 2.1 2.2 2.4 2.1 5 14.3 15.2 15.5 14.5 6 1.8 2.3 2.0 1.7 7 9.1 8.5 9.0 9.6 8 3.3 3.3 3.4 3.2 9 10.9 11.9 11.2 11.2 10 1.9 1.9 1.6 1.8 11 5.2 4.7 4.6 5.5 12 3.0 2.6 2.4 2.8 13 7.2 8.0 7.2 7.3 14 4.0 4.0 3.2 3.8 15 3.2 2.9 2.8 3.2 16 10.9 9.7 8.7 10.7 4-fold terrain series I: 1+5+9+13: fine texture, high convexity 45.7 48.0 48.8 45.7 II: 2+6+10+14: coarse texture, high convexity8.7 9.3 8.0 8.2 III: 3+7+11+15: fine texture, low convexity 26.4 24.9 26.3 27.3 IV: 4+8+12+16: coarse texture, low convexity19.3 17.7 16.9 18.7

Effect of layerwise structural inhomogeneity on stress- corrosion cracking of steel tubes

NASA Astrophysics Data System (ADS)

Perlovich, Yu A.; Krymskaya, O. A.; Isaenkova, M. G.; Morozov, N. S.; Fesenko, V. A.; Ryakhovskikh, I. V.; Esiev, T. S.

2016-04-01

Based on X-ray texture and structure analysis data of the material of main gas pipelines it was shown that the layerwise inhomogeneity of tubes is formed during their manufacturing. The degree of this inhomogeneity affects on the tendency of tubes to stress- corrosion cracking under exploitation. Samples of tubes were cut out from gas pipelines located under various operating conditions. Herewith the study was conducted both for sections with detected stress-corrosion defects and without them. Distributions along tube wall thickness for lattice parameters and half-width of X-ray lines were constructed. Crystallographic texture analysis of external and internal tube layers was also carried out. Obtained data testifies about considerable layerwise inhomogeneity of all samples. Despite the different nature of the texture inhomogeneity of gas pipeline tubes, the more inhomogeneous distribution of texture or structure features causes the increasing of resistance to stress- corrosion. The observed effect can be explained by saturation with interstitial impurities of the surface layer of the hot-rolled sheet and obtained therefrom tube. This results in rising of lattice parameters in the external layer of tube as compared to those in underlying metal. Thus, internal layers have a compressive effect on external layers in the rolling plane that prevents cracks opening at the tube surface. Moreover, the high mutual misorientation of grains within external and internal layers of tube results in the necessity to change the moving crack plane, so that the crack growth can be inhibited when reaching the layer with a modified texture.

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

NASA Astrophysics Data System (ADS)

Kaur, Mandeep; Rattan, Munish; Singh, Pushpinder

2017-12-01

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

FabricS: A user-friendly, complete and robust software for particle shape-fabric analysis

NASA Astrophysics Data System (ADS)

Moreno Chávez, G.; Castillo Rivera, F.; Sarocchi, D.; Borselli, L.; Rodríguez-Sedano, L. A.

2018-06-01

Shape-fabric is a textural parameter related to the spatial arrangement of elongated particles in geological samples. Its usefulness spans a range from sedimentary petrology to igneous and metamorphic petrology. Independently of the process being studied, when a material flows, the elongated particles are oriented with the major axis in the direction of flow. In sedimentary petrology this information has been used for studies of paleo-flow direction of turbidites, the origin of quartz sediments, and locating ignimbrite vents, among others. In addition to flow direction and its polarity, the method enables flow rheology to be inferred. The use of shape-fabric has been limited due to the difficulties of automatically measuring particles and analyzing them with reliable circular statistics programs. This has dampened interest in the method for a long time. Shape-fabric measurement has increased in popularity since the 1980s thanks to the development of new image analysis techniques and circular statistics software. However, the programs currently available are unreliable, old and are incompatible with newer operating systems, or require programming skills. The goal of our work is to develop a user-friendly program, in the MATLAB environment, with a graphical user interface, that can process images and includes editing functions, and thresholds (elongation and size) for selecting a particle population and analyzing it with reliable circular statistics algorithms. Moreover, the method also has to produce rose diagrams, orientation vectors, and a complete series of statistical parameters. All these requirements are met by our new software. In this paper, we briefly explain the methodology from collection of oriented samples in the field to the minimum number of particles needed to obtain reliable fabric data. We obtained the data using specific statistical tests and taking into account the degree of iso-orientation of the samples and the required degree of reliability. The program has been verified by means of several simulations performed using appropriately designed features and by analyzing real samples.

In vitro chronic hepatic disease characterization with a multiparametric ultrasonic approach.

PubMed

Meziri, M; Pereira, W C A; Abdelwahab, A; Degott, C; Laugier, P

2005-03-01

Although, high resolution, real-time ultrasonic (US) imaging is routinely available, image interpretation is based on grey-level and texture and quantitative evaluation is limited. Other potentially useful diagnostic information from US echoes may include modifications in tissue acoustic parameters (speed, attenuation and backscattering) resulting from disease development. Changes in acoustical parameters can be detected using time-of-flight and spectral analysis techniques. The objective of this study is to explore the potential of three parameters together (attenuation coefficient, US speed and integrated backscatter coefficient-IBC) to discriminate healthy and fibrosis subgroups in liver tissue. Echoes from 21 fresh in vitro samples of human liver and from a plane reflector were obtained using a 20-MHz central frequency transducer (6-30 MHz bandpass). The scan plane was parallel to the reflector placed beneath the liver. A 30 x 20 matrix of A-scans was obtained, with a 200-microm step. The samples were classified according to the Metavir scale in five different degrees of fibrosis. US speed, attenuation and IBC were estimated from standard methods described in the literature. Statistical tests were applied to the results of each parameter individually and indicated that it was not possible to identify all the fibrosis groups. Then a discriminant analysis was performed for the three parameters together resulting in a reasonable separation of fibrotic groups. Although the number of tissue samples is limited, this study opens the possibility of enhancing the discriminant capability of ultrasonic parameters of liver tissue disease when they are combined together.

The effect of surface waviness on friction between Neolite and quarry tiles.

PubMed

Chang, Wen-Ruey; Grönqvist, Raoul; Hirvonen, Mikko; Matz, Simon

2004-06-22

Friction is widely used as an indicator of surface slipperiness in preventing accidents in slips and falls. Surface texture affects friction, but it is not clear which surface characteristics are better correlated with friction. Highly correlated surface characteristics could be used as potential interventions to prevent slip and fall accidents. The dynamic friction between quarry tiles and a commonly used sole testing material, Neolite, using three different mixtures of glycerol and water as contaminants at the interface was correlated with the surface parameters of the tile surfaces. The surface texture was quantified with various surface roughness and surface waviness parameters using three different cut-off lengths to filter the measured profiles for obtaining the profiles of either surface roughness or surface waviness. The correlation coefficients between the surface parameters and the measured friction were affected by the glycerol contents and cut-off lengths. Surface waviness parameters could potentially be better indicators of friction than commonly used surface roughness parameters, especially when they were measured with commonly used cut-off lengths or when the viscosity of the liquid contaminant was high.

Skyrmions in magnetic multilayers

NASA Astrophysics Data System (ADS)

Jiang, Wanjun; Chen, Gong; Liu, Kai; Zang, Jiadong; te Velthuis, Suzanne G. E.; Hoffmann, Axel

2017-08-01

Symmetry breaking together with strong spin-orbit interaction gives rise to many exciting phenomena within condensed matter physics. A recent example is the existence of chiral spin textures, which are observed in magnetic systems lacking inversion symmetry. These chiral spin textures, including domain walls and magnetic skyrmions, are both fundamentally interesting and technologically promising. For example, they can be driven very efficiently by electrical currents, and exhibit many new physical properties determined by their real-space topological characteristics. Depending on the details of the competing interactions, these spin textures exist in different parameter spaces. However, the governing mechanism underlying their physical behaviors remains essentially the same. In this review article, the fundamental topological physics underlying these chiral spin textures, the key factors for materials optimization, and current developments and future challenges will be discussed. In the end, a few promising directions that will advance the development of skyrmion based spintronics will be highlighted.

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.

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.

Textures in a chiral smectic liquid-crystal film

NASA Astrophysics Data System (ADS)

Langer, Stephen A.; Sethna, James P.

1986-12-01

Freely suspended liquid-crystal films of the smectic-I phase of HOBACPC [R(-) hexyloxybenzylidene p'-amino-2-chloropropyl cinnamate] display distinctive stripe and droplet textures. We derive these patterns from a Landau expansion of the free energy using a vector order parameter. Strong pinning boundary conditions lead to boojums in the droplets and stable defect lines between the stripes. The boojum is a two-dimensional version of its namesake in superfluid 3A. The surface defect in the boojum is expelled from the smectic-I droplet in order to lower the internal gradient energy, leaving a defect-free texture. The expulsion distance and the width of the stripes are calculated in terms of the elastic constants.

Texture discrimination and multi-unit recording in the rat vibrissal nerve

PubMed Central

Albarracín, Ana L; Farfán, Fernando D; Felice, Carmelo J; Décima, Emilio E

2006-01-01

Background Rats distinguish objects differing in surface texture by actively moving their vibrissae. In this paper we characterized some aspects of texture sensing in anesthetized rats during active touch. We analyzed the multifiber discharge from a deep vibrissal nerve when the vibrissa sweeps materials (wood, metal, acrylic, sandpaper) having different textures. We polished these surfaces with sandpaper (P1000) to obtain close degrees of roughness and we induced vibrissal movement with two-branch facial nerve stimulation. We also consider the change in pressure against the vibrissa as a way to improve the tactile information acquisition. The signals were compared with a reference signal (control) – vibrissa sweeping the air – and were analyzed with the Root Mean Square (RMS) and the Power Spectrum Density (PSD). Results We extracted the information about texture discrimination hidden in the population activity of one vibrissa innervation, using the RMS values and the PSD. The pressure level 3 produced the best differentiation for RMS values and it could represent the "optimum" vibrissal pressure for texture discrimination. The frequency analysis (PSD) provided information only at low-pressure levels and showed that the differences are not related to the roughness of the materials but could be related to other texture parameters. Conclusion Our results suggest that the physical properties of different materials could be transduced by the trigeminal sensory system of rats, as are shown by amplitude and frequency changes. Likewise, varying the pressure could represent a behavioral strategy that improves the information acquisition for texture discrimination. PMID:16719904

Texture discrimination and multi-unit recording in the rat vibrissal nerve.

PubMed

Albarracín, Ana L; Farfán, Fernando D; Felice, Carmelo J; Décima, Emilio E

2006-05-23

Rats distinguish objects differing in surface texture by actively moving their vibrissae. In this paper we characterized some aspects of texture sensing in anesthetized rats during active touch. We analyzed the multifiber discharge from a deep vibrissal nerve when the vibrissa sweeps materials (wood, metal, acrylic, sandpaper) having different textures. We polished these surfaces with sandpaper (P1000) to obtain close degrees of roughness and we induced vibrissal movement with two-branch facial nerve stimulation. We also consider the change in pressure against the vibrissa as a way to improve the tactile information acquisition. The signals were compared with a reference signal (control)--vibrissa sweeping the air--and were analyzed with the Root Mean Square (RMS) and the Power Spectrum Density (PSD). We extracted the information about texture discrimination hidden in the population activity of one vibrissa innervation, using the RMS values and the PSD. The pressure level 3 produced the best differentiation for RMS values and it could represent the "optimum" vibrissal pressure for texture discrimination. The frequency analysis (PSD) provided information only at low-pressure levels and showed that the differences are not related to the roughness of the materials but could be related to other texture parameters. Our results suggest that the physical properties of different materials could be transduced by the trigeminal sensory system of rats, as are shown by amplitude and frequency changes. Likewise, varying the pressure could represent a behavioral strategy that improves the information acquisition for texture discrimination.

SAPO-34/AlMCM-41, as a novel hierarchical nanocomposite: preparation, characterization and investigation of synthesis factors using response surface methodology

NASA Astrophysics Data System (ADS)

Roohollahi, Hossein; Halladj, Rouein; Askari, Sima; Yaripour, Fereydoon

2018-06-01

SAPO-34/AlMCM-41, as a new hierarchical nanocomposite was successfully synthesized via hydrothermal and dry-gel conversion. In an experimental and statistical study, effect of five input parameters including synthesis period, drying temperature, NaOH/Si, water/dried-gel and SAPO% were investigated on range-order degree of mesochannels and the relative crystallinity. X-ray diffraction (XRD) patterns were recorded to characterize the ordered AlMCM-41 and crystalline SAPO-34 structures. Nitrogen adsorption-desorption technique, scanning electron microscopy (SEM), field-emission SEM (FESEM) equipped with an energy-dispersive X-ray spectroscopy (EDS-Map) and transmission electron microscopy (TEM) were used to study the textural properties, morphology and surface elemental composition. Two reduced polynomials were fitted to the responses with good precision. Further, based on analysis of variances, SAPO% and time duration of dry-gel conversion were observed as the most effective parameters on the composite structure. The hierarchical porosity, narrow pore size distribution, high external surface area and large specific pore volume were of interesting characteristics for this novel nanocomposite.

Subgrid spatial variability of soil hydraulic functions for hydrological modelling

NASA Astrophysics Data System (ADS)

Kreye, Phillip; Meon, Günter

2016-07-01

State-of-the-art hydrological applications require a process-based, spatially distributed hydrological model. Runoff characteristics are demanded to be well reproduced by the model. Despite that, the model should be able to describe the processes at a subcatchment scale in a physically credible way. The objective of this study is to present a robust procedure to generate various sets of parameterisations of soil hydraulic functions for the description of soil heterogeneity on a subgrid scale. Relations between Rosetta-generated values of saturated hydraulic conductivity (Ks) and van Genuchten's parameters of soil hydraulic functions were statistically analysed. An universal function that is valid for the complete bandwidth of Ks values could not be found. After concentrating on natural texture classes, strong correlations were identified for all parameters. The obtained regression results were used to parameterise sets of hydraulic functions for each soil class. The methodology presented in this study is applicable on a wide range of spatial scales and does not need input data from field studies. The developments were implemented into a hydrological modelling system.

Physicochemical properties of foal meat as affected by cooking methods.

PubMed

Lorenzo, José M; Cittadini, Aurora; Munekata, Paulo E; Domínguez, Rubén

2015-10-01

The present study deals with the effect of four different cooking techniques (roasting, grilling, microwave baking and frying with olive oil) on physicochemical parameters (cooking loss, WHC, texture and colour) and lipid oxidation (by TBARS measurement) of foal meat. Thermal treatments induced water loss (P<0.001), being lower in foal steaks cooked in the grill (25.8%) and higher in foal samples cooked in the microwave (39.5%). As it was expected, all the cooking methods increased TBARS index, since high temperature during cooking seems to cause an increase of the lipid oxidation in foal steaks. Statistical analysis displayed that WHC was affected (P<0.001) by thermal treatment, since the smallest WHC values were observed in samples from microwave treatment. Thermal treatment also caused a significant (P<0.001) increase in the force needed to cut the foal steaks. Regarding colour parameter, cooking led to an increase of L*-value (lightness) and b*-value (yellowness), while a*-value (redness) markedly decreased in all samples. Copyright © 2015 Elsevier Ltd. All rights reserved.

Human skin surface evaluation by image processing

NASA Astrophysics Data System (ADS)

Zhu, Liangen; Zhan, Xuemin; Xie, Fengying

2003-12-01

Human skin gradually lose its tension and becomes very dry as time flies by. Use of cosmetics is effective to prevent skin aging. Recently, there are many choices of products of cosmetics. To show their effects, It is desirable to develop a way to evaluate quantificationally skin surface condition. In this paper, An automatic skin evaluating method is proposed. The skin surface has the pattern called grid-texture. This pattern is composed of the valleys that spread vertically, horizontally, and obliquely and the hills separated by them. Changes of the grid are closely linked to the skin surface condition. They can serve as a good indicator for the skin condition. By measuring the skin grid using digital image processing technologies, we can evaluate skin surface about its aging, health, and alimentary status. In this method, the skin grid is first detected to form a closed net. Then, some skin parameters such as Roughness, tension, scale and gloss can be calculated from the statistical measurements of the net. Through analyzing these parameters, the condition of the skin can be monitored.

Statistical correlations between the in-mouth textural characteristics and the chemical composition of Shiraz wines.

PubMed

Gawel, Richard; Francis, Leigh; Waters, Elizabeth J

2007-04-04

The relationships between the levels of polyphenols, acidity, and red pigments in Shiraz wines and their perceived textural profiles as quantified by a trained sensory descriptive analysis panel were explored. A "chamois-like" feeling when the wine was held in the mouth appeared to be related to an absence of polyphenols. The in-mouth "chalk-like" texture was strongly associated with anthocyanin concentration and was negatively associated with alcohol level and acidity. The astringent subqualities of "velvet-like" and "emery-like" roughing were mostly related to polyphenol levels, but these attributes could not be adequately differentiated by the compositional variables under study. Wines that elicited a "puckery" sensation were characterized by relatively low anthocyanin levels, high acidity, and high pigmented polymer and tannin concentrations. The results of the study suggest that the in-mouth textural properties of Shiraz red wine are associated not only with their tannin composition and concentration but also with their acidity and anthocyanin and alcohol concentrations.

Interactions between soil texture, water, and nutrients control patterns of biocrusts abundance and structure

NASA Astrophysics Data System (ADS)

Young, Kristina; Bowker, Matthew; Reed, Sasha; Howell, Armin

2017-04-01

Heterogeneity in the abiotic environment structures biotic communities by controlling niche space and parameters. This has been widely observed and demonstrated in vascular plant and other aboveground communities. While soil organisms are presumably also strongly influenced by the physical and chemical dimensions of the edaphic environment, there are fewer studies linking the development, structure, productivity or function of surface soil communities to specific edaphic gradients. Here, we use biological soil crusts (biocrusts) as a model system to determine mechanisms regulating community structure of soil organisms. We chose soil texture to serve as an edaphic gradient because of soil texture's influence over biocrust distribution on a landscape level. We experimentally manipulated texture in constructed soil, and simultaneously manipulated two main outcomes of texture, water and nutrient availability, to determine the mechanism underlying texture's influence on biocrust abundance and structure. We grew biocrust communities from a field-sourced inoculum on four different soil textures, sieved from the same parent soil material, manipulating watering levels and nutrient additions across soil textures in a full-factorial design over a 5-month period of time. We measured abundance and structure of biocrusts over time, and measured two metrics of function, N2 fixation rates and soil stabilization, at the conclusion of the experiment. Our results showed finer soil textures resulted in faster biocrust community development and dominance by mosses, whereas coarser textures grew more slowly and had biocrust communities dominated by cyanobacteria and lichen. Additionally, coarser textured soils contained cyanobacterial filaments significantly deeper into the soil profile than fine textured soils. N2-fixation values increased with increasing moss cover and decreased with increasing cyanobacterial cover, however, the rate of change depended on soil texture and water amount. Soil shear resistance was highest on finer textured soil with the highest watering treatment, whereas compression resistance was highest on the coarsest textured soils with the highest watering amounts. Nutrient addition did not influence total cover or biocrust function, but did decrease lichen cover. Taken together, these results suggest that interactions between soil texture, water, and to a lesser degree nutrients, create predictable patterns in biocrust assemblage and offers a mechanistic understanding of edaphic controls over biocrust abundance and structure. These insights add to our increasing understanding of how edaphic gradients structure soil communities.

Global ensemble texture representations are critical to rapid scene perception.

PubMed

Brady, Timothy F; Shafer-Skelton, Anna; Alvarez, George A

2017-06-01

Traditionally, recognizing the objects within a scene has been treated as a prerequisite to recognizing the scene itself. However, research now suggests that the ability to rapidly recognize visual scenes could be supported by global properties of the scene itself rather than the objects within the scene. Here, we argue for a particular instantiation of this view: That scenes are recognized by treating them as a global texture and processing the pattern of orientations and spatial frequencies across different areas of the scene without recognizing any objects. To test this model, we asked whether there is a link between how proficient individuals are at rapid scene perception and how proficiently they represent simple spatial patterns of orientation information (global ensemble texture). We find a significant and selective correlation between these tasks, suggesting a link between scene perception and spatial ensemble tasks but not nonspatial summary statistics In a second and third experiment, we additionally show that global ensemble texture information is not only associated with scene recognition, but that preserving only global ensemble texture information from scenes is sufficient to support rapid scene perception; however, preserving the same information is not sufficient for object recognition. Thus, global ensemble texture alone is sufficient to allow activation of scene representations but not object representations. Together, these results provide evidence for a view of scene recognition based on global ensemble texture rather than a view based purely on objects or on nonspatially localized global properties. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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.

Consequences of using different soil texture determination methodologies for soil physical quality and unsaturated zone time lag estimates.

PubMed

Fenton, O; Vero, S; Ibrahim, T G; Murphy, P N C; Sherriff, S C; Ó hUallacháin, D

2015-11-01

Elucidation of when the loss of pollutants, below the rooting zone in agricultural landscapes, affects water quality is important when assessing the efficacy of mitigation measures. Investigation of this inherent time lag (t(T)) is divided into unsaturated (t(u)) and saturated (t(s)) components. The duration of these components relative to each other differs depending on soil characteristics and the landscape position. The present field study focuses on tu estimation in a scenario where the saturated zone is likely to constitute a higher proportion of t(T). In such instances, or where only initial breakthrough (IBT) or centre of mass (COM) is of interest, utilisation of site and depth specific "simple" textural class or actual sand-silt-clay percentages to generate soil water characteristic curves with associated soil hydraulic parameters is acceptable. With the same data it is also possible to estimate a soil physical quality (S) parameter for each soil layer which can be used to infer many other physical, chemical and biological quality indicators. In this study, hand texturing in the field was used to determine textural classes of a soil profile. Laboratory methods, including hydrometer, pipette and laser diffraction methods were used to determine actual sand-silt-clay percentages of sections of the same soil profile. Results showed that in terms of S, hand texturing resulted in a lower index value (inferring a degraded soil) than that of pipette, hydrometer and laser equivalents. There was no difference between S index values determined using the pipette, hydrometer and laser diffraction methods. The difference between the three laboratory methods on both the IBT and COM stages of t(u) were negligible, and in this instance were unlikely to affect either groundwater monitoring decisions, or to be of consequence from a policy perspective. When t(u) estimates are made over the full depth of the vadose zone, which may extend to several metres, errors resulting from the use of hydraulic parameters generated from hand texture data will be resultantly greater, and may lead to flawed predictions regarding the achievability of water policy targets. For this reason laboratory analysis, regardless of method, should be preferred to simple field assessments. Copyright © 2015 Elsevier B.V. All rights reserved.

The effects of segmentation algorithms on the measurement of 18F-FDG PET texture parameters in non-small cell lung cancer.

PubMed

Bashir, Usman; Azad, Gurdip; Siddique, Muhammad Musib; Dhillon, Saana; Patel, Nikheel; Bassett, Paul; Landau, David; Goh, Vicky; Cook, Gary

2017-12-01

Measures of tumour heterogeneity derived from 18-fluoro-2-deoxyglucose positron emission tomography/computed tomography ( 18 F-FDG PET/CT) scans are increasingly reported as potential biomarkers of non-small cell lung cancer (NSCLC) for classification and prognostication. Several segmentation algorithms have been used to delineate tumours, but their effects on the reproducibility and predictive and prognostic capability of derived parameters have not been evaluated. The purpose of our study was to retrospectively compare various segmentation algorithms in terms of inter-observer reproducibility and prognostic capability of texture parameters derived from non-small cell lung cancer (NSCLC) 18 F-FDG PET/CT images. Fifty three NSCLC patients (mean age 65.8 years; 31 males) underwent pre-chemoradiotherapy 18 F-FDG PET/CT scans. Three readers segmented tumours using freehand (FH), 40% of maximum intensity threshold (40P), and fuzzy locally adaptive Bayesian (FLAB) algorithms. Intraclass correlation coefficient (ICC) was used to measure the inter-observer variability of the texture features derived by the three segmentation algorithms. Univariate cox regression was used on 12 commonly reported texture features to predict overall survival (OS) for each segmentation algorithm. Model quality was compared across segmentation algorithms using Akaike information criterion (AIC). 40P was the most reproducible algorithm (median ICC 0.9; interquartile range [IQR] 0.85-0.92) compared with FLAB (median ICC 0.83; IQR 0.77-0.86) and FH (median ICC 0.77; IQR 0.7-0.85). On univariate cox regression analysis, 40P found 2 out of 12 variables, i.e. first-order entropy and grey-level co-occurence matrix (GLCM) entropy, to be significantly associated with OS; FH and FLAB found 1, i.e., first-order entropy. For each tested variable, survival models for all three segmentation algorithms were of similar quality, exhibiting comparable AIC values with overlapping 95% CIs. Compared with both FLAB and FH, segmentation with 40P yields superior inter-observer reproducibility of texture features. Survival models generated by all three segmentation algorithms are of at least equivalent utility. Our findings suggest that a segmentation algorithm using a 40% of maximum threshold is acceptable for texture analysis of 18 F-FDG PET in NSCLC.

Response monitoring of breast cancer patients receiving neoadjuvant chemotherapy using quantitative ultrasound, texture, and molecular features

PubMed Central

Gangeh, Mehrdad; Tadayyon, Hadi; Sadeghi-Naini, Ali; Gandhi, Sonal; Wright, Frances C.; Slodkowska, Elzbieta; Curpen, Belinda; Tran, William; Czarnota, Gregory J.

2018-01-01

Background Pathological response of breast cancer to chemotherapy is a prognostic indicator for long-term disease free and overall survival. Responses of locally advanced breast cancer in the neoadjuvant chemotherapy (NAC) settings are often variable, and the prediction of response is imperfect. The purpose of this study was to detect primary tumor responses early after the start of neoadjuvant chemotherapy using quantitative ultrasound (QUS), textural analysis and molecular features in patients with locally advanced breast cancer. Methods The study included ninety six patients treated with neoadjuvant chemotherapy. Breast tumors were scanned with a clinical ultrasound system prior to chemotherapy treatment, during the first, fourth and eighth week of treatment, and prior to surgery. Quantitative ultrasound parameters and scatterer-based features were calculated from ultrasound radio frequency (RF) data within tumor regions of interest. Additionally, texture features were extracted from QUS parametric maps. Prior to therapy, all patients underwent a core needle biopsy and histological subtypes and biomarker ER, PR, and HER2 status were determined. Patients were classified into three treatment response groups based on combination of clinical and pathological analyses: complete responders (CR), partial responders (PR), and non-responders (NR). Response classifications from QUS parameters, receptors status and pathological were compared. Discriminant analysis was performed on extracted parameters using a support vector machine classifier to categorize subjects into CR, PR, and NR groups at all scan times. Results Of the 96 patients, the number of CR, PR and NR patients were 21, 52, and 23, respectively. The best prediction of treatment response was achieved with the combination mean QUS values, texture and molecular features with accuracies of 78%, 86% and 83% at weeks 1, 4, and 8, after treatment respectively. Mean QUS parameters or clinical receptors status alone predicted the three response groups with accuracies less than 60% at all scan time points. Recurrence free survival (RFS) of response groups determined based on combined features followed similar trend as determined based on clinical and pathology. Conclusions This work demonstrates the potential of using QUS, texture and molecular features for predicting the response of primary breast tumors to chemotherapy early, and guiding the treatment planning of refractory patients. PMID:29298305

Assessment of risk of femoral neck fracture with radiographic texture parameters: a retrospective study.

PubMed

Thevenot, Jérôme; Hirvasniemi, Jukka; Pulkkinen, Pasi; Määttä, Mikko; Korpelainen, Raija; Saarakkala, Simo; Jämsä, Timo

2014-07-01

To investigate whether femoral neck fracture can be predicted retrospectively on the basis of clinical radiographs by using the combined analysis of bone geometry, textural analysis of trabecular bone, and bone mineral density (BMD). Formal ethics committee approval was obtained for the study, and all participants gave informed written consent. Pelvic radiographs and proximal femur BMD measurements were obtained in 53 women aged 79-82 years in 2006. By 2012, 10 of these patients had experienced a low-impact femoral neck fracture. A Laplacian-based semiautomatic custom algorithm was applied to the radiographs to calculate the texture parameters along the trabecular fibers in the lower neck area for all subjects. Intra- and interobserver reproducibility was calculated by using the root mean square average coefficient of variation to evaluate the robustness of the method. The best predictors of hip fracture were entropy (P = .007; reproducibility coefficient of variation < 1%), the neck-shaft angle (NSA) (P = .017), and the BMD (P = .13). For prediction of fracture, the area under the receiver operating characteristic curve was 0.753 for entropy, 0.608 for femoral neck BMD, and 0.698 for NSA. The area increased to 0.816 when entropy and NSA were combined and to 0.902 when entropy, NSA, and BMD were combined. Textural analysis of pelvic radiographs enables discrimination of patients at risk for femoral neck fracture, and our results show the potential of this conventional imaging method to yield better prediction than that achieved with dual-energy x-ray absorptiometry-based BMD. The combination of the entropy parameter with NSA and BMD can further enhance predictive accuracy. © RSNA, 2014.

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

PubMed

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

2017-03-01

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

Features of the normal choriocapillaris with OCT-angiography: Density estimation and textural properties.

PubMed

Montesano, Giovanni; Allegrini, Davide; Colombo, Leonardo; Rossetti, Luca M; Pece, Alfredo

2017-01-01

The main objective of our work is to perform an in depth analysis of the structural features of normal choriocapillaris imaged with OCT Angiography. Specifically, we provide an optimal radius for a circular Region of Interest (ROI) to obtain a stable estimate of the subfoveal choriocapillaris density and characterize its textural properties using Markov Random Fields. On each binarized image of the choriocapillaris OCT Angiography we performed simulated measurements of the subfoveal choriocapillaris densities with circular Regions of Interest (ROIs) of different radii and with small random displacements from the center of the Foveal Avascular Zone (FAZ). We then calculated the variability of the density measure with different ROI radii. We then characterized the textural features of choriocapillaris binary images by estimating the parameters of an Ising model. For each image we calculated the Optimal Radius (OR) as the minimum ROI radius required to obtain a standard deviation in the simulation below 0.01. The density measured with the individual OR was 0.52 ± 0.07 (mean ± STD). Similar density values (0.51 ± 0.07) were obtained using a fixed ROI radius of 450 μm. The Ising model yielded two parameter estimates (β = 0.34 ± 0.03; γ = 0.003 ± 0.012; mean ± STD), characterizing pixel clustering and white pixel density respectively. Using the estimated parameters to synthetize new random textures via simulation we obtained a good reproduction of the original choriocapillaris structural features and density. In conclusion, we developed an extensive characterization of the normal subfoveal choriocapillaris that might be used for flow analysis and applied to the investigation pathological alterations.

To be seen or to hide: visual characteristics of body patterns for camouflage and communication in the Australian giant cuttlefish Sepia apama.

PubMed

Zylinski, S; How, M J; Osorio, D; Hanlon, R T; Marshall, N J

2011-05-01

It might seem obvious that a camouflaged animal must generally match its background whereas to be conspicuous an organism must differ from the background. However, the image parameters (or statistics) that evaluate the conspicuousness of patterns and textures are seldom well defined, and animal coloration patterns are rarely compared quantitatively with their respective backgrounds. Here we examine this issue in the Australian giant cuttlefish Sepia apama. We confine our analysis to the best-known and simplest image statistic, the correlation in intensity between neighboring pixels. Sepia apama can rapidly change their body patterns from assumed conspicuous signaling to assumed camouflage, thus providing an excellent and unique opportunity to investigate how such patterns differ in a single visual habitat. We describe the intensity variance and spatial frequency power spectra of these differing body patterns and compare these patterns with the backgrounds against which they are viewed. The measured image statistics of camouflaged animals closely resemble their backgrounds, while signaling animals differ significantly from their backgrounds. Our findings may provide the basis for a set of general rules for crypsis and signals. Furthermore, our methods may be widely applicable to the quantitative study of animal coloration.

Prediction of Performance of Diamond Wire Saw with Respect to Texture Characteristics of Rock / Prognozowanie Wydajności Pracy Strunowej Piły Diamentowej W Odniesieniu Do Charakterystyki Tekstury Skał

NASA Astrophysics Data System (ADS)

Ghaysari, N.; Ataei, M.; Sereshki, F.; Mikaiel, R.

2012-12-01

In this study, prediction of production rate in diamond wire saw has been investigated. Performance measurements of diamond wire saw carried out in 7 different quarries of carbonate rocks in Iran. For determination textural properties, rock samples were collected from these quarries. At first, a thin section was prepared for each rock and then 5 digital photographs were taken from each section. After this, all images were digitized using AutoCAD software. Then, area, perimeter, longest diameter and shortest diameter were assigned. According to these parameters, all of the other textural characteristics and texture coefficient were determined too. The correlation between sawing rate and textural characteristics were evaluated using multiple and simple regression analyses. Then developed model was validated by P-value test. It was concluded that area, perimeter, diameter equivalent and index of grain size homogeneity are very effective on production rate. Production rate using diamond wire saw can reliably be predicted using developed model.

Broadband absorption enhancement in amorphous Si solar cells using metal gratings and surface texturing

NASA Astrophysics Data System (ADS)

Magdi, Sara; Swillam, Mohamed A.

2017-02-01

The efficiencies of thin film amorphous silicon (a-Si) solar cells are restricted by the small thickness required for efficient carrier collection. This thickness limitations result in poor light absorption. In this work, broadband absorption enhancement is theoretically achieved in a-Si solar cells by using nanostructured back electrode along with surface texturing. The back electrode is formed of Au nanogratings and the surface texturing consists of Si nanocones. The results were then compared to random texturing surfaces. Three dimensional finite difference time domain (FDTD) simulations are used to design and optimize the structure. The Au nanogratings achieved absorption enhancement in the long wavelengths due to sunlight coupling to surface plasmon polaritons (SPP) modes. High absorption enhancement was achieved at short wavelengths due to the decreased reflection and enhanced scattering inside the a-Si absorbing layer. Optimizations have been performed to obtain the optimal geometrical parameters for both the nanogratings and the periodic texturing. In addition, an enhancement factor (i.e. absorbed power in nanostructured device/absorbed power in reference device) was calculated to evaluate the enhancement obtained due to the incorporation of each nanostructure.

Dislocation structure in textured zirconium tensile-deformed along rolling and transverse directions determined by X-ray diffraction line profile analysis

NASA Astrophysics Data System (ADS)

Fan, Zhijian; Jóni, Bertalan; Xie, Lei; Ribárik, Gábor; Ungár, Tamás

2018-04-01

Specimens of cold-rolled zirconium were tensile-deformed along the rolling (RD) and the transverse (TD) directions. The stress-strain curves revealed a strong texture dependence. High resolution X-ray line profile analysis was used to determine the prevailing active slip-systems in the specimens with different textures. The reflections in the X-ray diffraction patterns were separated into two groups. One group corresponds to the major and the other group to the random texture component, respectively. The dislocation densities, the subgrain size and the prevailing active slip-systems were evaluated by using the convolutional multiple whole profile (CMWP) procedure. These microstructure parameters were evaluated separately in the two groups of reflections corresponding to the two different texture components. Significant differences were found in both, the evolution of dislocation densities and the development of the fractions of and type slip systems in the RD and TD specimens during tensile deformation. The differences between the RD and TD stress-strain curves are discussed in terms of the differences of the microstructure evolution.

Texture and hydride orientation relationship of Zircaloy-4 fuel clad tube during its fabrication for pressurized heavy water reactors

NASA Astrophysics Data System (ADS)

Vaibhaw, Kumar; Rao, S. V. R.; Jha, S. K.; Saibaba, N.; Jayaraj, R. N.

2008-12-01

Zircaloy-4 material is used for cladding tube in pressurized heavy water reactors (PHWRs) of 220 MWe and 540 MWe capacity in India. These tubes are fabricated by using various combinations of thermo-mechanical processes to achieve desired mechanical and corrosion properties. Cladding tube develops crystallographic texture during its fabrication, which has significant influence on its in-reactor performance. Due to radiolytic decomposition of water Zircaloy-4 picks-up hydrogen. This hydrogen in excess of its maximum solubility in reactor operating condition (˜300 °C), precipitates as zirconium hydrides causing embrittlement of cladding tube. Hydride orientation in the radial direction of the tube limits the service life and lowers the fuel burn-up in reactor. The orientation of the hydride primarily depends on texture developed during fabrication. A correlation between hydride orientation ( F n) with the texture in the tube during its fabrication has been developed using a second order polynomial. The present work is aimed at quantification and correlation of texture evolved in Zircaloy-4 cladding tube using Kearn's f-parameter during its fabrication process.

Quantitative analysis of domain texture in polycrystalline barium titanate by polarized Raman microprobe spectroscopy

NASA Astrophysics Data System (ADS)

Sakashita, Tatsuo; Chazono, Hirokazu; Pezzotti, Giuseppe

2007-12-01

A quantitative determination of domain distribution in polycrystalline barium titanate (BaTiO3, henceforth BT) ceramics has been pursued with the aid of a microprobe polarized Raman spectrometer. The crystallographic texture and domain orientation distribution of BT ceramics, which switched upon applying stress according to ferroelasticity principles, were determined from the relative intensity of selected phonon modes, taking into consideration a theoretical analysis of the angular dependence of phonon mode intensity for the tetragonal BT phase. Furthermore, the angular dependence of Raman intensity measured in polycrystalline BT depended on the statistical distribution of domain angles in the laser microprobe, which was explicitly taken into account in this work for obtaining a quantitative analysis of domain orientation for in-plane textured BT polycrystalline materials.

A cosmic microwave background feature consistent with a cosmic texture.

PubMed

Cruz, M; Turok, N; Vielva, P; Martínez-González, E; Hobson, M

2007-12-07

The Cosmic Microwave Background provides our most ancient image of the universe and our best tool for studying its early evolution. Theories of high-energy physics predict the formation of various types of topological defects in the very early universe, including cosmic texture, which would generate hot and cold spots in the Cosmic Microwave Background. We show through a Bayesian statistical analysis that the most prominent 5 degrees -radius cold spot observed in all-sky images, which is otherwise hard to explain, is compatible with having being caused by a texture. From this model, we constrain the fundamental symmetry-breaking energy scale to be (0) approximately 8.7 x 10(15) gigaelectron volts. If confirmed, this detection of a cosmic defect will probe physics at energies exceeding any conceivable terrestrial experiment.

Flesh quality and biochemistry of light-manipulated Atlantic cod (Gadus morhua) and the significance of collagen cross-links on fillet firmness and gaping.

PubMed

Hagen, Ørjan; Johnsen, Chris André

2016-01-01

The aim of our study was to investigate whether light-manipulation, causing accelerated or delayed maturation, could be used as a tool to improve fillet gaping score and texture of farmed cod (Gadus morhua L.) harvested during summer. Control and accelerated groups had completed spawning by the time of harvest, and expressed sexual dimorphism in various biometric and flesh quality parameters. Pyridinoline cross-links, a key biochemical parameter investigated, were positively correlated with texture (r(2) = 0.4), as also were cathepsin B&L and sex. Gaping was also impacted by pyridinoline cross-links, together with body mass and maturation. Interestingly, the level of gaping was significantly reduced with a pyridinoline cross-link concentration of >2500 pmols g(-1) dry mass. In conclusion, light-manipulation can be used as a tool to improve flesh texture of farmed cod with a low gaping score, but with compromise of increased dress out percentage for the accelerated group. Copyright © 2015 Elsevier Ltd. All rights reserved.

Laser marking as environment technology

NASA Astrophysics Data System (ADS)

Sobotova, Lydia; Badida, Miroslav

2017-11-01

The contribution deals with the laser marking as one of the progressive and environment friendly technologies with utilisation in many branches of industry. Engraving and other types of laser marking of different types of materials are very actual technologies these days. Laser marking decreases the waste creation in comparison with the other classical marking technologies, which use paintings or created chips. In this experimental investigation the laser marking surface texturing of material AL99,7 according to STN 42 4003:1993-08 (STN EN 573) has been conducted. The laser marking machine TruMark 6020 and software TruTops Mark were used. Laser surface texturing after laser marking has been realised under different combinations of process parameters: pulse frequency, pulse energy and laser beam scanning speed. The morphological characterization of engraving or annealing surfaces has been performed using scanning electron microscopy (SEM) technique. The evaluation of roughness of engraved surfaces has been realized according to STN EN ISO 4287 by using Surftest SJ 301. The aim of the contribution was to show how different laser parameters affect the surface texture and colour change of metallic materials while creating minimal waste.

High-Speed Friction Stir Welding of AA7075-T6 Sheet: Microstructure, Mechanical Properties, Micro-texture, and Thermal History

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

Zhang, Jingyi; Upadhyay, Piyush; Hovanski, Yuri

Friction-stir-welding (FSW) is a cost-effective and high quality joining process for aluminum alloys (especially heat-treatable allo ys) that has been applied successfully in the aerospace industry. However, the full potential of FSW on more cost-sensitive applications is still limited by the production rate, namely the welding speed of the process. The majority of literature evaluating FSW of aluminum alloys is based on welds made in the range of welding speeds around hundreds of millimeters per minute, and only a handful are at a moderate speed of 1 m/min. In this study we present a microstructural analysis of friction stir weldedmore » AA7075-T6 blanks with welding speeds up to 3 m/min. Textures, microstructures, mechanical properties, and weld quality are analyzed using TEM, EBSD, metallographic imaging, and Vickers hardness. Results are coupled with welding parameters to aid in the understanding of the complex material flow and texture gradients within the welds in an effort to optimize welding parameters for high speed processing.« less

Influence of laser parameters in surface texturing of Ti6Al4V and AA2024-T3 alloys

NASA Astrophysics Data System (ADS)

Ahuir-Torres, J. I.; Arenas, M. A.; Perrie, W.; de Damborenea, J.

2018-04-01

Laser texturing can be used for surface modification of metallic alloys in order to improve their properties under service conditions. The generation of textures is determined by the relationship between the laser processing parameters and the physicochemical properties of the alloy to be modified. In the present work the basic mechanism of dimple generation is studied in two alloys of technological interest, titanium alloy Ti6Al4V and aluminium alloy AA2024-T3. Laser treatment was performed using a pulsed solid state Nd: Vanadate (Nd: YVO4) laser with a pulse duration of 10 ps, operating at a wavelength of 1064 nm and 5 kHz repetition rate. Dimpled surface geometries were generated through ultrafast laser ablation while varying pulse energy between 1 μJ and 20 μJ/pulse and with pulse numbers from 10 to 200 pulses per spot. In addition, the generation of Laser Induced Periodic Surface Structures (LIPSS) nanostructures in both alloys, as well as the formation of random nanostructures in the impact zones are discussed.

Effects of fibre type and structure of longissimus lumborum (Ll), biceps femoris (Bf) and semimembranosus (Sm) deer muscles salting with different Nacl addition on proteolysis index and texture of dry-cured meats.

PubMed

Żochowska-Kujawska, J

2016-11-01

The aim of the present study was to describe the effect of fibre type and structure as well as NaCl level on the proteolysis index and texture parameters observed in dry-cured meats produced from individual deer muscles. The biceps femoris, semimembranosus and longissimus lumborum muscles were cut from deer main elements, shaped into blocks by trimming off the edges, cured by adding 4, 6 and 8% of salt (w/w) and dried in a ripening chamber for 29days. The results indicated that deer dry-cured muscles with higher percentage of red fibres (type I) showed higher texture parameters, proteolysis index as well as lower moisture losses than muscles with higher amount of white fibres (type IIB). Dry-cured deer muscles with lower NaCl content showed higher values of proteolysis index and lower hardness, cohesiveness, springiness, and chewiness, as well as lower changes in structure elements. Copyright © 2016. Published by Elsevier Ltd.

Sensory characterisation and consumer acceptability of potassium chloride and sunflower oil addition in small-caliber non-acid fermented sausages with a reduced content of sodium chloride and fat.

PubMed

Mora-Gallego, Héctor; Guàrdia, Maria Dolors; Serra, Xavier; Gou, Pere; Arnau, Jacint

2016-02-01

The effect of the simultaneous reduction of fat proportion (from 20% to 10% and 7%) and added salt (from 2.5% to 1.5%) and the subsequent addition of 0.64% KCl and sunflower oil (1.5% and 3.0%) on the physicochemical, instrumental colour and texture, sensory properties and consumer acceptability of small caliber non-acid fermented sausages (fuet type) was studied. This simultaneous reduction of fat and salt increased weight loss, moisture, water activity (aw), redness, instrumental texture parameters (hardness, chewiness and cohesiveness), sensory attributes (darkness, hardness, elasticity) and the consumer acceptability. The subsequent addition of 0.64% KCl to the leanest batch decreased the aw and barely affected instrumental texture parameters and consumer acceptability. Subsequent sunflower oil addition decreased hardness, chewiness and cohesiveness and increased crumbliness and oil flavour which may decrease the consumer acceptability. The simultaneous reduction of fat and NaCl with the addition of 0.64% KCl was the preferred option by the consumers. Copyright © 2015 Elsevier Ltd. All rights reserved.

A global data set of soil hydraulic properties and sub-grid variability of soil water retention and hydraulic conductivity curves

NASA Astrophysics Data System (ADS)

Montzka, Carsten; Herbst, Michael; Weihermüller, Lutz; Verhoef, Anne; Vereecken, Harry

2017-07-01

Agroecosystem models, regional and global climate models, and numerical weather prediction models require adequate parameterization of soil hydraulic properties. These properties are fundamental for describing and predicting water and energy exchange processes at the transition zone between solid earth and atmosphere, and regulate evapotranspiration, infiltration and runoff generation. Hydraulic parameters describing the soil water retention (WRC) and hydraulic conductivity (HCC) curves are typically derived from soil texture via pedotransfer functions (PTFs). Resampling of those parameters for specific model grids is typically performed by different aggregation approaches such a spatial averaging and the use of dominant textural properties or soil classes. These aggregation approaches introduce uncertainty, bias and parameter inconsistencies throughout spatial scales due to nonlinear relationships between hydraulic parameters and soil texture. Therefore, we present a method to scale hydraulic parameters to individual model grids and provide a global data set that overcomes the mentioned problems. The approach is based on Miller-Miller scaling in the relaxed form by Warrick, that fits the parameters of the WRC through all sub-grid WRCs to provide an effective parameterization for the grid cell at model resolution; at the same time it preserves the information of sub-grid variability of the water retention curve by deriving local scaling parameters. Based on the Mualem-van Genuchten approach we also derive the unsaturated hydraulic conductivity from the water retention functions, thereby assuming that the local parameters are also valid for this function. In addition, via the Warrick scaling parameter λ, information on global sub-grid scaling variance is given that enables modellers to improve dynamical downscaling of (regional) climate models or to perturb hydraulic parameters for model ensemble output generation. The present analysis is based on the ROSETTA PTF of Schaap et al. (2001) applied to the SoilGrids1km data set of Hengl et al. (2014). The example data set is provided at a global resolution of 0.25° at https://doi.org/10.1594/PANGAEA.870605.

Evaluating lubricant performance by 3D profilometry of wear scars

NASA Astrophysics Data System (ADS)

Georgescu, C.; Deleanu, L.; Pirvu, C.

2016-08-01

Due to improvement in analysing surface texture and optical instruments for investigating the texture surface, the authors propose to evaluate the lubricant performance by analysing the change in several 3D parameters in comparison to an analysis on 2D profile. All the surface of the wear scar generated on the four ball machine is investigated and the conclusion is that from the tribological point of view, the 3D parameters reflect better the surface quality evolution after testing. Investigation was done on the wear scars generated on the three fixed balls, for five lubricants: a non-additivated transmission mineral oil (T90), two grades of rapeseed oil (coarse degummed and refined) and two grades of soybean oil (coarse and degummed).

A multi-object statistical atlas adaptive for deformable registration errors in anomalous medical image segmentation

NASA Astrophysics Data System (ADS)

Botter Martins, Samuel; Vallin Spina, Thiago; Yasuda, Clarissa; Falcão, Alexandre X.

2017-02-01

Statistical Atlases have played an important role towards automated medical image segmentation. However, a challenge has been to make the atlas more adaptable to possible errors in deformable registration of anomalous images, given that the body structures of interest for segmentation might present significant differences in shape and texture. Recently, deformable registration errors have been accounted by a method that locally translates the statistical atlas over the test image, after registration, and evaluates candidate objects from a delineation algorithm in order to choose the best one as final segmentation. In this paper, we improve its delineation algorithm and extend the model to be a multi-object statistical atlas, built from control images and adaptable to anomalous images, by incorporating a texture classifier. In order to provide a first proof of concept, we instantiate the new method for segmenting, object-by-object and all objects simultaneously, the left and right brain hemispheres, and the cerebellum, without the brainstem, and evaluate it on MRT1-images of epilepsy patients before and after brain surgery, which removed portions of the temporal lobe. The results show efficiency gain with statistically significant higher accuracy, using the mean Average Symmetric Surface Distance, with respect to the original approach.

Network-scale dynamics of sediment mixtures: how do tectonics affect surface bed texture and channel slope?

NASA Astrophysics Data System (ADS)

Gasparini, N. M.; Bras, R. L.; Tucker, G. E.

2003-04-01

An alluvial channel's slope and bed texture are intimately linked. Along with fluvial discharge, these variables are the key players in setting alluvial transport rates. We know that both channel slope and mean grain size usually decrease downstream, but how sensitive are these variables to tectonic changes? Are basin concavity and downstream fining drastically disrupted during transitions from one tectonic regime to another? We explore these questions using the CHILD numerical landscape evolution model to generate alluvial networks composed of a sand and gravel mixture. The steady-state and transient patterns of both channel slope and sediment texture are investigated. The steady-state patterns in slope and sediment texture are verified independently by solving the erosion equations under equilibrium conditions, i.e. the case when the erosion rate is equal to the uplift rate across the entire landscape. The inclusion of surface texture as a free parameter (as opposed to just channel slope) leads to some surprising results. In all cases, an increase in uplift rate results in channel beds which are finer at equilibrium (for a given drainage area). Higher uplift rates imply larger equilibrium transport rates; this leads to finer channels that have a smaller critical shear stress to entrain material, and therefore more material can be transported for a given discharge (and channel slope). Changes in equilibrium slopes are less intuitive. An increase in uplift rates can cause channel slopes to increase, remain the same, or decrease, depending on model parameter values. In the surprising case in which equilibrium channel slopes decrease with increasing uplift rates, we suggest that surface texture changes more than compensate for the required increase in transport rates, causing channel slopes to decrease. These results highlight the important role of sediment grain size in determining transport rates and caution us against ignoring this important variable in fluvial networks.

Textural features of 18F-FDG PET after two cycles of neoadjuvant chemotherapy can predict pCR in patients with locally advanced breast cancer.

PubMed

Cheng, Lin; Zhang, Jianping; Wang, Yujie; Xu, Xiaoli; Zhang, Yongping; Zhang, Yingjian; Liu, Guangyu; Cheng, Jingyi

2017-08-01

This study was designed to evaluate the utility of textural features for predicting pathological complete response (pCR) to neoadjuvant chemotherapy (NAC). Sixty-one consecutive patients with locally advanced breast cancer underwent 18 F-FDG PET/CT scanning at baseline and after the second course of NAC. Changes to imaging parameters [maximum standardized uptake value (SUV max ), metabolic tumor volume (MTV), total lesion glycolysis (TLG)] and textural features (entropy, coarseness, skewness) between the 2 scans were measured by two independent radiologists. Pathological responses were reviewed by one pathologist, and the significance of the predictive value of each parameter was analyzed using a Chi-squared test. Receiver operating characteristic curve analysis was used to compare the area under the curve (AUC) for each parameter. pCR was observed more often in patients with HER2-positive tumors (22 patients) than in patients with HER2-negative tumors (5 patients) (71.0 vs. 16.7%, p < 0.001). ∆ %SUV max , ∆ %entropy and ∆ %coarseness were significantly useful for differentiating pCR from non-pCR in the HER2-negative group, and the AUCs for these parameters were 0.928, 0.808 and 0.800, respectively (p = 0.003, 0.032 and 0.037). In the HER2-positive group, ∆ %SUV max and ∆ %skewness were moderately useful for predicting pCR, and the respective AUCs were 0.747 and 0.758 (p = 0.033 and 0.026). Although there was no significant difference in the AUCs between groups for these parameters, an additional 3/22 patients in the HER2-positive group with pCR were identified when ∆ %skewness and ∆ %SUV max were considered together (p = 0.031). The absolute values for each parameter before NAC and after 2 cycles cannot predict pCR in our patients. Neither ∆ %MTV nor ∆ %TLG was efficiently predictive of pCR in any group. The early changes in the textural features of 18 F-FDG PET images after two cycles of NAC are predictive of pCR in both HER2-negative and HER2-positive patients; this evidence warrants confirmation by further research.

Compression Algorithm Analysis of In-Situ (S)TEM Video: Towards Automatic Event Detection and Characterization

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

Teuton, Jeremy R.; Griswold, Richard L.; Mehdi, Beata L.

Precise analysis of both (S)TEM images and video are time and labor intensive processes. As an example, determining when crystal growth and shrinkage occurs during the dynamic process of Li dendrite deposition and stripping involves manually scanning through each frame in the video to extract a specific set of frames/images. For large numbers of images, this process can be very time consuming, so a fast and accurate automated method is desirable. Given this need, we developed software that uses analysis of video compression statistics for detecting and characterizing events in large data sets. This software works by converting the datamore » into a series of images which it compresses into an MPEG-2 video using the open source “avconv” utility [1]. The software does not use the video itself, but rather analyzes the video statistics from the first pass of the video encoding that avconv records in the log file. This file contains statistics for each frame of the video including the frame quality, intra-texture and predicted texture bits, forward and backward motion vector resolution, among others. In all, avconv records 15 statistics for each frame. By combining different statistics, we have been able to detect events in various types of data. We have developed an interactive tool for exploring the data and the statistics that aids the analyst in selecting useful statistics for each analysis. Going forward, an algorithm for detecting and possibly describing events automatically can be written based on statistic(s) for each data type.« less

Comprehensive QTL mapping survey dissects the complex fruit texture physiology in apple (Malus x domestica Borkh.).

PubMed

Longhi, Sara; Moretto, Marco; Viola, Roberto; Velasco, Riccardo; Costa, Fabrizio

2012-02-01

Fruit ripening is a complex physiological process in plants whereby cell wall programmed changes occur mainly to promote seed dispersal. Cell wall modification also directly regulates the textural properties, a fundamental aspect of fruit quality. In this study, two full-sib populations of apple, with 'Fuji' as the common maternal parent, crossed with 'Delearly' and 'Pink Lady', were used to understand the control of fruit texture by QTL mapping and in silico gene mining. Texture was dissected with a novel high resolution phenomics strategy, simultaneously profiling both mechanical and acoustic fruit texture components. In 'Fuji × Delearly' nine linkage groups were associated with QTLs accounting from 15.6% to 49% of the total variance, and a highly significant QTL cluster for both textural components was mapped on chromosome 10 and co-located with Md-PG1, a polygalacturonase gene that, in apple, is known to be involved in cell wall metabolism processes. In addition, other candidate genes related to Md-NOR and Md-RIN transcription factors, Md-Pel (pectate lyase), and Md-ACS1 were mapped within statistical intervals. In 'Fuji × Pink Lady', a smaller set of linkage groups associated with the QTLs identified for fruit texture (15.9-34.6% variance) was observed. The analysis of the phenotypic variance over a two-dimensional PCA plot highlighted a transgressive segregation for this progeny, revealing two QTL sets distinctively related to both mechanical and acoustic texture components. The mining of the apple genome allowed the discovery of the gene inventory underlying each QTL, and functional profile assessment unravelled specific gene expression patterns of these candidate genes.

Breast density and parenchymal texture measures as potential risk factors for estrogen-receptor positive breast cancer

NASA Astrophysics Data System (ADS)

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

2014-03-01

Accurate assessment of a woman's risk to develop specific subtypes of breast cancer is critical for appropriate utilization of chemopreventative measures, such as with tamoxifen in preventing estrogen-receptor positive breast cancer. In this context, we investigate quantitative measures of breast density and parenchymal texture, measures of glandular tissue content and tissue structure, as risk factors for estrogen-receptor positive (ER+) breast cancer. Mediolateral oblique (MLO) view digital mammograms of the contralateral breast from 106 women with unilateral invasive breast cancer were retrospectively analyzed. Breast density and parenchymal texture were analyzed via fully-automated software. Logistic regression with feature selection and was performed to predict ER+ versus ER- cancer status. A combined model considering all imaging measures extracted was compared to baseline models consisting of density-alone and texture-alone features. Area under the curve (AUC) of the receiver operating characteristic (ROC) and Delong's test were used to compare the models' discriminatory capacity for receptor status. The density-alone model had a discriminatory capacity of 0.62 AUC (p=0.05). The texture-alone model had a higher discriminatory capacity of 0.70 AUC (p=0.001), which was not significantly different compared to the density-alone model (p=0.37). In contrast the combined density-texture logistic regression model had a discriminatory capacity of 0.82 AUC (p<0.001), which was statistically significantly higher than both the density-alone (p<0.001) and texture-alone regression models (p=0.04). The combination of breast density and texture measures may have the potential to identify women specifically at risk for estrogen-receptor positive breast cancer and could be useful in triaging women into appropriate risk-reduction strategies.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

The "Haptic Finger"- a new device for monitoring skin condition.

PubMed

Tanaka, Mami; Lévêque, Jean Luc; Tagami, Hachiro; Kikuchi, Katsuko; Chonan, Seifi

2003-05-01

Touching the skin is of great importance for the Clinician for assessing roughness, softness, firmness, etc. This type of clinical assessment is very subjective and therefore non-reproducible from one Clinician to another one or even from time to time for the same Clinician. In order to objectively monitor skin texture, we developed a new sensor, placed directly on the Clinician's finger, which generate some electric signal when slid over the skin surface. The base of this Haptic Finger sensor is a thin stainless steel plate on which sponge rubber, PVDF foil, acetate film and gauze are layered. The signal generated by the sensor was filtered and digitally stored before processing. In a first in vitro experiment, the sensor was moved over different skin models (sponge rubber covered by silicon rubber) of varying hardness and roughness. These experiments allowed the definition of two parameters characterizing textures. The first parameter is variance of the signal processed using wavelet analysis, representing an index of roughness. The second parameter is dispersion of the power spectrum density in the frequency domain, corresponding to hardness. To validate these parameters, the Haptic Finger was used to scan skin surfaces of 30 people, 14 of whom displayed a skin disorder: xerosis (n = 5), atopic dermatitis (n = 7), and psoriasis (n = 2). The results obtained by means of the sensor were compared with subjective, clinical evaluations by a Clinician who scored both roughness and hardness of the skin. Good agreement was observed between clinical assessment of the skin and the two parameters generated using the Haptic Finger. Use of this sensor could prove extremely valuable in cosmetic research where skin surface texture (in terms of tactile properties) is difficult to measure.

Tumor heterogeneity measured on F-18 fluorodeoxyglucose positron emission tomography/computed tomography combined with plasma Epstein-Barr Virus load predicts prognosis in patients with primary nasopharyngeal carcinoma.

PubMed

Chan, Sheng-Chieh; Chang, Kai-Ping; Fang, Yu-Hua Dean; Tsang, Ngan-Ming; Ng, Shu-Hang; Hsu, Cheng-Lung; Liao, Chun-Ta; Yen, Tzu-Chen

2017-01-01

Plasma Epstein-Barr virus (EBV) DNA concentrations predict prognosis in patients with nasopharyngeal carcinoma (NPC). Recent evidence also indicates that intratumor heterogeneity on F-18 fluorodeoxyglucose positron emission tomography ( 18 F-FDG PET) scans is predictive of treatment outcomes in different solid malignancies. Here, we sought to investigate the prognostic value of heterogeneity parameters in patients with primary NPC. Retrospective cohort study. We examined 101 patients with primary NPC who underwent pretreatment 18 F-FDG PET/computed tomography. Circulating levels of EBV DNA were measured in all participants. The following PET heterogeneity parameters were collected: histogram-based heterogeneity parameters, second-order texture features (uniformity, contrast, entropy, homogeneity, dissimilarity, inverse difference moment), and higher-order (coarseness, contrast, busyness, complexity, strength) texture features. The median follow-up time was 5.14 years. Total lesion glycolysis (TLG), tumor heterogeneity measured by histogram-based parameter skewness, and the majority of second-order or higher-order texture features were significantly associated with overall survival (OS) and/or recurrence-free survival (RFS). In multivariate analysis, age (P =.005), EBV DNA load (P = .0002), and uniformity (P = .001) independently predicted OS. Only skewness retained the independent prognostic significance for RFS. Tumor stage, standardized uptake value, or TLG did not show an independent association with survival endpoints. The combination of uniformity, EBV DNA load, and age resulted in a more reliable prognostic stratification (P < .001). Tumor heterogeneity is superior to traditional PET parameters for predicting outcomes in primary NPC. The combination of uniformity with EBV DNA load can improve prognostic stratification in this clinical entity. 4 Laryngoscope, 127:E22-E28, 2017. © 2016 The American Laryngological, Rhinological and Otological Society, Inc.

Zone-size nonuniformity of 18F-FDG PET regional textural features predicts survival in patients with oropharyngeal cancer.

PubMed

Cheng, Nai-Ming; Fang, Yu-Hua Dean; Lee, Li-yu; Chang, Joseph Tung-Chieh; Tsan, Din-Li; Ng, Shu-Hang; Wang, Hung-Ming; Liao, Chun-Ta; Yang, Lan-Yan; Hsu, Ching-Han; Yen, Tzu-Chen

2015-03-01

The question as to whether the regional textural features extracted from PET images predict prognosis in oropharyngeal squamous cell carcinoma (OPSCC) remains open. In this study, we investigated the prognostic impact of regional heterogeneity in patients with T3/T4 OPSCC. We retrospectively reviewed the records of 88 patients with T3 or T4 OPSCC who had completed primary therapy. Progression-free survival (PFS) and disease-specific survival (DSS) were the main outcome measures. In an exploratory analysis, a standardized uptake value of 2.5 (SUV 2.5) was taken as the cut-off value for the detection of tumour boundaries. A fixed threshold at 42 % of the maximum SUV (SUVmax 42 %) and an adaptive threshold method were then used for validation. Regional textural features were extracted from pretreatment (18)F-FDG PET/CT images using the grey-level run length encoding method and grey-level size zone matrix. The prognostic significance of PET textural features was examined using receiver operating characteristic (ROC) curves and Cox regression analysis. Zone-size nonuniformity (ZSNU) was identified as an independent predictor of PFS and DSS. Its prognostic impact was confirmed using both the SUVmax 42 % and the adaptive threshold segmentation methods. Based on (1) total lesion glycolysis, (2) uniformity (a local scale texture parameter), and (3) ZSNU, we devised a prognostic stratification system that allowed the identification of four distinct risk groups. The model combining the three prognostic parameters showed a higher predictive value than each variable alone. ZSNU is an independent predictor of outcome in patients with advanced T-stage OPSCC, and may improve their prognostic stratification.

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

Comparison of radiograph-based texture analysis and bone mineral density with three-dimensional microarchitecture of trabecular bone.

PubMed

Ranjanomennahary, P; Ghalila, S Sevestre; Malouche, D; Marchadier, A; Rachidi, M; Benhamou, Cl; Chappard, C

2011-01-01

Hip fracture is a serious health problem and textural methods are being developed to assess bone quality. The authors aimed to perform textural analysis at femur on high-resolution digital radiographs compared to three-dimensional (3D) microarchitecture comparatively to bone mineral density. Sixteen cadaveric femurs were imaged with an x-ray device using a C-MOS sensor. One 17 mm square region of interest (ROI) was selected in the femoral head (FH) and one in the great trochanter (GT). Two-dimensional (2D) textural features from the co-occurrence matrices were extracted. Site-matched measurements of bone mineral density were performed. Inside each ROI, a 16 mm diameter core was extracted. Apparent density (Dapp) and bone volume proportion (BV/TV(Arch)) were measured from a defatted bone core using Archimedes' principle. Microcomputed tomography images of the entire length of the core were obtained (Skyscan 1072) at 19.8 microm of resolution and usual 3D morphometric parameters were computed on the binary volume after calibration from BV/TV(Arch). Then, bone surface/bone volume, trabecular thickness, trabecular separation, and trabecular number were obtained by direct methods without model assumption and the structure model index was calculated. In univariate analysis, the correlation coefficients between 2D textural features and 3D morphological parameters reached 0.83 at the FH and 0.79 at the GT. In multivariate canonical correlation analysis, coefficients of the first component reached 0.95 at the FH and 0.88 at the GT. Digital radiographs, widely available and economically viable, are an alternative method for evaluating bone microarchitectural structure.

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.

Layer texture of hot-rolled BCC metals and its significance for stress-corrosion cracking of main gas pipelines

NASA Astrophysics Data System (ADS)

Perlovich, Yu. A.; Isaenkova, M. G.; Krymskaya, O. A.; Morozov, N. S.

2016-10-01

Based on data of X-ray texture analysis of hot-rolled BCC materials it was shown that the layerwise texture inhomogeneity of products is formed during their manufacturing. The effect can be explained by saturation with interstitial impurities of the surface layer, resulting in dynamical deformation aging (DDA). DDA prevents the dislocation slip under rolling and leads to an increase of lattice parameters in the external layer. The degree of arising inhomogeneity correlates with the tendency of hot-rolled sheets and obtained therefrom tubes to stress-corrosion cracking under exploitation, since internal layers have a compressive effect on external layers, and prevents opening of corrosion cracks at the tube surface.

Electromechanical properties of a textured ceramic material in the (1 - x)PMN- xPT system: Simulation based on the effective-medium method

NASA Astrophysics Data System (ADS)

Aleshin, V. I.; Raevskiĭ, I. P.; Sitalo, E. I.

2008-11-01

A complete set of dielectric, piezoelectric, and elastic parameters for the textured ceramic material 0.67PMN-0.33PT is calculated by the self-consistency method with due regard for the anisotropy and piezoelectric activity of the medium. It is shown that the best piezoelectric properties corresponding to those of a single crystal are observed for the ceramic material with a texture in which all crystallites are oriented parallel to the [001] direction of the parent perovskite cubic cell. The simplest models of the polarization of an untextured ceramic material with a random initial orientation of crystallites are considered. The results obtained are compared with experimental data.

The Scattering Properties of Natural Terrestrial Snows versus Icy Satellite Surfaces

NASA Technical Reports Server (NTRS)

Domingue, Deborah; Hartman, Beth; Verbiscer, Anne

1997-01-01

Our comparisons of the single particle scattering behavior of terrestrial snows and icy satellite regoliths to the laboratory particle scattering measurements of McGuire and Hapke demonstrate that the differences between icy satellite regoliths and their terrestrial counterparts are due to particle structures and textures. Terrestrial snow particle structures define a region in the single particle scattering function parameter space separate from the regions defined by the McGuire and Hapke artificial laboratory particles. The particle structures and textures of the grains composing icy satellites regoliths are not simple or uniform but consist of a variety of particle structure and texture types, some of which may be a combination of the particle types investigated by McGuire and Hapke.

Escape from washing out of baryon number in a two-zero-texture general Zee model compatible with the large mixing angle MSW solution

NASA Astrophysics Data System (ADS)

Hasegawa, K.; Lim, C. S.; Ogure, K.

2003-09-01

We propose a two-zero-texture general Zee model, compatible with the large mixing angle Mikheyev-Smirnov-Wolfenstein solution. The washing out of the baryon number does not occur in this model for an adequate parameter range. We check the consistency of a model with the constraints coming from flavor changing neutral current processes, the recent cosmic microwave background observation, and the Z-burst scenario.

TU-AB-BRA-04: Quantitative Radiomics: Sensitivity of PET Textural Features to Image Acquisition and Reconstruction Parameters Implies the Need for Standards

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

Nyflot, MJ; Yang, F; Byrd, D

Purpose: Despite increased use of heterogeneity metrics for PET imaging, standards for metrics such as textural features have yet to be developed. We evaluated the quantitative variability caused by image acquisition and reconstruction parameters on PET textural features. Methods: PET images of the NEMA IQ phantom were simulated with realistic image acquisition noise. 35 features based on intensity histograms (IH), co-occurrence matrices (COM), neighborhood-difference matrices (NDM), and zone-size matrices (ZSM) were evaluated within lesions (13, 17, 22, 28, 33 mm diameter). Variability in metrics across 50 independent images was evaluated as percent difference from mean for three phantom girths (850,more » 1030, 1200 mm) and two OSEM reconstructions (2 iterations, 28 subsets, 5 mm FWHM filtration vs 6 iterations, 28 subsets, 8.6 mm FWHM filtration). Also, patient sample size to detect a clinical effect of 30% with Bonferroni-corrected α=0.001 and 95% power was estimated. Results: As a class, NDM features demonstrated greatest sensitivity in means (5–50% difference for medium girth and reconstruction comparisons and 10–100% for large girth comparisons). Some IH features (standard deviation, energy, entropy) had variability below 10% for all sensitivity studies, while others (kurtosis, skewness) had variability above 30%. COM and ZSM features had complex sensitivities; correlation, energy, entropy (COM) and zone percentage, short-zone emphasis, zone-size non-uniformity (ZSM) had variability less than 5% while other metrics had differences up to 30%. Trends were similar for sample size estimation; for example, coarseness, contrast, and strength required 12, 38, and 52 patients to detect a 30% effect for the small girth case but 38, 88, and 128 patients in the large girth case. Conclusion: The sensitivity of PET textural features to image acquisition and reconstruction parameters is large and feature-dependent. Standards are needed to ensure that prospective trials which incorporate textural features are properly designed to detect clinical endpoints. Supported by NIH grants R01 CA169072, U01 CA148131, NCI Contract (SAIC-Frederick) 24XS036-004, and a research contract from GE Healthcare.« less

Intratumor heterogeneity characterized by textural features on baseline 18F-FDG PET images predicts response to concomitant radiochemotherapy in esophageal cancer.

PubMed

Tixier, Florent; Le Rest, Catherine Cheze; Hatt, Mathieu; Albarghach, Nidal; Pradier, Olivier; Metges, Jean-Philippe; Corcos, Laurent; Visvikis, Dimitris

2011-03-01

(18)F-FDG PET is often used in clinical routine for diagnosis, staging, and response to therapy assessment or prediction. The standardized uptake value (SUV) in the primary or regional area is the most common quantitative measurement derived from PET images used for those purposes. The aim of this study was to propose and evaluate new parameters obtained by textural analysis of baseline PET scans for the prediction of therapy response in esophageal cancer. Forty-one patients with newly diagnosed esophageal cancer treated with combined radiochemotherapy were included in this study. All patients underwent pretreatment whole-body (18)F-FDG PET. Patients were treated with radiotherapy and alkylatinlike agents (5-fluorouracil-cisplatin or 5-fluorouracil-carboplatin). Patients were classified as nonresponders (progressive or stable disease), partial responders, or complete responders according to the Response Evaluation Criteria in Solid Tumors. Different image-derived indices obtained from the pretreatment PET tumor images were considered. These included usual indices such as maximum SUV, peak SUV, and mean SUV and a total of 38 features (such as entropy, size, and magnitude of local and global heterogeneous and homogeneous tumor regions) extracted from the 5 different textures considered. The capacity of each parameter to classify patients with respect to response to therapy was assessed using the Kruskal-Wallis test (P < 0.05). Specificity and sensitivity (including 95% confidence intervals) for each of the studied parameters were derived using receiver-operating-characteristic curves. Relationships between pairs of voxels, characterizing local tumor metabolic nonuniformities, were able to significantly differentiate all 3 patient groups (P < 0.0006). Regional measures of tumor characteristics, such as size of nonuniform metabolic regions and corresponding intensity nonuniformities within these regions, were also significant factors for prediction of response to therapy (P = 0.0002). Receiver-operating-characteristic curve analysis showed that tumor textural analysis can provide nonresponder, partial-responder, and complete-responder patient identification with higher sensitivity (76%-92%) than any SUV measurement. Textural features of tumor metabolic distribution extracted from baseline (18)F-FDG PET images allow for the best stratification of esophageal carcinoma patients in the context of therapy-response prediction.

MEMS tactile display: from fabrication to characterization

NASA Astrophysics Data System (ADS)

Miki, Norihisa; Kosemura, Yumi; Watanabe, Junpei; Ishikawa, Hiroaki

2014-03-01

We report fabrication and characterization of MEMS-based tactile display that can display users various tactile information, such as Braille codes and surface textures. The display consists of 9 micro-actuators that are equipped with hydraulic displacement amplification mechanism (HDAM) to achieve large enough displacement to stimulate the human tactile receptors. HDAM encapsulates incompressible liquids. We developed a liquid encapsulation process, which we termed as Bonding-in-Liquid Technique, where bonding with a UV-curable resin in glycerin is conducted in the liquid, which prevented interfusion of air bubbles and deformation of the membrane during the bonding. HDAM successfully amplified the displacement generated by piezoelectric actuators by a factor of 6. The display could virtually produce "rough" and "smooth" surfaces, by controlling the vibration frequency, displacement, and the actuation periods of an actuator until the adjacent actuator was driven. We introduced a sample comparison method to characterize the surfaces, which involves human tactile sensation. First, we prepared samples whose mechanical properties are known. We displayed a surface texture to the user by controlling the parameters and then, the user selects a sample that has the most similar surface texture. By doing so, we can correlate the parameters with the mechanical properties of the sample as well as find the sets of the parameters that can provide similar tactile information to many users. The preliminary results with respect to roughness and hardness is presented.

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.

Design and characterization of textured surfaces for applications in the food industry

NASA Astrophysics Data System (ADS)

Lazzini, G.; Romoli, L.; Blunt, L.; Gemini, L.

2017-12-01

The aim of this work is to design, manufacture and characterize surface morphologies on AISI 316L stainless steel produced by a custom designed laser-texturing strategy. Surface textures were characterized at a micrometric dimension in terms of areal parameters compliant with ISO 25178, and correlations between these parameters and processing parameters (e.g. laser energy dose supplied to the material, repetition rate of the laser pulses and scanning velocity) were investigated. Preliminary efforts were devoted to the research of special requirements for surface morphology that, according to the commonly accepted research on the influence of surface roughness on cellular adhesion on surfaces, should discourage the formation of biofilms. The topographical characterization of the surfaces was performed with a coherence scanning interferometer. This approach showed that increasing doses of energy to the surfaces increased the global level of roughness as well as the surface complexity. Moreover, the behavior of the parameters S pk, S vk also indicates that, due to the ablation process, an increase in the energy dose causes an average increase in the height of the highest peaks and in the depth of the deepest dales. The study of the density of peaks S pd showed that none of the surfaces analyzed here seem to perfectly match the conditions dictated by the theories on cellular adhesion to confer anti-biofouling properties. However, this result seems to be mainly due to the limits of the resolving power of coherence scanning interferometry, which does not allow the resolution of sub-micrometric features which could be crucial in the prevention of cellular attachment.

Optimization of Vacuum Impregnation with Calcium Lactate of Minimally Processed Melon and Shelf-Life Study in Real Storage Conditions.

PubMed

Tappi, Silvia; Tylewicz, Urszula; Romani, Santina; Siroli, Lorenzo; Patrignani, Francesca; Dalla Rosa, Marco; Rocculi, Pietro

2016-10-05

Vacuum impregnation (VI) is a processing operation that permits the impregnation of fruit and vegetable porous tissues with a fast and more homogeneous penetration of active compounds compared to the classical diffusion processes. The objective of this research was to investigate the impact on VI treatment with the addition of calcium lactate on qualitative parameters of minimally processed melon during storage. For this aim, this work was divided in 2 parts. Initially, the optimization of process parameters was carried out in order to choose the optimal VI conditions for improving texture characteristics of minimally processed melon that were then used to impregnate melons for a shelf-life study in real storage conditions. On the basis of a 2 3 factorial design, the effect of Calcium lactate (CaLac) concentration between 0% and 5% and of minimum pressure (P) between 20 and 60 MPa were evaluated on color and texture. Processing parameters corresponding to 5% CaLac concentration and 60 MPa of minimum pressure were chosen for the storage study, during which the modifications of main qualitative parameters were evaluated. Despite of the high variability of the raw material, results showed that VI allowed a better maintenance of texture during storage. Nevertheless, other quality traits were negatively affected by the application of vacuum. Impregnated products showed a darker and more translucent appearance on the account of the alteration of the structural properties. Moreover microbial shelf-life was reduced to 4 d compared to the 7 obtained for control and dipped samples. © 2016 Institute of Food Technologists®.

Texture descriptions of lunar surface derived from LOLA data: Kilometer-scale roughness and entropy maps

NASA Astrophysics Data System (ADS)

Li, Bo; Ling, Zongcheng; Zhang, Jiang; Chen, Jian; Wu, Zhongchen; Ni, Yuheng; Zhao, Haowei

2015-11-01

The lunar global texture maps of roughness and entropy are derived at kilometer scales from Digital Elevation Models (DEMs) data obtained by Lunar Orbiter Laser Altimeter (LOLA) aboard on Lunar Reconnaissance Orbiter (LRO) spacecraft. We use statistical moments of a gray-level histogram of elevations in a neighborhood to compute the roughness and entropy value. Our texture descriptors measurements are shown in global maps at multi-sized square neighborhoods, whose length of side is 3, 5, 10, 20, 40 and 80 pixels, respectively. We found that large-scale topographical changes can only be displayed in maps with longer side of neighborhood, but the small scale global texture maps are more disorderly and unsystematic because of more complicated textures' details. Then, the frequency curves of texture maps are made out, whose shapes and distributions are changing as the spatial scales increases. Entropy frequency curve with minimum 3-pixel scale has large fluctuations and six peaks. According to this entropy curve we can classify lunar surface into maria, highlands, different parts of craters preliminarily. The most obvious textures in the middle-scale roughness and entropy maps are the two typical morphological units, smooth maria and rough highlands. For the impact crater, its roughness and entropy value are characterized by a multiple-ring structure obviously, and its different parts have different texture results. In the last, we made a 2D scatter plot between the two texture results of typical lunar maria and highlands. There are two clusters with largest dot density which are corresponded to the lunar highlands and maria separately. In the lunar mare regions (cluster A), there is a high correlation between roughness and entropy, but in the highlands (Cluster B), the entropy shows little change. This could be subjected to different geological processes of maria and highlands forming different landforms.

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.

Statistical Signal Models and Algorithms for Image Analysis

DTIC Science & Technology

1984-10-25

In this report, two-dimensional stochastic linear models are used in developing algorithms for image analysis such as classification, segmentation, and object detection in images characterized by textured backgrounds. These models generate two-dimensional random processes as outputs to which statistical inference procedures can naturally be applied. A common thread throughout our algorithms is the interpretation of the inference procedures in terms of linear prediction

Translating statistical images to text summaries for partially sighted persons on mobile devices: iconic image maps approach

NASA Astrophysics Data System (ADS)

Williams, Godfried B.

2005-03-01

This paper attempts to demonstrate a novel based idea for transforming statistical image data to text using autoassociative and unsupervised artificial neural network and iconic image maps using the shape and texture genetic algorithm, underlying concepts translating the image data to text. Full details of experiments could be assessed at http://www.uel.ac.uk/seis/applications/.

A texture-component Avrami model for predicting recrystallization textures, kinetics and grain size

NASA Astrophysics Data System (ADS)

Raabe, Dierk

2007-03-01

The study presents an analytical model for predicting crystallographic textures and the final grain size during primary static recrystallization of metals using texture components. The kinetics is formulated as a matrix variant of the Johnson-Mehl-Avrami-Kolmogorov equation. The matrix form is required since the kinetic and crystallographic evolution of the microstructure is described in terms of a limited set of growing (recrystallizing) and swept (deformed) texture components. The number of components required (5-10) defines the order of the matrix since the kinetic coupling occurs between all recrystallizing and all deformed components. Each such couple is characterized by corresponding values for the nucleation energy and grain boundary mobility. The values of these parameters can be obtained by analytical or numerical coarse graining according to a renormalization scheme which replaces many individual grains which grow via recrystallization in a deformed texture component by a single equivalent recrystallization texture component or by fitting to experimental data. Each deformed component is further characterized by an average stored deformation energy. Each element of the kinetic matrix, reflecting one of the possible couplings between a deformed and a recrystallizing texture component, is then derived in each time step by a set of two differential equations. The first equation describes the thermally activated nucleation and growth processes for the expanded (free) volume for a particular couple of a deformed and a recrystallizing texture component and the second equation is used for calculating the constrained (real) volume for that couple which corrects the free volume for those portions of the deformation component which were already swept. The new method is particularly developed for the fast and physically based process simulation of recrystallization textures with respect to processing. The present paper introduces the method and applies it to the primary recrystallization of low carbon steels.

Marine Stratocumulus Cloud Fields off the Coast of Southern California Observed Using LANDSAT Imagery. Part II: Textural Analysis.

NASA Astrophysics Data System (ADS)

Welch, R. M.; Sengupta, S. K.; Kuo, K. S.

1988-04-01

Statistical measures of the spatial distributions of gray levels (cloud reflectivities) are determined for LANDSAT Multispectral Scanner digital data. Textural properties for twelve stratocumulus cloud fields, seven cumulus fields, and two cirrus fields are examined using the Spatial Gray Level Co-Occurrence Matrix method. The co-occurrence statistics are computed for pixel separations ranging from 57 m to 29 km and at angles of 0°, 45°, 90° and 135°. Nine different textual measures are used to define the cloud field spatial relationships. However, the measures of contrast and correlation appear to be most useful in distinguishing cloud structure.Cloud field macrotexture describes general cloud field characteristics at distances greater than the size of typical cloud elements. It is determined from the spatial asymptotic values of the texture measures. The slope of the texture curves at small distances provides a measure of the microtexture of individual cloud cells. Cloud fields composed primarily of small cells have very steep slopes and reach their asymptotic values at short distances from the origin. As the cells composing the cloud field grow larger, the slope becomes more gradual and the asymptotic distance increases accordingly. Low asymptotic values of correlation show that stratocumulus cloud fields have no large scale organized structure.Besides the ability to distinguish cloud field structure, texture appears to be a potentially valuable tool in cloud classification. Stratocumulus clouds are characterized by low values of angular second moment and large values of entropy. Cirrus clouds appear to have extremely low values of contrast, low values of entropy, and very large values of correlation.Finally, we propose that sampled high spatial resolution satellite data be used in conjunction with coarser resolution operational satellite data to detect and identify cloud field structure and directionality and to locate regions of subresolution scale cloud contamination.

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.

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

Vibrational algorithms for quantitative crystallographic analyses of hydroxyapatite-based biomaterials: I, theoretical foundations.

PubMed

Pezzotti, Giuseppe; Zhu, Wenliang; Boffelli, Marco; Adachi, Tetsuya; Ichioka, Hiroaki; Yamamoto, Toshiro; Marunaka, Yoshinori; Kanamura, Narisato

2015-05-01

The Raman spectroscopic method has quantitatively been applied to the analysis of local crystallographic orientation in both single-crystal hydroxyapatite and human teeth. Raman selection rules for all the vibrational modes of the hexagonal structure were expanded into explicit functions of Euler angles in space and six Raman tensor elements (RTE). A theoretical treatment has also been put forward according to the orientation distribution function (ODF) formalism, which allows one to resolve the statistical orientation patterns of the nm-sized hydroxyapatite crystallite comprised in the Raman microprobe. Close-form solutions could be obtained for the Euler angles and their statistical distributions resolved with respect to the direction of the average texture axis. Polarized Raman spectra from single-crystalline hydroxyapatite and textured polycrystalline (teeth enamel) samples were compared, and a validation of the proposed Raman method could be obtained through confirming the agreement between RTE values obtained from different samples.

Dielectric properties of soils as a function of moisture content

NASA Technical Reports Server (NTRS)

Cihlar, J.; Ulaby, F. T.

1974-01-01

Soil dielectric constant measurements are reviewed and the dependence of the dielectric constant on various soil parameters is determined. Moisture content is given special attention because of its practical significance in remote sensing and because it represents the single most influential parameter as far as soil dielectric properties are concerned. Relative complex dielectric constant curves are derived as a function of volumetric soil water content at three frequencies (1.3 GHz, 4.0 GHz, and 10.0 GHz) for each of three soil textures (sand, loam, and clay). These curves, presented in both tabular and graphical form, were chosen as representative of the reported experimental data. Calculations based on these curves showed that the power reflection coefficient and emissivity, unlike skin depth, vary only slightly as a function of frequency and soil texture.

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

NASA Astrophysics Data System (ADS)

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

2015-05-01

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

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

Gaul, Alexander; Holzinger, Dennis; Müglich, Nicolas David

A magnetic domain texture has been deterministically engineered in a topographically flat exchange-biased (EB) thin film system. The texture consists of long-range periodically arranged unit cells of four individual domains, characterized by individual anisotropies, individual geometry, and with non-collinear remanent magnetizations. The texture has been engineered by a sequence of light-ion bombardment induced magnetic patterning of the EB layer system. The magnetic texture's in-plane spatial magnetization distribution and the corresponding domain walls have been characterized by scanning electron microscopy with polarization analysis (SEMPA). The influence of magnetic stray fields emerging from neighboring domain walls and the influence of the differentmore » anisotropies of the adjacent domains on the Néel type domain wall core's magnetization rotation sense and widths were investigated. It is shown that the usual energy degeneracy of clockwise and counterclockwise rotating magnetization through the walls is revoked, suppressing Bloch lines along the domain wall. Estimates of the domain wall widths for different domain configurations based on material parameters determined by vibrating sample magnetometry were quantitatively compared to the SEMPA data.« less

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.

Use of biomimetic hexagonal surface texture in friction against lubricated skin.

PubMed

Tsipenyuk, Alexey; Varenberg, Michael

2014-05-06

Smooth contact pads that evolved in insects, amphibians and mammals to enhance the attachment abilities of the animals' feet are often dressed with surface micropatterns of different shapes that act in the presence of a fluid secretion. One of the most striking surface patterns observed in contact pads of these animals is based on a hexagonal texture, which is recognized as a friction-oriented feature capable of suppressing both stick-slip and hydroplaning while enabling friction tuning. Here, we compare this design of natural friction surfaces to textures developed for working in similar conditions in disposable safety razors. When slid against lubricated human skin, the hexagonal surface texture is capable of generating about twice the friction of its technical competitors, which is related to it being much more effective at channelling of the lubricant fluid out of the contact zone. The draining channel shape and contact area fraction are found to be the most important geometrical parameters governing the fluid drainage rate.

Large-scale structure in a texture-seeded cold dark matter cosmogony

NASA Technical Reports Server (NTRS)

Park, Changbom; Spergel, David N.; Turok, Nail

1991-01-01

This paper studies the formation of large-scale structure by global texture in a flat universe dominated by cold dark matter. A code for evolution of the texture fields was combined with an N-body code for evolving the dark matter. The results indicate some promising aspects: with only one free parameter, the observed galaxy-galaxy correlation function is reproduced, clusters of galaxies are found to be significantly clustered on a scale of 20-50/h Mpc, and coherent structures of over 50/h Mpc in the galaxy distribution were found. The large-scale streaming motions observed are in good agreement with the observations: the average magnitude of the velocity field smoothed over 30/h Mpc is 430 km/sec. Global texture produces a cosmic Mach number that is compatible with observation. Also, significant evolution of clusters at low redshift was seen. Possible problems for the theory include too high velocity dispersions in clusters, and voids which are not as empty as those observed.

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.

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

PubMed

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

2015-01-01

Tablet disintegration characterisation is used in pharmaceutical research, development, and quality control. Standard methods used to characterise tablet disintegration are often dependent on visual observation in measurement of disintegration times. This presents a challenge for disintegration studies of tablets in opaque, physiologically relevant media that could be useful for tablet formulation optimisation. This study has explored an application of texture analysis disintegration testing, a non-visual, quantitative means of determining tablet disintegration end point, by analysing the disintegration behaviour of two tablet formulations in opaque media. In this study, the disintegration behaviour of one tablet formulation manufactured in-house, and Sybedia Flashtab placebo tablets in water, bovine, and human milk were characterised. A novel method is presented to characterise the disintegration process and to quantify the disintegration end points of the tablets in various media using load data generated by a texture analyser probe. The disintegration times in the different media were found to be statistically different (P<0.0001) from one another for both tablet formulations using one-way ANOVA. Using the Tukey post-hoc test, the Sybedia Flashtab placebo tablets were found not to have statistically significant disintegration times from each other in human versus bovine milk (adjusted P value 0.1685). Copyright © 2015 Elsevier B.V. All rights reserved.

Texture feature extraction based on wavelet transform and gray-level co-occurrence matrices applied to osteosarcoma diagnosis.

PubMed

Hu, Shan; Xu, Chao; Guan, Weiqiao; Tang, Yong; Liu, Yana

2014-01-01

Osteosarcoma is the most common malignant bone tumor among children and adolescents. In this study, image texture analysis was made to extract texture features from bone CR images to evaluate the recognition rate of osteosarcoma. To obtain the optimal set of features, Sym4 and Db4 wavelet transforms and gray-level co-occurrence matrices were applied to the image, with statistical methods being used to maximize the feature selection. To evaluate the performance of these methods, a support vector machine algorithm was used. The experimental results demonstrated that the Sym4 wavelet had a higher classification accuracy (93.44%) than the Db4 wavelet with respect to osteosarcoma occurrence in the epiphysis, whereas the Db4 wavelet had a higher classification accuracy (96.25%) for osteosarcoma occurrence in the diaphysis. Results including accuracy, sensitivity, specificity and ROC curves obtained using the wavelets were all higher than those obtained using the features derived from the GLCM method. It is concluded that, a set of texture features can be extracted from the wavelets and used in computer-aided osteosarcoma diagnosis systems. In addition, this study also confirms that multi-resolution analysis is a useful tool for texture feature extraction during bone CR image processing.

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.

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

PubMed

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

2017-10-01

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

Monitoring of bone regeneration process by means of texture analysis

NASA Astrophysics Data System (ADS)

Kokkinou, E.; Boniatis, I.; Costaridou, L.; Saridis, A.; Panagiotopoulos, E.; Panayiotakis, G.

2009-09-01

An image analysis method is proposed for the monitoring of the regeneration of the tibial bone. For this purpose, 130 digitized radiographs of 13 patients, who had undergone tibial lengthening by the Ilizarov method, were studied. For each patient, 10 radiographs, taken at an equal number of postoperative successive time moments, were available. Employing available software, 3 Regions Of Interest (ROIs), corresponding to the: (a) upper, (b) central, and (c) lower aspect of the gap, where bone regeneration was expected to occur, were determined on each radiograph. Employing custom developed algorithms: (i) a number of textural features were generated from each of the ROIs, and (ii) a texture-feature based regression model was designed for the quantitative monitoring of the bone regeneration process. Statistically significant differences (p < 0.05) were derived for the initial and the final textural features values, generated from the first and the last postoperatively obtained radiographs, respectively. A quadratic polynomial regression equation fitted data adequately (r2 = 0.9, p < 0.001). The suggested method may contribute to the monitoring of the tibial bone regeneration process.

Scatter metrology of photovoltaic textured surfaces

NASA Astrophysics Data System (ADS)

Stover, John C.; Hegstrom, Eric L.

2010-09-01

In recent years it has become common practice to texture many of the layered surfaces making up photovoltaic cells in order to increase light absorption and efficiency. Profilometry has been used to characterize the texture, but this is not satisfactory for in-line production systems which move surfaces too fast for that measurement. Scatterometry has been used successfully to measure roughness for many years. Its advantages include low cost, non-contact measurement and insensitivity to vibration; however, it also has some limitations. This paper presents scatter measurements made on a number of photovoltaic samples using two different scatterometers. It becomes clear that in many cases the surface roughness exceeds the optical smoothness limit (required to calculate surface statistics from scatter), but it is also clear that scatter measurement is a fast, sensitive indicator of texture and can be used to monitor whether design specifications are being met. A third key point is that there is a lot of surface dependent information available in the angular variations of the measured scatter. When the surface is inspected by integrating the scatter signal (often called a "Haze" measurement) this information is lost.

New best estimates for radionuclide solid-liquid distribution coefficients in soils. Part 2: naturally occurring radionuclides.

PubMed

Vandenhove, H; Gil-García, C; Rigol, A; Vidal, M

2009-09-01

Predicting the transfer of radionuclides in the environment for normal release, accidental, disposal or remediation scenarios in order to assess exposure requires the availability of an important number of generic parameter values. One of the key parameters in environmental assessment is the solid liquid distribution coefficient, K(d), which is used to predict radionuclide-soil interaction and subsequent radionuclide transport in the soil column. This article presents a review of K(d) values for uranium, radium, lead, polonium and thorium based on an extensive literature survey, including recent publications. The K(d) estimates were presented per soil groups defined by their texture and organic matter content (Sand, Loam, Clay and Organic), although the texture class seemed not to significantly affect K(d). Where relevant, other K(d) classification systems are proposed and correlations with soil parameters are highlighted. The K(d) values obtained in this compilation are compared with earlier review data.

Gluten-Free Precooked Rice-Yellow Pea Pasta: Effect of Extrusion-Cooking Conditions on Phenolic Acids Composition, Selected Properties and Microstructure.

PubMed

Bouasla, Abdallah; Wójtowicz, Agnieszka; Zidoune, Mohammed Nasereddine; Olech, Marta; Nowak, Renata; Mitrus, Marcin; Oniszczuk, Anna

2016-05-01

Rice/yellow pea flour blend (2/1 ratio) was used to produce gluten-free precooked pasta using a single-screw modified extrusion-cooker TS-45. The effect of moisture content (28%, 30%, and 32%) and screw speed (60, 80, and 100 rpm) on some quality parameters was assessed. The phenolic acids profile and selected pasta properties were tested, like pasting properties, water absorption capacity, cooking loss, texture characteristics, microstructure, and sensory overall acceptability. Results indicated that dough moisture content influenced all tested quality parameters of precooked pasta except firmness. Screw speed showed an effect only on some quality parameters. The extrusion-cooking process at 30% of dough moisture with 80 rpm is appropriate to obtain rice-yellow pea precooked pasta with high content of phenolics and adequate quality. These pasta products exhibited firm texture, low stickiness, and regular and compact interne structure confirmed by high score in sensory overall acceptability. © 2016 Institute of Food Technologists®

Effect of some plant starches and carrageenan as fat substitutes in chicken patties.

PubMed

Das, S K; Prabhakaran, P; Tanwar, V K; Biswas, S

2015-07-01

This study evaluated the effect of different flours on the physicochemical, textural, and sensory properties of chicken patties. pH; cooking yield %; water holding capacity (WHC); proximate analysis (cooked); cholesterol content; and storage stability studies of control (Con) and sorghum flour (SF; 10%w/w), finger millet flour (FMF; 10%w/w), and carrageenan (Cgn; 0.5% w/w) treated chicken patties were observed in this study. Texture profile analysis (TPA) parameters like hardness, springiness, cohesiveness, gumminess, chewiness, and sensory parameters were estimated on cooked patties. Highly significant (P < 0.01) difference in fat %, total ash %, and cholesterol content; significant (P < 0.05) difference in moisture % (cooked); and no significant (P > 0.05) difference in pH, WHC, and protein % among control and treatments were noticed. Storage stability was dependent on treatments and storage periods. Significant difference (P < 0.05) was observed in different TPA parameters among the treatments, except for hardness value. Sensory scores showed no significant difference (P > 0.05) between Con and treatments.