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

PubMed

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

2018-06-19

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

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

Validation of CBCT for the computation of textural biomarkers

NASA Astrophysics Data System (ADS)

Paniagua, Beatriz; Ruellas, Antonio C.; Benavides, Erika; Marron, Steve; Wolford, Larry; Cevidanes, Lucia

2015-03-01

Osteoarthritis (OA) is associated with significant pain and 42.6% of patients with TMJ disorders present with evidence of TMJ OA. However, OA diagnosis and treatment remain controversial, since there are no clear symptoms of the disease. The subchondral bone in the TMJ is believed to play a major role in the progression of OA. We hypothesize that the textural imaging biomarkers computed in high resolution Conebeam CT (hr- CBCT) and μCT scans are comparable. The purpose of this study is to test the feasibility of computing textural imaging biomarkers in-vivo using hr-CBCT, compared to those computed in μCT scans as our Gold Standard. Specimens of condylar bones obtained from condylectomies were scanned using μCT and hr- CBCT. Nine different textural imaging biomarkers (four co-occurrence features and five run-length features) from each pair of μCT and hr-CBCT were computed and compared. Pearson correlation coefficients were computed to compare textural biomarkers values of μCT and hr-CBCT. Four of the nine computed textural biomarkers showed a strong positive correlation between biomarkers computed in μCT and hr-CBCT. Higher correlations in Energy and Contrast, and in GLN (grey-level non-uniformity) and RLN (run length non-uniformity) indicate quantitative texture features can be computed reliably in hr-CBCT, when compared with μCT. The textural imaging biomarkers computed in-vivo hr-CBCT have captured the structure, patterns, contrast between neighboring regions and uniformity of healthy and/or pathologic subchondral bone. The ability to quantify bone texture non-invasively now makes it possible to evaluate the progression of subchondral bone alterations, in TMJ OA.

Validation of CBCT for the computation of textural biomarkers

PubMed Central

Paniagua, Beatriz; Ruellas, Antonio Carlos; Benavides, Erika; Marron, Steve; Woldford, Larry; Cevidanes, Lucia

2015-01-01

Osteoarthritis (OA) is associated with significant pain and 42.6% of patients with TMJ disorders present with evidence of TMJ OA. However, OA diagnosis and treatment remain controversial, since there are no clear symptoms of the disease. The subchondral bone in the TMJ is believed to play a major role in the progression of OA. We hypothesize that the textural imaging biomarkers computed in high resolution Conebeam CT (hr-CBCT) and μCT scans are comparable. The purpose of this study is to test the feasibility of computing textural imaging biomarkers in-vivo using hr-CBCT, compared to those computed in μCT scans as our Gold Standard. Specimens of condylar bones obtained from condylectomies were scanned using μCT and hr-CBCT. Nine different textural imaging biomarkers (four co-occurrence features and five run-length features) from each pair of μCT and hr-CBCT were computed and compared. Pearson correlation coefficients were computed to compare textural biomarkers values of μCT and hr-CBCT. Four of the nine computed textural biomarkers showed a strong positive correlation between biomarkers computed in μCT and hr-CBCT. Higher correlations in Energy and Contrast, and in GLN (grey-level non-uniformity) and RLN (run length non-uniformity) indicate quantitative texture features can be computed reliably in hr-CBCT, when compared with μCT. The textural imaging biomarkers computed in-vivo hr-CBCT have captured the structure, patterns, contrast between neighboring regions and uniformity of healthy and/or pathologic subchondral bone. The ability to quantify bone texture non-invasively now makes it possible to evaluate the progression of subchondral bone alterations, in TMJ OA. PMID:26085710

Validation of CBCT for the computation of textural biomarkers.

PubMed

Paniagua, Beatriz; Ruellas, Antonio Carlos; Benavides, Erika; Marron, Steve; Woldford, Larry; Cevidanes, Lucia

2015-03-17

Osteoarthritis (OA) is associated with significant pain and 42.6% of patients with TMJ disorders present with evidence of TMJ OA. However, OA diagnosis and treatment remain controversial, since there are no clear symptoms of the disease. The subchondral bone in the TMJ is believed to play a major role in the progression of OA. We hypothesize that the textural imaging biomarkers computed in high resolution Conebeam CT (hr-CBCT) and μCT scans are comparable. The purpose of this study is to test the feasibility of computing textural imaging biomarkers in-vivo using hr-CBCT, compared to those computed in μCT scans as our Gold Standard. Specimens of condylar bones obtained from condylectomies were scanned using μCT and hr-CBCT. Nine different textural imaging biomarkers (four co-occurrence features and five run-length features) from each pair of μCT and hr-CBCT were computed and compared. Pearson correlation coefficients were computed to compare textural biomarkers values of μCT and hr-CBCT. Four of the nine computed textural biomarkers showed a strong positive correlation between biomarkers computed in μCT and hr-CBCT. Higher correlations in Energy and Contrast, and in GLN (grey-level non-uniformity) and RLN (run length non-uniformity) indicate quantitative texture features can be computed reliably in hr-CBCT, when compared with μCT. The textural imaging biomarkers computed in-vivo hr-CBCT have captured the structure, patterns, contrast between neighboring regions and uniformity of healthy and/or pathologic subchondral bone. The ability to quantify bone texture non-invasively now makes it possible to evaluate the progression of subchondral bone alterations, in TMJ OA.

CT-based texture analysis potentially provides prognostic information complementary to interim fdg-pet for patients with hodgkin's and aggressive non-hodgkin's lymphomas.

PubMed

Ganeshan, B; Miles, K A; Babikir, S; Shortman, R; Afaq, A; Ardeshna, K M; Groves, A M; Kayani, I

2017-03-01

The purpose of this study was to investigate the ability of computed tomography texture analysis (CTTA) to provide additional prognostic information in patients with Hodgkin's lymphoma (HL) and high-grade non-Hodgkin's lymphoma (NHL). This retrospective, pilot-study approved by the IRB comprised 45 lymphoma patients undergoing routine 18F-FDG-PET-CT. Progression-free survival (PFS) was determined from clinical follow-up (mean-duration: 40 months; range: 10-62 months). Non-contrast-enhanced low-dose CT images were submitted to CTTA comprising image filtration to highlight features of different sizes followed by histogram-analysis using kurtosis. Prognostic value of CTTA was compared to PET FDG-uptake value, tumour-stage, tumour-bulk, lymphoma-type, treatment-regime, and interim FDG-PET (iPET) status using Kaplan-Meier analysis. Cox regression analysis determined the independence of significantly prognostic imaging and clinical features. A total of 27 patients had aggressive NHL and 18 had HL. Mean PFS was 48.5 months. There was no significant difference in pre-treatment CTTA between the lymphoma sub-types. Kaplan-Meier analysis found pre-treatment CTTA (medium feature scale, p=0.010) and iPET status (p<0.001) to be significant predictors of PFS. Cox analysis revealed that an interaction between pre-treatment CTTA and iPET status was the only independent predictor of PFS (HR: 25.5, 95% CI: 5.4-120, p<0.001). Specifically, pre-treatment CTTA risk stratified patients with negative iPET. CTTA can potentially provide prognostic information complementary to iPET for patients with HL and aggressive NHL. • CT texture-analysis (CTTA) provides prognostic information complementary to interim FDG-PET in Lymphoma. • Pre-treatment CTTA and interim PET status were significant predictors of progression-free survival. • Patients with negative interim PET could be further stratified by pre-treatment CTTA. • Provide precision surveillance where additional imaging reserved for patients at greatest recurrence-risk. • Assists in risk-adapted treatment strategy based on interim PET and CTTA.

Magnetization-prepared rapid acquisition with gradient echo magnetic resonance imaging signal and texture features for the prediction of mild cognitive impairment to Alzheimer’s disease progression

PubMed Central

Martinez-Torteya, Antonio; Rodriguez-Rojas, Juan; Celaya-Padilla, José M.; Galván-Tejada, Jorge I.; Treviño, Victor; Tamez-Peña, Jose

2014-01-01

Abstract. Early diagnoses of Alzheimer’s disease (AD) would confer many benefits. Several biomarkers have been proposed to achieve such a task, where features extracted from magnetic resonance imaging (MRI) have played an important role. However, studies have focused exclusively on morphological characteristics. This study aims to determine whether features relating to the signal and texture of the image could predict mild cognitive impairment (MCI) to AD progression. Clinical, biological, and positron emission tomography information and MRI images of 62 subjects from the AD neuroimaging initiative were used in this study, extracting 4150 features from each MRI. Within this multimodal database, a feature selection algorithm was used to obtain an accurate and small logistic regression model, generated by a methodology that yielded a mean blind test accuracy of 0.79. This model included six features, five of them obtained from the MRI images, and one obtained from genotyping. A risk analysis divided the subjects into low-risk and high-risk groups according to a prognostic index. The groups were statistically different (p-value=2.04e−11). These results demonstrated that MRI features related to both signal and texture add MCI to AD predictive power, and supported the ongoing notion that multimodal biomarkers outperform single-modality ones. PMID:26158047

Rheological changes induced by clast fragmentation in debris flows

NASA Astrophysics Data System (ADS)

Caballero, Lizeth; Sarocchi, Damiano; Soto, Enrique; Borselli, Lorenzo

2014-09-01

On the basis of rotating drum analogue experiments, we describe a fragmentation process acting within debris flows during transport and its influence on rheologic behavior. Our hypothesis is based on a detailed textural analysis including granulometry, clast morphology, and rheologic properties of the fluid matrix. Results of the experiments point out that breakage of certain granulometric classes produces fine particles like fine sand and silt. The population growth of fine clasts with time leads to an increase in yield strength and viscosity that progressively modifies the rheologic behavior. From a textural point of view, this is reflected in a bimodal granulometric distribution. Up to now this characteristic has been explained as the effect of bulking and/or sedimentation processes during transport. Our experimental results show that the type of fragmentation depends on particle size and is the consequence of strong clast-clast interaction and clast-fluid interactions. Coarse particles develop small fractures which cause the loss of sharp edges and asperities. Medium-sized particles develop through-going fractures that cause them to break apart. The latter process explains why intermediate granulometric classes progressively diminish with time in debris flows. Analogue experiments enable us to study the efficacy of clast fragmentation in modifying the textural character and flow behavior of debris flows without the influence of external factors such as erosion and sedimentation. The obtained results constitute the base of a new approach for modeling debris flow dynamics.

MRI signal and texture features for the prediction of MCI to Alzheimer's disease progression

NASA Astrophysics Data System (ADS)

Martínez-Torteya, Antonio; Rodríguez-Rojas, Juan; Celaya-Padilla, José M.; Galván-Tejada, Jorge I.; Treviño, Victor; Tamez-Peña, José G.

2014-03-01

An early diagnosis of Alzheimer's disease (AD) confers many benefits. Several biomarkers from different information modalities have been proposed for the prediction of MCI to AD progression, where features extracted from MRI have played an important role. However, studies have focused almost exclusively in the morphological characteristics of the images. This study aims to determine whether features relating to the signal and texture of the image could add predictive power. Baseline clinical, biological and PET information, and MP-RAGE images for 62 subjects from the Alzheimer's Disease Neuroimaging Initiative were used in this study. Images were divided into 83 regions and 50 features were extracted from each one of these. A multimodal database was constructed, and a feature selection algorithm was used to obtain an accurate and small logistic regression model, which achieved a cross-validation accuracy of 0.96. These model included six features, five of them obtained from the MP-RAGE image, and one obtained from genotyping. A risk analysis divided the subjects into low-risk and high-risk groups according to a prognostic index, showing that both groups are statistically different (p-value of 2.04e-11). The results demonstrate that MRI features related to both signal and texture, add MCI to AD predictive power, and support the idea that multimodal biomarkers outperform single-modality biomarkers.

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

PubMed

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

2017-06-01

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

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

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.

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

PubMed

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

2017-11-09

The purpose of this study was to investigate the diagnostic performance of mammographic texture analysis in the differential diagnosis of benign and malignant breast tumors. Digital mammography images were obtained from the Picture Archiving and Communication System at our institute. Texture features of mammographic images were calculated. Mann-Whitney U test was used to identify differences between the benign and malignant group. The receiver operating characteristic (ROC) curve analysis was used to assess the diagnostic performance of texture features. Significant differences of texture features of histogram, gray-level co-occurrence matrix (GLCM) and run length matrix (RLM) were found between the benign and malignant breast group (P < .05). The area under the ROC (AUROC) of histogram, GLCM, and RLM were 0.800, 0.787, and 0.761, with no differences between them (P > .05). The AUROCs of imaging-based diagnosis, texture analysis, and imaging-based diagnosis combined with texture analysis were 0.873, 0.863, and 0.961, respectively. When imaging-based diagnosis was combined with texture analysis, the AUROC was higher than that of imaging-based diagnosis or texture analysis (P < .05). Mammographic texture analysis is a reliable technique for differential diagnosis of benign and malignant breast tumors. Furthermore, the combination of imaging-based diagnosis and texture analysis can significantly improve diagnostic performance. Copyright © 2017 Elsevier Inc. All rights reserved.

Wavelet-based image analysis system for soil texture analysis

NASA Astrophysics Data System (ADS)

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

2003-05-01

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

Maillard-reaction-induced modification and aggregation of proteins and hardening of texture in protein bar model systems.

PubMed

Zhou, Peng; Guo, Mufan; Liu, Dasong; Liu, Xiaoming; Labuza, Teodore P

2013-03-01

The hardening of high-protein bars causes problems in their acceptability to consumers. The objective of this study was to determine the progress of the Maillard reaction in model systems of high-protein nutritional bars containing reducing sugars, and to illustrate the influences of the Maillard reaction on the modification and aggregation of proteins and the hardening of bar matrices during storage. The progress of the Maillard reaction, glycation, and aggregation of proteins, and textural changes in bar matrices were investigated during storage at 25, 35, and 45 °C. The initial development of the Maillard reaction caused little changes in hardness; however, further storage resulted in dramatic modification of protein with formation of high-molecular-weight polymers, resulting in the hardening in texture. The replacement of reducing sugars with nonreducing ingredients such as sugar alcohols in the formula minimized the changes in texture. The hardening of high-protein bars causes problems in their acceptability to consumers. Maillard reaction is one of the mechanisms contributing to the hardening of bar matrix, particularly for the late stage of storage. The replacement of reducing sugars with nonreducing ingredients such as sugar alcohols in the formula will minimize the changes in texture. © 2013 Institute of Food Technologists®

Development of Thin-Walled Magnesium Alloy Extrusions for Improved Crash Performance Based Upon Texture Control

NASA Astrophysics Data System (ADS)

Williams, Bruce W.; Agnew, Sean R.; Klein, Robert W.; McKinley, Jonathan

Recent investigations suggest that it is possible to achieve dramatic modifications to both strength and ductility of magnesium alloys through a combination of alloying, grain refinement, and texture control. The current work explores the possibility of altering the texture in extruded thin-walled magnesium alloy tubes for improved ductility during axial crush in which energy is absorbed through progressive buckling. The texture evolution was predicted using the viscoplastic self-consistent (VPSC) crystal plasticity model, with strain path input from continuum-based finite element simulations of extrusion. A limited diversity of textures can be induced by altering the strain path through the extrusion die design. In some cases, such as for simple bar extrusion, the textures predicted can be connected with simple shape change. In other cases, a subtle influence of strain path involving shear-reverse-shear is predicted. The most promising textures predicted for a variety of strain paths are selected for subsequent experimental study.

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

PubMed

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

2018-06-01

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

ADC texture—An imaging biomarker for high-grade glioma?

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

Brynolfsson, Patrik; Hauksson, Jón; Karlsson, Mikael

2014-10-15

Purpose: Survival for high-grade gliomas is poor, at least partly explained by intratumoral heterogeneity contributing to treatment resistance. Radiological evaluation of treatment response is in most cases limited to assessment of tumor size months after the initiation of therapy. Diffusion-weighted magnetic resonance imaging (MRI) and its estimate of the apparent diffusion coefficient (ADC) has been widely investigated, as it reflects tumor cellularity and proliferation. The aim of this study was to investigate texture analysis of ADC images in conjunction with multivariate image analysis as a means for identification of pretreatment imaging biomarkers. Methods: Twenty-three consecutive high-grade glioma patients were treatedmore » with radiotherapy (2 Gy/60 Gy) with concomitant and adjuvant temozolomide. ADC maps and T1-weighted anatomical images with and without contrast enhancement were collected prior to treatment, and (residual) tumor contrast enhancement was delineated. A gray-level co-occurrence matrix analysis was performed on the ADC maps in a cuboid encapsulating the tumor in coronal, sagittal, and transversal planes, giving a total of 60 textural descriptors for each tumor. In addition, similar examinations and analyses were performed at day 1, week 2, and week 6 into treatment. Principal component analysis (PCA) was applied to reduce dimensionality of the data, and the five largest components (scores) were used in subsequent analyses. MRI assessment three months after completion of radiochemotherapy was used for classifying tumor progression or regression. Results: The score scatter plots revealed that the first, third, and fifth components of the pretreatment examinations exhibited a pattern that strongly correlated to survival. Two groups could be identified: one with a median survival after diagnosis of 1099 days and one with 345 days, p = 0.0001. Conclusions: By combining PCA and texture analysis, ADC texture characteristics were identified, which seems to hold pretreatment prognostic information, independent of known prognostic factors such as age, stage, and surgical procedure. These findings encourage further studies with a larger patient cohort.« less

Structural evolution and growth mechanisms of RF-magnetron sputter-deposited hydroxyapatite thin films on the basis of unified principles

NASA Astrophysics Data System (ADS)

Ivanova, Anna A.; Surmeneva, Maria A.; Surmenev, Roman A.; Depla, Diederik

2017-12-01

The structural features of RF-magnetron sputter-deposited hydroxyapatite (HA) coatings are investigated in order to reveal the effect of the working gas composition and the sample position of the substrate relative to the target erosion zone. The film properties were observed to change as a result of bombardment with energetic ions. XRD analysis of the coated substrates indicates that with the increase of the ion-to-atom ratio, the fiber texture changes from a mixed (11 2 bar 2) + (0002) over (0002) orientation, finally reaching a (30 3 bar 0) out-of-plane orientation at high ion-to-atom ratios. TEM reveals that the microstructure of the HA coating consists of columnar grains and differs with the coating texture. The contribution of Ji/Ja to the development of microstructure and texture of the HA coating is schematically represented and discussed. The obtained results may contribute substantially to the progress of research into the development of HA coatings with tailored properties, and these coatings may be applied on the surfaces of metal implants used in bone surgery.

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

Texture analysis based on the Hermite transform for image classification and segmentation

NASA Astrophysics Data System (ADS)

Estudillo-Romero, Alfonso; Escalante-Ramirez, Boris; Savage-Carmona, Jesus

2012-06-01

Texture analysis has become an important task in image processing because it is used as a preprocessing stage in different research areas including medical image analysis, industrial inspection, segmentation of remote sensed imaginary, multimedia indexing and retrieval. In order to extract visual texture features a texture image analysis technique is presented based on the Hermite transform. Psychovisual evidence suggests that the Gaussian derivatives fit the receptive field profiles of mammalian visual systems. The Hermite transform describes locally basic texture features in terms of Gaussian derivatives. Multiresolution combined with several analysis orders provides detection of patterns that characterizes every texture class. The analysis of the local maximum energy direction and steering of the transformation coefficients increase the method robustness against the texture orientation. This method presents an advantage over classical filter bank design because in the latter a fixed number of orientations for the analysis has to be selected. During the training stage, a subset of the Hermite analysis filters is chosen in order to improve the inter-class separability, reduce dimensionality of the feature vectors and computational cost during the classification stage. We exhaustively evaluated the correct classification rate of real randomly selected training and testing texture subsets using several kinds of common used texture features. A comparison between different distance measurements is also presented. Results of the unsupervised real texture segmentation using this approach and comparison with previous approaches showed the benefits of our proposal.

Mechanical Model Analysis for Quantitative Evaluation of Liver Fibrosis Based on Ultrasound Tissue Elasticity Imaging

NASA Astrophysics Data System (ADS)

Shiina, Tsuyoshi; Maki, Tomonori; Yamakawa, Makoto; Mitake, Tsuyoshi; Kudo, Masatoshi; Fujimoto, Kenji

2012-07-01

Precise evaluation of the stage of chronic hepatitis C with respect to fibrosis has become an important issue to prevent the occurrence of cirrhosis and to initiate appropriate therapeutic intervention such as viral eradication using interferon. Ultrasound tissue elasticity imaging, i.e., elastography can visualize tissue hardness/softness, and its clinical usefulness has been studied to detect and evaluate tumors. We have recently reported that the texture of elasticity image changes as fibrosis progresses. To evaluate fibrosis progression quantitatively on the basis of ultrasound tissue elasticity imaging, we introduced a mechanical model of fibrosis progression and simulated the process by which hepatic fibrosis affects elasticity images and compared the results with those clinical data analysis. As a result, it was confirmed that even in diffuse diseases like chronic hepatitis, the patterns of elasticity images are related to fibrous structural changes caused by hepatic disease and can be used to derive features for quantitative evaluation of fibrosis stage.

Texture evolution during nitinol martensite detwinning and phase transformation

NASA Astrophysics Data System (ADS)

Cai, S.; Schaffer, J. E.; Ren, Y.; Yu, C.

2013-12-01

Nitinol has been widely used to make medical devices for years due to its unique shape memory and superelastic properties. However, the texture of the nitinol wires has been largely ignored due to inherent complexity. In this study, in situ synchrotron X-ray diffraction has been carried out during uniaxial tensile testing to investigate the texture evolution of the nitinol wires during martensite detwinning, variant reorientation, and phase transformation. It was found that the thermal martensitic nitinol wire comprised primarily an axial (1¯20), (120), and (102)-fiber texture. Detwinning initially converted the (120) and (102) fibers to the (1¯20) fiber and progressed to a (1¯30)-fiber texture by rigid body rotation. At strains above 10%, the (1¯30)-fiber was shifted to the (110) fiber by (21¯0) deformation twinning. The austenitic wire exhibited an axial (334)-fiber, which transformed to the near-(1¯30) martensite texture after the stress-induced phase transformation.

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

PubMed

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

2014-04-01

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

Description of textures by a structural analysis.

PubMed

Tomita, F; Shirai, Y; Tsuji, S

1982-02-01

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

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.

PROGRESS ON THE STUDY OF BETA TREATMENT OF URANIUM, AUGUST 1, 1961-NOVEMBER 30, 1961

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

Russell, R.B.; Wolff, A.K.

Variables affecting the texture and grain size of uranium during beta treatment are summarized. The effects of composition (ingot versus dingot), prior delta condition, prior texture, pre-quenching air delay, rod or tube size, quenching medium and applied stress on grain size, distontion, and G/sub 3/ gradients in the final beta-treated shapes are described. (N.W.R.)

Edge Contrast of the FLAIR Hyperintense Region Predicts Survival in Patients with High-Grade Gliomas following Treatment with Bevacizumab.

PubMed

Bahrami, N; Piccioni, D; Karunamuni, R; Chang, Y-H; White, N; Delfanti, R; Seibert, T M; Hattangadi-Gluth, J A; Dale, A; Farid, N; McDonald, C R

2018-04-05

Treatment with bevacizumab is standard of care for recurrent high-grade gliomas; however, monitoring response to treatment following bevacizumab remains a challenge. The purpose of this study was to determine whether quantifying the sharpness of the fluid-attenuated inversion recovery hyperintense border using a measure derived from texture analysis-edge contrast-improves the evaluation of response to bevacizumab in patients with high-grade gliomas. MRIs were evaluated in 33 patients with high-grade gliomas before and after the initiation of bevacizumab. Volumes of interest within the FLAIR hyperintense region were segmented. Edge contrast magnitude for each VOI was extracted using gradients of the 3D FLAIR images. Cox proportional hazards models were generated to determine the relationship between edge contrast and progression-free survival/overall survival using age and the extent of surgical resection as covariates. After bevacizumab, lower edge contrast of the FLAIR hyperintense region was associated with poorer progression-free survival ( P = .009) and overall survival ( P = .022) among patients with high-grade gliomas. Kaplan-Meier curves revealed that edge contrast cutoff significantly stratified patients for both progression-free survival (log-rank χ 2 = 8.3, P = .003) and overall survival (log-rank χ 2 = 5.5, P = .019). Texture analysis using edge contrast of the FLAIR hyperintense region may be an important predictive indicator in patients with high-grade gliomas following treatment with bevacizumab. Specifically, low FLAIR edge contrast may partially reflect areas of early tumor infiltration. This study adds to a growing body of literature proposing that quantifying features may be important for determining outcomes in patients with high-grade gliomas. © 2018 by American Journal of Neuroradiology.

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.

Image Based Biomarker of Breast Cancer Risk: Analysis of Risk Disparity Among Minority Populations

DTIC Science & Technology

2015-02-01

health disparity. • On August 2-5, 2011, Fengshan Liu and Charlie Wilson attended and presented at the Department of Defense Breast Cancer Research...DSU faculty met with UPENN mentors on January 24, 2011 and August 9, 2010 to discuss the progress and the future work of each DSU faculty. 14...training, focus on parenchymal texture 03/06/2012: Training on MIRC database 03/09/2012: Additional training on MIRC database • In August 2013

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.

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

PubMed Central

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

2009-01-01

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

Ion beam sputter modification of the surface morphology of biological implants

NASA Technical Reports Server (NTRS)

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

1976-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1977-01-01

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

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.

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.

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

NASA Astrophysics Data System (ADS)

Skrotzki, Werner; Oertel, Carl-Georg

2015-04-01

The 17th International Conference on Textures of Materials (ICOTOM 17) took place in Dresden, Germany, August 24-29, 2014. It belongs to the "triennial" series of ICOTOM meetings with a long tradition, starting in 1969 - Clausthal, 1971 - Cracow, 1973 - Pont-à-Mousson, 1975 - Cambridge, 1978 - Aachen, 1981 - Tokyo, 1984 - Noordwijkerhout, 1987 - Santa Fe, 1990 - Avignon, 1993 - Clausthal, 1996 - Xian, 1999 - Montreal, 2002 - Seoul, 2005 - Leuven, 2008 - Pittsburgh, 2011 - Mumbai, 2014 - Dresden. ICOTOM 17 was hosted by the Dresden University of Technology, Institute of Structural Physics. Following the tradition of the ICOTOM conferences, the main focus of ICOTOM-17 was to promote and strengthen the fundamental understanding of the basic processes that govern the formation of texture and its relation to the properties of polycrystalline materials. Nonetheless, it was the aim to forge links between basic research on model materials and applied research on engineering materials of technical importance. Thus, ICOTOM 17 provided a forum for the presentation and discussion of recent progress in research of texture and related anisotropy of mechanical and functional properties of all kinds of polycrystalline materials including natural materials like rocks. Particular attention was paid to recent advances in texture measurement and analysis as well as modeling of texture development for all kinds of processes like solidification, plastic deformation, recrystallization and grain growth, phase transformations, thin film deposition, etc. Hence, ICOTOM 17 was of great interest to materials scientists, engineers from many different areas and geoscientists. The topics covered by ICOTOM 17 were: 1. Mathematical, numerical and statistical methods of texture analysis 2. Deformation textures 3. Crystallization, recrystallization and growth textures 4. Transformation textures 5. Textures in functional materials 6. Textures in advanced materials 7. Textures in rocks 8. Texture related research on microstructures 9. Texture-induced anisotropy 10. Insight through new experimental methods 11. Technological applications of texture studies 12. Other new developments and future trends related to the field While there was large interest in the topics 2, 3 and 8, contributions to topic 7 were much less than expected. ICOTOM 17 attracted 266 scientists from 34 countries with about one third of the participants being students. This is a very good ratio showing that we could attract the young generation. There have been 216 oral and 76 poster presentations, three of which received a poster award. It is our pleasure to thank the members of the International ICOTOM Committee for their valuable help, especially for proposing and choosing the 15 plenary speakers as well as the distinguished scientist of the texture community for the "Bunge Award". 130 papers were submitted for publication in the proceedings, 116 were accepted after reviewing. We would like to express our thanks to all referees for their efficient and prompt efforts. We acknowledge particularly support from the German Research Society (DFG) and the City of Dresden. We are also grateful for industrial support from Bruker Nano GmbH, Oxford Instruments GmbH, Ametek GmbH / EDAX, Labosoft S.C., PANalytical GmbH and IOP Publishing. Finally we thank all members of the National Organizing Committee, Intercom Dresden and Conwerk / Laboratory Ten for the excellent organization of ICOTOM 17 and the very pleasant collaboration. On the first day of the conference three tutorials have been offered. Each of them has been attended by about 30 participants. 1. Texture-aided residual stress identification system (TARSIuS) (organized by Prof. Dr. J. Bonarski and Mr. B. Kania) 2. MTEX - MATLAB toolbox for quantitative texture analysis (organized by Dr. R. Hielscher and Mr. F. Bachmann) 3. Grain boundary engineering (organized by Prof. N. Bozzolo and Prof. Dr. A.D. Rollett) A highlight of ICOTOM 17 was the ceremony honoring Prof. Dr. Claude Esling with the Bunge Award for his distinguished contributions to the field of Textures of Materials and his continuous effort to pass on his knowledge to future generations of texture experts. The Bunge Award is named after Professor Hans Bunge († 2004), to whom the world's texture community is very much indebted not only for his magisterial work on the Mathematical Theory of Texture, but also for his lifelong promotion of the field of Textures of Materials. To the great delight of all participants, Helga Bunge and her son Prof. Hans-Peter Bunge, to whom many of the older generation have a personal relationship, attended the ceremony (see Fig. 1 in the PDF). Following the award ceremony Prof. Dr. Claude Esling gave an in memoriam tribute to Prof. Dr. Richard Penelle, who was an internationally recognized texture specialist. Details can be found in the proceedings paper by Esling et al. [this issue]. During the conference the International ICSMA Committee decided to convene the next conference in St. George, USA, in 2017. We wish the organizers of ICOTOM 18 great success and look forward to meeting you in St. George. Werner Skrotzki* (Chairman of ICOTOM 17, Dresden University of Technology) Carl-Georg Oertel (Dresden University of Technology) Guest Editors Dresden, March, 2015 (* Corresponding author; e-mail address: werner.skrotzki@tu-dresden.de)

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

PubMed

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

2016-02-01

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

Independent Component Analysis of Textures

NASA Technical Reports Server (NTRS)

Manduchi, Roberto; Portilla, Javier

2000-01-01

A common method for texture representation is to use the marginal probability densities over the outputs of a set of multi-orientation, multi-scale filters as a description of the texture. We propose a technique, based on Independent Components Analysis, for choosing the set of filters that yield the most informative marginals, meaning that the product over the marginals most closely approximates the joint probability density function of the filter outputs. The algorithm is implemented using a steerable filter space. Experiments involving both texture classification and synthesis show that compared to Principal Components Analysis, ICA provides superior performance for modeling of natural and synthetic textures.

The ontogeny of feeding in rats: V. Influence of texture, home odor, and sibling presence on ingestive behavior.

PubMed

Johanson, I B; Hall, W G

1981-12-01

Terry-cloth texture, home odor, and the presence of siblings modulate the ingestive behavior of infant rats. Unlike warmth, which affects ingestion in pups until at least 15 days of age, the relative importance of these other cues varies with the age of the pup. At 3 days, ingestion is dependent on warmth but is not influenced by the other cues. At 6 days, texture and home odor enhance ingestive behavior (intake, activity, mouthing, and probing), but the presence of siblings has no effect. Home odor or terry-cloth texture did not alter the ingestive behavior of 12-day-olds, but the presence of siblings enhanced milk intake. Thus, during development, the external sensory controls for ingestion become progressively more complex. Warmth serves as a primary permissive cue for ingestion in developing pups, but as pups grow older, other types of cues (such as odor, texture, or social stimuli) also gain significance.

Microstructure evolution and texture development in a friction stir-processed AISI D2 tool steel

NASA Astrophysics Data System (ADS)

Yasavol, N.; Abdollah-zadeh, A.; Vieira, M. T.; Jafarian, H. R.

2014-02-01

Crystallographic texture developments during friction stir processing (FSP) of AISI D2 tool were studied with respect to grain sizes in different tool rotation rates. Comparison of the grain sizes in various rotation rates confirmed that grain refinement occurred progressively in higher rotation rates by severe plastic deformation. It was found that the predominant mechanism during FSP should be dynamic recovery (DRV) happened concurrently with continuous dynamic recrystallization (CDRX) caused by particle-stimulated nucleation (PSN). The developed shear texture relates to the ideal shear textures of D1 and D2 in bcc metals. The prevalence of highly dense arrangement of close-packed planes of bcc and the lowest Taylor factor showed the lowest compressive residual stress which is responsible for better mechanical properties compared with the grain-precipitate refinement.

Effect of the wooden breast condition on shear force and texture profile analysis of raw and cooked broiler pectoralis major

USDA-ARS?s Scientific Manuscript database

The objective was to characterize texture properties of raw and cooked broiler fillets (Pectoralis major) with the wooden breast condition (WBC) using the instrumental texture techniques of Meullenet-Owens Razor Shear (MORS) and Texture Profile Analysis (TPA). Deboned (3 h post-mortem) broiler fille...

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.

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

PubMed

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

2015-09-01

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

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.

Trabecular morphometry by fractal signature analysis is a novel marker of osteoarthritis progression.

PubMed

Kraus, Virginia Byers; Feng, Sheng; Wang, ShengChu; White, Scott; Ainslie, Maureen; Brett, Alan; Holmes, Anthony; Charles, H Cecil

2009-12-01

To evaluate the effectiveness of using subchondral bone texture observed on a radiograph taken at baseline to predict progression of knee osteoarthritis (OA) over a 3-year period. A total of 138 participants in the Prediction of Osteoarthritis Progression study were evaluated at baseline and after 3 years. Fractal signature analysis (FSA) of the medial subchondral tibial plateau was performed on fixed flexion radiographs of 248 nonreplaced knees, using a commercially available software tool. OA progression was defined as a change in joint space narrowing (JSN) or osteophyte formation of 1 grade according to a standardized knee atlas. Statistical analysis of fractal signatures was performed using a new model based on correlating the overall shape of a fractal dimension curve with radius. Fractal signature of the medial tibial plateau at baseline was predictive of medial knee JSN progression (area under the curve [AUC] 0.75, of a receiver operating characteristic curve) but was not predictive of osteophyte formation or progression of JSN in the lateral compartment. Traditional covariates (age, sex, body mass index, knee pain), general bone mineral content, and joint space width at baseline were no more effective than random variables for predicting OA progression (AUC 0.52-0.58). The predictive model with maximum effectiveness combined fractal signature at baseline, knee alignment, traditional covariates, and bone mineral content (AUC 0.79). We identified a prognostic marker of OA that is readily extracted from a plain radiograph using FSA. Although the method needs to be validated in a second cohort, our results indicate that the global shape approach to analyzing these data is a potentially efficient means of identifying individuals at risk of knee OA progression.

A Transmission Electron Microscope Study of Experimentally Shocked Pregraphitic Carbon

NASA Technical Reports Server (NTRS)

Rietmeijer, Frans J. M.

1995-01-01

A transmission electron microscope study of experimental shock metamorphism in natural pre-graphitic carbon simulates the response of the most common natural carbons to increased shock pressure. The d-spacings of this carbon are insensitive to the shock pressure and have no apparent diagnostic value, but progressive comminution occurs in response to increased shock pressure up to 59.6 GPa. The function, P = 869.1 x (size(sub minimum )(exp -0.83), describes the relationship between the minimum root-mean-square subgrain size (nm) and shock pressure (GPa). While a subgrain texture of natural pregraphitic carbons carries little information when pre-shock textures are unknown, this texture may go unnoticed as a shock metamorphic feature.

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

PubMed

Park, Jeongho; Park, Soojin

2017-04-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2007-10-01

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

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

PubMed Central

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

2011-01-01

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

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.

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.

Texture development in naturally compacted and experimentally deformed silty clay sediments from the Nankai Trench and Forearc, Japan

NASA Astrophysics Data System (ADS)

Schumann, Kai; Stipp, Michael; Leiss, Bernd; Behrmann, Jan H.

2014-12-01

The petrophysical properties of fine-grained marine sediments to a large extent depend on the microstructure and crystallographic preferred orientations (CPOs). In this contribution we show that Rietveld-based synchrotron texture analysis is a new and valuable tool to quantify textures of water-saturated fine-grained phyllosilicate-rich sediments, and assess the effects of compaction and tectonic deformation. We studied the CPO of compositionally almost homogeneous silty clay drillcore samples from the Nankai Accretionary Prism slope and the incoming Philippine Sea plate, offshore SW Japan. Basal planes of phyllosilicates show bedding-parallel alignment increasing with drillhole depth, thus reflecting progressive burial and compaction. In some samples calcite and albite display a CPO due to crystallographically controlled non-isometric grain shapes, or nannofossil tests. Consolidated-undrained experimental deformation of a suite of thirteen samples from the prism slope shows that the CPOs of phyllosilicate and calcite basal planes develop normal to the experimental shortening axis. There is at least a qualitative relation between CPO intensity and strain magnitude. Scanning electron micrographs show concurrent evolution of preferred orientations of micropores and detrital illite flakes normal to axial shortening. This indicates that the microfabrics are sensitive strain gauges, and contribute to anisotropic physical properties along with the CPO.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

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.

Methods for comparing 3D surface attributes

NASA Astrophysics Data System (ADS)

Pang, Alex; Freeman, Adam

1996-03-01

A common task in data analysis is to compare two or more sets of data, statistics, presentations, etc. A predominant method in use is side-by-side visual comparison of images. While straightforward, it burdens the user with the task of discerning the differences between the two images. The user if further taxed when the images are of 3D scenes. This paper presents several methods for analyzing the extent, magnitude, and manner in which surfaces in 3D differ in their attributes. The surface geometry are assumed to be identical and only the surface attributes (color, texture, etc.) are variable. As a case in point, we examine the differences obtained when a 3D scene is rendered progressively using radiosity with different form factor calculation methods. The comparison methods include extensions of simple methods such as mapping difference information to color or transparency, and more recent methods including the use of surface texture, perturbation, and adaptive placements of error glyphs.

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.

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

Color, sensory and textural attributes of beef frankfurter, beef ham and meat-free sausage containing tomato pomace.

PubMed

Savadkoohi, Sobhan; Hoogenkamp, Henk; Shamsi, Kambiz; Farahnaky, Asgar

2014-08-01

The present investigation focuses on the textural properties, sensory attributes and color changes of beef frankfurter, beef ham and meat-free sausage produced by different levels of bleached tomato pomace. The texture and color profile were performed using an instrumental texture analyzer and colorimeter. The findings indicated that tomato pomace-added sausages had higher water holding capacity (WHC) compared to that of commercial samples. The frankfurters containing 5 and 7% (w/w) tomato pomace had the highest redness (a*), chroma (C*) and color differences (ΔE) values, while the meat-free sausages containing 7% (w/w) tomato pomace had significant (p<0.05) values for lightness (L*) and yellowness (b*). Furthermore, there were no significant (p>0.05) color differences between beef ham samples (with and without tomato pomace). A significant progression in the textural hardness and chewiness of systems containing tomato pomace was observed as well as higher sensory scores by panelists. According to sensorial evaluations, bleached tomato pomace improved the consumer acceptability and preference. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

PubMed

Di Cataldo, Santa; Ficarra, Elisa

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

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

Gao, M; Fan, T; Duan, J

2015-06-15

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

Structural analysis of natural textures.

PubMed

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

1986-01-01

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

Texture analysis at neutron diffractometer STRESS-SPEC

NASA Astrophysics Data System (ADS)

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

2011-06-01

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

3D Textural and Geochemical Analyses on Carbonado Diamond: Insights from Pores and the Minerals within Them

NASA Astrophysics Data System (ADS)

Eckley, S. A.; Ketcham, R. A.

2017-12-01

Carbonado is an enigmatic variety of polycrystalline diamond found only in placer deposits and Proterozoic metaconglomerates in Brazil and the Central African Republic with unknown primary origin. These highly porous black nodules possess a narrow range of isotopically light carbon (δ13C -31 to -24 ‰), a primarily crustal inclusion suite unusually enriched in REEs and actinides filling the pore spaces, a crystallization age from 2.6 to 3.8 Ga, and other atypical features which have led to a variety of formation theories from extra-solar to deep mantle. We have completed the first multi-sample 3D textural analysis on nine carbonados using high resolution X-ray CT (XCT), with follow-up geochemical work. We have documented a variety of textures in both pore structure and mineralogy within pores. All pore textures feature a preferred orientation. Spatial coherence in pore fillings in some specimens suggest that secondary minerals formed by in-situ breakdown of primary inclusion phases. This, combined with the presence of pseudomorphs, support the hypothesis that elements comprising the secondary minerals within the pore spaces are actually primary. SEM-EDS analysis of one carbonado's exterior revealed the presence of zircon; XCT analysis of the complete volume indicates zircon is present only on the exterior of that specimen, but may be interior to others. Anticipated follow-up work will include LA-ICP-MS U-Pb dating and REE analysis of the zircon, and step-leaching and ICP analysis of some specimens. Periodic XCT imaging will allow us to trace leaching progress and effectiveness. To provide further context for our observed pore fabrics, we also analyzed a framesite, a less porous polycrystalline diamond found in kimberlites thought to crystallize shortly before eruption. Both diamond varieties have bladed/elongated pores forming a foliation with a moderate lineation. The similarity in fabrics suggests a similar process could have formed both carbonados and framesites. These data can shed light on the origin and constrain the age of carbonado, which may have far-reaching implications on the timing, origin, and mobility of light-carbon fluids in the mantle, early Earth's redox conditions, and the nature of a crystallization environment that can concentrate highly incompatible elements.

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

NASA Astrophysics Data System (ADS)

An, Jubai; Zhu, Lisong

2006-01-01

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

MRI Texture Analysis of Background Parenchymal Enhancement of the Breast

PubMed Central

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

2017-01-01

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

Structural texture similarity metrics for image analysis and retrieval.

PubMed

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

2013-07-01

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

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.

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.

Fast Image Texture Classification Using Decision Trees

NASA Technical Reports Server (NTRS)

Thompson, David R.

2011-01-01

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

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

Instrumental texture characteristics of broiler pectoralis major with the woody breast condition

USDA-ARS?s Scientific Manuscript database

The objective was to characterize texture properties of raw and cooked broiler fillets (pectoralis major) with the woody breast condition (WBC) using instrumental texture techniques Meullenet-Owens Razor Shear (MORS) and texture profile analysis (TPA). Deboned (3 h postmortem) broiler fillets were c...

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

PubMed

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

2017-01-01

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

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

PubMed

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

2016-01-01

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

Texture analysis of 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.

Fault textures in volcanic conduits: evidence for seismic trigger mechanisms during silicic eruptions

NASA Astrophysics Data System (ADS)

Tuffen, Hugh; Dingwell, Don

2005-04-01

It is proposed that fault textures in two dissected rhyolitic conduits in Iceland preserve evidence for shallow seismogenic faulting within rising magma during the emplacement of highly viscous lava flows. Detailed field and petrographic analysis of such textures may shed light on the origin of long-period and hybrid volcanic earthquakes at active volcanoes. There is evidence at each conduit investigated for multiple seismogenic cycles, each of which involved four distinct evolutionary phases. In phase 1, shear fracture of unrelaxed magma was triggered by shear stress accumulation during viscous flow, forming the angular fracture networks that initiated faulting cycles. Transient pressure gradients were generated as the fractures opened, which led to fluidisation and clastic deposition of fine-grained particles that were derived from the fracture walls by abrasion. Fracture networks then progressively coalesced and rotated during subsequent slip (phase 2), developing into cataclasite zones with evidence for multiple localised slip events, fluidisation and grain size reduction. Phase 2 textures closely resemble those formed on seismogenic tectonic faults characterised by friction-controlled stick-slip behaviour. Increasing cohesion of cataclasites then led to aseismic, distributed ductile deformation (phase 3) and generated deformed cataclasite zones, which are enriched in metallic oxide microlites and resemble glassy pseudotachylite. Continued annealing and deformation eventually erased all structures in the cataclasite and formed microlite-rich flow bands in obsidian (phase 4). Overall, the mixed brittle-ductile textures formed in the magma appear similar to those formed in lower crustal rocks close to the brittle-ductile transition, with the rheological response mediated by strain-rate variations and frictional heating. Fault processes in highly viscous magma are compared with those elsewhere in the crust, and this comparison is used to appraise existing models of volcano seismic activity. Based on the textures observed, it is suggested that patterns of long-period and hybrid earthquakes at silicic lava domes reflect friction-controlled stick-slip movement and eventual healing of fault zones in magma, which are an accelerated and smaller-scale analogue of tectonic faults.

Extraction of texture features with a multiresolution neural network

NASA Astrophysics Data System (ADS)

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

1992-09-01

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

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

PubMed

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

2018-04-01

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

An assessment of the impact of pulsed electric fields processing factors on oxidation, color, texture, and sensory attributes of turkey breast meat.

PubMed

Arroyo, Cristina; Eslami, Sara; Brunton, Nigel P; Arimi, Joshua M; Noci, Francesco; Lyng, James G

2015-05-01

Pulsed electric fields (PEF) is a novel nonthermal technology that has the potential to cause physical disruption to muscle tissue which in turn could alter the sensorial aspects of meat in both a positive (e.g., enhanced tenderization) and a negative way (e.g., off-flavor development). If there is a risk of off-flavor development it should be identified prior to embarking on an extensive investigation on PEF in meat tenderization and turkey meat was chosen for this purpose as it is particularly prone to oxidation. The objective of this study was to investigate the effect of various PEF treatments on the quality attributes of turkey breast meat. Turkey breast meat obtained 1 d postslaughter was treated in a batch PEF chamber with increasing electric field strength up to 3 kV/cm and analyzed for lipid oxidation by thiobarbituric acid reactive substances assay (TBARS) with up to 5 d storage at 4°C in aerobic conditions. In a separate experiment, turkey breast meat samples were exposed to PEF under various combinations of pulse number, frequency, and voltage. Following PEF treatments weight loss, cook loss, lipid oxidation, texture, and color were assessed by instrumental methods. A sensory analysis was also performed to determine consumer acceptability for color, texture, and odor of the samples. Lipid oxidation in all PEF-treated samples progressed at the same rate with storage as the untreated samples and was not found to be significantly different to the control. Under the conditions examined PEF treatments did not induce differences in instrumentally measured weight loss, cook loss, lipid oxidation, texture, and color (raw and cooked) either on fresh or frozen samples. However, the sensory evaluation suggested that panelists could detect slight differences between the PEF-treated samples and the controls in terms of texture and odor. © 2015 Poultry Science Association Inc.

Comparative study of phase transition and textural changes upon calcination of two commercial titania samples: A pure anatase and a mixed anatase-rutile

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

Kordouli, Eleana; Dracopoulos, Vassileios; Vaimakis, Tiverios

2015-12-15

The effect of calcination temperature and time on structural and textural changes of two commercial TiO{sub 2} samples (pure anatase and a mixture of anatase and rutile) has been investigated using N{sub 2} physisorption, ex-situ and in-situ X-ray powder diffraction, differential scanning calorimetry and UV–vis diffuse reflectance spectroscopy. The increase of the calcination temperature (up to 700 °C) and time (up to 8 h) causes only textural changes in the pure anatase, whereas a transformation of the anatase to rutile takes place, in addition, in the mixed titania (containing anatase and rutile). The textural changes observed in pure anatase samplemore » were attributed to solid state diffusion leading to an increase in the size of anatase nanocrystals, through sintering. Thus, the mean pore diameter shifts to higher values and the pore volume and specific surface area decrease. The successful application of the Johnson–Mehl–Avrami–Kolmogorov model in the kinetic data concerning the pure anatase indicates a mass transfer control of sintering process. Similar textural changes were also observed upon calcination of the sample containing anatase and rutile. In this case not only sintering but the anatase to rutile transformation contributes also to the textural changes. Kinetic analysis showed that the rutile nanocrystals in the mixed titania served as seed for by-passing the high energy barrier nucleation step allowing/facilitating thus the anatase to rutile transformation. A fine control of the anatase to rutile ratio and thus of energy-gap and the population of hetero-junctions may be obtained by adjusting the calcination temperature and time. - Graphical Abstract: Dependence of anatase content of P25 on the calcination temperature (600 °C (■), 650 °C (●), 700 °C (▲)) and time. - Highlights: • Increase of calcination temperature up to 800 °C and time up to 8 h causes only textural changes in pure anatase • Progressive transformation of anatase to rutile with time takes place in the mixed titania above 600 °C • A high activation energy barrier inhibits the solid state transformation in pure anatase • Rutile nanocrystals in mixed titania serve as seeding for favouring transformation • Calcination temperature and time allow a fine control of E{sub g} and heterojunctions population in mixed titania.« less

Friction Stir Back Extrusion of Aluminium Alloys for Automotive Applications

NASA Astrophysics Data System (ADS)

Xu, Zeren

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

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

PubMed

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

2014-09-01

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

Effects of hydraulic roughness on surface textures of gravel‐bed rivers

USGS Publications Warehouse

Buffington, John M.; Montgomery, David R.

1999-01-01

Field studies of forest gravel‐bed rivers in northwestern Washington and southeastern Alaska demonstrate that bed‐surface grain size is responsive to hydraulic roughness caused by bank irregularities, bars, and wood debris. We evaluate textural response by comparing reach‐average median grain size (D50) to that predicted from the total bank‐full boundary shear stress (т0bf), representing a hypothetical reference condition of low hydraulic roughness. For a given т0bf, channels with progressively greater hydraulic roughness have systematically finer bed surfaces, presumably due to reduced bed shear stress, resulting in lower channel competence and diminished bed load transport capacity, both of which promote textural fining. In channels with significant hydraulic roughness, observed values D50 can be up to 90% smaller than those predicted from т0bf. We find that wood debris plays an important role at our study sites, not only providing hydraulic roughness but also influencing pool spacing, frequency of textural patches, and the amplitude and wavelength of bank and bar topography and their consequent roughness. Our observations also have biological implications. We find that textural fining due to hydraulic roughness can create usable salmonid spawning gravels in channels that otherwise would be too coarse.

Thickness effects on the texture development of fluorine-doped SnO2 thin films: The role of surface and strain energy

NASA Astrophysics Data System (ADS)

Consonni, V.; Rey, G.; Roussel, H.; Bellet, D.

2012-02-01

Polycrystalline fluorine-doped SnO2 thin films have been grown by ultrasonic spray pyrolysis with a thickness varying in the range of 40 to 600 nm. A texture transition from ⟨110⟩ to ⟨100⟩ and ⟨301⟩ crystallographic orientations has experimentally been shown by x-ray diffraction measurements as film thickness is increased, showing that a process of abnormal grain growth has occurred. The texture effects are considered within a thermodynamic approach, in which the minimization of total free energy constitutes the driving force for grain growth. For very small film thickness, it is found that the ⟨110⟩ preferred orientation is due to surface energy minimization, as the (110) planes have the lowest surface energy in the rutile structure. In contrast, as film thickness is increased, the ⟨100⟩ and ⟨301⟩ crystallographic orientations are progressively predominant, owing to elastic strain energy minimization in which the anisotropic character is considered in the elastic biaxial modulus. A texture map is eventually determined, revealing the expected texture as a function of elastic strain and film thickness.

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.

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

NASA Astrophysics Data System (ADS)

Cui, Chen; Asari, Vijayan K.

2014-03-01

Biometric features such as fingerprints, iris patterns, and face features help to identify people and restrict access to secure areas by performing advanced pattern analysis and matching. Face recognition is one of the most promising biometric methodologies for human identification in a non-cooperative security environment. However, the recognition results obtained by face recognition systems are a affected by several variations that may happen to the patterns in an unrestricted environment. As a result, several algorithms have been developed for extracting different facial features for face recognition. Due to the various possible challenges of data captured at different lighting conditions, viewing angles, facial expressions, and partial occlusions in natural environmental conditions, automatic facial recognition still remains as a difficult issue that needs to be resolved. In this paper, we propose a novel approach to tackling some of these issues by analyzing the local textural descriptions for facial feature representation. The textural information is extracted by an enhanced local binary pattern (ELBP) description of all the local regions of the face. The relationship of each pixel with respect to its neighborhood is extracted and employed to calculate the new representation. ELBP reconstructs a much better textural feature extraction vector from an original gray level image in different lighting conditions. The dimensionality of the texture image is reduced by principal component analysis performed on each local face region. Each low dimensional vector representing a local region is now weighted based on the significance of the sub-region. The weight of each sub-region is determined by employing the local variance estimate of the respective region, which represents the significance of the region. The final facial textural feature vector is obtained by concatenating the reduced dimensional weight sets of all the modules (sub-regions) of the face image. Experiments conducted on various popular face databases show promising performance of the proposed algorithm in varying lighting, expression, and partial occlusion conditions. Four databases were used for testing the performance of the proposed system: Yale Face database, Extended Yale Face database B, Japanese Female Facial Expression database, and CMU AMP Facial Expression database. The experimental results in all four databases show the effectiveness of the proposed system. Also, the computation cost is lower because of the simplified calculation steps. Research work is progressing to investigate the effectiveness of the proposed face recognition method on pose-varying conditions as well. It is envisaged that a multilane approach of trained frameworks at different pose bins and an appropriate voting strategy would lead to a good recognition rate in such situation.

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.

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.

Pushkin to Shukshin: Complementary Strands in the Texture of Soviet Life.

ERIC Educational Resources Information Center

Zevin, Patricia Ernenwein

1980-01-01

Discusses English reading texts used in the Soviet Union, which are English translations of Russian literature. Notes that such literature divides attention between the traditional and the progressive elements of Soviet culture. (DF)

Microstructural, textural and thermal evolution of an exhumed strike-slip fault and insights into localization and rheological transition

NASA Astrophysics Data System (ADS)

Cao, Shuyun; Neubauer, Franz; Liu, Junlai; Bernroider, Manfred; Genser, Johann

2016-04-01

The presence of deep exhumed crustal rocks with a dominant but contrasting mineralogy results in shear concentration in the rheological weakest layer, which exhibits contrasting patterns of fabrics and thermal conditions during their formation. We tested a combination of methodologies including microstructural and textural investigations, geochronology and geothermometry on deformed rocks from exhumed strike-slip fault, Ailao Shan-Red River, SE, Asian. Results indicate that the exhumed deep crustal rocks since late Oligocene (ca. 28 Ma) to Pliocene (ca. 4 Ma) typically involve dynamic microstructural, textural and thermal evolution processes, which typically record a progressive deformation and syn-kinematic reactions from ductile to semi-ductile and brittle behavior during exhumation. This transformation also resulted in dramatic strength reduction that promoted strain localization along the strike-slip and transtensional faults. Detailed analysis has revealed the co-existence of microfabrics ranging from high-temperatures (granulite facies conditions) to overprinting low-temperatures (lower greenschist facies conditions). The high-temperature microstructures and textures are in part or entirely altered by subsequent, overprinting low-temperature shearing. In quartz-rich rocks, quartz was deformed in the dislocation creep regime and records transition of microfabrics and slip systems during decreasing temperature, which lasted until retrogression related to final exhumation. As a result, grain-size reduction associated by fluids circulating within the strike-slip fault zone at brittle-ductile transition leads to rock softening, which resulted in strain localization, weak rock rheology and the overall hot thermal structure of the crust. Decompression occurred during shearing and as a result of tectonic exhumation. All these results demonstrate that the ductile to ductile-brittle transition involves a combination of different deformation mechanisms, rheological transition features and feedbacks between deformation, decreasing temperature and fluids.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Texture analysis of Napoleonic War Era copper bolts

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

Subedar, Mahesh M.; Karam, Lina J.

2015-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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

NASA Astrophysics Data System (ADS)

Brosnan, Kristen H.

In this study, XRD and electron backscatter diffraction (EBSD) techniques were used to characterize the fiber texture in oriented PMN-28PT and the intensity data were fit with a texture model (the March-Dollase equation) that describes the texture in terms of texture fraction (f), and the width of the orientation distribution (r). EBSD analysis confirmed the <001> orientation of the microstructure, with no distinguishable randomly oriented, fine grain matrix. Although XRD rocking curve and EBSD data analysis gave similar f and r values, XRD rocking curve analysis was the most efficient and gave a complete description of texture fraction and texture orientation (f = 0.81 and r = 0.21, respectively). XRD rocking curve analysis was the preferred approach for characterization of the texture volume and the orientation distribution of texture in fiber-oriented PMN-PT. The dielectric, piezoelectric and electromechanical properties for random ceramic, 69 vol% textured, 81 vol% textured, and single crystal PMN-28PT were fully characterized and compared. The room temperature dielectric constant at 1 kHz for highly textured PMN-28PT was epsilonr ≥ 3600 with low dielectric loss (tan delta = 0.004). The temperature dependence of the dielectric constant for 81 vol% textured ceramic followed a similar trend as the single crystal PMN-28PT up to the rhombohedral to tetragonal transition temperature (TRT) at 104°C. 81 vol% textured PMN-28PT consistently displayed 60 to 65% of the single crystal PMN-28PT piezoelectric coefficient (d33) and 1.5 to 3.0 times greater than the random ceramic d33 (measured by Berlincourt meter, unipolar strain-field curves, IEEE standard resonance method, and laser vibrometry). The 81 vol% textured PMN-28PT displayed similarly low piezoelectric hysteresis as single crystal PMN-28PT measured by strain-field curves at 5 kV/cm. 81 vol% textured PMN-28PT and single crystal PMN-28PT displayed similar mechanical quality factors of QM = 74 and 76, respectively. The electromechanical coupling (k 33) of 81 vol% textured PMN-28PT (k33 = 0.79) was a significant fraction of single crystal (k33 = 0.91) and was higher than a commercial PMN-PT ceramic (k33 ˜ 0.74). The nonlinearity of the dielectric and piezoelectric response were investigated in textured ceramics and single crystal PMN-28PT using the Rayleigh approach. The reversible piezoelectric coefficient was found to increase significantly and the hysteretic contribution to the piezoelectric coefficient decreased significantly with an increase in texture volume. This indicates that increasing the texture volume decreases the non-180° domain wall contribution to the piezoelectric response in PMN-28PT. Finally, 81 vol% textured ceramics were also integrated into a Navy SONAR transducer design. In-water characterization of the transducers showed higher source levels, higher in-water coupling, higher acoustic intensity, and more bandwidth for the 81 vol% textured PMN-28PT tonpilz single elements compared to the ceramic PMN-28PT tonpilz element. In addition, an 81 vol% textured PMN-28PT tonpilz element showed large scale linearity in sound pressure levels as a function of drive level under high drive conditions (up to 2.33 kV/cm). The maximum electromechanical coupling obtained by the 81 vol% textured PMN-28PT transducer under high drive conditions was keff = 0.69. However, the resonance frequency shifted significantly during high drive tests (Deltafs = -19% at 3.7 kV/cm), evidence of a "soft" characteristic of the 81 vol% textured PMN-28PT, possibly caused by Sr2+ from the template particles. The results suggest there are limitations on the preload compressive stress (and thus drive level) for these textured ceramics, but this could be addressed with compositional modifications. The dielectric, piezoelectric and electromechanical properties have been significantly improved in textured PMN-PT ceramics of this study. Furthermore, scale-up in processing for incorporation into devices of highly textured ceramics with reproducible texture (and hence narrow properties distribution) was achieved in these materials. SONAR applications could benefit from textured ceramic parts because of their ease of processing, compositional homogeneity and potentially lower cost. (Abstract shortened by UMI.)

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

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

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

NASA Astrophysics Data System (ADS)

Novaković, S.; Tomašević, I.

2017-09-01

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

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

Treesearch

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

2002-01-01

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

Pandora Fretum Crater

NASA Technical Reports Server (NTRS)

2002-01-01

[figure removed for brevity, see original site] (Released 26 July 2002) Another in a series of craters with unusual interior deposits, this THEMIS image shows an unnamed crater in the southern hemisphere Pandora Fretum region near the Hellas Basin. Craters with eroded layered deposits are quite common on Mars but the crusty textured domes in the center of the image make this crater more unusual. Looking vaguely like granitic intrusions, there erosional style is distinct from the rest of the interior deposit which shows a very obvious layered morphology. While it is unlikely that the domes are granite plutons, it is possible that they do represent some other shallowly emplaced magmatic intrusion. More likely still is that variations in induration of the layered deposit allow for variations in the erosional morphology. Note how the surface of the crater floor in the northernmost portion of the image has a texture similar to that of the domes. This may represent an incipient form of the erosion that has produced the domes but has not progressed as far. An analysis of other craters in the area may shed light on the origin of the domes.

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.

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

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

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

2012-02-15

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

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

NASA Astrophysics Data System (ADS)

Serebryany, V. N.; Kochubei, A. Ya.; Kurtasov, S. F.; Mel'Nikov, K. E.

2007-02-01

Quantitative texture analysis is used to study texture formation in an MA2-1 magnesium alloy subjected to axisymmetric upsetting at temperatures of 250-450°C and strain rates of 10-4-100 -1. The deformed structure is examined by optical microscopy, and the results obtained are used to plot the structural-state diagram of the alloy after 50% upsetting. The experimental textures are compared with the textures calculated in terms of a thermoactivation model.

Multi Texture Analysis of Colorectal Cancer Continuum Using Multispectral Imagery

PubMed Central

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

2016-01-01

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

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

Crop identification of SAR data using digital textural analysis

NASA Technical Reports Server (NTRS)

Nuesch, D. R.

1983-01-01

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

X-ray tomographic microscopy analysis of the dendrite orientation transition in Al-Zn

NASA Astrophysics Data System (ADS)

Friedli, Jonathan; Fife, Julie L.; Di Napoli, Paolo; Rappaz, Michel

2012-07-01

Recently, Gonzales and Rappaz [Met. Mat. Trans. A37:2797, 2006] showed the influence of an increasing zinc content on the growth directions of aluminum dendrites. langle100rangle and langle110rangle dendrites were observed below 25wt.% and above 55wt.% zinc, respectively, whereas textured seaweeds and langle320rangle dendrites were observed at intermediate compositions. Considering the complexity of these structures, it is necessary to first characterize them in further details and second, to model them using the phase field method. The so-called Dendrite Orientation Transition (DOT) was thus reinvestigated in quenched Bridgman solidification samples. The combination of X-ray tomographic microscopy and electron backscattered diffraction (EBSD) analysis on a whole range of compositions, from 5 to 90wt.% Zn, allowed insights with unprecedented details about texture, growth directions and mechanisms of the aforementioned structures. We show that seaweeds rather than dendrites are found at all intermediate compositions. Their growth was confirmed to be constrained within a (100) symmetry plane. However, new findings indicate that the observed macroscopic texture does not necessarily correspond to the actual growth directions of the microstructure. Further, it seems to operate by an alternating growth direction mechanism and could be linked to the competition between the langle100rangle and langle110rangle characters of regular dendrites observed at the limits of the DOT. These characters, as well as 3D seaweeds, are observed in phase-field simulations of equiaxed growth and directional solidification, respectively. This study emphasizes the importance of accurate experimental data to validate numerical models and details the progress that such combinations provide for the understanding of growth mechanisms.

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

PubMed

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

2015-11-01

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

Pectin engineering to modify product quality in potato.

PubMed

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

2011-10-01

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

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

USDA-ARS?s Scientific Manuscript database

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

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

Texture analysis of medical images for radiotherapy applications

PubMed Central

Rizzo, Giovanna

2017-01-01

The high-throughput extraction of quantitative information from medical images, known as radiomics, has grown in interest due to the current necessity to quantitatively characterize tumour heterogeneity. In this context, texture analysis, consisting of a variety of mathematical techniques that can describe the grey-level patterns of an image, plays an important role in assessing the spatial organization of different tissues and organs. For these reasons, the potentiality of texture analysis in the context of radiotherapy has been widely investigated in several studies, especially for the prediction of the treatment response of tumour and normal tissues. Nonetheless, many different factors can affect the robustness, reproducibility and reliability of textural features, thus limiting the impact of this technique. In this review, an overview of the most recent works that have applied texture analysis in the context of radiotherapy is presented, with particular focus on the assessment of tumour and tissue response to radiations. Preliminary, the main factors that have an influence on features estimation are discussed, highlighting the need of more standardized image acquisition and reconstruction protocols and more accurate methods for region of interest identification. Despite all these limitations, texture analysis is increasingly demonstrating its ability to improve the characterization of intratumour heterogeneity and the prediction of clinical outcome, although prospective studies and clinical trials are required to draw a more complete picture of the full potential of this technique. PMID:27885836

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.

A neural model of visual figure-ground segregation from kinetic occlusion.

PubMed

Barnes, Timothy; Mingolla, Ennio

2013-01-01

Freezing is an effective defense strategy for some prey, because their predators rely on visual motion to distinguish objects from their surroundings. An object moving over a background progressively covers (deletes) and uncovers (accretes) background texture while simultaneously producing discontinuities in the optic flow field. These events unambiguously specify kinetic occlusion and can produce a crisp edge, depth perception, and figure-ground segmentation between identically textured surfaces--percepts which all disappear without motion. Given two abutting regions of uniform random texture with different motion velocities, one region appears to be situated farther away and behind the other (i.e., the ground) if its texture is accreted or deleted at the boundary between the regions, irrespective of region and boundary velocities. Consequently, a region with moving texture appears farther away than a stationary region if the boundary is stationary, but it appears closer (i.e., the figure) if the boundary is moving coherently with the moving texture. A computational model of visual areas V1 and V2 shows how interactions between orientation- and direction-selective cells first create a motion-defined boundary and then signal kinetic occlusion at that boundary. Activation of model occlusion detectors tuned to a particular velocity results in the model assigning the adjacent surface with a matching velocity to the far depth. A weak speed-depth bias brings faster-moving texture regions forward in depth in the absence of occlusion (shearing motion). These processes together reproduce human psychophysical reports of depth ordering for key cases of kinetic occlusion displays. Copyright © 2012 Elsevier Ltd. All rights reserved.

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.

Effect of slice thickness on brain magnetic resonance image texture analysis

PubMed Central

2010-01-01

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

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

DOT National Transportation Integrated Search

1975-01-01

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

Computer Graphics Research Laboratory Quarterly Progress Report Number 49, July-September 1993

DTIC Science & Technology

1993-11-22

20 Texture Sampling and Strength Guided Motion: Jeffry S. Nimeroff 23 21 Radiosity : Min-Zhi Shao 24 22 Blended Shape Primitives: Douglas DeCarlo 25 23...placement. "* Extensions of radiosity rendering. "* A discussion of blended shape primitives and the applications in computer vision and computer...user. Radiosity : An improved version of the radiosity renderer is included. This version uses a fast over- relaxation progressive refinement algorithm

Clustering document fragments using background color and texture information

NASA Astrophysics Data System (ADS)

Chanda, Sukalpa; Franke, Katrin; Pal, Umapada

2012-01-01

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

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

PubMed

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

2018-02-01

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

The neutron texture diffractometer at the China Advanced Research Reactor

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

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

PubMed

Lanza, Barbara; Amoruso, Filomena

2018-02-02

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

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

PubMed

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

2017-02-01

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

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

PubMed

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

2016-01-13

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

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

NASA Astrophysics Data System (ADS)

Eldosouky, Ahmed M.; Elkhateeb, Sayed O.

2018-06-01

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

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

ERIC Educational Resources Information Center

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

2005-01-01

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

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

USDA-ARS?s Scientific Manuscript database

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

Texture segmentation by genetic programming.

PubMed

Song, Andy; Ciesielski, Vic

2008-01-01

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

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

NASA Astrophysics Data System (ADS)

Yang, Masaki J. S.

2017-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2012-03-01

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

Cortical mechanisms for the segregation and representation of acoustic textures.

PubMed

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

2010-02-10

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

GLOSS AND TEXTURE CONTROL OF POWDER COATED FILMS. (R827685E04)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Early Articular Cartilage MRI T2 Changes After Anterior Cruciate Ligament Reconstruction Correlate With Later Changes in T2 and Cartilage Thickness

PubMed Central

Williams, Ashley; Winalski, Carl S.; Chu, Constance R.

2018-01-01

Anterior cruciate ligament (ACL) injury is a known risk factor for future development of osteoarthritis (OA). This human clinical study seeks to determine if early changes to cartilage MRI T2 maps between baseline and 6 months following ACL reconstruction (ACLR) are associated with changes to cartilage T2 and cartilage thickness between baseline and 2 years after ACLR. Changes to T2 texture metrics and T2 mean values in medial knee cartilage of 17 human subjects 6 months after ACLR were compared to 2-year changes in T2 and in cartilage thickness of the same areas. T2 texture and mean assessments were also compared to that of 11 uninjured controls. In ACLR subjects, six-month changes in mean T2 correlated to 2-year changes in mean T2 (R = 0.80, p = 0.0001), and 6-month changes to T2 texture metrics, but not T2 mean, correlated with 2-year changes in medial femoral cartilage thickness in 9 of the 20 texture features assessed (R = 0.48–0.72, p ≤ 0.05). Both mean T2 and texture differed (p < 0.05) between ALCR subjects and uninjured controls. Clinical Significance These results show that short-term longitudinal evaluation of T2 map and textural changes may provide early warning of cartilage at risk for progressive degeneration after ACL injury and reconstruction. PMID:27381512

Combining multiple features for color texture classification

NASA Astrophysics Data System (ADS)

Cusano, Claudio; Napoletano, Paolo; Schettini, Raimondo

2016-11-01

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

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

PubMed

Lira, Jorge

2017-05-01

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

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

NASA Technical Reports Server (NTRS)

Key, J.

1990-01-01

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

Textural features of pretreatment 18F-FDG PET/CT images: prognostic significance in patients with advanced T-stage oropharyngeal squamous cell carcinoma.

PubMed

Cheng, Nai-Ming; Fang, Yu-Hua Dean; Chang, Joseph Tung-Chieh; Huang, Chung-Guei; Tsan, Din-Li; Ng, Shu-Hang; Wang, Hung-Ming; Lin, Chien-Yu; Liao, Chun-Ta; Yen, Tzu-Chen

2013-10-01

Previous studies have shown that total lesion glycolysis (TLG) may serve as a prognostic indicator in oropharyngeal squamous cell carcinoma (OPSCC). We sought to investigate whether the textural features of pretreatment (18)F-FDG PET/CT images can provide any additional prognostic information over TLG and clinical staging in patients with advanced T-stage OPSCC. We retrospectively analyzed the pretreatment (18)F-FDG PET/CT images of 70 patients with advanced T-stage OPSCC who had completed concurrent chemoradiotherapy, bioradiotherapy, or radiotherapy with curative intent. All of the patients had data on human papillomavirus (HPV) infection and were followed up for at least 24 mo or until death. A standardized uptake value (SUV) of 2.5 was taken as a cutoff for tumor boundary. The textural features of pretreatment (18)F-FDG PET/CT images were extracted from histogram analysis (SUV variance and SUV entropy), normalized gray-level cooccurrence matrix (uniformity, entropy, dissimilarity, contrast, homogeneity, inverse different moment, and correlation), and neighborhood gray-tone difference matrix (coarseness, contrast, busyness, complexity, and strength). Receiver-operating-characteristic curves were used to identify the optimal cutoff values for the textural features and TLG. Thirteen patients were HPV-positive. Multivariate Cox regression analysis showed that age, tumor TLG, and uniformity were independently associated with progression-free survival (PFS) and disease-specific survival (DSS). TLG, uniformity, and HPV positivity were significantly associated with overall survival (OS). A prognostic scoring system based on TLG and uniformity was derived. Patients who presented with TLG > 121.9 g and uniformity ≤ 0.138 experienced significantly worse PFS, DSS, and OS rates than those without (P < 0.001, < 0.001, and 0.002, respectively). Patients with TLG > 121.9 g or uniformity ≤ 0.138 were further divided according to age, and different PFS and DSS were observed. Uniformity extracted from the normalized gray-level cooccurrence matrix represents an independent prognostic predictor in patients with advanced T-stage OPSCC. A scoring system was developed and may serve as a risk-stratification strategy for guiding therapy.

Effect of homogenization on the properties and microstructure of Mozzarella cheese from buffalo milk.

PubMed

Abd El-Gawad, Mona A M; Ahmed, Nawal S; El-Abd, M M; Abd El-Rafee, S

2012-04-02

The name pasta filata refers to a unique plasticizing and texturing treatments of the fresh curd in hot water that imparts to the finished cheese its characteristic fibrous structure and melting properties. Mozzarella cheese made from standardized homogenized and non-homogenized buffalo milk with 3 and 1.5%fat. The effect of homogenization on rheological, microstructure and sensory evaluation was carried out. Fresh raw buffalo milk and starter cultures of Streptococcus thermophilus and Lactobacillus delbrueckii ssp. bulgaricus were used. The coagulants were calf rennet powder (HA-LA). Standardized buffalo milk was homogenized at 25 kg/cm2 pressure after heating to 60°C using homogenizer. Milk and cheese were analysed. Microstructure of the cheese samples was investigated either with an application of transmission or scanning electron microscope. Statistical analyses were applied on the obtained data. Soluble nitrogen total volatile free fatty acids, soluble tyrosine and tryptophan increased with using homogenized milk and also, increased with relatively decrease in case of homogenized Mozzarella cheese. Meltability of Mozzarella cheese increased with increasing the fat content and storage period and decrease with homogenization. Mozzarella cheese firmness increased with homogenization and also, increased with progressing of storage period. Flavour score, appearance and total score of Mozzarella cheese increased with homogenization and storage period progress, while body and texture score decreased with homogenization and increased with storage period progress. Microstructure of Mozzarella cheese showed the low fat cheese tends to be harder, more crumbly and less smooth than normal. Curd granule junctions were prominent in non-homogenized milk cheese. Homogenization of milk cheese caused changes in the microstructure of the Mozzarella cheese. Microstructure studies of cheese revealed that cheese made from homogenized milk is smoother and has a finer texture than non-homogenized but is also, firmer and more elastic.

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.

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

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

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

PubMed

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

2008-01-01

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

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

PubMed

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

2018-05-14

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

Degassing of basaltic magma: decompression experiments and implications for interpreting the textures of volcanic rocks

NASA Astrophysics Data System (ADS)

Le Gall, Nolwenn; Pichavant, Michel; Cai, Biao; Lee, Peter; Burton, Mike

2017-04-01

Decompression experiments were performed to simulate the ascent of basaltic magma, with the idea of approaching the textural features of volcanic rocks to provide insights into degassing processes. The experiments were conducted in an internally heated pressure vessel between NNO-1.4 and +0.9. H2O-only (4.9 wt%) and H2O-CO2-bearing (0.71-2.45 wt% H2O, 818-1094 ppm CO2) melts, prepared from Stromboli pumice, were synthesized at 1200°C and 200 MPa, continuously decompressed between 200 and 25 MPa at a rate of either 39 or 78 kPa/s (or 1.5 and 3 m/s, respectively), and rapidly quenched. Run products were characterized both texturally (by X-ray computed tomography and scanning electron microscopy) and chemically (by IR spectroscopy and electron microprobe analysis), and then compared with products from basaltic Plinian eruptions and Stromboli paroxysms (bubble textures, glass inclusions). The obtained results demonstrate that textures are controlled by the kinetics of nucleation, growth, coalescence and outgassing of the bubbles, as well as by fragmentation, which largely depend on the presence of CO2 in the melt and the achievement in chemical equilibrium. Textures of the H2O-only melts result from two nucleation events, the first at high pressure (200 < P < 150 MPa) and the second at low pressure (50 < P < 25 MPa), preceding fragmentation. Both events, restricted to narrow P intervals, are driven by melt H2O supersaturation. In contrast, textures of the H2O-CO2-bearing basaltic melts result from continuous bubble nucleation, which is driven by the generation of melts supersaturated in CO2. This persistent non-equilibrium degassing causes the bubbles to evolve through power law distributions, as small bubbles continue to form and grow. This is what is observed in Plinian products. From our results, the evolution to mixed power law-exponential distributions, as found in Stromboli products, is indicative of the prevalence of bubble coalescence and an evolution toward chemical equilibrium. In line with this, a strong correlation was found between experimental and natural bubble textures (bubble number densities, shapes, sizes and distributions), having implications for interpreting bubbles in volcanic rocks and quantifying magma ascent rates. Next step will be to perform in situ decompression experiments to simulate both degassing and crystallization of basaltic magma during ascent in the shallow volcanic conduit (P < 50 MPa), using synchrotron X-ray imaging. The obtained 4D (3D + time) data will help us refine our understanding of magma ascent processes. This experimental programme requires first technology adaptation and development, which is in progress.

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

NASA Astrophysics Data System (ADS)

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

2017-02-01

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

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.

Spectral dependence of texture features integrated with hyperspectral data for area target classification improvement

NASA Astrophysics Data System (ADS)

Bangs, Corey F.; Kruse, Fred A.; Olsen, Chris R.

2013-05-01

Hyperspectral data were assessed to determine the effect of integrating spectral data and extracted texture feature data on classification accuracy. Four separate spectral ranges (hundreds of spectral bands total) were used from the Visible and Near Infrared (VNIR) and Shortwave Infrared (SWIR) portions of the electromagnetic spectrum. Haralick texture features (contrast, entropy, and correlation) were extracted from the average gray-level image for each of the four spectral ranges studied. A maximum likelihood classifier was trained using a set of ground truth regions of interest (ROIs) and applied separately to the spectral data, texture data, and a fused dataset containing both. Classification accuracy was measured by comparison of results to a separate verification set of test ROIs. Analysis indicates that the spectral range (source of the gray-level image) used to extract the texture feature data has a significant effect on the classification accuracy. This result applies to texture-only classifications as well as the classification of integrated spectral data and texture feature data sets. Overall classification improvement for the integrated data sets was near 1%. Individual improvement for integrated spectral and texture classification of the "Urban" class showed approximately 9% accuracy increase over spectral-only classification. Texture-only classification accuracy was highest for the "Dirt Path" class at approximately 92% for the spectral range from 947 to 1343nm. This research demonstrates the effectiveness of texture feature data for more accurate analysis of hyperspectral data and the importance of selecting the correct spectral range to be used for the gray-level image source to extract these features.

Pneumothorax detection in chest radiographs using local and global texture signatures

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

The effect of texture on the shaft surface on the sealing performance of radial lip seals

NASA Astrophysics Data System (ADS)

Guo, Fei; Jia, XiaoHong; Gao, Zhi; Wang, YuMing

2014-07-01

On the basis of elastohydrodynamic model, the present study numerically analyzes the effect of various microdimple texture shapes, namely, circular, square, oriented isosceles triangular, on the pumping rate and the friction torque of radial lip seals, and determines the microdimple texture shape that can produce positive pumping rate. The area ratio, depth and shape dimension of a single texture are the most important geometric parameters which influence the tribological performance. According to the selected texture shape, parameter analysis is conducted to determine the optimal combination for the above three parameters. Simultaneously, the simulated performances of radial lip seal with texture on the shaft surface are compared with those of the conventional lip seal without any texture on the shaft surface.

Early classification of Alzheimer's disease using hippocampal texture from structural MRI

NASA Astrophysics Data System (ADS)

Zhao, Kun; Ding, Yanhui; Wang, Pan; Dou, Xuejiao; Zhou, Bo; Yao, Hongxiang; An, Ningyu; Zhang, Yongxin; Zhang, Xi; Liu, Yong

2017-03-01

Convergent evidence has been collected to support that Alzheimer's disease (AD) is associated with reduction in hippocampal volume based on anatomical magnetic resonance imaging (MRI) and impaired functional connectivity based on functional MRI. Radiomics texture analysis has been previously successfully used to identify MRI biomarkers of several diseases, including AD, mild cognitive impairment and multiple sclerosis. In this study, our goal was to determine if MRI hippocampal textures, including the intensity, shape, texture and wavelet features, could be served as an MRI biomarker of AD. For this purpose, the texture marker was trained and evaluated from MRI data of 48 AD and 39 normal samples. The result highlights the presence of hippocampal texture abnormalities in AD, and the possibility that texture may serve as a neuroimaging biomarker for AD.

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

PubMed

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

2014-01-01

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

The use of an ion-beam source to alter the surface morphology of biological implant materials

NASA Technical Reports Server (NTRS)

Weigand, A. J.

1978-01-01

An electron bombardment, ion thruster was used as a neutralized-ion beam sputtering source to texture the surfaces of biological implant materials. Scanning electron microscopy was used to determine surface morphology changes of all materials after ion-texturing. Electron spectroscopy for chemical analysis was used to determine the effects of ion texturing on the surface chemical composition of some polymers. Liquid contact angle data were obtained for ion textured and untextured polymer samples. Results of tensile and fatigue tests of ion-textured metal alloys are presented. Preliminary data of tissue response to ion textured surfaces of some metals, polytetrafluoroethylene, alumina, and segmented polyurethane were obtained.

Aesthetic perception of visual textures: a holistic exploration using texture analysis, psychological experiment, and perception modeling.

PubMed

Liu, Jianli; Lughofer, Edwin; Zeng, Xianyi

2015-01-01

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

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

PubMed

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

2018-04-01

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

Decoupling of superposed textures in an electrically biased piezoceramic with a 100 preferred orientation

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

Fancher, Chris M.; Blendell, John E.; Bowman, Keith J.

2017-02-07

A method leveraging Rietveld full-pattern texture analysis to decouple induced domain texture from a preferred grain orientation is presented in this paper. The proposed method is demonstrated by determining the induced domain texture in a polar polymorph of 100 oriented 0.91Bi 1/2Na 1/2TiO 3-0.07BaTiO 3-0.02K 0.5Na 0.5NbO 3. Domain textures determined using the present method are compared with results obtained via single peak fitting. Texture determined using single peak fitting estimated more domain alignment than that determined using the Rietveld based method. These results suggest that the combination of grain texture and phase transitions can lead to single peak fittingmore » under or over estimating domain texture. Finally, while demonstrated for a bulk piezoelectric, the proposed method can be applied to quantify domain textures in multi-component systems and thin films.« less

Texture in steel plates revealed by laser ultrasonic surface acoustic waves velocity dispersion analysis.

PubMed

Yin, Anmin; Wang, Xiaochen; Glorieux, Christ; Yang, Quan; Dong, Feng; He, Fei; Wang, Yanlong; Sermeus, Jan; Van der Donck, Tom; Shu, Xuedao

2017-07-01

A photoacoustic, laser ultrasonics based approach in an Impulsive Stimulated Scattering (ISS) implementation was used to investigate the texture in polycrystalline metal plates. The angular dependence of the 'polycrystalline' surface acoustic wave (SAW) velocity measured along regions containing many grains was experimentally determined and compared with simulated results that were based on the angular dependence of the 'single grain' SAW velocity within single grains and the grain orientation distribution. The polycrystalline SAW velocities turn out to vary with texture. The SAW velocities and their angular variations for {110} texture were found to be larger than that the ones for {111} texture or the strong γ fiber texture. The SAW velocities for {001} texture were larger than for {111} texture, but with almost the same angular dependence. The results infer the feasibility to apply angular SAW angular dispersion measurements by laser ultrasonics for on-line texture monitoring. Copyright © 2017 Elsevier B.V. All rights reserved.

The analysis of image feature robustness using cometcloud

PubMed Central

Qi, Xin; Kim, Hyunjoo; Xing, Fuyong; Parashar, Manish; Foran, David J.; Yang, Lin

2012-01-01

The robustness of image features is a very important consideration in quantitative image analysis. The objective of this paper is to investigate the robustness of a range of image texture features using hematoxylin stained breast tissue microarray slides which are assessed while simulating different imaging challenges including out of focus, changes in magnification and variations in illumination, noise, compression, distortion, and rotation. We employed five texture analysis methods and tested them while introducing all of the challenges listed above. The texture features that were evaluated include co-occurrence matrix, center-symmetric auto-correlation, texture feature coding method, local binary pattern, and texton. Due to the independence of each transformation and texture descriptor, a network structured combination was proposed and deployed on the Rutgers private cloud. The experiments utilized 20 randomly selected tissue microarray cores. All the combinations of the image transformations and deformations are calculated, and the whole feature extraction procedure was completed in 70 minutes using a cloud equipped with 20 nodes. Center-symmetric auto-correlation outperforms all the other four texture descriptors but also requires the longest computational time. It is roughly 10 times slower than local binary pattern and texton. From a speed perspective, both the local binary pattern and texton features provided excellent performance for classification and content-based image retrieval. PMID:23248759

Texture analysis of high-resolution FLAIR images for TLE

NASA Astrophysics Data System (ADS)

Jafari-Khouzani, Kourosh; Soltanian-Zadeh, Hamid; Elisevich, Kost

2005-04-01

This paper presents a study of the texture information of high-resolution FLAIR images of the brain with the aim of determining the abnormality and consequently the candidacy of the hippocampus for temporal lobe epilepsy (TLE) surgery. Intensity and volume features of the hippocampus from FLAIR images of the brain have been previously shown to be useful in detecting the abnormal hippocampus in TLE. However, the small size of the hippocampus may limit the texture information. High-resolution FLAIR images show more details of the abnormal intensity variations of the hippocampi and therefore are more suitable for texture analysis. We study and compare the low and high-resolution FLAIR images of six epileptic patients. The hippocampi are segmented manually by an expert from T1-weighted MR images. Then the segmented regions are mapped on the corresponding FLAIR images for texture analysis. The 2-D wavelet transforms of the hippocampi are employed for feature extraction. We compare the ability of the texture features from regular and high-resolution FLAIR images to distinguish normal and abnormal hippocampi. Intracranial EEG results as well as surgery outcome are used as gold standard. The results show that the intensity variations of the hippocampus are related to the abnormalities in the TLE.

Three-dimensional ultrasound-based texture analysis of the effect of atorvastatin on carotid atherosclerosis

NASA Astrophysics Data System (ADS)

Awad, Joseph; Krasinski, Adam; Spence, David; Parraga, Grace; Fenster, Aaron

2010-03-01

Carotid atherosclerosis is the major cause of ischemic stroke, a leading cause of death and disability. This is driving the development of image analysis methods to quantitatively evaluate local arterial effects of potential treatments of carotid disease. Here we investigate the use of novel texture analysis tools to detect potential changes in the carotid arteries after statin therapy. Three-dimensional (3D) carotid ultrasound images were acquired from the left and right carotid arteries of 35 subjects (16 treated with 80 mg atorvastatin and 19 treated with placebo) at baseline and after 3 months of treatment. Two-hundred and seventy texture features were extracted from 3D ultrasound carotid artery images. These images previously had their vessel walls (VW) manually segmented. Highly ranked individual texture features were selected and compared to the VW volume (VWV) change using 3 measures: distance between classes, Wilcoxon rank sum test, and accuracy of the classifiers. Six classifiers were used. Using texture feature (L7R7) increases the average accuracy and area under the ROC curve to 74.4% and 0.72 respectively compared to 57.2% and 0.61 using VWV change. Thus, the results demonstrate that texture features are more sensitive in detecting drug effects on the carotid vessel wall than VWV change.

Computer-Aided Grading of Lymphangioleiomyomatosis (LAM) using HRCT

PubMed Central

Yao, Jianhua; Avila, Nilo; Dwyer, Andrew; Taveira-DaSilva, Angelo M.; Hathaway, Olanda M.; Moss, Joel

2010-01-01

Lymphangioleiomyomatosis (LAM) is a multisystem disorder associated with proliferation of smooth muscle-like cells, which leads to destruction of lung parenchyma. Subjective grading of LAM on HRCT is imprecise and can be arduous especially in cases with severe involvement. We propose a computer-aided evaluation system that grades LAM involvement based on analysis of lung texture patterns. A committee of support vector machines is employed for classification. The system was tested on 36 patients. The computer grade demonstrates good correlation with subjective radiologist grade (R=0.91, p<0.0001) and pulmonary functional tests (R=0.85, p<0.0001). The grade also provides precise progression assessment of disease over time. PMID:21625320

Textural signatures for wetland vegetation

NASA Technical Reports Server (NTRS)

Whitman, R. I.; Marcellus, K. L.

1973-01-01

This investigation indicates that unique textural signatures do exist for specific wetland communities at certain times in the growing season. When photographs with the proper resolution are obtained, the textural features can identify the spectral features of the vegetation community seen with lower resolution mapping data. The development of a matrix of optimum textural signatures is the goal of this research. Seasonal variations of spectral and textural features are particularly important when performing a vegetations analysis of fresh water marshes. This matrix will aid in flight planning, since expected seasonal variations and resolution requirements can be established prior to a given flight mission.

Efficient Data Mining for Local Binary Pattern in Texture Image Analysis

PubMed Central

Kwak, Jin Tae; Xu, Sheng; Wood, Bradford J.

2015-01-01

Local binary pattern (LBP) is a simple gray scale descriptor to characterize the local distribution of the grey levels in an image. Multi-resolution LBP and/or combinations of the LBPs have shown to be effective in texture image analysis. However, it is unclear what resolutions or combinations to choose for texture analysis. Examining all the possible cases is impractical and intractable due to the exponential growth in a feature space. This limits the accuracy and time- and space-efficiency of LBP. Here, we propose a data mining approach for LBP, which efficiently explores a high-dimensional feature space and finds a relatively smaller number of discriminative features. The features can be any combinations of LBPs. These may not be achievable with conventional approaches. Hence, our approach not only fully utilizes the capability of LBP but also maintains the low computational complexity. We incorporated three different descriptors (LBP, local contrast measure, and local directional derivative measure) with three spatial resolutions and evaluated our approach using two comprehensive texture databases. The results demonstrated the effectiveness and robustness of our approach to different experimental designs and texture images. PMID:25767332

Color and texture associations in voice-induced synesthesia

PubMed Central

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

2013-01-01

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

Spatially resolved texture and microstructure evolution of additively manufactured and gas gun deformed 304L stainless steel investigated by neutron diffraction and electron backscatter diffraction

DOE PAGES

Takajo, Shigehiro; Brown, Donald William; Clausen, Bjorn; ...

2018-04-30

In this study, we report the characterization of a 304L stainless steel cylindrical projectile produced by additive manufacturing. The projectile was compressively deformed using a Taylor Anvil Gas Gun, leading to a huge strain gradient along the axis of the deformed cylinder. Spatially resolved neutron diffraction measurements on the HIgh Pressure Preferred Orientation time-of-flight diffractometer (HIPPO) and Spectrometer for Materials Research at Temperature and Stress diffractometer (SMARTS) beamlines at the Los Alamos Neutron Science CEnter (LANSCE) with Rietveld and single-peak analysis were used to quantitatively evaluate the volume fractions of the α, γ, and ε phases as well as residualmore » strain and texture. The texture of the γ phase is consistent with uniaxial compression, while the α texture can be explained by the Kurdjumov–Sachs relationship from the γ texture after deformation. This indicates that the material first deformed in the γ phase and subsequently transformed at larger strains. The ε phase was only found in volumes close to the undeformed material with a texture connected to the γ texture by the Shoji–Nishiyama orientation relationship. This allows us to conclude that the ε phase occurs as an intermediate phase at lower strain, and is superseded by the α phase when strain increases further. We found a proportionality between the root-mean-squared microstrain of the γ phase, dominated by the dislocation density, with the α volume fraction, consistent with strain-induced martensite α formation. In conclusion, knowledge of the sample volume with the ε phase from the neutron diffraction analysis allowed us to identify the ε phase by electron back scatter diffraction analysis, complementing the neutron diffraction analysis with characterization on the grain level.« less

Spatially resolved texture and microstructure evolution of additively manufactured and gas gun deformed 304L stainless steel investigated by neutron diffraction and electron backscatter diffraction

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

Takajo, Shigehiro; Brown, Donald William; Clausen, Bjorn

In this study, we report the characterization of a 304L stainless steel cylindrical projectile produced by additive manufacturing. The projectile was compressively deformed using a Taylor Anvil Gas Gun, leading to a huge strain gradient along the axis of the deformed cylinder. Spatially resolved neutron diffraction measurements on the HIgh Pressure Preferred Orientation time-of-flight diffractometer (HIPPO) and Spectrometer for Materials Research at Temperature and Stress diffractometer (SMARTS) beamlines at the Los Alamos Neutron Science CEnter (LANSCE) with Rietveld and single-peak analysis were used to quantitatively evaluate the volume fractions of the α, γ, and ε phases as well as residualmore » strain and texture. The texture of the γ phase is consistent with uniaxial compression, while the α texture can be explained by the Kurdjumov–Sachs relationship from the γ texture after deformation. This indicates that the material first deformed in the γ phase and subsequently transformed at larger strains. The ε phase was only found in volumes close to the undeformed material with a texture connected to the γ texture by the Shoji–Nishiyama orientation relationship. This allows us to conclude that the ε phase occurs as an intermediate phase at lower strain, and is superseded by the α phase when strain increases further. We found a proportionality between the root-mean-squared microstrain of the γ phase, dominated by the dislocation density, with the α volume fraction, consistent with strain-induced martensite α formation. In conclusion, knowledge of the sample volume with the ε phase from the neutron diffraction analysis allowed us to identify the ε phase by electron back scatter diffraction analysis, complementing the neutron diffraction analysis with characterization on the grain level.« less

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

PubMed

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

2012-11-30

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

Domain Engineered Magnetoelectric Thin Films for High Sensitivity Resonant Magnetic Field Sensors

DTIC Science & Technology

2011-12-01

synthesis and texture analysis Sol-gel deposition and RF sputtering process was developed for deposition of PZT on Pt/Ti/Si02/Si (hereafter...well textured (i.e. with preferred crystalline orientation). To texture and obtain crack-free thick PZT RF films, we employed pre- treated substrates...and post-deposition annealing. One pre-treatment was the use of seed layer of textured PZT sol-gel thin film of thickness 65-85nm [1]. • Oean

Textural features for radar image analysis

NASA Technical Reports Server (NTRS)

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

1981-01-01

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

Texture-dependent motion signals in primate middle temporal area

PubMed Central

Gharaei, Saba; Tailby, Chris; Solomon, Selina S; Solomon, Samuel G

2013-01-01

Neurons in the middle temporal (MT) area of primate cortex provide an important stage in the analysis of visual motion. For simple stimuli such as bars and plaids some neurons in area MT – pattern cells – seem to signal motion independent of contour orientation, but many neurons – component cells – do not. Why area MT supports both types of receptive field is unclear. To address this we made extracellular recordings from single units in area MT of anaesthetised marmoset monkeys and examined responses to two-dimensional images with a large range of orientations and spatial frequencies. Component and pattern cell response remained distinct during presentation of these complex spatial textures. Direction tuning curves were sharpest in component cells when a texture contained a narrow range of orientations, but were similar across all neurons for textures containing all orientations. Response magnitude of pattern cells, but not component cells, increased with the spatial bandwidth of the texture. In addition, response variability in all neurons was reduced when the stimulus was rich in spatial texture. Fisher information analysis showed that component cells provide more informative responses than pattern cells when a texture contains a narrow range of orientations, but pattern cells had more informative responses for broadband textures. Component cells and pattern cells may therefore coexist because they provide complementary and parallel motion signals. PMID:24000175

Investigation of the Influence of Shapes-Texture on Surface Deformation of UHMWPE as a Bearing Material in Static Normal Load and Rolling Contact

NASA Astrophysics Data System (ADS)

Lestari, W. D.; Ismail, R.; Jamari, J.; Bayuseno, A. P.

2017-05-01

Surface texture is a common method for improving wear properties of a tribo-pair of soft and hard bearing material. The reduction of wear rates on the contacting surface material is becoming important issues. In the present study, analysis of the contact pressure on the flat surface of UHMWPE (Ultra High Molecular Weight Polyethylene) under the static- and rolling motion with the surface of steel ball used the 3D finite element method (FEM) (the ABAQUS software version 6.12). Five shaped-texture models (square, circle, ellipse, triangle, and chevron) were presented on the flat surface for analysis. The normal load of 17, 30 and 50 N was deliberately set-up for static and rolling contact analysis. The contact pressure was determined to predict the wear behavior of the shaped-texture on the flat surface of UHMWPE. The results have shown that the static normal load yielded the lowest von-Mises stress distribution on the shaped-texture of the ellipse for all values applied a load, while the square shape experienced the highest stress distribution. Under rolling contact, however, the increasing load yielded the increasing von Mises stress distribution for the texture with a triangle shape. Moreover, the texture shapes for circle, ellipse, and chevron respectively, may undergo the lowest stress distribution for all load. The wear calculation provided that the circle and square shape may undergo the highest wear rates. Obviously, the surface texture of circle, ellipse, and chevron may experience the lowest wear rates and is potential for use in the surface engineering of bearing materials.

Breast Implant-Associated Anaplastic Large Cell Lymphoma in Australia and New Zealand: High-Surface-Area Textured Implants Are Associated with Increased Risk.

PubMed

Loch-Wilkinson, Anna; Beath, Kenneth J; Knight, Robert John William; Wessels, William Louis Fick; Magnusson, Mark; Papadopoulos, Tim; Connell, Tony; Lofts, Julian; Locke, Michelle; Hopper, Ingrid; Cooter, Rodney; Vickery, Karen; Joshi, Preeti Avinash; Prince, H Miles; Deva, Anand K

2017-10-01

The association between breast implants and breast implant-associated anaplastic large cell lymphoma (ALCL) has been confirmed. Implant-related risk has been difficult to estimate to date due to incomplete datasets. All cases in Australia and New Zealand were identified and analyzed. Textured implants reported in this group were subjected to surface area analysis. Sales data from three leading breast implant manufacturers (i.e., Mentor, Allergan, and Silimed) dating back to 1999 were secured to estimate implant-specific risk. Fifty-five cases of breast implant-associated ALCL were diagnosed in Australia and New Zealand between 2007 and 2016. The mean age of patients was 47.1 years and the mean time of implant exposure was 7.46 years. There were four deaths in the series related to mass and/or metastatic presentation. All patients were exposed to textured implants. Surface area analysis confirmed that higher surface area was associated with 64 of the 75 implants used (85.3 percent). Biocell salt loss textured (Allergan, Inamed, and McGhan) implants accounted for 58.7 percent of the implants used in this series. Comparative analysis showed the risk of developing breast implant-associated ALCL to be 14.11 times higher with Biocell textured implants and 10.84 higher with polyurethane (Silimed) textured implants compared with Siltex textured implants. This study has calculated implant-specific risk of breast implant-associated ALCL. Higher-surface-area textured implants have been shown to significantly increase the risk of breast implant-associated ALCL in Australia and New Zealand. The authors present a unifying hypothesis to explain these observations.

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.

Time-frequency feature representation using multi-resolution texture analysis and acoustic activity detector for real-life speech emotion recognition.

PubMed

Wang, Kun-Ching

2015-01-14

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

Mammographic parenchymal texture as an imaging marker of hormonal activity: a comparative study between pre- and post-menopausal women

NASA Astrophysics Data System (ADS)

Daye, Dania; Bobo, Ezra; Baumann, Bethany; Ioannou, Antonios; Conant, Emily F.; Maidment, Andrew D. A.; Kontos, Despina

2011-03-01

Mammographic parenchymal texture patterns have been shown to be related to breast cancer risk. Yet, little is known about the biological basis underlying this association. Here, we investigate the potential of mammographic parenchymal texture patterns as an inherent phenotypic imaging marker of endogenous hormonal exposure of the breast tissue. Digital mammographic (DM) images in the cranio-caudal (CC) view of the unaffected breast from 138 women diagnosed with unilateral breast cancer were retrospectively analyzed. Menopause status was used as a surrogate marker of endogenous hormonal activity. Retroareolar 2.5cm2 ROIs were segmented from the post-processed DM images using an automated algorithm. Parenchymal texture features of skewness, coarseness, contrast, energy, homogeneity, grey-level spatial correlation, and fractal dimension were computed. Receiver operating characteristic (ROC) curve analysis was performed to evaluate feature classification performance in distinguishing between 72 pre- and 66 post-menopausal women. Logistic regression was performed to assess the independent effect of each texture feature in predicting menopause status. ROC analysis showed that texture features have inherent capacity to distinguish between pre- and post-menopausal statuses (AUC>0.5, p<0.05). Logistic regression including all texture features yielded an ROC curve with an AUC of 0.76. Addition of age at menarche, ethnicity, contraception use and hormonal replacement therapy (HRT) use lead to a modest model improvement (AUC=0.78) while texture features maintained significant contribution (p<0.05). The observed differences in parenchymal texture features between pre- and post- menopausal women suggest that mammographic texture can potentially serve as a surrogate imaging marker of endogenous hormonal activity.

Mammographic phenotypes of breast cancer risk driven by breast anatomy

NASA Astrophysics Data System (ADS)

Gastounioti, Aimilia; Oustimov, Andrew; Hsieh, Meng-Kang; Pantalone, Lauren; Conant, Emily F.; Kontos, Despina

2017-03-01

Image-derived features of breast parenchymal texture patterns have emerged as promising risk factors for breast cancer, paving the way towards personalized recommendations regarding women's cancer risk evaluation and screening. The main steps to extract texture features of the breast parenchyma are the selection of regions of interest (ROIs) where texture analysis is performed, the texture feature calculation and the texture feature summarization in case of multiple ROIs. In this study, we incorporate breast anatomy in these three key steps by (a) introducing breast anatomical sampling for the definition of ROIs, (b) texture feature calculation aligned with the structure of the breast and (c) weighted texture feature summarization considering the spatial position and the underlying tissue composition of each ROI. We systematically optimize this novel framework for parenchymal tissue characterization in a case-control study with digital mammograms from 424 women. We also compare the proposed approach with a conventional methodology, not considering breast anatomy, recently shown to enhance the case-control discriminatory capacity of parenchymal texture analysis. The case-control classification performance is assessed using elastic-net regression with 5-fold cross validation, where the evaluation measure is the area under the curve (AUC) of the receiver operating characteristic. Upon optimization, the proposed breast-anatomy-driven approach demonstrated a promising case-control classification performance (AUC=0.87). In the same dataset, the performance of conventional texture characterization was found to be significantly lower (AUC=0.80, DeLong's test p-value<0.05). Our results suggest that breast anatomy may further leverage the associations of parenchymal texture features with breast cancer, and may therefore be a valuable addition in pipelines aiming to elucidate quantitative mammographic phenotypes of breast cancer risk.

Simulation of complex magnesium alloy texture using the axial component fit method with central normal distributions

NASA Astrophysics Data System (ADS)

Ivanova, T. M.; Serebryany, V. N.

2017-12-01

The component fit method in quantitative texture analysis assumes that the texture of the polycrystalline sample can be represented by a superposition of weighted standard distributions those are characterized by position in the orientation space, shape and sharpness of the scattering. The components of the peak and axial shapes are usually used. It is known that an axial texture develops in materials subjected to direct pressing. In this paper we considered the possibility of modelling a texture of a magnesium sample subjected to equal-channel angular pressing with axial components only. The results obtained make it possible to conclude that ECAP is also a process leading to the appearance of an axial texture in magnesium alloys.

Texture and phase analysis of deformed SUS304 by using HIPPO

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

Takajo, Shigehiro; Vogel, Sven C.

2016-11-15

These slides represent the author's research activity at Los Alamos National Laboratory (LANL), which is about texture and phase analysis of deformed SUS304 by using HIPPO. The following topics are covered: diffraction histogram at each sample position, diffraction histogram (all bank data averaged), possiblity of ε-phase, MAUD analysis with including ε-phase.

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

NASA Technical Reports Server (NTRS)

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

1974-01-01

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

Texton-based analysis of paintings

NASA Astrophysics Data System (ADS)

van der Maaten, Laurens J. P.; Postma, Eric O.

2010-08-01

The visual examination of paintings is traditionally performed by skilled art historians using their eyes. Recent advances in intelligent systems may support art historians in determining the authenticity or date of creation of paintings. In this paper, we propose a technique for the examination of brushstroke structure that views the wildly overlapping brushstrokes as texture. The analysis of the painting texture is performed with the help of a texton codebook, i.e., a codebook of small prototypical textural patches. The texton codebook can be learned from a collection of paintings. Our textural analysis technique represents paintings in terms of histograms that measure the frequency by which the textons in the codebook occur in the painting (so-called texton histograms). We present experiments that show the validity and effectiveness of our technique for textural analysis on a collection of digitized high-resolution reproductions of paintings by Van Gogh and his contemporaries. As texton histograms cannot be easily be interpreted by art experts, the paper proposes to approaches to visualize the results on the textural analysis. The first approach visualizes the similarities between the histogram representations of paintings by employing a recently proposed dimensionality reduction technique, called t-SNE. We show that t-SNE reveals a clear separation of paintings created by Van Gogh and those created by other painters. In addition, the period of creation is faithfully reflected in the t-SNE visualizations. The second approach visualizes the similarities and differences between paintings by highlighting regions in a painting in which the textural structure of the painting is unusual. We illustrate the validity of this approach by means of an experiment in which we highlight regions in a painting by Monet that are not very "Van Gogh-like". Taken together, we believe the tools developed in this study are well capable of assisting for art historians in support of their study of paintings.

Septate-tubular textures in 2.0-Ga pillow lavas from the Pechenga Greenstone Belt: a nano-spectroscopic approach to investigate their biogenicity.

PubMed

Fliegel, D; Wirth, R; Simonetti, A; Furnes, H; Staudigel, H; Hanski, E; Muehlenbachs, K

2010-12-01

Pillow lava rims and interpillow hyaloclastites from the upper part of the Pechenga Greenstone Belt, Kola Peninsula, N-Russia contain rare tubular textures 15-20 μm in diameter and up to several hundred μm long in prehnite-pumpellyite to lower greenschist facies meta-volcanic glass. The textures are septate with regular compartments 5-20 μm across and exhibit branching, stopping and no intersecting features. Synchrotron micro-energy dispersive X-ray was used to image elemental distributions; scanning transmission X-ray microscopy, Fe L-edge and C K-edge were used to identify iron and carbon speciation at interfaces between the tubular textures and the host rock. In situ U-Pb radiometric dating by LA-MC-ICP-MS (laser ablation multicollector inductively coupled plasma mass spectrometry) of titanite from pillow lavas yielded a metamorphic age of 1790 ± 89 Ma. Focused ion-beam milling combined with transmission electron microscopy was used to analyze the textures in three dimensions. Electron diffraction showed that the textures are mineralized by orientated pumpellyite. On the margins of the tubes, an interface between mica or chlorite and the pumpellyite shows evidence of dissolution reactions where the pumpellyite is replaced by mica/chlorite. A thin poorly crystalline Fe-phase, probably precipitated out of solution, occurs at the interface between pumpellyite and mica/chlorite. This sequence of phases leads to the hypothesis that the tubes were initially hollow, compartmentalized structures in volcanic glass that were mineralized by pumpellyite during low-grade metamorphism. Later, a Fe-bearing fluid mineralized the compartments between the pumpellyite and lastly the pumpellyite was partially dissolved and replaced by chlorite during greenschist metamorphism. The most plausible origin for a septate-tubular texture is a progressive etching of the host matrix by several generations of microbes and subsequently these tubes were filled by authigenic mineral precipitates. This preserves the textures in the rock record over geological time. The micro textures reported here thus represent a pumpellyite-mineralized trace fossil that records a Paleoproterozoic sub-seafloor biosphere. © 2010 Blackwell Publishing Ltd.

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

PubMed

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

2017-06-22

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

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

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

Nawrocki, J; Chino, J; Craciunescu, O

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

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

USDA-ARS?s Scientific Manuscript database

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

Detection of Focal Cortical Dysplasia Lesions in MRI Using Textural Features

NASA Astrophysics Data System (ADS)

Loyek, Christian; Woermann, Friedrich G.; Nattkemper, Tim W.

Focal cortical dysplasia (FCD) is a frequent cause of medically refractory partial epilepsy. The visual identification of FCD lesions on magnetic resonance images (MRI) is a challenging task in standard radiological analysis. Quantitative image analysis which tries to assist in the diagnosis of FCD lesions is an active field of research. In this work we investigate the potential of different texture features, in order to explore to what extent they are suitable for detecting lesional tissue. As a result we can show first promising results based on segmentation and texture classification.

Preference evaluation of ground beef by untrained subjects with three levels of finely textured beef

PubMed Central

Depue, Sandra Molly; Neilson, Morgan Marie

2018-01-01

After receiving bad publicity in 2012 and being removed from many ground beef products, finely textured beef (referred to as ‘pink slime’ by some) is making a comeback. Some of its proponents argue that consumers prefer ground beef containing finely textured beef, but no objective scientific party has tested this claim—that is the purpose of the present study. Over 200 untrained subjects participated in a sensory analysis in which they tasted one ground beef sample with no finely textured beef, another with 15% finely textured beef (by weight), and another with more than 15%. Beef with 15% finely textured beef has an improved juiciness (p < 0.01) and tenderness (p < 0.01) quality. However, subjects rate the flavor-liking and overall likeability the same regardless of the finely textured beef content. Moreover, when the three beef types are consumed as part of a slider (small hamburger), subjects are indifferent to the level of finely textured beef. PMID:29342174

Field-Scale Evaluation of Infiltration Parameters From Soil Texture for Hydrologic Analysis

NASA Astrophysics Data System (ADS)

Springer, Everett P.; Cundy, Terrance W.

1987-02-01

Recent interest in predicting soil hydraulic properties from simple physical properties such as texture has major implications in the parameterization of physically based models of surface runoff. This study was undertaken to (1) compare, on a field scale, soil hydraulic parameters predicted from texture to those derived from field measurements and (2) compare simulated overland flow response using these two parameter sets. The parameters for the Green-Ampt infiltration equation were obtained from field measurements and using texture-based predictors for two agricultural fields, which were mapped as single soil units. Results of the analyses were that (1) the mean and variance of the field-based parameters were not preserved by the texture-based estimates, (2) spatial and cross correlations between parameters were induced by the texture-based estimation procedures, (3) the overland flow simulations using texture-based parameters were significantly different than those from field-based parameters, and (4) simulations using field-measured hydraulic conductivities and texture-based storage parameters were very close to simulations using only field-based parameters.

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.

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

PubMed

Valdés Hernández, Maria Del C; González-Castro, Victor; Chappell, Francesca M; Sakka, Eleni; Makin, Stephen; Armitage, Paul A; Nailon, William H; Wardlaw, Joanna M

2017-01-01

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

Negating Tissue Contracture Improves Volume Maintenance and Longevity of In Vivo Engineered Tissues.

PubMed

Lytle, Ian F; Kozlow, Jeffrey H; Zhang, Wen X; Buffington, Deborah A; Humes, H David; Brown, David L

2015-10-01

Engineering large, complex tissues in vivo requires robust vascularization to optimize survival, growth, and function. Previously, the authors used a "chamber" model that promotes intense angiogenesis in vivo as a platform for functional three-dimensional muscle and renal engineering. A silicone membrane used to define the structure and to contain the constructs is successful in the short term. However, over time, generated tissues contract and decrease in size in a manner similar to capsular contracture seen around many commonly used surgical implants. The authors hypothesized that modification of the chamber structure or internal surface would promote tissue adherence and maintain construct volume. Three chamber configurations were tested against volume maintenance. Previously studied, smooth silicone surfaces were compared to chambers modified for improved tissue adherence, with multiple transmembrane perforations or lined with a commercially available textured surface. Tissues were allowed to mature long term in a rat model, before analysis. On explantation, average tissue masses were 49, 102, and 122 mg; average volumes were 74, 158 and 176 μl; and average cross-sectional areas were 1.6, 6.7, and 8.7 mm for the smooth, perforated, and textured groups, respectively. Both perforated and textured designs demonstrated significantly greater measures than the smooth-surfaced constructs in all respects. By modifying the design of chambers supporting vascularized, three-dimensional, in vivo tissue engineering constructs, generated tissue mass, volume, and area can be maintained over a long time course. Successful progress in the scale-up of construct size should follow, leading to improved potential for development of increasingly complex engineered tissues.

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

Li, B; Yu, H; Jara, H

Purpose: To compare enhanced Laws texture derived from parametric proton density (PD) maps to other MRI-based surrogate markers (T2, PD, ADC) in assessing degrees of liver fibrosis in a murine model of hepatic fibrosis using 11.7T scanner. Methods: This animal study was IACUC approved. Fourteen mice were divided into control (n=1) and experimental (n=13). The latter were fed a DDC-supplemented diet to induce hepatic fibrosis. Liver specimens were imaged using an 11.7T scanner; the parametric PD, T2, and ADC maps were generated from spin-echo pulsed field gradient and multi-echo spin-echo acquisitions. Enhanced Laws texture analysis was applied to the PDmore » maps: first, hepatic blood vessels and liver margins were segmented/removed using an automated dual-clustering algorithm; secondly, an optimal thresholding algorithm was applied to reduce the partial volume artifact; next, mean and stdev were corrected to minimize grayscale variation across images; finally, Laws texture was extracted. Degrees of fibrosis was assessed by an experienced pathologist and digital image analysis (%Area Fibrosis). Scatterplots comparing enhanced Laws texture, T2, PD, and ADC values to degrees of fibrosis were generated and correlation coefficients were calculated. Unenhanced Laws texture was also compared to assess the effectiveness of the proposed enhancements. Results: Hepatic fibrosis and the enhanced Laws texture were strongly correlated with higher %Area Fibrosis associated with higher Laws texture (r=0.89). Only a moderate correlation was detected between %Area Fibrosis and unenhanced Laws texture (r=0.70). Strong correlation also existed between ADC and %Area Fibrosis (r=0.86). Moderate correlations were seen between %Area Fibrosis and PD (r=0.65) and T2 (r=0.66). Conclusions: Higher degrees of hepatic fibrosis are associated with increased Laws texture. The proposed enhancements improve the accuracy of Laws texture. Enhanced Laws texture features are more accurate than PD and T2 in assessing fibrosis, and can potentially serve as an accurate surrogate marker for hepatic fibrosis.« less

Genome-wide association study unravels the genetic control of the apple volatilome and its interplay with fruit texture.

PubMed

Farneti, Brian; Di Guardo, Mario; Khomenko, Iuliia; Cappellin, Luca; Biasioli, Franco; Velasco, Riccardo; Costa, Fabrizio

2017-03-01

Fruit quality represents a fundamental factor guiding consumers' preferences. Among apple quality traits, volatile organic compounds and texture features play a major role. Proton Transfer Reaction-Time of Flight-Mass Spectrometry (PTR-ToF-MS), coupled with an artificial chewing device, was used to profile the entire apple volatilome of 162 apple accessions, while the fruit texture was dissected with a TAXT-AED texture analyzer. The array of volatile compounds was classed into seven major groups and used in a genome-wide association analysis carried out with 9142 single nucleotide polymorphisms (SNPs). Marker-trait associations were identified on seven chromosomes co-locating with important candidate genes for aroma, such as MdAAT1 and MdIGS. The integration of volatilome and fruit texture data conducted with a multiple factor analysis unraveled contrasting behavior, underlying opposite regulation of the two fruit quality aspects. The association analysis using the first two principal components identified two QTLs located on chromosomes 10 and 2, respectively. The distinction of the apple accessions on the basis of the allelic configuration of two functional markers, MdPG1 and MdACO1, shed light on the type of interplay existing between fruit texture and the production of volatile organic compounds. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

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

PubMed

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

2018-04-01

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

Lung texture in serial thoracic CT scans: Assessment of change introduced by image registration1

PubMed Central

Cunliffe, Alexandra R.; Al-Hallaq, Hania A.; Labby, Zacariah E.; Pelizzari, Charles A.; Straus, Christopher; Sensakovic, William F.; Ludwig, Michelle; Armato, Samuel G.

2012-01-01

Purpose: The aim of this study was to quantify the effect of four image registration methods on lung texture features extracted from serial computed tomography (CT) scans obtained from healthy human subjects. Methods: Two chest CT scans acquired at different time points were collected retrospectively for each of 27 patients. Following automated lung segmentation, each follow-up CT scan was registered to the baseline scan using four algorithms: (1) rigid, (2) affine, (3) B-splines deformable, and (4) demons deformable. The registration accuracy for each scan pair was evaluated by measuring the Euclidean distance between 150 identified landmarks. On average, 1432 spatially matched 32 × 32-pixel region-of-interest (ROI) pairs were automatically extracted from each scan pair. First-order, fractal, Fourier, Laws’ filter, and gray-level co-occurrence matrix texture features were calculated in each ROI, for a total of 140 features. Agreement between baseline and follow-up scan ROI feature values was assessed by Bland–Altman analysis for each feature; the range spanned by the 95% limits of agreement of feature value differences was calculated and normalized by the average feature value to obtain the normalized range of agreement (nRoA). Features with small nRoA were considered “registration-stable.” The normalized bias for each feature was calculated from the feature value differences between baseline and follow-up scans averaged across all ROIs in every patient. Because patients had “normal” chest CT scans, minimal change in texture feature values between scan pairs was anticipated, with the expectation of small bias and narrow limits of agreement. Results: Registration with demons reduced the Euclidean distance between landmarks such that only 9% of landmarks were separated by ≥1 mm, compared with rigid (98%), affine (95%), and B-splines (90%). Ninety-nine of the 140 (71%) features analyzed yielded nRoA > 50% for all registration methods, indicating that the majority of feature values were perturbed following registration. Nineteen of the features (14%) had nRoA < 15% following demons registration, indicating relative feature value stability. Student's t-tests showed that the nRoA of these 19 features was significantly larger when rigid, affine, or B-splines registration methods were used compared with demons registration. Demons registration yielded greater normalized bias in feature value change than B-splines registration, though this difference was not significant (p = 0.15). Conclusions: Demons registration provided higher spatial accuracy between matched anatomic landmarks in serial CT scans than rigid, affine, or B-splines algorithms. Texture feature changes calculated in healthy lung tissue from serial CT scans were smaller following demons registration compared with all other algorithms. Though registration altered the values of the majority of texture features, 19 features remained relatively stable after demons registration, indicating their potential for detecting pathologic change in serial CT scans. Combined use of accurate deformable registration using demons and texture analysis may allow for quantitative evaluation of local changes in lung tissue due to disease progression or treatment response. PMID:22894392

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.

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

NASA Astrophysics Data System (ADS)

Sierra, Heidy; Brooks, Dana; Dimarzio, Charles

2010-07-01

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

Perceived beauty of random texture patterns: A preference for complexity.

PubMed

Friedenberg, Jay; Liby, Bruce

2016-07-01

We report two experiments on the perceived aesthetic quality of random density texture patterns. In each experiment a square grid was filled with a progressively larger number of elements. Grid size in Experiment 1 was 10×10 with elements added to create a variety of textures ranging from 10%-100% fill levels. Participants rated the beauty of the patterns. Average judgments across all observers showed an inverted U-shaped function that peaked near middle densities. In Experiment 2 grid size was increased to 15×15 to see if observers preferred patterns with a fixed density or a fixed number of elements. The results of the second experiment were nearly identical to that of the first showing a preference for density over fixed element number. Ratings in both studies correlated positively with a GIF compression metric of complexity and with edge length. Within the range of stimuli used, observers judge more complex patterns to be more beautiful. Copyright © 2016 Elsevier B.V. All rights reserved.

Recrystallization texture in nickel heavily deformed by accumulative roll bonding

NASA Astrophysics Data System (ADS)

Mishin, O. V.; Zhang, Y. B.; Godfrey, A.

2017-07-01

The recrystallization behavior of Ni processed by accumulative roll bonding to a total accumulated von Mises strain of 4.8 has been examined, and analyzed with respect to heterogeneity in the deformation microstructure. The regions near the bonding interface are found to be more refined and contain particle deformation zones around fragments of the steel wire brush used to prepare the surface for bonding. Sample-scale gradients are also observed, manifested as differences between the subsurface, intermediate and central layers, where the distributions of texture components are different. These heterogeneities affect the progress of recrystallization. While the subsurface and near-interface regions typically contain lower frequencies of cube-oriented grains than anywhere else in the sample, a strong cube texture forms in the sample during recrystallization, attributed to both a high nucleation rate and fast growth rate of cube-oriented grains. The observations highlight the sensitivity of recrystallization to heterogeneity in the deformation microstructure and demonstrate the importance of characterizing this heterogeneity over several length scales.

3D Texture Features Mining for MRI Brain Tumor Identification

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

Texture Feature Extraction and Classification for Iris Diagnosis

NASA Astrophysics Data System (ADS)

Ma, Lin; Li, Naimin

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

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

Histogram contrast analysis and the visual segregation of IID textures.

PubMed

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

1994-09-01

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

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

PubMed Central

Wang, Kun-Ching

2015-01-01

The classification of emotional speech is mostly considered in speech-related research on human-computer interaction (HCI). In this paper, the purpose is to present a novel feature extraction based on multi-resolutions texture image information (MRTII). The MRTII feature set is derived from multi-resolution texture analysis for characterization and classification of different emotions in a speech signal. The motivation is that we have to consider emotions have different intensity values in different frequency bands. In terms of human visual perceptual, the texture property on multi-resolution of emotional speech spectrogram should be a good feature set for emotion classification in speech. Furthermore, the multi-resolution analysis on texture can give a clearer discrimination between each emotion than uniform-resolution analysis on texture. In order to provide high accuracy of emotional discrimination especially in real-life, an acoustic activity detection (AAD) algorithm must be applied into the MRTII-based feature extraction. Considering the presence of many blended emotions in real life, in this paper make use of two corpora of naturally-occurring dialogs recorded in real-life call centers. Compared with the traditional Mel-scale Frequency Cepstral Coefficients (MFCC) and the state-of-the-art features, the MRTII features also can improve the correct classification rates of proposed systems among different language databases. Experimental results show that the proposed MRTII-based feature information inspired by human visual perception of the spectrogram image can provide significant classification for real-life emotional recognition in speech. PMID:25594590

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

PubMed

Hu, Leland S; Ning, Shuluo; Eschbacher, Jennifer M; Gaw, Nathan; Dueck, Amylou C; Smith, Kris A; Nakaji, Peter; Plasencia, Jonathan; Ranjbar, Sara; Price, Stephen J; Tran, Nhan; Loftus, Joseph; Jenkins, Robert; O'Neill, Brian P; Elmquist, William; Baxter, Leslie C; Gao, Fei; Frakes, David; Karis, John P; Zwart, Christine; Swanson, Kristin R; Sarkaria, Jann; Wu, Teresa; Mitchell, J Ross; Li, Jing

2015-01-01

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

Potential Performance Criteria for Combat Ration Packs - Texture Profile Analysis

DTIC Science & Technology

2014-11-01

12 3.3.1 Apricot & coconut muesli bar...Figure 5 Texture vs aw of canned puddings stored at 30 °C for up to 730 days. 3.3 Muesli Bar The three muesli bars (apricot and coconut , tropical...Apricot & coconut muesli bar No significant changes were observed during storage for texture attributes, except at 40 °C for break strength and

Origin of texture development in orthorhombic uranium

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

Zecevic, Miroslav; Knezevic, Marko; Beyerlein, Irene Jane

We study texture evolution of alpha-uranium (α-U) during plane strain compression and uniaxial compression to high strains at different temperatures. We combine a multiscale polycrystal constitutive model and detailed analysis of texture data to uncover the slip and twinning modes responsible for the formation of individual texture components. The analysis indicates that during plane strain compression, floor slip (001)[100] results in the formation of two pronounced {001}{001} texture peaks tilted 10–15° away from the normal toward the rolling direction. During both high-temperature (573 K) through-thickness compression and plane strain compression, the active slip modes are floor slip (001)[100] and chimneymore » slip 1/2{110} <11¯0> with slightly different ratios. {130} <31¯0> deformation twinning is profuse during rolling and in-plane compression and decreases with increasing temperature, but is not as active for through-thickness compression. Lastly, we comment on some similarities between rolling textures of α-U, which has a c/a ratio of 1.734, and those that develop in hexagonal close packed metals with similarly high c/a ratios like Zn (1.856) and Cd (1.885) and are dominated by basal slip.« less

Origin of texture development in orthorhombic uranium

DOE PAGES

Zecevic, Miroslav; Knezevic, Marko; Beyerlein, Irene Jane; ...

2016-04-09

We study texture evolution of alpha-uranium (α-U) during plane strain compression and uniaxial compression to high strains at different temperatures. We combine a multiscale polycrystal constitutive model and detailed analysis of texture data to uncover the slip and twinning modes responsible for the formation of individual texture components. The analysis indicates that during plane strain compression, floor slip (001)[100] results in the formation of two pronounced {001}{001} texture peaks tilted 10–15° away from the normal toward the rolling direction. During both high-temperature (573 K) through-thickness compression and plane strain compression, the active slip modes are floor slip (001)[100] and chimneymore » slip 1/2{110} <11¯0> with slightly different ratios. {130} <31¯0> deformation twinning is profuse during rolling and in-plane compression and decreases with increasing temperature, but is not as active for through-thickness compression. Lastly, we comment on some similarities between rolling textures of α-U, which has a c/a ratio of 1.734, and those that develop in hexagonal close packed metals with similarly high c/a ratios like Zn (1.856) and Cd (1.885) and are dominated by basal slip.« less

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

Microstructure, texture evolution and magnetic properties of strip-casting non-oriented 6.5 wt.% Si electrical steel doped with cerium

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

Li, Hao-Ze, E-mail: lhzqq83@163.com; Liu, Hai-Tao; Liu, Zhen-Yu, E-mail: zyliu@mail.neu.edu.cn

A 0.3 mm thick non-oriented 6.5 wt.% Si electrical steel sheet doped with cerium is produced by twin-roll strip casting, hot rolling, warm rolling and annealing. A detailed study of the cerium precipitates in the as-cast strip, microstructure and texture evolution at different processing stages is carried out by electron probe micro-analysis, optical microscopy, X-ray diffraction and electron backscattered diffraction analysis. Grain interior distributing precipitates identified as Ce-oxides, Ce-oxysulfides and Ce-phosphides, and boundary distributing Ce-oxides and Ce-phosphides are observed in the as-cast strip. The initial as-cast strip is characterized by a much finer solidification microstructure and dominated by obvious //ND texture through the strip thickness. After hot and warm rolling, inhomogeneous microstructure containing large amounts of in-grain shear bands is characterized by mixed < 110 >//RD and < 111 >//ND textures. The texture of the annealed sheet with a relatively large average grain size is far more optimized by the domination of the beneficial cube, rotated cube, (001)< 120 > to (001)< 130 > and Goss texture components, and the elimination of the detrimental γ-fiber texture, leading to a superior magnetic induction and improved iron loss. - Highlights: • An Fe–6.5 wt.% Si as-cast strip doped with cerium was produced. • A thin warm rolled sheet with limited edge cracks was obtained. • Microstructure and texture evolution at each stage were investigated. • Strong λ-fiber and Goss recrystallization textures were formed. • The magnetic properties of the annealed sheet were significantly improved.« less

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Grain structure, texture and mechanical property evolution of automotive aluminium sheet during high power ultrasonic welding

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

Haddadi, Farid, E-mail: farid.haddadi@gmail.com

High power ultrasonic spot welding (HPUSW) is a joining technique which is performed within less than a second and provides a more energy-efficient alternative to friction stir spot welding (FSSW), which is considered a longer cycle manufacturing process for joining automotive alloys. To date, only a few reports exist on the deformation mechanisms that take place during high power ultrasonic spot welding. In this work, dynamic recrystallization and grain growth were examined using electron backscatter diffraction (EBSD). HPUSW causes extensive deformation within the weld zone where the temperature increases to 440 °C. An ultra-fine grain structure was observed in amore » thin band of flat weld interface within a short welding time of 0.10 s. With increasing welding time the interface was displaced and ‘folds’ or ‘crests’ appeared together with shear bands. The weld interface progressively changed from flat to sinusoidal and eventually to a convoluted wave-like pattern when the tool fully penetrated the workpiece, having a wavelength of ~ 1 mm after 0.40 s. Finally, the microstructure and texture varied significantly depending on the location within the weld. Although the texture near the weld interface was relatively weak, a shift was observed with increasing welding time from an initially Cube-dominated texture to one where the typical β-fibre Brass component prevailed. - Highlights: •Lap shear strength of ~2.9 kN was achieved in 0.30 sec welding time. •Temperature approached 440 °C along the weld centreline for the highest welding time. •The texture near the teeth was dominated by Brass, P and S components at optimum condition. •The weld interface showed typical β-fibre deformation texture at optimum condition.« less

Radiomics Evaluation of Histological Heterogeneity Using Multiscale Textures Derived From 3D Wavelet Transformation of Multispectral Images.

PubMed

Chaddad, Ahmad; Daniel, Paul; Niazi, Tamim

2018-01-01

Colorectal cancer (CRC) is markedly heterogeneous and develops progressively toward malignancy through several stages which include stroma (ST), benign hyperplasia (BH), intraepithelial neoplasia (IN) or precursor cancerous lesion, and carcinoma (CA). Identification of the malignancy stage of CRC pathology tissues (PT) allows the most appropriate therapeutic intervention. This study investigates multiscale texture features extracted from CRC pathology sections using 3D wavelet transform (3D-WT) filter. Multiscale features were extracted from digital whole slide images of 39 patients that were segmented in a pre-processing step using an active contour model. The capacity for multiscale texture to compare and classify between PTs was investigated using ANOVA significance test and random forest classifier models, respectively. 12 significant features derived from the multiscale texture (i.e., variance, entropy, and energy) were found to discriminate between CRC grades at a significance value of p  < 0.01 after correction. Combining multiscale texture features lead to a better predictive capacity compared to prediction models based on individual scale features with an average (±SD) classification accuracy of 93.33 (±3.52)%, sensitivity of 88.33 (± 4.12)%, and specificity of 96.89 (± 3.88)%. Entropy was found to be the best classifier feature across all the PT grades with an average of the area under the curve (AUC) value of 91.17, 94.21, 97.70, 100% for ST, BH, IN, and CA, respectively. Our results suggest that multiscale texture features based on 3D-WT are sensitive enough to discriminate between CRC grades with the entropy feature, the best predictor of pathology grade.

Diet of upper paleolithic modern humans: evidence from microwear texture analysis.

PubMed

El Zaatari, Sireen; Hublin, Jean-Jacques

2014-04-01

This article presents the results of the occlusal molar microwear texture analysis of 32 adult Upper Paleolithic modern humans from a total of 21 European sites dating to marine isotope stages 3 and 2. The occlusal molar microwear textures of these specimens were analyzed with the aim of examining the effects of the climatic, as well as the cultural, changes on the diets of the Upper Paleolithic modern humans. The results of this analysis do not reveal any environmentally driven dietary shifts for the Upper Paleolithic hominins indicating that the climatic and their associated paleoecological changes did not force these humans to significantly alter their diets in order to survive. However, the microwear texture analysis does detect culturally related changes in the Upper Paleolithic humans' diets. Specifically, significant differences in diet were found between the earlier Upper Paleolithic individuals, i.e., those belonging to the Aurignacian and Gravettian contexts, and the later Magdalenian ones, such that the diet of the latter group was more varied and included more abrasive foods compared with those of the former. Copyright © 2014 Wiley Periodicals, Inc.

3D Texture Analysis in Renal Cell Carcinoma Tissue Image Grading

PubMed Central

Cho, Nam-Hoon; Choi, Heung-Kook

2014-01-01

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

Quantitative three-dimensional microtextural analyses of tooth wear as a tool for dietary discrimination in fishes

PubMed Central

Purnell, Mark; Seehausen, Ole; Galis, Frietson

2012-01-01

Resource polymorphisms and competition for resources are significant factors in speciation. Many examples come from fishes, and cichlids are of particular importance because of their role as model organisms at the interface of ecology, development, genetics and evolution. However, analysis of trophic resource use in fishes can be difficult and time-consuming, and for fossil fish species it is particularly problematic. Here, we present evidence from cichlids that analysis of tooth microwear based on high-resolution (sub-micrometre scale) three-dimensional data and new ISO standards for quantification of surface textures provides a powerful tool for dietary discrimination and investigation of trophic resource exploitation. Our results suggest that three-dimensional approaches to analysis offer significant advantages over two-dimensional operator-scored methods of microwear analysis, including applicability to rough tooth surfaces that lack distinct scratches and pits. Tooth microwear textures develop over a longer period of time than is represented by stomach contents, and analyses based on textures are less prone to biases introduced by opportunistic feeding. They are more sensitive to subtle dietary differences than isotopic analysis. Quantitative textural analysis of tooth microwear has a useful role to play, complementing existing approaches, in trophic analysis of fishes—both extant and extinct. PMID:22491979

Entropy-Based Adaptive Nuclear Texture Features are Independent Prognostic Markers in a Total Population of Uterine Sarcomas

PubMed Central

Nielsen, Birgitte; Hveem, Tarjei Sveinsgjerd; Kildal, Wanja; Abeler, Vera M; Kristensen, Gunnar B; Albregtsen, Fritz; Danielsen, Håvard E; Rohde, Gustavo K

2015-01-01

Nuclear texture analysis measures the spatial arrangement of the pixel gray levels in a digitized microscopic nuclear image and is a promising quantitative tool for prognosis of cancer. The aim of this study was to evaluate the prognostic value of entropy-based adaptive nuclear texture features in a total population of 354 uterine sarcomas. Isolated nuclei (monolayers) were prepared from 50 µm tissue sections and stained with Feulgen-Schiff. Local gray level entropy was measured within small windows of each nuclear image and stored in gray level entropy matrices, and two superior adaptive texture features were calculated from each matrix. The 5-year crude survival was significantly higher (P < 0.001) for patients with high texture feature values (72%) than for patients with low feature values (36%). When combining DNA ploidy classification (diploid/nondiploid) and texture (high/low feature value), the patients could be stratified into three risk groups with 5-year crude survival of 77, 57, and 34% (Hazard Ratios (HR) of 1, 2.3, and 4.1, P < 0.001). Entropy-based adaptive nuclear texture was an independent prognostic marker for crude survival in multivariate analysis including relevant clinicopathological features (HR = 2.1, P = 0.001), and should therefore be considered as a potential prognostic marker in uterine sarcomas. © The Authors. Published 2014 International Society for Advancement of Cytometry PMID:25483227

Surface scaling analysis of textured MgO thin films fabricated by energetic particle self-assisted deposition

NASA Astrophysics Data System (ADS)

Feng, Feng; Zhang, Xiangsong; Qu, Timing; Liu, Binbin; Huang, Junlong; Li, Jun; Xiao, Shaozhu; Han, Zhenghe; Feng, Pingfa

2018-04-01

In the fabrication of a high-temperature superconducting coated conductor, the surface roughness and texture of buffer layers can significantly affect the epitaxially grown superconductor layer. A biaxially textured MgO buffer layer fabricated by ion beam assisted deposition (IBAD) is widely used in the coated conductor manufacture due to its low thickness requirement. In our previous study, a new method called energetic particle self-assisted deposition (EPSAD), which employed only a sputtering deposition apparatus without an ion source, was proposed for fabricating biaxially textured MgO films on non-textured substrates. In this study, our aim was to investigate the deposition mechanism of EPSAD-MgO thin films. The behavior of the surface roughness (evaluated by Rq) was studied using atomic force microscopy (AFM) measurements with three scan scales, while the in-plane and out-of-plane textures were measured using X-ray diffraction (XRD). It was found that the variations of surface roughness and textures along with the increase in the thickness of EPSAD-MgO samples were very similar to those of IBAD-MgO reported in the literature, revealing the similarity of their deposition mechanisms. Moreover, fractal geometry was utilized to conduct the scaling analysis of EPSAD-MgO film's surface. Different scaling behaviors were found in two scale ranges, and the indications of the fractal properties in different scale ranges were discussed.

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

PubMed

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

2011-04-01

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

Genomics of lactic acid bacteria: Current status and potential applications.

PubMed

Wu, Chongde; Huang, Jun; Zhou, Rongqing

2017-08-01

Lactic acid bacteria (LAB) are widely used for the production of a variety of foods and feed raw materials where they contribute to flavor and texture of the fermented products. In addition, specific LAB strains are considered as probiotic due to their health-promoting effects in consumers. Recently, the genome sequencing of LAB is booming and the increased amount of published genomics data brings unprecedented opportunity for us to reveal the important traits of LAB. This review describes the recent progress on LAB genomics and special emphasis is placed on understanding the industry-related physiological features based on genomics analysis. Moreover, strategies to engineer metabolic capacity and stress tolerance of LAB with improved industrial performance are also discussed.

Achondrite Binda; Ordinary Eucrite or the Only Crystalline Howardite?

NASA Astrophysics Data System (ADS)

Yanai, K.

1996-03-01

Binda meteorite, originally classified as howardite (Hey, 1966), was reclassified as eucrite of monomict breccia (Duke and Silver, 1967). Binda was recognized as the most Mg-rich eucrite (or most Fe-rich diogenite) with crystalline-unbrecciated texture for long time. Therefore Binda is believed to have genetic significance in relation to eucrites and diogenites, because in howardite group Binda is the only specimen with unbrecciated or monomict and crystalline texture. Re-examination of Binda was carried out by EPMA, microscope analysis and wet chemical analysis. Binda is the most common (ordinary) encrite showing crystalline texture with slightly brecciated.

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

NASA Astrophysics Data System (ADS)

Wen, Lianggong

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

Crystallographic texture and microstructural changes in fusion welds of recrystallized Zry-4 rolled plates

NASA Astrophysics Data System (ADS)

Moya Riffo, A.; Vicente Alvarez, M. A.; Santisteban, J. R.; Vizcaino, P.; Limandri, S.; Daymond, M. R.; Kerr, D.; Okasinski, J.; Almer, J.; Vogel, S. C.

2017-05-01

This work presents a detailed characterization of the microstructural and crystallographic texture changes observed in the transition region in a weld between two Zircaloy-4 cold rolled and recrystallized plates. The microstructural study was performed by optical microscopy under polarized light and scanning electron microscopy (SEM). Texture changes were characterized at different lengthscales: in the micrometric size, orientation imaging maps (OIM) were constructed by electron backscatter diffraction (EBSD), in the millimetre scale, high energy XRD experiments were done at the Advanced Photon Source (USA) and compared to neutron diffraction texture determinations performed in the HIPPO instrument at Los Alamos National Laboratory. In the heat affected zone (HAZ) we observed the development of Widmanstätten microstructures, typical of the α(hcp) to β(bcc) phase transformation. Associated with these changes a rotation of the c-poles is found in the HAZ and fusion zone. While the base material shows the typical texture of a cold rolled plate, with their c-poles pointing 35° apart from the normal direction of the plate in the normal-transversal line, in the HAZ, c-poles align along the transversal direction of the plate and then re-orient along different directions, all of these changes occurring within a lengthscale in the order of mm. The evolution of texture in this narrow region was captured by both OIM and XRD, and is consistent with previous measurements done by Neutron Diffraction in the HIPPO diffractometer at Los Alamos National Laboratory, USA. The microstructural and texture changes along the HAZ were interpreted as arising due to the effect of differences in the cooling rate and β grain size on the progress of the different α variants during transformation. Fast cooling rates and large β grains are associated to weak variant selection during the β->α transformation, while slow cooling rates and fine β grains result in strong variant selection.

Crystallographic texture and microstructural changes in fusion welds of recrystallized Zry-4 rolled plates

DOE PAGES

Riffo, A. Moya; Vicente Alvarez, M. A.; Santisteban, J. R.; ...

2017-02-08

This study presents a detailed characterization of the microstructural and crystallographic texture changes observed in the transition region in a weld between two Zircaloy-4 cold rolled and recrystallized plates. The microstructural study was performed by optical microscopy under polarized light and scanning electron microscopy (SEM). Texture changes were characterized at different lengthscales: in the micrometric size, orientation imaging maps (OIM) were constructed by electron backscatter diffraction (EBSD), in the millimetre scale, high energy XRD experiments were done at the Advanced Photon Source (USA) and compared to neutron diffraction texture determinations performed in the HIPPO instrument at Los Alamos National Laboratory.more » In the heat affected zone (HAZ) we observed the development of Widmanstätten microstructures, typical of the α( hcp) to β( bcc) phase transformation. Associated with these changes a rotation of the c-poles is found in the HAZ and fusion zone. While the base material shows the typical texture of a cold rolled plate, with their c-poles pointing 35° apart from the normal direction of the plate in the normal-transversal line, in the HAZ, c-poles align along the transversal direction of the plate and then re-orient along different directions, all of these changes occurring within a lengthscale in the order of mm. The evolution of texture in this narrow region was captured by both OIM and XRD, and is consistent with previous measurements done by Neutron Diffraction in the HIPPO diffractometer at Los Alamos National Laboratory, USA. The microstructural and texture changes along the HAZ were interpreted as arising due to the effect of differences in the cooling rate and β grain size on the progress of the different α variants during transformation. Fast cooling rates and large β grains are associated to weak variant selection during the β–>α transformation, while slow cooling rates and fine β grains result in strong variant selection.« less

Crystallographic texture and microstructural changes in fusion welds of recrystallized Zry-4 rolled plates

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

Riffo, A. Moya; Vicente Alvarez, M. A.; Santisteban, J. R.

This study presents a detailed characterization of the microstructural and crystallographic texture changes observed in the transition region in a weld between two Zircaloy-4 cold rolled and recrystallized plates. The microstructural study was performed by optical microscopy under polarized light and scanning electron microscopy (SEM). Texture changes were characterized at different lengthscales: in the micrometric size, orientation imaging maps (OIM) were constructed by electron backscatter diffraction (EBSD), in the millimetre scale, high energy XRD experiments were done at the Advanced Photon Source (USA) and compared to neutron diffraction texture determinations performed in the HIPPO instrument at Los Alamos National Laboratory.more » In the heat affected zone (HAZ) we observed the development of Widmanstätten microstructures, typical of the α( hcp) to β( bcc) phase transformation. Associated with these changes a rotation of the c-poles is found in the HAZ and fusion zone. While the base material shows the typical texture of a cold rolled plate, with their c-poles pointing 35° apart from the normal direction of the plate in the normal-transversal line, in the HAZ, c-poles align along the transversal direction of the plate and then re-orient along different directions, all of these changes occurring within a lengthscale in the order of mm. The evolution of texture in this narrow region was captured by both OIM and XRD, and is consistent with previous measurements done by Neutron Diffraction in the HIPPO diffractometer at Los Alamos National Laboratory, USA. The microstructural and texture changes along the HAZ were interpreted as arising due to the effect of differences in the cooling rate and β grain size on the progress of the different α variants during transformation. Fast cooling rates and large β grains are associated to weak variant selection during the β–>α transformation, while slow cooling rates and fine β grains result in strong variant selection.« less

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

Texture analysis improves level set segmentation of the anterior abdominal wall

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

Xu, Zhoubing; Allen, Wade M.; Baucom, Rebeccah B.

2013-12-15

Purpose: The treatment of ventral hernias (VH) has been a challenging problem for medical care. Repair of these hernias is fraught with failure; recurrence rates ranging from 24% to 43% have been reported, even with the use of biocompatible mesh. Currently, computed tomography (CT) is used to guide intervention through expert, but qualitative, clinical judgments, notably, quantitative metrics based on image-processing are not used. The authors propose that image segmentation methods to capture the three-dimensional structure of the abdominal wall and its abnormalities will provide a foundation on which to measure geometric properties of hernias and surrounding tissues and, therefore,more » to optimize intervention.Methods: In this study with 20 clinically acquired CT scans on postoperative patients, the authors demonstrated a novel approach to geometric classification of the abdominal. The authors’ approach uses a texture analysis based on Gabor filters to extract feature vectors and follows a fuzzy c-means clustering method to estimate voxelwise probability memberships for eight clusters. The memberships estimated from the texture analysis are helpful to identify anatomical structures with inhomogeneous intensities. The membership was used to guide the level set evolution, as well as to derive an initial start close to the abdominal wall.Results: Segmentation results on abdominal walls were both quantitatively and qualitatively validated with surface errors based on manually labeled ground truth. Using texture, mean surface errors for the outer surface of the abdominal wall were less than 2 mm, with 91% of the outer surface less than 5 mm away from the manual tracings; errors were significantly greater (2–5 mm) for methods that did not use the texture.Conclusions: The authors’ approach establishes a baseline for characterizing the abdominal wall for improving VH care. Inherent texture patterns in CT scans are helpful to the tissue classification, and texture analysis can improve the level set segmentation around the abdominal region.« less

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.

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

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

Desseroit, M; Cheze Le Rest, C; Tixier, F

2014-06-15

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

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

NASA Astrophysics Data System (ADS)

Jerram, D. A.

2006-12-01

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

Accuracy and Precision of Silicon Based Impression Media for Quantitative Areal Texture Analysis

PubMed Central

Goodall, Robert H.; Darras, Laurent P.; Purnell, Mark A.

2015-01-01

Areal surface texture analysis is becoming widespread across a diverse range of applications, from engineering to ecology. In many studies silicon based impression media are used to replicate surfaces, and the fidelity of replication defines the quality of data collected. However, while different investigators have used different impression media, the fidelity of surface replication has not been subjected to quantitative analysis based on areal texture data. Here we present the results of an analysis of the accuracy and precision with which different silicon based impression media of varying composition and viscosity replicate rough and smooth surfaces. Both accuracy and precision vary greatly between different media. High viscosity media tested show very low accuracy and precision, and most other compounds showed either the same pattern, or low accuracy and high precision, or low precision and high accuracy. Of the media tested, mid viscosity President Jet Regular Body and low viscosity President Jet Light Body (Coltène Whaledent) are the only compounds to show high levels of accuracy and precision on both surface types. Our results show that data acquired from different impression media are not comparable, supporting calls for greater standardisation of methods in areal texture analysis. PMID:25991505

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).

The Wear Behavior of Textured Steel Sliding against Polymers

PubMed Central

Wang, Meiling; Zhang, Changtao; Wang, Xiaolei

2017-01-01

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

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

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.

Multiscale Modeling and Process Optimization for Engineered Microstructural Complexity

DTIC Science & Technology

2007-10-26

Ferroelectric Ceramics , Materials Science Forum, 404-407, 413-418 2002. 42. R. T. Brewer, H. A. Atwater Rapid biaxial texture development during...Multiscale Study of Internal Stress and Texture in Electroceramics, 106th Annual Meeting of the American Ceramic Society, Indianapolis, Indiana, 20...Rogan, Texture and Strain Analysis of PZT by In-Situ Neutron Diffraction, MRS Spring Meeting, San Francisco, CA; April 2002. 43. E. Ustundag

Hierarchical classification strategy for Phenotype extraction from epidermal growth factor receptor endocytosis screening.

PubMed

Cao, Lu; Graauw, Marjo de; Yan, Kuan; Winkel, Leah; Verbeek, Fons J

2016-05-03

Endocytosis is regarded as a mechanism of attenuating the epidermal growth factor receptor (EGFR) signaling and of receptor degradation. There is increasing evidence becoming available showing that breast cancer progression is associated with a defect in EGFR endocytosis. In order to find related Ribonucleic acid (RNA) regulators in this process, high-throughput imaging with fluorescent markers is used to visualize the complex EGFR endocytosis process. Subsequently a dedicated automatic image and data analysis system is developed and applied to extract the phenotype measurement and distinguish different developmental episodes from a huge amount of images acquired through high-throughput imaging. For the image analysis, a phenotype measurement quantifies the important image information into distinct features or measurements. Therefore, the manner in which prominent measurements are chosen to represent the dynamics of the EGFR process becomes a crucial step for the identification of the phenotype. In the subsequent data analysis, classification is used to categorize each observation by making use of all prominent measurements obtained from image analysis. Therefore, a better construction for a classification strategy will support to raise the performance level in our image and data analysis system. In this paper, we illustrate an integrated analysis method for EGFR signalling through image analysis of microscopy images. Sophisticated wavelet-based texture measurements are used to obtain a good description of the characteristic stages in the EGFR signalling. A hierarchical classification strategy is designed to improve the recognition of phenotypic episodes of EGFR during endocytosis. Different strategies for normalization, feature selection and classification are evaluated. The results of performance assessment clearly demonstrate that our hierarchical classification scheme combined with a selected set of features provides a notable improvement in the temporal analysis of EGFR endocytosis. Moreover, it is shown that the addition of the wavelet-based texture features contributes to this improvement. Our workflow can be applied to drug discovery to analyze defected EGFR endocytosis processes.

Role of physical bolus properties as sensory inputs in the trigger of swallowing.

PubMed

Peyron, Marie-Agnès; Gierczynski, Isabelle; Hartmann, Christoph; Loret, Chrystel; Dardevet, Dominique; Martin, Nathalie; Woda, Alain

2011-01-01

Swallowing is triggered when a food bolus being prepared by mastication has reached a defined state. However, although this view is consensual and well supported, the physical properties of the swallowable bolus have been under-researched. We tested the hypothesis that measuring bolus physical changes during the masticatory sequence to deglutition would reveal the bolus properties potentially involved in swallowing initiation. Twenty normo-dentate young adults were instructed to chew portions of cereal and spit out the boluses at different times in the masticatory sequence. The mechanical properties of the collected boluses were measured by a texture profile analysis test currently used in food science. The median particle size of the boluses was evaluated by sieving. In a simultaneous sensory study, twenty-five other subjects expressed their perception of bolus texture dominating at any mastication time. Several physical changes appeared in the food bolus as it was formed during mastication: (1) in rheological terms, bolus hardness rapidly decreased as the masticatory sequence progressed, (2) by contrast, adhesiveness, springiness and cohesiveness regularly increased until the time of swallowing, (3) median particle size, indicating the bolus particle size distribution, decreased mostly during the first third of the masticatory sequence, (4) except for hardness, the rheological changes still appeared in the boluses collected just before swallowing, and (5) physical changes occurred, with sensory stickiness being described by the subjects as a dominant perception of the bolus at the end of mastication. Although these physical and sensory changes progressed in the course of mastication, those observed just before swallowing seem to be involved in swallowing initiation. They can be considered as strong candidates for sensory inputs from the bolus that are probably crucially involved in the triggering of swallowing, since they appeared in boluses prepared in various mastication strategies by different subjects.

Evidences of Multiple Magma Injections in Quaternary Balerang and Rajabasa Volcanoes, Indonesia

NASA Astrophysics Data System (ADS)

Hasibuan, R. F.; Ohba, T.; Abdurrachman, M.

2016-12-01

Quaternary Balerang and Rajabasa volcanoes are situated along the nearly north-south lineament with a most explosive Krakatau volcanic complex in the south and effusive Sukadana basalt plateau in the north. Some studies have elucidated that Krakatau volcano has multiple magma storage regions beneath together with evidences of magma mixing process. By considering these circumstances, it is necessary to know lateral variations of magmas and to characterize volcanic rocks from Rajabasa volcanic complex which is located between these distinct magmatic systems, in terms of magmatic processes and evolution. Methodologies we used are X-ray fluorescence to determine the whole rock chemistry, K-Ar isotope dating to determine the lifespan of the volcano, as well as EPMA analysis to obtain the chemical composition of minerals. The rock chemistry or TAS plot shows a linear trend, ranging from basaltic (51 wt.%) to rhyolitic (75 wt.%), indicating a chemical heterogeneity of magma. When SiO2 contents are correlated with the relative ages, we found a broad tendency that SiO2 contents progressively decrease with age. The Rajabasa volcano lifespan is known formed at 0.31 Ma while one of the youngest lava is identified erupted at 0.12 Ma. Some plagioclase crystals exhibit disequilibrium textures, like highly sieved core and clear rim regions, also overgrowth rim on the plagioclase and pyroxene crystals whose composition more primitive than the core's composition, indicating magmatic recharge events. Reverse zoning and resorption textures associated with compositional step zoning or progressive zoning are quite common as well in clinopyroxene and plagioclase crystals. By considering these evidences, we conclude that injection of a hotter basaltic magma into colder and more felsic magma occurred beneath the volcanoes.

Mapping the Natchez Trace Parkway

USGS Publications Warehouse

Rangoonwala, Amina; Bannister, Terri; Ramsey, Elijah W.

2011-01-01

Based on a National Park Service (NPS) landcover classification, a landcover map of the 715-km (444-mile) NPS Natchez Trace Parkway (hereafter referred to as the "Parkway") was created. The NPS landcover classification followed National Vegetation Classification (NVC) protocols. The landcover map, which extended the initial landcover classification to the entire Parkway, was based on color-infrared photography converted to 1-m raster-based digital orthophoto quarter quadrangles, according to U.S. Geological Survey mapping standards. Our goal was to include as many alliance classes as possible in the Parkway landcover map. To reach this goal while maintaining a consistent and quantifiable map product throughout the Parkway extent, a mapping strategy was implemented based on the migration of class-based spectral textural signatures and the congruent progressive refinement of those class signatures along the Parkway. Progressive refinement provided consistent mapping by evaluating the spectral textural distinctiveness of the alliance-association classes, and where necessary, introducing new map classes along the Parkway. By following this mapping strategy, the use of raster-based image processing and geographic information system analyses for the map production provided a quantitative and reproducible product. Although field-site classification data were severely limited, the combination of spectral migration of class membership along the Parkway and the progressive classification strategy produced an organization of alliances that was internally highly consistent. The organization resulted from the natural patterns or alignments of spectral variance and the determination of those spectral patterns that were compositionally similar in the dominant species as NVC alliances. Overall, the mapped landcovers represented the existent spectral textural patterns that defined and encompassed the complex variety of compositional alliances and associations of the Parkway. Based on that mapped representation, forests dominate the Parkway landscape. Grass is the second largest Parkway land cover, followed by scrub-shrub and shrubland classes and pine plantations. The map provides a good representation of the landcover patterns and their changes over the extent of the Parkway, south to north.

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®

Superpixel-based structure classification for laparoscopic surgery

NASA Astrophysics Data System (ADS)

Bodenstedt, Sebastian; Görtler, Jochen; Wagner, Martin; Kenngott, Hannes; Müller-Stich, Beat Peter; Dillmann, Rüdiger; Speidel, Stefanie

2016-03-01

Minimally-invasive interventions offers multiple benefits for patients, but also entails drawbacks for the surgeon. The goal of context-aware assistance systems is to alleviate some of these difficulties. Localizing and identifying anatomical structures, maligned tissue and surgical instruments through endoscopic image analysis is paramount for an assistance system, making online measurements and augmented reality visualizations possible. Furthermore, such information can be used to assess the progress of an intervention, hereby allowing for a context-aware assistance. In this work, we present an approach for such an analysis. First, a given laparoscopic image is divided into groups of connected pixels, so-called superpixels, using the SEEDS algorithm. The content of a given superpixel is then described using information regarding its color and texture. Using a Random Forest classifier, we determine the class label of each superpixel. We evaluated our approach on a publicly available dataset for laparoscopic instrument detection and achieved a DICE score of 0.69.

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.

Nondestructive evaluation of loading and fatigue effects in Haynes(R) 230(R) alloy

NASA Astrophysics Data System (ADS)

Saleh, Tarik Adel

Nondestructive evaluation is a useful method for studying the effects of deformation and fatigue. In this dissertation I employed neutron and X-ray diffraction, nonlinear resonant ultrasound spectroscopy (NRUS), and infrared thermography to study the effects of deformation and fatigue on two different nickel based superalloys. The alloys studied were HAYNES 230, a solid solution strengthened alloy with 4% M6C carbides, and secondarily HASTELLOY C-2000 a similar single phase alloy. Using neutron and X-ray diffraction, the deformation behavior of HAYNES 230 was revealed to be composite-like during compression, but unusual in tension, where the carbides provide strengthening until just after the macroscopic yield strength and then they begin to debond and crack, creating a tension-compression asymmetry that is revealed clearly by in situ diffraction. In fatigue of HAYNES 230, the hkl elastic strains changed very little in tension-tension fatigue. However, in situ tension-compression studies showed large changes over the initial stages of fatigue. The HAYNES 230 samples studies had two distinct starting textures, measured by neutron diffraction. Some samples were texture free initially and deformed in tension and compression to fiber textures. Other samples started with a bimodal texture due to cross-rolling and incomplete annealing. The final texture of these bimodal samples is shown through modeling to be a superposition of the initial texture and typical FCC deformation mechanisms. The texture-free samples deformed significantly more macroscopically and in internal elastic strains than the samples with the cross-rolled texture. In contrast to the relative insensitivity of neutron diffraction to the effects of tension-tension fatigue, NRUS revealed large differences between as-received and progressively fatigued samples. This showed that microcracking and void formation are the primary mechanisms responsible for fatigue damage in tension-tension fatigue. NRUS is shown to be a useful complimentary technique to neutron diffraction to evaluate fatigue damage. Finally, infrared thermography is used to show temperature changes over the course of fatigue in HASTELLOY C-2000. Four stages of temperature are shown over the course of a single fatigue test. Both empirical and theoretical relationships between steady state temperature and fatigue life are developed and presented.

Optical differentiation between malignant and benign lymphadenopathy by grey scale texture analysis of endobronchial ultrasound convex probe images.

PubMed

Nguyen, Phan; Bashirzadeh, Farzad; Hundloe, Justin; Salvado, Olivier; Dowson, Nicholas; Ware, Robert; Masters, Ian Brent; Bhatt, Manoj; Kumar, Aravind Ravi; Fielding, David

2012-03-01

Morphologic and sonographic features of endobronchial ultrasound (EBUS) convex probe images are helpful in predicting metastatic lymph nodes. Grey scale texture analysis is a well-established methodology that has been applied to ultrasound images in other fields of medicine. The aim of this study was to determine if this methodology could differentiate between benign and malignant lymphadenopathy of EBUS images. Lymph nodes from digital images of EBUS procedures were manually mapped to obtain a region of interest and were analyzed in a prediction set. The regions of interest were analyzed for the following grey scale texture features in MATLAB (version 7.8.0.347 [R2009a]): mean pixel value, difference between maximal and minimal pixel value, SEM pixel value, entropy, correlation, energy, and homogeneity. Significant grey scale texture features were used to assess a validation set compared with fluoro-D-glucose (FDG)-PET-CT scan findings where available. Fifty-two malignant nodes and 48 benign nodes were in the prediction set. Malignant nodes had a greater difference in the maximal and minimal pixel values, SEM pixel value, entropy, and correlation, and a lower energy (P < .0001 for all values). Fifty-one lymph nodes were in the validation set; 44 of 51 (86.3%) were classified correctly. Eighteen of these lymph nodes also had FDG-PET-CT scan assessment, which correctly classified 14 of 18 nodes (77.8%), compared with grey scale texture analysis, which correctly classified 16 of 18 nodes (88.9%). Grey scale texture analysis of EBUS convex probe images can be used to differentiate malignant and benign lymphadenopathy. Preliminary results are comparable to FDG-PET-CT scan.

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

PubMed

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Texture and structure contribution to low-temperature plasticity enhancement of Mg-Al-Zn-Mn Alloy MA2-1hp after ECAP and annealing

NASA Astrophysics Data System (ADS)

Serebryany, V. N.; D'yakonov, G. S.; Kopylov, V. I.; Salishchev, G. A.; Dobatkin, S. V.

2013-05-01

Equal channel angular pressing (ECAP) in magnesium alloys due to severe plastic shear deformations provides both grain refinement and the slope of the initial basal texture at 40°-50° to the pressing direction. These changes in microstructure and texture contribute to the improvement of low-temperature plasticity of the alloys. Quantitative texture X-ray diffraction analysis and diffraction of backscattered electrons are used to study the main textural and structural factors responsible for enhanced low-temperature plasticity based on the example of magnesium alloy MA2-1hp of the Mg-Al-Zn-Mn system. The possible mechanisms of deformation that lead to this positive effect are discussed.

Texture of Frozen Food

NASA Astrophysics Data System (ADS)

Wani, Kohmei

Quantitative determination of textural quality of frozen food due to freezing and storage conditions is complicated,since the texture is consisted of multi-dimensiona1 factors. The author reviewed the importance of texture in food quality and the factors which is proposed by a priori estimation. New classification of expression words of textural properties by subjective evaluation and an application of four elements mechanical model for analysis of physical characteristics was studied on frozen meat patties. Combination of freezing-thawing condition on the subjective properties and physiochemical characteristics of beef lean meat and hamachi fish (Yellow-tail) meat was studied. Change of the plasticity and the deformability of these samples differed by freezing-thawing rate and cooking procedure. Also optimum freezing-thawing condition was differed from specimens.

Micro friction stir lap welding of AISI 430 ferritic stainless steel: a study on the mechanical properties, microstructure, texture and magnetic properties

NASA Astrophysics Data System (ADS)

Mostaan, Hossein; Safari, Mehdi; Bakhtiari, Arash

2018-04-01

In this study, the effect of friction stir welding of AISI 430 (X6Cr17, material number 1.4016) ferritic stainless steel is examined. Two thin sheets with dimensions of 0.4 × 50 × 200 mm3 are joined in lap configuration. Optical microscopy and field emission electron microscopy were used in order to microstructural evaluations and fracture analysis, respectively. Tensile test and microhardness measurements are employed in order to study the mechanical behaviors of welds. Also, vibrational sample magnetometry (VSM) is employed for characterizing magnetic properties of welded samples. Texture analysis is carried out in order to clarify the change mechanism of magnetic properties in the welded area. The results show that AISI 430 sheets are successfully joined considering both, the appearance of the welding bead and the strength of the welded joint. It is found that by friction stir welding of AISI 430 sheets, texture components with easy axes magnetization have been replaced by texture components with harder magnetization axes. VSM analysis showed that friction stir welding leads to increase in residual induction (Br) and coercivity (Hc). This increase is attributed to the grain refining due the friction stir welding and formation of texture components with harder axes of magnetizations.

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.

RADIATION PRESERVATION OF FRESH STRAWBERRIES AND GRAPES. Report No. 2 (Progress) for March 5, 1959-December 31, 1959

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

Maxie, E.C.; Nelson, K.E.

1960-10-31

Royal apricots are softened markedly at doses of 200,000 rads and greater. This appears to be a radiation effect on texture for the time of the onset of the climacteric was not altered. The ripening of Bartlett pears was inhibited by doses of 100.000 and 200,000 rads. Similatcd transit tests with Shasta strawberries indicate that irradiation at doses of 100.000 and 200.000 rads with an 8-Mev electron beain from a linear accelerator had no significant ill effects on the texture of the berries. Taste panel evaluations indicate that acceptance of Shasta strawberries is not adversely effected by irradiation at dosesmore » up to 200,000 rads. (auth)« less

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

Gupta, Shashaank; Belianinov, Alex; Okatan, Mahmut B

(001)pc textured K0.5Na0.5NbO3 (KNN) ceramic was found to exhibit a 65% improvement in the longitudinal piezoelectric response as compared to its random counterpart. Piezoresponse force microscopy study revealed the existence of larger 180 and non-180 domains for textured ceramic as compared to that of the random ceramic. Improvement in piezoresponse by the development of (001)pc texture is discussed in terms of the crystallographic nature of KNN and domain morphology. A comparative analysis performed with a rhombohedral composition suggested that the improvement in longitudinal piezoresponse of polycrystalline ceramics by the development of (001)pc texture is limited by the crystal structure.

Light extraction efficiency of GaN-based LED with pyramid texture by using ray path analysis.

PubMed

Pan, Jui-Wen; Wang, Chia-Shen

2012-09-10

We study three different gallium-nitride (GaN) based light emitting diode (LED) cases based on the different locations of the pyramid textures. In case 1, the pyramid texture is located on the sapphire top surface, in case 2, the pyramid texture is locate on the P-GaN top surface, while in case 3, the pyramid texture is located on both the sapphire and P-GaN top surfaces. We study the relationship between the light extraction efficiency (LEE) and angle of slant of the pyramid texture. The optimization of total LEE was highest for case 3 among the three cases. Moreover, the seven escape paths along which most of the escaped photon flux propagated were selected in a simulation of the LEDs. The seven escape paths were used to estimate the slant angle for the optimization of LEE and to precisely analyze the photon escape path.

The use of an ion-beam source to alter the surface morphology of biological implant materials

NASA Technical Reports Server (NTRS)

Weigand, A. J.

1978-01-01

An electron-bombardment ion-thruster was used as a neutralized-ion-beam sputtering source to texture the surfaces of biological implant materials. The materials investigated included 316 stainless steel; titanium-6% aluminum, 4% vanadium; cobalt-20% chromium, 15% tungsten; cobalt-35% nickel, 20% chromium, 10% molybdenum; polytetrafluoroethylene; polyoxymethylene; silicone and polyurethane copolymer; 32%-carbon-impregnated polyolefin; segmented polyurethane; silicone rubber; and alumina. Scanning electron microscopy was used to determine surface morphology changes of all materials after ion-texturing. Electron spectroscopy for chemical analysis was used to determine the effects of ion-texturing on the surface chemical composition of some polymers. Liquid contact angle data were obtained for ion-textured and untextured polymer samples. Results of tensile and fatigue tests of ion-textured metal alloys are presented. Preliminary data of tissue response to ion-textured surfaces of some metals, polytetrafluoroethylene, alumina, and segmented polyurethane have been obtained.

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.

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.

The effect of SUV discretization in quantitative FDG-PET Radiomics: the need for standardized methodology in tumor texture analysis

NASA Astrophysics Data System (ADS)

Leijenaar, Ralph T. H.; Nalbantov, Georgi; Carvalho, Sara; van Elmpt, Wouter J. C.; Troost, Esther G. C.; Boellaard, Ronald; Aerts, Hugo J. W. L.; Gillies, Robert J.; Lambin, Philippe

2015-08-01

FDG-PET-derived textural features describing intra-tumor heterogeneity are increasingly investigated as imaging biomarkers. As part of the process of quantifying heterogeneity, image intensities (SUVs) are typically resampled into a reduced number of discrete bins. We focused on the implications of the manner in which this discretization is implemented. Two methods were evaluated: (1) RD, dividing the SUV range into D equally spaced bins, where the intensity resolution (i.e. bin size) varies per image; and (2) RB, maintaining a constant intensity resolution B. Clinical feasibility was assessed on 35 lung cancer patients, imaged before and in the second week of radiotherapy. Forty-four textural features were determined for different D and B for both imaging time points. Feature values depended on the intensity resolution and out of both assessed methods, RB was shown to allow for a meaningful inter- and intra-patient comparison of feature values. Overall, patients ranked differently according to feature values-which was used as a surrogate for textural feature interpretation-between both discretization methods. Our study shows that the manner of SUV discretization has a crucial effect on the resulting textural features and the interpretation thereof, emphasizing the importance of standardized methodology in tumor texture analysis.

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

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

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.

Deciphering the genetic control of fruit texture in apple by multiple family-based analysis and genome-wide association

PubMed Central

Di Guardo, Mario; Bink, Marco C.A.M.; Guerra, Walter; Letschka, Thomas; Lozano, Lidia; Busatto, Nicola; Poles, Lara; Tadiello, Alice; Bianco, Luca; Visser, Richard G.F.; van de Weg, Eric

2017-01-01

Abstract Fruit texture is a complex feature composed of mechanical and acoustic properties relying on the modifications occurring in the cell wall throughout fruit development and ripening. Apple is characterized by a large variation in fruit texture behavior that directly impacts both the consumer’s appreciation and post-harvest performance. To decipher the genetic control of fruit texture comprehensively, two complementing quantitative trait locus (QTL) mapping approaches were employed. The first was represented by a pedigree-based analysis (PBA) carried out on six full-sib pedigreed families, while the second was a genome-wide association study (GWAS) performed on a collection of 233 apple accessions. Both plant materials were genotyped with a 20K single nucleotide polymorphism (SNP) array and phenotyped with a sophisticated high-resolution texture analyzer. The overall QTL results indicated the fundamental role of chromosome 10 in controlling the mechanical properties, while chromosomes 2 and 14 were more associated with the acoustic response. The latter QTL, moreover, showed a consistent relationship between the QTL-estimated genotypes and the acoustic performance assessed among seedlings. The in silico annotation of these intervals revealed interesting candidate genes potentially involved in fruit texture regulation, as suggested by the gene expression profile. The joint integration of these approaches sheds light on the specific control of fruit texture, enabling important genetic information to assist in the selection of valuable fruit quality apple varieties. PMID:28338805

Deciphering the genetic control of fruit texture in apple by multiple family-based analysis and genome-wide association.

PubMed

Di Guardo, Mario; Bink, Marco C A M; Guerra, Walter; Letschka, Thomas; Lozano, Lidia; Busatto, Nicola; Poles, Lara; Tadiello, Alice; Bianco, Luca; Visser, Richard G F; van de Weg, Eric; Costa, Fabrizio

2017-03-01

Fruit texture is a complex feature composed of mechanical and acoustic properties relying on the modifications occurring in the cell wall throughout fruit development and ripening. Apple is characterized by a large variation in fruit texture behavior that directly impacts both the consumer's appreciation and post-harvest performance. To decipher the genetic control of fruit texture comprehensively, two complementing quantitative trait locus (QTL) mapping approaches were employed. The first was represented by a pedigree-based analysis (PBA) carried out on six full-sib pedigreed families, while the second was a genome-wide association study (GWAS) performed on a collection of 233 apple accessions. Both plant materials were genotyped with a 20K single nucleotide polymorphism (SNP) array and phenotyped with a sophisticated high-resolution texture analyzer. The overall QTL results indicated the fundamental role of chromosome 10 in controlling the mechanical properties, while chromosomes 2 and 14 were more associated with the acoustic response. The latter QTL, moreover, showed a consistent relationship between the QTL-estimated genotypes and the acoustic performance assessed among seedlings. The in silico annotation of these intervals revealed interesting candidate genes potentially involved in fruit texture regulation, as suggested by the gene expression profile. The joint integration of these approaches sheds light on the specific control of fruit texture, enabling important genetic information to assist in the selection of valuable fruit quality apple varieties. © The Author 2017. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Effect of Par Frying on Composition and Texture of Breaded and Battered Catfish

PubMed Central

Woods, Kristin; Lea, Jeanne M.; Brashear, Suzanne S.; Boue, Stephen M.; Daigle, Kim W.; Bett-Garber, Karen L.

2018-01-01

Catfish is often consumed as a breaded and battered fried product; however, there is increasing interest in breaded and battered baked products as a healthier alternative. Par frying can improve the texture properties of breaded and battered baked products, but there are concerns about the increase in lipid uptake from par frying. The objective of this study was to examine the effect of different batters (rice, corn, and wheat) and the effect of par frying on the composition and texture properties of baked catfish. Catfish fillets were cut strips and then coated with batters, which had similar viscosities. Half of the strips were par fried in 177 °C vegetable oil for 1 min and the other half were not par fried. Samples were baked at 177 °C for 25 min. Analysis included % batter adhesion, cooking loss, protein, lipid, ash, and moisture, plus hardness and fracture quality measured using a texture analyzer. A trained sensory panel evaluated both breading and flesh texture attributes. Results found the lipid content of par fried treatments were significantly higher for both corn and wheat batters than for non-par fried treatments. Sensory analysis indicated that the texture of the coatings in the par fried treatments were significantly greater for hardness attributes. Fillet flakiness was significantly greater in the par fried treatments and corn-based batters had moister fillet strips compared to the wheat flour batters. Texture analyzer hardness values were higher for the par fried treatments. PMID:29570660

Material quality assessment of silk nanofibers based on swarm intelligence

NASA Astrophysics Data System (ADS)

Brandoli Machado, Bruno; Nunes Gonçalves, Wesley; Martinez Bruno, Odemir

2013-02-01

In this paper, we propose a novel approach for texture analysis based on artificial crawler model. Our method assumes that each agent can interact with the environment and each other. The evolution process converges to an equilibrium state according to the set of rules. For each textured image, the feature vector is composed by signatures of the live agents curve at each time. Experimental results revealed that combining the minimum and maximum signatures into one increase the classification rate. In addition, we pioneer the use of autonomous agents for characterizing silk fibroin scaffolds. The results strongly suggest that our approach can be successfully employed for texture analysis.

BCC skin cancer diagnosis based on texture analysis techniques

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

Functional surfaces for tribological applications: inspiration and design

NASA Astrophysics Data System (ADS)

Abdel-Aal, Hisham A.

2016-12-01

Surface texturing has been recognized as a method for enhancing the tribological properties of surfaces for many years. Adding a controlled texture to one of two faces in relative motion can have many positive effects, such as reduction of friction and wear and increase in load capacity. To date, the true potential of texturing has not been realized not because of the lack of enabling texturing technologies but because of the severe lack of detailed information about the mechanistic functional details of texturing in a tribological situation. Experimental as well as theoretical analysis of textured surfaces define important metrics for performance evaluation. These metrics represent the interaction between geometry of the texturing element and surface topology. To date, there is no agreement on the optimal values that should be implemented given a particular surface. More importantly, a well-defined methodology for the generation of deterministic textures of optimized designs virtually does not exist. Nature, on the other hand, offers many examples of efficient texturing strategies (geometries and topologies) specifically applied to mitigate frictional effects in a variety of situations. Studying these examples may advance the technology of surface engineering. This paper therefore, provides a comparative review of surface texturing that manifest viable synergy between tribology and biology. We attempt to provide successful emerging examples where borrowing from nature has inspired viable surface solutions that address difficult tribological problems both in dry and lubricated contact situations.

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

PubMed

Baldissin, Maurício Martins; Souza, Edna Marina de

2013-12-01

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

Zizyphus spina-christi protects against carbon tetrachloride-induced liver fibrosis in rats.

PubMed

Amin, Amr; Mahmoud-Ghoneim, Doaa

2009-08-01

The study of chronic hepatic fibrosis has been receiving an escalating attention in the past two decades. The aim of the study was to examine the effects of the water extract of Zizyphus spina-christi (L.) (ZSC) on carbon tetrachloride (CCl(4))-induced hepatic fibrosis. ZSC extract was daily administered [alone (ZSC-control group) or along with CCl(4) (protected groups)] at 0.125 (low dose), 0.250 (medium dose) and 0.350 (high dose) g/kg b.wt. for 8 weeks. Histo-pathological, biochemical and histology texture analyses revealed that ZSC significantly impede the progression of hepatic fibrosis. ZSC resulted in a significant amelioration of liver injury judged by the reduced activities of serum ALT and AST. Oral administration of ZSC has also restored normal levels of malondialdehyde and retained control activities of endogenous antioxidants such as SOD, CAT and GSH. Furthermore, ZSC reduced the expression of alpha-smooth muscle actin, the deposition of types I and III collagen in CCl(4)-injured rats. Texture analysis of microscopic images along with fibrosis index calculation showed improvement in the quality of type I collagen distribution and its quantity after administration of ZSC extract. These results demonstrate that administration of ZSC may be useful in the treatment and prevention of hepatic fibrosis.

Application of the angle measure technique as image texture analysis method for the identification of uranium ore concentrate samples: New perspective in nuclear forensics.

PubMed

Fongaro, Lorenzo; Ho, Doris Mer Lin; Kvaal, Knut; Mayer, Klaus; Rondinella, Vincenzo V

2016-05-15

The identification of interdicted nuclear or radioactive materials requires the application of dedicated techniques. In this work, a new approach for characterizing powder of uranium ore concentrates (UOCs) is presented. It is based on image texture analysis and multivariate data modelling. 26 different UOCs samples were evaluated applying the Angle Measure Technique (AMT) algorithm to extract textural features on samples images acquired at 250× and 1000× magnification by Scanning Electron Microscope (SEM). At both magnifications, this method proved effective to classify the different types of UOC powder based on the surface characteristics that depend on particle size, homogeneity, and graininess and are related to the composition and processes used in the production facilities. Using the outcome data from the application of the AMT algorithm, the total explained variance was higher than 90% with Principal Component Analysis (PCA), while partial least square discriminant analysis (PLS-DA) applied only on the 14 black colour UOCs powder samples, allowed their classification only on the basis of their surface texture features (sensitivity>0.6; specificity>0.6). This preliminary study shows that this method was able to distinguish samples with similar composition, but obtained from different facilities. The mean angle spectral data obtained by the image texture analysis using the AMT algorithm can be considered as a specific fingerprint or signature of UOCs and could be used for nuclear forensic investigation. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Plaque echodensity and textural features are associated with histologic carotid plaque instability.

PubMed

Doonan, Robert J; Gorgui, Jessica; Veinot, Jean P; Lai, Chi; Kyriacou, Efthyvoulos; Corriveau, Marc M; Steinmetz, Oren K; Daskalopoulou, Stella S

2016-09-01

Carotid plaque echodensity and texture features predict cerebrovascular symptomatology. Our purpose was to determine the association of echodensity and textural features obtained from a digital image analysis (DIA) program with histologic features of plaque instability as well as to identify the specific morphologic characteristics of unstable plaques. Patients scheduled to undergo carotid endarterectomy were recruited and underwent carotid ultrasound imaging. DIA was performed to extract echodensity and textural features using Plaque Texture Analysis software (LifeQ Medical Ltd, Nicosia, Cyprus). Carotid plaque surgical specimens were obtained and analyzed histologically. Principal component analysis (PCA) was performed to reduce imaging variables. Logistic regression models were used to determine if PCA variables and individual imaging variables predicted histologic features of plaque instability. Image analysis data from 160 patients were analyzed. Individual imaging features of plaque echolucency and homogeneity were associated with a more unstable plaque phenotype on histology. These results were independent of age, sex, and degree of carotid stenosis. PCA reduced 39 individual imaging variables to five PCA variables. PCA1 and PCA2 were significantly associated with overall plaque instability on histology (both P = .02), whereas PCA3 did not achieve statistical significance (P = .07). DIA features of carotid plaques are associated with histologic plaque instability as assessed by multiple histologic features. Importantly, unstable plaques on histology appear more echolucent and homogeneous on ultrasound imaging. These results are independent of stenosis, suggesting that image analysis may have a role in refining the selection of patients who undergo carotid endarterectomy. Copyright © 2016 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.

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.

Estimating of Soil Texture Using Landsat Imagery: a Case Study in Thatta Tehsil, Sindh

NASA Astrophysics Data System (ADS)

Khalil, Zahid

2016-07-01

Soil texture is considered as an important environment factor for agricultural growth. It is the most essential part for soil classification in large scale. Today the precise soil information in large scale is of great demand from various stakeholders including soil scientists, environmental managers, land use planners and traditional agricultural users. With the increasing demand of soil properties in fine scale spatial resolution made the traditional laboratory methods inadequate. In addition the costs of soil analysis with precision agriculture systems are more expensive than traditional methods. In this regard, the application of geo-spatial techniques can be used as an alternative for examining soil analysis. This study aims to examine the ability of Geo-spatial techniques in identifying the spatial patterns of soil attributes in fine scale. Around 28 samples of soil were collected from the different areas of Thatta Tehsil, Sindh, Pakistan for analyzing soil texture. An Ordinary Least Square (OLS) regression analysis was used to relate the reflectance values of Landsat8 OLI imagery with the soil variables. The analysis showed there was a significant relationship (p<0.05) of band 2 and 5 with silt% (R2 = 0.52), and band 4 and 6 with clay% (R2 =0.40). The equation derived from OLS analysis was then used for the whole study area for deriving soil attributes. The USDA textural classification triangle was implementing for the derivation of soil texture map in GIS environment. The outcome revealed that the 'sandy loam' was in great quantity followed by loam, sandy clay loam and clay loam. The outcome shows that the Geo-spatial techniques could be used efficiently for mapping soil texture of a larger area in fine scale. This technology helped in decreasing cost, time and increase detailed information by reducing field work to a considerable level.

"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.

Statistical analyses of soil properties on a quaternary terrace sequence in the upper sava river valley, Slovenia, Yugoslavia

USGS Publications Warehouse

Vidic, N.; Pavich, M.; Lobnik, F.

1991-01-01

Alpine glaciations, climatic changes and tectonic movements have created a Quaternary sequence of gravely carbonate sediments in the upper Sava River Valley, Slovenia, Yugoslavia. The names for terraces, assigned in this model, Gu??nz, Mindel, Riss and Wu??rm in order of decreasing age, are used as morphostratigraphic terms. Soil chronosequence on the terraces was examined to evaluate which soil properties are time dependent and can be used to help constrain the ages of glaciofluvial sedimentation. Soil thickness, thickness of Bt horizons, amount and continuity of clay coatings and amount of Fe and Me concretions increase with soil age. The main source of variability consists of solutions of carbonate, leaching of basic cations and acidification of soils, which are time dependent and increase with the age of soils. The second source of variability is the content of organic matter, which is less time dependent, but varies more within soil profiles. Textural changes are significant, presented by solution of carbonate pebbles and sand, and formation is silt loam matrix, which with age becomes finer, with clay loam or clayey texture. The oldest, Gu??nz, terrace shows slight deviation from general progressive trends of changes of soil properties with time. The hypothesis of single versus multiple depositional periods of deposition was tested with one-way analysis of variance (ANOVA) on a staggered, nested hierarchical sampling design on a terrace of largest extent and greatest gravel volume, the Wu??rm terrace. The variability of soil properties is generally higher within subareas than between areas of the terrace, except for the soil thickness. Observed differences in soil thickness between the areas of the terrace could be due to multiple periods of gravel deposition, or to the initial differences of texture of the deposits. ?? 1991.

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

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.

Process metallurgy simulation for metal drawing process optimization by using two-scale finite element method

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

Nakamachi, Eiji; Yoshida, Takashi; Yamaguchi, Toshihiko

2014-10-06

We developed two-scale FE analysis procedure based on the crystallographic homogenization method by considering the hierarchical structure of poly-crystal aluminium alloy metal. It can be characterized as the combination of two-scale structure, such as the microscopic polycrystal structure and the macroscopic elastic plastic continuum. Micro polycrystal structure can be modeled as a three dimensional representative volume element (RVE). RVE is featured as by 3×3×3 eight-nodes solid finite elements, which has 216 crystal orientations. This FE analysis code can predict the deformation, strain and stress evolutions in the wire drawing processes in the macro- scales, and further the crystal texture andmore » hardening evolutions in the micro-scale. In this study, we analyzed the texture evolution in the wire drawing processes by our two-scale FE analysis code under conditions of various drawing angles of dice. We evaluates the texture evolution in the surface and center regions of the wire cross section, and to clarify the effects of processing conditions on the texture evolution.« less

Process metallurgy simulation for metal drawing process optimization by using two-scale finite element method

NASA Astrophysics Data System (ADS)

Nakamachi, Eiji; Yoshida, Takashi; Kuramae, Hiroyuki; Morimoto, Hideo; Yamaguchi, Toshihiko; Morita, Yusuke

2014-10-01

We developed two-scale FE analysis procedure based on the crystallographic homogenization method by considering the hierarchical structure of poly-crystal aluminium alloy metal. It can be characterized as the combination of two-scale structure, such as the microscopic polycrystal structure and the macroscopic elastic plastic continuum. Micro polycrystal structure can be modeled as a three dimensional representative volume element (RVE). RVE is featured as by 3×3×3 eight-nodes solid finite elements, which has 216 crystal orientations. This FE analysis code can predict the deformation, strain and stress evolutions in the wire drawing processes in the macro- scales, and further the crystal texture and hardening evolutions in the micro-scale. In this study, we analyzed the texture evolution in the wire drawing processes by our two-scale FE analysis code under conditions of various drawing angles of dice. We evaluates the texture evolution in the surface and center regions of the wire cross section, and to clarify the effects of processing conditions on the texture evolution.

An application of Chan-Vese method used to determine the ROI area in CT lung screening

NASA Astrophysics Data System (ADS)

Prokop, Paweł; Surtel, Wojciech

2016-09-01

The article presents two approaches of determining the ROI area in CT lung screening. First approach is based on a classic method of framing the image in order to determine the ROI by using a MaZda tool. Second approach is based on segmentation of CT images of the lungs and reducing the redundant information from the image. Of the two approaches of an Active Contour, it was decided to choose the Chan-Vese method. In order to determine the effectiveness of the approach, it was performed an analysis of received ROI texture and extraction of textural features. In order to determine the effectiveness of the method, it was performed an analysis of the received ROI textures and extraction of the texture features, by using a Mazda tool. The results were compared and presented in the form of the radar graphs. The second approach proved to be effective and appropriate and consequently it is used for further analysis of CT images, in the computer-aided diagnosis of sarcoidosis.

Relationship between trabecular texture features of CT images and an amount of bone cement volume injection in percutaneous vertebroplasty

NASA Astrophysics Data System (ADS)

Tack, Gye Rae; Choi, Hyung Guen; Shin, Kyu-Chul; Lee, Sung J.

2001-06-01

Percutaneous vertebroplasty is a surgical procedure that was introduced for the treatment of compression fracture of the vertebrae. This procedure includes puncturing vertebrae and filling with polymethylmethacrylate (PMMA). Recent studies have shown that the procedure could provide structural reinforcement for the osteoporotic vertebrae while being minimally invasive and safe with immediate pain relief. However, treatment failures due to disproportionate PMMA volume injection have been reported as one of complications in vertebroplasty. It is believed that control of PMMA volume is one of the most critical factors that can reduce the incidence of complications. In this study, appropriate amount of PMMA volume was assessed based on the imaging data of a given patient under the following hypotheses: (1) a relationship can be drawn between the volume of PMMA injection and textural features of the trabecular bone in preoperative CT images and (2) the volume of PMMA injection can be estimated based on 3D reconstruction of postoperative CT images. Gray-level run length analysis was used to determine the textural features of the trabecular bone. The width of trabecular (T-texture) and the width of intertrabecular spaces (I-texture) were calculated. The correlation between PMMA volume and textural features of patient's CT images was also examined to evaluate the appropriate PMMA amount. Results indicated that there was a strong correlation between the actual PMMA injection volume and the area of the intertrabecular space and that of trabecular bone calculated from the CT image (correlation coefficient, requals0.96 and requals-0.95, respectively). T- texture (requals-0.93) did correlate better with the actual PMMA volume more than the I-texture (requals0.57). Therefore, it was demonstrated that appropriate PMMA injection volume could be predicted based on the textural analysis for better clinical management of the osteoporotic spine.

SU-F-R-40: Robustness Test of Computed Tomography Textures of Lung Tissues to Varying Scanning Protocols Using a Realistic Phantom Environment

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

Lee, S; Markel, D; Hegyi, G

2016-06-15

Purpose: The reliability of computed tomography (CT) textures is an important element of radiomics analysis. This study investigates the dependency of lung CT textures on different breathing phases and changes in CT image acquisition protocols in a realistic phantom setting. Methods: We investigated 11 CT texture features for radiation-induced lung disease from 3 categories (first-order, grey level co-ocurrence matrix (GLCM), and Law’s filter). A biomechanical swine lung phantom was scanned at two breathing phases (inhale/exhale) and two scanning protocols set for PET/CT and diagnostic CT scanning. Lung volumes acquired from the CT images were divided into 2-dimensional sub-regions with amore » grid spacing of 31 mm. The distribution of the evaluated texture features from these sub-regions were compared between the two scanning protocols and two breathing phases. The significance of each factor on feature values were tested at 95% significance level using analysis of covariance (ANCOVA) model with interaction terms included. Robustness of a feature to a scanning factor was defined as non-significant dependence on the factor. Results: Three GLCM textures (variance, sum entropy, difference entropy) were robust to breathing changes. Two GLCM (variance, sum entropy) and 3 Law’s filter textures (S5L5, E5L5, W5L5) were robust to scanner changes. Moreover, the two GLCM textures (variance, sum entropy) were consistent across all 4 scanning conditions. First-order features, especially Hounsfield unit intensity features, presented the most drastic variation up to 39%. Conclusion: Amongst the studied features, GLCM and Law’s filter texture features were more robust than first-order features. However, the majority of the features were modified by either breathing phase or scanner changes, suggesting a need for calibration when retrospectively comparing scans obtained at different conditions. Further investigation is necessary to identify the sensitivity of individual image acquisition parameters.« less

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.

Potato tuber pectin structure is influenced by pectin methyl esterase activity and impacts on cooked potato texture.

PubMed

Ross, Heather A; Wright, Kathryn M; McDougall, Gordon J; Roberts, Alison G; Chapman, Sean N; Morris, Wayne L; Hancock, Robert D; Stewart, Derek; Tucker, Gregory A; James, Euan K; Taylor, Mark A

2011-01-01

Although cooked potato tuber texture is an important trait that influences consumer preference, a detailed understanding of tuber textural properties at the molecular level is lacking. Previous work has identified tuber pectin methyl esterase activity (PME) as a potential factor impacting on textural properties. In this study, tuber PME isoform and gene expression profiles have been determined in potato germplasm with differing textural properties as assessed using an amended wedge fracture method and a sloughing assay, revealing major differences between the potato types. Differences in pectin structure between potato types with different textural properties were revealed using monoclonal antibodies specific for different pectic epitopes. Chemical analysis of tuber pectin clearly demonstrated that, in tubers containing a higher level of total PME activity, there was a reduced degree of methylation of cell wall pectin and consistently higher peak force and work done values during the fracture of cooked tuber samples, demonstrating the link between PME activity, the degree of methylation of cell wall pectin, and cooked tuber textural properties.

Potato tuber pectin structure is influenced by pectin methyl esterase activity and impacts on cooked potato texture

PubMed Central

Ross, Heather A.; Wright, Kathryn M.; McDougall, Gordon J.; Roberts, Alison G.; Chapman, Sean N.; Morris, Wayne L.; Hancock, Robert D.; Stewart, Derek; Tucker, Gregory A.; James, Euan K.; Taylor, Mark A.

2011-01-01

Although cooked potato tuber texture is an important trait that influences consumer preference, a detailed understanding of tuber textural properties at the molecular level is lacking. Previous work has identified tuber pectin methyl esterase activity (PME) as a potential factor impacting on textural properties. In this study, tuber PME isoform and gene expression profiles have been determined in potato germplasm with differing textural properties as assessed using an amended wedge fracture method and a sloughing assay, revealing major differences between the potato types. Differences in pectin structure between potato types with different textural properties were revealed using monoclonal antibodies specific for different pectic epitopes. Chemical analysis of tuber pectin clearly demonstrated that, in tubers containing a higher level of total PME activity, there was a reduced degree of methylation of cell wall pectin and consistently higher peak force and work done values during the fracture of cooked tuber samples, demonstrating the link between PME activity, the degree of methylation of cell wall pectin, and cooked tuber textural properties. PMID:20855456

Automatic Texture Mapping of Architectural and Archaeological 3d Models

NASA Astrophysics Data System (ADS)

Kersten, T. P.; Stallmann, D.

2012-07-01

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

Evolution of microstructure in stainless martensitic steel for seamless tubing

NASA Astrophysics Data System (ADS)

Pyshmintsev, I. Yu.; Bityukov, S. M.; Pastukhov, V. I.; Danilov, S. V.; Vedernikova, L. O.; Lobanov, M. L.

2017-12-01

Scanning electron microscopy with orientation analysis by the electron backscatter diffraction (EBSD) method is used to study microstructures and textures formed in the 0.08C-13Cr-3Ni-Mo-V-Nb steel through seamless tube production route: after hot deformation by extrusion; after quenching from various temperatures and subsequent high tempering. It is shown that the martensitic microstructure formed both after hot deformation and after quenching is characterized by the presence of deformation crystallographic texture, which is predetermined by the texture of austenite. The effect of heat treatment on texture, packet refinement, lath width, precipitation of carbides and Charpy impact energy is analyzed.

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

NASA Astrophysics Data System (ADS)

Florindo, João. Batista

2018-04-01

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

Fundamental and progress of Bi2Te3-based thermoelectric materials

NASA Astrophysics Data System (ADS)

Hong, Min; Chen, Zhi-Gang; Zou, Jin

2018-04-01

Thermoelectric materials, enabling the directing conversion between heat and electricity, are one of the promising candidates for overcoming environmental pollution and the upcoming energy shortage caused by the over-consumption of fossil fuels. Bi2Te3-based alloys are the classical thermoelectric materials working near room temperature. Due to the intensive theoretical investigations and experimental demonstrations, significant progress has been achieved to enhance the thermoelectric performance of Bi2Te3-based thermoelectric materials. In this review, we first explored the fundamentals of thermoelectric effect and derived the equations for thermoelectric properties. On this basis, we studied the effect of material parameters on thermoelectric properties. Then, we analyzed the features of Bi2Te3-based thermoelectric materials, including the lattice defects, anisotropic behavior and the strong bipolar conduction at relatively high temperature. Then we accordingly summarized the strategies for enhancing the thermoelectric performance, including point defect engineering, texture alignment, and band gap enlargement. Moreover, we highlighted the progress in decreasing thermal conductivity using nanostructures fabricated by solution grown method, ball milling, and melt spinning. Lastly, we employed modeling analysis to uncover the principles of anisotropy behavior and the achieved enhancement in Bi2Te3, which will enlighten the enhancement of thermoelectric performance in broader materials.

Efficient optical analysis of surface texture combinations for silicon solar cells

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Use of registration-based contour propagation in texture analysis for esophageal cancer pathologic response prediction

NASA Astrophysics Data System (ADS)

Yip, Stephen S. F.; Coroller, Thibaud P.; Sanford, Nina N.; Huynh, Elizabeth; Mamon, Harvey; Aerts, Hugo J. W. L.; Berbeco, Ross I.

2016-01-01

Change in PET-based textural features has shown promise in predicting cancer response to treatment. However, contouring tumour volumes on longitudinal scans is time-consuming. This study investigated the usefulness of contour propagation in texture analysis for the purpose of pathologic response prediction in esophageal cancer. Forty-five esophageal cancer patients underwent PET/CT scans before and after chemo-radiotherapy. Patients were classified into responders and non-responders after the surgery. Physician-defined tumour ROIs on pre-treatment PET were propagated onto the post-treatment PET using rigid and ten deformable registration algorithms. PET images were converted into 256 discrete values. Co-occurrence, run-length, and size zone matrix textures were computed within all ROIs. The relative difference of each texture at different treatment time-points was used to predict the pathologic responders. Their predictive value was assessed using the area under the receiver-operating-characteristic curve (AUC). Propagated ROIs from different algorithms were compared using Dice similarity index (DSI). Contours propagated by the fast-demons, fast-free-form and rigid algorithms did not fully capture the high FDG uptake regions of tumours. Fast-demons propagated ROIs had the least agreement with other contours (DSI  =  58%). Moderate to substantial overlap were found in the ROIs propagated by all other algorithms (DSI  =  69%-79%). Rigidly propagated ROIs with co-occurrence texture failed to significantly differentiate between responders and non-responders (AUC  =  0.58, q-value  =  0.33), while the differentiation was significant with other textures (AUC  =  0.71‒0.73, p  <  0.009). Among the deformable algorithms, fast-demons (AUC  =  0.68‒0.70, q-value  <  0.03) and fast-free-form (AUC  =  0.69‒0.74, q-value  <  0.04) were the least predictive. ROIs propagated by all other deformable algorithms with any texture significantly predicted pathologic responders (AUC  =  0.72‒0.78, q-value  <  0.01). Propagated ROIs using deformable registration for all textures can lead to accurate prediction of pathologic response, potentially expediting the temporal texture analysis process. However, fast-demons, fast-free-form, and rigid algorithms should be applied with care due to their inferior performance compared to other algorithms.

Transcriptomic insights into citrus segment membrane's cell wall components relating to fruit sensory texture.

PubMed

Wang, Xun; Lin, Lijin; Tang, Yi; Xia, Hui; Zhang, Xiancong; Yue, Maolan; Qiu, Xia; Xu, Ke; Wang, Zhihui

2018-04-23

During fresh fruit consumption, sensory texture is one factor that affects the organoleptic qualities. Chemical components of plant cell walls, including pectin, cellulose, hemicellulose and lignin, play central roles in determining the textural qualities. To explore the genes and regulatory pathways involved in fresh citrus' perceived sensory texture, we performed mRNA-seq analyses of the segment membranes of two citrus cultivars, Shiranui and Kiyomi, with different organoleptic textures. Segment membranes were sampled at two developmental stages of citrus fruit, the beginning and end of the expansion period. More than 3000 differentially expressed genes were identified. The gene ontology analysis revealed that more categories were significantly enriched in 'Shiranui' than in 'Kiyomi' at both developmental stages. In total, 108 significantly enriched pathways were obtained, with most belonging to metabolism. A detailed transcriptomic analysis revealed potential critical genes involved in the metabolism of cell wall structures, for example, GAUT4 in pectin synthesis, CESA1, 3 and 6, and SUS4 in cellulose synthesis, CSLC5, XXT1 and XXT2 in hemicellulose synthesis, and CSE in lignin synthesis. Low levels, or no expression, of genes involved in cellulose and hemicellulose, such as CESA4, CESA7, CESA8, IRX9 and IRX14, confirmed that secondary cell walls were negligible or absent in citrus segment membranes. A chemical component analysis of the segment membranes from mature fruit revealed that the pectin, cellulose and lignin contents, and the segment membrane's weight (% of segment) were greater in 'Kiyomi'. Organoleptic quality of citrus is easily overlooked. It is mainly determined by sensory texture perceived in citrus segment membrane properties. We performed mRNA-seq analyses of citrus segment membranes to explore the genes and regulatory pathways involved in fresh citrus' perceived sensory texture. Transcriptomic data showed high repeatability between two independent biological replicates. The expression levels of genes involved in cell wall structure metabolism, including pectin, cellulose, hemicellulose and lignin, were investigated. Meanwhile, chemical component contents of the segment membranes from mature fruit were analyzed. This study provided detailed transcriptional regulatory profiles of different organoleptic citrus qualities and integrated insights into the mechanisms affecting citrus' sensory texture.

Food texture analysis in the 21st century

USDA-ARS?s Scientific Manuscript database

The study of food texture encompasses sensory, physiological, and structural aspects. Research in this area must be multidisciplinary in nature, accounting for consumer perception and acceptability, rheology, and structural aspects. This brief review of the field covers sensory panels, instrumenta...

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.

Morphological texture assessment of oral bone as a screening tool for osteoporosis

NASA Astrophysics Data System (ADS)

Analoui, Mostafa; Eggertsson, Hafsteinn; Eckert, George

2001-07-01

Three classes of texture analysis approaches have been employed to assess the textural characteristic of oral bone. A set of linear structuring elements was used to compute granulometric features of trabecular bone. Multifractal analysis was also used to compute the fractal dimension of the corresponding tissues. In addition, some statistical features and histomorphometric parameters were computed. To assess the proposed approach we acquired digital intraoral radiographs of 47 subjects (14 males and 33 females). All radiographs were captured at 12 bits/pixel. Images were converted to binary form through a sliding locally adaptive thresholding approach. Each subject was scanned by DEXA for bone dosimetry. Subject were classified into one of the following three categories according World Health Organization (WHO) standard (1) healthy, (2) with osteopenia and (3) osteoporosis. In this study fractal dimension showed very low correlation with bone mineral density (BMD) measurements, which did not reach a level of statistical significance (p<0.5). However, entropy of pattern spectrum (EPS), along with statistical features and histomorphometric parameters, has shown correlation coefficients ranging from low to high, with statistical significance for both males and females. The results of this study indicate the utility of this approach for bone texture analysis. It is conjectured that designing a 2-D structuring element, specially tuned to trabecular bone texture, will increase the efficacy of the proposed method.

Remote sensing of selective logging in Amazonia Assessing limitations based on detailed field observations, Landsat ETM+, and textural analysis.

Treesearch

Gregory P. Asner; Michael Keller; Rodrigo Pereira; Johan C. Zweede

2002-01-01

We combined a detailed field study of forest canopy damage with calibrated Landsat 7 Enhanced Thematic Mapper Plus (ETM+) reflectance data and texture analysis to assess the sensitivity of basic broadband optical remote sensing to selective logging in Amazonia. Our field study encompassed measurements of ground damage and canopy gap fractions along a chronosequence of...

Texture functions in image analysis: A computationally efficient solution

NASA Technical Reports Server (NTRS)

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

1983-01-01

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

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

DTIC Science & Technology

1992-01-01

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

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

PubMed

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

2014-03-01

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

Segmentation and texture analysis of structural biomarkers using neighborhood-clustering-based level set in MRI of the schizophrenic brain.

PubMed

Latha, Manohar; Kavitha, Ganesan

2018-02-03

Schizophrenia (SZ) is a psychiatric disorder that especially affects individuals during their adolescence. There is a need to study the subanatomical regions of SZ brain on magnetic resonance images (MRI) based on morphometry. In this work, an attempt was made to analyze alterations in structure and texture patterns in images of the SZ brain using the level-set method and Laws texture features. T1-weighted MRI of the brain from Center of Biomedical Research Excellence (COBRE) database were considered for analysis. Segmentation was carried out using the level-set method. Geometrical and Laws texture features were extracted from the segmented brain stem, corpus callosum, cerebellum, and ventricle regions to analyze pattern changes in SZ. The level-set method segmented multiple brain regions, with higher similarity and correlation values compared with an optimized method. The geometric features obtained from regions of the corpus callosum and ventricle showed significant variation (p < 0.00001) between normal and SZ brain. Laws texture feature identified a heterogeneous appearance in the brain stem, corpus callosum and ventricular regions, and features from the brain stem were correlated with Positive and Negative Syndrome Scale (PANSS) score (p < 0.005). A framework of geometric and Laws texture features obtained from brain subregions can be used as a supplement for diagnosis of psychiatric disorders.

Quantitative and qualitative variation of fat in model vanilla custard desserts: effects on sensory properties and consumer acceptance.

PubMed

Tomaschunas, Maja; Köhn, Ehrhard; Bennwitz, Petra; Hinrichs, Jörg; Busch-Stockfisch, Mechthild

2013-06-01

The effects of variation in fat content (0.1% to 15.8%) and type of fat, using different types of milk, dairy cream, or vegetable fat cream, on sensory characteristics and consumer acceptance of starch-based vanilla model custards were studied. Descriptive analysis with trained panelists and consumer testing with untrained assessors were applied. Descriptive data were related to hedonic data using principal component analysis to determine drivers of liking and disliking. Results demonstrated an increasing effect of fat concerning visual and oral thickness, creamy flavor, and fat-related texture properties, as well as a decreasing effect concerning yellow color and surface shine. A lack of fat caused moderate intensities in pudding-like flavor attributes and an intensive jelly texture. Adding a vegetable fat cream led to lower intensities in attributes yellow color, cooked flavor, thick, and jelly texture, whereas intensities in vegetable fat flavor and fat-related texture properties increased. All consumers favored custards with medium fat contents, being high in pudding-like and vegetable fat flavor as well as in fat-related texture attributes. Nonfat custards were rejected due to jelly texture and moderate intensities in pudding-flavor attributes. High-fat samples were liked by some consumers, but their high intensities in thickness, white color, and creamy flavor also drove disliking for others. © 2013 Institute of Food Technologists®

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

Parenchymal texture analysis in digital mammography: A fully automated pipeline for breast cancer risk assessment.

PubMed

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

2015-07-01

Mammographic percent density (PD%) is known to be a strong risk factor for breast cancer. Recent studies also suggest that parenchymal texture features, which are more granular descriptors of the parenchymal pattern, can provide additional information about breast cancer risk. To date, most studies have measured mammographic texture within selected regions of interest (ROIs) in the breast, which cannot adequately capture the complexity of the parenchymal pattern throughout the whole breast. To better characterize patterns of the parenchymal tissue, the authors have developed a fully automated software pipeline based on a novel lattice-based strategy to extract a range of parenchymal texture features from the entire breast region. Digital mammograms from 106 cases with 318 age-matched controls were retrospectively analyzed. The lattice-based approach is based on a regular grid virtually overlaid on each mammographic image. Texture features are computed from the intersection (i.e., lattice) points of the grid lines within the breast, using a local window centered at each lattice point. Using this strategy, a range of statistical (gray-level histogram, co-occurrence, and run-length) and structural (edge-enhancing, local binary pattern, and fractal dimension) features are extracted. To cover the entire breast, the size of the local window for feature extraction is set equal to the lattice grid spacing and optimized experimentally by evaluating different windows sizes. The association between their lattice-based texture features and breast cancer was evaluated using logistic regression with leave-one-out cross validation and further compared to that of breast PD% and commonly used single-ROI texture features extracted from the retroareolar or the central breast region. Classification performance was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC). DeLong's test was used to compare the different ROCs in terms of AUC performance. The average univariate performance of the lattice-based features is higher when extracted from smaller than larger window sizes. While not every individual texture feature is superior to breast PD% (AUC: 0.59, STD: 0.03), their combination in multivariate analysis has significantly better performance (AUC: 0.85, STD: 0.02, p < 0.001). The lattice-based texture features also outperform the single-ROI texture features when extracted from the retroareolar or the central breast region (AUC: 0.60-0.74, STD: 0.03). Adding breast PD% does not make a significant performance improvement to the lattice-based texture features or the single-ROI features (p > 0.05). The proposed lattice-based strategy for mammographic texture analysis enables to characterize the parenchymal pattern over the entire breast. As such, these features provide richer information compared to currently used descriptors and may ultimately improve breast cancer risk assessment. Larger studies are warranted to validate these findings and also compare to standard demographic and reproductive risk factors.

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

PubMed

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

2016-08-01

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

Microstructure and Crystallographic Texture Evolution During the Friction-Stir Processing of a Precipitation-Hardenable Aluminum Alloy

NASA Astrophysics Data System (ADS)

Nadammal, Naresh; Kailas, Satish V.; Szpunar, Jerzy; Suwas, Satyam

2015-05-01

Friction-stir processing (FSP) has been proven as a successful method for the grain refinement of high-strength aluminum alloys. The most important attributes of this process are the fine-grain microstructure and characteristic texture, which impart suitable properties in the as-processed material. In the current work, FSP of the precipitation-hardenable aluminum alloy 2219 has been carried out and the consequent evolution of microstructure and texture has been studied. The as-processed materials were characterized using electron back-scattered diffraction, x-ray diffraction, and electron probe microanalysis. Onion-ring formation was observed in the nugget zone, which has been found to be related to the precipitation response and crystallographic texture of the alloy. Texture development in the alloy has been attributed to the combined effect of shear deformation and dynamic recrystallization. The texture was found heterogeneous even within the nugget zone. A microtexture analysis revealed the dominance of shear texture components, with C component at the top of nugget zone and the B and A2* components in the middle and bottom. The bulk texture measurement in the nugget zone revealed a dominant C component. The development of a weaker texture along with the presence of some large particles in the nugget zone indicates particle-stimulated nucleation as the dominant nucleation mechanism during FSP. Grain growth follows the Burke and Turnbull mechanism and geometrical coalescence.

An extensive analysis of various texture feature extractors to detect Diabetes Mellitus using facial specific regions.

PubMed

Shu, Ting; Zhang, Bob; Yan Tang, Yuan

2017-04-01

Researchers have recently discovered that Diabetes Mellitus can be detected through non-invasive computerized method. However, the focus has been on facial block color features. In this paper, we extensively study the effects of texture features extracted from facial specific regions at detecting Diabetes Mellitus using eight texture extractors. The eight methods are from four texture feature families: (1) statistical texture feature family: Image Gray-scale Histogram, Gray-level Co-occurance Matrix, and Local Binary Pattern, (2) structural texture feature family: Voronoi Tessellation, (3) signal processing based texture feature family: Gaussian, Steerable, and Gabor filters, and (4) model based texture feature family: Markov Random Field. In order to determine the most appropriate extractor with optimal parameter(s), various parameter(s) of each extractor are experimented. For each extractor, the same dataset (284 Diabetes Mellitus and 231 Healthy samples), classifiers (k-Nearest Neighbors and Support Vector Machines), and validation method (10-fold cross validation) are used. According to the experiments, the first and third families achieved a better outcome at detecting Diabetes Mellitus than the other two. The best texture feature extractor for Diabetes Mellitus detection is the Image Gray-scale Histogram with bin number=256, obtaining an accuracy of 99.02%, a sensitivity of 99.64%, and a specificity of 98.26% by using SVM. Copyright © 2017 Elsevier Ltd. All rights reserved.

Muscle Protein Profiles Used for Prediction of Texture of Farmed Salmon (Salmo salar L.).

PubMed

Ørnholt-Johansson, Gine; Frosch, Stina; Gudjónsdóttir, María; Wulff, Tune; Jessen, Flemming

2017-04-26

A soft texture is undesired in Atlantic salmon as it leads to downgrading and reduced yield, yet it is a factor for which the cause is not fully understood. This lack of understanding highlights the need for identifying the cause of the soft texture and developing solutions by which the processing industry can improve the yield. Changes in muscle protein profiles can occur both pre- and postharvest and constitute an overall characterization of the muscle properties including texture. The aim of this study was to investigate this relationship between specific muscle proteins and the texture of the salmon fillet. Samples for 2D-gel-based proteomics were taken from the fillet above the lateral line at the same position as where the texture had been measured. The resulting protein profiles were analyzed using multivariate data analysis. Sixteen proteins were found to correlate to the measured texture, showing that it is possible to predict peak force based on a small subset of proteins. Additionally, eight of the 16 proteins were identified by tandem mass spectrometry including serum albumin, dipeptidyl peptidase 3, heat shock protein 70, annexins, and a protein presumed to be a titin fragment. It is contemplated that the identification of these proteins and their significance for the measured texture will contribute to further understanding of the Atlantic salmon muscle texture.

Dynamic texture recognition using local binary patterns with an application to facial expressions.

PubMed

Zhao, Guoying; Pietikäinen, Matti

2007-06-01

Dynamic texture (DT) is an extension of texture to the temporal domain. Description and recognition of DTs have attracted growing attention. In this paper, a novel approach for recognizing DTs is proposed and its simplifications and extensions to facial image analysis are also considered. First, the textures are modeled with volume local binary patterns (VLBP), which are an extension of the LBP operator widely used in ordinary texture analysis, combining motion and appearance. To make the approach computationally simple and easy to extend, only the co-occurrences of the local binary patterns on three orthogonal planes (LBP-TOP) are then considered. A block-based method is also proposed to deal with specific dynamic events such as facial expressions in which local information and its spatial locations should also be taken into account. In experiments with two DT databases, DynTex and Massachusetts Institute of Technology (MIT), both the VLBP and LBP-TOP clearly outperformed the earlier approaches. The proposed block-based method was evaluated with the Cohn-Kanade facial expression database with excellent results. The advantages of our approach include local processing, robustness to monotonic gray-scale changes, and simple computation.

Quantitative texture analysis of talc in mantle hydrated mylonites

NASA Astrophysics Data System (ADS)

Benitez-Perez, J. M.; Gomez Barreiro, J.; Wenk, H. R.; Vogel, S. C.; Soda, Y.; Voltolini, M.; Martinez-Catalan, J. R.

2014-12-01

A quantitative texture analysis of talc-serpentinite mylonites developed in highly deformed ultramafic rocks from different orogenic contexts have been done with neutorn diffraction at HIPPO (Los Álamos National Laboratory). Mineral assemblage, metamorphic evolution and deformative fabric of these samples could be correlated with those verified along the shallow levels (<100km; <5GPa) of a subduction zone. The hydration of mantle (ultramafic) rocks at those levels it is likely to occur dynamically, with important implications on seismogenesis. Given the high anisotropy of the major phases in the samples (i.e. talc and antigorite) it is expected to influence seismic anisotropy of the whole system, in the presence of texture. However to date there was no data on the crystallographic preferred orientation of talc and examples of antigorite textures are very limited. We explore the contribution of talc texture to the seismic anisotropy of mantle hydrated mylonites. Acknowledgements: This work has been funded by research project CGL2011-22728 of Spanish Ministry of Economy and Competitiveness. JGB and JMBP are grateful to the Ramón y Cajal and FPI funding programs. Access to HIPPO (LANSCE) to conduct diffraction experiments is kindly acknowledged.

Abnormal Image Detection in Endoscopy Videos Using a Filter Bank and Local Binary Patterns

PubMed Central

Nawarathna, Ruwan; Oh, JungHwan; Muthukudage, Jayantha; Tavanapong, Wallapak; Wong, Johnny; de Groen, Piet C.; Tang, Shou Jiang

2014-01-01

Finding mucosal abnormalities (e.g., erythema, blood, ulcer, erosion, and polyp) is one of the most essential tasks during endoscopy video review. Since these abnormalities typically appear in a small number of frames (around 5% of the total frame number), automated detection of frames with an abnormality can save physician’s time significantly. In this paper, we propose a new multi-texture analysis method that effectively discerns images showing mucosal abnormalities from the ones without any abnormality since most abnormalities in endoscopy images have textures that are clearly distinguishable from normal textures using an advanced image texture analysis method. The method uses a “texton histogram” of an image block as features. The histogram captures the distribution of different “textons” representing various textures in an endoscopy image. The textons are representative response vectors of an application of a combination of Leung and Malik (LM) filter bank (i.e., a set of image filters) and a set of Local Binary Patterns on the image. Our experimental results indicate that the proposed method achieves 92% recall and 91.8% specificity on wireless capsule endoscopy (WCE) images and 91% recall and 90.8% specificity on colonoscopy images. PMID:25132723

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

NASA Astrophysics Data System (ADS)

McGhee, Paul

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

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.

The von Mises stress distribution on the surface of UHMWPE with texture-shaped variation in the presence of normal load and dry sliding contact

NASA Astrophysics Data System (ADS)

Lestari, W. D.; Jamari, J.; Bayuseno, A. P.

2017-04-01

The texture shapes play a key role in the tribological performance of the surface material. This paper presents a study on the use of the 3D finite element method for surface stress analysis on the different texture shape under load and dry sliding contact. The five texture-shaped model was investigated in this work, namely square, circle, ellipse, triangle, and chevron. The result shown that the square shape has the highest value of von Mises resultant stress under static load. In contrast, the dry sliding contact on the triangle shape provided the highest von Mises stress distribution. The lowest value of von Mises stress can be found in the texture pattern of circle, square, and chevron under influence of load for 17 N, 30 N, and 50 N, respectively. Those texture patterns applied to surface of Ultra High Molecular Weight Polyethylene (UHMWPE) may have a strong effect on the reduction of wear rate and enhance tribological performance.

Effect of pullulan on the water distribution, microstructure and textural properties of rice starch gels during cold storage.

PubMed

Chen, Long; Tian, Yaoqi; Tong, Qunyi; Zhang, Zipei; Jin, Zhengyu

2017-01-01

The effects of pullulan on the water distribution, microstructure and textural properties of rice starch gels during cold storage were investigated by low field-nuclear magnetic resonance (LF-NMR), scanning electron microscope (SEM), and texture profile analysis (TPA). The addition of pullulan reduced the transversal relaxation time of rice starch gels during cold storage. The microstructure of rice starch gel with 0.5% pullulan was denser and more uniform compared with that of rice starch without pullulan in each period of storage time. With regard to textural properties, 0.01% pullulan addition did not significantly change the texture of rice starch gels, while 0.5% pullulan addition appeared to reduce the hardness and retain the springiness of rice starch gels (P⩽0.05). The restriction effects of pullulan on water mobility and starch retrogradation were hypothesized to be mainly responsible for the water retention, gel structure maintenance, and modification of the textural attributes of rice starch gels. Copyright © 2016 Elsevier Ltd. All rights reserved.

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).

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.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Impact of storage on dark chocolate: texture and polymorphic changes.

PubMed

Nightingale, Lia M; Lee, Soo-Yeun; Engeseth, Nicki J

2011-01-01

Chocolate storage is critical to final product quality. Inadequate storage, especially with temperature fluctuations, may lead to rearrangement of triglycerides that make up the bulk of the chocolate matrix; this rearrangement may lead to fat bloom. Bloom is the main cause of quality loss in the chocolate industry. The effect of storage conditions leading to bloom formation on texture and flavor attributes by human and instrumental measures has yet to be reported. Therefore, the impact of storage conditions on the quality of dark chocolate by sensory and instrumental measurements was determined. Dark chocolate was kept under various conditions and analyzed at 0, 4, and 8 wk of storage. Ten members of a descriptive panel analyzed texture and flavor. Instrumental methods included texture analysis, color measurement, lipid polymorphism by X-ray diffraction and differential scanning calorimetry, triglyceride concentration by gas chromatography, and surface properties by atomic force microscopy. Results were treated by analysis of variance, cluster analysis, principal component analysis, and linear partial least squares regression analysis. Chocolate stored 8 wk at high temperature without fluctuations and 4 wk with fluctuations transitioned from form V to VI. Chocolates stored at high temperature with and without fluctuations were harder, more fracturable, more toothpacking, had longer melt time, were less sweet, and had less cream flavor. These samples had rougher surfaces, fewer but larger grains, and a heterogeneous surface. Overall, all stored dark chocolate experienced instrumental or perceptual changes attributed to storage condition. Chocolates stored at high temperature with and without fluctuations were most visually and texturally compromised. Practical Application: Many large chocolate companies do their own "in-house" unpublished research and smaller confectionery facilities do not have the means to conduct their own research. Therefore, this study relating sensory and instrumental data provides published evidence available for application throughout the confectionery industry.

Differentiating benign from malignant mediastinal lymph nodes visible at EBUS using grey-scale textural analysis.

PubMed

Edey, Anthony J; Pollentine, Adrian; Doody, Claire; Medford, Andrew R L

2015-04-01

Recent data suggest that grey-scale textural analysis on endobronchial ultrasound (EBUS) imaging can differentiate benign from malignant lymphadenopathy. The objective of studies was to evaluate grey-scale textural analysis and examine its clinical utility. Images from 135 consecutive clinically indicated EBUS procedures were evaluated retrospectively using MATLAB software (MathWorks, Natick, MA, USA). Manual node mapping was performed to obtain a region of interest and grey-scale textural features (range of pixel values and entropy) were analysed. The initial analysis involved 94 subjects and receiver operating characteristic (ROC) curves were generated. The ROC thresholds were then applied on a second cohort (41 subjects) to validate the earlier findings. A total of 371 images were evaluated. There was no difference in proportions of malignant disease (56% vs 53%, P = 0.66) in the prediction (group 1) and validation (group 2) sets. There was no difference in range of pixel values in group 1 but entropy was significantly higher in the malignant group (5.95 vs 5.77, P = 0.03). Higher entropy was seen in adenocarcinoma versus lymphoma (6.00 vs 5.50, P < 0.05). An ROC curve for entropy gave an area under the curve of 0.58 with 51% sensitivity and 71% specificity for entropy greater than 5.94 for malignancy. In group 2, the entropy threshold phenotyped only 47% of benign cases and 20% of malignant cases correctly. These findings suggest that use of EBUS grey-scale textural analysis for differentiation of malignant from benign lymphadenopathy may not be accurate. Further studies are required. © 2015 Asian Pacific Society of Respirology.

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.

Discrimination of osteoarthritic and rheumatoid human synovial cells in culture by nuclear image analysis.

PubMed

Delage, B; Giroud, F; Monet, J D; Ekindjian, O G; Cals, M J

1999-06-01

Rheumatoid arthritic (RA) and osteoarthritic (OA) synovial cells in culture differ in their metabolic and proliferative behaviour. To assess links between these properties and nuclear changes, we used image analysis to study chromatin texture, together with nuclear morphometry and densitometry of OA and RA cells in primary culture. Chromatin pattern at the third day (D3) was heterogeneous and granular with chromatin clumps whereas at the final stage (D11) of culture a homogeneous and finely granular chromatin texture was observed. This evolution indicates global chromatin decondensation. These characteristics were more marked for RA than for OA nuclei. At each culture time, RA nuclei could be discriminated with high confidence from OA ones from parameters evaluating the organization of the chromatine texture. Nuclear image analysis is thus a useful tool for investigating synovial cell biology.

Uterus segmentation in dynamic MRI using LBP texture descriptors

NASA Astrophysics Data System (ADS)

Namias, R.; Bellemare, M.-E.; Rahim, M.; Pirró, N.

2014-03-01

Pelvic floor disorders cover pathologies of which physiopathology is not well understood. However cases get prevalent with an ageing population. Within the context of a project aiming at modelization of the dynamics of pelvic organs, we have developed an efficient segmentation process. It aims at alleviating the radiologist with a tedious one by one image analysis. From a first contour delineating the uterus-vagina set, the organ border is tracked along a dynamic mri sequence. The process combines movement prediction, local intensity and texture analysis and active contour geometry control. Movement prediction allows a contour intitialization for next image in the sequence. Intensity analysis provides image-based local contour detection enhanced by local binary pattern (lbp) texture descriptors. Geometry control prohibits self intersections and smoothes the contour. Results show the efficiency of the method with images produced in clinical routine.

Collagen morphology and texture analysis: from statistics to classification

PubMed Central

Mostaço-Guidolin, Leila B.; Ko, Alex C.-T.; Wang, Fei; Xiang, Bo; Hewko, Mark; Tian, Ganghong; Major, Arkady; Shiomi, Masashi; Sowa, Michael G.

2013-01-01

In this study we present an image analysis methodology capable of quantifying morphological changes in tissue collagen fibril organization caused by pathological conditions. Texture analysis based on first-order statistics (FOS) and second-order statistics such as gray level co-occurrence matrix (GLCM) was explored to extract second-harmonic generation (SHG) image features that are associated with the structural and biochemical changes of tissue collagen networks. Based on these extracted quantitative parameters, multi-group classification of SHG images was performed. With combined FOS and GLCM texture values, we achieved reliable classification of SHG collagen images acquired from atherosclerosis arteries with >90% accuracy, sensitivity and specificity. The proposed methodology can be applied to a wide range of conditions involving collagen re-modeling, such as in skin disorders, different types of fibrosis and muscular-skeletal diseases affecting ligaments and cartilage. PMID:23846580

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.

Diagnosis of human prostate carcinoma cancer stem cells enriched from DU145 cell lines changes with microscopic texture analysis in radiation and hyperthermia treatment using run-length matrix.

PubMed

Abbasian Ardakani, Ali; Rajaee, Jila; Khoei, Samideh

2017-11-01

Hyperthermia and radiation have the ability to induce structural and morphological changes on both macroscopic and microscopic level. Normal and damage cells have a different texture but may be perceived by human eye, as having the same texture. To explore the potential of texture analysis based on run-length matrix, a total of 32 sphere images for each group and treatment regime were used in this study. Cells were subjected to the treatment with different doses of 6 MeV electron radiation (0 2, 4 and 6 Gy), hyperthermia (at 43° C in 0, 30, 60 and 90 min) and radiation + hyperthermia (at 43 °C in 30 min with 2, 4 and 6 Gy dose), respectively. Twenty run-length matrix (RLM) features were extracted as descriptors for each selected region of interest for texture analysis. Linear discriminant analysis was employed to transform raw data to lower-dimensional spaces and increase discriminative power. The features were classified by the first nearest neighbor classifier. RLM features represented the best performance with sensitivity, specificity, accuracy, positive predictive value (PPV) and negative predictive value (NPV) of 100% between 0 and 6 Gy radiation, 0 and 6 Gy radiation + hyperthermia, 0 and 90 min and 30 and 90 min hyperthermia groups. The area under receiver operating characteristic curve was 1 for these groups. RLM features have a high potential to characterize cell changes during different treatment regimes.

FFDM image quality assessment using computerized image texture analysis

NASA Astrophysics Data System (ADS)

Berger, Rachelle; Carton, Ann-Katherine; Maidment, Andrew D. A.; Kontos, Despina

2010-04-01

Quantitative measures of image quality (IQ) are routinely obtained during the evaluation of imaging systems. These measures, however, do not necessarily correlate with the IQ of the actual clinical images, which can also be affected by factors such as patient positioning. No quantitative method currently exists to evaluate clinical IQ. Therefore, we investigated the potential of using computerized image texture analysis to quantitatively assess IQ. Our hypothesis is that image texture features can be used to assess IQ as a measure of the image signal-to-noise ratio (SNR). To test feasibility, the "Rachel" anthropomorphic breast phantom (Model 169, Gammex RMI) was imaged with a Senographe 2000D FFDM system (GE Healthcare) using 220 unique exposure settings (target/filter, kVs, and mAs combinations). The mAs were varied from 10%-300% of that required for an average glandular dose (AGD) of 1.8 mGy. A 2.5cm2 retroareolar region of interest (ROI) was segmented from each image. The SNR was computed from the ROIs segmented from images linear with dose (i.e., raw images) after flat-field and off-set correction. Image texture features of skewness, coarseness, contrast, energy, homogeneity, and fractal dimension were computed from the Premium ViewTM postprocessed image ROIs. Multiple linear regression demonstrated a strong association between the computed image texture features and SNR (R2=0.92, p<=0.001). When including kV, target and filter as additional predictor variables, a stronger association with SNR was observed (R2=0.95, p<=0.001). The strong associations indicate that computerized image texture analysis can be used to measure image SNR and potentially aid in automating IQ assessment as a component of the clinical workflow. Further work is underway to validate our findings in larger clinical datasets.

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

PubMed Central

2012-01-01

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

Aesthetics by Numbers: Links between Perceived Texture Qualities and Computed Visual Texture Properties.

PubMed

Jacobs, Richard H A H; Haak, Koen V; Thumfart, Stefan; Renken, Remco; Henson, Brian; Cornelissen, Frans W

2016-01-01

Our world is filled with texture. For the human visual system, this is an important source of information for assessing environmental and material properties. Indeed-and presumably for this reason-the human visual system has regions dedicated to processing textures. Despite their abundance and apparent relevance, only recently the relationships between texture features and high-level judgments have captured the interest of mainstream science, despite long-standing indications for such relationships. In this study, we explore such relationships, as these might be used to predict perceived texture qualities. This is relevant, not only from a psychological/neuroscience perspective, but also for more applied fields such as design, architecture, and the visual arts. In two separate experiments, observers judged various qualities of visual textures such as beauty, roughness, naturalness, elegance, and complexity. Based on factor analysis, we find that in both experiments, ~75% of the variability in the judgments could be explained by a two-dimensional space, with axes that are closely aligned to the beauty and roughness judgments. That a two-dimensional judgment space suffices to capture most of the variability in the perceived texture qualities suggests that observers use a relatively limited set of internal scales on which to base various judgments, including aesthetic ones. Finally, for both of these judgments, we determined the relationship with a large number of texture features computed for each of the texture stimuli. We find that the presence of lower spatial frequencies, oblique orientations, higher intensity variation, higher saturation, and redness correlates with higher beauty ratings. Features that captured image intensity and uniformity correlated with roughness ratings. Therefore, a number of computational texture features are predictive of these judgments. This suggests that perceived texture qualities-including the aesthetic appreciation-are sufficiently universal to be predicted-with reasonable accuracy-based on the computed feature content of the textures.

Aesthetics by Numbers: Links between Perceived Texture Qualities and Computed Visual Texture Properties

PubMed Central

Jacobs, Richard H. A. H.; Haak, Koen V.; Thumfart, Stefan; Renken, Remco; Henson, Brian; Cornelissen, Frans W.

2016-01-01

Our world is filled with texture. For the human visual system, this is an important source of information for assessing environmental and material properties. Indeed—and presumably for this reason—the human visual system has regions dedicated to processing textures. Despite their abundance and apparent relevance, only recently the relationships between texture features and high-level judgments have captured the interest of mainstream science, despite long-standing indications for such relationships. In this study, we explore such relationships, as these might be used to predict perceived texture qualities. This is relevant, not only from a psychological/neuroscience perspective, but also for more applied fields such as design, architecture, and the visual arts. In two separate experiments, observers judged various qualities of visual textures such as beauty, roughness, naturalness, elegance, and complexity. Based on factor analysis, we find that in both experiments, ~75% of the variability in the judgments could be explained by a two-dimensional space, with axes that are closely aligned to the beauty and roughness judgments. That a two-dimensional judgment space suffices to capture most of the variability in the perceived texture qualities suggests that observers use a relatively limited set of internal scales on which to base various judgments, including aesthetic ones. Finally, for both of these judgments, we determined the relationship with a large number of texture features computed for each of the texture stimuli. We find that the presence of lower spatial frequencies, oblique orientations, higher intensity variation, higher saturation, and redness correlates with higher beauty ratings. Features that captured image intensity and uniformity correlated with roughness ratings. Therefore, a number of computational texture features are predictive of these judgments. This suggests that perceived texture qualities—including the aesthetic appreciation—are sufficiently universal to be predicted—with reasonable accuracy—based on the computed feature content of the textures. PMID:27493628

A common framework for the analysis of complex motion? Standstill and capture illusions

PubMed Central

Dürsteler, Max R.

2014-01-01

A series of illusions was created by presenting stimuli, which consisted of two overlapping surfaces each defined by textures of independent visual features (i.e., modulation of luminance, color, depth, etc.). When presented concurrently with a stationary 2-D luminance texture, observers often fail to perceive the motion of an overlapping stereoscopically defined depth-texture. This illusory motion standstill arises due to a failure to represent two independent surfaces (one for luminance and one for depth textures) and motion transparency (the ability to perceive motion of both surfaces simultaneously). Instead the stimulus is represented as a single non-transparent surface taking on the stationary nature of the luminance-defined texture. By contrast, if it is the 2D-luminance defined texture that is in motion, observers often perceive the stationary depth texture as also moving. In this latter case, the failure to represent the motion transparency of the two textures gives rise to illusionary motion capture. Our past work demonstrated that the illusions of motion standstill and motion capture can occur for depth-textures that are rotating, or expanding / contracting, or else spiraling. Here I extend these findings to include stereo-shearing. More importantly, it is the motion (or lack thereof) of the luminance texture that determines how the motion of the depth will be perceived. This observation is strongly in favor of a single pathway for complex motion that operates on luminance-defines texture motion signals only. In addition, these complex motion illusions arise with chromatically-defined textures with smooth transitions between their colors. This suggests that in respect to color motion perception the complex motions' pathway is only able to accurately process signals from isoluminant colored textures with sharp transitions between colors, and/or moving at high speeds, which is conceivable if it relies on inputs from a hypothetical dual opponent color pathway. PMID:25566023

Textured silicon nitride: processing and anisotropic properties

PubMed Central

Zhu, Xinwen; Sakka, Yoshio

2008-01-01

Textured silicon nitride (Si3N4) has been intensively studied over the past 15 years because of its use for achieving its superthermal and mechanical properties. In this review we present the fundamental aspects of the processing and anisotropic properties of textured Si3N4, with emphasis on the anisotropic and abnormal grain growth of β-Si3N4, texture structure and texture analysis, processing methods and anisotropic properties. On the basis of the texturing mechanisms, the processing methods described in this article have been classified into two types: hot-working (HW) and templated grain growth (TGG). The HW method includes the hot-pressing, hot-forging and sinter-forging techniques, and the TGG method includes the cold-pressing, extrusion, tape-casting and strong magnetic field alignment techniques for β-Si3N4 seed crystals. Each processing technique is thoroughly discussed in terms of theoretical models and experimental data, including the texturing mechanisms and the factors affecting texture development. Also, methods of synthesizing the rodlike β-Si3N4 single crystals are presented. Various anisotropic properties of textured Si3N4 and their origins are thoroughly described and discussed, such as hardness, elastic modulus, bending strength, fracture toughness, fracture energy, creep behavior, tribological and wear behavior, erosion behavior, contact damage behavior and thermal conductivity. Models are analyzed to determine the thermal anisotropy by considering the intrinsic thermal anisotropy, degree of orientation and various microstructure factors. Textured porous Si3N4 with a unique microstructure composed of oriented elongated β-Si3N4 and anisotropic pores is also described for the first time, with emphasis on its unique mechanical and thermal-mechanical properties. Moreover, as an important related material, textured α-Sialon is also reviewed, because the presence of elongated α-Sialon grains allows the production of textured α-Sialon using the same methods as those used for textured β-Si3N4 and β-Sialon. PMID:27877995

Textures of water-rich mud sediments from the continental margin offshore Costa Rica (IODP expeditions 334 and 344)

NASA Astrophysics Data System (ADS)

Kuehn, Rebecca; Stipp, Michael; Leiss, Bernd

2017-04-01

During sedimentation and burial at continental margins, clay-rich sediments develop crystallographic preferred orientations (textures) depending on the ongoing compaction as well as size distribution and shape fabrics of the grains. Such textures can control the deformational properties of these sediments and hence the strain distribution in active continental margins and also the frictional behavior along and around the plate boundary. Strain-hardening and discontinuous deformation may lead to earthquake nucleation at or below the updip limit of the seismogenic zone. We want to investigate the active continental margin offshore Costa Rica where the oceanic Cocos plate is subducted below the Caribbean plate at a rate of approximately 9 cm per year. The Costa Rica trench is well-known for shallow seismogenesis and tsunami generation. As it is an erosive continental margin, both the incoming sediments from the Nazca plate as well as the slope sediments of the continental margin can be important for earthquake nucleation and faulting causing sea-floor breakage. To investigate texture and composition of the sediments and hence their deformational properties we collected samples from varying depth of 7 different drilling locations across the trench retrieved during IODP expeditions 334 and 344 as part of the Costa Rica Seismogenesis Project (CRISP). Texture analysis was carried out by means of synchrotron diffraction, as only this method is suitable for water-bearing samples. As knowledge on the sediment composition is required as input parameter for the texture data analysis, additional X-ray powder diffraction analysis on the sample material has been carried out. Samples for texture measurements were prepared from the original drill cores using an internally developed cutter which allows to produce cylindrical samples with a diameter of about 1.5 cm. The samples are oriented with respect to the drill core axis. Synchrotron texture measurements were conducted at the ESRF (European Synchrotron Radiation Facility) in Grenoble and the DESY (German Electron Synchrotron) in Hamburg. Samples were measured in transmission mode perpendicular to their cylinder axis with a beam diameter of 500 µm. Measurements were taken from 0 to 175° in 5° steps resulting in 36 images from a 2D image plate detector. Measurement time was in a range from 1 to 3 seconds. Due to the different, low symmetric mineral phases a large number of mostly overlapping reflections results. Such data can only be analyzed by the Rietveld method, in our case implemented in the software package MAUD (Materials Analysis Using Diffraction). Preliminary results show distinct textures depending on the composition and the origin of the samples, i.e. on drilling location and depth, which may be critical for strain localization and faulting of these samples. The results are also important for the analysis of experimentally deformed samples from the same drill cores which showed structurally weak and structurally strong deformation behavior during triaxial compression.

Effect of Annealing on Microstructure, Texture and Tensile Properties of Twin-Roll Cast AZ31B

NASA Astrophysics Data System (ADS)

Masoumi, Mohsen; Zarandi, Faramarz; Pekguleryuz, Mihriban O.

Twin-roll cast (TRC) AZ31 alloy (Mg-3wt.%Al-1wt.%Zn) was subjected to heat treatment at 420 °C. As a result, the intensity of the original basal texture was reduced considerably. Crystallographic orientation analysis revealed that such a change in the texture is due to particle-stimulated nucleation of new grains with random orientations. The tensile test results indicate that annealing slightly increases ultimate tensile strength (UTS), however, dramatically improves the elongation.

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

Wavelet Analysis for RADARSAT Exploitation: Demonstration of Algorithms for Maritime Surveillance

DTIC Science & Technology

2007-02-01

this study , we demonstrate wavelet analysis for exploitation of RADARSAT ocean imagery, including wind direction estimation, oceanic and atmospheric ...of image striations that can arise as a texture pattern caused by turbulent coherent structures in the marine atmospheric boundary layer. The image...associated change in the pattern texture (i.e., the nature of the turbulent atmospheric structures) across the front. Due to the large spatial scale of

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

NASA Astrophysics Data System (ADS)

Purnell, Mark; Nedza, Christopher; Rychlik, Leszek

2017-04-01

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

Clustered-dot halftoning with direct binary search.

PubMed

Goyal, Puneet; Gupta, Madhur; Staelin, Carl; Fischer, Mani; Shacham, Omri; Allebach, Jan P

2013-02-01

In this paper, we present a new algorithm for aperiodic clustered-dot halftoning based on direct binary search (DBS). The DBS optimization framework has been modified for designing clustered-dot texture, by using filters with different sizes in the initialization and update steps of the algorithm. Following an intuitive explanation of how the clustered-dot texture results from this modified framework, we derive a closed-form cost metric which, when minimized, equivalently generates stochastic clustered-dot texture. An analysis of the cost metric and its influence on the texture quality is presented, which is followed by a modification to the cost metric to reduce computational cost and to make it more suitable for screen design.

Laser surface texturing of polypropylene to increase adhesive bonding

NASA Astrophysics Data System (ADS)

Mandolfino, Chiara; Pizzorni, Marco; Lertora, Enrico; Gambaro, Carla

2018-05-01

In this paper, the main parameters of laser surface texturing of polymeric substrates have been studied. The final aim of the texturing is to increase the performance of bonded joints of grey-pigmented polypropylene substrates. The experimental investigation was carried out starting from the identification of the most effective treatment parameters, in order to achieve a good texture without compromising the characteristics of the bulk material. For each of these parameters, three values were individuated and 27 sets of samples were realised. The surface treatment was analysed and related to the mechanical characteristics of the bonded joints performing lap-shear tests. A statistical analysis in order to find the most influential parameter completed the work.

Texture-adaptive hyperspectral video acquisition system with a spatial light modulator

NASA Astrophysics Data System (ADS)

Fang, Xiaojing; Feng, Jiao; Wang, Yongjin

2014-10-01

We present a new hybrid camera system based on spatial light modulator (SLM) to capture texture-adaptive high-resolution hyperspectral video. The hybrid camera system records a hyperspectral video with low spatial resolution using a gray camera and a high-spatial resolution video using a RGB camera. The hyperspectral video is subsampled by the SLM. The subsampled points can be adaptively selected according to the texture characteristic of the scene by combining with digital imaging analysis and computational processing. In this paper, we propose an adaptive sampling method utilizing texture segmentation and wavelet transform (WT). We also demonstrate the effectiveness of the sampled pattern on the SLM with the proposed method.

Transcriptomic analysis of apple fruit ripening and texture attributes

USDA-ARS?s Scientific Manuscript database

Molecular events regulating cultivar-specific apple fruit ripening and sensory quality are largely unknown. Such knowledge is essential for genomic-assisted apple breeding and postharvest quality management. The ripening behavior and texture attributes of two apple cultivars, ‘Pink Lady’ and ‘Honey...

Tumour heterogeneity in glioblastoma assessed by MRI texture analysis: a potential marker of survival

PubMed Central

Pérez-Beteta, Julián; Luque, Belén; Arregui, Elena; Calvo, Manuel; Borrás, José M; López, Carlos; Martino, Juan; Velasquez, Carlos; Asenjo, Beatriz; Benavides, Manuel; Herruzo, Ismael; Martínez-González, Alicia; Pérez-Romasanta, Luis; Arana, Estanislao; Pérez-García, Víctor M

2016-01-01

Objective: The main objective of this retrospective work was the study of three-dimensional (3D) heterogeneity measures of post-contrast pre-operative MR images acquired with T1 weighted sequences of patients with glioblastoma (GBM) as predictors of clinical outcome. Methods: 79 patients from 3 hospitals were included in the study. 16 3D textural heterogeneity measures were computed including run-length matrix (RLM) features (regional heterogeneity) and co-occurrence matrix (CM) features (local heterogeneity). The significance of the results was studied using Kaplan–Meier curves and Cox proportional hazards analysis. Correlation between the variables of the study was assessed using the Spearman's correlation coefficient. Results: Kaplan–Meyer survival analysis showed that 4 of the 11 RLM features and 4 of the 5 CM features considered were robust predictors of survival. The median survival differences in the most significant cases were of over 6 months. Conclusion: Heterogeneity measures computed on the post-contrast pre-operative T1 weighted MR images of patients with GBM are predictors of survival. Advances in knowledge: Texture analysis to assess tumour heterogeneity has been widely studied. However, most works develop a two-dimensional analysis, focusing only on one MRI slice to state tumour heterogeneity. The study of fully 3D heterogeneity textural features as predictors of clinical outcome is more robust and is not dependent on the selected slice of the tumour. PMID:27319577

Tumour heterogeneity in glioblastoma assessed by MRI texture analysis: a potential marker of survival.

PubMed

Molina, David; Pérez-Beteta, Julián; Luque, Belén; Arregui, Elena; Calvo, Manuel; Borrás, José M; López, Carlos; Martino, Juan; Velasquez, Carlos; Asenjo, Beatriz; Benavides, Manuel; Herruzo, Ismael; Martínez-González, Alicia; Pérez-Romasanta, Luis; Arana, Estanislao; Pérez-García, Víctor M

2016-07-04

The main objective of this retrospective work was the study of three-dimensional (3D) heterogeneity measures of post-contrast pre-operative MR images acquired with T 1 weighted sequences of patients with glioblastoma (GBM) as predictors of clinical outcome. 79 patients from 3 hospitals were included in the study. 16 3D textural heterogeneity measures were computed including run-length matrix (RLM) features (regional heterogeneity) and co-occurrence matrix (CM) features (local heterogeneity). The significance of the results was studied using Kaplan-Meier curves and Cox proportional hazards analysis. Correlation between the variables of the study was assessed using the Spearman's correlation coefficient. Kaplan-Meyer survival analysis showed that 4 of the 11 RLM features and 4 of the 5 CM features considered were robust predictors of survival. The median survival differences in the most significant cases were of over 6 months. Heterogeneity measures computed on the post-contrast pre-operative T 1 weighted MR images of patients with GBM are predictors of survival. Texture analysis to assess tumour heterogeneity has been widely studied. However, most works develop a two-dimensional analysis, focusing only on one MRI slice to state tumour heterogeneity. The study of fully 3D heterogeneity textural features as predictors of clinical outcome is more robust and is not dependent on the selected slice of the tumour.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Formation mechanisms of periodic longitudinal microstructure and texture patterns in friction stir welded magnesium AZ80

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

Hiscocks, J., E-mail: j.hiscocks@queensu.ca

Many studies of friction stir welding have shown that periodicity of metal flow around the tool pin may result in the formation of periodic differences in microstructure and texture in the weld nugget area correlated with the weld pitch. The current work investigates the periodicity of magnesium weld microtexture in the nugget region and its association with material flow using optical and electron microscopy. Two welds created in AZ80 at different processing conditions are presented in detail, one illustrating periodic longitudinal texture change, and one showing for the first time that periodic variations in texture, grain size, or composition aremore » not defining features of periodic nugget flow. While nugget texture is dominated by shear deformation, it was found here to be affected to a lesser degree by compaction of material behind the welding tool, which led to reduction in intensity of the shear texture fiber. The decreased tendency for magnesium based alloys to form periodic patterns as compared to aluminum based alloys is explained with reference to the shear textures. - Highlights: •It is shown here that periodic material flow in the nugget does not necessitate longitudinal texture patterns. •Longitudinal texture patterns are shown to be present or absent in Mg AZ80 based on processing conditions. •Texture in the nugget is mainly dictated by shear deformation, but has measurable effects from other deformation modes. •Explanation of why longitudinal texture change is frequently reported in aluminum but not magnesium alloys is provided. •A new vector visualization of material flow based on EBSD data analysis is shown.« less

Particle shape-controlled sorting and transport behaviour of mixed siliciclastic/bioclastic sediments in a mesotidal lagoon, South Africa

NASA Astrophysics Data System (ADS)

Flemming, Burghard W.

2017-08-01

This study investigates the effect of particle shape on the transport and deposition of mixed siliciclastic-bioclastic sediments in the lower mesotidal Langebaan Lagoon along the South Atlantic coast of South Africa. As the two sediment components have undergone mutual sorting for the last 7 ka, they can be expected to have reached a highest possible degree of hydraulic equivalence. A comparison of sieve and settling tube data shows that, with progressive coarsening of the size fractions, the mean diameters of individual sediment components increasingly depart from the spherical quartz standard, the experimental data demonstrating the hydraulic incompatibility of the sieve data. Overall, the spatial distribution patterns of textural parameters (mean settling diameter, sorting and skewness) of the siliciclastic and bioclastic sediment components are very similar. Bivariate plots between them reveal linear trends when averaged over small intervals. A systematic deviation is observed in sorting, the trend ranging from uniformity at poorer sorting levels to a progressively increasing lag of the bioclastic component relative to the siliciclastic one as overall sorting improves. The deviation amounts to 0.8 relative sorting units at the optimal sorting level. The small textural differences between the two components are considered to reflect the influence of particle shape, which prevents the bioclastic fraction from achieving complete textural equivalence with the siliciclastic one. This is also reflected in the inferred transport behaviour of the two shape components, the bioclastic fraction moving closer to the bed than the siliciclastic one because of the higher drag experienced by low shape factor particles. As a consequence, the bed-phase development of bioclastic sediments departs significantly from that of siliciclastic sediments. Systematic flume experiments, however, are currently still lacking.

Scanning electron microscopy investigations of laboratory-grown gas clathrate hydrates formed from melting ice, and comparison to natural hydrates

USGS Publications Warehouse

Stern, L.A.; Kirby, S.H.; Circone, S.; Durham, W.B.

2004-01-01

Scanning electron microscopy (SEM) was used to investigate grain texture and pore structure development within various compositions of pure sI and sII gas hydrates synthesized in the laboratory, as well as in natural samples retrieved from marine (Gulf of Mexico) and permafrost (NW Canada) settings. Several samples of methane hydrate were also quenched after various extents of partial reaction for assessment of mid-synthesis textural progression. All laboratory-synthesized hydrates were grown under relatively high-temperature and high-pressure conditions from rounded ice grains with geometrically simple pore shapes, yet all resulting samples displayed extensive recrystallization with complex pore geometry. Growth fronts of mesoporous methane hydrate advancing into dense ice reactant were prevalent in those samples quenched after limited reaction below and at the ice point. As temperatures transgress the ice point, grain surfaces continue to develop a discrete "rind" of hydrate, typically 5 to 30 ??m thick. The cores then commonly melt, with rind microfracturing allowing migration of the melt to adjacent grain boundaries where it also forms hydrate. As the reaction continues under progressively warmer conditions, the hydrate product anneals to form dense and relatively pore-free regions of hydrate grains, in which grain size is typically several tens of micrometers. The prevalence of hollow, spheroidal shells of hydrate, coupled with extensive redistribution of reactant and product phases throughout reaction, implies that a diffusion-controlled shrinking-core model is an inappropriate description of sustained hydrate growth from melting ice. Completion of reaction at peak synthesis conditions then produces exceptional faceting and euhedral crystal growth along exposed pore walls. Further recrystallization or regrowth can then accompany even short-term exposure of synthetic hydrates to natural ocean-floor conditions, such that the final textures may closely mimic those observed in natural samples of marine origin. Of particular note, both the mesoporous and highly faceted textures seen at different stages during synthetic hydrate growth were notably absent from all examined hydrates recovered from a natural marine-environment setting.

Mechanical and chemical effects of ion-texturing biomedical polymers

NASA Technical Reports Server (NTRS)

Weigand, A. J.; Cenkus, M. A.

1979-01-01

To determine whether sputter etching may provide substantial polymer surface texturing with insignificant changes in chemical and mechanical properties, an 8 cm beam diameter, electron bombardment, argon ion source was used to sputter etch (ion-texture process) nine biomedical polymers. The materials included silicone rubber, 32% carbon impregnated polyolefin, polyoxymethylene, polytetrafluoroethylene, ultrahigh molecular weight (UHMW) polyethylene, UHMW polyethylene with carbon fibers (10%), and several polyurethanes (bioelectric, segmented, and cross linked). Ion textured microtensile specimens of each material except UHMW polyethylene and UHMW polyethylene with 10% carbon fibers were used to determine the effect of ion texturing on tensile properties. Scanning electron microscopy was used to determine surface morphology changes, and electron spectroscopy for chemical analysis was used to analyze the near surface chemical changes that result from ion texturing. Ion energies of 500 eV with beam current densities ranging from 0.08 to 0.19 mA/sq cm were used to ion texture the various materials. Standard microtensile specimens of seven polymers were exposed to a saline environment for 24 hours prior to and during the tensile testing. The surface chemical changes resulting from sputter etching are minimal in spite of the often significant changes in the surface morphology.

Land use classification using texture information in ERTS-A MSS imagery

NASA Technical Reports Server (NTRS)

Haralick, R. M. (Principal Investigator); Shanmugam, K. S.; Bosley, R.

1973-01-01

The author has identified the following significant results. Preliminary digital analysis of ERTS-1 MSS imagery reveals that the textural features of the imagery are very useful for land use classification. A procedure for extracting the textural features of ERTS-1 imagery is presented and the results of a land use classification scheme based on the textural features are also presented. The land use classification algorithm using textural features was tested on a 5100 square mile area covered by part of an ERTS-1 MSS band 5 image over the California coastline. The image covering this area was blocked into 648 subimages of size 8.9 square miles each. Based on a color composite of the image set, a total of 7 land use categories were identified. These land use categories are: coastal forest, woodlands, annual grasslands, urban areas, large irrigated fields, small irrigated fields, and water. The automatic classifier was trained to identify the land use categories using only the textural characteristics of the subimages; 75 percent of the subimages were assigned correct identifications. Since texture and spectral features provide completely different kinds of information, a significant increase in identification accuracy will take place when both features are used together.

Texture-based segmentation and analysis of emphysema depicted on CT images

NASA Astrophysics Data System (ADS)

Tan, Jun; Zheng, Bin; Wang, Xingwei; Lederman, Dror; Pu, Jiantao; Sciurba, Frank C.; Gur, David; Leader, J. Ken

2011-03-01

In this study we present a texture-based method of emphysema segmentation depicted on CT examination consisting of two steps. Step 1, a fractal dimension based texture feature extraction is used to initially detect base regions of emphysema. A threshold is applied to the texture result image to obtain initial base regions. Step 2, the base regions are evaluated pixel-by-pixel using a method that considers the variance change incurred by adding a pixel to the base in an effort to refine the boundary of the base regions. Visual inspection revealed a reasonable segmentation of the emphysema regions. There was a strong correlation between lung function (FEV1%, FEV1/FVC, and DLCO%) and fraction of emphysema computed using the texture based method, which were -0.433, -.629, and -0.527, respectively. The texture-based method produced more homogeneous emphysematous regions compared to simple thresholding, especially for large bulla, which can appear as speckled regions in the threshold approach. In the texture-based method, single isolated pixels may be considered as emphysema only if neighboring pixels meet certain criteria, which support the idea that single isolated pixels may not be sufficient evidence that emphysema is present. One of the strength of our complex texture-based approach to emphysema segmentation is that it goes beyond existing approaches that typically extract a single or groups texture features and individually analyze the features. We focus on first identifying potential regions of emphysema and then refining the boundary of the detected regions based on texture patterns.

The unsteady end to a powerful Plinian eruption: insights from a Vulcanian block apron from the 1912 eruption of Novarupta, Alaska

NASA Astrophysics Data System (ADS)

Isgett, S. J.; Houghton, B. F.; Burgisser, A.; Arbaret, L.

2016-12-01

Current models propose a static conduit architecture prior to Vulcanian eruptions where a dense, outgassed dome/plug overlies an orderly, texturally horizontally layered conduit. Blocks from a Vulcanian phase (Episode IV) during the 1912 eruption of Novarupta provide special insight to the state of the magma within a complex shallow conduit prior to fragmentation. Extreme conduit heterogeneity is seen in a diverse range of dacitic block types, including pumiceous, dense, flow-banded, and variably welded breccia clasts, all with a range of surface-breadcrusting. Diverse 2D and 3D textures suggest a variety of degassing states, with ranges of vesicle textures (e.g. bubble number, shape, and size) in each of the block types. The nonbreadcrusted pumice exhibit textures similar to preceding Plinian phases, reflecting bubble nucleation, growth, and coalescence followed by fragmentation. Breadcrusted rind and dense dacite textures are the result of bubble collapse with the dense dacites progressing furthest along the outgassing pathway. Residual water contents within the quenched glass are all less than 0.5 wt% and indicate that the melt came from the upper 100 m of the conduit. There is no correlation between water content and vesicularity. Overall, the evidence indicates 1) the mingling of variably degassed and outgassed melts in varying states of chemical disequilibrium over a narrow depth range close to the surface and 2) fragmentation was probably driven by the melt forming the non-breadcrusted pumices which we consider was probably newly arrived in the shallow conduit at the time of fragmentation. We therefore propose a revised, dynamic model applicable to Vulcanian explosions in the context of downscaling Plinian eruptions that involves vigorous mingling of melts that are all actively degassing and outgassing to varying degrees within the shallow conduit.

Analyzing the texture changes in the quantitative phase maps of adipocytes

NASA Astrophysics Data System (ADS)

Roitshtain, Darina; Sharabani-Yosef, Orna; Gefen, Amit; Shaked, Natan T.

2016-03-01

We present a new analysis tool for studying texture changes in the quantitative phase maps of live cells acquired by wide-field interferometry. The sensitivity of wide-field interferometry systems to small changes in refractive index enables visualizing cells and inner cell organelles without the using fluorescent dyes or other cell-invasive approaches, which may affect the measurement and require external labeling. Our label-free texture-analysis tool is based directly on the optical path delay profile of the sample and does not necessitate decoupling refractive index and thickness in the cell quantitative phase profile; thus, relevant parameters can be calculated using a single-frame acquisition. Our experimental system includes low-coherence wide-field interferometer, combined with simultaneous florescence microscopy system for validation. We used this system and analysis tool for studying lipid droplets formation in adipocytes. The latter demonstration is relevant for various cellular functions such as lipid metabolism, protein storage and degradation to viral replication. These processes are functionally linked to several physiological and pathological conditions, including obesity and metabolic diseases. Quantification of these biological phenomena based on the texture changes in the cell phase map has a potential as a new cellular diagnosis tool.

Texture analysis applied to second harmonic generation image data for ovarian cancer classification

NASA Astrophysics Data System (ADS)

Wen, Bruce L.; Brewer, Molly A.; Nadiarnykh, Oleg; Hocker, James; Singh, Vikas; Mackie, Thomas R.; Campagnola, Paul J.

2014-09-01

Remodeling of the extracellular matrix has been implicated in ovarian cancer. To quantitate the remodeling, we implement a form of texture analysis to delineate the collagen fibrillar morphology observed in second harmonic generation microscopy images of human normal and high grade malignant ovarian tissues. In the learning stage, a dictionary of "textons"-frequently occurring texture features that are identified by measuring the image response to a filter bank of various shapes, sizes, and orientations-is created. By calculating a representative model based on the texton distribution for each tissue type using a training set of respective second harmonic generation images, we then perform classification between images of normal and high grade malignant ovarian tissues. By optimizing the number of textons and nearest neighbors, we achieved classification accuracy up to 97% based on the area under receiver operating characteristic curves (true positives versus false positives). The local analysis algorithm is a more general method to probe rapidly changing fibrillar morphologies than global analyses such as FFT. It is also more versatile than other texture approaches as the filter bank can be highly tailored to specific applications (e.g., different disease states) by creating customized libraries based on common image features.

3D texture analysis for classification of second harmonic generation images of human ovarian cancer

NASA Astrophysics Data System (ADS)

Wen, Bruce; Campbell, Kirby R.; Tilbury, Karissa; Nadiarnykh, Oleg; Brewer, Molly A.; Patankar, Manish; Singh, Vikas; Eliceiri, Kevin. W.; Campagnola, Paul J.

2016-10-01

Remodeling of the collagen architecture in the extracellular matrix (ECM) has been implicated in ovarian cancer. To quantify these alterations we implemented a form of 3D texture analysis to delineate the fibrillar morphology observed in 3D Second Harmonic Generation (SHG) microscopy image data of normal (1) and high risk (2) ovarian stroma, benign ovarian tumors (3), low grade (4) and high grade (5) serous tumors, and endometrioid tumors (6). We developed a tailored set of 3D filters which extract textural features in the 3D image sets to build (or learn) statistical models of each tissue class. By applying k-nearest neighbor classification using these learned models, we achieved 83-91% accuracies for the six classes. The 3D method outperformed the analogous 2D classification on the same tissues, where we suggest this is due the increased information content. This classification based on ECM structural changes will complement conventional classification based on genetic profiles and can serve as an additional biomarker. Moreover, the texture analysis algorithm is quite general, as it does not rely on single morphological metrics such as fiber alignment, length, and width but their combined convolution with a customizable basis set.

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

PubMed

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

2017-11-03

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

Cellular automata rule characterization and classification using texture descriptors

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Modelling Nonlinear Dynamic Textures using Hybrid DWT-DCT and Kernel PCA with GPU

NASA Astrophysics Data System (ADS)

Ghadekar, Premanand Pralhad; Chopade, Nilkanth Bhikaji

2016-12-01

Most of the real-world dynamic textures are nonlinear, non-stationary, and irregular. Nonlinear motion also has some repetition of motion, but it exhibits high variation, stochasticity, and randomness. Hybrid DWT-DCT and Kernel Principal Component Analysis (KPCA) with YCbCr/YIQ colour coding using the Dynamic Texture Unit (DTU) approach is proposed to model a nonlinear dynamic texture, which provides better results than state-of-art methods in terms of PSNR, compression ratio, model coefficients, and model size. Dynamic texture is decomposed into DTUs as they help to extract temporal self-similarity. Hybrid DWT-DCT is used to extract spatial redundancy. YCbCr/YIQ colour encoding is performed to capture chromatic correlation. KPCA is applied to capture nonlinear motion. Further, the proposed algorithm is implemented on Graphics Processing Unit (GPU), which comprise of hundreds of small processors to decrease time complexity and to achieve parallelism.

Structural, textural and sensory impact of sodium reduction on long fermented pizza.

PubMed

Bernklau, Isabelle; Neußer, Christian; Moroni, Alice V; Gysler, Christof; Spagnolello, Alessandro; Chung, Wookyung; Jekle, Mario; Becker, Thomas

2017-11-01

The aim of this study was to elucidate the microstructural, textural, and sensory impact of sodium reduction and its partial replacement by potassium chloride in pizza dough and crusts prepared by a traditional long fermentation process. For the first time, macrostructural changes in texture were elucidated and quantified by a novel protein network analysis. The fermentation process exerted a strengthening effect in the doughs, allowing to reduce sodium up to 25% without any negative impact on texture. Sodium reduction by 15% did not cause any significant textural changes in pizza crusts and partial replacement by KCl resulted in a strengthened dough and firmer pizza crust. The use of toppings masked the effect of lowering the sodium content, allowing to increase the reduction level from 15% to 35%. A reduction of NaCl by 25% with an addition of KCl achieved high acceptance in the sensory evaluation. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

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

PubMed Central

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

2018-01-01

Surface texture (ST) has been confirmed as an effective and economical surface treatment technique that can be applied to a great range of materials and presents growing interests in various engineering fields. Ti6Al4V which is the most frequently and successfully used titanium alloy has long been restricted in tribological-related operations due to the shortcomings of low surface hardness, high friction coefficient, and poor abrasive wear resistance. Ti6Al4V has benefited from surface texture-based surface treatments over the last decade. This review begins with a brief introduction, analysis approaches, and processing methods of surface texture. The specific applications of the surface texture-based surface treatments for improving surface performance of Ti6Al4V are thoroughly reviewed from the point of view of tribology and biology. PMID:29587358

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

PubMed

Mamat, Hasmadi; Hill, Sandra E

2014-09-01

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

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

NASA Technical Reports Server (NTRS)

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

1998-01-01

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

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

PubMed

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

2010-01-01

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

Analysis of crystallographic preferred orientations of experimentally deformed Black Hills Quartzite

NASA Astrophysics Data System (ADS)

Kilian, Rüdiger; Heilbronner, Renée

2017-10-01

The crystallographic preferred orientations (textures) of three samples of Black Hills Quartzite (BHQ) deformed experimentally in the dislocation creep regimes 1, 2 and 3 (according to Hirth and Tullis, 1992) have been analyzed using electron backscatter diffraction (EBSD). All samples were deformed to relatively high strain at temperatures of 850 to 915 °C and are almost completely dynamically recrystallized. A texture transition from peripheral [c] axes in regime 1 to a central [c] maximum in regime 3 is observed. Separate pole figures are calculated for different grain sizes, aspect ratios and long-axis trends of grains, and high and low levels of intragranular deformation intensity as measured by the mean grain kernel average misorientation (gKAM). Misorientation relations are analyzed for grains of different texture components (named Y, B, R and σ grains, with reference to previously published prism, basal, rhomb and σ1 grains). Results show that regimes 1 and 3 correspond to clear end-member textures, with regime 2 being transitional. Texture strength and the development of a central [c]-axis maximum from a girdle distribution depend on deformation intensity at the grain scale and on the contribution of dislocation creep, which increases towards regime 3. Adding to this calculations of resolved shear stresses and misorientation analysis, it becomes clear that the peripheral [c]-axis maximum in regime 1 is not due to deformation by basal a slip. Instead, we interpret the texture transition as a result of different texture forming processes, one being more efficient at high stresses (nucleation or growth of grains with peripheral [c] axes), the other depending on strain (dislocation glide involving prism and rhomb a slip systems), and not as a result of temperature-dependent activity of different slip systems.

Uric acid versus non-uric acid urinary stones: differentiation with single energy CT texture analysis.

PubMed

Zhang, G-M-Y; Sun, H; Shi, B; Xu, M; Xue, H-D; Jin, Z-Y

2018-05-21

To evaluate the accuracy of computed tomography (CT) texture analysis (TA) to differentiate uric acid (UA) stones from non-UA stones on unenhanced CT in patients with urinary calculi with ex vivo Fourier transform infrared spectroscopy (FTIR) as the reference standard. Fourteen patients with 18 UA stones and 31 patients with 32 non-UA stones were included. All the patients had preoperative CT evaluation and subsequent surgical removal of the stones. CTTA was performed on CT images using commercially available research software. Each texture feature was evaluated using the non-parametric Mann-Whitney test. Receiver operating characteristic (ROC) curves were created and the area under the ROC curve (AUC) was calculated for texture parameters that were significantly different. The features were used to train support vector machine (SVM) classifiers. Diagnostic accuracy was evaluated. Compared to non-UA stones, UA stones had significantly lower mean, standard deviation and mean of positive pixels but higher kurtosis (p<0.001) on both unfiltered and filtered texture scales. There were no significant differences in entropy or skewness between UA and non-UA stones. The average SVM accuracy of texture features for differentiating UA from non-UA stones ranged from 88% to 92% (after 10-fold cross validation). A model incorporating standard deviation, skewness, and kurtosis from unfiltered texture scale images resulted in an AUC of 0.965±00.029 with a sensitivity of 94.4% and specificity of 93.7%. CTTA can be used to accurately differentiate UA stones from non-UA stones in vivo using unenhanced CT images. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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

PubMed

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

2008-09-01

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

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

DOE PAGES

Steiner, Matthew A.; Klein, Robert W.; Calhoun, Christopher A.; ...

2017-01-01

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

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

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

Steiner, Matthew A.; Klein, Robert W.; Calhoun, Christopher A.

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

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

PubMed

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

2017-01-01

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

CT texture features of liver parenchyma for predicting development of metastatic disease and overall survival in patients with colorectal cancer.

PubMed

Lee, Scott J; Zea, Ryan; Kim, David H; Lubner, Meghan G; Deming, Dustin A; Pickhardt, Perry J

2018-04-01

To determine if identifiable hepatic textural features are present at abdominal CT in patients with colorectal cancer (CRC) prior to the development of CT-detectable hepatic metastases. Four filtration-histogram texture features (standard deviation, skewness, entropy and kurtosis) were extracted from the liver parenchyma on portal venous phase CT images at staging and post-treatment surveillance. Surveillance scans corresponded to the last scan prior to the development of CT-detectable CRC liver metastases in 29 patients (median time interval, 6 months), and these were compared with interval-matched surveillance scans in 60 CRC patients who did not develop liver metastases. Predictive models of liver metastasis-free survival and overall survival were built using regularised Cox proportional hazards regression. Texture features did not significantly differ between cases and controls. For Cox models using all features as predictors, all coefficients were shrunk to zero, suggesting no association between any CT texture features and outcomes. Prognostic indices derived from entropy features at surveillance CT incorrectly classified patients into risk groups for future liver metastases (p < 0.001). On surveillance CT scans immediately prior to the development of CRC liver metastases, we found no evidence suggesting that changes in identifiable hepatic texture features were predictive of their development. • No correlation between liver texture features and metastasis-free survival was observed. • Liver texture features incorrectly classified patients into risk groups for liver metastases. • Standardised texture analysis workflows need to be developed to improve research reproducibility.

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

SU-E-J-256: Predicting Metastasis-Free Survival of Rectal Cancer Patients Treated with Neoadjuvant Chemo-Radiotherapy by Data-Mining of CT Texture Features of Primary Lesions

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

Zhong, H; Wang, J; Shen, L

Purpose: The purpose of this study is to investigate the relationship between computed tomographic (CT) texture features of primary lesions and metastasis-free survival for rectal cancer patients; and to develop a datamining prediction model using texture features. Methods: A total of 220 rectal cancer patients treated with neoadjuvant chemo-radiotherapy (CRT) were enrolled in this study. All patients underwent CT scans before CRT. The primary lesions on the CT images were delineated by two experienced oncologists. The CT images were filtered by Laplacian of Gaussian (LoG) filters with different filter values (1.0–2.5: from fine to coarse). Both filtered and unfiltered imagesmore » were analyzed using Gray-level Co-occurrence Matrix (GLCM) texture analysis with different directions (transversal, sagittal, and coronal). Totally, 270 texture features with different species, directions and filter values were extracted. Texture features were examined with Student’s t-test for selecting predictive features. Principal Component Analysis (PCA) was performed upon the selected features to reduce the feature collinearity. Artificial neural network (ANN) and logistic regression were applied to establish metastasis prediction models. Results: Forty-six of 220 patients developed metastasis with a follow-up time of more than 2 years. Sixtyseven texture features were significantly different in t-test (p<0.05) between patients with and without metastasis, and 12 of them were extremely significant (p<0.001). The Area-under-the-curve (AUC) of ANN was 0.72, and the concordance index (CI) of logistic regression was 0.71. The predictability of ANN was slightly better than logistic regression. Conclusion: CT texture features of primary lesions are related to metastasisfree survival of rectal cancer patients. Both ANN and logistic regression based models can be developed for prediction.« less

Breast-implant texturing associated with delamination of capsular layers: A histological analysis of the double capsule phenomenon.

PubMed

Efanov, J I; Giot, J P; Fernandez, J; Danino, M A

2017-06-01

Macro-texturing of breast implants was developed with the double goal of improving implant stabilization within the breast cavity and decreasing the rate of capsular contractures. However, recent evidence suggests that double capsular formation, a potentially worrisome phenomenon associated with late seromas and biofilms, occurs with preponderance in macro-textured implants. Our objective was to analyze histologically different regions of double capsules to determine if they are more prone to mechanical movements. A prospective analysis including patients undergoing second-stage expander to definitive breast-implant reconstruction post-mastectomy was conducted after intraoperative identification of the double capsule phenomenon. Two samples were collected from each capsules around the implant, located centrally and laterally. The specimens were sent for histological analysis by the institution's pathologist. In total, 10 patients were identified intraoperatively with partial double capsule phenomenon. Among samples retrieved from the lateral aspect of the breast implant, all were associated with delamination and fractures in the collagen matrix of the double capsules. This phenomenon was not observed in any sample from the dome of the breast. Breast-implant macro-texturing plays an important role on delamination of capsules on lateral portions of the breast, which may have an etiologic role in double capsule formation. Manufacturing implants with macro-texturing on one side and smooth surface on the other could diminish mechanical shear forces responsible for these findings. Copyright © 2017 Elsevier Masson SAS. All rights reserved.

Are pretreatment 18F-FDG PET tumor textural features in non-small cell lung cancer associated with response and survival after chemoradiotherapy?

PubMed

Cook, Gary J R; Yip, Connie; Siddique, Muhammad; Goh, Vicky; Chicklore, Sugama; Roy, Arunabha; Marsden, Paul; Ahmad, Shahreen; Landau, David

2013-01-01

There is evidence in some solid tumors that textural features of tumoral uptake in (18)F-FDG PET images are associated with response to chemoradiotherapy and survival. We have investigated whether a similar relationship exists in non-small cell lung cancer (NSCLC). Fifty-three patients (mean age, 65.8 y; 31 men, 22 women) with NSCLC treated with chemoradiotherapy underwent pretreatment (18)F-FDG PET/CT scans. Response was assessed by CT Response Evaluation Criteria in Solid Tumors (RECIST) at 12 wk. Overall survival (OS), progression-free survival (PFS), and local PFS (LPFS) were recorded. Primary tumor texture was measured by the parameters coarseness, contrast, busyness, and complexity. The following parameters were also derived from the PET data: primary tumor standardized uptake values (SUVs) (mean SUV, maximum SUV, and peak SUV), metabolic tumor volume, and total lesion glycolysis. Compared with nonresponders, RECIST responders showed lower coarseness (mean, 0.012 vs. 0.027; P = 0.004) and higher contrast (mean, 0.11 vs. 0.044; P = 0.002) and busyness (mean, 0.76 vs. 0.37; P = 0.027). Neither complexity nor any of the SUV parameters predicted RECIST response. By Kaplan-Meier analysis, OS, PFS, and LPFS were lower in patients with high primary tumor coarseness (median, 21.1 mo vs. not reached, P = 0.003; 12.6 vs. 25.8 mo, P = 0.002; and 12.9 vs. 20.5 mo, P = 0.016, respectively). Tumor coarseness was an independent predictor of OS on multivariable analysis. Contrast and busyness did not show significant associations with OS (P = 0.075 and 0.059, respectively), but PFS and LPFS were longer in patients with high levels of each (for contrast: median of 20.5 vs. 12.6 mo, P = 0.015, and median not reached vs. 24 mo, P = 0.02; and for busyness: median of 20.5 vs. 12.6 mo, P = 0.01, and median not reached vs. 24 mo, P = 0.006). Neither complexity nor any of the SUV parameters showed significant associations with the survival parameters. In NSCLC, baseline (18)F-FDG PET scan uptake showing abnormal texture as measured by coarseness, contrast, and busyness is associated with nonresponse to chemoradiotherapy by RECIST and with poorer prognosis. Measurement of tumor metabolic heterogeneity with these parameters may provide indices that can be used to stratify patients in clinical trials for lung cancer chemoradiotherapy.

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.

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

Advanced Technology for Portable Personal Visualization.

DTIC Science & Technology

1992-06-01

interactive radiosity . 6 Advanced Technology for Portable Personal Visualization Progress Report January-June 1992 9 2.5 Virtual-Environment Ultrasound...the system, with support for textures, model partitioning, more complex radiosity emitters, and the replacement of model parts with objects from our...model libraries. "* Add real-time, interactive radiosity to the display program on Pixel-Planes 5. "* Move the real-time model mesh-generation to the

Structural Integrity of Water Reactor Pressure Boundary Components.

DTIC Science & Technology

1979-12-31

fatigue crack growth is also on-going. Substantial progress in all three of the areas - fatigue data generation, fractography and micromechanism... Fractographie Examinations During the past year, there have been several fractographic studies and fractographically-related research efforts which have been...in the T-L orientation were characterized by a m icrostructural texture running parallel to the macroscopic crack propagation direction (Fig. 31). This

Status of silicon solar cell technology

NASA Technical Reports Server (NTRS)

Brandhorst, H. W., Jr.

1976-01-01

Major progress in solar cell technology leading to increased efficiency has occurred since 1970. Technical approaches leading to this increased output include surface texturing, improved antireflection coatings, reduced grid pattern area coverage, shallow junctions and back surface fields. The status of these developments and their incorporation into cell production is discussed. Future research and technology trends leading to further efficiency increases and substantial cost reductions are described.

A radiomics model from joint FDG-PET and MRI texture features for the prediction of lung metastases in soft-tissue sarcomas of the extremities

NASA Astrophysics Data System (ADS)

Vallières, M.; Freeman, C. R.; Skamene, S. R.; El Naqa, I.

2015-07-01

This study aims at developing a joint FDG-PET and MRI texture-based model for the early evaluation of lung metastasis risk in soft-tissue sarcomas (STSs). We investigate if the creation of new composite textures from the combination of FDG-PET and MR imaging information could better identify aggressive tumours. Towards this goal, a cohort of 51 patients with histologically proven STSs of the extremities was retrospectively evaluated. All patients had pre-treatment FDG-PET and MRI scans comprised of T1-weighted and T2-weighted fat-suppression sequences (T2FS). Nine non-texture features (SUV metrics and shape features) and forty-one texture features were extracted from the tumour region of separate (FDG-PET, T1 and T2FS) and fused (FDG-PET/T1 and FDG-PET/T2FS) scans. Volume fusion of the FDG-PET and MRI scans was implemented using the wavelet transform. The influence of six different extraction parameters on the predictive value of textures was investigated. The incorporation of features into multivariable models was performed using logistic regression. The multivariable modeling strategy involved imbalance-adjusted bootstrap resampling in the following four steps leading to final prediction model construction: (1) feature set reduction; (2) feature selection; (3) prediction performance estimation; and (4) computation of model coefficients. Univariate analysis showed that the isotropic voxel size at which texture features were extracted had the most impact on predictive value. In multivariable analysis, texture features extracted from fused scans significantly outperformed those from separate scans in terms of lung metastases prediction estimates. The best performance was obtained using a combination of four texture features extracted from FDG-PET/T1 and FDG-PET/T2FS scans. This model reached an area under the receiver-operating characteristic curve of 0.984 ± 0.002, a sensitivity of 0.955 ± 0.006, and a specificity of 0.926 ± 0.004 in bootstrapping evaluations. Ultimately, lung metastasis risk assessment at diagnosis of STSs could improve patient outcomes by allowing better treatment adaptation.

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

PubMed

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

2017-10-01

Starch characteristics significantly influence the functionality and end-use quality of cereals and pseudo-cereals. This study examined the composition and properties of starch from 11 pure varieties and 2 commercial samples of quinoa in relationship to the texture of cooked quinoa. Nearly all starch properties and characteristics differed among these samples. Results showed that total starch content of seeds ranged from 53.2 to 75.1 g/100 g apparent amylose content ranged from 2.7% to 16.9%; total amylose ranged from 4.7% to 17.3%; and the degree of amylose-lipid complex ranged from 3.4% to 43.3%. Amylose leaching ranged from 31 mg/100 g starch in "Japanese Strain" to 862 mg/100 g starch in "49ALC." "Japanese Strain" starch also exhibited the highest water solubility (4.5%) and the lowest swelling power (17). α-Amylase activity in "1ESP," "Col.#6197," "Japanese Strain," "QQ63," "Yellow Commercial," and "Red Commercial" (0.03 to 0.09 CU) were significantly lower than the levels of the other quinoa samples (0.20 to 1.16 CU). Additionally, gel texture, thermal properties, and pasting properties of quinoa starches were investigated. Lastly, correlation analysis showed that the quinoa samples with higher amylose content tended to yield harder, stickier, more cohesive, more gummy, and more chewy texture after cooking. A higher degree of amylose-lipid complex and amylose leaching were associated with softer and less chewy cooked quinoa TPA texture. Higher starch enthalpy correlated with firmer, more adhesive, more cohesive, and chewier texture. In sum, starch plays a significant role in the texture of cooked quinoa. The research determined starch characteristics among a diverse set of pure quinoa varieties and commercial samples, and identified the relationships between starch properties and cooked quinoa texture. The results can help breeders and food manufacturers to understand better the relationships among quinoa starch characteristics, cooked quinoa texture, and the best use of different cultivars. © 2017 Institute of Food Technologists®.

Array automated assembly, phase 2

NASA Technical Reports Server (NTRS)

Taylor, W. E.

1978-01-01

An analysis was made of cost tradeoffs for shaping modified square wafers from cylindrical crystals. Tests were conducted of the effectiveness of texture etching for removal of surface damage on sawed wafers. A single step texturing etch appeared adequate for removal of surface damage on wafers cut with multiple blade reciprocating slurry saws.

Fractal lacunarity of trabecular bone and magnetic resonance imaging: New perspectives for osteoporotic fracture risk assessment

PubMed Central

Zaia, Annamaria

2015-01-01

Osteoporosis represents one major health condition for our growing elderly population. It accounts for severe morbidity and increased mortality in postmenopausal women and it is becoming an emerging health concern even in aging men. Screening of the population at risk for bone degeneration and treatment assessment of osteoporotic patients to prevent bone fragility fractures represent useful tools to improve quality of life in the elderly and to lighten the related socio-economic impact. Bone mineral density (BMD) estimate by means of dual-energy X-ray absorptiometry is normally used in clinical practice for osteoporosis diagnosis. Nevertheless, BMD alone does not represent a good predictor of fracture risk. From a clinical point of view, bone microarchitecture seems to be an intriguing aspect to characterize bone alteration patterns in aging and pathology. The widening into clinical practice of medical imaging techniques and the impressive advances in information technologies together with enhanced capacity of power calculation have promoted proliferation of new methods to assess changes of trabecular bone architecture (TBA) during aging and osteoporosis. Magnetic resonance imaging (MRI) has recently arisen as a useful tool to measure bone structure in vivo. In particular, high-resolution MRI techniques have introduced new perspectives for TBA characterization by non-invasive non-ionizing methods. However, texture analysis methods have not found favor with clinicians as they produce quite a few parameters whose interpretation is difficult. The introduction in biomedical field of paradigms, such as theory of complexity, chaos, and fractals, suggests new approaches and provides innovative tools to develop computerized methods that, by producing a limited number of parameters sensitive to pathology onset and progression, would speed up their application into clinical practice. Complexity of living beings and fractality of several physio-anatomic structures suggest fractal analysis as a promising approach to quantify morpho-functional changes in both aging and pathology. In this particular context, fractal lacunarity seems to be the proper tool to characterize TBA texture as it is able to describe both discontinuity of bone network and sizes of bone marrow spaces, whose changes are an index of bone fracture risk. In this paper, an original method of MRI texture analysis, based on TBA fractal lacunarity is described and discussed in the light of new perspectives for early diagnosis of osteoporotic fractures. PMID:25793162

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.

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

NASA Astrophysics Data System (ADS)

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

2012-09-01

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

Activity of pyramidal I and II < c + a > slip in Mg alloys as revealed by texture development

NASA Astrophysics Data System (ADS)

Zecevic, Miroslav; Beyerlein, Irene J.; Knezevic, Marko

2018-02-01

Due to the geometry of the hexagonal close-packed (HCP) lattice, there are two types of pyramidal slip modes: { 10 1 bar 1 } 〈 11 2 bar 3 bar 〉 or type I and { 1 bar 1 bar 22 } 〈 11 2 bar 3 〉 or type II in HCP crystalline materials. Here we use crystal plasticity to examine the importance of crystallographic slip by pyramidal type I and type II on texture evolution. The study is applied to an Mg-4%Li alloy. An elastic-plastic polycrystal model is employed to elucidate the reorientation tendencies of these two slip modes in rolling of a textured polycrystal. Comparisons with experimental texture measurements indicate that both pyramidal I and II type slip were active during rolling deformation, with pyramidal I being the dominant mode. A single-slip-mode analysis is used to identify the orientations that prefer pyramidal I vs. II type slip when acting alone in a crystal. The analysis applies not only to Mg-4%Li, but identifies the key texture components in HCP crystals that would help distinguish the activity of pyramidal I from pyramidal II slip in rolling deformation.

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.

Face Aging Effect Simulation Using Hidden Factor Analysis Joint Sparse Representation.

PubMed

Yang, Hongyu; Huang, Di; Wang, Yunhong; Wang, Heng; Tang, Yuanyan

2016-06-01

Face aging simulation has received rising investigations nowadays, whereas it still remains a challenge to generate convincing and natural age-progressed face images. In this paper, we present a novel approach to such an issue using hidden factor analysis joint sparse representation. In contrast to the majority of tasks in the literature that integrally handle the facial texture, the proposed aging approach separately models the person-specific facial properties that tend to be stable in a relatively long period and the age-specific clues that gradually change over time. It then transforms the age component to a target age group via sparse reconstruction, yielding aging effects, which is finally combined with the identity component to achieve the aged face. Experiments are carried out on three face aging databases, and the results achieved clearly demonstrate the effectiveness and robustness of the proposed method in rendering a face with aging effects. In addition, a series of evaluations prove its validity with respect to identity preservation and aging effect generation.

Palm vein recognition based on directional empirical mode decomposition

NASA Astrophysics Data System (ADS)

Lee, Jen-Chun; Chang, Chien-Ping; Chen, Wei-Kuei

2014-04-01

Directional empirical mode decomposition (DEMD) has recently been proposed to make empirical mode decomposition suitable for the processing of texture analysis. Using DEMD, samples are decomposed into a series of images, referred to as two-dimensional intrinsic mode functions (2-D IMFs), from finer to large scale. A DEMD-based 2 linear discriminant analysis (LDA) for palm vein recognition is proposed. The proposed method progresses through three steps: (i) a set of 2-D IMF features of various scale and orientation are extracted using DEMD, (ii) the 2LDA method is then applied to reduce the dimensionality of the feature space in both the row and column directions, and (iii) the nearest neighbor classifier is used for classification. We also propose two strategies for using the set of 2-D IMF features: ensemble DEMD vein representation (EDVR) and multichannel DEMD vein representation (MDVR). In experiments using palm vein databases, the proposed MDVR-based 2LDA method achieved recognition accuracy of 99.73%, thereby demonstrating its feasibility for palm vein recognition.

FAST TRACK COMMUNICATION: Directional annealing-induced texture in melt-spun (Sm12Co88)99Nb1 alloy

NASA Astrophysics Data System (ADS)

Jayaraman, T. V.; Rogge, P.; Shield, J. E.

2010-07-01

Developing texture in nanocrystalline permanent magnet alloys is of significant importance. Directional annealing is shown to produce texture in the permanent magnet alloy (Sm12Co88)99Nb1. Melt spinning produced isotropic grain structures of the hard magnetic metastable SmCo7 phase, with grain sizes of ~300 nm. Conventional annealing of melt-spun (Sm12Co88)99Nb1 alloy produced Sm2Co17 phase with random crystallographic orientation. Directional annealing of melt-spun (Sm12Co88)99Nb1 alloy, with appropriate combinations of annealing temperature and translational velocity, produced Sm2Co17 phase with (0 0 0 6) in-plane texture, as determined by x-ray diffraction analysis and magnetic measurements. The magnetization results show out-of-plane remanence higher than the in-plane remanence resulting in the degree of 'magnetic' texture in the order of 25-40%. Coercivity values above 2 kOe were maintained. The texture development via directional annealing while minimizing exposure to elevated temperatures provides a new route to anisotropic high-energy permanent magnets.

Equal channel angular extrusion for bulk processing of Fe–Co–2V soft magnetic alloys, part II: Texture analysis and magnetic properties

DOE PAGES

Kustas, Andrew B.; Michael, Joseph R.; Susan, Don F.; ...

2018-06-04

In Part I, equal channel angular extrusion (ECAE) was demonstrated as a novel, simple-shear deformation process for producing bulk forms of the low ductility Fe–Co–2V (Hiperco 50A®) soft ferromagnetic alloy with refined grain sizes. Microstructures and mechanical properties were discussed. In this Part II contribution, the crystallographic textures and quasi-static magnetic properties of ECAE-processed Hiperco were characterized. The textures were of a simple-shear character defined by partial {110} and <111> fibers inclined relative to the extrusion direction, in agreement with the expectations for simple-shear deformation textures of BCC metals. These textures were observed throughout all processing conditions and only slightlymore » reduced in intensity by subsequent recrystallization heat treatments. Characterization of the magnetic properties revealed a lower coercivity and higher permeability for ECAE-processed Hiperco specimens relative to the conventionally processed and annealed Hiperco bar. In conclusion, the effects of the resultant microstructure and texture on the coercivity and permeability magnetic properties are discussed.« less

Equal channel angular extrusion for bulk processing of Fe–Co–2V soft magnetic alloys, part II: Texture analysis and magnetic properties

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

Kustas, Andrew B.; Michael, Joseph R.; Susan, Don F.

In Part I, equal channel angular extrusion (ECAE) was demonstrated as a novel, simple-shear deformation process for producing bulk forms of the low ductility Fe–Co–2V (Hiperco 50A®) soft ferromagnetic alloy with refined grain sizes. Microstructures and mechanical properties were discussed. In this Part II contribution, the crystallographic textures and quasi-static magnetic properties of ECAE-processed Hiperco were characterized. The textures were of a simple-shear character defined by partial {110} and <111> fibers inclined relative to the extrusion direction, in agreement with the expectations for simple-shear deformation textures of BCC metals. These textures were observed throughout all processing conditions and only slightlymore » reduced in intensity by subsequent recrystallization heat treatments. Characterization of the magnetic properties revealed a lower coercivity and higher permeability for ECAE-processed Hiperco specimens relative to the conventionally processed and annealed Hiperco bar. In conclusion, the effects of the resultant microstructure and texture on the coercivity and permeability magnetic properties are discussed.« less

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.

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.

Quantification of Reflection Patterns in Ground-Penetrating Radar Data

NASA Astrophysics Data System (ADS)

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

2005-12-01

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

Texture for script identification.

PubMed

Busch, Andrew; Boles, Wageeh W; Sridharan, Sridha

2005-11-01

The problem of determining the script and language of a document image has a number of important applications in the field of document analysis, such as indexing and sorting of large collections of such images, or as a precursor to optical character recognition (OCR). In this paper, we investigate the use of texture as a tool for determining the script of a document image, based on the observation that text has a distinct visual texture. An experimental evaluation of a number of commonly used texture features is conducted on a newly created script database, providing a qualitative measure of which features are most appropriate for this task. Strategies for improving classification results in situations with limited training data and multiple font types are also proposed.

Ultrastructure of selected struvite-containing urinary calculi from dogs.

PubMed

Domingo-Neumann, R A; Ruby, A L; Ling, G V; Schiffman, P S; Johnson, D L

1996-09-01

To elucidate the ultrastructural details of struvite-containing urinary calculi from dogs. 38 specimens were selected from a collection of approximately 13,000 canine urinary calculi: 18 of these were composed entirely of struvite, and 20 consisted of struvite and calcium phosphate (apatite). Qualitative and quantitative analyses of specimens included use of plain and polarized light microscopy, x-ray diffractometry, scanning electron microscopy with backscattered electron imagery, x-ray fluorescence scans, and electron microprobe analysis. 4 textural types were recognized among struvite calculi, and 4 textural types of struvite-apatite calculi were described. Evidences of calculus dissolution were described from 4 calculi studied. The presence of small, well interconnected primary pores in struvite-containing urinary calculi from dogs appears to be a significant factor in determining the possible interaction of calculi with changes in the urine composition. The progress of dissolution from the calculus surface to the calculus interior appears to be largely affected by the primary porosity originally present between crystals forming the calculus framework. Apatite was observed to be more resistant to dissolution than struvite. The prevalence of fine concentric laminations having low porosity, and the common occurrence of apatite among struvite-containing urinary calculi from dogs may be 2 reasons why the efficacy of dietary and medicinal manipulations in dissolving urinary calculi is greater among cats than it is among dogs.

Estimation of Articular Cartilage Surface Roughness Using Gray-Level Co-Occurrence Matrix of Laser Speckle Image.

PubMed

Youssef, Doaa; El-Ghandoor, Hatem; Kandel, Hamed; El-Azab, Jala; Hassab-Elnaby, Salah

2017-06-28

The application of He-Ne laser technologies for description of articular cartilage degeneration, one of the most common diseases worldwide, is an innovative usage of these technologies used primarily in material engineering. Plain radiography and magnetic resonance imaging are insufficient to allow the early assessment of the disease. As surface roughness of articular cartilage is an important indicator of articular cartilage degeneration progress, a safe and noncontact technique based on laser speckle image to estimate the surface roughness is provided. This speckle image from the articular cartilage surface, when illuminated by laser beam, gives very important information about the physical properties of the surface. An experimental setup using a low power He-Ne laser and a high-resolution digital camera was implemented to obtain speckle images of ten bovine articular cartilage specimens prepared for different average roughness values. Texture analysis method based on gray-level co-occurrence matrix (GLCM) analyzed on the captured speckle images is used to characterize the surface roughness of the specimens depending on the computation of Haralick's texture features. In conclusion, this promising method can accurately estimate the surface roughness of articular cartilage even for early signs of degeneration. The method is effective for estimation of average surface roughness values ranging from 0.09 µm to 2.51 µm with an accuracy of 0.03 µm.

Estimation of Articular Cartilage Surface Roughness Using Gray-Level Co-Occurrence Matrix of Laser Speckle Image

PubMed Central

El-Ghandoor, Hatem; Kandel, Hamed; El-Azab, Jala; Hassab-Elnaby, Salah

2017-01-01

The application of He-Ne laser technologies for description of articular cartilage degeneration, one of the most common diseases worldwide, is an innovative usage of these technologies used primarily in material engineering. Plain radiography and magnetic resonance imaging are insufficient to allow the early assessment of the disease. As surface roughness of articular cartilage is an important indicator of articular cartilage degeneration progress, a safe and noncontact technique based on laser speckle image to estimate the surface roughness is provided. This speckle image from the articular cartilage surface, when illuminated by laser beam, gives very important information about the physical properties of the surface. An experimental setup using a low power He-Ne laser and a high-resolution digital camera was implemented to obtain speckle images of ten bovine articular cartilage specimens prepared for different average roughness values. Texture analysis method based on gray-level co-occurrence matrix (GLCM) analyzed on the captured speckle images is used to characterize the surface roughness of the specimens depending on the computation of Haralick’s texture features. In conclusion, this promising method can accurately estimate the surface roughness of articular cartilage even for early signs of degeneration. The method is effective for estimation of average surface roughness values ranging from 0.09 µm to 2.51 µm with an accuracy of 0.03 µm. PMID:28773080

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.

Many local pattern texture features: which is better for image-based multilabel human protein subcellular localization classification?

PubMed

Yang, Fan; Xu, Ying-Ying; Shen, Hong-Bin

2014-01-01

Human protein subcellular location prediction can provide critical knowledge for understanding a protein's function. Since significant progress has been made on digital microscopy, automated image-based protein subcellular location classification is urgently needed. In this paper, we aim to investigate more representative image features that can be effectively used for dealing with the multilabel subcellular image samples. We prepared a large multilabel immunohistochemistry (IHC) image benchmark from the Human Protein Atlas database and tested the performance of different local texture features, including completed local binary pattern, local tetra pattern, and the standard local binary pattern feature. According to our experimental results from binary relevance multilabel machine learning models, the completed local binary pattern, and local tetra pattern are more discriminative for describing IHC images when compared to the traditional local binary pattern descriptor. The combination of these two novel local pattern features and the conventional global texture features is also studied. The enhanced performance of final binary relevance classification model trained on the combined feature space demonstrates that different features are complementary to each other and thus capable of improving the accuracy of classification.

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.

Domain Engineered Magnetoelectric Thin Films for High Sensitivity Resonant Magnetic Field Sensors

DTIC Science & Technology

2012-02-28

texture E analysis w cated by poo re accounted n measurem 8 sol-gel samp d PZT sol-g as utilized t r fit between in the mo ent spot). les shown i el...nsformer str nted by aero ure. ure 34: Un were grow as varied in D) as show texturing in . D pattern of the films d ucture. Figu sol jet depo ipoled PZT ...the detailed characterization was the development of prediction models for texturing of PZT sol-gel thin films, an understanding of the analytical

Near-affine-invariant texture learning for lung tissue analysis using isotropic wavelet frames.

PubMed

Depeursinge, Adrien; Van de Ville, Dimitri; Platon, Alexandra; Geissbuhler, Antoine; Poletti, Pierre-Alexandre; Müller, Henning

2012-07-01

We propose near-affine-invariant texture descriptors derived from isotropic wavelet frames for the characterization of lung tissue patterns in high-resolution computed tomography (HRCT) imaging. Affine invariance is desirable to enable learning of nondeterministic textures without a priori localizations, orientations, or sizes. When combined with complementary gray-level histograms, the proposed method allows a global classification accuracy of 76.9% with balanced precision among five classes of lung tissue using a leave-one-patient-out cross validation, in accordance with clinical practice.

High Strength and Ductility of Additively Manufactured 316L Stainless Steel Explained

NASA Astrophysics Data System (ADS)

Shamsujjoha, Md.; Agnew, Sean R.; Fitz-Gerald, James M.; Moore, William R.; Newman, Tabitha A.

2018-04-01

Structure-property relationships of an additively manufactured 316L stainless steel were explored. A scanning electron microscope and electron backscattered diffraction (EBSD) analysis revealed a fine cellular-dendritic (0.5 to 2 μm) substructure inside large irregularly shaped grains ( 100 μm). The cellular structure grows along the <100> crystallographic directions. However, texture analysis revealed that the main <100> texture component is inclined by 15 deg from the building direction. X-ray diffraction line profile analysis indicated a high dislocation density of 1 × 1015 m-2 in the as-built material, which correlates well with the observed EBSD microstructure and high-yield strength, via the traditional Taylor hardening equation. Significant variations in strain hardening behavior and ductility were observed for the horizontal (HB) and vertical (VB) built samples. Ductility of HB and VB samples measured 49 and 77 pct, respectively. The initial growth texture and subsequent texture evolution during tensile deformation are held responsible for the observed anisotropy. Notably, EBSD analysis of deformed samples showed deformation twins, which predominately form in the grains with <111> aligned parallel to the loading direction. The VB samples showed higher twinning activity, higher strain hardening rates at high strain, and therefore, higher ductility. Analysis of annealed samples revealed that the observed microstructures and properties are thermally stable, with only a moderate decrease in strength and very similar levels of ductility and anisotropy, compared with the as-built condition.

High Strength and Ductility of Additively Manufactured 316L Stainless Steel Explained

NASA Astrophysics Data System (ADS)

Shamsujjoha, Md.; Agnew, Sean R.; Fitz-Gerald, James M.; Moore, William R.; Newman, Tabitha A.

2018-07-01

Structure-property relationships of an additively manufactured 316L stainless steel were explored. A scanning electron microscope and electron backscattered diffraction (EBSD) analysis revealed a fine cellular-dendritic (0.5 to 2 μm) substructure inside large irregularly shaped grains ( 100 μm). The cellular structure grows along the <100> crystallographic directions. However, texture analysis revealed that the main <100> texture component is inclined by 15 deg from the building direction. X-ray diffraction line profile analysis indicated a high dislocation density of 1 × 1015 m-2 in the as-built material, which correlates well with the observed EBSD microstructure and high-yield strength, via the traditional Taylor hardening equation. Significant variations in strain hardening behavior and ductility were observed for the horizontal (HB) and vertical (VB) built samples. Ductility of HB and VB samples measured 49 and 77 pct, respectively. The initial growth texture and subsequent texture evolution during tensile deformation are held responsible for the observed anisotropy. Notably, EBSD analysis of deformed samples showed deformation twins, which predominately form in the grains with <111> aligned parallel to the loading direction. The VB samples showed higher twinning activity, higher strain hardening rates at high strain, and therefore, higher ductility. Analysis of annealed samples revealed that the observed microstructures and properties are thermally stable, with only a moderate decrease in strength and very similar levels of ductility and anisotropy, compared with the as-built condition.

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.

Cross-Modal Associations between Sounds and Drink Tastes/Textures: A Study with Spontaneous Production of Sound-Symbolic Words.

PubMed

Sakamoto, Maki; Watanabe, Junji

2016-03-01

Many languages have a word class whose speech sounds are linked to sensory experiences. Several recent studies have demonstrated cross-modal associations (or correspondences) between sounds and gustatory sensations by asking participants to match predefined sound-symbolic words (e.g., "maluma/takete") with the taste/texture of foods. Here, we further explore cross-modal associations using the spontaneous production of words and semantic ratings of sensations. In the experiment, after drinking liquids, participants were asked to express their taste/texture using Japanese sound-symbolic words, and at the same time, to evaluate it in terms of criteria expressed by adjectives. Because the Japanese language has a large vocabulary of sound-symbolic words, and Japanese people frequently use them to describe taste/texture, analyzing a variety of Japanese sound-symbolic words spontaneously produced to express taste/textures might enable us to explore the mechanism of taste/texture categorization. A hierarchical cluster analysis based on the relationship between linguistic sounds and taste/texture evaluations revealed the structure of sensation categories. The results indicate that an emotional evaluation like pleasant/unpleasant is the primary cluster in gustation. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Evolution of fabric in Chitradurga granite (south India) - A study based on microstructure, anisotropy of magnetic susceptibility (AMS) and vorticity analysis

NASA Astrophysics Data System (ADS)

Mondal, Tridib Kumar

2018-01-01

In this paper, the fabric in massive granite ( 2.6 Ga) from the Chitradurga region (Western Dharwar Craton, south India) is analyzed using microstructure, anisotropy of magnetic susceptibility (AMS) study and kinematic vorticity analysis. The microstructural investigation on the granite shows a progressive textural overprint from magmatic, through high-T to low-T solid-state deformation textures. The mean magnetic foliation in the rocks of the region is dominantly NW-SE striking which have developed during regional D1/D2 deformation on account of NE-SW shortening. The plunge of the magnetic lineation varies from NW to vertical to SE, and interpreted to be a consequence of regional D3 deformation on account of NW-SE to E-W shortening. The vorticity analysis from magnetic fabric in the region reveals that the NW-SE oriented fabric formed under pure shear condition during D1/D2 regional deformation. However, some parts of the region particularly close to the adjacent Chitradurga Shear Zone show that the magnetic fabrics are oblique to the foliation as well as shear zone orientation and inferred to be controlled by simple shearing during D3 regional deformation. The shape preferred orientation (SPO) analysis from oriented thin sections suggest that the shape of the recrystallized quartz grains define the magnetic fabric in Chitradurga granite and the degree of the SPO reduces away from the Chitradurga Shear Zone. It is interpreted that the change in magnetic fabrics in some parts of the granite in the region are dominantly controlled by the late stage sinistral shearing which occurred during the development of Chitradurga Shear Zone. Anisotropy of magnetic susceptibility (AMS) data of granite from the Chitradurga region (West Dharwar Craton, southern India). Km = Mean susceptibility; Pj = corrected degree of magnetic anisotropy; T = shape parameter. K1 and K3 are the maximum and minimum principal axes of the AMS ellipsoid, respectively. dec = Declination; inc = Inclination.

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

Textural analysis of historical aerial photography to characterize woody plant encroachment in South African savanna

Treesearch

Andrew T. Hudak; Carol A. Wessman

1998-01-01

Transitions from grassland to shrubland through woody plant encroachment result in potentially significant shifts in savanna ecosystem function. Given high resolution imagery, a textural index could prove useful for mapping woody plant densities and monitoring woody plant encroachment across savanna landscapes. Spatial heterogeneity introduced through mixtures of...

Height growth of red pine on fine-textured soils.

Treesearch

David H. Alban; Donald H. Prettyman

1984-01-01

Height growth was determined by stem analysis for red pine in 12 natural and 10 planted stands on well-drained, fine textured soils. Growth closely followed the Gervorkiantz site index curves. When calculating site index, an age adjustment is desirable if the trees take longer than 8 years to attain breast height.

Characterization of bottom sediments in the Río de la Plata estuary

NASA Astrophysics Data System (ADS)

Simionato, Claudia G.; Moreira, Diego

2016-04-01

Bottom sediments and surface water samples were collected in the intermediate and outer Río de la Plata Estuary during 2009-2010, in six repeated cruises, with 26 stations each. Samples were processed for grain size using a laser particle size analyzer, and water and organic matter contents. The aim of this work is to analyze this data set to provide a comprehensive and objective characterization of the bottom sediments distribution, to study their composition and to progress in the construction of a conceptual model of the involved physical mechanisms. Principal Components Analysis is applied to the bottom sediments size histograms to investigate the spatial patterns. Variations in grain-size parameters contain information on possible sediment transport patterns, which were analyzed by means of trend vectors. Sediments show a gradational arrangement of textures, sand dominant at the head, silt in the intermediate estuary and clayey silt and clay at its mouth; textures become progressively more poorly sorted offshore, and the water and organic matter contents increase. And seem to be strongly related to the geometry and the hydrodynamics. Along the Northern coast of the intermediate estuary, well sorted medium and fine silt predominates, whereas in the Southern coast, coarser and less sorted silt prevails, due to differences in tidal currents and/or in water pathways. Around Barra del Indio, clay prevails over silt and sand, and the water and organic matter contents reach a maximum, probably due flocculation, and the reduction of the currents. Immediately seawards the salt wedge, net transport reverses its direction and well sorted coarser sand from the adjacent shelf dominates. Relict sediment is observed around the Santa Lucía River, consisting of poorly sorted fine silt and clay. The inferred net transport suggests convergence at the Barra del Indio shoal, which is consistent with the constant growing of the banks.

Role of Physical Bolus Properties as Sensory Inputs in the Trigger of Swallowing

PubMed Central

Peyron, Marie-Agnès; Gierczynski, Isabelle; Hartmann, Christoph; Loret, Chrystel; Dardevet, Dominique; Martin, Nathalie; Woda, Alain

2011-01-01

Background Swallowing is triggered when a food bolus being prepared by mastication has reached a defined state. However, although this view is consensual and well supported, the physical properties of the swallowable bolus have been under-researched. We tested the hypothesis that measuring bolus physical changes during the masticatory sequence to deglutition would reveal the bolus properties potentially involved in swallowing initiation. Methods Twenty normo-dentate young adults were instructed to chew portions of cereal and spit out the boluses at different times in the masticatory sequence. The mechanical properties of the collected boluses were measured by a texture profile analysis test currently used in food science. The median particle size of the boluses was evaluated by sieving. In a simultaneous sensory study, twenty-five other subjects expressed their perception of bolus texture dominating at any mastication time. Findings Several physical changes appeared in the food bolus as it was formed during mastication: (1) in rheological terms, bolus hardness rapidly decreased as the masticatory sequence progressed, (2) by contrast, adhesiveness, springiness and cohesiveness regularly increased until the time of swallowing, (3) median particle size, indicating the bolus particle size distribution, decreased mostly during the first third of the masticatory sequence, (4) except for hardness, the rheological changes still appeared in the boluses collected just before swallowing, and (5) physical changes occurred, with sensory stickiness being described by the subjects as a dominant perception of the bolus at the end of mastication. Conclusions Although these physical and sensory changes progressed in the course of mastication, those observed just before swallowing seem to be involved in swallowing initiation. They can be considered as strong candidates for sensory inputs from the bolus that are probably crucially involved in the triggering of swallowing, since they appeared in boluses prepared in various mastication strategies by different subjects. PMID:21738616

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.

Optimal decision-making in mammals: insights from a robot study of rodent texture discrimination

PubMed Central

Lepora, Nathan F.; Fox, Charles W.; Evans, Mathew H.; Diamond, Mathew E.; Gurney, Kevin; Prescott, Tony J.

2012-01-01

Texture perception is studied here in a physical model of the rat whisker system consisting of a robot equipped with a biomimetic vibrissal sensor. Investigations of whisker motion in rodents have led to several explanations for texture discrimination, such as resonance or stick-slips. Meanwhile, electrophysiological studies of decision-making in monkeys have suggested a neural mechanism of evidence accumulation to threshold for competing percepts, described by a probabilistic model of Bayesian sequential analysis. For our robot whisker data, we find that variable reaction-time decision-making with sequential analysis performs better than the fixed response-time maximum-likelihood estimation. These probabilistic classifiers also use whatever available features of the whisker signals aid the discrimination, giving improved performance over a single-feature strategy, such as matching the peak power spectra of whisker vibrations. These results cast new light on how the various proposals for texture discrimination in rodents depend on the whisker contact mechanics and suggest the possibility of a common account of decision-making across mammalian species. PMID:22279155

Effects of Flavor and Texture on the Sensory Perception of Gouda-Type Cheese Varieties during Ripening Using Multivariate Analysis.

PubMed

Shiota, Makoto; Iwasawa, Ai; Suzuki-Iwashima, Ai; Iida, Fumiko

2015-12-01

The impact of flavor composition, texture, and other factors on desirability of different commercial sources of Gouda-type cheese using multivariate analyses on the basis of sensory and instrumental analyses were investigated. Volatile aroma compounds were measured using headspace solid-phase microextraction gas chromatography/mass spectrometry (GC/MS) and steam distillation extraction (SDE)-GC/MS, and fatty acid composition, low-molecular-weight compounds, including amino acids, and organic acids, as well pH, texture, and color were measured to determine their relationship with sensory perception. Orthogonal partial least squares-discriminant analysis (OPLS-DA) was performed to discriminate between 2 different ripening periods in 7 sample sets, revealing that ethanol, ethyl acetate, hexanoic acid, and octanoic acid increased with increasing sensory attribute scores for sweetness, fruity, and sulfurous. A partial least squares (PLS) regression model was constructed to predict the desirability of cheese using these parameters. We showed that texture and buttery flavors are important factors affecting the desirability of Gouda-type cheeses for Japanese consumers using these multivariate analyses. © 2015 Institute of Food Technologists®

Topology-guided deformable registration with local importance preservation for biomedical images

NASA Astrophysics Data System (ADS)

Zheng, Chaojie; Wang, Xiuying; Zeng, Shan; Zhou, Jianlong; Yin, Yong; Feng, Dagan; Fulham, Michael

2018-01-01

The demons registration (DR) model is well recognized for its deformation capability. However, it might lead to misregistration due to erroneous diffusion direction when there are no overlaps between corresponding regions. We propose a novel registration energy function, introducing topology energy, and incorporating a local energy function into the DR in a progressive registration scheme, to address these shortcomings. The topology energy that is derived from the topological information of the images serves as a direction inference to guide diffusion transformation to retain the merits of DR. The local energy constrains the deformation disparity of neighbouring pixels to maintain important local texture and density features. The energy function is minimized in a progressive scheme steered by a topology tree graph and we refer to it as topology-guided deformable registration (TDR). We validated our TDR on 20 pairs of synthetic images with Gaussian noise, 20 phantom PET images with artificial deformations and 12 pairs of clinical PET-CT studies. We compared it to three methods: (1) free-form deformation registration method, (2) energy-based DR and (3) multi-resolution DR. The experimental results show that our TDR outperformed the other three methods in regard to structural correspondence and preservation of the local important information including texture and density, while retaining global correspondence.

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.

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

PubMed

Kinoshita, Manabu; Sakai, Mio; Arita, Hideyuki; Shofuda, Tomoko; Chiba, Yasuyoshi; Kagawa, Naoki; Watanabe, Yoshiyuki; Hashimoto, Naoya; Fujimoto, Yasunori; Yoshimine, Toshiki; Nakanishi, Katsuyuki; Kanemura, Yonehiro

2016-01-01

Reports have suggested that tumor textures presented on T2-weighted images correlate with the genetic status of glioma. Therefore, development of an image analyzing framework that is capable of objective and high throughput image texture analysis for large scale image data collection is needed. The current study aimed to address the development of such a framework by introducing two novel parameters for image textures on T2-weighted images, i.e., Shannon entropy and Prewitt filtering. Twenty-two WHO grade 2 and 28 grade 3 glioma patients were collected whose pre-surgical MRI and IDH1 mutation status were available. Heterogeneous lesions showed statistically higher Shannon entropy than homogenous lesions (p = 0.006) and ROC curve analysis proved that Shannon entropy on T2WI was a reliable indicator for discrimination of homogenous and heterogeneous lesions (p = 0.015, AUC = 0.73). Lesions with well-defined borders exhibited statistically higher Edge mean and Edge median values using Prewitt filtering than those with vague lesion borders (p = 0.0003 and p = 0.0005 respectively). ROC curve analysis also proved that both Edge mean and median values were promising indicators for discrimination of lesions with vague and well defined borders and both Edge mean and median values performed in a comparable manner (p = 0.0002, AUC = 0.81 and p < 0.0001, AUC = 0.83, respectively). Finally, IDH1 wild type gliomas showed statistically lower Shannon entropy on T2WI than IDH1 mutated gliomas (p = 0.007) but no difference was observed between IDH1 wild type and mutated gliomas in Edge median values using Prewitt filtering. The current study introduced two image metrics that reflect lesion texture described on T2WI. These two metrics were validated by readings of a neuro-radiologist who was blinded to the results. This observation will facilitate further use of this technique in future large scale image analysis of glioma.

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

PubMed

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

2018-03-01

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

Texture Analysis and Machine Learning for Detecting Myocardial Infarction in Noncontrast Low-Dose Computed Tomography: Unveiling the Invisible.

PubMed

Mannil, Manoj; von Spiczak, Jochen; Manka, Robert; Alkadhi, Hatem

2018-06-01

The aim of this study was to test whether texture analysis and machine learning enable the detection of myocardial infarction (MI) on non-contrast-enhanced low radiation dose cardiac computed tomography (CCT) images. In this institutional review board-approved retrospective study, we included non-contrast-enhanced electrocardiography-gated low radiation dose CCT image data (effective dose, 0.5 mSv) acquired for the purpose of calcium scoring of 27 patients with acute MI (9 female patients; mean age, 60 ± 12 years), 30 patients with chronic MI (8 female patients; mean age, 68 ± 13 years), and in 30 subjects (9 female patients; mean age, 44 ± 6 years) without cardiac abnormality, hereafter termed controls. Texture analysis of the left ventricle was performed using free-hand regions of interest, and texture features were classified twice (Model I: controls versus acute MI versus chronic MI; Model II: controls versus acute and chronic MI). For both classifications, 6 commonly used machine learning classifiers were used: decision tree C4.5 (J48), k-nearest neighbors, locally weighted learning, RandomForest, sequential minimal optimization, and an artificial neural network employing deep learning. In addition, 2 blinded, independent readers visually assessed noncontrast CCT images for the presence or absence of MI. In Model I, best classification results were obtained using the k-nearest neighbors classifier (sensitivity, 69%; specificity, 85%; false-positive rate, 0.15). In Model II, the best classification results were found with the locally weighted learning classification (sensitivity, 86%; specificity, 81%; false-positive rate, 0.19) with an area under the curve from receiver operating characteristics analysis of 0.78. In comparison, both readers were not able to identify MI in any of the noncontrast, low radiation dose CCT images. This study indicates the ability of texture analysis and machine learning in detecting MI on noncontrast low radiation dose CCT images being not visible for the radiologists' eye.

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.

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

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

Fang, Y; Huang, H; Su, T

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

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

PubMed

Khoje, Suchitra

2018-02-01

Images of four qualities of mangoes and guavas are evaluated for color and textural features to characterize and classify them, and to model the fruit appearance grading. The paper discusses three approaches to identify most discriminating texture features of both the fruits. In the first approach, fruit's color and texture features are selected using Mahalanobis distance. A total of 20 color features and 40 textural features are extracted for analysis. Using Mahalanobis distance and feature intercorrelation analyses, one best color feature (mean of a* [L*a*b* color space]) and two textural features (energy a*, contrast of H*) are selected as features for Guava while two best color features (R std, H std) and one textural features (energy b*) are selected as features for mangoes with the highest discriminate power. The second approach studies some common wavelet families for searching the best classification model for fruit quality grading. The wavelet features extracted from five basic mother wavelets (db, bior, rbior, Coif, Sym) are explored to characterize fruits texture appearance. In third approach, genetic algorithm is used to select only those color and wavelet texture features that are relevant to the separation of the class, from a large universe of features. The study shows that image color and texture features which were identified using a genetic algorithm can distinguish between various qualities classes of fruits. The experimental results showed that support vector machine classifier is elected for Guava grading with an accuracy of 97.61% and artificial neural network is elected from Mango grading with an accuracy of 95.65%. The proposed method is nondestructive fruit quality assessment method. The experimental results has proven that Genetic algorithm along with wavelet textures feature has potential to discriminate fruit quality. Finally, it can be concluded that discussed method is an accurate, reliable, and objective tool to determine fruit quality namely Mango and Guava, and might be applicable to in-line sorting systems. © 2017 Wiley Periodicals, Inc.

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.

Radiomics biomarkers for accurate tumor progression prediction of oropharyngeal cancer

NASA Astrophysics Data System (ADS)

Hadjiiski, Lubomir; Chan, Heang-Ping; Cha, Kenny H.; Srinivasan, Ashok; Wei, Jun; Zhou, Chuan; Prince, Mark; Papagerakis, Silvana

2017-03-01

Accurate tumor progression prediction for oropharyngeal cancers is crucial for identifying patients who would best be treated with optimized treatment and therefore minimize the risk of under- or over-treatment. An objective decision support system that can merge the available radiomics, histopathologic and molecular biomarkers in a predictive model based on statistical outcomes of previous cases and machine learning may assist clinicians in making more accurate assessment of oropharyngeal tumor progression. In this study, we evaluated the feasibility of developing individual and combined predictive models based on quantitative image analysis from radiomics, histopathology and molecular biomarkers for oropharyngeal tumor progression prediction. With IRB approval, 31, 84, and 127 patients with head and neck CT (CT-HN), tumor tissue microarrays (TMAs) and molecular biomarker expressions, respectively, were collected. For 8 of the patients all 3 types of biomarkers were available and they were sequestered in a test set. The CT-HN lesions were automatically segmented using our level sets based method. Morphological, texture and molecular based features were extracted from CT-HN and TMA images, and selected features were merged by a neural network. The classification accuracy was quantified using the area under the ROC curve (AUC). Test AUCs of 0.87, 0.74, and 0.71 were obtained with the individual predictive models based on radiomics, histopathologic, and molecular features, respectively. Combining the radiomics and molecular models increased the test AUC to 0.90. Combining all 3 models increased the test AUC further to 0.94. This preliminary study demonstrates that the individual domains of biomarkers are useful and the integrated multi-domain approach is most promising for tumor progression prediction.

Hybrid processing and anisotropic sintering shrinkage in textured ZnO ceramics

PubMed Central

Keskinbora, Kahraman; Suzuki, Tohru S; Ozgur Ozer, I; Sakka, Yoshio; Suvaci, Ender

2010-01-01

We have studied the combined effects of the templated grain growth and magnetic alignment processes on sintering, anisotropic sintering shrinkage, microstructure development and texture in ZnO ceramics. Suspensions of 0–10 vol % ZnO template particles were slip cast in a 12 T rotating magnetic field. Sintering and texture characteristics were investigated via thermomechanical analysis and electron backscatter diffraction, respectively. Sintering as well as texture characteristics depend on template concentration. For the studied ZnO system, there is a critical template concentration (2 vol % in this study) above which densification is limited by the templates owing to constrained sintering. Below this limit, the densification is enhanced and the anisotropic shrinkage is reduced, which is attributed to densifying characteristics of the templates. PMID:27877373

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

PubMed Central

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

2017-01-01

Background: Non-invasive characterization of the pathological features of Alzheimer's disease (AD) could enhance patient management and the development of therapeutic strategies. Magnetic resonance imaging texture analysis (MRTA) has been used previously to extract texture descriptors from structural clinical scans in AD to determine cerebral tissue heterogeneity. In this study, we examined the potential of MRTA to specifically identify tau pathology in an AD mouse model and compared the MRTA metrics to histological measures of tau burden. Methods: MRTA was applied to T2 weighted high-resolution MR images of nine 8.5-month-old rTg4510 tau pathology (TG) mice and 16 litter matched wild-type (WT) mice. MRTA comprised of the filtration-histogram technique, where the filtration step extracted and enhanced features of different sizes (fine, medium, and coarse texture scales), followed by quantification of texture using histogram analysis (mean gray level intensity, mean intensity, entropy, uniformity, skewness, standard-deviation, and kurtosis). MRTA was applied to manually segmented regions of interest (ROI) drawn within the cortex, hippocampus, and thalamus regions and the level of tau burden was assessed in equivalent regions using histology. Results: Texture parameters were markedly different between WT and TG in the cortex (E, p < 0.01, K, p < 0.01), the hippocampus (K, p < 0.05) and in the thalamus (K, p < 0.01). In addition, we observed significant correlations between histological measurements of tau burden and kurtosis in the cortex, hippocampus and thalamus. Conclusions: MRTA successfully differentiated WT and TG in brain regions with varying degrees of tau pathology (cortex, hippocampus, and thalamus) based on T2 weighted MR images. Furthermore, the kurtosis measurement correlated with histological measures of tau burden. This initial study indicates that MRTA may have a role in the early diagnosis of AD and the assessment of tau pathology using routinely acquired structural MR images. PMID:29163005

Robust surface roughness indices and morphological interpretation

NASA Astrophysics Data System (ADS)

Trevisani, Sebastiano; Rocca, Michele

2016-04-01

Geostatistical-based image/surface texture indices based on variogram (Atkison and Lewis, 2000; Herzfeld and Higginson, 1996; Trevisani et al., 2012) and on its robust variant MAD (median absolute differences, Trevisani and Rocca, 2015) offer powerful tools for the analysis and interpretation of surface morphology (potentially not limited to solid earth). In particular, the proposed robust index (Trevisani and Rocca, 2015) with its implementation based on local kernels permits the derivation of a wide set of robust and customizable geomorphometric indices capable to outline specific aspects of surface texture. The stability of MAD in presence of signal noise and abrupt changes in spatial variability is well suited for the analysis of high-resolution digital terrain models. Moreover, the implementation of MAD by means of a pixel-centered perspective based on local kernels, with some analogies to the local binary pattern approach (Lucieer and Stein, 2005; Ojala et al., 2002), permits to create custom roughness indices capable to outline different aspects of surface roughness (Grohmann et al., 2011; Smith, 2015). In the proposed poster, some potentialities of the new indices in the context of geomorphometry and landscape analysis will be presented. At same time, challenges and future developments related to the proposed indices will be outlined. Atkinson, P.M., Lewis, P., 2000. Geostatistical classification for remote sensing: an introduction. Computers & Geosciences 26, 361-371. Grohmann, C.H., Smith, M.J., Riccomini, C., 2011. Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland. IEEE Transactions on Geoscience and Remote Sensing 49, 1220-1213. Herzfeld, U.C., Higginson, C.A., 1996. Automated geostatistical seafloor classification - Principles, parameters, feature vectors, and discrimination criteria. Computers and Geosciences, 22 (1), pp. 35-52. Lucieer, A., Stein, A., 2005. Texture-based landform segmentation of LiDAR imagery. International Journal of Applied Earth Observation and Geoinformation 6, 261-270. Ojala, T., Pietikäinen, M. & Mäenpää, T. 2002. "Multiresolution gray-scale and rotation invariant texture classification with local binary patterns", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 7, pp. 971-987. Smith, M.W. 2014. "Roughness in the Earth Sciences", Earth-Science Reviews, vol. 136, pp. 202-225. Trevisani, S., Cavalli, M. & Marchi, L. 2012. "Surface texture analysis of a high-resolution DTM: Interpreting an alpine basin", Geomorphology, vol. 161-162, pp. 26-39. Trevisani, S., Rocca, M. 2015. MAD: robust image texture analysis for applications in high resolution geomorphometry. Comput. Geosci. 81, 78-92. doi:10.1016/j.cageo.2015.04.003.

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

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.

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.

Pyroclast textural variation as an indicator of eruption column steadiness in andesitic Plinian eruptions at Mt. Ruapehu

USGS Publications Warehouse

Pardo, Natalia; Cronin, Shane J.; Wright, Heather M.N.; Schipper, C. Ian; Smith, Ian; Stewart, Bob

2014-01-01

Between 27 and 11 cal. ka BP, a transition is observed in Plinian eruptions at Mt. Ruapehu, indicating evolution from non-collapsing (steady and oscillatory) eruption columns to partially collapsing columns (both wet and dry). To determine the causes of these variations over this eruptive interval, we examined lapilli fall deposits from four eruptions representing the climactic phases of each column type. All eruptions involve andesite to basaltic andesite magmas containing plagioclase, clinopyroxene, orthopyroxene and magnetite phenocrysts. Differences occur in the dominant pumice texture, the degree of bulk chemistry and textural variability, the average microcrystallinity and the composition of groundmass glass. In order to investigate the role of ascent and degassing processes on column stability, vesicle textures were quantified by gas volume pycnometry (porosity), X-ray synchrotron and computed microtomography (μ-CT) imagery from representative clasts from each eruption. These data were linked to groundmass crystallinity and glass geochemistry. Pumice textures were classified into six types (foamy, sheared, fibrous, microvesicular, microsheared and dense) according to the vesicle content, size and shape and microlite content. Bulk porosities vary from 19 to 95 % among all textural types. Melt-referenced vesicle number density ranges between 1.8 × 102 and 8.9 × 102 mm−3, except in fibrous textures, where it spans from 0.3 × 102 to 53 × 102 mm−3. Vesicle-free magnetite number density varies within an order of magnitude from 0.4 × 102 to 4.5 × 102 mm−3 in samples with dacitic groundmass glass and between 0.0 and 2.3 × 102 mm−3 in samples with rhyolitic groundmass. The data indicate that columns that collapsed to produce pyroclastic flows contained pumice with the greatest variation in bulk composition (which overlaps with but extends to slightly more silicic compositions than other eruptive products); textures indicating heterogeneous bubble nucleation, progressively more complex growth history and shear-localization; and the highest degrees of microlite crystallization, most evolved melt compositions and lowest relative temperatures. These findings suggest that collapsing columns in Ruapehu have been produced when strain localization is prominent, early bubble nucleation occurs and variation in decompression rate across the conduit is greatest. This study shows that examination of pumice from steady phases that precede column collapse may be used to predict subsequent column behaviour.

Changes in protein structures to improve the rheology and texture of reduced-fat sausages using high pressure processing.

PubMed

Yang, Huijuan; Khan, Muhammad Ammar; Yu, Xiaobo; Zheng, Haibo; Han, Minyi; Xu, Xinglian; Zhou, Guanghong

2016-11-01

This study investigated the role of high-pressure processing (HPP) for improving the functional properties of meat batters and the textural properties of reduced-fat sausages. Application of 200MPa pressure at 10°C for 2min to pork batters containing various fat contents (0-30%) affected their rheological properties, cooking losses, color, textual properties and their protein imaging. The results revealed that both application of 200MPa and increasing fat content decreased cooking loss, as well as improved the textural and rheological properties. Cooking losses, texture and sensory evaluation of 200MPa treated sausages having 20% fat were similar to those of the 0.1MPa treated sausages having 30% fat. Principal component analysis revealed that certain quality attributes were affected differently by the levels of fat addition and by HPP. These findings indicated the potential of HPP for improving yield and texture of emulsion-type sausages having reduced fat contents. Copyright © 2016 Elsevier Ltd. All rights reserved.

Texture profile analysis of yogurt as influenced by partially hydrolyzed guar gum and process variables.

PubMed

Mudgil, Deepak; Barak, Sheweta; Khatkar, B S

2017-11-01

Effect of partially hydrolyzed guar gum (PHGG) level (1-5%), culture level (1.5-3.5%) and incubation time (4-8 h) on texture profile of yogurt was studied using response surface methodology. The fortification of partially hydrolyzed guar gum in yogurt decreased the firmness and gumminess while it increased the adhesiveness, cohesiveness and springiness of yogurt significantly at p  < 0.01. The culture level did not affect the textural properties of yogurt significantly except gumminess whereas textural properties of yogurt were negatively correlated with incubation time. The coefficient of determination for hardness/hardness, adhesiveness, cohesiveness, springiness and gumminess were 0.9216, 0.9397, 0.8914, 0.8971 and 0.9156, respectively, which revealed that the models obtained were significant as coefficient of determination value was close to one. The optimum conditions obtained were PHGG level 3.37%, culture level 1.96% and incubation time 5.96 h which leads to preparation of yogurt with desired textural characteristics.

The relation of apple texture with cell wall nanostructure studied using an atomic force microscope.

PubMed

Cybulska, Justyna; Zdunek, Artur; Psonka-Antonczyk, Katarzyna M; Stokke, Bjørn T

2013-01-30

In this study, the relation of the nanostructure of cell walls with their texture was investigated for six different apple cultivars. Cell wall material (CWM) and cellulose microfibrils were imaged by atomic force microscope (AFM). The mean diameter of cellulose microfibrils for each cultivar was estimated based on the AFM height topographs obtained using the tapping mode of dried specimens. Additionally, crystallinity of cellulose microfibrils and pectin content was determined. Texture of apple cultivars was evaluated by sensory and instrumental analysis. Differences in cellulose diameter as determined from the AFM height topographs of the nanostructure of cell walls of the apple cultivars are found to relate to the degree of crystallinity and pectin content. Cultivars with thicker cellulose microfibrils also revealed crisper, harder and juicier texture, and greater acoustic emission. The data suggest that microfibril thickness affects the mechanical strength of cell walls which has consequences for sensory and instrumental texture. Copyright © 2012 Elsevier Ltd. All rights reserved.

Inference of segmented color and texture description by tensor voting.

PubMed

Jia, Jiaya; Tang, Chi-Keung

2004-06-01

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

Texture and Tempered Condition Combined Effects on Fatigue Behavior in an Al-Cu-Li Alloy

NASA Astrophysics Data System (ADS)

Wang, An; Liu, Zhiyi; Liu, Meng; Wu, Wenting; Bai, Song; Yang, Rongxian

2017-05-01

Texture and tempered condition combined effects on fatigue behavior in an Al-Cu-Li alloy have been investigated using tensile testing, cyclic loading testing, scanning electron microscope (SEM), transmission electron microscopy (TEM) and texture analysis. Results showed that in near-threshold region, T4-tempered samples possessed the lowest fatigue crack propagation (FCP) rate. In Paris regime, T4-tempered sample had similar FCP rate with T6-tempered sample. T83-tempered sample exhibited the greatest FCP rate among the three tempered conditions. 3% pre-stretching in T83-tempered sample resulted in a reducing intensity of Goss texture and facilitated T1 precipitation. SEM results showed that less crack deflection was observed in T83-tempered sample, as compared to other two tempered samples. It was the combined effects of a lower intensity of Goss texture and T1 precipitates retarding the reversible dislocation slipping in the plastic zone ahead the crack tip.

Foreign object detection and removal to improve automated analysis of chest radiographs

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

Hogeweg, Laurens; Sanchez, Clara I.; Melendez, Jaime

2013-07-15

Purpose: Chest radiographs commonly contain projections of foreign objects, such as buttons, brassier clips, jewellery, or pacemakers and wires. The presence of these structures can substantially affect the output of computer analysis of these images. An automated method is presented to detect, segment, and remove foreign objects from chest radiographs.Methods: Detection is performed using supervised pixel classification with a kNN classifier, resulting in a probability estimate per pixel to belong to a projected foreign object. Segmentation is performed by grouping and post-processing pixels with a probability above a certain threshold. Next, the objects are replaced by texture inpainting.Results: The methodmore » is evaluated in experiments on 257 chest radiographs. The detection at pixel level is evaluated with receiver operating characteristic analysis on pixels within the unobscured lung fields and an A{sub z} value of 0.949 is achieved. Free response operator characteristic analysis is performed at the object level, and 95.6% of objects are detected with on average 0.25 false positive detections per image. To investigate the effect of removing the detected objects through inpainting, a texture analysis system for tuberculosis detection is applied to images with and without pathology and with and without foreign object removal. Unprocessed, the texture analysis abnormality score of normal images with foreign objects is comparable to those with pathology. After removing foreign objects, the texture score of normal images with and without foreign objects is similar, while abnormal images, whether they contain foreign objects or not, achieve on average higher scores.Conclusions: The authors conclude that removal of foreign objects from chest radiographs is feasible and beneficial for automated image analysis.« less

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

PubMed

Pantic, Igor; Pantic, Senka

2012-10-01

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

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

PubMed

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

2016-02-01

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

Quantification of ultrasonic texture intra-heterogeneity via volumetric stochastic modeling for tissue characterization.

PubMed

Al-Kadi, Omar S; Chung, Daniel Y F; Carlisle, Robert C; Coussios, Constantin C; Noble, J Alison

2015-04-01

Intensity variations in image texture can provide powerful quantitative information about physical properties of biological tissue. However, tissue patterns can vary according to the utilized imaging system and are intrinsically correlated to the scale of analysis. In the case of ultrasound, the Nakagami distribution is a general model of the ultrasonic backscattering envelope under various scattering conditions and densities where it can be employed for characterizing image texture, but the subtle intra-heterogeneities within a given mass are difficult to capture via this model as it works at a single spatial scale. This paper proposes a locally adaptive 3D multi-resolution Nakagami-based fractal feature descriptor that extends Nakagami-based texture analysis to accommodate subtle speckle spatial frequency tissue intensity variability in volumetric scans. Local textural fractal descriptors - which are invariant to affine intensity changes - are extracted from volumetric patches at different spatial resolutions from voxel lattice-based generated shape and scale Nakagami parameters. Using ultrasound radio-frequency datasets we found that after applying an adaptive fractal decomposition label transfer approach on top of the generated Nakagami voxels, tissue characterization results were superior to the state of art. Experimental results on real 3D ultrasonic pre-clinical and clinical datasets suggest that describing tumor intra-heterogeneity via this descriptor may facilitate improved prediction of therapy response and disease characterization. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Convolutional neural network approach for enhanced capture of breast parenchymal complexity patterns associated with breast cancer risk

NASA Astrophysics Data System (ADS)

Oustimov, Andrew; Gastounioti, Aimilia; Hsieh, Meng-Kang; Pantalone, Lauren; Conant, Emily F.; Kontos, Despina

2017-03-01

We assess the feasibility of a parenchymal texture feature fusion approach, utilizing a convolutional neural network (ConvNet) architecture, to benefit breast cancer risk assessment. Hypothesizing that by capturing sparse, subtle interactions between localized motifs present in two-dimensional texture feature maps derived from mammographic images, a multitude of texture feature descriptors can be optimally reduced to five meta-features capable of serving as a basis on which a linear classifier, such as logistic regression, can efficiently assess breast cancer risk. We combine this methodology with our previously validated lattice-based strategy for parenchymal texture analysis and we evaluate the feasibility of this approach in a case-control study with 424 digital mammograms. In a randomized split-sample setting, we optimize our framework in training/validation sets (N=300) and evaluate its descriminatory performance in an independent test set (N=124). The discriminatory capacity is assessed in terms of the the area under the curve (AUC) of the receiver operator characteristic (ROC). The resulting meta-features exhibited strong classification capability in the test dataset (AUC = 0.90), outperforming conventional, non-fused, texture analysis which previously resulted in an AUC=0.85 on the same case-control dataset. Our results suggest that informative interactions between localized motifs exist and can be extracted and summarized via a fairly simple ConvNet architecture.

Wettability transition of laser textured brass surfaces inside different mediums

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Computer-aided diagnosis of melanoma using border and wavelet-based texture analysis.

PubMed

Garnavi, Rahil; Aldeen, Mohammad; Bailey, James

2012-11-01

This paper presents a novel computer-aided diagnosis system for melanoma. The novelty lies in the optimised selection and integration of features derived from textural, borderbased and geometrical properties of the melanoma lesion. The texture features are derived from using wavelet-decomposition, the border features are derived from constructing a boundaryseries model of the lesion border and analysing it in spatial and frequency domains, and the geometry features are derived from shape indexes. The optimised selection of features is achieved by using the Gain-Ratio method, which is shown to be computationally efficient for melanoma diagnosis application. Classification is done through the use of four classifiers; namely, Support Vector Machine, Random Forest, Logistic Model Tree and Hidden Naive Bayes. The proposed diagnostic system is applied on a set of 289 dermoscopy images (114 malignant, 175 benign) partitioned into train, validation and test image sets. The system achieves and accuracy of 91.26% and AUC value of 0.937, when 23 features are used. Other important findings include (i) the clear advantage gained in complementing texture with border and geometry features, compared to using texture information only, and (ii) higher contribution of texture features than border-based features in the optimised feature set.

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

Topological image texture analysis for quality assessment

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Factors affecting dry-cured ham consumer acceptability.

PubMed

Morales, R; Guerrero, L; Aguiar, A P S; Guàrdia, M D; Gou, P

2013-11-01

The objectives of the present study were (1) to compare the relative importance of price, processing time, texture and intramuscular fat in purchase intention of dry-cured ham through conjoint analysis, (2) to evaluate the effect of dry-cured ham appearance on consumer expectations, and (3) to describe the consumer sensory preferences of dry-cured ham using external preference mapping. Texture and processing time influenced the consumer preferences in conjoint analysis. Red colour intensity, colour uniformity, external fat and white film presence/absence influenced consumer expectations. The consumer disliked hams with bitter and metallic flavour and with excessive saltiness and piquantness. Differences between expected and experienced acceptability were found, which indicates that the visual preference of consumers does not allow them to select a dry-cured ham that satisfies their sensory preferences of flavour and texture. Copyright © 2013 Elsevier Ltd. All rights reserved.

Descriptive sensory and instrumental texture profile analysis of woody breast in marinated chicken.

PubMed

Aguirre, M E; Owens, C M; Miller, R K; Alvarado, C Z

2018-04-01

The broiler industry is currently experiencing a muscle anomaly referred to as "woody breast," and the effect of different cooking methods on the marination properties of severe woody breast (SWB) has not yet been reported. This study compared the texture attributes of marinated (injected) normal (NOR) and SWB using a convection oven and a flat-top grill. The objectives were 1) to develop and validate a descriptive texture attribute panel with 6 trained panelists using a 16-point scale and 2) to evaluate the instrumental texture profile analysis (TPA) using a texture analyzer. Sixty-four NOR and SWB were obtained from a commercial facility. Fillet color (L*, a*, b*) and pH were measured before marination. In each of 2 trials, the breast muscles were injected in bulk with 15% brine (0.48 STPP, 0.55% NaCl, final concentration), and marinade retention was determined after 20 minutes. The meat was vacuum packaged, stored at -20°C (7 d sensory; 29 d TPA) and then thawed (4°C, 24 h). Fillets were cooked to 73°C on a flat-top grill (176°C) or in an oven (176°C), and cook loss % was determined. Panelist samples (2 × 2 cm) and TPA samples (4 × 2 cm) were cut into 3 pieces. Color and pH were higher for SWB than NOR fillets (P < 0.05). Marinade retention was 83.21% for NOR meat and 59.23% for SWB meat. The flat-top grill method resulted in higher cook loss than oven (P < 0.05). SWB had higher cook loss when compared to NOR (P < 0.05). Sensory texture descriptors springiness, hardness, denseness, cohesiveness, fracturability, fibrousness, crunchiness, and chewiness were higher for SWB than NOR fillets (P < 0.05). TPA attributes also showed higher values for SWB compared to NOR (P < 0.05). No differences in texture were found between the grill and oven for sensory and TPA attributes. In summary, marinated SWB has significant texture differences when compared to NOR, regardless of cooking method.

P04.19 Recommendations for computation of textural measures obtained from 3D brain tumor MRIs: A robustness analysis points out the need for standardization.

PubMed Central

Molina, D.; Pérez-Beteta, J.; Martínez-González, A.; Velásquez, C.; Martino, J.; Luque, B.; Revert, A.; Herruzo, I.; Arana, E.; Pérez-García, V. M.

2017-01-01

Abstract Introduction: Textural analysis refers to a variety of mathematical methods used to quantify the spatial variations in grey levels within images. In brain tumors, textural features have a great potential as imaging biomarkers having been shown to correlate with survival, tumor grade, tumor type, etc. However, these measures should be reproducible under dynamic range and matrix size changes for their clinical use. Our aim is to study this robustness in brain tumors with 3D magnetic resonance imaging, not previously reported in the literature. Materials and methods: 3D T1-weighted images of 20 patients with glioblastoma (64.80 ± 9.12 years-old) obtained from a 3T scanner were analyzed. Tumors were segmented using an in-house semi-automatic 3D procedure. A set of 16 3D textural features of the most common types (co-occurrence and run-length matrices) were selected, providing regional (run-length based measures) and local information (co-ocurrence matrices) on the tumor heterogeneity. Feature robustness was assessed by means of the coefficient of variation (CV) under both dynamic range (16, 32 and 64 gray levels) and/or matrix size (256x256 and 432x432) changes. Results: None of the textural features considered were robust under dynamic range changes. The textural co-occurrence matrix feature Entropy was the only textural feature robust (CV < 10%) under spatial resolution changes. Conclusions: In general, textural measures of three-dimensional brain tumor images are neither robust under dynamic range nor under matrix size changes. Thus, it becomes mandatory to fix standards for image rescaling after acquisition before the textural features are computed if they are to be used as imaging biomarkers. For T1-weighted images a dynamic range of 16 grey levels and a matrix size of 256x256 (and isotropic voxel) is found to provide reliable and comparable results and is feasible with current MRI scanners. The implications of this work go beyond the specific tumor type and MRI sequence studied here and pose the need for standardization in textural feature calculation of oncological images. FUNDING: James S. Mc. Donnell Foundation (USA) 21st Century Science Initiative in Mathematical and Complex Systems Approaches for Brain Cancer [Collaborative award 220020450 and planning grant 220020420], MINECO/FEDER [MTM2015-71200-R], JCCM [PEII-2014-031-P].

Development of Microstructure and Crystallographic Texture in a Double-Sided Friction Stir Welded Microalloyed Steel

NASA Astrophysics Data System (ADS)

Rahimi, S.; Wynne, B. P.; Baker, T. N.

2017-01-01

The evolution of microstructure and crystallographic texture has been investigated in double-sided friction stir welded microalloyed steel, using electron backscatter diffraction (EBSD). The microstructure analyses show that the center of stirred zone reached a temperature between Ac1 and Ac3 during FSW, resulting in a dual-phase austenitic/ ferritic microstructure. The temperatures in the thermo-mechanically affected zone and the overlapped area between the first and second weld pass did not exceed the Ac1. The shear generated by the rotation probe occurs in austenitic/ferritic phase field where the austenite portion of the microstructure is transformed to a bainitic ferrite, on cooling. Analysis of crystallographic textures with regard to shear flow lines generated by the probe tool shows the dominance of simple shear components across the whole weld. The austenite texture at Ac1 - Ac3 is dominated by the B { {1bar{1}2} }< 110rangle and bar{B} { {bar{1}1bar{2}} }< bar{1}bar{1}0rangle simple shear texture components, where the bainite phase textures formed on cooling were inherited from the shear textures of the austenite phase with relatively strong variant selection. The ferrite portion of the stirred zone and the ferrites in the thermo-mechanically affected zones and the overlapped area underwent shear deformation with textures dominated by the D1 { {bar{1}bar{1}2} }< 111rangle and D2 { {11bar{2}} }< 111rangle simple shear texture components. The formation of ultrafine equiaxed ferrite with submicron grain size has been observed in the overlapped area between the first and second weld pass. This is due to continuous dynamic strain-induced recrystallization as a result of simultaneous severe shear deformation and drastic undercooling.

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.

Determination of mango fruit from binary image using randomized Hough transform

NASA Astrophysics Data System (ADS)

Rizon, Mohamed; Najihah Yusri, Nurul Ain; Abdul Kadir, Mohd Fadzil; bin Mamat, Abd. Rasid; Abd Aziz, Azim Zaliha; Nanaa, Kutiba

2015-12-01

A method of detecting mango fruit from RGB input image is proposed in this research. From the input image, the image is processed to obtain the binary image using the texture analysis and morphological operations (dilation and erosion). Later, the Randomized Hough Transform (RHT) method is used to find the best ellipse fits to each binary region. By using the texture analysis, the system can detect the mango fruit that is partially overlapped with each other and mango fruit that is partially occluded by the leaves. The combination of texture analysis and morphological operator can isolate the partially overlapped fruit and fruit that are partially occluded by leaves. The parameters derived from RHT method was used to calculate the center of the ellipse. The center of the ellipse acts as the gripping point for the fruit picking robot. As the results, the rate of detection was up to 95% for fruit that is partially overlapped and partially covered by leaves.

Thin-sectioning and microanalysis of individual extraterrestrial particles

NASA Technical Reports Server (NTRS)

Bradley, J. P.

1986-01-01

A long standing constraint on the study of micrometeorites has centered on difficulties in preparing them for analysis. This is due largely to their small dimensions and consequent practical limitations on sample manipulation. Chondritic micrometeorites provide a good example; although much has been learned about their chemistry and mineralogy almost nothing was known about such basic properties as texture and petrographic associations. The only way to assess such properties is to examine microstructure indigenous to the particles. Unfortunately, almost all micrometeorites, out of necessity, have been crushed and dispersed onto appropriate substances prior to analysis, and most information about texture and petrography was lost. Recently, thin-sections of individual extraterrestrial particles have been prepared using an ultramicrotome equipped with a diamond knife. This procedure has been applied to stratospheric micrometeorites and Solar Max impact debris. In both cases the sections have enabled observation of a variety of internal particle features, including textures, porosity, and petrographic associations. The sectioning procedure is described and analysis results for chondritic micrometeoroids and select particles from Solar Max are presented.

COMPARISON OF POND AND RACEWAY PRODUCTION METHODS ON TEXTURE OF CHANNEL CATFISH (Ictalurus punctatus) FILLETS, SHOWING A DEPENDENCY ON SIZE AND FILLET POSITION

USDA-ARS?s Scientific Manuscript database

The objective of this study was to compare the effect of the production environment (pond vs in-pond raceway) on the chemical composition, color, and textural properties of channel catfish fillets. Compositional analysis consisted of percent moisture, lipid, protein, and ash content. Additional sa...

Termite infestation associated with type of soil in pulau pinang, malaysia (isoptera: rhinotermitidae).

PubMed

Majid, Abdul Hafiz Ab; Ahmad, Abu Hassan

2013-12-01

Nine soil samples from nine buildings infested with Coptotermes gestroi in Pulau Pinang, Malaysia, were tested for the type of soil texture. The soil texture analysis procedures used the hydrometer method. Four of nine buildings (44%) yielded loamy sand-type soil, whereas five of nine buildings (56%) contained sandy loam-type soil.

Termite Infestation Associated with Type of Soil in Pulau Pinang, Malaysia (Isoptera: Rhinotermitidae)

PubMed Central

Majid, Abdul Hafiz Ab; Ahmad, Abu Hassan

2013-01-01

Nine soil samples from nine buildings infested with Coptotermes gestroi in Pulau Pinang, Malaysia, were tested for the type of soil texture. The soil texture analysis procedures used the hydrometer method. Four of nine buildings (44%) yielded loamy sand-type soil, whereas five of nine buildings (56%) contained sandy loam-type soil. PMID:24575252

Genetic analysis of grain attributes, milling performance, and end-use quality traits in hard red spring wheat (Triticum aestivum L.)

USDA-ARS?s Scientific Manuscript database

Wheat kernel texture dictates U.S. wheat market class and culinary end-uses. Of interest to wheat breeders is to identify quantitative trait loci (QTL) for wheat kernel texture, milling performance, or end-use quality because it is imperative for wheat breeders to ascertain the genetic architecture ...

Vessel Classification in Cosmo-Skymed SAR Data Using Hierarchical Feature Selection

NASA Astrophysics Data System (ADS)

Makedonas, A.; Theoharatos, C.; Tsagaris, V.; Anastasopoulos, V.; Costicoglou, S.

2015-04-01

SAR based ship detection and classification are important elements of maritime monitoring applications. Recently, high-resolution SAR data have opened new possibilities to researchers for achieving improved classification results. In this work, a hierarchical vessel classification procedure is presented based on a robust feature extraction and selection scheme that utilizes scale, shape and texture features in a hierarchical way. Initially, different types of feature extraction algorithms are implemented in order to form the utilized feature pool, able to represent the structure, material, orientation and other vessel type characteristics. A two-stage hierarchical feature selection algorithm is utilized next in order to be able to discriminate effectively civilian vessels into three distinct types, in COSMO-SkyMed SAR images: cargos, small ships and tankers. In our analysis, scale and shape features are utilized in order to discriminate smaller types of vessels present in the available SAR data, or shape specific vessels. Then, the most informative texture and intensity features are incorporated in order to be able to better distinguish the civilian types with high accuracy. A feature selection procedure that utilizes heuristic measures based on features' statistical characteristics, followed by an exhaustive research with feature sets formed by the most qualified features is carried out, in order to discriminate the most appropriate combination of features for the final classification. In our analysis, five COSMO-SkyMed SAR data with 2.2m x 2.2m resolution were used to analyse the detailed characteristics of these types of ships. A total of 111 ships with available AIS data were used in the classification process. The experimental results show that this method has good performance in ship classification, with an overall accuracy reaching 83%. Further investigation of additional features and proper feature selection is currently in progress.

An Investigation of Dust Storms Observed with the Mars Color Imager

NASA Technical Reports Server (NTRS)

Guzewich, Scott D.; Toigo, Anthony D.; Wang, Huiqun

2017-01-01

Daily global imaging by the Mars Color Imager (MARCI) continues the record of the Mars Orbiter Camera (MOC) and has allowed creation of a long-duration record of Martian dust storms. We observe dust storms over the first two Mars years of the MARCI record, including tracking individual storms over multiple sols, as well as tracking the growth and recession of the seasonal polar caps. Using the combined 6 Mars year record of textured dust storms (storms with visible textures on the observed dust cloud tops), we study the relationship between textured dust storm activity and meteorology (as simulated by the MarsWRF general circulation model) and surface properties. We find that textured dust storms preferentially occur in places and seasons with above average surface wind stress. Textured dust storm occurrence also has a modest linear anti-correlation with surface albedo (0.43) and topography (0.40). Lastly, we perform an empirical orthogonal function (EOF) analysis on the distribution of occurrence of textured dust storms and find that over 50 of the variance in textured dust storm activity can be explained by two EOF modes. We associate the first EOF mode with cap-edge storms just before Ls = 180deg and the second EOF mode with flushing dust storms that occur from Ls = 180-210deg and again near Ls = 320deg.

TU-CD-BRB-08: Radiomic Analysis of FDG-PET Identifies Novel Prognostic Imaging Biomarkers in Locally Advanced Pancreatic Cancer Patients Treated with SBRT

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

Cui, Y; Shirato, H; Song, J

2015-06-15

Purpose: This study aims to identify novel prognostic imaging biomarkers in locally advanced pancreatic cancer (LAPC) using quantitative, high-throughput image analysis. Methods: 86 patients with LAPC receiving chemotherapy followed by SBRT were retrospectively studied. All patients had a baseline FDG-PET scan prior to SBRT. For each patient, we extracted 435 PET imaging features of five types: statistical, morphological, textural, histogram, and wavelet. These features went through redundancy checks, robustness analysis, as well as a prescreening process based on their concordance indices with respect to the relevant outcomes. We then performed principle component analysis on the remaining features (number ranged frommore » 10 to 16), and fitted a Cox proportional hazard regression model using the first 3 principle components. Kaplan-Meier analysis was used to assess the ability to distinguish high versus low-risk patients separated by median predicted survival. To avoid overfitting, all evaluations were based on leave-one-out cross validation (LOOCV), in which each holdout patient was assigned to a risk group according to the model obtained from a separate training set. Results: For predicting overall survival (OS), the most dominant imaging features were wavelet coefficients. There was a statistically significant difference in OS between patients with predicted high and low-risk based on LOOCV (hazard ratio: 2.26, p<0.001). Similar imaging features were also strongly associated with local progression-free survival (LPFS) (hazard ratio: 1.53, p=0.026) on LOOCV. In comparison, neither SUVmax nor TLG was associated with LPFS (p=0.103, p=0.433) (Table 1). Results for progression-free survival and distant progression-free survival showed similar trends. Conclusion: Radiomic analysis identified novel imaging features that showed improved prognostic value over conventional methods. These features characterize the degree of intra-tumor heterogeneity reflected on FDG-PET images, and their biological underpinnings warrant further investigation. If validated in large, prospective cohorts, this method could be used to stratify patients based on individualized risk.« less

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

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.

Topographic Controls on Spatial Patterns of Soil Texture and Moisture in a Semi-arid Montane Catchment with Aspect-Dependent Vegetation

NASA Astrophysics Data System (ADS)

Lehman, B. M.; Niemann, J. D.

2008-12-01

Soil moisture exerts significant control over the partitioning of latent and sensible energy fluxes, the magnitude of both vertical and lateral water fluxes, the physiological and water-use characteristics of vegetation, and nutrient cycling. Considerable progress has been made in determining how soil characteristics, topography, and vegetation influence spatial patterns of soil moisture in humid environments at the catchment, hillslope, and plant scales. However, understanding of the controls on soil moisture patterns beyond the plant scale in semi-arid environments remains more limited. This study examines the relationships between the spatial patterns of near surface soil moisture (upper 5 cm), terrain indices, and soil properties in a small, semi-arid, montane catchment. The 8 ha catchment, located in the Cache La Poudre River Canyon in north-central Colorado, has a total relief of 115 m and an average elevation of 2193 m. It is characterized by steep slopes and shallow, gravelly/sandy soils with scattered granite outcroppings. Depth to bedrock ranges from 0 m to greater than 1 m. Vegetation in the catchment is highly correlated with topographic aspect. In particular, north-facing hillslopes are predominately vegetated by ponderosa pines, while south-facing slopes are mostly vegetated by several shrub species. Soil samples were collected at a 30 m resolution to characterize soil texture and bulk density, and several datasets consisting of more than 300 point measurements of soil moisture were collected using time domain reflectometry (TDR) between Fall 2007 and Summer 2008 at a 15 m resolution. Results from soil textural analysis performed with sieving and the ASTM standard hydrometer method show that soil texture is finer on the north-facing hillslope than on the south-facing hillslope. Cos(aspect) is the best univariate predictor of silts, while slope is the best predictor of coarser fractions up to fine gravel. Bulk density increases with depth but shows no significant relationship with topographic indices. When the catchment average soil moisture is low, the variance of soil moisture increases with the average. When the average is high, the variance remains relatively constant. Little of the variation in soil moisture is explained by topographic indices when the catchment is either very wet or dry; however, when the average soil moisture takes on intermediate values, cos(aspect) is consistently the best predictor among the terrain indices considered.

SAR backscatter from coniferous forest gaps

NASA Technical Reports Server (NTRS)

Day, John L.; Davis, Frank W.

1992-01-01

A study is in progress comparing Airborne Synthetic Aperture Radar (AIRSAR) backscatter from coniferous forest plots containing gaps to backscatter from adjacent gap-free plots. Issues discussed are how do gaps in the range of 400 to 1600 sq m (approximately 4-14 pixels at intermediate incidence angles) affect forest backscatter statistics and what incidence angles, wavelengths, and polarizations are most sensitive to forest gaps. In order to visualize the slant-range imaging of forest and gaps, a simple conceptual model is used. This strictly qualitative model has led us to hypothesize that forest radar returns at short wavelengths (eg., C-band) and large incidence angles (e.g., 50 deg) should be most affected by the presence of gaps, whereas returns at long wavelengths and small angles should be least affected. Preliminary analysis of 1989 AIRSAR data from forest near Mt. Shasta supports the hypothesis. Current forest backscatter models such as MIMICS and Santa Barbara Discontinuous Canopy Backscatter Model have in several cases correctly predicted backscatter from forest stands based on inputs of measured or estimated forest parameters. These models do not, however, predict within-stand SAR scene texture, or 'intrinsic scene variability' as Ulaby et al. has referred to it. For instance, the Santa Barbara model, which may be the most spatially coupled of the existing models, is not truly spatial. Tree locations within a simulated pixel are distributed according to a Poisson process, as they are in many natural forests, but tree size is unrelated to location, which is not the case in nature. Furthermore, since pixels of a simulated stand are generated independently in the Santa Barbara model, spatial processes larger than one pixel are not modeled. Using a different approach, Oliver modeled scene texture based on an hypothetical forest geometry. His simulated scenes do not agree well with SAR data, perhaps due to the simple geometric model used. Insofar as texture is the expression of biological forest processes, such as succession and disease, and physical ones, such as fire and wind-throw, it contains useful information about the forest, and has value in image interpretation and classification. Forest gaps are undoubtedly important contributors to scene variance. By studying the localized effects of gaps on forest backscatter, guided by our qualitative model, we hope to understand more clearly the manner in which spatial heterogeneities in forests produce variations in backscatter, which collectively give rise to scene texture.

Intratumor partitioning and texture analysis of dynamic contrast-enhanced (DCE)-MRI identifies relevant tumor subregions to predict pathological response of breast cancer to neoadjuvant chemotherapy.

PubMed

Wu, Jia; Gong, Guanghua; Cui, Yi; Li, Ruijiang

2016-11-01

To predict pathological response of breast cancer to neoadjuvant chemotherapy (NAC) based on quantitative, multiregion analysis of dynamic contrast enhancement magnetic resonance imaging (DCE-MRI). In this Institutional Review Board-approved study, 35 patients diagnosed with stage II/III breast cancer were retrospectively investigated using 3T DCE-MR images acquired before and after the first cycle of NAC. First, principal component analysis (PCA) was used to reduce the dimensionality of the DCE-MRI data with high temporal resolution. We then partitioned the whole tumor into multiple subregions using k-means clustering based on the PCA-defined eigenmaps. Within each tumor subregion, we extracted four quantitative Haralick texture features based on the gray-level co-occurrence matrix (GLCM). The change in texture features in each tumor subregion between pre- and during-NAC was used to predict pathological complete response after NAC. Three tumor subregions were identified through clustering, each with distinct enhancement characteristics. In univariate analysis, all imaging predictors except one extracted from the tumor subregion associated with fast washout were statistically significant (P < 0.05) after correcting for multiple testing, with area under the receiver operating characteristic (ROC) curve (AUC) or AUCs between 0.75 and 0.80. In multivariate analysis, the proposed imaging predictors achieved an AUC of 0.79 (P = 0.002) in leave-one-out cross-validation. This improved upon conventional imaging predictors such as tumor volume (AUC = 0.53) and texture features based on whole-tumor analysis (AUC = 0.65). The heterogeneity of the tumor subregion associated with fast washout on DCE-MRI predicted pathological response to NAC in breast cancer. J. Magn. Reson. Imaging 2016;44:1107-1115. © 2016 International Society for Magnetic Resonance in Medicine.

Fatigue mechanism of textured Pb(Mg1/3Nb2/3)O3-PbTiO3 ceramics

NASA Astrophysics Data System (ADS)

Yan, Yongke; Zhou, Yuan; Gupta, Shashaank; Priya, Shashank

2013-08-01

Grain orientation, BaTiO3 heterogeneous template content, and electrode materials are expected to play an important role in controlling the polarization fatigue behavior of ⟨001⟩ textured Pb(Mg1/3Nb2/3)O3-PbTiO3 ceramics. A comparative analysis with randomly oriented ceramics showed that ⟨001⟩ grain orientation/texture exhibits improved fatigue characteristics due to the reduced switching activation energy and high domain mobility. The hypothesis was validated from the systematic characterization of polarization—electric field behavior and domain wall density. The defect accumulation at the grain boundary and clamping effect arising from the presence of BaTiO3 heterogeneous template in the final microstructure was found to be the main cause for polarization degradation in textured ceramic.

Nondestructive characterization of textured a-Si:H/c-Si heterojunction solar cell structures with nanometer-scale a-Si:H and In2O3:Sn layers by spectroscopic ellipsometry

NASA Astrophysics Data System (ADS)

Matsuki, Nobuyuki; Fujiwara, Hiroyuki

2013-07-01

Nanometer-scale hydrogenated amorphous silicon (a-Si:H) layers formed on crystalline silicon (c-Si) with pyramid-shaped textures have been characterized by spectroscopic ellipsometry (SE) using a tilt angle measurement configuration, in an attempt to establish a nondestructive method for the structural characterization of the a-Si:H/c-Si heterojunction solar cells. By applying an a-Si:H dielectric function model developed recently, the thickness and SiH2 content of the a-Si:H layer have been determined even on the textured substrates. Furthermore, from the SE analysis incorporating the Drude model, the carrier properties of the In2O3:Sn layers in the textured solar-cell structure have been characterized.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2015-08-01

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

Classification of pre-sliced pork and Turkey ham qualities based on image colour and textural features and their relationships with consumer responses.

PubMed

Iqbal, Abdullah; Valous, Nektarios A; Mendoza, Fernando; Sun, Da-Wen; Allen, Paul

2010-03-01

Images of three qualities of pre-sliced pork and Turkey hams were evaluated for colour and textural features to characterize and classify them, and to model the ham appearance grading and preference responses of a group of consumers. A total of 26 colour features and 40 textural features were extracted for analysis. Using Mahalanobis distance and feature inter-correlation analyses, two best colour [mean of S (saturation in HSV colour space), std. deviation of b*, which indicates blue to yellow in L*a*b* colour space] and three textural features [entropy of b*, contrast of H (hue of HSV colour space), entropy of R (red of RGB colour space)] for pork, and three colour (mean of R, mean of H, std. deviation of a*, which indicates green to red in L*a*b* colour space) and two textural features [contrast of B, contrast of L* (luminance or lightness in L*a*b* colour space)] for Turkey hams were selected as features with the highest discriminant power. High classification performances were reached for both types of hams (>99.5% for pork and >90.5% for Turkey) using the best selected features or combinations of them. In spite of the poor/fair agreement among ham consumers as determined by Kappa analysis (Kappa-value<0.4) for sensory grading (surface colour, colour uniformity, bitonality, texture appearance and acceptability), a dichotomous logistic regression model using the best image features was able to explain the variability of consumers' responses for all sensorial attributes with accuracies higher than 74.1% for pork hams and 83.3% for Turkey hams. Copyright 2009 Elsevier Ltd. All rights reserved.