Shape-Tailored Features and their Application to Texture Segmentation

KAUST Repository

Khan, Naeemullah

2014-04-01

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

Tribological analysis of the ventral scale structure in a Python regius in relation to laser textured surfaces

International Nuclear Information System (INIS)

Abdel-Aal, H A; El Mansori, M

2013-01-01

Laser texturing is one of the leading technologies applied to modify surface topography. To date, however, a standardized procedure to generate deterministic textures is virtually non-existent. In nature, especially in squamata, there are many examples of deterministic structured textures that allow species to control friction and condition their tribological response for efficient function. In this work, we draw a comparison between industrial surfaces and reptilian surfaces. We chose the Python regius species as a bio-analogue with a deterministic surface. We first study the structural make up of the ventral scales of the snake (both construction and metrology). We further compare the metrological features of the ventral scales to experimentally recommended performance indicators of industrial surfaces extracted from open literature. The results indicate the feasibility of engineering a laser textured surface based on the reptilian ornamentation constructs. It is shown that the metrological features, key to efficient function of a rubbing deterministic surface, are already optimized in the reptile. We further show that optimization in reptilian surfaces is based on synchronizing surface form, textures and aspects to condition the frictional response. Mimicking reptilian surfaces, we argue, may form a design methodology potentially capable of generating advanced deterministic surface constructs capable of efficient tribological function. (paper)

Textural features for image classification

Science.gov (United States)

Haralick, R. M.; Dinstein, I.; Shanmugam, K.

1973-01-01

Description of some easily computable textural features based on gray-tone spatial dependances, and illustration of their application in category-identification tasks of three different kinds of image data - namely, photomicrographs of five kinds of sandstones, 1:20,000 panchromatic aerial photographs of eight land-use categories, and ERTS multispectral imagery containing several land-use categories. Two kinds of decision rules are used - one for which the decision regions are convex polyhedra (a piecewise-linear decision rule), and one for which the decision regions are rectangular parallelpipeds (a min-max decision rule). In each experiment the data set was divided into two parts, a training set and a test set. Test set identification accuracy is 89% for the photomicrographs, 82% for the aerial photographic imagery, and 83% for the satellite imagery. These results indicate that the easily computable textural features probably have a general applicability for a wide variety of image-classification applications.

Model-Based Learning of Local Image Features for Unsupervised Texture Segmentation

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Kiechle, Martin; Storath, Martin; Weinmann, Andreas; Kleinsteuber, Martin

2018-04-01

Features that capture well the textural patterns of a certain class of images are crucial for the performance of texture segmentation methods. The manual selection of features or designing new ones can be a tedious task. Therefore, it is desirable to automatically adapt the features to a certain image or class of images. Typically, this requires a large set of training images with similar textures and ground truth segmentation. In this work, we propose a framework to learn features for texture segmentation when no such training data is available. The cost function for our learning process is constructed to match a commonly used segmentation model, the piecewise constant Mumford-Shah model. This means that the features are learned such that they provide an approximately piecewise constant feature image with a small jump set. Based on this idea, we develop a two-stage algorithm which first learns suitable convolutional features and then performs a segmentation. We note that the features can be learned from a small set of images, from a single image, or even from image patches. The proposed method achieves a competitive rank in the Prague texture segmentation benchmark, and it is effective for segmenting histological images.

Classification of interstitial lung disease patterns with topological texture features

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

2010-03-01

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

Breast density pattern characterization by histogram features and texture descriptors

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Pedro Cunha Carneiro

2017-04-01

Full Text Available Abstract Introduction Breast cancer is the first leading cause of death for women in Brazil as well as in most countries in the world. Due to the relation between the breast density and the risk of breast cancer, in medical practice, the breast density classification is merely visual and dependent on professional experience, making this task very subjective. The purpose of this paper is to investigate image features based on histograms and Haralick texture descriptors so as to separate mammographic images into categories of breast density using an Artificial Neural Network. Methods We used 307 mammographic images from the INbreast digital database, extracting histogram features and texture descriptors of all mammograms and selecting them with the K-means technique. Then, these groups of selected features were used as inputs of an Artificial Neural Network to classify the images automatically into the four categories reported by radiologists. Results An average accuracy of 92.9% was obtained in a few tests using only some of the Haralick texture descriptors. Also, the accuracy rate increased to 98.95% when texture descriptors were mixed with some features based on a histogram. Conclusion Texture descriptors have proven to be better than gray levels features at differentiating the breast densities in mammographic images. From this paper, it was possible to automate the feature selection and the classification with acceptable error rates since the extraction of the features is suitable to the characteristics of the images involving the problem.

Relevance of echo-structure and texture features

DEFF Research Database (Denmark)

Karemore, Gopal; Mullick, Jhinuk Basu; KV, Dr. Rajagopal

2010-01-01

Aim: Echostructure is an essential parameter for the evaluation of circumscribed lesions and can be described as a texture feature on ultrasound images. Present study evaluates the possibility of distinguishing between benign and malignant breast tumors using various texture features. Materials...... and Methods: 58 cases of breast tumor (29 each from benign and malignant) were documented under standardized conditions using a linear array machine and 7.5 MHz transducer. In each sonographic image, ROI of tumor was marked and then subjected to the evaluation of tumor status using five parameters of second...... performance ROC= 0.78(pbenign and malignant tumors. It also reveals that when evaluating images of a breast tumor...

Texture Feature Extraction and Classification for Iris Diagnosis

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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.

Dominant color and texture feature extraction for banknote discrimination

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Wang, Junmin; Fan, Yangyu; Li, Ning

2017-07-01

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

Pedestrian count estimation using texture feature with spatial distribution

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Hongyu Hu

2016-12-01

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

Classification of Textures Using Filter Based Local Feature Extraction

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Bocekci Veysel Gokhan

2016-01-01

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

T2-weighted MRI-derived textural features reflect prostate cancer aggressiveness: preliminary results.

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Nketiah, Gabriel; Elschot, Mattijs; Kim, Eugene; Teruel, Jose R; Scheenen, Tom W; Bathen, Tone F; Selnæs, Kirsten M

2017-07-01

To evaluate the diagnostic relevance of T2-weighted (T2W) MRI-derived textural features relative to quantitative physiological parameters derived from diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI in Gleason score (GS) 3+4 and 4+3 prostate cancers. 3T multiparametric-MRI was performed on 23 prostate cancer patients prior to prostatectomy. Textural features [angular second moment (ASM), contrast, correlation, entropy], apparent diffusion coefficient (ADC), and DCE pharmacokinetic parameters (K trans and V e ) were calculated from index tumours delineated on the T2W, DW, and DCE images, respectively. The association between the textural features and prostatectomy GS and the MRI-derived parameters, and the utility of the parameters in differentiating between GS 3+4 and 4+3 prostate cancers were assessed statistically. ASM and entropy correlated significantly (p textural features correlated insignificantly with K trans and V e . GS 4+3 cancers had significantly lower ASM and higher entropy than 3+4 cancers, but insignificant differences in median ADC, K trans , and V e . The combined texture-MRI parameters yielded higher classification accuracy (91%) than the individual parameter sets. T2W MRI-derived textural features could serve as potential diagnostic markers, sensitive to the pathological differences in prostate cancers. • T2W MRI-derived textural features correlate significantly with Gleason score and ADC. • T2W MRI-derived textural features differentiate Gleason score 3+4 from 4+3 cancers. • T2W image textural features could augment tumour characterization.

Effect of texture randomization on the slip and interfacial robustness in turbulent flows over superhydrophobic surfaces

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Seo, Jongmin; Mani, Ali

2018-04-01

Superhydrophobic surfaces demonstrate promising potential for skin friction reduction in naval and hydrodynamic applications. Recent developments of superhydrophobic surfaces aiming for scalable applications use random distribution of roughness, such as spray coating and etched process. However, most previous analyses of the interaction between flows and superhydrophobic surfaces studied periodic geometries that are economically feasible only in laboratory-scale experiments. In order to assess the drag reduction effectiveness as well as interfacial robustness of superhydrophobic surfaces with randomly distributed textures, we conduct direct numerical simulations of turbulent flows over randomly patterned interfaces considering a range of texture widths w+≈4 -26 , and solid fractions ϕs=11 %-25 % . Slip and no-slip boundary conditions are implemented in a pattern, modeling the presence of gas-liquid interfaces and solid elements. Our results indicate that slip of randomly distributed textures under turbulent flows is about 30 % less than those of surfaces with aligned features of the same size. In the small texture size limit w+≈4 , the slip length of the randomly distributed textures in turbulent flows is well described by a previously introduced Stokes flow solution of randomly distributed shear-free holes. By comparing DNS results for patterned slip and no-slip boundary against the corresponding homogenized slip length boundary conditions, we show that turbulent flows over randomly distributed posts can be represented by an isotropic slip length in streamwise and spanwise direction. The average pressure fluctuation on a gas pocket is similar to that of the aligned features with the same texture size and gas fraction, but the maximum interface deformation at the leading edge of the roughness element is about twice as large when the textures are randomly distributed. The presented analyses provide insights on implications of texture randomness on drag

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

International Nuclear Information System (INIS)

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

2015-01-01

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

Quantitative Characterisation of Surface Texture

DEFF Research Database (Denmark)

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

2000-01-01

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

Influence of surface roughness on the friction property of textured surface

OpenAIRE

Yuankai Zhou; Hua Zhu; Wenqian Zhang; Xue Zuo; Yan Li; Jianhua Yang

2015-01-01

In contrast with dimple textures, surface roughness is a texture at the micro-scale, essentially which will influence the load-bearing capacity of lubricant film. The numerical simulation was carried out to investigate the influence of surface roughness on friction property of textured surface. The lubricant film pressure was obtained using the method of computational fluid dynamics according to geometric model of round dimple, and the renormalization-group k–ε turbulent model was adopted in ...

Parametric classification of handvein patterns based on texture features

Science.gov (United States)

Al Mahafzah, Harbi; Imran, Mohammad; Supreetha Gowda H., D.

2018-04-01

In this paper, we have developed Biometric recognition system adopting hand based modality Handvein,which has the unique pattern for each individual and it is impossible to counterfeit and fabricate as it is an internal feature. We have opted in choosing feature extraction algorithms such as LBP-visual descriptor, LPQ-blur insensitive texture operator, Log-Gabor-Texture descriptor. We have chosen well known classifiers such as KNN and SVM for classification. We have experimented and tabulated results of single algorithm recognition rate for Handvein under different distance measures and kernel options. The feature level fusion is carried out which increased the performance level.

Inline inspection of textured plastics surfaces

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Michaeli, Walter; Berdel, Klaus

2011-02-01

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

Spin texture of the surface state of three-dimensional Dirac material Ca3PbO

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Kariyado, Toshikaze

2015-04-01

The bulk and surface electronic structures of a candidate three-dimensional Dirac material Ca3PbO and its family are discussed especially focusing on the spin texture on the surface states. We first explain the basic features of the bulk band structure of Ca3PbO, such as emergence of Dirac fermions near the Fermi energy, and compare it with the other known three-dimensional Dirac semimetals. Then, the surface bands and spin-texture on them are investigated in detail. It is shown that the surface bands exhibit strong momentum-spin locking, which may be useful in some application for spin manipulation, induced by a combination of the inversion symmetry breaking at the surface and the strong spin-orbit coupling of Pb atoms. The surface band structure and the spin-textures are sensitive to the surface types.

Spin texture of the surface state of three-dimensional Dirac material Ca3PbO

International Nuclear Information System (INIS)

Kariyado, Toshikaze

2015-01-01

The bulk and surface electronic structures of a candidate three-dimensional Dirac material Ca 3 PbO and its family are discussed especially focusing on the spin texture on the surface states. We first explain the basic features of the bulk band structure of Ca 3 PbO, such as emergence of Dirac fermions near the Fermi energy, and compare it with the other known three-dimensional Dirac semimetals. Then, the surface bands and spin-texture on them are investigated in detail. It is shown that the surface bands exhibit strong momentum-spin locking, which may be useful in some application for spin manipulation, induced by a combination of the inversion symmetry breaking at the surface and the strong spin-orbit coupling of Pb atoms. The surface band structure and the spin-textures are sensitive to the surface types. (paper)

Prostate cancer detection: Fusion of cytological and textural features.

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Nguyen, Kien; Jain, Anil K; Sabata, Bikash

2011-01-01

A computer-assisted system for histological prostate cancer diagnosis can assist pathologists in two stages: (i) to locate cancer regions in a large digitized tissue biopsy, and (ii) to assign Gleason grades to the regions detected in stage 1. Most previous studies on this topic have primarily addressed the second stage by classifying the preselected tissue regions. In this paper, we address the first stage by presenting a cancer detection approach for the whole slide tissue image. We propose a novel method to extract a cytological feature, namely the presence of cancer nuclei (nuclei with prominent nucleoli) in the tissue, and apply this feature to detect the cancer regions. Additionally, conventional image texture features which have been widely used in the literature are also considered. The performance comparison among the proposed cytological textural feature combination method, the texture-based method and the cytological feature-based method demonstrates the robustness of the extracted cytological feature. At a false positive rate of 6%, the proposed method is able to achieve a sensitivity of 78% on a dataset including six training images (each of which has approximately 4,000×7,000 pixels) and 1 1 whole-slide test images (each of which has approximately 5,000×23,000 pixels). All images are at 20X magnification.

A Study of Feature Extraction Using Divergence Analysis of Texture Features

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

1982-01-01

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

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

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Pattichis Marios S

2007-11-01

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

Application of textural features to the objective diagnosis of Alzheimer-type dementia

International Nuclear Information System (INIS)

Kodama, Naoki; Shimada, Tetsuo; Kaeriyama, Tomoharu; Kaneko, Tomoyuki; Fukumoto, Ichiro; Kobayashi, Yoshio

2003-01-01

In this study, patients with Alzheimer-type dementia were compared with healthy elderly individuals by means of 13 textural features to evaluate the application of these features to the objective diagnosis of the dementia. A statistically significant difference was found in 8 of the 13 textural features between dementia patients and healthy controls. Discriminant analysis using the eight features demonstrated a sensitivity of 91.2% and a specificity of 86.4%, with an overall accuracy of 89.1%. Multiple discriminant analysis using the eight features by dementia stage showed an overall accuracy of 78.2% for discrimination of four stages. These results indicate that quantitative textural feature measurements can be used as an objective diagnostic technique for Alzheimer-type dementia. (author)

Prostate cancer detection: Fusion of cytological and textural features

Directory of Open Access Journals (Sweden)

Kien Nguyen

2011-01-01

Full Text Available A computer-assisted system for histological prostate cancer diagnosis can assist pathologists in two stages: (i to locate cancer regions in a large digitized tissue biopsy, and (ii to assign Gleason grades to the regions detected in stage 1. Most previous studies on this topic have primarily addressed the second stage by classifying the preselected tissue regions. In this paper, we address the first stage by presenting a cancer detection approach for the whole slide tissue image. We propose a novel method to extract a cytological feature, namely the presence of cancer nuclei (nuclei with prominent nucleoli in the tissue, and apply this feature to detect the cancer regions. Additionally, conventional image texture features which have been widely used in the literature are also considered. The performance comparison among the proposed cytological textural feature combination method, the texture-based method and the cytological feature-based method demonstrates the robustness of the extracted cytological feature. At a false positive rate of 6%, the proposed method is able to achieve a sensitivity of 78% on a dataset including six training images (each of which has approximately 4,000x7,000 pixels and 1 1 whole-slide test images (each of which has approximately 5,000x23,000 pixels. All images are at 20X magnification.

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

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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.

SEGMENTATION OF POLARIMETRIC SAR IMAGES USIG WAVELET TRANSFORMATION AND TEXTURE FEATURES

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A. Rezaeian

2015-12-01

Full Text Available Polarimetric Synthetic Aperture Radar (PolSAR sensors can collect useful observations from earth’s surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT. Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.

Segmentation of Polarimetric SAR Images Usig Wavelet Transformation and Texture Features

Science.gov (United States)

Rezaeian, A.; Homayouni, S.; Safari, A.

2015-12-01

Polarimetric Synthetic Aperture Radar (PolSAR) sensors can collect useful observations from earth's surfaces and phenomena for various remote sensing applications, such as land cover mapping, change and target detection. These data can be acquired without the limitations of weather conditions, sun illumination and dust particles. As result, SAR images, and in particular Polarimetric SAR (PolSAR) are powerful tools for various environmental applications. Unlike the optical images, SAR images suffer from the unavoidable speckle, which causes the segmentation of this data difficult. In this paper, we use the wavelet transformation for segmentation of PolSAR images. Our proposed method is based on the multi-resolution analysis of texture features is based on wavelet transformation. Here, we use the information of gray level value and the information of texture. First, we produce coherency or covariance matrices and then generate span image from them. In the next step of proposed method is texture feature extraction from sub-bands is generated from discrete wavelet transform (DWT). Finally, PolSAR image are segmented using clustering methods as fuzzy c-means (FCM) and k-means clustering. We have applied the proposed methodology to full polarimetric SAR images acquired by the Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) L-band system, during July, in 2012 over an agricultural area in Winnipeg, Canada.

The structure of surface texture knowledge

International Nuclear Information System (INIS)

Yan Wang; Scott, Paul J; Jiang Xiangqian

2005-01-01

This research aims to create an intelligent knowledge-based system for engineering and bio-medical engineering surface texture, which will provide expert knowledge of surface texture to link surface function, specification of micro- and nano-geometry through manufacture, and verification. The intelligent knowledge base should be capable of incorporating knowledge from multiple sources (standards, books, experts, etc), adding new knowledge from these sources and still remain a coherent reliable system. A new data model based on category theory will be adopted to construct this system

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

Science.gov (United States)

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

2011-04-01

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

Laser surface textured titanium alloy (Ti–6Al–4V): Part 1 – Surface characterization

Energy Technology Data Exchange (ETDEWEB)

Pfleging, Wilhelm [Karlsruhe Institute of Technology, IAM-AWP, P.O. Box 3640, 76021 Karlsruhe (Germany); Karlsruhe Nano Micro Facility, H.-von-Helmholtz-Pl. 1, 76344 Egg.-Leopoldshafen (Germany); Kumari, Renu [Department of Metal. and Maters. Eng., I. I. T. Kharagpur, WB 721302 (India); Besser, Heino [Karlsruhe Institute of Technology, IAM-AWP, P.O. Box 3640, 76021 Karlsruhe (Germany); Scharnweber, Tim [Karlsruhe Institute of Technology, IBG-1, P.O. Box 3640, 76021 Karlsruhe (Germany); Majumdar, Jyotsna Dutta, E-mail: jyotsna@metal.iitkgp.ernet.in [Department of Metal. and Maters. Eng., I. I. T. Kharagpur, WB 721302 (India)

2015-11-15

Highlights: • Texturing of Ti–6Al–4V with linear and dimple patterns are developed with ArF laser. • Linear textures have width of 25 μm and are at an interval of 20 μm. • Dimple textures are equi-spaced and have a diameter of 60 μm. • Significant refinement of microstructure in textured zone as compared to substrate. • Increased wettability of the textured surface against simulated body fluid. - Abstract: In the present study, a detailed study of the characterization of laser-surface textured titanium alloy (Ti–6Al–4V) with line and dimple geometry developed by using an ArF excimer laser operating at a wavelength of 193 nm with a pulse length of 5 ns is undertaken. The characterization of the textured surface (both the top surface and cross section) is carried out by scanning electron microscopy, electron back scattered diffraction (EBSD) technique and X-ray diffraction techniques. There is refinement of microstructure along with presence of titanium oxides (rutile, anatase and few Ti{sub 2}O{sub 3} phase) in the textured surface as compared to as-received one. The area fractions of linear texture and dimple texture measured by image analysis software are 45% and 20%, respectively. The wettability is increased after laser texturing. The total surface energy is decreased due to linear (29.6 mN/m) texturing and increased due to dimple (67.6 mN/m) texturing as compared to as-received Ti–6Al–4V (37 mN/m). The effect of polar component is more in influencing the surface energy of textured surface.

Laser surface textured titanium alloy (Ti–6Al–4V): Part 1 – Surface characterization

International Nuclear Information System (INIS)

Pfleging, Wilhelm; Kumari, Renu; Besser, Heino; Scharnweber, Tim; Majumdar, Jyotsna Dutta

2015-01-01

Highlights: • Texturing of Ti–6Al–4V with linear and dimple patterns are developed with ArF laser. • Linear textures have width of 25 μm and are at an interval of 20 μm. • Dimple textures are equi-spaced and have a diameter of 60 μm. • Significant refinement of microstructure in textured zone as compared to substrate. • Increased wettability of the textured surface against simulated body fluid. - Abstract: In the present study, a detailed study of the characterization of laser-surface textured titanium alloy (Ti–6Al–4V) with line and dimple geometry developed by using an ArF excimer laser operating at a wavelength of 193 nm with a pulse length of 5 ns is undertaken. The characterization of the textured surface (both the top surface and cross section) is carried out by scanning electron microscopy, electron back scattered diffraction (EBSD) technique and X-ray diffraction techniques. There is refinement of microstructure along with presence of titanium oxides (rutile, anatase and few Ti_2O_3 phase) in the textured surface as compared to as-received one. The area fractions of linear texture and dimple texture measured by image analysis software are 45% and 20%, respectively. The wettability is increased after laser texturing. The total surface energy is decreased due to linear (29.6 mN/m) texturing and increased due to dimple (67.6 mN/m) texturing as compared to as-received Ti–6Al–4V (37 mN/m). The effect of polar component is more in influencing the surface energy of textured surface.

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

Science.gov (United States)

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

2016-12-01

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

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

International Nuclear Information System (INIS)

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

2014-01-01

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

Dynamic facial expression recognition based on geometric and texture features

Science.gov (United States)

Li, Ming; Wang, Zengfu

2018-04-01

Recently, dynamic facial expression recognition in videos has attracted growing attention. In this paper, we propose a novel dynamic facial expression recognition method by using geometric and texture features. In our system, the facial landmark movements and texture variations upon pairwise images are used to perform the dynamic facial expression recognition tasks. For one facial expression sequence, pairwise images are created between the first frame and each of its subsequent frames. Integration of both geometric and texture features further enhances the representation of the facial expressions. Finally, Support Vector Machine is used for facial expression recognition. Experiments conducted on the extended Cohn-Kanade database show that our proposed method can achieve a competitive performance with other methods.

Influence of surface roughness on the friction property of textured surface

Directory of Open Access Journals (Sweden)

Yuankai Zhou

2015-02-01

Full Text Available In contrast with dimple textures, surface roughness is a texture at the micro-scale, essentially which will influence the load-bearing capacity of lubricant film. The numerical simulation was carried out to investigate the influence of surface roughness on friction property of textured surface. The lubricant film pressure was obtained using the method of computational fluid dynamics according to geometric model of round dimple, and the renormalization-group k–ε turbulent model was adopted in the computation. The numerical simulation results suggest that there is an optimum dimensionless surface roughness, and near this value, the maximum load-bearing capacity can be achieved. The load-bearing capacity is determined by the surface texture, the surface roughness, and the interaction between them. To get information of friction coefficient, the experiments were conducted. This experiment was used to evaluate the simulation. The experimental results show that for the frequency of 4 and 6 Hz, friction coefficient decreases at first and then increases with decreasing surface roughness, which indicates that there exists the optimum region of surface roughness leading to the best friction reduction effect, and it becomes larger when area fractions increase from 2% to 10%. The experimental results agree well with the simulation results.

SAR Image Classification Based on Its Texture Features

Institute of Scientific and Technical Information of China (English)

LI Pingxiang; FANG Shenghui

2003-01-01

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

Low-Level Color and Texture Feature Extraction of Coral Reef Components

Directory of Open Access Journals (Sweden)

Ma. Sheila Angeli Marcos

2003-06-01

Full Text Available The purpose of this study is to develop a computer-based classifier that automates coral reef assessmentfrom digitized underwater video. We extract low-level color and texture features from coral images toserve as input to a high-level classifier. Low-level features for color were labeled blue, green, yellow/brown/orange, and gray/white, which are described by the normalized chromaticity histograms of thesemajor colors. The color matching capability of these features was determined through a technique called“Histogram Backprojection”. The low-level texture feature marks a region as coarse or fine dependingon the gray-level variance of the region.

T2-weighted MRI-derived textural features reflect prostate cancer aggressiveness: preliminary results

Energy Technology Data Exchange (ETDEWEB)

Nketiah, Gabriel; Elschot, Mattijs; Kim, Eugene; Teruel, Jose R. [NTNU, Norwegian University of Science and Technology, Department of Circulation and Medical Imaging, Faculty of Medicine, Trondheim (Norway); Scheenen, Tom W. [Radboud University Medical Center, Department of Radiology and Nuclear Medicine, Nijmegen (Netherlands); Bathen, Tone F.; Selnaes, Kirsten M. [NTNU, Norwegian University of Science and Technology, Department of Circulation and Medical Imaging, Faculty of Medicine, Trondheim (Norway); St. Olavs Hospital, Trondheim University Hospital, Trondheim (Norway)

2017-07-15

To evaluate the diagnostic relevance of T2-weighted (T2W) MRI-derived textural features relative to quantitative physiological parameters derived from diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI in Gleason score (GS) 3+4 and 4+3 prostate cancers. 3T multiparametric-MRI was performed on 23 prostate cancer patients prior to prostatectomy. Textural features [angular second moment (ASM), contrast, correlation, entropy], apparent diffusion coefficient (ADC), and DCE pharmacokinetic parameters (K{sup trans} and V{sub e}) were calculated from index tumours delineated on the T2W, DW, and DCE images, respectively. The association between the textural features and prostatectomy GS and the MRI-derived parameters, and the utility of the parameters in differentiating between GS 3+4 and 4+3 prostate cancers were assessed statistically. ASM and entropy correlated significantly (p < 0.05) with both GS and median ADC. Contrast correlated moderately with median ADC. The textural features correlated insignificantly with K{sup trans} and V{sub e}. GS 4+3 cancers had significantly lower ASM and higher entropy than 3+4 cancers, but insignificant differences in median ADC, K{sup trans}, and V{sub e}. The combined texture-MRI parameters yielded higher classification accuracy (91%) than the individual parameter sets. T2W MRI-derived textural features could serve as potential diagnostic markers, sensitive to the pathological differences in prostate cancers. (orig.)

Significance of MPEG-7 textural features for improved mass detection in mammography.

Science.gov (United States)

Eltonsy, Nevine H; Tourassi, Georgia D; Fadeev, Aleksey; Elmaghraby, Adel S

2006-01-01

The purpose of the study is to investigate the significance of MPEG-7 textural features for improving the detection of masses in screening mammograms. The detection scheme was originally based on morphological directional neighborhood features extracted from mammographic regions of interest (ROIs). Receiver Operating Characteristics (ROC) was performed to evaluate the performance of each set of features independently and merged into a back-propagation artificial neural network (BPANN) using the leave-one-out sampling scheme (LOOSS). The study was based on a database of 668 mammographic ROIs (340 depicting cancer regions and 328 depicting normal parenchyma). Overall, the ROC area index of the BPANN using the directional morphological features was Az=0.85+/-0.01. The MPEG-7 edge histogram descriptor-based BPNN showed an ROC area index of Az=0.71+/-0.01 while homogeneous textural descriptors using 30 and 120 channels helped the BPNN achieve similar ROC area indexes of Az=0.882+/-0.02 and Az=0.877+/-0.01 respectively. After merging the MPEG-7 homogeneous textural features with the directional neighborhood features the performance of the BPANN increased providing an ROC area index of Az=0.91+/-0.01. MPEG-7 homogeneous textural descriptor significantly improved the morphology-based detection scheme.

Texture Analysis of Hydrophobic Polycarbonate and Polydimethylsiloxane Surfaces via Persistent Homology

Directory of Open Access Journals (Sweden)

Ali Nabi Duman

2017-09-01

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

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

DEFF Research Database (Denmark)

Galavis, P.E.; Hollensen, Christian; Jallow, N.

2010-01-01

Background. Characterization of textural features (spatial distributions of image intensity levels) has been considered as a tool for automatic tumor segmentation. The purpose of this work is to study the variability of the textural features in PET images due to different acquisition modes...... reconstruction parameters. Lesions were segmented on a default image using the threshold of 40% of maximum SUV. Fifty different texture features were calculated inside the tumors. The range of variations of the features were calculated with respect to the average value. Results. Fifty textural features were...... classified based on the range of variation in three categories: small, intermediate and large variability. Features with small variability (range 30%). Conclusion. Textural features such as entropy-first order, energy, maximal correlation coefficient, and low-gray level run emphasis exhibited small...

Development of measurement standards for verifying functional performance of surface texture measuring instruments

Energy Technology Data Exchange (ETDEWEB)

Fujii, A [Life and Industrial Product Development Department Olympus Corporation, 2951 Ishikawa-machi, Hachiouji-shi, Tokyo (Japan); Suzuki, H [Industrial Marketing and Planning Department Olympus Corporation, Shinjyuku Monolith, 3-1 Nishi-Shinjyuku 2-chome, Tokyo (Japan); Yanagi, K, E-mail: a_fujii@ot.olympus.co.jp [Department of Mechanical Engineering, Nagaoka University of Technology, 1603-1 Kamitomioka-machi, Nagaoka-shi, Niigata (Japan)

2011-08-19

A new measurement standard is proposed for verifying overall functional performance of surface texture measuring instruments. Its surface is composed of sinusoidal surface waveforms of chirp signals along horizontal cross sections of the material measure. One of the notable features is that the amplitude of each cycle in the chirp signal form is geometrically modulated so that the maximum slope is kept constant. The maximum slope of the chirp-like signal is gradually decreased according to movement in the lateral direction. We fabricated the measurement standard by FIB processing, and it was calibrated by AFM. We tried to evaluate the functional performance of Laser Scanning Microscope by this standard in terms of amplitude response with varying slope angles. As a result, it was concluded that the proposed standard can easily evaluate the performance of surface texture measuring instruments.

Control and characterization of textured, hydrophobic ionomer surfaces

Science.gov (United States)

Wang, Xueyuan

Polymer thin films are of increasing interest in many industrial and technological applications. Superhydrophobic, self-cleaning surfaces have attracted a lot of attention for their application in self-cleaning, anti-sticking coatings, stain resistance, or anti-contamination surfaces in diverse technologies, including medical, transportation, textiles, electronics and paints. This thesis focuses on the preparation of nanometer to micrometer-size particle textured surfaces which are desirable for super water repellency. Textured surfaces consisting of nanometer to micrometer-sized lightly sulfonated polystyrene ionomer (SPS) particles were prepared by rapid evaporation of the solvent from a dilute polymer solution cast onto silica. The effect of the solvent used to spin coat the film, the molecular weight of the ionomer, and the rate of solvent evaporation were investigated. The nano-particle or micron-particle textured ionomer surfaces were prepared by either spin coating or solution casting ionomer solutions at controlled evaporation rates. The surface morphologies were consistent with a spinodal decomposition mechanism where the surface first existed as a percolated-like structure and then ripened into droplets if molecular mobility was retained for sufficient time. The SPS particles or particle aggregates were robust and resisted deformation even after annealing at 120°C for one week. The water contact angles on as-prepared surfaces were relatively low, ~ 90° since the polar groups in ionomer reduce the surface hydrophobicity. After chemical vapor deposition of 1H,1H,2H,2H-perfluorooctyltrichlorosilane, the surface contact angles increased to ~ 109° on smooth surfaces and ~140° on the textured surfaces. Water droplets stuck to these surfaces even when tilted 90 degrees. Superhydrophobic surfaces were prepared by spraying coating ionomer solutions and Chemical Vapor Deposition (CVD) of 1H,1H,2H,2H-perfluorooctyltrichlorosilane onto textured surfaces. The

Light scattering effect of ITO:Zr/AZO films deposited on periodic textured glass surface morphologies for silicon thin film solar cells

Energy Technology Data Exchange (ETDEWEB)

Hussain, Shahzada Qamar [Sungkyunkwan University, Department of Energy Science, Suwon (Korea, Republic of); COMSATS Institute of Information Technology, Department of Physics, Lahore (Pakistan); Kwon, Gi Duk; Kim, Sunbo; Balaji, Nagarajan; Shin, Chonghoon; Kim, Sangho; Khan, Shahbaz; Pribat, Didier [Sungkyunkwan University, Department of Energy Science, Suwon (Korea, Republic of); Ahn, Shihyun; Le, Anh Huy Tuan; Park, Hyeongsik; Raja, Jayapal; Lee, Youn-Jung [Sungkyunkwan University, College of Information and Communication Engineering, Suwon (Korea, Republic of); Razaq, Aamir [COMSATS Institute of Information Technology, Department of Physics, Lahore (Pakistan); Velumani, S. [Sungkyunkwan University, College of Information and Communication Engineering, Suwon (Korea, Republic of); Department of Electrical Engineering (SEES), Mexico City (Mexico); Yi, Junsin [Sungkyunkwan University, Department of Energy Science, Suwon (Korea, Republic of); Sungkyunkwan University, College of Information and Communication Engineering, Suwon (Korea, Republic of)

2015-09-15

Various SF{sub 6}/Ar plasma-textured periodic glass surface morphologies for high transmittance, haze ratio and low sheet resistance of ITO:Zr films are reported. The SF{sub 6}/Ar plasma-textured glass surface morphologies were changed from low aspect ratio to high aspect ratio with the increase in RF power from 500 to 600 W. The micro- and nano-size features of textured glass surface morphologies enhanced the haze ratio in visible as well as NIR wavelength region. Micro-size textured features also influenced the sheet resistance and electrical characteristics of ITO:Zr films due to step coverage. The ITO:Zr/AZO bilayer was used as front TCO electrode for p-i-n amorphous silicon thin film solar cells with current density-voltage characteristics as: V{sub oc} = 875 mV, FF = 70.90 %, J{sub sc} = 11.31 mA/cm{sup 2}, η = 7.02 %. (orig.)

Histogram-based adaptive gray level scaling for texture feature classification of colorectal polyps

Science.gov (United States)

Pomeroy, Marc; Lu, Hongbing; Pickhardt, Perry J.; Liang, Zhengrong

2018-02-01

Texture features have played an ever increasing role in computer aided detection (CADe) and diagnosis (CADx) methods since their inception. Texture features are often used as a method of false positive reduction for CADe packages, especially for detecting colorectal polyps and distinguishing them from falsely tagged residual stool and healthy colon wall folds. While texture features have shown great success there, the performance of texture features for CADx have lagged behind primarily because of the more similar features among different polyps types. In this paper, we present an adaptive gray level scaling and compare it to the conventional equal-spacing of gray level bins. We use a dataset taken from computed tomography colonography patients, with 392 polyp regions of interest (ROIs) identified and have a confirmed diagnosis through pathology. Using the histogram information from the entire ROI dataset, we generate the gray level bins such that each bin contains roughly the same number of voxels Each image ROI is the scaled down to two different numbers of gray levels, using both an equal spacing of Hounsfield units for each bin, and our adaptive method. We compute a set of texture features from the scaled images including 30 gray level co-occurrence matrix (GLCM) features and 11 gray level run length matrix (GLRLM) features. Using a random forest classifier to distinguish between hyperplastic polyps and all others (adenomas and adenocarcinomas), we find that the adaptive gray level scaling can improve performance based on the area under the receiver operating characteristic curve by up to 4.6%.

MRI texture features as biomarkers to predict MGMT methylation status in glioblastomas

Energy Technology Data Exchange (ETDEWEB)

Korfiatis, Panagiotis; Kline, Timothy L.; Erickson, Bradley J., E-mail: bje@mayo.edu [Department of Radiology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Coufalova, Lucie [Department of Radiology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Department of Neurosurgery of First Faculty of Medicine, Charles University in Prague, Military University Hospital, Prague 128 21 (Czech Republic); International Clinical Research Center, St. Anne’s University Hospital Brno, Brno 656 91 (Czech Republic); Lachance, Daniel H. [Department of Neurology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Parney, Ian F. [Department of Neurologic Surgery, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Carter, Rickey E. [Department of Health Sciences Research, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States); Buckner, Jan C. [Department of Medical Oncology, Mayo Clinic, 200 1st Street SW, Rochester, Minnesota 55905 (United States)

2016-06-15

Purpose: Imaging biomarker research focuses on discovering relationships between radiological features and histological findings. In glioblastoma patients, methylation of the O{sup 6}-methylguanine methyltransferase (MGMT) gene promoter is positively correlated with an increased effectiveness of current standard of care. In this paper, the authors investigate texture features as potential imaging biomarkers for capturing the MGMT methylation status of glioblastoma multiforme (GBM) tumors when combined with supervised classification schemes. Methods: A retrospective study of 155 GBM patients with known MGMT methylation status was conducted. Co-occurrence and run length texture features were calculated, and both support vector machines (SVMs) and random forest classifiers were used to predict MGMT methylation status. Results: The best classification system (an SVM-based classifier) had a maximum area under the receiver-operating characteristic (ROC) curve of 0.85 (95% CI: 0.78–0.91) using four texture features (correlation, energy, entropy, and local intensity) originating from the T2-weighted images, yielding at the optimal threshold of the ROC curve, a sensitivity of 0.803 and a specificity of 0.813. Conclusions: Results show that supervised machine learning of MRI texture features can predict MGMT methylation status in preoperative GBM tumors, thus providing a new noninvasive imaging biomarker.

MRI texture features as biomarkers to predict MGMT methylation status in glioblastomas

International Nuclear Information System (INIS)

Korfiatis, Panagiotis; Kline, Timothy L.; Erickson, Bradley J.; Coufalova, Lucie; Lachance, Daniel H.; Parney, Ian F.; Carter, Rickey E.; Buckner, Jan C.

2016-01-01

Purpose: Imaging biomarker research focuses on discovering relationships between radiological features and histological findings. In glioblastoma patients, methylation of the O 6 -methylguanine methyltransferase (MGMT) gene promoter is positively correlated with an increased effectiveness of current standard of care. In this paper, the authors investigate texture features as potential imaging biomarkers for capturing the MGMT methylation status of glioblastoma multiforme (GBM) tumors when combined with supervised classification schemes. Methods: A retrospective study of 155 GBM patients with known MGMT methylation status was conducted. Co-occurrence and run length texture features were calculated, and both support vector machines (SVMs) and random forest classifiers were used to predict MGMT methylation status. Results: The best classification system (an SVM-based classifier) had a maximum area under the receiver-operating characteristic (ROC) curve of 0.85 (95% CI: 0.78–0.91) using four texture features (correlation, energy, entropy, and local intensity) originating from the T2-weighted images, yielding at the optimal threshold of the ROC curve, a sensitivity of 0.803 and a specificity of 0.813. Conclusions: Results show that supervised machine learning of MRI texture features can predict MGMT methylation status in preoperative GBM tumors, thus providing a new noninvasive imaging biomarker.

Automatic inspection of textured surfaces by support vector machines

Science.gov (United States)

Jahanbin, Sina; Bovik, Alan C.; Pérez, Eduardo; Nair, Dinesh

2009-08-01

Automatic inspection of manufactured products with natural looking textures is a challenging task. Products such as tiles, textile, leather, and lumber project image textures that cannot be modeled as periodic or otherwise regular; therefore, a stochastic modeling of local intensity distribution is required. An inspection system to replace human inspectors should be flexible in detecting flaws such as scratches, cracks, and stains occurring in various shapes and sizes that have never been seen before. A computer vision algorithm is proposed in this paper that extracts local statistical features from grey-level texture images decomposed with wavelet frames into subbands of various orientations and scales. The local features extracted are second order statistics derived from grey-level co-occurrence matrices. Subsequently, a support vector machine (SVM) classifier is trained to learn a general description of normal texture from defect-free samples. This algorithm is implemented in LabVIEW and is capable of processing natural texture images in real-time.

Friction behavior of nano-textured polyimide surfaces measured by AFM colloidal probe

Energy Technology Data Exchange (ETDEWEB)

Zhang, Xiaoliang [College of Equipment Manufacturing, Hebei University of Engineering, Handan 056038 (China); State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000 (China); Wu, Chunxia; Che, Hongwei; Hou, Junxian [College of Equipment Manufacturing, Hebei University of Engineering, Handan 056038 (China); Jia, Junhong, E-mail: jhjia@licp.cas.cn [State Key Laboratory of Solid Lubrication, Lanzhou Institute of Chemical Physics, Chinese Academy of Sciences, Lanzhou 730000 (China)

2014-11-30

Highlights: • Flat PI film and nano-textured PI film were prepared by spin-coating process. • The nano-textured PI surface has effectively reduced the adhesion and friction. • Friction increased with the increasing of contact area and adhesion. • The growth rate of friction decreased with the increasing of applied load. - Abstract: Flat polyimide (PI) film and silicon dioxide nanoparticle-textured PI film were prepared by means of the spin-coating technique. The adhesion and friction properties of the flat PI surface and nano-textured PI surface were investigated by a series of Atomic force microscope (AFM) colloidal probes. Experimental results revealed that the nano-textured PI surface can significantly reduce the adhesive force and friction force, compared with the flat PI surface. The main reason is that the nano-textures can reduce the contact area between the sample surface and colloidal probe. The effect of colloidal probe size on the friction behavior of the flat and nano-textured PI surfaces was evaluated. The adhesive force and friction force of nano-textured PI surface were increased with the increasing of the size of interacting pairs (AFM colloidal probe) due to the increased contact area. Moreover, the friction forces of flat and nano-textured PI surfaces were increased with applied load and sliding velocity.

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

Science.gov (United States)

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.

Textural kinetics: a novel dynamic contrast-enhanced (DCE)-MRI feature for breast lesion classification.

Science.gov (United States)

Agner, Shannon C; Soman, Salil; Libfeld, Edward; McDonald, Margie; Thomas, Kathleen; Englander, Sarah; Rosen, Mark A; Chin, Deanna; Nosher, John; Madabhushi, Anant

2011-06-01

Dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) of the breast has emerged as an adjunct imaging tool to conventional X-ray mammography due to its high detection sensitivity. Despite the increasing use of breast DCE-MRI, specificity in distinguishing malignant from benign breast lesions is low, and interobserver variability in lesion classification is high. The novel contribution of this paper is in the definition of a new DCE-MRI descriptor that we call textural kinetics, which attempts to capture spatiotemporal changes in breast lesion texture in order to distinguish malignant from benign lesions. We qualitatively and quantitatively demonstrated on 41 breast DCE-MRI studies that textural kinetic features outperform signal intensity kinetics and lesion morphology features in distinguishing benign from malignant lesions. A probabilistic boosting tree (PBT) classifier in conjunction with textural kinetic descriptors yielded an accuracy of 90%, sensitivity of 95%, specificity of 82%, and an area under the curve (AUC) of 0.92. Graph embedding, used for qualitative visualization of a low-dimensional representation of the data, showed the best separation between benign and malignant lesions when using textural kinetic features. The PBT classifier results and trends were also corroborated via a support vector machine classifier which showed that textural kinetic features outperformed the morphological, static texture, and signal intensity kinetics descriptors. When textural kinetic attributes were combined with morphologic descriptors, the resulting PBT classifier yielded 89% accuracy, 99% sensitivity, 76% specificity, and an AUC of 0.91.

Wettability transition of laser textured brass surfaces inside different mediums

Science.gov (United States)

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

2018-01-01

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

Bio-inspired design of ice-retardant devices based on benthic marine invertebrates: the effect of surface texture

Directory of Open Access Journals (Sweden)

Homayun Mehrabani

2014-09-01

Full Text Available Growth of ice on surfaces poses a challenge for both organisms and for devices that come into contact with liquids below the freezing point. Resistance of some organisms to ice formation and growth, either in subtidal environments (e.g., Antarctic anchor ice, or in environments with moisture and cold air (e.g., plants, intertidal begs examination of how this is accomplished. Several factors may be important in promoting or mitigating ice formation. As a start, here we examine the effect of surface texture alone. We tested four candidate surfaces, inspired by hard-shelled marine invertebrates and constructed using a three-dimensional printing process. We examined sub-polar marine organisms to develop sample textures and screened them for ice formation and accretion in submerged conditions using previous methods for comparison to data for Antarctic organisms. The sub-polar organisms tested were all found to form ice readily. We also screened artificial 3-D printed samples using the same previous methods, and developed a new test to examine ice formation from surface droplets as might be encountered in environments with moist, cold air. Despite limitations inherent to our techniques, it appears surface texture plays only a small role in delaying the onset of ice formation: a stripe feature (corresponding to patterning found on valves of blue mussels, Mytilus edulis, or on the spines of the Antarctic sea urchin Sterechinus neumayeri slowed ice formation an average of 25% compared to a grid feature (corresponding to patterning found on sub-polar butterclams, Saxidomas nuttalli. The geometric dimensions of the features have only a small (∼6% effect on ice formation. Surface texture affects ice formation, but does not explain by itself the large variation in ice formation and species-specific ice resistance observed in other work. This suggests future examination of other factors, such as material elastic properties and surface coatings, and their

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

Science.gov (United States)

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

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

Evaluation of Tire/Surfacing/Base Contact Stresses and Texture Depth

Directory of Open Access Journals (Sweden)

W.J.vdM. Steyn

2015-03-01

Full Text Available Tire rolling resistance has a major impact on vehicle fuel consumption. Rolling resistance is the loss of energy due to the interaction between the tire and the pavement surface. This interaction is a complicated combination of stresses and strains which depend on both tire and pavement related factors. These include vehicle speed, vehicle weight, tire material and type, road camber, tire inflation pressure, pavement surfacing texture etc. In this paper the relationship between pavement surface texture depth and tire/surfacing contact stress and area is investigated. Texture depth and tire/surfacing contact stress were measured for a range of tire inflation pressures on five different pavement surfaces. In the analysis the relationship between texture and the generated contact stresses as well as the contact stress between the surfacing and base layer are presented and discussed, and the anticipated effect of these relationships on the rolling resistance of vehicles on the surfacings, and subsequent vehicle fuel economy discussed.

Investigation of the biofouling properties of several algae on different textured chemical modified silicone surfaces

Energy Technology Data Exchange (ETDEWEB)

Xu, Jihai [Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201 (China); University of Chinese Academy of Sciences, Beijing 100049 (China); Zhao, Wenjie, E-mail: zhaowj@nimte.ac.cn [Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201 (China); Peng, Shusen; Zeng, Zhixiang; Zhang, Xin [Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201 (China); Wu, Xuedong, E-mail: xdwu@nimte.ac.cn [Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201 (China); Xue, Qunji [Key Laboratory of Marine Materials and Related Technologies, Zhejiang Key Laboratory of Marine Materials and Protective Technologies, Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences, Ningbo 315201 (China)

2014-08-30

Highlights: • Engineered pillars, pits and grooves spaced 3–12 μm apart were fabricated on siloxane modified acrylic resin films. • The effect of feature size, geometry, and wettability on the settlement of different algae was evaluated. • The feature size and geometry displayed a substantial correlation with the antifouling properties. • A comparatively physical fouling deterrent mechanism was analyzed. - Abstract: Engineered pillars, pits and grooves spaced 3, 6, 9 and 12 μm apart were fabricated on siloxane modified acrylic resin films. The effect of feature size, geometry, and wettability on the settlement of different algae was evaluated. These films showed various antifouling performances to Ulothrix, Closterium and Navicula. For Navicula (length: 10–12 μm), the feature size and geometry displayed a substantial correlation with the antifouling properties. The film with pillars spaced 3 μm reduced Navicula settlement by 73% compared to the control surface. For Closterium (length: 45–55 μm), their responses were governed by the same underlying thermodynamic principles as wettability, the largest reduction in Closterium, 81%, was obtained on the surface with grooves spaced 12 μm apart. For Ulothrix (length: 5–8 mm), the surface also showed the best antifouling performance, the reduction ratio of the settlement on the surface with grooves spaced 12 μm apart could even reach 92%. At last, physical fouling deterrent mechanisms for the films with various textures were analyzed in detail. The feature size and geometry display a substantial correlation with the antifouling properties when the size of fouling algae is close to the textures. With the increasing size for algae, antifouling performance was getting better on surface with pillars or grooves because the algae are bridged between two or more features other than stabilizing its entire mass on one single feature or able to settle between features.

Investigation of the biofouling properties of several algae on different textured chemical modified silicone surfaces

International Nuclear Information System (INIS)

Xu, Jihai; Zhao, Wenjie; Peng, Shusen; Zeng, Zhixiang; Zhang, Xin; Wu, Xuedong; Xue, Qunji

2014-01-01

Highlights: • Engineered pillars, pits and grooves spaced 3–12 μm apart were fabricated on siloxane modified acrylic resin films. • The effect of feature size, geometry, and wettability on the settlement of different algae was evaluated. • The feature size and geometry displayed a substantial correlation with the antifouling properties. • A comparatively physical fouling deterrent mechanism was analyzed. - Abstract: Engineered pillars, pits and grooves spaced 3, 6, 9 and 12 μm apart were fabricated on siloxane modified acrylic resin films. The effect of feature size, geometry, and wettability on the settlement of different algae was evaluated. These films showed various antifouling performances to Ulothrix, Closterium and Navicula. For Navicula (length: 10–12 μm), the feature size and geometry displayed a substantial correlation with the antifouling properties. The film with pillars spaced 3 μm reduced Navicula settlement by 73% compared to the control surface. For Closterium (length: 45–55 μm), their responses were governed by the same underlying thermodynamic principles as wettability, the largest reduction in Closterium, 81%, was obtained on the surface with grooves spaced 12 μm apart. For Ulothrix (length: 5–8 mm), the surface also showed the best antifouling performance, the reduction ratio of the settlement on the surface with grooves spaced 12 μm apart could even reach 92%. At last, physical fouling deterrent mechanisms for the films with various textures were analyzed in detail. The feature size and geometry display a substantial correlation with the antifouling properties when the size of fouling algae is close to the textures. With the increasing size for algae, antifouling performance was getting better on surface with pillars or grooves because the algae are bridged between two or more features other than stabilizing its entire mass on one single feature or able to settle between features

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

International Nuclear Information System (INIS)

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

2012-01-01

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

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

Science.gov (United States)

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

2014-02-01

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

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

Directory of Open Access Journals (Sweden)

Wei Feng Wang

2013-02-01

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

Importance of Surface Texture to Infrared Remote Sensing Interpretations

Science.gov (United States)

Kirkland, L. E.; Adams, P. M.; Herr, K. C.; Salisbury, J. W.

2001-11-01

Thermal infrared remote sensing may be used to identify minerals present on the surface using diagnostic spectral bands. As band depth (spectral contrast) exhibited by the mineral increases, the mineral is easier to detect. In order to determine the expected spectral contrast, thermal infrared spectra of typical mineral endmembers are commonly measured in the laboratory. For example, for calcite, well-crystalline limestone is commonly studied. However, carbonates occur in several forms, including thin coatings, indurated carbonate (calcrete), and hot springs deposits. Different formation pathways may cause different microstructures and surface textures. This in turn can also affect the surface texture of the weathered material. Different surface textures can affect the measured band contrast, through roughness that causes a cavity (hohlraum) effect, and particle size and roughness on a scale that causes volume scattering. Thus since detection limits vary with the spectral contrast, surface texture can be an important variable in how detectable a mineral is. To study these issues, we have examined limestone and calcrete deposits at Mormon Mesa, Nevada that have two distinctly different microstructures and surface texture [Kirkland et al., 2001]. The limestone studied has larger grains and the grains frequently have flat, smooth surfaces on the order of 10-50 microns in cross-section length. The calcrete has smaller, more angular calcite grains, which exhibit almost no flat surfaces longer than 5 microns in cross-section length. We will show scanning electron microscope images to compare the different microstructures and surface textures of both the fresh and weathered surfaces, and we will show corresponding thermal infrared spectra to illustrate the different spectral signatures. The results demonstrate the importance of understanding the microstructure of mineral deposits to accurately interpret infrared remote sensing data, especially for studies that lack ground

Effects of Two-stage Heat Treatment on Delayed Coke and Study of Their Surface Texture Characteristics

Science.gov (United States)

Im, Ui-Su; Kim, Jiyoung; Lee, Seon Ho; Lee, Byung-Rok; Peck, Dong-Hyun; Jung, Doo-Hwan

2017-12-01

In the present study, surface texture features and chemical properties of two types of cokes, made from coal tar by either 1-stage heat treatment or 2-stage heat treatment, were researched. The relationship between surface texture characteristics and the chemical properties was identified through molecular weight distribution, insolubility of coal tar, weight loss with temperature increase, coking yield, and polarized light microscope analysis. Rapidly cleared anisotropy texture in cokes was observed in accordance with the coking temperature rise. Quinoline insolubility and toluene insolubility of coal tar increased with a corresponding increases in coking temperature. In particular, the cokes produced by the 2-stage heat treatment (2S-C) showed surface structure of needle cokes at a temperature approximately 50°C lower than the 1-stage heat treatment (1S-C). Additionally, the coking yield of 2S-C increased by approximately 14% in comparison with 1S-C.

SURFACE TEXTURE ANALYSIS FOR FUNCTIONALITY CONTROL

DEFF Research Database (Denmark)

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

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

Dropwise condensation on inclined textured surfaces

CERN Document Server

Khandekar, Sameer

2014-01-01

Dropwise Condensation on Textured Surfaces presents a holistic framework for understanding dropwise condensation through mathematical modeling and meaningful experiments. The book presents a review of the subject required to build up models as well as to design experiments. Emphasis is placed on the effect of physical and chemical texturing and their effect on the bulk transport phenomena. Application of the model to metal vapor condensation is of special interest. The unique behavior of liquid metals, with their low Prandtl number and high surface tension, is also discussed. The model predicts instantaneous drop size distribution for a given level of substrate subcooling and derives local as well as spatio-temporally averaged heat transfer rates and wall shear stress.

Friction reduction using discrete surface textures: principle and design

International Nuclear Information System (INIS)

Hsu, Stephen M; Jing, Yang; Hua, Diann; Zhang, Huan

2014-01-01

There have been many reports on the use of dimples, grooves, and other surface textures to control friction in sliding interfaces. The effectiveness of surface textures in friction reduction has been demonstrated in conformal contacts under high speed low load applications such as mechanical seals and automotive water pump seals, etc., resulting in reduced friction and longer durability. For sliding components with higher contact pressures or lower speeds, conflicting results were reported. Reasons for the inconsistency may be due to the differences in texture fabrication techniques, lack of dimple size and shape uniformity, and different tester used. This paper examines the basic principles on which surface textural patterns influence friction under the three principle lubrication regimes: hydrodynamic, elastohydrodynamic, and boundary lubrication regimes. Our findings suggest that each regime requires specific dimple size, shape, depth, and areal density to achieve friction reduction. Control experiments were also conducted to explore mechanisms of friction reduction. The dimple geometric shape and the dimple's orientation with respect to the sliding direction influence friction significantly. The underlying mechanisms for friction control via textures are discussed. (paper)

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

Science.gov (United States)

Chang, Yu-Ning; Chang, Herng-Hua

2015-01-01

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

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

DEFF Research Database (Denmark)

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

2014-01-01

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

Filtering Color Mapped Textures and Surfaces

OpenAIRE

Heitz , Eric; Nowrouzezahrai , Derek; Poulin , Pierre; Neyret , Fabrice

2013-01-01

International audience; Color map textures applied directly to surfaces, to geometric microsurface details, or to procedural functions (such as noise), are commonly used to enhance visual detail. Their simplicity and ability to mimic a wide range of realistic appearances have led to their adoption in many rendering problems. As with any textured or geometric detail, proper filtering is needed to reduce aliasing when viewed across a range of distances, but accurate and efficient color map filt...

In vivo placental MRI shape and textural features predict fetal growth restriction and postnatal outcome.

Science.gov (United States)

Dahdouh, Sonia; Andescavage, Nickie; Yewale, Sayali; Yarish, Alexa; Lanham, Diane; Bulas, Dorothy; du Plessis, Adre J; Limperopoulos, Catherine

2018-02-01

To investigate the ability of three-dimensional (3D) MRI placental shape and textural features to predict fetal growth restriction (FGR) and birth weight (BW) for both healthy and FGR fetuses. We recruited two groups of pregnant volunteers between 18 and 39 weeks of gestation; 46 healthy subjects and 34 FGR. Both groups underwent fetal MR imaging on a 1.5 Tesla GE scanner using an eight-channel receiver coil. We acquired T2-weighted images on either the coronal or the axial plane to obtain MR volumes with a slice thickness of either 4 or 8 mm covering the full placenta. Placental shape features (volume, thickness, elongation) were combined with textural features; first order textural features (mean, variance, kurtosis, and skewness of placental gray levels), as well as, textural features computed on the gray level co-occurrence and run-length matrices characterizing placental homogeneity, symmetry, and coarseness. The features were used in two machine learning frameworks to predict FGR and BW. The proposed machine-learning based method using shape and textural features identified FGR pregnancies with 86% accuracy, 77% precision and 86% recall. BW estimations were 0.3 ± 13.4% (mean percentage error ± standard error) for healthy fetuses and -2.6 ± 15.9% for FGR. The proposed FGR identification and BW estimation methods using in utero placental shape and textural features computed on 3D MR images demonstrated high accuracy in our healthy and high-risk cohorts. Future studies to assess the evolution of each feature with regard to placental development are currently underway. 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:449-458. © 2017 International Society for Magnetic Resonance in Medicine.

Ethnicity distinctiveness through iris texture features using Gabor filters

CSIR Research Space (South Africa)

Mabuza-Hocquet, Gugulethu P

2017-02-01

Full Text Available Research in iris biometrics has been focused on utilizing iris features as a means of identity verification and authentication. However, not enough research work has been done to explore iris textures to determine soft biometrics such as gender...

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

Science.gov (United States)

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

2018-03-01

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

Nanocrystalline nickel films with lotus leaf texture for superhydrophobic and low friction surfaces

Science.gov (United States)

Shafiei, Mehdi; Alpas, Ahmet T.

2009-11-01

Nanostructured Ni films with high hardness, high hydrophobicity and low coefficient of friction (COF) were fabricated. The surface texture of lotus leaf was replicated using a cellulose acetate film, on which a nanocrystalline (NC) Ni coating with a grain size of 30 ± 4 nm was electrodeposited to obtain a self-sustaining film with a hardness of 4.42 GPa. The surface texture of the NC Ni obtained in this way featured a high density (4 × 10 3 mm -2) of conical protuberances with an average height of 10.0 ± 2.0 μm and a tip radius of 2.5 ± 0.5 μm. This structure increased the water repellency and reduced the COF, compared to smooth NC Ni surfaces. The application of a short-duration (120 s) electrodeposition process that deposited "Ni crowns" with a larger radius of 6.0 ± 0.5 μm on the protuberances, followed by a perfluoropolyether (PFPE) solution treatment succeeded in producing a surface texture consisting of nanotextured protuberances that resulted in a very high water contact angle of 156°, comparable to that of the superhydrophobic lotus leaf. Additionally, the microscale protuberances eliminated the initial high COF peaks observed when smooth NC Ni films were tested, and the PFPE treatment resulted in a 60% reduction in the steady-state COFs.

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

International Nuclear Information System (INIS)

Bordatchev, Evgueni V; Hafiz, Abdullah M K

2014-01-01

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

Parallel implementation of Gray Level Co-occurrence Matrices and Haralick texture features on cell architecture

NARCIS (Netherlands)

Shahbahrami, A.; Pham, T.A.; Bertels, K.L.M.

2011-01-01

Texture features extraction algorithms are key functions in various image processing applications such as medical images, remote sensing, and content-based image retrieval. The most common way to extract texture features is the use of Gray Level Co-occurrence Matrices (GLCMs). The GLCM contains the

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

Science.gov (United States)

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

2017-10-20

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

Modulation of dry tribological property of stainless steel by femtosecond laser surface texturing

Science.gov (United States)

Wang, Zhuo; Zhao, Quanzhong; Wang, Chengwei; Zhang, Yang

2015-06-01

We reported on the modification of tribological properties of stainless steel by femtosecond laser surface microstructuring. Regular arranged micro-grooved textures with different spacing were produced on the AISI 304L steel surfaces by an 800-nm femtosecond laser. The tribological properties of smooth surface and textured surface were investigated by carrying out reciprocating ball-on-flat tests against Al2O3 ceramic balls under dry friction. Results show that the spacing of micro-grooves had a significant impact on friction coefficient of textured surfaces. Furthermore, the wear behaviors of smooth and textured surface were also investigated. Femtosecond laser surface texturing had a marked potential for modulating friction and wear properties if the micro-grooves were distributed in an appropriate manner.

Analysis of the effect of spatial resolution on texture features in the classification of breast masses in mammograms

International Nuclear Information System (INIS)

Rangayyan, R.M.; Nguyen, T.M.; Ayres, F.J.; Nandi, A.K.

2007-01-01

The present study investigates the effect of spatial resolution on co-occurrence matrix-based texture features in discriminating breast lesions as benign masses or malignant tumors. The highest classification result, in terms of the area under the receiver operating characteristics (ROC) curve, of A z 0.74, was obtained at the spatial resolution of 800 μm using all 14 of Haralick's texture features computed using the margins, or ribbons, of the breast masses as seen on mammograms. Furthermore, our study indicates that texture features computed using the ribbons resulted in higher classification accuracy than the same texture features computed using the corresponding regions of interest within the mass boundaries drawn by an expert radiologist. Classification experiments using each single texture feature showed that the texture F 8 , sum entropy, gives consistently high classification results with an average A z of 0.64 across all levels of resolution. At certain levels of resolution, the textures F 5 , F 9 , and F 11 individually gave the highest classification result with A z = 0.70. (orig.)

EUROMET SUPPLEMENTARY COMPARISON - SURFACE TEXTURE

DEFF Research Database (Denmark)

Koenders, L.; Andreasen, Jan Lasson; De Chiffre, Leonardo

At the length meeting in Prague in Oct. 1999 a new comparison was suggested on surface texture. The last comparison on this field was finished in 1989. In the meantime the instrumentation, the standards and the written standards have been improved including some software filters. The pilot labora...

a Statistical Texture Feature for Building Collapse Information Extraction of SAR Image

Science.gov (United States)

Li, L.; Yang, H.; Chen, Q.; Liu, X.

2018-04-01

Synthetic Aperture Radar (SAR) has become one of the most important ways to extract post-disaster collapsed building information, due to its extreme versatility and almost all-weather, day-and-night working capability, etc. In view of the fact that the inherent statistical distribution of speckle in SAR images is not used to extract collapsed building information, this paper proposed a novel texture feature of statistical models of SAR images to extract the collapsed buildings. In the proposed feature, the texture parameter of G0 distribution from SAR images is used to reflect the uniformity of the target to extract the collapsed building. This feature not only considers the statistical distribution of SAR images, providing more accurate description of the object texture, but also is applied to extract collapsed building information of single-, dual- or full-polarization SAR data. The RADARSAT-2 data of Yushu earthquake which acquired on April 21, 2010 is used to present and analyze the performance of the proposed method. In addition, the applicability of this feature to SAR data with different polarizations is also analysed, which provides decision support for the data selection of collapsed building information extraction.

Multilevel binomial logistic prediction model for malignant pulmonary nodules based on texture features of CT image

International Nuclear Information System (INIS)

Wang Huan; Guo Xiuhua; Jia Zhongwei; Li Hongkai; Liang Zhigang; Li Kuncheng; He Qian

2010-01-01

Purpose: To introduce multilevel binomial logistic prediction model-based computer-aided diagnostic (CAD) method of small solitary pulmonary nodules (SPNs) diagnosis by combining patient and image characteristics by textural features of CT image. Materials and methods: Describe fourteen gray level co-occurrence matrix textural features obtained from 2171 benign and malignant small solitary pulmonary nodules, which belongs to 185 patients. Multilevel binomial logistic model is applied to gain these initial insights. Results: Five texture features, including Inertia, Entropy, Correlation, Difference-mean, Sum-Entropy, and age of patients own aggregating character on patient-level, which are statistically different (P < 0.05) between benign and malignant small solitary pulmonary nodules. Conclusion: Some gray level co-occurrence matrix textural features are efficiently descriptive features of CT image of small solitary pulmonary nodules, which can profit diagnosis of earlier period lung cancer if combined patient-level characteristics to some extent.

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

Science.gov (United States)

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

2018-05-01

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

Stabilization of Leidenfrost vapour layer by textured superhydrophobic surfaces

KAUST Repository

Vakarelski, Ivan Uriev

2012-09-12

In 1756, Leidenfrost observed that water drops skittered on a sufficiently hot skillet, owing to levitation by an evaporative vapour film. Such films are stable only when the hot surface is above a critical temperature, and are a central phenomenon in boiling. In this so-called Leidenfrost regime, the low thermal conductivity of the vapour layer inhibits heat transfer between the hot surface and the liquid. When the temperature of the cooling surface drops below the critical temperature, the vapour film collapses and the system enters a nucleate-boiling regime, which can result in vapour explosions that are particularly detrimental in certain contexts, such as in nuclear power plants. The presence of these vapour films can also reduce liquid-solid drag. Here we show how vapour film collapse can be completely suppressed at textured superhydrophobic surfaces. At a smooth hydrophobic surface, the vapour film still collapses on cooling, albeit at a reduced critical temperature, and the system switches explosively to nucleate boiling. In contrast, at textured, superhydrophobic surfaces, the vapour layer gradually relaxes until the surface is completely cooled, without exhibiting a nucleate-boiling phase. This result demonstrates that topological texture on superhydrophobic materials is critical in stabilizing the vapour layer and thus in controlling-by heat transfer-the liquid-gas phase transition at hot surfaces. This concept can potentially be applied to control other phase transitions, such as ice or frost formation, and to the design of low-drag surfaces at which the vapour phase is stabilized in the grooves of textures without heating. © 2012 Macmillan Publishers Limited. All rights reserved.

Stabilization of Leidenfrost vapour layer by textured superhydrophobic surfaces

KAUST Repository

Vakarelski, Ivan Uriev; Patankar, Neelesh A.; Marston, Jeremy; Chan, Derek Y C; Thoroddsen, Sigurdur T

2012-01-01

In 1756, Leidenfrost observed that water drops skittered on a sufficiently hot skillet, owing to levitation by an evaporative vapour film. Such films are stable only when the hot surface is above a critical temperature, and are a central phenomenon in boiling. In this so-called Leidenfrost regime, the low thermal conductivity of the vapour layer inhibits heat transfer between the hot surface and the liquid. When the temperature of the cooling surface drops below the critical temperature, the vapour film collapses and the system enters a nucleate-boiling regime, which can result in vapour explosions that are particularly detrimental in certain contexts, such as in nuclear power plants. The presence of these vapour films can also reduce liquid-solid drag. Here we show how vapour film collapse can be completely suppressed at textured superhydrophobic surfaces. At a smooth hydrophobic surface, the vapour film still collapses on cooling, albeit at a reduced critical temperature, and the system switches explosively to nucleate boiling. In contrast, at textured, superhydrophobic surfaces, the vapour layer gradually relaxes until the surface is completely cooled, without exhibiting a nucleate-boiling phase. This result demonstrates that topological texture on superhydrophobic materials is critical in stabilizing the vapour layer and thus in controlling-by heat transfer-the liquid-gas phase transition at hot surfaces. This concept can potentially be applied to control other phase transitions, such as ice or frost formation, and to the design of low-drag surfaces at which the vapour phase is stabilized in the grooves of textures without heating. © 2012 Macmillan Publishers Limited. All rights reserved.

Experimental Study on Tribological Properties of Laser Textured 45 Steel Surface

Directory of Open Access Journals (Sweden)

Li Zhi Peng

2016-01-01

Full Text Available In order to study the influence of pits’ size parameters on the tribological properties of textured friction pairs, using the Nd:YAG laser micro machining system and the “single pulse at the same point, interval more times” processing technics to process the pits on the surface of 45 steel. The dimension parameters of pits texture were obtained by orthogonal experimental design. The tribological experiment of GCr15 pin/45 steel disc was carried out by UMT-2 test machine. The surface morphology of the specimens was analyzed by using scanning electron microscopy. The experimental results show that the pits texture on the surface of 45 steel can effectively reduce the friction coefficient and the wear on the condition of oil-rich lubrication. The textured specimen with diameter 60μm, depth 6μm and surface density 10% has the lowest friction coefficient, and the friction coefficient is reduced by 21% compared with the smooth specimen. By analyzing the wear morphology on the surface of 45 steel, it is found that the surface of pits texture can obviously reduce the wear.

Effect of environmental dust particles on laser textured yttria-stabilized zirconia surface in humid air ambient

Science.gov (United States)

Yilbas, B. S.; Ali, H.; Al-Sharafi, A.; Al-Sulaiman, F.; Karatas, C.

2018-05-01

Zirconium nitride is used as a selective surface for concentrated solar heating applications and one of the methods to form a zirconium nitride is texturing of zirconia surface by a high intensity laser beam under high pressure nitrogen gas environment. Laser texturing also provides hydrophobic surface characteristics via forming micro/nano pillars at the surface; however, environmental dust settlement on textured surface influences the surface characteristics significantly. In the present study, laser texturing of zirconia surface and effects of the dust particles on the textured surface in a humid air ambient are investigated. Analytical tools are used to assess the morphological changes on the laser textured surface prior and after the dust settlement in the humid air ambient. It is found that laser textured surface has hydrophobic characteristics. The mud formed during condensate of water on the dust particles alters the characteristics of the laser textured surface. The tangential force required to remove the dry mud from the textured surface remains high; in which case, the dried liquid solution at the mud-textured surface interface is responsible for the strong adhesion of the dry mud on the textured surface. The textured surface becomes hydrophilic after the dry mud was removed from the surface by a desalinated water jet.

Surface texture measurement for additive manufacturing

International Nuclear Information System (INIS)

Triantaphyllou, Andrew; Tomita, Ben; Milne, Katherine A; Giusca, Claudiu L; Macaulay, Gavin D; Roerig, Felix; Hoebel, Matthias; Leach, Richard K

2015-01-01

The surface texture of additively manufactured metallic surfaces made by powder bed methods is affected by a number of factors, including the powder’s particle size distribution, the effect of the heat source, the thickness of the printed layers, the angle of the surface relative to the horizontal build bed and the effect of any post processing/finishing. The aim of the research reported here is to understand the way these surfaces should be measured in order to characterise them. In published research to date, the surface texture is generally reported as an Ra value, measured across the lay. The appropriateness of this method for such surfaces is investigated here. A preliminary investigation was carried out on two additive manufacturing processes—selective laser melting (SLM) and electron beam melting (EBM)—focusing on the effect of build angle and post processing. The surfaces were measured using both tactile and optical methods and a range of profile and areal parameters were reported. Test coupons were manufactured at four angles relative to the horizontal plane of the powder bed using both SLM and EBM. The effect of lay—caused by the layered nature of the manufacturing process—was investigated, as was the required sample area for optical measurements. The surfaces were also measured before and after grit blasting. (paper)

Surface texture measurement for additive manufacturing

Science.gov (United States)

Triantaphyllou, Andrew; Giusca, Claudiu L.; Macaulay, Gavin D.; Roerig, Felix; Hoebel, Matthias; Leach, Richard K.; Tomita, Ben; Milne, Katherine A.

2015-06-01

The surface texture of additively manufactured metallic surfaces made by powder bed methods is affected by a number of factors, including the powder’s particle size distribution, the effect of the heat source, the thickness of the printed layers, the angle of the surface relative to the horizontal build bed and the effect of any post processing/finishing. The aim of the research reported here is to understand the way these surfaces should be measured in order to characterise them. In published research to date, the surface texture is generally reported as an Ra value, measured across the lay. The appropriateness of this method for such surfaces is investigated here. A preliminary investigation was carried out on two additive manufacturing processes—selective laser melting (SLM) and electron beam melting (EBM)—focusing on the effect of build angle and post processing. The surfaces were measured using both tactile and optical methods and a range of profile and areal parameters were reported. Test coupons were manufactured at four angles relative to the horizontal plane of the powder bed using both SLM and EBM. The effect of lay—caused by the layered nature of the manufacturing process—was investigated, as was the required sample area for optical measurements. The surfaces were also measured before and after grit blasting.

Parametric features of image textures in 18F-FDG PET/CT evaluation of lung nodules

International Nuclear Information System (INIS)

Wang Changmei; Guan Yihui; Zhang Wenqiang; Zuo Chuantao; Hua Fengchun

2013-01-01

Objective: To evaluate the parametric features of image textures on 18 F-FDG PET/CT for the differentiation between malignant and benign pulmonary nodules and compare the diagnostic performance of these parameters with SUV max . Methods: 18 F-FDG PET/CT images of 170 patients (102 males, 68 females, age range: 29-81 (mean 59) years) with pulmonary nodules were retrospectively evaluated. Eighty-nine pulmonary nodules (230 slices) were malignant and 81 (193 slices) were benign. The pulmonary nodules were contoured on CT images and mapped to the co-registered PET images. Thirteen parameters of textural features were extracted and SUV max was measured. Logistic regression analysis was used to identify the significant texture parameters and create a regression model. The efficacy of the textural features and SUV max to distinguish between malignant and benign pulmonary nodules was evaluated by ROC curve analysis. The textural features of squamous cell carcinoma and adenocarcinoma were compared via the Mann-Whitney u test. The sensitivity and specificity of the textural features and SUV max for the differential diagnosis were compared with χ 2 test. Results: Logistic regression model identified 4 textural features (skewness (β=1.7058), kurtosis (β=-1.0989), angular second moment (ASM, 3=-4.4140) and strength (β=0.5626); all P<0.05) to have significant correlation with the malignancy of lung nodules. The AUC of ROC curve was 0.775 (95% CI 0.732-0.819; P<0.001) with the sensitivity of 89.6% (206/230) and specificity of 50.8% (98/193). ASM and strength had statistically significant differences between squamous cell carcinoma and adenocarcinoma [ASM: 0.0303 (95% CI 0.0392-0.0724) vs 0.0594 (95% CI 0.0721-0.0947); strength: 2.4714 (95% CI 2.4632-4.1050) vs 1.5945 (95% CI 1.9003-2.4652); u=3082.0 and 3115.0, both P<0.01]. The AUC of SUV max -based diagnosis was 0.757 (95% CI 0.711-0.802; P<0.001) with the sensitivity of 80.9% (186/230) and specificity of 50.3% (97/193) at

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

Directory of Open Access Journals (Sweden)

Jia Uddin

2014-01-01

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

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

Science.gov (United States)

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

2017-09-01

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

Experimental Study on Momentum Transfer of Surface Texture in Taylor-Couette Flow

Science.gov (United States)

Xue, Yabo; Yao, Zhenqiang; Cheng, De

2017-05-01

The behavior of Taylor-Couette (TC) flow has been extensively studied. However, no suitable torque prediction models exist for high-capacity fluid machinery. The Eckhardt-Grossmann-Lohse (EGL) theory, derived based on the Navier-Stokes equations, is proposed to model torque behavior. This theory suggests that surfaces are the significant energy transfer interfaces between cylinders and annular flow. This study mainly focuses on the effects of surface texture on momentum transfer behavior through global torque measurement. First, a power-law torque behavior model is built to reveal the relationship between dimensionless torque and the Taylor number based on the EGL theory. Second, TC flow apparatus is designed and built based on the CNC machine tool to verify the torque behavior model. Third, four surface texture films are tested to check the effects of surface texture on momentum transfer. A stereo microscope and three-dimensional topography instrument are employed to analyze surface morphology. Global torque behavior is measured by rotating a multi component dynamometer, and the effects of surface texture on the annular flow behavior are observed via images obtained using a high-speed camera. Finally, torque behaviors under four different surface conditions are fitted and compared. The experimental results indicate that surface textures have a remarkable influence on torque behavior, and that the peak roughness of surface texture enhances the momentum transfer by strengthening the fluctuation in the TC flow.

Texturing in titanium grade 2 surface irradiate with ultrashort pulse laser

International Nuclear Information System (INIS)

Nogueira, Alessandro Francelino

2015-01-01

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

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

Science.gov (United States)

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

2010-10-01

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

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

International Nuclear Information System (INIS)

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

2010-01-01

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

Texture segregation, surface representation and figure-ground separation.

Science.gov (United States)

Grossberg, S; Pessoa, L

1998-09-01

A widespread view is that most texture segregation can be accounted for by differences in the spatial frequency content of texture regions. Evidence from both psychophysical and physiological studies indicate, however, that beyond these early filtering stages, there are stages of 3-D boundary segmentation and surface representation that are used to segregate textures. Chromatic segregation of element-arrangement patterns--as studied by Beck and colleagues--cannot be completely explained by the filtering mechanisms previously employed to account for achromatic segregation. An element arrangement pattern is composed of two types of elements that are arranged differently in different image regions (e.g. vertically on top and diagonally on the bottom). FACADE theory mechanisms that have previously been used to explain data about 3-D vision and figure-ground separation are here used to simulate chromatic texture segregation data, including data with equiluminant elements on dark or light homogeneous backgrounds, or backgrounds composed of vertical and horizontal dark or light stripes, or horizontal notched stripes. These data include the fact that segregation of patterns composed of red and blue squares decreases with increasing luminance of the interspaces. Asymmetric segregation properties under 3-D viewing conditions with the equiluminant elements close or far are also simulated. Two key model properties are a spatial impenetrability property that inhibits boundary grouping across regions with non-collinear texture elements and a boundary-surface consistency property that uses feedback between boundary and surface representations to eliminate spurious boundary groupings and separate figures from their backgrounds.

Switchable Super-Hydrophilic/Hydrophobic Indium Tin Oxide (ITO) Film Surfaces on Reactive Ion Etching (RIE) Textured Si Wafer.

Science.gov (United States)

Kim, Hwa-Min; Litao, Yao; Kim, Bonghwan

2015-11-01

We have developed a surface texturing process for pyramidal surface features along with an indium tin oxide (ITO) coating process to fabricate super-hydrophilic conductive surfaces. The contact angle of a water droplet was less than 5 degrees, which means that an extremely high wettability is achievable on super-hydrophilic surfaces. We have also fabricated a super-hydrophobic conductive surface using an additional coating of polytetrafluoroethylene (PTFE) on the ITO layer coated on the textured Si surface; the ITO and PTFE films were deposited by using a conventional sputtering method. We found that a super-hydrophilic conductive surface is produced by ITO coated on the pyramidal Si surface (ITO/Si), with contact angles of approximately 0 degrees and a resistivity of 3 x 10(-4) Ω x cm. These values are highly dependent on the substrate temperature during the sputtering process. We also found that the super-hydrophobic conductive surface produced by the additional coating of PTFE on the pyramidal Si surface with an ITO layer (PTFE/ITO/Si) has a contact angle of almost 160 degrees and a resistivity of 3 x 10(-4) Ω x cm, with a reflectance lower than 9%. Therefore, these processes can be used to fabricate multifunctional features of ITO films for switchable super-hydrophilic and super-hydrophobic surfaces.

Memory color of natural familiar objects: effects of surface texture and 3-D shape.

Science.gov (United States)

Vurro, Milena; Ling, Yazhu; Hurlbert, Anya C

2013-06-28

Natural objects typically possess characteristic contours, chromatic surface textures, and three-dimensional shapes. These diagnostic features aid object recognition, as does memory color, the color most associated in memory with a particular object. Here we aim to determine whether polychromatic surface texture, 3-D shape, and contour diagnosticity improve memory color for familiar objects, separately and in combination. We use solid three-dimensional familiar objects rendered with their natural texture, which participants adjust in real time to match their memory color for the object. We analyze mean, accuracy, and precision of the memory color settings relative to the natural color of the objects under the same conditions. We find that in all conditions, memory colors deviate slightly but significantly in the same direction from the natural color. Surface polychromaticity, shape diagnosticity, and three dimensionality each improve memory color accuracy, relative to uniformly colored, generic, or two-dimensional shapes, respectively. Shape diagnosticity improves the precision of memory color also, and there is a trend for polychromaticity to do so as well. Differently from other studies, we find that the object contour alone also improves memory color. Thus, enhancing the naturalness of the stimulus, in terms of either surface or shape properties, enhances the accuracy and precision of memory color. The results support the hypothesis that memory color representations are polychromatic and are synergistically linked with diagnostic shape representations.

Doping profile measurement on textured silicon surface

Science.gov (United States)

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

2018-04-01

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

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

Science.gov (United States)

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

2013-01-01

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

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

Science.gov (United States)

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

2017-06-22

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

Texture, microstructure, and fractal features of the low-cycle fatigue failure of the metal in pipeline welded joints

Science.gov (United States)

Usov, V. V.; Gopkalo, E. E.; Shkatulyak, N. M.; Gopkalo, A. P.; Cherneva, T. S.

2015-09-01

Crystallographic texture and fracture features are studied after low-cycle fatigue tests of laboratory specimens cut from the base metal and the characteristic zones of a welded joint in a pipeline after its longterm operation. The fractal dimensions of fracture surfaces are determined. The fractal dimension is shown to increase during the transition from ductile to quasi-brittle fracture, and a relation between the fractal dimension of a fracture surface and the fatigue life of the specimen is found.

Optimization of surface morphology and scattering properties of TCO/AIT textured glass front electrode for thin film solar cells

Energy Technology Data Exchange (ETDEWEB)

Addonizio, M.L., E-mail: marialuisa.addonizio@enea.it; Fusco, L.; Antonaia, A.; Cominale, F.; Usatii, I.

2015-12-01

Graphical abstract: - Highlights: • Aluminium induced texture (AIT) method has been used for obtaining highly textured glass substrates. • The effect of wet etch step on morphological and optical properties has been analyzed. • The morphology features have been optimized in order to obtain the best scattering properties. • Different ZnO surface textures, depending on the underlying glass substrate structures, are obtained. • The effect of different glass texture on optical confinement has been tested in a-Si:H devices. - Abstract: Aluminium induced texture (AIT) method has been used for obtaining highly textured glass substrate suitable for silicon based thin film solar cell technology. Wet etch step parameters of AIT process have been varied and effect of different etchants and different etching times on morphological and optical properties has been analyzed. The resulting morphology features (shape, size distribution, inclination angle) have been optimized in order to obtain the best scattering properties. ZnO:Ga (GZO) films have been deposited by sputtering technique on AIT-processed glass. Two different ZnO surface morphologies have been obtained, strongly depending on the underlying glass substrate morphology induced by different etching times. Very rough and porous texture (σ{sub rms} ∼ 150 nm) was obtained on glass etched 2 min showing cauliflower-like structure, whereas a softer texture (σ{sub rms} ∼ 78 nm) was obtained on glass etched 7 min giving wider and smoother U-shaped craters. The effect of different glass textures on optical confinement has been tested in amorphous silicon based p-i-n devices. Devices fabricated on GZO/high textured glass showed a quantum efficiency enhancement due to both an effective light trapping phenomenon and an effective anti-reflective optical behaviour. Short etching time produce smaller cavities (<1 μm) with deep U-shape characterized by high roughness, high inclination angle and low autocorrelation

Feature-aware natural texture synthesis

KAUST Repository

Wu, Fuzhang; Dong, Weiming; Kong, Yan; Mei, Xing; Yan, Dongming; Zhang, Xiaopeng; Paul, Jean Claude

2014-01-01

This article presents a framework for natural texture synthesis and processing. This framework is motivated by the observation that given examples captured in natural scene, texture synthesis addresses a critical problem, namely, that synthesis

Computer Texture Mapping for Laser Texturing of Injection Mold

Directory of Open Access Journals (Sweden)

Yongquan Zhou

2014-04-01

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

Dynamic air layer on textured superhydrophobic surfaces

KAUST Repository

Vakarelski, Ivan Uriev

2013-09-03

We provide an experimental demonstration that a novel macroscopic, dynamic continuous air layer or plastron can be sustained indefinitely on textured superhydrophobic surfaces in air-supersaturated water by a natural gas influx mechanism. This type of plastron is an intermediate state between Leidenfrost vapor layers on superheated surfaces and the equilibrium Cassie-Baxter wetting state on textured superhydrophobic surfaces. We show that such a plastron can be sustained on the surface of a centimeter-sized superhydrophobic sphere immersed in heated water and variations of its dynamic behavior with air saturation of the water can be regulated by rapid changes of the water temperature. The simple experimental setup allows for quantification of the air flux into the plastron and identification of the air transport model of the plastron growth. Both the observed growth dynamics of such plastrons and millimeter-sized air bubbles seeded on the hydrophilic surface under identical air-supersaturated solution conditions are consistent with the predictions of a well-mixed gas transport model. © 2013 American Chemical Society.

Influence of surface texturing on the performance of tilting pad thrust bearings

OpenAIRE

Gropper, Daniel; Wang, Ling; Harvey, Terry J.; Meck, Klaus-Dieter; Gviniashvili, Vladimir

2016-01-01

Surface textures have been shown to have the potential of enhancing the performance of hydrodynamic bearings and many other applications. However, a comprehensive literature review by the authors has revealed that the application of surface texturing is still limited due to major challenges, such as the complexity of computational models and the large variety of operating conditions encountered in conventional industrial applications. In the present work, the potential of surface texturing fo...

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

Science.gov (United States)

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

2018-04-01

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

Microstructure and Texture in Surface Deformation Layer of Al-Zn-Mg-Cu Alloy Processed by Milling

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CHEN Yanxia

2017-12-01

Full Text Available The microstructural and crystallographic features of the surface deformation layer in Al-Zn-Mg-Cu alloy induced by milling were investigated by means of transmission electron microscopy (TEM and precession electron diffraction (PED assisted nanoscale orientation mapping. The result shows that the surface deformation layer is composed by the top surface of equiaxed nanograins/ultrafine grains and the subsurface of lamellar nanograins/ultrafine grains surrounded by coarse grain boundary precipitates (GBPs. The recrystallized nanograins/ultrafine grains in the deformation layer show direct evidence that dynamic recrystallization plays an important role in grain refining process. The GBPs and grain interior precipitates (GIPs show a great difference in size and density with the matrix due to the thermally and mechanically induced precipitate redistribution. The crystallographic texture of the surface deformation layer is proved to be a mixture of approximate copper{112}, rotated cube{001} and F {111}. The severe shear deformation of the surface induced by milling is responsible for the texture evolution.

Assessing Asphalt and Concrete Pavement Surface Texture in the Field

Directory of Open Access Journals (Sweden)

Saad I. Sarsam

2016-06-01

Full Text Available The incorporation of safety characteristics into the traditional pavement structural design or in the functional evaluation of pavement condition has not been established yet. The design has focused on the structural capacity of the roadway so that the pavement can withstand specific level of repetitive loading over the design life. On the other hand, the surface texture condition was neither included in the AASHTO design procedure nor in the present serviceability index measurements. The pavement surface course should provide adequate levels of friction and ride quality and maintain low levels of noise and roughness. Many transportation departments perform routine skid resistant testing, the type of equipment used for testing varies depending on the preference of each transportation department. It was felt that modeling of the surface texture condition using different methods of testing may assist in solving such problem. In this work, Macro texture and Micro texture of asphalt and cement concrete pavement surface have been investigated in the field using four different methods (The Sand Patch Method, Outflow Time Method, British Pendulum Tester and Photogrammetry Technique. Two different grain sizes of sand have been utilized in conducting the Sand Patch while the Micro texture was investigated using the British Pendulum tester method at wet pavement surface conditions. The test results of the four methods were correlated to the skid number. It was concluded that such modeling could provide instant data in the field for pavement condition which may help in pavement maintenance management.

SU-F-R-35: Repeatability of Texture Features in T1- and T2-Weighted MR Images

International Nuclear Information System (INIS)

Mahon, R; Weiss, E; Karki, K; Hugo, G; Ford, J

2016-01-01

Purpose: To evaluate repeatability of lung tumor texture features from inspiration/expiration MR image pairs for potential use in patient specific care models and applications. Repeatability is a desirable and necessary characteristic of features included in such models. Methods: T1-weighted Volumetric Interpolation Breath-Hold Examination (VIBE) and/or T2-weighted MRI scans were acquired for 15 patients with non-small cell lung cancer before and during radiotherapy for a total of 32 and 34 same session inspiration-expiration breath-hold image pairs respectively. Bias correction was applied to the VIBE (VIBE-BC) and T2-weighted (T2-BC) images. Fifty-nine texture features at five wavelet decomposition ratios were extracted from the delineated primary tumor including: histogram(HIST), gray level co-occurrence matrix(GLCM), gray level run length matrix(GLRLM), gray level size zone matrix(GLSZM), and neighborhood gray tone different matrix (NGTDM) based features. Repeatability of the texture features for VIBE, VIBE-BC, T2-weighted, and T2-BC image pairs was evaluated by the concordance correlation coefficient (CCC) between corresponding image pairs, with a value greater than 0.90 indicating repeatability. Results: For the VIBE image pairs, the percentage of repeatable texture features by wavelet ratio was between 20% and 24% of the 59 extracted features; the T2-weighted image pairs exhibited repeatability in the range of 44–49%. The percentage dropped to 10–20% for the VIBE-BC images, and 12–14% for the T2-BC images. In addition, five texture features were found to be repeatable in all four image sets including two GLRLM, two GLZSM, and one NGTDN features. No single texture feature category was repeatable among all three image types; however, certain categories performed more consistently on a per image type basis. Conclusion: We identified repeatable texture features on T1- and T2-weighted MRI scans. These texture features should be further investigated for use

SU-F-R-35: Repeatability of Texture Features in T1- and T2-Weighted MR Images

Energy Technology Data Exchange (ETDEWEB)

Mahon, R; Weiss, E; Karki, K; Hugo, G [Virginia Commonwealth University, Richmond, VA (United States); Ford, J [University of Miami Miller School of Medicine, Miami, FL (United States)

2016-06-15

Purpose: To evaluate repeatability of lung tumor texture features from inspiration/expiration MR image pairs for potential use in patient specific care models and applications. Repeatability is a desirable and necessary characteristic of features included in such models. Methods: T1-weighted Volumetric Interpolation Breath-Hold Examination (VIBE) and/or T2-weighted MRI scans were acquired for 15 patients with non-small cell lung cancer before and during radiotherapy for a total of 32 and 34 same session inspiration-expiration breath-hold image pairs respectively. Bias correction was applied to the VIBE (VIBE-BC) and T2-weighted (T2-BC) images. Fifty-nine texture features at five wavelet decomposition ratios were extracted from the delineated primary tumor including: histogram(HIST), gray level co-occurrence matrix(GLCM), gray level run length matrix(GLRLM), gray level size zone matrix(GLSZM), and neighborhood gray tone different matrix (NGTDM) based features. Repeatability of the texture features for VIBE, VIBE-BC, T2-weighted, and T2-BC image pairs was evaluated by the concordance correlation coefficient (CCC) between corresponding image pairs, with a value greater than 0.90 indicating repeatability. Results: For the VIBE image pairs, the percentage of repeatable texture features by wavelet ratio was between 20% and 24% of the 59 extracted features; the T2-weighted image pairs exhibited repeatability in the range of 44–49%. The percentage dropped to 10–20% for the VIBE-BC images, and 12–14% for the T2-BC images. In addition, five texture features were found to be repeatable in all four image sets including two GLRLM, two GLZSM, and one NGTDN features. No single texture feature category was repeatable among all three image types; however, certain categories performed more consistently on a per image type basis. Conclusion: We identified repeatable texture features on T1- and T2-weighted MRI scans. These texture features should be further investigated for use

Fingerprint-Inspired Flexible Tactile Sensor for Accurately Discerning Surface Texture.

Science.gov (United States)

Cao, Yudong; Li, Tie; Gu, Yang; Luo, Hui; Wang, Shuqi; Zhang, Ting

2018-04-01

Inspired by the epidermal-dermal and outer microstructures of the human fingerprint, a novel flexible sensor device is designed to improve haptic perception and surface texture recognition, which is consisted of single-walled carbon nanotubes, polyethylene, and polydimethylsiloxane with interlocked and outer micropyramid arrays. The sensor shows high pressure sensitivity (-3.26 kPa -1 in the pressure range of 0-300 Pa), and it can detect the shear force changes induced by the dynamic interaction between the outer micropyramid structure on the sensor and the tested material surface, and the minimum dimension of the microstripe that can be discerned is as low as 15 µm × 15 µm (interval × width). To demonstrate the texture discrimination capability, the sensors are tested for accurately discerning various surface textures, such as the textures of different fabrics, Braille characters, the inverted pyramid patterns, which will have great potential in robot skins and haptic perception, etc. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

[Visual Texture Agnosia in Humans].

Science.gov (United States)

Suzuki, Kyoko

2015-06-01

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

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

International Nuclear Information System (INIS)

Xie, Y; Wang, J; Wang, C; Chang, Z

2016-01-01

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

2018-03-01

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

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

Science.gov (United States)

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

2015-10-01

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

Control of crystallographic texture and surface morphology of Pt/Tio2 templates for enhanced PZT thin film texture.

Science.gov (United States)

Fox, Austin J; Drawl, Bill; Fox, Glen R; Gibbons, Brady J; Trolier-McKinstry, Susan

2015-01-01

Optimized processing conditions for Pt/TiO2/SiO2/Si templating electrodes were investigated. These electrodes are used to obtain [111] textured thin film lead zirconate titanate (Pb[ZrxTi1-x ]O3 0 ≤ x ≤ 1) (PZT). Titanium deposited by dc magnetron sputtering yields [0001] texture on a thermally oxidized Si wafer. It was found that by optimizing deposition time, pressure, power, and the chamber pre-conditioning, the Ti texture could be maximized while maintaining low surface roughness. When oxidized, titanium yields [100]-oriented rutile. This seed layer has as low as a 4.6% lattice mismatch with [111] Pt; thus, it is possible to achieve strongly oriented [111] Pt. The quality of the orientation and surface roughness of the TiO2 and the Ti directly affect the achievable Pt texture and surface morphology. A transition between optimal crystallographic texture and the smoothest templating surface occurs at approximately 30 nm of original Ti thickness (45 nm TiO2). This corresponds to 0.5 nm (2 nm for TiO2) rms roughness as determined by atomic force microscopy and a full-width at half-maximum (FWHM) of the rocking curve 0002 (200) peak of 5.5/spl degrees/ (3.1/spl degrees/ for TiO2). A Pb[Zr0.52Ti 0.48]O3 layer was deposited and shown to template from the textured Pt electrode, with a maximum [111] Lotgering factor of 87% and a minimum 111 FWHM of 2.4/spl degrees/ at approximately 30 nm of original Ti.

Surface Textures and Features Indicative of Endogenous Growth at the McCartys Flow Field, NM, as an Analog to Martian Volcanic Plains

Science.gov (United States)

Bleacher, Jacob E.; Crumpler, L. S.; Garry, W. B.; Zimbelman, J. R.; Self, S.; Aubele, J. C.

2012-01-01

Basaltic lavas typically form channels or tubes, which are recognized on the Earth and Mars. Although largely unrecognized in the planetary community, terrestrial inflated sheet flows also display morphologies that share many commonalities with lava plains on Mars. The McCartys lava flow field is among the youngest (approx.3000 yrs) basaltic flows in the continental United States. The southwest sections of the flow displays smooth, flat-topped plateaus with irregularly shaped pits and hummocky inter-plateau units that form a polygonal surface. Plateaus are typically elongate in map view, up to 20 m high and display lineations within the glassy crust. Lineated surfaces occasionally display small < 1m diameter lava coils. Lineations are generally straight and parallel each other, sometimes for over 100 meters. The boundaries between plateaus and depressions are also lineated and tilted to angles sometimes approaching vertical. Plateau-parallel cracks, sometimes containing squeeze-ups, mark the boundary between tilted crust and plateau. Some plateau depressions display level floors with hummocky surfaces, while some are bowl shaped with floors covered in broken lava slabs. The lower walls of pits sometimes display lateral, sagged lava wedges. Infrequently, pit floors display the upper portion of a tumulus from an older flow. In some places the surface crust has been disrupted forming a slabby texture. Slabs are typically on the scale of a meter or less across and no less than 7-10 cm thick. The slabs preserve the lineated textures of the undisturbed plateau crust. It appears that this style of terrain represents the emplacement of an extensive sheet that experiences inflation episodes within preferred regions where lateral spreading of the sheet is inhibited, thereby forming plateaus. Rough surfaces represent inflation-related disruption of pahoehoe lava and not a a lava. Depressions are often the result of non-inflation and can be clearly identified by lateral

Design and characterization of textured surfaces for applications in the food industry

Science.gov (United States)

Lazzini, G.; Romoli, L.; Blunt, L.; Gemini, L.

2017-12-01

The aim of this work is to design, manufacture and characterize surface morphologies on AISI 316L stainless steel produced by a custom designed laser-texturing strategy. Surface textures were characterized at a micrometric dimension in terms of areal parameters compliant with ISO 25178, and correlations between these parameters and processing parameters (e.g. laser energy dose supplied to the material, repetition rate of the laser pulses and scanning velocity) were investigated. Preliminary efforts were devoted to the research of special requirements for surface morphology that, according to the commonly accepted research on the influence of surface roughness on cellular adhesion on surfaces, should discourage the formation of biofilms. The topographical characterization of the surfaces was performed with a coherence scanning interferometer. This approach showed that increasing doses of energy to the surfaces increased the global level of roughness as well as the surface complexity. Moreover, the behavior of the parameters S pk, S vk also indicates that, due to the ablation process, an increase in the energy dose causes an average increase in the height of the highest peaks and in the depth of the deepest dales. The study of the density of peaks S pd showed that none of the surfaces analyzed here seem to perfectly match the conditions dictated by the theories on cellular adhesion to confer anti-biofouling properties. However, this result seems to be mainly due to the limits of the resolving power of coherence scanning interferometry, which does not allow the resolution of sub-micrometric features which could be crucial in the prevention of cellular attachment.

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

Science.gov (United States)

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

2009-02-01

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

Texture Feature Analysis for Different Resolution Level of Kidney Ultrasound Images

Science.gov (United States)

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

2017-08-01

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

Classification of Carotid Plaque Echogenicity by Combining Texture Features and Morphologic Characteristics.

Science.gov (United States)

Huang, Xiaowei; Zhang, Yanling; Qian, Ming; Meng, Long; Xiao, Yang; Niu, Lili; Zheng, Rongqin; Zheng, Hairong

2016-10-01

Anechoic carotid plaques on sonography have been used to predict future cardiovascular or cerebrovascular events. The purpose of this study was to investigate whether carotid plaque echogenicity could be assessed objectively by combining texture features extracted by MaZda software (Institute of Electronics, Technical University of Lodz, Lodz, Poland) and morphologic characteristics, which may provide a promising method for early prediction of acute cardiovascular disease. A total of 268 plaque images were collected from 136 volunteers and classified into 85 hyperechoic, 83 intermediate, and 100 anechoic plaques. About 300 texture features were extracted from histogram, absolute gradient, run-length matrix, gray-level co-occurrence matrix, autoregressive model, and wavelet transform algorithms by MaZda. The morphologic characteristics, including degree of stenosis, maximum plaque intima-media thickness, and maximum plaque length, were measured by B-mode sonography. Statistically significant features were selected by analysis of covariance. The most discriminative features were obtained from statistically significant features by linear discriminant analysis. The K-nearest neighbor classifier was used to classify plaque echogenicity based on statistically significant and most discriminative features. A total of 30 statistically significant features were selected among the plaques, and 2 most discriminative features were obtained from the statistically significant features. The classification accuracy rates for 3 types of plaques based on statistically significant and most discriminative features were 72.03% (κ= 0.571; P MaZda and morphologic characteristics.

Wet-Chemical Surface Texturing of Sputter-Deposited ZnO:Al Films as Front Electrode for Thin-Film Silicon Solar Cells

Directory of Open Access Journals (Sweden)

Xia Yan

2015-01-01

Full Text Available Transparent conductive oxides (TCOs play a major role as the front electrodes of thin-film silicon (Si solar cells, as they can provide optical scattering and hence improved photon absorption inside the devices. In this paper we report on the surface texturing of aluminium-doped zinc oxide (ZnO:Al or AZO films for improved light trapping in thin-film Si solar cells. The AZO films are deposited onto soda-lime glass sheets via pulsed DC magnetron sputtering. Several promising AZO texturing methods are investigated using diluted hydrochloric (HCl and hydrofluoric acid (HF, through a two-step etching process. The developed texturing procedure combines the advantages of the HCl-induced craters and the smaller and jagged—but laterally more uniform—features created by HF etching. In the two-step process, the second etching step further enhances the optical haze, while simultaneously improving the uniformity of the texture features created by the HCl etch. The resulting AZO films show large haze values of above 40%, good scattering into large angles, and a surface angle distribution that is centred at around 30°, which is known from the literature to provide efficient light trapping for thin-film Si solar cells.

TEXTURAL DESCRIPTORS FOR MULTIPHASIC ORE PARTICLES

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Laura Pérez-Barnuevo

2012-11-01

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

Nanosecond laser textured superhydrophobic metallic surfaces and their chemical sensing applications

Science.gov (United States)

Ta, Duong V.; Dunn, Andrew; Wasley, Thomas J.; Kay, Robert W.; Stringer, Jonathan; Smith, Patrick J.; Connaughton, Colm; Shephard, Jonathan D.

2015-12-01

This work demonstrates superhydrophobic behavior on nanosecond laser patterned copper and brass surfaces. Compared with ultrafast laser systems previously used for such texturing, infrared nanosecond fiber lasers offer a lower cost and more robust system combined with potentially much higher processing rates. The wettability of the textured surfaces develops from hydrophilicity to superhydrophobicity over time when exposed to ambient conditions. The change in the wetting property is attributed to the partial deoxidation of oxides on the surface induced during laser texturing. Textures exhibiting steady state contact angles of up to ∼152° with contact angle hysteresis of around 3-4° have been achieved. Interestingly, the superhydrobobic surfaces have the self-cleaning ability and have potential for chemical sensing applications. The principle of these novel chemical sensors is based on the change in contact angle with the concentration of methanol in a solution. To demonstrate the principle of operation of such a sensor, it is found that the contact angle of methanol solution on the superhydrophobic surfaces exponentially decays with increasing concentration. A significant reduction, of 128°, in contact angle on superhydrophobic brass is observed, which is one order of magnitude greater than that for the untreated surface (12°), when percent composition of methanol reaches to 28%.

Linear feature selection in texture analysis - A PLS based method

DEFF Research Database (Denmark)

Marques, Joselene; Igel, Christian; Lillholm, Martin

2013-01-01

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

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

Science.gov (United States)

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

1973-01-01

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

Prognostic Value and Reproducibility of Pretreatment CT Texture Features in Stage III Non-Small Cell Lung Cancer

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Fried, David V. [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas (United States); Tucker, Susan L. [Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Zhou, Shouhao [Division of Quantitative Sciences, Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Liao, Zhongxing [Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Mawlawi, Osama [Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas (United States); Ibbott, Geoffrey [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas (United States); Court, Laurence E., E-mail: LECourt@mdanderson.org [Department of Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, Texas (United States); Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas (United States)

2014-11-15

Purpose: To determine whether pretreatment CT texture features can improve patient risk stratification beyond conventional prognostic factors (CPFs) in stage III non-small cell lung cancer (NSCLC). Methods and Materials: We retrospectively reviewed 91 cases with stage III NSCLC treated with definitive chemoradiation therapy. All patients underwent pretreatment diagnostic contrast enhanced computed tomography (CE-CT) followed by 4-dimensional CT (4D-CT) for treatment simulation. We used the average-CT and expiratory (T50-CT) images from the 4D-CT along with the CE-CT for texture extraction. Histogram, gradient, co-occurrence, gray tone difference, and filtration-based techniques were used for texture feature extraction. Penalized Cox regression implementing cross-validation was used for covariate selection and modeling. Models incorporating texture features from the 33 image types and CPFs were compared to those with models incorporating CPFs alone for overall survival (OS), local-regional control (LRC), and freedom from distant metastases (FFDM). Predictive Kaplan-Meier curves were generated using leave-one-out cross-validation. Patients were stratified based on whether their predicted outcome was above or below the median. Reproducibility of texture features was evaluated using test-retest scans from independent patients and quantified using concordance correlation coefficients (CCC). We compared models incorporating the reproducibility seen on test-retest scans to our original models and determined the classification reproducibility. Results: Models incorporating both texture features and CPFs demonstrated a significant improvement in risk stratification compared to models using CPFs alone for OS (P=.046), LRC (P=.01), and FFDM (P=.005). The average CCCs were 0.89, 0.91, and 0.67 for texture features extracted from the average-CT, T50-CT, and CE-CT, respectively. Incorporating reproducibility within our models yielded 80.4% (±3.7% SD), 78.3% (±4.0% SD), and 78

Prognostic Value and Reproducibility of Pretreatment CT Texture Features in Stage III Non-Small Cell Lung Cancer

International Nuclear Information System (INIS)

Fried, David V.; Tucker, Susan L.; Zhou, Shouhao; Liao, Zhongxing; Mawlawi, Osama; Ibbott, Geoffrey; Court, Laurence E.

2014-01-01

Purpose: To determine whether pretreatment CT texture features can improve patient risk stratification beyond conventional prognostic factors (CPFs) in stage III non-small cell lung cancer (NSCLC). Methods and Materials: We retrospectively reviewed 91 cases with stage III NSCLC treated with definitive chemoradiation therapy. All patients underwent pretreatment diagnostic contrast enhanced computed tomography (CE-CT) followed by 4-dimensional CT (4D-CT) for treatment simulation. We used the average-CT and expiratory (T50-CT) images from the 4D-CT along with the CE-CT for texture extraction. Histogram, gradient, co-occurrence, gray tone difference, and filtration-based techniques were used for texture feature extraction. Penalized Cox regression implementing cross-validation was used for covariate selection and modeling. Models incorporating texture features from the 33 image types and CPFs were compared to those with models incorporating CPFs alone for overall survival (OS), local-regional control (LRC), and freedom from distant metastases (FFDM). Predictive Kaplan-Meier curves were generated using leave-one-out cross-validation. Patients were stratified based on whether their predicted outcome was above or below the median. Reproducibility of texture features was evaluated using test-retest scans from independent patients and quantified using concordance correlation coefficients (CCC). We compared models incorporating the reproducibility seen on test-retest scans to our original models and determined the classification reproducibility. Results: Models incorporating both texture features and CPFs demonstrated a significant improvement in risk stratification compared to models using CPFs alone for OS (P=.046), LRC (P=.01), and FFDM (P=.005). The average CCCs were 0.89, 0.91, and 0.67 for texture features extracted from the average-CT, T50-CT, and CE-CT, respectively. Incorporating reproducibility within our models yielded 80.4% (±3.7% SD), 78.3% (±4.0% SD), and 78

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

International Nuclear Information System (INIS)

Yang, F; Yang, Y; Young, L

2016-01-01

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

Tribological Properties of Surface-Textured and Plasma-Nitrided Pure Titanium Under Oil Lubrication Condition

Science.gov (United States)

Zhang, Baosen; Dong, Qiangsheng; Ba, Zhixin; Wang, Zhangzhong; Shi, Hancheng; Xue, Yanting

2018-01-01

Plasma nitriding was conducted as post-treatment for surface texture on pure titanium to obtain a continuous nitriding layer. Supersonic fine particles bombarding (SFPB) was carried out to prepare surface texture. The surface morphologies and chemical composition were analyzed using scanning electron microscope and energy disperse spectroscopy. The microstructures of modified layers were characterized by transmission electron microscope. The tribological properties of surface-textured and duplex-treated pure titanium under oil lubrication condition were systematically investigated in the ball-on-plate reciprocating mode. The effects of applied load and sliding velocity on the tribological behavior were analyzed. The results show that after duplex treatments, the grains size in modified layer becomes slightly larger, and hardness is obviously improved. Wear resistance of duplex-treated pure titanium is significantly improved referenced to untreated and surface-textured pure titanium, which is 3.22 times as much as untreated pure titanium and 2.15 times of that for surface-textured pure titanium, respectively.

The application of slip length models to larger textures in turbulent flows over superhydrophobic surfaces

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Fairhall, Chris; Garcia-Mayoral, Ricardo

2017-11-01

We present results from direct numerical simulations of turbulent flows over superhydrophobic surfaces. We assess the validity of simulations where the surface is modelled as homogeneous slip lengths, comparing them to simulations where the surface texture is resolved. Our results show that once the coherent flow induced by the texture is removed from the velocity fields, the remaining flow sees the surface as homogeneous. We then investigate how the overlying turbulence is modified by the presence of surface texture. For small textures, we show that turbulence is shifted closer to the wall due to the presence of slip, but otherwise remains essentially unmodified. For larger textures, the texture interacts with the turbulent lengthscales, thereby modifying the overlying turbulence. We also show that the saturation of the effect of the spanwise slip length (Fukagata et al. 2006, Busse & Sandham 2012, Seo & Mani 2016), which is drag increasing, is caused by the impermeability imposed at the surface. This work was supported by the Engineering and Physical Sciences Research Council.

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

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

2014-03-01

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

Tumor recognition in wireless capsule endoscopy images using textural features and SVM-based feature selection.

Science.gov (United States)

Li, Baopu; Meng, Max Q-H

2012-05-01

Tumor in digestive tract is a common disease and wireless capsule endoscopy (WCE) is a relatively new technology to examine diseases for digestive tract especially for small intestine. This paper addresses the problem of automatic recognition of tumor for WCE images. Candidate color texture feature that integrates uniform local binary pattern and wavelet is proposed to characterize WCE images. The proposed features are invariant to illumination change and describe multiresolution characteristics of WCE images. Two feature selection approaches based on support vector machine, sequential forward floating selection and recursive feature elimination, are further employed to refine the proposed features for improving the detection accuracy. Extensive experiments validate that the proposed computer-aided diagnosis system achieves a promising tumor recognition accuracy of 92.4% in WCE images on our collected data.

The Feature Extraction Based on Texture Image Information for Emotion Sensing in Speech

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Kun-Ching Wang

2014-09-01

Full Text Available In this paper, we present a novel texture image feature for Emotion Sensing in Speech (ESS. This idea is based on the fact that the texture images carry emotion-related information. The feature extraction is derived from time-frequency representation of spectrogram images. First, we transform the spectrogram as a recognizable image. Next, we use a cubic curve to enhance the image contrast. Then, the texture image information (TII derived from the spectrogram image can be extracted by using Laws’ masks to characterize emotional state. In order to evaluate the effectiveness of the proposed emotion recognition in different languages, we use two open emotional databases including the Berlin Emotional Speech Database (EMO-DB and eNTERFACE corpus and one self-recorded database (KHUSC-EmoDB, to evaluate the performance cross-corpora. The results of the proposed ESS system are presented using support vector machine (SVM as a classifier. Experimental results show that the proposed TII-based feature extraction inspired by visual perception can provide significant classification for ESS systems. The two-dimensional (2-D TII feature can provide the discrimination between different emotions in visual expressions except for the conveyance pitch and formant tracks. In addition, the de-noising in 2-D images can be more easily completed than de-noising in 1-D speech.

Computerized detection of diffuse lung disease in MDCT: the usefulness of statistical texture features

International Nuclear Information System (INIS)

Wang Jiahui; Li Qiang; Li Feng; Doi Kunio

2009-01-01

Accurate detection of diffuse lung disease is an important step for computerized diagnosis and quantification of this disease. It is also a difficult clinical task for radiologists. We developed a computerized scheme to assist radiologists in the detection of diffuse lung disease in multi-detector computed tomography (CT). Two radiologists selected 31 normal and 37 abnormal CT scans with ground glass opacity, reticular, honeycombing and nodular disease patterns based on clinical reports. The abnormal cases in our database must contain at least an abnormal area with a severity of moderate or severe level that was subjectively rated by the radiologists. Because statistical texture features may lack the power to distinguish a nodular pattern from a normal pattern, the abnormal cases that contain only a nodular pattern were excluded. The areas that included specific abnormal patterns in the selected CT images were then delineated as reference standards by an expert chest radiologist. The lungs were first segmented in each slice by use of a thresholding technique, and then divided into contiguous volumes of interest (VOIs) with a 64 x 64 x 64 matrix size. For each VOI, we determined and employed statistical texture features, such as run-length and co-occurrence matrix features, to distinguish abnormal from normal lung parenchyma. In particular, we developed new run-length texture features with clear physical meanings to considerably improve the accuracy of our detection scheme. A quadratic classifier was employed for distinguishing between normal and abnormal VOIs by the use of a leave-one-case-out validation scheme. A rule-based criterion was employed to further determine whether a case was normal or abnormal. We investigated the impact of new and conventional texture features, VOI size and the dimensionality for regions of interest on detecting diffuse lung disease. When we employed new texture features for 3D VOIs of 64 x 64 x 64 voxels, our system achieved the

Combination of radiological and gray level co-occurrence matrix textural features used to distinguish solitary pulmonary nodules by computed tomography.

Science.gov (United States)

Wu, Haifeng; Sun, Tao; Wang, Jingjing; Li, Xia; Wang, Wei; Huo, Da; Lv, Pingxin; He, Wen; Wang, Keyang; Guo, Xiuhua

2013-08-01

The objective of this study was to investigate the method of the combination of radiological and textural features for the differentiation of malignant from benign solitary pulmonary nodules by computed tomography. Features including 13 gray level co-occurrence matrix textural features and 12 radiological features were extracted from 2,117 CT slices, which came from 202 (116 malignant and 86 benign) patients. Lasso-type regularization to a nonlinear regression model was applied to select predictive features and a BP artificial neural network was used to build the diagnostic model. Eight radiological and two textural features were obtained after the Lasso-type regularization procedure. Twelve radiological features alone could reach an area under the ROC curve (AUC) of 0.84 in differentiating between malignant and benign lesions. The 10 selected characters improved the AUC to 0.91. The evaluation results showed that the method of selecting radiological and textural features appears to yield more effective in the distinction of malignant from benign solitary pulmonary nodules by computed tomography.

Ensemble based system for whole-slide prostate cancer probability mapping using color texture features.

LENUS (Irish Health Repository)

DiFranco, Matthew D

2011-01-01

We present a tile-based approach for producing clinically relevant probability maps of prostatic carcinoma in histological sections from radical prostatectomy. Our methodology incorporates ensemble learning for feature selection and classification on expert-annotated images. Random forest feature selection performed over varying training sets provides a subset of generalized CIEL*a*b* co-occurrence texture features, while sample selection strategies with minimal constraints reduce training data requirements to achieve reliable results. Ensembles of classifiers are built using expert-annotated tiles from training images, and scores for the probability of cancer presence are calculated from the responses of each classifier in the ensemble. Spatial filtering of tile-based texture features prior to classification results in increased heat-map coherence as well as AUC values of 95% using ensembles of either random forests or support vector machines. Our approach is designed for adaptation to different imaging modalities, image features, and histological decision domains.

Suitability of texture features to assess changes in trabecular bone architecture

DEFF Research Database (Denmark)

Veenland, JF; Grashuis, JL; Weinans, H

2002-01-01

The purpose of this study was to determine the ability of texture features to assess changes in trabecular bone architecture as projected in radiographs. Micro-CT datasets of trabecular bone were processed to simulate different changes in architecture. Radiographs were simulated by projecting the...

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

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Bala Emilia

2016-06-01

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

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

Science.gov (United States)

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

2017-10-01

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

Angle-dependent lubricated tribological properties of stainless steel by femtosecond laser surface texturing

Science.gov (United States)

Wang, Zhuo; Li, Yang-Bo; Bai, Feng; Wang, Cheng-Wei; Zhao, Quan-Zhong

2016-07-01

Lubricated tribological properties of stainless steel were investigated by femtosecond laser surface texturing. Regular-arranged micro-grooved textures with different spacing and micro-groove inclination angles (between micro-groove path and sliding direction) were produced on AISI 304L steel surfaces by an 800 nm femtosecond laser. The spacing of micro-groove was varied from 25 to 300 μm, and the inclination angles of micro-groove were measured as 90° and 45°. The tribological properties of the smooth and textured surfaces with micro-grooves were investigated by reciprocating ball-on-flat tests against Al2O3 ceramic balls under starved oil lubricated conditions. Results showed that the spacing of micro-grooves significantly affected the tribological property. With the increase of micro-groove spacing, the average friction coefficients and wear rates of textured surfaces initially decreased then increased. The tribological performance also depended on the inclination angles of micro-grooves. Among the investigated patterns, the micro-grooves perpendicular to the sliding direction exhibited the lowest average friction coefficient and wear rate to a certain extent. Femtosecond laser-induced surface texturing may remarkably improve friction and wear properties if the micro-grooves were properly distributed.

DNS of flows over superhydrophobic surfaces with small texture

Science.gov (United States)

Fairhall, Chris; Garcia-Mayoral, Ricardo

2015-11-01

We present results from direct numerical simulations of turbulent flows over superhydrophobic surfaces with small texture sizes, comparable to those of practical application. Textures studied with DNS are usually much larger, as the cost of the simulations would otherwise be prohibitive. For this reason, a multi-block code that allows for finer resolution near the walls has been developed. We focus particularly on the pressure distribution at the wall. This distribution can cause the deformation of the gas pockets, which can ultimately lead to their loss and that of the drag reduction effect. The layout of the texture causes stagnation pressures which can contribute substantially to the wall pressure signal (Seo et al. JFM, under review). We study a range of different textures and their influence on these pressures.

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

Science.gov (United States)

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

2015-03-01

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

Surface texture generation during cylindrical milling in the aspect of cutting force variations

International Nuclear Information System (INIS)

Wojciechowski, S; Twardowski, P; Pelic, M

2014-01-01

The work presented here concentrates on surface texture analysis, after cylindrical milling of hardened steel. Cutting force variations occurring in the machining process have direct influence on the cutter displacements and thus on the generated surface texture. Therefore, in these experiments, the influence of active number of teeth (z c ) on the cutting force variations was investigated. Cutting forces and cutter displacements were measured during machining process (online) using, namely piezoelectric force dynamometer and 3D laser vibrometer. Surface roughness parameters were measured using stylus surface profiler. The surface roughness model including cutting parameters (f z , D) and cutting force variations was also developed. The research revealed that in cylindrical milling process, cutting force variations have immediate influence on surface texture generation

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

Science.gov (United States)

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

2015-09-01

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

Improved Main Shaft Seal Life in Gas Turbines Using Laser Surface Texturing

Science.gov (United States)

McNickle, Alan D.; Etsion, Izhak

2002-10-01

This paper presents a general overview of the improved main shaft seal life in gas turbines using laser surface texturing (LST). The contents include: 1) Laser Surface Texturing System; 2) Seal Schematic with LST applied; 3) Dynamic Rig Tests; 4) Surface Finish Definitions; 5) Wear Test Rig; 6) Dynamic Test Rig; 7) Seal Cross Section-Rig Test; and 8) Typical Test Results. This paper is in viewgraph form.

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

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Naiming Lin

2018-03-01

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

Effect of zooming on texture features of ultrasonic images

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Kyriacou Efthyvoulos

2006-01-01

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

Color Texture Image Retrieval Based on Local Extrema Features and Riemannian Distance

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Minh-Tan Pham

2017-10-01

Full Text Available A novel efficient method for content-based image retrieval (CBIR is developed in this paper using both texture and color features. Our motivation is to represent and characterize an input image by a set of local descriptors extracted from characteristic points (i.e., keypoints within the image. Then, dissimilarity measure between images is calculated based on the geometric distance between the topological feature spaces (i.e., manifolds formed by the sets of local descriptors generated from each image of the database. In this work, we propose to extract and use the local extrema pixels as our feature points. Then, the so-called local extrema-based descriptor (LED is generated for each keypoint by integrating all color, spatial as well as gradient information captured by its nearest local extrema. Hence, each image is encoded by an LED feature point cloud and Riemannian distances between these point clouds enable us to tackle CBIR. Experiments performed on several color texture databases including Vistex, STex, color Brodazt, USPtex and Outex TC-00013 using the proposed approach provide very efficient and competitive results compared to the state-of-the-art methods.

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

Science.gov (United States)

Cui, Chen; Asari, Vijayan K.

2014-03-01

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

Probability mapping of scarred myocardium using texture and intensity features in CMR images

Science.gov (United States)

2013-01-01

Background The myocardium exhibits heterogeneous nature due to scarring after Myocardial Infarction (MI). In Cardiac Magnetic Resonance (CMR) imaging, Late Gadolinium (LG) contrast agent enhances the intensity of scarred area in the myocardium. Methods In this paper, we propose a probability mapping technique using Texture and Intensity features to describe heterogeneous nature of the scarred myocardium in Cardiac Magnetic Resonance (CMR) images after Myocardial Infarction (MI). Scarred tissue and non-scarred tissue are represented with high and low probabilities, respectively. Intermediate values possibly indicate areas where the scarred and healthy tissues are interwoven. The probability map of scarred myocardium is calculated by using a probability function based on Bayes rule. Any set of features can be used in the probability function. Results In the present study, we demonstrate the use of two different types of features. One is based on the mean intensity of pixel and the other on underlying texture information of the scarred and non-scarred myocardium. Examples of probability maps computed using the mean intensity of pixel and the underlying texture information are presented. We hypothesize that the probability mapping of myocardium offers alternate visualization, possibly showing the details with physiological significance difficult to detect visually in the original CMR image. Conclusion The probability mapping obtained from the two features provides a way to define different cardiac segments which offer a way to identify areas in the myocardium of diagnostic importance (like core and border areas in scarred myocardium). PMID:24053280

Temporal analysis of intratumoral metabolic heterogeneity characterized by textural features in cervical cancer.

Science.gov (United States)

Yang, Fei; Thomas, Maria A; Dehdashti, Farrokh; Grigsby, Perry W

2013-05-01

The aim of this pilot study was to explore heterogeneity in the temporal behavior of intratumoral [(18)F]fluorodeoxyglucose (FDG) accumulation at a regional scale in patients with cervical cancer undergoing chemoradiotherapy. Included in the study were 20 patients with FIGO stages IB1 to IVA cervical cancer treated with combined chemoradiotherapy. Patients underwent FDG PET/CT before treatment, during weeks 2 and 4 of treatment, and 12 weeks after completion of therapy. Patients were classified based on response to therapy as showing a complete metabolic response (CMR), a partial metabolic response (PMR), or residual disease and the development of new disease (NEW). Based on the presence of residual primary tumor following therapy, patients were divided into two groups, CMR and PMR/NEW. Temporal profiles of intratumoral FDG heterogeneity as characterized by textural features at a regional scale were assessed and compared with those of the standardized uptake value (SUV) indices (SUVmax and SUVmean) within the context of differentiating response groups. Textural features at a regional scale with emphasis on characterizing contiguous regions of high uptake in tumors decreased significantly with time (P features describing contiguous regions of low uptake along with those measuring the nonuniformity of contiguous isointense regions in tumors exhibited significant temporal changes in the PMR/NEW group (P textural features may provide an adjunctive or alternative option for understanding tumor response to chemoradiotherapy and interpreting FDG accumulation dynamics in patients with malignant cervical tumors during the course of the disease.

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

Science.gov (United States)

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

2015-12-01

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

Controlling the stainless steel surface wettability by nanosecond direct laser texturing at high fluences

Science.gov (United States)

Gregorčič, P.; Šetina-Batič, B.; Hočevar, M.

2017-12-01

This work investigates the influence of the direct laser texturing at high fluences (DLT-HF) on surface morphology, chemistry, and wettability. We use a Nd:YAG laser ( λ = 1064 nm) with pulse duration of 95 ns to process stainless steel surface. The surface morphology and chemistry after the texturing is examined by using scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDS), and electron backscatter diffraction (EBSD), while the surface wettability is evaluated by measuring the static contact angle. Immediately after the texturing, the surface is superhydrophilic in a saturated Wenzel regime. However, this state is not stable and the superhydrophilic-to-superhydrophobic transition happens if the sample is kept in atmospheric air for 30 days. After this period, the laser-textured stainless steel surface expresses lotus-leaf-like behavior. By using a high-speed camera at 10,000 fps, we measured that the water droplet completely rebound from this superhydrophobic surface after the contact time of 12 ms.

Effect of strontium tantalate surface texture on nickel nanoparticle dispersion by electroless deposition

Energy Technology Data Exchange (ETDEWEB)

Compean-González, C.L. [Universidad Autónoma de Nuevo León, Facultad de Ingeniería Civil, Departamento de Ecomateriales y Energía, Av. Universidad s/n, Ciudad Universitaria, San Nicolás de los Garza, Nuevo León C.P. 66451 (Mexico); Arredondo-Torres, V.M. [Facultad de Químico Farmacobiología, Universidad Michoacana de San Nicolás de Hidalgo, Tzintzuntzan #173, Col. Matamoros, Morelia, Michoacán C.P. 58240 (Mexico); Zarazúa-Morin, M.E. [Universidad Autónoma de Nuevo León, Facultad de Ingeniería Civil, Departamento de Ecomateriales y Energía, Av. Universidad s/n, Ciudad Universitaria, San Nicolás de los Garza, Nuevo León C.P. 66451 (Mexico); Figueroa-Torres, M.Z., E-mail: m.zyzlila@gmail.com [Universidad Autónoma de Nuevo León, Facultad de Ingeniería Civil, Departamento de Ecomateriales y Energía, Av. Universidad s/n, Ciudad Universitaria, San Nicolás de los Garza, Nuevo León C.P. 66451 (Mexico)

2015-09-15

Highlights: • Efficient short-time procedure for nickel nanoparticles dispersion by electroless. • Nanoparticles are spherical in shape with an average size of 15 nm. • Influence of surface texture on deposition temperature and time was observed. • Nickel deposition can be done below 50 °C. - Abstract: The present work studies the effect of smooth and porous texture of Sr{sub 2}Ta{sub 2}O{sub 7} on its surface modification with nickel nanoparticles through electroless deposition technique. The influence of temperature to control Ni nanoparticles loading amount and dispersion were analyzed. Nitrogen adsorption isotherms were used to examine surface texture characteristics. The morphology was observed by scanning electron microscopy (MEB) equipped with an energy dispersive spectrometry system (EDS), which was used to determine the amount of deposited Ni. The material with smooth texture (SMT) consists of big agglomerates of semispherical shape particles of 400 nm. Whilst the porous texture (PRT) exhibit a pore-wall formed of needles shape particles of around 200 nm in size. Results indicated that texture characteristics strongly influence the deposition reaction rate; for PRT oxide, Ni deposition can be done from 20 °C while for SMT oxide deposition begins at 40 °C. Analysis of Sr{sub 2}Ta{sub 2}O{sub 7} surface indicated that in both textures, Ni nanoparticles with spherical shape in the range of 10–20 nm were obtained.

Ion beam texturing

Science.gov (United States)

Hudson, W. R.

1977-01-01

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

Effects of surface roughness, texture and polymer degradation on cathodic delamination of epoxy coated steel samples

International Nuclear Information System (INIS)

Khun, N.W.; Frankel, G.S.

2013-01-01

Highlights: ► Cathodic delamination of epoxy coated steel samples was studied using SKP. ► Delamination of the coating decreased with increased substrate surface roughness. ► Delamination of the coating was faster on the substrate with parallel surface scratches. ► Delamination of the coating exposed to weathering conditions increased with prolonged exposure. - Abstract: The Scanning Kelvin Probe (SKP) technique was used to investigate the effects of surface roughness, texture and polymer degradation on cathodic delamination of epoxy coated steel. The cathodic delamination rate of the epoxy coatings dramatically decreased with increased surface roughness of the underlying steel substrate. The surface texture of the steel substrates also had a significant effect in that samples with parallel abrasion lines exhibiting faster cathodic delamination in the direction of the lines compared to the direction perpendicular to the lines. The cathodic delamination kinetics of epoxy coatings previously exposed to weathering conditions increased with prolonged exposure due to pronounced polymer degradation. SEM observation confirmed that the cyclic exposure to UV radiation and water condensation caused severe deterioration in the polymer structures with surface cracking and erosion. The SKP results clearly showed that the cathodic delamination of the epoxy coatings was significantly influenced by the surface features of the underlying steel substrates and the degradation of the coatings.

Classification of grass pollen through the quantitative analysis of surface ornamentation and texture.

Science.gov (United States)

Mander, Luke; Li, Mao; Mio, Washington; Fowlkes, Charless C; Punyasena, Surangi W

2013-11-07

Taxonomic identification of pollen and spores uses inherently qualitative descriptions of morphology. Consequently, identifications are restricted to categories that can be reliably classified by multiple analysts, resulting in the coarse taxonomic resolution of the pollen and spore record. Grass pollen represents an archetypal example; it is not routinely identified below family level. To address this issue, we developed quantitative morphometric methods to characterize surface ornamentation and classify grass pollen grains. This produces a means of quantifying morphological features that are traditionally described qualitatively. We used scanning electron microscopy to image 240 specimens of pollen from 12 species within the grass family (Poaceae). We classified these species by developing algorithmic features that quantify the size and density of sculptural elements on the pollen surface, and measure the complexity of the ornamentation they form. These features yielded a classification accuracy of 77.5%. In comparison, a texture descriptor based on modelling the statistical distribution of brightness values in image patches yielded a classification accuracy of 85.8%, and seven human subjects achieved accuracies between 68.33 and 81.67%. The algorithmic features we developed directly relate to biologically meaningful features of grass pollen morphology, and could facilitate direct interpretation of unsupervised classification results from fossil material.

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

Directory of Open Access Journals (Sweden)

Kun-Ching Wang

2015-01-01

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

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

Science.gov (United States)

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

2017-11-01

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

Forward impact extrusion of surface textured steel blanks using coated tooling

Science.gov (United States)

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

2017-10-01

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

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

Energy Technology Data Exchange (ETDEWEB)

Andrews, M; Abazeed, M; Woody, N; Stephans, K; Videtic, G; Xia, P; Zhuang, T [The Cleveland Clinic Foundation, Cleveland, OH (United States)

2016-06-15

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 to 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.

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

International Nuclear Information System (INIS)

Andrews, M; Abazeed, M; Woody, N; Stephans, K; Videtic, G; Xia, P; Zhuang, T

2016-01-01

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 to 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.

Characteristics of laser textured silicon surface and effect of mud adhesion on hydrophobicity

Energy Technology Data Exchange (ETDEWEB)

Yilbas, B.S., E-mail: bsyilbas@kfupm.edu.sa [ME Department, King Fahd University of Petroleum & Minerals, Kfupm box 1913, Dhahran 31261 (Saudi Arabia); Ali, H. [ME Department, King Fahd University of Petroleum & Minerals, Kfupm box 1913, Dhahran 31261 (Saudi Arabia); Khaled, M. [CHEM Department, King Fahd University of Petroleum & Minerals, Dhahran (Saudi Arabia); Al-Aqeeli, N.; Abu-Dheir, N. [ME Department, King Fahd University of Petroleum & Minerals, Kfupm box 1913, Dhahran 31261 (Saudi Arabia); Varanasi, K.K. [Mechanical Engineering, Massachusetts Institute of Technology, Boston, MA (United States)

2015-10-01

Highlights: • Laser treatment increases surface microhardness and slightly lowers surface fracture toughness. • Residual stress formed is compressive and self-annealing effect of laser tracks lowers residual stress. • Nitride species lowers surface energy and adhesion work required to remove dust. • Mud residues do not have notable effect on fracture toughness and microhardness of treated surface. • Mud residues lower surface hydrophobicity. - Abstract: Laser gas assisted texturing of silicon wafer surface is carried out. Morphological and metallurgical changes in the treated layer are examined using the analytical tools. Microhardness and fracture toughness of the laser treated surface are measured using the indentation technique while residual stress formed is determined from the X-ray diffraction data. The hydrophobicity of the textured surfaces are assessed incorporating the contact angle data and compared with those of as received workpiece surfaces. Environmental dust accumulation and mud formation, due to air humidity, at the laser treated and as received workpiece surfaces are simulated and the effect of the mud residues on the properties of the laser treated surface are studied. The adhesion work due to the presence of the mud on the laser treated surface is also measured. It is found that laser textured surface composes of micro/nano poles and fibers, which in turn improves the surface hydrophobicity significantly. In addition, formation of nitride species contributes to microhardness increase and enhancement of surface hydrophobicity due to their low surface energy. The mud residues do not influence the fracture toughness and microhardness of the laser textured surface; however, they reduced the surface hydrophobicity significantly.

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

International Nuclear Information System (INIS)

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

2015-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2015-06-15

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

Personal recognition using finger knuckle shape oriented features and texture analysis

Directory of Open Access Journals (Sweden)

K. Usha

2016-10-01

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

Textured surface structures formed using new techniques on transparent conducting Al-doped zinc oxide films prepared by magnetron sputtering

International Nuclear Information System (INIS)

Minami, Tadatsugu; Miyata, Toshihiro; Uozaki, Ryousuke; Sai, Hitoshi; Koida, Takashi

2016-01-01

Surface-textured Al-doped ZnO (AZO) films formed using two new techniques based on magnetron sputtering deposition were developed by optimizing the light scattering properties to be suitable for transparent electrode applications in thin-film silicon solar cells. Scrambled egg-like surface-textured AZO films were prepared using a new texture formation technique that post-etched pyramidal surface-textured AZO films prepared under deposition conditions suppressing c-axis orientation. In addition, double surface-textured AZO films were prepared using another new texture formation technique that completely removed, by post-etching, the pyramidal surface-textured AZO films previously prepared onto the initially deposited low resistivity AZO films; simultaneously, the surface of the low resistivity films was slightly etched. However, the obtained very high haze value in the range from the near ultraviolet to visible light in the scrambled egg-like surface-textured AZO films did not contribute significantly to the obtainable photovoltaic properties in the solar cells fabricated using the films. Significant light scattering properties as well as a low sheet resistance could be achieved in the double surface-textured AZO films. In addition, a significant improvement of external quantum efficiency in the range from the near ultraviolet to visible light was achieved in superstrate-type n-i-p μc-Si:H solar cells fabricated using a double surface-textured AZO film prepared under optimized conditions as the transparent electrode. - Highlights: • Double surface-textured AZO films prepared using a new texture formation technique • Extensive light scattering properties with low sheet resistance achieved in the double surface-textured AZO films • Improved external quantum efficiency of μc-Si:H solar cells using a double surface-textured AZO film

Textured surface structures formed using new techniques on transparent conducting Al-doped zinc oxide films prepared by magnetron sputtering

Energy Technology Data Exchange (ETDEWEB)

Minami, Tadatsugu [Optoelectronic Device System R& D Center, Kanazawa Institute of Technology, Nonoichi, Ishikawa 921-8501 (Japan); Miyata, Toshihiro, E-mail: tmiyata@neptune.kanazawa-it.ac.jp [Optoelectronic Device System R& D Center, Kanazawa Institute of Technology, Nonoichi, Ishikawa 921-8501 (Japan); Uozaki, Ryousuke [Optoelectronic Device System R& D Center, Kanazawa Institute of Technology, Nonoichi, Ishikawa 921-8501 (Japan); Sai, Hitoshi; Koida, Takashi [Research Center for Photovoltaics, National Institute of Advanced Industrial Science and Technology (AIST), Tsukuba, Ibaraki 305-8568 (Japan)

2016-09-01

Surface-textured Al-doped ZnO (AZO) films formed using two new techniques based on magnetron sputtering deposition were developed by optimizing the light scattering properties to be suitable for transparent electrode applications in thin-film silicon solar cells. Scrambled egg-like surface-textured AZO films were prepared using a new texture formation technique that post-etched pyramidal surface-textured AZO films prepared under deposition conditions suppressing c-axis orientation. In addition, double surface-textured AZO films were prepared using another new texture formation technique that completely removed, by post-etching, the pyramidal surface-textured AZO films previously prepared onto the initially deposited low resistivity AZO films; simultaneously, the surface of the low resistivity films was slightly etched. However, the obtained very high haze value in the range from the near ultraviolet to visible light in the scrambled egg-like surface-textured AZO films did not contribute significantly to the obtainable photovoltaic properties in the solar cells fabricated using the films. Significant light scattering properties as well as a low sheet resistance could be achieved in the double surface-textured AZO films. In addition, a significant improvement of external quantum efficiency in the range from the near ultraviolet to visible light was achieved in superstrate-type n-i-p μc-Si:H solar cells fabricated using a double surface-textured AZO film prepared under optimized conditions as the transparent electrode. - Highlights: • Double surface-textured AZO films prepared using a new texture formation technique • Extensive light scattering properties with low sheet resistance achieved in the double surface-textured AZO films • Improved external quantum efficiency of μc-Si:H solar cells using a double surface-textured AZO film.

Modulated surface textures for enhanced scattering in thin-film silicon solar cells

NARCIS (Netherlands)

Isabella, O.; Battaglia, C.; Ballif, C.; Zeman, M.

2012-01-01

Nano-scale randomly textured front transparent oxides are superposed on micro-scale etched glass substrates to form modulated surface textures. The resulting enhanced light scattering is implemented in single and double junction thin-film silicon solar cells.

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

Science.gov (United States)

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

2012-09-01

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

Military personnel recognition system using texture, colour, and SURF features

Science.gov (United States)

Irhebhude, Martins E.; Edirisinghe, Eran A.

2014-06-01

This paper presents an automatic, machine vision based, military personnel identification and classification system. Classification is done using a Support Vector Machine (SVM) on sets of Army, Air Force and Navy camouflage uniform personnel datasets. In the proposed system, the arm of service of personnel is recognised by the camouflage of a persons uniform, type of cap and the type of badge/logo. The detailed analysis done include; camouflage cap and plain cap differentiation using gray level co-occurrence matrix (GLCM) texture feature; classification on Army, Air Force and Navy camouflaged uniforms using GLCM texture and colour histogram bin features; plain cap badge classification into Army, Air Force and Navy using Speed Up Robust Feature (SURF). The proposed method recognised camouflage personnel arm of service on sets of data retrieved from google images and selected military websites. Correlation-based Feature Selection (CFS) was used to improve recognition and reduce dimensionality, thereby speeding the classification process. With this method success rates recorded during the analysis include 93.8% for camouflage appearance category, 100%, 90% and 100% rates of plain cap and camouflage cap categories for Army, Air Force and Navy categories, respectively. Accurate recognition was recorded using SURF for the plain cap badge category. Substantial analysis has been carried out and results prove that the proposed method can correctly classify military personnel into various arms of service. We show that the proposed method can be integrated into a face recognition system, which will recognise personnel in addition to determining the arm of service which the personnel belong. Such a system can be used to enhance the security of a military base or facility.

Feature Extraction of Weld Defectology in Digital Image of Radiographic Film Using Geometric Invariant Moment and Statistical Texture

International Nuclear Information System (INIS)

Muhtadan

2009-01-01

The purpose of this research is to perform feature extraction in weld defect of digital image of radiographic film using geometric invariant moment and statistical texture method. Feature extraction values can be use as values that used to classify and pattern recognition on interpretation of weld defect in digital image of radiographic film by computer automatically. Weld defectology type that used in this research are longitudinal crack, transversal crack, distributed porosity, clustered porosity, wormhole, and no defect. Research methodology on this research are program development to read digital image, then performing image cropping to localize weld position, and then applying geometric invariant moment and statistical texture formulas to find feature values. The result of this research are feature extraction values that have tested with RST (rotation, scale, transformation) treatment and yield moment values that more invariant there are ϕ 3 , ϕ 4 , ϕ 5 from geometric invariant moment method. Feature values from statistical texture that are average intensity, average contrast, smoothness, 3 rd moment, uniformity, and entropy, they used as feature extraction values. (author)

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

Science.gov (United States)

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

2013-01-01

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

Effects of surface treatments on the translucency, opalescence, and surface texture of dental monolithic zirconia ceramics.

Science.gov (United States)

Kim, Hee-Kyung; Kim, Sung-Hun; Lee, Jai-Bong; Ha, Seung-Ryong

2016-06-01

Surface polishing or glazing may increase the appearance of depth of monolithic zirconia restorations. The purpose of this in vitro study was to investigate the effects of surface treatments on the translucency, opalescence, and surface texture of dental monolithic zirconia ceramics. Forty-five monolithic zirconia specimens (16.3×16.4×2.0 mm) were divided into groups I to V, according to the number of colorings each received. Each group was then divided into 3 subgroups (n=3) according to the surface treatment: N=no treatment; P=polished; and G=glazed. CIElab color coordinates were obtained relative to D65 on a reflection spectrophotometer. The translucency parameter (TP) and opalescence parameter (OP) were calculated. One specimen per subgroups I and V was selected for evaluation of surface roughness (Ra) and was examined with scanning electron microscopy (SEM). Data were analyzed with 2-way ANOVA and pairwise comparisons (α=.05). Statistical powers were verified to evaluate results (α=.05). The interaction effects of surface treatments combined with the number of colorings were significant for TP, OP, and Ra (P.05), whereas glazing significantly decreased OP and Ra in most groups. SEM images demonstrated that surface treatments affected the surface texture of monolithic zirconia ceramics. Surface treatments combined with coloring strongly affect the surface texture of dental monolithic zirconia ceramics. Copyright © 2016 Editorial Council for the Journal of Prosthetic Dentistry. Published by Elsevier Inc. All rights reserved.

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

Science.gov (United States)

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

2017-07-01

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

Analysis of iris surface features in populations of diverse ancestry

Science.gov (United States)

Edwards, Melissa; Cha, David; Krithika, S.; Johnson, Monique; Parra, Esteban J.

2016-01-01

There are many textural elements that can be found in the human eye, including Fuchs’ crypts, Wolfflin nodules, pigment spots, contraction furrows and conjunctival melanosis. Although iris surface features have been well-studied in populations of European ancestry, the worldwide distribution of these traits is poorly understood. In this paper, we develop a new method of characterizing iris features from photographs of the iris. We then apply this method to a diverse sample of East Asian, European and South Asian ancestry. All five iris features showed significant differences in frequency between the three populations, indicating that iris features are largely population dependent. Although none of the features were correlated with each other in the East and South Asian groups, Fuchs’ crypts were significantly correlated with contraction furrows and pigment spots and contraction furrows were significantly associated with pigment spots in the European group. The genetic marker SEMA3A rs10235789 was significantly associated with Fuchs’ crypt grade in the European, East Asian and South Asian samples and a borderline association between TRAF3IP1 rs3739070 and contraction furrow grade was found in the European sample. The study of iris surface features in diverse populations may provide valuable information of forensic, biomedical and ophthalmological interest. PMID:26909168

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

Science.gov (United States)

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

2012-04-01

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

Picosecond laser micro/nano surface texturing of nickel for superhydrophobicity

Science.gov (United States)

Wang, X. C.; Wang, B.; Xie, H.; Zheng, H. Y.; Lam, Y. C.

2018-03-01

A single step direct picosecond laser texturing process was demonstrated to be able to obtain a superhydrophobic surface on a nickel substrate, a key material for mold fabrication in the manufacture of various devices, including polymeric microfluidic devices. A two-scale hierarchical surface structure of regular 2D array micro-bumps with nano-ripples was produced on a nickel surface. The laser textured surface initially showed superhydrophilicity with almost complete wetting of the structured surface just after laser treatment, then quickly changed to nearly superhydrophobic with a water contact angle (WCA) of 140° in less than 1 d, and finally became superhydrophobic with a WCA of more than 150° and a contact angle hysteresis (CAH) of less than 5°. The mechanism involved in the process is discussed in terms of surface morphology and surface chemistry. The ultra-fast laser induced NiO catalytic effect was thought to play a key role in modifying the surface chemistry so as to lower the surface energy. The developed process has the potential to improve the performance of nickel mold in the fabrication of microfluidic devices.

Textural Analysis of Fatique Crack Surfaces: Image Pre-processing

Directory of Open Access Journals (Sweden)

H. Lauschmann

2000-01-01

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

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

Science.gov (United States)

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

2016-01-01

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

Metrics and textural features of MRI diffusion to improve classification of pediatric posterior fossa tumors.

Science.gov (United States)

Rodriguez Gutierrez, D; Awwad, A; Meijer, L; Manita, M; Jaspan, T; Dineen, R A; Grundy, R G; Auer, D P

2014-05-01

Qualitative radiologic MR imaging review affords limited differentiation among types of pediatric posterior fossa brain tumors and cannot detect histologic or molecular subtypes, which could help to stratify treatment. This study aimed to improve current posterior fossa discrimination of histologic tumor type by using support vector machine classifiers on quantitative MR imaging features. This retrospective study included preoperative MRI in 40 children with posterior fossa tumors (17 medulloblastomas, 16 pilocytic astrocytomas, and 7 ependymomas). Shape, histogram, and textural features were computed from contrast-enhanced T2WI and T1WI and diffusivity (ADC) maps. Combinations of features were used to train tumor-type-specific classifiers for medulloblastoma, pilocytic astrocytoma, and ependymoma types in separation and as a joint posterior fossa classifier. A tumor-subtype classifier was also produced for classic medulloblastoma. The performance of different classifiers was assessed and compared by using randomly selected subsets of training and test data. ADC histogram features (25th and 75th percentiles and skewness) yielded the best classification of tumor type (on average >95.8% of medulloblastomas, >96.9% of pilocytic astrocytomas, and >94.3% of ependymomas by using 8 training samples). The resulting joint posterior fossa classifier correctly assigned >91.4% of the posterior fossa tumors. For subtype classification, 89.4% of classic medulloblastomas were correctly classified on the basis of ADC texture features extracted from the Gray-Level Co-Occurence Matrix. Support vector machine-based classifiers using ADC histogram features yielded very good discrimination among pediatric posterior fossa tumor types, and ADC textural features show promise for further subtype discrimination. These findings suggest an added diagnostic value of quantitative feature analysis of diffusion MR imaging in pediatric neuro-oncology. © 2014 by American Journal of Neuroradiology.

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

Directory of Open Access Journals (Sweden)

Humayun Irshad

2013-01-01

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

Screening Mississippi River Levees Using Texture-Based and Polarimetric-Based Features from Synthetic Aperture Radar Data

Directory of Open Access Journals (Sweden)

Lalitha Dabbiru

2017-03-01

Full Text Available This article reviews the use of synthetic aperture radar remote sensing data for earthen levee mapping with an emphasis on finding the slump slides on the levees. Earthen levees built on the natural levees parallel to the river channel are designed to protect large areas of populated and cultivated land in the Unites States from flooding. One of the signs of potential impending levee failure is the appearance of slump slides. On-site inspection of levees is expensive and time-consuming; therefore, a need to develop efficient techniques based on remote sensing technologies is mandatory to prevent failures under flood loading. Analysis of multi-polarized radar data is one of the viable tools for detecting the problem areas on the levees. In this study, we develop methods to detect anomalies on the levee, such as slump slides and give levee managers new tools to prioritize their tasks. This paper presents results of applying the National Aeronautics and Space Administration (NASA Jet Propulsion Lab (JPL’s Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR quad-polarized L-band data to detect slump slides on earthen levees. The study area encompasses a portion of levees of the lower Mississippi River in the United States. In this paper, we investigate the performance of polarimetric and texture features for efficient levee classification. Texture features derived from the gray level co-occurrence (GLCM matrix and discrete wavelet transform were computed and analyzed for efficient levee classification. The pixel-based polarimetric decomposition features, such as entropy, anisotropy, and scattering angle were also computed and applied to the support vector machine classifier to characterize the radar imagery and compared the results with texture-based classification. Our experimental results showed that inclusion of textural features derived from the SAR data using the discrete wavelet transform (DWT features and GLCM features provided

Game theory-based visual tracking approach focusing on color and texture features.

Science.gov (United States)

Jin, Zefenfen; Hou, Zhiqiang; Yu, Wangsheng; Chen, Chuanhua; Wang, Xin

2017-07-20

It is difficult for a single-feature tracking algorithm to achieve strong robustness under a complex environment. To solve this problem, we proposed a multifeature fusion tracking algorithm that is based on game theory. By focusing on color and texture features as two gamers, this algorithm accomplishes tracking by using a mean shift iterative formula to search for the Nash equilibrium of the game. The contribution of different features is always keeping the state of optical balance, so that the algorithm can fully take advantage of feature fusion. According to the experiment results, this algorithm proves to possess good performance, especially under the condition of scene variation, target occlusion, and similar interference.

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

Science.gov (United States)

Hedir, Mehdia; Haddad, Boualem

2017-10-01

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

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

Directory of Open Access Journals (Sweden)

Jianli eLiu

2015-11-01

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

Breast density pattern characterization by histogram features and texture descriptors

OpenAIRE

Carneiro,Pedro Cunha; Franco,Marcelo Lemos Nunes; Thomaz,Ricardo de Lima; Patrocinio,Ana Claudia

2017-01-01

Abstract Introduction Breast cancer is the first leading cause of death for women in Brazil as well as in most countries in the world. Due to the relation between the breast density and the risk of breast cancer, in medical practice, the breast density classification is merely visual and dependent on professional experience, making this task very subjective. The purpose of this paper is to investigate image features based on histograms and Haralick texture descriptors so as to separate mammo...

Dynamic crystallization of a eucrite basalt. [achondrite textural features produced by superheating and differing cooling rates

Science.gov (United States)

Walker, D.; Powell, M. A.; Hays, J. F.; Lofgren, G. E.

1978-01-01

The textural features produced in Stannern, a non-porpyritic representative of the eucrite basaltic achondrite class of meteorite, at differing cooling rates and various degrees of initial superheating were studied. Textures produced from mildly superheated melts were found to be fasciculate rather than porphyritic as the result of the cosaturated bulk chemistry of Stannern. The qualitative type of texture apparently depends mainly on the degree of initial superheating, whereas cooling rate exerts a strong influence on the coarseness of texture. Increasing the degree of superheating produces textures from intergranular/subophitic to fasciculate/porphyritic. With initial superheating to 1200 deg C the transition to quasi-porphyritic is controlled by cooling rate, but the development of phenocrysts is merely an overprint on the fasciculate background texture of the groundmass. The suppression of fasciculate texture is completed by a decrease of the degree of initial superheating below the plagioclast entry and suppression of quasi-porphyritic texture is completed by decrease of the degree of initial superheating below pyroxene entry; these qualitative changes do not seem to be produced by changes of cooling rate. A grain size/cooling rate dependence has been used to deduce the cooling rate of fasciculate-textured Stannern clasts (10.1 to 100 deg C/hr).

T2-weighted MRI-derived textural features reflect prostate cancer aggressiveness: preliminary results

NARCIS (Netherlands)

Nketiah, G.; Elschot, M.; Kim, E.; Teruel, J.R.; Scheenen, T.W.J.; Bathen, T.F.; Selnaes, K.M.

2017-01-01

PURPOSE: To evaluate the diagnostic relevance of T2-weighted (T2W) MRI-derived textural features relative to quantitative physiological parameters derived from diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) MRI in Gleason score (GS) 3+4 and 4+3 prostate cancers. MATERIALS AND METHODS:

Influence of citric acid on the surface texture of glass ionomer restorative materials.

Science.gov (United States)

Reddy, Dappili Swami Ranga; Kumar, Ramachandran Anil; Venkatesan, Sokkalingam Mothilal; Narayan, Gopal Shankar; Duraivel, Dasarathan; Indra, Rajamani

2014-09-01

This study determined the effectiveness of G-coat plus surface protective agent over petroleum jelly on the surface texture of conventional Glass ionomer restorative materials. Three chemically cured conventional glass ionomer restorative materials type II, type IX and ketac molar were evaluated in this study. Sixty specimens were made for each restorative material. They were divided into two groups of thirty specimens each. Of the sixty specimens, thirty were coated with G-coat plus (a nano-filler coating) and the rest with petroleum jelly. Thirty samples of both protective coating agents were randomly divided into six groups of five specimens and conditioned in citric acid solutions of differing pH (pH 2, 3, 4, 5, 6 & 7). Each specimen was kept in citric acid for three hours a day, and the rest of time stored in salivary substitute. This procedure was repeated for 8 days. After conditioning, the surface roughness (Ra, μm) of each specimen was measured using a surface profilometer (Taylor & Habson, UK). Data was analyzed using one-way analysis of variance (ANOVA) and Tukey's HSD test at a significance level of 0.05. The surface textures of all the tested glass ionomer restorative materials protected with G-coat plus were not significantly affected by acids at low pH. The surface textures of all the tested glass ionomer restorative materials protected with petroleum jelly coating were significantly affected by acids at low pH. The effects of pH on the surface texture of glass ionomer restoratives are material dependent. Among all the materials tested the surface texture of Type II GIC (Group I) revealed marked deterioration when conditioned in solutions of low pH and was statistically significant. Hence, a protective coating either with G-coat plus or with light polymerized low viscosity unfilled resin adhesives is mandatory for all the glass ionomer restorations to increase the wear resistance of the restorative materials.

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

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

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

2012-01-01

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

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

Science.gov (United States)

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

2013-01-01

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

Facial expression recognition in the wild based on multimodal texture features

Science.gov (United States)

Sun, Bo; Li, Liandong; Zhou, Guoyan; He, Jun

2016-11-01

Facial expression recognition in the wild is a very challenging task. We describe our work in static and continuous facial expression recognition in the wild. We evaluate the recognition results of gray deep features and color deep features, and explore the fusion of multimodal texture features. For the continuous facial expression recognition, we design two temporal-spatial dense scale-invariant feature transform (SIFT) features and combine multimodal features to recognize expression from image sequences. For the static facial expression recognition based on video frames, we extract dense SIFT and some deep convolutional neural network (CNN) features, including our proposed CNN architecture. We train linear support vector machine and partial least squares classifiers for those kinds of features on the static facial expression in the wild (SFEW) and acted facial expression in the wild (AFEW) dataset, and we propose a fusion network to combine all the extracted features at decision level. The final achievement we gained is 56.32% on the SFEW testing set and 50.67% on the AFEW validation set, which are much better than the baseline recognition rates of 35.96% and 36.08%.

Investigations on femtosecond laser modified micro-textured surface with anti-friction property on bearing steel GCr15

Science.gov (United States)

Yang, Lijun; Ding, Ye; Cheng, Bai; He, Jiangtao; Wang, Genwang; Wang, Yang

2018-03-01

This work puts forward femtosecond laser modification of micro-textured surface on bearing steel GCr15 in order to reduce frictional wear and enhance load capacity during its application. Multi pulses femtosecond laser ablation experiments are established for the confirmation of laser spot radius as well as single pulse threshold fluence and pulse incubation coefficient of bulk material. Analytical models are set up in combination with hydrodynamics lubrication theory. Corresponding simulations are carried out on to explore influences of surface and cross sectional morphology of textures on hydrodynamics lubrication effect based on Navier-Stokes (N-S) equation. Technological experiments focus on the impacts of femtosecond laser machining variables, like scanning times, scanning velocity, pulse frequency and scanning gap on morphology of grooves as well as realization of optimized textures proposed by simulations, mechanisms of which are analyzed from multiple perspectives. Results of unidirectional rotating friction tests suggest that spherical texture with depth-to-width ratio of 0.2 can significantly improve tribological properties at low loading and velocity condition comparing with un-textured and other textured surfaces, which also verifies the accuracy of simulations and feasibility of femtosecond laser in modification of micro-textured surface.

Surface passivation of nano-textured fluorescent SiC by atomic layer deposited TiO2

DEFF Research Database (Denmark)

Lu, Weifang; Ou, Yiyu; Jokubavicius, Valdas

2016-01-01

Nano-textured surfaces have played a key role in optoelectronic materials to enhance the light extraction efficiency. In this work, morphology and optical properties of nano-textured SiC covered with atomic layer deposited (ALD) TiO2 were investigated. In order to obtain a high quality surface fo...

Features of the normal choriocapillaris with OCT-angiography: Density estimation and textural properties.

Science.gov (United States)

Montesano, Giovanni; Allegrini, Davide; Colombo, Leonardo; Rossetti, Luca M; Pece, Alfredo

2017-01-01

The main objective of our work is to perform an in depth analysis of the structural features of normal choriocapillaris imaged with OCT Angiography. Specifically, we provide an optimal radius for a circular Region of Interest (ROI) to obtain a stable estimate of the subfoveal choriocapillaris density and characterize its textural properties using Markov Random Fields. On each binarized image of the choriocapillaris OCT Angiography we performed simulated measurements of the subfoveal choriocapillaris densities with circular Regions of Interest (ROIs) of different radii and with small random displacements from the center of the Foveal Avascular Zone (FAZ). We then calculated the variability of the density measure with different ROI radii. We then characterized the textural features of choriocapillaris binary images by estimating the parameters of an Ising model. For each image we calculated the Optimal Radius (OR) as the minimum ROI radius required to obtain a standard deviation in the simulation below 0.01. The density measured with the individual OR was 0.52 ± 0.07 (mean ± STD). Similar density values (0.51 ± 0.07) were obtained using a fixed ROI radius of 450 μm. The Ising model yielded two parameter estimates (β = 0.34 ± 0.03; γ = 0.003 ± 0.012; mean ± STD), characterizing pixel clustering and white pixel density respectively. Using the estimated parameters to synthetize new random textures via simulation we obtained a good reproduction of the original choriocapillaris structural features and density. In conclusion, we developed an extensive characterization of the normal subfoveal choriocapillaris that might be used for flow analysis and applied to the investigation pathological alterations.

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

Science.gov (United States)

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

2018-01-01

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

Development of natively textured surface hydrogenated Ga-doped ZnO-TCO thin films for solar cells via magnetron sputtering

International Nuclear Information System (INIS)

Wang, Fei; Chen, Xin-liang; Geng, Xin-hua; Zhang, De-kun; Wei, Chang-chun; Huang, Qian; Zhang, Xiao-dan; Zhao, Ying

2012-01-01

Highlights: ► Natively textured surface hydrogenated gallium-doped zinc oxide (HGZO) thin films have been deposited via magnetron sputtering on glass substrates. ► The directly deposited HGZO thin films present rough crater-type surface morphology. ► Typical HGZO thin film exhibits a high electron mobility of 41.3 cm 2 /V s and a relative low sheet resistance of ∼7.0 Ω. ► These HGZO thin films have high optical transmittances in the visible and near infrared region (∼380–1100 nm). ► A gradient H 2 growth method for fabricating HGZO thin films has been proposed in magnetron sputtering process. - Abstract: The main purposes are to obtain high quality transparent conductive oxide (TCO) based on zinc oxide (ZnO) thin films with high optical transparency in the visible and near infrared spectral range, high electrical conductivity and good light-scattering capability to enhance the path of the light inside the Si-based thin film solar cells. Natively textured surface hydrogenated gallium-doped ZnO (HGZO) thin films have been deposited via pulsed direct current (DC) magnetron sputtering on glass substrates at a substrate temperature of 553 K. These natively textured HGZO thin films exhibit high optical transmittance (over 80%) in the visible and near infrared region (λ = 380–1100 nm) and excellent electrical properties. The optimized HGZO thin film with crater-type textured surface obtained at the hydrogen flow rate of ∼2.0 sccm exhibits a high electron mobility of 41.3 cm 2 /V s and a relatively low sheet resistance of ∼7.0 Ω. The influences of hydrogen flow rates on the surface morphology, electrical and optical properties of HGZO thin films were investigated in detail. In addition, we put forward a method of gradient H 2 growth technique for fabricating HGZO thin films so as to obtain rough surface structure with good light-scattering capability and high electrical conductivity. “Crater-like” surface feature size and optical transmittance

Broadband absorption enhancement in amorphous Si solar cells using metal gratings and surface texturing

Science.gov (United States)

Magdi, Sara; Swillam, Mohamed A.

2017-02-01

The efficiencies of thin film amorphous silicon (a-Si) solar cells are restricted by the small thickness required for efficient carrier collection. This thickness limitations result in poor light absorption. In this work, broadband absorption enhancement is theoretically achieved in a-Si solar cells by using nanostructured back electrode along with surface texturing. The back electrode is formed of Au nanogratings and the surface texturing consists of Si nanocones. The results were then compared to random texturing surfaces. Three dimensional finite difference time domain (FDTD) simulations are used to design and optimize the structure. The Au nanogratings achieved absorption enhancement in the long wavelengths due to sunlight coupling to surface plasmon polaritons (SPP) modes. High absorption enhancement was achieved at short wavelengths due to the decreased reflection and enhanced scattering inside the a-Si absorbing layer. Optimizations have been performed to obtain the optimal geometrical parameters for both the nanogratings and the periodic texturing. In addition, an enhancement factor (i.e. absorbed power in nanostructured device/absorbed power in reference device) was calculated to evaluate the enhancement obtained due to the incorporation of each nanostructure.

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

International Nuclear Information System (INIS)

Yang, F; Byrd, D; Bowen, S; Kinahan, P; Sandison, G

2015-01-01

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

Shape-Tailored Features and their Application to Texture Segmentation

KAUST Repository

Khan, Naeemullah

2014-01-01

Texture Segmentation is one of the most challenging areas of computer vision. One reason for this difficulty is the huge variety and variability of textures occurring in real world, making it very difficult to quantitatively study textures. One

Extracting Corresponding Point Based on Texture Synthesis for Nearly Flat Textureless Object Surface

Directory of Open Access Journals (Sweden)

Min Mao

2015-01-01

Full Text Available Since the image feature points are always gathered at the range with significant intensity change, such as textured portions or edges of an image, which can be detected by the state-of-the-art intensity based point-detectors, there is nearly no point in the areas of low textured detected by classical interest-point detectors. In this paper we describe a novel algorithm based on affine transform and graph cut for interest point detecting and matching from wide baseline image pairs with weakly textured object. The detection and matching mechanism can be separated into three steps: firstly, the information on the large textureless areas will be enhanced by adding textures through the proposed texture synthesis algorithm TSIQ. Secondly, the initial interest-point set is detected by classical interest-point detectors. Finally, graph cuts are used to find the globally optimal set of matching points on stereo pairs. The efficacy of the proposed algorithm is verified by three kinds of experiments, that is, the influence of point detecting from synthetic texture with different texture sample, the stability under the different geometric transformations, and the performance to improve the quasi-dense matching algorithm, respectively.

Dental microwear textures: reconstructing diets of fossil mammals

International Nuclear Information System (INIS)

DeSantis, Larisa R G

2016-01-01

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

Surface fractal dimensions and textural properties of mesoporous alkaline-earth hydroxyapatites

International Nuclear Information System (INIS)

Vilchis-Granados, J.; Granados-Correa, F.; Barrera-Díaz, C.E.

2013-01-01

This work examines the surface fractal dimensions (D f ) and textural properties of three different alkaline-earth hydroxyapatites. Calcium, strontium and barium hydroxyapatite compounds were successfully synthesized via chemical precipitation method and characterized using X-ray diffraction, scanning electron microscopy, energy dispersive X-ray spectrometry, Fourier transform infrared spectroscopy, and N 2 -physisorption measurements. Surface fractal dimensions were determined using single N 2 -adsorption/desorption isotherms method to quantify the irregular surface of as-prepared compounds. The obtained materials were also characterized through their surface hydroxyl group content, determined by the mass titration method. It was found that the D f values for the three materials covered the range of 0.77 ± 0.04–2.33 ± 0.11; these results indicated that the materials tend to have smooth surfaces, except the irregular surface of barium hydroxyapatite. Moreover, regarding the synthesized calcium hydroxyapatite exhibited better textural properties compared with the synthesized strontium and barium hydroxyapatites for adsorbent purposes. However, barium hydroxyapatite shows irregular surface, indicating a high population of active sites across the surface, in comparison with the others studied hydroxyapatites. Finally, the results showed a linear correlation between the surface hydroxyl group content at the external surface of materials and their surface fractal dimensions.

Evaluation of Shape and Textural Features from CT as Prognostic Biomarkers in Non-small Cell Lung Cancer.

Science.gov (United States)

Bianconi, Francesco; Fravolini, Mario Luca; Bello-Cerezo, Raquel; Minestrini, Matteo; Scialpi, Michele; Palumbo, Barbara

2018-04-01

We retrospectively investigated the prognostic potential (correlation with overall survival) of 9 shape and 21 textural features from non-contrast-enhanced computed tomography (CT) in patients with non-small-cell lung cancer. We considered a public dataset of 203 individuals with inoperable, histologically- or cytologically-confirmed NSCLC. Three-dimensional shape and textural features from CT were computed using proprietary code and their prognostic potential evaluated through four different statistical protocols. Volume and grey-level run length matrix (GLRLM) run length non-uniformity were the only two features to pass all four protocols. Both features correlated negatively with overall survival. The results also showed a strong dependence on the evaluation protocol used. Tumour volume and GLRLM run-length non-uniformity from CT were the best predictor of survival in patients with non-small-cell lung cancer. We did not find enough evidence to claim a relationship with survival for the other features. Copyright© 2018, International Institute of Anticancer Research (Dr. George J. Delinasios), All rights reserved.

Ultra short pulse laser generated surface textures for anti-ice applications in aviation

NARCIS (Netherlands)

Römer, G.W.; Del Cerro, D.A.; Sipkema, R.C.J.; Groenendijk, M.N.W.; Huis in 't Veld, A.J.

2009-01-01

By laser ablation with ultra short laser pulses in the pico- and femto-second range, well controlled dual scaled micro- and nano-scaled surface textures can be obtained. The micro-scale of the texture is mainly determined by the dimensions of the laser spot, whereas the superimposed nano-structure

Haralick textural features on T2 -weighted MRI are associated with biochemical recurrence following radiotherapy for peripheral zone prostate cancer.

Science.gov (United States)

Gnep, Khémara; Fargeas, Auréline; Gutiérrez-Carvajal, Ricardo E; Commandeur, Frédéric; Mathieu, Romain; Ospina, Juan D; Rolland, Yan; Rohou, Tanguy; Vincendeau, Sébastien; Hatt, Mathieu; Acosta, Oscar; de Crevoisier, Renaud

2017-01-01

To explore the association between magnetic resonance imaging (MRI), including Haralick textural features, and biochemical recurrence following prostate cancer radiotherapy. In all, 74 patients with peripheral zone localized prostate adenocarcinoma underwent pretreatment 3.0T MRI before external beam radiotherapy. Median follow-up of 47 months revealed 11 patients with biochemical recurrence. Prostate tumors were segmented on T 2 -weighted sequences (T 2 -w) and contours were propagated onto the coregistered apparent diffusion coefficient (ADC) images. We extracted 140 image features from normalized T 2 -w and ADC images corresponding to first-order (n = 6), gradient-based (n = 4), and second-order Haralick textural features (n = 130). Four geometrical features (tumor diameter, perimeter, area, and volume) were also computed. Correlations between Gleason score and MRI features were assessed. Cox regression analysis and random survival forests (RSF) were performed to assess the association between MRI features and biochemical recurrence. Three T 2 -w and one ADC Haralick textural features were significantly correlated with Gleason score (P recurrence (P recurrence following prostate cancer radiotherapy. 3 J. Magn. Reson. Imaging 2017;45:103-117. © 2016 International Society for Magnetic Resonance in Medicine.

Superhydrophylic textures fabricated by femtosecond laser pulses on sub-micro- and nano-crystalline titanium surfaces

International Nuclear Information System (INIS)

Kolobov, Yury R; Smolyakova, Marina Yu; Kolobova, Anastasia Yu; Ionin, Andrey A; Kudryashov, Sergey I; Makarov, Sergey V; Saltuganov, Pavel N; Zayarny, Dmitry A; Ligachev, Alexander E

2014-01-01

Sub-micron quasi-regular surface textures were fabricated on surfaces of pure titanium (VT1-0) with micro- and ultrafine-grained bulk structures by multiple femtosecond laser pulses in the scanning mode and characterized by scanning electron and atomic force microscopy. Their wetting characteristics acquired for the initial non-textured and as-textured samples, as well as upon ultrasonic and plasma cleaning, demonstrate corresponding drastic changes of the wetting angles from 87° to ≤ 10°, with much more pronounced contamination, cleaning and wetting effects for the ultrafine-grained titanium. (letter)

Geometric Total Variation for Texture Deformation

DEFF Research Database (Denmark)

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

2010-01-01

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

A New Rig for Testing Textured Surfaces in Pure Sliding Conditions

DEFF Research Database (Denmark)

Godi, Alessandro; Grønbæk, J.; Mohaghegh, Kamran

2013-01-01

machineries are necessary: a press to provide the normal pressure and a tensile machine to perform the axial movements. The test is calibrated so that the correspondence between the normal pressure and the container advancement is found. Preliminary tests are carried out involving a multifunctional and a fine......Throughout the years, it has become more and more important to find new methods for reducing friction and wear occurrence in machine elements. A possible solution is found in texturing the surfaces under tribological contact, as demonstrated by the development and spread of plateau-honed surface...... for cylinder liners. To prove the efficacy of a particular textured surface, it is paramount to perform experimental tests under controlled laboratory conditions. In this paper, a new test rig simulating pure sliding conditions is presented, dubbed axial sliding test. It presents four major components: a rod...

Ion-beam texturing of uniaxially textured Ni films

International Nuclear Information System (INIS)

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

2005-01-01

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

Textural features of 18F-fluorodeoxyglucose positron emission tomography scanning in diagnosing aortic prosthetic graft infection.

Science.gov (United States)

Saleem, Ben R; Beukinga, Roelof J; Boellaard, Ronald; Glaudemans, Andor W J M; Reijnen, Michel M P J; Zeebregts, Clark J; Slart, Riemer H J A

2017-05-01

The clinical problem in suspected aortoiliac graft infection (AGI) is to obtain proof of infection. Although 18 F-fluorodeoxyglucose ( 18 F-FDG) positron emission tomography scanning (PET) has been suggested to play a pivotal role, an evidence-based interpretation is lacking. The objective of this retrospective study was to examine the feasibility and utility of 18 F-FDG uptake heterogeneity characterized by textural features to diagnose AGI. Thirty patients with a history of aortic graft reconstruction who underwent 18 F-FDG PET/CT scanning were included. Sixteen patients were suspected to have an AGI (group I). AGI was considered proven only in the case of a positive bacterial culture. Positive cultures were found in 10 of the 16 patients (group Ia), and in the other six patients, cultures remained negative (group Ib). A control group was formed of 14 patients undergoing 18 F-FDG PET for other reasons (group II). PET images were assessed using conventional maximal standardized uptake value (SUVmax), tissue-to-background ratio (TBR), and visual grading scale (VGS). Additionally, 64 different 18 F-FDG PET based textural features were applied to characterize 18 F-FDG uptake heterogeneity. To select candidate predictors, univariable logistic regression analysis was performed (α = 0.16). The accuracy was satisfactory in case of an AUC > 0.8. The feature selection process yielded the textural features named variance (AUC = 0.88), high grey level zone emphasis (AUC = 0.87), small zone low grey level emphasis (AUC = 0.80), and small zone high grey level emphasis (AUC = 0.81) most optimal for distinguishing between groups I and II. SUVmax, TBR, and VGS were also able to distinguish between these groups with AUCs of 0.87, 0.78, and 0.90, respectively. The textural feature named short run high grey level emphasis was able to distinguish group Ia from Ib (AUC = 0.83), while for the same task the TBR and VGS were not found to be predictive. SUVmax

False Discovery Rates in PET and CT Studies with Texture Features: A Systematic Review.

Directory of Open Access Journals (Sweden)

Anastasia Chalkidou

Full Text Available A number of recent publications have proposed that a family of image-derived indices, called texture features, can predict clinical outcome in patients with cancer. However, the investigation of multiple indices on a single data set can lead to significant inflation of type-I errors. We report a systematic review of the type-I error inflation in such studies and review the evidence regarding associations between patient outcome and texture features derived from positron emission tomography (PET or computed tomography (CT images.For study identification PubMed and Scopus were searched (1/2000-9/2013 using combinations of the keywords texture, prognostic, predictive and cancer. Studies were divided into three categories according to the sources of the type-I error inflation and the use or not of an independent validation dataset. For each study, the true type-I error probability and the adjusted level of significance were estimated using the optimum cut-off approach correction, and the Benjamini-Hochberg method. To demonstrate explicitly the variable selection bias in these studies, we re-analyzed data from one of the published studies, but using 100 random variables substituted for the original image-derived indices. The significance of the random variables as potential predictors of outcome was examined using the analysis methods used in the identified studies.Fifteen studies were identified. After applying appropriate statistical corrections, an average type-I error probability of 76% (range: 34-99% was estimated with the majority of published results not reaching statistical significance. Only 3/15 studies used a validation dataset. For the 100 random variables examined, 10% proved to be significant predictors of survival when subjected to ROC and multiple hypothesis testing analysis.We found insufficient evidence to support a relationship between PET or CT texture features and patient survival. Further fit for purpose validation of these

False Discovery Rates in PET and CT Studies with Texture Features: A Systematic Review.

Science.gov (United States)

Chalkidou, Anastasia; O'Doherty, Michael J; Marsden, Paul K

2015-01-01

A number of recent publications have proposed that a family of image-derived indices, called texture features, can predict clinical outcome in patients with cancer. However, the investigation of multiple indices on a single data set can lead to significant inflation of type-I errors. We report a systematic review of the type-I error inflation in such studies and review the evidence regarding associations between patient outcome and texture features derived from positron emission tomography (PET) or computed tomography (CT) images. For study identification PubMed and Scopus were searched (1/2000-9/2013) using combinations of the keywords texture, prognostic, predictive and cancer. Studies were divided into three categories according to the sources of the type-I error inflation and the use or not of an independent validation dataset. For each study, the true type-I error probability and the adjusted level of significance were estimated using the optimum cut-off approach correction, and the Benjamini-Hochberg method. To demonstrate explicitly the variable selection bias in these studies, we re-analyzed data from one of the published studies, but using 100 random variables substituted for the original image-derived indices. The significance of the random variables as potential predictors of outcome was examined using the analysis methods used in the identified studies. Fifteen studies were identified. After applying appropriate statistical corrections, an average type-I error probability of 76% (range: 34-99%) was estimated with the majority of published results not reaching statistical significance. Only 3/15 studies used a validation dataset. For the 100 random variables examined, 10% proved to be significant predictors of survival when subjected to ROC and multiple hypothesis testing analysis. We found insufficient evidence to support a relationship between PET or CT texture features and patient survival. Further fit for purpose validation of these image

The study of road surface micro-texture's effects for the pavement's decontamination by high pressure water washing

International Nuclear Information System (INIS)

Kobayashi, Masatoshi; Shimizu, Tadaaki; Hirayama, Takahiro

2014-01-01

In the result of “decontamination technical demonstration project” by Ministry of the Environment, it has became clear that the effect variation is larger in high pressure water washing method, compared with others in road surface decontamination technology. In this study, we have hypothesized the fact at the difference of micro-texture of the road surface, by carrying out high pressure water washing method in different kinds of road surfaces and verified the relation between washing efficiency and micro-texture road surface. Positive correlation has admitted between the washing number of times and radiation reduction rate and the trend of primary regression equation (i.e. radiation reduction rate per washing time) is indicating that decreasing tendency of radiation carried by the increasing of micro-texture of the road surface. Here, we proposed the method to estimated essential washing number of times to achieve the targeted radiation reduction rate from the relation of that trend and micro-texture of the road surface. (author)

Emergent Momentum-Space Skyrmion Texture on the Surface of Topological Insulators

Science.gov (United States)

Mohanta, Narayan; Kampf, Arno P.; Kopp, Thilo

The quantum anomalous Hall effect has been theoretically predicted and experimentally verified in magnetic topological insulators. In addition, the surface states of these materials exhibit a hedgehog-like ``spin'' texture in momentum space. Here, we apply the previously formulated low-energy model for Bi2Se3, a parent compound for magnetic topological insulators, to a slab geometry in which an exchange field acts only within one of the surface layers. In this sample set up, the hedgehog transforms into a skyrmion texture beyond a critical exchange field. This critical field marks a transition between two topologically distinct phases. The topological phase transition takes place without energy gap closing at the Fermi level and leaves the transverse Hall conductance unchanged and quantized to e2 / 2 h . The momentum-space skyrmion texture persists in a finite field range. It may find its realization in hybrid heterostructures with an interface between a three-dimensional topological insulator and a ferromagnetic insulator. The work was supported by the Deutsche Forschungsgemeinschaft through TRR 80.

Response monitoring of breast cancer patients receiving neoadjuvant chemotherapy using quantitative ultrasound, texture, and molecular features.

Directory of Open Access Journals (Sweden)

Lakshmanan Sannachi

Full Text Available Pathological response of breast cancer to chemotherapy is a prognostic indicator for long-term disease free and overall survival. Responses of locally advanced breast cancer in the neoadjuvant chemotherapy (NAC settings are often variable, and the prediction of response is imperfect. The purpose of this study was to detect primary tumor responses early after the start of neoadjuvant chemotherapy using quantitative ultrasound (QUS, textural analysis and molecular features in patients with locally advanced breast cancer.The study included ninety six patients treated with neoadjuvant chemotherapy. Breast tumors were scanned with a clinical ultrasound system prior to chemotherapy treatment, during the first, fourth and eighth week of treatment, and prior to surgery. Quantitative ultrasound parameters and scatterer-based features were calculated from ultrasound radio frequency (RF data within tumor regions of interest. Additionally, texture features were extracted from QUS parametric maps. Prior to therapy, all patients underwent a core needle biopsy and histological subtypes and biomarker ER, PR, and HER2 status were determined. Patients were classified into three treatment response groups based on combination of clinical and pathological analyses: complete responders (CR, partial responders (PR, and non-responders (NR. Response classifications from QUS parameters, receptors status and pathological were compared. Discriminant analysis was performed on extracted parameters using a support vector machine classifier to categorize subjects into CR, PR, and NR groups at all scan times.Of the 96 patients, the number of CR, PR and NR patients were 21, 52, and 23, respectively. The best prediction of treatment response was achieved with the combination mean QUS values, texture and molecular features with accuracies of 78%, 86% and 83% at weeks 1, 4, and 8, after treatment respectively. Mean QUS parameters or clinical receptors status alone predicted the

Evaporation dynamics of completely wetting drops on geometrically textured surfaces

Science.gov (United States)

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

2017-10-01

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

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

Science.gov (United States)

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

2017-02-01

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

Dynamic Leidenfrost temperature on micro-textured surfaces: Acoustic wave absorption into thin vapor layer

Science.gov (United States)

Jerng, Dong Wook; Kim, Dong Eok

2018-01-01

The dynamic Leidenfrost phenomenon is governed by three types of pressure potentials induced via vapor hydrodynamics, liquid dynamic pressure, and the water hammer effect resulting from the generation of acoustic waves at the liquid-vapor interface. The prediction of the Leidenfrost temperature for a dynamic droplet needs quantitative evaluation and definition for each of the pressure fields. In particular, the textures on a heated surface can significantly affect the vapor hydrodynamics and the water hammer pressure. We present a quantitative model for evaluating the water hammer pressure on micro-textured surfaces taking into account the absorption of acoustic waves into the thin vapor layer. The model demonstrates that the strength of the acoustic flow into the liquid droplet, which directly contributes to the water hammer pressure, depends on the magnitude of the acoustic resistance (impedance) in the droplet and the vapor region. In consequence, the micro-textures of the surface and the increased spacing between them reduce the water hammer coefficient ( kh ) defined as the ratio of the acoustic flow into the droplet to total generated flow. Aided by numerical calculations that solve the laminar Navier-Stokes equation for the vapor flow, we also predict the dynamic Leidenfrost temperature on a micro-textured surface with reliable accuracy consistent with the experimental data.

Surface Texturing-Plasma Nitriding Duplex Treatment for Improving Tribological Performance of AISI 316 Stainless Steel

Directory of Open Access Journals (Sweden)

Naiming Lin

2016-10-01

Full Text Available Surface texturing-plasma nitriding duplex treatment was conducted on AISI 316 stainless steel to improve its tribological performance. Tribological behaviors of ground 316 substrates, plasma-nitrided 316 (PN-316, surface-textured 316 (ST-316, and duplex-treated 316 (DT-316 in air and under grease lubrication were investigated using a pin-on-disc rotary tribometer against counterparts of high carbon chromium bearing steel GCr15 and silicon nitride Si3N4 balls. The variations in friction coefficient, mass loss, and worn trace morphology of the tested samples were systemically investigated and analyzed. The results showed that a textured surface was formed on 316 after electrochemical processing in a 15 wt % NaCl solution. Grooves and dimples were found on the textured surface. As plasma nitriding was conducted on a 316 substrate and ST-316, continuous and uniform nitriding layers were successfully fabricated on the surfaces of the 316 substrate and ST-316. Both of the obtained nitriding layers presented thickness values of more than 30 μm. The nitriding layers were composed of iron nitrides and chromium nitride. The 316 substrate and ST-316 received improved surface hardness after plasma nitriding. When the tribological tests were carried out under dry sliding and grease lubrication conditions, the tested samples showed different tribological behaviors. As expected, the DT-316 samples revealed the most promising tribological properties, reflected by the lowest mass loss and worn morphologies. The DT-316 received the slightest damage, and its excellent tribological performance was attributed to the following aspects: firstly, the nitriding layer had high surface hardness; secondly, the surface texture was able to capture wear debris, store up grease, and then provide continuous lubrication.

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

International Nuclear Information System (INIS)

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

2015-01-01

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

Thin plate spline feature point matching for organ surfaces in minimally invasive surgery imaging

Science.gov (United States)

Lin, Bingxiong; Sun, Yu; Qian, Xiaoning

2013-03-01

Robust feature point matching for images with large view angle changes in Minimally Invasive Surgery (MIS) is a challenging task due to low texture and specular reflections in these images. This paper presents a new approach that can improve feature matching performance by exploiting the inherent geometric property of the organ surfaces. Recently, intensity based template image tracking using a Thin Plate Spline (TPS) model has been extended for 3D surface tracking with stereo cameras. The intensity based tracking is also used here for 3D reconstruction of internal organ surfaces. To overcome the small displacement requirement of intensity based tracking, feature point correspondences are used for proper initialization of the nonlinear optimization in the intensity based method. Second, we generate simulated images from the reconstructed 3D surfaces under all potential view positions and orientations, and then extract feature points from these simulated images. The obtained feature points are then filtered and re-projected to the common reference image. The descriptors of the feature points under different view angles are stored to ensure that the proposed method can tolerate a large range of view angles. We evaluate the proposed method with silicon phantoms and in vivo images. The experimental results show that our method is much more robust with respect to the view angle changes than other state-of-the-art methods.

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

Science.gov (United States)

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

2017-07-01

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

A Local Texture-Based Superpixel Feature Coding for Saliency Detection Combined with Global Saliency

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Bingfei Nan

2015-12-01

Full Text Available Because saliency can be used as the prior knowledge of image content, saliency detection has been an active research area in image segmentation, object detection, image semantic understanding and other relevant image-based applications. In the case of saliency detection from cluster scenes, the salient object/region detected needs to not only be distinguished clearly from the background, but, preferably, to also be informative in terms of complete contour and local texture details to facilitate the successive processing. In this paper, a Local Texture-based Region Sparse Histogram (LTRSH model is proposed for saliency detection from cluster scenes. This model uses a combination of local texture patterns and color distribution as well as contour information to encode the superpixels to characterize the local feature of image for region contrast computing. Combining the region contrast as computed with the global saliency probability, a full-resolution salient map, in which the salient object/region detected adheres more closely to its inherent feature, is obtained on the bases of the corresponding high-level saliency spatial distribution as well as on the pixel-level saliency enhancement. Quantitative comparisons with five state-of-the-art saliency detection methods on benchmark datasets are carried out, and the comparative results show that the method we propose improves the detection performance in terms of corresponding measurements.

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

International Nuclear Information System (INIS)

Masotti, Matteo; Lanconelli, Nico; Campanini, Renato

2009-01-01

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

All Organic Polymers Based Morphing Skin with Controllable Surface Texture

KAUST Repository

Favero Bolson, Natanael

2018-05-01

Smart skins are integrating an increasing number of functionalities in order to improve the interaction between the systems they equip and their ambient environment. Here we have developed an electromechanical soft actuator with controlled surface texture due to applied thermal gradient via electrical voltage. The device was fabricated and integrated with optimized process parameters for a prepared heater element [doped PEDOT: PSS (poly-(3, 4 ethylenedioxythiophene): poly (styrene sulfonic acid))], a soft actuator (Ecoflex 00-50/ethanol) and overall packaging case [PDMS (polydimethylsiloxane)]. To study a potential application of the proposed smart skin, we analyze the fluid drag reduction in a texture controlled water flow unit. As a result, we obtained a reduction of approximately 14% in the skin drag friction coefficient during the actuation. We conclude that the proposed soft actuator device is a preferred option for a texture-controlled skin that reduces the skin drag friction coefficient.

Anti-reflection textured structures by wet etching and island lithography for surface-enhanced Raman spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Chao, Bo-Kai [Department of Materials Science and Engineering, National Taiwan University, Taipei 10617, Taiwan (China); Cheng, Hsin-Hung [Department of Marine Engineering, Taipei College of Maritime Technology, Taipei 11174, Taiwan (China); Nien, Li-Wei; Chen, Miin-Jang [Department of Materials Science and Engineering, National Taiwan University, Taipei 10617, Taiwan (China); Nagao, Tadaaki [Center for Materials Nanoarchitectonics, National Institute for Materials Science, Tsukuba, Ibaraki 305-0044 (Japan); Li, Jia-Han [Department of Engineering Science and Ocean Engineering, National Taiwan University, Taipei 10617, Taiwan (China); Hsueh, Chun-Hway, E-mail: hsuehc@ntu.edu.tw [Department of Materials Science and Engineering, National Taiwan University, Taipei 10617, Taiwan (China)

2015-12-01

Graphical abstract: - Highlights: • We fabricated textured SERS substrate with a high surface area and low reflectance. • Large surface area of substrate contains more gold nanodroplets to absorb analytes. • Low reflectance of textured SERS substrate enabled multiple reflections of incident laser light. • We obtained strong SERS enhancement from nanopillar-on-pyramid SERS substrate. - Abstract: A high surface area and low reflection textured surface-enhanced Raman scattering (SERS) substrate with plasmonic gold nanodroplets fabricated by wet etching and island lithography was reported in the present study. Specifically, four textured substrates, planar, pyramid, nanopillar, and nanopillar-on-pyramid, were fabricated. The fabricated structures were simulated using the finite-difference time-domain method and the results agreed with the reflection and dark-field scattering measurements. Although the SERS signals varied in different measured regions because of the random nanostructure, the SERS substrates with nanopillar-on-pyramid structure always have the stronger enhancement factor than the SERS substrates with only pyramids or nanopillars. Based on the atomic force microscope and reflection measurements, the nanopillar-on-pyramid structure provided a large surface area and multiple reflections for SERS enhancement, which was about 3 orders of magnitude larger than that of the planar substrate. Our results can be applied to fabricate the inexpensive, large surface area, and high SERS enhancement substrates.

Laser surface texturing for high control of interference fit joint load bearing

Science.gov (United States)

Obeidi, M. Ahmed; McCarthy, E.; Brabazon, D.

2017-10-01

Laser beams attract the attention of researchers, engineers and manufacturer as they can deliver high energy with finite controlled processing parameters and heat affected zone (HAZ) on almost all kind of materials [1-3]. Laser beams can be generated in the broad range of wavelengths, energies and beam modes in addition to the unique property of propagation in straight lines with less or negligible divergence [3]. These features made lasers preferential for metal treatment and surface modification over the conventional machining and heat treatment methods. Laser material forming and processing is prosperous and competitive because of its flexibility and the creation of new solutions and techniques [3-5]. This study is focused on the laser surface texture of 316L stainless steel pins for the application of interference fit, widely used in automotive and aerospace industry. The main laser processing parameters applied are the power, frequency and the overlapping laser beam scans. The produced samples were characterized by measuring the increase in the insertion diameter, insertion and removal force, surface morphology and cross section alteration and the modified layer chemical composition and residual stresses.

Stretchable surfaces with programmable 3D texture morphing for synthetic camouflaging skins

Science.gov (United States)

Pikul, J. H.; Li, S.; Bai, H.; Hanlon, R. T.; Cohen, I.; Shepherd, R. F.

2017-10-01

Technologies that use stretchable materials are increasingly important, yet we are unable to control how they stretch with much more sophistication than inflating balloons. Nature, however, demonstrates remarkable control of stretchable surfaces; for example, cephalopods can project hierarchical structures from their skin in milliseconds for a wide range of textural camouflage. Inspired by cephalopod muscular morphology, we developed synthetic tissue groupings that allowed programmable transformation of two-dimensional (2D) stretchable surfaces into target 3D shapes. The synthetic tissue groupings consisted of elastomeric membranes embedded with inextensible textile mesh that inflated to within 10% of their target shapes by using a simple fabrication method and modeling approach. These stretchable surfaces transform from flat sheets to 3D textures that imitate natural stone and plant shapes and camouflage into their background environments.

Improved bioactivity of selective laser melting titanium: Surface modification with micro-/nano-textured hierarchical topography and bone regeneration performance evaluation

Energy Technology Data Exchange (ETDEWEB)

Xu, Jia-yun [Department of Oral Implantology, Guanghua School of Stomatology, Hospital of Stomatology, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Stomatology, Guangzhou 510055 (China); Chen, Xian-shuai; Zhang, Chun-yu [Guangzhou Institute of Advanced Technology, Chinese Academy of Science, Guangzhou 511458 (China); Liu, Yun; Wang, Jing [Department of Oral Implantology, Guanghua School of Stomatology, Hospital of Stomatology, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Stomatology, Guangzhou 510055 (China); Deng, Fei-long, E-mail: drdfl@163.com [Department of Oral Implantology, Guanghua School of Stomatology, Hospital of Stomatology, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Stomatology, Guangzhou 510055 (China)

2016-11-01

Selective laser melting (SLM) titanium requires surface modification to improve its bioactivity. The microrough surface of it can be utilized as the micro primary substrate to create a micro-/nano-textured topography for improved bone regeneration. In this study, the microrough SLM titanium substrate was optimized by sandblasting, and nano-porous features of orderly arranged nanotubes and disorderly arranged nanonet were produced by anodization (SAN) and alkali-heat treatment (SAH), respectively. The results were compared with the control group of an untreated surface (native-SLM) and a microtopography only surface treated by acid etching (SLA). The effects of the different topographies on cell functions and bone formation performance were evaluated in vitro and in vivo. It was found that micro-/nano-textured topographies of SAN and SAH showed enhanced cell behaviour relative to the microtopography of SLA with significantly higher proliferation on the 1st, 3rd, 5th and 7th day (P < 0.05) and higher total protein contents on the 14th day (P < 0.05). In vivo, SAN and SAH formed more successively regenerated bone, which resulted in higher bone-implant contact (BIC%) and bone-bonding force than native-SLM and SLA. In addition, the three-dimensional nanonet of SAH was expected to be more similar to native extracellular matrix (ECM) and thus led to better bone formation. The alkaline phosphatase activity of SAH was significantly higher than the other three groups at an earlier stage of the 7th day (P < 0.05) and the BIC% was nearly double that of native-SLM and SLA in the 8th week. In conclusion, the addition of nano-porous features on the microrough SLM titanium surface is effective in improving the bioactivity and bone regeneration performance, in which the ECM-like nanonet with a disorderly arranged biomimetic feature is suggested to be more efficient than nanotubes. - Highlights: • SLM titanium is modified by adding nano-porous features to the microrough substrate

Improved bioactivity of selective laser melting titanium: Surface modification with micro-/nano-textured hierarchical topography and bone regeneration performance evaluation

International Nuclear Information System (INIS)

Xu, Jia-yun; Chen, Xian-shuai; Zhang, Chun-yu; Liu, Yun; Wang, Jing; Deng, Fei-long

2016-01-01

Selective laser melting (SLM) titanium requires surface modification to improve its bioactivity. The microrough surface of it can be utilized as the micro primary substrate to create a micro-/nano-textured topography for improved bone regeneration. In this study, the microrough SLM titanium substrate was optimized by sandblasting, and nano-porous features of orderly arranged nanotubes and disorderly arranged nanonet were produced by anodization (SAN) and alkali-heat treatment (SAH), respectively. The results were compared with the control group of an untreated surface (native-SLM) and a microtopography only surface treated by acid etching (SLA). The effects of the different topographies on cell functions and bone formation performance were evaluated in vitro and in vivo. It was found that micro-/nano-textured topographies of SAN and SAH showed enhanced cell behaviour relative to the microtopography of SLA with significantly higher proliferation on the 1st, 3rd, 5th and 7th day (P < 0.05) and higher total protein contents on the 14th day (P < 0.05). In vivo, SAN and SAH formed more successively regenerated bone, which resulted in higher bone-implant contact (BIC%) and bone-bonding force than native-SLM and SLA. In addition, the three-dimensional nanonet of SAH was expected to be more similar to native extracellular matrix (ECM) and thus led to better bone formation. The alkaline phosphatase activity of SAH was significantly higher than the other three groups at an earlier stage of the 7th day (P < 0.05) and the BIC% was nearly double that of native-SLM and SLA in the 8th week. In conclusion, the addition of nano-porous features on the microrough SLM titanium surface is effective in improving the bioactivity and bone regeneration performance, in which the ECM-like nanonet with a disorderly arranged biomimetic feature is suggested to be more efficient than nanotubes. - Highlights: • SLM titanium is modified by adding nano-porous features to the microrough substrate

Fast Image Texture Classification Using Decision Trees

Science.gov (United States)

Thompson, David R.

2011-01-01

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

Non-negative matrix factorization in texture feature for classification of dementia with MRI data

Science.gov (United States)

Sarwinda, D.; Bustamam, A.; Ardaneswari, G.

2017-07-01

This paper investigates applications of non-negative matrix factorization as feature selection method to select the features from gray level co-occurrence matrix. The proposed approach is used to classify dementia using MRI data. In this study, texture analysis using gray level co-occurrence matrix is done to feature extraction. In the feature extraction process of MRI data, we found seven features from gray level co-occurrence matrix. Non-negative matrix factorization selected three features that influence of all features produced by feature extractions. A Naïve Bayes classifier is adapted to classify dementia, i.e. Alzheimer's disease, Mild Cognitive Impairment (MCI) and normal control. The experimental results show that non-negative factorization as feature selection method able to achieve an accuracy of 96.4% for classification of Alzheimer's and normal control. The proposed method also compared with other features selection methods i.e. Principal Component Analysis (PCA).

Classification of pre-sliced pork and Turkey ham qualities based on image colour and textural features and their relationships with consumer responses.

Science.gov (United States)

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-valuetexture 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.

Natural texture retrieval based on perceptual similarity measurement

Science.gov (United States)

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

2018-04-01

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

Textural features of {sup 18}F-fluorodeoxyglucose positron emission tomography scanning in diagnosing aortic prosthetic graft infection

Energy Technology Data Exchange (ETDEWEB)

Saleem, Ben R.; Zeebregts, Clark J. [University of Groningen, University Medical Center Groningen, Department of Surgery, Division of Vascular Surgery, P.O. Box 30 001, Groningen (Netherlands); Beukinga, Roelof J.; Slart, Riemer H.J.A. [University of Groningen, University Medical Center Groningen, Nuclear Medicine and Molecular Imaging, Groningen (Netherlands); University of Twente, Department of Biomedical Photonic Imaging (BMPI), Enschede (Netherlands); Boellaard, Ronald; Glaudemans, Andor W.J.M. [University of Groningen, University Medical Center Groningen, Nuclear Medicine and Molecular Imaging, Groningen (Netherlands); Reijnen, Michel M.P.J. [Rijnstate Hospital, Department of Surgery, Arnhem (Netherlands)

2017-05-15

The clinical problem in suspected aortoiliac graft infection (AGI) is to obtain proof of infection. Although {sup 18}F-fluorodeoxyglucose ({sup 18}F-FDG) positron emission tomography scanning (PET) has been suggested to play a pivotal role, an evidence-based interpretation is lacking. The objective of this retrospective study was to examine the feasibility and utility of {sup 18}F-FDG uptake heterogeneity characterized by textural features to diagnose AGI. Thirty patients with a history of aortic graft reconstruction who underwent {sup 18}F-FDG PET/CT scanning were included. Sixteen patients were suspected to have an AGI (group I). AGI was considered proven only in the case of a positive bacterial culture. Positive cultures were found in 10 of the 16 patients (group Ia), and in the other six patients, cultures remained negative (group Ib). A control group was formed of 14 patients undergoing {sup 18}F-FDG PET for other reasons (group II). PET images were assessed using conventional maximal standardized uptake value (SUVmax), tissue-to-background ratio (TBR), and visual grading scale (VGS). Additionally, 64 different {sup 18}F-FDG PET based textural features were applied to characterize {sup 18}F-FDG uptake heterogeneity. To select candidate predictors, univariable logistic regression analysis was performed (α = 0.16). The accuracy was satisfactory in case of an AUC > 0.8. The feature selection process yielded the textural features named variance (AUC = 0.88), high grey level zone emphasis (AUC = 0.87), small zone low grey level emphasis (AUC = 0.80), and small zone high grey level emphasis (AUC = 0.81) most optimal for distinguishing between groups I and II. SUVmax, TBR, and VGS were also able to distinguish between these groups with AUCs of 0.87, 0.78, and 0.90, respectively. The textural feature named short run high grey level emphasis was able to distinguish group Ia from Ib (AUC = 0.83), while for the same task the TBR and VGS were not found to be predictive

Textural features of "1"8F-fluorodeoxyglucose positron emission tomography scanning in diagnosing aortic prosthetic graft infection

International Nuclear Information System (INIS)

Saleem, Ben R.; Zeebregts, Clark J.; Beukinga, Roelof J.; Slart, Riemer H.J.A.; Boellaard, Ronald; Glaudemans, Andor W.J.M.; Reijnen, Michel M.P.J.

2017-01-01

The clinical problem in suspected aortoiliac graft infection (AGI) is to obtain proof of infection. Although "1"8F-fluorodeoxyglucose ("1"8F-FDG) positron emission tomography scanning (PET) has been suggested to play a pivotal role, an evidence-based interpretation is lacking. The objective of this retrospective study was to examine the feasibility and utility of "1"8F-FDG uptake heterogeneity characterized by textural features to diagnose AGI. Thirty patients with a history of aortic graft reconstruction who underwent "1"8F-FDG PET/CT scanning were included. Sixteen patients were suspected to have an AGI (group I). AGI was considered proven only in the case of a positive bacterial culture. Positive cultures were found in 10 of the 16 patients (group Ia), and in the other six patients, cultures remained negative (group Ib). A control group was formed of 14 patients undergoing "1"8F-FDG PET for other reasons (group II). PET images were assessed using conventional maximal standardized uptake value (SUVmax), tissue-to-background ratio (TBR), and visual grading scale (VGS). Additionally, 64 different "1"8F-FDG PET based textural features were applied to characterize "1"8F-FDG uptake heterogeneity. To select candidate predictors, univariable logistic regression analysis was performed (α = 0.16). The accuracy was satisfactory in case of an AUC > 0.8. The feature selection process yielded the textural features named variance (AUC = 0.88), high grey level zone emphasis (AUC = 0.87), small zone low grey level emphasis (AUC = 0.80), and small zone high grey level emphasis (AUC = 0.81) most optimal for distinguishing between groups I and II. SUVmax, TBR, and VGS were also able to distinguish between these groups with AUCs of 0.87, 0.78, and 0.90, respectively. The textural feature named short run high grey level emphasis was able to distinguish group Ia from Ib (AUC = 0.83), while for the same task the TBR and VGS were not found to be predictive. SUVmax was found predictive

SU-F-R-45: The Prognostic Value of Radiotherapy Based On the Changes of Texture Features Between Pre-Treatment and Post-Treatment FDG PET Image for NSCLC Patients

International Nuclear Information System (INIS)

Ma, C; Yin, Y

2016-01-01

Purpose: The purpose of this research is investigating which texture features extracted from FDG-PET images by gray-level co-occurrence matrix(GLCM) have a higher prognostic value than the other texture features. Methods: 21 non-small cell lung cancer(NSCLC) patients were approved in the study. Patients underwent 18F-FDG PET/CT scans with both pre-treatment and post-treatment. Firstly, the tumors were extracted by our house developed software. Secondly, the clinical features including the maximum SUV and tumor volume were extracted by MIM vista software, and texture features including angular second moment, contrast, inverse different moment, entropy and correlation were extracted using MATLAB.The differences can be calculated by using post-treatment features to subtract pre-treatment features. Finally, the SPSS software was used to get the Pearson correlation coefficients and Spearman rank correlation coefficients between the change ratios of texture features and change ratios of clinical features. Results: The Pearson and Spearman rank correlation coefficient between contrast and SUV maximum is 0.785 and 0.709. The P and S value between inverse difference moment and tumor volume is 0.953 and 0.942. Conclusion: This preliminary study showed that the relationships between different texture features and the same clinical feature are different. Finding the prognostic value of contrast and inverse difference moment were higher than the other three textures extracted by GLCM.

SU-F-R-45: The Prognostic Value of Radiotherapy Based On the Changes of Texture Features Between Pre-Treatment and Post-Treatment FDG PET Image for NSCLC Patients

Energy Technology Data Exchange (ETDEWEB)

Ma, C; Yin, Y [Shandong Cancer Hospital and Institute, China, Jinan, Shandong (China)

2016-06-15

Purpose: The purpose of this research is investigating which texture features extracted from FDG-PET images by gray-level co-occurrence matrix(GLCM) have a higher prognostic value than the other texture features. Methods: 21 non-small cell lung cancer(NSCLC) patients were approved in the study. Patients underwent 18F-FDG PET/CT scans with both pre-treatment and post-treatment. Firstly, the tumors were extracted by our house developed software. Secondly, the clinical features including the maximum SUV and tumor volume were extracted by MIM vista software, and texture features including angular second moment, contrast, inverse different moment, entropy and correlation were extracted using MATLAB.The differences can be calculated by using post-treatment features to subtract pre-treatment features. Finally, the SPSS software was used to get the Pearson correlation coefficients and Spearman rank correlation coefficients between the change ratios of texture features and change ratios of clinical features. Results: The Pearson and Spearman rank correlation coefficient between contrast and SUV maximum is 0.785 and 0.709. The P and S value between inverse difference moment and tumor volume is 0.953 and 0.942. Conclusion: This preliminary study showed that the relationships between different texture features and the same clinical feature are different. Finding the prognostic value of contrast and inverse difference moment were higher than the other three textures extracted by GLCM.

Effect of surface shear on cube texture formation in heavy cold-rolled Cu-45 at%Ni alloy substrates

DEFF Research Database (Denmark)

Tian, Hui; Suo, Hongli; Liang, Yaru

2015-01-01

Two types of Cu-45 at%Ni alloy thin tapes with and without surface shear were obtained by different heavy cold rolling processes. The deformation and recrystallization textures of the two tapes were thoroughly investigated by electron back scattering diffraction technique. The results showed...... that a shear texture mainly covered the surface of the heavy deformed tapes because of the fraction between the surface of rolling mills and the thin tapes when the rolling force strongly reduced at high strain, which significantly reduced the fraction of rolling texture on the surface of the Cu-45at %Ni alloy...

Depth perception: cuttlefish (Sepia officinalis) respond to visual texture density gradients.

Science.gov (United States)

Josef, Noam; Mann, Ofri; Sykes, António V; Fiorito, Graziano; Reis, João; Maccusker, Steven; Shashar, Nadav

2014-11-01

Studies concerning the perceptual processes of animals are not only interesting, but are fundamental to the understanding of other developments in information processing among non-humans. Carefully used visual illusions have been proven to be an informative tool for understanding visual perception. In this behavioral study, we demonstrate that cuttlefish are responsive to visual cues involving texture gradients. Specifically, 12 out of 14 animals avoided swimming over a solid surface with a gradient picture that to humans resembles an illusionary crevasse, while only 5 out of 14 avoided a non-illusionary texture. Since texture gradients are well-known cues for depth perception in vertebrates, we suggest that these cephalopods were responding to the depth illusion created by the texture density gradient. Density gradients and relative densities are key features in distance perception in vertebrates. Our results suggest that they are fundamental features of vision in general, appearing also in cephalopods.

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

Science.gov (United States)

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.

Unsupervised consensus cluster analysis of [18F]-fluoroethyl-L-tyrosine positron emission tomography identified textural features for the diagnosis of pseudoprogression in high-grade glioma.

Science.gov (United States)

Kebir, Sied; Khurshid, Zain; Gaertner, Florian C; Essler, Markus; Hattingen, Elke; Fimmers, Rolf; Scheffler, Björn; Herrlinger, Ulrich; Bundschuh, Ralph A; Glas, Martin

2017-01-31

Timely detection of pseudoprogression (PSP) is crucial for the management of patients with high-grade glioma (HGG) but remains difficult. Textural features of O-(2-[18F]fluoroethyl)-L-tyrosine positron emission tomography (FET-PET) mirror tumor uptake heterogeneity; some of them may be associated with tumor progression. Fourteen patients with HGG and suspected of PSP underwent FET-PET imaging. A set of 19 conventional and textural FET-PET features were evaluated and subjected to unsupervised consensus clustering. The final diagnosis of true progression vs. PSP was based on follow-up MRI using RANO criteria. Three robust clusters have been identified based on 10 predominantly textural FET-PET features. None of the patients with PSP fell into cluster 2, which was associated with high values for textural FET-PET markers of uptake heterogeneity. Three out of 4 patients with PSP were assigned to cluster 3 that was largely associated with low values of textural FET-PET features. By comparison, tumor-to-normal brain ratio (TNRmax) at the optimal cutoff 2.1 was less predictive of PSP (negative predictive value 57% for detecting true progression, p=0.07 vs. 75% with cluster 3, p=0.04). Clustering based on textural O-(2-[18F]fluoroethyl)-L-tyrosine PET features may provide valuable information in assessing the elusive phenomenon of pseudoprogression.

Production of stable superhydrophilic surfaces on 316L steel by simultaneous laser texturing and SiO2 deposition

Science.gov (United States)

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

2018-01-01

Superhydrophilic surfaces with liquid contact angles of less than 5 ° have attracted much interest in practical applications including self-cleaning, cell manipulation, adhesion enhancement, anti-fogging, fluid flow control and evaporative cooling. Standard laser metal texturing method often result in unstable wetting characteristics, i.e. changing from super hydrophilic to hydrophobic in a few days or weeks. In this paper, a simple one step method is reported for fabricating a stable superhydrophilic metallic surface that lasted for at least 6 months. Here, 316L stainless steel substrates were textured using a nanosecond laser with in-situ SiO2 deposition. Morphology and chemistry of laser-textured surfaces were characterised using SEM, XRD, XPS and an optical 3D profiler. Static wettability analysis was carried out over a period of 6 months after the laser treatment. The effect of surface roughness on wettability was also studied. Results showed that the wettability of the textured surfaces could be controlled by changing the scanning speed of laser beam and number of passes. The main reason for the realisation of the stable superhydrophilic surface is the combination of the melted glass particles mainly Si and O with that of stainless steel in the micro-textured patterns. This study presents a useful method

Predicting the effect of surface texture on the qualitative form of prehension.

Directory of Open Access Journals (Sweden)

Ian John Flatters

Full Text Available Reach-to-grasp movements change quantitatively in a lawful (i.e. predictable manner with changes in object properties. We explored whether altering object texture would produce qualitative changes in the form of the precontact movement patterns. Twelve participants reached to lift objects from a tabletop. Nine objects were produced, each with one of three grip surface textures (high-friction, medium-friction and low-friction and one of three widths (50 mm, 70 mm and 90 mm. Each object was placed at three distances (100 mm, 300 mm and 500 mm, representing a total of 27 trial conditions. We observed two distinct movement patterns across all trials--participants either: (i brought their arm to a stop, secured the object and lifted it from the tabletop; or (ii grasped the object 'on-the-fly', so it was secured in the hand while the arm was moving. A majority of grasps were on-the-fly when the texture was high-friction and none when the object was low-friction, with medium-friction producing an intermediate proportion. Previous research has shown that the probability of on-the-fly behaviour is a function of grasp surface accuracy constraints. A finger friction rig was used to calculate the coefficients of friction for the objects and these calculations showed that the area available for a stable grasp (the 'functional grasp surface size' increased with surface friction coefficient. Thus, knowledge of functional grasp surface size is required to predict the probability of observing a given qualitative form of grasping in human prehensile behaviour.

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

Science.gov (United States)

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

2017-12-01

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

Effect of SiC particle impact nano-texturing on tribological performance of 304L stainless steel

Science.gov (United States)

Lorenzo-Martin, C.; Ajayi, O. O.

2014-10-01

Topographical features on sliding contact surfaces are known to have a significant impact on friction and wear. Indeed, various forms of surface texturing are being used to improve and/or control the tribological performance of sliding surfaces. In this paper, the effect of random surface texturing produced by a mechanical impact process is studied for friction and wear behavior of 304L stainless steel (SS) under dry and marginal oil lubrication. The surface processing was applied to 304L SS flat specimens and tested under reciprocating ball-on-flat sliding contact, with a 440C stainless steel ball. Under dry contact, the impact textured surface exhibited two order of magnitude lower wear than the isotropically ground surface of the same material. After 1500 s of sliding and wearing through of the processed surface layer following occurring of scuffing, the impact textured surface underwent a transition in wear and friction behavior. Under marginal oil lubrication, however, no such transition occurred, and the wear for the impact textured surface was consistently two orders of magnitude lower than that for the ground material. Mechanisms for the tribological performance enhancement are proposed.

Optical and electrical properties of porous silicon layer formed on the textured surface by electrochemical etching

Science.gov (United States)

Weiying, Ou; Lei, Zhao; Hongwei, Diao; Jun, Zhang; Wenjing, Wang

2011-05-01

Porous silicon (PS) layers were formed on textured crystalline silicon by electrochemical etching in HF-based electrolyte. Optical and electrical properties of the TMAH textured surfaces with PS formation are studied. Moreover, the influences of the initial structures and the anodizing time on the optical and electrical properties of the surfaces after PS formation are investigated. The results show that the TMAH textured surfaces with PS formation present a dramatic decrease in reflectance. The longer the anodizing time is, the lower the reflectance. Moreover, an initial surface with bigger pyramids achieved lower reflectance in a short wavelength range. A minimum reflectance of 3.86% at 460 nm is achieved for a short anodizing time of 2 min. Furthermore, the reflectance spectrum of the sample, which was etched in 3 vol.% TMAH for 25 min and then anodized for 20 min, is extremely flat and lies between 3.67% and 6.15% in the wavelength range from 400 to 1040 nm. In addition, for a short anodizing time, a slight increase in the effective carrier lifetime is observed. Our results indicate that PS layers formed on a TMAH textured surface for a short anodization treatment can be used as both broadband antireflection coatings and passivation layers for the application in solar cells.

Optical and electrical properties of porous silicon layer formed on the textured surface by electrochemical etching

Energy Technology Data Exchange (ETDEWEB)

Ou Weiying; Zhao Lei; Diao Hongwei; Zhang Jun; Wang Wenjing, E-mail: wjwangwj@126.com [Key Laboratory of Solar Thermal Energy and Photovoltaic System, Institute of Electrical Engineering, Chinese Academy of Sciences, Beijing 100190 (China)

2011-05-15

Porous silicon (PS) layers were formed on textured crystalline silicon by electrochemical etching in HF-based electrolyte. Optical and electrical properties of the TMAH textured surfaces with PS formation are studied. Moreover, the influences of the initial structures and the anodizing time on the optical and electrical properties of the surfaces after PS formation are investigated. The results show that the TMAH textured surfaces with PS formation present a dramatic decrease in reflectance. The longer the anodizing time is, the lower the reflectance. Moreover, an initial surface with bigger pyramids achieved lower reflectance in a short wavelength range. A minimum reflectance of 3.86% at 460 nm is achieved for a short anodizing time of 2 min. Furthermore, the reflectance spectrum of the sample, which was etched in 3 vol.% TMAH for 25 min and then anodized for 20 min, is extremely flat and lies between 3.67% and 6.15% in the wavelength range from 400 to 1040 nm. In addition, for a short anodizing time, a slight increase in the effective carrier lifetime is observed. Our results indicate that PS layers formed on a TMAH textured surface for a short anodization treatment can be used as both broadband antireflection coatings and passivation layers for the application in solar cells. (semiconductor technology)

Effect of machining parameters on surface textures in EDM of Fe-Mn-Al alloy

International Nuclear Information System (INIS)

Guu, Y.H.; Hou, Max Ti-Kuang

2007-01-01

In this work, the surface characteristics caused by EDM were analyzed by means of the atomic force microscopy (AFM) technique. An empirical model of Fe-Mn-Al alloy was proposed based on the experimental data. A qualitative energy dispersive spectroscopic analyzer was used to measure the chemical composition of the specimen. Surface hardness was determined with a microhardness tester. Experimental results indicate that the EDM process causes a ridged surface and induces machining damage in the surface layer, and increases the surface roughness. The depth of micro-cracks, micro-voids and machined damage increase with an increase in the amount of pulsed current and pulse-on duration. The effect of the magnitude of the pulse-on duration on the surface texture of the specimen is more significant than the pulsed current. Furthermore, the AFM method reveals the 3D surface textures of the EDM specimen with a nanometer scale

Identification of individual features in areal surface topography data by means of template matching and the ring projection transform

International Nuclear Information System (INIS)

Senin, Nicola; Moretti, Michele; Blunt, Liam A

2014-01-01

Starting from areal surface topography data as provided by current commercial three-dimensional (3D) profilometers and 3D digital microscopes, this work investigates the problem of automatically identifying and extracting functionally relevant, individual features within the acquisition area. Feature identification is achieved by adopting an original template-matching algorithmic procedure, based on applying the ring projection transform in combination with a parametric template. The proposed algorithmic procedure addresses in particular template-matching scenarios where significant variability may be associated with the features to be compared to the reference template. The algorithm is applied to a test case involving the characterization of the surface texture of a superabrasive polishing tool used in hard-disk manufacturing. (paper)

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

International Nuclear Information System (INIS)

Zhong, H; Wang, J; Shen, L; Hu, W; Wan, J; Zhou, Z; Zhang, Z

2015-01-01

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 images 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

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

Science.gov (United States)

Bharatish, A.; Soundarapandian, S.

2018-04-01

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

HOS cell adhesion on Ti6Al4V surfaces texturized by laser engraving

Science.gov (United States)

Sandoval Amador, A.; Carreño Garcia, H.; Escobar Rivero, P.; Peña Ballesteros, D. Y.; Estupiñán Duran, H. A.

2016-02-01

The cell adhesion of the implant is determinate by the chemical composition, topography, wettability, surface energy and biocompatibility of the biomaterial. In this work the interaction between human osteosarcoma HOS cells and textured Ti6Al4V surfaces were evaluated. Ti6Al4V surfaces were textured using a CO2 laser in order to obtain circular spots on the surfaces. Test surfaces were uncoated (C1) used as a control surface, and surfaces with points obtained by laser engraving, with 1mm spacing (C2) and 0.5mm (C3). The HOS cells were cultured in RPMI-1640 medium with 10% fetal bovine serum and 1% antibiotics. No cells toxicity after one month incubation time occurred. The increased cell adhesion and cell spreading was observed after 1, 3 and 5 days without significant differences between the sample surfaces (C2 and C3) and control (uncoated) at the end of the experiment.

HOS cell adhesion on Ti6Al4V surfaces texturized by laser engraving

International Nuclear Information System (INIS)

Sandoval Amador, A; Carreño Garcia, H; Escobar Rivero, P; Peña Ballesteros, D Y; Estupiñán Duran, H A

2016-01-01

The cell adhesion of the implant is determinate by the chemical composition, topography, wettability, surface energy and biocompatibility of the biomaterial. In this work the interaction between human osteosarcoma HOS cells and textured Ti 6 Al 4 V surfaces were evaluated. Ti 6 Al 4 V surfaces were textured using a CO 2 laser in order to obtain circular spots on the surfaces. Test surfaces were uncoated (C1) used as a control surface, and surfaces with points obtained by laser engraving, with 1mm spacing (C2) and 0.5mm (C3). The HOS cells were cultured in RPMI-1640 medium with 10% fetal bovine serum and 1% antibiotics. No cells toxicity after one month incubation time occurred. The increased cell adhesion and cell spreading was observed after 1, 3 and 5 days without significant differences between the sample surfaces (C2 and C3) and control (uncoated) at the end of the experiment. (paper)

Visual texture perception via graph-based semi-supervised learning

Science.gov (United States)

Zhang, Qin; Dong, Junyu; Zhong, Guoqiang

2018-04-01

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

Tribological Behavior of Oil-Lubricated Laser Textured Steel Surfaces in Conformal Flat and Non-Conformal Contacts

Energy Technology Data Exchange (ETDEWEB)

Kovalchenko, A. M. [Inst. for Problems of Materials Science, Dept. 7, 3 Krzhizhanovsky Street, Kyiv 03142, UA (Corresponding author), e-mail: andrii.kovalchenko@gatech.edu; Erdemir, A. [Argonne National Lab., Energy Systems Division, 9700 South Cass Avenue, Argonne, IL 60439 US; Ajayi, O. O. [Argonne National Lab., Energy Systems Division, 9700 South Cass Avenue, Argonne, IL 60439 US; Etsion, I. [Technion-Israel Inst. of Technology, Dept. of Mechanical Engineering, Haifa 32000, IL

2017-01-30

Changing the surface texture of sliding surfaces is an effective way to manipulate friction and wear of lubricated surfaces. Having realized its potential, we have done very extensive studies on the effects of laser surface texturing (LST, which involves the creation of an array of microdimples on a surface) on friction and wear behavior of oil-lubricated steel surfaces in the early 2000s. In this paper, we reviewed some of our research accomplishments and assessed future directions of the laser texturing field in many diverse industrial applications. Our studies specifically addressed the impact of laser texturing on friction and wear of both the flat conformal and initial non-conformal point contact configurations using a pin-on-disk test rig under fully-flooded synthetic oil lubricants with different viscosities. Electrical resistance measurement between pin and LST disks was also used to determine the operating lubrication regimes in relation to friction. In conformal contact, we confirmed that LST could significantly expand the operating conditions for hydrodynamic lubrication to significantly much higher loads and slower speeds. In particular, with LST and higher viscosity oils, the low-friction full hydrodynamic regime was shifted to the far left in the Stribeck diagram. Overall, the beneficial effects of laser surface texturing were more pronounced at higher speeds and loads and with higher viscosity oil. LST was also observed to reduce the magnitude of friction coefficients in the boundary regime. For the non-conformal contact configuration, we determined that LST would produce more abrasive wear on the rubbing counterface compared to the untreated surfaces due to a reduction in lubricant fluid film thickness, as well as the highly uneven and rough nature of the textured surfaces. However, this higher initial wear rate has led to faster generation of a conformal contact, and thus transition from the high-friction boundary to lower friction mixed

Improved bioactivity of selective laser melting titanium: Surface modification with micro-/nano-textured hierarchical topography and bone regeneration performance evaluation.

Science.gov (United States)

Xu, Jia-Yun; Chen, Xian-Shuai; Zhang, Chun-Yu; Liu, Yun; Wang, Jing; Deng, Fei-Long

2016-11-01

Selective laser melting (SLM) titanium requires surface modification to improve its bioactivity. The microrough surface of it can be utilized as the micro primary substrate to create a micro-/nano-textured topography for improved bone regeneration. In this study, the microrough SLM titanium substrate was optimized by sandblasting, and nano-porous features of orderly arranged nanotubes and disorderly arranged nanonet were produced by anodization (SAN) and alkali-heat treatment (SAH), respectively. The results were compared with the control group of an untreated surface (native-SLM) and a microtopography only surface treated by acid etching (SLA). The effects of the different topographies on cell functions and bone formation performance were evaluated in vitro and in vivo. It was found that micro-/nano-textured topographies of SAN and SAH showed enhanced cell behaviour relative to the microtopography of SLA with significantly higher proliferation on the 1st, 3rd, 5th and 7th day (P<0.05) and higher total protein contents on the 14th day (P<0.05). In vivo, SAN and SAH formed more successively regenerated bone, which resulted in higher bone-implant contact (BIC%) and bone-bonding force than native-SLM and SLA. In addition, the three-dimensional nanonet of SAH was expected to be more similar to native extracellular matrix (ECM) and thus led to better bone formation. The alkaline phosphatase activity of SAH was significantly higher than the other three groups at an earlier stage of the 7th day (P<0.05) and the BIC% was nearly double that of native-SLM and SLA in the 8th week. In conclusion, the addition of nano-porous features on the microrough SLM titanium surface is effective in improving the bioactivity and bone regeneration performance, in which the ECM-like nanonet with a disorderly arranged biomimetic feature is suggested to be more efficient than nanotubes. Copyright © 2016 Elsevier B.V. All rights reserved.

Please Don't Move-Evaluating Motion Artifact From Peripheral Quantitative Computed Tomography Scans Using Textural Features.

Science.gov (United States)

Rantalainen, Timo; Chivers, Paola; Beck, Belinda R; Robertson, Sam; Hart, Nicolas H; Nimphius, Sophia; Weeks, Benjamin K; McIntyre, Fleur; Hands, Beth; Siafarikas, Aris

Most imaging methods, including peripheral quantitative computed tomography (pQCT), are susceptible to motion artifacts particularly in fidgety pediatric populations. Methods currently used to address motion artifact include manual screening (visual inspection) and objective assessments of the scans. However, previously reported objective methods either cannot be applied on the reconstructed image or have not been tested for distal bone sites. Therefore, the purpose of the present study was to develop and validate motion artifact classifiers to quantify motion artifact in pQCT scans. Whether textural features could provide adequate motion artifact classification performance in 2 adolescent datasets with pQCT scans from tibial and radial diaphyses and epiphyses was tested. The first dataset was split into training (66% of sample) and validation (33% of sample) datasets. Visual classification was used as the ground truth. Moderate to substantial classification performance (J48 classifier, kappa coefficients from 0.57 to 0.80) was observed in the validation dataset with the novel texture-based classifier. In applying the same classifier to the second cross-sectional dataset, a slight-to-fair (κ = 0.01-0.39) classification performance was observed. Overall, this novel textural analysis-based classifier provided a moderate-to-substantial classification of motion artifact when the classifier was specifically trained for the measurement device and population. Classification based on textural features may be used to prescreen obviously acceptable and unacceptable scans, with a subsequent human-operated visual classification of any remaining scans. Copyright © 2017 The International Society for Clinical Densitometry. Published by Elsevier Inc. All rights reserved.

[18]Fluorodeoxyglucose positron emission tomography for the textural features of cervical cancer associated with lymph node metastasis and histological type

International Nuclear Information System (INIS)

Shen, Wei-Chih; Chen, Shang-Wen; Liang, Ji-An; Hsieh, Te-Chun; Yen, Kuo-Yang; Kao, Chia-Hung

2017-01-01

In this study, we investigated the correlation between the lymph node (LN) status or histological types and textural features of cervical cancers on "1"8F-fluorodeoxyglucose positron emission tomography/computed tomography. We retrospectively reviewed the imaging records of 170 patients with International Federation of Gynecology and Obstetrics stage IB-IVA cervical cancer. Four groups of textural features were studied in addition to the maximum standardized uptake value (SUV_m_a_x), metabolic tumor volume, and total lesion glycolysis (TLG). Moreover, we studied the associations between the indices and clinical parameters, including the LN status, clinical stage, and histology. Receiver operating characteristic curves were constructed to evaluate the optimal predictive performance among the various textural indices. Quantitative differences were determined using the Mann-Whitney U test. Multivariate logistic regression analysis was performed to determine the independent factors, among all the variables, for predicting LN metastasis. Among all the significant indices related to pelvic LN metastasis, homogeneity derived from the gray-level co-occurrence matrix (GLCM) was the sole independent predictor. By combining SUV_m_a_x, the risk of pelvic LN metastasis can be scored accordingly. The TLG_m_e_a_n was the independent feature of positive para-aortic LNs. Quantitative differences between squamous and nonsquamous histology can be determined using short-zone emphasis (SZE) from the gray-level size zone matrix (GLSZM). This study revealed that in patients with cervical cancer, pelvic or para-aortic LN metastases can be predicted by using textural feature of homogeneity from the GLCM and TLG_m_e_a_n_, respectively. SZE from the GLSZM is the sole feature associated with quantitative differences between squamous and nonsquamous histology. (orig.)

[18]Fluorodeoxyglucose Positron Emission Tomography for the Textural Features of Cervical Cancer Associated with Lymph Node Metastasis and Histological Type.

Science.gov (United States)

Shen, Wei-Chih; Chen, Shang-Wen; Liang, Ji-An; Hsieh, Te-Chun; Yen, Kuo-Yang; Kao, Chia-Hung

2017-09-01

In this study, we investigated the correlation between the lymph node (LN) status or histological types and textural features of cervical cancers on 18 F-fluorodeoxyglucose positron emission tomography/computed tomography. We retrospectively reviewed the imaging records of 170 patients with International Federation of Gynecology and Obstetrics stage IB-IVA cervical cancer. Four groups of textural features were studied in addition to the maximum standardized uptake value (SUV max ), metabolic tumor volume, and total lesion glycolysis (TLG). Moreover, we studied the associations between the indices and clinical parameters, including the LN status, clinical stage, and histology. Receiver operating characteristic curves were constructed to evaluate the optimal predictive performance among the various textural indices. Quantitative differences were determined using the Mann-Whitney U test. Multivariate logistic regression analysis was performed to determine the independent factors, among all the variables, for predicting LN metastasis. Among all the significant indices related to pelvic LN metastasis, homogeneity derived from the gray-level co-occurrence matrix (GLCM) was the sole independent predictor. By combining SUV max , the risk of pelvic LN metastasis can be scored accordingly. The TLG mean was the independent feature of positive para-aortic LNs. Quantitative differences between squamous and nonsquamous histology can be determined using short-zone emphasis (SZE) from the gray-level size zone matrix (GLSZM). This study revealed that in patients with cervical cancer, pelvic or para-aortic LN metastases can be predicted by using textural feature of homogeneity from the GLCM and TLG mean, respectively. SZE from the GLSZM is the sole feature associated with quantitative differences between squamous and nonsquamous histology.

[18]Fluorodeoxyglucose positron emission tomography for the textural features of cervical cancer associated with lymph node metastasis and histological type

Energy Technology Data Exchange (ETDEWEB)

Shen, Wei-Chih [Asia University, Department of Computer Science and Information Engineering, Taichung (China); Chen, Shang-Wen [China Medical University Hospital, Department of Radiation Oncology, Taichung (China); China Medical University, School of Medicine, Taichung (China); Taipei Medical University, School of Medicine, Taipei (China); China Medical University, Graduate Institute of Clinical Medical Science, School of Medicine, College of Medicine, Taichung (China); Liang, Ji-An [China Medical University Hospital, Department of Radiation Oncology, Taichung (China); China Medical University, Graduate Institute of Clinical Medical Science, School of Medicine, College of Medicine, Taichung (China); Hsieh, Te-Chun; Yen, Kuo-Yang [China Medical University Hospital, Department of Nuclear Medicine and PET Center, Taichung (China); China Medical University, Department of Biomedical Imaging and Radiological Science, Taichung (China); Kao, Chia-Hung [China Medical University, Graduate Institute of Clinical Medical Science, School of Medicine, College of Medicine, Taichung (China); China Medical University Hospital, Department of Nuclear Medicine and PET Center, Taichung (China); Asia University, Department of Bioinformatics and Medical Engineering, Taichung (China)

2017-09-15

In this study, we investigated the correlation between the lymph node (LN) status or histological types and textural features of cervical cancers on {sup 18}F-fluorodeoxyglucose positron emission tomography/computed tomography. We retrospectively reviewed the imaging records of 170 patients with International Federation of Gynecology and Obstetrics stage IB-IVA cervical cancer. Four groups of textural features were studied in addition to the maximum standardized uptake value (SUV{sub max}), metabolic tumor volume, and total lesion glycolysis (TLG). Moreover, we studied the associations between the indices and clinical parameters, including the LN status, clinical stage, and histology. Receiver operating characteristic curves were constructed to evaluate the optimal predictive performance among the various textural indices. Quantitative differences were determined using the Mann-Whitney U test. Multivariate logistic regression analysis was performed to determine the independent factors, among all the variables, for predicting LN metastasis. Among all the significant indices related to pelvic LN metastasis, homogeneity derived from the gray-level co-occurrence matrix (GLCM) was the sole independent predictor. By combining SUV{sub max}, the risk of pelvic LN metastasis can be scored accordingly. The TLG{sub mean} was the independent feature of positive para-aortic LNs. Quantitative differences between squamous and nonsquamous histology can be determined using short-zone emphasis (SZE) from the gray-level size zone matrix (GLSZM). This study revealed that in patients with cervical cancer, pelvic or para-aortic LN metastases can be predicted by using textural feature of homogeneity from the GLCM and TLG{sub mean,} respectively. SZE from the GLSZM is the sole feature associated with quantitative differences between squamous and nonsquamous histology. (orig.)

Comparison of features response in texture-based iris segmentation

CSIR Research Space (South Africa)

Bachoo, A

2009-03-01

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

Wetting and other physical characteristics of polycarbonate surface textured using laser ablation

Energy Technology Data Exchange (ETDEWEB)

Yilbas, B.S., E-mail: bsyilbas@kfupm.edu.sa [ME Department, King Fahd University of Petroleum and Minerals, Dhahran (Saudi Arabia); Khaled, M. [CHEM Department, King Fahd University of Petroleum and Minerals, Dhahran (Saudi Arabia); Abu-Dheir, N.; Al-Aqeeli, N.; Said, S.A.M. [ME Department, King Fahd University of Petroleum and Minerals, Dhahran (Saudi Arabia); Ahmed, A.O.M. [CHEM Department, King Fahd University of Petroleum and Minerals, Dhahran (Saudi Arabia); Varanasi, K.K.; Toumi, Y.K. [Mechanical Engineering, Massachusetts Institute of Technology, Boston (United States)

2014-11-30

Highlights: • Laser causes micro/nano size pores and shallow fine-size cavities. • Crystallinity at surface is 18% after laser treatment increasing hydrophobicity. • Surface hydrophobicity improves after laser treatment. • Microhardness increases twofold after laser treatment process. • Residual stress is compressive and scratch hardness is 110 ± 11 MPa. • Optical transmittance reduces by 15% after laser treatment. - Abstract: Surface texturing of polycarbonate glass is carried out for improved hydrophobicity via controlled laser ablation at the surface. Optical and physical characteristics of the laser treated layer are examined using analytical tools including optical, atomic force, and scanning electron microscopes, Fourier transform infrared spectroscopy, and X-ray diffraction. Contact angle measurements are carried out to assess the hydrophobicity of the laser treated surface. Residual stress in the laser ablated layer is determined using the curvature method, and microhardnes and scratch resistance are analyzed using a micro-tribometer. Findings reveal that textured surfaces compose of micro/nano pores with fine cavities and increase the contact angle to hydrophobicity such a way that contact angles in the range of 120° are resulted. Crystallization of the laser treated surface reduces the optical transmittance by 15%, contributes to residual stress formation, and enhances the microhardness by twice the value of untreated polycarbonate surface. In addition, laser treatment improves surface scratch resistance by 40%.

Characterization of the major histopathological components of thyroid nodules using sonographic textural features for clinical diagnosis and management.

Science.gov (United States)

Chen, Shao-Jer; Yu, Sung-Nien; Tzeng, Jeh-En; Chen, Yen-Ting; Chang, Ku-Yaw; Cheng, Kuo-Sheng; Hsiao, Fu-Tsung; Wei, Chang-Kuo

2009-02-01

In this study, the characteristic sonographic textural feature that represents the major histopathologic components of the thyroid nodules was objectively quantified to facilitate clinical diagnosis and management. A total of 157 regions-of-interest thyroid ultrasound image was recruited in the study. The sonographic system used was the GE LOGIQ 700), (General Electric Healthcare, Chalfant St. Giles, UK). The parameters affecting image acquisition were kept in the same condition for all lesions. Commonly used texture analysis methods were applied to characterize thyroid ultrasound images. Image features were classified according to the corresponding pathologic findings. To estimate their relevance and performance to classification, ReliefF was used as a feature selector. Among the various textural features, the sum average value derived from co-occurrence matrix can well reflect echogenicity and can effectively differentiate between follicles and fibrosis base thyroid nodules. Fibrosis shows lowest echogenicity and lowest difference sum average value. Enlarged follicles show highest echogenicity and difference sum average values. Papillary cancer or follicular tumors show the difference sum average values and echogenicity between. The rule of thumb for the echogenicity is that the more follicles are mixed in, the higher the echo of the follicular tumor and papillary cancer will be and vice versa for fibrosis mixed. Areas with intermediate and lower echo should address the possibility of follicular or papillary neoplasm mixed with either follicles or fibrosis. These areas provide more cellular information for ultrasound guided aspiration

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

Science.gov (United States)

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

2012-05-01

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

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-01-01

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

The effect of texture unit shape on silicon surface on the absorption properties

Energy Technology Data Exchange (ETDEWEB)

Hua, Xiao-She; Zhang, Yi-Jie; Wang, Hao-Wei [Institute of Ecological and Environmental Materials, School of Environmental Science and Engineering, Shanghai Jiao Tong University, Shanghai 200240 (China)

2010-02-15

Improving the utilization ratio of sunlight is a key factor for the development of solar cell. In this work, different structures including triangular pyramid, rectangular pyramid, hexangular pyramid and cone structure are established to investigate the influences of many factors, like geometrical shape, density and the top angle of the texture unit on silicon front surface to sunlight absorption. Ray-tracing technology is used for simulation. The simulation results indicate that the triangular pyramid texture on silicon front surface performs the best, and its total absorption rate is more than 90% for the light with wavelength between 640 and 1080 nm when the top angle of pyramid is less than 100 . (author)

Non-Uniform Laser Surface Texturing of an Un-Tapered Square Pad for Tribological Applications

Directory of Open Access Journals (Sweden)

Antonio Ancona

2017-10-01

Full Text Available Femtosecond laser surface micro-texturing has emerged as a promising technology to enhance the tribological properties of different kinds of electromechanical devices. In this research paper, we have exploited the intrinsic flexibility and micrometric accuracy of femtosecond laser ablation to realize complex micro-structural modifications on the surface of a laboratory prototype of a steel thrust bearing (un-tapered pad. The Bruggeman Texture Hydrodynamics theory (BTH is employed for the design of the anisotropic and non-uniform texture maximizing the thrust load of the pad prototype. The preliminary experimental results, reported in this work, show that the non-uniform micro-texture largely affects the friction characteristics of the contact. In particular, in agreement with the BTH predictions, the tribo-system shows friction properties that are strongly sensitive to the direction of the sliding speed, as a consequence of the micro-fluid dynamics which are designed to occur only in a specific sliding direction. We suggest that the joint action of virtual prototyping (BTH lubrication theory and ultrafast laser micro-prototyping can lead to unconventional and impressive results in terms of enhanced or tailored contact mechanics properties of the generic lubricated tribopair.

Zone-size nonuniformity of 18F-FDG PET regional textural features predicts survival in patients with oropharyngeal cancer.

Science.gov (United States)

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.

SU-F-R-31: Identification of Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induced Lung Disease

Energy Technology Data Exchange (ETDEWEB)

Choi, W; Riyahi, S; Lu, W [University of Maryland School of Medicine, Baltimore, MD (United States)

2016-06-15

Purpose: Normal lung CT texture features have been used for the prediction of radiation-induced lung disease (radiation pneumonitis and radiation fibrosis). For these features to be clinically useful, they need to be relatively invariant (robust) to tumor size and not correlated with normal lung volume. Methods: The free-breathing CTs of 14 lung SBRT patients were studied. Different sizes of GTVs were simulated with spheres placed at the upper lobe and lower lobe respectively in the normal lung (contralateral to tumor). 27 texture features (9 from intensity histogram, 8 from grey-level co-occurrence matrix [GLCM] and 10 from grey-level run-length matrix [GLRM]) were extracted from [normal lung-GTV]. To measure the variability of a feature F, the relative difference D=|Fref -Fsim|/Fref*100% was calculated, where Fref was for the entire normal lung and Fsim was for [normal lung-GTV]. A feature was considered as robust if the largest non-outlier (Q3+1.5*IQR) D was less than 5%, and considered as not correlated with normal lung volume when their Pearson correlation was lower than 0.50. Results: Only 11 features were robust. All first-order intensity-histogram features (mean, max, etc.) were robust, while most higher-order features (skewness, kurtosis, etc.) were unrobust. Only two of the GLCM and four of the GLRM features were robust. Larger GTV resulted greater feature variation, this was particularly true for unrobust features. All robust features were not correlated with normal lung volume while three unrobust features showed high correlation. Excessive variations were observed in two low grey-level run features and were later identified to be from one patient with local lung diseases (atelectasis) in the normal lung. There was no dependence on GTV location. Conclusion: We identified 11 robust normal lung CT texture features that can be further examined for the prediction of radiation-induced lung disease. Interestingly, low grey-level run features identified normal

An international comparison of surface texture parameters quantification on polymer artefacts using optical instruments

DEFF Research Database (Denmark)

Tosello, Guido; Haitjema, H.; Leach, R.K.

2016-01-01

An international comparison of optical instruments measuring polymer surfaces with arithmetic mean height values in the sub-micrometre range has been carried out. The comparison involved sixteen optical surface texture instruments (focus variation instruments, confocal microscopes and coherent...

Semantic attributes based texture generation

Science.gov (United States)

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

2018-04-01

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

TU-CD-BRB-01: Normal Lung CT Texture Features Improve Predictive Models for Radiation Pneumonitis

International Nuclear Information System (INIS)

Krafft, S; Briere, T; Court, L; Martel, M

2015-01-01

Purpose: Existing normal tissue complication probability (NTCP) models for radiation pneumonitis (RP) traditionally rely on dosimetric and clinical data but are limited in terms of performance and generalizability. Extraction of pre-treatment image features provides a potential new category of data that can improve NTCP models for RP. We consider quantitative measures of total lung CT intensity and texture in a framework for prediction of RP. Methods: Available clinical and dosimetric data was collected for 198 NSCLC patients treated with definitive radiotherapy. Intensity- and texture-based image features were extracted from the T50 phase of the 4D-CT acquired for treatment planning. A total of 3888 features (15 clinical, 175 dosimetric, and 3698 image features) were gathered and considered candidate predictors for modeling of RP grade≥3. A baseline logistic regression model with mean lung dose (MLD) was first considered. Additionally, a least absolute shrinkage and selection operator (LASSO) logistic regression was applied to the set of clinical and dosimetric features, and subsequently to the full set of clinical, dosimetric, and image features. Model performance was assessed by comparing area under the curve (AUC). Results: A simple logistic fit of MLD was an inadequate model of the data (AUC∼0.5). Including clinical and dosimetric parameters within the framework of the LASSO resulted in improved performance (AUC=0.648). Analysis of the full cohort of clinical, dosimetric, and image features provided further and significant improvement in model performance (AUC=0.727). Conclusions: To achieve significant gains in predictive modeling of RP, new categories of data should be considered in addition to clinical and dosimetric features. We have successfully incorporated CT image features into a framework for modeling RP and have demonstrated improved predictive performance. Validation and further investigation of CT image features in the context of RP NTCP

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

Science.gov (United States)

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

2018-04-01

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

Intraneural stimulation elicits discrimination of textural features by artificial fingertip in intact and amputee humans.

Science.gov (United States)

Oddo, Calogero Maria; Raspopovic, Stanisa; Artoni, Fiorenzo; Mazzoni, Alberto; Spigler, Giacomo; Petrini, Francesco; Giambattistelli, Federica; Vecchio, Fabrizio; Miraglia, Francesca; Zollo, Loredana; Di Pino, Giovanni; Camboni, Domenico; Carrozza, Maria Chiara; Guglielmelli, Eugenio; Rossini, Paolo Maria; Faraguna, Ugo; Micera, Silvestro

2016-03-08

Restoration of touch after hand amputation is a desirable feature of ideal prostheses. Here, we show that texture discrimination can be artificially provided in human subjects by implementing a neuromorphic real-time mechano-neuro-transduction (MNT), which emulates to some extent the firing dynamics of SA1 cutaneous afferents. The MNT process was used to modulate the temporal pattern of electrical spikes delivered to the human median nerve via percutaneous microstimulation in four intact subjects and via implanted intrafascicular stimulation in one transradial amputee. Both approaches allowed the subjects to reliably discriminate spatial coarseness of surfaces as confirmed also by a hybrid neural model of the median nerve. Moreover, MNT-evoked EEG activity showed physiologically plausible responses that were superimposable in time and topography to the ones elicited by a natural mechanical tactile stimulation. These findings can open up novel opportunities for sensory restoration in the next generation of neuro-prosthetic hands.

Electromechanical performance of an ionic polymer–metal composite actuator with hierarchical surface texture

International Nuclear Information System (INIS)

He, Qingsong; Yu, Min; Zhang, Xiaoqing; Dai, Zhendong

2013-01-01

Two stainless steel templates were fabricated using electric-spark machining, and a hierarchical surface texture of ionic polymer was produced using both polishing and replication methods, which produced microscale and nanoscale groove-shaped microstructures at the surface of the polymer. The surface morphology of the Nafion membrane and metal electrode were observed using scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). SEM and EDS line-scan analysis indicated that the interfacial surface area was considerably increased and an excellent metal electrode was obtained with the production of a hierarchical surface texture. The displacement, blocking force, and electric current were measured using home-built apparatus. The results revealed that the combined polishing and replication method significantly improved the electromechanical performance of the ionic polymer–metal composite (IPMC). Compared with sandblasted Nafion-based IPMC, the blocking force, displacement, and electric current of the replicated Nafion-based IPMC were 4.39, 2.35, and 1.87 times higher, respectively. The IPMC fabricated in this work exhibited a competitive blocking force compared with recently reported actuators. (paper)

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

Directory of Open Access Journals (Sweden)

Georgia S. Araujo

2017-12-01

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

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

Science.gov (United States)

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

2012-11-01

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

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

International Nuclear Information System (INIS)

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

2012-01-01

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

Multi Texture Analysis of Colorectal Cancer Continuum Using Multispectral Imagery.

Directory of Open Access Journals (Sweden)

Ahmad Chaddad

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

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

Science.gov (United States)

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

2018-03-30

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

TextureCam Field Test Results from the Mojave Desert, California: Autonomous Instrument Classification of Sediment and Rock Surfaces

Science.gov (United States)

Castano, R.; Abbey, W. J.; Bekker, D. L.; Cabrol, N. A.; Francis, R.; Manatt, K.; Ortega, K.; Thompson, D. R.; Wagstaff, K.

2013-12-01

TextureCam is an intelligent camera that uses integrated image analysis to classify sediment and rock surfaces into basic visual categories. This onboard image understanding can improve the autonomy of exploration spacecraft during the long periods when they are out of contact with operators. This could increase the number of science activities performed in each command cycle by, for example, autonomously targeting science features of opportunity with narrow field of view remote sensing, identifying clean surfaces for autonomous placement of arm-mounted instruments, or by detecting high value images for prioritized downlink. TextureCam incorporates image understanding directly into embedded hardware with a Field Programmable Gate Array (FPGA). This allows the instrument to perform the classification in real time without taxing the primary spacecraft computing resources. We use a machine learning approach in which operators train a statistical model of surface appearance using examples from previously acquired images. A random forest model extrapolates from these training cases, using the statistics of small image patches to characterize the texture of each pixel independently. Applying this model to each pixel in a new image yields a map of surface units. We deployed a prototype instrument in the Cima Volcanic Fields during a series of experiments in May 2013. We imaged each environment with a tripod-mounted RGB camera connected directly to the FPGA board for real time processing. Our first scenario assessed ground surface cover on open terrain atop a weathered volcanic flow. We performed a transect consisting of 16 forward-facing images collected at 1m intervals. We trained the system to categorize terrain into four classes: sediment, basalt cobbles, basalt pebbles, and basalt with iron oxide weathering. Accuracy rates with regards to the fraction of the actual feature that was labeled correctly by the automated system were calculated. Lower accuracy rates were

SU-E-J-251: Incorporation of Pre-Therapy 18F-FDG Uptake with CT Texture Features in a Predictive Model for Radiation Pneumonitis Development

International Nuclear Information System (INIS)

Anthony, G; Cunliffe, A; Armato, S; Al-Hallaq, H; Castillo, R; Pham, N; Guerrero, T

2015-01-01

Purpose: To determine whether the addition of standardized uptake value (SUV) statistical variables to CT lung texture features can improve a predictive model of radiation pneumonitis (RP) development in patients undergoing radiation therapy. Methods: Anonymized data from 96 esophageal cancer patients (18 RP-positive cases of Grade ≥ 2) were retrospectively collected including pre-therapy PET/CT scans, pre-/posttherapy diagnostic CT scans and RP status. Twenty texture features (firstorder, fractal, Laws’ filter and gray-level co-occurrence matrix) were calculated from diagnostic CT scans and compared in anatomically matched regions of the lung. The mean, maximum, standard deviation, and 50th–95th percentiles of the SUV values for all lung voxels in the corresponding PET scans were acquired. For each texture feature, a logistic regression-based classifier consisting of (1) the average change in that texture feature value between the pre- and post-therapy CT scans and (2) the pre-therapy SUV standard deviation (SUV SD ) was created. The RP-classification performance of each logistic regression model was compared to the performance of its texture feature alone by computing areas under the receiver operating characteristic curves (AUCs). T-tests were performed to determine whether the mean AUC across texture features changed significantly when SUV SD was added to the classifier. Results: The AUC for single-texturefeature classifiers ranged from 0.58–0.81 in high-dose (≥ 30 Gy) regions of the lungs and from 0.53–0.71 in low-dose (< 10 Gy) regions. Adding SUVSD in a logistic regression model using a 50/50 data partition for training and testing significantly increased the mean AUC by 0.08, 0.06 and 0.04 in the low-, medium- and high-dose regions, respectively. Conclusion: Addition of SUVSD from a pre-therapy PET scan to a single CT-based texture feature improves RP-classification performance on average. These findings demonstrate the potential for more

SU-E-J-251: Incorporation of Pre-Therapy 18F-FDG Uptake with CT Texture Features in a Predictive Model for Radiation Pneumonitis Development

Energy Technology Data Exchange (ETDEWEB)

Anthony, G; Cunliffe, A; Armato, S; Al-Hallaq, H [The University of Chicago, Chicago, IL (United States); Castillo, R [Univ Texas Medical Branch of Galveston, Pearland, TX (United States); Pham, N [Baylor College of Medicine, Houston, TX (United States); Guerrero, T [Beaumont Health System, Royal Oak, MI (United States)

2015-06-15

Purpose: To determine whether the addition of standardized uptake value (SUV) statistical variables to CT lung texture features can improve a predictive model of radiation pneumonitis (RP) development in patients undergoing radiation therapy. Methods: Anonymized data from 96 esophageal cancer patients (18 RP-positive cases of Grade ≥ 2) were retrospectively collected including pre-therapy PET/CT scans, pre-/posttherapy diagnostic CT scans and RP status. Twenty texture features (firstorder, fractal, Laws’ filter and gray-level co-occurrence matrix) were calculated from diagnostic CT scans and compared in anatomically matched regions of the lung. The mean, maximum, standard deviation, and 50th–95th percentiles of the SUV values for all lung voxels in the corresponding PET scans were acquired. For each texture feature, a logistic regression-based classifier consisting of (1) the average change in that texture feature value between the pre- and post-therapy CT scans and (2) the pre-therapy SUV standard deviation (SUV{sub SD}) was created. The RP-classification performance of each logistic regression model was compared to the performance of its texture feature alone by computing areas under the receiver operating characteristic curves (AUCs). T-tests were performed to determine whether the mean AUC across texture features changed significantly when SUV{sub SD} was added to the classifier. Results: The AUC for single-texturefeature classifiers ranged from 0.58–0.81 in high-dose (≥ 30 Gy) regions of the lungs and from 0.53–0.71 in low-dose (< 10 Gy) regions. Adding SUVSD in a logistic regression model using a 50/50 data partition for training and testing significantly increased the mean AUC by 0.08, 0.06 and 0.04 in the low-, medium- and high-dose regions, respectively. Conclusion: Addition of SUVSD from a pre-therapy PET scan to a single CT-based texture feature improves RP-classification performance on average. These findings demonstrate the potential for

Simulating the Effect of Modulated Tool-Path Chip Breaking On Surface Texture and Chip Length

Energy Technology Data Exchange (ETDEWEB)

Smith, K.S.; McFarland, J.T.; Tursky, D. A.; Assaid, T. S.; Barkman, W. E.; Babelay, Jr., E. F.

2010-04-30

One method for creating broken chips in turning processes involves oscillating the cutting tool in the feed direction utilizing the CNC machine axes. The University of North Carolina at Charlotte and the Y-12 National Security Complex have developed and are refining a method to reliably control surface finish and chip length based on a particular machine's dynamic performance. Using computer simulations it is possible to combine the motion of the machine axes with the geometry of the cutting tool to predict the surface characteristics and map the surface texture for a wide range of oscillation parameters. These data allow the selection of oscillation parameters to simultaneously ensure broken chips and acceptable surface characteristics. This paper describes the machine dynamic testing and characterization activities as well as the computational method used for evaluating and predicting chip length and surface texture.

TU-AB-BRA-04: Quantitative Radiomics: Sensitivity of PET Textural Features to Image Acquisition and Reconstruction Parameters Implies the Need for Standards

International Nuclear Information System (INIS)

Nyflot, MJ; Yang, F; Byrd, D; Bowen, SR; Sandison, GA; Kinahan, PE

2015-01-01

Purpose: Despite increased use of heterogeneity metrics for PET imaging, standards for metrics such as textural features have yet to be developed. We evaluated the quantitative variability caused by image acquisition and reconstruction parameters on PET textural features. Methods: PET images of the NEMA IQ phantom were simulated with realistic image acquisition noise. 35 features based on intensity histograms (IH), co-occurrence matrices (COM), neighborhood-difference matrices (NDM), and zone-size matrices (ZSM) were evaluated within lesions (13, 17, 22, 28, 33 mm diameter). Variability in metrics across 50 independent images was evaluated as percent difference from mean for three phantom girths (850, 1030, 1200 mm) and two OSEM reconstructions (2 iterations, 28 subsets, 5 mm FWHM filtration vs 6 iterations, 28 subsets, 8.6 mm FWHM filtration). Also, patient sample size to detect a clinical effect of 30% with Bonferroni-corrected α=0.001 and 95% power was estimated. Results: As a class, NDM features demonstrated greatest sensitivity in means (5–50% difference for medium girth and reconstruction comparisons and 10–100% for large girth comparisons). Some IH features (standard deviation, energy, entropy) had variability below 10% for all sensitivity studies, while others (kurtosis, skewness) had variability above 30%. COM and ZSM features had complex sensitivities; correlation, energy, entropy (COM) and zone percentage, short-zone emphasis, zone-size non-uniformity (ZSM) had variability less than 5% while other metrics had differences up to 30%. Trends were similar for sample size estimation; for example, coarseness, contrast, and strength required 12, 38, and 52 patients to detect a 30% effect for the small girth case but 38, 88, and 128 patients in the large girth case. Conclusion: The sensitivity of PET textural features to image acquisition and reconstruction parameters is large and feature-dependent. Standards are needed to ensure that prospective trials

TU-AB-BRA-04: Quantitative Radiomics: Sensitivity of PET Textural Features to Image Acquisition and Reconstruction Parameters Implies the Need for Standards

Energy Technology Data Exchange (ETDEWEB)

Nyflot, MJ; Yang, F; Byrd, D; Bowen, SR; Sandison, GA; Kinahan, PE [University of Washington, Seattle, WA (United States)

2015-06-15

Purpose: Despite increased use of heterogeneity metrics for PET imaging, standards for metrics such as textural features have yet to be developed. We evaluated the quantitative variability caused by image acquisition and reconstruction parameters on PET textural features. Methods: PET images of the NEMA IQ phantom were simulated with realistic image acquisition noise. 35 features based on intensity histograms (IH), co-occurrence matrices (COM), neighborhood-difference matrices (NDM), and zone-size matrices (ZSM) were evaluated within lesions (13, 17, 22, 28, 33 mm diameter). Variability in metrics across 50 independent images was evaluated as percent difference from mean for three phantom girths (850, 1030, 1200 mm) and two OSEM reconstructions (2 iterations, 28 subsets, 5 mm FWHM filtration vs 6 iterations, 28 subsets, 8.6 mm FWHM filtration). Also, patient sample size to detect a clinical effect of 30% with Bonferroni-corrected α=0.001 and 95% power was estimated. Results: As a class, NDM features demonstrated greatest sensitivity in means (5–50% difference for medium girth and reconstruction comparisons and 10–100% for large girth comparisons). Some IH features (standard deviation, energy, entropy) had variability below 10% for all sensitivity studies, while others (kurtosis, skewness) had variability above 30%. COM and ZSM features had complex sensitivities; correlation, energy, entropy (COM) and zone percentage, short-zone emphasis, zone-size non-uniformity (ZSM) had variability less than 5% while other metrics had differences up to 30%. Trends were similar for sample size estimation; for example, coarseness, contrast, and strength required 12, 38, and 52 patients to detect a 30% effect for the small girth case but 38, 88, and 128 patients in the large girth case. Conclusion: The sensitivity of PET textural features to image acquisition and reconstruction parameters is large and feature-dependent. Standards are needed to ensure that prospective trials

Numerical modelling of microdroplet self-propelled jumping on micro-textured surface

Science.gov (United States)

Attarzadeh, S. M. Reza; Dolatabadi, Ali; Chun Kim, Kyung

2015-11-01

Understanding various stages of single and multiple droplet impact on a super-hydrophobic surface is of interest for many industrial applications such as aerospace industry. In this study, the phenomenon of coalescence induced droplets self-propelled jumping on a micro-textured super-hydrophobic surface is numerically simulated using Volume of Fluid (VOF) method. This model mimics the scenario of coalescing cloud-sized particles over the surface structure of an aircraft. The VOF coupled with a dynamic contact angle model is used to simulate the coalescence of two equal size droplets, that are initially placed very closed to each other with their interface overlapping with each other's which triggers the incipience of their coalescence. The textured surface is modeled as a series of equally spaced squared pillars, with 111° as the intrinsic contact angle all over the solid contact area. It is shown that the radial velocity of coalescing liquid bridge is reverted to upward direction due to the counter action of the surface to the basal area of droplet in contact. The presence of air beneath the droplet inside micro grooves which aimed at repelling water droplet is also captured in this model. The simulated results are found in good agreement with experimental observations. The authors gratefully acknowledge the financial support from Natural Sciences and Engineering Research Council of Canada (NSERC), Consortium de Recherche et d'innovation en Aerospatiale au Quebec (CRIAQ), Bombardier Aerospace, Pratt Whitney Canada.

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

Science.gov (United States)

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

2014-01-13

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

Investigating the use of texture features for analysis of breast lesions on contrast-enhanced cone beam CT

Science.gov (United States)

Wang, Xixi; Nagarajan, Mahesh B.; Conover, David; Ning, Ruola; O'Connell, Avice; Wismueller, Axel

2014-04-01

Cone beam computed tomography (CBCT) has found use in mammography for imaging the entire breast with sufficient spatial resolution at a radiation dose within the range of that of conventional mammography. Recently, enhancement of lesion tissue through the use of contrast agents has been proposed for cone beam CT. This study investigates whether the use of such contrast agents improves the ability of texture features to differentiate lesion texture from healthy tissue on CBCT in an automated manner. For this purpose, 9 lesions were annotated by an experienced radiologist on both regular and contrast-enhanced CBCT images using two-dimensional (2D) square ROIs. These lesions were then segmented, and each pixel within the lesion ROI was assigned a label - lesion or non-lesion, based on the segmentation mask. On both sets of CBCT images, four three-dimensional (3D) Minkowski Functionals were used to characterize the local topology at each pixel. The resulting feature vectors were then used in a machine learning task involving support vector regression with a linear kernel (SVRlin) to classify each pixel as belonging to the lesion or non-lesion region of the ROI. Classification performance was assessed using the area under the receiver-operating characteristic (ROC) curve (AUC). Minkowski Functionals derived from contrastenhanced CBCT images were found to exhibit significantly better performance at distinguishing between lesion and non-lesion areas within the ROI when compared to those extracted from CBCT images without contrast enhancement (p < 0.05). Thus, contrast enhancement in CBCT can improve the ability of texture features to distinguish lesions from surrounding healthy tissue.

High throughput parallel backside contacting and periodic texturing for high-efficiency solar cells

Science.gov (United States)

Daniel, Claus; Blue, Craig A.; Ott, Ronald D.

2014-08-19

Disclosed are configurations of long-range ordered features of solar cell materials, and methods for forming same. Some features include electrical access openings through a backing layer to a photovoltaic material in the solar cell. Some features include textured features disposed adjacent a surface of a solar cell material. Typically the long-range ordered features are formed by ablating the solar cell material with a laser interference pattern from at least two laser beams.

Noncontact Surface Roughness Estimation Using 2D Complex Wavelet Enhanced ResNet for Intelligent Evaluation of Milled Metal Surface Quality

Directory of Open Access Journals (Sweden)

Weifang Sun

2018-03-01

Full Text Available Machined surfaces are rough from a microscopic perspective no matter how finely they are finished. Surface roughness is an important factor to consider during production quality control. Using modern techniques, surface roughness measurements are beneficial for improving machining quality. With optical imaging of machined surfaces as input, a convolutional neural network (CNN can be utilized as an effective way to characterize hierarchical features without prior knowledge. In this paper, a novel method based on CNN is proposed for making intelligent surface roughness identifications. The technical scheme incorporates there elements: texture skew correction, image filtering, and intelligent neural network learning. Firstly, a texture skew correction algorithm, based on an improved Sobel operator and Hough transform, is applied such that surface texture directions can be adjusted. Secondly, two-dimensional (2D dual tree complex wavelet transform (DTCWT is employed to retrieve surface topology information, which is more effective for feature classifications. In addition, residual network (ResNet is utilized to ensure automatic recognition of the filtered texture features. The proposed method has verified its feasibility as well as its effectiveness in actual surface roughness estimation experiments using the material of spheroidal graphite cast iron 500-7 in an agricultural machinery manufacturing company. Testing results demonstrate the proposed method has achieved high-precision surface roughness estimation.

Bilinear magnetoelectric resistance as a probe of three-dimensional spin texture in topological surface states

Science.gov (United States)

He, Pan; Zhang, Steven S.-L.; Zhu, Dapeng; Liu, Yang; Wang, Yi; Yu, Jiawei; Vignale, Giovanni; Yang, Hyunsoo

2018-05-01

Surface states of three-dimensional topological insulators exhibit the phenomenon of spin-momentum locking, whereby the orientation of an electron spin is determined by its momentum. Probing the spin texture of these states is of critical importance for the realization of topological insulator devices, but the main technique currently available is spin- and angle-resolved photoemission spectroscopy. Here we reveal a close link between the spin texture and a new kind of magnetoresistance, which depends on the relative orientation of the current with respect to the magnetic field as well as the crystallographic axes, and scales linearly with both the applied electric and magnetic fields. This bilinear magnetoelectric resistance can be used to map the spin texture of topological surface states by simple transport measurements. For a prototypical Bi2Se3 single layer, we can map both the in-plane and out-of-plane components of the spin texture (the latter arising from hexagonal warping). Theoretical calculations suggest that the bilinear magnetoelectric resistance originates from conversion of a non-equilibrium spin current into a charge current under application of the external magnetic field.

Zone-size nonuniformity of {sup 18}F-FDG PET regional textural features predicts survival in patients with oropharyngeal cancer

Energy Technology Data Exchange (ETDEWEB)

Cheng, Nai-Ming [Chang Gung Memorial Hospital and Chang Gung University, Departments of Nuclear Medicine, Taiyuan (China); Chang Gung Memorial Hospital, Department of Nuclear Medicine, Keelung (China); National Tsing Hua University, Department of Biomedical Engineering and Environmental Sciences, Hsinchu (China); Fang, Yu-Hua Dean [Chang Gung University, Department of Electrical Engineering, Taiyuan (China); Lee, Li-yu [Chang Gung University College of Medicine, Department of Pathology, Chang Gung Memorial Hospital, Taoyuan (China); Chang, Joseph Tung-Chieh; Tsan, Din-Li [Chang Gung University College of Medicine, Department of Radiation Oncology, Chang Gung Memorial Hospital, Taoyuan (China); Ng, Shu-Hang [Chang Gung University College of Medicine, Department of Diagnostic Radiology, Chang Gung Memorial Hospital, Taoyuan (China); Wang, Hung-Ming [Chang Gung University College of Medicine, Division of Hematology/Oncology, Department of Internal Medicine, Chang Gung Memorial Hospital, Taoyuan (China); Liao, Chun-Ta [Chang Gung University College of Medicine, Department of Otolaryngology-Head and Neck Surgery, Chang Gung Memorial Hospital, Taoyuan (China); Yang, Lan-Yan [Chang Gung Memorial Hospital, Biostatistics Unit, Clinical Trial Center, Taoyuan (China); Hsu, Ching-Han [National Tsing Hua University, Department of Biomedical Engineering and Environmental Sciences, Hsinchu (China); Yen, Tzu-Chen [Chang Gung Memorial Hospital and Chang Gung University, Departments of Nuclear Medicine, Taiyuan (China); Chang Gung University College of Medicine, Department of Nuclear Medicine and Molecular Imaging Center, Chang Gung Memorial Hospital, Taipei (China)

2014-10-23

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 (SUV{sub max} 42 %) and an adaptive threshold method were then used for validation. Regional textural features were extracted from pretreatment {sup 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 SUV{sub max} 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. (orig.)

Differences in the surface texture of aggregate particles determined by 3D model derived from optic microscope measurements

Directory of Open Access Journals (Sweden)

Jozef Komačka

2015-12-01

Full Text Available The surface texture of aggregate particles was investigated based on the 3D model of surface generated from the measurements by optic microscope. New software MicroSYS was developed to determine the wrapping plane of 3D model of aggregate using the function called “Thin plate spline“. New parameter for evaluation of surface texture of aggregate particle was proposed as the volumetric difference between two planes (wrapping plane and aggregate surface. Applicability of this parameters was tested on two aggregate fractions (4/8 and 8/11 coming form 11 quarries in Slovakia. The tested aggregates differed from petrography point of view and ranged from soft to hard. The difference among the quarries and also between fractions of aggregate was found out. The better surface texture was observed for the finner fraction of aggregate. Simultaneously, the better results were determined in the case of aggregate produced from the ingeous intrusive or extrusive rocks comparing to the sedimentary carbonate rocks aggregate.

Laser surface texturing of polymers for biomedical applications

Science.gov (United States)

Riveiro, Antonio; Maçon, Anthony L. B.; del Val, Jesus; Comesaña, Rafael; Pou, Juan

2018-02-01

Polymers are materials widely used in biomedical science because of their biocompatibility, and good mechanical properties (which, in some cases, are similar to those of human tissues); however, these materials are, in general, chemically and biologically inert. Surface characteristics, such as topography (at the macro-, micro, and nanoscale), surface chemistry, surface energy, charge or wettability are interrelated properties, and they cooperatively influence the biological performance of materials when used for biomedical applications. They regulate the biological response at the implant/tissue interface (e.g., influencing the cell adhesion, cell orientation, cell motility, etc.). Several surface processing techniques have been explored to modulate these properties for biomedical applications. Despite their potentials, these methods have limitations that prevent their applicability. In this regard, laser-based methods, in particular laser surface texturing (LST), can be an interesting alternative. Different works have showed the potentiality of this technique to control the surface properties of biomedical polymers and enhance their biological performance; however, more research is needed to obtain the desired biological response. This work provides a general overview of the basics and applications of LST for the surface modification of polymers currently used in the clinical practice (e.g. PEEK, UHMWPE, PP, etc.). The modification of roughness, wettability, and their impact on the biological response is addressed to offer new insights on the surface modification of biomedical polymers.

Synthesis of nano-textured biocompatible scaffolds from chicken eggshells

International Nuclear Information System (INIS)

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

2012-01-01

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

Arc-textured metal surfaces for high thermal emittance space radiators

International Nuclear Information System (INIS)

Banks, B.A.; Rutledge, S.K.; Mirtich, M.J.; Behrend, T.; Hotes, D.; Kussmaul, M.; Barry, J.; Stidham, C.; Stueber, T.; DiFilippo, F.

1994-01-01

Carbon arc electrical discharges struck across the surfaces of metals such as Nb-1% Zr, alter the morphology to produce a high thermal emittance surface. Metal from the surface and carbon from the arc electrode vaporize during arcing, and then condense on the metal surface to produce a microscopically rough surface having a high thermal emittance. Quantitative spectral reflectance measurements from 0.33 to 15 μm were made on metal surfaces which were carbon arc treated in an inert gas environment. The resulting spectral reflectance data were then used to calculate thermal emittance as a function of temperature for various methods of arc treatment. The results of arc treatment on various metals are presented for both ac and dc arcs. Surface characterization data, including thermal emittance as a function of temperature, scanning electron microscopy, and atomic oxygen durability, are also presented. Ac arc texturing was found to increase the thermal emittance at 800 K from 0.05. to 0.70

TH-E-BRF-04: Characterizing the Response of Texture-Based CT Image Features for Quantification of Radiation-Induced Normal Lung Damage

International Nuclear Information System (INIS)

Krafft, S; Court, L; Briere, T; Martel, M

2014-01-01

Purpose: Radiation induced lung damage (RILD) is an important dose-limiting toxicity for patients treated with radiation therapy. Scoring systems for RILD are subjective and limit our ability to find robust predictors of toxicity. We investigate the dose and time-related response for texture-based lung CT image features that serve as potential quantitative measures of RILD. Methods: Pre- and post-RT diagnostic imaging studies were collected for retrospective analysis of 21 patients treated with photon or proton radiotherapy for NSCLC. Total lung and selected isodose contours (0–5, 5–15, 15–25Gy, etc.) were deformably registered from the treatment planning scan to the pre-RT and available follow-up CT studies for each patient. A CT image analysis framework was utilized to extract 3698 unique texture-based features (including co-occurrence and run length matrices) for each region of interest defined by the isodose contours and the total lung volume. Linear mixed models were fit to determine the relationship between feature change (relative to pre-RT), planned dose and time post-RT. Results: Seventy-three follow-up CT scans from 21 patients (median: 3 scans/patient) were analyzed to describe CT image feature change. At the p=0.05 level, dose affected feature change in 2706 (73.1%) of the available features. Similarly, time affected feature change in 408 (11.0%) of the available features. Both dose and time were significant predictors of feature change in a total of 231 (6.2%) of the extracted image features. Conclusion: Characterizing the dose and time-related response of a large number of texture-based CT image features is the first step toward identifying objective measures of lung toxicity necessary for assessment and prediction of RILD. There is evidence that numerous features are sensitive to both the radiation dose and time after RT. Beyond characterizing feature response, further investigation is warranted to determine the utility of these features as

TU-F-CAMPUS-J-05: Effect of Uncorrelated Noise Texture On Computed Tomography Quantitative Image Features

International Nuclear Information System (INIS)

Oliver, J; Budzevich, M; Moros, E; Zhang, G; Hunt, D

2015-01-01

Purpose: To investigate the relationship between quantitative image features (i.e. radiomics) and statistical fluctuations (i.e. electronic noise) in clinical Computed Tomography (CT) using the standardized American College of Radiology (ACR) CT accreditation phantom and patient images. Methods: Three levels of uncorrelated Gaussian noise were added to CT images of phantom and patients (20) acquired in static mode and respiratory tracking mode. We calculated the noise-power spectrum (NPS) of the original CT images of the phantom, and of the phantom images with added Gaussian noise with means of 50, 80, and 120 HU. Concurrently, on patient images (original and noise-added images), image features were calculated: 14 shape, 19 intensity (1st order statistics from intensity volume histograms), 18 GLCM features (2nd order statistics from grey level co-occurrence matrices) and 11 RLM features (2nd order statistics from run-length matrices). These features provide the underlying structural information of the images. GLCM (size 128x128) was calculated with a step size of 1 voxel in 13 directions and averaged. RLM feature calculation was performed in 13 directions with grey levels binning into 128 levels. Results: Adding the electronic noise to the images modified the quality of the NPS, shifting the noise from mostly correlated to mostly uncorrelated voxels. The dramatic increase in noise texture did not affect image structure/contours significantly for patient images. However, it did affect the image features and textures significantly as demonstrated by GLCM differences. Conclusion: Image features are sensitive to acquisition factors (simulated by adding uncorrelated Gaussian noise). We speculate that image features will be more difficult to detect in the presence of electronic noise (an uncorrelated noise contributor) or, for that matter, any other highly correlated image noise. This work focuses on the effect of electronic, uncorrelated, noise and future work shall

Texture and wettability of metallic lotus leaves

Science.gov (United States)

Frankiewicz, C.; Attinger, D.

2016-02-01

Superhydrophobic surfaces with the self-cleaning behavior of lotus leaves are sought for drag reduction and phase change heat transfer applications. These superrepellent surfaces have traditionally been fabricated by random or deterministic texturing of a hydrophobic material. Recently, superrepellent surfaces have also been made from hydrophilic materials, by deterministic texturing using photolithography, without low-surface energy coating. Here, we show that hydrophilic materials can also be made superrepellent to water by chemical texturing, a stochastic rather than deterministic process. These metallic surfaces are the first analog of lotus leaves, in terms of wettability, texture and repellency. A mechanistic model is also proposed to describe the influence of multiple tiers of roughness on wettability and repellency. This demonstrated ability to make hydrophilic materials superrepellent without deterministic structuring or additional coatings opens the way to large scale and robust manufacturing of superrepellent surfaces.Superhydrophobic surfaces with the self-cleaning behavior of lotus leaves are sought for drag reduction and phase change heat transfer applications. These superrepellent surfaces have traditionally been fabricated by random or deterministic texturing of a hydrophobic material. Recently, superrepellent surfaces have also been made from hydrophilic materials, by deterministic texturing using photolithography, without low-surface energy coating. Here, we show that hydrophilic materials can also be made superrepellent to water by chemical texturing, a stochastic rather than deterministic process. These metallic surfaces are the first analog of lotus leaves, in terms of wettability, texture and repellency. A mechanistic model is also proposed to describe the influence of multiple tiers of roughness on wettability and repellency. This demonstrated ability to make hydrophilic materials superrepellent without deterministic structuring or additional

Quantitative evaluation methods of skin condition based on texture feature parameters

Directory of Open Access Journals (Sweden)

Hui Pang

2017-03-01

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

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

Science.gov (United States)

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

2017-03-01

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

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

Science.gov (United States)

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

2009-01-01

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

Separate channels for processing form, texture, and color: evidence from FMRI adaptation and visual object agnosia.

Science.gov (United States)

Cavina-Pratesi, C; Kentridge, R W; Heywood, C A; Milner, A D

2010-10-01

Previous neuroimaging research suggests that although object shape is analyzed in the lateral occipital cortex, surface properties of objects, such as color and texture, are dealt with in more medial areas, close to the collateral sulcus (CoS). The present study sought to determine whether there is a single medial region concerned with surface properties in general or whether instead there are multiple foci independently extracting different surface properties. We used stimuli varying in their shape, texture, or color, and tested healthy participants and 2 object-agnosic patients, in both a discrimination task and a functional MR adaptation paradigm. We found a double dissociation between medial and lateral occipitotemporal cortices in processing surface (texture or color) versus geometric (shape) properties, respectively. In Experiment 2, we found that the medial occipitotemporal cortex houses separate foci for color (within anterior CoS and lingual gyrus) and texture (caudally within posterior CoS). In addition, we found that areas selective for shape, texture, and color individually were quite distinct from those that respond to all of these features together (shape and texture and color). These latter areas appear to correspond to those associated with the perception of complex stimuli such as faces and places.

Fast Characterization of Moving Samples with Nano-Textured Surfaces

DEFF Research Database (Denmark)

Madsen, Morten Hannibal; Hansen, Poul-Erik; Zalkovskij, Maksim

2015-01-01

Characterization of structures using conventional optical microscopy is restricted by the diffraction limit. Techniques like atomic force and scanning electron microscopy can investigate smaller structures but are very time consuming. We show that using scatterometry, a technique based on optical...... diffraction, integrated into a commercial light microscope we can characterize nano-textured surfaces in a few milliseconds. The adapted microscope has two detectors, a CCD camera used to easily find an area of interest and a spectrometer for the measurements. We demonstrate that the microscope has...

Modeling of liquid–gas meniscus for textured surfaces: effects of curvature and local slip length

International Nuclear Information System (INIS)

Gaddam, Anvesh; Garg, Mayank; Agrawal, Amit; Joshi, Suhas S

2015-01-01

Surface texturing at the micro/nanolevel allows air to be trapped in sufficiently small cavities, thereby reducing the flow resistance over the surface in the laminar regime. The nature of the liquid–gas meniscus plays an important role in defining the boundary condition and it depends on the flow conditions and geometrical properties of textures. In the present work, we employ the unsteady volume of fluid model to investigate the behavior of the liquid–gas meniscus for ridges arranged normal to the flow direction to substantiate the frictional resistance of flow in a microchannel. It is found that the assumption of ‘zero shear stress’ at the liquid–gas interface grossly overpredicts the effective slip length with meniscus curvature and local partial slip length playing the dominant role. Numerical simulations performed in the laminar regime (20  <  Re  <  120) over single layered ridges normal to the flow direction revealed the effect of texture geometry on the reduction in pressure drop. In single layered structures, lotus-like geometries exhibited a greater reduction in drag (more than 30%) when compared to all other texture geometries. It is recognized that the flow experiences expansion and contraction cycles as it flows over the transverse ridges increasing the frictional resistance. Our findings will help to modify the boundary condition at the liquid–gas meniscus for accurate modeling in the laminar regime and to optimize the texture geometry to improve drag reduction. (paper)

Crystal surface analysis using matrix textural features classified by a Probabilistic Neural Network

International Nuclear Information System (INIS)

Sawyer, C.R.; Quach, V.T.; Nason, D.; van den Berg, L.

1991-01-01

A system is under development in which surface quality of a growing bulk mercuric iodide crystal is monitored by video camera at regular intervals for early detection of growth irregularities. Mercuric iodide single crystals are employed in radiation detectors. A microcomputer system is used for image capture and processing. The digitized image is divided into multiple overlappings subimage and features are extracted from each subimage based on statistical measures of the gray tone distribution, according to the method of Haralick [1]. Twenty parameters are derived from each subimage and presented to a Probabilistic Neural Network (PNN) [2] for classification. This number of parameters was found to be optimal for the system. The PNN is a hierarchical, feed-forward network that can be rapidly reconfigured as additional training data become available. Training data is gathered by reviewing digital images of many crystals during their growth cycle and compiling two sets of images, those with and without irregularities. 6 refs., 4 figs

Pretreatment 18F-FDG PET Textural Features in Locally Advanced Non-Small Cell Lung Cancer: Secondary Analysis of ACRIN 6668/RTOG 0235.

Science.gov (United States)

Ohri, Nitin; Duan, Fenghai; Snyder, Bradley S; Wei, Bo; Machtay, Mitchell; Alavi, Abass; Siegel, Barry A; Johnson, Douglas W; Bradley, Jeffrey D; DeNittis, Albert; Werner-Wasik, Maria; El Naqa, Issam

2016-06-01

In a secondary analysis of American College of Radiology Imaging Network (ACRIN) 6668/RTOG 0235, high pretreatment metabolic tumor volume (MTV) on (18)F-FDG PET was found to be a poor prognostic factor for patients treated with chemoradiotherapy for locally advanced non-small cell lung cancer (NSCLC). Here we utilize the same dataset to explore whether heterogeneity metrics based on PET textural features can provide additional prognostic information. Patients with locally advanced NSCLC underwent (18)F-FDG PET prior to treatment. A gradient-based segmentation tool was used to contour each patient's primary tumor. MTV, maximum SUV, and 43 textural features were extracted for each tumor. To address overfitting and high collinearity among PET features, the least absolute shrinkage and selection operator (LASSO) method was applied to identify features that were independent predictors of overall survival (OS) after adjusting for MTV. Recursive binary partitioning in a conditional inference framework was utilized to identify optimal thresholds. Kaplan-Meier curves and log-rank testing were used to compare outcomes among patient groups. Two hundred one patients met inclusion criteria. The LASSO procedure identified 1 textural feature (SumMean) as an independent predictor of OS. The optimal cutpoint for MTV was 93.3 cm(3), and the optimal SumMean cutpoint for tumors above 93.3 cm(3) was 0.018. This grouped patients into three categories: low tumor MTV (n = 155; median OS, 22.6 mo), high tumor MTV and high SumMean (n = 23; median OS, 20.0 mo), and high tumor MTV and low SumMean (n = 23; median OS, 6.2 mo; log-rank P textural PET features in the context of established prognostic factors. We have also identified a promising feature that may have prognostic value in locally advanced NSCLC patients with large tumors who are treated with chemoradiotherapy. Validation studies are warranted. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Pretreatment 18F-FDG PET Textural Features in Locally Advanced Non–Small Cell Lung Cancer: Secondary Analysis of ACRIN 6668/RTOG 0235

Science.gov (United States)

Ohri, Nitin; Duan, Fenghai; Snyder, Bradley S.; Wei, Bo; Machtay, Mitchell; Alavi, Abass; Siegel, Barry A.; Johnson, Douglas W.; Bradley, Jeffrey D.; DeNittis, Albert; Werner-Wasik, Maria; El Naqa, Issam

2016-01-01

In a secondary analysis of American College of Radiology Imaging Network (ACRIN) 6668/RTOG 0235, high pretreatment metabolic tumor volume (MTV) on 18F-FDG PET was found to be a poor prognostic factor for patients treated with chemoradiotherapy for locally advanced non–small cell lung cancer (NSCLC). Here we utilize the same dataset to explore whether heterogeneity metrics based on PET textural features can provide additional prognostic information. Methods Patients with locally advanced NSCLC underwent 18F-FDG PET prior to treatment. A gradient-based segmentation tool was used to contour each patient’s primary tumor. MTV, maximum SUV, and 43 textural features were extracted for each tumor. To address over-fitting and high collinearity among PET features, the least absolute shrinkage and selection operator (LASSO) method was applied to identify features that were independent predictors of overall survival (OS) after adjusting for MTV. Recursive binary partitioning in a conditional inference framework was utilized to identify optimal thresholds. Kaplan–Meier curves and log-rank testing were used to compare outcomes among patient groups. Results Two hundred one patients met inclusion criteria. The LASSO procedure identified 1 textural feature (SumMean) as an independent predictor of OS. The optimal cutpoint for MTV was 93.3 cm3, and the optimal Sum-Mean cutpoint for tumors above 93.3 cm3 was 0.018. This grouped patients into three categories: low tumor MTV (n = 155; median OS, 22.6 mo), high tumor MTV and high SumMean (n = 23; median OS, 20.0 mo), and high tumor MTV and low SumMean (n = 23; median OS, 6.2 mo; log-rank P textural PET features in the context of established prognostic factors. We have also identified a promising feature that may have prognostic value in locally advanced NSCLC patients with large tumors who are treated with chemoradiotherapy. Validation studies are warranted. PMID:26912429

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

Energy Technology Data Exchange (ETDEWEB)

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

2014-06-15

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

An explorative childhood pneumonia analysis based on ultrasonic imaging texture features

Science.gov (United States)

Zenteno, Omar; Diaz, Kristians; Lavarello, Roberto; Zimic, Mirko; Correa, Malena; Mayta, Holger; Anticona, Cynthia; Pajuelo, Monica; Oberhelman, Richard; Checkley, William; Gilman, Robert H.; Figueroa, Dante; Castañeda, Benjamín.

2015-12-01

According to World Health Organization, pneumonia is the respiratory disease with the highest pediatric mortality rate accounting for 15% of all deaths of children under 5 years old worldwide. The diagnosis of pneumonia is commonly made by clinical criteria with support from ancillary studies and also laboratory findings. Chest imaging is commonly done with chest X-rays and occasionally with a chest CT scan. Lung ultrasound is a promising alternative for chest imaging; however, interpretation is subjective and requires adequate training. In the present work, a two-class classification algorithm based on four Gray-level co-occurrence matrix texture features (i.e., Contrast, Correlation, Energy and Homogeneity) extracted from lung ultrasound images from children aged between six months and five years is presented. Ultrasound data was collected using a L14-5/38 linear transducer. The data consisted of 22 positive- and 68 negative-diagnosed B-mode cine-loops selected by a medical expert and captured in the facilities of the Instituto Nacional de Salud del Niño (Lima, Peru), for a total number of 90 videos obtained from twelve children diagnosed with pneumonia. The classification capacity of each feature was explored independently and the optimal threshold was selected by a receiver operator characteristic (ROC) curve analysis. In addition, a principal component analysis was performed to evaluate the combined performance of all the features. Contrast and correlation resulted the two more significant features. The classification performance of these two features by principal components was evaluated. The results revealed 82% sensitivity, 76% specificity, 78% accuracy and 0.85 area under the ROC.

Altering textural properties of fermented milk by using surface-engineered Lactococcus lactis.

Science.gov (United States)

Tarazanova, Mariya; Huppertz, Thom; Kok, Jan; Bachmann, Herwig

2018-05-09

Lactic acid bacteria are widely used for the fermentation of dairy products. While bacterial acidification rates, proteolytic activity and the production of exopolysaccharides are known to influence textural properties of fermented milk products, little is known about the role of the microbial surface on microbe-matrix interactions in dairy products. To investigate how alterations of the bacterial cell surface affect fermented milk properties, 25 isogenic Lactococcus lactis strains that differed with respect to surface charge, hydrophobicity, cell chaining, cell-clumping, attachment to milk proteins, pili expression and EPS production were used to produce fermented milk. We show that overexpression of pili increases surface hydrophobicity of various strains from 3-19% to 94-99%. A profound effect of different cell surface properties was an altered spatial distribution of the cells in the fermented product. Aggregated cells tightly fill the cavities of the protein matrix, while chaining cells seem to be localized randomly. A positive correlation was found between pili overexpression and viscosity and gel hardness of fermented milk. Gel hardness also positively correlated with clumping of cells in the fermented milk. Viscosity of fermented milk was also higher when it was produced with cells with a chaining phenotype or with cells that overexpress exopolysaccharides. Our results show that alteration of cell surface morphology affects textural parameters of fermented milk and cell localization in the product. This is indicative of a cell surface-dependent potential of bacterial cells as structure elements in fermented foods. © 2018 The Authors. Microbial Biotechnology published by John Wiley & Sons Ltd and Society for Applied Microbiology.

Sliding behavior of oil droplets on nanosphere stacking layers with different surface textures

International Nuclear Information System (INIS)

Hsieh, Chien-Te; Wu, Fang-Lin; Chen, Wei-Yu

2010-01-01

Two facile coating techniques, gravitational sediment and spin coating, were applied for the creation of silica sphere stacking layers with different textures onto glass substrates that display various sliding abilities toward liquid drops with different surface tensions, ranged from 25.6 to 72.3 mN/m. The resulting silica surface exhibits oil repellency, long-period durability > 30 days, and oil sliding capability. The two-tier texture offers a better roll-off ability toward liquid drops with a wide range of γ L , ranged from 30.2 to 72.3 mN/m, i.e., when the sliding angle (SA) ad ) appears to describe the sliding behavior within the W ad region: 2.20-3.03 mN/m. The smaller W ad , the easier drop sliding (i.e., the smaller SA value) takes place on the surfaces. The W ad value ∼3.03 mN/m shows a critical kinetic barrier for drop sliding on the silica surfaces from stationary to movement states. This work proposes a mathematical model to simulate the sliding behavior of oil drops on a nanosphere stacking layer, confirming the anti-oil contamination capability.

Assessing Asphalt and Concrete Pavement Surface Texture in the Field

OpenAIRE

Saad I. Sarsam; Huda N. Al Shareef

2016-01-01

The incorporation of safety characteristics into the traditional pavement structural design or in the functional evaluation of pavement condition has not been established yet. The design has focused on the structural capacity of the roadway so that the pavement can withstand specific level of repetitive loading over the design life. On the other hand, the surface texture condition was neither included in the AASHTO design procedure nor in the present serviceability index measurements. The ...

Automatic Glaucoma Detection Based on Optic Disc Segmentation and Texture Feature Extraction

Directory of Open Access Journals (Sweden)

Maíla de Lima Claro

2016-08-01

Full Text Available The use of digital image processing techniques is prominent in medical settings for the automatic diagnosis of diseases. Glaucoma is the second leading cause of blindness in the world and it has no cure. Currently, there are treatments to prevent vision loss, but the disease must be detected in the early stages. Thus, the objective of this work is to develop an automatic detection method of Glaucoma in retinal images. The methodology used in the study were: acquisition of image database, Optic Disc segmentation, texture feature extraction in different color models and classiffication of images in glaucomatous or not. We obtained results of 93% accuracy.

MO-G-BRF-01: BEST IN PHYSICS (JOINT IMAGING-THERAPY) - Sensitivity of PET-Based Texture Features to Respiratory Motion in Non-Small Cell Lung Cancer (NSCLC)

Energy Technology Data Exchange (ETDEWEB)

Yip, S; Aerts, H; Berbeco, R [Brigham and Womens Hospital, Boston, MA (United States); Farber Cancer Institute, Boston, MA (United States); McCall, K [Brigham and Womens Hospital, Boston, MA (United States); Aristophanous, M [Farber Cancer Institute, Boston, MA (United States); Chen, A [UT MD Anderson Cancer Center, Houston, TX, (United States)

2014-06-15

Purpose: PET-based texture features are used to quantify tumor heterogeneity due to their predictive power in treatment outcome. We investigated the sensitivity of texture features to tumor motion by comparing whole body (3D) and respiratory-gated (4D) PET imaging. Methods: Twenty-six patients (34 lesions) received 3D and 4D [F-18]FDG-PET scans before chemo-radiotherapy. The acquired 4D data were retrospectively binned into five breathing phases to create the 4D image sequence. Four texture features (Coarseness, Contrast, Busyness, and Complexity) were computed within the the physician-defined tumor volume. The relative difference (δ) in each measure between the 3D- and 4D-PET imaging was calculated. Wilcoxon signed-rank test (p<0.01) was used to determine if δ was significantly different from zero. Coefficient of variation (CV) was used to determine the variability in the texture features between all 4D-PET phases. Pearson correlation coefficient was used to investigate the impact of tumor size and motion amplitude on δ. Results: Significant differences (p<<0.01) between 3D and 4D imaging were found for Coarseness, Busyness, and Complexity. The difference for Contrast was not significant (p>0.24). 4D-PET increased Busyness (∼20%) and Complexity (∼20%), and decreased Coarseness (∼10%) and Contrast (∼5%) compared to 3D-PET. Nearly negligible variability (CV=3.9%) was found between the 4D phase bins for Coarseness and Complexity. Moderate variability was found for Contrast and Busyness (CV∼10%). Poor correlation was found between the tumor volume and δ for the texture features (R=−0.34−0.34). Motion amplitude had moderate impact on δ for Contrast and Busyness (R=−0.64− 0.54) and no impact for Coarseness and Complexity (R=−0.29−0.17). Conclusion: Substantial differences in textures were found between 3D and 4D-PET imaging. Moreover, the variability between phase bins for Coarseness and Complexity was negligible, suggesting that similar

MO-G-BRF-01: BEST IN PHYSICS (JOINT IMAGING-THERAPY) - Sensitivity of PET-Based Texture Features to Respiratory Motion in Non-Small Cell Lung Cancer (NSCLC)

International Nuclear Information System (INIS)

Yip, S; Aerts, H; Berbeco, R; McCall, K; Aristophanous, M; Chen, A

2014-01-01

Purpose: PET-based texture features are used to quantify tumor heterogeneity due to their predictive power in treatment outcome. We investigated the sensitivity of texture features to tumor motion by comparing whole body (3D) and respiratory-gated (4D) PET imaging. Methods: Twenty-six patients (34 lesions) received 3D and 4D [F-18]FDG-PET scans before chemo-radiotherapy. The acquired 4D data were retrospectively binned into five breathing phases to create the 4D image sequence. Four texture features (Coarseness, Contrast, Busyness, and Complexity) were computed within the the physician-defined tumor volume. The relative difference (δ) in each measure between the 3D- and 4D-PET imaging was calculated. Wilcoxon signed-rank test (p<0.01) was used to determine if δ was significantly different from zero. Coefficient of variation (CV) was used to determine the variability in the texture features between all 4D-PET phases. Pearson correlation coefficient was used to investigate the impact of tumor size and motion amplitude on δ. Results: Significant differences (p<<0.01) between 3D and 4D imaging were found for Coarseness, Busyness, and Complexity. The difference for Contrast was not significant (p>0.24). 4D-PET increased Busyness (∼20%) and Complexity (∼20%), and decreased Coarseness (∼10%) and Contrast (∼5%) compared to 3D-PET. Nearly negligible variability (CV=3.9%) was found between the 4D phase bins for Coarseness and Complexity. Moderate variability was found for Contrast and Busyness (CV∼10%). Poor correlation was found between the tumor volume and δ for the texture features (R=−0.34−0.34). Motion amplitude had moderate impact on δ for Contrast and Busyness (R=−0.64− 0.54) and no impact for Coarseness and Complexity (R=−0.29−0.17). Conclusion: Substantial differences in textures were found between 3D and 4D-PET imaging. Moreover, the variability between phase bins for Coarseness and Complexity was negligible, suggesting that similar

Effects of textural and surface characteristics of microporous activated carbons on the methane adsorption capacity at high pressures

International Nuclear Information System (INIS)

Bastos-Neto, M.; Canabrava, D.V.; Torres, A.E.B.; Rodriguez-Castellon, E.; Jimenez-Lopez, A.; Azevedo, D.C.S.; Cavalcante, C.L.

2007-01-01

The objective of this study is to relate textural and surface characteristics of selected microporous activated carbons to their methane storage capacity. In this work, a magnetic suspension balance (Rubotherm, Germany) was used to measure methane adsorption isotherms of several activated carbon samples. Textural characteristics were assessed by nitrogen adsorption on a regular surface area analyzer (Autosorb-MP, by Quantachrome, USA). N 2 adsorption was analysed by conventional models (BET, DR, HK) and by Monte Carlo molecular simulations. Elemental and surface analyses were performed by X-ray photoelectronic spectroscopy (XPS) for the selected samples. A comparative analysis was then carried out with the purpose of defining some correlation among the variables under study. For the system under study, pore size distribution and micropore volume seem to be a determining factor as long as the solid surface is perfectly hydrophobic. It was concluded that the textural parameters per se do not unequivocally determine natural gas storage capacities. Surface chemistry and methane adsorption equilibria must be taken into account in the decision-making process of choosing an adsorbent for gas storage

Depth image enhancement using perceptual texture priors

Science.gov (United States)

Bang, Duhyeon; Shim, Hyunjung

2015-03-01

A depth camera is widely used in various applications because it provides a depth image of the scene in real time. However, due to the limited power consumption, the depth camera presents severe noises, incapable of providing the high quality 3D data. Although the smoothness prior is often employed to subside the depth noise, it discards the geometric details so to degrade the distance resolution and hinder achieving the realism in 3D contents. In this paper, we propose a perceptual-based depth image enhancement technique that automatically recovers the depth details of various textures, using a statistical framework inspired by human mechanism of perceiving surface details by texture priors. We construct the database composed of the high quality normals. Based on the recent studies in human visual perception (HVP), we select the pattern density as a primary feature to classify textures. Upon the classification results, we match and substitute the noisy input normals with high quality normals in the database. As a result, our method provides the high quality depth image preserving the surface details. We expect that our work is effective to enhance the details of depth image from 3D sensors and to provide a high-fidelity virtual reality experience.

Development of a surface topography instrument for automotive textured steel plate

Science.gov (United States)

Wang, Zhen; Wang, Shenghuai; Chen, Yurong; Xie, Tiebang

2010-08-01

The surface topography of automotive steel plate is decisive to its stamping, painting and image clarity performances. For measuring this kind of surface topography, an instrument has been developed based on the principle of vertical scanning white light microscopy interference principle. The microscopy interference system of this instrument is designed based on the structure of Linnik interference microscopy. The 1D worktable of Z direction is designed and introduced in details. The work principle of this instrument is analyzed. In measuring process, the interference microscopy is derived as a whole and the measured surface is scanned in vertical direction. The measurement accuracy and validity is verified by templates. Surface topography of textured steel plate is also measured by this instrument.

Modeling Human Aesthetic Perception of Visual Textures

NARCIS (Netherlands)

Thumfart, Stefan; Jacobs, Richard H. A. H.; Lughofer, Edwin; Eitzinger, Christian; Cornelissen, Frans W.; Groissboeck, Werner; Richter, Roland

Texture is extensively used in areas such as product design and architecture to convey specific aesthetic information. Using the results of a psychological experiment, we model the relationship between computational texture features and aesthetic properties of visual textures. Contrary to previous

Orbital selective spin-texture in a topological insulator

Energy Technology Data Exchange (ETDEWEB)

Singh, Bahadur, E-mail: bahadursingh24@gmail.com; Prasad, R. [Department of Physics, Indian Institute of Technology Kanpur, Kanpur 208016 (India)

2015-05-15

Three-dimensional topological insulators support a metallic non-trivial surface state with unique spin texture, where spin and momentum are locked perpendicular to each other. In this work, we investigate the orbital selective spin-texture associated with the topological surface states in Sb2Te{sub 3}, using the first principles calculations. Sb2Te{sub 3} is a strong topological insulator with a p-p type bulk band inversion at the Γ-point and supports a single topological metallic surface state with upper (lower) Dirac-cone has left (right) handed spin-texture. Here, we show that the topological surface state has an additional locking between the spin and orbitals, leading to an orbital selective spin-texture. The out-of-plane orbitals (p{sub z} orbitals) have an isotropic orbital texture for both the Dirac cones with an associated left and right handed spin-texture for the upper and lower Dirac cones, respectively. In contrast, the in-planar orbital texture (p{sub x} and p{sub y} projections) is tangential for the upper Dirac-cone and is radial for the lower Dirac-cone surface state. The dominant in-planar orbital texture in both the Dirac cones lead to a right handed orbital-selective spin-texture.

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

Science.gov (United States)

Zyout, Imad; Czajkowska, Joanna; Grzegorzek, Marcin

2015-12-01

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

The role of the background: texture segregation and figure-ground segmentation.

Science.gov (United States)

Caputo, G

1996-09-01

The effects of a texture surround composed of line elements on a stimulus within which a target line element segregates, were studied. Detection and discrimination of the target when it had the same orientation as the surround were impaired at short presentation time; on the other hand, no effect was present when they were reciprocally orthogonal. These results are interpreted as background completion in texture segregation; a texture made up of similar elements is represented as a continuous surface with contour and contrast of an embedded element inhibited. This interpretation is further confirmed with a simple line protruding from an annulus. Generally, the results are taken as evidence that local features are prevented from segmenting when they are parts of a global entity.