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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

2014-01-13

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

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

NASA Astrophysics Data System (ADS)

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

1994-11-01

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

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

PubMed Central

Mehrabani, Homayun; Ray, Neil; Tse, Kyle

2014-01-01

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 interaction with surface pattern. PMID:25279268

Textural evolution of partially-molten planetary materials in microgravity

NASA Technical Reports Server (NTRS)

Watson, E. B.

1987-01-01

Recent Earth-based experiments examining the textural evolution of partially-molten rocks have revealed two important ways in which surface energy considerations affect magma. An initial experimental program addressing surface-energy effects on partially-molten materials in microgravity would involve simple, isothermal treatment of natural samples (meteorites, perioditic komatiite) at preselected temperatures in the melting range. Textural evolution would be assessed by time studies in which the only experiment variable would be run duration. Textural characterization of each sample would be done by quenching, recover, and sectioning for generally later, computer-aided interpretation of features.

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

PubMed

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

2016-08-01

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

Decorating surfaces with bidirectional texture functions.

PubMed

Zhou, Kun; Du, Peng; Wang, Lifeng; Matsushita, Yasuyuki; Shi, Jiaoying; Guo, Baining; Shum, Heung-Yeung

2005-01-01

We present a system for decorating arbitrary surfaces with bidirectional texture functions (BTF). Our system generates BTFs in two steps. First, we automatically synthesize a BTF over the target surface from a given BTF sample. Then, we let the user interactively paint BTF patches onto the surface such that the painted patches seamlessly integrate with the background patterns. Our system is based on a patch-based texture synthesis approach known as quilting. We present a graphcut algorithm for BTF synthesis on surfaces and the algorithm works well for a wide variety of BTF samples, including those which present problems for existing algorithms. We also describe a graphcut texture painting algorithm for creating new surface imperfections (e.g., dirt, cracks, scratches) from existing imperfections found in input BTF samples. Using these algorithms, we can decorate surfaces with real-world textures that have spatially-variant reflectance, fine-scale geometry details, and surfaces imperfections. A particularly attractive feature of BTF painting is that it allows us to capture imperfections of real materials and paint them onto geometry models. We demonstrate the effectiveness of our system with examples.

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

NASA Astrophysics Data System (ADS)

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.

Geometry- and Length Scale-Dependent Deformation and Recovery on Micro- and Nanopatterned Shape Memory Polymer Surfaces

PubMed Central

Lee, Wei Li; Low, Hong Yee

2016-01-01

Micro- and nanoscale surface textures, when optimally designed, present a unique approach to improve surface functionalities. Coupling surface texture with shape memory polymers may generate reversibly tuneable surface properties. A shape memory polyetherurethane is used to prepare various surface textures including 2 μm- and 200 nm-gratings, 250 nm-pillars and 200 nm-holes. The mechanical deformation via stretching and recovery of the surface texture are investigated as a function of length scales and shapes. Results show the 200 nm-grating exhibiting more deformation than 2 μm-grating. Grating imparts anisotropic and surface area-to-volume effects, causing different degree of deformation between gratings and pillars under the same applied macroscopic strain. Full distribution of stress within the film causes the holes to deform more substantially than the pillars. In the recovery study, unlike a nearly complete recovery for the gratings after 10 transformation cycles, the high contribution of surface energy impedes the recovery of holes and pillars. The surface textures are shown to perform a switchable wetting function. This study provides insights into how geometric features of shape memory surface patterns can be designed to modulate the shape programming and recovery, and how the control of reversibly deformable surface textures can be applied to transfer microdroplets. PMID:27026290

Deep Filter Banks for Texture Recognition, Description, and Segmentation.

PubMed

Cimpoi, Mircea; Maji, Subhransu; Kokkinos, Iasonas; Vedaldi, Andrea

Visual textures have played a key role in image understanding because they convey important semantics of images, and because texture representations that pool local image descriptors in an orderless manner have had a tremendous impact in diverse applications. In this paper we make several contributions to texture understanding. First, instead of focusing on texture instance and material category recognition, we propose a human-interpretable vocabulary of texture attributes to describe common texture patterns, complemented by a new describable texture dataset for benchmarking. Second, we look at the problem of recognizing materials and texture attributes in realistic imaging conditions, including when textures appear in clutter, developing corresponding benchmarks on top of the recently proposed OpenSurfaces dataset. Third, we revisit classic texture represenations, including bag-of-visual-words and the Fisher vectors, in the context of deep learning and show that these have excellent efficiency and generalization properties if the convolutional layers of a deep model are used as filter banks. We obtain in this manner state-of-the-art performance in numerous datasets well beyond textures, an efficient method to apply deep features to image regions, as well as benefit in transferring features from one domain to another.

Cloud classification in polar regions using AVHRR textural and spectral signatures

NASA Technical Reports Server (NTRS)

Welch, R. M.; Sengupta, S. K.; Weger, R. C.; Christopher, S. A.; Kuo, K. S.; Carsey, F. D.

1990-01-01

Arctic clouds and ice-covered surfaces are classified on the basis of textural and spectral features obtained with AVHRR 1.1-km spatial resolution imagery over the Beaufort Sea during May-October, 1989. Scenes were acquired about every 5 days, for a total of 38 cases. A list comprising 20 arctic-surface and cloud classes is compiled using spectral measures defined by Garand (1988).

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

NASA Astrophysics Data System (ADS)

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.

Evaluation and recognition of skin images with aging by support vector machine

NASA Astrophysics Data System (ADS)

Hu, Liangjun; Wu, Shulian; Li, Hui

2016-10-01

Aging is a very important issue not only in dermatology, but also cosmetic science. Cutaneous aging involves both chronological and photoaging aging process. The evaluation and classification of aging is an important issue with the medical cosmetology workers nowadays. The purpose of this study is to assess chronological-age-related and photo-age-related of human skin. The texture features of skin surface skin, such as coarseness, contrast were analyzed by Fourier transform and Tamura. And the aim of it is to detect the object hidden in the skin texture in difference aging skin. Then, Support vector machine was applied to train the texture feature. The different age's states were distinguished by the support vector machine (SVM) classifier. The results help us to further understand the mechanism of different aging skin from texture feature and help us to distinguish the different aging states.

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

PubMed

Iqbal, Abdullah; Valous, Nektarios A; Mendoza, Fernando; Sun, Da-Wen; Allen, Paul

2010-03-01

Images of three qualities of pre-sliced pork and Turkey hams were evaluated for colour and textural features to characterize and classify them, and to model the ham appearance grading and preference responses of a group of consumers. A total of 26 colour features and 40 textural features were extracted for analysis. Using Mahalanobis distance and feature inter-correlation analyses, two best colour [mean of S (saturation in HSV colour space), std. deviation of b*, which indicates blue to yellow in L*a*b* colour space] and three textural features [entropy of b*, contrast of H (hue of HSV colour space), entropy of R (red of RGB colour space)] for pork, and three colour (mean of R, mean of H, std. deviation of a*, which indicates green to red in L*a*b* colour space) and two textural features [contrast of B, contrast of L* (luminance or lightness in L*a*b* colour space)] for Turkey hams were selected as features with the highest discriminant power. High classification performances were reached for both types of hams (>99.5% for pork and >90.5% for Turkey) using the best selected features or combinations of them. In spite of the poor/fair agreement among ham consumers as determined by Kappa analysis (Kappa-value<0.4) for sensory grading (surface colour, colour uniformity, bitonality, texture appearance and acceptability), a dichotomous logistic regression model using the best image features was able to explain the variability of consumers' responses for all sensorial attributes with accuracies higher than 74.1% for pork hams and 83.3% for Turkey hams. Copyright 2009 Elsevier Ltd. All rights reserved.

Extraction of texture features with a multiresolution neural network

NASA Astrophysics Data System (ADS)

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

1992-09-01

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

Abiotic Versus Biotic Weathering Of Olivine As Possible Biosignatures

NASA Technical Reports Server (NTRS)

Longazo, Teresa G.; Wentworth, Susan J.; Clemett, Simon J.; Southam, Gordon; McKay, David S.

2001-01-01

We are investigating the weathering of silicate minerals by both purely inorganic, and biologically mediated processes using field-emission scanning electron microscopy (FESEM) and energy dispersive x-ray spectroscopy (EDS). By resolving surface textures and chemical compositions of weathered surfaces at the sub-micron scale we hope to be able to distinguish abiotic from biotic weathering processes and so establish a new biosignature applicable to the study of astromaterials including but not limited to the Martian meteorites. Sterilized olivine grains (San Carlos, Arizona) no more than 1-2 mm in their longest dimension were optically assayed to be uniform in color and free of inclusions were selected as weathering subjects. Prior to all experiments surface morphologies and Fe/Mg ratios were determined for each grain using FE-SEM and EDS. Experiments were divided into two categories abiotic and biotic and were compared with "naturally" weathered samples. For the preliminary experiments, two trials (open and closed to the ambient laboratory environment) were performed under abiotic conditions, and three trials under biotic conditions (control, day 1 and day 2). The open system abiotic trials used sterile grains heated at 98 C and 200 C for both 24 and 48 hours in 1L double distilled de-ionized water. The closed system abiotic trials were conducted under the same conditions but in a sealed two layer steel/Teflon "bomb" apparatus. The biotic trials used sterile grains mounted in a flow-through device attached to a wellhead on the Columbia River aquifer. Several discolored, altered, grains were selected to document "natural" weathering surface textures for comparison with the experimental samples. Preliminary results indicate there are qualitative differences in weathered surface textures among all the designed experiments. The olivine grains in abiotic trials displayed etching, pitting, denticulate margins, dissolution and clay formation. The scale of the features ranged from tens to a few microns with textures that remained relatively sharp and were crystallographically controlled. These results were comparable to that observed in the "naturally" weathered comparison/reference grains. Chemical analysis by EDS indicates these textures correlated with the relative loss of Mg and Fe cations by diffusional processes. In contrast the biotic results indicated changes in the etching patterns on the scale of hundreds of nm, which are neither sharp nor crystallographically controlled (nanoetching). Organisms, organic debris and/or extracellular polymeric substances (biofilm) were often in close proximity or direct contact with the nanoetching. While there are many poorly constrained variables in natural weathering experiments to contend with, such as the time scale, the chemistry of the fluids and degree of biologic participation, some preliminary observations can be made: (1) certain distinct surface textures appear correlated with the specific processes giving rise to these textures; (2) the process of diffusing cations can produce many similar styles of surface textural changes; and (3) the main difference between abiotic and biotically produced weathering is the scale (microns versus nanometers) and the style (crystallographically versus noncrystallographically controlled) of the textural features. Further investigation into nanosize scale surface textures should attempt to quantify both textures and chemical changes of the role of microorganisms in the weathering of silicates. Additional experiments addressing nanoscale textures of shock features for comparison with the current data set.

Dental microwear textures: reconstructing diets of fossil mammals

NASA Astrophysics Data System (ADS)

DeSantis, Larisa R. G.

2016-06-01

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.

Accuracy in breast shape alignment with 3D surface fitting algorithms.

PubMed

Riboldi, Marco; Gierga, David P; Chen, George T Y; Baroni, Guido

2009-04-01

Surface imaging is in use in radiotherapy clinical practice for patient setup optimization and monitoring. Breast alignment is accomplished by searching for a tentative spatial correspondence between the reference and daily surface shape models. In this study, the authors quantify whole breast shape alignment by relying on texture features digitized on 3D surface models. Texture feature localization was validated through repeated measurements in a silicone breast phantom, mounted on a high precision mechanical stage. Clinical investigations on breast shape alignment included 133 fractions in 18 patients treated with accelerated partial breast irradiation. The breast shape was detected with a 3D video based surface imaging system so that breathing was compensated. An in-house algorithm for breast alignment, based on surface fitting constrained by nipple matching (constrained surface fitting), was applied. Results were compared with a commercial software where no constraints are utilized (unconstrained surface fitting). Texture feature localization was validated within 2 mm in each anatomical direction. Clinical data show that unconstrained surface fitting achieves adequate accuracy in most cases, though nipple mismatch is considerably higher than residual surface distances (3.9 mm vs 0.6 mm on average). Outliers beyond 1 cm can be experienced as the result of a degenerate surface fit, where unconstrained surface fitting is not sufficient to establish spatial correspondence. In the constrained surface fitting algorithm, average surface mismatch within 1 mm was obtained when nipple position was forced to match in the [1.5; 5] mm range. In conclusion, optimal results can be obtained by trading off the desired overall surface congruence vs matching of selected landmarks (constraint). Constrained surface fitting is put forward to represent an improvement in setup accuracy for those applications where whole breast positional reproducibility is an issue.

Use of biomimetic hexagonal surface texture in friction against lubricated skin.

PubMed

Tsipenyuk, Alexey; Varenberg, Michael

2014-05-06

Smooth contact pads that evolved in insects, amphibians and mammals to enhance the attachment abilities of the animals' feet are often dressed with surface micropatterns of different shapes that act in the presence of a fluid secretion. One of the most striking surface patterns observed in contact pads of these animals is based on a hexagonal texture, which is recognized as a friction-oriented feature capable of suppressing both stick-slip and hydroplaning while enabling friction tuning. Here, we compare this design of natural friction surfaces to textures developed for working in similar conditions in disposable safety razors. When slid against lubricated human skin, the hexagonal surface texture is capable of generating about twice the friction of its technical competitors, which is related to it being much more effective at channelling of the lubricant fluid out of the contact zone. The draining channel shape and contact area fraction are found to be the most important geometrical parameters governing the fluid drainage rate.

Deciphering the Origin of Plume-Textured Geodes.

ERIC Educational Resources Information Center

Garlick, George Donald; Jones, Francis Tucker

1990-01-01

Presented is an interpretation of the inward and outward growth and formation of plume textured geodes available from southern Brazil. Field occurrence, morphology of vesicles, growth history, closure of the agate shell, microscopic features, coherent reflection of light from convoluted surfaces, and accessory minerals of the inner cavity are…

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

PubMed

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.

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

PubMed

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.

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

PubMed

Fink, B; Grammer, K; Thornhill, R

2001-03-01

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

Plastics and beaches: a degrading relationship.

PubMed

Corcoran, Patricia L; Biesinger, Mark C; Grifi, Meriem

2009-01-01

Plastic debris in Earth's oceans presents a serious environmental issue because breakdown by chemical weathering and mechanical erosion is minimal at sea. Following deposition on beaches, plastic materials are exposed to UV radiation and physical processes controlled by wind, current, wave and tide action. Plastic particles from Kauai's beaches were sampled to determine relationships between composition, surface textures, and plastics degradation. SEM images indicated that beach plastics feature both mechanically eroded and chemically weathered surface textures. Granular oxidation textures were concentrated along mechanically weakened fractures and along the margins of the more rounded plastic particles. Particles with oxidation textures also produced the most intense peaks in the lower wavenumber region of FTIR spectra. The textural results suggest that plastic debris is particularly conducive to both chemical and mechanical breakdown in beach environments, which cannot be said for plastics in other natural settings on Earth.

[Visual Texture Agnosia in Humans].

PubMed

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.

Efficient optical analysis of surface texture combinations for silicon solar cells

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

An RBF-based reparameterization method for constrained texture mapping.

PubMed

Yu, Hongchuan; Lee, Tong-Yee; Yeh, I-Cheng; Yang, Xiaosong; Li, Wenxi; Zhang, Jian J

2012-07-01

Texture mapping has long been used in computer graphics to enhance the realism of virtual scenes. However, to match the 3D model feature points with the corresponding pixels in a texture image, surface parameterization must satisfy specific positional constraints. However, despite numerous research efforts, the construction of a mathematically robust, foldover-free parameterization that is subject to positional constraints continues to be a challenge. In the present paper, this foldover problem is addressed by developing radial basis function (RBF)-based reparameterization. Given initial 2D embedding of a 3D surface, the proposed method can reparameterize 2D embedding into a foldover-free 2D mesh, satisfying a set of user-specified constraint points. In addition, this approach is mesh free. Therefore, generating smooth texture mapping results is possible without extra smoothing optimization.

Metal catalyst technique for texturing silicon solar cells

DOEpatents

Ruby, Douglas S.; Zaidi, Saleem H.

2001-01-01

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

The Influence of Local Geometric Effects on Mars Polar Processes

NASA Technical Reports Server (NTRS)

Hecht, M. H.

2005-01-01

Using simple, qualitative heat balance models, this paper addresses textures and structures that will result from the evolution of volatile layers by accretion and by ablation. Such phenomena may have global implications that are not apparent when only flat or sloped surfaces are modeled. In general, structures such as mounds or depressions formed out of volatile materials will evolve in shape such that the growth or retreat of any particular surface will be maximized. It can be shown that the local radius of curvature is proportional to the growth or retreat rate. For example, icy surfaces will tend to form facets that face the dominant sun direction. Two such cases are evaluated: a) Features associated with condensation of volatiles, include cold-trapping and redistribution, such as the concentration of frost around the Viking 2 lander [1]. Here I will focus on textures that likely result from the formation of seasonal CO2 deposits. b) Features associated with sublimation of volatiles, such as those described by Ingersoll et. al. [2] result in textured surfaces that affect both the apparent emissivity and albedo. Similar calculations have been performed with respect to the "Swiss cheese" features on the South Polar Cap [3]. Here, I evaluate the likely sublimation rates from optimal ice scarp structures and their implications for the long-term evolution of the polar caps and formation of layered terrain.

Separate processing of texture and form in the ventral stream: evidence from FMRI and visual agnosia.

PubMed

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

2010-02-01

Real-life visual object recognition requires the processing of more than just geometric (shape, size, and orientation) properties. Surface properties such as color and texture are equally important, particularly for providing information about the material properties of objects. Recent neuroimaging research suggests that geometric and surface properties are dealt with separately within the lateral occipital cortex (LOC) and the collateral sulcus (CoS), respectively. Here we compared objects that differed either in aspect ratio or in surface texture only, keeping all other visual properties constant. Results on brain-intact participants confirmed that surface texture activates an area in the posterior CoS, quite distinct from the area activated by shape within LOC. We also tested 2 patients with visual object agnosia, one of whom (DF) performed well on the texture task but at chance on the shape task, whereas the other (MS) showed the converse pattern. This behavioral double dissociation was matched by a parallel neuroimaging dissociation, with activation in CoS but not LOC in patient DF and activation in LOC but not CoS in patient MS. These data provide presumptive evidence that the areas respectively activated by shape and texture play a causally necessary role in the perceptual discrimination of these features.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Lunar textural analysis based on WAC-derived kilometer-scale roughness and entropy maps

NASA Astrophysics Data System (ADS)

Li, Bo; Wang, XueQiang; Zhang, Jiang; Chen, Jian; Ling, Zongcheng

2016-06-01

In general, textures are thought to be some complicated repeated patterns formed by elements, or primitives which are sorted in certain rules. Lunar surfaces record the interactions between its outside environment and itself, thus, based on high-resolution DEM model or image data, there are some topographic features which have different roughness and entropy values or signatures on lunar surfaces. Textures of lunar surfaces can help us to concentrate on typical topographic and photometric variations and reveal the relationships between obvious features (craters, impact basins, sinuous rilles (SRs) and ridges) with resurfacing processes on the Moon. In this paper, the term surface roughness is an expression of the variability of a topographic or photometric surface at kilometer scale, and the term entropy can characterize the variability inherent in a geological and topographic unit and evaluate the uncertainty of predictions made by a given geological process. We use the statistical moments of gray-level histograms in different-sized neighborhoods (e.g., 3, 5, 10, 20, 40 and 80 pixels) to compute the kilometer-scale roughness and entropy values, using the mosaic image from 70°N to 70°S obtained by Lunar Reconnaissance Orbiter (LRO) Wide Angle Camera (WAC). Large roughness and entropy signatures were only found in the larger scale maps, while the smallest 3-pixel scale map had more disorderly and unsystematic textures. According to the entropy values in 10-pixel scale entropy map, we made a frequency curve and categorized lunar surfaces into three types, shadow effects, maria and highlands. A 2D scatter plot of entropy versus roughness values was produced and we found that there were two point clusters corresponding to the highlands and maria, respectively. In the last, we compared the topographic and photometric signatures derived from Lunar Orbiter Laser Altimeter (LOLA) data and WAC mosaic image. On the lunar surfaces, the ridges have obvious multilevel topographic textures which are sensitive to the topographic changes, while the ejecta deposits of fresh craters appear obvious photometric textures which are sensitive to the brightness variations.

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

PubMed

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

2016-02-01

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

Search for Past Life on Mars: Possible Relict Biogenic Activity in Martian Meteorite ALH84001

NASA Technical Reports Server (NTRS)

McKay, David S.; Gibson, Everett K., Jr.; Thomas-Keprta, Kathie L.; Vali, Hojatollah; Romanek, Christopher S.; Clemett, Simon J.; Chillier, Xavier D. F.; Maechling, Claude R.; Zare, Richard N.

1996-01-01

Fresh fracture surfaces of the martian meteorite ALH84001 contain abundant polycyclic aromatic hydrocarbons (PAHs). These fresh fracture surfaces also display carbonate globules. Contamination studies suggest the PAHs are indigenous to the meteorite. High resolution scanning and transmission electron microscopy study of surface textures and internal structures of selected carbonate globules show that the globules contain fine-grained, secondary phases of single-domain magnetite and Fe-monosulfides. The carbonate globules are similar in texture and size to some terrestrial bacterially induced carbonate precipitates. Although inorganic formation is possible, formation of the globules by biogenic processes could explain many of the observed features including the PAHs. The PAHs, the carbonate globules, and their associated secondary mineral phases and textures could thus be fossil remains of a past martian biota.

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

PubMed Central

Dürsteler, Max R.

2014-01-01

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

Wavelet-based image analysis system for soil texture analysis

NASA Astrophysics Data System (ADS)

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

2003-05-01

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

Microstructure, microtexture and precipitation in the ultrafine-grained surface layer of an Al-Zn-Mg-Cu alloy processed by sliding friction treatment

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

Chen, Yanxia

2017-01-15

Precipitate redistribution and texture evolution are usually two concurrent aspects accompanying grain refinement induced by various surface treatment. However, the detailed precipitate redistribution characteristics and process, as well as crystallographic texture in the surface refined grain layer, are still far from full understanding. In this study, we focused on the microstructural and crystallographic features of the sliding friction treatment (SFT) induced surface deformation layer in a 7050 aluminum alloy. With the combination of transmission electron microscopy (TEM) and high angle angular dark field scanning TEM (HAADF-STEM) observations, a surface ultrafine grain (UFG) layer composed of both equiaxed and lamellar ultrafinemore » grains and decorated by high density of coarse grain boundary precipitates (GBPs) were revealed. Further precession electron diffraction (PED) assisted orientation mapping unraveled that high angle grain boundaries rather than low angle grain boundaries are the most favorable nucleation sites for GBPs. The prominent precipitate redistribution can be divided into three successive and interrelated stages, i.e. the mechanically induced precipitate dissolution, solute diffusion and reprecipitation. The quantitative prediction based on pipe diffusion along dislocations and grain boundary diffusion proved the distribution feasibility of GBPs around UFGs. Based on PED and electron backscatter diffraction (EBSD) analyses, the crystallographic texture of the surface UFG layer was identified as a shear texture composed of major rotated cube texture (001) 〈110〉 and minor (111) 〈112〉, while that of the adjoining lamellar coarse grained matrix was pure brass. The SFT induced surface severe shear deformation is responsible for texture evolution. - Highlights: •The surface ultrafine grain layer in a 7050 aluminum alloy was focused. •Precipitate redistribution and texture evolution were discussed. •The quantitative prediction proved the distribution feasibility of GBPs. •Precession electron diffraction orientation mapping showed a shear texture.« less

Femtosecond laser full and partial texturing of steel surfaces to reduce friction in lubricated contact

NASA Astrophysics Data System (ADS)

Ancona, Antonio; Carbone, Giuseppe; De Filippis, Michele; Volpe, Annalisa; Lugarà, Pietro Mario

2014-12-01

Minimizing mechanical losses and friction in vehicle engines would have a great impact on reducing fuel consumption and exhaust emissions, to the benefit of environmental protection. With this scope, laser surface texturing (LST) with femtosecond pulses is an emerging technology, which consists of creating, by laser ablation, an array of high-density microdimples on the surface of a mechanical device. The microtexture decreases the effective contact area and, in case of lubricated contact, acts as oil reservoir and trap for wear debris, leading to an overall friction reduction. Depending on the lubrication regime and on the texture geometry, several mechanisms may concur to modify friction such as the local reduction of the shear stress, the generation of a hydrodynamic lift between the surfaces or the formation of eddy-like flows at the bottom of the dimple cavities. All these effects have been investigated by fabricating and characterizing several LST surfaces by femtosecond laser ablation with different features: partial/full texture, circular/elliptical dimples, variable diameters, and depths but equivalent areal density. More than 85% of friction reduction has been obtained from the circular dimple geometry, but the elliptical texture allows adjusting the friction coefficient by changing its orientation with respect to the sliding direction.

Surface Erosion and Flow

NASA Image and Video Library

2003-04-09

The mottled surface texture and flow features observed in this NASA Mars Odyssey image suggest materials may be, or have been, mixed with ice. There is also evidence in some areas for infilling of sediments as crater rims and ridges appear covered.

Measurement, modeling and perception of painted surfaces: A Multi-scale Analysis of the Touch-up Problem

NASA Astrophysics Data System (ADS)

Kalghatgi, Suparna Kishore

Real-world surfaces typically have geometric features at a range of spatial scales. At the microscale, opaque surfaces are often characterized by bidirectional reflectance distribution functions (BRDF), which describes how a surface scatters incident light. At the mesoscale, surfaces often exhibit visible texture -- stochastic or patterned arrangements of geometric features that provide visual information about surface properties such as roughness, smoothness, softness, etc. These textures also affect how light is scattered by the surface, but the effects are at a different spatial scale than those captured by the BRDF. Through this research, we investigate how microscale and mesoscale surface properties interact to contribute to overall surface appearance. This behavior is also the cause of the well-known "touch-up problem" in the paint industry, where two regions coated with exactly the same paint, look different in color, gloss and/or texture because of differences in application methods. At first, samples were created by applying latex paint to standard wallboard surfaces. Two application methods- spraying and rolling were used. The BRDF and texture properties of the samples were measured, which revealed differences at both the microscale and mesoscale. This data was then used as input for a physically-based image synthesis algorithm, to generate realistic images of the surfaces under different viewing conditions. In order to understand the factors that govern touch-up visibility, psychophysical tests were conducted using calibrated, digital photographs of the samples as stimuli. Images were presented in pairs and a two alternative forced choice design was used for the experiments. These judgments were then used as data for a Thurstonian scaling analysis to produce psychophysical scales of visibility, which helped determine the effect of paint formulation, application methods, and viewing and illumination conditions on the touch-up problem. The results can be used as base data towards development of a psychophysical model that relates physical differences in paint formulation and application methods to visual differences in surface appearance.

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

PubMed

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

2012-11-30

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

A Combined Use of Decomposition and Texture for Terrain Classification of Fully Polarimetric SAR Images

NASA Astrophysics Data System (ADS)

Rodionova, N. V.

2007-03-01

This p aper presents two-stag e unsupervised terrain classification of fully polarimetr ic SA R data using Freeman and Durden decomposition based on three simp le scattering mechanisms: surface, volume and double bounce (first step), and textur al features (uncorrelated uniformity , contr ast, inv erse mo men t and entropy) obtained from grey lev el co-occurrence matr ices (GLCM) (second step). Textural f eatures ar e defined in moving w indow 5x5 pixels w ith N=32 (N - number of grey lev els) . This algorith m preserves th e purity of domin ant polarimetric scattering properties and defines textural features in each scatter ing category. It is shown better object discrimin ation after app lying textur e w ith in fix ed scattering category. Speckle r eduction is one of th e main mo ments in imag e interpr etation improvement because of its great influen ce on textur e. Results from unfiltered and Lee filtered polar imetr ic SAR imag es show that the v alues of contrast and en tropy decr ease and th e values of uniformity and inverse moment increase with speckle reduction, that's tru e for all polarizations (HH, VV, HV). Th e d iscr imination b etw een objects increases after speckle f ilter ing. Polar ization influen ce on textur e features is def ined by calculating th e features in SAR images w ith HH , VV and HV polarizations before and after speck le filter ing, and then creating RG B images. It is shown mor e polarization inf luence on textur e features (uniformity , inverse mo ment and entropy) before filtering and less influen ce - after speck le f iltering. I t's not true for contrast wher e polar ization influen ce is not ch anged practically w ith filtering. SIR-C/X-SA R SLC L-band imag es of Moscow r egion are used for illustr ation.

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

NASA Astrophysics Data System (ADS)

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

2008-03-01

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

Wrinkled, wavelength-tunable graphene-based surface topographies for directing cell alignment and morphology

PubMed Central

Wang, Zhongying; Tonderys, Daniel; Leggett, Susan E.; Williams, Evelyn Kendall; Kiani, Mehrdad T.; Steinberg, Ruben Spitz; Qiu, Yang; Wong, Ian Y.; Hurt, Robert H.

2015-01-01

Textured surfaces with periodic topographical features and long-range order are highly attractive for directing cell-material interactions. They mimic physiological environments more accurately than planar surfaces and can fundamentally alter cell alignment, shape, gene expression, and cellular assembly into superstructures or microtissues. Here we demonstrate for the first time that wrinkled graphene-based surfaces are suitable as textured cell attachment substrates, and that engineered wrinkling can dramatically alter cell alignment and morphology. The wrinkled surfaces are fabricated by graphene oxide wet deposition onto pre-stretched elastomers followed by relaxation and mild thermal treatment to stabilize the films in cell culture medium. Multilayer graphene oxide films form periodic, delaminated buckle textures whose wavelengths and amplitudes can be systematically tuned by variation in the wet deposition process. Human and murine fibroblasts attach to these textured films and remain viable, while developing pronounced alignment and elongation relative to those on planar graphene controls. Compared to lithographic patterning of nanogratings, this method has advantages in the simplicity and scalability of fabrication, as well as the opportunity to couple the use of topographic cues with the unique conductive, adsorptive, or barrier properties of graphene materials for functional biomedical devices. PMID:25848137

Shape from texture: an evaluation of visual cues

NASA Astrophysics Data System (ADS)

Mueller, Wolfgang; Hildebrand, Axel

1994-05-01

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

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

PubMed

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.

Femtosecond Laser Texturing of Surfaces for Tribological Applications

PubMed Central

Kirner, Sabrina V.; Griepentrog, Michael; Spaltmann, Dirk

2018-01-01

Laser texturing is an emerging technology for generating surface functionalities on basis of optical, mechanical, or chemical properties. Taking benefit of laser sources with ultrashort (fs) pulse durations features outstanding precision of machining and negligible rims or burrs surrounding the laser-irradiation zone. Consequently, additional mechanical or chemical post-processing steps are usually not required for fs-laser surface texturing (fs-LST). This work aimed to provide a bridge between research in the field of tribology and laser materials processing. The paper reviews the current state-of-the-art in fs-LST, with a focus on the tribological performance (friction and wear) of specific self-organized surface structures (so-called ripples, grooves, and spikes) on steel and titanium alloys. On the titanium alloy, specific sickle-shaped hybrid micro-nanostructures were also observed and tribologically tested. Care is taken to identify accompanying effects affecting the materials hardness, superficial oxidation, nano- and microscale topographies, and the role of additives contained in lubricants, such as commercial engine oil. PMID:29762544

Femtosecond Laser Texturing of Surfaces for Tribological Applications.

PubMed

Bonse, Jörn; Kirner, Sabrina V; Griepentrog, Michael; Spaltmann, Dirk; Krüger, Jörg

2018-05-15

Laser texturing is an emerging technology for generating surface functionalities on basis of optical, mechanical, or chemical properties. Taking benefit of laser sources with ultrashort (fs) pulse durations features outstanding precision of machining and negligible rims or burrs surrounding the laser-irradiation zone. Consequently, additional mechanical or chemical post-processing steps are usually not required for fs-laser surface texturing (fs-LST). This work aimed to provide a bridge between research in the field of tribology and laser materials processing. The paper reviews the current state-of-the-art in fs-LST, with a focus on the tribological performance (friction and wear) of specific self-organized surface structures (so-called ripples, grooves, and spikes) on steel and titanium alloys. On the titanium alloy, specific sickle-shaped hybrid micro-nanostructures were also observed and tribologically tested. Care is taken to identify accompanying effects affecting the materials hardness, superficial oxidation, nano- and microscale topographies, and the role of additives contained in lubricants, such as commercial engine oil.

Smectic C liquid crystal growth through surface orientation by ZnxCd1-xSe thin films

NASA Astrophysics Data System (ADS)

Katranchev, B.; Petrov, M.; Bineva, I.; Levi, Z.; Mineva, M.

2012-12-01

A smectic C liquid crystal (LC) texture, consisting of distinct local single crystals (DLSCs) was grown using predefined orientation of ternary nanocrystalline thin films of ZnxCd1-xSe. The surface morphology and orientation features of the ZnxCd1-xSe films were investigated by AFM measurements and micro-texture polarization analysis. The ZnxCd1-xSe surface causes a substantial enlargement of the smectic C DLSCs and induction of a surface bistable state. The specific character of the morphology of this coating leads to the decrease of the corresponding anchoring energy. Two new chiral states, not typical for this LC were indicated. The physical mechanism providing these new effects is presented.

Feature recognition and detection for ancient architecture based on machine vision

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Wood texture classification by fuzzy neural networks

NASA Astrophysics Data System (ADS)

Gonzaga, Adilson; de Franca, Celso A.; Frere, Annie F.

1999-03-01

The majority of scientific papers focusing on wood classification for pencil manufacturing take into account defects and visual appearance. Traditional methodologies are base don texture analysis by co-occurrence matrix, by image modeling, or by tonal measures over the plate surface. In this work, we propose to classify plates of wood without biological defects like insect holes, nodes, and cracks, by analyzing their texture. By this methodology we divide the plate image in several rectangular windows or local areas and reduce the number of gray levels. From each local area, we compute the histogram of difference sand extract texture features, given them as input to a Local Neuro-Fuzzy Network. Those features are from the histogram of differences instead of the image pixels due to their better performance and illumination independence. Among several features like media, contrast, second moment, entropy, and IDN, the last three ones have showed better results for network training. Each LNN output is taken as input to a Partial Neuro-Fuzzy Network (PNFN) classifying a pencil region on the plate. At last, the outputs from the PNFN are taken as input to a Global Fuzzy Logic doing the plate classification. Each pencil classification within the plate is done taking into account each quality index.

Direct femtosecond laser surface structuring of crystalline silicon at 400 nm

NASA Astrophysics Data System (ADS)

Nivas, Jijil JJ; Anoop, K. K.; Bruzzese, Riccardo; Philip, Reji; Amoruso, Salvatore

2018-03-01

We have analyzed the effects of the laser pulse wavelength (400 nm) on femtosecond laser surface structuring of silicon. The features of the produced surface structures are investigated as a function of the number of pulses, N, and compared with the surface textures produced by more standard near-infrared (800 nm) laser pulses at a similar level of excitation. Our experimental findings highlight the importance of the light wavelength for the formation of the supra-wavelength grooves, and, for a large number of pulses (N ≈ 1000), the generation of other periodic structures (stripes) at 400 nm, which are not observed at 800 nm. These results provide interesting information on the generation of various surface textures, addressing the effect of the laser pulse wavelength on the generation of grooves and stripes.

Appearance and characterization of fruit image textures for quality sorting using wavelet transform and genetic algorithms.

PubMed

Khoje, Suchitra

2018-02-01

Images of four qualities of mangoes and guavas are evaluated for color and textural features to characterize and classify them, and to model the fruit appearance grading. The paper discusses three approaches to identify most discriminating texture features of both the fruits. In the first approach, fruit's color and texture features are selected using Mahalanobis distance. A total of 20 color features and 40 textural features are extracted for analysis. Using Mahalanobis distance and feature intercorrelation analyses, one best color feature (mean of a* [L*a*b* color space]) and two textural features (energy a*, contrast of H*) are selected as features for Guava while two best color features (R std, H std) and one textural features (energy b*) are selected as features for mangoes with the highest discriminate power. The second approach studies some common wavelet families for searching the best classification model for fruit quality grading. The wavelet features extracted from five basic mother wavelets (db, bior, rbior, Coif, Sym) are explored to characterize fruits texture appearance. In third approach, genetic algorithm is used to select only those color and wavelet texture features that are relevant to the separation of the class, from a large universe of features. The study shows that image color and texture features which were identified using a genetic algorithm can distinguish between various qualities classes of fruits. The experimental results showed that support vector machine classifier is elected for Guava grading with an accuracy of 97.61% and artificial neural network is elected from Mango grading with an accuracy of 95.65%. The proposed method is nondestructive fruit quality assessment method. The experimental results has proven that Genetic algorithm along with wavelet textures feature has potential to discriminate fruit quality. Finally, it can be concluded that discussed method is an accurate, reliable, and objective tool to determine fruit quality namely Mango and Guava, and might be applicable to in-line sorting systems. © 2017 Wiley Periodicals, Inc.

Mapping soil features from multispectral scanner data

NASA Technical Reports Server (NTRS)

Kristof, S. J.; Zachary, A. L.

1974-01-01

In being able to identify quickly gross variations in soil features, the computer-aided classification of multispectral scanner data can be an effective aid to soil surveying. Variations in soil tone are easily seen as well as variations in features related to soil tone, e.g., drainage patterns and organic matter content. Changes in surface texture also affect the reflectance properties of soils. Inasmuch as conventional soil classes are based on both surface and subsurface soil characteristics, the technique described here can be expected only to augment and not replace traditional soil mapping.

Visual texture perception via graph-based semi-supervised learning

NASA Astrophysics Data System (ADS)

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.

Correlations Between Textures and Infrared Spectra of the Martian Surface in Valles Marineris

NASA Astrophysics Data System (ADS)

Ralston, S. J.; Wray, J. J.

2013-12-01

RALSTON, S. J., School of Earth and Atmospheric Sciences, Georgia Institute of Technology, 311 Ferst Drive, Atlanta, GA 30332, sralston3@gatech.edu, WRAY, James, School of Earth and Atmospheric Sciences, Georgia Institute of Technology, 311 Ferst Drive, Atlanta, GA 30332, jwray@eas.gatech.edu In the past few decades, a wealth of information has become available on the appearance and composition of the Martian surface. While some previous research has examined possible correlations between certain surface features and mineralogy (such as the hypothesized connection between Recurring Slope Lineae and perchlorate salts), little has yet been done to determine possible correlations between mineralogy and texture in less extraordinary circumstances. In this project, one hundred images taken from across the Valles Marineris region were examined both in infrared (obtained from the CRISM instrument aboard the Mars Reconnaissance Orbiter) and in visible-light images from the HiRISE camera. Spectra were obtained from regions of interest, focusing mainly on the identification of monohydrated and polyhydrated sulfates. Other materials were included in the imaging, including phyllosilicate clays, gypsum, and jarosite, although those materials proved less abundant than the sulfates. The areas from which the spectra were taken were then examined in visible-light wavelengths using HiRISE images to determine textural qualities. The focus of this research was on two particular textures, a 'reticulated' texture and a 'stepped texture,' hypothesized to correlate to monohydrated and polyhydrated sulfates, respectively. Results showed that over 55% of areas containing monohydrated sulfates also contained reticulate texture, whereas areas that contained other materials, such as polyhydrated sulfates and clays, had only a 2-8% correlation with reticulate texture. The stepped texture was shown to have no significant correlation to any one material, although other texture/mineral pairs did show some correlation. This presentation will cover the range of textures and mineralogy found throughout Valles Marineris.

Conveying the 3D Shape of Transparent Surfaces Via Texture

NASA Technical Reports Server (NTRS)

Interrante, Victoria; Fuchs, Henry; Pizer, Stephen

1997-01-01

Transparency can be a useful device for depicting multiple overlapping surfaces in a single image. The challenge is to render the transparent surfaces in such a way that their three-dimensional shape can be readily understood and their depth distance from underlying structures clearly perceived. This paper describes our investigations into the use of sparsely-distributed discrete, opaque texture as an 'artistic device' for more explicitly indicating the relative depth of a transparent surface and for communicating the essential features of its 3D shape in an intuitively meaningful and minimally occluding way. The driving application for this work is the visualization of layered surfaces in radiation therapy treatment planning data, and the technique is illustrated on transparent isointensity surfaces of radiation dose. We describe the perceptual motivation and artistic inspiration for defining a stroke texture that is locally oriented in the direction of greatest normal curvature (and in which individual strokes are of a length proportional to the magnitude of the curvature in the direction they indicate), and discuss several alternative methods for applying this texture to isointensity surfaces defined in a volume. We propose an experimental paradigm for objectively measuring observers' ability to judge the shape and depth of a layered transparent surface, in the course of a task relevant to the needs of radiotherapy treatment planning, and use this paradigm to evaluate the practical effectiveness of our approach through a controlled observer experiment based on images generated from actual clinical data.

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

DOE PAGES

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

2017-01-01

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

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

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

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

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

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

NASA Astrophysics Data System (ADS)

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

2017-11-01

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

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

PubMed

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.

Detection of sub-kilometer craters in high resolution planetary images using shape and texture features

NASA Astrophysics Data System (ADS)

Bandeira, Lourenço; Ding, Wei; Stepinski, Tomasz F.

2012-01-01

Counting craters is a paramount tool of planetary analysis because it provides relative dating of planetary surfaces. Dating surfaces with high spatial resolution requires counting a very large number of small, sub-kilometer size craters. Exhaustive manual surveys of such craters over extensive regions are impractical, sparking interest in designing crater detection algorithms (CDAs). As a part of our effort to design a CDA, which is robust and practical for planetary research analysis, we propose a crater detection approach that utilizes both shape and texture features to identify efficiently sub-kilometer craters in high resolution panchromatic images. First, a mathematical morphology-based shape analysis is used to identify regions in an image that may contain craters; only those regions - crater candidates - are the subject of further processing. Second, image texture features in combination with the boosting ensemble supervised learning algorithm are used to accurately classify previously identified candidates into craters and non-craters. The design of the proposed CDA is described and its performance is evaluated using a high resolution image of Mars for which sub-kilometer craters have been manually identified. The overall detection rate of the proposed CDA is 81%, the branching factor is 0.14, and the overall quality factor is 72%. This performance is a significant improvement over the previous CDA based exclusively on the shape features. The combination of performance level and computational efficiency offered by this CDA makes it attractive for practical application.

Image segmentation using association rule features.

PubMed

Rushing, John A; Ranganath, Heggere; Hinke, Thomas H; Graves, Sara J

2002-01-01

A new type of texture feature based on association rules is described. Association rules have been used in applications such as market basket analysis to capture relationships present among items in large data sets. It is shown that association rules can be adapted to capture frequently occurring local structures in images. The frequency of occurrence of these structures can be used to characterize texture. Methods for segmentation of textured images based on association rule features are described. Simulation results using images consisting of man made and natural textures show that association rule features perform well compared to other widely used texture features. Association rule features are used to detect cumulus cloud fields in GOES satellite images and are found to achieve higher accuracy than other statistical texture features for this problem.

Investigation of KDP crystal surface based on an improved bidimensional empirical mode decomposition method

NASA Astrophysics Data System (ADS)

Lu, Lei; Yan, Jihong; Chen, Wanqun; An, Shi

2018-03-01

This paper proposed a novel spatial frequency analysis method for the investigation of potassium dihydrogen phosphate (KDP) crystal surface based on an improved bidimensional empirical mode decomposition (BEMD) method. Aiming to eliminate end effects of the BEMD method and improve the intrinsic mode functions (IMFs) for the efficient identification of texture features, a denoising process was embedded in the sifting iteration of BEMD method. With removing redundant information in decomposed sub-components of KDP crystal surface, middle spatial frequencies of the cutting and feeding processes were identified. Comparative study with the power spectral density method, two-dimensional wavelet transform (2D-WT), as well as the traditional BEMD method, demonstrated that the method developed in this paper can efficiently extract texture features and reveal gradient development of KDP crystal surface. Furthermore, the proposed method was a self-adaptive data driven technique without prior knowledge, which overcame shortcomings of the 2D-WT model such as the parameters selection. Additionally, the proposed method was a promising tool for the application of online monitoring and optimal control of precision machining process.

Natural texture retrieval based on perceptual similarity measurement

NASA Astrophysics Data System (ADS)

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.

Multi Texture Analysis of Colorectal Cancer Continuum Using Multispectral Imagery

PubMed Central

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

2016-01-01

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

Real-time color-based texture analysis for sophisticated defect detection on wooden surfaces

NASA Astrophysics Data System (ADS)

Polzleitner, Wolfgang; Schwingshakl, Gert

2004-10-01

We describe a scanning system developed for the classification and grading of surfaces of wooden tiles. The system uses color imaging sensors to analyse the surfaces of either hard- or softwood material in terms of the texture formed by grain lines (orientation, spatial frequency, and color), various types of colorization, and other defects like knots, heart wood, cracks, holes, etc. The analysis requires two major tracks: the assignment of a tile to its texture class (like A, B, C, 1, 2, 3, Waste), and the detection of defects that decrease the commercial value of the tile (heart wood, knots, etc.). The system was initially developed under the international IMS program (Intelligent Manufacturing Systems) by an industry consortium. During the last two years it has been further developed, and several industrial systems have been installed, and are presently used in production of hardwood flooring. The methods implemented reflect some of the latest developments in the field of pattern recognition: genetic feature selection, two-dimensional second order statistics, special color space transforms, and classification by neural networks. In the industrial scenario we describe, many of the features defining a class cannot be described mathematically. Consequently a focus was the design of a learning architecture, where prototype texture samples are presented to the system, which then automatically finds the internal representation necessary for classification. The methods used in this approach have a wide applicability to problems of inspection, sorting, and optimization of high-value material typically used in the furniture, flooring, and related wood manufacturing industries.

A fast button surface defects detection method based on convolutional neural network

NASA Astrophysics Data System (ADS)

Liu, Lizhe; Cao, Danhua; Wu, Songlin; Wu, Yubin; Wei, Taoran

2018-01-01

Considering the complexity of the button surface texture and the variety of buttons and defects, we propose a fast visual method for button surface defect detection, based on convolutional neural network (CNN). CNN has the ability to extract the essential features by training, avoiding designing complex feature operators adapted to different kinds of buttons, textures and defects. Firstly, we obtain the normalized button region and then use HOG-SVM method to identify the front and back side of the button. Finally, a convolutional neural network is developed to recognize the defects. Aiming at detecting the subtle defects, we propose a network structure with multiple feature channels input. To deal with the defects of different scales, we take a strategy of multi-scale image block detection. The experimental results show that our method is valid for a variety of buttons and able to recognize all kinds of defects that have occurred, including dent, crack, stain, hole, wrong paint and uneven. The detection rate exceeds 96%, which is much better than traditional methods based on SVM and methods based on template match. Our method can reach the speed of 5 fps on DSP based smart camera with 600 MHz frequency.

Multi-Scale Fractal Analysis of Image Texture and Pattern

NASA Technical Reports Server (NTRS)

Emerson, Charles W.

1998-01-01

Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely independent of scale. Self-similarity is defined as a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. An ideal fractal (or monofractal) curve or surface has a constant dimension over all scales, although it may not be an integer value. This is in contrast to Euclidean or topological dimensions, where discrete one, two, and three dimensions describe curves, planes, and volumes. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution. However, most geographical phenomena are not strictly self-similar at all scales, but they can often be modeled by a stochastic fractal in which the scaling and self-similarity properties of the fractal have inexact patterns that can be described by statistics. Stochastic fractal sets relax the monofractal self-similarity assumption and measure many scales and resolutions in order to represent the varying form of a phenomenon as a function of local variables across space. In image interpretation, pattern is defined as the overall spatial form of related features, and the repetition of certain forms is a characteristic pattern found in many cultural objects and some natural features. Texture is the visual impression of coarseness or smoothness caused by the variability or uniformity of image tone or color. A potential use of fractals concerns the analysis of image texture. In these situations it is commonly observed that the degree of roughness or inexactness in an image or surface is a function of scale and not of experimental technique. The fractal dimension of remote sensing data could yield quantitative insight on the spatial complexity and information content contained within these data. A software package known as the Image Characterization and Modeling System (ICAMS) was used to explore how fractal dimension is related to surface texture and pattern. The ICAMS software was verified using simulated images of ideal fractal surfaces with specified dimensions. The fractal dimension for areas of homogeneous land cover in the vicinity of Huntsville, Alabama was measured to investigate the relationship between texture and resolution for different land covers.

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

PubMed

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

2017-04-01

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

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

PubMed

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

2016-05-15

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

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

PubMed

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.

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

PubMed

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

2014-02-01

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

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

NASA Astrophysics Data System (ADS)

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.

Multi-fractal texture features for brain tumor and edema segmentation

NASA Astrophysics Data System (ADS)

Reza, S.; Iftekharuddin, K. M.

2014-03-01

In this work, we propose a fully automatic brain tumor and edema segmentation technique in brain magnetic resonance (MR) images. Different brain tissues are characterized using the novel texture features such as piece-wise triangular prism surface area (PTPSA), multi-fractional Brownian motion (mBm) and Gabor-like textons, along with regular intensity and intensity difference features. Classical Random Forest (RF) classifier is used to formulate the segmentation task as classification of these features in multi-modal MRIs. The segmentation performance is compared with other state-of-art works using a publicly available dataset known as Brain Tumor Segmentation (BRATS) 2012 [1]. Quantitative evaluation is done using the online evaluation tool from Kitware/MIDAS website [2]. The results show that our segmentation performance is more consistent and, on the average, outperforms other state-of-the art works in both training and challenge cases in the BRATS competition.

Segmentation of Polarimetric SAR Images Usig Wavelet Transformation and Texture Features

NASA Astrophysics Data System (ADS)

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.

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

PubMed

Liu, Jianli; Lughofer, Edwin; Zeng, Xianyi

2015-01-01

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

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

PubMed

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

2018-04-01

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

Cutaneous texture discrimination following transection of the dorsal spinal column in monkeys.

PubMed

Vierck, C J; Cooper, B Y

1998-01-01

Transection of the dorsal spinal column in monkeys has been shown to impair discrimination of the frequency or duration of repetitive tactile stimulation, without recovery over extended periods of postoperative testing. These deficits would be likely to prevent discrimination between textures presented passively and in sequence, if repetitive temporal sequences were distinguishing features of the textures. However, previous investigations of texture discrimination after dorsal column section did not obtain a deficit on tests involving active palpation of sandpaper surfaces. In the present study, rows of raised dots were stroked across the glabrous skin of one foot so that temporal entrainment of neural activity would constitute a prominent cue. The rows were oriented mediolaterally, and the textures moved proximodistally across the skin surface (varying the spacing between the rows). Four monkeys were trained to release a lever when the rougher of two textures was in contact with the skin, and the rough texture was preceded by one to three passes of a smooth texture. Stable levels of preoperative performance ranged from 78.6 to 85.7% correct responses. After interruption of the ipsilateral dorsal column, each monkey was impaired over at least 2 months of testing. One animal did not show evidence of recovery; two recovered partially from the initial deficit; and one returned to preoperative levels of performance after extensive retraining. These results are interpreted in terms of aberrant inhibitory influences which result from repetitive stimulation after a dorsal column lesion.

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

PubMed

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

2018-05-14

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

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

PubMed

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 < 0.05) with both GS and median ADC. Contrast correlated moderately with median ADC. The 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.

A System for Drawing Synthetic Images of Forested Landscapes

Treesearch

Timothy P. McDonald

1997-01-01

A software package for drawing images of forested landscapes was developed. Programs included in the system convert topographic and stand polygon information output from a GIS into a form that can be read by a general-purpose ray-tracing renderer. Other programs generate definitions for surface features, mainly trees but ground surface textural properties as well. The...

Textural features for radar image analysis

NASA Technical Reports Server (NTRS)

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

1981-01-01

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

Fast Image Texture Classification Using Decision Trees

NASA Technical Reports Server (NTRS)

Thompson, David R.

2011-01-01

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

Analyzing and improving surface texture by dual-rotation magnetorheological finishing

NASA Astrophysics Data System (ADS)

Wang, Yuyue; Zhang, Yun; Feng, Zhijing

2016-01-01

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

Automated Texture Classification of the Mawrth Vallis Landing Site Region

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

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

PubMed

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

2018-04-01

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

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

NASA Technical Reports Server (NTRS)

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

1974-01-01

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

Fractal analysis of seafloor textures for target detection in synthetic aperture sonar imagery

NASA Astrophysics Data System (ADS)

Nabelek, T.; Keller, J.; Galusha, A.; Zare, A.

2018-04-01

Fractal analysis of an image is a mathematical approach to generate surface related features from an image or image tile that can be applied to image segmentation and to object recognition. In undersea target countermeasures, the targets of interest can appear as anomalies in a variety of contexts, visually different textures on the seafloor. In this paper, we evaluate the use of fractal dimension as a primary feature and related characteristics as secondary features to be extracted from synthetic aperture sonar (SAS) imagery for the purpose of target detection. We develop three separate methods for computing fractal dimension. Tiles with targets are compared to others from the same background textures without targets. The different fractal dimension feature methods are tested with respect to how well they can be used to detect targets vs. false alarms within the same contexts. These features are evaluated for utility using a set of image tiles extracted from a SAS data set generated by the U.S. Navy in conjunction with the Office of Naval Research. We find that all three methods perform well in the classification task, with a fractional Brownian motion model performing the best among the individual methods. We also find that the secondary features are just as useful, if not more so, in classifying false alarms vs. targets. The best classification accuracy overall, in our experimentation, is found when the features from all three methods are combined into a single feature vector.

Novel chromatin texture features for the classification of pap smears

NASA Astrophysics Data System (ADS)

Bejnordi, Babak E.; Moshavegh, Ramin; Sujathan, K.; Malm, Patrik; Bengtsson, Ewert; Mehnert, Andrew

2013-03-01

This paper presents a set of novel structural texture features for quantifying nuclear chromatin patterns in cells on a conventional Pap smear. The features are derived from an initial segmentation of the chromatin into bloblike texture primitives. The results of a comprehensive feature selection experiment, including the set of proposed structural texture features and a range of different cytology features drawn from the literature, show that two of the four top ranking features are structural texture features. They also show that a combination of structural and conventional features yields a classification performance of 0.954±0.019 (AUC±SE) for the discrimination of normal (NILM) and abnormal (LSIL and HSIL) slides. The results of a second classification experiment, using only normal-appearing cells from both normal and abnormal slides, demonstrates that a single structural texture feature measuring chromatin margination yields a classification performance of 0.815±0.019. Overall the results demonstrate the efficacy of the proposed structural approach and that it is possible to detect malignancy associated changes (MACs) in Papanicoloau stain.

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

PubMed Central

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

2009-01-01

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

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

NASA Astrophysics Data System (ADS)

Addonizio, M. L.; Fusco, L.; Antonaia, A.; Cominale, F.; Usatii, I.

2015-12-01

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 (σrms ∼ 150 nm) was obtained on glass etched 2 min showing cauliflower-like structure, whereas a softer texture (σrms ∼ 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 length. This surface morphology promoted a large light scattering phenomenon, as evidenced by haze value and by angular resolved scattering (ARS) behaviour, into a large range of diffraction angles, giving high probability of effective light trapping inside a PV device.

Realization of Quasi‐Omnidirectional Solar Cells with Superior Electrical Performance by All‐Solution‐Processed Si Nanopyramids

PubMed Central

Zhong, Sihua; Wang, Wenjie; Tan, Miao; Zhuang, Yufeng

2017-01-01

Abstract Large‐scale (156 mm × 156 mm) quasi‐omnidirectional solar cells are successfully realized and featured by keeping high cell performance over broad incident angles (θ), via employing Si nanopyramids (SiNPs) as surface texture. SiNPs are produced by the proposed metal‐assisted alkaline etching method, which is an all‐solution‐processed method and highly simple together with cost‐effective. Interestingly, compared to the conventional Si micropyramids (SiMPs)‐textured solar cells, the SiNPs‐textured solar cells possess lower carrier recombination and thus superior electrical performances, showing notable distinctions from other Si nanostructures‐textured solar cells. Furthermore, SiNPs‐textured solar cells have very little drop of quantum efficiency with increasing θ, demonstrating the quasi‐omnidirectional characteristic. As an overall result, both the SiNPs‐textured homojunction and heterojunction solar cells possess higher daily electric energy production with a maximum relative enhancement approaching 2.5%, when compared to their SiMPs‐textured counterparts. The quasi‐omnidirectional solar cell opens a new opportunity for photovoltaics to produce more electric energy with a low cost. PMID:29201616

Realization of Quasi-Omnidirectional Solar Cells with Superior Electrical Performance by All-Solution-Processed Si Nanopyramids.

PubMed

Zhong, Sihua; Wang, Wenjie; Tan, Miao; Zhuang, Yufeng; Shen, Wenzhong

2017-11-01

Large-scale (156 mm × 156 mm) quasi-omnidirectional solar cells are successfully realized and featured by keeping high cell performance over broad incident angles (θ), via employing Si nanopyramids (SiNPs) as surface texture. SiNPs are produced by the proposed metal-assisted alkaline etching method, which is an all-solution-processed method and highly simple together with cost-effective. Interestingly, compared to the conventional Si micropyramids (SiMPs)-textured solar cells, the SiNPs-textured solar cells possess lower carrier recombination and thus superior electrical performances, showing notable distinctions from other Si nanostructures-textured solar cells. Furthermore, SiNPs-textured solar cells have very little drop of quantum efficiency with increasing θ, demonstrating the quasi-omnidirectional characteristic. As an overall result, both the SiNPs-textured homojunction and heterojunction solar cells possess higher daily electric energy production with a maximum relative enhancement approaching 2.5%, when compared to their SiMPs-textured counterparts. The quasi-omnidirectional solar cell opens a new opportunity for photovoltaics to produce more electric energy with a low cost.

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

PubMed

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

2018-04-01

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

Influence of Surface Texture and Roughness of Softer and Harder Counter Materials on Friction During Sliding

NASA Astrophysics Data System (ADS)

Menezes, Pradeep L.; Kishore; Kailas, Satish V.; Lovell, Michael R.

2015-01-01

Surface texture influences friction during sliding contact conditions. In the present investigation, the effect of surface texture and roughness of softer and harder counter materials on friction during sliding was analyzed using an inclined scratch testing system. In the experiments, two test configurations, namely (a) steel balls against aluminum alloy flats of different surface textures and (b) aluminum alloy pins against steel flats of different surface textures, are utilized. The surface textures were classified into unidirectionally ground, 8-ground, and randomly polished. For a given texture, the roughness of the flat surfaces was varied using grinding or polishing methods. Optical profilometer and scanning electron microscope were used to characterize the contact surfaces before and after the experiments. Experimental results showed that the surface textures of both harder and softer materials are important in controlling the frictional behavior. The softer material surface textures showed larger variations in friction between ground and polished surfaces. However, the harder material surface textures demonstrated a better control over friction among the ground surfaces. Although the effect of roughness on friction was less significant when compared to textures, the harder material roughness showed better correlations when compared to the softer material roughness.

Texture analysis improves level set segmentation of the anterior abdominal wall

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

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

2013-12-15

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

General Method for the Synthesis of Hollow Mesoporous Carbon Spheres with Tunable Textural Properties.

PubMed

Mezzavilla, Stefano; Baldizzone, Claudio; Mayrhofer, Karl J J; Schüth, Ferdi

2015-06-17

A versatile synthetic procedure to prepare hollow mesoporous carbon spheres (HMCS) is presented here. This approach is based on the deposition of a homogeneous hybrid polymer/silica composite shell on the outer surface of silica spheres through the surfactant-assisted simultaneous polycondensation of silica and polymer precursors in a colloidal suspension. Such composite materials can be further processed to give hollow mesoporous carbon spheres. The flexibility of this method allows for independent control of the morphological (i.e., core diameter and shell thickness) and textural features of the carbon spheres. In particular, it is demonstrated that the size of the pores within the mesoporous shell can be precisely tailored over an extended range (2-20 nm) by simply adjusting the reaction conditions. In a similar fashion, also the specific carbon surface area as well as the total shell porosity can be tuned. Most importantly, the textural features can be adjusted without affecting the dimension or the morphology of the spheres. The possibility to directly modify the shell textural properties by varying the synthetic parameters in a scalable process represents a distinct asset over the multistep hard-templating (nanocasting) routes. As an exemplary application, Pt nanoparticles were encapsulated in the mesoporous shell of HMCS. The resulting Pt@HMCS catalyst showed an enhanced stability during the oxygen reduction reaction, one of the most important reactions in electrocatalysis. This new synthetic procedure could allow the expansion, perhaps even beyond the lab-scale, of advanced carbon nanostructured supports for applications in catalysis.

The Effects of Grain Size and Texture on Dynamic Abnormal Grain Growth in Mo

NASA Astrophysics Data System (ADS)

Noell, Philip J.; Taleff, Eric M.

2016-10-01

This is the first report of abnormal grain morphologies specific to a Mo sheet material produced from a commercial-purity arc-melted ingot. Abnormal grains initiated and grew during plastic deformation of this material at temperatures of 1793 K and 1813 K (1520 °C and 1540 °C). This abnormal grain growth during high-temperature plastic deformation is termed dynamic abnormal grain growth, DAGG. DAGG in this material readily consumes nearly all grains near the sheet center while leaving many grains near the sheet surface unconsumed. Crystallographic texture, grain size, and other microstructural features are characterized. After recrystallization, a significant through-thickness variation in crystallographic texture exists in this material but does not appear to directly influence DAGG propagation. Instead, dynamic normal grain growth, which may be influenced by texture, preferentially occurs near the sheet surface prior to DAGG. The large grains thus produced near the sheet surface inhibit the subsequent growth of the abnormal grains produced by DAGG, which preferentially consume the finer grains near the sheet center. This produces abnormal grains that span the sheet center but leave unconsumed polycrystalline microstructure near the sheet surface. Abnormal grains are preferentially oriented with the < 110rangle approximately along the tensile axis. These results provide additional new evidence that boundary curvature is the primary driving force for DAGG in Mo.

A parametric texture model based on deep convolutional features closely matches texture appearance for humans.

PubMed

Wallis, Thomas S A; Funke, Christina M; Ecker, Alexander S; Gatys, Leon A; Wichmann, Felix A; Bethge, Matthias

2017-10-01

Our visual environment is full of texture-"stuff" like cloth, bark, or gravel as distinct from "things" like dresses, trees, or paths-and humans are adept at perceiving subtle variations in material properties. To investigate image features important for texture perception, we psychophysically compare a recent parametric model of texture appearance (convolutional neural network [CNN] model) that uses the features encoded by a deep CNN (VGG-19) with two other models: the venerable Portilla and Simoncelli model and an extension of the CNN model in which the power spectrum is additionally matched. Observers discriminated model-generated textures from original natural textures in a spatial three-alternative oddity paradigm under two viewing conditions: when test patches were briefly presented to the near-periphery ("parafoveal") and when observers were able to make eye movements to all three patches ("inspection"). Under parafoveal viewing, observers were unable to discriminate 10 of 12 original images from CNN model images, and remarkably, the simpler Portilla and Simoncelli model performed slightly better than the CNN model (11 textures). Under foveal inspection, matching CNN features captured appearance substantially better than the Portilla and Simoncelli model (nine compared to four textures), and including the power spectrum improved appearance matching for two of the three remaining textures. None of the models we test here could produce indiscriminable images for one of the 12 textures under the inspection condition. While deep CNN (VGG-19) features can often be used to synthesize textures that humans cannot discriminate from natural textures, there is currently no uniformly best model for all textures and viewing conditions.

Computer-aided diagnosis of melanoma using border and wavelet-based texture analysis.

PubMed

Garnavi, Rahil; Aldeen, Mohammad; Bailey, James

2012-11-01

This paper presents a novel computer-aided diagnosis system for melanoma. The novelty lies in the optimised selection and integration of features derived from textural, borderbased and geometrical properties of the melanoma lesion. The texture features are derived from using wavelet-decomposition, the border features are derived from constructing a boundaryseries model of the lesion border and analysing it in spatial and frequency domains, and the geometry features are derived from shape indexes. The optimised selection of features is achieved by using the Gain-Ratio method, which is shown to be computationally efficient for melanoma diagnosis application. Classification is done through the use of four classifiers; namely, Support Vector Machine, Random Forest, Logistic Model Tree and Hidden Naive Bayes. The proposed diagnostic system is applied on a set of 289 dermoscopy images (114 malignant, 175 benign) partitioned into train, validation and test image sets. The system achieves and accuracy of 91.26% and AUC value of 0.937, when 23 features are used. Other important findings include (i) the clear advantage gained in complementing texture with border and geometry features, compared to using texture information only, and (ii) higher contribution of texture features than border-based features in the optimised feature set.

Shell anomalies observed in a population of Archaias angulatus (Foraminifera) from the Florida Keys (USA) sampled in 1982-83 and 2006-07

USGS Publications Warehouse

Souder, H.C.; McCloskey, B.; Hallock, P.; Byrne, R.

2010-01-01

Archived specimens of Archaias angulatus collected live at a depth of < 2. m in John Pennekamp Coral Reef State Park, Key Largo, Florida, in June, September and December 1982, and March 1983, were compared to specimens collected live from the same site and months in 2006-07. Shells were examined using light microscopy for anomalous features, which were then documented using scanning electron microscopy. Seven different types of morphological abnormalities and five different surface texture anomalies were observed. Physical abnormalities included profoundly deformed, curled, asymmetrical, and uncoiled shells, irregular suture lines, surface protrusions, and breakage/repair. Textural anomalies observed were surface pits, dissolution features, microborings, microbial biofilms, and the presence of epibionts including bryzoans, cyanobacteria and foraminifers. The same kinds of features were found in this A. angulatus population in both 1982-83 collections and 2006-07 collections. Within-date variability was higher in specimens collected in 1982-83, while between-date variability was higher in 2006-07; overall the range of variability was similar. Given that the site was originally chosen for study because these foraminifers were so abundant, the lack of significant change indicates that the variability of the geochemical habitat is still within the range that A. angulatus can thrive. ?? 2010.

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2018-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-05-01

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

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

PubMed

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

2007-11-29

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

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

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

Nawrocki, J; Chino, J; Das, S

Purpose: This study examines the effect on texture analysis due to variable reconstruction of PET images in the context of an adaptive FDG PET protocol for node positive gynecologic cancer patients. By measuring variability in texture features from baseline and intra-treatment PET-CT, we can isolate unreliable texture features due to large variation. Methods: A subset of seven patients with node positive gynecological cancers visible on PET was selected for this study. Prescribed dose varied between 45–50.4Gy, with a 55–70Gy boost to the PET positive nodes. A baseline and intratreatment (between 30–36Gy) PET-CT were obtained on a Siemens Biograph mCT. Eachmore » clinical PET image set was reconstructed 6 times using a TrueX+TOF algorithm with varying iterations and Gaussian filter. Baseline and intra-treatment primary GTVs were segmented using PET Edge (MIM Software Inc., Cleveland, OH), a semi-automatic gradient-based algorithm, on the clinical PET and transferred to the other reconstructed sets. Using an in-house MATLAB program, four 3D texture matrices describing relationships between voxel intensities in the GTV were generated: co-occurrence, run length, size zone, and neighborhood difference. From these, 39 textural features characterizing texture were calculated in addition to SUV histogram features. The percent variability among parameters was first calculated. Each reconstructed texture feature from baseline and intra-treatment per patient was normalized to the clinical baseline scan and compared using the Wilcoxon signed-rank test in order to isolate variations due to reconstruction parameters. Results: For the baseline scans, 13 texture features showed a mean range greater than 10%. For the intra scans, 28 texture features showed a mean range greater than 10%. Comparing baseline to intra scans, 25 texture features showed p <0.05. Conclusion: Variability due to different reconstruction parameters increased with treatment, however, the majority of texture features showed significant changes during treatment independent of reconstruction effects.« less

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Automatic grading of appearance retention of carpets using intensity and range images

NASA Astrophysics Data System (ADS)

Orjuela Vargas, Sergio Alejandro; Ortiz-Jaramillo, Benhur; Vansteenkiste, Ewout; Rooms, Filip; De Meulemeester, Simon; de Keyser, Robain; Van Langenhove, Lieva; Philips, Wilfried

2012-04-01

Textiles are mainly used for decoration and protection. In both cases, their original appearance and its retention are important factors for customers. Therefore, evaluation of appearance parameters are critical for quality assurance purposes, during and after manufacturing, to determine the lifetime and/or beauty of textile products. In particular, appearance retention of textile products is commonly certified with grades, which are currently assigned by human experts. However, manufacturers would prefer a more objective system. We present an objective system for grading appearance retention, particularly, for textile floor coverings. Changes in appearance are quantified by using linear regression models on texture features extracted from intensity and range images. Range images are obtained by our own laser scanner, reconstructing the carpet surface using two methods that have been previously presented. We extract texture features using a variant of the local binary pattern technique based on detecting those patterns whose frequencies are related to the appearance retention grades. We test models for eight types of carpets. Results show that the proposed approach describes the degree of wear with a precision within the range allowed to human inspectors by international standards. The methodology followed in this experiment has been designed to be general for evaluating global deviation of texture in other types of textiles, as well as other surface materials.

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

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

Ma, C; Yin, Y

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 calculatedmore » 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.« less

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

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

Dissociations between Featural versus Conjunction-based Texture Processing in Infancy: Analyses of Three Potential Contributing Factors.

ERIC Educational Resources Information Center

Bertin, Evelin; Bhatt, Ramesh S.

2001-01-01

Examined three possible explanations for findings that infants detect textural discrepancies based on individual features more readily than on feature conjunctions. Found that none of the proposed factors could explain 5.5-month-olds' superior processing of featural over conjunction-based textural discrepancies. Findings suggest that in infancy,…

Detection of flood effects in montane streams based on fusion of 2D and 3D information from UAV imagery

NASA Astrophysics Data System (ADS)

Langhammer, Jakub; Vacková, Tereza

2017-04-01

In the contribution, we are presenting a novel method, enabling objective detection and classification of the alluvial features resulting from flooding, based on the imagery, acquired by the unmanned aerial vehicles (UAVs, drones). We have proposed and tested a workflow, using two key data products of the UAV photogrammetry - the 2D orthoimage and 3D digital elevation model, together with derived information on surface texture for the consequent classification of erosional and depositional features resulting from the flood. The workflow combines the photogrammetric analysis of the UAV imagery, texture analysis of the DEM, and the supervised image classification. Application of the texture analysis and use of DEM data is aimed to enhance 2D information, resulting from the high-resolution orthoimage by adding the newly derived bands, which enhance potential for detection and classification of key types of fluvial features in the stream and the floodplain. The method was tested on the example of a snowmelt-driven flood in a montane stream in Sumava Mts., Czech Republic, Central Europe, that occurred in December 2015. Using the UAV platform DJI Inspire 1 equipped with the RGB camera there was acquired imagery covering a 1 km long stretch of a meandering creek with elevated fluvial dynamics. Agisoft Photoscan Pro was used to derive a point cloud and further the high-resolution seamless orthoimage and DEM, Orfeo toolkit and SAGA GIS tools were used for DEM analysis. From the UAV-based data inputs, a multi-band dataset was derived as a source for the consequent classification of fluvial landforms. The RGB channels of the derived orthoimage were completed by the selected texture feature layers and the information on 3D properties of the riverscape - the normalized DEM and terrain ruggedness. Haralick features, derived from the RGB channels, are used for extracting information on the surface texture, the terrain ruggedness index is used as a measure of local topographical variability. Based on this dataset, the supervised classification was performed to identify the fluvial features, including the fresh and old accumulations of different size, fresh bank erosion, in-stream features and the riparian zone vegetation, verified later by the field survey. The classification based on the fusion of high-resolution 2D and 3D data, derived from UAV imagery, enabled to identify and quantify the extent of recent and old accumulations, to distinguish the coarse and fine sediments or to separate the shallow and deep zones in the submerged zone of the channel. With the high operability of the data acquisition process, the proposed method appears to be a promising tool for rapid mapping and classification of flood effects in streams and floodplains.

Texture segmentation by genetic programming.

PubMed

Song, Andy; Ciesielski, Vic

2008-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

Mammographic phenotypes of breast cancer risk driven by breast anatomy

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

Electrical manipulation of dynamic magnetic impurity and spin texture of helical Dirac fermions

NASA Astrophysics Data System (ADS)

Wang, Rui-Qiang; Zhong, Min; Zheng, Shi-Han; Yang, Mou; Wang, Guang-Hui

2016-05-01

We have theoretically investigated the spin inelastic scattering of helical electrons off a high-spin nanomagnet absorbed on a topological surface. The nanomagnet is treated as a dynamic quantum spin and driven by the spin transfer torque effect. We proposed a mechanism to electrically manipulate the spin texture of helical Dirac fermions rather than by an external magnetic field. By tuning the bias voltage and the direction of impurity magnetization, we present rich patterns of spin texture, from which important fingerprints exclusively associated with the spin helical feature are obtained. Furthermore, it is found that the nonmagnetic potential can create the resonance state in the spin density with different physics as the previously reported resonance of charge density.

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

NASA Technical Reports Server (NTRS)

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

2001-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Windy Mars: A Dynamic Planet as Seen by the HiRISE Camera

NASA Technical Reports Server (NTRS)

Bridges, N. T.; Geissler, P. E.; McEwen, A. S.; Thomson, B. J.; Chuang, F. C.; Herkenhoff, K. E.; Keszthelyi, L. P.; Martnez-Alonso, S.

2007-01-01

With a dynamic atmosphere and a large supply of particulate material, the surface of Mars is heavily influenced by wind-driven, or aeolian, processes. The High Resolution Imaging Science Experiment (HiRISE) camera on the Mars Reconnaissance Orbiter (MRO) provides a new view of Martian geology, with the ability to see decimeter-size features. Current sand movement, and evidence for recent bedform development, is observed. Dunes and ripples generally exhibit complex surfaces down to the limits of resolution. Yardangs have diverse textures, with some being massive at HiRISE scale, others having horizontal and cross-cutting layers of variable character, and some exhibiting blocky and polygonal morphologies. 'Reticulate' (fine polygonal texture) bedforms are ubiquitous in the thick mantle at the highest elevations.

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

NASA Technical Reports Server (NTRS)

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

1973-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-09-01

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

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

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

Lee, S; Markel, D; Hegyi, G

2016-06-15

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

Analysis of Texture Using the Fractal Model

NASA Technical Reports Server (NTRS)

Navas, William; Espinosa, Ramon Vasquez

1997-01-01

Properties such as the fractal dimension (FD) can be used for feature extraction and classification of regions within an image. The FD measures the degree of roughness of a surface, so this number is used to characterize a particular region, in order to differentiate it from another. There are two basic approaches discussed in the literature to measure FD: the blanket method, and the box counting method. Both attempt to measure FD by estimating the change in surface area with respect to the change in resolution. We tested both methods but box counting resulted computationally faster and gave better results. Differential Box Counting (DBC) was used to segment a collage containing three textures. The FD is independent of directionality and brightness so five features were used derived from the original image to account for directionality and gray level biases. FD can not be measured on a point, so we use a window that slides across the image giving values of FD to the pixel on the center of the window. Windowing blurs the boundaries of adjacent classes, so an edge-preserving, feature-smoothing algorithm is used to improve classification within segments and to make the boundaries sharper. Segmentation using DBC was 90.8910 accurate.

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

PubMed

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

2010-01-01

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

Novel high-resolution computed tomography-based radiomic classifier for screen-identified pulmonary nodules in the National Lung Screening Trial.

PubMed

Peikert, Tobias; Duan, Fenghai; Rajagopalan, Srinivasan; Karwoski, Ronald A; Clay, Ryan; Robb, Richard A; Qin, Ziling; Sicks, JoRean; Bartholmai, Brian J; Maldonado, Fabien

2018-01-01

Optimization of the clinical management of screen-detected lung nodules is needed to avoid unnecessary diagnostic interventions. Herein we demonstrate the potential value of a novel radiomics-based approach for the classification of screen-detected indeterminate nodules. Independent quantitative variables assessing various radiologic nodule features such as sphericity, flatness, elongation, spiculation, lobulation and curvature were developed from the NLST dataset using 726 indeterminate nodules (all ≥ 7 mm, benign, n = 318 and malignant, n = 408). Multivariate analysis was performed using least absolute shrinkage and selection operator (LASSO) method for variable selection and regularization in order to enhance the prediction accuracy and interpretability of the multivariate model. The bootstrapping method was then applied for the internal validation and the optimism-corrected AUC was reported for the final model. Eight of the originally considered 57 quantitative radiologic features were selected by LASSO multivariate modeling. These 8 features include variables capturing Location: vertical location (Offset carina centroid z), Size: volume estimate (Minimum enclosing brick), Shape: flatness, Density: texture analysis (Score Indicative of Lesion/Lung Aggression/Abnormality (SILA) texture), and surface characteristics: surface complexity (Maximum shape index and Average shape index), and estimates of surface curvature (Average positive mean curvature and Minimum mean curvature), all with P<0.01. The optimism-corrected AUC for these 8 features is 0.939. Our novel radiomic LDCT-based approach for indeterminate screen-detected nodule characterization appears extremely promising however independent external validation is needed.

The Importance of Chaos and Lenticulae on Europa for the JIMO Mission

NASA Technical Reports Server (NTRS)

Spaun, Nicole A.

2003-01-01

The Galileo Solid State Imaging (SSI) experiment provided high-resolution images of Europa's surface allowing identification of surface features barely distinguishable at Voyager's resolution. SSI revealed the visible pitting on Europa's surface to be due to large disrupted features, chaos, and smaller sub-circular patches, lenticulae. Chaos features contain a hummocky matrix material and commonly contain dislocated blocks of ridged plains. Lenticulae are morphologically interrelated and can be divided into three classes: domes, spots, and micro-chaos. Domes are broad, upwarped features that generally do not disrupt the texture of the ridged plains. Spots are areas of low albedo that are generally smooth in texture compared to other units. Micro-chaos are disrupted features with a hummocky matrix material, resembling that observed within chaos regions. Chaos and lenticulae are ubiquitous in the SSI regional map observations, which average approximately 200 meters per pixel (m/pxl) in resolution, and appear in several of the ultra-high resolution, i.e., better than 50 m/pxl, images of Europa as well. SSI also provided a number of multi-spectral observations of chaos and lenticulae. Using this dataset we have undertaken a thorough study of the morphology, size, spacing, stratigraphy, and color of chaos and lenticulae to determine their properties and evaluate models of their formation. Geological mapping indicates that chaos and micro-chaos have a similar internal morphology of in-situ degradation suggesting that a similar process was operating during their formation. The size distribution denotes a dominant size of 4-8 km in diameter for features containing hummocky material (i.e., chaos and micro-chaos). Results indicate a dominant spacing of 15 - 36 km apart. Chaos and lenticulae are generally among the youngest features stratigraphically observed on the surface, suggesting a recent change in resurfacing style. Also, the reddish non-icy materials on Europa's surface have high concentrations in many chaos and lenticulae features. Nonetheless, a complete global map of the distribution of chaos and lenticulae is not possible with the SSI dataset. Only <20% of the surface has been imaged at 200 m/pxl or better resolution, mostly of the near-equatorial regions. Color and ultra-high-res images have much less surface coverage. Thus we suggest that full global imaging of Europa at 200 m/pxl or better resolution, preferably in multi-spectral wavelengths, should be a high priority for the JIMO mission.

Contact-free palm-vein recognition based on local invariant features.

PubMed

Kang, Wenxiong; Liu, Yang; Wu, Qiuxia; Yue, Xishun

2014-01-01

Contact-free palm-vein recognition is one of the most challenging and promising areas in hand biometrics. In view of the existing problems in contact-free palm-vein imaging, including projection transformation, uneven illumination and difficulty in extracting exact ROIs, this paper presents a novel recognition approach for contact-free palm-vein recognition that performs feature extraction and matching on all vein textures distributed over the palm surface, including finger veins and palm veins, to minimize the loss of feature information. First, a hierarchical enhancement algorithm, which combines a DOG filter and histogram equalization, is adopted to alleviate uneven illumination and to highlight vein textures. Second, RootSIFT, a more stable local invariant feature extraction method in comparison to SIFT, is adopted to overcome the projection transformation in contact-free mode. Subsequently, a novel hierarchical mismatching removal algorithm based on neighborhood searching and LBP histograms is adopted to improve the accuracy of feature matching. Finally, we rigorously evaluated the proposed approach using two different databases and obtained 0.996% and 3.112% Equal Error Rates (EERs), respectively, which demonstrate the effectiveness of the proposed approach.

Contact-Free Palm-Vein Recognition Based on Local Invariant Features

PubMed Central

Kang, Wenxiong; Liu, Yang; Wu, Qiuxia; Yue, Xishun

2014-01-01

Contact-free palm-vein recognition is one of the most challenging and promising areas in hand biometrics. In view of the existing problems in contact-free palm-vein imaging, including projection transformation, uneven illumination and difficulty in extracting exact ROIs, this paper presents a novel recognition approach for contact-free palm-vein recognition that performs feature extraction and matching on all vein textures distributed over the palm surface, including finger veins and palm veins, to minimize the loss of feature information. First, a hierarchical enhancement algorithm, which combines a DOG filter and histogram equalization, is adopted to alleviate uneven illumination and to highlight vein textures. Second, RootSIFT, a more stable local invariant feature extraction method in comparison to SIFT, is adopted to overcome the projection transformation in contact-free mode. Subsequently, a novel hierarchical mismatching removal algorithm based on neighborhood searching and LBP histograms is adopted to improve the accuracy of feature matching. Finally, we rigorously evaluated the proposed approach using two different databases and obtained 0.996% and 3.112% Equal Error Rates (EERs), respectively, which demonstrate the effectiveness of the proposed approach. PMID:24866176

Space Object Classification Using Fused Features of Time Series Data

NASA Astrophysics Data System (ADS)

Jia, B.; Pham, K. D.; Blasch, E.; Shen, D.; Wang, Z.; Chen, G.

In this paper, a fused feature vector consisting of raw time series and texture feature information is proposed for space object classification. The time series data includes historical orbit trajectories and asteroid light curves. The texture feature is derived from recurrence plots using Gabor filters for both unsupervised learning and supervised learning algorithms. The simulation results show that the classification algorithms using the fused feature vector achieve better performance than those using raw time series or texture features only.

Depth image enhancement using perceptual texture priors

NASA Astrophysics Data System (ADS)

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.

Inline inspection of textured plastics surfaces

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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.

Textural signatures for wetland vegetation

NASA Technical Reports Server (NTRS)

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

1973-01-01

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

Combination of Functional Nanoengineering and Nanosecond Laser Texturing for Design of Superhydrophobic Aluminum Alloy with Exceptional Mechanical and Chemical Properties.

PubMed

Boinovich, Ludmila B; Modin, Evgeny B; Sayfutdinova, Adeliya R; Emelyanenko, Kirill A; Vasiliev, Alexander L; Emelyanenko, Alexandre M

2017-10-24

Industrial application of metallic materials is hindered by several shortcomings, such as proneness to corrosion, erosion under abrasive loads, damage due to poor cold resistance, or weak resistance to thermal shock stresses, etc. In this study, using the aluminum-magnesium alloy as an example of widely spread metallic materials, we show that a combination of functional nanoengineering and nanosecond laser texturing with the appropriate treatment regimes can be successfully used to transform a metal into a superhydrophobic material with exceptional mechanical and chemical properties. It is demonstrated that laser chemical processing of the surface may be simultaneously used to impart multimodal roughness and to modify the composition and physicochemical properties of a thick surface layer of the substrate itself. Such integration of topographical and physicochemical modification leads to specific surface nanostructures such as nanocavities filled with hydrophobic agent and hard oxynitride nanoinclusions. The combination of superhydrophobic state, nano- and micro features of the hierarchical surface, and the appropriate composition of the surface textured layer allowed us to provide the surface with the outstanding level of resistance of superhydrophobic coatings to external chemical and mechanical impacts. In particular, experimental data presented in this study indicate high resistance of the fabricated coatings to pitting corrosion, superheated water vapor, sand abrasive wear, and rapid temperature cycling from liquid nitrogen to room temperatures, without notable degradation of superhydrophobic performance.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Ion beam texturing

NASA Technical Reports Server (NTRS)

Hudson, W. R.

1976-01-01

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

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

PubMed

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

2015-11-01

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

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

PubMed

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

2011-06-01

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

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization.

PubMed

Molina, David; Pérez-Beteta, Julián; Martínez-González, Alicia; Martino, Juan; Velasquez, Carlos; Arana, Estanislao; Pérez-García, Víctor M

2017-01-01

Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images.

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

PubMed Central

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

2015-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-03-01

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

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

PubMed

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

2015-04-01

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

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

PubMed

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

2015-07-01

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

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

PubMed

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

2017-06-22

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

Adhesive behavior of micro/nano-textured surfaces

NASA Astrophysics Data System (ADS)

Zhang, Yuyan; Wang, Xiaoli; Li, Hanqing; Wang, Ben

2015-02-01

A numerical model of the adhesive contact between a rigid smooth sphere and an elastic textured surface based on the Lennard-Jones interatomic potential law and the Hamaker summation method is established. Textures are considered by introducing the texture height distribution into the gap equation. Simulation results show that the pull-off force on textured surfaces decreases compared to that on smooth surfaces. Furthermore, effects of sphere-shaped textures on reducing adhesion are more obvious than cylinder-shaped or cube-shaped textures when the coverage area ratio, maximum height and interval of textures are fixed. For surfaces with sphere-shaped textures, variation trends of the mean pull-off force with texture density are not monotonous, and there exists a certain range of texture densities in which the mean pull-off force is small and its variation is insignificant. In addition, the pull-off force depends also on the maximum height and radius of textures. On one hand, if the texture radius is fixed, larger maximum height results in smaller pull-off force, and if the maximum height is fixed, the pull-off force tends to increase almost linearly with increases in texture radius. On the other hand, if the height-diameter ratio of textures is fixed, the pull-off force reaches a minimum at an optimum texture radius or maximum height.

Biological influences on modern sulfates: Textures and composition of gypsum deposits from Guerrero Negro, Baja California Sur, Mexico

NASA Astrophysics Data System (ADS)

Vogel, Marilyn B.; Des Marais, David J.; Parenteau, Mary N.; Jahnke, Linda L.; Turk, Kendra A.; Kubo, Michael D. Y.

2010-01-01

Gypsum (CaSO 4·2H 2O) deposits from a range of sedimentary environments at Guerrero Negro, Baja California Sur, Mexico were investigated for microscale texture and composition in order to differentiate features formed under substantial microbial influence from those for which microbial effects were relatively minor or absent. Gypsum deposits were classified according to their sedimentary environment, textures, crystal habit, brine composition and other geochemical factors. The environments studied included subaqueous sediments in anchialine pools and in solar salterns, as well as subsurface sediments of mudflats and saltpans. Gypsum that developed in the apparent absence of biofilms included crystals precipitated in the water column and subsedimentary discs that precipitated from phreatic brines. Subsedimentary gypsum developed in sabkha environments exhibited a sinuous microtexture and poikilitically enclosed detrital particles. Water column precipitates had euhedral prismatic habits and extensive penetrative twinning. Gypsum deposits influenced by biofilms included bottom nucleated crusts and gypsolites developing in anchialine pools and saltern ponds. Gypsum precipitating within benthic biofilms, and in biofilms within subaerial sediment surfaces provided compelling evidence of biological influences on crystal textures and habits. This evidence included irregular, high relief surface textures, accessory minerals (S°, Ca-carbonate, Sr/Ca-sulfate and Mg-hydroxide) and distinctive crystal habits such as equant forms and crystals having distorted prism faces.

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

Variations in algorithm implementation among quantitative texture analysis software packages

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Documentation of procedures for textural/spatial pattern recognition techniques

NASA Technical Reports Server (NTRS)

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

1976-01-01

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

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

USGS Publications Warehouse

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

1993-01-01

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

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Windy Mars: A dynamic planet as seen by the HiRISE camera

USGS Publications Warehouse

Bridges, N.T.; Geissler, P.E.; McEwen, A.S.; Thomson, B.J.; Chuang, F.C.; Herkenhoff, K. E.; Keszthelyi, L.P.; Martinez-Alonso, S.

2007-01-01

With a dynamic atmosphere and a large supply of particulate material, the surface of Mars is heavily influenced by wind-driven, or aeolian, processes. The High Resolution Imaging Science Experiment (HiRISE) camera on the Mars Reconnaissance Orbiter (MRO) provides a new view of Martian geology, with the ability to see decimeter-size features. Current sand movement, and evidence for recent bedform development, is observed. Dunes and ripples generally exhibit complex surfaces down to the limits of resolution. Yardangs have diverse textures, with some being massive at HiRISE scale, others having horizontal and cross-cutting layers of variable character, and some exhibiting blocky and polygonal morphologies. "Reticulate" (fine polygonal texture) bedforms are ubiquitus in the thick mantle at the highest elevations. Copyright 2007 by the American Geophysical Union.

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

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

Zhong, H; Wang, J; Shen, L

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

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

Deep-learning derived features for lung nodule classification with limited datasets

NASA Astrophysics Data System (ADS)

Thammasorn, P.; Wu, W.; Pierce, L. A.; Pipavath, S. N.; Lampe, P. D.; Houghton, A. M.; Haynor, D. R.; Chaovalitwongse, W. A.; Kinahan, P. E.

2018-02-01

Only a few percent of indeterminate nodules found in lung CT images are cancer. However, enabling earlier diagnosis is important to avoid invasive procedures or long-time surveillance to those benign nodules. We are evaluating a classification framework using radiomics features derived with a machine learning approach from a small data set of indeterminate CT lung nodule images. We used a retrospective analysis of 194 cases with pulmonary nodules in the CT images with or without contrast enhancement from lung cancer screening clinics. The nodules were contoured by a radiologist and texture features of the lesion were calculated. In addition, sematic features describing shape were categorized. We also explored a Multiband network, a feature derivation path that uses a modified convolutional neural network (CNN) with a Triplet Network. This was trained to create discriminative feature representations useful for variable-sized nodule classification. The diagnostic accuracy was evaluated for multiple machine learning algorithms using texture, shape, and CNN features. In the CT contrast-enhanced group, the texture or semantic shape features yielded an overall diagnostic accuracy of 80%. Use of a standard deep learning network in the framework for feature derivation yielded features that substantially underperformed compared to texture and/or semantic features. However, the proposed Multiband approach of feature derivation produced results similar in diagnostic accuracy to the texture and semantic features. While the Multiband feature derivation approach did not outperform the texture and/or semantic features, its equivalent performance indicates promise for future improvements to increase diagnostic accuracy. Importantly, the Multiband approach adapts readily to different size lesions without interpolation, and performed well with relatively small amount of training data.

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

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

Apte, Aditya P.; Deasy, Joseph O.

2016-06-15

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

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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

PubMed

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1973-01-01

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

Lack of robustness of textural measures obtained from 3D brain tumor MRIs impose a need for standardization

PubMed Central

Pérez-Beteta, Julián; Martínez-González, Alicia; Martino, Juan; Velasquez, Carlos; Arana, Estanislao; Pérez-García, Víctor M.

2017-01-01

Purpose Textural measures have been widely explored as imaging biomarkers in cancer. However, their robustness under dynamic range and spatial resolution changes in brain 3D magnetic resonance images (MRI) has not been assessed. The aim of this work was to study potential variations of textural measures due to changes in MRI protocols. Materials and methods Twenty patients harboring glioblastoma with pretreatment 3D T1-weighted MRIs were included in the study. Four different spatial resolution combinations and three dynamic ranges were studied for each patient. Sixteen three-dimensional textural heterogeneity measures were computed for each patient and configuration including co-occurrence matrices (CM) features and run-length matrices (RLM) features. The coefficient of variation was used to assess the robustness of the measures in two series of experiments corresponding to (i) changing the dynamic range and (ii) changing the matrix size. Results No textural measures were robust under dynamic range changes. Entropy was the only textural feature robust under spatial resolution changes (coefficient of variation under 10% in all cases). Conclusion Textural measures of three-dimensional brain tumor images are not robust neither under dynamic range nor under matrix size changes. Standards should be harmonized to use textural features as imaging biomarkers in radiomic-based studies. The implications of this work go beyond the specific tumor type studied here and pose the need for standardization in textural feature calculation of oncological images. PMID:28586353

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

PubMed

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.

The analysis of image feature robustness using cometcloud

PubMed Central

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

2012-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-08-01

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

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

PubMed

Pieniazek, Facundo; Messina, Valeria

2016-11-01

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

Fast detection of vascular plaque in optical coherence tomography images using a reduced feature set

NASA Astrophysics Data System (ADS)

Prakash, Ammu; Ocana Macias, Mariano; Hewko, Mark; Sowa, Michael; Sherif, Sherif

2018-03-01

Optical coherence tomography (OCT) images are capable of detecting vascular plaque by using the full set of 26 Haralick textural features and a standard K-means clustering algorithm. However, the use of the full set of 26 textural features is computationally expensive and may not be feasible for real time implementation. In this work, we identified a reduced set of 3 textural feature which characterizes vascular plaque and used a generalized Fuzzy C-means clustering algorithm. Our work involves three steps: 1) the reduction of a full set 26 textural feature to a reduced set of 3 textural features by using genetic algorithm (GA) optimization method 2) the implementation of an unsupervised generalized clustering algorithm (Fuzzy C-means) on the reduced feature space, and 3) the validation of our results using histology and actual photographic images of vascular plaque. Our results show an excellent match with histology and actual photographic images of vascular tissue. Therefore, our results could provide an efficient pre-clinical tool for the detection of vascular plaque in real time OCT imaging.

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

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

Fried, David V.; Graduate School of Biomedical Sciences, The University of Texas Health Science Center at Houston, Houston, Texas; Tucker, Susan L.

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 wasmore » 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 78.8% (±3.9% SD) classification reproducibility in terms of OS, LRC, and FFDM, respectively. Conclusions: Pretreatment tumor texture may provide prognostic information beyond that obtained from CPFs. Models incorporating feature reproducibility achieved classification rates of ∼80%. External validation would be required to establish texture as a prognostic factor.« less

Perceiving Object Shape from Specular Highlight Deformation, Boundary Contour Deformation, and Active Haptic Manipulation.

PubMed

Norman, J Farley; Phillips, Flip; Cheeseman, Jacob R; Thomason, Kelsey E; Ronning, Cecilia; Behari, Kriti; Kleinman, Kayla; Calloway, Autum B; Lamirande, Davora

2016-01-01

It is well known that motion facilitates the visual perception of solid object shape, particularly when surface texture or other identifiable features (e.g., corners) are present. Conventional models of structure-from-motion require the presence of texture or identifiable object features in order to recover 3-D structure. Is the facilitation in 3-D shape perception similar in magnitude when surface texture is absent? On any given trial in the current experiments, participants were presented with a single randomly-selected solid object (bell pepper or randomly-shaped "glaven") for 12 seconds and were required to indicate which of 12 (for bell peppers) or 8 (for glavens) simultaneously visible objects possessed the same shape. The initial single object's shape was defined either by boundary contours alone (i.e., presented as a silhouette), specular highlights alone, specular highlights combined with boundary contours, or texture. In addition, there was a haptic condition: in this condition, the participants haptically explored with both hands (but could not see) the initial single object for 12 seconds; they then performed the same shape-matching task used in the visual conditions. For both the visual and haptic conditions, motion (rotation in depth or active object manipulation) was present in half of the trials and was not present for the remaining trials. The effect of motion was quantitatively similar for all of the visual and haptic conditions-e.g., the participants' performance in Experiment 1 was 93.5 percent higher in the motion or active haptic manipulation conditions (when compared to the static conditions). The current results demonstrate that deforming specular highlights or boundary contours facilitate 3-D shape perception as much as the motion of objects that possess texture. The current results also indicate that the improvement with motion that occurs for haptics is similar in magnitude to that which occurs for vision.

Perceiving Object Shape from Specular Highlight Deformation, Boundary Contour Deformation, and Active Haptic Manipulation

PubMed Central

Cheeseman, Jacob R.; Thomason, Kelsey E.; Ronning, Cecilia; Behari, Kriti; Kleinman, Kayla; Calloway, Autum B.; Lamirande, Davora

2016-01-01

It is well known that motion facilitates the visual perception of solid object shape, particularly when surface texture or other identifiable features (e.g., corners) are present. Conventional models of structure-from-motion require the presence of texture or identifiable object features in order to recover 3-D structure. Is the facilitation in 3-D shape perception similar in magnitude when surface texture is absent? On any given trial in the current experiments, participants were presented with a single randomly-selected solid object (bell pepper or randomly-shaped “glaven”) for 12 seconds and were required to indicate which of 12 (for bell peppers) or 8 (for glavens) simultaneously visible objects possessed the same shape. The initial single object’s shape was defined either by boundary contours alone (i.e., presented as a silhouette), specular highlights alone, specular highlights combined with boundary contours, or texture. In addition, there was a haptic condition: in this condition, the participants haptically explored with both hands (but could not see) the initial single object for 12 seconds; they then performed the same shape-matching task used in the visual conditions. For both the visual and haptic conditions, motion (rotation in depth or active object manipulation) was present in half of the trials and was not present for the remaining trials. The effect of motion was quantitatively similar for all of the visual and haptic conditions–e.g., the participants’ performance in Experiment 1 was 93.5 percent higher in the motion or active haptic manipulation conditions (when compared to the static conditions). The current results demonstrate that deforming specular highlights or boundary contours facilitate 3-D shape perception as much as the motion of objects that possess texture. The current results also indicate that the improvement with motion that occurs for haptics is similar in magnitude to that which occurs for vision. PMID:26863531

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

NASA Astrophysics Data System (ADS)

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.

Functional surfaces for tribological applications: inspiration and design

NASA Astrophysics Data System (ADS)

Abdel-Aal, Hisham A.

2016-12-01

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

SERS Engineering Collaboration

DTIC Science & Technology

2012-06-01

laser beam. In the second approach, a pulsed laser was used to texture a silicon wafer to form sharp features. Silver was evaporated onto the wafer...orders of magnitude larger than that measured on a gold nanoparticle array on a glass substrate. The largest SERS enhancement for a silver device was...surface plasmons," Yizhuo Chu and Kenneth B. Crozier, Optics Letters vol. 34, 244 (2009) K3. "Gold nanorings as substrates for surface-enhanced Raman

A Fourier-based textural feature extraction procedure

NASA Technical Reports Server (NTRS)

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

1986-01-01

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

The adsorption of pharmaceutically active compounds from aqueous solutions onto activated carbons.

PubMed

Rakić, Vesna; Rac, Vladislav; Krmar, Marija; Otman, Otman; Auroux, Aline

2015-01-23

In this study, the adsorption of pharmaceutically active compounds - salicylic acid, acetylsalicylic acid, atenolol and diclofenac-Na onto activated carbons has been studied. Three different commercial activated carbons, possessing ∼650, 900 or 1500m(2)g(-1) surface areas were used as solid adsorbents. These materials were fully characterized - their textural, surface features and points of zero charge have been determined. The adsorption was studied from aqueous solutions at 303K using batch adsorption experiments and titration microcalorimetry, which was employed in order to obtain the heats evolved as a result of adsorption. The maximal adsorption capacities of investigated solids for all target pharmaceuticals are in the range of 10(-4)molg(-1). The obtained maximal retention capacities are correlated with the textural properties of applied activated carbon. The roles of acid/base features of activated carbons and of molecular structures of adsorbate molecules have been discussed. The obtained results enabled to estimate the possibility to use the activated carbons in the removal of pharmaceuticals by adsorption. Copyright © 2014 Elsevier B.V. All rights reserved.

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

PubMed

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.

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

PubMed

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

2017-07-01

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

Deformational Features and Microstructure Evolution of Copper Fabricated by a Single Pass of the Elliptical Cross-Section Spiral Equal-Channel Extrusion (ECSEE) Process

NASA Astrophysics Data System (ADS)

Wang, Chengpeng; Li, Fuguo; Liu, Juncheng

2018-04-01

The objectives of this work are to study the deformational feature, textures, microstructures, and dislocation configurations of ultrafine-grained copper processed by the process of elliptical cross-section spiral equal-channel extrusion (ECSEE). The deformation patterns of simple shear and pure shear in the ECSEE process were evaluated with the analytical method of geometric strain. The influence of the main technical parameters of ECSEE die on the effective strain distribution on the surface of ECSEE-fabricated samples was examined by the finite element simulation. The high friction factor could improve the effective strain accumulation of material deformation. Moreover, the pure copper sample fabricated by ECSEE ion shows a strong rotated cube shear texture. The refining mechanism of the dislocation deformation is dominant in copper processed by a single pass of ECSEE. The inhomogeneity of the micro-hardness distribution on the longitudinal section of the ECSEE-fabricated sample is consistent with the strain and microstructure distribution features.

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

NASA Astrophysics Data System (ADS)

An, Jubai; Zhu, Lisong

2006-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1993-01-01

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

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

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

Cui, Y; Pollom, E; Loo, B

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

Characterization and origin of spongillite-hosting sediment from João Pinheiro, Minas Gerais, Brazil

NASA Astrophysics Data System (ADS)

Almeida, A. C. S.; Varajão, A. F. D. C.; Gomes, N. S.; Varajão, C. A. C.; Volkmer-Ribeiro, C.

2010-03-01

Spongillite from João Pinheiro, Minas Gerais, Brazil is mainly known for its use in brick production and in the refractory industry. Very few studies have focused on its geological context. Spongillite-rich deposits occur in shallow ponds on a karstic planation surface developed on rocks of the Neoproterozoic São Francisco Supergroup. Cenozoic siliciclastic sediments are related to this surface. A field study of these deposits and analysis of multispectral images showed a SE-NW preferential drainage system at SE, suggesting that Mesozoic Areado Group sandstones were the source area of the spongillite-hosting sediments. Mineralogical and textural characterization by optical microscopic analysis, X-ray diffraction (XRD), differential and gravimetric thermal analysis (DTA-GTA), infrared spectroscopy (IR) and scanning electron microscopy (SEM) of seven open-pit spongillite-rich deposits (Avião, Carvoeiro, Vânio, Preguiça, Divisa, Severino, Feijão) showed a sedimentological similarity between the deposits. They are lens-shaped and are characterized at the bottom by sand facies, in the middle by spicules-rich muddy-sand facies and at the top by organic matter-rich muddy-sand facies. Petrographically, the spongillite-hosting sediments and the siliclastic sediments of the Areado Group show detrital phases with similar mineralogical and textural features, such as the presence of well-sorted quartz grains and surface features of abrasion typical of aeolian reworking that occurred in the depositional environment in which the sandstones of the Areado Group were formed. Detrital heavy minerals, such as staurolite, zircon, tourmaline, and clay minerals, such as kaolinite, low amounts of illite, scarce chlorite and mixed-layer chlorite/smectite and illite/smectite occur in the spongillite-hosting sediments and in sandstones from the Areado Group. In both formations, staurolite has similar chemical composition. These mineralogical and textural features show that the sediments of the Areado Group constitute the main source of the pond sediments that host spongillite.

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

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Automatic extraction of tree crowns from aerial imagery in urban environment

NASA Astrophysics Data System (ADS)

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

2006-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-03-01

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

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

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

Xie, Y; Wang, J; Wang, C

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

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

NASA Astrophysics Data System (ADS)

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

2012-06-01

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

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

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

Mahon, R; Weiss, E; Karki, K

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 themore » 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 in specific applications such as tissue classification and changes during radiation therapy utilizing a standard imaging protocol. Authors have the following disclosures: a research agreement with Philips Medical systems (Hugo, Weiss), a license agreement with Varian Medical Systems (Hugo, Weiss), research grants from the National Institute of Health (Hugo, Weiss), UpToDate royalties (Weiss), and none(Mahon, Ford, Karki). Authors have no potential conflicts of interest to disclose.« less

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

PubMed

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

2015-01-01

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

Powder-in-tube and thick-film methods of fabricating high temperature superconductors having enhanced biaxial texture

DOEpatents

Goyal, Amit; Kroeger, Donald M.

2003-11-11

A method for forming an electronically active biaxially textured article includes the steps of providing a substrate having a single crystal metal or metal alloy surface, deforming the substrate to form an elongated substrate surface having biaxial texture and depositing an epitaxial electronically active layer on the biaxially textured surface. The method can include at least one annealing step after the deforming step to produce the biaxially textured substrate surface. The invention can be used to form improved biaxially textured articles, such as superconducting wire and tape articles having improved J.sub.c values.

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

NASA Astrophysics Data System (ADS)

Eldosouky, Ahmed M.; Elkhateeb, Sayed O.

2018-06-01

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

Behavior of severely supercooled water drops impacting on superhydrophobic surfaces

NASA Astrophysics Data System (ADS)

Maitra, Tanmoy; Antonini, Carlo; Tiwari, Manish K.; Mularczyk, Adrian; Imeri, Zulkufli; Schoch, Philippe; Poulikakos, Dimos

2014-11-01

Surface icing, commonplace in nature and technology, has broad implications to daily life. To prevent surface icing, superhydrophobic surfaces/coatings with rationally controlled roughness features (both at micro and nano-scale) are considered to be a promising candidate. However, to fabricate/synthesize a high performance icephobic surface or coating, understanding the dynamic interaction between water and the surface during water drop impact in supercooled state is necessary. In this work, we investigate the water/substrate interaction using drop impact experiments down to -17°C. It is found that the resulting increased viscous effect of water at low temperature significantly affects all stages of drop dynamics such as maximum spreading, contact time and meniscus penetration into the superhydrophobic texture. Most interestingly, the viscous effect on the meniscus penetration into roughness feature leads to clear change in the velocity threshold for rebounding to sticking transition by 25% of supercooled drops. Swiss National Science Foundation (SNF) Grant 200021_135479.

Freezing effect on bread appearance evaluated by digital imaging

NASA Astrophysics Data System (ADS)

Zayas, Inna Y.

1999-01-01

In marketing channels, bread is sometimes delivered in a frozen sate for distribution. Changes occur in physical dimensions, crumb grain and appearance of slices. Ten loaves, twelve bread slices per loaf were scanned for digital image analysis and then frozen in a commercial refrigerator. The bread slices were stored for four weeks scanned again, permitted to thaw and scanned a third time. Image features were extracted, to determine shape, size and image texture of the slices. Different thresholds of grey levels were set to detect changes that occurred in crumb, images were binarized at these settings. The number of pixels falling into these gray level settings were determined for each slice. Image texture features of subimages of each slice were calculated to quantify slice crumb grain. The image features of the slice size showed shrinking of bread slices, as a results of freezing and storage, although shape of slices did not change markedly. Visible crumb texture changes occurred and these changes were depicted by changes in image texture features. Image texture features showed that slice crumb changed differently at the center of a slice compared to a peripheral area close to the crust. Image texture and slice features were sufficient for discrimination of slices before and after freezing and after thawing.

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

NASA Technical Reports Server (NTRS)

Weigand, A. J.

1978-01-01

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

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

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

Nawrocki, J; Chino, J; Craciunescu, O

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

Image ratio features for facial expression recognition application.

PubMed

Song, Mingli; Tao, Dacheng; Liu, Zicheng; Li, Xuelong; Zhou, Mengchu

2010-06-01

Video-based facial expression recognition is a challenging problem in computer vision and human-computer interaction. To target this problem, texture features have been extracted and widely used, because they can capture image intensity changes raised by skin deformation. However, existing texture features encounter problems with albedo and lighting variations. To solve both problems, we propose a new texture feature called image ratio features. Compared with previously proposed texture features, e.g., high gradient component features, image ratio features are more robust to albedo and lighting variations. In addition, to further improve facial expression recognition accuracy based on image ratio features, we combine image ratio features with facial animation parameters (FAPs), which describe the geometric motions of facial feature points. The performance evaluation is based on the Carnegie Mellon University Cohn-Kanade database, our own database, and the Japanese Female Facial Expression database. Experimental results show that the proposed image ratio feature is more robust to albedo and lighting variations, and the combination of image ratio features and FAPs outperforms each feature alone. In addition, we study asymmetric facial expressions based on our own facial expression database and demonstrate the superior performance of our combined expression recognition system.

Classification of interstitial lung disease patterns with topological texture features

NASA Astrophysics Data System (ADS)

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.

Cloud field classification based on textural features

NASA Technical Reports Server (NTRS)

Sengupta, Sailes Kumar

1989-01-01

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

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

PubMed

Wang, Kun-Ching

2015-01-14

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

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

PubMed Central

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

2017-01-01

Rationale 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. Methods 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. Results 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). Principal Conclusions Clustering based on textural O-(2-[18F]fluoroethyl)-L-tyrosine PET features may provide valuable information in assessing the elusive phenomenon of pseudoprogression. PMID:28030820

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

PubMed

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

2018-04-01

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

Wall-based measurement features provides an improved IVUS coronary artery risk assessment when fused with plaque texture-based features during machine learning paradigm.

PubMed

Banchhor, Sumit K; Londhe, Narendra D; Araki, Tadashi; Saba, Luca; Radeva, Petia; Laird, John R; Suri, Jasjit S

2017-12-01

Planning of percutaneous interventional procedures involves a pre-screening and risk stratification of the coronary artery disease. Current screening tools use stand-alone plaque texture-based features and therefore lack the ability to stratify the risk. This IRB approved study presents a novel strategy for coronary artery disease risk stratification using an amalgamation of IVUS plaque texture-based and wall-based measurement features. Due to common genetic plaque makeup, carotid plaque burden was chosen as a gold standard for risk labels during training-phase of machine learning (ML) paradigm. Cross-validation protocol was adopted to compute the accuracy of the ML framework. A set of 59 plaque texture-based features was padded with six wall-based measurement features to show the improvement in stratification accuracy. The ML system was executed using principle component analysis-based framework for dimensionality reduction and uses support vector machine classifier for training and testing-phases. The ML system produced a stratification accuracy of 91.28%, demonstrating an improvement of 5.69% when wall-based measurement features were combined with plaque texture-based features. The fused system showed an improvement in mean sensitivity, specificity, positive predictive value, and area under the curve by: 6.39%, 4.59%, 3.31% and 5.48%, respectively when compared to the stand-alone system. While meeting the stability criteria of 5%, the ML system also showed a high average feature retaining power and mean reliability of 89.32% and 98.24%, respectively. The ML system showed an improvement in risk stratification accuracy when the wall-based measurement features were fused with the plaque texture-based features. Copyright © 2017 Elsevier Ltd. All rights reserved.

Surface texturing of fluoropolymers

NASA Technical Reports Server (NTRS)

Banks, B. A.; Mirtich, M. J.; Sovey, J. S. (Inventor)

1982-01-01

A method is disclosed for improving surface texture for adhesive bonding, metal bonding, substrate plating, decal substrate preparation, and biomedical implant applications. The surface to be bonded is dusted in a controlled fashion to produce a disbursed layer of fine mesh particles which serve as masks. The surface texture is produced by impinging gas ions on the masked surface. The textured surface takes the form of pillars or cones. The bonding material, such as a liquid epoxy, flows between the pillars which results in a bond having increased strength. For bonding metals a thin film of metal is vapor or sputter deposited onto the textured surface. Electroplating or electroless plating is then used to increase the metal thickness in the desired amount.

Generalizing roughness: experiments with flow-oriented roughness

NASA Astrophysics Data System (ADS)

Trevisani, Sebastiano

2015-04-01

Surface texture analysis applied to High Resolution Digital Terrain Models (HRDTMs) improves the capability to characterize fine-scale morphology and permits the derivation of useful morphometric indexes. An important indicator to be taken into account in surface texture analysis is surface roughness, which can have a discriminant role in the detection of different geomorphic processes and factors. The evaluation of surface roughness is generally performed considering it as an isotropic surface parameter (e.g., Cavalli, 2008; Grohmann, 2011). However, surface texture has often an anisotropic character, which means that surface roughness could change according to the considered direction. In some applications, for example involving surface flow processes, the anisotropy of roughness should be taken into account (e.g., Trevisani, 2012; Smith, 2014). Accordingly, we test the application of a flow-oriented directional measure of roughness, computed considering surface gravity-driven flow. For the calculation of flow-oriented roughness we use both classical variogram-based roughness (e.g., Herzfeld,1996; Atkinson, 2000) as well as an ad-hoc developed robust modification of variogram (i.e. MAD, Trevisani, 2014). The presented approach, based on a D8 algorithm, shows the potential impact of considering directionality in the calculation of roughness indexes. The use of flow-oriented roughness could improve the definition of effective proxies of impedance to flow. Preliminary results on the integration of directional roughness operators with morphometric-based models, are promising and can be extended to more complex approaches. Atkinson, P.M., Lewis, P., 2000. Geostatistical classification for remote sensing: an introduction. Computers & Geosciences 26, 361-371. Cavalli, M. & Marchi, L. 2008, "Characterization of the surface morphology of an alpine alluvial fan using airborne LiDAR", Natural Hazards and Earth System Science, vol. 8, no. 2, pp. 323-333. Grohmann, C.H., Smith, M.J., Riccomini, C., 2011. Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland. IEEE Transactions on Geoscience and Remote Sensing 49, 1220-1213. Herzfeld, U.C., Higginson, C.A., 1996. Automated geostatistical seafloor classification - Principles, parameters, feature vectors, and discrimination criteria. Computers and Geosciences, 22 (1), pp. 35-52. Smith, M.W. 2014, "Roughness in the Earth Sciences", Earth-Science Reviews, vol. 136, pp. 202-225. Trevisani, S., Cavalli, M. & Marchi, L. 2012, "Surface texture analysis of a high-resolution DTM: Interpreting an alpine basin", Geomorphology, vol. 161-162, pp. 26-39. Trevisani S., Rocca M., 2014. Geomorphometric analysis of fine-scale morphology for extensive areas: a new surface-texture operator. Geophysical Research Abstracts, Vol. 16, EGU2014-5612, 2014. EGU General Assembly 2014.

Microbially Mediated Glass Alteration in the Geological Record: Textural clues for Microbial Functions.

NASA Astrophysics Data System (ADS)

Staudigel, H.; Furnes, H.; McLoughlin, N.; Banerjee, N.

2007-12-01

Fe and Mn oxidizing microbes interact with their environment through the microbially mediated formation of Fe/Mn oxides and through the corrosion textures they may leave behind in the solids they colonize and from which they extract nutrients. Understanding the geo-biology of Fe and Mn oxidation may focus on the study of the microbes themselves, the mineral products, its biocorrosion features and the relationships between these types of observations. We have reviewed our own data on glass bio-corrosion and in particular the wider literature on microbial mineral tunneling to develop a two stage biocorrosion model for volcanic glass that offers feedback for our understanding of the mechanisms and the dynamics of microbial dissolution. Traces of microbially mediated dissolution of volcanic glass are commonly observed in volcanic glass found in submarine volcanoes on the seafloor, and in uplifted submarine volcanoes of almost any geological age back to the origin of life. Two main bioalteration textures care observed, granular and tubular. Based on a comparison of these features in particular with tunneling by ectomycorrhizal fungi, we propose two distinct types of biocorrosion that affects glass: (1) Granular alteration textures, made up of colonies of microbe-sized, near spherical mineral - filled cavities that form irregular clusters ranging to a tens of micron thick bands at the glas surfaces. These granular textures are interpreted as the result of microbial colonization. accompanied by dissolution of the glass in their contact surface, deposition of authigenic minerals and the formation of a biofilm, that eventually seals the glass from easy access by seawater for hydration, or from microbes accessing Fe (II) in the glass. (2) The most spectacular bioalteration feature, repesented by the formation of tubes cannot be easily formed by the former mechanism because near spherical, individual microbes are likely not to produce the directionality that is required to produce the near linear or sometimes coiled tubes. Instead, we envision the activity of hyphae-like organelles or filaments, that may radiate out from a host body located in direct contact with circulating water, possibly penetrating a biofilm and entering/drilling into the fresh glass. Such microdrilling is well described in soils, where hyphae can slowly drill into silicates, in a process that takes about 1000 years to become visible as tunnels.

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

PubMed

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

2010-10-01

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

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

PubMed Central

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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%.

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

PubMed

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

2016-11-02

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

Relation between plastic surface microtexturation and Ag film percolation and resistivity

NASA Astrophysics Data System (ADS)

Rapeaux, Michel; Tribut, Laurent

2017-09-01

Reinforced polycarbonate samples are textured by laser to get hydrophilic or hydrophobic surface. Then, Ag films are deposited on textured and non-textured samples by magnetron sputtering. In-situ resistivity measurement has been done to determine the electrical percolation threshold according to the texturation. Results are discussed and texturation is presented as one option to improve surface insulation in circuit breaker after a short-circuit event.

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

PubMed

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.

Pleistocene permafrost features in soils in the South-western Italian Alps

NASA Astrophysics Data System (ADS)

D'Amico, Michele; Catoni, Marcella; Bonifacio, Eleonora; Zanini, Ermanno

2015-04-01

Because of extensive Pleistocenic glaciations which erased most of the previously existing soils, slope steepness and climatic conditions favoring soil erosion, most soils observed on the Alps (and in other mid-latitude mountain ranges) developed only during the Holocene. However, in few sites, particularly in the outermost sections of the Alpine range, Pleistocene glaciers covered only small and scattered surfaces because of the low altitude reached in the basins, and ancient soils could be preserved for long periods of time on particularly stable surfaces. In some cases, these soils retain good memories of past periglacial activity. We described and sampled soils on stable surfaces in the Upper Tanaro valley, Ligurian Alps (Southwestern Piemonte, Italy). The sampling sites were between 600 to 1600 m of altitude, under present day lower montane Castanea sativa/Ostrya carpinifolia forests, montane Fagus sylvatica and Pinus uncinata forests or montane heath/grazed grassland, on different quartzitic substrata. The surface morphology often showed strongly developed, fossil periglacial patterned ground forms, such as coarse stone circles on flat surfaces, or stone stripes on steeper slopes. The stone circles could be up to 5 m wide, while the sorted stripes could be as wide as 12-15 m. A strong lateral cryogenic textural sorting characterized the fine fraction too, with sand dominating close to the stone rims of the patterned ground features and silt and clay the central parts. The surface 60-120 cm of the soils were podzolized during the Holocene; as a result of the textural lateral sorting, the thickness of the podzolic E and Bs horizons varied widely across the patterns. The lower boundary of the Holocene Podzols was abrupt, and corresponded with dense layers with thick coarse laminar structure and illuvial silt accumulation (Cjj horizons). Dense Cjj diapiric inclusions were sometimes preserved in the central parts of the patterns. Where cover beds were developed, more superimposed podzol cycles were observed: the deeper podzols, included in the dense layer, were strongly cryoturbated and showed convoluted horizons and buried organic horizons. The presence of the dense Cjj horizons also influenced surface soil hydrology, which in turn influenced the expression of E and Bs horizons, in addition to textural lateral variability. In conclusion, surface morphology and soil properties evidence the presence of permafrost during cold Pleistocene phases, with an active layer 60-120 cm thick, associated with a particularly strong cryoturbation. However, all the permafrost features were not necessarily formed during the same periods, and dating of different materials would be necessary in order to obtain precise paleoenvironmental reconstructions of cold Quaternary phases in the Alps.

Effect of triangular texture on the tribological performance of die steel with TiN coatings under lubricated sliding condition

NASA Astrophysics Data System (ADS)

Chen, Ping; Xiang, Xin; Shao, Tianmin; La, Yingqian; Li, Junling

2016-12-01

The friction and wear of stamping die surface can affect the service life of stamping die and the quality of stamping products. Surface texturing and surface coating have been widely used to improve the tribological performance of mechanical components. This study experimentally investigated the effect of triangular surface texture on the friction and wear properties of the die steel substrate with TiN coatings under oil lubrication. TiN coatings were deposited on a die steel (50Cr) substrate through a multi-arc ion deposition system, and then triangular surface texturing was fabricated by a laser surface texturing. The friction and wear test was conducted by a UMT-3 pin-on-disk tribometer under different sliding speeds and different applied loads, respectively. The adhesion test was performed to evaluate the effectiveness of triangular texturing on the interfacial bonding strength between the TiN coating and the die steel substrate. Results show that the combination method of surface texturing process and surface coating process has excellent tribological properties (the lowest frictional coefficient and wear volume), compared with the single texturing process or the single coating process. The tribological performance is improved resulting from the high hardness and low elastic modulus of TiN coatings, and the generation of hydrodynamic pressure, function of micro-trap for wear debris and micro-reservoirs for lubricating oil of the triangular surface texture. In addition, the coating bonding strength of the texturing sample is 3.63 MPa, higher than that of the single coating sample (3.48 MPa), but the mechanisms remain to be further researched.

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

PubMed

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

2011-04-01

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

Bayesian Fusion of Color and Texture Segmentations

NASA Technical Reports Server (NTRS)

Manduchi, Roberto

2000-01-01

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

Electric Arc and Electrochemical Surface Texturing Technologies

NASA Technical Reports Server (NTRS)

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

1997-01-01

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

Hybrid texture generator

NASA Astrophysics Data System (ADS)

Miyata, Kazunori; Nakajima, Masayuki

1995-04-01

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

Surface-texture evolution of different chemical-vapor-deposited zinc sulfide flats polished with various magnetorheological fluids

DOE PAGES

Salzman, S.; Romanofsky, H. J.; Jacobs, S. D.; ...

2015-08-19

The macro-structure of chemical-vapor-deposited (CVD) zinc sulfide (ZnS) substrates is characterizedby cone-like structures that start growing at the early stages of deposition. As deposition progresses,these cones grow larger and reach centimeter size in height and millimeter size in width. It is challengingto polish out these features from the top layer, particularly for the magnetorheological finishing (MRF)process. A conventional MR fluid tends to leave submillimeter surface artifacts on the finished surface,which is a direct result of the cone-like structure. Here we describe the MRF process of polishing four CVD ZnS substrates, manufactured by four differentvendors, with conventional MR fluid at pHmore » 10 and zirconia-coated-CI (carbonyl iron) MR fluids at pH 4, 5,and 6. We report on the surface–texture evolution of the substrates as they were MRF polished with thedifferent fluids. We show that performances of the zirconia-coated-CI MR fluid at pH 4 are significantlyhigher than that of the same fluid at pH levels of 5 and 6 and moderately higher than that of a conventionalMR fluid at pH 10. An improvement in surface–texture variability from part to part was also observedwith the pH 4 MR fluid.« less

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

PubMed

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

2017-11-09

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

Fast segmentation of industrial quality pavement images using Laws texture energy measures and k -means clustering

NASA Astrophysics Data System (ADS)

Mathavan, Senthan; Kumar, Akash; Kamal, Khurram; Nieminen, Michael; Shah, Hitesh; Rahman, Mujib

2016-09-01

Thousands of pavement images are collected by road authorities daily for condition monitoring surveys. These images typically have intensity variations and texture nonuniformities that make their segmentation challenging. The automated segmentation of such pavement images is crucial for accurate, thorough, and expedited health monitoring of roads. In the pavement monitoring area, well-known texture descriptors, such as gray-level co-occurrence matrices and local binary patterns, are often used for surface segmentation and identification. These, despite being the established methods for texture discrimination, are inherently slow. This work evaluates Laws texture energy measures as a viable alternative for pavement images for the first time. k-means clustering is used to partition the feature space, limiting the human subjectivity in the process. Data classification, hence image segmentation, is performed by the k-nearest neighbor method. Laws texture energy masks are shown to perform well with resulting accuracy and precision values of more than 80%. The implementations of the algorithm, in both MATLAB® and OpenCV/C++, are extensively compared against the state of the art for execution speed, clearly showing the advantages of the proposed method. Furthermore, the OpenCV-based segmentation shows a 100% increase in processing speed when compared to the fastest algorithm available in literature.

Surface Texturing of Polyimide Composite by Micro-Ultrasonic Machining

NASA Astrophysics Data System (ADS)

Qu, N. S.; Zhang, T.; Chen, X. L.

2018-03-01

In this study, micro-dimples were prepared on a polyimide composite surface to obtain the dual benefits of polymer materials and surface texture. Micro-ultrasonic machining is employed for the first time for micro-dimple fabrication on polyimide composite surfaces. Surface textures of simple patterns were fabricated successfully with dimple depths of 150 μm, side lengths of 225-425 μm, and area ratios of 10-30%. The friction coefficient of the micro-dimple surfaces with side lengths of 325 or 425 μm could be increased by up to 100% of that of non-textured surfaces, alongside a significant enhancement of wear resistance. The results show that surface texturing of polyimide composite can be applied successfully to increase the friction coefficient and reduce wear, thereby contributing to a large output torque.

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

NASA Astrophysics Data System (ADS)

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

2012-09-01

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

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

PubMed

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

2018-03-30

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

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

PubMed Central

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

2018-01-01

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

Robust surface roughness indices and morphological interpretation

NASA Astrophysics Data System (ADS)

Trevisani, Sebastiano; Rocca, Michele

2016-04-01

Geostatistical-based image/surface texture indices based on variogram (Atkison and Lewis, 2000; Herzfeld and Higginson, 1996; Trevisani et al., 2012) and on its robust variant MAD (median absolute differences, Trevisani and Rocca, 2015) offer powerful tools for the analysis and interpretation of surface morphology (potentially not limited to solid earth). In particular, the proposed robust index (Trevisani and Rocca, 2015) with its implementation based on local kernels permits the derivation of a wide set of robust and customizable geomorphometric indices capable to outline specific aspects of surface texture. The stability of MAD in presence of signal noise and abrupt changes in spatial variability is well suited for the analysis of high-resolution digital terrain models. Moreover, the implementation of MAD by means of a pixel-centered perspective based on local kernels, with some analogies to the local binary pattern approach (Lucieer and Stein, 2005; Ojala et al., 2002), permits to create custom roughness indices capable to outline different aspects of surface roughness (Grohmann et al., 2011; Smith, 2015). In the proposed poster, some potentialities of the new indices in the context of geomorphometry and landscape analysis will be presented. At same time, challenges and future developments related to the proposed indices will be outlined. Atkinson, P.M., Lewis, P., 2000. Geostatistical classification for remote sensing: an introduction. Computers & Geosciences 26, 361-371. Grohmann, C.H., Smith, M.J., Riccomini, C., 2011. Multiscale Analysis of Topographic Surface Roughness in the Midland Valley, Scotland. IEEE Transactions on Geoscience and Remote Sensing 49, 1220-1213. Herzfeld, U.C., Higginson, C.A., 1996. Automated geostatistical seafloor classification - Principles, parameters, feature vectors, and discrimination criteria. Computers and Geosciences, 22 (1), pp. 35-52. Lucieer, A., Stein, A., 2005. Texture-based landform segmentation of LiDAR imagery. International Journal of Applied Earth Observation and Geoinformation 6, 261-270. Ojala, T., Pietikäinen, M. & Mäenpää, T. 2002. "Multiresolution gray-scale and rotation invariant texture classification with local binary patterns", IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 7, pp. 971-987. Smith, M.W. 2014. "Roughness in the Earth Sciences", Earth-Science Reviews, vol. 136, pp. 202-225. Trevisani, S., Cavalli, M. & Marchi, L. 2012. "Surface texture analysis of a high-resolution DTM: Interpreting an alpine basin", Geomorphology, vol. 161-162, pp. 26-39. Trevisani, S., Rocca, M. 2015. MAD: robust image texture analysis for applications in high resolution geomorphometry. Comput. Geosci. 81, 78-92. doi:10.1016/j.cageo.2015.04.003.

Contourlet textual features: improving the diagnosis of solitary pulmonary nodules in two dimensional CT images.

PubMed

Wang, Jingjing; Sun, Tao; Gao, Ni; Menon, Desmond Dev; Luo, Yanxia; Gao, Qi; Li, Xia; Wang, Wei; Zhu, Huiping; Lv, Pingxin; Liang, Zhigang; Tao, Lixin; Liu, Xiangtong; Guo, Xiuhua

2014-01-01

To determine the value of contourlet textural features obtained from solitary pulmonary nodules in two dimensional CT images used in diagnoses of lung cancer. A total of 6,299 CT images were acquired from 336 patients, with 1,454 benign pulmonary nodule images from 84 patients (50 male, 34 female) and 4,845 malignant from 252 patients (150 male, 102 female). Further to this, nineteen patient information categories, which included seven demographic parameters and twelve morphological features, were also collected. A contourlet was used to extract fourteen types of textural features. These were then used to establish three support vector machine models. One comprised a database constructed of nineteen collected patient information categories, another included contourlet textural features and the third one contained both sets of information. Ten-fold cross-validation was used to evaluate the diagnosis results for the three databases, with sensitivity, specificity, accuracy, the area under the curve (AUC), precision, Youden index, and F-measure were used as the assessment criteria. In addition, the synthetic minority over-sampling technique (SMOTE) was used to preprocess the unbalanced data. Using a database containing textural features and patient information, sensitivity, specificity, accuracy, AUC, precision, Youden index, and F-measure were: 0.95, 0.71, 0.89, 0.89, 0.92, 0.66, and 0.93 respectively. These results were higher than results derived using the database without textural features (0.82, 0.47, 0.74, 0.67, 0.84, 0.29, and 0.83 respectively) as well as the database comprising only textural features (0.81, 0.64, 0.67, 0.72, 0.88, 0.44, and 0.85 respectively). Using the SMOTE as a pre-processing procedure, new balanced database generated, including observations of 5,816 benign ROIs and 5,815 malignant ROIs, and accuracy was 0.93. Our results indicate that the combined contourlet textural features of solitary pulmonary nodules in CT images with patient profile information could potentially improve the diagnosis of lung cancer.

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

PubMed

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

2014-03-01

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

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

PubMed

Latha, Manohar; Kavitha, Ganesan

2018-02-03

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

Rotation-invariant image and video description with local binary pattern features.

PubMed

Zhao, Guoying; Ahonen, Timo; Matas, Jiří; Pietikäinen, Matti

2012-04-01

In this paper, we propose a novel approach to compute rotation-invariant features from histograms of local noninvariant patterns. We apply this approach to both static and dynamic local binary pattern (LBP) descriptors. For static-texture description, we present LBP histogram Fourier (LBP-HF) features, and for dynamic-texture recognition, we present two rotation-invariant descriptors computed from the LBPs from three orthogonal planes (LBP-TOP) features in the spatiotemporal domain. LBP-HF is a novel rotation-invariant image descriptor computed from discrete Fourier transforms of LBP histograms. The approach can be also generalized to embed any uniform features into this framework, and combining the supplementary information, e.g., sign and magnitude components of the LBP, together can improve the description ability. Moreover, two variants of rotation-invariant descriptors are proposed to the LBP-TOP, which is an effective descriptor for dynamic-texture recognition, as shown by its recent success in different application problems, but it is not rotation invariant. In the experiments, it is shown that the LBP-HF and its extensions outperform noninvariant and earlier versions of the rotation-invariant LBP in the rotation-invariant texture classification. In experiments on two dynamic-texture databases with rotations or view variations, the proposed video features can effectively deal with rotation variations of dynamic textures (DTs). They also are robust with respect to changes in viewpoint, outperforming recent methods proposed for view-invariant recognition of DTs.

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

PubMed Central

Wang, Kun-Ching

2015-01-01

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

Texture feature extraction based on wavelet transform and gray-level co-occurrence matrices applied to osteosarcoma diagnosis.

PubMed

Hu, Shan; Xu, Chao; Guan, Weiqiao; Tang, Yong; Liu, Yana

2014-01-01

Osteosarcoma is the most common malignant bone tumor among children and adolescents. In this study, image texture analysis was made to extract texture features from bone CR images to evaluate the recognition rate of osteosarcoma. To obtain the optimal set of features, Sym4 and Db4 wavelet transforms and gray-level co-occurrence matrices were applied to the image, with statistical methods being used to maximize the feature selection. To evaluate the performance of these methods, a support vector machine algorithm was used. The experimental results demonstrated that the Sym4 wavelet had a higher classification accuracy (93.44%) than the Db4 wavelet with respect to osteosarcoma occurrence in the epiphysis, whereas the Db4 wavelet had a higher classification accuracy (96.25%) for osteosarcoma occurrence in the diaphysis. Results including accuracy, sensitivity, specificity and ROC curves obtained using the wavelets were all higher than those obtained using the features derived from the GLCM method. It is concluded that, a set of texture features can be extracted from the wavelets and used in computer-aided osteosarcoma diagnosis systems. In addition, this study also confirms that multi-resolution analysis is a useful tool for texture feature extraction during bone CR image processing.

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

PubMed

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.

BRAIN TUMOR SEGMENTATION WITH SYMMETRIC TEXTURE AND SYMMETRIC INTENSITY-BASED DECISION FORESTS.

PubMed

Bianchi, Anthony; Miller, James V; Tan, Ek Tsoon; Montillo, Albert

2013-04-01

Accurate automated segmentation of brain tumors in MR images is challenging due to overlapping tissue intensity distributions and amorphous tumor shape. However, a clinically viable solution providing precise quantification of tumor and edema volume would enable better pre-operative planning, treatment monitoring and drug development. Our contributions are threefold. First, we design efficient gradient and LBPTOP based texture features which improve classification accuracy over standard intensity features. Second, we extend our texture and intensity features to symmetric texture and symmetric intensity which further improve the accuracy for all tissue classes. Third, we demonstrate further accuracy enhancement by extending our long range features from 100mm to a full 200mm. We assess our brain segmentation technique on 20 patients in the BraTS 2012 dataset. Impact from each contribution is measured and the combination of all the features is shown to yield state-of-the-art accuracy and speed.

3D Texture Features Mining for MRI Brain Tumor Identification

NASA Astrophysics Data System (ADS)

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

2014-03-01

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

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

NASA Astrophysics Data System (ADS)

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.

Bio-mimicking nano and micro-structured surface fabrication for antibacterial properties in medical implants.

PubMed

Jaggessar, Alka; Shahali, Hesam; Mathew, Asha; Yarlagadda, Prasad K D V

2017-10-02

Orthopaedic and dental implants have become a staple of the medical industry and with an ageing population and growing culture for active lifestyles, this trend is forecast to continue. In accordance with the increased demand for implants, failure rates, particularly those caused by bacterial infection, need to be reduced. The past two decades have led to developments in antibiotics and antibacterial coatings to reduce revision surgery and death rates caused by infection. The limited effectiveness of these approaches has spurred research into nano-textured surfaces, designed to mimic the bactericidal properties of some animal, plant and insect species, and their topographical features. This review discusses the surface structures of cicada, dragonfly and butterfly wings, shark skin, gecko feet, taro and lotus leaves, emphasising the relationship between nano-structures and high surface contact angles on self-cleaning and bactericidal properties. Comparison of these surfaces shows large variations in structure dimension and configuration, indicating that there is no one particular surface structure that exhibits bactericidal behaviour against all types of microorganisms. Recent bio-mimicking fabrication methods are explored, finding hydrothermal synthesis to be the most commonly used technique, due to its environmentally friendly nature and relative simplicity compared to other methods. In addition, current proposed bactericidal mechanisms between bacteria cells and nano-textured surfaces are presented and discussed. These models could be improved by including additional parameters such as biological cell membrane properties, adhesion forces, bacteria dynamics and nano-structure mechanical properties. This paper lastly reviews the mechanical stability and cytotoxicity of micro and nano-structures and materials. While the future of nano-biomaterials is promising, long-term effects of micro and nano-structures in the body must be established before nano-textures can be used on orthopaedic implant surfaces as way of inhibiting bacterial adhesion.

Investigation of the tribology behaviour of the graphene nanosheets as oil additives on textured alloy cast iron surface

NASA Astrophysics Data System (ADS)

Zheng, Dan; Cai, Zhen-bing; Shen, Ming-xue; Li, Zheng-yang; Zhu, Min-hao

2016-11-01

Tribological properties of graphene nanosheets (GNS) as lubricating oil additives on textured surfaces were investigated using a UMT-2 tribotester. The lubricating fluids keeping a constant temperature of 100 °C were applied to a GCr15 steel ball and an RTCr2 alloy cast iron plate with various texture designs (original surface, dimple density of 22.1%, 19.6% and 44.2%). The oil with GNS adding showed good tribological properties (wear reduced 50%), especially on the textured surfaces (the reduction in wear was high at over 90%). A combined effect between GNS additives and laser surface texturing (LST) was revealed, which is not a simple superposition of the two factors mentioned. A mechanism is proposed to explain for these results -the graphene layers sheared at the sliding contact interfaces, and form a protective film, which is closely related with the GNS structures and surface texture patterns.

Radiomic texture-curvature (RTC) features for precision medicine of patients with rheumatoid arthritis-associated interstitial lung disease

NASA Astrophysics Data System (ADS)

Watari, Chinatsu; Matsuhiro, Mikio; Näppi, Janne J.; Nasirudin, Radin A.; Hironaka, Toru; Kawata, Yoshiki; Niki, Noboru; Yoshida, Hiroyuki

2018-03-01

We investigated the effect of radiomic texture-curvature (RTC) features of lung CT images in the prediction of the overall survival of patients with rheumatoid arthritis-associated interstitial lung disease (RA-ILD). We retrospectively collected 70 RA-ILD patients who underwent thin-section lung CT and serial pulmonary function tests. After the extraction of the lung region, we computed hyper-curvature features that included the principal curvatures, curvedness, bright/dark sheets, cylinders, blobs, and curvature scales for the bronchi and the aerated lungs. We also computed gray-level co-occurrence matrix (GLCM) texture features on the segmented lungs. An elastic-net penalty method was used to select and combine these features with a Cox proportional hazards model for predicting the survival of the patient. Evaluation was performed by use of concordance index (C-index) as a measure of prediction performance. The C-index values of the texture features, hyper-curvature features, and the combination thereof (RTC features) in predicting patient survival was estimated by use of bootstrapping with 2,000 replications, and they were compared with an established clinical prognostic biomarker known as the gender, age, and physiology (GAP) index by means of two-sided t-test. Bootstrap evaluation yielded the following C-index values for the clinical and radiomic features: (a) GAP index: 78.3%; (b) GLCM texture features: 79.6%; (c) hypercurvature features: 80.8%; and (d) RTC features: 86.8%. The RTC features significantly outperformed any of the other predictors (P < 0.001). The Kaplan-Meier survival curves of patients stratified to low- and high-risk groups based on the RTC features showed statistically significant (P < 0.0001) difference. Thus, the RTC features can provide an effective imaging biomarker for predicting the overall survival of patients with RA-ILD.

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

NASA Astrophysics Data System (ADS)

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.

Breast cancer detection in rotational thermography images using texture features

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

Orbital selective spin-texture in a topological insulator

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

Singh, Bahadur, E-mail: bahadursingh24@gmail.com; Prasad, R.

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 anmore » 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.« less

Generating Enhanced Natural Environments and Terrain for Interactive Combat Simulations (GENETICS)

DTIC Science & Technology

2005-09-01

split to avoid T-junctions ........................................................................52 Figure 2-23 Longest edge bisection...database. This feature allows trainers the flexibility to use the same terrain repeatedly or use a new one each time, forcing trainees to avoid ...model are favored to create a good surface approximation. Cracks are avoided by projecting primitives and their respective textures onto multiple

Rock classification based on resistivity patterns in electrical borehole wall images

NASA Astrophysics Data System (ADS)

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

2007-06-01

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

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

NASA Technical Reports Server (NTRS)

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 squeeze-outs along the pit walls that form when the rising crust exposes the still liquid core of the sheet. The plains of Tharsis and Elysium, Mars, display many analogous features

Surface texture can bias tactile form perception.

PubMed

Nakatani, Masashi; Howe, Robert D; Tachi, Susumu

2011-01-01

The sense of touch is believed to provide a reliable perception of the object's properties; however, our tactile perceptions could be illusory at times. A recently reported tactile illusion shows that a raised form can be perceived as indented when it is surrounded by textured areas. This phenomenon suggests that the form perception can be influenced by the surface textures in its adjacent areas. As perception of texture and that of form have been studied independently of each other, the present study examined whether textures, in addition to the geometric edges, contribute to the tactile form perception. We examined the perception of the flat and raised contact surface (3.0 mm width) with various heights (0.1, 0.2, 0.3 mm), which had either textured or non-textured adjacent areas, under the static, passive and active touch conditions. Our results showed that texture decreased the raised perception of the surface with a small height (0.1 mm) and decreased the flat perception of the physically flat surface under the passive and active touch conditions. We discuss a possible mechanism underlying the effect of the textures on the form perception based on previous neurophysiological findings.

Conveying 3D shape with texture: recent advances and experimental findings

NASA Astrophysics Data System (ADS)

Interrante, Victoria; Kim, Sunghee; Hagh-Shenas, Haleh

2002-06-01

If we could design the perfect texture pattern to apply to any smooth surface in order to enable observers to more accurately perceive the surface's shape in a static monocular image taken from an arbitrary generic viewpoint under standard lighting conditions, what would the characteristics of that texture pattern be? In order to gain insight into this question, our group has developed an efficient algorithm for synthesizing a high resolution texture pattern, derived from a provided 2D sample, over an arbitrary doubly curved surface in such a way that the orientation of the texture is constrained to follow a specified underlying vector field over the surface, at a per-pixel level, without evidence of seams or projective distortion artifacts. In this paper, we report the findings of a recent experiment in which we attempt to use this new texture synthesis method to assess the shape information carrying capacity of two different types of directional texture patterns (unidirectional and bi-directional) under three different orientation conditions (following the first principal direction, following a constant uniform direction, or swirling sinusoidally in the surface). In a four alternative forced choice task, we asked participants to identify the quadrant in which two B-spline surfaces, illuminated from different random directions and simultaneously and persistently displayed, differed in their shapes. We found, after all subjects had gained sufficient training in the task, that accuracy increased fairly consistently with increasing magnitude of surface shape disparity, but that the characteristics of this increase differed under the different texture orientation conditions. Subjects were able to more reliably perceive smaller shape differences when the surfaces were textured with a pattern whose orientation followed one of the principal directions than when the surfaces were textured with a pattern that either gradually swirled in the surface or followed a constant uniform direction in the tangent plane regardless of the surface shape characteristics. These findings appear to support our hypothesis that anisotropic textures aligned with the first principal direction may facilitate shape perception, for a generic view, by making more, reliable information about the extent of the surface curvature explicitly available to the observer than would be available if the texture pattern were oriented in any other way.

Human mesenchymal stem cell behavior on femtosecond laser-textured Ti-6Al-4V surfaces.

PubMed

Cunha, Alexandre; Zouani, Omar Farouk; Plawinski, Laurent; Botelho do Rego, Ana Maria; Almeida, Amélia; Vilar, Rui; Durrieu, Marie-Christine

2015-01-01

The aim of the present work was to investigate ultrafast laser surface texturing as a surface treatment of Ti-6Al-4V alloy dental and orthopedic implants to improve osteoblastic commitment of human mesenchymal stem cells (hMSCs). Surface texturing was carried out by direct writing with an Yb:KYW chirped-pulse regenerative amplification laser system with a central wavelength of 1030 nm and a pulse duration of 500 fs. The surface topography and chemical composition were investigated by scanning electron microscopy and x-ray photoelectron spectroscopy, respectively. Three types of surface textures with potential interest to improve implant osseointegration can be produced by this method: laser-induced periodic surface structures (LIPSSs); nanopillars (NPs); and microcolumns covered with LIPSSs, forming a bimodal roughness distribution. The potential of the laser treatment in improving hMSC differentiation was assessed by in vitro study of hMSCs spreading, adhesion, elongation and differentiation using epifluorescence microscopy at different times after cell seeding, after specific stainings and immunostainings. Cell area and focal adhesion area were lower on the laser-textured surfaces than on a polished reference surface. Obviously, the laser-textured surfaces have an impact on cell shape. Osteoblastic commitment was observed independently of the surface topography after 2 weeks of cell seeding. When the cells were cultured (after 4 weeks of seeding) in osteogenic medium, LIPSS- and NP- textured surfaces enhanced matrix mineralization and bone-like nodule formation as compared with polished and microcolumn-textured surfaces. The present work shows that surface nanotextures consisting of LIPSSs and NPs can, potentially, improve hMSC differentiation into an osteoblastic lineage.

SU-E-J-113: Effects of Deformable Registration On First-Order Texture Maps Calculated From Thoracic Lung CT Scans

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

Smith, C; Cunliffe, A; Al-Hallaq, H

Purpose: To determine the stability of eight first-order texture features following the deformable registration of serial computed tomography (CT) scans. Methods: CT scans at two different time points from 10 patients deemed to have no lung abnormalities by a radiologist were collected. Following lung segmentation using an in-house program, texture maps were calculated from 32×32-pixel regions of interest centered at every pixel in the lungs. The texture feature value of the ROI was assigned to the center pixel of the ROI in the corresponding location of the texture map. Pixels in the square ROI not contained within the segmented lungmore » were not included in the calculation. To quantify the agreement between ROI texture features in corresponding pixels of the baseline and follow-up texture maps, the Fraunhofer MEVIS EMPIRE10 deformable registration algorithm was used to register the baseline and follow-up scans. Bland-Altman analysis was used to compare registered scan pairs by computing normalized bias (nBias), defined as the feature value change normalized to the mean feature value, and normalized range of agreement (nRoA), defined as the range spanned by the 95% limits of agreement normalized to the mean feature value. Results: Each patient’s scans contained between 6.8–15.4 million ROIs. All of the first-order features investigated were found to have an nBias value less than 0.04% and an nRoA less than 19%, indicating that the variability introduced by deformable registration was low. Conclusion: The eight first-order features investigated were found to be registration stable. Changes in CT texture maps could allow for temporal-spatial evaluation of the evolution of lung abnormalities relating to a variety of diseases on a patient-by-patient basis. SGA and HA receives royalties and licensing fees through the University of Chicago for computer-aided diagnosis technology. Research reported in this publication was supported by the National Institute Of General Medical Sciences of the National Institutes of Health under Award Number R25GM109439.« less

TU-AB-BRA-05: Repeatability of [F-18]-NaF PET Imaging Biomarkers for Bone Lesions: A Multicenter Study

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

Lin, C; Bradshaw, T; Perk, T

2015-06-15

Purpose: Quantifying the repeatability of imaging biomarkers is critical for assessing therapeutic response. While therapeutic efficacy has been traditionally quantified by SUV metrics, imaging texture features have shown potential for use as quantitative biomarkers. In this study we evaluated the repeatability of quantitative {sup 18}F-NaF PET-derived SUV metrics and texture features in bone lesions from patients in a multicenter study. Methods: Twenty-nine metastatic castrate-resistant prostate cancer patients received whole-body test-retest NaF PET/CT scans from one of three harmonized imaging centers. Bone lesions of volume greater than 1.5 cm{sup 3} were identified and automatically segmented using a SUV>15 threshold. From eachmore » lesion, 55 NaF PET-derived texture features (including first-order, co-occurrence, grey-level run-length, neighbor gray-level, and neighbor gray-tone difference matrix) were extracted. The test-retest repeatability of each SUV metric and texture feature was assessed with Bland-Altman analysis. Results: A total of 315 bone lesions were evaluated. Of the traditional SUV metrics, the repeatability coefficient (RC) was 12.6 SUV for SUVmax, 2.5 SUV for SUVmean, and 4.3 cm{sup 3} for volume. Their respective intralesion coefficients of variation (COVs) were 12%, 17%, and 6%. Of the texture features, COV was lowest for entropy (0.03%) and highest for kurtosis (105%). Lesion intraclass correlation coefficient (ICC) was lowest for maximum correlation coefficient (ICC=0.848), and highest for entropy (ICC=0.985). Across imaging centers, repeatability of texture features and SUV varied. For example, across imaging centers, COV for SUVmax ranged between 11–23%. Conclusion: Many NaF PET-derived SUV metrics and texture features for bone lesions demonstrated high repeatability, such as SUVmax, entropy, and volume. Several imaging texture features demonstrated poor repeatability, such as SUVtotal and SUVstd. These results can be used to establish response criteria for NaF PET-based treatment response assessment. Prostate Cancer Foundation (PCF)« less

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Dynamic facial expression recognition based on geometric and texture features

NASA Astrophysics Data System (ADS)

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.

P04.19 Recommendations for computation of textural measures obtained from 3D brain tumor MRIs: A robustness analysis points out the need for standardization.

PubMed Central

Molina, D.; Pérez-Beteta, J.; Martínez-González, A.; Velásquez, C.; Martino, J.; Luque, B.; Revert, A.; Herruzo, I.; Arana, E.; Pérez-García, V. M.

2017-01-01

Abstract Introduction: Textural analysis refers to a variety of mathematical methods used to quantify the spatial variations in grey levels within images. In brain tumors, textural features have a great potential as imaging biomarkers having been shown to correlate with survival, tumor grade, tumor type, etc. However, these measures should be reproducible under dynamic range and matrix size changes for their clinical use. Our aim is to study this robustness in brain tumors with 3D magnetic resonance imaging, not previously reported in the literature. Materials and methods: 3D T1-weighted images of 20 patients with glioblastoma (64.80 ± 9.12 years-old) obtained from a 3T scanner were analyzed. Tumors were segmented using an in-house semi-automatic 3D procedure. A set of 16 3D textural features of the most common types (co-occurrence and run-length matrices) were selected, providing regional (run-length based measures) and local information (co-ocurrence matrices) on the tumor heterogeneity. Feature robustness was assessed by means of the coefficient of variation (CV) under both dynamic range (16, 32 and 64 gray levels) and/or matrix size (256x256 and 432x432) changes. Results: None of the textural features considered were robust under dynamic range changes. The textural co-occurrence matrix feature Entropy was the only textural feature robust (CV < 10%) under spatial resolution changes. Conclusions: In general, textural measures of three-dimensional brain tumor images are neither robust under dynamic range nor under matrix size changes. Thus, it becomes mandatory to fix standards for image rescaling after acquisition before the textural features are computed if they are to be used as imaging biomarkers. For T1-weighted images a dynamic range of 16 grey levels and a matrix size of 256x256 (and isotropic voxel) is found to provide reliable and comparable results and is feasible with current MRI scanners. The implications of this work go beyond the specific tumor type and MRI sequence studied here and pose the need for standardization in textural feature calculation of oncological images. FUNDING: James S. Mc. Donnell Foundation (USA) 21st Century Science Initiative in Mathematical and Complex Systems Approaches for Brain Cancer [Collaborative award 220020450 and planning grant 220020420], MINECO/FEDER [MTM2015-71200-R], JCCM [PEII-2014-031-P].

Combining multiple features for color texture classification

NASA Astrophysics Data System (ADS)

Cusano, Claudio; Napoletano, Paolo; Schettini, Raimondo

2016-11-01

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

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

NASA Technical Reports Server (NTRS)

Gibbons, D. F.

1977-01-01

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

Texture-specific bag of visual words model and spatial cone matching-based method for the retrieval of focal liver lesions using multiphase contrast-enhanced CT images.

PubMed

Xu, Yingying; Lin, Lanfen; Hu, Hongjie; Wang, Dan; Zhu, Wenchao; Wang, Jian; Han, Xian-Hua; Chen, Yen-Wei

2018-01-01

The bag of visual words (BoVW) model is a powerful tool for feature representation that can integrate various handcrafted features like intensity, texture, and spatial information. In this paper, we propose a novel BoVW-based method that incorporates texture and spatial information for the content-based image retrieval to assist radiologists in clinical diagnosis. This paper presents a texture-specific BoVW method to represent focal liver lesions (FLLs). Pixels in the region of interest (ROI) are classified into nine texture categories using the rotation-invariant uniform local binary pattern method. The BoVW-based features are calculated for each texture category. In addition, a spatial cone matching (SCM)-based representation strategy is proposed to describe the spatial information of the visual words in the ROI. In a pilot study, eight radiologists with different clinical experience performed diagnoses for 20 cases with and without the top six retrieved results. A total of 132 multiphase computed tomography volumes including five pathological types were collected. The texture-specific BoVW was compared to other BoVW-based methods using the constructed dataset of FLLs. The results show that our proposed model outperforms the other three BoVW methods in discriminating different lesions. The SCM method, which adds spatial information to the orderless BoVW model, impacted the retrieval performance. In the pilot trial, the average diagnosis accuracy of the radiologists was improved from 66 to 80% using the retrieval system. The preliminary results indicate that the texture-specific features and the SCM-based BoVW features can effectively characterize various liver lesions. The retrieval system has the potential to improve the diagnostic accuracy and the confidence of the radiologists.

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

PubMed

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

2018-04-01

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

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

PubMed

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: <0.001-0.036). Unsupervised clustering achieved accuracy of 0.75 (sensitivity: 0.70; specificity: 0.79). Combination of ≥3 qualitative MR features accurately distinguished LMS from ALM. TA was 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.

Effect of layerwise structural inhomogeneity on stress- corrosion cracking of steel tubes

NASA Astrophysics Data System (ADS)

Perlovich, Yu A.; Krymskaya, O. A.; Isaenkova, M. G.; Morozov, N. S.; Fesenko, V. A.; Ryakhovskikh, I. V.; Esiev, T. S.

2016-04-01

Based on X-ray texture and structure analysis data of the material of main gas pipelines it was shown that the layerwise inhomogeneity of tubes is formed during their manufacturing. The degree of this inhomogeneity affects on the tendency of tubes to stress- corrosion cracking under exploitation. Samples of tubes were cut out from gas pipelines located under various operating conditions. Herewith the study was conducted both for sections with detected stress-corrosion defects and without them. Distributions along tube wall thickness for lattice parameters and half-width of X-ray lines were constructed. Crystallographic texture analysis of external and internal tube layers was also carried out. Obtained data testifies about considerable layerwise inhomogeneity of all samples. Despite the different nature of the texture inhomogeneity of gas pipeline tubes, the more inhomogeneous distribution of texture or structure features causes the increasing of resistance to stress- corrosion. The observed effect can be explained by saturation with interstitial impurities of the surface layer of the hot-rolled sheet and obtained therefrom tube. This results in rising of lattice parameters in the external layer of tube as compared to those in underlying metal. Thus, internal layers have a compressive effect on external layers in the rolling plane that prevents cracks opening at the tube surface. Moreover, the high mutual misorientation of grains within external and internal layers of tube results in the necessity to change the moving crack plane, so that the crack growth can be inhibited when reaching the layer with a modified texture.

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

PubMed

Chang, Yu-Ning; Chang, Herng-Hua

2015-01-01

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

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

PubMed

Chaddad, Ahmad; Daniel, Paul; Niazi, Tamim

2018-01-01

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

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

PubMed

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

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

Voss, M.; Blundell, B.

2015-12-01

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

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

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

Nakamachi, Eiji; Yoshida, Takashi; Yamaguchi, Toshihiko

2014-10-06

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

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

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

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

NASA Astrophysics Data System (ADS)

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

2012-03-01

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

Crystallographic texture of straight-rolled ?-uranium foils via neutron and X-ray diffraction

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

Einhorn, J. R.; Steiner, M. A.; Vogel, S. C.

The texture of recrystallized straight-rolled ?-uranium foils, a component in prospective irradiation target designs for medical isotope production, has been measured by neutron diffraction, as well as X-ray diffraction using both Cu and Mo sources. Variations in the penetration depth of neutron and X-ray radiation allow for determination of both the bulk and surface textures. The bulk ?-uranium foil texture is similar to the warm straight-rolled plate texture, with the addition of a notable splitting of the (001) poles along the transverse direction. The surface texture of the foils is similar to the bulk, with an additional (001) texture componentmore » that is oriented between the rolling and normal directions. Differences between the surface and bulk textures are expected to arise from shear forces during the rolling process and the influence that distinct strain histories have on subsequent texture evolution during recrystallization.« less

Crystallographic texture of straight-rolled ?-uranium foils via neutron and X-ray diffraction

DOE PAGES

Einhorn, J. R.; Steiner, M. A.; Vogel, S. C.; ...

2017-05-25

The texture of recrystallized straight-rolled ?-uranium foils, a component in prospective irradiation target designs for medical isotope production, has been measured by neutron diffraction, as well as X-ray diffraction using both Cu and Mo sources. Variations in the penetration depth of neutron and X-ray radiation allow for determination of both the bulk and surface textures. The bulk ?-uranium foil texture is similar to the warm straight-rolled plate texture, with the addition of a notable splitting of the (001) poles along the transverse direction. The surface texture of the foils is similar to the bulk, with an additional (001) texture componentmore » that is oriented between the rolling and normal directions. Differences between the surface and bulk textures are expected to arise from shear forces during the rolling process and the influence that distinct strain histories have on subsequent texture evolution during recrystallization.« less

Multi-stage classification method oriented to aerial image based on low-rank recovery and multi-feature fusion sparse representation.

PubMed

Ma, Xu; Cheng, Yongmei; Hao, Shuai

2016-12-10

Automatic classification of terrain surfaces from an aerial image is essential for an autonomous unmanned aerial vehicle (UAV) landing at an unprepared site by using vision. Diverse terrain surfaces may show similar spectral properties due to the illumination and noise that easily cause poor classification performance. To address this issue, a multi-stage classification algorithm based on low-rank recovery and multi-feature fusion sparse representation is proposed. First, color moments and Gabor texture feature are extracted from training data and stacked as column vectors of a dictionary. Then we perform low-rank matrix recovery for the dictionary by using augmented Lagrange multipliers and construct a multi-stage terrain classifier. Experimental results on an aerial map database that we prepared verify the classification accuracy and robustness of the proposed method.

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

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

Korfiatis, Panagiotis; Kline, Timothy L.; Erickson, Bradley J., E-mail: bje@mayo.edu

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 classifiersmore » 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.« less

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-10-01

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

Possible climate-related signals in high-resolution topography of lobate debris aprons in Tempe Terra, Mars

NASA Astrophysics Data System (ADS)

Grindrod, Peter M.; Fawcett, Stephen A.

2011-10-01

Lobate debris aprons are common features in the mid-latitudes of Mars that are assumed to be the result of the flow of ice-rich material. We produce high-resolution digital elevation models of two of these features in the Tempe Terra region of Mars using HiRISE stereo images. We identify two main topographic features of different wavelength using a power spectrum analysis approach. Short wavelength features, between approximately 10 and 20 m in length, correspond to a polygonal surface texture present throughout our study area. Long wavelength features, between approximately 700 and 1800 m in length, correspond to broad ridges that are up to 20 m in amplitude. We interpret both topographic signals to be the likely result of climate change affecting the debris contribution and/or the flow regime of the lobate debris aprons. The apparent surface age of about 300 Ma could be evidence of an astronomical forcing mechanism recorded in these lobate debris aprons at this time in Mars' history.

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

NASA Technical Reports Server (NTRS)

Weigand, A. J.

1978-01-01

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

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

NASA Astrophysics Data System (ADS)

Bharatish, A.; Soundarapandian, S.

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

Bharatish, A.; Soundarapandian, S.

2018-06-01

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

Influence of Laser Shock Texturing on W9 Steel Surface Friction Property

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Scanning-electron-microscopy observations and mechanical characteristics of ion-beam-sputtered surgical implant alloys

NASA Technical Reports Server (NTRS)

Weigand, A. J.; Meyer, M. L.; Ling, J. S.

1977-01-01

An electron bombardment ion thruster was used as an ion source to sputter the surfaces of orthopedic prosthetic metals. Scanning electron microscopy photomicrographs were made of each ion beam textured surface. The effect of ion texturing an implant surface on its bond to bone cement was investigated. A Co-Cr-W alloy and surgical stainless steel were used as representative hard tissue implant materials to determine effects of ion texturing on bulk mechanical properties. Work was done to determine the effect of substrate temperature on the development of an ion textured surface microstructure. Results indicate that the ultimate strength of the bulk materials is unchanged by ion texturing and that the microstructure will develop more rapidly if the substrate is heated prior to ion texturing.

Parametric classification of handvein patterns based on texture features

NASA Astrophysics Data System (ADS)

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.

Comparison of radiograph-based texture analysis and bone mineral density with three-dimensional microarchitecture of trabecular bone.

PubMed

Ranjanomennahary, P; Ghalila, S Sevestre; Malouche, D; Marchadier, A; Rachidi, M; Benhamou, Cl; Chappard, C

2011-01-01

Hip fracture is a serious health problem and textural methods are being developed to assess bone quality. The authors aimed to perform textural analysis at femur on high-resolution digital radiographs compared to three-dimensional (3D) microarchitecture comparatively to bone mineral density. Sixteen cadaveric femurs were imaged with an x-ray device using a C-MOS sensor. One 17 mm square region of interest (ROI) was selected in the femoral head (FH) and one in the great trochanter (GT). Two-dimensional (2D) textural features from the co-occurrence matrices were extracted. Site-matched measurements of bone mineral density were performed. Inside each ROI, a 16 mm diameter core was extracted. Apparent density (Dapp) and bone volume proportion (BV/TV(Arch)) were measured from a defatted bone core using Archimedes' principle. Microcomputed tomography images of the entire length of the core were obtained (Skyscan 1072) at 19.8 microm of resolution and usual 3D morphometric parameters were computed on the binary volume after calibration from BV/TV(Arch). Then, bone surface/bone volume, trabecular thickness, trabecular separation, and trabecular number were obtained by direct methods without model assumption and the structure model index was calculated. In univariate analysis, the correlation coefficients between 2D textural features and 3D morphological parameters reached 0.83 at the FH and 0.79 at the GT. In multivariate canonical correlation analysis, coefficients of the first component reached 0.95 at the FH and 0.88 at the GT. Digital radiographs, widely available and economically viable, are an alternative method for evaluating bone microarchitectural structure.

Hepatic CT image query using Gabor features

NASA Astrophysics Data System (ADS)

Zhao, Chenguang; Cheng, Hongyan; Zhuang, Tiange

2004-07-01

A retrieval scheme for liver computerize tomography (CT) images based on Gabor texture is presented. For each hepatic CT image, we manually delineate abnormal regions within liver area. Then, a continuous Gabor transform is utilized to analyze the texture of the pathology bearing region and extract the corresponding feature vectors. For a given sample image, we compare its feature vector with those of other images. Similar images with the highest rank are retrieved. In experiments, 45 liver CT images are collected, and the effectiveness of Gabor texture for content based retrieval is verified.

Doped LZO buffer layers for laminated conductors

DOEpatents

Paranthaman, Mariappan Parans [Knoxville, TN; Schoop, Urs [Westborough, MA; Goyal, Amit [Knoxville, TN; Thieme, Cornelis Leo Hans [Westborough, MA; Verebelyi, Darren T [Oxford, MA; Rupich, Martin W [Framingham, MA

2010-03-23

A laminated conductor includes a metallic substrate having a surface, a biaxially textured buffer layer supported by the surface of the substrate, the biaxially textured buffer layer comprising LZO and a dopant for mitigating metal diffusion through the LZO, and a biaxially textured conductor layer supported by the biaxially textured buffer layer.

Contourlet Textual Features: Improving the Diagnosis of Solitary Pulmonary Nodules in Two Dimensional CT Images

PubMed Central

Wang, Jingjing; Sun, Tao; Gao, Ni; Menon, Desmond Dev; Luo, Yanxia; Gao, Qi; Li, Xia; Wang, Wei; Zhu, Huiping; Lv, Pingxin; Liang, Zhigang; Tao, Lixin; Liu, Xiangtong; Guo, Xiuhua

2014-01-01

Objective To determine the value of contourlet textural features obtained from solitary pulmonary nodules in two dimensional CT images used in diagnoses of lung cancer. Materials and Methods A total of 6,299 CT images were acquired from 336 patients, with 1,454 benign pulmonary nodule images from 84 patients (50 male, 34 female) and 4,845 malignant from 252 patients (150 male, 102 female). Further to this, nineteen patient information categories, which included seven demographic parameters and twelve morphological features, were also collected. A contourlet was used to extract fourteen types of textural features. These were then used to establish three support vector machine models. One comprised a database constructed of nineteen collected patient information categories, another included contourlet textural features and the third one contained both sets of information. Ten-fold cross-validation was used to evaluate the diagnosis results for the three databases, with sensitivity, specificity, accuracy, the area under the curve (AUC), precision, Youden index, and F-measure were used as the assessment criteria. In addition, the synthetic minority over-sampling technique (SMOTE) was used to preprocess the unbalanced data. Results Using a database containing textural features and patient information, sensitivity, specificity, accuracy, AUC, precision, Youden index, and F-measure were: 0.95, 0.71, 0.89, 0.89, 0.92, 0.66, and 0.93 respectively. These results were higher than results derived using the database without textural features (0.82, 0.47, 0.74, 0.67, 0.84, 0.29, and 0.83 respectively) as well as the database comprising only textural features (0.81, 0.64, 0.67, 0.72, 0.88, 0.44, and 0.85 respectively). Using the SMOTE as a pre-processing procedure, new balanced database generated, including observations of 5,816 benign ROIs and 5,815 malignant ROIs, and accuracy was 0.93. Conclusion Our results indicate that the combined contourlet textural features of solitary pulmonary nodules in CT images with patient profile information could potentially improve the diagnosis of lung cancer. PMID:25250576

Wettability transition of laser textured brass surfaces inside different mediums

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

18F-FDG PET radiomics approaches: comparing and clustering features in cervical cancer.

PubMed

Tsujikawa, Tetsuya; Rahman, Tasmiah; Yamamoto, Makoto; Yamada, Shizuka; Tsuyoshi, Hideaki; Kiyono, Yasushi; Kimura, Hirohiko; Yoshida, Yoshio; Okazawa, Hidehiko

2017-11-01

The aims of our study were to find the textural features on 18 F-FDG PET/CT which reflect the different histological architectures between cervical cancer subtypes and to make a visual assessment of the association between 18 F-FDG PET textural features in cervical cancer. Eighty-three cervical cancer patients [62 squamous cell carcinomas (SCCs) and 21 non-SCCs (NSCCs)] who had undergone pretreatment 18 F-FDG PET/CT were enrolled. A texture analysis was performed on PET/CT images, from which 18 PET radiomics features were extracted including first-order features such as standardized uptake value (SUV), metabolic tumor volume (MTV) and total lesion glycolysis (TLG), second- and high-order textural features using SUV histogram, normalized gray-level co-occurrence matrix (NGLCM), and neighborhood gray-tone difference matrix, respectively. These features were compared between SCC and NSCC using a Bonferroni adjusted P value threshold of 0.0028 (0.05/18). To assess the association between PET features, a heat map analysis with hierarchical clustering, one of the radiomics approaches, was performed. Among 18 PET features, correlation, a second-order textural feature derived from NGLCM, was a stable parameter and it was the only feature which showed a robust trend toward significant difference between SCC and NSCC. Cervical SCC showed a higher correlation (0.70 ± 0.07) than NSCC (0.64 ± 0.07, P = 0.0030). The other PET features did not show any significant differences between SCC and NSCC. A higher correlation in SCC might reflect higher structural integrity and stronger spatial/linear relationship of cancer cells compared with NSCC. A heat map with a PET feature dendrogram clearly showed 5 distinct clusters, where correlation belonged to a cluster including MTV and TLG. However, the association between correlation and MTV/TLG was not strong. Correlation was a relatively independent PET feature in cervical cancer. 18 F-FDG PET textural features might reflect the differences in histological architecture between cervical cancer subtypes. PET radiomics approaches reveal the association between PET features and will be useful for finding a single feature or a combination of features leading to precise diagnoses, potential prognostic models, and effective therapeutic strategies.

Effect of surface topographic features on the optical properties of skin: a phantom study

NASA Astrophysics Data System (ADS)

Liu, Guangli; Chen, Jianfeng; Zhao, Zuhua; Zhao, Gang; Dong, Erbao; Chu, Jiaru; Xu, Ronald X.

2016-10-01

Tissue-simulating phantoms are used to validate and calibrate optical imaging systems and to understand light transport in biological tissue. Light propagation in a strongly turbid medium such as skin tissue experiences multiple scattering and diffuse reflection from the surface. Surface roughness introduces phase shifts and optical path length differences for light which is scattered within the skin tissue and reflected from the surface. In this paper, we study the effect of mismatched surface roughness on optical measurement and subsequent determination of optical properties of skin tissue. A series of phantoms with controlled surface features and optical properties corresponding to normal human skin are fabricated. The fabrication of polydimethylsiloxane (PDMS) phantoms with known surface roughness follows a standard soft lithography process. Surface roughness of skin-simulating phantoms are measured with Bruker stylus profiler. The diffuse reflectance of the phantom is validated by a UV/VIS spectrophotometer. The results show that surface texture and roughness have considerable influence on the optical characteristics of skin. This study suggests that surface roughness should be considered as an important contributing factor for the determination of tissue optical properties.

Cooling of hot bubbles by surface texture during the boiling crisis

NASA Astrophysics Data System (ADS)

Dhillon, Navdeep; Buongiorno, Jacopo; Varanasi, Kripa

2015-11-01

We report the existence of maxima in critical heat flux (CHF) enhancement for pool boiling on textured hydrophilic surfaces and reveal the interaction mechanism between bubbles and surface texture that governs the boiling crisis phenomenon. Boiling is a process of fundamental importance in many engineering and industrial applications but the maximum heat flux that can be absorbed by the boiling liquid (or CHF) is limited by the boiling crisis. Enhancing the CHF of industrial boilers by surface texturing can lead to substantial energy savings and reduction in greenhouse gas emissions on a global scale. However, the fundamental mechanisms behind this enhancement are not well understood, with some previous studies indicating that CHF should increase monotonically with increasing texture density. However, using pool boiling experiments on a parametrically designed set of plain and nano-textured micropillar surfaces, we show that there is an optimum intermediate texture density that maximizes CHF and further that the length scale of this texture is of fundamental significance. Using imbibition experiments and high-speed optical and infrared imaging, we reveal the fundamental mechanisms governing the CHF enhancement maxima in boiling crisis. We acknowledge funding from the Chevron corporation.

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

NASA Astrophysics Data System (ADS)

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.

Differential diagnosis of CT focal liver lesions using texture features, feature selection and ensemble driven classifiers.

PubMed

Mougiakakou, Stavroula G; Valavanis, Ioannis K; Nikita, Alexandra; Nikita, Konstantina S

2007-09-01

The aim of the present study is to define an optimally performing computer-aided diagnosis (CAD) architecture for the classification of liver tissue from non-enhanced computed tomography (CT) images into normal liver (C1), hepatic cyst (C2), hemangioma (C3), and hepatocellular carcinoma (C4). To this end, various CAD architectures, based on texture features and ensembles of classifiers (ECs), are comparatively assessed. Number of regions of interests (ROIs) corresponding to C1-C4 have been defined by experienced radiologists in non-enhanced liver CT images. For each ROI, five distinct sets of texture features were extracted using first order statistics, spatial gray level dependence matrix, gray level difference method, Laws' texture energy measures, and fractal dimension measurements. Two different ECs were constructed and compared. The first one consists of five multilayer perceptron neural networks (NNs), each using as input one of the computed texture feature sets or its reduced version after genetic algorithm-based feature selection. The second EC comprised five different primary classifiers, namely one multilayer perceptron NN, one probabilistic NN, and three k-nearest neighbor classifiers, each fed with the combination of the five texture feature sets or their reduced versions. The final decision of each EC was extracted by using appropriate voting schemes, while bootstrap re-sampling was utilized in order to estimate the generalization ability of the CAD architectures based on the available relatively small-sized data set. The best mean classification accuracy (84.96%) is achieved by the second EC using a fused feature set, and the weighted voting scheme. The fused feature set was obtained after appropriate feature selection applied to specific subsets of the original feature set. The comparative assessment of the various CAD architectures shows that combining three types of classifiers with a voting scheme, fed with identical feature sets obtained after appropriate feature selection and fusion, may result in an accurate system able to assist differential diagnosis of focal liver lesions from non-enhanced CT images.

Laser surface texturing of 316L stainless steel in air and water: A method for increasing hydrophilicity via direct creation of microstructures

NASA Astrophysics Data System (ADS)

Razi, Sepehr; Madanipour, Khosro; Mollabashi, Mahmoud

2016-06-01

Laser processing of materials in water contact is sometimes employed for improving the machining, cutting or welding quality. Here, we demonstrate surface patterning of stainless steel grade 316L by nano-second laser processing in air and water. Suitable adjustments of laser parameters offer a variety of surface patterns on the treated targets. Furthermore alterations of different surface features such as surface chemistry and wettability are investigated in various processing circumstances. More than surface morphology, remarkable differences are observed in the surface oxygen content and wettability of the samples treated in air and water at the same laser processing conditions. Mechanisms of the changes are discussed extensively.

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

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

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

2014-06-15

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

Location and Geologic Setting for the Three U.S. Mars Landers

NASA Technical Reports Server (NTRS)

Parker, T. J.; Kirk, R. L.

1999-01-01

Super resolution of the horizon at both Viking landing sites has revealed "new" features we use for triangulation, similar to the approach used during the Mars Pathfinder Mission. We propose alternative landing site locations for both landers for which we believe the confidence is very high. Super resolution of VL-1 images also reveals some of the drift material at the site to consist of gravel-size deposits. Since our proposed location for VL-2 is NOT on the Mie ejecta blanket, the blocky surface around the lander may represent the meter-scale texture of "smooth palins" in the region. The Viking Lander panchromatic images typically offer more repeat coverage than does the IMP on Mars Pathfinder, due to the longer duration of these landed missions. Sub-pixel offsets, necessary for super resolution to work, appear to be attributable to thermal effects on the lander and settling of the lander over time. Due to the greater repeat coverage (particularly in the near and mid-fields) and all-panchromatic images, the gain in resolution by super resolution processing is better for Viking than it is with most IMP image sequences. This enhances the study of textural details near the lander and enables the identification rock and surface textures at greater distances from the lander. Discernment of stereo in super resolution im-ages is possible to great distances from the lander, but is limited by the non-rotating baseline between the two cameras and the shorter height of the cameras above the ground compared to IMP. With super resolution, details of horizon features, such as blockiness and crater rim shapes, may be better correlated with Orbiter images. A number of horizon features - craters and ridges - were identified at VL-1 during the misison, and a few hils and subtle ridges were identified at VL-2. We have added a few "new" horizon features for triangulation at the VL-2 landing site in Utopia Planitia. These features were used for independent triangulation with features visible in Viking Orbiter and MGS MOC images, though the actual location of VL-1 lies in a data dropout in the MOC image of the area. Additional information is contained in the original extended abstract.

Unsupervised feature learning for autonomous rock image classification

NASA Astrophysics Data System (ADS)

Shu, Lei; McIsaac, Kenneth; Osinski, Gordon R.; Francis, Raymond

2017-09-01

Autonomous rock image classification can enhance the capability of robots for geological detection and enlarge the scientific returns, both in investigation on Earth and planetary surface exploration on Mars. Since rock textural images are usually inhomogeneous and manually hand-crafting features is not always reliable, we propose an unsupervised feature learning method to autonomously learn the feature representation for rock images. In our tests, rock image classification using the learned features shows that the learned features can outperform manually selected features. Self-taught learning is also proposed to learn the feature representation from a large database of unlabelled rock images of mixed class. The learned features can then be used repeatedly for classification of any subclass. This takes advantage of the large dataset of unlabelled rock images and learns a general feature representation for many kinds of rocks. We show experimental results supporting the feasibility of self-taught learning on rock images.

Locating potential biosignatures on Europa from surface geology observations.

PubMed

Figueredo, Patricio H; Greeley, Ronald; Neuer, Susanne; Irwin, Louis; Schulze-Makuch, Dirk

2003-01-01

We evaluated the astrobiological potential of the major classes of geologic units on Europa with respect to possible biosignatures preservation on the basis of surface geology observations. These observations are independent of any formational model and therefore provide an objective, though preliminary, evaluation. The assessment criteria include high mobility of material, surface concentration of non-ice components, relative youth, textural roughness, and environmental stability. Our review determined that, as feature classes, low-albedo smooth plains, smooth bands, and chaos hold the highest potential, primarily because of their relative young age, the emplacement of low-viscosity material, and indications of material exchange with the subsurface. Some lineaments and impact craters may be promising sites for closer study despite the comparatively lower astrobiological potential of their classes. This assessment will be expanded by multidisciplinary examination of the potential for habitability of specific features.

Efficient Data Mining for Local Binary Pattern in Texture Image Analysis

PubMed Central

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

2015-01-01

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

Multi-Feature Classification of Multi-Sensor Satellite Imagery Based on Dual-Polarimetric Sentinel-1A, Landsat-8 OLI, and Hyperion Images for Urban Land-Cover Classification.

PubMed

Zhou, Tao; Li, Zhaofu; Pan, Jianjun

2018-01-27

This paper focuses on evaluating the ability and contribution of using backscatter intensity, texture, coherence, and color features extracted from Sentinel-1A data for urban land cover classification and comparing different multi-sensor land cover mapping methods to improve classification accuracy. Both Landsat-8 OLI and Hyperion images were also acquired, in combination with Sentinel-1A data, to explore the potential of different multi-sensor urban land cover mapping methods to improve classification accuracy. The classification was performed using a random forest (RF) method. The results showed that the optimal window size of the combination of all texture features was 9 × 9, and the optimal window size was different for each individual texture feature. For the four different feature types, the texture features contributed the most to the classification, followed by the coherence and backscatter intensity features; and the color features had the least impact on the urban land cover classification. Satisfactory classification results can be obtained using only the combination of texture and coherence features, with an overall accuracy up to 91.55% and a kappa coefficient up to 0.8935, respectively. Among all combinations of Sentinel-1A-derived features, the combination of the four features had the best classification result. Multi-sensor urban land cover mapping obtained higher classification accuracy. The combination of Sentinel-1A and Hyperion data achieved higher classification accuracy compared to the combination of Sentinel-1A and Landsat-8 OLI images, with an overall accuracy of up to 99.12% and a kappa coefficient up to 0.9889. When Sentinel-1A data was added to Hyperion images, the overall accuracy and kappa coefficient were increased by 4.01% and 0.0519, respectively.

Textured Image Segmentation

DTIC Science & Technology

1980-01-01

descriminated by frequency domain features. It has been shown (201 that Fourier features provide useful information for aerial classification and for...Package for the Social. Sciences (SPSS). These descriminant algorithms are documented in Appendix C. Source textures are known, so that cluster

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

NASA Astrophysics Data System (ADS)

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

2014-07-01

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

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

PubMed

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

2016-09-01

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

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

Mouterde, Timothée; Lehoucq, Gaëlle; Xavier, Stéphane

Nanometre-scale features with special shapes impart a broad spectrum of unique properties to the surface of insects. These properties are essential for the animal’s survival, and include the low light reflectance of moth eyes, the oil repellency of springtail carapaces and the ultra-adhesive nature of palmtree bugs. Antireflective mosquito eyes and cicada wings are also known to exhibit some antifogging and self-cleaning properties. In all cases, the combination of small feature size and optimal shape provides exceptional surface properties. In this work, we investigate the underlying antifogging mechanism in model materials designed to mimic natural systems, and explain the importancemore » of the texture’s feature size and shape. While exposure to fog strongly compromises the water-repellency of hydrophobic structures, this failure can be minimized by scaling the texture down to nanosize. Furthermore, this undesired effect even becomes non-measurable if the hydrophobic surface consists of nanocones, which generate antifogging efficiency close to unity and water departure of droplets smaller than 2 μm.« less

Antifogging abilities of model nanotextures

DOE PAGES

Mouterde, Timothée; Lehoucq, Gaëlle; Xavier, Stéphane; ...

2017-02-27

Nanometre-scale features with special shapes impart a broad spectrum of unique properties to the surface of insects. These properties are essential for the animal’s survival, and include the low light reflectance of moth eyes, the oil repellency of springtail carapaces and the ultra-adhesive nature of palmtree bugs. Antireflective mosquito eyes and cicada wings are also known to exhibit some antifogging and self-cleaning properties. In all cases, the combination of small feature size and optimal shape provides exceptional surface properties. In this work, we investigate the underlying antifogging mechanism in model materials designed to mimic natural systems, and explain the importancemore » of the texture’s feature size and shape. While exposure to fog strongly compromises the water-repellency of hydrophobic structures, this failure can be minimized by scaling the texture down to nanosize. Furthermore, this undesired effect even becomes non-measurable if the hydrophobic surface consists of nanocones, which generate antifogging efficiency close to unity and water departure of droplets smaller than 2 μm.« less

Antifogging abilities of model nanotextures

NASA Astrophysics Data System (ADS)

Mouterde, Timothée; Lehoucq, Gaëlle; Xavier, Stéphane; Checco, Antonio; Black, Charles T.; Rahman, Atikur; Midavaine, Thierry; Clanet, Christophe; Quéré, David

2017-06-01

Nanometre-scale features with special shapes impart a broad spectrum of unique properties to the surface of insects. These properties are essential for the animal’s survival, and include the low light reflectance of moth eyes, the oil repellency of springtail carapaces and the ultra-adhesive nature of palmtree bugs. Antireflective mosquito eyes and cicada wings are also known to exhibit some antifogging and self-cleaning properties. In all cases, the combination of small feature size and optimal shape provides exceptional surface properties. In this work, we investigate the underlying antifogging mechanism in model materials designed to mimic natural systems, and explain the importance of the texture’s feature size and shape. While exposure to fog strongly compromises the water-repellency of hydrophobic structures, this failure can be minimized by scaling the texture down to nanosize. This undesired effect even becomes non-measurable if the hydrophobic surface consists of nanocones, which generate antifogging efficiency close to unity and water departure of droplets smaller than 2 μm.

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

PubMed

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

2017-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-03-01

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

Estimating local scaling properties for the classification of interstitial lung disease patterns

NASA Astrophysics Data System (ADS)

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

2011-03-01

Local scaling properties of texture regions 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 honeycombing, a stack of 70 axial, lung kernel reconstructed images were acquired from HRCT chest exams. 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 the estimation of local scaling properties with Scaling Index Method (SIM). 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 including the Bonferroni correction. The best classification results were obtained by the set of SIM features, which performed significantly better than all the standard GLCM and MD features (p < 0.005) for both classifiers with the highest accuracy (94.1%, 93.7%; 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 texture features using local scaling properties can provide superior classification performance in computer-assisted diagnosis of interstitial lung diseases when compared to standard texture analysis methods.

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

PubMed

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

2017-09-01

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

ProteinShader: illustrative rendering of macromolecules

PubMed Central

Weber, Joseph R

2009-01-01

Background Cartoon-style illustrative renderings of proteins can help clarify structural features that are obscured by space filling or balls and sticks style models, and recent advances in programmable graphics cards offer many new opportunities for improving illustrative renderings. Results The ProteinShader program, a new tool for macromolecular visualization, uses information from Protein Data Bank files to produce illustrative renderings of proteins that approximate what an artist might create by hand using pen and ink. A combination of Hermite and spherical linear interpolation is used to draw smooth, gradually rotating three-dimensional tubes and ribbons with a repeating pattern of texture coordinates, which allows the application of texture mapping, real-time halftoning, and smooth edge lines. This free platform-independent open-source program is written primarily in Java, but also makes extensive use of the OpenGL Shading Language to modify the graphics pipeline. Conclusion By programming to the graphics processor unit, ProteinShader is able to produce high quality images and illustrative rendering effects in real-time. The main feature that distinguishes ProteinShader from other free molecular visualization tools is its use of texture mapping techniques that allow two-dimensional images to be mapped onto the curved three-dimensional surfaces of ribbons and tubes with minimum distortion of the images. PMID:19331660

Texture analysis of radiometric signatures of new sea ice forming in Arctic leads

NASA Technical Reports Server (NTRS)

Eppler, Duane T.; Farmer, L. Dennis

1991-01-01

Analysis of 33.6-GHz, high-resolution, passive microwave images suggests that new sea ice accumulating in open leads is characterized by a unique textural signature which can be used to discriminate new ice forming in this environment from adjacent surfaces of similar radiometric temperature. Ten training areas were selected from the data set, three of which consisted entirely of first-year ice, four entirely of multilayer ice, and three of new ice in open leads in the process of freezing. A simple gradient operator was used to characterize the radiometric texture in each training region in terms of the degree to which radiometric gradients are oriented. New ice in leads has a sufficiently high proportion of well-oriented features to distinguish it uniquely from first-year ice and multiyear ice. The predominance of well-oriented features probably reflects physical processes by which new ice accumulates in open leads. Banded structures, which are evident in aerial photographs of new ice, apparently give rise to the radiometric signature observed, in which the trend of brightness temperature gradients is aligned parallel to lead trends. First-year ice and multiyear ice, which have been subjected to a more random growth and process history, lack this banded structure and therefore are characterized by signatures in which well-aligned elements are less dominant.

Efficacy of texture, shape, and intensity feature fusion for posterior-fossa tumor segmentation in MRI.

PubMed

Ahmed, Shaheen; Iftekharuddin, Khan M; Vossough, Arastoo

2011-03-01

Our previous works suggest that fractal texture feature is useful to detect pediatric brain tumor in multimodal MRI. In this study, we systematically investigate efficacy of using several different image features such as intensity, fractal texture, and level-set shape in segmentation of posterior-fossa (PF) tumor for pediatric patients. We explore effectiveness of using four different feature selection and three different segmentation techniques, respectively, to discriminate tumor regions from normal tissue in multimodal brain MRI. We further study the selective fusion of these features for improved PF tumor segmentation. Our result suggests that Kullback-Leibler divergence measure for feature ranking and selection and the expectation maximization algorithm for feature fusion and tumor segmentation offer the best results for the patient data in this study. We show that for T1 and fluid attenuation inversion recovery (FLAIR) MRI modalities, the best PF tumor segmentation is obtained using the texture feature such as multifractional Brownian motion (mBm) while that for T2 MRI is obtained by fusing level-set shape with intensity features. In multimodality fused MRI (T1, T2, and FLAIR), mBm feature offers the best PF tumor segmentation performance. We use different similarity metrics to evaluate quality and robustness of these selected features for PF tumor segmentation in MRI for ten pediatric patients.

Hyperspectral remote sensing image retrieval system using spectral and texture features.

PubMed

Zhang, Jing; Geng, Wenhao; Liang, Xi; Li, Jiafeng; Zhuo, Li; Zhou, Qianlan

2017-06-01

Although many content-based image retrieval systems have been developed, few studies have focused on hyperspectral remote sensing images. In this paper, a hyperspectral remote sensing image retrieval system based on spectral and texture features is proposed. The main contributions are fourfold: (1) considering the "mixed pixel" in the hyperspectral image, endmembers as spectral features are extracted by an improved automatic pixel purity index algorithm, then the texture features are extracted with the gray level co-occurrence matrix; (2) similarity measurement is designed for the hyperspectral remote sensing image retrieval system, in which the similarity of spectral features is measured with the spectral information divergence and spectral angle match mixed measurement and in which the similarity of textural features is measured with Euclidean distance; (3) considering the limited ability of the human visual system, the retrieval results are returned after synthesizing true color images based on the hyperspectral image characteristics; (4) the retrieval results are optimized by adjusting the feature weights of similarity measurements according to the user's relevance feedback. The experimental results on NASA data sets can show that our system can achieve comparable superior retrieval performance to existing hyperspectral analysis schemes.

Analysis of iris surface features in populations of diverse ancestry

PubMed Central

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

Semantic attributes based texture generation

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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

NASA Astrophysics Data System (ADS)

Lu, Weifang; Ou, Yiyu; Jokubavicius, Valdas; Fadil, Ahmed; Syväjärvi, Mikael; Petersen, Paul Michael; Ou, Haiyan

2016-07-01

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 for TiO2 deposition, a three-step cleaning procedure was introduced after RIE etching. The morphology of anatase TiO2 indicates that the nano-textured substrate has a much higher surface nucleated grain density than a flat substrate at the beginning of the deposition process. The corresponding reflectance increases with TiO2 thickness due to increased surface diffuse reflection. The passivation effect of ALD TiO2 thin film on the nano-textured fluorescent 6H-SiC sample was also investigated and a PL intensity improvement of 8.05% was obtained due to the surface passivation.

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

PubMed

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

2013-01-01

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

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

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

Ma, C; Yin, Y

2014-06-01

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

Classification Features of US Images Liver Extracted with Co-occurrence Matrix Using the Nearest Neighbor Algorithm

NASA Astrophysics Data System (ADS)

Moldovanu, Simona; Bibicu, Dorin; Moraru, Luminita; Nicolae, Mariana Carmen

2011-12-01

Co-occurrence matrix has been applied successfully for echographic images characterization because it contains information about spatial distribution of grey-scale levels in an image. The paper deals with the analysis of pixels in selected regions of interest of an US image of the liver. The useful information obtained refers to texture features such as entropy, contrast, dissimilarity and correlation extract with co-occurrence matrix. The analyzed US images were grouped in two distinct sets: healthy liver and steatosis (or fatty) liver. These two sets of echographic images of the liver build a database that includes only histological confirmed cases: 10 images of healthy liver and 10 images of steatosis liver. The healthy subjects help to compute four textural indices and as well as control dataset. We chose to study these diseases because the steatosis is the abnormal retention of lipids in cells. The texture features are statistical measures and they can be used to characterize irregularity of tissues. The goal is to extract the information using the Nearest Neighbor classification algorithm. The K-NN algorithm is a powerful tool to classify features textures by means of grouping in a training set using healthy liver, on the one hand, and in a holdout set using the features textures of steatosis liver, on the other hand. The results could be used to quantify the texture information and will allow a clear detection between health and steatosis liver.

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

PubMed

Kumbhare, Dinesh A; Ahmed, Sara; Behr, Michael G; Noseworthy, Michael D

2018-01-01

Objective-The objective of this study is to assess the discriminative ability of textural analyses to assist in the differentiation of the myofascial trigger point (MTrP) region from normal regions of skeletal muscle. Also, to measure the ability to reliably differentiate between three clinically relevant groups: healthy asymptomatic, latent MTrPs, and active MTrP. Methods-18 and 19 patients were identified with having active and latent MTrPs in the trapezius muscle, respectively. We included 24 healthy volunteers. Images were obtained by research personnel, who were blinded with respect to the clinical status of the study participant. Histograms provided first-order parameters associated with image grayscale. Haralick, Galloway, and histogram-related features were used in texture analysis. Blob analysis was conducted on the regions of interest (ROIs). Principal component analysis (PCA) was performed followed by multivariate analysis of variance (MANOVA) to determine the statistical significance of the features. Results-92 texture features were analyzed for factorability using Bartlett's test of sphericity, which was significant. The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.94. PCA demonstrated rotated eigenvalues of the first eight components (each comprised of multiple texture features) explained 94.92% of the cumulative variance in the ultrasound image characteristics. The 24 features identified by PCA were included in the MANOVA as dependent variables, and the presence of a latent or active MTrP or healthy muscle were independent variables. Conclusion-Texture analysis techniques can discriminate between the three clinically relevant groups.

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

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

Andrews, M; Abazeed, M; Woody, N

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

HOS cell adhesion on Ti6Al4V ELI texturized by CO2 laser

NASA Astrophysics Data System (ADS)

Sandoval-Amador, A.; Bayona–Alvarez, Y. M.; Carreño Garcia, H.; Escobar-Rivero, P.; Y Peña-Ballesteros, D.

2017-12-01

In this work, the response of HOS cells on Ti6Al4V ELI textured surfaces by a CO2 laser was evaluated. The test surfaces were; smooth Ti6Al4V, used as the control, and four textured surfaces with linear geometry. These four surfaces had different separation distances between textured lines, D1 (1000 microns), D2 (750 microns), D3 (500 microns) and D4 (250 microns). Toxicity of textured surfaces was assessed by MTT and the cellular adhesion test was performed using HOS ATCC CRL 1543 line cells. This test was done after 5 days of culture in a RPMI 1640 medium supplemented with 10% fetal bovine serum and 1% antibiotics. The results showed that the linear textures present 23% toxicity after 30 days of incubation, nevertheless, the adhesion tests results are inconclusive in such conditions and therefore the effect of the line separation on the cell adhesion cannot be determined.

Crop identification of SAR data using digital textural analysis

NASA Technical Reports Server (NTRS)

Nuesch, D. R.

1983-01-01

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

Texture Feature Extraction and Classification for Iris Diagnosis

NASA Astrophysics Data System (ADS)

Ma, Lin; Li, Naimin

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

Robust weak anti-localisation effect in strongly textured nanocrystalline Bi2Se3 samples

NASA Astrophysics Data System (ADS)

Pereira, V. M. M.; Henriques, M. S. C.; Paixão, J. A.

2018-05-01

Topological insulators are a quantum state of matter that has recently created a great interest among the scientific community, with Bi2Se3 being one of the most extensively studied materials. Here, we demonstrate that polycrystalline nanostructured samples of Bi2Se3 preserve the existence of topological surface states, where electrons cannot be localised. The nanosheet crystals were synthesised by a microwave-assisted method and their structure, composition and morphology thoroughly characterised. The transport properties of a textured polycrystalline sample with strong preferred orientation along the c-axis were measured, showing the presence of the weak anti-localisation effect and Shubnikov-de Haas oscillations. These features are robust against the presence of non-magnetic impurities and structural defects.

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

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-05-01

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

Combined Effect of Textured Patterns and Graphene Flake Additives on Tribological Behavior under Boundary Lubrication

PubMed Central

Cai, Zhen-bing; Zhao, Lei; Zhang, Xu; Yue, Wen; Zhu, Min-hao

2016-01-01

A ball-on-plate wear test was employed to investigate the effectiveness of graphene (GP) nanoparticles dispersed in a synthetic-oil-based lubricant in reducing wear. The effect by area ratio of elliptically shaped dimple textures and elevated temperatures were also explored. Pure PAO4 based oil and a mixture of this oil with 0.01 wt% GP were compared as lubricants. At pit area ratio of 5%, GP-base oil effectively reduced friction and wear, especially at 60 and 100°C. Under pure PAO4 oil lubrication, the untextured surfaces gained low friction coefficients (COFs) and wear rates under 60 and 100°C. With increasing laser—texture area ratio, the COF and wear rate decreased at 25 and 150°C but increased at 60 and 100°C. Under the GP-based oil lubrication, the textured surface with 5% area ratio achieved the lowest COF among those of the area ratios tested at all test temperatures. Meanwhile, the textured surface with 20% area ratio obtained the highest COF among those of the area ratios. With the joint action of GP and texture, the textured surface with 10% area ratio exhibited the best anti-wear performance among all of the textured surfaces at all test temperatures. PMID:27054762

A validated computational model for the design of surface textures in full-film lubricated sliding

NASA Astrophysics Data System (ADS)

Schuh, Jonathon; Lee, Yong Hoon; Allison, James; Ewoldt, Randy

2016-11-01

Our recent experimental work showed that asymmetry is needed for surface textures to decrease friction in full-film lubricated sliding (thrust bearings) with Newtonian fluids; textures reduce the shear load and produce a separating normal force. The sign of the separating normal force is not predicted by previous 1-D theories. Here we model the flow with the Reynolds equation in cylindrical coordinates, numerically implemented with a pseudo-spectral method. The model predictions match experiments, rationalize the sign of the normal force, and allow for design of surface texture geometry. To minimize sliding friction with angled cylindrical textures, an optimal angle of asymmetry β exists. The optimal angle depends on the film thickness but not the sliding velocity within the applicable range of the model. The model has also been used to optimize generalized surface texture topography while satisfying manufacturability constraints.

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

Texture Fish

ERIC Educational Resources Information Center

Stone, Julie

2007-01-01

In an effort to provide an opportunity for her first graders to explore texture through an engaging subject, the author developed a three-part lesson that features fish in a mixed-media artwork: (1) Exploring Textured Paint; (2) Creating the Fish; and (3) Role Playing. In this lesson, students effectively explore texture through painting, drawing,…

Rolling process for producing biaxially textured substrates

DOEpatents

Goyal, Amit

2004-05-25

A method of preparing a biaxially textured article includes the steps of: rolling a metal preform while applying shear force thereto to form as-rolled biaxially textured substrate having an a rotated cube texture wherein a (100) cube face thereof is parallel to a surface of said substrate, and wherein a [100] direction thereof is at an angle of at least 30.degree. relative to the rolling direction; and depositing onto the surface of the biaxially textured substrate at least one epitaxial layer of another material to form a biaxially textured article.

Multiresolution texture models for brain tumor segmentation in MRI.

PubMed

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

2011-01-01

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

Microtextured metals for stray-light suppression in the Clementine startracker

NASA Technical Reports Server (NTRS)

Johnson, E. A.

1993-01-01

Anodized blacks for suppressing stray light in optical systems can now be replaced by microscopically textured metal surfaces. An application of these black surfaces to the Clementine star-tracker navigational system, which will be launched in early 1994 to examine the Moon, en route to intercept an asteroid, is detailed. Rugged black surfaces with Lambertian BRDF less than 10(exp -2) srad(sup -1) are critical for suppressing stray light in the star-tracker optical train. Previously available materials spall under launch vibrations to contaminate mirrors and lenses. Microtextured aluminum is nearly as dark, but much less fragile. It is made by differential ion beam sputtering, which generates light-trapping pores and cones slightly smaller than the wavelength to be absorbed. This leaves a sturdy but light-absorbing surface that can survive challenging conditions without generating debris or contaminants. Both seeded ion beams and plasma immersion (from ECR plasmas) extraction can produce these microscopic textures without fragile interfaces. Process parameters control feature size, spacing, and optical effects (THR, BRDF). Both broad and narrow absorption bands can be engineered with tuning for specific wavelengths and applications. Examples are presented characterized by FTIR in reflection librators (0.95 normal emissivity), heat rejection, and enhanced nucleate boiling.

Machine vision based quality inspection of flat glass products

NASA Astrophysics Data System (ADS)

Zauner, G.; Schagerl, M.

2014-03-01

This application paper presents a machine vision solution for the quality inspection of flat glass products. A contact image sensor (CIS) is used to generate digital images of the glass surfaces. The presented machine vision based quality inspection at the end of the production line aims to classify five different glass defect types. The defect images are usually characterized by very little `image structure', i.e. homogeneous regions without distinct image texture. Additionally, these defect images usually consist of only a few pixels. At the same time the appearance of certain defect classes can be very diverse (e.g. water drops). We used simple state-of-the-art image features like histogram-based features (std. deviation, curtosis, skewness), geometric features (form factor/elongation, eccentricity, Hu-moments) and texture features (grey level run length matrix, co-occurrence matrix) to extract defect information. The main contribution of this work now lies in the systematic evaluation of various machine learning algorithms to identify appropriate classification approaches for this specific class of images. In this way, the following machine learning algorithms were compared: decision tree (J48), random forest, JRip rules, naive Bayes, Support Vector Machine (multi class), neural network (multilayer perceptron) and k-Nearest Neighbour. We used a representative image database of 2300 defect images and applied cross validation for evaluation purposes.

Wetting and spreading behaviors of impinging microdroplets on textured surfaces

NASA Astrophysics Data System (ADS)

Kwon, Dae Hee; Lee, Sang Joon; CenterBiofluid and Biomimic Reseach Team

2012-11-01

Textured surfaces having an array of microscale pillars have been receiving large attention because of their potential uses for robust superhydrophobic and superoleophobic surfaces. In many practical applications, the textured surfaces usually accompany impinging small-scale droplets. To better understand the impinging phenomena on the textured surfaces, the wetting and spreading behaviors of water microdroplets are investigated experimentally. Microdroplets with diameter less than 50 μm are ejected from a piezoelectric printhead with varying Weber number. The final wetting state of an impinging droplet can be estimated by comparing the wetting pressures of the droplet and the capillary pressure of the textured surface. The wetting behaviors obtained experimentally are well agreed with the estimated results. In addition, the transition from bouncing to non-bouncing behaviors in the partially penetrated wetting state is observed. This transition implies the possibility of withdrawal of the penetrated liquid from the inter-pillar space. The maximum spreading factors (ratio of the maximum spreading diameter to the initial diameter) of the impinging droplets have close correlation with the texture area fraction of the surfaces. This work was supported by Creative Research Initiatives (Diagnosis of Biofluid Flow Phenomena and Biomimic Research) of MEST/KOSEF.

Structural analysis of natural textures.

PubMed

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

1986-01-01

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

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

NASA Astrophysics Data System (ADS)

Zhang, Xiaoliang; Jia, Junhong

2015-08-01

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

Estimation of Articular Cartilage Surface Roughness Using Gray-Level Co-Occurrence Matrix of Laser Speckle Image.

PubMed

Youssef, Doaa; El-Ghandoor, Hatem; Kandel, Hamed; El-Azab, Jala; Hassab-Elnaby, Salah

2017-06-28

The application of He-Ne laser technologies for description of articular cartilage degeneration, one of the most common diseases worldwide, is an innovative usage of these technologies used primarily in material engineering. Plain radiography and magnetic resonance imaging are insufficient to allow the early assessment of the disease. As surface roughness of articular cartilage is an important indicator of articular cartilage degeneration progress, a safe and noncontact technique based on laser speckle image to estimate the surface roughness is provided. This speckle image from the articular cartilage surface, when illuminated by laser beam, gives very important information about the physical properties of the surface. An experimental setup using a low power He-Ne laser and a high-resolution digital camera was implemented to obtain speckle images of ten bovine articular cartilage specimens prepared for different average roughness values. Texture analysis method based on gray-level co-occurrence matrix (GLCM) analyzed on the captured speckle images is used to characterize the surface roughness of the specimens depending on the computation of Haralick's texture features. In conclusion, this promising method can accurately estimate the surface roughness of articular cartilage even for early signs of degeneration. The method is effective for estimation of average surface roughness values ranging from 0.09 µm to 2.51 µm with an accuracy of 0.03 µm.

Estimation of Articular Cartilage Surface Roughness Using Gray-Level Co-Occurrence Matrix of Laser Speckle Image

PubMed Central

El-Ghandoor, Hatem; Kandel, Hamed; El-Azab, Jala; Hassab-Elnaby, Salah

2017-01-01

The application of He-Ne laser technologies for description of articular cartilage degeneration, one of the most common diseases worldwide, is an innovative usage of these technologies used primarily in material engineering. Plain radiography and magnetic resonance imaging are insufficient to allow the early assessment of the disease. As surface roughness of articular cartilage is an important indicator of articular cartilage degeneration progress, a safe and noncontact technique based on laser speckle image to estimate the surface roughness is provided. This speckle image from the articular cartilage surface, when illuminated by laser beam, gives very important information about the physical properties of the surface. An experimental setup using a low power He-Ne laser and a high-resolution digital camera was implemented to obtain speckle images of ten bovine articular cartilage specimens prepared for different average roughness values. Texture analysis method based on gray-level co-occurrence matrix (GLCM) analyzed on the captured speckle images is used to characterize the surface roughness of the specimens depending on the computation of Haralick’s texture features. In conclusion, this promising method can accurately estimate the surface roughness of articular cartilage even for early signs of degeneration. The method is effective for estimation of average surface roughness values ranging from 0.09 µm to 2.51 µm with an accuracy of 0.03 µm. PMID:28773080

Lithological and textural controls on radar and diurnal thermal signatures of weathered volcanic deposits, Lunar Crater region, Nevada

NASA Technical Reports Server (NTRS)

Plaut, Jeffrey J.; Rivard, Benoit

1992-01-01

Radar backscatter intensity as measured by calibrated synthetic aperture radar (SAR) systems is primarily controlled by three factors: local incidence angle, wavelength-scale roughness, and dielectric permittivity of surface materials. Radar observations may be of limited use for geological investigations of surface composition, unless the relationships between lithology and the above characteristics can be adequately understood. In arid terrains, such as the Southwest U.S., weathering signatures (e.g. soil development, fracturing, debris grain size and shape, and hill slope characteristics) are controlled to some extent by lithologic characteristics of the parent bedrock. These textural features of outcrops and their associated debris will affect radar backscatter to varying degrees, and the multiple-wavelength capability of the JPL Airborne SAR (AIRSAR) system allows sampling of textures at three distinct scales. Diurnal temperature excursions of geologic surfaces are controlled primarily by the thermal inertia of surface materials, which is a measure of the resistance of a material to a change in temperature. Other influences include albedo, surface slopes affecting insolation, local meteorological conditions and surface emissivity at the relevant thermal wavelengths. To first order, thermal inertia variations on arid terrain surfaces result from grain size distribution and porosity differences, at scales ranging from micrometers to tens of meters. Diurnal thermal emission observations, such as those made by the JPL Thermal Infrared Multispectral Scanner (TIMS) airborne instrument, are thus influenced by geometric surface characteristics at scales comparable to those controlling radar backscatter. A preliminary report on a project involving a combination of field, laboratory and remote sensing observations of weathered felsic-to basaltic volcanic rock units exposed in the southern part of the Lunar Crater Volcanic Field, in the Pancake Range of central Nevada is presented. Focus is on the relationship of radar backscatter cross sections at multiple wavelengths, apparent diurnal temperature excursions identified in multi-temporal TIMS images, surface geometries related to weathering style, and parent bedrock lithology.

Wetting state and maximum spreading factor of microdroplets impacting on superhydrophobic textured surfaces with anisotropic arrays of pillars

NASA Astrophysics Data System (ADS)

Kwon, Dae Hee; Huh, Hyung Kyu; Lee, Sang Joon

2013-07-01

The dynamic behaviors of microdroplets that impact on textured surfaces with various patterns of microscale pillars are experimentally investigated in this study. A piezoelectric inkjet is used to generate the microdroplets that have a diameter of less than 46 μm and a controlled Weber number. The impact and spreading dynamics of an individual droplet are captured by using a high-speed imaging system. The anisotropic and directional wettability and the wetting states on the textured surfaces with anisotropically arranged pillars are revealed for the first time in this study. The impalement transition from the Cassie-Baxter state to the partially impaled state is evaluated by balancing the wetting pressure P wet and the capillary pressure P C even on the anisotropic textured surfaces. The maximum spreading factor is measured and compared with the theoretical prediction to elucidate the wettability of the textured surfaces. For a given Weber number, the maximum spreading factor decreases as the texture area fraction of the textured surface decreases. In addition, the maximum spreading factors along the direction of longer inter-pillar spacing always have smaller values than those along the direction of shorter inter-pillar spacing when a droplet impacts on the anisotropic arrays of pillars.

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

NASA Astrophysics Data System (ADS)

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

2016-07-01

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

From Pluto Mountains to Its Plains

NASA Image and Video Library

2015-09-24

Images of Pluto taken by NASA New Horizons spacecraft before closest approach on July 14, 2015, reveal features as small as 270 yards (250 meters) across, from craters to faulted mountain blocks, to the textured surface of the vast basin informally called Sputnik Planum. Enhanced color has been added from the global color image. This image is about 330 miles (530 kilometers) across. http://photojournal.jpl.nasa.gov/catalog/PIA19955

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

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

Yang, F; Yang, Y; Young, L

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

Mechanical and chemical effects of ion-texturing biomedical polymers

NASA Technical Reports Server (NTRS)

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

1979-01-01

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

Structural features of resorcinol-formaldehyde resin chars and interfacial behavior of water co-adsorbed with low-molecular weight organics

NASA Astrophysics Data System (ADS)

Gun'ko, Vladimir M.; Bogatyrov, Viktor M.; Turov, Vladimir V.; Leboda, Roman; Skubiszewska-Zięba, Jadwiga; Urubkov, Iliya V.

2013-10-01

Products of resorcinol-formaldehyde resin carbonization (chars) are characterized by different morphology (particle shape and sizes) and texture (specific surface area, pore volume and pore size distribution) depending on water content during resin polymerization. At a low amount of water (Cw = 37.8 wt.%) during synthesis resulting in strongly cross-linked polymers, carbonization gives nonporous particles. An increase in the water content to 62.7 wt.% results in a nano/mesoporous char, but if Cw = 73.3 wt.%, a char is purely nanoporous. Despite these textural differences, the Raman spectra of all the chars are similar because of the similarity in the structure of their carbon sheets with a significant contribution of sp3 C atoms. However, the difference in the spatial organization of the carbon sheet stacks in the particles results in the significant differences in the textural and morphological characteristics and in the adsorption properties of chars with respect to water, methane, benzene, hydrogen, methylene chloride, and dimethylsulfoxide.

Interpreting U-Pb data from primary and secondary features in lunar zircon

NASA Astrophysics Data System (ADS)

Grange, M. L.; Pidgeon, R. T.; Nemchin, A. A.; Timms, N. E.; Meyer, C.

2013-01-01

In this paper, we describe primary and secondary microstructures and textural characteristics found in lunar zircon and discuss the relationships between these features and the zircon U-Pb isotopic systems and the significance of these features for understanding lunar processes. Lunar zircons can be classified according to: (i) textural relationships between zircon and surrounding minerals in the host breccias, (ii) the internal microstructures of the zircon grains as identified by optical microscopy, cathodoluminescence (CL) imaging and electron backscattered diffraction (EBSD) mapping and (iii) results of in situ ion microprobe analyses of the Th-U-Pb isotopic systems. Primary zircon can occur as part of a cogenetic mineral assemblage (lithic clast) or as an individual mineral clast and is unzoned, or has sector and/or oscillatory zoning. The age of primary zircon is obtained when multiple ion microprobe analyses across the polished surface of the grain give reproducible and essentially concordant data. A secondary set of microstructures, superimposed on primary zircon, include localised recrystallised domains, localised amorphous domains, crystal-plastic deformation, planar deformation features and fractures, and are associated with impact processes. The first two secondary microstructures often yield internally consistent and close to concordant U-Pb ages that we interpret as dating impact events. Others secondary microstructures such as planar deformation features, crystal-plastic deformation and micro-fractures can provide channels for Pb diffusion and result in partial resetting of the U-Pb isotopic systems.

Ice Volcanoes on Pluto?

NASA Image and Video Library

2015-11-10

NASA New Horizons scientists believe that the informally named feature Wright Mons, located south of Sputnik Planum on Pluto, and another, Piccard Mons, could have been formed by the cryovolcanic eruption of ices from beneath Pluto surface. Sputnik Planum on Pluto, is an unusual feature that's about 100 miles (160 kilometers) wide and 13,000 feet (4 kilometers) high. It displays a summit depression (visible in the center of the image) that's approximately 35 miles (56 kilometers) across, with a distinctive hummocky texture on its sides. The rim of the summit depression also shows concentric fracturing. http://photojournal.jpl.nasa.gov/catalog/PIA20155

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

PubMed

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

Use of structured surfaces for friction and wear control on bearing surfaces

NASA Astrophysics Data System (ADS)

Wang, Ling

2014-10-01

Surface texturing with purposely made regular micropatterns on flat or curved surfaces, as opposed to random roughness inherited from machining processes, has attracted significant attention in recent years. At the 2013 World Tribology Congress in Turin alone there were over 40 presentations related to surface texturing for tribological applications, from magnetic hard discs and hydrodynamic bearings to artificial joints. Although surface texturing has been reported being successfully applied in industrial applications such as seals, pistons, and thrust pad bearings, the demand for robust design is still high. Etsion has recently reviewed the modeling research mainly conducted by his group Etsion I (2013 Friction 1 195-209). This paper aims to review the state-of-the-art development of surface texturing made by a wider range of researchers.

Poor textural image tie point matching via graph theory

NASA Astrophysics Data System (ADS)

Yuan, Xiuxiao; Chen, Shiyu; Yuan, Wei; Cai, Yang

2017-07-01

Feature matching aims to find corresponding points to serve as tie points between images. Robust matching is still a challenging task when input images are characterized by low contrast or contain repetitive patterns, occlusions, or homogeneous textures. In this paper, a novel feature matching algorithm based on graph theory is proposed. This algorithm integrates both geometric and radiometric constraints into an edge-weighted (EW) affinity tensor. Tie points are then obtained by high-order graph matching. Four pairs of poor textural images covering forests, deserts, bare lands, and urban areas are tested. For comparison, three state-of-the-art matching techniques, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), and features from accelerated segment test (FAST), are also used. The experimental results show that the matching recall obtained by SIFT, SURF, and FAST varies from 0 to 35% in different types of poor textures. However, through the integration of both geometry and radiometry and the EW strategy, the recall obtained by the proposed algorithm is better than 50% in all four image pairs. The better matching recall improves the number of correct matches, dispersion, and positional accuracy.

Image-Based 3D Face Modeling System

NASA Astrophysics Data System (ADS)

Park, In Kyu; Zhang, Hui; Vezhnevets, Vladimir

2005-12-01

This paper describes an automatic system for 3D face modeling using frontal and profile images taken by an ordinary digital camera. The system consists of four subsystems including frontal feature detection, profile feature detection, shape deformation, and texture generation modules. The frontal and profile feature detection modules automatically extract the facial parts such as the eye, nose, mouth, and ear. The shape deformation module utilizes the detected features to deform the generic head mesh model such that the deformed model coincides with the detected features. A texture is created by combining the facial textures augmented from the input images and the synthesized texture and mapped onto the deformed generic head model. This paper provides a practical system for 3D face modeling, which is highly automated by aggregating, customizing, and optimizing a bunch of individual computer vision algorithms. The experimental results show a highly automated process of modeling, which is sufficiently robust to various imaging conditions. The whole model creation including all the optional manual corrections takes only 2[InlineEquation not available: see fulltext.]3 minutes.

3D Texture Analysis in Renal Cell Carcinoma Tissue Image Grading

PubMed Central

Cho, Nam-Hoon; Choi, Heung-Kook

2014-01-01

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

Automatic segmentation of low-visibility moving objects through energy analyis of the local 3D spectrum

NASA Astrophysics Data System (ADS)

Nestares, Oscar; Miravet, Carlos; Santamaria, Javier; Fonolla Navarro, Rafael

1999-05-01

Automatic object segmentation in highly noisy image sequences, composed by a translating object over a background having a different motion, is achieved through joint motion-texture analysis. Local motion and/or texture is characterized by the energy of the local spatio-temporal spectrum, as different textures undergoing different translational motions display distinctive features in their 3D (x,y,t) spectra. Measurements of local spectrum energy are obtained using a bank of directional 3rd order Gaussian derivative filters in a multiresolution pyramid in space- time (10 directions, 3 resolution levels). These 30 energy measurements form a feature vector describing texture-motion for every pixel in the sequence. To improve discrimination capability and reduce computational cost, we automatically select those 4 features (channels) that best discriminate object from background, under the assumptions that the object is smaller than the background and has a different velocity or texture. In this way we reject features irrelevant or dominated by noise, that could yield wrong segmentation results. This method has been successfully applied to sequences with extremely low visibility and for objects that are even invisible for the eye in absence of motion.

Textured-surface quartz resonator fluid density and viscosity monitor

DOEpatents

Martin, Stephen J.; Wiczer, James J.; Cernosek, Richard W.; Frye, Gregory C.; Gebert, Charles T.; Casaus, Leonard; Mitchell, Mary A.

1998-08-25

A pair of thickness-shear mode resonators, one smooth and one with a textured surface, allows fluid density and viscosity to be independently resolved. A textured surface, either randomly rough or regularly patterned, leads to trapping of liquid at the device surface. The synchronous motion of this trapped liquid with the oscillating device surface allows the device to weigh the liquid; this leads to an additional response that depends on liquid density. This additional response enables a pair of devices, one smooth and one textured, to independently resolve liquid density and viscosity; the difference in responses determines the density while the smooth device determines the density-viscosity product, and thus, the pair determines both density and viscosity.

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

DOT National Transportation Integrated Search

1975-01-01

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

Effects of Textured Insoles on Balance in People with Parkinson’s Disease

PubMed Central

Qiu, Feng; Cole, Michael H.; Davids, Keith W.; Hennig, Ewald M.; Silburn, Peter A.; Netscher, Heather; Kerr, Graham K.

2013-01-01

Background Degradation of the somatosensory system has been implicated in postural instability and increased falls risk for older people and Parkinson’s disease (PD) patients. Here we demonstrate that textured insoles provide a passive intervention that is an inexpensive and accessible means to enhance the somatosensory input from the plantar surface of the feet. Methods 20 healthy older adults (controls) and 20 participants with PD were recruited for the study. We evaluated effects of manipulating somatosensory information from the plantar surface of the feet using textured insoles. Participants performed standing tests, on two different surfaces (firm and foam), under three footwear conditions: 1) barefoot; 2) smooth insoles; and 3) textured insoles. Standing balance was evaluated using a force plate yielding data on the range of anterior-posterior and medial-lateral sway, as well as standard deviations for anterior-posterior and medial-lateral sway. Results On the firm surface with eyes open both the smooth and textured insoles reduced medial-lateral sway in the PD group to a similar level as the controls. Only the textured insole decreased medial-lateral sway and medial-lateral sway standard deviation in the PD group on both surfaces, with and without visual input. Greatest benefits were observed in the PD group while wearing the textured insoles, and when standing on the foam surface with eyes closed. Conclusions Data suggested that textured insoles may provide a low-cost means of improving postural stability in high falls-risk groups, such as people with PD. PMID:24349486

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)

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

Yip, S; Aerts, H; Berbeco, R

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. Wilcoxonmore » 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 quantification can be obtained from all phases. Texture features, blurred out by respiratory motion during 3D-PET acquisition, can be better resolved by 4D-PET imaging with any phase.« less

Comparison of Texture Features Used for Classification of Life Stages of Malaria Parasite.

PubMed

Bairagi, Vinayak K; Charpe, Kshipra C

2016-01-01

Malaria is a vector borne disease widely occurring at equatorial region. Even after decades of campaigning of malaria control, still today it is high mortality causing disease due to improper and late diagnosis. To prevent number of people getting affected by malaria, the diagnosis should be in early stage and accurate. This paper presents an automatic method for diagnosis of malaria parasite in the blood images. Image processing techniques are used for diagnosis of malaria parasite and to detect their stages. The diagnosis of parasite stages is done using features like statistical features and textural features of malaria parasite in blood images. This paper gives a comparison of the textural based features individually used and used in group together. The comparison is made by considering the accuracy, sensitivity, and specificity of the features for the same images in database.

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

Ranjanomennahary, P.; Ghalila, S. Sevestre; Malouche, D

Purpose: Hip fracture is a serious health problem and textural methods are being developed to assess bone quality. The authors aimed to perform textural analysis at femur on high-resolution digital radiographs compared to three-dimensional (3D) microarchitecture comparatively to bone mineral density. Methods: Sixteen cadaveric femurs were imaged with an x-ray device using a C-MOS sensor. One 17 mm square region of interest (ROI) was selected in the femoral head (FH) and one in the great trochanter (GT). Two-dimensional (2D) textural features from the co-occurrence matrices were extracted. Site-matched measurements of bone mineral density were performed. Inside each ROI, a 16more » mm diameter core was extracted. Apparent density (D{sub app}) and bone volume proportion (BV/TV{sub Arch}) were measured from a defatted bone core using Archimedes' principle. Microcomputed tomography images of the entire length of the core were obtained (Skyscan 1072) at 19.8 {mu}m of resolution and usual 3D morphometric parameters were computed on the binary volume after calibration from BV/TV{sub Arch}. Then, bone surface/bone volume, trabecular thickness, trabecular separation, and trabecular number were obtained by direct methods without model assumption and the structure model index was calculated. Results: In univariate analysis, the correlation coefficients between 2D textural features and 3D morphological parameters reached 0.83 at the FH and 0.79 at the GT. In multivariate canonical correlation analysis, coefficients of the first component reached 0.95 at the FH and 0.88 at the GT. Conclusions: Digital radiographs, widely available and economically viable, are an alternative method for evaluating bone microarchitectural structure.« less

Magnetorheological finishing with chemically modified fluids for studying material removal of single-crystal ZnS

NASA Astrophysics Data System (ADS)

Salzman, S.; Romanofsky, H. J.; Clara, Y. I.; Giannechini, L. J.; West, Garrett J.; Lambropoulos, J. C.; Jacobs, S. D.

2013-09-01

Magnetorheological finishing (MRF) of polycrystalline, chemical-vapor-deposited (CVD) zinc sulfide (ZnS) and zinc selenide (ZnSe) can leave millimeter-size artifacts on the part surface. These pebble-like features come from the anisotropic mechanical and chemical properties of the ceramic material and from the CVD growth process itself. The resulting surface texture limits the use of MRF for polishing aspheric and other complex shapes using these important infrared (IR) ceramics. An investigation of the individual contributions of chemistry and mechanics to polishing of other polycrystalline ceramics has been employed in the past to overcome similar material anisotropy problems. The approach taken was to study the removal process for the different single-crystal orientations that comprise the ceramic, making adjustments to mechanics (polishing abrasive type and concentration) and polishing slurry chemistry (primarily pH) to equalize the removal rate for all crystal orientations. Polishing with the modified slurry was shown to prevent the development of surface texture. Here we present mechanical (microhardness testing) and chemical (acid etching) studies performed on the four single-crystal orientations of ZnS: 100, 110, 111, and 311. We found that the (111) plane is 35% to 55% harder and 30% to 40% more resistant to chemical etching than the other three planes. This relatively high degree of variation in these properties can help to explain the surface texture developed from MRF of the polycrystalline material. Theoretical calculations of microhardness, planar, and bond densities are presented and compared with the experimental data. Here surface characterization of these single-crystal orientations of ZnS for material removal and roughness with chemically modified MR fluids at various pH levels between pH 4 and pH 6 are presented for the first time.

Automated Array Assembly, Phase 2

NASA Technical Reports Server (NTRS)

Carbajal, B. G.

1979-01-01

The solar cell module process development activities in the areas of surface preparation are presented. The process step development was carried out on texture etching including the evolution of a conceptual process model for the texturing process; plasma etching; and diffusion studies that focused on doped polymer diffusion sources. Cell processing was carried out to test process steps and a simplified diode solar cell process was developed. Cell processing was also run to fabricate square cells to populate sample minimodules. Module fabrication featured the demonstration of a porcelainized steel glass structure that should exceed the 20 year life goal of the low cost silicon array program. High efficiency cell development was carried out in the development of the tandem junction cell and a modification of the TJC called the front surface field cell. Cell efficiencies in excess of 16 percent at AM1 have been attained with only modest fill factors. The transistor-like model was proposed that fits the cell performance and provides a guideline for future improvements in cell performance.

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

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

Texture analysis of pulmonary parenchyma in normal and emphysematous lung

NASA Astrophysics Data System (ADS)

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

1996-04-01

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

Nanometer-scale features in dolomite from Pennsylvanian rocks, Paradox Basin, Utah

NASA Astrophysics Data System (ADS)

Gournay, Jonas P.; Kirkland, Brenda L.; Folk, Robert L.; Lynch, F. Leo

1999-07-01

Scanning electron microscopy reveals an association between early dolomite in the Pennsylvanian Desert Creek (Paradox Fm.) and small (approximately 0.1 μm) nanometer-scale textures, termed `nannobacteria'. Three diagenetically distinct dolomites are present: early dolomite, limpid dolomite, and baroque dolomite. In this study, only the early dolomite contained nanometer-scale features. These textures occur as discrete balls and rods, clumps of balls, and chains of balls. Precipitation experiments demonstrate that these textures may be the result of precipitation in an organic-rich micro-environment. The presence of these nanometer-scale textures in Pennsylvanian rocks suggests that these early dolomites precipitated in organic-rich, bacterial environments.

Prostate cancer detection: Fusion of cytological and textural features.

PubMed

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.

Prostate cancer detection: Fusion of cytological and textural features

PubMed Central

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. PMID:22811959

Geologic interpretation of Seasat SAR imagery near the Rio Lacantum, Mexico

NASA Technical Reports Server (NTRS)

Rebillard, PH.; Dixon, T.

1984-01-01

A mosaic of the Seasat Synthetic Aperture Radar (SAR) optically processed images over Central America is presented. A SAR image of the Rio Lacantum area (southeastern Mexico) has been digitally processed and its interpretation is presented. The region is characterized by low relief and a dense vegetation canopy. Surface is believed to be indicative of subsurface structural features. The Seasat-SAR system had a steep imaging geometry (incidence angle 23 + or - 3 deg off-nadir) which is favorable for detection of subtle topographic variations. Subtle textural features in the image corresponding to surface topography were enhanced by image processing techniques. A structural and lithologic interpretation of the processed images is presented. Lineaments oriented NE-SW dominate and intersect broad folds trending NW-SE. Distinctive karst topography characterizes one high relief area

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

NASA Astrophysics Data System (ADS)

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

2001-06-01

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

Skin cancer texture analysis of OCT images based on Haralick, fractal dimension, Markov random field features, and the complex directional field features

NASA Astrophysics Data System (ADS)

Raupov, Dmitry S.; Myakinin, Oleg O.; Bratchenko, Ivan A.; Zakharov, Valery P.; Khramov, Alexander G.

2016-10-01

In this paper, we propose a report about our examining of the validity of OCT in identifying changes using a skin cancer texture analysis compiled from Haralick texture features, fractal dimension, Markov random field method and the complex directional features from different tissues. Described features have been used to detect specific spatial characteristics, which can differentiate healthy tissue from diverse skin cancers in cross-section OCT images (B- and/or C-scans). In this work, we used an interval type-II fuzzy anisotropic diffusion algorithm for speckle noise reduction in OCT images. The Haralick texture features as contrast, correlation, energy, and homogeneity have been calculated in various directions. A box-counting method is performed to evaluate fractal dimension of skin probes. Markov random field have been used for the quality enhancing of the classifying. Additionally, we used the complex directional field calculated by the local gradient methodology to increase of the assessment quality of the diagnosis method. Our results demonstrate that these texture features may present helpful information to discriminate tumor from healthy tissue. The experimental data set contains 488 OCT-images with normal skin and tumors as Basal Cell Carcinoma (BCC), Malignant Melanoma (MM) and Nevus. All images were acquired from our laboratory SD-OCT setup based on broadband light source, delivering an output power of 20 mW at the central wavelength of 840 nm with a bandwidth of 25 nm. We obtained sensitivity about 97% and specificity about 73% for a task of discrimination between MM and Nevus.

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

PubMed

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

2017-12-01

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

Distinct cognitive mechanisms involved in the processing of single objects and object ensembles

PubMed Central

Cant, Jonathan S.; Sun, Sol Z.; Xu, Yaoda

2015-01-01

Behavioral research has demonstrated that the shape and texture of single objects can be processed independently. Similarly, neuroimaging results have shown that an object's shape and texture are processed in distinct brain regions with shape in the lateral occipital area and texture in parahippocampal cortex. Meanwhile, objects are not always seen in isolation and are often grouped together as an ensemble. We recently showed that the processing of ensembles also involves parahippocampal cortex and that the shape and texture of ensemble elements are processed together within this region. These neural data suggest that the independence seen between shape and texture in single-object perception would not be observed in object-ensemble perception. Here we tested this prediction by examining whether observers could attend to the shape of ensemble elements while ignoring changes in an unattended texture feature and vice versa. Across six behavioral experiments, we replicated previous findings of independence between shape and texture in single-object perception. In contrast, we observed that changes in an unattended ensemble feature negatively impacted the processing of an attended ensemble feature only when ensemble features were attended globally. When they were attended locally, thereby making ensemble processing similar to single-object processing, interference was abolished. Overall, these findings confirm previous neuroimaging results and suggest that distinct cognitive mechanisms may be involved in single-object and object-ensemble perception. Additionally, they show that the scope of visual attention plays a critical role in determining which type of object processing (ensemble or single object) is engaged by the visual system. PMID:26360156

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

NASA Astrophysics Data System (ADS)

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 observed for pebble and iron oxide resulting from the intrinsic ambiguity between these categories and the basalt cobble class. The second scenario classified strata in the exposed layers of a younger lava flow incised by a channel. The instrument classified the section into five layers: the channel bed, sorted volcanic gravel, gravel in a clay matrix, oxidized clay, and massive blocks. Performance was poor (<30% true positives) for the massive block class, since this material was often covered by clay very similar to the matrix below. We disregarded this top layer. The performance on the remaining layers of the column was better than 95%, a level that would significantly improve autonomous targeting with respect to random sampling. Future development will continue to refine the classification algorithms as well as the speed of the data processing hardware. Acknowledgements: The TextureCam project is supported by the NASA Astrobiology Science and Technology Instrument Development program (NNH10ZDA001N-ASTID) and National Park Service permit MOJA-2013-SCI-0011. This work was carried out at the Jet Propulsion Laboratory, California Institute of Technology under a contract with the National Aeronautics and Space Administration. Copyright 2013, California Institute of Technology.

Texture-based approach to palmprint retrieval for personal identification

NASA Astrophysics Data System (ADS)

Li, Wenxin; Zhang, David; Xu, Z.; You, J.

2000-12-01

This paper presents a new approach to palmprint retrieval for personal identification. Three key issues in image retrieval are considered - feature selection, similarity measures and dynamic search for the best matching of the sample in the image database. We propose a texture-based method for palmprint feature representation. The concept of texture energy is introduced to define a palm print's global and local features, which are characterized with high convergence of inner-palm similarities and good dispersion of inter-palm discrimination. The search is carried out in a layered fashion: first global features are used to guide the fast selection of a small set of similar candidates from the database from the database and then local features are used to decide the final output within the candidate set. The experimental results demonstrate the effectiveness and accuracy of the proposed method.

Texture-based approach to palmprint retrieval for personal identification

NASA Astrophysics Data System (ADS)

Li, Wenxin; Zhang, David; Xu, Z.; You, J.

2001-01-01

This paper presents a new approach to palmprint retrieval for personal identification. Three key issues in image retrieval are considered - feature selection, similarity measures and dynamic search for the best matching of the sample in the image database. We propose a texture-based method for palmprint feature representation. The concept of texture energy is introduced to define a palm print's global and local features, which are characterized with high convergence of inner-palm similarities and good dispersion of inter-palm discrimination. The search is carried out in a layered fashion: first global features are used to guide the fast selection of a small set of similar candidates from the database from the database and then local features are used to decide the final output within the candidate set. The experimental results demonstrate the effectiveness and accuracy of the proposed method.

BCC skin cancer diagnosis based on texture analysis techniques

NASA Astrophysics Data System (ADS)

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

2011-03-01

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

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

NASA Astrophysics Data System (ADS)

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.

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

NASA Astrophysics Data System (ADS)

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.

Doped Y.sub.2O.sub.3 buffer layers for laminated conductors

DOEpatents

Paranthaman, Mariappan Parans [Knoxville, TN; Schoop, Urs [Westborough, MA; Goyal, Amit [Knoxville, TN; Thieme, Cornelis Leo Hans [Westborough, MA; Verebelyi, Darren T [Oxford, MA; Rupich, Martin W [Framingham, MA

2007-08-21

A laminated conductor includes a metallic substrate having a surface, a biaxially textured buffer layer supported by the surface of the metallic substrate, the biaxially textured buffer layer comprising Y.sub.2O.sub.3 and a dopant for blocking cation diffusion through the Y.sub.2O.sub.3, and a biaxially textured conductor layer supported by the biaxially textured buffer layer.

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

Sorensen, J; Duran, C; Stingo, F

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 Levelmore » 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 able to reliably differentiate between most tissues types regardless of energy level. Dr Godoy has received a dual-energy CT research grant from Siemens Healthcare. That grant did not directly fund this research.« less

Multi-Feature Classification of Multi-Sensor Satellite Imagery Based on Dual-Polarimetric Sentinel-1A, Landsat-8 OLI, and Hyperion Images for Urban Land-Cover Classification

PubMed Central

Pan, Jianjun

2018-01-01

This paper focuses on evaluating the ability and contribution of using backscatter intensity, texture, coherence, and color features extracted from Sentinel-1A data for urban land cover classification and comparing different multi-sensor land cover mapping methods to improve classification accuracy. Both Landsat-8 OLI and Hyperion images were also acquired, in combination with Sentinel-1A data, to explore the potential of different multi-sensor urban land cover mapping methods to improve classification accuracy. The classification was performed using a random forest (RF) method. The results showed that the optimal window size of the combination of all texture features was 9 × 9, and the optimal window size was different for each individual texture feature. For the four different feature types, the texture features contributed the most to the classification, followed by the coherence and backscatter intensity features; and the color features had the least impact on the urban land cover classification. Satisfactory classification results can be obtained using only the combination of texture and coherence features, with an overall accuracy up to 91.55% and a kappa coefficient up to 0.8935, respectively. Among all combinations of Sentinel-1A-derived features, the combination of the four features had the best classification result. Multi-sensor urban land cover mapping obtained higher classification accuracy. The combination of Sentinel-1A and Hyperion data achieved higher classification accuracy compared to the combination of Sentinel-1A and Landsat-8 OLI images, with an overall accuracy of up to 99.12% and a kappa coefficient up to 0.9889. When Sentinel-1A data was added to Hyperion images, the overall accuracy and kappa coefficient were increased by 4.01% and 0.0519, respectively. PMID:29382073

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

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

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

Anthony, G; Cunliffe, A; Armato, S

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 valuesmore » 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 more accurate prediction of RP using information from multiple imaging modalities. Supported, in part, by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health under grant number T32 EB002103; SGA receives royalties and licensing fees through the University of Chicago for computer-aided diagnosis technology. HA receives royalties through the University of Chicago for computer-aided diagnosis technology.« less

Systems and Methods of Laser Texturing of Material Surfaces and Their Applications

NASA Technical Reports Server (NTRS)

Gupta, Mool C. (Inventor); Nayak, Barada K. (Inventor)

2014-01-01

The surface of a material is textured and by exposing the surface to pulses from an ultrafast laser. The laser treatment causes pillars to form on the treated surface. These pillars provide for greater light absorption. Texturing and crystallization can be carried out as a single step process. The crystallization of the material provides for higher electric conductivity and changes in optical and electronic properties of the material. The method may be performed in vacuum or a gaseous environment. The gaseous environment may aid in texturing and/or modifying physical and chemical properties of the surfaces. This method may be used on various material surfaces, such as semiconductors, metals and their alloys, ceramics, polymers, glasses, composites, as well as crystalline, nanocrystalline, polycrystalline, microcrystalline, and amorphous phases.

Full-gap superconductivity in spin-polarised surface states of topological semimetal β-PdBi2.

PubMed

Iwaya, K; Kohsaka, Y; Okawa, K; Machida, T; Bahramy, M S; Hanaguri, T; Sasagawa, T

2017-10-17

A bulk superconductor possessing a topological surface state at the Fermi level is a promising system to realise long-sought topological superconductivity. Although several candidate materials have been proposed, experimental demonstrations concurrently exploring spin textures and superconductivity at the surface have remained elusive. Here we perform spectroscopic-imaging scanning tunnelling microscopy on the centrosymmetric superconductor β-PdBi 2 that hosts a topological surface state. By combining first-principles electronic-structure calculations and quasiparticle interference experiments, we determine the spin textures at the surface, and show not only the topological surface state but also all other surface bands exhibit spin polarisations parallel to the surface. We find that the superconducting gap fully opens in all the spin-polarised surface states. This behaviour is consistent with a possible spin-triplet order parameter expected for such in-plane spin textures, but the observed superconducting gap amplitude is comparable to that of the bulk, suggesting that the spin-singlet component is predominant in β-PdBi 2 .Although several materials have been proposed as topological superconductors, spin textures and superconductivity at the surface remain elusive. Here, Iwaya et al. determine the spin textures at the surface of a superconductor β-PdBi 2 and find the superconducting gap opening in all spin-polarised surface states.

Convolutional neural network approach for enhanced capture of breast parenchymal complexity patterns associated with breast cancer risk

NASA Astrophysics Data System (ADS)

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

2017-03-01

We assess the feasibility of a parenchymal texture feature fusion approach, utilizing a convolutional neural network (ConvNet) architecture, to benefit breast cancer risk assessment. Hypothesizing that by capturing sparse, subtle interactions between localized motifs present in two-dimensional texture feature maps derived from mammographic images, a multitude of texture feature descriptors can be optimally reduced to five meta-features capable of serving as a basis on which a linear classifier, such as logistic regression, can efficiently assess breast cancer risk. We combine this methodology with our previously validated lattice-based strategy for parenchymal texture analysis and we evaluate the feasibility of this approach in a case-control study with 424 digital mammograms. In a randomized split-sample setting, we optimize our framework in training/validation sets (N=300) and evaluate its descriminatory performance in an independent test set (N=124). The discriminatory capacity is assessed in terms of the the area under the curve (AUC) of the receiver operator characteristic (ROC). The resulting meta-features exhibited strong classification capability in the test dataset (AUC = 0.90), outperforming conventional, non-fused, texture analysis which previously resulted in an AUC=0.85 on the same case-control dataset. Our results suggest that informative interactions between localized motifs exist and can be extracted and summarized via a fairly simple ConvNet architecture.

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

NASA Astrophysics Data System (ADS)

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

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

NASA Astrophysics Data System (ADS)

Książek, Judyta

2015-10-01

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

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

NASA Technical Reports Server (NTRS)

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).

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Vibratory tactile display for textures

NASA Technical Reports Server (NTRS)

Ikei, Yasushi; Ikeno, Akihisa; Fukuda, Shuichi

1994-01-01

We have developed a tactile display that produces vibratory stimulus to a fingertip in contact with a vibrating tactor matrix. The display depicts tactile surface textures while the user is exploring a virtual object surface. A piezoelectric actuator drives the individual tactor in accordance with both the finger movement and the surface texture being traced. Spatiotemporal display control schemes were examined for presenting the fundamental surface texture elements. The temporal duration of vibratory stimulus was experimentally optimized to simulate the adaptation process of cutaneous sensation. The selected duration time for presenting a single line edge agreed with the time threshold of tactile sensation. Then spatial stimulus disposition schemes were discussed for representation of other edge shapes. As an alternative means not relying on amplitude control, a method of augmented duration at the edge was investigated. Spatial resolution of the display was measured for the lines presented both in perpendicular and parallel to a finger axis. Discrimination of texture density was also measured on random dot textures.

Fabrication of multi-functional silicon surface by direct laser writing

NASA Astrophysics Data System (ADS)

Verma, Ashwani Kumar; Soni, R. K.

2018-05-01

We present a simple, quick and one-step methodology based on nano-second laser direct writing for the fabrication of micro-nanostructures on silicon surface. The fabricated surfaces suppress the optical reflection by multiple reflection due to light trapping effect to a much lower value than polished silicon surface. These textured surfaces offer high enhancement ability after gold nanoparticle deposition and then explored for Surface Enhanced Raman Scattering (SERS) for specific molecular detection. The effect of laser scanning line interval on optical reflection and SERS signal enhancement ability was also investigated. Our results indicate that low optical reflection substrates exhibit uniform SERS enhancement with enhancement factor of the order of 106. Furthermore, this methodology provide an alternative approach for cost-effective large area fabrication with good control over feature size.

Power spectral ensity of markov texture fields

NASA Technical Reports Server (NTRS)

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

1984-01-01

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

Effects of anisotropic surface texture on the performance of ionic polymer-metal composite (IPMC)

NASA Astrophysics Data System (ADS)

He, Qingsong; Yu, Min; Ding, Haitao; Guo, Dongjie; Dai, Zhendong

2010-04-01

Ionic polymer metal composite (IPMC), an electrically activated polymer (EAP), has attracted great attention for the excellent properties such as large deformation, light weight, low noise, flexibility and low driving voltages, which makes the material a possible application as artificial muscle if the output force can be increased. To improve the property, we manufactured the Nafion membrane by casting from liquid solution, modified the surface by sandblasting or polishing, and obtained the isotropic and anisotropic surface texture respectively. The microstructure of the Nafion surface and metal electrode, effects of surface texture on the output force and displacement of IPMC were studied. Results show that the output force of IPMC with the anisotropic surface texture is 2~4 times higher than that with the isotropic surface texture without enormous sacrifice of the displacement. The output force may reach to 6.63gf (Sinusoidal 3.5V and 0.1Hz, length 20mm, width 5mm and thickness 0.66mm), which suggest an effective way to improve the mechanical properties of IPMC.

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

PubMed Central

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

2012-01-01

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

Uniform Local Binary Pattern Based Texture-Edge Feature for 3D Human Behavior Recognition.

PubMed

Ming, Yue; Wang, Guangchao; Fan, Chunxiao

2015-01-01

With the rapid development of 3D somatosensory technology, human behavior recognition has become an important research field. Human behavior feature analysis has evolved from traditional 2D features to 3D features. In order to improve the performance of human activity recognition, a human behavior recognition method is proposed, which is based on a hybrid texture-edge local pattern coding feature extraction and integration of RGB and depth videos information. The paper mainly focuses on background subtraction on RGB and depth video sequences of behaviors, extracting and integrating historical images of the behavior outlines, feature extraction and classification. The new method of 3D human behavior recognition has achieved the rapid and efficient recognition of behavior videos. A large number of experiments show that the proposed method has faster speed and higher recognition rate. The recognition method has good robustness for different environmental colors, lightings and other factors. Meanwhile, the feature of mixed texture-edge uniform local binary pattern can be used in most 3D behavior recognition.

Secondary electron emission characteristics of ion-textured copper and high-purity isotropic graphite surfaces

NASA Technical Reports Server (NTRS)

Curren, A. N.; Jensen, K. A.

1984-01-01

Experimentally determined values of true secondary electron emission and relative values of reflected primary electron yield for untreated and ion textured oxygen free high conductivity copper and untreated and ion textured high purity isotropic graphite surfaces are presented for a range of primary electron beam energies and beam impingement angles. This investigation was conducted to provide information that would improve the efficiency of multistage depressed collectors (MDC's) for microwave amplifier traveling wave tubes in space communications and aircraft applications. For high efficiency, MDC electrode surfaces must have low secondary electron emission characteristics. Although copper is a commonly used material for MDC electrodes, it exhibits relatively high levels of secondary electron emission if its surface is not treated for emission control. Recent studies demonstrated that high purity isotropic graphite is a promising material for MDC electrodes, particularly with ion textured surfaces. The materials were tested at primary electron beam energies of 200 to 2000 eV and at direct (0 deg) to near grazing (85 deg) beam impingement angles. True secondary electron emission and relative reflected primary electron yield characteristics of the ion textured surfaces were compared with each other and with those of untreated surfaces of the same materials. Both the untreated and ion textured graphite surfaces and the ion treated copper surface exhibited sharply reduced secondary electron emission characteristics relative to those of untreated copper. The ion treated graphite surface yielded the lowest emission levels.

Optical and electrical properties of ion beam textured Kapton and Teflon

NASA Technical Reports Server (NTRS)

Mirtich, M. J.; Sovey, J. S.

1977-01-01

Results are given for ion beam texturing of polyimide (Kapton) and fluorinated ethylene propylene (Teflon) by means of a 30-cm diam electron bombardment argon ion source. Ion beam-textured Kapton and Teflon surfaces are evaluated for various beam energies, current densities, and exposure times. The optical properties and sheet resistance are measured after each exposure. Provided in the paper are optical spectral data, resistivity measurements, calculated absorptance and emittance measurements, and surface structure SEM micrographs for various exposures to argon ions. It is found that Kapton becomes conducting and Teflon nonconducting when ion beam-textured. Textured Kapton exhibits large changes in the transmittance and solar absorptance, but only slight changes in reflectance. Surface texturing of Teflon may allow better adherence of subsequent sputtered metallic films for a high absorptance value. The results are valuable in spacecraft charging applications.

Texturization of as-cut p-type monocrystalline silicon wafer using different wet chemical solutions

NASA Astrophysics Data System (ADS)

Hashmi, Galib; Hasanuzzaman, Muhammad; Basher, Mohammad Khairul; Hoq, Mahbubul; Rahman, Md. Habibur

2018-06-01

Implementing texturization process on the monocrystalline silicon substrate reduces reflection and enhances light absorption of the substrate. Thus texturization is one of the key elements to increase the efficiency of solar cell. Considering as-cut monocrystalline silicon wafer as base substrate, in this work different concentrations of Na2CO3 and NaHCO3 solution, KOH-IPA (isopropyl alcohol) solution and tetramethylammonium hydroxide solution with different time intervals have been investigated for texturization process. Furthermore, saw damage removal process was conducted with 10% NaOH solution, 20 wt% KOH-13.33 wt% IPA solution and HF/nitric/acetic acid solution. The surface morphology of saw damage, saw damage removed surface and textured wafer were observed using optical microscope and field emission scanning electron microscopy. Texturization causes pyramidal micro structures on the surface of (100) oriented monocrystalline silicon wafer. The height of the pyramid on the silicon surface varies from 1.5 to 3.2 µm and the inclined planes of the pyramids are acute angle. Contact angle value indicates that the textured wafer's surface fall in between near-hydrophobic to hydrophobic range. With respect to base material absolute reflectance 1.049-0.75% within 250-800 nm wavelength region, 0.1-0.026% has been achieved within the same wavelength region when textured with 0.76 wt% KOH-4 wt% IPA solution for 20 min. Furthermore, an alternative route of using 1 wt% Na2CO3-0.2 wt% NaHCO3 solution for 50 min has been exploited in the texturization process.

Welcome to Surface Topography: Metrology and Properties

NASA Astrophysics Data System (ADS)

Leach, Richard

2013-11-01

I am delighted to welcome readers to this inaugural issue of Surface Topography: Metrology and Properties (STMP). In these days of citation indexes and academic reviews, it is a tough, and maybe a brave, job to start a new journal. But the subject area has never been more active and we are seeing genuine breakthroughs in the use of surfaces to control functional performance. Most manufactured parts rely on some form of control of their surface characteristics. The surface is usually defined as that feature on a component or device, which interacts with either the environment in which it is housed (or in which the device operates), or with another surface. The surface topography and material characteristics of a part can affect how fluids interact with it, how the part looks and feels and how two bearing parts will slide together. The need to control, and hence measure, surface features is becoming increasingly important as we move into a miniaturized world. Surface features can become the dominant functional features of a part and may become large in comparison to the overall size of an object. Research into surface texture measurement and characterization has been carried out for over a century and is now more active than ever, especially as new areal surface texture specification standards begin to be introduced. The range of disciplines for which the function of a surface relates to its topography is very diverse; from metal sheet manufacturing to art restoration, from plastic electronics to forensics. Until now, there has been no obvious publishing venue to bring together all these applications with the underlying research and theory, or to unite those working in academia with engineering and industry. Hence the creation of Surface Topography: Metrology and Properties . STMP will publish the best work being done across this broad discipline in one journal, helping researchers to share common themes and highlighting and promoting the extraordinary benefits this field yields across an array of applications in the modern world. To this end, we have gathered leading experts from across our scope to form our inaugural editorial board. Their broad subject knowledge and experience will help to guide the journal and ensure we meet our goal of high-quality research, published quickly, across the breadth of the subject. We are committed to providing a rapid and yet rigorous peer review process. As a launch promotion, all STMP's published content will be free to readers during 2013. The editorial board and I hope you will be as excited by the possibilities of this new journal as we are, and that you will choose to both submit your research and read STMP in the months and years to come. We look forward to reading your papers!

Ganymede and Callisto - Surface textural dichotomies and photometric analysis

NASA Technical Reports Server (NTRS)

Buratti, Bonnie J.

1991-01-01

Complete solar phase curves of the Ganymede and Callisto leading and trailing hemispheres, which have been obtained by reducing Voyager imaging observations and combining them with ground-based telescopic data, are presently fit to scattering models in order to derive hemispherical values of the single scattering albedo, the single particle phase function (SPPF), the compaction state (CS) of the optically active portion of the regolith, and the mean slope angle of macroscopic features. While Callisto's leading side is composed of particles that are more strongly backscattering than the trailing side, no hemispheric differences are found in the CS, surface roughness, or SPPF.

Detection of pigment network in dermatoscopy images using texture analysis

PubMed Central

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

2011-01-01

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

Character of skin on photo-thermal response and its regeneration process using second-harmonic generation microscopy.

PubMed

Wu, Shu-lian; Li, Hui; Zhang, Xiao-man; Chen, Wei R; Wang, Yun-Xia

2014-01-01

Quantitative characterization of skin collagen on photo-thermal response and its regeneration process is an important but difficult task. In this study, morphology and spectrum characteristics of collagen during photo-thermal response and its light-induced remodeling process were obtained by second-harmonic generation microscope in vivo. The texture feature of collagen orientation index and fractal dimension was extracted by image processing. The aim of this study is to detect the information hidden in skin texture during the process of photo-thermal response and its regeneration. The quantitative relations between injured collagen and texture feature were established for further analysis of the injured characteristics. Our results show that it is feasible to determine the main impacts of phototherapy on the skin. It is important to understand the process of collagen remodeling after photo-thermal injuries from texture feature.

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

PubMed

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 < 0.05). Twenty-eight T 2 -w Haralick features and all four geometrical features were significantly associated with biochemical recurrence (P < 0.05). The most relevant features were Haralick features T 2 -w contrast, T 2 -w difference variance, ADC median, along with tumor volume and tumor area (C-index from 0.76 to 0.82; P < 0.05). By combining these most powerful features in an RSF model, the obtained C-index was 0.90. T 2 -w Haralick features appear to be strongly associated with biochemical recurrence following prostate cancer radiotherapy. 3 J. Magn. Reson. Imaging 2017;45:103-117. © 2016 International Society for Magnetic Resonance in Medicine.

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

NASA Astrophysics Data System (ADS)

Kato, Noriji; Fukui, Motofumi; Isozaki, Takashi

2009-02-01

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

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

PubMed

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

2017-03-01

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

The performance improvement of automatic classification among obstructive lung diseases on the basis of the features of shape analysis, in addition to texture analysis at HRCT

NASA Astrophysics Data System (ADS)

Lee, Youngjoo; Kim, Namkug; Seo, Joon Beom; Lee, JuneGoo; Kang, Suk Ho

2007-03-01

In this paper, we proposed novel shape features to improve classification performance of differentiating obstructive lung diseases, based on HRCT (High Resolution Computerized Tomography) images. The images were selected from HRCT images, obtained from 82 subjects. For each image, two experienced radiologists selected rectangular ROIs with various sizes (16x16, 32x32, and 64x64 pixels), representing each disease or normal lung parenchyma. Besides thirteen textural features, we employed additional seven shape features; cluster shape features, and Top-hat transform features. To evaluate the contribution of shape features for differentiation of obstructive lung diseases, several experiments were conducted with two different types of classifiers and various ROI sizes. For automated classification, the Bayesian classifier and support vector machine (SVM) were implemented. To assess the performance and cross-validation of the system, 5-folding method was used. In comparison to employing only textural features, adding shape features yields significant enhancement of overall sensitivity(5.9, 5.4, 4.4% in the Bayesian and 9.0, 7.3, 5.3% in the SVM), in the order of ROI size 16x16, 32x32, 64x64 pixels, respectively (t-test, p<0.01). Moreover, this enhancement was largely due to the improvement on class-specific sensitivity of mild centrilobular emphysema and bronchiolitis obliterans which are most hard to differentiate for radiologists. According to these experimental results, adding shape features to conventional texture features is much useful to improve classification performance of obstructive lung diseases in both Bayesian and SVM classifiers.

Automated classification of articular cartilage surfaces based on surface texture.

PubMed

Stachowiak, G P; Stachowiak, G W; Podsiadlo, P

2006-11-01

In this study the automated classification system previously developed by the authors was used to classify articular cartilage surfaces with different degrees of wear. This automated system classifies surfaces based on their texture. Plug samples of sheep cartilage (pins) were run on stainless steel discs under various conditions using a pin-on-disc tribometer. Testing conditions were specifically designed to produce different severities of cartilage damage due to wear. Environmental scanning electron microscope (SEM) (ESEM) images of cartilage surfaces, that formed a database for pattern recognition analysis, were acquired. The ESEM images of cartilage were divided into five groups (classes), each class representing different wear conditions or wear severity. Each class was first examined and assessed visually. Next, the automated classification system (pattern recognition) was applied to all classes. The results of the automated surface texture classification were compared to those based on visual assessment of surface morphology. It was shown that the texture-based automated classification system was an efficient and accurate method of distinguishing between various cartilage surfaces generated under different wear conditions. It appears that the texture-based classification method has potential to become a useful tool in medical diagnostics.

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

PubMed

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

2015-03-01

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

Arc-textured high emittance radiator surfaces

NASA Technical Reports Server (NTRS)

Banks, Bruce A. (Inventor)

1991-01-01

High emittance radiator surfaces are produced by arc-texturing. This process produces such a surface on a metal by scanning it with a low voltage electric arc from a carbon electrode in an inert environment.

Computer-aided diagnosis in phase contrast imaging X-ray computed tomography for quantitative characterization of ex vivo human patellar cartilage.

PubMed

Nagarajan, Mahesh B; Coan, Paola; Huber, Markus B; Diemoz, Paul C; Glaser, Christian; Wismuller, Axel

2013-10-01

Visualization of ex vivo human patellar cartilage matrix through the phase contrast imaging X-ray computed tomography (PCI-CT) has been previously demonstrated. Such studies revealed osteoarthritis-induced changes to chondrocyte organization in the radial zone. This study investigates the application of texture analysis to characterizing such chondrocyte patterns in the presence and absence of osteoarthritic damage. Texture features derived from Minkowski functionals (MF) and gray-level co-occurrence matrices (GLCM) were extracted from 842 regions of interest (ROI) annotated on PCI-CT images of ex vivo human patellar cartilage specimens. These texture features were subsequently used in a machine learning task with support vector regression to classify ROIs as healthy or osteoarthritic; classification performance was evaluated using the area under the receiver operating characteristic curve (AUC). The best classification performance was observed with the MF features perimeter (AUC: 0.94 ±0.08 ) and "Euler characteristic" (AUC: 0.94 ±0.07 ), and GLCM-derived feature "Correlation" (AUC: 0.93 ±0.07). These results suggest that such texture features can provide a detailed characterization of the chondrocyte organization in the cartilage matrix, enabling classification of cartilage as healthy or osteoarthritic with high accuracy.

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

NASA Astrophysics Data System (ADS)

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.

Engineering the Pores of Biomass-Derived Carbon: Insights for Achieving Ultrahigh Stability at High Power in High-Energy Supercapacitors.

PubMed

Thangavel, Ranjith; Kaliyappan, Karthikeyan; Ramasamy, Hari Vignesh; Sun, Xueliang; Lee, Yun-Sung

2017-07-10

Electrochemical supercapacitors with high energy density are promising devices due to their simple construction and long-term cycling performance. The development of a supercapacitor based on electrical double-layer charge storage with high energy density that can preserve its cyclability at higher power presents an ongoing challenge. Herein, we provide insights to achieve a high energy density at high power with an ultrahigh stability in an electrical double-layer capacitor (EDLC) system by using carbon from a biomass precursor (cinnamon sticks) in a sodium ion-based organic electrolyte. Herein, we investigated the dependence of EDLC performance on structural, textural, and functional properties of porous carbon engineered by using various activation agents. The results demonstrate that the performance of EDLCs is not only dependent on their textural properties but also on their structural features and surface functionalities, as is evident from the electrochemical studies. The electrochemical results are highly promising and revealed that the porous carbon with poor textural properties has great potential to deliver high capacitance and outstanding stability over 300 000 cycles compared with porous carbon with good textural properties. A very low capacitance degradation of around 0.066 % per 1000 cycles, along with high energy density (≈71 Wh kg -1 ) and high power density, have been achieved. These results offer a new platform for the application of low-surface-area biomass-derived carbons in the design of highly stable high-energy supercapacitors. © 2017 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

NASA Astrophysics Data System (ADS)

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

2016-01-01

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

Ion sputter textured graphite electrode plates

NASA Technical Reports Server (NTRS)

Curren, A. N.; Forman, R.; Sovey, J. S.; Wintucky, E. G. (Inventor)

1983-01-01

A specially textured surface of pyrolytic graphite exhibits extremely low yields of secondary electrons and reduced numbers of reflected primary electrons after impingement of high energy primary electrons. Electrode plates of this material are used in multistage depressed collectors. An ion flux having an energy between 500 iV and 1000 iV and a current density between 1.0 mA/sq cm and 6.0 mA/sq cm produces surface roughening or texturing which is in the form of needles or spires. Such textured surfaces are especially useful as anode collector plates in high tube devices.

Atomic Oxygen Erosion Yield Dependence Upon Texture Development in Polymers

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

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

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

Yang, F; Byrd, D; Bowen, S

2015-06-15

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

Textural characterization of histopathological images for oral sub-mucous fibrosis detection.

PubMed

Krishnan, M Muthu Rama; Shah, Pratik; Choudhary, Anirudh; Chakraborty, Chandan; Paul, Ranjan Rashmi; Ray, Ajoy K

2011-10-01

In the field of quantitative microscopy, textural information plays a significant role very often in tissue characterization and diagnosis, in addition to morphology and intensity. The aim of this work is to improve the classification accuracy based on textural features for the development of a computer assisted screening of oral sub-mucous fibrosis (OSF). In fact, a systematic approach is introduced in order to grade the histopathological tissue sections into normal, OSF without dysplasia and OSF with dysplasia, which would help the oral onco-pathologists to screen the subjects rapidly. In totality, 71 textural features are extracted from epithelial region of the tissue sections using various wavelet families, Gabor-wavelet, local binary pattern, fractal dimension and Brownian motion curve, followed by preprocessing and segmentation. Wavelet families contribute a common set of 9 features, out of which 8 are significant and other 61 out of 62 obtained from the rest of the extractors are also statistically significant (p<0.05) in discriminating the three stages. Based on mean distance criteria, the best wavelet family (i.e., biorthogonal3.1 (bior3.1)) is selected for classifier design. support vector machine (SVM) is trained by 146 samples based on 69 textural features and its classification accuracy is computed for each of the combinations of wavelet family and rest of the extractors. Finally, it has been investigated that bior3.1 wavelet coefficients leads to higher accuracy (88.38%) in combination with LBP and Gabor wavelet features through three-fold cross validation. Results are shown and discussed in detail. It is shown that combining more than one texture measure instead of using just one might improve the overall accuracy. Copyright © 2011 Elsevier Ltd. All rights reserved.

Validation of CBCT for the computation of textural biomarkers

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

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

PubMed

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

2016-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

Validation of CBCT for the computation of textural biomarkers

PubMed Central

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

2015-01-01

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

Validation of CBCT for the computation of textural biomarkers.

PubMed

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

2015-03-17

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

Critical heat flux maxima during boiling crisis on textured surfaces

PubMed Central

Dhillon, Navdeep Singh; Buongiorno, Jacopo; Varanasi, Kripa K.

2015-01-01

Enhancing the critical heat flux (CHF) of industrial boilers by surface texturing can lead to substantial energy savings and global reduction in greenhouse gas emissions, but fundamentally this phenomenon is not well understood. Prior studies on boiling crisis indicate that CHF monotonically increases with increasing texture density. Here we report on the existence of maxima in CHF enhancement at intermediate texture density using measurements on parametrically designed plain and nano-textured micropillar surfaces. Using high-speed optical and infrared imaging, we study the dynamics of dry spot heating and rewetting phenomena and reveal that the dry spot heating timescale is of the same order as that of the gravity and liquid imbibition-induced dry spot rewetting timescale. Based on these insights, we develop a coupled thermal-hydraulic model that relates CHF enhancement to rewetting of a hot dry spot on the boiling surface, thereby revealing the mechanism governing the hitherto unknown CHF enhancement maxima. PMID:26346098

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

PubMed

Pan, Jui-Wen; Wang, Chia-Shen

2012-09-10

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

Ion beam sputter modification of the surface morphology of biological implants

NASA Technical Reports Server (NTRS)

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

1976-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1977-01-01

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

South Polar Textures

NASA Image and Video Library

2014-10-07

While yesterday image showed a texture of oval depressions swiss cheese, this image from NASA 2001 Mars Odyssey spacecraft shows a linear surface texture of the south polar cap. This texture is described as looking like a thumbprint.

Processing vertical size disparities in distinct depth planes.

PubMed

Duke, Philip A; Howard, Ian P

2012-08-17

A textured surface appears slanted about a vertical axis when the image in one eye is horizontally enlarged relative to the image in the other eye. The surface appears slanted in the opposite direction when the same image is vertically enlarged. Two superimposed textured surfaces with different horizontal size disparities appear as two surfaces that differ in slant. Superimposed textured surfaces with equal and opposite vertical size disparities appear as a single frontal surface. The vertical disparities are averaged. We investigated whether vertical size disparities are averaged across two superimposed textured surfaces in different depth planes or whether they induce distinct slants in the two depth planes. In Experiment 1, two superimposed textured surfaces with different vertical size disparities were presented in two depth planes defined by horizontal disparity. The surfaces induced distinct slants when the horizontal disparity was more than ±5 arcmin. Thus, vertical size disparities are not averaged over surfaces with different horizontal disparities. In Experiment 2 we confirmed that vertical size disparities are processed in surfaces away from the horopter, so the results of Experiment 1 cannot be explained by the processing of vertical size disparities in a fixated surface only. Together, these results show that vertical size disparities are processed separately in distinct depth planes. The results also suggest that vertical size disparities are not used to register slant globally by their effect on the registration of binocular direction of gaze.

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

PubMed Central

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

2016-01-01

The main objective of this study is to find out the importance of machine vision approach for the classification of five types of land cover data such as bare land, desert rangeland, green pasture, fertile cultivated land, and Sutlej river land. A novel spectra-statistical framework is designed to classify the subjective land cover data types accurately. Multispectral data of these land covers were acquired by using a handheld device named multispectral radiometer in the form of five spectral bands (blue, green, red, near infrared, and shortwave infrared) while texture data were acquired with a digital camera by the transformation of acquired images into 229 texture features for each image. The most discriminant 30 features of each image were obtained by integrating the three statistical features selection techniques such as Fisher, Probability of Error plus Average Correlation, and Mutual Information (F + PA + MI). Selected texture data clustering was verified by nonlinear discriminant analysis while linear discriminant analysis approach was applied for multispectral data. For classification, the texture and multispectral data were deployed to artificial neural network (ANN: n-class). By implementing a cross validation method (80-20), we received an accuracy of 91.332% for texture data and 96.40% for multispectral data, respectively. PMID:27376088

Texture analysis of high-resolution FLAIR images for TLE

NASA Astrophysics Data System (ADS)

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

2005-04-01

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

TU-G-204-05: The Effects of CT Acquisition and Reconstruction Conditions On Computed Texture Feature Values of Lung Lesions

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

Lo, P; Young, S; Kim, G

2015-06-15

Purpose: Texture features have been investigated as a biomarker of response and malignancy. Because these features reflect local differences in density, they may be influenced by acquisition and reconstruction parameters. The purpose of this study was to investigate the effects of radiation dose level and reconstruction method on features derived from lung lesions. Methods: With IRB approval, 33 lung tumor cases were identified from clinically indicated thoracic CT scans in which the raw projection (sinogram) data were available. Based on a previously-published technique, noise was added to the raw data to simulate reduced-dose versions of each case at 25%, 10%more » and 3% of the original dose. Original and simulated reduced dose projection data were reconstructed with conventional and two iterative-reconstruction settings, yielding 12 combinations of dose/recon conditions. One lesion from each case was contoured. At the reference condition (full dose, conventional recon), 17 lesions were randomly selected for repeat contouring (repeatability). For each lesion at each dose/recon condition, 151 texture measures were calculated. A paired differences approach was employed to compare feature variation from repeat contours at the reference condition to the variation observed in other dose/recon conditions (reproducibility). The ratio of standard deviation of the reproducibility to repeatability was used as the variation measure for each feature. Results: The mean variation (standard deviation) across dose levels and kernel was significantly different with a ratio of 2.24 (±5.85) across texture features (p=0.01). The mean variation (standard deviation) across dose levels with conventional recon was also significantly different with 2.30 (7.11) (p=0.025). The mean variation across reconstruction settings of original dose has a trend in showing difference with 1.35 (2.60) among all features (p=0.09). Conclusion: Texture features varied considerably with variations in dose and reconstruction condition. Care should be taken to standardize these conditions when using texture as a quantitative feature. This effort supported in part by a grant from the National Cancer Institute’s Quantitative Imaging Network (QIN): U01 CA181156; The UCLA Department of Radiology has a Master Research Agreement with Siemens Healthcare; Dr. McNitt-Gray has previously received research support from Siemens Healthcare.« less

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

PubMed

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.

Textured carbon on copper: A novel surface with extremely low secondary electron emission characteristics

NASA Technical Reports Server (NTRS)

Curren, A. N.; Jensen, K. A.

1985-01-01

Experimentally determined values of true secondary electron emission and relative values of reflected primary electron yield for a range of primary electron beam energies and beam impingement angles are presented for a series of novel textured carbon surfaces on copper substrates. (All copper surfaces used in this study were oxygen-free, high-conductivity grade). The purpose of this investigation is to provide information necessary to develop high-efficiency multistage depressed collectors (MDC's) for microwave amplifier traveling-wave tubes (TWT's) for communications and aircraft applications. To attain the highest TWT signal quality and overall efficiency, the MDC electrode surface must have low secondary electron emission characteristics. While copper is the material most commonly used for MDC electrodes, it exhibits relatively high levels of secondary electron emission unless its surface is treated for emission control. The textured carbon surface on copper substrate described in this report is a particularly promising candidate for the MDC electrode application. Samples of textured carbon surfaces on copper substrates typical of three different levels of treatment are prepared and tested for this study. The materials are tested at primary electron beam energies of 200 to 2000 eV and at direct (0 deg) to near-grazing (85 deg) beam impingement angles. True secondary electron emission and relative reflected primary electron yield characteristics of the textured surfaces are compared with each other and with those of untreated copper. All the textured carbon surfaces on copper substrate tested exhibited sharply lower secondary electron emission characteristics than those of an untreated copper surface.

Lidar-enhanced geologic mapping, examples from the Medford and Hood River areas, Oregon

NASA Astrophysics Data System (ADS)

Wiley, T. J.; McClaughry, J. D.

2012-12-01

Lidar-based 3-foot digital elevation models (DEMs) and derivatives (slopeshade, hillshade, contours) were used to help map geology across 1700 km2 (650 mi2) near Hood River and Medford, Oregon. Techniques classically applied to interpret coarse DEMs and small-scale topographic maps were adapted to take advantage of lidar's high resolution. Penetration and discrimination of plant cover by the laser system allowed recognition of fine patterns and textures related to underlying geologic units and associated soils. Surficial geologic maps were improved by the ability to examine tiny variations in elevation and slope. Recognition of low-relief features of all sizes was enhanced where pixel elevation ranges of centimeters to meters, established by knowledge of the site or by trial, were displayed using thousands of sequential colors. Features can also be depicted relative to stream level by preparing a DEM that compensates for gradient. Near Medford, lidar-derived contour maps with 1- to 3-foot intervals revealed incised bajada with young, distal lobes defined by concentric contour lines. Bedrock geologic maps were improved by recognizing geologic features associated with surface textures and patterns or topographic anomalies. In sedimentary and volcanic terrain, structure was revealed by outcrops or horizons lying at one stratigraphic level. Creating a triangulated irregular network (TIN) facet from positions of three or more such points gives strike and dip. Each map area benefited from hundreds of these measurements. A more extensive DEM in the plane of the TIN facet can be subtracted from surface elevation (lidar DEM) to make a DEM with elevation zero where the stratigraphic horizon lies at the surface. The distribution of higher and lower stratigraphic horizons can be shown by highlighting areas similarly higher or lower on the same DEM. Poor fit of contacts or faults projected between field traverses suggest the nature and amount of intervening geologic structure. Intrusive bodies were locally delimited by linear mounds where contact metamorphism hardened soft, fractured country rock. Bedrock faults were revealed where fault traces formed topographic anomalies or where topography associated with stratigraphic horizons or bedding-parallel textural fabrics was offset. This was important for identification of young faults and associated earthquake hazards. Previously unknown Holocene faults southwest of Hood River appear as subtle lineaments redirecting modern drainages or offsetting glacial moraines or glaciated bedrock. West of Medford, the presence young faulting was confirmed by elevation data that showed bedrock in the channel of the Rogue River at higher elevations below Gold Ray dam than in boreholes upstream. Such obscure structural features would have gone unrecognized using traditional topographic analysis or field reconnaissance. Fieldwork verified that lidar techniques improved our early geologic models, resolution of geologic features, and mapping of surficial and bedrock geology between traverses.

Robo-Psychophysics: Extracting Behaviorally Relevant Features from the Output of Sensors on a Prosthetic Finger.

PubMed

Delhaye, Benoit P; Schluter, Erik W; Bensmaia, Sliman J

2016-01-01

Efforts are underway to restore sensorimotor function in amputees and tetraplegic patients using anthropomorphic robotic hands. For this approach to be clinically viable, sensory signals from the hand must be relayed back to the patient. To convey tactile feedback necessary for object manipulation, behaviorally relevant information must be extracted in real time from the output of sensors on the prosthesis. In the present study, we recorded the sensor output from a state-of-the-art bionic finger during the presentation of different tactile stimuli, including punctate indentations and scanned textures. Furthermore, the parameters of stimulus delivery (location, speed, direction, indentation depth, and surface texture) were systematically varied. We developed simple decoders to extract behaviorally relevant variables from the sensor output and assessed the degree to which these algorithms could reliably extract these different types of sensory information across different conditions of stimulus delivery. We then compared the performance of the decoders to that of humans in analogous psychophysical experiments. We show that straightforward decoders can extract behaviorally relevant features accurately from the sensor output and most of them outperform humans.

Efficacy of texture, shape, and intensity features for robust posterior-fossa tumor segmentation in MRI

NASA Astrophysics Data System (ADS)

Ahmed, S.; Iftekharuddin, K. M.; Ogg, R. J.; Laningham, F. H.

2009-02-01

Our previous works suggest that fractal-based texture features are very useful for detection, segmentation and classification of posterior-fossa (PF) pediatric brain tumor in multimodality MRI. In this work, we investigate and compare efficacy of our texture features such as fractal and multifractional Brownian motion (mBm), and intensity along with another useful level-set based shape feature in PF tumor segmentation. We study feature selection and ranking using Kullback -Leibler Divergence (KLD) and subsequent tumor segmentation; all in an integrated Expectation Maximization (EM) framework. We study the efficacy of all four features in both multimodality as well as disparate MRI modalities such as T1, T2 and FLAIR. Both KLD feature plots and information theoretic entropy measure suggest that mBm feature offers the maximum separation between tumor and non-tumor tissues in T1 and FLAIR MRI modalities. The same metrics show that intensity feature offers the maximum separation between tumor and non-tumor tissue in T2 MRI modality. The efficacies of these features are further validated in segmenting PF tumor using both single modality and multimodality MRI for six pediatric patients with over 520 real MR images.

Enhancement of endothelialisation of coronary stents by laser surface engineering.

PubMed

Li, Lin; Mirhosseini, Nazanin; Michael, Alun; Liu, Zhu; Wang, Tao

2013-11-01

Coronary stents have been widely used in the treatment of coronary heart disease. However, complications have hampered the long-term success of the device. Bare-metal stents (BMS) have a high rate of restenosis and poor endothelialisation. The drug-eluting stents (DES), although dramatically reduce restenosis, significantly prevent endothelialisation leading to late thrombosis and behave the same way as BMS after drug releasing. Rapid adhesion and growth of endothelial cells on the stent surface is a key process for early vascular healing after coronary stenting which contributes to the reduction of major complications. Surface properties manipulate cell growth and directly determine the success and life-span of the implants. However, the ideal surface properties of coronary stents are not yet fully understood. The objective of this research is to understand how surface micro/nano textures and associated material chemistry changes generated by a laser beam affect the behavior of endothelial cells on bare metal 316L stents. A high power laser beam was applied to modifying the surface properties of 316L coronary stent material and the commercial coronary stents, followed by examination of the adhesion and proliferation of human coronary endothelial cells that were growing on the surfaces. Surface properties were examined by scanning electron microscopy, contact angle measurement, and X-ray photoelectron spectroscopy. A novel surface with combined micro/nano features was created on stent material 316L and coronary stent with a specific surface chemistry. This surface gives rise to a threefold increase in the adhesion and eightfold increase in the proliferation of endothelial cells. Interestingly, such effects were only observed when the surface texture was produced in the nitrogen atmosphere suggesting the importance of the surface chemistry, including the dramatic increase of chromium nitride, for the interaction of endothelial cells with the material surface. This novel surface is also super-hydrophilic with close to zero water/cell culture fluid contact angles and low cytotoxicity. A novel surface created by laser surface-engineering with a combination of defined surface texture and surface chemistry was found beneficial for the improvement of coronary stent endothelialisation. The technology presented here could work with both DES and BMS with added benefit for the improvement of the biocompatibility of current coronary stents. © 2013 Wiley Periodicals, Inc.

Detection of Focal Cortical Dysplasia Lesions in MRI Using Textural Features

NASA Astrophysics Data System (ADS)

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

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

SU-D-BRA-07: A Phantom Study to Assess the Variability in Radiomics Features Extracted From Cone-Beam CT Images

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

Fave, X; Fried, D; UT Health Science Center Graduate School of Biomedical Sciences, Houston, TX

2015-06-15

Purpose: Several studies have demonstrated the prognostic potential for texture features extracted from CT images of non-small cell lung cancer (NSCLC) patients. The purpose of this study was to determine if these features could be extracted with high reproducibility from cone-beam CT (CBCT) images in order for features to be easily tracked throughout a patient’s treatment. Methods: Two materials in a radiomics phantom, designed to approximate NSCLC tumor texture, were used to assess the reproducibility of 26 features. This phantom was imaged on 9 CBCT scanners, including Elekta and Varian machines. Thoracic and head imaging protocols were acquired on eachmore » machine. CBCT images from 27 NSCLC patients imaged using the thoracic protocol on Varian machines were obtained for comparison. The variance for each texture measured from these patients was compared to the variance in phantom values for different manufacturer/protocol subsets. Levene’s test was used to identify features which had a significantly smaller variance in the phantom scans versus the patient data. Results: Approximately half of the features (13/26 for material1 and 15/26 for material2) had a significantly smaller variance (p<0.05) between Varian thoracic scans of the phantom compared to patient scans. Many of these same features remained significant for the head scans on Varian (12/26 and 8/26). However, when thoracic scans from Elekta and Varian were combined, only a few features were still significant (4/26 and 5/26). Three features (skewness, coarsely filtered mean and standard deviation) were significant in almost all manufacturer/protocol subsets. Conclusion: Texture features extracted from CBCT images of a radiomics phantom are reproducible and show significantly less variation than the same features measured from patient images when images from the same manufacturer or with similar parameters are used. Reproducibility between CBCT scanners may be high enough to allow the extraction of meaningful texture values for patients. This project was funded in part by the Cancer Prevention Research Institute of Texas (CPRIT). Xenia Fave is a recipient of the American Association of Physicists in Medicine Graduate Fellowship.« less

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

A multifunctional polymeric nanofilm with robust chemical performances for special wettability.

PubMed

Wang, Yabin; Lin, Feng; Dong, Yaping; Liu, Zhong; Li, Wu; Huang, Yudong

2016-03-07

A multifunctional polymeric nanofilm of a triazinedithiolsilane compound, which can protect metallic substrates and activate the corresponding surface simultaneously, is introduced onto a copper mesh surface via facile solution-immersion approaches. The resultant interface exhibits hydrophilic features due to the existence of silanol groups (SiOH) outward and has the potential to act as a superhydrophilic and underwater superoleophobic material. As the polymeric nanofilm atop the copper mesh is modified with long-chain octadecyltrichlorosilane (OTS), the functionalized surface becomes superhydrophobic and superoleophilic. The OTS-modified polymeric nanofilm shows outstanding chemical durability and stability that are seldom concurrently satisfied for a material with special wettability, owing to its inherent architecture. These textures generate high separation efficiency, durable separation capability and excellent thermal stability. The protective ability, originating from the textures of the underlying cross-linked disulfide units (-SS-) and siloxane networks (SiOSi) on the top of the nanofilm, prolongs the chemical durability. The activating capability stemming from the residual SiOH groups improves the chemical stability as a result of the chemical bonds developed by these sites. The significant point of this investigation lies in enlightening us on the fabrication of multifunctional polymeric nanofilms on different metal surfaces using various triazinedithiolsilane compounds, and on the construction of interfaces with controllable wettable performances in demanding research or industrial applications.

Combined texture feature analysis of segmentation and classification of benign and malignant tumour CT slices.

PubMed

Padma, A; Sukanesh, R

2013-01-01

A computer software system is designed for the segmentation and classification of benign from malignant tumour slices in brain computed tomography (CT) images. This paper presents a method to find and select both the dominant run length and co-occurrence texture features of region of interest (ROI) of the tumour region of each slice to be segmented by Fuzzy c means clustering (FCM) and evaluate the performance of support vector machine (SVM)-based classifiers in classifying benign and malignant tumour slices. Two hundred and six tumour confirmed CT slices are considered in this study. A total of 17 texture features are extracted by a feature extraction procedure, and six features are selected using Principal Component Analysis (PCA). This study constructed the SVM-based classifier with the selected features and by comparing the segmentation results with the experienced radiologist labelled ground truth (target). Quantitative analysis between ground truth and segmented tumour is presented in terms of segmentation accuracy, segmentation error and overlap similarity measures such as the Jaccard index. The classification performance of the SVM-based classifier with the same selected features is also evaluated using a 10-fold cross-validation method. The proposed system provides some newly found texture features have an important contribution in classifying benign and malignant tumour slices efficiently and accurately with less computational time. The experimental results showed that the proposed system is able to achieve the highest segmentation and classification accuracy effectiveness as measured by jaccard index and sensitivity and specificity.

Role of Viscous Dissipative Processes on the Wetting of Textured Surfaces

PubMed Central

Grewal, H. S.; Nam Kim, Hong; Cho, Il-Joo; Yoon, Eui-Sung

2015-01-01

We investigate the role of viscous forces on the wetting of hydrophobic, semi-hydrophobic, and hydrophilic textured surfaces as second-order effects. We show that during the initial contact, the transition from inertia- to viscous-dominant regime occurs regardless of their surface topography and chemistry. Furthermore, we demonstrate the effect of viscosity on the apparent contact angle under quasi-static conditions by modulating the ratio of a water/glycerol mixture and show the effect of viscosity, especially on the semi-hydrophobic and hydrophobic textured substrates. The reason why the viscous force does not affect the apparent contact angle of the hydrophilic surface is explained based on the relationship between the disjoining pressure and surface chemistry. We further propose a wetting model that can predict the apparent contact angle of a liquid drop on a textured substrate by incorporating a viscous force component in the force balance equation. This model can predict apparent contact angles on semi-hydrophobic and hydrophobic textured surfaces exhibiting Wenzel state more accurately than the Wenzel model, indicating the importance of viscous forces in determining the apparent contact angle. The modified model can be applied for estimating the wetting properties of arbitrary engineered surfaces. PMID:26390958

Nanostructured GaAs solar cells via metal-assisted chemical etching of emitter layers.

PubMed

Song, Yunwon; Choi, Keorock; Jun, Dong-Hwan; Oh, Jungwoo

2017-10-02

GaAs solar cells with nanostructured emitter layers were fabricated via metal-assisted chemical etching. Au nanoparticles produced via thermal treatment of Au thin films were used as etch catalysts to texture an emitter surface with nanohole structures. Epi-wafers with emitter layers 0.5, 1.0, and 1.5 um in thickness were directly textured and a window layer removal process was performed before metal catalyst deposition. A nanohole-textured emitter layer provides effective light trapping capabilities, reducing the surface reflection of a textured solar cell by 11.0%. However, because the nanostructures have high surface area to volume ratios and large numbers of defects, various photovoltaic properties were diminished by high recombination losses. Thus, we have studied the application of nanohole structures to GaAs emitter solar cells and investigated the cells' antireflection and photovoltaic properties as a function of the nanohole structure and emitter thickness. Due to decreased surface reflection and improved shunt resistance, the solar cell efficiency increased from 4.25% for non-textured solar cells to 7.15% for solar cells textured for 5 min.

Geological Evidence for Recent Ice Ages on Mars

NASA Astrophysics Data System (ADS)

Head, J. W.; Mustard, J. F.; Kreslavsky, M. A.; Milliken, R. E.; Marchant, D. R.

2003-12-01

A primary cause of ice ages on Earth is orbital forcing from variations in orbital parameters of the planet. On Mars such variations are known to be much more extreme. Recent exploration of Mars has revealed abundant water ice in the near-surface at high latitudes in both hemispheres. We outline evidence that these near-surface, water-ice rich mantling deposits represent a mixture of ice and dust that is layered, meters thick, and latitude dependent. These units were formed during a geologically recent major martian ice age, and were emplaced in response to the changing stability of water ice and dust on the surface during variations in orbital parameters. Evidence for these units include a smoothing of topography at subkilometer baselines from about 30o north and south latitudes to the poles, a distinctive dissected texture in MOC images in the +/-30o-60o latitude band, latitude-dependent sets of topographic characteristics and morphologic features (e.g., polygons, 'basketball' terrain texture, gullies, viscous flow features), and hydrogen concentrations consistent with the presence of abundant ice at shallow depths above 60o latitude. The most equatorward extent of these ice-rich deposits was emplaced down to latitudes equivalent to Saudi Arabia and the southern United States on Earth during the last major martian ice age, probably about 0.4-2.1 million years ago. Mars is currently in an inter-ice age period and the ice-rich deposits are presently undergoing reworking, degradation and retreat in response to the current stability relations of near-surface ice. Unlike Earth, martian ice ages are characterized by warmer climates in the polar regions and the enhanced role of atmospheric water ice and dust transport and deposition to produce widespread and relatively evenly distributed smooth deposits at mid-latitudes during obliquity maxima.

Method for Surface Texturing Titanium Products

NASA Technical Reports Server (NTRS)

Banks, Bruce A. (Inventor)

1998-01-01

The present invention teaches a method of producing a textured surface upon an arbitrarily configured titanium or titanium alloy object for the purpose of improving bonding between the object and other materials such as polymer matrix composites and/or human bone for the direct in-growth of orthopaedic implants. The titanium or titanium alloy object is placed in an electrolytic cell having an ultrasonically agitated solution of sodium chloride therein whereby a pattern of uniform "pock mark" like pores or cavities are produced upon the object's surface. The process is very cost effective compared to other methods of producing rough surfaces on titanium and titanium alloy components. The surface textures produced by the present invention are etched directly into the parent metal at discrete sites separated by areas unaffected by the etching process. Bonding materials to such surface textures on titanium or titanium alloy can thus support a shear load even if adhesion of the bonding material is poor.

Transfer the multiscale texture of crystalline Si onto thin-film micromorph cell by UV nanoimprint for light trapping

NASA Astrophysics Data System (ADS)

Liu, Daiming; Wang, Qingkang; Wang, Qing

2018-05-01

Surface texturing is of great significance in light trapping for solar cells. Herein, the multiscale texture, consisting of microscale pyramids and nanoscale porous arrangement, was fabricated on crystalline Si by KOH etching and Ag-assisted HF etching processes and subsequently replicated onto glass with high fidelity by UV nanoimprint method. Light trapping of the multiscale texture was studied by spectral (reflectance, haze ratio) characterizations. Results reveal the multiscale texture provides the broadband reflection reducing, the highlighted light scattering and the additional self-cleaning behaviors. Compared with bare cell, the multiscale textured micromorph cell achieves a 4% relative increase in power conversion efficiency. This surface texturing route paves a promising way for developing low-cost, large-scale and high-efficiency solar applications.

Using artificial intelligence strategies for process-related automated inspection in the production environment

NASA Astrophysics Data System (ADS)

Anding, K.; Kuritcyn, P.; Garten, D.

2016-11-01

In this paper a new method for the automatic visual inspection of metallic surfaces is proposed by using Convolutional Neural Networks (CNN). The different combinations of network parameters were developed and tested. The obtained results of CNN were analysed and compared with the results of our previous investigations with color and texture features as input parameters for a Support Vector Machine. Advantages and disadvantages of the different classifying methods are explained.

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

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

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

2009-11-15

Purpose: Texture analysis of femur radiographs may serve as a potential low cost technique to predict osteoporotic fracture risk and has received considerable attention in the past years. A further application of this technique may be the measurement of the quality of specific bone compartments to provide useful information for treatment of bone fractures. Two challenges of texture analysis are the selection of the best suitable texture measure and reproducible placement of regions of interest (ROIs). The goal of this in vitro study was to automatically place ROIs in radiographs of proximal femur specimens and to calculate correlations between variousmore » different texture analysis methods and the femurs' anchorage strength. Methods: Radiographs were obtained from 14 femoral specimens and bone mineral density (BMD) was measured in the femoral neck. Biomechanical testing was performed to assess the anchorage strength in terms of failure load, breakaway torque, and number of cycles. Images were segmented using a framework that is based on the usage of level sets and statistical in-shape models. Five ROIs were automatically placed in the head, upper and lower neck, trochanteric, and shaft compartment in an atlas subject. All other subjects were registered rigidly, affinely, and nonlinearly, and the resulting transformation was used to map the five ROIs onto the individual femora. Results: In each ROI, texture features were extracted using gray level co-occurence matrices (GLCM), third-order GLCM, morphological gradients (MGs), Minkowski dimensions (MDs), Minkowski functionals (MFs), Gaussian Markov random fields, and scaling index method (SIM). Coefficients of determination for each texture feature with parameters of anchorage strength were computed. In a stepwise multiregression analysis, the most predictive parameters were identified in different models. Texture features were highly correlated with anchorage strength estimated by the failure load of up to R{sup 2}=0.61 (MF and MG features, p<0.01) and were partially independent of BMD. The correlations were dependent on the choice of the ROI and the texture measure. The best predictive multiregression model for failure load R{sub adj}{sup 2}=0.86 (p<0.001) included a set of recently developed texture methods (MF and SIM) but excluded bone mineral density and commonly used texture measures. Conclusions: The results suggest that texture information contained in trabecular bone structure visualized on radiographs may predict whether an implant anchorage can be used and may determine the local bone quality from preoperative radiographs.« less

Flow Charts: Visualization of Vector Fields on Arbitrary Surfaces

PubMed Central

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

2009-01-01

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

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

PubMed

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.

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

NASA Astrophysics Data System (ADS)

Khatri, Chandra B.; Sharma, Satish C.

2018-02-01

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

Texture for script identification.

PubMed

Busch, Andrew; Boles, Wageeh W; Sridharan, Sridha

2005-11-01

The problem of determining the script and language of a document image has a number of important applications in the field of document analysis, such as indexing and sorting of large collections of such images, or as a precursor to optical character recognition (OCR). In this paper, we investigate the use of texture as a tool for determining the script of a document image, based on the observation that text has a distinct visual texture. An experimental evaluation of a number of commonly used texture features is conducted on a newly created script database, providing a qualitative measure of which features are most appropriate for this task. Strategies for improving classification results in situations with limited training data and multiple font types are also proposed.

Quantification of texture match of the skin graft: function and morphology of the stratum corneum.

PubMed

Inoue, K; Matsumoto, K

1986-01-01

In an attempt to analyze the "texture match" of grafted skin, functional and morphological aspects of the stratum corneum were studied using the Skin Surface Hydrometer (IBS Inc.) and the scanning electron microscope. The results showed that hygroscopicity and water holding capacity of the stratum corneum played a crucial role in making the skin surface soft and smooth. Morphologically there were regional differences in the surface pattern and the mean area of corneocytes, suggesting that these differences affect skin texture. It is suggested that the present functional and morphological studies of the stratum corneum can provide a quantitative measure of the "texture match".

Development of surface friction guidelines for LADOTD.

DOT National Transportation Integrated Search

2012-04-01

The main objective of this study was to develop a Louisiana pavement surface friction guideline that considers polished stone value (PSV) and mixture : type alike in terms of both micro- and macro- surface textures. The polishing and texture properti...

Structure and properties of polyethylene films used in heavy lift balloons

NASA Technical Reports Server (NTRS)

Khoury, F.; Crissman, J. M.; Fanconi, B. M.; Wagner, H. L.; Botz, L. H.

1985-01-01

The following features of five polyethylene films used by NASA in the construction of heavy lift balloons have been examined: molecular weight, molecular weight distribution, branching, melting behavior, density, surface texture, birefringence, orientation of crystalline regions, unlaxial deformation in the machine and transverse directions, and the effect of sample geometry and strain rate on deformation behavior. The goal of this exploratory study was to determine whether there are significant differences in any of the above mentioned features, or combination of features between the films. The acquisition of such information is a first step towards determining whether there are any specific correlations between film characteristics and the incidence of catastrophic failure of balloons during ascent through the troposphere. This exploratory study has resulted in the identification of similarities and differences between various features of the films.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Texture classification of normal tissues in computed tomography using Gabor filters

NASA Astrophysics Data System (ADS)

Dettori, Lucia; Bashir, Alia; Hasemann, Julie

2007-03-01

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

Classification of glioblastoma and metastasis for neuropathology intraoperative diagnosis: a multi-resolution textural approach to model the background

NASA Astrophysics Data System (ADS)

Ahmad Fauzi, Mohammad Faizal; Gokozan, Hamza Numan; Elder, Brad; Puduvalli, Vinay K.; Otero, Jose J.; Gurcan, Metin N.

2014-03-01

Brain cancer surgery requires intraoperative consultation by neuropathology to guide surgical decisions regarding the extent to which the tumor undergoes gross total resection. In this context, the differential diagnosis between glioblastoma and metastatic cancer is challenging as the decision must be made during surgery in a short time-frame (typically 30 minutes). We propose a method to classify glioblastoma versus metastatic cancer based on extracting textural features from the non-nuclei region of cytologic preparations. For glioblastoma, these regions of interest are filled with glial processes between the nuclei, which appear as anisotropic thin linear structures. For metastasis, these regions correspond to a more homogeneous appearance, thus suitable texture features can be extracted from these regions to distinguish between the two tissue types. In our work, we use the Discrete Wavelet Frames to characterize the underlying texture due to its multi-resolution capability in modeling underlying texture. The textural characterization is carried out in primarily the non-nuclei regions after nuclei regions are segmented by adapting our visually meaningful decomposition segmentation algorithm to this problem. k-nearest neighbor method was then used to classify the features into glioblastoma or metastasis cancer class. Experiment on 53 images (29 glioblastomas and 24 metastases) resulted in average accuracy as high as 89.7% for glioblastoma, 87.5% for metastasis and 88.7% overall. Further studies are underway to incorporate nuclei region features into classification on an expanded dataset, as well as expanding the classification to more types of cancers.

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

PubMed

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

2017-07-01

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

Factors affecting the establishment of direct-seeded pine on surface-mine spoils

Treesearch

William T. Plass

1974-01-01

In a greenhouse study the emergence, survival, and growth of seven species of pine were related to chemical and textural characteristics of 12 Kentucky spoils. The results identify three factors that may affect the establishment of direct-seeded pine on surface-mine spoils. First, fine-textured spoil material may restrict seedling emergence. Coarse-textured sandstones...

Sharp improvement of flashover strength from composite micro-textured surfaces

NASA Astrophysics Data System (ADS)

Huo, Yankun; Liu, Wenyuan; Ke, Changfeng; Chang, Chao; Chen, Changhua

2017-09-01

A composite micro-textured surface structure is proposed and demonstrated to enhance the surface flashover strength of polymer insulators used in vacuum. The structure is fabricated in two stages, with periodic triangular grooves of approximately 210 μm in width formed in the first stage and micro-holes of approximately 2 μm coated on the inner surface of grooves in the second. The aim is to exploit the synergistic effects between the grooves and micro-holes to suppress the secondary electron yield to obtain a better flashover performance. To acquire insulators with the composite micro-textured surface, the CO2 laser processing technique is applied to treat the surface of the PMMA insulators. The test results show that the flashover voltages of the insulators with the two-stage fabricated structure increase by 150% compared with the untreated samples in the best state. Compared with the traditional macro-groove structures on insulators, the proposed composite micro-textured insulators exhibit a better surface flashover performance.

Enabling Highly Effective Boiling from Superhydrophobic Surfaces

NASA Astrophysics Data System (ADS)

Allred, Taylor P.; Weibel, Justin A.; Garimella, Suresh V.

2018-04-01

A variety of industrial applications such as power generation, water distillation, and high-density cooling rely on heat transfer processes involving boiling. Enhancements to the boiling process can improve the energy efficiency and performance across multiple industries. Highly wetting textured surfaces have shown promise in boiling applications since capillary wicking increases the maximum heat flux that can be dissipated. Conversely, highly nonwetting textured (superhydrophobic) surfaces have been largely dismissed for these applications as they have been shown to promote formation of an insulating vapor film that greatly diminishes heat transfer efficiency. The current Letter shows that boiling from a superhydrophobic surface in an initial Wenzel state, in which the surface texture is infiltrated with liquid, results in remarkably low surface superheat with nucleate boiling sustained up to a critical heat flux typical of hydrophilic wetting surfaces, and thus upends this conventional wisdom. Two distinct boiling behaviors are demonstrated on both micro- and nanostructured superhydrophobic surfaces based on the initial wetting state. For an initial surface condition in which vapor occupies the interstices of the surface texture (Cassie-Baxter state), premature film boiling occurs, as has been commonly observed in the literature. However, if the surface texture is infiltrated with liquid (Wenzel state) prior to boiling, drastically improved thermal performance is observed; in this wetting state, the three-phase contact line is pinned during vapor bubble growth, which prevents the development of a vapor film over the surface and maintains efficient nucleate boiling behavior.

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

NASA Astrophysics Data System (ADS)

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

2016-03-01

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

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

PubMed

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.

Texture and color features for tile classification

NASA Astrophysics Data System (ADS)

Baldrich, Ramon; Vanrell, Maria; Villanueva, Juan J.

1999-09-01

In this paper we present the results of a preliminary computer vision system to classify the production of a ceramic tile industry. We focus on the classification of a specific type of tiles whose production can be affected by external factors, such as humidity, temperature, origin of clays and pigments. Variations on these uncontrolled factors provoke small differences in the color and the texture of the tiles that force to classify all the production. A constant and non- subjective classification would allow avoiding devolution from customers and unnecessary stock fragmentation. The aim of this work is to simulate the human behavior on this classification task by extracting a set of features from tile images. These features are induced by definitions from experts. To compute them we need to mix color and texture information and to define global and local measures. In this work, we do not seek a general texture-color representation, we only deal with textures formed by non-oriented colored-blobs randomly distributed. New samples are classified using Discriminant Analysis functions derived from known class tile samples. The last part of the paper is devoted to explain the correction of acquired images in order to avoid time and geometry illumination changes.

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

NASA Astrophysics Data System (ADS)

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

2015-03-01

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

Transparent conducting oxide contacts and textured metal back reflectors for thin film silicon solar cells

NASA Astrophysics Data System (ADS)

Franken, R. H.-J.

2006-09-01

With the growing population and the increasing environmental problems of the 'common' fossil and nuclear energy production, the need for clean and sustainable energy sources is evident. Solar energy conversion, such as in photovoltaic (PV) systems, can play a major role in the urgently needed energy transition in electricity production. At the present time PV module production is dominated by the crystalline wafer technology. Thin film silicon technology is an alternative solar energy technology that operates at lower efficiencies, however, it has several significant advantages, such as the possibility of deposition on cheap (flexible) substrates and the much smaller silicon material consumption. Because of the small thickness of the solar cells, light trapping schemes are needed in order to obtain enough light absorption and current generation. This thesis describes the research on thin film silicon solar cells with the focus on the optimization of the transparent conducting oxide (TCO) layers and textured metal Ag substrate layers for the use as enhanced light scattering back reflectors in n-i-p type of solar cells. First we analyzed ZnO:Al (TCO) layers deposited in an radio frequent (rf) magnetron deposition system equipped with a 7 inch target. We have focused on the improvement of the electrical properties without sacrificing the optical properties by increasing the mobility and decreasing the grain boundary density. Furthermore, we described some of the effects on light trapping of ZnO:Al enhanced back reflectors. The described effects are able to explain the observed experimental data. Furthermore, we present a relation between the surface morphology of the Ag back contact and the current enhancement in microcrystalline (muc-Si:H) solar cells. We show the importance of the lateral feature sizes of the Ag surface on the light scattering and introduce a method to characterize the quality of the back reflector by combining the vertical and lateral feature sizes at this surface. Additionally, we show that we can control the lateral feature sizes and obtain an optimized roughness for light scattering. With this new knowledge we were able to indicate the influence of the surface plasmon absorption of the textured Ag layers on the current enhancement and recognize this effect as one of the limiting factors to the current increase in thin film solar cells. Finally we present the dark and light current voltage (J-V) parameters of muc-Si:H solar cells as a function of the rms roughness of the substrate. We show that increased roughness can result in an increased defect density of the absorbing silicon layer (i layer), which limits the current collection in the solar cell. The presented research gives better understanding of the effect of TCOs and textured interfaces on light trapping and current enhancement in thin film silicon solar cells. The thesis explains some fundamental insights in light scattering and reveals some material and morphology features that are dominantly limiting the current generation in muc-Si:H solar cells deposited on light scattering back reflectors. Furthermore, it presents a method to obtain optimized back scattering contacts at deposition temperatures below 300 oC, which opens the possibility for the use of heat resistant plastic substrates. We improved the muc-Si:H solar cell efficiency with flat back reflectors from 4.5 % and 14.6 mA/cm2 to 8.5 % and 23.4 mA/cm2 with the use of optimized back reflectors.

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

NASA Astrophysics Data System (ADS)

Magdi, Sara; Swillam, Mohamed A.

2017-02-01

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

Topological patterns of mesh textures in serpentinites

NASA Astrophysics Data System (ADS)

Miyazawa, M.; Suzuki, A.; Shimizu, H.; Okamoto, A.; Hiraoka, Y.; Obayashi, I.; Tsuji, T.; Ito, T.

2017-12-01

Serpentinization is a hydration process that forms serpentine minerals and magnetite within the oceanic lithosphere. Microfractures crosscut these minerals during the reactions, and the structures look like mesh textures. It has been known that the patterns of microfractures and the system evolutions are affected by the hydration reaction and fluid transport in fractures and within matrices. This study aims at quantifying the topological patterns of the mesh textures and understanding possible conditions of fluid transport and reaction during serpentinization in the oceanic lithosphere. Two-dimensional simulation by the distinct element method (DEM) generates fracture patterns due to serpentinization. The microfracture patterns are evaluated by persistent homology, which measures features of connected components of a topological space and encodes multi-scale topological features in the persistence diagrams. The persistence diagrams of the different mesh textures are evaluated by principal component analysis to bring out the strong patterns of persistence diagrams. This approach help extract feature values of fracture patterns from high-dimensional and complex datasets.

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

NASA Astrophysics Data System (ADS)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2017-03-01

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

Chemical solution deposition method of fabricating highly aligned MgO templates

DOEpatents

Paranthaman, Mariappan Parans [Knoxville, TN; Sathyamurthy, Srivatsan [Knoxville, TN; Aytug, Tolga [Knoxville, TN; Arendt, Paul N [Los Alamos, NM; Stan, Liliana [Los Alamos, NM; Foltyn, Stephen R [Los Alamos, NM

2012-01-03

A superconducting article includes a substrate having an untextured metal surface; an untextured barrier layer of La.sub.2Zr.sub.2O.sub.7 or Gd.sub.2Zr.sub.2O.sub.7 supported by and in contact with the surface of the substrate; a biaxially textured buffer layer supported by the untextured barrier layer; and a biaxially textured superconducting layer supported by the biaxially textured buffer layer. Moreover, a method of forming a buffer layer on a metal substrate includes the steps of: providing a substrate having an untextured metal surface; coating the surface of the substrate with a barrier layer precursor; converting the precursor to an untextured barrier layer; and depositing a biaxially textured buffer layer above and supported by the untextured barrier layer.

The effects of phase on the perception of 3D shape from texture: psychophysics and modeling.

PubMed

Thaler, Lore; Todd, James T; Dijkstra, Tjeerd M H

2007-02-01

Two experiments are reported in which observers judged the apparent shapes of elliptical cylinders with eight different textures that were presented with scrambled and unscrambled phase spectra. The results revealed that the apparent depths of these surfaces varied linearly with the ground truth in all conditions, and that the overall magnitude of surface relief was systematically underestimated. In general, the apparent depth of a surface is significantly attenuated when the phase spectrum of its texture is randomly scrambled, though the magnitude of this effect varies for different types of texture. A new computational model of 3D shape from texture is proposed in which apparent depth is estimated from the relative density of edges in different local regions of an image, and the predictions of this model are highly correlated with the observers' judgments.

Method for forming a nano-textured substrate

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

Jeong, Sangmoo; Hu, Liangbing; Cui, Yi

A method for forming a nano-textured surface on a substrate is disclosed. An illustrative embodiment of the present invention comprises dispensing of a nanoparticle ink of nanoparticles and solvent onto the surface of a substrate, distributing the ink to form substantially uniform, liquid nascent layer of the ink, and enabling the solvent to evaporate from the nanoparticle ink thereby inducing the nanoparticles to assemble into an texture layer. Methods in accordance with the present invention enable rapid formation of large-area substrates having a nano-textured surface. Embodiments of the present invention are well suited for texturing substrates using high-speed, large scale,more » roll-to-roll coating equipment, such as that used in office product, film coating, and flexible packaging applications. Further, embodiments of the present invention are well suited for use with rigid or flexible substrates.« less

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

PubMed

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.

Texture coarseness responsive neurons and their mapping in layer 2–3 of the rat barrel cortex in vivo

PubMed Central

Garion, Liora; Dubin, Uri; Rubin, Yoav; Khateb, Mohamed; Schiller, Yitzhak; Azouz, Rony; Schiller, Jackie

2014-01-01

Texture discrimination is a fundamental function of somatosensory systems, yet the manner by which texture is coded and spatially represented in the barrel cortex are largely unknown. Using in vivo two-photon calcium imaging in the rat barrel cortex during artificial whisking against different surface coarseness or controlled passive whisker vibrations simulating different coarseness, we show that layer 2–3 neurons within barrel boundaries differentially respond to specific texture coarsenesses, while only a minority of neurons responded monotonically with increased or decreased surface coarseness. Neurons with similar preferred texture coarseness were spatially clustered. Multi-contact single unit recordings showed a vertical columnar organization of texture coarseness preference in layer 2–3. These findings indicate that layer 2–3 neurons perform high hierarchical processing of tactile information, with surface coarseness embodied by distinct neuronal subpopulations that are spatially mapped onto the barrel cortex. DOI: http://dx.doi.org/10.7554/eLife.03405.001 PMID:25233151