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Sample records for 3d texture features

  1. Differentiating bladder carcinoma from bladder wall using 3D textural features: an initial study

    NASA Astrophysics Data System (ADS)

    Xu, Xiaopan; Zhang, Xi; Liu, Yang; Tian, Qiang; Zhang, Guopeng; Lu, Hongbing

    2016-03-01

    Differentiating bladder tumors from wall tissues is of critical importance for the detection of invasion depth and cancer staging. The textural features embedded in bladder images have demonstrated their potentials in carcinomas detection and classification. The purpose of this study was to investigate the feasibility of differentiating bladder carcinoma from bladder wall using three-dimensional (3D) textural features extracted from MR bladder images. The widely used 2D Tamura features were firstly wholly extended to 3D, and then different types of 3D textural features including 3D features derived from gray level co-occurrence matrices (GLCM) and grey level-gradient co-occurrence matrix (GLGCM), as well as 3D Tamura features, were extracted from 23 volumes of interest (VOIs) of bladder tumors and 23 VOIs of patients' bladder wall. Statistical results show that 30 out of 47 features are significantly different between cancer tissues and wall tissues. Using these features with significant differences between these two types of tissues, classification performance with a supported vector machine (SVM) classifier demonstrates that the combination of three types of selected 3D features outperform that of using only one type of features. All the observations demonstrate that significant textural differences exist between carcinomatous tissues and bladder wall, and 3D textural analysis may be an effective way for noninvasive staging of bladder cancer.

  2. 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.

  3. Uniform Local Binary Pattern Based Texture-Edge Feature for 3D Human Behavior Recognition

    PubMed Central

    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. PMID:25942404

  4. Computerized lung cancer malignancy level analysis using 3D texture features

    NASA Astrophysics Data System (ADS)

    Sun, Wenqing; Huang, Xia; Tseng, Tzu-Liang; Zhang, Jianying; Qian, Wei

    2016-03-01

    Based on the likelihood of malignancy, the nodules are classified into five different levels in Lung Image Database Consortium (LIDC) database. In this study, we tested the possibility of using threedimensional (3D) texture features to identify the malignancy level of each nodule. Five groups of features were implemented and tested on 172 nodules with confident malignancy levels from four radiologists. These five feature groups are: grey level co-occurrence matrix (GLCM) features, local binary pattern (LBP) features, scale-invariant feature transform (SIFT) features, steerable features, and wavelet features. Because of the high dimensionality of our proposed features, multidimensional scaling (MDS) was used for dimension reduction. RUSBoost was applied for our extracted features for classification, due to its advantages in handling imbalanced dataset. Each group of features and the final combined features were used to classify nodules highly suspicious for cancer (level 5) and moderately suspicious (level 4). The results showed that the area under the curve (AUC) and accuracy are 0.7659 and 0.8365 when using the finalized features. These features were also tested on differentiating benign and malignant cases, and the reported AUC and accuracy were 0.8901 and 0.9353.

  5. Techniques for Revealing 3d Hidden Archeological Features: Morphological Residual Models as Virtual-Polynomial Texture Maps

    NASA Astrophysics Data System (ADS)

    Pires, H.; Martínez Rubio, J.; Elorza Arana, A.

    2015-02-01

    The recent developments in 3D scanning technologies are not been accompanied by visualization interfaces. We are still using the same types of visual codes as when maps and drawings were made by hand. The available information in 3D scanning data sets is not being fully exploited by current visualization techniques. In this paper we present recent developments regarding the use of 3D scanning data sets for revealing invisible information from archaeological sites. These sites are affected by a common problem, decay processes, such as erosion, that never ceases its action and endangers the persistence of last vestiges of some peoples and cultures. Rock art engravings, or epigraphical inscriptions, are among the most affected by these processes because they are, due to their one nature, carved at the surface of rocks often exposed to climatic agents. The study and interpretation of these motifs and texts is strongly conditioned by the degree of conservation of the imprints left by our ancestors. Every single detail in the remaining carvings can make a huge difference in the conclusions taken by specialists. We have selected two case-studies severely affected by erosion to present the results of the on-going work dedicated to explore in new ways the information contained in 3D scanning data sets. A new method for depicting subtle morphological features in the surface of objects or sites has been developed. It allows to contrast human patterns still present at the surface but invisible to naked eye or by any other archaeological inspection technique. It was called Morphological Residual Model (MRM) because of its ability to contrast the shallowest morphological details, to which we refer as residuals, contained in the wider forms of the backdrop. Afterwards, we have simulated the process of building Polynomial Texture Maps - a widespread technique that as been contributing to archaeological studies for some years - in a 3D virtual environment using the results of MRM

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

    SciTech Connect

    Yang, F; Nyflot, M; Bowen, S; Kinahan, P; Sandison, G

    2014-06-15

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

  7. 3D Flow Visualization Using Texture Advection

    NASA Technical Reports Server (NTRS)

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

    2001-01-01

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

  8. Automatic Texture Mapping of Architectural and Archaeological 3d Models

    NASA Astrophysics Data System (ADS)

    Kersten, T. P.; Stallmann, D.

    2012-07-01

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

  9. 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.

  10. Incorporation of texture-based features in optimal graph-theoretic approach with application to the 3D segmentation of intraretinal surfaces in SD-OCT volumes

    NASA Astrophysics Data System (ADS)

    Antony, Bhavna J.; Abràmoff, Michael D.; Sonka, Milan; Kwon, Young H.; Garvin, Mona K.

    2012-02-01

    While efficient graph-theoretic approaches exist for the optimal (with respect to a cost function) and simultaneous segmentation of multiple surfaces within volumetric medical images, the appropriate design of cost functions remains an important challenge. Previously proposed methods have used simple cost functions or optimized a combination of the same, but little has been done to design cost functions using learned features from a training set, in a less biased fashion. Here, we present a method to design cost functions for the simultaneous segmentation of multiple surfaces using the graph-theoretic approach. Classified texture features were used to create probability maps, which were incorporated into the graph-search approach. The efficiency of such an approach was tested on 10 optic nerve head centered optical coherence tomography (OCT) volumes obtained from 10 subjects that presented with glaucoma. The mean unsigned border position error was computed with respect to the average of manual tracings from two independent observers and compared to our previously reported results. A significant improvement was noted in the overall means which reduced from 9.25 +/- 4.03μm to 6.73 +/- 2.45μm (p < 0.01) and is also comparable with the inter-observer variability of 8.85 +/- 3.85μm.

  11. Novel 3D Compression Methods for Geometry, Connectivity and Texture

    NASA Astrophysics Data System (ADS)

    Siddeq, M. M.; Rodrigues, M. A.

    2016-06-01

    A large number of applications in medical visualization, games, engineering design, entertainment, heritage, e-commerce and so on require the transmission of 3D models over the Internet or over local networks. 3D data compression is an important requirement for fast data storage, access and transmission within bandwidth limitations. The Wavefront OBJ (object) file format is commonly used to share models due to its clear simple design. Normally each OBJ file contains a large amount of data (e.g. vertices and triangulated faces, normals, texture coordinates and other parameters) describing the mesh surface. In this paper we introduce a new method to compress geometry, connectivity and texture coordinates by a novel Geometry Minimization Algorithm (GM-Algorithm) in connection with arithmetic coding. First, each vertex ( x, y, z) coordinates are encoded to a single value by the GM-Algorithm. Second, triangle faces are encoded by computing the differences between two adjacent vertex locations, which are compressed by arithmetic coding together with texture coordinates. We demonstrate the method on large data sets achieving compression ratios between 87 and 99 % without reduction in the number of reconstructed vertices and triangle faces. The decompression step is based on a Parallel Fast Matching Search Algorithm (Parallel-FMS) to recover the structure of the 3D mesh. A comparative analysis of compression ratios is provided with a number of commonly used 3D file formats such as VRML, OpenCTM and STL highlighting the performance and effectiveness of the proposed method.

  12. A statistical description of 3D lung texture from CT data

    NASA Astrophysics Data System (ADS)

    Chaisaowong, Kraisorn; Paul, Andreas

    2015-03-01

    A method was described to create a statistical description of 3D lung texture from CT data. The second order statistics, i.e. the gray level co-occurrence matrix (GLCM), has been applied to characterize texture of lung by defining the joint probability distribution of pixel pairs. The required GLCM was extended to three-dimensional image regions to deal with CT volume data. For a fine-scale lung segmentation, both the 3D GLCM of lung and thorax without lung are required. Once the co-occurrence densities are measured, the 3D models of the joint probability density function for each describing direction of involving voxel pairs and for each class (lung or thorax) are estimated using mixture of Gaussians through the expectation-maximization algorithm. This leads to a feature space that describes the 3D lung texture.

  13. Realistic texture extraction for 3D face models robust to self-occlusion

    NASA Astrophysics Data System (ADS)

    Qu, Chengchao; Monari, Eduardo; Schuchert, Tobias; Beyerer, Jürgen

    2015-02-01

    In the context of face modeling, probably the most well-known approach to represent 3D faces is the 3D Morphable Model (3DMM). When 3DMM is fitted to a 2D image, the shape as well as the texture and illumination parameters are simultaneously estimated. However, if real facial texture is needed, texture extraction from the 2D image is necessary. This paper addresses the possible problems in texture extraction of a single image caused by self-occlusion. Unlike common approaches that leverage the symmetric property of the face by mirroring the visible facial part, which is sensitive to inhomogeneous illumination, this work first generates a virtual texture map for the skin area iteratively by averaging the color of neighbored vertices. Although this step creates unrealistic, overly smoothed texture, illumination stays constant between the real and virtual texture. In the second pass, the mirrored texture is gradually blended with the real or generated texture according to the visibility. This scheme ensures a gentle handling of illumination and yet yields realistic texture. Because the blending area only relates to non-informative area, main facial features still have unique appearance in different face halves. Evaluation results reveal realistic rendering in novel poses robust to challenging illumination conditions and small registration errors.

  14. Automatic Texture Reconstruction of 3d City Model from Oblique Images

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  15. Exploiting Textured 3D Models for Developing Serious Games

    NASA Astrophysics Data System (ADS)

    Kontogianni, G.; Georgopoulos, A.

    2015-08-01

    Digital technologies have affected significantly many fields of computer graphics such as Games and especially the field of the Serious Games. These games are usually used for educational proposes in many fields such as Health Care, Military applications, Education, Government etc. Especially Digital Cultural Heritage is a scientific area that Serious Games are applied and lately many applications appear in the related literature. Realistic 3D textured models which have been produced using different photogrammetric methods could be a useful tool for the creation of Serious Game applications in order to make the final result more realistic and close to the reality. The basic goal of this paper is how 3D textured models which are produced by photogrammetric methods can be useful for developing a more realistic environment of a Serious Game. The application of this project aims at the creation of an educational game for the Ancient Agora of Athens. The 3D models used vary not only as far as their production methods (i.e. Time of Flight laser scanner, Structure from Motion, Virtual historical reconstruction etc.) is concerned, but also as far as their era as some of them illustrated according to their existing situation and some others according to how these monuments looked like in the past. The Unity 3D® game developing environment was used for creating this application, in which all these models were inserted in the same file format. For the application two diachronic virtual tours of the Athenian Agora were produced. The first one illustrates the Agora as it is today and the second one at the 2nd century A.D. Finally the future perspective for the evolution of this game is presented which includes the addition of some questions that the user will be able to answer. Finally an evaluation is scheduled to be performed at the end of the project.

  16. Surface classification and detection of latent fingerprints based on 3D surface texture parameters

    NASA Astrophysics Data System (ADS)

    Gruhn, Stefan; Fischer, Robert; Vielhauer, Claus

    2012-06-01

    In the field of latent fingerprint detection in crime scene forensics the classification of surfaces has importance. A new method for the scientific analysis of image based information for forensic science was investigated in the last years. Our image acquisition based on a sensor using Chromatic White Light (CWL) with a lateral resolution up to 2 μm. The used FRT-MicroProf 200 CWL 600 measurement device is able to capture high-resolution intensity and topography images in an optical and contact-less way. In prior work, we have suggested to use 2D surface texture parameters to classify various materials, which was a novel approach in the field of criminalistic forensic using knowledge from surface appearance and a chromatic white light sensor. A meaningful and useful classification of different crime scene specific surfaces is not existent. In this work, we want to extend such considerations by the usage of fourteen 3D surface parameters, called 'Birmingham 14'. In our experiment we define these surface texture parameters and use them to classify ten different materials in this test set-up and create specific material classes. Further it is shown in first experiments, that some surface texture parameters are sensitive to separate fingerprints from carrier surfaces. So far, the use of surface roughness is mainly known within the framework of material quality control. The analysis and classification of the captured 3D-topography images from crime scenes is important for the adaptive preprocessing depending on the surface texture. The adaptive preprocessing in dependency of surface classification is necessary for precise detection because of the wide variety of surface textures. We perform a preliminary study in usage of these 3D surface texture parameters as feature for the fingerprint detection. In combination with a reference sample we show that surface texture parameters can be an indication for a fingerprint and can be a feature in latent fingerprint detection.

  17. 3D texture analysis for classification of second harmonic generation images of human ovarian cancer

    PubMed Central

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

    2016-01-01

    Remodeling of the collagen architecture in the extracellular matrix (ECM) has been implicated in ovarian cancer. To quantify these alterations we implemented a form of 3D texture analysis to delineate the fibrillar morphology observed in 3D Second Harmonic Generation (SHG) microscopy image data of normal (1) and high risk (2) ovarian stroma, benign ovarian tumors (3), low grade (4) and high grade (5) serous tumors, and endometrioid tumors (6). We developed a tailored set of 3D filters which extract textural features in the 3D image sets to build (or learn) statistical models of each tissue class. By applying k-nearest neighbor classification using these learned models, we achieved 83–91% accuracies for the six classes. The 3D method outperformed the analogous 2D classification on the same tissues, where we suggest this is due the increased information content. This classification based on ECM structural changes will complement conventional classification based on genetic profiles and can serve as an additional biomarker. Moreover, the texture analysis algorithm is quite general, as it does not rely on single morphological metrics such as fiber alignment, length, and width but their combined convolution with a customizable basis set. PMID:27767180

  18. Medical image retrieval system using multiple features from 3D ROIs

    NASA Astrophysics Data System (ADS)

    Lu, Hongbing; Wang, Weiwei; Liao, Qimei; Zhang, Guopeng; Zhou, Zhiming

    2012-02-01

    Compared to a retrieval using global image features, features extracted from regions of interest (ROIs) that reflect distribution patterns of abnormalities would benefit more for content-based medical image retrieval (CBMIR) systems. Currently, most CBMIR systems have been designed for 2D ROIs, which cannot reflect 3D anatomical features and region distribution of lesions comprehensively. To further improve the accuracy of image retrieval, we proposed a retrieval method with 3D features including both geometric features such as Shape Index (SI) and Curvedness (CV) and texture features derived from 3D Gray Level Co-occurrence Matrix, which were extracted from 3D ROIs, based on our previous 2D medical images retrieval system. The system was evaluated with 20 volume CT datasets for colon polyp detection. Preliminary experiments indicated that the integration of morphological features with texture features could improve retrieval performance greatly. The retrieval result using features extracted from 3D ROIs accorded better with the diagnosis from optical colonoscopy than that based on features from 2D ROIs. With the test database of images, the average accuracy rate for 3D retrieval method was 76.6%, indicating its potential value in clinical application.

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

    SciTech Connect

    Apostol, Lian; Boudousq, Vincent; Basset, Oliver; Odet, Christophe; Yot, Sophie; Tabary, Joachim; Dinten, Jean-Marc; Boller, Elodie; Kotzki, Pierre-Olivier; Peyrin, Francoise

    2006-09-15

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

  20. Standard Features and Their Impact on 3D Engineering Graphics

    ERIC Educational Resources Information Center

    Waldenmeyer, K. M.; Hartman, N. W.

    2009-01-01

    The prevalence of feature-based 3D modeling in industry has necessitated the accumulation and maintenance of standard feature libraries. Currently, firms who use standard features to design parts are storing and utilizing these libraries through their existing product data management (PDM) systems. Standard features have enabled companies to…

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

    NASA Astrophysics Data System (ADS)

    Sierra, Heidy; Brooks, Dana; Dimarzio, Charles

    2010-07-01

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

  2. Consistent Multi-View Texturing of Detailed 3d Surface Models

    NASA Astrophysics Data System (ADS)

    Davydova, K.; Kuschk, G.; Hoegner, L.; Reinartz, P.; Stilla, U.

    2015-03-01

    Texture mapping techniques are used to achieve a high degree of realism for computer generated large-scale and detailed 3D surface models by extracting the texture information from photographic images and applying it to the object surfaces. Due to the fact that a single image cannot capture all parts of the scene, a number of images should be taken. However, texturing the object surfaces from several images can lead to lighting variations between the neighboring texture fragments. In this paper we describe the creation of a textured 3D scene from overlapping aerial images using a Markov Random Field energy minimization framework. We aim to maximize the quality of the generated texture mosaic, preserving the resolution from the original images, and at the same time to minimize the seam visibilities between adjacent fragments. As input data we use a triangulated mesh of the city center of Munich and multiple camera views of the scene from different directions.

  3. Registration of 3D spectral OCT volumes using 3D SIFT feature point matching

    NASA Astrophysics Data System (ADS)

    Niemeijer, Meindert; Garvin, Mona K.; Lee, Kyungmoo; van Ginneken, Bram; Abràmoff, Michael D.; Sonka, Milan

    2009-02-01

    The recent introduction of next generation spectral OCT scanners has enabled routine acquisition of high resolution, 3D cross-sectional volumetric images of the retina. 3D OCT is used in the detection and management of serious eye diseases such as glaucoma and age-related macular degeneration. For follow-up studies, image registration is a vital tool to enable more precise, quantitative comparison of disease states. This work presents a registration method based on a recently introduced extension of the 2D Scale-Invariant Feature Transform (SIFT) framework1 to 3D.2 The SIFT feature extractor locates minima and maxima in the difference of Gaussian scale space to find salient feature points. It then uses histograms of the local gradient directions around each found extremum in 3D to characterize them in a 4096 element feature vector. Matching points are found by comparing the distance between feature vectors. We apply this method to the rigid registration of optic nerve head- (ONH) and macula-centered 3D OCT scans of the same patient that have only limited overlap. Three OCT data set pairs with known deformation were used for quantitative assessment of the method's robustness and accuracy when deformations of rotation and scaling were considered. Three-dimensional registration accuracy of 2.0+/-3.3 voxels was observed. The accuracy was assessed as average voxel distance error in N=1572 matched locations. The registration method was applied to 12 3D OCT scans (200 x 200 x 1024 voxels) of 6 normal eyes imaged in vivo to demonstrate the clinical utility and robustness of the method in a real-world environment.

  4. Scale Space Graph Representation and Kernel Matching for Non Rigid and Textured 3D Shape Retrieval.

    PubMed

    Garro, Valeria; Giachetti, Andrea

    2016-06-01

    In this paper we introduce a novel framework for 3D object retrieval that relies on tree-based shape representations (TreeSha) derived from the analysis of the scale-space of the Auto Diffusion Function (ADF) and on specialized graph kernels designed for their comparison. By coupling maxima of the Auto Diffusion Function with the related basins of attraction, we can link the information at different scales encoding spatial relationships in a graph description that is isometry invariant and can easily incorporate texture and additional geometrical information as node and edge features. Using custom graph kernels it is then possible to estimate shape dissimilarities adapted to different specific tasks and on different categories of models, making the procedure a powerful and flexible tool for shape recognition and retrieval. Experimental results demonstrate that the method can provide retrieval scores similar or better than state-of-the-art on textured and non textured shape retrieval benchmarks and give interesting insights on effectiveness of different shape descriptors and graph kernels.

  5. 3D texture-based classification applied on brain white matter lesions on MR images

    NASA Astrophysics Data System (ADS)

    Leite, Mariana; Gobbi, David; Salluzi, Marina; Frayne, Richard; Lotufo, Roberto; Rittner, Letícia

    2016-03-01

    Lesions in the brain white matter are among the most frequently observed incidental findings on MR images. This paper presents a 3D texture-based classification to distinguish normal appearing white matter from white matter containing lesions, and compares it with the 2D approach. Texture analysis were based on 55 texture attributes extracted from gray-level histogram, gray-level co-occurrence matrix, run-length matrix and gradient. The results show that the 3D approach achieves an accuracy rate of 99.28%, against 97.41% of the 2D approach by using a support vector machine classifier. Furthermore, the most discriminating texture attributes on both 2D and 3D cases were obtained from the image histogram and co-occurrence matrix.

  6. 2D/3D Monte Carlo Feature Profile Simulator FPS-3D

    NASA Astrophysics Data System (ADS)

    Moroz, Paul

    2010-11-01

    Numerical simulation of etching/deposition profiles is important for semiconductor industry, as it allows analysis and prediction of the outcome of materials processing on a micron and sub-micron scale. The difficulty, however, is in making such a simulator a reliable, general, and easy to use tool applicable to different situations, for example, with different ratios of ion to neutral fluxes, different chemistries, different energies of incoming particles, and different angular and energy dependencies for surface reactions, without recompiling the code each time when the parameters change. The FPS-3D simulator [1] does not need recompilation when the features, materials, gases, or plasma are changed -- modifications to input, chemistry, and flux files are enough. The code allows interaction of neutral low-energy species with the surface mono-layer, while considering finite penetration depth into the volume for fast particles and ions. The FPS-3D code can simulate etching and deposition processes, both for 2D and 3D geometries. FPS-3D is using an advanced graphics package from HFS for presenting real-time process and profile evolution. The presentation will discuss the FPS-3D code with examples for different process conditions. The author is thankful to Drs. S.-Y. Kang of TEL TDC and P. Miller of HFS for valuable discussions. [4pt] [1] P. Moroz, URP.00101, GEC, Saratoga, NY, 2009.

  7. Real-time volume rendering of 4D image using 3D texture mapping

    NASA Astrophysics Data System (ADS)

    Hwang, Jinwoo; Kim, June-Sic; Kim, Jae Seok; Kim, In Young; Kim, Sun Il

    2001-05-01

    Four dimensional image is 3D volume data that varies with time. It is used to express deforming or moving object in virtual surgery of 4D ultrasound. It is difficult to render 4D image by conventional ray-casting or shear-warp factorization methods because of their time-consuming rendering time or pre-processing stage whenever the volume data are changed. Even 3D texture mapping is used, repeated volume loading is also time-consuming in 4D image rendering. In this study, we propose a method to reduce data loading time using coherence between currently loaded volume and previously loaded volume in order to achieve real time rendering based on 3D texture mapping. Volume data are divided into small bricks and each brick being loaded is tested for similarity to one which was already loaded in memory. If the brick passed the test, it is defined as 3D texture by OpenGL functions. Later, the texture slices of the brick are mapped into polygons and blended by OpenGL blending functions. All bricks undergo this test. Continuously deforming fifty volumes are rendered in interactive time with SGI ONYX. Real-time volume rendering based on 3D texture mapping is currently available on PC.

  8. Extracting Semantically Annotated 3d Building Models with Textures from Oblique Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Frommholz, D.; Linkiewicz, M.; Meissner, H.; Dahlke, D.; Poznanska, A.

    2015-03-01

    This paper proposes a method for the reconstruction of city buildings with automatically derived textures that can be directly used for façade element classification. Oblique and nadir aerial imagery recorded by a multi-head camera system is transformed into dense 3D point clouds and evaluated statistically in order to extract the hull of the structures. For the resulting wall, roof and ground surfaces high-resolution polygonal texture patches are calculated and compactly arranged in a texture atlas without resampling. The façade textures subsequently get analyzed by a commercial software package to detect possible windows whose contours are projected into the original oriented source images and sparsely ray-casted to obtain their 3D world coordinates. With the windows being reintegrated into the previously extracted hull the final building models are stored as semantically annotated CityGML "LOD-2.5" objects.

  9. Biologically Inspired Model for Inference of 3D Shape from Texture.

    PubMed

    Gomez, Olman; Neumann, Heiko

    2016-01-01

    A biologically inspired model architecture for inferring 3D shape from texture is proposed. The model is hierarchically organized into modules roughly corresponding to visual cortical areas in the ventral stream. Initial orientation selective filtering decomposes the input into low-level orientation and spatial frequency representations. Grouping of spatially anisotropic orientation responses builds sketch-like representations of surface shape. Gradients in orientation fields and subsequent integration infers local surface geometry and globally consistent 3D depth. From the distributions in orientation responses summed in frequency, an estimate of the tilt and slant of the local surface can be obtained. The model suggests how 3D shape can be inferred from texture patterns and their image appearance in a hierarchically organized processing cascade along the cortical ventral stream. The proposed model integrates oriented texture gradient information that is encoded in distributed maps of orientation-frequency representations. The texture energy gradient information is defined by changes in the grouped summed normalized orientation-frequency response activity extracted from the textured object image. This activity is integrated by directed fields to generate a 3D shape representation of a complex object with depth ordering proportional to the fields output, with higher activity denoting larger distance in relative depth away from the viewer.

  10. Biologically Inspired Model for Inference of 3D Shape from Texture

    PubMed Central

    Gomez, Olman; Neumann, Heiko

    2016-01-01

    A biologically inspired model architecture for inferring 3D shape from texture is proposed. The model is hierarchically organized into modules roughly corresponding to visual cortical areas in the ventral stream. Initial orientation selective filtering decomposes the input into low-level orientation and spatial frequency representations. Grouping of spatially anisotropic orientation responses builds sketch-like representations of surface shape. Gradients in orientation fields and subsequent integration infers local surface geometry and globally consistent 3D depth. From the distributions in orientation responses summed in frequency, an estimate of the tilt and slant of the local surface can be obtained. The model suggests how 3D shape can be inferred from texture patterns and their image appearance in a hierarchically organized processing cascade along the cortical ventral stream. The proposed model integrates oriented texture gradient information that is encoded in distributed maps of orientation-frequency representations. The texture energy gradient information is defined by changes in the grouped summed normalized orientation-frequency response activity extracted from the textured object image. This activity is integrated by directed fields to generate a 3D shape representation of a complex object with depth ordering proportional to the fields output, with higher activity denoting larger distance in relative depth away from the viewer. PMID:27649387

  11. Biologically Inspired Model for Inference of 3D Shape from Texture.

    PubMed

    Gomez, Olman; Neumann, Heiko

    2016-01-01

    A biologically inspired model architecture for inferring 3D shape from texture is proposed. The model is hierarchically organized into modules roughly corresponding to visual cortical areas in the ventral stream. Initial orientation selective filtering decomposes the input into low-level orientation and spatial frequency representations. Grouping of spatially anisotropic orientation responses builds sketch-like representations of surface shape. Gradients in orientation fields and subsequent integration infers local surface geometry and globally consistent 3D depth. From the distributions in orientation responses summed in frequency, an estimate of the tilt and slant of the local surface can be obtained. The model suggests how 3D shape can be inferred from texture patterns and their image appearance in a hierarchically organized processing cascade along the cortical ventral stream. The proposed model integrates oriented texture gradient information that is encoded in distributed maps of orientation-frequency representations. The texture energy gradient information is defined by changes in the grouped summed normalized orientation-frequency response activity extracted from the textured object image. This activity is integrated by directed fields to generate a 3D shape representation of a complex object with depth ordering proportional to the fields output, with higher activity denoting larger distance in relative depth away from the viewer. PMID:27649387

  12. Texture-based visualization of unsteady 3D flow by real-time advection and volumetric illumination.

    PubMed

    Weiskopf, Daniel; Schafhitzel, Tobias; Ertl, Thomas

    2007-01-01

    This paper presents an interactive technique for the dense texture-based visualization of unsteady 3D flow, taking into account issues of computational efficiency and visual perception. High efficiency is achieved by a 3D graphics processing unit (GPU)-based texture advection mechanism that implements logical 3D grid structures by physical memory in the form of 2D textures. This approach results in fast read and write access to physical memory, independent of GPU architecture. Slice-based direct volume rendering is used for the final display. We investigate two alternative methods for the volumetric illumination of the result of texture advection: First, gradient-based illumination that employs a real-time computation of gradients, and, second, line-based lighting based on illumination in codimension 2. In addition to the Phong model, perception-guided rendering methods are considered, such as cool/warm shading, halo rendering, or color-based depth cueing. The problems of clutter and occlusion are addressed by supporting a volumetric importance function that enhances features of the flow and reduces visual complexity in less interesting regions. GPU implementation aspects, performance measurements, and a discussion of results are included to demonstrate our visualization approach.

  13. Automated Recognition of 3D Features in GPIR Images

    NASA Technical Reports Server (NTRS)

    Park, Han; Stough, Timothy; Fijany, Amir

    2007-01-01

    A method of automated recognition of three-dimensional (3D) features in images generated by ground-penetrating imaging radar (GPIR) is undergoing development. GPIR 3D images can be analyzed to detect and identify such subsurface features as pipes and other utility conduits. Until now, much of the analysis of GPIR images has been performed manually by expert operators who must visually identify and track each feature. The present method is intended to satisfy a need for more efficient and accurate analysis by means of algorithms that can automatically identify and track subsurface features, with minimal supervision by human operators. In this method, data from multiple sources (for example, data on different features extracted by different algorithms) are fused together for identifying subsurface objects. The algorithms of this method can be classified in several different ways. In one classification, the algorithms fall into three classes: (1) image-processing algorithms, (2) feature- extraction algorithms, and (3) a multiaxis data-fusion/pattern-recognition algorithm that includes a combination of machine-learning, pattern-recognition, and object-linking algorithms. The image-processing class includes preprocessing algorithms for reducing noise and enhancing target features for pattern recognition. The feature-extraction algorithms operate on preprocessed data to extract such specific features in images as two-dimensional (2D) slices of a pipe. Then the multiaxis data-fusion/ pattern-recognition algorithm identifies, classifies, and reconstructs 3D objects from the extracted features. In this process, multiple 2D features extracted by use of different algorithms and representing views along different directions are used to identify and reconstruct 3D objects. In object linking, which is an essential part of this process, features identified in successive 2D slices and located within a threshold radius of identical features in adjacent slices are linked in a

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

    NASA Astrophysics Data System (ADS)

    Jerram, D. A.; Morgan, D. J.; Pankhurst, M. J.

    2014-12-01

    The crystal cargo that is found in volcanic and plutonic rocks contains a wealth of information about magmatic mush processes, crystallisation history, crystal entrainment and recycling. Phenocryst populations predominantly record episodes of growth/nucleation and bulk geochemical changes within an evolving crystal-melt body. Ante- and xeno-crysts provide useful clues to the nature of mush interaction with wall rock and with principal magma(s). Furthermore, crystal evolutions (core to rim) record pathways through pressure, temperature and compositional space. These can often illustrate complex recycling within systems, describing the plumbing architecture. Understanding this architecture underpins our knowledge of how igneous systems can interact with the crust, grow, freeze, re-mobilise and prime for eruption. Initially, 2D studies produced corrected 3D crystal size distributions to help provide information about nucleation and residence times. It immediately became clear that crystal shape is an important factor in determining the confidence placed upon 3D reconstructions of 2D data. Additionally studies utilised serial sections of medium- to coarse-grain-size populations which allowed 3D reconstruction using modelling software to be improved, since size and shape etc. can be directly constrained. Finally the advent of textural studies using X-ray tomography has revolutionised the way in which we can inspect the crystal cargo in mushy systems, allowing us to image in great detail crystal packing arrangements, 3D CSDs, shapes and orientations etc. The latest most innovative studies use X-ray micro-computed tomography to rapidly characterise chemical populations within the crystal cargo, adding a further dimension to this approach, and implies the ability to untangle magmatic chemical components to better understand their individual and combined evolution. In this contribution key examples of the different types of textural analysis techniques in 2D and 3D

  15. Feature detection on 3D images of dental imprints

    NASA Astrophysics Data System (ADS)

    Mokhtari, Marielle; Laurendeau, Denis

    1994-09-01

    A computer vision approach for the extraction of feature points on 3D images of dental imprints is presented. The position of feature points are needed for the measurement of a set of parameters for automatic diagnosis of malocclusion problems in orthodontics. The system for the acquisition of the 3D profile of the imprint, the procedure for the detection of the interstices between teeth, and the approach for the identification of the type of tooth are described, as well as the algorithm for the reconstruction of the surface of each type of tooth. A new approach for the detection of feature points, called the watershed algorithm, is described in detail. The algorithm is a two-stage procedure which tracks the position of local minima at four different scales and produces a final map of the position of the minima. Experimental results of the application of the watershed algorithm on actual 3D images of dental imprints are presented for molars, premolars and canines. The segmentation approach for the analysis of the shape of incisors is also described in detail.

  16. Design and fabrication of cast orthopedic implants with freeform surface textures from 3-D printed ceramic shell.

    PubMed

    Curodeau, A; Sachs, E; Caldarise, S

    2000-09-01

    Three-dimensional printing is a solid freeform fabrication process, which creates parts directly from a computer model. The parts are built by repetitively spreading a layer of powder and selectively joining the powder in the layer by ink-jet printing of a binder material. 3D printing was applied to the fabrication of sub-millimeter surface textures with overhang and undercut geometries for use in orthopedic prostheses as bony ingrowth structures. 3D printing is used to fabricate ceramic molds of alumina powder and silica binder, and these molds are used to cast the bony ingrowth surfaces of Co-Cr (ASTM F75) alloy. Minimum positive feature sizes of the ceramic mold and, therefore, minimum negative feature sizes of castings were determined to be approximately 200 x 200 x 175 microm and were limited by the strength of ceramic needed to withstand handling. Minimum negative feature sizes in the ceramic mold and, therefore, minimum positive features in the casting were found to be approximately 350 x 350 x 175 microm and were determined by limitations on removal of powder from the ceramic and the pressure required to fill these small features with molten metal during casting. Textures were designed with 5 layers of distinct geometric definition, allowing for the design of overhung geometry with overall porosity ranging from 30-70%. Features as small as 350 x 350 x 200 microm were included in these designs and successfully cast.

  17. 3D automatic liver segmentation using feature-constrained Mahalanobis distance in CT images.

    PubMed

    Salman Al-Shaikhli, Saif Dawood; Yang, Michael Ying; Rosenhahn, Bodo

    2016-08-01

    Automatic 3D liver segmentation is a fundamental step in the liver disease diagnosis and surgery planning. This paper presents a novel fully automatic algorithm for 3D liver segmentation in clinical 3D computed tomography (CT) images. Based on image features, we propose a new Mahalanobis distance cost function using an active shape model (ASM). We call our method MD-ASM. Unlike the standard active shape model (ST-ASM), the proposed method introduces a new feature-constrained Mahalanobis distance cost function to measure the distance between the generated shape during the iterative step and the mean shape model. The proposed Mahalanobis distance function is learned from a public database of liver segmentation challenge (MICCAI-SLiver07). As a refinement step, we propose the use of a 3D graph-cut segmentation. Foreground and background labels are automatically selected using texture features of the learned Mahalanobis distance. Quantitatively, the proposed method is evaluated using two clinical 3D CT scan databases (MICCAI-SLiver07 and MIDAS). The evaluation of the MICCAI-SLiver07 database is obtained by the challenge organizers using five different metric scores. The experimental results demonstrate the availability of the proposed method by achieving an accurate liver segmentation compared to the state-of-the-art methods. PMID:26501155

  18. Dynamical Systems Analysis of Fully 3D Ocean Features

    NASA Astrophysics Data System (ADS)

    Pratt, L. J.

    2011-12-01

    Dynamical systems analysis of transport and stirring processes has been developed most thoroughly for 2D flow fields. The calculation of manifolds, turnstile lobes, transport barriers, etc. based on observations of the ocean is most often conducted near the sea surface, whereas analyses at depth, usually carried out with model output, is normally confined to constant-z surfaces. At the meoscale and larger, ocean flows are quasi 2D, but smaller scale (submesoscale) motions, including mixed layer phenomena with significant vertical velocity, may be predominantly 3D. The zoology of hyperbolic trajectories becomes richer in such cases and their attendant manifolds are much more difficult to calculate. I will describe some of the basic geometrical features and corresponding Lagrangian Coherent Features expected to arise in upper ocean fronts, eddies, and Langmuir circulations. Traditional GFD models such as the rotating can flow may capture the important generic features. The dynamical systems approach is most helpful when these features are coherent and persistent and the implications and difficulties for this requirement in fully 3D flows will also be discussed.

  19. The extraction of 3D shape from texture and shading in the human brain.

    PubMed

    Georgieva, Svetlana S; Todd, James T; Peeters, Ronald; Orban, Guy A

    2008-10-01

    We used functional magnetic resonance imaging to investigate the human cortical areas involved in processing 3-dimensional (3D) shape from texture (SfT) and shading. The stimuli included monocular images of randomly shaped 3D surfaces and a wide variety of 2-dimensional (2D) controls. The results of both passive and active experiments reveal that the extraction of 3D SfT involves the bilateral caudal inferior temporal gyrus (caudal ITG), lateral occipital sulcus (LOS) and several bilateral sites along the intraparietal sulcus. These areas are largely consistent with those involved in the processing of 3D shape from motion and stereo. The experiments also demonstrate, however, that the analysis of 3D shape from shading is primarily restricted to the caudal ITG areas. Additional results from psychophysical experiments reveal that this difference in neuronal substrate cannot be explained by a difference in strength between the 2 cues. These results underscore the importance of the posterior part of the lateral occipital complex for the extraction of visual 3D shape information from all depth cues, and they suggest strongly that the importance of shading is diminished relative to other cues for the analysis of 3D shape in parietal regions.

  20. THE THOMSON SURFACE. III. TRACKING FEATURES IN 3D

    SciTech Connect

    Howard, T. A.; DeForest, C. E.; Tappin, S. J.; Odstrcil, D.

    2013-03-01

    In this, the final installment in a three-part series on the Thomson surface, we present simulated observations of coronal mass ejections (CMEs) observed by a hypothetical polarizing white light heliospheric imager. Thomson scattering yields a polarization signal that can be exploited to locate observed features in three dimensions relative to the Thomson surface. We consider how the appearance of the CME changes with the direction of trajectory, using simulations of a simple geometrical shape and also of a more realistic CME generated using the ENLIL model. We compare the appearance in both unpolarized B and polarized pB light, and show that there is a quantifiable difference in the measured brightness of a CME between unpolarized and polarized observations. We demonstrate a technique for using this difference to extract the three-dimensional (3D) trajectory of large objects such as CMEs. We conclude with a discussion on how a polarizing heliospheric imager could be used to extract 3D trajectory information about CMEs or other observed features.

  1. Assist feature printability prediction by 3-D resist profile reconstruction

    NASA Astrophysics Data System (ADS)

    Zheng, Xin; Huang, Jensheng; Chin, Fook; Kazarian, Aram; Kuo, Chun-Chieh

    2012-06-01

    properties may then be used to optimize the printability vs. efficacy of an SRAF either prior to or during an Optical Proximity Correction (OPC) run. The process models that are used during OPC have never been able to reliably predict which SRAFs will print. This appears to be due to the fact that OPC process models are generally created using data that does not include printed subresolution patterns. An enhancement to compact modeling capability to predict Assist Features (AF) printability is developed and discussed. A hypsometric map representing 3-D resist profile was built by applying a first principle approximation to estimate the "energy loss" from the resist top to bottom. Such a 3-D resist profile is an extrapolation of a well calibrated traditional OPC model without any additional information. Assist features are detected at either top of resist (dark field) or bottom of resist (bright field). Such detection can be done by just extracting top or bottom resist models from our 3-D resist model. There is no measurement of assist features needed when we build AF but it can be included if interested but focusing on resist calibration to account for both exposure dosage and focus change sensitivities. This approach significantly increases resist model's capability for predicting printed SRAF accuracy. And we don't need to calibrate an SRAF model in addition to the OPC model. Without increase in computation time, this compact model can draw assist feature contour with real placement and size at any vertical plane. The result is compared and validated with 3-D rigorous modeling as well as SEM images. Since this method does not change any form of compact modeling, it can be integrated into current MBAF solutions without any additional work.

  2. Registration of Feature-Poor 3D Measurements from Fringe Projection

    PubMed Central

    von Enzberg, Sebastian; Al-Hamadi, Ayoub; Ghoneim, Ahmed

    2016-01-01

    We propose a novel method for registration of partly overlapping three-dimensional surface measurements for stereo-based optical sensors using fringe projection. Based on two-dimensional texture matching, it allows global registration of surfaces with poor and ambiguous three-dimensional features, which are common to surface inspection applications. No prior information about relative sensor position is necessary, which makes our approach suitable for semi-automatic and manual measurement. The algorithm is robust and works with challenging measurements, including uneven illumination, surfaces with specular reflection as well as sparsely textured surfaces. We show that precisions of 1 mm and below can be achieved along the surfaces, which is necessary for further local 3D registration. PMID:26927106

  3. a Low-Cost and Portable System for 3d Reconstruction of Texture-Less Objects

    NASA Astrophysics Data System (ADS)

    Hosseininaveh, A.; Yazdan, R.; Karami, A.; Moradi, M.; Ghorbani, F.

    2015-12-01

    The optical methods for 3D modelling of objects can be classified into two categories including image-based and range-based methods. Structure from Motion is one of the image-based methods implemented in commercial software. In this paper, a low-cost and portable system for 3D modelling of texture-less objects is proposed. This system includes a rotating table designed and developed by using a stepper motor and a very light rotation plate. The system also has eight laser light sources with very dense and strong beams which provide a relatively appropriate pattern on texture-less objects. In this system, regarding to the step of stepper motor, images are semi automatically taken by a camera. The images can be used in structure from motion procedures implemented in Agisoft software.To evaluate the performance of the system, two dark objects were used. The point clouds of these objects were obtained by spraying a light powders on the objects and exploiting a GOM laser scanner. Then these objects were placed on the proposed turntable. Several convergent images were taken from each object while the laser light sources were projecting the pattern on the objects. Afterward, the images were imported in VisualSFM as a fully automatic software package for generating an accurate and complete point cloud. Finally, the obtained point clouds were compared to the point clouds generated by the GOM laser scanner. The results showed the ability of the proposed system to produce a complete 3D model from texture-less objects.

  4. Extracting textural features from tactile sensors.

    PubMed

    Edwards, J; Lawry, J; Rossiter, J; Melhuish, C

    2008-09-01

    This paper describes an experiment to quantify texture using an artificial finger equipped with a microphone to detect frictional sound. Using a microphone to record tribological data is a biologically inspired approach that emulates the Pacinian corpuscle. Artificial surfaces were created to constrain the subsequent analysis to specific textures. Recordings of the artificial surfaces were made to create a library of frictional sounds for data analysis. These recordings were mapped to the frequency domain using fast Fourier transforms for direct comparison, manipulation and quantifiable analysis. Numerical features such as modal frequency and average value were calculated to analyze the data and compared with attributes generated from principal component analysis (PCA). It was found that numerical features work well for highly constrained data but cannot classify multiple textural elements. PCA groups textures according to a natural similarity. Classification of the recordings using k nearest neighbors shows a high accuracy for PCA data. Clustering of the PCA data shows that similar discs are grouped together with few classification errors. In contrast, clustering of numerical features produces erroneous classification by splitting discs between clusters. The temperature of the finger is shown to have a direct relation to some of the features and subsequent data in PCA. PMID:18583731

  5. Very fast road database verification using textured 3D city models obtained from airborne imagery

    NASA Astrophysics Data System (ADS)

    Bulatov, Dimitri; Ziems, Marcel; Rottensteiner, Franz; Pohl, Melanie

    2014-10-01

    Road databases are known to be an important part of any geodata infrastructure, e.g. as the basis for urban planning or emergency services. Updating road databases for crisis events must be performed quickly and with the highest possible degree of automation. We present a semi-automatic algorithm for road verification using textured 3D city models, starting from aerial or even UAV-images. This algorithm contains two processes, which exchange input and output, but basically run independently from each other. These processes are textured urban terrain reconstruction and road verification. The first process contains a dense photogrammetric reconstruction of 3D geometry of the scene using depth maps. The second process is our core procedure, since it contains various methods for road verification. Each method represents a unique road model and a specific strategy, and thus is able to deal with a specific type of roads. Each method is designed to provide two probability distributions, where the first describes the state of a road object (correct, incorrect), and the second describes the state of its underlying road model (applicable, not applicable). Based on the Dempster-Shafer Theory, both distributions are mapped to a single distribution that refers to three states: correct, incorrect, and unknown. With respect to the interaction of both processes, the normalized elevation map and the digital orthophoto generated during 3D reconstruction are the necessary input - together with initial road database entries - for the road verification process. If the entries of the database are too obsolete or not available at all, sensor data evaluation enables classification of the road pixels of the elevation map followed by road map extraction by means of vectorization and filtering of the geometrically and topologically inconsistent objects. Depending on the time issue and availability of a geo-database for buildings, the urban terrain reconstruction procedure has semantic models

  6. Inlining 3d Reconstruction, Multi-Source Texture Mapping and Semantic Analysis Using Oblique Aerial Imagery

    NASA Astrophysics Data System (ADS)

    Frommholz, D.; Linkiewicz, M.; Poznanska, A. M.

    2016-06-01

    This paper proposes an in-line method for the simplified reconstruction of city buildings from nadir and oblique aerial images that at the same time are being used for multi-source texture mapping with minimal resampling. Further, the resulting unrectified texture atlases are analyzed for façade elements like windows to be reintegrated into the original 3D models. Tests on real-world data of Heligoland/ Germany comprising more than 800 buildings exposed a median positional deviation of 0.31 m at the façades compared to the cadastral map, a correctness of 67% for the detected windows and good visual quality when being rendered with GPU-based perspective correction. As part of the process building reconstruction takes the oriented input images and transforms them into dense point clouds by semi-global matching (SGM). The point sets undergo local RANSAC-based regression and topology analysis to detect adjacent planar surfaces and determine their semantics. Based on this information the roof, wall and ground surfaces found get intersected and limited in their extension to form a closed 3D building hull. For texture mapping the hull polygons are projected into each possible input bitmap to find suitable color sources regarding the coverage and resolution. Occlusions are detected by ray-casting a full-scale digital surface model (DSM) of the scene and stored in pixel-precise visibility maps. These maps are used to derive overlap statistics and radiometric adjustment coefficients to be applied when the visible image parts for each building polygon are being copied into a compact texture atlas without resampling whenever possible. The atlas bitmap is passed to a commercial object-based image analysis (OBIA) tool running a custom rule set to identify windows on the contained façade patches. Following multi-resolution segmentation and classification based on brightness and contrast differences potential window objects are evaluated against geometric constraints and

  7. 3D lung image retrieval using localized features

    NASA Astrophysics Data System (ADS)

    Depeursinge, Adrien; Zrimec, Tatjana; Busayarat, Sata; Müller, Henning

    2011-03-01

    The interpretation of high-resolution computed tomography (HRCT) images of the chest showing disorders of the lung tissue associated with interstitial lung diseases (ILDs) is time-consuming and requires experience. Whereas automatic detection and quantification of the lung tissue patterns showed promising results in several studies, its aid for the clinicians is limited to the challenge of image interpretation, letting the radiologists with the problem of the final histological diagnosis. Complementary to lung tissue categorization, providing visually similar cases using content-based image retrieval (CBIR) is in line with the clinical workflow of the radiologists. In a preliminary study, a Euclidean distance based on volume percentages of five lung tissue types was used as inter-case distance for CBIR. The latter showed the feasibility of retrieving similar histological diagnoses of ILD based on visual content, although no localization information was used for CBIR. However, to retrieve and show similar images with pathology appearing at a particular lung position was not possible. In this work, a 3D localization system based on lung anatomy is used to localize low-level features used for CBIR. When compared to our previous study, the introduction of localization features allows improving early precision for some histological diagnoses, especially when the region of appearance of lung tissue disorders is important.

  8. 3D displacement field measurement with correlation based on the micro-geometrical surface texture

    NASA Astrophysics Data System (ADS)

    Bubaker-Isheil, Halima; Serri, Jérôme; Fontaine, Jean-François

    2011-07-01

    Image correlation methods are widely used in experimental mechanics to obtain displacement field measurements. Currently, these methods are applied using digital images of the initial and deformed surfaces sprayed with black or white paint. Speckle patterns are then captured and the correlation is performed with a high degree of accuracy to an order of 0.01 pixels. In 3D, however, stereo-correlation leads to a lower degree of accuracy. Correlation techniques are based on the search for a sub-image (or pattern) displacement field. The work presented in this paper introduces a new correlation-based approach for 3D displacement field measurement that uses an additional 3D laser scanner and a CMM (Coordinate Measurement Machine). Unlike most existing methods that require the presence of markers on the observed object (such as black speckle, grids or random patterns), this approach relies solely on micro-geometrical surface textures such as waviness, roughness and aperiodic random defects. The latter are assumed to remain sufficiently small thus providing an adequate estimate of the particle displacement. The proposed approach can be used in a wide range of applications such as sheet metal forming with large strains. The method proceeds by first obtaining cloud points using the 3D laser scanner mounted on a CMM. These points are used to create 2D maps that are then correlated. In this respect, various criteria have been investigated for creating maps consisting of patterns, which facilitate the correlation procedure. Once the maps are created, the correlation between both configurations (initial and moved) is carried out using traditional methods developed for field measurements. Measurement validation was conducted using experiments in 2D and 3D with good results for rigid displacements in 2D, 3D and 2D rotations.

  9. Within-guild dietary discrimination from 3-D textural analysis of tooth microwear in insectivorous mammals

    PubMed Central

    Purnell, M A; Crumpton, N; Gill, P G; Jones, G; Rayfield, E J

    2013-01-01

    Resource exploitation and competition for food are important selective pressures in animal evolution. A number of recent investigations have focused on linkages between diversification, trophic morphology and diet in bats, partly because their roosting habits mean that for many bat species diet can be quantified relatively easily through faecal analysis. Dietary analysis in mammals is otherwise invasive, complicated, time consuming and expensive. Here we present evidence from insectivorous bats that analysis of three-dimensional (3-D) textures of tooth microwear using International Organization for Standardization (ISO) roughness parameters derived from sub-micron surface data provides an additional, powerful tool for investigation of trophic resource exploitation in mammals. Our approach, like scale-sensitive fractal analysis, offers considerable advantages over two-dimensional (2-D) methods of microwear analysis, including improvements in robustness, repeatability and comparability of studies. Our results constitute the first analysis of microwear textures in carnivorous mammals based on ISO roughness parameters. They demonstrate that the method is capable of dietary discrimination, even between cryptic species with subtly different diets within trophic guilds, and even when sample sizes are small. We find significant differences in microwear textures between insectivore species whose diet contains different proportions of ‘hard’ prey (such as beetles) and ‘soft’ prey (such as moths), and multivariate analyses are able to distinguish between species with different diets based solely on their tooth microwear textures. Our results show that, compared with previous 2-D analyses of microwear in bats, ISO roughness parameters provide a much more sophisticated characterization of the nature of microwear surfaces and can yield more robust and subtle dietary discrimination. ISO-based textural analysis of tooth microwear thus has a useful role to play

  10. 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.

  11. Wood Recognition Using Image Texture Features

    PubMed Central

    Wang, Hang-jun; Zhang, Guang-qun; Qi, Heng-nian

    2013-01-01

    Inspired by theories of higher local order autocorrelation (HLAC), this paper presents a simple, novel, yet very powerful approach for wood recognition. The method is suitable for wood database applications, which are of great importance in wood related industries and administrations. At the feature extraction stage, a set of features is extracted from Mask Matching Image (MMI). The MMI features preserve the mask matching information gathered from the HLAC methods. The texture information in the image can then be accurately extracted from the statistical and geometrical features. In particular, richer information and enhanced discriminative power is achieved through the length histogram, a new histogram that embodies the width and height histograms. The performance of the proposed approach is compared to the state-of-the-art HLAC approaches using the wood stereogram dataset ZAFU WS 24. By conducting extensive experiments on ZAFU WS 24, we show that our approach significantly improves the classification accuracy. PMID:24146821

  12. A 3D printed fluidic device that enables integrated features.

    PubMed

    Anderson, Kari B; Lockwood, Sarah Y; Martin, R Scott; Spence, Dana M

    2013-06-18

    Fluidic devices fabricated using conventional soft lithography are well suited as prototyping methods. Three-dimensional (3D) printing, commonly used for producing design prototypes in industry, allows for one step production of devices. 3D printers build a device layer by layer based on 3D computer models. Here, a reusable, high throughput, 3D printed fluidic device was created that enables flow and incorporates a membrane above a channel in order to study drug transport and affect cells. The device contains 8 parallel channels, 3 mm wide by 1.5 mm deep, connected to a syringe pump through standard, threaded fittings. The device was also printed to allow integration with commercially available membrane inserts whose bottoms are constructed of a porous polycarbonate membrane; this insert enables molecular transport to occur from the channel to above the well. When concentrations of various antibiotics (levofloxacin and linezolid) are pumped through the channels, approximately 18-21% of the drug migrates through the porous membrane, providing evidence that this device will be useful for studies where drug effects on cells are investigated. Finally, we show that mammalian cells cultured on this membrane can be affected by reagents flowing through the channels. Specifically, saponin was used to compromise cell membranes, and a fluorescent label was used to monitor the extent, resulting in a 4-fold increase in fluorescence for saponin treated cells.

  13. Accurate 3d Textured Models of Vessels for the Improvement of the Educational Tools of a Museum

    NASA Astrophysics Data System (ADS)

    Soile, S.; Adam, K.; Ioannidis, C.; Georgopoulos, A.

    2013-02-01

    Besides the demonstration of the findings, modern museums organize educational programs which aim to experience and knowledge sharing combined with entertainment rather than to pure learning. Toward that effort, 2D and 3D digital representations are gradually replacing the traditional recording of the findings through photos or drawings. The present paper refers to a project that aims to create 3D textured models of two lekythoi that are exhibited in the National Archaeological Museum of Athens in Greece; on the surfaces of these lekythoi scenes of the adventures of Odysseus are depicted. The project is expected to support the production of an educational movie and some other relevant interactive educational programs for the museum. The creation of accurate developments of the paintings and of accurate 3D models is the basis for the visualization of the adventures of the mythical hero. The data collection was made by using a structured light scanner consisting of two machine vision cameras that are used for the determination of geometry of the object, a high resolution camera for the recording of the texture, and a DLP projector. The creation of the final accurate 3D textured model is a complicated and tiring procedure which includes the collection of geometric data, the creation of the surface, the noise filtering, the merging of individual surfaces, the creation of a c-mesh, the creation of the UV map, the provision of the texture and, finally, the general processing of the 3D textured object. For a better result a combination of commercial and in-house software made for the automation of various steps of the procedure was used. The results derived from the above procedure were especially satisfactory in terms of accuracy and quality of the model. However, the procedure was proved to be time consuming while the use of various software packages presumes the services of a specialist.

  14. Sensitivity and specificity of 3-D texture analysis of lung parenchyma is better than 2-D for discrimination of lung pathology in stage 0 COPD

    NASA Astrophysics Data System (ADS)

    Xu, Ye; Sonka, Milan; McLennan, Geoffrey; Guo, Junfeng; Hoffman, Eric

    2005-04-01

    Lung parenchyma evaluation via multidetector-row CT (MDCT), has significantly altered clinical practice in the early detection of lung disease. Our goal is to enhance our texture-based tissue classification ability to differentiate early pathologic processes by extending our 2-D Adaptive Multiple Feature Method (AMFM) to 3-D AMFM. We performed MDCT on 34 human volunteers in five categories: emphysema in severe Chronic Obstructive Pulmonary Disease (COPD) as EC, emphysema in mild COPD (MC), normal appearing lung in COPD (NC), non-smokers with normal lung function (NN), smokers with normal function (NS). We volumetrically excluded the airway and vessel regions, calculated 24 volumetric texture features for each Volume of Interest (VOI); and used Bayesian rules for discrimination. Leave-one-out and half-half methods were used for testing. Sensitivity, specificity and accuracy were calculated. The accuracy of the leave-one-out method for the four-class classification in the form of 3-D/2-D is: EC: 84.9%/70.7%, MC: 89.8%/82.7%; NC: 87.5.0%/49.6%; NN: 100.0%/60.0%. The accuracy of the leave-one-out method for the two-class classification in the form of 3-D/2-D is: NN: 99.3%/71.6%; NS: 99.7%/74.5%. We conclude that 3-D AMFM analysis of the lung parenchyma improves discrimination compared to 2-D analysis of the same images.

  15. Design, fabrication, and implementation of voxel-based 3D printed textured phantoms for task-based image quality assessment in CT

    NASA Astrophysics Data System (ADS)

    Solomon, Justin; Ba, Alexandre; Diao, Andrew; Lo, Joseph; Bier, Elianna; Bochud, François; Gehm, Michael; Samei, Ehsan

    2016-03-01

    In x-ray computed tomography (CT), task-based image quality studies are typically performed using uniform background phantoms with low-contrast signals. Such studies may have limited clinical relevancy for modern non-linear CT systems due to possible influence of background texture on image quality. The purpose of this study was to design and implement anatomically informed textured phantoms for task-based assessment of low-contrast detection. Liver volumes were segmented from 23 abdominal CT cases. The volumes were characterized in terms of texture features from gray-level co-occurrence and run-length matrices. Using a 3D clustered lumpy background (CLB) model, a fitting technique based on a genetic optimization algorithm was used to find the CLB parameters that were most reflective of the liver textures, accounting for CT system factors of spatial blurring and noise. With the modeled background texture as a guide, a cylinder phantom (165 mm in diameter and 30 mm height) was designed, containing 20 low-contrast spherical signals (6 mm in diameter at targeted contrast levels of ~3.2, 5.2, 7.2, 10, and 14 HU, 4 repeats per signal). The phantom was voxelized and input into a commercial multi-material 3D printer (Object Connex 350), with custom software for voxel-based printing. Using principles of digital half-toning and dithering, the 3D printer was programmed to distribute two base materials (VeroWhite and TangoPlus, nominal voxel size of 42x84x30 microns) to achieve the targeted spatial distribution of x-ray attenuation properties. The phantom was used for task-based image quality assessment of a clinically available iterative reconstruction algorithm (Sinogram Affirmed Iterative Reconstruction, SAFIRE) using a channelized Hotelling observer paradigm. Images of the textured phantom and a corresponding uniform phantom were acquired at six dose levels and observer model performance was estimated for each condition (5 contrasts x 6 doses x 2 reconstructions x 2

  16. Using GNG to improve 3D feature extraction--application to 6DoF egomotion.

    PubMed

    Viejo, Diego; Garcia, Jose; Cazorla, Miguel; Gil, David; Johnsson, Magnus

    2012-08-01

    Several recent works deal with 3D data in mobile robotic problems, e.g. mapping or egomotion. Data comes from any kind of sensor such as stereo vision systems, time of flight cameras or 3D lasers, providing a huge amount of unorganized 3D data. In this paper, we describe an efficient method to build complete 3D models from a Growing Neural Gas (GNG). The GNG is applied to the 3D raw data and it reduces both the subjacent error and the number of points, keeping the topology of the 3D data. The GNG output is then used in a 3D feature extraction method. We have performed a deep study in which we quantitatively show that the use of GNG improves the 3D feature extraction method. We also show that our method can be applied to any kind of 3D data. The 3D features obtained are used as input in an Iterative Closest Point (ICP)-like method to compute the 6DoF movement performed by a mobile robot. A comparison with standard ICP is performed, showing that the use of GNG improves the results. Final results of 3D mapping from the egomotion calculated are also shown. PMID:22386789

  17. Optical devices featuring textured semiconductor layers

    DOEpatents

    Moustakas, Theodore D.; Cabalu, Jasper S.

    2011-10-11

    A semiconductor sensor, solar cell or emitter, or a precursor therefor, has a substrate and one or more textured semiconductor layers deposited onto the substrate. The textured layers enhance light extraction or absorption. Texturing in the region of multiple quantum wells greatly enhances internal quantum efficiency if the semiconductor is polar and the quantum wells are grown along the polar direction. Electroluminescence of LEDs of the invention is dichromatic, and results in variable color LEDs, including white LEDs, without the use of phosphor.

  18. Optical devices featuring textured semiconductor layers

    DOEpatents

    Moustakas, Theodore D.; Cabalu, Jasper S.

    2012-08-07

    A semiconductor sensor, solar cell or emitter, or a precursor therefor, has a substrate and one or more textured semiconductor layers deposited onto the substrate. The textured layers enhance light extraction or absorption. Texturing in the region of multiple quantum wells greatly enhances internal quantum efficiency if the semiconductor is polar and the quantum wells are grown along the polar direction. Electroluminescence of LEDs of the invention is dichromatic, and results in variable color LEDs, including white LEDs, without the use of phosphor.

  19. Exploring Brushlet Based 3D Textures in Transfer Function Specification for Direct Volume Rendering of Abdominal Organs.

    PubMed

    Alper Selver, M

    2015-02-01

    Intuitive and differentiating domains for transfer function (TF) specification for direct volume rendering is an important research area for producing informative and useful 3D images. One of the emerging branches of this research is the texture based transfer functions. Although several studies in two, three, and four dimensional image processing show the importance of using texture information, these studies generally focus on segmentation. However, TFs can also be built effectively using appropriate texture information. To accomplish this, methods should be developed to collect wide variety of shape, orientation, and texture of biological tissues and organs. In this study, volumetric data (i.e., domain of a TF) is enhanced using brushlet expansion, which represents both low and high frequency textured structures at different quadrants in transform domain. Three methods (i.e., expert based manual, atlas and machine learning based automatic) are proposed for selection of the quadrants. Non-linear manipulation of the complex brushlet coefficients is also used prior to the tiling of selected quadrants and reconstruction of the volume. Applications to abdominal data sets acquired with CT, MR, and PET show that the proposed volume enhancement effectively improves the quality of 3D rendering using well-known TF specification techniques. PMID:26357028

  20. Feature edge extraction from 3D triangular meshes using a thinning algorithm

    NASA Astrophysics Data System (ADS)

    Nomura, Masaru; Hamada, Nozomu

    2001-11-01

    Highly detailed geometric models, which are represented as dense triangular meshes are becoming popular in computer graphics. Since such 3D meshes often have huge information, we require some methods to treat them efficiently in the 3D mesh processing such as, surface simplification, subdivision surface, curved surface approximation and morphing. In these applications, we often extract features of 3D meshes such as feature vertices and feature edges in preprocessing step. An automatic extraction method of feature edges is treated in this study. In order to realize the feature edge extraction method, we first introduce the concavity and convexity evaluation value. Then the histogram of the concavity and convexity evaluation value is used to separate the feature edge region. We apply a thinning algorithm, which is used in 2D binary image processing. It is shown that the proposed method can extract appropriate feature edges from 3D meshes.

  1. Computation of morphological texture features for medical imaging applications

    NASA Astrophysics Data System (ADS)

    Patel, Manish J.; Kehtarnavaz, Nasser; Dougherty, Edward R.; Batman, Sinan; Sivakumar, Krishnamoorthy; Popov, Antony T.

    1998-06-01

    Texture is an important attribute which is widely used in various image analysis applications. Among texture features, morphological texture features are least utilized in medical image analysis. From a computational standpoint, extracting morphological texture features from an image is a challenging task. The computational problem is made even greater in medical imaging applications where large images such as mammograms are to be analyzed. This paper discusses an efficient method to compute morphological texture features for any geometry of a structuring element corresponding to a texture type. A benchmarking of the code on three machines (Sun SPARC 20, Pentium II based Dell 400 workstation, and SGI Power Challenge 10000XL) as well as a parallel processing implementation was performed to obtain an optimum processing configuration. A sample processed mammogram is shown to illustrate the code outcome.

  2. SU-E-QI-17: Dependence of 3D/4D PET Quantitative Image Features On Noise

    SciTech Connect

    Oliver, J; Budzevich, M; Zhang, G; Latifi, K; Dilling, T; Balagurunathan, Y; Gu, Y; Grove, O; Feygelman, V; Gillies, R; Moros, E; Lee, H.

    2014-06-15

    Purpose: Quantitative imaging is a fast evolving discipline where a large number of features are extracted from images; i.e., radiomics. Some features have been shown to have diagnostic, prognostic and predictive value. However, they are sensitive to acquisition and processing factors; e.g., noise. In this study noise was added to positron emission tomography (PET) images to determine how features were affected by noise. Methods: Three levels of Gaussian noise were added to 8 lung cancer patients PET images acquired in 3D mode (static) and using respiratory tracking (4D); for the latter images from one of 10 phases were used. A total of 62 features: 14 shape, 19 intensity (1stO), 18 GLCM textures (2ndO; from grey level co-occurrence matrices) and 11 RLM textures (2ndO; from run-length matrices) features were extracted from segmented tumors. Dimensions of GLCM were 256×256, calculated using 3D images with a step size of 1 voxel in 13 directions. Grey levels were binned into 256 levels for RLM and features were calculated in all 13 directions. Results: Feature variation generally increased with noise. Shape features were the most stable while RLM were the most unstable. Intensity and GLCM features performed well; the latter being more robust. The most stable 1stO features were compactness, maximum and minimum length, standard deviation, root-mean-squared, I30, V10-V90, and entropy. The most stable 2ndO features were entropy, sum-average, sum-entropy, difference-average, difference-variance, difference-entropy, information-correlation-2, short-run-emphasis, long-run-emphasis, and run-percentage. In general, features computed from images from one of the phases of 4D scans were more stable than from 3D scans. Conclusion: This study shows the need to characterize image features carefully before they are used in research and medical applications. It also shows that the performance of features, and thereby feature selection, may be assessed in part by noise analysis.

  3. Subjective and Objective Video Quality Assessment of 3D Synthesized Views With Texture/Depth Compression Distortion.

    PubMed

    Liu, Xiangkai; Zhang, Yun; Hu, Sudeng; Kwong, Sam; Kuo, C-C Jay; Peng, Qiang

    2015-12-01

    The quality assessment for synthesized video with texture/depth compression distortion is important for the design, optimization, and evaluation of the multi-view video plus depth (MVD)-based 3D video system. In this paper, the subjective and objective studies for synthesized view assessment are both conducted. First, a synthesized video quality database with texture/depth compression distortion is presented with subjective scores given by 56 subjects. The 140 videos are synthesized from ten MVD sequences with different texture/depth quantization combinations. Second, a full reference objective video quality assessment (VQA) method is proposed concerning about the annoying temporal flicker distortion and the change of spatio-temporal activity in the synthesized video. The proposed VQA algorithm has a good performance evaluated on the entire synthesized video quality database, and is particularly prominent on the subsets which have significant temporal flicker distortion induced by depth compression and view synthesis process. PMID:26292342

  4. Assessing the biomechanical strength of trabecular bone in vitro using 3D anisotropic nonlinear texture measures: the scaling vector method

    NASA Astrophysics Data System (ADS)

    Monetti, Roberto A.; Bohm, Holger F.; Muller, Dirk; Rummeny, Ernst J.; Link, Thomas M.; Rath, Christoph W.

    2004-05-01

    We introduce the scaling vector method (SVM): a technique to obtain local non-linear structural information from data sets suitable in cases where anisotropy plays an important role. We apply the SVM to High Resolution Magnetic Resonance Images (HRMRI) of human proximal femur specimens IN VITRO which contain a large portion of bone tissue forming a complex network of mineralized trabeculae oriented along the major stress lines. By means of the SVM, we extract a 3D non-linear local anisotropic texture measure which we use to compare with similar isotropic texture measures, bone mineral density (BMD) and standard isotropic 2D (linear) morphometric parameters in the prediction of the biomechanical properties of the trabecular bone. Our results show that structural non-linear anisotropic texture measures which account for the preferential direction of the trabeculae are superior to isotropic and bulk measures in the prediction of the mechanical properties of the human proximal femur in vitro.

  5. Optical devices featuring nonpolar textured semiconductor layers

    DOEpatents

    Moustakas, Theodore D; Moldawer, Adam; Bhattacharyya, Anirban; Abell, Joshua

    2013-11-26

    A semiconductor emitter, or precursor therefor, has a substrate and one or more textured semiconductor layers deposited onto the substrate in a nonpolar orientation. The textured layers enhance light extraction, and the use of nonpolar orientation greatly enhances internal quantum efficiency compared to conventional devices. Both the internal and external quantum efficiencies of emitters of the invention can be 70-80% or higher. The invention provides highly efficient light emitting diodes suitable for solid state lighting.

  6. A novel 3D wavelet based filter for visualizing features in noisy biological data

    SciTech Connect

    Moss, W C; Haase, S; Lyle, J M; Agard, D A; Sedat, J W

    2005-01-05

    We have developed a 3D wavelet-based filter for visualizing structural features in volumetric data. The only variable parameter is a characteristic linear size of the feature of interest. The filtered output contains only those regions that are correlated with the characteristic size, thus denoising the image. We demonstrate the use of the filter by applying it to 3D data from a variety of electron microscopy samples including low contrast vitreous ice cryogenic preparations, as well as 3D optical microscopy specimens.

  7. A Multiscale Constraints Method Localization of 3D Facial Feature Points

    PubMed Central

    Li, Hong-an; Zhang, Yongxin; Li, Zhanli; Li, Huilin

    2015-01-01

    It is an important task to locate facial feature points due to the widespread application of 3D human face models in medical fields. In this paper, we propose a 3D facial feature point localization method that combines the relative angle histograms with multiscale constraints. Firstly, the relative angle histogram of each vertex in a 3D point distribution model is calculated; then the cluster set of the facial feature points is determined using the cluster algorithm. Finally, the feature points are located precisely according to multiscale integral features. The experimental results show that the feature point localization accuracy of this algorithm is better than that of the localization method using the relative angle histograms. PMID:26539244

  8. Classification of Informal Settlements Through the Integration of 2d and 3d Features Extracted from Uav Data

    NASA Astrophysics Data System (ADS)

    Gevaert, C. M.; Persello, C.; Sliuzas, R.; Vosselman, G.

    2016-06-01

    Unmanned Aerial Vehicles (UAVs) are capable of providing very high resolution and up-to-date information to support informal settlement upgrading projects. In order to provide accurate basemaps, urban scene understanding through the identification and classification of buildings and terrain is imperative. However, common characteristics of informal settlements such as small, irregular buildings with heterogeneous roof material and large presence of clutter challenge state-of-the-art algorithms. Especially the dense buildings and steeply sloped terrain cause difficulties in identifying elevated objects. This work investigates how 2D radiometric and textural features, 2.5D topographic features, and 3D geometric features obtained from UAV imagery can be integrated to obtain a high classification accuracy in challenging classification problems for the analysis of informal settlements. It compares the utility of pixel-based and segment-based features obtained from an orthomosaic and DSM with point-based and segment-based features extracted from the point cloud to classify an unplanned settlement in Kigali, Rwanda. Findings show that the integration of 2D and 3D features leads to higher classification accuracies.

  9. Fuzzy zoning for feature matching technique in 3D reconstruction of nasal endoscopic images.

    PubMed

    Rattanalappaiboon, Surapong; Bhongmakapat, Thongchai; Ritthipravat, Panrasee

    2015-12-01

    3D reconstruction from nasal endoscopic images greatly supports an otolaryngologist in examining nasal passages, mucosa, polyps, sinuses, and nasopharyx. In general, structure from motion is a popular technique. It consists of four main steps; (1) camera calibration, (2) feature extraction, (3) feature matching, and (4) 3D reconstruction. Scale Invariant Feature Transform (SIFT) algorithm is normally used for both feature extraction and feature matching. However, SIFT algorithm relatively consumes computational time particularly in the feature matching process because each feature in an image of interest is compared with all features in the subsequent image in order to find the best matched pair. A fuzzy zoning approach is developed for confining feature matching area. Matching between two corresponding features from different images can be efficiently performed. With this approach, it can greatly reduce the matching time. The proposed technique is tested with endoscopic images created from phantoms and compared with the original SIFT technique in terms of the matching time and average errors of the reconstructed models. Finally, original SIFT and the proposed fuzzy-based technique are applied to 3D model reconstruction of real nasal cavity based on images taken from a rigid nasal endoscope. The results showed that the fuzzy-based approach was significantly faster than traditional SIFT technique and provided similar quality of the 3D models. It could be used for creating a nasal cavity taken by a rigid nasal endoscope.

  10. Novel multiresolution mammographic density segmentation using pseudo 3D features and adaptive cluster merging

    NASA Astrophysics Data System (ADS)

    He, Wenda; Juette, Arne; Denton, Erica R. E.; Zwiggelaar, Reyer

    2015-03-01

    Breast cancer is the most frequently diagnosed cancer in women. Early detection, precise identification of women at risk, and application of appropriate disease prevention measures are by far the most effective ways to overcome the disease. Successful mammographic density segmentation is a key aspect in deriving correct tissue composition, ensuring an accurate mammographic risk assessment. However, mammographic densities have not yet been fully incorporated with non-image based risk prediction models, (e.g. the Gail and the Tyrer-Cuzick model), because of unreliable segmentation consistency and accuracy. This paper presents a novel multiresolution mammographic density segmentation, a concept of stack representation is proposed, and 3D texture features were extracted by adapting techniques based on classic 2D first-order statistics. An unsupervised clustering technique was employed to achieve mammographic segmentation, in which two improvements were made; 1) consistent segmentation by incorporating an optimal centroids initialisation step, and 2) significantly reduced the number of missegmentation by using an adaptive cluster merging technique. A set of full field digital mammograms was used in the evaluation. Visual assessment indicated substantial improvement on segmented anatomical structures and tissue specific areas, especially in low mammographic density categories. The developed method demonstrated an ability to improve the quality of mammographic segmentation via clustering, and results indicated an improvement of 26% in segmented image with good quality when compared with the standard clustering approach. This in turn can be found useful in early breast cancer detection, risk-stratified screening, and aiding radiologists in the process of decision making prior to surgery and/or treatment.

  11. Automatic 3D segmentation of the kidney in MR images using wavelet feature extraction and probability shape model

    NASA Astrophysics Data System (ADS)

    Akbari, Hamed; Fei, Baowei

    2012-02-01

    Numerical estimation of the size of the kidney is useful in evaluating conditions of the kidney, especially, when serial MR imaging is performed to evaluate the kidney function. This paper presents a new method for automatic segmentation of the kidney in three-dimensional (3D) MR images, by extracting texture features and statistical matching of geometrical shape of the kidney. A set of Wavelet-based support vector machines (W-SVMs) is trained on the MR images. The W-SVMs capture texture priors of MRI for classification of the kidney and non-kidney tissues in different zones around the kidney boundary. In the segmentation procedure, these W-SVMs are trained to tentatively label each voxel around the kidney model as a kidney or non-kidney voxel by texture matching. A probability kidney model is created using 10 segmented MRI data. The model is initially localized based on the intensity profiles in three directions. The weight functions are defined for each labeled voxel for each Wavelet-based, intensity-based, and model-based label. Consequently, each voxel has three labels and three weights for the Wavelet feature, intensity, and probability model. Using a 3D edge detection method, the model is re-localized and the segmented kidney is modified based on a region growing method in the model region. The probability model is re-localized based on the results and this loop continues until the segmentation converges. Experimental results with mouse MRI data show the good performance of the proposed method in segmenting the kidney in MR images.

  12. 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

  13. Construction of 3-D geologic framework and textural models for Cuyama Valley groundwater basin, California

    USGS Publications Warehouse

    Sweetkind, Donald S.; Faunt, Claudia C.; Hanson, Randall T.

    2013-01-01

    Groundwater is the sole source of water supply in Cuyama Valley, a rural agricultural area in Santa Barbara County, California, in the southeasternmost part of the Coast Ranges of California. Continued groundwater withdrawals and associated water-resource management concerns have prompted an evaluation of the hydrogeology and water availability for the Cuyama Valley groundwater basin by the U.S. Geological Survey, in cooperation with the Water Agency Division of the Santa Barbara County Department of Public Works. As a part of the overall groundwater evaluation, this report documents the construction of a digital three-dimensional geologic framework model of the groundwater basin suitable for use within a numerical hydrologic-flow model. The report also includes an analysis of the spatial variability of lithology and grain size, which forms the geologic basis for estimating aquifer hydraulic properties. The geologic framework was constructed as a digital representation of the interpreted geometry and thickness of the principal stratigraphic units within the Cuyama Valley groundwater basin, which include younger alluvium, older alluvium, and the Morales Formation, and underlying consolidated bedrock. The framework model was constructed by creating gridded surfaces representing the altitude of the top of each stratigraphic unit from various input data, including lithologic and electric logs from oil and gas wells and water wells, cross sections, and geologic maps. Sediment grain-size data were analyzed in both two and three dimensions to help define textural variations in the Cuyama Valley groundwater basin and identify areas with similar geologic materials that potentially have fairly uniform hydraulic properties. Sediment grain size was used to construct three-dimensional textural models that employed simple interpolation between drill holes and two-dimensional textural models for each stratigraphic unit that incorporated spatial structure of the textural data.

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

    NASA Astrophysics Data System (ADS)

    Alizadehashrafi, B.

    2015-12-01

    The pulse function (PF) is a technique based on procedural preprocessing system to generate a computerized virtual photo of the façade with in a fixed size square(Alizadehashrafi et al., 2009, Musliman et al., 2010). Dynamic Pulse Function (DPF) is an enhanced version of PF which can create the final photo, proportional to real geometry. This can avoid distortion while projecting the computerized photo on the generated 3D model(Alizadehashrafi and Rahman, 2013). The challenging issue that might be handled for having 3D model in LoD3 rather than LOD2, is the final aim that have been achieved in this paper. In the technique based DPF the geometries of the windows and doors are saved in an XML file schema which does not have any connections with the 3D model in LoD2 and CityGML format. In this research the parameters of Dynamic Pulse Functions are utilized via Ruby programming language in SketchUp Trimble to generate (exact position and deepness) the windows and doors automatically in LoD3 based on the same concept of DPF. The advantage of this technique is automatic generation of huge number of similar geometries e.g. windows by utilizing parameters of DPF along with defining entities and window layers. In case of converting the SKP file to CityGML via FME software or CityGML plugins the 3D model contains the semantic database about the entities and window layers which can connect the CityGML to MySQL(Alizadehashrafi and Baig, 2014). The concept behind DPF, is to use logical operations to project the texture on the background image which is dynamically proportional to real geometry. The process of projection is based on two vertical and horizontal dynamic pulses starting from upper-left corner of the background wall in down and right directions respectively based on image coordinate system. The logical one/zero on the intersections of two vertical and horizontal dynamic pulses projects/does not project the texture on the background image. It is possible to define

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

    NASA Astrophysics Data System (ADS)

    Alizadehashrafi, B.

    2015-12-01

    The pulse function (PF) is a technique based on procedural preprocessing system to generate a computerized virtual photo of the façade with in a fixed size square(Alizadehashrafi et al., 2009, Musliman et al., 2010). Dynamic Pulse Function (DPF) is an enhanced version of PF which can create the final photo, proportional to real geometry. This can avoid distortion while projecting the computerized photo on the generated 3D model(Alizadehashrafi and Rahman, 2013). The challenging issue that might be handled for having 3D model in LoD3 rather than LOD2, is the final aim that have been achieved in this paper. In the technique based DPF the geometries of the windows and doors are saved in an XML file schema which does not have any connections with the 3D model in LoD2 and CityGML format. In this research the parameters of Dynamic Pulse Functions are utilized via Ruby programming language in SketchUp Trimble to generate (exact position and deepness) the windows and doors automatically in LoD3 based on the same concept of DPF. The advantage of this technique is automatic generation of huge number of similar geometries e.g. windows by utilizing parameters of DPF along with defining entities and window layers. In case of converting the SKP file to CityGML via FME software or CityGML plugins the 3D model contains the semantic database about the entities and window layers which can connect the CityGML to MySQL(Alizadehashrafi and Baig, 2014). The concept behind DPF, is to use logical operations to project the texture on the background image which is dynamically proportional to real geometry. The process of projection is based on two vertical and horizontal dynamic pulses starting from upper-left corner of the background wall in down and right directions respectively based on image coordinate system. The logical one/zero on the intersections of two vertical and horizontal dynamic pulses projects/does not project the texture on the background image. It is possible to define

  16. 3D tooth microwear texture analysis in fishes as a test of dietary hypotheses of durophagy

    NASA Astrophysics Data System (ADS)

    Purnell, Mark A.; Darras, Laurent P. G.

    2016-03-01

    An understanding of how extinct animals functioned underpins our understanding of past evolutionary events, including adaptive radiations, and the role of functional innovation and adaptation as drivers of both micro- and macroevolution. Yet analysis of function in extinct animals is fraught with difficulty. Hypotheses that interpret molariform teeth in fishes as evidence of durophagous (shell-crushing) diets provide a good example of the particular problems inherent in the methods of functional morphology. This is because the assumed close coupling of form and function upon which the approach is based is weakened by, among other things, behavioural flexibility and the absence of a clear one to one relationship between structures and functions. Here we show that ISO 25178-2 standard parameters for surface texture, derived from analysis of worn surfaces of molariform teeth of fishes, vary significantly between species that differ in the amount of hard-shelled prey they consume. Two populations of the Sheepshead Seabream (Archosargus probatocephalus) were studied. This fish is not a dietary specialist, and one of the populations is known to consume more vegetation and less hard-shelled prey than the other; this is reflected in significant differences in their microwear textures. The Archosargus populations differ significantly in their microwear from the specialist shell-crusher Anarhichas lupus (the Atlantic Wolffish). Multivariate analysis of these three groups of fishes lends further support to the relationship between diet and tooth microwear, and provides robust validation of the approach. Application of the multivariate models derived from microwear texture in Archosargus and Anarhichas to a third fish species—the cichlid Astatoreochromis alluaudi—successfully separates wild caught fish that ate hard-shelled prey from lab-raised fish that did not. This cross-taxon validation demonstrates that quantitative analysis of tooth microwear texture can

  17. Holographic microscopy and microfluidics platform for measuring wall stress and 3D flow over surfaces textured by micro-pillars

    PubMed Central

    Bocanegra Evans, Humberto; Gorumlu, Serdar; Aksak, Burak; Castillo, Luciano; Sheng, Jian

    2016-01-01

    Understanding how fluid flow interacts with micro-textured surfaces is crucial for a broad range of key biological processes and engineering applications including particle dispersion, pathogenic infections, and drag manipulation by surface topology. We use high-speed digital holographic microscopy (DHM) in combination with a correlation based de-noising algorithm to overcome the optical interference generated by surface roughness and to capture a large number of 3D particle trajectories in a microfluidic channel with one surface patterned with micropillars. It allows us to obtain a 3D ensembled velocity field with an uncertainty of 0.06% and 2D wall shear stress distribution at the resolution of ~65 μPa. Contrary to laminar flow in most microfluidics, we find that the flow is three-dimensional and complex for the textured microchannel. While the micropillars affect the velocity flow field locally, their presence is felt globally in terms of wall shear stresses at the channel walls. These findings imply that micro-scale mixing and wall stress sensing/manipulation can be achieved through hydro-dynamically smooth but topologically rough micropillars. PMID:27353632

  18. Holographic microscopy and microfluidics platform for measuring wall stress and 3D flow over surfaces textured by micro-pillars

    NASA Astrophysics Data System (ADS)

    Bocanegra Evans, Humberto; Gorumlu, Serdar; Aksak, Burak; Castillo, Luciano; Sheng, Jian

    2016-06-01

    Understanding how fluid flow interacts with micro-textured surfaces is crucial for a broad range of key biological processes and engineering applications including particle dispersion, pathogenic infections, and drag manipulation by surface topology. We use high-speed digital holographic microscopy (DHM) in combination with a correlation based de-noising algorithm to overcome the optical interference generated by surface roughness and to capture a large number of 3D particle trajectories in a microfluidic channel with one surface patterned with micropillars. It allows us to obtain a 3D ensembled velocity field with an uncertainty of 0.06% and 2D wall shear stress distribution at the resolution of ~65 μPa. Contrary to laminar flow in most microfluidics, we find that the flow is three-dimensional and complex for the textured microchannel. While the micropillars affect the velocity flow field locally, their presence is felt globally in terms of wall shear stresses at the channel walls. These findings imply that micro-scale mixing and wall stress sensing/manipulation can be achieved through hydro-dynamically smooth but topologically rough micropillars.

  19. A neural model of 3D shape-from-texture: multiple-scale filtering, boundary grouping, and surface filling-in.

    PubMed

    Grossberg, Stephen; Kuhlmann, Levin; Mingolla, Ennio

    2007-03-01

    A neural model is presented of how cortical areas V1, V2, and V4 interact to convert a textured 2D image into a representation of curved 3D shape. Two basic problems are solved to achieve this: (1) Patterns of spatially discrete 2D texture elements are transformed into a spatially smooth surface representation of 3D shape. (2) Changes in the statistical properties of texture elements across space induce the perceived 3D shape of this surface representation. This is achieved in the model through multiple-scale filtering of a 2D image, followed by a cooperative-competitive grouping network that coherently binds texture elements into boundary webs at the appropriate depths using a scale-to-depth map and a subsequent depth competition stage. These boundary webs then gate filling-in of surface lightness signals in order to form a smooth 3D surface percept. The model quantitatively simulates challenging psychophysical data about perception of prolate ellipsoids [Todd, J., & Akerstrom, R. (1987). Perception of three-dimensional form from patterns of optical texture. Journal of Experimental Psychology: Human Perception and Performance, 13(2), 242-255]. In particular, the model represents a high degree of 3D curvature for a certain class of images, all of whose texture elements have the same degree of optical compression, in accordance with percepts of human observers. Simulations of 3D percepts of an elliptical cylinder, a slanted plane, and a photo of a golf ball are also presented.

  20. Scene classification of infrared images based on texture feature

    NASA Astrophysics Data System (ADS)

    Zhang, Xiao; Bai, Tingzhu; Shang, Fei

    2008-12-01

    Scene Classification refers to as assigning a physical scene into one of a set of predefined categories. Utilizing the method texture feature is good for providing the approach to classify scenes. Texture can be considered to be repeating patterns of local variation of pixel intensities. And texture analysis is important in many applications of computer image analysis for classification or segmentation of images based on local spatial variations of intensity. Texture describes the structural information of images, so it provides another data to classify comparing to the spectrum. Now, infrared thermal imagers are used in different kinds of fields. Since infrared images of the objects reflect their own thermal radiation, there are some shortcomings of infrared images: the poor contrast between the objectives and background, the effects of blurs edges, much noise and so on. Because of these shortcomings, it is difficult to extract to the texture feature of infrared images. In this paper we have developed an infrared image texture feature-based algorithm to classify scenes of infrared images. This paper researches texture extraction using Gabor wavelet transform. The transformation of Gabor has excellent capability in analysis the frequency and direction of the partial district. Gabor wavelets is chosen for its biological relevance and technical properties In the first place, after introducing the Gabor wavelet transform and the texture analysis methods, the infrared images are extracted texture feature by Gabor wavelet transform. It is utilized the multi-scale property of Gabor filter. In the second place, we take multi-dimensional means and standard deviation with different scales and directions as texture parameters. The last stage is classification of scene texture parameters with least squares support vector machine (LS-SVM) algorithm. SVM is based on the principle of structural risk minimization (SRM). Compared with SVM, LS-SVM has overcome the shortcoming of

  1. 3D polygonal representation of dense point clouds by triangulation, segmentation, and texture projection

    NASA Astrophysics Data System (ADS)

    Tajbakhsh, Touraj

    2010-02-01

    A basic concern of computer graphic is the modeling and realistic representation of three-dimensional objects. In this paper we present our reconstruction framework which determines a polygonal surface from a set of dense points such those typically obtained from laser scanners. We deploy the concept of adaptive blobs to achieve a first volumetric representation of the object. In the next step we estimate a coarse surface using the marching cubes method. We propose to deploy a depth-first search segmentation algorithm traversing a graph representation of the obtained polygonal mesh in order to identify all connected components. A so called supervised triangulation maps the coarse surfaces onto the dense point cloud. We optimize the mesh topology using edge exchange operations. For photo-realistic visualization of objects we finally synthesize optimal low-loss textures from available scene captures of different projections. We evaluate our framework on artificial data as well as real sensed data.

  2. 3D modelling of soil texture: mapping and incertitude estimation in centre-France

    NASA Astrophysics Data System (ADS)

    Ciampalini, Rossano; Martin, Manuel P.; Saby, Nicolas P. A.; Richer de Forges, Anne C.; Nehlig, Pierre; Martelet, Guillaume; Arrouays, Dominique

    2014-05-01

    Soil texture is an important component of all soil physical-chemical processes. The spatial variability of soil texture plays a crucial role in the evaluation and modelling of all distributed processes. The object of this study is to determine the spatial variation of soil granulometric fractions (i.e., clay, silt, sand) in the region "Centre" of France in relation to the main controlling factors, and to create extended maps of these properties following GlobalSoilMap specifications. For this purpose we used 2487 soil profiles of the French soil database (IGCS - Inventory Management and Soil Conservation) and continuum depth values of the properties within the soil profiles have been calculated with a quadratic splines methodology optimising the spline parameters in each soil profile. We used environmental covariates to predict soil properties within the region at depth intervals 0-5, 5-15, 15-30, 30-60, 60-100, and 100-200 cm. Concerning environmental covariates, we used SRTM and ASTER DEM with 90m and 30m resolution, respectively, to generate terrain parameters and topographic indexes. Other covariates we used are Gamma Ray maps, Corine land cover, available geological and soil maps of the region at scales 1M, 250k and 50k. Soil texture is modeled with the application of the compositional data analysis theory namely, alr-transform (Aitchison, 1986) which considers in statistical calculation the complementary dependence between the different granulometric classes (i.e. 100% constraint). The prediction models of the alr-transformed variables have been developed with the use of boosting regression trees (BRT), then, using a LMM - Linear Mixed Model - that separates a fixed effect from a random effect related to the continuous spatially correlated variation of the property. In this case, the LMM is applied to the two co-regionalized properties (clay and sand alr-transforms). Model uncertainty mapping represents a practical way to describe efficiency and limits of

  3. RELAP5-3D Code Includes ATHENA Features and Models

    SciTech Connect

    Riemke, Richard A.; Davis, Cliff B.; Schultz, Richard R.

    2006-07-01

    Version 2.3 of the RELAP5-3D computer program includes all features and models previously available only in the ATHENA version of the code. These include the addition of new working fluids (i.e., ammonia, blood, carbon dioxide, glycerol, helium, hydrogen, lead-bismuth, lithium, lithium-lead, nitrogen, potassium, sodium, and sodium-potassium) and a magnetohydrodynamic model that expands the capability of the code to model many more thermal-hydraulic systems. In addition to the new working fluids along with the standard working fluid water, one or more noncondensable gases (e.g., air, argon, carbon dioxide, carbon monoxide, helium, hydrogen, krypton, nitrogen, oxygen, SF{sub 6}, xenon) can be specified as part of the vapor/gas phase of the working fluid. These noncondensable gases were in previous versions of RELAP5-3D. Recently four molten salts have been added as working fluids to RELAP5-3D Version 2.4, which has had limited release. These molten salts will be in RELAP5-3D Version 2.5, which will have a general release like RELAP5-3D Version 2.3. Applications that use these new features and models are discussed in this paper. (authors)

  4. RELAP5-3D Code Includes Athena Features and Models

    SciTech Connect

    Richard A. Riemke; Cliff B. Davis; Richard R. Schultz

    2006-07-01

    Version 2.3 of the RELAP5-3D computer program includes all features and models previously available only in the ATHENA version of the code. These include the addition of new working fluids (i.e., ammonia, blood, carbon dioxide, glycerol, helium, hydrogen, lead-bismuth, lithium, lithium-lead, nitrogen, potassium, sodium, and sodium-potassium) and a magnetohydrodynamic model that expands the capability of the code to model many more thermal-hydraulic systems. In addition to the new working fluids along with the standard working fluid water, one or more noncondensable gases (e.g., air, argon, carbon dioxide, carbon monoxide, helium, hydrogen, krypton, nitrogen, oxygen, sf6, xenon) can be specified as part of the vapor/gas phase of the working fluid. These noncondensable gases were in previous versions of RELAP5- 3D. Recently four molten salts have been added as working fluids to RELAP5-3D Version 2.4, which has had limited release. These molten salts will be in RELAP5-3D Version 2.5, which will have a general release like RELAP5-3D Version 2.3. Applications that use these new features and models are discussed in this paper.

  5. 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.

  6. Process monitor of 3D-device features by using FIB and CD-SEM

    NASA Astrophysics Data System (ADS)

    Kawada, Hiroki; Ikota, Masami; Sakai, Hideo; Torikawa, Shota; Tomimatsu, Satoshi; Onishi, Tsuyoshi

    2016-03-01

    For yield improvement of 3D-device manufacturing, metrology for the variability of individual device-features is on hot issue. Transmission Electron Microscope (TEM) can be used for monitoring the individual cross-section. However, efficiency of process monitoring is limited by the speed of measurement including preparation of lamella sample. In this work we demonstrate speedy 3D-profile measurement of individual line-features without the lamella sampling. For instance, we make a-few-micrometer-wide and 45-degree-descending slope in dense line-features by using Focused Ion Beam (FIB) tool capable of 300mm-wafer. On the descending slope, obliquely cut cross-section of the line features appears. Then, we transfer the wafer to Critical-Dimension Secondary Electron Microscope (CDSEM) to measure the oblique cross-section in normal top-down view. As the descending angle is 45 degrees, the oblique cross-section looks like a cross-section normal to the wafer surface. For every single line-features the 3D dimensions are measured. To the reference metrology of the Scanning TEM (STEM), nanometric linearity and precision are confirmed for the height and the width under the hard mask of the line features. Without cleaving wafer the 60 cells on the wafer can be measured in 3 hours, which allows us of near-line process monitor of in-wafer uniformity.

  7. Segmentation of 3D EBSD data for subgrain boundary identification and feature characterization.

    PubMed

    Loeb, Andrew; Ferry, Michael; Bassman, Lori

    2016-02-01

    Subgrain structures formed during plastic deformation of metals can be observed by electron backscatter diffraction (EBSD) but are challenging to identify automatically. We have adapted a 2D image segmentation technique, fast multiscale clustering (FMC), to 3D EBSD data using a novel variance function to accommodate quaternion data. This adaptation, which has been incorporated into the free open source texture analysis software package MTEX, is capable of segmenting based on subtle and gradual variation as well as on sharp boundaries within the data. FMC has been further modified to group the resulting closed 3D segment boundaries into distinct coherent surfaces based on local normals of a triangulated surface. We demonstrate the excellent capabilities of this technique with application to 3D EBSD data sets generated from cold rolled aluminum containing well-defined microbands, cold rolled and partly recrystallized extra low carbon steel microstructure containing three magnitudes of boundary misorientations, and channel-die plane strain compressed Goss-oriented nickel crystal containing microbands with very subtle changes in orientation. PMID:26630071

  8. 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. PMID:26158105

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

    PubMed Central

    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

    2015-01-01

    Abstract. 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., >63  pixels2) and with a larger offset length (i.e., >7  pixels), 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. PMID:26158105

  10. Band structure and spin texture of Bi2Se3 3 d ferromagnetic metal interface

    NASA Astrophysics Data System (ADS)

    Zhang, Jia; Velev, Julian P.; Dang, Xiaoqian; Tsymbal, Evgeny Y.

    2016-07-01

    The spin-helical surface states in a three-dimensional topological insulator (TI), such as Bi2Se3 , are predicted to have superior efficiency in converting charge current into spin polarization. This property is said to be responsible for the giant spin-orbit torques observed in ferromagnetic metal/TI structures. In this work, using first-principles and model tight-binding calculations, we investigate the interface between the topological insulator Bi2Se3 and 3 d -transition ferromagnetic metals Ni and Co. We find that the difference in the work functions of the topological insulator and the ferromagnetic metals shift the topological surface states down about 0.5 eV below the Fermi energy where the hybridization of these surface states with the metal bands destroys their helical spin structure. The band alignment of Bi2Se3 and Ni (Co) places the Fermi energy far in the conduction band of bulk Bi2Se3 , where the spin of the carriers is aligned with the magnetization in the metal. Our results indicate that the topological surface states are unlikely to be responsible for the huge spin-orbit torque effect observed experimentally in these systems.

  11. Interpretation and mapping of geological features using mobile devices for 3D outcrop modelling

    NASA Astrophysics Data System (ADS)

    Buckley, Simon J.; Kehl, Christian; Mullins, James R.; Howell, John A.

    2016-04-01

    Advances in 3D digital geometric characterisation have resulted in widespread adoption in recent years, with photorealistic models utilised for interpretation, quantitative and qualitative analysis, as well as education, in an increasingly diverse range of geoscience applications. Topographic models created using lidar and photogrammetry, optionally combined with imagery from sensors such as hyperspectral and thermal cameras, are now becoming commonplace in geoscientific research. Mobile devices (tablets and smartphones) are maturing rapidly to become powerful field computers capable of displaying and interpreting 3D models directly in the field. With increasingly high-quality digital image capture, combined with on-board sensor pose estimation, mobile devices are, in addition, a source of primary data, which can be employed to enhance existing geological models. Adding supplementary image textures and 2D annotations to photorealistic models is therefore a desirable next step to complement conventional field geoscience. This contribution reports on research into field-based interpretation and conceptual sketching on images and photorealistic models on mobile devices, motivated by the desire to utilise digital outcrop models to generate high quality training images (TIs) for multipoint statistics (MPS) property modelling. Representative training images define sedimentological concepts and spatial relationships between elements in the system, which are subsequently modelled using artificial learning to populate geocellular models. Photorealistic outcrop models are underused sources of quantitative and qualitative information for generating TIs, explored further in this research by linking field and office workflows through the mobile device. Existing textured models are loaded to the mobile device, allowing rendering in a 3D environment. Because interpretation in 2D is more familiar and comfortable for users, the developed application allows new images to be captured

  12. Computational Identification of Genomic Features That Influence 3D Chromatin Domain Formation

    PubMed Central

    Mourad, Raphaël; Cuvier, Olivier

    2016-01-01

    Recent advances in long-range Hi-C contact mapping have revealed the importance of the 3D structure of chromosomes in gene expression. A current challenge is to identify the key molecular drivers of this 3D structure. Several genomic features, such as architectural proteins and functional elements, were shown to be enriched at topological domain borders using classical enrichment tests. Here we propose multiple logistic regression to identify those genomic features that positively or negatively influence domain border establishment or maintenance. The model is flexible, and can account for statistical interactions among multiple genomic features. Using both simulated and real data, we show that our model outperforms enrichment test and non-parametric models, such as random forests, for the identification of genomic features that influence domain borders. Using Drosophila Hi-C data at a very high resolution of 1 kb, our model suggests that, among architectural proteins, BEAF-32 and CP190 are the main positive drivers of 3D domain borders. In humans, our model identifies well-known architectural proteins CTCF and cohesin, as well as ZNF143 and Polycomb group proteins as positive drivers of domain borders. The model also reveals the existence of several negative drivers that counteract the presence of domain borders including P300, RXRA, BCL11A and ELK1. PMID:27203237

  13. 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.

  14. Changes in quantitative 3D shape features of the optic nerve head associated with age

    NASA Astrophysics Data System (ADS)

    Christopher, Mark; Tang, Li; Fingert, John H.; Scheetz, Todd E.; Abramoff, Michael D.

    2013-02-01

    Optic nerve head (ONH) structure is an important biological feature of the eye used by clinicians to diagnose and monitor progression of diseases such as glaucoma. ONH structure is commonly examined using stereo fundus imaging or optical coherence tomography. Stereo fundus imaging provides stereo views of the ONH that retain 3D information useful for characterizing structure. In order to quantify 3D ONH structure, we applied a stereo correspondence algorithm to a set of stereo fundus images. Using these quantitative 3D ONH structure measurements, eigen structures were derived using principal component analysis from stereo images of 565 subjects from the Ocular Hypertension Treatment Study (OHTS). To evaluate the usefulness of the eigen structures, we explored associations with the demographic variables age, gender, and race. Using regression analysis, the eigen structures were found to have significant (p < 0.05) associations with both age and race after Bonferroni correction. In addition, classifiers were constructed to predict the demographic variables based solely on the eigen structures. These classifiers achieved an area under receiver operating characteristic curve of 0.62 in predicting a binary age variable, 0.52 in predicting gender, and 0.67 in predicting race. The use of objective, quantitative features or eigen structures can reveal hidden relationships between ONH structure and demographics. The use of these features could similarly allow specific aspects of ONH structure to be isolated and associated with the diagnosis of glaucoma, disease progression and outcomes, and genetic factors.

  15. 3D transrectal ultrasound (TRUS) prostate segmentation based on optimal feature learning framework

    NASA Astrophysics Data System (ADS)

    Yang, Xiaofeng; Rossi, Peter J.; Jani, Ashesh B.; Mao, Hui; Curran, Walter J.; Liu, Tian

    2016-03-01

    We propose a 3D prostate segmentation method for transrectal ultrasound (TRUS) images, which is based on patch-based feature learning framework. Patient-specific anatomical features are extracted from aligned training images and adopted as signatures for each voxel. The most robust and informative features are identified by the feature selection process to train the kernel support vector machine (KSVM). The well-trained SVM was used to localize the prostate of the new patient. Our segmentation technique was validated with a clinical study of 10 patients. The accuracy of our approach was assessed using the manual segmentations (gold standard). The mean volume Dice overlap coefficient was 89.7%. In this study, we have developed a new prostate segmentation approach based on the optimal feature learning framework, demonstrated its clinical feasibility, and validated its accuracy with manual segmentations.

  16. Statistical Analysis of Haralick Texture Features to Discriminate Lung Abnormalities

    PubMed Central

    Zayed, Nourhan; Elnemr, Heba A.

    2015-01-01

    The Haralick texture features are a well-known mathematical method to detect the lung abnormalities and give the opportunity to the physician to localize the abnormality tissue type, either lung tumor or pulmonary edema. In this paper, statistical evaluation of the different features will represent the reported performance of the proposed method. Thirty-seven patients CT datasets with either lung tumor or pulmonary edema were included in this study. The CT images are first preprocessed for noise reduction and image enhancement, followed by segmentation techniques to segment the lungs, and finally Haralick texture features to detect the type of the abnormality within the lungs. In spite of the presence of low contrast and high noise in images, the proposed algorithms introduce promising results in detecting the abnormality of lungs in most of the patients in comparison with the normal and suggest that some of the features are significantly recommended than others. PMID:26557845

  17. Statistical Analysis of Haralick Texture Features to Discriminate Lung Abnormalities.

    PubMed

    Zayed, Nourhan; Elnemr, Heba A

    2015-01-01

    The Haralick texture features are a well-known mathematical method to detect the lung abnormalities and give the opportunity to the physician to localize the abnormality tissue type, either lung tumor or pulmonary edema. In this paper, statistical evaluation of the different features will represent the reported performance of the proposed method. Thirty-seven patients CT datasets with either lung tumor or pulmonary edema were included in this study. The CT images are first preprocessed for noise reduction and image enhancement, followed by segmentation techniques to segment the lungs, and finally Haralick texture features to detect the type of the abnormality within the lungs. In spite of the presence of low contrast and high noise in images, the proposed algorithms introduce promising results in detecting the abnormality of lungs in most of the patients in comparison with the normal and suggest that some of the features are significantly recommended than others. PMID:26557845

  18. Validate and update of 3D urban features using multi-source fusion

    NASA Astrophysics Data System (ADS)

    Arrington, Marcus; Edwards, Dan; Sengers, Arjan

    2012-06-01

    As forecast by the United Nations in May 2007, the population of the world transitioned from a rural to an urban demographic majority with more than half living in urban areas.1 Modern urban environments are complex 3- dimensional (3D) landscapes with 4-dimensional patterns of activity that challenge various traditional 1-dimensional and 2-dimensional sensors to accurately sample these man-made terrains. Depending on geographic location, data resulting from LIDAR, multi-spectral, electro-optical, thermal, ground-based static and mobile sensors may be available with multiple collects along with more traditional 2D GIS features. Reconciling differing data sources over time to correctly portray the dynamic urban landscape raises significant fusion and representational challenges particularly as higher levels of spatial resolution are available and expected by users. This paper presents a framework for integrating the imperfect answers of our differing sensors and data sources into a powerful representation of the complex urban environment. A case study is presented involving the integration of temporally diverse 2D, 2.5D and 3D spatial data sources over Kandahar, Afghanistan. In this case study we present a methodology for validating and augmenting 2D/2.5D urban feature and attribute data with LIDAR to produce validated 3D objects. We demonstrate that nearly 15% of buildings in Kandahar require understanding nearby vegetation before 3-D validation can be successful. We also address urban temporal change detection at the object level. Finally we address issues involved with increased sampling resolution since urban features are rarely simple cubes but in the case of Kandahar involve balconies, TV dishes, rooftop walls, small rooms, and domes among other things.

  19. Cirrhosis Classification Based on Texture Classification of Random Features

    PubMed Central

    Shao, Ying; Guo, Dongmei; Zheng, Yuanjie; Zhao, Zuowei; Qiu, Tianshuang

    2014-01-01

    Accurate staging of hepatic cirrhosis is important in investigating the cause and slowing down the effects of cirrhosis. Computer-aided diagnosis (CAD) can provide doctors with an alternative second opinion and assist them to make a specific treatment with accurate cirrhosis stage. MRI has many advantages, including high resolution for soft tissue, no radiation, and multiparameters imaging modalities. So in this paper, multisequences MRIs, including T1-weighted, T2-weighted, arterial, portal venous, and equilibrium phase, are applied. However, CAD does not meet the clinical needs of cirrhosis and few researchers are concerned with it at present. Cirrhosis is characterized by the presence of widespread fibrosis and regenerative nodules in the hepatic, leading to different texture patterns of different stages. So, extracting texture feature is the primary task. Compared with typical gray level cooccurrence matrix (GLCM) features, texture classification from random features provides an effective way, and we adopt it and propose CCTCRF for triple classification (normal, early, and middle and advanced stage). CCTCRF does not need strong assumptions except the sparse character of image, contains sufficient texture information, includes concise and effective process, and makes case decision with high accuracy. Experimental results also illustrate the satisfying performance and they are also compared with typical NN with GLCM. PMID:24707317

  20. Avalanche for shape and feature-based virtual screening with 3D alignment.

    PubMed

    Diller, David J; Connell, Nancy D; Welsh, William J

    2015-11-01

    This report introduces a new ligand-based virtual screening tool called Avalanche that incorporates both shape- and feature-based comparison with three-dimensional (3D) alignment between the query molecule and test compounds residing in a chemical database. Avalanche proceeds in two steps. The first step is an extremely rapid shape/feature based comparison which is used to narrow the focus from potentially millions or billions of candidate molecules and conformations to a more manageable number that are then passed to the second step. The second step is a detailed yet still rapid 3D alignment of the remaining candidate conformations to the query conformation. Using the 3D alignment, these remaining candidate conformations are scored, re-ranked and presented to the user as the top hits for further visualization and evaluation. To provide further insight into the method, the results from two prospective virtual screens are presented which show the ability of Avalanche to identify hits from chemical databases that would likely be missed by common substructure-based or fingerprint-based search methods. The Avalanche method is extended to enable patent landscaping, i.e., structural refinements to improve the patentability of hits for deployment in drug discovery campaigns. PMID:26458937

  1. Hand Gesture Spotting Based on 3D Dynamic Features Using Hidden Markov Models

    NASA Astrophysics Data System (ADS)

    Elmezain, Mahmoud; Al-Hamadi, Ayoub; Michaelis, Bernd

    In this paper, we propose an automatic system that handles hand gesture spotting and recognition simultaneously in stereo color image sequences without any time delay based on Hidden Markov Models (HMMs). Color and 3D depth map are used to segment hand regions. The hand trajectory will determine in further step using Mean-shift algorithm and Kalman filter to generate 3D dynamic features. Furthermore, k-means clustering algorithm is employed for the HMMs codewords. To spot meaningful gestures accurately, a non-gesture model is proposed, which provides confidence limit for the calculated likelihood by other gesture models. The confidence measures are used as an adaptive threshold for spotting meaningful gestures. Experimental results show that the proposed system can successfully recognize isolated gestures with 98.33% and meaningful gestures with 94.35% reliability for numbers (0-9).

  2. Recognizing objects in 3D point clouds with multi-scale local features.

    PubMed

    Lu, Min; Guo, Yulan; Zhang, Jun; Ma, Yanxin; Lei, Yinjie

    2014-01-01

    Recognizing 3D objects from point clouds in the presence of significant clutter and occlusion is a highly challenging task. In this paper, we present a coarse-to-fine 3D object recognition algorithm. During the phase of offline training, each model is represented with a set of multi-scale local surface features. During the phase of online recognition, a set of keypoints are first detected from each scene. The local surfaces around these keypoints are further encoded with multi-scale feature descriptors. These scene features are then matched against all model features to generate recognition hypotheses, which include model hypotheses and pose hypotheses. Finally, these hypotheses are verified to produce recognition results. The proposed algorithm was tested on two standard datasets, with rigorous comparisons to the state-of-the-art algorithms. Experimental results show that our algorithm was fully automatic and highly effective. It was also very robust to occlusion and clutter. It achieved the best recognition performance on all of these datasets, showing its superiority compared to existing algorithms.

  3. Facial expression identification using 3D geometric features from Microsoft Kinect device

    NASA Astrophysics Data System (ADS)

    Han, Dongxu; Al Jawad, Naseer; Du, Hongbo

    2016-05-01

    Facial expression identification is an important part of face recognition and closely related to emotion detection from face images. Various solutions have been proposed in the past using different types of cameras and features. Microsoft Kinect device has been widely used for multimedia interactions. More recently, the device has been increasingly deployed for supporting scientific investigations. This paper explores the effectiveness of using the device in identifying emotional facial expressions such as surprise, smile, sad, etc. and evaluates the usefulness of 3D data points on a face mesh structure obtained from the Kinect device. We present a distance-based geometric feature component that is derived from the distances between points on the face mesh and selected reference points in a single frame. The feature components extracted across a sequence of frames starting and ending by neutral emotion represent a whole expression. The feature vector eliminates the need for complex face orientation correction, simplifying the feature extraction process and making it more efficient. We applied the kNN classifier that exploits a feature component based similarity measure following the principle of dynamic time warping to determine the closest neighbors. Preliminary tests on a small scale database of different facial expressions show promises of the newly developed features and the usefulness of the Kinect device in facial expression identification.

  4. Visual Object Recognition with 3D-Aware Features in KITTI Urban Scenes

    PubMed Central

    Yebes, J. Javier; Bergasa, Luis M.; García-Garrido, Miguel Ángel

    2015-01-01

    Driver assistance systems and autonomous robotics rely on the deployment of several sensors for environment perception. Compared to LiDAR systems, the inexpensive vision sensors can capture the 3D scene as perceived by a driver in terms of appearance and depth cues. Indeed, providing 3D image understanding capabilities to vehicles is an essential target in order to infer scene semantics in urban environments. One of the challenges that arises from the navigation task in naturalistic urban scenarios is the detection of road participants (e.g., cyclists, pedestrians and vehicles). In this regard, this paper tackles the detection and orientation estimation of cars, pedestrians and cyclists, employing the challenging and naturalistic KITTI images. This work proposes 3D-aware features computed from stereo color images in order to capture the appearance and depth peculiarities of the objects in road scenes. The successful part-based object detector, known as DPM, is extended to learn richer models from the 2.5D data (color and disparity), while also carrying out a detailed analysis of the training pipeline. A large set of experiments evaluate the proposals, and the best performing approach is ranked on the KITTI website. Indeed, this is the first work that reports results with stereo data for the KITTI object challenge, achieving increased detection ratios for the classes car and cyclist compared to a baseline DPM. PMID:25903553

  5. Visual Object Recognition with 3D-Aware Features in KITTI Urban Scenes.

    PubMed

    Yebes, J Javier; Bergasa, Luis M; García-Garrido, Miguel Ángel

    2015-01-01

    Driver assistance systems and autonomous robotics rely on the deployment of several sensors for environment perception. Compared to LiDAR systems, the inexpensive vision sensors can capture the 3D scene as perceived by a driver in terms of appearance and depth cues. Indeed, providing 3D image understanding capabilities to vehicles is an essential target in order to infer scene semantics in urban environments. One of the challenges that arises from the navigation task in naturalistic urban scenarios is the detection of road participants (e.g., cyclists, pedestrians and vehicles). In this regard, this paper tackles the detection and orientation estimation of cars, pedestrians and cyclists, employing the challenging and naturalistic KITTI images. This work proposes 3D-aware features computed from stereo color images in order to capture the appearance and depth peculiarities of the objects in road scenes. The successful part-based object detector, known as DPM, is extended to learn richer models from the 2.5D data (color and disparity), while also carrying out a detailed analysis of the training pipeline. A large set of experiments evaluate the proposals, and the best performing approach is ranked on the KITTI website. Indeed, this is the first work that reports results with stereo data for the KITTI object challenge, achieving increased detection ratios for the classes car and cyclist compared to a baseline DPM. PMID:25903553

  6. Visual Object Recognition with 3D-Aware Features in KITTI Urban Scenes.

    PubMed

    Yebes, J Javier; Bergasa, Luis M; García-Garrido, Miguel Ángel

    2015-04-20

    Driver assistance systems and autonomous robotics rely on the deployment of several sensors for environment perception. Compared to LiDAR systems, the inexpensive vision sensors can capture the 3D scene as perceived by a driver in terms of appearance and depth cues. Indeed, providing 3D image understanding capabilities to vehicles is an essential target in order to infer scene semantics in urban environments. One of the challenges that arises from the navigation task in naturalistic urban scenarios is the detection of road participants (e.g., cyclists, pedestrians and vehicles). In this regard, this paper tackles the detection and orientation estimation of cars, pedestrians and cyclists, employing the challenging and naturalistic KITTI images. This work proposes 3D-aware features computed from stereo color images in order to capture the appearance and depth peculiarities of the objects in road scenes. The successful part-based object detector, known as DPM, is extended to learn richer models from the 2.5D data (color and disparity), while also carrying out a detailed analysis of the training pipeline. A large set of experiments evaluate the proposals, and the best performing approach is ranked on the KITTI website. Indeed, this is the first work that reports results with stereo data for the KITTI object challenge, achieving increased detection ratios for the classes car and cyclist compared to a baseline DPM.

  7. Feature, design intention and constraint preservation for direct modeling of 3D freeform surfaces

    NASA Astrophysics Data System (ADS)

    Fu, Luoting; Kara, Levent Burak; Shimada, Kenji

    2012-06-01

    Direct modeling has recently emerged as a suitable approach for 3D free-form shape modeling in industrial design. It has several advantages over the conventional, parametric modeling techniques, including natural user interactions, as well as the underlying, automatic feature-preserving shape deformation algorithms. However, current direct modeling packages still lack several capabilities critical for product design, such as managing aesthetic design intentions, and enforcing dimensional, geometric constraints. In this paper, we describe a novel 3D surface editing system capable of jointly accommodating aesthetic design intentions expressed in the form of surface painting and color-coded annotations, as well as engineering constraints expressed as dimensions. The proposed system is built upon differential coordinates and constrained least squares, and is intended for conceptual design that involves frequent shape tuning and explorations. We also provide an extensive review of the state-of-the-art direct modeling approaches for 3D mesh-based, freeform surfaces, with an emphasis on the two broad categories of shape deformation algorithms developed in the relevant field of geometric modeling. [Figure not available: see fulltext.

  8. Airborne LIDAR and high resolution satellite data for rapid 3D feature extraction

    NASA Astrophysics Data System (ADS)

    Jawak, S. D.; Panditrao, S. N.; Luis, A. J.

    2014-11-01

    This work uses the canopy height model (CHM) based workflow for individual tree crown delineation and 3D feature extraction approach (Overwatch Geospatial's proprietary algorithm) for building feature delineation from high-density light detection and ranging (LiDAR) point cloud data in an urban environment and evaluates its accuracy by using very high-resolution panchromatic (PAN) (spatial) and 8-band (multispectral) WorldView-2 (WV-2) imagery. LiDAR point cloud data over San Francisco, California, USA, recorded in June 2010, was used to detect tree and building features by classifying point elevation values. The workflow employed includes resampling of LiDAR point cloud to generate a raster surface or digital terrain model (DTM), generation of a hill-shade image and an intensity image, extraction of digital surface model, generation of bare earth digital elevation model (DEM) and extraction of tree and building features. First, the optical WV-2 data and the LiDAR intensity image were co-registered using ground control points (GCPs). The WV-2 rational polynomial coefficients model (RPC) was executed in ERDAS Leica Photogrammetry Suite (LPS) using supplementary *.RPB file. In the second stage, ortho-rectification was carried out using ERDAS LPS by incorporating well-distributed GCPs. The root mean square error (RMSE) for the WV-2 was estimated to be 0.25 m by using more than 10 well-distributed GCPs. In the second stage, we generated the bare earth DEM from LiDAR point cloud data. In most of the cases, bare earth DEM does not represent true ground elevation. Hence, the model was edited to get the most accurate DEM/ DTM possible and normalized the LiDAR point cloud data based on DTM in order to reduce the effect of undulating terrain. We normalized the vegetation point cloud values by subtracting the ground points (DEM) from the LiDAR point cloud. A normalized digital surface model (nDSM) or CHM was calculated from the LiDAR data by subtracting the DEM from the DSM

  9. 3D CAD model retrieval method based on hierarchical multi-features

    NASA Astrophysics Data System (ADS)

    An, Ran; Wang, Qingwen

    2015-12-01

    The classical "Shape Distribution D2" algorithm takes the distance between two random points on a surface of CAD model as statistical features, and based on that it generates a feature vector to calculate the dissimilarity and achieve the retrieval goal. This algorithm has a simple principle, high computational efficiency and can get a better retrieval results for the simple shape models. Based on the analysis of D2 algorithm's shape distribution curve, this paper enhances the algorithm's descriptive ability for a model's overall shape through the statistics of the angle between two random points' normal vectors, especially for the distinctions between the model's plane features and curved surface features; meanwhile, introduce the ratio that a line between two random points cut off by the model's surface to enhance the algorithm's descriptive ability for a model's detailed features; finally, integrating the two shape describing methods with the original D2 algorithm, this paper proposes a new method based the hierarchical multi-features. Experimental results showed that this method has bigger improvements and could get a better retrieval results compared with the traditional 3D CAD model retrieval method.

  10. Characterization of impact craters in 3D meshes using a feature lines approach

    NASA Astrophysics Data System (ADS)

    Jorda, L.; Mari, J.; Viseur, S.; Bouley, S.

    2013-12-01

    Impact craters are observed at the surface of most solar system bodies: terrestrial planets, satellites and asteroids.The measurement of their size-frequency distribution (SFD) is the only method available to estimate the age of the observed geological units, assuming a rate and velocity distributions of impactors and a crater scaling law. The age of the geological units is fundamental to establish a chronology of events explaining the global evolution of the surface. In addition, the detailed characterization of the crater properties (depth-to-diameter ratio and radial profile) yields a better understanding of the geological processes which altered the observed surfaces. Crater detection is usually performed manually directly from the acquired images. However, this method can become prohibitive when dealing with small craters extracted from very large data sets. A large number of solar system objects is being mapped at a very high spatial resolution by space probes since a few decades, emphasizing the need for new automatic methods of crater detection. Powerful computers are now available to produce and analyze huge 3D models of the surface in the form of 3D meshes containing tens to hundreds of billions of facets. This motivates the development of a new family of automatic crater detection algorithms (CDAs). The automatic CDAs developed so far were mainly based on morphological analyses and pattern recognition techniques on 2D images. Since a few years, new CDAs based on 3D models are being developed. Our objective is to develop and test against existing methods an automatic CDA using a new approach based on the discrete differential properties of 3D meshes. The method produces the feature lines (the crest and the ravine lines) lying on the surface. It is based on a double step algorithm: first, the regions of interest are flagged according to curvature properties, and then an original skeletonization approach is applied to extract the feature lines. This new

  11. The Wavelet Element Method. Part 2; Realization and Additional Features in 2D and 3D

    NASA Technical Reports Server (NTRS)

    Canuto, Claudio; Tabacco, Anita; Urban, Karsten

    1998-01-01

    The Wavelet Element Method (WEM) provides a construction of multiresolution systems and biorthogonal wavelets on fairly general domains. These are split into subdomains that are mapped to a single reference hypercube. Tensor products of scaling functions and wavelets defined on the unit interval are used on the reference domain. By introducing appropriate matching conditions across the interelement boundaries, a globally continuous biorthogonal wavelet basis on the general domain is obtained. This construction does not uniquely define the basis functions but rather leaves some freedom for fulfilling additional features. In this paper we detail the general construction principle of the WEM to the 1D, 2D and 3D cases. We address additional features such as symmetry, vanishing moments and minimal support of the wavelet functions in each particular dimension. The construction is illustrated by using biorthogonal spline wavelets on the interval.

  12. 3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes.

    PubMed

    Zhong, Zichun; Guo, Xiaohu; Cai, Yiqi; Yang, Yin; Wang, Jing; Jia, Xun; Mao, Weihua

    2016-01-01

    By using prior information of planning CT images and feature-based nonuniform meshes, this paper demonstrates that volumetric images can be efficiently registered with a very small portion of 2D projection images of a Cone-Beam Computed Tomography (CBCT) scan. After a density field is computed based on the extracted feature edges from planning CT images, nonuniform tetrahedral meshes will be automatically generated to better characterize the image features according to the density field; that is, finer meshes are generated for features. The displacement vector fields (DVFs) are specified at the mesh vertices to drive the deformation of original CT images. Digitally reconstructed radiographs (DRRs) of the deformed anatomy are generated and compared with corresponding 2D projections. DVFs are optimized to minimize the objective function including differences between DRRs and projections and the regularity. To further accelerate the above 3D-2D registration, a procedure to obtain good initial deformations by deforming the volume surface to match 2D body boundary on projections has been developed. This complete method is evaluated quantitatively by using several digital phantoms and data from head and neck cancer patients. The feature-based nonuniform meshing method leads to better results than either uniform orthogonal grid or uniform tetrahedral meshes. PMID:27019849

  13. 3D facial expression recognition using maximum relevance minimum redundancy geometrical features

    NASA Astrophysics Data System (ADS)

    Rabiu, Habibu; Saripan, M. Iqbal; Mashohor, Syamsiah; Marhaban, Mohd Hamiruce

    2012-12-01

    In recent years, facial expression recognition (FER) has become an attractive research area, which besides the fundamental challenges, it poses, finds application in areas, such as human-computer interaction, clinical psychology, lie detection, pain assessment, and neurology. Generally the approaches to FER consist of three main steps: face detection, feature extraction and expression recognition. The recognition accuracy of FER hinges immensely on the relevance of the selected features in representing the target expressions. In this article, we present a person and gender independent 3D facial expression recognition method, using maximum relevance minimum redundancy geometrical features. The aim is to detect a compact set of features that sufficiently represents the most discriminative features between the target classes. Multi-class one-against-one SVM classifier was employed to recognize the seven facial expressions; neutral, happy, sad, angry, fear, disgust, and surprise. The average recognition accuracy of 92.2% was recorded. Furthermore, inter database homogeneity was investigated between two independent databases the BU-3DFE and UPM-3DFE the results showed a strong homogeneity between the two databases.

  14. Automated Feature Based Tls Data Registration for 3d Building Modeling

    NASA Astrophysics Data System (ADS)

    Kitamura, K.; Kochi, N.; Kaneko, S.

    2012-07-01

    In this paper we present a novel method for the registration of point cloud data obtained using terrestrial laser scanner (TLS). The final goal of our investigation is the automated reconstruction of CAD drawings and the 3D modeling of objects surveyed by TLS. Because objects are scanned from multiple positions, individual point cloud need to be registered to the same coordinate system. We propose in this paper an automated feature based registration procedure. Our proposed method does not require the definition of initial values or the placement of targets and is robust against noise and background elements. A feature extraction procedure is performed for each point cloud as pre-processing. The registration of the point clouds from different viewpoints is then performed by utilizing the extracted features. The feature extraction method which we had developed previously (Kitamura, 2010) is used: planes and edges are extracted from the point cloud. By utilizing these features, the amount of information to process is reduced and the efficiency of the whole registration procedure is increased. In this paper, we describe the proposed algorithm and, in order to demonstrate its effectiveness, we show the results obtained by using real data.

  15. 3D-2D Deformable Image Registration Using Feature-Based Nonuniform Meshes

    PubMed Central

    Guo, Xiaohu; Cai, Yiqi; Yang, Yin; Wang, Jing; Jia, Xun

    2016-01-01

    By using prior information of planning CT images and feature-based nonuniform meshes, this paper demonstrates that volumetric images can be efficiently registered with a very small portion of 2D projection images of a Cone-Beam Computed Tomography (CBCT) scan. After a density field is computed based on the extracted feature edges from planning CT images, nonuniform tetrahedral meshes will be automatically generated to better characterize the image features according to the density field; that is, finer meshes are generated for features. The displacement vector fields (DVFs) are specified at the mesh vertices to drive the deformation of original CT images. Digitally reconstructed radiographs (DRRs) of the deformed anatomy are generated and compared with corresponding 2D projections. DVFs are optimized to minimize the objective function including differences between DRRs and projections and the regularity. To further accelerate the above 3D-2D registration, a procedure to obtain good initial deformations by deforming the volume surface to match 2D body boundary on projections has been developed. This complete method is evaluated quantitatively by using several digital phantoms and data from head and neck cancer patients. The feature-based nonuniform meshing method leads to better results than either uniform orthogonal grid or uniform tetrahedral meshes. PMID:27019849

  16. Relative contributions of 2D and 3D cues in a texture segmentation task, implications for the roles of striate and extrastriate cortex in attentional selection.

    PubMed

    Zhaoping, Li; Guyader, Nathalie; Lewis, Alex

    2009-01-01

    Experimental evidence has given strong support to the theory that the primary visual cortex (V1) realizes a bottom-up saliency map (A. R. Koene & L. Zhaoping, 2007; Z. Li, 2002; L. Zhaoping, 2008a; L. Zhaoping & K. A. May, 2007). Unlike the conventional models of texture segmentation, this theory predicted that segmenting two textures in an image I(rel) comprising obliquely oriented bars would become much more difficult when a task-irrelevant texture I(ir) of spatially alternating horizontal and vertical bars is superposed on the original texture I(rel). The irrelevant texture I(ir) interferes with I(rel)'s ability to direct attention. This predicted interference was confirmed (L. Zhaoping & K. A. May, 2007) in the form of a prolonged task reaction time (RT). In this study, we investigate whether and how 3D depth perception, believed to be processed mostly beyond V1 and starting in V2 (J. S. Bakin, K. Nakayama, & C. D. Gilbert, 2000; B. G. Cumming & A. J. Parker, 2000; F. T. Qiu & R. von der Heydt, 2005; R. von der Heydt, H. Zhou, & H. S. Friedman, 2000), contribute additionally to direct attention. We measured the reduction of the interference or the RT when the position of the texture grid for I(ir) was offset horizontally from that for I(rel), forming an offset, 2D, stimulus. This reduction was compared with that when this positional offset was only present in the input image to one eye, or when it was in the opposite directions in the images for the two eyes, creating a 3D stimulus with a depth separation between I(ir) and I(rel). The contribution by 3D processes to attentional guidance would be manifested by any extra RT reduction associated with the 3D stimulus over the offset 2D stimulus. This 3D contribution was not present unless the task was so difficult that RT (by button press) based on 2D cues alone was longer than about 1 second. Our findings suggest that, without other top-down factors, V1 plays a dominant role in attentional guidance during an

  17. Evaluation of feature-based 3-d registration of probabilistic volumetric scenes

    NASA Astrophysics Data System (ADS)

    Restrepo, Maria I.; Ulusoy, Ali O.; Mundy, Joseph L.

    2014-12-01

    Automatic estimation of the world surfaces from aerial images has seen much attention and progress in recent years. Among current modeling technologies, probabilistic volumetric models (PVMs) have evolved as an alternative representation that can learn geometry and appearance in a dense and probabilistic manner. Recent progress, in terms of storage and speed, achieved in the area of volumetric modeling, opens the opportunity to develop new frameworks that make use of the PVM to pursue the ultimate goal of creating an entire map of the earth, where one can reason about the semantics and dynamics of the 3-d world. Aligning 3-d models collected at different time-instances constitutes an important step for successful fusion of large spatio-temporal information. This paper evaluates how effectively probabilistic volumetric models can be aligned using robust feature-matching techniques, while considering different scenarios that reflect the kind of variability observed across aerial video collections from different time instances. More precisely, this work investigates variability in terms of discretization, resolution and sampling density, errors in the camera orientation, and changes in illumination and geographic characteristics. All results are given for large-scale, outdoor sites. In order to facilitate the comparison of the registration performance of PVMs to that of other 3-d reconstruction techniques, the registration pipeline is also carried out using Patch-based Multi-View Stereo (PMVS) algorithm. Registration performance is similar for scenes that have favorable geometry and the appearance characteristics necessary for high quality reconstruction. In scenes containing trees, such as a park, or many buildings, such as a city center, registration performance is significantly more accurate when using the PVM.

  18. Vertical Corner Feature Based Precise Vehicle Localization Using 3D LIDAR in Urban Area.

    PubMed

    Im, Jun-Hyuck; Im, Sung-Hyuck; Jee, Gyu-In

    2016-01-01

    Tall buildings are concentrated in urban areas. The outer walls of buildings are vertically erected to the ground and almost flat. Therefore, the vertical corners that meet the vertical planes are present everywhere in urban areas. These corners act as convenient landmarks, which can be extracted by using the light detection and ranging (LIDAR) sensor. A vertical corner feature based precise vehicle localization method is proposed in this paper and implemented using 3D LIDAR (Velodyne HDL-32E). The vehicle motion is predicted by accumulating the pose increment output from the iterative closest point (ICP) algorithm based on the geometric relations between the scan data of the 3D LIDAR. The vertical corner is extracted using the proposed corner extraction method. The vehicle position is then corrected by matching the prebuilt corner map with the extracted corner. The experiment was carried out in the Gangnam area of Seoul, South Korea. In the experimental results, the maximum horizontal position error is about 0.46 m and the 2D Root Mean Square (RMS) horizontal error is about 0.138 m. PMID:27517936

  19. Vertical Corner Feature Based Precise Vehicle Localization Using 3D LIDAR in Urban Area.

    PubMed

    Im, Jun-Hyuck; Im, Sung-Hyuck; Jee, Gyu-In

    2016-08-10

    Tall buildings are concentrated in urban areas. The outer walls of buildings are vertically erected to the ground and almost flat. Therefore, the vertical corners that meet the vertical planes are present everywhere in urban areas. These corners act as convenient landmarks, which can be extracted by using the light detection and ranging (LIDAR) sensor. A vertical corner feature based precise vehicle localization method is proposed in this paper and implemented using 3D LIDAR (Velodyne HDL-32E). The vehicle motion is predicted by accumulating the pose increment output from the iterative closest point (ICP) algorithm based on the geometric relations between the scan data of the 3D LIDAR. The vertical corner is extracted using the proposed corner extraction method. The vehicle position is then corrected by matching the prebuilt corner map with the extracted corner. The experiment was carried out in the Gangnam area of Seoul, South Korea. In the experimental results, the maximum horizontal position error is about 0.46 m and the 2D Root Mean Square (RMS) horizontal error is about 0.138 m.

  20. Vertical Corner Feature Based Precise Vehicle Localization Using 3D LIDAR in Urban Area

    PubMed Central

    Im, Jun-Hyuck; Im, Sung-Hyuck; Jee, Gyu-In

    2016-01-01

    Tall buildings are concentrated in urban areas. The outer walls of buildings are vertically erected to the ground and almost flat. Therefore, the vertical corners that meet the vertical planes are present everywhere in urban areas. These corners act as convenient landmarks, which can be extracted by using the light detection and ranging (LIDAR) sensor. A vertical corner feature based precise vehicle localization method is proposed in this paper and implemented using 3D LIDAR (Velodyne HDL-32E). The vehicle motion is predicted by accumulating the pose increment output from the iterative closest point (ICP) algorithm based on the geometric relations between the scan data of the 3D LIDAR. The vertical corner is extracted using the proposed corner extraction method. The vehicle position is then corrected by matching the prebuilt corner map with the extracted corner. The experiment was carried out in the Gangnam area of Seoul, South Korea. In the experimental results, the maximum horizontal position error is about 0.46 m and the 2D Root Mean Square (RMS) horizontal error is about 0.138 m. PMID:27517936

  1. The Learner Characteristics, Features of Desktop 3D Virtual Reality Environments, and College Chemistry Instruction: A Structural Equation Modeling Analysis

    ERIC Educational Resources Information Center

    Merchant, Zahira; Goetz, Ernest T.; Keeney-Kennicutt, Wendy; Kwok, Oi-man; Cifuentes, Lauren; Davis, Trina J.

    2012-01-01

    We examined a model of the impact of a 3D desktop virtual reality environment on the learner characteristics (i.e. perceptual and psychological variables) that can enhance chemistry-related learning achievements in an introductory college chemistry class. The relationships between the 3D virtual reality features and the chemistry learning test as…

  2. Bispectrum feature extraction of gearbox faults based on nonnegative Tucker3 decomposition with 3D calculations

    NASA Astrophysics Data System (ADS)

    Wang, Haijun; Xu, Feiyun; Zhao, Jun'ai; Jia, Minping; Hu, Jianzhong; Huang, Peng

    2013-11-01

    Nonnegative Tucker3 decomposition(NTD) has attracted lots of attentions for its good performance in 3D data array analysis. However, further research is still necessary to solve the problems of overfitting and slow convergence under the anharmonic vibration circumstance occurred in the field of mechanical fault diagnosis. To decompose a large-scale tensor and extract available bispectrum feature, a method of conjugating Choi-Williams kernel function with Gauss-Newton Cartesian product based on nonnegative Tucker3 decomposition(NTD_EDF) is investigated. The complexity of the proposed method is reduced from o( n N lg n) in 3D spaces to o( R 1 R 2 nlg n) in 1D vectors due to its low rank form of the Tucker-product convolution. Meanwhile, a simultaneously updating algorithm is given to overcome the overfitting, slow convergence and low efficiency existing in the conventional one-by-one updating algorithm. Furthermore, the technique of spectral phase analysis for quadratic coupling estimation is used to explain the feature spectrum extracted from the gearbox fault data by the proposed method in detail. The simulated and experimental results show that the sparser and more inerratic feature distribution of basis images can be obtained with core tensor by the NTD_EDF method compared with the one by the other methods in bispectrum feature extraction, and a legible fault expression can also be performed by power spectral density(PSD) function. Besides, the deviations of successive relative error(DSRE) of NTD_EDF achieves 81.66 dB against 15.17 dB by beta-divergences based on NTD(NTD_Beta) and the time-cost of NTD_EDF is only 129.3 s, which is far less than 1 747.9 s by hierarchical alternative least square based on NTD (NTD_HALS). The NTD_EDF method proposed not only avoids the data overfitting and improves the computation efficiency but also can be used to extract more inerratic and sparser bispectrum features of the gearbox fault.

  3. Features of the urban atmosphere as detected by RASS and 3D sonics

    NASA Astrophysics Data System (ADS)

    Piringer, Martin; Lotteraner, Christoph

    2010-05-01

    In contrast to the classical homogeneous atmospheric boundary layer, the urban boundary layer is more complex due to several specific features and processes caused by the buildings which introduce a large amount of vertical surfaces, high roughness elements, and artificial materials. The most well-known result is the urban heat island, but urban areas also influence the wind field, precipitation, atmospheric stability, and the mixing height. The last two are essential to determine the spread of pollutants in urban areas. Atmospheric stability can properly be derived with 3D sonics via the sensible heat flux; The mixing height can be deduced from vertical temperature profiles provided by Sodar-RASS systems. The contribution will highlight the methodologies, give examples, and critically discuss advantages and shortcomings of the instruments and the methods applied.

  4. 3-D modeling useful tool for planning. [mapping groundwater and soil pollution and subsurface features

    SciTech Connect

    Calmbacher, C.W. )

    1992-12-01

    Visualizing and delineating subsurface geological features, groundwater contaminant plumes, soil contamination, geological faults, shears and other features can prove invaluable to environmental consultants, engineers, geologists and hydrogeologists. Three-dimensional modeling is useful for a variety of applications from planning remediation to site planning design. The problem often is figuring out how to convert drilling logs, map lists or contaminant levels from soil and groundwater into a 3-D model. Three-dimensional subsurface modeling is not a new requirement, but a flexible, easily applied method of developing such models has not always been readily available. LYNX Geosystems Inc. has developed the Geoscience Modeling System (GMS) in answer to the needs of those regularly having to do three-dimensional geostatistical modeling. The GMS program has been designed to allow analysis, interpretation and visualization of complex geological features and soil and groundwater contamination. This is a powerful program driven by a 30 volume modeling technology engine. Data can be entered, stored, manipulated and analyzed in ways that will present very few limitations to the user. The program has selections for Geoscience Data Management, Geoscience Data Analysis, Geological Modeling (interpretation and analysis), Geostatistical Modeling and an optional engineering component.

  5. FeatureMap3D--a tool to map protein features and sequence conservation onto homologous structures in the PDB.

    PubMed

    Wernersson, Rasmus; Rapacki, Kristoffer; Staerfeldt, Hans-Henrik; Sackett, Peter Wad; Mølgaard, Anne

    2006-07-01

    FeatureMap3D is a web-based tool that maps protein features onto 3D structures. The user provides sequences annotated with any feature of interest, such as post-translational modifications, protease cleavage sites or exonic structure and FeatureMap3D will then search the Protein Data Bank (PDB) for structures of homologous proteins. The results are displayed both as an annotated sequence alignment, where the user-provided annotations as well as the sequence conservation between the query and the target sequence are displayed, and also as a publication-quality image of the 3D protein structure with the selected features and sequence conservation enhanced. The results are also returned in a readily parsable text format as well as a PyMol (http://pymol.sourceforge.net/) script file, which allows the user to easily modify the protein structure image to suit a specific purpose. FeatureMap3D can also be used without sequence annotation, to evaluate the quality of the alignment of the input sequences to the most homologous structures in the PDB, through the sequence conservation colored 3D structure visualization tool. FeatureMap3D is available at: http://www.cbs.dtu.dk/services/FeatureMap3D/. PMID:16845115

  6. Multi-fractal detrended texture feature for brain tumor classification

    NASA Astrophysics Data System (ADS)

    Reza, Syed M. S.; Mays, Randall; Iftekharuddin, Khan M.

    2015-03-01

    We propose a novel non-invasive brain tumor type classification using Multi-fractal Detrended Fluctuation Analysis (MFDFA) [1] in structural magnetic resonance (MR) images. This preliminary work investigates the efficacy of the MFDFA features along with our novel texture feature known as multifractional Brownian motion (mBm) [2] in classifying (grading) brain tumors as High Grade (HG) and Low Grade (LG). Based on prior performance, Random Forest (RF) [3] is employed for tumor grading using two different datasets such as BRATS-2013 [4] and BRATS-2014 [5]. Quantitative scores such as precision, recall, accuracy are obtained using the confusion matrix. On an average 90% precision and 85% recall from the inter-dataset cross-validation confirm the efficacy of the proposed method.

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

    NASA Astrophysics Data System (ADS)

    Irhebhude, Martins E.; Edirisinghe, Eran A.

    2014-06-01

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

  8. R2OBBIE-3D, a Fast Robotic High-Resolution System for Quantitative Phenotyping of Surface Geometry and Colour-Texture

    PubMed Central

    Manukyan, Liana; Milinkovitch, Michel C.

    2015-01-01

    While recent imaging techniques provide insights into biological processes from the molecular to the cellular scale, phenotypes at larger scales remain poorly amenable to quantitative analyses. For example, investigations of the biophysical mechanisms generating skin morphological complexity and diversity would greatly benefit from 3D geometry and colour-texture reconstructions. Here, we report on R2OBBIE-3D, an integrated system that combines a robotic arm, a high-resolution digital colour camera, an illumination basket of high-intensity light-emitting diodes and state-of-the-art 3D-reconstruction approaches. We demonstrate that R2OBBIE generates accurate 3D models of biological objects between 1 and 100 cm, makes multiview photometric stereo scanning possible in practical processing times, and enables the capture of colour-texture and geometric resolutions better than 15 μm without the use of magnifying lenses. R2OBBIE has the potential to greatly improve quantitative analyses of phenotypes in addition to providing multiple new applications in, e.g., biomedical science. PMID:26039509

  9. R(2)OBBIE-3D, a Fast Robotic High-Resolution System for Quantitative Phenotyping of Surface Geometry and Colour-Texture.

    PubMed

    Martins, António F; Bessant, Michel; Manukyan, Liana; Milinkovitch, Michel C

    2015-01-01

    While recent imaging techniques provide insights into biological processes from the molecular to the cellular scale, phenotypes at larger scales remain poorly amenable to quantitative analyses. For example, investigations of the biophysical mechanisms generating skin morphological complexity and diversity would greatly benefit from 3D geometry and colour-texture reconstructions. Here, we report on R(2)OBBIE-3D, an integrated system that combines a robotic arm, a high-resolution digital colour camera, an illumination basket of high-intensity light-emitting diodes and state-of-the-art 3D-reconstruction approaches. We demonstrate that R(2)OBBIE generates accurate 3D models of biological objects between 1 and 100 cm, makes multiview photometric stereo scanning possible in practical processing times, and enables the capture of colour-texture and geometric resolutions better than 15 μm without the use of magnifying lenses. R(2)OBBIE has the potential to greatly improve quantitative analyses of phenotypes in addition to providing multiple new applications in, e.g., biomedical science. PMID:26039509

  10. Local phase tensor features for 3-D ultrasound to statistical shape+pose spine model registration.

    PubMed

    Hacihaliloglu, Ilker; Rasoulian, Abtin; Rohling, Robert N; Abolmaesumi, Purang

    2014-11-01

    Most conventional spine interventions are performed under X-ray fluoroscopy guidance. In recent years, there has been a growing interest to develop nonionizing imaging alternatives to guide these procedures. Ultrasound guidance has emerged as a leading alternative. However, a challenging problem is automatic identification of the spinal anatomy in ultrasound data. In this paper, we propose a local phase-based bone feature enhancement technique that can robustly identify the spine surface in ultrasound images. The local phase information is obtained using a gradient energy tensor filter. This information is used to construct local phase tensors in ultrasound images, which highlight the spine surface. We show that our proposed approach results in a more distinct enhancement of the bone surfaces compared to recently proposed techniques based on monogenic scale-space filters and logarithmic Gabor filters. We also demonstrate that registration accuracy of a statistical shape+pose model of the spine to 3-D ultrasound images can be significantly improved, using the proposed method, compared to those obtained using monogenic scale-space filters and logarithmic Gabor filters.

  11. 3D-printed paper spray ionization cartridge with fast wetting and continuous solvent supply features.

    PubMed

    Salentijn, Gert I J; Permentier, Hjalmar P; Verpoorte, Elisabeth

    2014-12-01

    We report the development of a 3D-printed cartridge for paper spray ionization (PSI) that can be used almost immediately after solvent introduction in a dedicated reservoir and allows prolonged spray generation from a paper tip. The fast wetting feature described in this work is based on capillary action through paper and movement of fluid between paper and the cartridge material (polylactic acid, PLA). The influence of solvent composition, PLA conditioning of the cartridge with isopropanol, and solvent volume introduced into the reservoir have been investigated with relation to wetting time and the amount of solvent consumed for wetting. Spray has been demonstrated with this cartridge for tens of minutes, without any external pumping. It is shown that fast wetting and spray generation can easily be achieved using a number of solvent mixtures commonly used for PSI. The PSI cartridge was applied to the analysis of lidocaine from a paper tip using different solvent mixtures, and to the analysis of lidocaine from a serum sample. Finally, a demonstration of online paper chromatography-mass spectrometry is given.

  12. Identifying Key Structural Features and Spatial Relationships in Archean Microbialites Using 2D and 3D Visualization Methods

    NASA Astrophysics Data System (ADS)

    Stevens, E. W.; Sumner, D. Y.

    2009-12-01

    Microbialites in the 2521 ± 3 Ma Gamohaan Formation, South Africa, have several different end-member morphologies which show distinct growth structures and spatial relationships. We characterized several growth structures and spatial relationships in two samples (DK20 and 2_06) using a combination of 2D and 3D analytical techniques. There are two main goals in studying complicated microbialites with a combination of 2D and 3D methods. First, one can better understand microbialite growth by identifying important structures and structural relationships. Once structures are identified, the order in which the structures formed and how they are related can be inferred from observations of crosscutting relationships. Second, it is important to use both 2D and 3D methods to correlate 3D observations with those in 2D that are more common in the field. Combining analysis provides significantly more insight into the 3D morphology of microbial structures. In our studies, 2D analysis consisted of describing polished slabs and serial sections created by grinding down the rock 100 microns at a time. 3D analysis was performed on serial sections visualized in 3D using Vrui and 3DVisualizer software developed at KeckCAVES, UCD (http://keckcaves.org). Data were visualized on a laptop and in an immersive cave system. Both samples contain microbial laminae and more vertically orients microbial "walls" called supports. The relationships between these features created voids now filled with herringbone and blocky calcite crystals. DK20, a classic plumose structure, contains two types of support structures. Both are 1st order structures (1st order structures with organic inclusions and 1st without organic inclusions) interpreted as planar features based on 2D analysis. In the 2D analysis the 1st order structures show v branching relationships as well as single cuspate relationships (two 1st order structures with inclusions merging upward), and single tented relationships (three supports

  13. 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.

  14. Feasibility study on 3-D shape analysis of high-aspect-ratio features using through-focus scanning optical microscopy

    PubMed Central

    Attota, Ravi Kiran; Weck, Peter; Kramar, John A.; Bunday, Benjamin; Vartanian, Victor

    2016-01-01

    In-line metrologies currently used in the semiconductor industry are being challenged by the aggressive pace of device scaling and the adoption of novel device architectures. Metrology and process control of three-dimensional (3-D) high-aspect-ratio (HAR) features are becoming increasingly important and also challenging. In this paper we present a feasibility study of through-focus scanning optical microscopy (TSOM) for 3-D shape analysis of HAR features. TSOM makes use of 3-D optical data collected using a conventional optical microscope for 3-D shape analysis. Simulation results of trenches and holes down to the 11 nm node are presented. The ability of TSOM to analyze an array of HAR features or a single isolated HAR feature is also presented. This allows for the use of targets with area over 100 times smaller than that of conventional gratings, saving valuable real estate on the wafers. Indications are that the sensitivity of TSOM may match or exceed the International Technology Roadmap for Semiconductors (ITRS) measurement requirements for the next several years. Both simulations and preliminary experimental results are presented. The simplicity, lowcost, high throughput, and nanometer scale 3-D shape sensitivity of TSOM make it an attractive inspection and process monitoring solution for nanomanufacturing. PMID:27464112

  15. Multi-feature-based plaque characterization in ex vivo MRI trained by registration to 3D histology

    NASA Astrophysics Data System (ADS)

    van Engelen, Arna; Niessen, Wiro J.; Klein, Stefan; Groen, Harald C.; Verhagen, Hence JM; Wentzel, Jolanda J.; van der Lugt, Aad; de Bruijne, Marleen

    2012-01-01

    We present a new method for automated characterization of atherosclerotic plaque composition in ex vivo MRI. It uses MRI intensities as well as four other types of features: smoothed, gradient magnitude and Laplacian images at several scales, and the distances to the lumen and outer vessel wall. The ground truth for fibrous, necrotic and calcified tissue was provided by histology and μCT in 12 carotid plaque specimens. Semi-automatic registration of a 3D stack of histological slices and μCT images to MRI allowed for 3D rotations and in-plane deformations of histology. By basing voxelwise classification on different combinations of features, we evaluated their relative importance. To establish whether training by 3D registration yields different results than training by 2D registration, we determined plaque composition using (1) a 2D slice-based registration approach for three manually selected MRI and histology slices per specimen, and (2) an approach that uses only the three corresponding MRI slices from the 3D-registered volumes. Voxelwise classification accuracy was best when all features were used (73.3 ± 6.3%) and was significantly better than when only original intensities and distance features were used (Friedman, p < 0.05). Although 2D registration or selection of three slices from the 3D set slightly decreased accuracy, these differences were non-significant.

  16. Feasibility study on 3-D shape analysis of high-aspect-ratio features using through-focus scanning optical microscopy.

    PubMed

    Attota, Ravi Kiran; Weck, Peter; Kramar, John A; Bunday, Benjamin; Vartanian, Victor

    2016-07-25

    In-line metrologies currently used in the semiconductor industry are being challenged by the aggressive pace of device scaling and the adoption of novel device architectures. Metrology and process control of three-dimensional (3-D) high-aspect-ratio (HAR) features are becoming increasingly important and also challenging. In this paper we present a feasibility study of through-focus scanning optical microscopy (TSOM) for 3-D shape analysis of HAR features. TSOM makes use of 3-D optical data collected using a conventional optical microscope for 3-D shape analysis. Simulation results of trenches and holes down to the 11 nm node are presented. The ability of TSOM to analyze an array of HAR features or a single isolated HAR feature is also presented. This allows for the use of targets with area over 100 times smaller than that of conventional gratings, saving valuable real estate on the wafers. Indications are that the sensitivity of TSOM may match or exceed the International Technology Roadmap for Semiconductors (ITRS) measurement requirements for the next several years. Both simulations and preliminary experimental results are presented. The simplicity, lowcost, high throughput, and nanometer scale 3-D shape sensitivity of TSOM make it an attractive inspection and process monitoring solution for nanomanufacturing. PMID:27464112

  17. Texture

    SciTech Connect

    Gee, Glendon W.

    2005-01-03

    The chapter focuses on the quantitative aspect of soil texture, the classification of size separates, methods for obtaining particle-size distributions, textural classifications, and how quantitative textural information can be used to estimate other soil properties.

  18. Texture features analysis for coastline extraction in remotely sensed images

    NASA Astrophysics Data System (ADS)

    De Laurentiis, Raimondo; Dellepiane, Silvana G.; Bo, Giancarlo

    2002-01-01

    The accurate knowledge of the shoreline position is of fundamental importance in several applications such as cartography and ships positioning1. Moreover, the coastline could be seen as a relevant parameter for the monitoring of the coastal zone morphology, as it allows the retrieval of a much more precise digital elevation model of the entire coastal area. The study that has been carried out focuses on the development of a reliable technique for the detection of coastlines in remotely sensed images. An innovative approach which is based on the concepts of fuzzy connectivity and texture features extraction has been developed for the location of the shoreline. The system has been tested on several kind of images as SPOT, LANDSAT and the results obtained are good. Moreover, the algorithm has been tested on a sample of a SAR interferogram. The breakthrough consists in the fact that the coastline detection is seen as an important features in the framework of digital elevation model (DEM) retrieval. In particular, the coast could be seen as a boundary line all data beyond which (the ones representing the sea) are not significant. The processing for the digital elevation model could be refined, just considering the in-land data.

  19. Morphological features of the macerated cranial bones registered by the 3D vision system for potential use in forensic anthropology.

    PubMed

    Skrzat, Janusz; Sioma, Andrzej; Kozerska, Magdalena

    2013-01-01

    In this paper we present potential usage of the 3D vision system for registering features of the macerated cranial bones. Applied 3D vision system collects height profiles of the object surface and from that data builds a three-dimensional image of the surface. This method appeared to be accurate enough to capture anatomical details of the macerated bones. With the aid of the 3D vision system we generated images of the surface of the human calvaria which was used for testing the system. Performed reconstruction visualized the imprints of the dural vascular system, cranial sutures, and the three-layer structure of the cranial bones observed in the cross-section. We figure out that the 3D vision system may deliver data which can enhance estimation of sex from the osteological material.

  20. A Study of Feature Extraction Using Divergence Analysis of Texture Features

    NASA Technical Reports Server (NTRS)

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

    1982-01-01

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

  1. Wavelet based rotation invariant texture feature for lung tissue classification and retrieval

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

    This paper evaluates the performance of recently proposed rotation invariant texture feature extraction method for the classi¯cation and retrieval of lung tissues a®ected with Interstitial Lung Diseases (ILDs). The method makes use of principle texture direction as the reference direction and extracts texture features using Discrete Wavelet Transform (DWT). A private database containing high resolution computed tomography (HRCT) images belonging to ¯ve category of lung tissue is used for the experiment. The experimental result shows that the texture appearances of lung tissues are anisotropic in nature and hence rotation invariant features achieve better retrieval as well as classi¯cation accuracy.

  2. Integration of a 3D perspective view in the navigation display: featuring pilot's mental model

    NASA Astrophysics Data System (ADS)

    Ebrecht, L.; Schmerwitz, S.

    2015-05-01

    Synthetic vision systems (SVS) appear as spreading technology in the avionic domain. Several studies prove enhanced situational awareness when using synthetic vision. Since the introduction of synthetic vision a steady change and evolution started concerning the primary flight display (PFD) and the navigation display (ND). The main improvements of the ND comprise the representation of colored ground proximity warning systems (EGPWS), weather radar, and TCAS information. Synthetic vision seems to offer high potential to further enhance cockpit display systems. Especially, concerning the current trend having a 3D perspective view in a SVS-PFD while leaving the navigational content as well as methods of interaction unchanged the question arouses if and how the gap between both displays might evolve to a serious problem. This issue becomes important in relation to the transition and combination of strategic and tactical flight guidance. Hence, pros and cons of 2D and 3D views generally as well as the gap between the egocentric perspective 3D view of the PFD and the exocentric 2D top and side view of the ND will be discussed. Further a concept for the integration of a 3D perspective view, i.e., bird's eye view, in synthetic vision ND will be presented. The combination of 2D and 3D views in the ND enables a better correlation of the ND and the PFD. Additionally, this supports the building of pilot's mental model. The authors believe it will improve the situational and spatial awareness. It might prove to further raise the safety margin when operating in mountainous areas.

  3. A Novel Medical Freehand Sketch 3D Model Retrieval Method by Dimensionality Reduction and Feature Vector Transformation

    PubMed Central

    Jing, Zhang; Sheng, Kang Bao

    2016-01-01

    To assist physicians to quickly find the required 3D model from the mass medical model, we propose a novel retrieval method, called DRFVT, which combines the characteristics of dimensionality reduction (DR) and feature vector transformation (FVT) method. The DR method reduces the dimensionality of feature vector; only the top M low frequency Discrete Fourier Transform coefficients are retained. The FVT method does the transformation of the original feature vector and generates a new feature vector to solve the problem of noise sensitivity. The experiment results demonstrate that the DRFVT method achieves more effective and efficient retrieval results than other proposed methods. PMID:27293478

  4. Multi-resolution Gabor wavelet feature extraction for needle detection in 3D ultrasound

    NASA Astrophysics Data System (ADS)

    Pourtaherian, Arash; Zinger, Svitlana; Mihajlovic, Nenad; de With, Peter H. N.; Huang, Jinfeng; Ng, Gary C.; Korsten, Hendrikus H. M.

    2015-12-01

    Ultrasound imaging is employed for needle guidance in various minimally invasive procedures such as biopsy guidance, regional anesthesia and brachytherapy. Unfortunately, a needle guidance using 2D ultrasound is very challenging, due to a poor needle visibility and a limited field of view. Nowadays, 3D ultrasound systems are available and more widely used. Consequently, with an appropriate 3D image-based needle detection technique, needle guidance and interventions may significantly be improved and simplified. In this paper, we present a multi-resolution Gabor transformation for an automated and reliable extraction of the needle-like structures in a 3D ultrasound volume. We study and identify the best combination of the Gabor wavelet frequencies. High precision in detecting the needle voxels leads to a robust and accurate localization of the needle for the intervention support. Evaluation in several ex-vivo cases shows that the multi-resolution analysis significantly improves the precision of the needle voxel detection from 0.23 to 0.32 at a high recall rate of 0.75 (gain 40%), where a better robustness and confidence were confirmed in the practical experiments.

  5. 3D palmprint data fast acquisition and recognition

    NASA Astrophysics Data System (ADS)

    Wang, Xiaoxu; Huang, Shujun; Gao, Nan; Zhang, Zonghua

    2014-11-01

    This paper presents a fast 3D (Three-Dimension) palmprint capturing system and develops an efficient 3D palmprint feature extraction and recognition method. In order to fast acquire accurate 3D shape and texture of palmprint, a DLP projector triggers a CCD camera to realize synchronization. By generating and projecting green fringe pattern images onto the measured palm surface, 3D palmprint data are calculated from the fringe pattern images. The periodic feature vector can be derived from the calculated 3D palmprint data, so undistorted 3D biometrics is obtained. Using the obtained 3D palmprint data, feature matching test have been carried out by Gabor filter, competition rules and the mean curvature. Experimental results on capturing 3D palmprint show that the proposed acquisition method can fast get 3D shape information of palmprint. Some initial experiments on recognition show the proposed method is efficient by using 3D palmprint data.

  6. Automatic segmentation and 3D feature extraction of protein aggregates in Caenorhabditis elegans

    NASA Astrophysics Data System (ADS)

    Rodrigues, Pedro L.; Moreira, António H. J.; Teixeira-Castro, Andreia; Oliveira, João; Dias, Nuno; Rodrigues, Nuno F.; Vilaça, João L.

    2012-03-01

    In the last years, it has become increasingly clear that neurodegenerative diseases involve protein aggregation, a process often used as disease progression readout and to develop therapeutic strategies. This work presents an image processing tool to automatic segment, classify and quantify these aggregates and the whole 3D body of the nematode Caenorhabditis Elegans. A total of 150 data set images, containing different slices, were captured with a confocal microscope from animals of distinct genetic conditions. Because of the animals' transparency, most of the slices pixels appeared dark, hampering their body volume direct reconstruction. Therefore, for each data set, all slices were stacked in one single 2D image in order to determine a volume approximation. The gradient of this image was input to an anisotropic diffusion algorithm that uses the Tukey's biweight as edge-stopping function. The image histogram median of this outcome was used to dynamically determine a thresholding level, which allows the determination of a smoothed exterior contour of the worm and the medial axis of the worm body from thinning its skeleton. Based on this exterior contour diameter and the medial animal axis, random 3D points were then calculated to produce a volume mesh approximation. The protein aggregations were subsequently segmented based on an iso-value and blended with the resulting volume mesh. The results obtained were consistent with qualitative observations in literature, allowing non-biased, reliable and high throughput protein aggregates quantification. This may lead to a significant improvement on neurodegenerative diseases treatment planning and interventions prevention.

  7. Automatic segmentation of pulmonary fissures in computed tomography images using 3D surface features.

    PubMed

    Yu, Mali; Liu, Hong; Gong, Jianping; Jin, Renchao; Han, Ping; Song, Enmin

    2014-02-01

    Pulmonary interlobar fissures are important anatomic structures in human lungs and are useful in locating and classifying lung abnormalities. Automatic segmentation of fissures is a difficult task because of their low contrast and large variability. We developed a fully automatic training-free approach for fissure segmentation based on the local bending degree (LBD) and the maximum bending index (MBI). The LBD is determined by the angle between the eigenvectors of two Hessian matrices for a pair of adjacent voxels. It is used to construct a constraint to extract the candidate surfaces in three-dimensional (3D) space. The MBI is a measure to discriminate cylindrical surfaces from planar surfaces in 3D space. Our approach for segmenting fissures consists of five steps, including lung segmentation, plane-like structure enhancement, surface extraction with LBD, initial fissure identification with MBI, and fissure extension based on local plane fitting. When applying our approach to 15 chest computed tomography (CT) scans, the mean values of the positive predictive value, the sensitivity, the root-mean square (RMS) distance, and the maximal RMS are 91 %, 88 %, 1.01 ± 0.99 mm, and 11.56 mm, respectively, which suggests that our algorithm can efficiently segment fissures in chest CT scans.

  8. FDSOI bottom MOSFETs stability versus top transistor thermal budget featuring 3D monolithic integration

    NASA Astrophysics Data System (ADS)

    Fenouillet-Beranger, C.; Previtali, B.; Batude, P.; Nemouchi, F.; Cassé, M.; Garros, X.; Tosti, L.; Rambal, N.; Lafond, D.; Dansas, H.; Pasini, L.; Brunet, L.; Deprat, F.; Grégoire, M.; Mellier, M.; Vinet, M.

    2015-11-01

    To set up specification for 3D monolithic integration, for the first time, the thermal stability of state-of-the-art FDSOI (Fully Depleted SOI) transistors electrical performance is quantified. Post fabrication annealings are performed on FDSOI transistors to mimic the thermal budget associated to top layer processing. Degradation of the silicide for thermal treatments beyond 400 °C is identified as the main responsible for performance degradation for PMOS devices. For the NMOS transistors, arsenic (As) and phosphorus (P) dopants deactivation adds up to this effect. By optimizing both the n-type extension implantations and the bottom silicide process, thermal stability of FDSOI can be extended to allow relaxing upwards the thermal budget authorized for top transistors processing.

  9. Geometric and topological feature extraction of linear segments from 2D cross-section data of 3D point clouds

    NASA Astrophysics Data System (ADS)

    Ramamurthy, Rajesh; Harding, Kevin; Du, Xiaoming; Lucas, Vincent; Liao, Yi; Paul, Ratnadeep; Jia, Tao

    2015-05-01

    Optical measurement techniques are often employed to digitally capture three dimensional shapes of components. The digital data density output from these probes range from a few discrete points to exceeding millions of points in the point cloud. The point cloud taken as a whole represents a discretized measurement of the actual 3D shape of the surface of the component inspected to the measurement resolution of the sensor. Embedded within the measurement are the various features of the part that make up its overall shape. Part designers are often interested in the feature information since those relate directly to part function and to the analytical models used to develop the part design. Furthermore, tolerances are added to these dimensional features, making their extraction a requirement for the manufacturing quality plan of the product. The task of "extracting" these design features from the point cloud is a post processing task. Due to measurement repeatability and cycle time requirements often automated feature extraction from measurement data is required. The presence of non-ideal features such as high frequency optical noise and surface roughness can significantly complicate this feature extraction process. This research describes a robust process for extracting linear and arc segments from general 2D point clouds, to a prescribed tolerance. The feature extraction process generates the topology, specifically the number of linear and arc segments, and the geometry equations of the linear and arc segments automatically from the input 2D point clouds. This general feature extraction methodology has been employed as an integral part of the automated post processing algorithms of 3D data of fine features.

  10. Preliminary 3D In-situ measurements of the texture evolution of strained H2O ice during annealing using neutron Laue diffractometry

    NASA Astrophysics Data System (ADS)

    Journaux, Baptiste; Montagnat, Maurine; Chauve, Thomas; Ouladdiaf, Bachir; Allibon, John

    2015-04-01

    Dynamic recrystallization (DRX) strongly affects the evolution of microstructure (grain size and shape) and texture (crystal preferred orientation) in materials during deformation at high temperature. Since texturing leads to anisotropic physical properties, predicting the effect of DRX is essential for industrial applications, for interpreting geophysical data and modeling geodynamic flows, and predicting ice sheet flow and climate evolution. A large amount of literature is available related to metallurgy, geology or glaciology, but there remains overall fundamental questions about the relationship between nucleation, grain boundary migration and texture development at the microscopic scale. Previous measurements of DRX in ice were either conducted using 2D ex-situ techniques such as AITA [1,2] or Electron Backscattering Diffraction (EBSD) [3], or using 3D statistical ex-situ [4] or in-situ [5] techniques. Nevertheless, all these techniques failed to observe at the scale of nucleation processes during DRX in full 3D. Here we present a new approach using neutron Laue diffraction, which enable to perform 3D measurements of in-situ texture evolution of strained polycrystalline H2O ice (>2% at 266 K) during annealing at the microscopic scale. Thanks the CYCLOPS instrument [6] (Institut Laue Langevin Grenoble, France) and the intrinsic low background of this setup, preliminary observations enabled us to follow, in H2O ice, the evolution of serrated grain boundaries, and kink-band during annealing. Our observations show a significant evolution of the texture and internal misorientation over the course of few hours at an annealing temperature of 268.5 K. In the contrary, ice kink-band structures seem to be very stable over time at near melting temperatures. The same samples have been analyzed ex-situ using EBSD for comparison. These results represent a first step toward in-situ microscopic measurements of dynamic recrystallization processes in ice during strain. This

  11. Efficient feature-based 2D/3D registration of transesophageal echocardiography to x-ray fluoroscopy for cardiac interventions

    NASA Astrophysics Data System (ADS)

    Hatt, Charles R.; Speidel, Michael A.; Raval, Amish N.

    2014-03-01

    We present a novel 2D/ 3D registration algorithm for fusion between transesophageal echocardiography (TEE) and X-ray fluoroscopy (XRF). The TEE probe is modeled as a subset of 3D gradient and intensity point features, which facilitates efficient 3D-to-2D perspective projection. A novel cost-function, based on a combination of intensity and edge features, evaluates the registration cost value without the need for time-consuming generation of digitally reconstructed radiographs (DRRs). Validation experiments were performed with simulations and phantom data. For simulations, in silica XRF images of a TEE probe were generated in a number of different pose configurations using a previously acquired CT image. Random misregistrations were applied and our method was used to recover the TEE probe pose and compare the result to the ground truth. Phantom experiments were performed by attaching fiducial markers externally to a TEE probe, imaging the probe with an interventional cardiac angiographic x-ray system, and comparing the pose estimated from the external markers to that estimated from the TEE probe using our algorithm. Simulations found a 3D target registration error of 1.08(1.92) mm for biplane (monoplane) geometries, while the phantom experiment found a 2D target registration error of 0.69mm. For phantom experiments, we demonstrated a monoplane tracking frame-rate of 1.38 fps. The proposed feature-based registration method is computationally efficient, resulting in near real-time, accurate image based registration between TEE and XRF.

  12. Optimization of a 3D Dynamic Culturing System for In Vitro Modeling of Frontotemporal Neurodegeneration-Relevant Pathologic Features.

    PubMed

    Tunesi, Marta; Fusco, Federica; Fiordaliso, Fabio; Corbelli, Alessandro; Biella, Gloria; Raimondi, Manuela T

    2016-01-01

    Frontotemporal lobar degeneration (FTLD) is a severe neurodegenerative disorder that is diagnosed with increasing frequency in clinical setting. Currently, no therapy is available and in addition the molecular basis of the disease are far from being elucidated. Consequently, it is of pivotal importance to develop reliable and cost-effective in vitro models for basic research purposes and drug screening. To this respect, recent results in the field of Alzheimer's disease have suggested that a tridimensional (3D) environment is an added value to better model key pathologic features of the disease. Here, we have tried to add complexity to the 3D cell culturing concept by using a microfluidic bioreactor, where cells are cultured under a continuous flow of medium, thus mimicking the interstitial fluid movement that actually perfuses the body tissues, including the brain. We have implemented this model using a neuronal-like cell line (SH-SY5Y), a widely exploited cell model for neurodegenerative disorders that shows some basic features relevant for FTLD modeling, such as the release of the FTLD-related protein progranulin (PRGN) in specific vesicles (exosomes). We have efficiently seeded the cells on 3D scaffolds, optimized a disease-relevant oxidative stress experiment (by targeting mitochondrial function that is one of the possible FTLD-involved pathological mechanisms) and evaluated cell metabolic activity in dynamic culture in comparison to static conditions, finding that SH-SY5Y cells cultured in 3D scaffold are susceptible to the oxidative damage triggered by a mitochondrial-targeting toxin (6-OHDA) and that the same cells cultured in dynamic conditions kept their basic capacity to secrete PRGN in exosomes once recovered from the bioreactor and plated in standard 2D conditions. We think that a further improvement of our microfluidic system may help in providing a full device where assessing basic FTLD-related features (including PRGN dynamic secretion) that may be

  13. Optimization of a 3D Dynamic Culturing System for In Vitro Modeling of Frontotemporal Neurodegeneration-Relevant Pathologic Features.

    PubMed

    Tunesi, Marta; Fusco, Federica; Fiordaliso, Fabio; Corbelli, Alessandro; Biella, Gloria; Raimondi, Manuela T

    2016-01-01

    Frontotemporal lobar degeneration (FTLD) is a severe neurodegenerative disorder that is diagnosed with increasing frequency in clinical setting. Currently, no therapy is available and in addition the molecular basis of the disease are far from being elucidated. Consequently, it is of pivotal importance to develop reliable and cost-effective in vitro models for basic research purposes and drug screening. To this respect, recent results in the field of Alzheimer's disease have suggested that a tridimensional (3D) environment is an added value to better model key pathologic features of the disease. Here, we have tried to add complexity to the 3D cell culturing concept by using a microfluidic bioreactor, where cells are cultured under a continuous flow of medium, thus mimicking the interstitial fluid movement that actually perfuses the body tissues, including the brain. We have implemented this model using a neuronal-like cell line (SH-SY5Y), a widely exploited cell model for neurodegenerative disorders that shows some basic features relevant for FTLD modeling, such as the release of the FTLD-related protein progranulin (PRGN) in specific vesicles (exosomes). We have efficiently seeded the cells on 3D scaffolds, optimized a disease-relevant oxidative stress experiment (by targeting mitochondrial function that is one of the possible FTLD-involved pathological mechanisms) and evaluated cell metabolic activity in dynamic culture in comparison to static conditions, finding that SH-SY5Y cells cultured in 3D scaffold are susceptible to the oxidative damage triggered by a mitochondrial-targeting toxin (6-OHDA) and that the same cells cultured in dynamic conditions kept their basic capacity to secrete PRGN in exosomes once recovered from the bioreactor and plated in standard 2D conditions. We think that a further improvement of our microfluidic system may help in providing a full device where assessing basic FTLD-related features (including PRGN dynamic secretion) that may be

  14. SNL3dFace

    SciTech Connect

    Russ, Trina; Koch, Mark; Koudelka, Melissa; Peters, Ralph; Little, Charles; Boehnen, Chris; Peters, Tanya

    2007-07-20

    This software distribution contains MATLAB and C++ code to enable identity verification using 3D images that may or may not contain a texture component. The code is organized to support system performance testing and system capability demonstration through the proper configuration of the available user interface. Using specific algorithm parameters the face recognition system has been demonstrated to achieve a 96.6% verification rate (Pd) at 0.001 false alarm rate. The system computes robust facial features of a 3D normalized face using Principal Component Analysis (PCA) and Fisher Linear Discriminant Analysis (FLDA). A 3D normalized face is obtained by alighning each face, represented by a set of XYZ coordinated, to a scaled reference face using the Iterative Closest Point (ICP) algorithm. The scaled reference face is then deformed to the input face using an iterative framework with parameters that control the deformed surface regulation an rate of deformation. A variety of options are available to control the information that is encoded by the PCA. Such options include the XYZ coordinates, the difference of each XYZ coordinates from the reference, the Z coordinate, the intensity/texture values, etc. In addition to PCA/FLDA feature projection this software supports feature matching to obtain similarity matrices for performance analysis. In addition, this software supports visualization of the STL, MRD, 2D normalized, and PCA synthetic representations in a 3D environment.

  15. Impact of 3D features on ion collisional transport in ITER

    NASA Astrophysics Data System (ADS)

    Bustos, A.; Castejón, F.; Fernández, L. A.; García, J.; Martin-Mayor, V.; Reynolds, J. M.; Seki, R.; Velasco, J. L.

    2010-12-01

    The influence of magnetic ripple on ion collisional transport in ITER (Shimada et al 2007 Progress in the ITER Physics Basis: chapter 1. Overview and summary Nucl. Fusion 47 S1) is calculated using the Monte Carlo orbit code ISDEP (Castejón et al 2007 Plasma Phys. Control. Fusion 49 753). The ripple is introduced as a perturbation to the 2D equilibrium configuration of the device, given by the HELENA code (Huysmans 1991 CP90 Conf. on Computational Physics (Amsterdam, The Netherlands, 1990) (Singapore: World Scientific) p 371), obtaining a 3D configuration. Since the intensity of the ripple can change depending on the design of the test blanket modules that will be introduced in ITER, a scan of the ripple intensity has been performed to study the changes in confinement properties. The main result is that an increase in the perturbation leads to a degradation of the confinement due to an increase in the radial fluxes. The selective ion losses cause modifications in the ion distribution function. In this work most of the computing time has been provided by a new Citizen Supercomputer called Ibercivis.

  16. Performance of linear and nonlinear texture measures in 2D and 3D for monitoring architectural changes in osteoporosis using computer-generated models of trabecular bone

    NASA Astrophysics Data System (ADS)

    Boehm, Holger F.; Link, Thomas M.; Monetti, Roberto A.; Mueller, Dirk; Rummeny, Ernst J.; Raeth, Christoph W.

    2005-04-01

    Osteoporosis is a metabolic bone disease leading to de-mineralization and increased risk of fracture. The two major factors that determine the biomechanical competence of bone are the degree of mineralization and the micro-architectural integrity. Today, modern imaging modalities (high resolution MRI, micro-CT) are capable of depicting structural details of trabecular bone tissue. From the image data, structural properties obtained by quantitative measures are analysed with respect to the presence of osteoporotic fractures of the spine (in-vivo) or correlated with biomechanical strength as derived from destructive testing (in-vitro). Fairly well established are linear structural measures in 2D that are originally adopted from standard histo-morphometry. Recently, non-linear techniques in 2D and 3D based on the scaling index method (SIM), the standard Hough transform (SHT), and the Minkowski Functionals (MF) have been introduced, which show excellent performance in predicting bone strength and fracture risk. However, little is known about the performance of the various parameters with respect to monitoring structural changes due to progression of osteoporosis or as a result of medical treatment. In this contribution, we generate models of trabecular bone with pre-defined structural properties which are exposed to simulated osteoclastic activity. We apply linear and non-linear texture measures to the models and analyse their performance with respect to detecting architectural changes. This study demonstrates, that the texture measures are capable of monitoring structural changes of complex model data. The diagnostic potential varies for the different parameters and is found to depend on the topological composition of the model and initial "bone density". In our models, non-linear texture measures tend to react more sensitively to small structural changes than linear measures. Best performance is observed for the 3rd and 4th Minkowski Functionals and for the scaling

  17. Visualizing and Tracking Evolving Features in 3D Unstructured and Adaptive Datasets

    SciTech Connect

    Silver, D.; Zabusky, N.

    2002-08-01

    The massive amounts of time-varying datasets being generated demand new visualization and quantification techniques. Visualization alone is not sufficient. Without proper measurement information/computations real science cannot be done. Our focus is this work was to combine visualization with quantification of the data to allow for advanced querying and searching. As part of this proposal, we have developed a feature extraction adn tracking methodology which allows researcher to identify features of interest and follow their evolution over time. The implementation is distributed and operates over data In-situ: where it is stored and when it was computed.

  18. Feature-location binding in 3D: Feature judgments are biased by 2D location but not position-in-depth.

    PubMed

    Finlayson, Nonie J; Golomb, Julie D

    2016-10-01

    A fundamental aspect of human visual perception is the ability to recognize and locate objects in the environment. Importantly, our environment is predominantly three-dimensional (3D), but while there is considerable research exploring the binding of object features and location, it is unknown how depth information interacts with features in the object binding process. A recent paradigm called the spatial congruency bias demonstrated that 2D location is fundamentally bound to object features, such that irrelevant location information biases judgments of object features, but irrelevant feature information does not bias judgments of location or other features. Here, using the spatial congruency bias paradigm, we asked whether depth is processed as another type of location, or more like other features. We initially found that depth cued by binocular disparity biased judgments of object color. However, this result seemed to be driven more by the disparity differences than the depth percept: Depth cued by occlusion and size did not bias color judgments, whereas vertical disparity information (with no depth percept) did bias color judgments. Our results suggest that despite the 3D nature of our visual environment, only 2D location information - not position-in-depth - seems to be automatically bound to object features, with depth information processed more similarly to other features than to 2D location. PMID:27468654

  19. Feature-location binding in 3D: Feature judgments are biased by 2D location but not position-in-depth.

    PubMed

    Finlayson, Nonie J; Golomb, Julie D

    2016-10-01

    A fundamental aspect of human visual perception is the ability to recognize and locate objects in the environment. Importantly, our environment is predominantly three-dimensional (3D), but while there is considerable research exploring the binding of object features and location, it is unknown how depth information interacts with features in the object binding process. A recent paradigm called the spatial congruency bias demonstrated that 2D location is fundamentally bound to object features, such that irrelevant location information biases judgments of object features, but irrelevant feature information does not bias judgments of location or other features. Here, using the spatial congruency bias paradigm, we asked whether depth is processed as another type of location, or more like other features. We initially found that depth cued by binocular disparity biased judgments of object color. However, this result seemed to be driven more by the disparity differences than the depth percept: Depth cued by occlusion and size did not bias color judgments, whereas vertical disparity information (with no depth percept) did bias color judgments. Our results suggest that despite the 3D nature of our visual environment, only 2D location information - not position-in-depth - seems to be automatically bound to object features, with depth information processed more similarly to other features than to 2D location.

  20. Texture feature standardization in digital mammography for improving generalizability across devices

    NASA Astrophysics Data System (ADS)

    Wang, Yan; Keller, Brad M.; Zheng, Yuanjie; Acciavatti, Raymond J.; Gee, James C.; Maidment, Andrew D. A.; Kontos, Despina

    2013-02-01

    Growing evidence suggests a relationship between mammographic texture and breast cancer risk. For studies performing texture analysis on digital mammography (DM) images from various DM systems, it is important to evaluate if different systems could introduce inherent differences in the images analyzed and how to construct a methodological framework to identify and standardize such effects, if these differences exist. In this study, we compared two DM systems, the GE Senographe 2000D and DS using a validated physical breast phantom (Rachel, Gammex). The GE 2000D and DS systems use the same detector, but a different automated exposure control (AEC) system, resulting in differences in dose performance. On each system, images of the phantom are acquired five times in the Cranio-Caudal (CC) view with the same clinically optimized phototimer setting. Three classes of texture features, namely grey-level histogram, cooccurrence, and run-length texture features (a total of 26 features), are generated within the breast region from the raw DM images and compared between the two imaging systems. To alleviate system effects, a range of standardization steps are applied to the feature extraction process: z-score normalization is performed as the initial step to standardize image intensities, and the parameters in generating co-occurrence features are varied to decrease system differences introduced by detector blurring effects. To identify texture features robust to detectors (i.e. the ones minimally affected only by electronic noise), the distribution of each texture feature is compared between the two systems using the Kolmogorov-Smirnov (K-S) test at 0.05 significance, where features with p>0.05 are deemed robust to inherent system differences. Our approach could provide a basis for texture feature standardization across different DM imaging systems and provide a systematic methodology for selecting generalizable texture descriptors in breast cancer risk assessment.

  1. Surface processes on the asteroid deduced from the external 3D shapes and surface features of Itokawa particles

    NASA Astrophysics Data System (ADS)

    Tsuchiyama, A.; Matsumoto, T.

    2015-10-01

    Particles on the surface of S-type Asteroid 25143 Itokawa were successfully recovered by the Hayabusa mission of JAXA (e.g., [1,2]). They are not only the first samples recovered from an asteroid, but also the second extraterrestrial regolith to have been sampled, the first being the Moon by Apollo and Luna missions. The analysis of tiny sample particles (20-200 μm) shows that the Itokawa surface material is consistent with LL chondrites suffered by space weathering as expected and brought an end to the origin of meteorites (e.g., [2-4]). In addition, the examination of Itokawa particles allow studies of surface processes on the asteroid because regolith particles can be regarded as an interface with the space environment, where the impacts of small objects and irradiation by the solar wind and galactic cosmic rays should have been recorded. External 3D shapes and surface features of Itokawa regolith particles were examined. Two kinds of surface modification, formation of space-weathering rims mainly by solar wind implantation and surface abrasion by grain migration, were recognized. Spectral change of the asteroid proceeded by formation of space-weathering rims and refreshment of the regolith surfaces. External 3D shapes and surface morphologies of the regolith particles can provide information about formation and evolution history of regolith particles in relation to asteroidal surface processes. 3D shapes of Itokawa regolith particles were obtained using microtomography [3]. The surface nanomiromorpholgy of Itokawa particles were also observed using FE-SEM [5]. However, the number of particles was limited and genial feature on the surface morphology has not been understood. In this study, the surface morphology of Itokawa regolith particles was systematically investigated together with their 3D structures.

  2. A comparison study of textural features between FFDM and film mammogram images

    NASA Astrophysics Data System (ADS)

    Jing, Hao; Yang, Yongyi; Wernick, Miles N.; Yarusso, Laura M.; Nishikawa, Robert M.

    2011-03-01

    In this work, we conducted an imaging study to make a direct, quantitative comparison of image features measured by film and full-field digital mammography (FFDM). We acquired images of cadaver breast specimens containing simulated microcalcifications using both a GE digital mammography system and a screen-film system. To quantify the image features, we calculated and compared a set of 12 texture features derived from spatial gray-level dependence matrices. Our results demonstrate that there is a great degree of agreement between film and FFDM, with the correlation coefficient of the feature vector (formed by the 12 textural features) being 0.9569 between the two; in addition, a paired sign test reveals no significant difference between film and FFDM features. These results indicate that textural features may be interchangeable between film and FFDM for CAD algorithms.

  3. Design-based texture feature fusion using Gabor filters and co-occurrence probabilities.

    PubMed

    Clausi, David A; Deng, Huang

    2005-07-01

    A design-based method to fuse Gabor filter and grey level co-occurrence probability (GLCP) features for improved texture recognition is presented. The fused feature set utilizes both the Gabor filter's capability of accurately capturing lower and mid-frequency texture information and the GLCP's capability in texture information relevant to higher frequency components. Evaluation methods include comparing feature space separability and comparing image segmentation classification rates. The fused feature sets are demonstrated to produce higher feature space separations, as well as higher segmentation accuracies relative to the individual feature sets. Fused feature sets also outperform individual feature sets for noisy images, across different noise magnitudes. The curse of dimensionality is demonstrated not to affect segmentation using the proposed the 48-dimensional fused feature set. Gabor magnitude responses produce higher segmentation accuracies than linearly normalized Gabor magnitude responses. Feature reduction using principal component analysis is acceptable for maintaining the segmentation performance, but feature reduction using the feature contrast method dramatically reduced the segmentation accuracy. Overall, the designed fused feature set is advocated as a means for improving texture segmentation performance.

  4. 3D Face modeling using the multi-deformable method.

    PubMed

    Hwang, Jinkyu; Yu, Sunjin; Kim, Joongrock; Lee, Sangyoun

    2012-01-01

    In this paper, we focus on the problem of the accuracy performance of 3D face modeling techniques using corresponding features in multiple views, which is quite sensitive to feature extraction errors. To solve the problem, we adopt a statistical model-based 3D face modeling approach in a mirror system consisting of two mirrors and a camera. The overall procedure of our 3D facial modeling method has two primary steps: 3D facial shape estimation using a multiple 3D face deformable model and texture mapping using seamless cloning that is a type of gradient-domain blending. To evaluate our method's performance, we generate 3D faces of 30 individuals and then carry out two tests: accuracy test and robustness test. Our method shows not only highly accurate 3D face shape results when compared with the ground truth, but also robustness to feature extraction errors. Moreover, 3D face rendering results intuitively show that our method is more robust to feature extraction errors than other 3D face modeling methods. An additional contribution of our method is that a wide range of face textures can be acquired by the mirror system. By using this texture map, we generate realistic 3D face for individuals at the end of the paper. PMID:23201976

  5. 3D Face Modeling Using the Multi-Deformable Method

    PubMed Central

    Hwang, Jinkyu; Yu, Sunjin; Kim, Joongrock; Lee, Sangyoun

    2012-01-01

    In this paper, we focus on the problem of the accuracy performance of 3D face modeling techniques using corresponding features in multiple views, which is quite sensitive to feature extraction errors. To solve the problem, we adopt a statistical model-based 3D face modeling approach in a mirror system consisting of two mirrors and a camera. The overall procedure of our 3D facial modeling method has two primary steps: 3D facial shape estimation using a multiple 3D face deformable model and texture mapping using seamless cloning that is a type of gradient-domain blending. To evaluate our method's performance, we generate 3D faces of 30 individuals and then carry out two tests: accuracy test and robustness test. Our method shows not only highly accurate 3D face shape results when compared with the ground truth, but also robustness to feature extraction errors. Moreover, 3D face rendering results intuitively show that our method is more robust to feature extraction errors than other 3D face modeling methods. An additional contribution of our method is that a wide range of face textures can be acquired by the mirror system. By using this texture map, we generate realistic 3D face for individuals at the end of the paper. PMID:23201976

  6. 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.

  7. 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.

  8. Classification of High Resolution C-Band PolSAR Data on Polarimetric and Texture Features

    NASA Astrophysics Data System (ADS)

    Zhao, Lei; Chen, Erxue; Li, Zengyuan; Feng, Qi; Li, Lan

    2014-11-01

    PolSAR image classification is an important technique in the remote sensing area. For high resolution PolSAR image, polarimetric and texture features are equally important for the high resolution PolSAR image classification. The texture features are mainly extracted through Gray Level Co-occurrence Matrix (GLCM) method, but this method has some deficiencies. First, GLCM method can only work on gray-scale images; Secondly, the number of texture features extracted by GLCM method is generally up dozens, or even hundreds. Too many features may exist larger redundancy and will increase the complexity of classification. Therefore, this paper introduces a new texture feature factor-RK that derived from PolSAR image non-Gaussian statistic model.Using the domestic airborne C-band PolSAR image data, we completed classification combined the polarization and texture characteristics.The results showed that this new texture feature factor-RK can overcome the above drawbacks and can achieve same performance compared with GLCM method.

  9. Impact of the biophysical features of a 3D gelatin microenvironment on glioblastoma malignancy.

    PubMed

    Pedron, S; Harley, B A C

    2013-12-01

    Three-dimensional tissue engineered constructs provide a platform to examine how the local extracellular matrix (ECM) contributes to the malignancy of cancers such as human glioblastoma multiforme. Improved resolution of how local matrix biophysical features impact glioma proliferation, genomic and signal transduction paths, as well as phenotypic malignancy markers would complement recent improvements in our understanding of molecular mechanisms associated with enhanced malignancy. Here, we report the use of a gelatin methacrylate (GelMA) platform to create libraries of three-dimensional biomaterials to identify combinations of biophysical features that promote malignant phenotypes of human U87MG glioma cells. We noted key biophysical properties, namely matrix density, crosslinking density, and biodegradability, that significantly impact glioma cell morphology, proliferation, and motility. Gene expression profiles and secreted markers of increased malignancy, notably VEGF, MMP-2, MMP-9, HIF-1, and the ECM protein fibronectin, were also significantly impacted by the local biophysical environment as well as matrix-induced deficits in diffusion-mediated oxygen and nutrient biotransport. Overall, this biomaterial system provides a flexible platform to explore the role biophysical factors play in the etiology, growth, and subsequent invasive spreading of gliomas.

  10. SNL3dFace

    2007-07-20

    This software distribution contains MATLAB and C++ code to enable identity verification using 3D images that may or may not contain a texture component. The code is organized to support system performance testing and system capability demonstration through the proper configuration of the available user interface. Using specific algorithm parameters the face recognition system has been demonstrated to achieve a 96.6% verification rate (Pd) at 0.001 false alarm rate. The system computes robust facial featuresmore » of a 3D normalized face using Principal Component Analysis (PCA) and Fisher Linear Discriminant Analysis (FLDA). A 3D normalized face is obtained by alighning each face, represented by a set of XYZ coordinated, to a scaled reference face using the Iterative Closest Point (ICP) algorithm. The scaled reference face is then deformed to the input face using an iterative framework with parameters that control the deformed surface regulation an rate of deformation. A variety of options are available to control the information that is encoded by the PCA. Such options include the XYZ coordinates, the difference of each XYZ coordinates from the reference, the Z coordinate, the intensity/texture values, etc. In addition to PCA/FLDA feature projection this software supports feature matching to obtain similarity matrices for performance analysis. In addition, this software supports visualization of the STL, MRD, 2D normalized, and PCA synthetic representations in a 3D environment.« less

  11. Rotation and Scale Invariant Wavelet Feature for Content-Based Texture Image Retrieval.

    ERIC Educational Resources Information Center

    Lee, Moon-Chuen; Pun, Chi-Man

    2003-01-01

    Introduces a rotation and scale invariant log-polar wavelet texture feature for image retrieval. The underlying feature extraction process involves a log-polar transform followed by an adaptive row shift invariant wavelet packet transform. Experimental results show that this rotation and scale invariant wavelet feature is quite effective for image…

  12. Two nanosized 3d-4f clusters featuring four Ln6 octahedra encapsulating a Zn4 tetrahedron.

    PubMed

    Zheng, Xiu-Ying; Wang, Shi-Qiang; Tang, Wen; Zhuang, Gui-Lin; Kong, Xiang-Jian; Ren, Yan-Ping; Long, La-Sheng; Zheng, Lan-Sun

    2015-07-01

    Two high-nuclearity 3d-4f clusters Ln24Zn4 (Ln = Gd and Sm) featuring four Ln6 octahedra encapsulating a Zn4 tetrahedron were obtained through the self-assembly of Zn(OAc)2 and Ln(ClO4)3. Quantum Monte Carlo (QMC) simulations show the antiferromagnetic coupling between Gd(3+) ions. Studies of the magnetocaloric effect (MCE) show that the Gd24Zn4 cluster exhibits the entropy change (-ΔSm) of 31.4 J kg(-1) K(-1).

  13. Diagnostic Performance of 3D Standing CT Imaging For Detection of Knee Osteoarthritis Features

    PubMed Central

    Segal, Neil A; Nevitt, Michael C.; Lynch, John A; Niu, Jingbo; Torner, James C; Guermazi, Ali

    2016-01-01

    Objective To determine the diagnostic performance of standing computerized tomography (SCT) of the knee for osteophytes and subchondral cysts compared to fixed-flexion radiography, using magnetic resonance imaging (MRI) as the reference standard. Methods Twenty participants were recruited from the Multicenter Osteoarthritis Study (MOST). Participants' knees were imaged with SCT while standing in a knee-positioning frame, and with PA fixed-flexion radiography and 1T MRI. Medial and lateral marginal osteophytes and subchondral cysts were scored on bilateral radiographs and coronal SCT images using the OARSI grading system and on coronal MRI using Whole Organ MRI Scoring (WORMS). Imaging modalities were read separately with images in random order. Sensitivity, specificity, and accuracy for the detection of lesions were calculated and differences between modalities were tested using McNemar's test. Results Participants' mean age was 66.8 years, BMI was 29.6kg/m2 and 50% were women. Of the 160 surfaces (medial and lateral femur and tibia for 40 knees), MRI revealed 84 osteophytes and 10 subchondral cysts. In comparison with osteophytes and subchondral cysts detected by MRI, SCT was significantly more sensitive (93% and 100%; p<0.004) and accurate (95% and 99%; p<0.001 for osteophytes) than plain radiographs (sensitivity: 60% and 10% and accuracy 79% and 94% respectively). For osteophytes, differences in sensitivity and accuracy were greatest at the medial femur (p=0.002). Conclusions In comparison with MRI, SCT imaging was more sensitive and accurate for detection of osteophytes and subchondral cysts than conventional fixed-flexion radiography. Additional study is warranted to assess diagnostic performance of SCT measures of joint space width, progression of OA features and the patellofemoral joint. PMID:26313455

  14. Optimization of a 3D Dynamic Culturing System for In Vitro Modeling of Frontotemporal Neurodegeneration-Relevant Pathologic Features

    PubMed Central

    Tunesi, Marta; Fusco, Federica; Fiordaliso, Fabio; Corbelli, Alessandro; Biella, Gloria; Raimondi, Manuela T.

    2016-01-01

    Frontotemporal lobar degeneration (FTLD) is a severe neurodegenerative disorder that is diagnosed with increasing frequency in clinical setting. Currently, no therapy is available and in addition the molecular basis of the disease are far from being elucidated. Consequently, it is of pivotal importance to develop reliable and cost-effective in vitro models for basic research purposes and drug screening. To this respect, recent results in the field of Alzheimer’s disease have suggested that a tridimensional (3D) environment is an added value to better model key pathologic features of the disease. Here, we have tried to add complexity to the 3D cell culturing concept by using a microfluidic bioreactor, where cells are cultured under a continuous flow of medium, thus mimicking the interstitial fluid movement that actually perfuses the body tissues, including the brain. We have implemented this model using a neuronal-like cell line (SH-SY5Y), a widely exploited cell model for neurodegenerative disorders that shows some basic features relevant for FTLD modeling, such as the release of the FTLD-related protein progranulin (PRGN) in specific vesicles (exosomes). We have efficiently seeded the cells on 3D scaffolds, optimized a disease-relevant oxidative stress experiment (by targeting mitochondrial function that is one of the possible FTLD-involved pathological mechanisms) and evaluated cell metabolic activity in dynamic culture in comparison to static conditions, finding that SH-SY5Y cells cultured in 3D scaffold are susceptible to the oxidative damage triggered by a mitochondrial-targeting toxin (6-OHDA) and that the same cells cultured in dynamic conditions kept their basic capacity to secrete PRGN in exosomes once recovered from the bioreactor and plated in standard 2D conditions. We think that a further improvement of our microfluidic system may help in providing a full device where assessing basic FTLD-related features (including PRGN dynamic secretion) that may

  15. Generated 3D-common feature hypotheses using the HipHop method for developing new topoisomerase I inhibitors.

    PubMed

    Ataei, Sanaz; Yilmaz, Serap; Ertan-Bolelli, Tugba; Yildiz, Ilkay

    2015-07-01

    The continued interest in designing novel topoisomerase I (Topo I) inhibitors and the lack of adequate ligand-based computer-aided drug discovery efforts combined with the drawbacks of structure-based design prompted us to explore the possibility of developing ligand-based three-dimensional (3D) pharmacophore(s). This approach avoids the pitfalls of structure-based techniques because it only focuses on common features among known ligands; furthermore, the pharmacophore model can be used as 3D search queries to discover new Topo I inhibitory scaffolds. In this article, we employed the HipHop module using Discovery Studio to construct plausible binding hypotheses for clinically used Topo I inhibitors, such as camptothecin, topotecan, belotecan, and SN-38, which is an active metabolite of irinotecan. The docked pose of topotecan was selected as a reference compound. The first hypothesis (Hypo 01) among the obtained 10 hypotheses was chosen for further analysis. Hypo 01 had six features, which were two hydrogen-bond acceptors, one hydrogen-bond donor, one hydrophob aromatic and one hydrophob aliphatic, and one ring aromatic. Our obtained hypothesis was checked by using some of the aromathecin derivatives which were published for their Topo I inhibitory potency. Moreover, five structures were found to be possible anti-Topo I compounds from the DruglikeDiverse database. From this research, it can be suggested that our model could be useful for further studies in order to design new potent Topo I-targeting antitumor drugs. PMID:25914208

  16. Generated 3D-common feature hypotheses using the HipHop method for developing new topoisomerase I inhibitors.

    PubMed

    Ataei, Sanaz; Yilmaz, Serap; Ertan-Bolelli, Tugba; Yildiz, Ilkay

    2015-07-01

    The continued interest in designing novel topoisomerase I (Topo I) inhibitors and the lack of adequate ligand-based computer-aided drug discovery efforts combined with the drawbacks of structure-based design prompted us to explore the possibility of developing ligand-based three-dimensional (3D) pharmacophore(s). This approach avoids the pitfalls of structure-based techniques because it only focuses on common features among known ligands; furthermore, the pharmacophore model can be used as 3D search queries to discover new Topo I inhibitory scaffolds. In this article, we employed the HipHop module using Discovery Studio to construct plausible binding hypotheses for clinically used Topo I inhibitors, such as camptothecin, topotecan, belotecan, and SN-38, which is an active metabolite of irinotecan. The docked pose of topotecan was selected as a reference compound. The first hypothesis (Hypo 01) among the obtained 10 hypotheses was chosen for further analysis. Hypo 01 had six features, which were two hydrogen-bond acceptors, one hydrogen-bond donor, one hydrophob aromatic and one hydrophob aliphatic, and one ring aromatic. Our obtained hypothesis was checked by using some of the aromathecin derivatives which were published for their Topo I inhibitory potency. Moreover, five structures were found to be possible anti-Topo I compounds from the DruglikeDiverse database. From this research, it can be suggested that our model could be useful for further studies in order to design new potent Topo I-targeting antitumor drugs.

  17. Obtaining 3d models of surface snow and ice features (penitentes) with a Xbox Kinect

    NASA Astrophysics Data System (ADS)

    Nicholson, Lindsey; Partan, Benjamin; Pętlicki, Michał; MacDonell, Shelley

    2014-05-01

    Penitentes are snow or ice spikes that can reach several metres in height. They are a common feature of snow and ice surfaces in the semi-arid Andes as their formation is favoured by very low humidity, persistently low temperatures and sustained high solar radiation. While the conditions of their formation are relatively well constrained it is not yet clear how their presence influences the rate of mass loss and meltwater production from the mountain cryosphere and there is a need for accurate measurements of ablation within penitente fields through time in order to evaluate how well existing energy balance models perform for surfaces with penitentes. The complex surface morphology poses a challenge to measuring the mass loss at snow or glacier surfaces as (i) the spatial distribution of surface lowering within a penitente field is very heterogeneous, and (ii) the steep walls and sharp edges of the penitentes limit the line of sight view for surveying from fixed positions. In this work we explored whether these problems can be solved by using the Xbox Kinect sensor to generate small scale digital terrain models (DTMs) of sample areas of snow and ice penitentes. The study site was Glaciar Tapado in Chile (30°08'S; 69°55'W) where three sample sites were monitored from November 2013 to January 2014. The range of the Kinect sensor was found to be restricted to about 1 m over snow and ice, and scanning was only possible after dusk. Moving the sensor around the penitente field was challenging and often resulted in fragmented scans. However, despite these challenges, the scans obtained could be successfully combined in MeshLab software to produce good surface representations of the penitentes. GPS locations of target stakes in the sample plots allow the DTMs to be orientated correctly in space so the morphology of the penitente field and the volume loss through time can be fully described. At the study site in snow penitentes the Kinect DTM was compared with the quality

  18. 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.

  19. Texture feature analysis for prediction of postoperative liver failure prior to surgery

    NASA Astrophysics Data System (ADS)

    Simpson, Amber L.; Do, Richard K.; Parada, E. Patricia; Miga, Michael I.; Jarnagin, William R.

    2014-03-01

    Texture analysis of preoperative CT images of the liver is undertaken in this study. Standard texture features were extracted from portal-venous phase contrast-enhanced CT scans of 36 patients prior to major hepatic resection and correlated to postoperative liver failure. Differences between patients with and without postoperative liver failure were statistically significant for contrast (measure of local variation), correlation (linear dependency of gray levels on neighboring pixels), cluster prominence (asymmetry), and normalized inverse difference moment (local homogeneity). Though texture features have been used to diagnose and characterize lesions, to our knowledge, parenchymal statistical variation has not been quantified and studied. We demonstrate that texture analysis is a valuable tool for quantifying liver function prior to surgery, which may help to identify and change the preoperative management of patients at higher risk for overall morbidity.

  20. Smooth versus Textured Surfaces: Feature-Based Category Selectivity in Human Visual Cortex

    PubMed Central

    Tootell, Roger

    2016-01-01

    Abstract In fMRI studies, human lateral occipital (LO) cortex is thought to respond selectively to images of objects, compared with nonobjects. However, it remains unresolved whether all objects evoke equivalent levels of activity in LO, and, if not, which image features produce stronger activation. Here, we used an unbiased parametric texture model to predict preferred versus nonpreferred stimuli in LO. Observation and psychophysical results showed that predicted preferred stimuli (both objects and nonobjects) had smooth (rather than textured) surfaces. These predictions were confirmed using fMRI, for objects and nonobjects. Similar preferences were also found in the fusiform face area (FFA). Consistent with this: (1) FFA and LO responded more strongly to nonfreckled (smooth) faces, compared with otherwise identical freckled (textured) faces; and (2) strong functional connections were found between LO and FFA. Thus, LO and FFA may be part of an information-processing stream distinguished by feature-based category selectivity (smooth > textured).

  1. Smooth versus Textured Surfaces: Feature-Based Category Selectivity in Human Visual Cortex

    PubMed Central

    Tootell, Roger

    2016-01-01

    Abstract In fMRI studies, human lateral occipital (LO) cortex is thought to respond selectively to images of objects, compared with nonobjects. However, it remains unresolved whether all objects evoke equivalent levels of activity in LO, and, if not, which image features produce stronger activation. Here, we used an unbiased parametric texture model to predict preferred versus nonpreferred stimuli in LO. Observation and psychophysical results showed that predicted preferred stimuli (both objects and nonobjects) had smooth (rather than textured) surfaces. These predictions were confirmed using fMRI, for objects and nonobjects. Similar preferences were also found in the fusiform face area (FFA). Consistent with this: (1) FFA and LO responded more strongly to nonfreckled (smooth) faces, compared with otherwise identical freckled (textured) faces; and (2) strong functional connections were found between LO and FFA. Thus, LO and FFA may be part of an information-processing stream distinguished by feature-based category selectivity (smooth > textured). PMID:27699206

  2. Wood Texture Features Extraction by Using GLCM Combined With Various Edge Detection Methods

    NASA Astrophysics Data System (ADS)

    Fahrurozi, A.; Madenda, S.; Ernastuti; Kerami, D.

    2016-06-01

    An image forming specific texture can be distinguished manually through the eye. However, sometimes it is difficult to do if the texture owned quite similar. Wood is a natural material that forms a unique texture. Experts can distinguish the quality of wood based texture observed in certain parts of the wood. In this study, it has been extracted texture features of the wood image that can be used to identify the characteristics of wood digitally by computer. Feature extraction carried out using Gray Level Co-occurrence Matrices (GLCM) built on an image from several edge detection methods applied to wood image. Edge detection methods used include Roberts, Sobel, Prewitt, Canny and Laplacian of Gaussian. The image of wood taken in LE2i laboratory, Universite de Bourgogne from the wood sample in France that grouped by their quality by experts and divided into four types of quality. Obtained a statistic that illustrates the distribution of texture features values of each wood type which compared according to the edge operator that is used and selection of specified GLCM parameters.

  3. 3D reconstruction of the Shigella T3SS transmembrane regions reveals 12-fold symmetry and novel features throughout

    PubMed Central

    Hodgkinson, Julie L.; Horsley, Ashley; Stabat, David; Simon, Martha; Johnson, Steven; da Fonseca, Paula C. A.; Morris, Edward P.; Wall, Joseph S.; Lea, Susan M.; Blocker, Ariel J.

    2009-01-01

    Type III secretion systems (T3SSs) mediate bacterial protein translocation into eukaryotic cells, a process essential for virulence of many Gram-negative pathogens. They are composed of a cytoplasmic secretion machinery and a base bridging both bacterial membranes into which a hollow, external needle is embedded. When isolated, the latter two parts are termed ‘needle complex’ (NC). Incomplete understanding of NC structure hampers studies of T3SS function. To estimate the stoichiometry of its components, the mass f its sub-domains was measured by scanning transmission electron microscopy (STEM). Subunit symmetries were determined by analysis of top and side views within negatively stained samples in low dose transmission electron microscopy (TEM). Application of 12-fold symmetry allowed generation of a 21-25Å resolution three-dimensional (3D) reconstruction of the NC base, revealing many new features and permitting tentative docking of the crystal structure of EscJ, an inner membrane component. PMID:19396171

  4. Automatic Ship Detection in Single-Pol SAR Images Using Texture Features in Artificial Neural Networks

    NASA Astrophysics Data System (ADS)

    Khesali, E.; Enayati, H.; Modiri, M.; Mohseni Aref, M.

    2015-12-01

    This paper presents a novel method for detecting ships from high-resolution synthetic aperture radar (SAR) images. This method categorizes ship targets from single-pol SAR images using texture features in artificial neural networks. As such, the method tries to overcome the lack of an operational solution that is able to reliably detect ships with one SAR channel. The method has the following three main stages: 1) feature extraction; 2) feature selection; and 3) ship detection. The first part extracts different texture features from SAR image. These textures include occurrence and co occurrence measures with different window sizes. Then, best features are selected. Finally, the artificial neural network is used to extract ship pixels from sea ones. In post processing stage some morphological filters are used to improve the result. The effectiveness of the proposed method is verified using Sentinel-1 data in VV polarization. Experimental results indicate that the proposed algorithm can be implemented with time-saving, high precision ship extraction, feature analysis, and detection. The results also show that using texture features the algorithm properly discriminates speckle noise from ships.

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

    NASA Astrophysics Data System (ADS)

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

    2014-04-01

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

  6. An intelligent recovery progress evaluation system for ACL reconstructed subjects using integrated 3-D kinematics and EMG features.

    PubMed

    Malik, Owais A; Senanayake, S M N Arosha; Zaheer, Dansih

    2015-03-01

    An intelligent recovery evaluation system is presented for objective assessment and performance monitoring of anterior cruciate ligament reconstructed (ACL-R) subjects. The system acquires 3-D kinematics of tibiofemoral joint and electromyography (EMG) data from surrounding muscles during various ambulatory and balance testing activities through wireless body-mounted inertial and EMG sensors, respectively. An integrated feature set is generated based on different features extracted from data collected for each activity. The fuzzy clustering and adaptive neuro-fuzzy inference techniques are applied to these integrated feature sets in order to provide different recovery progress assessment indicators (e.g., current stage of recovery, percentage of recovery progress as compared to healthy group, etc.) for ACL-R subjects. The system was trained and tested on data collected from a group of healthy and ACL-R subjects. For recovery stage identification, the average testing accuracy of the system was found above 95% (95-99%) for ambulatory activities and above 80% (80-84%) for balance testing activities. The overall recovery evaluation performed by the proposed system was found consistent with the assessment made by the physiotherapists using standard subjective/objective scores. The validated system can potentially be used as a decision supporting tool by physiatrists, physiotherapists, and clinicians for quantitative rehabilitation analysis of ACL-R subjects in conjunction with the existing recovery monitoring systems.

  7. Detection of hypertensive retinopathy using vessel measurements and textural features.

    PubMed

    Agurto, Carla; Joshi, Vinayak; Nemeth, Sheila; Soliz, Peter; Barriga, Simon

    2014-01-01

    Features that indicate hypertensive retinopathy have been well described in the medical literature. This paper presents a new system to automatically classify subjects with hypertensive retinopathy (HR) using digital color fundus images. Our method consists of the following steps: 1) normalization and enhancement of the image; 2) determination of regions of interest based on automatic location of the optic disc; 3) segmentation of the retinal vasculature and measurement of vessel width and tortuosity; 4) extraction of color features; 5) classification of vessel segments as arteries or veins; 6) calculation of artery-vein ratios using the six widest (major) vessels for each category; 7) calculation of mean red intensity and saturation values for all arteries; 8) calculation of amplitude-modulation frequency-modulation (AM-FM) features for entire image; and 9) classification of features into HR and non-HR using linear regression. This approach was tested on 74 digital color fundus photographs taken with TOPCON and CANON retinal cameras using leave-one out cross validation. An area under the ROC curve (AUC) of 0.84 was achieved with sensitivity and specificity of 90% and 67%, respectively. PMID:25571216

  8. Texture feature selection with relevance learning to classify interstitial lung disease patterns

    NASA Astrophysics Data System (ADS)

    Huber, Markus B.; Bunte, Kerstin; Nagarajan, Mahesh B.; Biehl, Michael; Ray, Lawrence A.; Wismueller, Axel

    2011-03-01

    The Generalized Matrix Learning Vector Quantization (GMLVQ) is used to estimate the relevance of texture features in their ability to classify interstitial lung disease patterns in high-resolution computed tomography (HRCT) images. After a stochastic gradient descent, the GMLVQ algorithm provides a discriminative distance measure of relevance factors, which can account for pairwise correlations between different texture features and their importance for the classification of healthy and diseased patterns. Texture features were extracted from gray-level co-occurrence matrices (GLCMs), and were ranked and selected according to their relevance obtained by GMLVQ and, for comparison, to a mutual information (MI) criteria. A k-nearest-neighbor (kNN) classifier and a Support Vector Machine with a radial basis function kernel (SVMrbf) were optimized in a 10-fold crossvalidation for different texture feature sets. In our experiment with real-world data, the feature sets selected by the GMLVQ approach had a significantly better classification performance compared with feature sets selected by a MI ranking.

  9. Textural feature selection for enhanced detection of stationary humans in through-the-wall radar imagery

    NASA Astrophysics Data System (ADS)

    Chaddad, A.; Ahmad, F.; Amin, M. G.; Sevigny, P.; DiFilippo, D.

    2014-05-01

    Feature-based methods have been recently considered in the literature for detection of stationary human targets in through-the-wall radar imagery. Specifically, textural features, such as contrast, correlation, energy, entropy, and homogeneity, have been extracted from gray-level co-occurrence matrices (GLCMs) to aid in discriminating the true targets from multipath ghosts and clutter that closely mimic the target in size and intensity. In this paper, we address the task of feature selection to identify the relevant subset of features in the GLCM domain, while discarding those that are either redundant or confusing, thereby improving the performance of feature-based scheme to distinguish between targets and ghosts/clutter. We apply a Decision Tree algorithm to find the optimal combination of co-occurrence based textural features for the problem at hand. We employ a K-Nearest Neighbor classifier to evaluate the performance of the optimal textural feature based scheme in terms of its target and ghost/clutter discrimination capability and use real-data collected with the vehicle-borne multi-channel through-the-wall radar imaging system by Defence Research and Development Canada. For the specific data analyzed, it is shown that the identified dominant features yield a higher classification accuracy, with lower number of false alarms and missed detections, compared to the full GLCM based feature set.

  10. Multi-sourced, 3D geometric characterization of volcanogenic karst features: Integrating lidar, sonar, and geophysical datasets (Invited)

    NASA Astrophysics Data System (ADS)

    Sharp, J. M.; Gary, M. O.; Reyes, R.; Halihan, T.; Fairfield, N.; Stone, W. C.

    2009-12-01

    Karstic aquifers can form very complex hydrogeological systems and 3-D mapping has been difficult, but Lidar, phased array sonar, and improved earth resistivity techniques show promise in this and in linking metadata to models. Zacatón, perhaps the Earth’s deepest cenote, has a sub-aquatic void space exceeding 7.5 x 106 cubic m3. It is the focus of this study which has created detailed 3D maps of the system. These maps include data from above and beneath the the water table and within the rock matrix to document the extent of the immense karst features and to interpret the geologic processes that formed them. Phase 1 used high resolution (20 mm) Lidar scanning of surficial features of four large cenotes. Scan locations, selected to achieve full feature coverage once registered, were established atop surface benchmarks with UTM coordinates established using GPS and Total Stations. The combined datasets form a geo-registered mesh of surface features down to water level in the cenotes. Phase 2 conducted subsurface imaging using Earth Resistivity Imaging (ERI) geophysics. ERI identified void spaces isolated from open flow conduits. A unique travertine morphology exists in which some cenotes are dry or contain shallow lakes with flat travertine floors; some water-filled cenotes have flat floors without the cone of collapse material; and some have collapse cones. We hypothesize that the floors may have large water-filled voids beneath them. Three separate flat travertine caps were imaged: 1) La Pilita, which is partially open, exposing cap structure over a deep water-filled shaft; 2) Poza Seca, which is dry and vegetated; and 3) Tule, which contains a shallow (<1 m) lake. A fourth line was run adjacent to cenote Verde. La Pilita ERI, verified by SCUBA, documented the existence of large water-filled void zones ERI at Poza Seca showed a thin cap overlying a conductive zone extending to at least 25 m depth beneath the cap with no lower boundary of this zone evident

  11. 3D kinetic picture of magnetotail explosions and characteristic auroral features prior to and after substorm onset

    NASA Astrophysics Data System (ADS)

    Sitnov, M. I.; Merkin, V. G.; Motoba, T.

    2015-12-01

    Recent findings in theory, observations and 3D particle-in-cell simulations of magnetotail explosions reveal a complex picture of reconnection, buoyancy and flapping motions, which have interesting correlations with the auroral morphology. First, the formation of the tailward Bz gradient as a theoretical prerequisite for tearing, ballooning/interchange and flapping instabilities is consistent with the structure of the pre-onset quiet arc and the associated deep minimum of Bz. Another distinctive pre-onset feature, equatorward extension of the auroral oval in the late growth phase, is conventionally associated with earthward motion of the inner edge of the plasma sheet. However, if open magnetic flux saturates in the late growth phase, it may also be treated as a signature of magnetic flux accumulation tailward of the Bz minimum, which is also favorable for the tail plasma sheet instabilities. 3D PIC simulations of similar magnetotail equilibria with a tailward Bz gradient show spontaneous formation of earthward flows led by dipolarization fronts. They are structured in the dawn-dusk direction on the ion inertial scale, consistent with the minimum scales of the observed auroral beads. At the same time, simulations show the formation of a new X-line in the wake of the dipolarization front with no significant spatial modulation in the dawn-dusk direction suggesting smooth profiles of the substorm current wedge as well as poleward parts of auroral streamers. Flapping motions, which also grow at the dipolarization front, extend beyond it, up to the new X-line region. To understand auroral manifestations of tail structures in our simulations we investigate the plasma moments at the plasma sheet boundary.

  12. 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. PMID:24289618

  13. Comparison of multiresolution features for texture classification of carotid atherosclerosis from B-mode ultrasound.

    PubMed

    Tsiaparas, Nikolaos N; Golemati, Spyretta; Andreadis, Ioannis; Stoitsis, John S; Valavanis, Ioannis; Nikita, Konstantina S

    2011-01-01

    In this paper, a multiresolution approach is suggested for texture classification of atherosclerotic tissue from B-mode ultrasound. Four decomposition schemes, namely, the discrete wavelet transform, the stationary wavelet transform, wavelet packets (WP), and Gabor transform (GT), as well as several basis functions, were investigated in terms of their ability to discriminate between symptomatic and asymptomatic cases. The mean and standard deviation of the detail subimages produced for each decomposition scheme were used as texture features. Feature selection included 1) ranking the features in terms of their divergence values and 2) appropriately thresholding by a nonlinear correlation coefficient. The selected features were subsequently input into two classifiers using support vector machines (SVM) and probabilistic neural networks. WP analysis and the coiflet 1 produced the highest overall classification performance (90% for diastole and 75% for systole) using SVM. This might reflect WP's ability to reveal differences in different frequency bands, and therefore, characterize efficiently the atheromatous tissue. An interesting finding was that the dominant texture features exhibited horizontal directionality, suggesting that texture analysis may be affected by biomechanical factors (plaque strains).

  14. Medical image retrieval based on texture and shape feature co-occurrence

    NASA Astrophysics Data System (ADS)

    Zhou, Yixiao; Huang, Yan; Ling, Haibin; Peng, Jingliang

    2012-03-01

    With the rapid development and wide application of medical imaging technology, explosive volumes of medical image data are produced every day all over the world. As such, it becomes increasingly challenging to manage and utilize such data effectively and efficiently. In particular, content-based medical image retrieval has been intensively researched in the past decade or so. In this work, we propose a novel approach to content-based medical image retrieval utilizing the co-occurrence of both the texture and the shape features in contrast to most previous algorithms that use purely the texture or the shape feature. Specifically, we propose a novel form of representation for the co-occurrence of the texture and the shape features in an image, i.e., the gray level and edge direction co-occurrence matrix (GLEDCOM). Based on GLEDCOM, we define eleven features forming a feature vector that is used to measure the similarity between images. As a result, it consistently yields outstanding performance on both images rich in texture (e.g., image of brain) and images with dominant smooth regions and sharp edges (e.g., image of bladder). As demonstrated by experiments, the mean precision of retrieval with GLEDCOM algorithm outperforms a set of representative algorithms including the gray level co-occurrence matrix (GLCM) based, the Hu's seven moment invariants (HSMI) based, the uniformity estimation method (UEM) based and the the modified Zernike moments (MZM) based algorithms by 10%-20%.

  15. Comparison of Texture Features Used for Classification of Life Stages of Malaria Parasite

    PubMed Central

    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. PMID:27247560

  16. 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.

  17. 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. PMID:26405887

  18. Texture feature extraction and analysis for polyp differentiation via computed tomography colonography

    PubMed Central

    Hu, Yifan; Song, Bowen; Han, Hao; Pickhardt, Perry J.; Zhu, Wei; Duan, Chaijie; Zhang, Hao; Barish, Matthew A.; Lascarides, Chris E.

    2016-01-01

    Image textures in computed tomography colonography (CTC) have great potential for differentiating non-neoplastic from neoplastic polyps and thus can advance the current CTC detection-only paradigm to a new level toward optimal polyp management to prevent the deadly colorectal cancer. However, image textures are frequently compromised due to noise smoothing and other error-correction operations in most CT image reconstructions. Furthermore, because of polyp orientation variation in patient space, texture features extracted in that space can vary accordingly, resulting in variable results. To address these issues, this study proposes an adaptive approach to extract and analyze the texture features for polyp differentiation. Firstly, derivative operations are performed on the CT intensity image to amplify the textures, e.g. in the 1st order derivative (gradient) and 2nd order derivative (curvature) images, with adequate noise control. Then the Haralick co-occurrence matrix (CM) is used to calculate texture measures along each of the 13 directions (defined by the 1st and 2nd order image voxel neighbors) through the polyp volume in the intensity, gradient and curvature images. Instead of taking the mean and range of each CM measure over the 13 directions as the so-called Haralick texture features, the Karhunen-Loeve transform is performed to map the 13 directions into an orthogonal coordinate system where all the CM measures are projected onto the new coordinates so that the resulted texture features are less dependent on the polyp spatial orientation variation. While the ideas for amplifying textures and stabilizing spatial variation are simple, their impacts are significant for the task of differentiating non-neoplastic from neoplastic polyps as demonstrated by experiments using 384 polyp datasets, of which 52 are non-neoplastic polyps and the rest are neoplastic polyps. By the merit of area under the curve of receiver operating characteristic, the innovative ideas

  19. Robust textural features for real time face recognition

    NASA Astrophysics Data System (ADS)

    Cui, Chen; Asari, Vijayan K.; Braun, Andrew D.

    2015-03-01

    Automatic face recognition in real life environment is challenged by various issues such as the object motion, lighting conditions, poses and expressions. In this paper, we present the development of a system based on a refined Enhanced Local Binary Pattern (ELBP) feature set and a Support Vector Machine (SVM) classifier to perform face recognition in a real life environment. Instead of counting the number of 1's in ELBP, we use the 8-bit code of the thresholded data as per the ELBP rule, and then binarize the image with a predefined threshold value, removing the small connections on the binarized image. The proposed system is currently trained with several people's face images obtained from video sequences captured by a surveillance camera. One test set contains the disjoint images of the trained people's faces to test the accuracy and the second test set contains the images of non-trained people's faces to test the percentage of the false positives. The recognition rate among 570 images of 9 trained faces is around 94%, and the false positive rate with 2600 images of 34 non-trained faces is around 1%. Research work is progressing for the recognition of partially occluded faces as well. An appropriate weighting strategy will be applied to the different parts of the face area to achieve a better performance.

  20. Morphological and texture features for cancer tissues microscopic images

    NASA Astrophysics Data System (ADS)

    Marghani, Khaled A.; Dlay, Satnam S.; Sharif, Bayan S.; Sims, Andrew J.

    2003-05-01

    Accurate and reliable decision making in cancer prognosis can help in the planning of appropriate surgery and therapy and, in general, optimize patient management through the different stages of the disease. In this paper, we present a novel fractal geometry algorithm as a potential method for classifying colorectal histopathological images. 102 microscopic samples of colon tissue were examined in order to identify abnormalities using a morphogical feature approach based on segmenting the image into different classes, derived from fractal dimension. The obtained mean fractal dimension (FD) for normal object tissue was 1.797+/- 0.0381 (n = 44) compared with 1.866+/-0.0262 for malignant samples (n = 58). In brief, this study was able to demonstrate the value of fractal dimension based on morphological approach in the analysis of microscopic colon cancer images. Although, the obtained results are strongly significant in the separation between normal and malignant colorectal images, further analyses are essential to incorporate this methodology into routine clinical practice by supporting pathologist decision.

  1. 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)

    SciTech Connect

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

    2014-06-15

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

  2. A Statistical-Textural-Features Based Approach for Classification of Solid Drugs Using Surface Microscopic Images

    PubMed Central

    2014-01-01

    The quality of pharmaceutical products plays an important role in pharmaceutical industry as well as in our lives. Usage of defective tablets can be harmful for patients. In this research we proposed a nondestructive method to identify defective and nondefective tablets using their surface morphology. Three different environmental factors temperature, humidity and moisture are analyzed to evaluate the performance of the proposed method. Multiple textural features are extracted from the surface of the defective and nondefective tablets. These textural features are gray level cooccurrence matrix, run length matrix, histogram, autoregressive model and HAAR wavelet. Total textural features extracted from images are 281. We performed an analysis on all those 281, top 15, and top 2 features. Top 15 features are extracted using three different feature reduction techniques: chi-square, gain ratio and relief-F. In this research we have used three different classifiers: support vector machine, K-nearest neighbors and naïve Bayes to calculate the accuracies against proposed method using two experiments, that is, leave-one-out cross-validation technique and train test models. We tested each classifier against all selected features and then performed the comparison of their results. The experimental work resulted in that in most of the cases SVM performed better than the other two classifiers. PMID:25371702

  3. 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.

  4. Atlas and feature based 3D pathway visualization enhancement for skull base pre-operative fast planning from head CT

    NASA Astrophysics Data System (ADS)

    Aghdasi, Nava; Li, Yangming; Berens, Angelique; Moe, Kris S.; Bly, Randall A.; Hannaford, Blake

    2015-03-01

    Minimally invasive neuroendoscopic surgery provides an alternative to open craniotomy for many skull base lesions. These techniques provides a great benefit to the patient through shorter ICU stays, decreased post-operative pain and quicker return to baseline function. However, density of critical neurovascular structures at the skull base makes planning for these procedures highly complex. Furthermore, additional surgical portals are often used to improve visualization and instrument access, which adds to the complexity of pre-operative planning. Surgical approach planning is currently limited and typically involves review of 2D axial, coronal, and sagittal CT and MRI images. In addition, skull base surgeons manually change the visualization effect to review all possible approaches to the target lesion and achieve an optimal surgical plan. This cumbersome process relies heavily on surgeon experience and it does not allow for 3D visualization. In this paper, we describe a rapid pre-operative planning system for skull base surgery using the following two novel concepts: importance-based highlight and mobile portal. With this innovation, critical areas in the 3D CT model are highlighted based on segmentation results. Mobile portals allow surgeons to review multiple potential entry portals in real-time with improved visualization of critical structures located inside the pathway. To achieve this we used the following methods: (1) novel bone-only atlases were manually generated, (2) orbits and the center of the skull serve as features to quickly pre-align the patient's scan with the atlas, (3) deformable registration technique was used for fine alignment, (4) surgical importance was assigned to each voxel according to a surgical dictionary, and (5) pre-defined transfer function was applied to the processed data to highlight important structures. The proposed idea was fully implemented as independent planning software and additional

  5. Blurred face recognition by fusing blur-invariant texture and structure features

    NASA Astrophysics Data System (ADS)

    Zhu, Mengyu; Cao, Zhiguo; Xiao, Yang; Xie, Xiaokang

    2015-10-01

    Blurred face recognition is still remaining as a challenge task, but with wide applications. Image blur can largely affect recognition performance. The local phase quantization (LPQ) was proposed to extract the blur-invariant texture information. It was used for blurred face recognition and achieved good performance. However, LPQ considers only the phase blur-invariant texture information, which is not sufficient. In addition, LPQ is extracted holistically, which cannot fully explore its discriminative power on local spatial properties. In this paper, we propose a novel method for blurred face recognition. The texture and structure blur-invariant features are extracted and fused to generate a more complete description on blurred image. For texture blur-invariant feature, LPQ is extracted in a densely sampled way and vector of locally aggregated descriptors (VLAD) is employed to enhance its performance. For structure blur-invariant feature, the histogram of oriented gradient (HOG) is used. To further enhance its blur invariance, we improve HOG by eliminating weak gradient magnitude which is more sensitive to image blur than the strong gradient. The improved HOG is then fused with the original HOG by canonical correlation analysis (CCA). At last, we fuse them together by CCA to form the final blur-invariant representation of the face image. The experiments are performed on three face datasets. The results demonstrate that our improvements and our proposition can have a good performance in blurred face recognition.

  6. Retrieval Using Texture Features in High Resolution Multi-spectral Satellite Imagery

    SciTech Connect

    Newsam, S D; Kamath, C

    2004-01-22

    Texture features have long been used in remote sensing applications to represent and retrieve image regions similar to a query region. Various representations of texture have been proposed based on the Fourier power spectrum, spatial co-occurrence, wavelets, Gabor filters, etc. These representations vary in their computational complexity and their suitability for representing different region types. Much of the work done thus far has focused on panchromatic imagery at low to moderate spatial resolutions, such as images from Landsat 1-7 which have a resolution of 15-30 m/pixel, and from SPOT 1-5 which have a resolution of 2.5-20 m/pixel. However, it is not clear which texture representation works best for the new classes of high resolution panchromatic (60-100 cm/pixel) and multi-spectral (4 bands for red, green, blue, and near infra-red at 2.4-4 m/pixel) imagery. It is also not clear how the different spectral bands should be combined. In this paper, we investigate the retrieval performance of several different texture representations using multi-spectral satellite images from IKONOS. A query-by-example framework, along with a manually chosen ground truth dataset, allows different combinations of texture representations and spectral bands to be compared. We focus on the specific problem of retrieving inhabited regions from images of urban and rural scenes. Preliminary results show that (1) the use of all spectral bands improves the retrieval performance, and (2) co-occurrence, wavelet and Gabor texture features perform comparably.

  7. Changes on image texture features of breakfast flakes cereals during water absorption.

    PubMed

    Medina, Wenceslao T; Quevedo, Roberto A; Aguilera, José M

    2013-02-01

    Normally breakfast cereal flakes are consumed by pouring them into a bowl and covering them with fresh or cold milk. During this process the liquid uptake causes changes in the surface and internal matrix of breakfast cereals that influence texture and integrity. Some breakfast cereal as flakes have a translucent structure that could provide information about the solid matrix and air cells and how they change during liquid absorption. The objective of the study was to assess the image texture changes of corn flakes and frosted flakes during water absorption at 5, 15 and 25 °C, employing 11 image feature textures extracted from grey-level co-occurrence matrix and grey-level run length matrix (at three directions) and to relate the fractal dimension (FD) of images with rupture force (RF) reduction during soaking of both flakes at 5 °C. The most relevant result from principal component analysis calculated with a matrix of 54 (soaking times) × 22 (texture features), shows that it was possible to distinguish an isolated group consisting of different soaking times at the same water temperature in each breakfast cereal flakes evaluated, corroborating that superficial liquid imbibition is important during the liquid absorption process when flakes are soaked. Furthermore, standardized FD could be related to RF in the period when samples tend to search for an equilibrium state.

  8. Changes on image texture features of breakfast flakes cereals during water absorption.

    PubMed

    Medina, Wenceslao T; Quevedo, Roberto A; Aguilera, José M

    2013-02-01

    Normally breakfast cereal flakes are consumed by pouring them into a bowl and covering them with fresh or cold milk. During this process the liquid uptake causes changes in the surface and internal matrix of breakfast cereals that influence texture and integrity. Some breakfast cereal as flakes have a translucent structure that could provide information about the solid matrix and air cells and how they change during liquid absorption. The objective of the study was to assess the image texture changes of corn flakes and frosted flakes during water absorption at 5, 15 and 25 °C, employing 11 image feature textures extracted from grey-level co-occurrence matrix and grey-level run length matrix (at three directions) and to relate the fractal dimension (FD) of images with rupture force (RF) reduction during soaking of both flakes at 5 °C. The most relevant result from principal component analysis calculated with a matrix of 54 (soaking times) × 22 (texture features), shows that it was possible to distinguish an isolated group consisting of different soaking times at the same water temperature in each breakfast cereal flakes evaluated, corroborating that superficial liquid imbibition is important during the liquid absorption process when flakes are soaked. Furthermore, standardized FD could be related to RF in the period when samples tend to search for an equilibrium state. PMID:23345324

  9. Local rigid registration for multimodal texture feature extraction from medical images

    NASA Astrophysics Data System (ADS)

    Steger, Sebastian

    2011-03-01

    The joint extraction of texture features from medical images of different modalities requires an accurate image registration at the target structures. In many cases rigid registration of the entire images does not achieve the desired accuracy whereas deformable registration is too complex and may result in undesired deformations. This paper presents a novel region of interest alignment approach based on local rigid registration enabling image fusion for multimodal texture feature extraction. First rigid registration on the entire images is performed to obtain an initial guess. Then small cubic regions around the target structure are clipped from all images and individually rigidly registered. The approach was applied to extract texture features in clinically acquired CT and MR images from lymph nodes in the oropharynx for an oral cancer reoccurrence prediction framework. Visual inspection showed that in all of the 30 cases at least a subtle misalignment was perceivable for the globally rigidly aligned images. After applying the presented approach the alignment of the target structure significantly improved in 19 cases. In 12 cases no alignment mismatch whatsoever was perceptible without requiring the complexity of deformable registration and without deforming the target structure. Further investigation showed that if the resolutions of the individual modalities differ significantly, partial volume effects occur, diminishing the significance of the multimodal features even for perfectly aligned images.

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

    PubMed Central

    2013-01-01

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

  11. 3D face analysis for demographic biometrics

    SciTech Connect

    Tokola, Ryan A; Mikkilineni, Aravind K; Boehnen, Chris Bensing

    2015-01-01

    Despite being increasingly easy to acquire, 3D data is rarely used for face-based biometrics applications beyond identification. Recent work in image-based demographic biometrics has enjoyed much success, but these approaches suffer from the well-known limitations of 2D representations, particularly variations in illumination, texture, and pose, as well as a fundamental inability to describe 3D shape. This paper shows that simple 3D shape features in a face-based coordinate system are capable of representing many biometric attributes without problem-specific models or specialized domain knowledge. The same feature vector achieves impressive results for problems as diverse as age estimation, gender classification, and race classification.

  12. Spectrum and Image Texture Features Analysis for Early Blight Disease Detection on Eggplant Leaves.

    PubMed

    Xie, Chuanqi; He, Yong

    2016-01-01

    This study investigated both spectrum and texture features for detecting early blight disease on eggplant leaves. Hyperspectral images for healthy and diseased samples were acquired covering the wavelengths from 380 to 1023 nm. Four gray images were identified according to the effective wavelengths (408, 535, 624 and 703 nm). Hyperspectral images were then converted into RGB, HSV and HLS images. Finally, eight texture features (mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment and correlation) based on gray level co-occurrence matrix (GLCM) were extracted from gray images, RGB, HSV and HLS images, respectively. The dependent variables for healthy and diseased samples were set as 0 and 1. K-Nearest Neighbor (KNN) and AdaBoost classification models were established for detecting healthy and infected samples. All models obtained good results with the classification rates (CRs) over 88.46% in the testing sets. The results demonstrated that spectrum and texture features were effective for early blight disease detection on eggplant leaves. PMID:27187387

  13. Spectrum and Image Texture Features Analysis for Early Blight Disease Detection on Eggplant Leaves

    PubMed Central

    Xie, Chuanqi; He, Yong

    2016-01-01

    This study investigated both spectrum and texture features for detecting early blight disease on eggplant leaves. Hyperspectral images for healthy and diseased samples were acquired covering the wavelengths from 380 to 1023 nm. Four gray images were identified according to the effective wavelengths (408, 535, 624 and 703 nm). Hyperspectral images were then converted into RGB, HSV and HLS images. Finally, eight texture features (mean, variance, homogeneity, contrast, dissimilarity, entropy, second moment and correlation) based on gray level co-occurrence matrix (GLCM) were extracted from gray images, RGB, HSV and HLS images, respectively. The dependent variables for healthy and diseased samples were set as 0 and 1. K-Nearest Neighbor (KNN) and AdaBoost classification models were established for detecting healthy and infected samples. All models obtained good results with the classification rates (CRs) over 88.46% in the testing sets. The results demonstrated that spectrum and texture features were effective for early blight disease detection on eggplant leaves. PMID:27187387

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

    NASA Astrophysics Data System (ADS)

    Cui, Chen; Asari, Vijayan K.

    2014-03-01

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

  15. Incorporating texture features in a computer-aided breast lesion diagnosis system for automated three-dimensional breast ultrasound

    PubMed Central

    Liu, Haixia; Tan, Tao; van Zelst, Jan; Mann, Ritse; Karssemeijer, Nico; Platel, Bram

    2014-01-01

    Abstract. We investigated the benefits of incorporating texture features into an existing computer-aided diagnosis (CAD) system for classifying benign and malignant lesions in automated three-dimensional breast ultrasound images. The existing system takes into account 11 different features, describing different lesion properties; however, it does not include texture features. In this work, we expand the system by including texture features based on local binary patterns, gray level co-occurrence matrices, and Gabor filters computed from each lesion to be diagnosed. To deal with the resulting large number of features, we proposed a combination of feature-oriented classifiers combining each group of texture features into a single likelihood, resulting in three additional features used for the final classification. The classification was performed using support vector machine classifiers, and the evaluation was done with 10-fold cross validation on a dataset containing 424 lesions (239 benign and 185 malignant lesions). We compared the classification performance of the CAD system with and without texture features. The area under the receiver operating characteristic curve increased from 0.90 to 0.91 after adding texture features (p<0.001). PMID:26158036

  16. Synthesis and characterization of magnetic solids featuring 3d-4f heterometallic oxides comprised of spin chains and 3d-6p noncentrosymmetric oxides templated by acentric salt units

    NASA Astrophysics Data System (ADS)

    West, Jennings Palmer

    solvent media is the fact that the salt itself or the alkali/alkaline-earth oxides formed in situ can be incorporated in phase formations. Both of the aforementioned cases, if incorporated, lead to an additional and different type of nonmagnetic spacer for the formation of low-dimensional 3d-4 f extended solids. It is believed that these nonmagnetic, ionic spacers are more disruptive to magnetic super-super-exchange in comparison to the nonmagnetic oxyanionic spacers, and should assist further in achieving truly confined magnetic sublattices. In the studies presented, the overall highlight considering structure and property correlations will be most exemplified through the comparison of two different pseudo-one-dimensional (1D), 3d-4 f arsenate systems (Chapters 3 and 4) where it is observed that further spacing of the 3d-4f sublattices leads to interesting low-dimensional magnetic behavior. In addition, an extension of one of these pseudo-1D, 3d-4f systems (Chapter 5) will highlight the intriguing properties resulting from the study of a family of compounds whereby a double aliovalent substitution has been performed with respect to the parent family. This particular system features a solid solution series where charge disorder exists, and in terms of magnetic properties, there are unique variations in comparison to the parent family. And finally, in relation to heterometallic system types, a new noncentrosymmetric phosphate family containing mixed 3d-6p (where 3 d = Mn, Fe; 6p = Bi3+) will be discussed (Chapter 6). As will be mentioned, new 3d-6p systems were explored originally for host materials where lanthanides could be substituted. Independent of lanthanide substitutions that are yet to be proven, the combination of both bulk acentricity and magnetically active ions makes systems of this type worthy of study due to multiferroic potentials aimed toward the coupling of polarization and magnetization.

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  18. Textural feature based target detection in through-the-wall radar imagery

    NASA Astrophysics Data System (ADS)

    Sengur, A.; Amin, M.; Ahmad, F.; Sévigny, P.; DiFilippo, D.

    2013-05-01

    Stationary target detection in through-the-wall radar imaging (TWRI) using image segmentation techniques has recently been considered in the literature. Specifically, histogram thresholding methods have been used to aid in removing the clutter, resulting in `clean' radar images with target regions only. In this paper, we show that histogram thresholding schemes are effective only against clutter regions, which are distinct from target regions. Target detection using these methods becomes challenging, if not impossible, in the presence of multipath ghosts and clutter that closely mimics the target in size and intensity. Because of the small variations between the target regions and such clutter and multipath ghosts, we propose a textural feature based classifier for through-the-wall target detection. The feature based scheme is applied as a follow-on step after application of histogram thresholding techniques. The training set consists of feature vectors based on gray level co-occurrence matrices corresponding to the target and ghost/clutter image regions. Feature vectors are then used in training a minimum distance classifier based on Mahalanobis distance metric. Performance of the proposed scheme is evaluated using real-data collected with Defence Research and Development Canada's vehicle-borne TWRI system. The results show that the proposed textural feature based method yields much improved results compared to histogram thresholding based segmentation methods for the considered cases.

  19. Novel Methods for Separation of Gangue from Limestone and Coal using Multispectral and Joint Color-Texture Features

    NASA Astrophysics Data System (ADS)

    Tripathy, Debi Prasad; Guru Raghavendra Reddy, K.

    2016-02-01

    Ore sorting is a useful tool to remove gangue material from the ore and increase the quality of the ore. The vast developments in the area of artificial intelligence allow fast processing of full-color digital images for the preferred investigations. The associated gangue minerals from limestone and coal mines were identified using three different approaches. All the methods were based on extensions of the co-occurrence matrix method. In the first method, the color features were extracted from RGB color planes and texture features were extracted using a multispectral extension, in which co-occurrence matrices were computed both between and within the color bands. The second method used joint color-texture features where color features were added to gray scale texture features. The last method used gray scale texture features computed on a quantized color image. Results showed that the accuracy for separation of gangue from limestone, a joint color-texture method was 98 % and for separation of gangue from coal, multispectral method with correlation and joint color-texture method were 100 % respectively. Combined multispectral and joint color-texture methods gave good accuracy with 64 gray levels quantization for separation of gangue from limestone and coal.

  20. Using multiscale texture and density features for near-term breast cancer risk analysis

    PubMed Central

    Sun, Wenqing; Tseng, Tzu-Liang (Bill); Qian, Wei; Zhang, Jianying; Saltzstein, Edward C.; Zheng, Bin; Lure, Fleming; Yu, Hui; Zhou, Shi

    2015-01-01

    Purpose: To help improve efficacy of screening mammography by eventually establishing a new optimal personalized screening paradigm, the authors investigated the potential of using the quantitative multiscale texture and density feature analysis of digital mammograms to predict near-term breast cancer risk. Methods: The authors’ dataset includes digital mammograms acquired from 340 women. Among them, 141 were positive and 199 were negative/benign cases. The negative digital mammograms acquired from the “prior” screening examinations were used in the study. Based on the intensity value distributions, five subregions at different scales were extracted from each mammogram. Five groups of features, including density and texture features, were developed and calculated on every one of the subregions. Sequential forward floating selection was used to search for the effective combinations. Using the selected features, a support vector machine (SVM) was optimized using a tenfold validation method to predict the risk of each woman having image-detectable cancer in the next sequential mammography screening. The area under the receiver operating characteristic curve (AUC) was used as the performance assessment index. Results: From a total number of 765 features computed from multiscale subregions, an optimal feature set of 12 features was selected. Applying this feature set, a SVM classifier yielded performance of AUC = 0.729 ± 0.021. The positive predictive value was 0.657 (92 of 140) and the negative predictive value was 0.755 (151 of 200). Conclusions: The study results demonstrated a moderately high positive association between risk prediction scores generated by the quantitative multiscale mammographic image feature analysis and the actual risk of a woman having an image-detectable breast cancer in the next subsequent examinations. PMID:26127038

  1. Support vector machine model for diagnosing pneumoconiosis based on wavelet texture features of digital chest radiographs.

    PubMed

    Zhu, Biyun; Chen, Hui; Chen, Budong; Xu, Yan; Zhang, Kuan

    2014-02-01

    This study aims to explore the classification ability of decision trees (DTs) and support vector machines (SVMs) to discriminate between the digital chest radiographs (DRs) of pneumoconiosis patients and control subjects. Twenty-eight wavelet-based energy texture features were calculated at the lung fields on DRs of 85 healthy controls and 40 patients with stage I and stage II pneumoconiosis. DTs with algorithm C5.0 and SVMs with four different kernels were trained by samples with two combinations of the texture features to classify a DR as of a healthy subject or of a patient with pneumoconiosis. All of the models were developed with fivefold cross-validation, and the final performances of each model were compared by the area under receiver operating characteristic (ROC) curve. For both SVM (with a radial basis function kernel) and DT (with algorithm C5.0), areas under ROC curves (AUCs) were 0.94 ± 0.02 and 0.86 ± 0.04 (P = 0.02) when using the full feature set and 0.95 ± 0.02 and 0.88 ± 0.04 (P = 0.05) when using the selected feature set, respectively. When built on the selected texture features, the SVM with a polynomial kernel showed a higher diagnostic performance with an AUC value of 0.97 ± 0.02 than SVMs with a linear kernel, a radial basis function kernel and a sigmoid kernel with AUC values of 0.96 ± 0.02 (P = 0.37), 0.95 ± 0.02 (P = 0.24), and 0.90 ± 0.03 (P = 0.01), respectively. The SVM model with a polynomial kernel built on the selected feature set showed the highest diagnostic performance among all tested models when using either all the wavelet texture features or the selected ones. The model has a good potential in diagnosing pneumoconiosis based on digital chest radiographs.

  2. Quantitative nuclear texture features analysis confirms WHO classification 2004 for lung carcinomas.

    PubMed

    Schmid, Katharina; Angerstein, Nina; Geleff, Silvana; Gschwendtner, Andreas

    2006-03-01

    The purpose of this study was to discriminate the main subsets of lung carcinomas of the WHO classification of 2004 by nuclear chromatin texture feature analysis. Our collective comprised 56 typical and 19 atypical carcinoids, 37 small-cell carcinomas, 15 large-cell neuroendocrine carcinomas, 42 adenocarcinomas, and 26 squamous cell carcinomas. After Feulgen staining, cell nuclei were automatically measured using a high-resolution image analyser (CytoSavant Oncometrics, Vancouver, BC, Canada). Texture features describing the granularity and the compactness of the nuclear chromatin were extracted for calculation of classification rules, which allowed the discrimination of different tumor groups. By applying the classification rule that described the granularity of the nuclear chromatin (defined by four different parameters) small-cell and non-small-cell lung carcinoma could correctly be discriminated in 93%. No significant discrimination was possible between the different subtypes of large-cell carcinomas, including large-cell neuroendocrine carcinoma. When using compactness of chromatin (defined by four texture parameters) as a means of discrimination, carcinoids and non-small-cell lung carcinomas were correctly distinguished in 92%. No significant discrimination between neuroendocrine tumors was achieved though. Our findings are in accordance with the new WHO classification of 2004: neuroendocrine tumors of the lung are now classified according only to their mitotic counts and presence of necrosis but not by their morphology; their discrimination by the means of nuclear image analysis is not sufficient and therefore not appropriate any longer. PMID:16462732

  3. 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.

  4. 3D World Building System

    ScienceCinema

    None

    2016-07-12

    This video provides an overview of the Sandia National Laboratories developed 3-D World Model Building capability that provides users with an immersive, texture rich 3-D model of their environment in minutes using a laptop and color and depth camera.

  5. 3D World Building System

    SciTech Connect

    2013-10-30

    This video provides an overview of the Sandia National Laboratories developed 3-D World Model Building capability that provides users with an immersive, texture rich 3-D model of their environment in minutes using a laptop and color and depth camera.

  6. Softness perceptive texture method

    NASA Astrophysics Data System (ADS)

    Kobayashi, Yuichi; Suzuki, Masami; Ohya, Jun

    2004-06-01

    We have been studying about people's visual impression and image features for texture images in order to clarify the human subjective interpretation mechanism for images[1]. In corresponding image features of human impressions for the images, we found that the impressions for material were bottle-necked. We have studied a new analysis method which gives the impression for material from texture images. Especially, we mainly focused on the properties of visual targets which people can feel tactile sense. In this paper, we propose a new texture analysis method which is based on frequency analysis with 3D texture which is designed for photorealistic rendering. We found that our new method can estimate not only the surface roughness but also the surface softness.

  7. Classification of pulmonary nodules in lung CT images using shape and texture features

    NASA Astrophysics Data System (ADS)

    Dhara, Ashis Kumar; Mukhopadhyay, Sudipta; Dutta, Anirvan; Garg, Mandeep; Khandelwal, Niranjan; Kumar, Prafulla

    2016-03-01

    Differentiation of malignant and benign pulmonary nodules is important for prognosis of lung cancer. In this paper, benign and malignant nodules are classified using support vector machine. Several shape-based and texture-based features are used to represent the pulmonary nodules in the feature space. A semi-automated technique is used for nodule segmentation. Relevant features are selected for efficient representation of nodules in the feature space. The proposed scheme and the competing technique are evaluated on a data set of 542 nodules of Lung Image Database Consortium and Image Database Resource Initiative. The nodules with composite rank of malignancy "1","2" are considered as benign and "4","5" are considered as malignant. Area under the receiver operating characteristics curve is 0:9465 for the proposed method. The proposed method outperforms the competing technique.

  8. Development of a Novel 3D Culture System for Screening Features of a Complex Implantable Device for CNS Repair

    PubMed Central

    2013-01-01

    Tubular scaffolds which incorporate a variety of micro- and nanotopographies have a wide application potential in tissue engineering especially for the repair of spinal cord injury (SCI). We aim to produce metabolically active differentiated tissues within such tubes, as it is crucially important to evaluate the biological performance of the three-dimensional (3D) scaffold and optimize the bioprocesses for tissue culture. Because of the complex 3D configuration and the presence of various topographies, it is rarely possible to observe and analyze cells within such scaffolds in situ. Thus, we aim to develop scaled down mini-chambers as simplified in vitro simulation systems, to bridge the gap between two-dimensional (2D) cell cultures on structured substrates and three-dimensional (3D) tissue culture. The mini-chambers were manipulated to systematically simulate and evaluate the influences of gravity, topography, fluid flow, and scaffold dimension on three exemplary cell models that play a role in CNS repair (i.e., cortical astrocytes, fibroblasts, and myelinating cultures) within a tubular scaffold created by rolling up a microstructured membrane. Since we use CNS myelinating cultures, we can confirm that the scaffold does not affect neural cell differentiation. It was found that heterogeneous cell distribution within the tubular constructs was caused by a combination of gravity, fluid flow, topography, and scaffold configuration, while cell survival was influenced by scaffold length, porosity, and thickness. This research demonstrates that the mini-chambers represent a viable, novel, scale down approach for the evaluation of complex 3D scaffolds as well as providing a microbioprocessing strategy for tissue engineering and the potential repair of SCI. PMID:24279373

  9. 3D non-rigid registration using surface and local salient features for transrectal ultrasound image-guided prostate biopsy

    NASA Astrophysics Data System (ADS)

    Yang, Xiaofeng; Akbari, Hamed; Halig, Luma; Fei, Baowei

    2011-03-01

    We present a 3D non-rigid registration algorithm for the potential use in combining PET/CT and transrectal ultrasound (TRUS) images for targeted prostate biopsy. Our registration is a hybrid approach that simultaneously optimizes the similarities from point-based registration and volume matching methods. The 3D registration is obtained by minimizing the distances of corresponding points at the surface and within the prostate and by maximizing the overlap ratio of the bladder neck on both images. The hybrid approach not only capture deformation at the prostate surface and internal landmarks but also the deformation at the bladder neck regions. The registration uses a soft assignment and deterministic annealing process. The correspondences are iteratively established in a fuzzy-to-deterministic approach. B-splines are used to generate a smooth non-rigid spatial transformation. In this study, we tested our registration with pre- and postbiopsy TRUS images of the same patients. Registration accuracy is evaluated using manual defined anatomic landmarks, i.e. calcification. The root-mean-squared (RMS) of the difference image between the reference and floating images was decreased by 62.6+/-9.1% after registration. The mean target registration error (TRE) was 0.88+/-0.16 mm, i.e. less than 3 voxels with a voxel size of 0.38×0.38×0.38 mm3 for all five patients. The experimental results demonstrate the robustness and accuracy of the 3D non-rigid registration algorithm.

  10. Global Calibration Method of a Camera Using the Constraint of Line Features and 3D World Points

    NASA Astrophysics Data System (ADS)

    Xu, Guan; Zhang, Xinyuan; Li, Xiaotao; Su, Jian; Hao, Zhaobing

    2016-08-01

    We present a reliable calibration method using the constraint of 2D projective lines and 3D world points to elaborate the accuracy of the camera calibration. Based on the relationship between the 3D points and the projective plane, the constraint equations of the transformation matrix are generated from the 3D points and 2D projective lines. The transformation matrix is solved by the singular value decomposition. The proposed method is compared with the point-based calibration to verify the measurement validity. The mean values of the root-mean-square errors using the proposed method are 7.69×10-4, 6.98×10-4, 2.29×10-4, and 1.09×10-3 while the ones of the original method are 8.10×10-4, 1.29×10-2, 2.58×10-2, and 8.12×10-3. Moreover, the average logarithmic errors of the calibration method are evaluated and compared with the former method in different Gaussian noises and projective lines. The variances of the average errors using the proposed method are 1.70×10-5, 1.39×10-4, 1.13×10-4, and 4.06×10-4, which indicates the stability and accuracy of the method.

  11. Combining multispectral images and selected textural features from high-resolution images to improve discrimination of forest canopies

    NASA Astrophysics Data System (ADS)

    Ruiz, Luis A.; Inan, Igor; Baridon, Juan E.; Lanfranco, Jorge W.

    1998-12-01

    Discrimination of vegetation canopies for production of forestry and land use thematic cartography from multispectral satellite images requires high spectral and spatial resolutions, usually not available in this type of images. A methodology is proposed to improve a vegetation oriented classification from a Landsat TM image by adding texture information obtained from panchromatic aerial photographs. Multispectral classification was used to create a mask of the forested areas that was applied over the aerial mosaic composition. Further vegetation classes were defined based on textural differences, and eight texture features derived from the gray level co-occurrence matrix, three textural energy indicators and a factor of edgeness were tested. A selection of optimal features and textural parameters such as number of gray levels, window size and distance between pixels was performed using principal components and stepwise discriminant analysis techniques with a set of representative samples from each class. After a texture segmentation of panchromatic aerial imagery using optimal parameters and features was completed, a post-classification process based on morphological operations was applied to avoid the neighboring effect generated by the texture analysis. Overall accuracy in the identification of texture classes using the four best feathers was 86.6%, while the 88% of accuracy was achieved in the classification of the complete image. This method is useful for discrimination of certain vegetation classes with low spectral separability and arranged in small forest units, increasing the classification detail in those areas of particular interest.

  12. Staging of cervical cancer based on tumor heterogeneity characterized by texture features on 18F-FDG PET images

    NASA Astrophysics Data System (ADS)

    Mu, Wei; Chen, Zhe; Liang, Ying; Shen, Wei; Yang, Feng; Dai, Ruwei; Wu, Ning; Tian, Jie

    2015-07-01

    The aim of the study is to assess the staging value of the tumor heterogeneity characterized by texture features and other commonly used semi-quantitative indices extracted from 18F-FDG PET images of cervical cancer (CC) patients. Forty-two patients suffering CC at different stages were enrolled in this study. Firstly, we proposed a new tumor segmentation method by combining the intensity and gradient field information in a level set framework. Secondly, fifty-four 3D texture features were studied besides of SUVs (SUVmax, SUVmean, SUVpeak) and metabolic tumor volume (MTV). Through correlation analysis, receiver-operating-characteristic (ROC) curves analysis, some independent indices showed statistically significant differences between the early stage (ES, stages I and II) and the advanced stage (AS, stages III and IV). Then the tumors represented by those independent indices could be automatically classified into ES and AS, and the most discriminative feature could be chosen. Finally, the robustness of the optimal index with respect to sampling schemes and the quality of the PET images were validated. Using the proposed segmentation method, the dice similarity coefficient and Hausdorff distance were 91.78   ±   1.66% and 7.94   ±   1.99 mm, respectively. According to the correlation analysis, all the fifty-eight indices could be divided into 20 groups. Six independent indices were selected for their highest areas under the ROC curves (AUROC), and showed significant differences between ES and AS (P  <  0.05). Through automatic classification with the support vector machine (SVM) Classifier, run percentage (RP) was the most discriminative index with the higher accuracy (88.10%) and larger AUROC (0.88). The Pearson correlation of RP under different sampling schemes is 0.9991   ±   0.0011. RP is a highly stable feature and well correlated with tumor stage in CC, which suggests it could differentiate ES and AS with high

  13. Shape and texture based novel features for automated juxtapleural nodule detection in lung CTs.

    PubMed

    Taşcı, Erdal; Uğur, Aybars

    2015-05-01

    Lung cancer is one of the types of cancer with highest mortality rate in the world. In case of early detection and diagnosis, the survival rate of patients significantly increases. In this study, a novel method and system that provides automatic detection of juxtapleural nodule pattern have been developed from cross-sectional images of lung CT (Computerized Tomography). Shape-based and both shape and texture based 7 features are contributed to the literature for lung nodules. System that we developed consists of six main stages called preprocessing, lung segmentation, detection of nodule candidate regions, feature extraction, feature selection (with five feature ranking criteria) and classification. LIDC dataset containing cross-sectional images of lung CT has been utilized, 1410 nodule candidate regions and 40 features have been extracted from 138 cross-sectional images for 24 patients. Experimental results for 10 classifiers are obtained and presented. Adding our derived features to known 33 features has increased nodule recognition performance from 0.9639 to 0.9679 AUC value on generalized linear model regression (GLMR) for 22 selected features and being reached one of the most successful results in the literature. PMID:25732079

  14. Segmentation of anatomical branching structures based on texture features and conditional random field

    NASA Astrophysics Data System (ADS)

    Nuzhnaya, Tatyana; Bakic, Predrag; Kontos, Despina; Megalooikonomou, Vasileios; Ling, Haibin

    2012-02-01

    This work is a part of our ongoing study aimed at understanding a relation between the topology of anatomical branching structures with the underlying image texture. Morphological variability of the breast ductal network is associated with subsequent development of abnormalities in patients with nipple discharge such as papilloma, breast cancer and atypia. In this work, we investigate complex dependence among ductal components to perform segmentation, the first step for analyzing topology of ductal lobes. Our automated framework is based on incorporating a conditional random field with texture descriptors of skewness, coarseness, contrast, energy and fractal dimension. These features are selected to capture the architectural variability of the enhanced ducts by encoding spatial variations between pixel patches in galactographic image. The segmentation algorithm was applied to a dataset of 20 x-ray galactograms obtained at the Hospital of the University of Pennsylvania. We compared the performance of the proposed approach with fully and semi automated segmentation algorithms based on neural network classification, fuzzy-connectedness, vesselness filter and graph cuts. Global consistency error and confusion matrix analysis were used as accuracy measurements. For the proposed approach, the true positive rate was higher and the false negative rate was significantly lower compared to other fully automated methods. This indicates that segmentation based on CRF incorporated with texture descriptors has potential to efficiently support the analysis of complex topology of the ducts and aid in development of realistic breast anatomy phantoms.

  15. 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.

  16. Entropy-based adaptive nuclear texture features are independent prognostic markers in a total population of uterine sarcomas.

    PubMed

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

    2015-04-01

    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.

  17. 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. PMID:24200578

  18. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  20. A synergistic approach to the design, fabrication and evaluation of 3D printed micro and nano featured scaffolds for vascularized bone tissue repair

    NASA Astrophysics Data System (ADS)

    Holmes, Benjamin; Bulusu, Kartik; Plesniak, Michael; Zhang, Lijie Grace

    2016-02-01

    3D bioprinting has begun to show great promise in advancing the development of functional tissue/organ replacements. However, to realize the true potential of 3D bioprinted tissues for clinical use requires the fabrication of an interconnected and effective vascular network. Solving this challenge is critical, as human tissue relies on an adequate network of blood vessels to transport oxygen, nutrients, other chemicals, biological factors and waste, in and out of the tissue. Here, we have successfully designed and printed a series of novel 3D bone scaffolds with both bone formation supporting structures and highly interconnected 3D microvascular mimicking channels, for efficient and enhanced osteogenic bone regeneration as well as vascular cell growth. Using a chemical functionalization process, we have conjugated our samples with nano hydroxyapatite (nHA), for the creation of novel micro and nano featured devices for vascularized bone growth. We evaluated our scaffolds with mechanical testing, hydrodynamic measurements and in vitro human mesenchymal stem cell (hMSC) adhesion (4 h), proliferation (1, 3 and 5 d) and osteogenic differentiation (1, 2 and 3 weeks). These tests confirmed bone-like physical properties and vascular-like flow profiles, as well as demonstrated enhanced hMSC adhesion, proliferation and osteogenic differentiation. Additional in vitro experiments with human umbilical vein endothelial cells also demonstrated improved vascular cell growth, migration and organization on micro-nano featured scaffolds.

  1. A synergistic approach to the design, fabrication and evaluation of 3D printed micro and nano featured scaffolds for vascularized bone tissue repair

    PubMed Central

    Holmes, Benjamin; Bulusu, Kartik; Plesniak, Michael; Zhang, Lijie Grace

    2016-01-01

    3D bioprinting has begun to show great promise in advancing the development of functional tissue/organ replacements. However, to realize the true potential of 3D bioprinted tissues for clinical use requires the fabrication of an interconnected and effective vascular network. Solving this challenge is critical, as human tissue relies on an adequate network of blood vessels to transport oxygen, nutrients, other chemicals, biological factors and waste, in and out of the tissue. Here, we have successfully designed and printed a series of novel 3D bone scaffolds with both bone formation supporting structures and highly interconnected 3D microvascular mimicking channels, for efficient and enhanced osteogenic bone regeneration as well as vascular cell growth. Using a chemical functionalization process, we have conjugated our samples with nano hydroxyapatite (nHA), for the creation of novel micro and nano featured devices for vascularized bone growth. We evaluated our scaffolds with mechanical testing, hydrodynamic measurements and in vitro human mesenchymal stem cell (hMSC) adhesion (4 h), proliferation (1, 3 and 5 d) and osteogenic differentiation (1, 2 and 3 weeks). These tests confirmed bone-like physical properties and vascular-like flow profiles, as well as demonstrated enhanced hMSC adhesion, proliferation and osteogenic differentiation. Additional in vitro experiments with human umbilical vein endothelial cells also demonstrated improved vascular cell growth, migration and organization on micro-nano featured scaffolds. PMID:26758780

  2. A synergistic approach to the design, fabrication and evaluation of 3D printed micro and nano featured scaffolds for vascularized bone tissue repair.

    PubMed

    Holmes, Benjamin; Bulusu, Kartik; Plesniak, Michael; Zhang, Lijie Grace

    2016-02-12

    3D bioprinting has begun to show great promise in advancing the development of functional tissue/organ replacements. However, to realize the true potential of 3D bioprinted tissues for clinical use requires the fabrication of an interconnected and effective vascular network. Solving this challenge is critical, as human tissue relies on an adequate network of blood vessels to transport oxygen, nutrients, other chemicals, biological factors and waste, in and out of the tissue. Here, we have successfully designed and printed a series of novel 3D bone scaffolds with both bone formation supporting structures and highly interconnected 3D microvascular mimicking channels, for efficient and enhanced osteogenic bone regeneration as well as vascular cell growth. Using a chemical functionalization process, we have conjugated our samples with nano hydroxyapatite (nHA), for the creation of novel micro and nano featured devices for vascularized bone growth. We evaluated our scaffolds with mechanical testing, hydrodynamic measurements and in vitro human mesenchymal stem cell (hMSC) adhesion (4 h), proliferation (1, 3 and 5 d) and osteogenic differentiation (1, 2 and 3 weeks). These tests confirmed bone-like physical properties and vascular-like flow profiles, as well as demonstrated enhanced hMSC adhesion, proliferation and osteogenic differentiation. Additional in vitro experiments with human umbilical vein endothelial cells also demonstrated improved vascular cell growth, migration and organization on micro-nano featured scaffolds.

  3. General fusion approaches for the age determination of latent fingerprint traces: results for 2D and 3D binary pixel feature fusion

    NASA Astrophysics Data System (ADS)

    Merkel, Ronny; Gruhn, Stefan; Dittmann, Jana; Vielhauer, Claus; Bräutigam, Anja

    2012-03-01

    Determining the age of latent fingerprint traces found at crime scenes is an unresolved research issue since decades. Solving this issue could provide criminal investigators with the specific time a fingerprint trace was left on a surface, and therefore would enable them to link potential suspects to the time a crime took place as well as to reconstruct the sequence of events or eliminate irrelevant fingerprints to ensure privacy constraints. Transferring imaging techniques from different application areas, such as 3D image acquisition, surface measurement and chemical analysis to the domain of lifting latent biometric fingerprint traces is an upcoming trend in forensics. Such non-destructive sensor devices might help to solve the challenge of determining the age of a latent fingerprint trace, since it provides the opportunity to create time series and process them using pattern recognition techniques and statistical methods on digitized 2D, 3D and chemical data, rather than classical, contact-based capturing techniques, which alter the fingerprint trace and therefore make continuous scans impossible. In prior work, we have suggested to use a feature called binary pixel, which is a novel approach in the working field of fingerprint age determination. The feature uses a Chromatic White Light (CWL) image sensor to continuously scan a fingerprint trace over time and retrieves a characteristic logarithmic aging tendency for 2D-intensity as well as 3D-topographic images from the sensor. In this paper, we propose to combine such two characteristic aging features with other 2D and 3D features from the domains of surface measurement, microscopy, photography and spectroscopy, to achieve an increase in accuracy and reliability of a potential future age determination scheme. Discussing the feasibility of such variety of sensor devices and possible aging features, we propose a general fusion approach, which might combine promising features to a joint age determination scheme

  4. Towards automated firearm identification based on high resolution 3D data: rotation-invariant features for multiple line-profile-measurement of firing pin shapes

    NASA Astrophysics Data System (ADS)

    Fischer, Robert; Vielhauer, Claus

    2015-03-01

    Understanding and evaluation of potential evidence, as well as evaluation of automated systems for forensic examinations currently play an important role within the domain of digital crime scene analysis. The application of 3D sensing and pattern recognition systems for automatic extraction and comparison of firearm related tool marks is an evolving field of research within this domain. In this context, the design and evaluation of rotation-invariant features for use on topography data play a particular important role. In this work, we propose and evaluate a 3D imaging system along with two novel features based on topography data and multiple profile-measurement-lines for automatic matching of firing pin shapes. Our test set contains 72 cartridges of three manufactures shot by six different 9mm guns. The entire pattern recognition workflow is addressed. This includes the application of confocal microscopy for data acquisition, preprocessing covers outlier handling, data normalization, as well as necessary segmentation and registration. Feature extraction involves the two introduced features for automatic comparison and matching of 3D firing pin shapes. The introduced features are called `Multiple-Circle-Path' (MCP) and `Multiple-Angle-Path' (MAP). Basically both features are compositions of freely configurable amounts of circular or straight path-lines combined with statistical evaluations. During the first part of evaluation (E1), we examine how well it is possible to differentiate between two 9mm weapons of the same mark and model. During second part (E2), we evaluate the discrimination accuracy regarding the set of six different 9mm guns. During the third part (E3), we evaluate the performance of the features in consideration of different rotation angles. In terms of E1, the best correct classification rate is 100% and in terms of E2 the best result is 86%. The preliminary results for E3 indicate robustness of both features regarding rotation. However, in future

  5. Shape-based and texture-based feature extraction for classification of microcalcifications in mammograms

    NASA Astrophysics Data System (ADS)

    Soltanian-Zadeh, Hamid; Pourabdollah-Nezhad, Siamak; Rafiee Rad, Farshid

    2001-07-01

    This paper presents and compares two image processing methods for differentiating benign from malignant microcalcifications in mammograms. The gold standard method for differentiating benign from malignant microcalcifications is biopsy, which is invasive. The goal of the proposed methods is to reduce rate of biopsies with negative results. In the first method, we extract 17 shape features from each mammogram. These features are related to shapes of individual microcalcifications or to their clusters. In the second method, we extract 44 texture features from each mammogram using co-occurrence method of Haralick. Next, we select best features from each set using a genetic algorithm, to maximize area under ROC curve. This curve is created using a k-nearest neighbor (kNN) classifier and a malignancy criterion. Finally, we evaluate the methods by comparing ROC's with greatest areas obtained using each method. We applied the proposed methods, with different values of k in kNN classifier, to 74 malignant and 29 benign microcalcification clusters. Truth for each mammogram was established based on the biopsy results. We found greatest area under ROC curve for each set of features used in each method. For shape features this area was 0.82 (k = 7) and for Haralick features it was 0.72(k=9).

  6. Tracking naturally occurring indoor features in 2-D and 3-D with lidar range/amplitude data

    SciTech Connect

    Adams, M.D.; Kerstens, A.

    1998-09-01

    Sensor-data processing for the interpretation of a mobile robot`s indoor environment, and the manipulation of this data for reliable localization, are still some of the most important issues in robotics. This article presents algorithms that determine the true position of a mobile robot, based on real 2-D and 3-D optical range and intensity data. The authors start with the physics of the particular type of sensor used, so that the extraction of reliable and repeatable information (namely, edge coordinates) can be determined, taking into account the noise associated with each range sample and the possibility of optical multiple-path effects. Again, applying the physical model of the sensor, the estimated positions of the mobile robot and the uncertainty in these positions are determined. They demonstrate real experiments using 2-D and 3-D scan data taken in indoor environments. To update the robot`s position reliably, the authors address the problem of matching the information recorded in a scan to, first, an a priori map, and second, to information recorded in previous scans, eliminating the need for an a priori map.

  7. Towards real-time 3D US to CT bone image registration using phase and curvature feature based GMM matching.

    PubMed

    Brounstein, Anna; Hacihaliloglu, Ilker; Guy, Pierre; Hodgson, Antony; Abugharbieh, Rafeef

    2011-01-01

    In order to use pre-operatively acquired computed tomography (CT) scans to guide surgical tool movements in orthopaedic surgery, the CT scan must first be registered to the patient's anatomy. Three-dimensional (3D) ultrasound (US) could potentially be used for this purpose if the registration process could be made sufficiently automatic, fast and accurate, but existing methods have difficulties meeting one or more of these criteria. We propose a near-real-time US-to-CT registration method that matches point clouds extracted from local phase images with points selected in part on the basis of local curvature. The point clouds are represented as Gaussian Mixture Models (GMM) and registration is achieved by minimizing the statistical dissimilarity between the GMMs using an L2 distance metric. We present quantitative and qualitative results on both phantom and clinical pelvis data and show a mean registration time of 2.11 s with a mean accuracy of 0.49 mm.

  8. Chemical and textural surface features of pyroclasts from hydrovolcanic eruption sequences

    SciTech Connect

    Wohletz, K.H.

    1987-12-31

    The purpose of this paper is to examine the vertical textural variations observed in stratigraphic sections of ash and show how these can be related to the eruptive history of volcanic vents. Samples were systematically taken from near-vent localities in vertical sequences of ash layers. Both size distributions and petrologic (chemical) constraints are among the features used in interpretation of textural features of the ash samples. The samples studied in this report were taken from four small (less than 2 km diameter) volcanoes: Crater Elegante and Cerro Colorado in Sonora, Mexico, and Panum Crater and Obsidian Dome, California. All four are typical volcanoes formed by hydrovolcanic eruptions. Crater Elegante is a basaltic tuff ring and Cerro Colorado is a tuff cone. The California examples are rhyolitic tuff rings. All are less than 10/sup 5/ years old. The significance of selecting these four volcanoes is that their pyroclasts have been formed by explosive mixing of meteoric water with magma as it approached the surface.

  9. [Measurement of sown area of safflower based on PCA and texture features classification and remote sensing imagery].

    PubMed

    Na, Ren-Hua; Zheng, Jiang-Hua; Guo, Bao-Lin; Sen, Ba-Ti; Shi, Min-Hui; Sun, Zhi-Qun; Jia, Xiao-Guang; Li, Xiao-Jin

    2013-11-01

    To improve accuracy of estimation in planted safflower acreage,we selected agricultural area in Yumin County, Xinjiang as the study area. There safflower was concentrated planted. Supervised classification based on Principal Component Analysis (PCA) and texture feature were used to obtain the safflower acreage from image captured by ZY-3. The classification result was compared with only spectral feature and spectral feature with texture feature. The research result shows that this method can effectively solve the problem of low accuracy and fracture classification result in single data source classification. The overall accuracy is 87.519 1%, which increases by 7.117 2% compared with single data source classification. Therefore, the classification method based on PCA and texture features can be adapted to RS image classification and estimate the acreage of safflower. This study provides a feasible solution for estimation of planted safflower acreage by image captured by ZY-3 satellite.

  10. Quantitative 3-D Imaging, Segmentation and Feature Extraction of the Respiratory System in Small Mammals for Computational Biophysics Simulations

    SciTech Connect

    Trease, Lynn L.; Trease, Harold E.; Fowler, John

    2007-03-15

    One of the critical steps toward performing computational biology simulations, using mesh based integration methods, is in using topologically faithful geometry derived from experimental digital image data as the basis for generating the computational meshes. Digital image data representations contain both the topology of the geometric features and experimental field data distributions. The geometric features that need to be captured from the digital image data are three-dimensional, therefore the process and tools we have developed work with volumetric image data represented as data-cubes. This allows us to take advantage of 2D curvature information during the segmentation and feature extraction process. The process is basically: 1) segmenting to isolate and enhance the contrast of the features that we wish to extract and reconstruct, 2) extracting the geometry of the features in an isosurfacing technique, and 3) building the computational mesh using the extracted feature geometry. “Quantitative” image reconstruction and feature extraction is done for the purpose of generating computational meshes, not just for producing graphics "screen" quality images. For example, the surface geometry that we extract must represent a closed water-tight surface.

  11. Exploiting quality and texture features to estimate age and gender from fingerprints

    NASA Astrophysics Data System (ADS)

    Marasco, Emanuela; Lugini, Luca; Cukic, Bojan

    2014-05-01

    Age and gender of an individual, when available, can contribute to identification decisions provided by primary biometrics and help improve matching performance. In this paper, we propose a system which automatically infers age and gender from the fingerprint image. Current approaches for predicting age and gender generally exploit features such as ridge count, and white lines count that are manually extracted. Existing automated approaches have significant limitations in accuracy especially when dealing with data pertaining to elderly females. The model proposed in this paper exploits image quality features synthesized from 40 different frequency bands, and image texture properties captured using the Local Binary Pattern (LBP) and the Local Phase Quantization (LPQ) operators. We evaluate the performance of the proposed approach using fingerprint images collected from 500 users with an optical sensor. The approach achieves prediction accuracy of 89.1% for age and 88.7% for gender.

  12. A CAD system for cerebral glioma based on texture features in DT-MR images

    NASA Astrophysics Data System (ADS)

    de Nunzio, G.; Pastore, G.; Donativi, M.; Castellano, A.; Falini, A.

    2011-08-01

    Tumor cells in cerebral glioma invade the surrounding tissues preferentially along white-matter tracts, spreading beyond the abnormal area seen on conventional MR images. Diffusion Tensor Imaging can reveal large peritumoral abnormalities in gliomas, which are not apparent on MRI.Our aim was to characterize pathological vs. healthy tissue in DTI datasets by 3D statistical Texture Analysis, developing an automatic segmentation technique (CAD, Computer Assisted Detection) for cerebral glioma based on a supervised classifier (an artificial neural network). A Matlab GUI (Graphical User Interface) was created to help the physician in the assisted diagnosis process and to optimize interactivity with the segmentation system, especially for patient follow-up during chemotherapy, and for preoperative assessment of tumor extension. Preliminary tissue classification results were obtained for the p map (the calculated area under the ROC curve, AUC, was 0.96) and the FA map (AUC=0.98). Test images were automatically segmented by tissue classification; manual and automatic segmentations were compared, showing good concordance.

  13. Towards real-time 3D US to CT bone image registration using phase and curvature feature based GMM matching.

    PubMed

    Brounstein, Anna; Hacihaliloglu, Ilker; Guy, Pierre; Hodgson, Antony; Abugharbieh, Rafeef

    2011-01-01

    In order to use pre-operatively acquired computed tomography (CT) scans to guide surgical tool movements in orthopaedic surgery, the CT scan must first be registered to the patient's anatomy. Three-dimensional (3D) ultrasound (US) could potentially be used for this purpose if the registration process could be made sufficiently automatic, fast and accurate, but existing methods have difficulties meeting one or more of these criteria. We propose a near-real-time US-to-CT registration method that matches point clouds extracted from local phase images with points selected in part on the basis of local curvature. The point clouds are represented as Gaussian Mixture Models (GMM) and registration is achieved by minimizing the statistical dissimilarity between the GMMs using an L2 distance metric. We present quantitative and qualitative results on both phantom and clinical pelvis data and show a mean registration time of 2.11 s with a mean accuracy of 0.49 mm. PMID:22003622

  14. An Approach to 3d Digital Modeling of Surfaces with Poor Texture by Range Imaging Techniques. `SHAPE from Stereo' VS. `SHAPE from Silhouette' in Digitizing Jorge Oteiza's Sculptures

    NASA Astrophysics Data System (ADS)

    García Fernández, J.; Álvaro Tordesillas, A.; Barba, S.

    2015-02-01

    Despite eminent development of digital range imaging techniques, difficulties persist in the virtualization of objects with poor radiometric information, in other words, objects consisting of homogeneous colours (totally white, black, etc.), repetitive patterns, translucence, or materials with specular reflection. This is the case for much of the Jorge Oteiza's works, particularly in the sculpture collection of the Museo Fundación Jorge Oteiza (Navarra, Spain). The present study intend to analyse and asses the performance of two digital 3D-modeling methods based on imaging techniques, facing cultural heritage in singular cases, determined by radiometric characteristics as mentioned: Shape from Silhouette and Shape from Stereo. On the other hand, the text proposes the definition of a documentation workflow and presents the results of its application in the collection of sculptures created by Oteiza.

  15. Unsupervised segmentation of ultrasound images by fusion of spatio-frequential textural features

    NASA Astrophysics Data System (ADS)

    Benameur, S.; Mignotte, M.; Lavoie, F.

    2011-03-01

    Image segmentation plays an important role in both qualitative and quantitative analysis of medical ultrasound images. However, due to their poor resolution and strong speckle noise, segmenting objects from this imaging modality remains a challenging task and may not be satisfactory with traditional image segmentation methods. To this end, this paper presents a simple, reliable, and conceptually different segmentation technique to locate and extract bone contours from ultrasound images. Instead of considering a new elaborate (texture) segmentation model specifically adapted for the ultrasound images, our technique proposes to fuse (i.e. efficiently combine) several segmentation maps associated with simpler segmentation models in order to get a final reliable and accurate segmentation result. More precisely, our segmentation model aims at fusing several K-means clustering results, each one exploiting, as simple cues, a set of complementary textural features, either spatial or frequential. Eligible models include the gray-level co-occurrence matrix, the re-quantized histogram, the Gabor filter bank, and local DCT coefficients. The experiments reported in this paper demonstrate the efficiency and illustrate all the potential of this segmentation approach.

  16. Classifying spatially heterogeneous wetland communities using machine learning algorithms and spectral and textural features.

    PubMed

    Szantoi, Zoltan; Escobedo, Francisco J; Abd-Elrahman, Amr; Pearlstine, Leonard; Dewitt, Bon; Smith, Scot

    2015-05-01

    Mapping of wetlands (marsh vs. swamp vs. upland) is a common remote sensing application.Yet, discriminating between similar freshwater communities such as graminoid/sedge fromremotely sensed imagery is more difficult. Most of this activity has been performed using medium to low resolution imagery. There are only a few studies using highspatial resolutionimagery and machine learning image classification algorithms for mapping heterogeneouswetland plantcommunities. This study addresses this void by analyzing whether machine learning classifierssuch as decisiontrees (DT) and artificial neural networks (ANN) can accurately classify graminoid/sedgecommunities usinghigh resolution aerial imagery and image texture data in the Everglades National Park, Florida.In addition tospectral bands, the normalized difference vegetation index, and first- and second-order texturefeatures derivedfrom the near-infrared band were analyzed. Classifier accuracies were assessed using confusiontablesand the calculated kappa coefficients of the resulting maps. The results indicated that an ANN(multilayerperceptron based on backpropagation) algorithm produced a statistically significantly higheraccuracy(82.04%) than the DT (QUEST) algorithm (80.48%) or the maximum likelihood (80.56%)classifier (α<0.05). Findings show that using multiple window sizes provided the best results. First-ordertexture featuresalso provided computational advantages and results that were not significantly different fromthose usingsecond-order texture features.

  17. Non-invasive health status detection system using Gabor filters based on facial block texture features.

    PubMed

    Shu, Ting; Zhang, Bob

    2015-04-01

    Blood tests allow doctors to check for certain diseases and conditions. However, using a syringe to extract the blood can be deemed invasive, slightly painful, and its analysis time consuming. In this paper, we propose a new non-invasive system to detect the health status (Healthy or Diseased) of an individual based on facial block texture features extracted using the Gabor filter. Our system first uses a non-invasive capture device to collect facial images. Next, four facial blocks are located on these images to represent them. Afterwards, each facial block is convolved with a Gabor filter bank to calculate its texture value. Classification is finally performed using K-Nearest Neighbor and Support Vector Machines via a Library for Support Vector Machines (with four kernel functions). The system was tested on a dataset consisting of 100 Healthy and 100 Diseased (with 13 forms of illnesses) samples. Experimental results show that the proposed system can detect the health status with an accuracy of 93 %, a sensitivity of 94 %, a specificity of 92 %, using a combination of the Gabor filters and facial blocks. PMID:25722202

  18. Text-independent writer identification and verification using textural and allographic features.

    PubMed

    Bulacu, Marius; Schomaker, Lambert

    2007-04-01

    The identification of a person on the basis of scanned images of handwriting is a useful biometric modality with application in forensic and historic document analysis and constitutes an exemplary study area within the research field of behavioral biometrics. We developed new and very effective techniques for automatic writer identification and verification that use probability distribution functions (PDFs) extracted from the handwriting images to characterize writer individuality. A defining property of our methods is that they are designed to be independent of the textual content of the handwritten samples. Our methods operate at two levels of analysis: the texture level and the character-shape (allograph) level. At the texture level, we use contour-based joint directional PDFs that encode orientation and curvature information to give an intimate characterization of individual handwriting style. In our analysis at the allograph level, the writer is considered to be characterized by a stochastic pattern generator of ink-trace fragments, or graphemes. The PDF of these simple shapes in a given handwriting sample is characteristic for the writer and is computed using a common shape codebook obtained by grapheme clustering. Combining multiple features (directional, grapheme, and run-length PDFs) yields increased writer identification and verification performance. The proposed methods are applicable to free-style handwriting (both cursive and isolated) and have practical feasibility, under the assumption that a few text lines of handwritten material are available in order to obtain reliable probability estimates.

  19. 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

    2016-01-01

    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. PMID:26952132

  20. 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

    SciTech Connect

    Desseroit, M; Cheze Le Rest, C; Tixier, F; Majdoub, M; Visvikis, D; Hatt, M; Guillevin, R; Perdrisot, R

    2014-06-15

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

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

    SciTech Connect

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

    2014-11-15

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

  2. 3D brain tumor segmentation in multimodal MR images based on learning population- and patient-specific feature sets.

    PubMed

    Jiang, Jun; Wu, Yao; Huang, Meiyan; Yang, Wei; Chen, Wufan; Feng, Qianjin

    2013-01-01

    Brain tumor segmentation is a clinical requirement for brain tumor diagnosis and radiotherapy planning. Automating this process is a challenging task due to the high diversity in appearance of tumor tissue among different patients and the ambiguous boundaries of lesions. In this paper, we propose a method to construct a graph by learning the population- and patient-specific feature sets of multimodal magnetic resonance (MR) images and by utilizing the graph-cut to achieve a final segmentation. The probabilities of each pixel that belongs to the foreground (tumor) and the background are estimated by global and custom classifiers that are trained through learning population- and patient-specific feature sets, respectively. The proposed method is evaluated using 23 glioma image sequences, and the segmentation results are compared with other approaches. The encouraging evaluation results obtained, i.e., DSC (84.5%), Jaccard (74.1%), sensitivity (87.2%), and specificity (83.1%), show that the proposed method can effectively make use of both population- and patient-specific information. PMID:23816459

  3. Textured surface identification in noisy color images

    NASA Astrophysics Data System (ADS)

    Celenk, Mehmet

    1996-06-01

    Automatic identification of textured surfaces is essential in many imaging applications such as image data compression and scene recognition. In these applications, a vision system is required to detect and identify irregular textures in the noisy color images. This work proposes a method for texture field characterization based on the local textural features. We first divide a given color image into n multiplied by n local windows and extract textural features in each window independently. In this step, the size of a window should be small enough so that each window can include only two texture fields. Separation of texture areas in a local window is first carried out by the Otsu or Kullback threshold selection technique on three color components separately. The 3-D class separation is then performed using the Fisher discriminant. The result of local texture classification is combined by the K-means clustering algorithm. The texture fields detected in a window are characterized by their mean vectors and an element-to-set membership relation. We have experimented with the local feature extraction part of the method using a color image of irregular textures. Results show that the method is effective for capturing the local textural features.

  4. Bootstrapping 3D fermions

    DOE PAGES

    Iliesiu, Luca; Kos, Filip; Poland, David; Pufu, Silviu S.; Simmons-Duffin, David; Yacoby, Ran

    2016-03-17

    We study the conformal bootstrap for a 4-point function of fermions <ψψψψ> in 3D. We first introduce an embedding formalism for 3D spinors and compute the conformal blocks appearing in fermion 4-point functions. Using these results, we find general bounds on the dimensions of operators appearing in the ψ × ψ OPE, and also on the central charge CT. We observe features in our bounds that coincide with scaling dimensions in the GrossNeveu models at large N. Finally, we also speculate that other features could coincide with a fermionic CFT containing no relevant scalar operators.

  5. An explorative childhood pneumonia analysis based on ultrasonic imaging texture features

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

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

  6. 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,…

  7. Creating 3D realistic head: from two orthogonal photos to multiview face contents

    NASA Astrophysics Data System (ADS)

    Lin, Yuan; Lin, Qian; Tang, Feng; Tang, Liang; Lim, Sukhwan; Wang, Shengjin

    2011-03-01

    3D Head models have many applications, such as virtual conference, 3D web game, and so on. The existing several web-based face modeling solutions that can create a 3D face model from one or two user uploaded face images, are limited to generating the 3D model of only face region. The accuracy of such reconstruction is very limited for side views, as well as hair regions. The goal of our research is to develop a framework for reconstructing the realistic 3D human head based on two approximate orthogonal views. Our framework takes two images, and goes through segmentation, feature points detection, 3D bald head reconstruction, 3D hair reconstruction and texture mapping to create a 3D head model. The main contribution of the paper is that the processing steps are applies to both the face region as well as the hair region.

  8. Terrestrial laser scanning point clouds time series for the monitoring of slope movements: displacement measurement using image correlation and 3D feature tracking

    NASA Astrophysics Data System (ADS)

    Bornemann, Pierrick; Jean-Philippe, Malet; André, Stumpf; Anne, Puissant; Julien, Travelletti

    2016-04-01

    Dense multi-temporal point clouds acquired with terrestrial laser scanning (TLS) have proved useful for the study of structure and kinematics of slope movements. Most of the existing deformation analysis methods rely on the use of interpolated data. Approaches that use multiscale image correlation provide a precise and robust estimation of the observed movements; however, for non-rigid motion patterns, these methods tend to underestimate all the components of the movement. Further, for rugged surface topography, interpolated data introduce a bias and a loss of information in some local places where the point cloud information is not sufficiently dense. Those limits can be overcome by using deformation analysis exploiting directly the original 3D point clouds assuming some hypotheses on the deformation (e.g. the classic ICP algorithm requires an initial guess by the user of the expected displacement patterns). The objective of this work is therefore to propose a deformation analysis method applied to a series of 20 3D point clouds covering the period October 2007 - October 2015 at the Super-Sauze landslide (South East French Alps). The dense point clouds have been acquired with a terrestrial long-range Optech ILRIS-3D laser scanning device from the same base station. The time series are analyzed using two approaches: 1) a method of correlation of gradient images, and 2) a method of feature tracking in the raw 3D point clouds. The estimated surface displacements are then compared with GNSS surveys on reference targets. Preliminary results tend to show that the image correlation method provides a good estimation of the displacement fields at first order, but shows limitations such as the inability to track some deformation patterns, and the use of a perspective projection that does not maintain original angles and distances in the correlated images. Results obtained with 3D point clouds comparison algorithms (C2C, ICP, M3C2) bring additional information on the

  9. MAP3D: a media processor approach for high-end 3D graphics

    NASA Astrophysics Data System (ADS)

    Darsa, Lucia; Stadnicki, Steven; Basoglu, Chris

    1999-12-01

    Equator Technologies, Inc. has used a software-first approach to produce several programmable and advanced VLIW processor architectures that have the flexibility to run both traditional systems tasks and an array of media-rich applications. For example, Equator's MAP1000A is the world's fastest single-chip programmable signal and image processor targeted for digital consumer and office automation markets. The Equator MAP3D is a proposal for the architecture of the next generation of the Equator MAP family. The MAP3D is designed to achieve high-end 3D performance and a variety of customizable special effects by combining special graphics features with high performance floating-point and media processor architecture. As a programmable media processor, it offers the advantages of a completely configurable 3D pipeline--allowing developers to experiment with different algorithms and to tailor their pipeline to achieve the highest performance for a particular application. With the support of Equator's advanced C compiler and toolkit, MAP3D programs can be written in a high-level language. This allows the compiler to successfully find and exploit any parallelism in a programmer's code, thus decreasing the time to market of a given applications. The ability to run an operating system makes it possible to run concurrent applications in the MAP3D chip, such as video decoding while executing the 3D pipelines, so that integration of applications is easily achieved--using real-time decoded imagery for texturing 3D objects, for instance. This novel architecture enables an affordable, integrated solution for high performance 3D graphics.

  10. Application of computer-extracted breast tissue texture features in predicting false-positive recalls from screening mammography

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

    Mammographic texture features have been shown to have value in breast cancer risk assessment. Previous models have also been developed that use computer-extracted mammographic features of breast tissue complexity to predict the risk of false-positive (FP) recall from breast cancer screening with digital mammography. This work details a novel locallyadaptive parenchymal texture analysis algorithm that identifies and extracts mammographic features of local parenchymal tissue complexity potentially relevant for false-positive biopsy prediction. This algorithm has two important aspects: (1) the adaptive nature of automatically determining an optimal number of region-of-interests (ROIs) in the image and each ROI's corresponding size based on the parenchymal tissue distribution over the whole breast region and (2) characterizing both the local and global mammographic appearances of the parenchymal tissue that could provide more discriminative information for FP biopsy risk prediction. Preliminary results show that this locallyadaptive texture analysis algorithm, in conjunction with logistic regression, can predict the likelihood of false-positive biopsy with an ROC performance value of AUC=0.92 (p<0.001) with a 95% confidence interval [0.77, 0.94]. Significant texture feature predictors (p<0.05) included contrast, sum variance and difference average. Sensitivity for false-positives was 51% at the 100% cancer detection operating point. Although preliminary, clinical implications of using prediction models incorporating these texture features may include the future development of better tools and guidelines regarding personalized breast cancer screening recommendations. Further studies are warranted to prospectively validate our findings in larger screening populations and evaluate their clinical utility.

  11. Some features of bulk melt-textured high-temperature superconductors subjected to alternating magnetic fields

    NASA Astrophysics Data System (ADS)

    Vanderbemden, P.; Molenberg, I.; Simeonova, P.; Lovchinov, V.

    2014-12-01

    Monolithic, large grain, (RE)Ba2Cu3O7 high-temperature superconductors (where RE denotes a rare-earth ion) are known to be able to trap fields in excess of several teslas and represent thus an extremely promising competing technology for permanent magnet in several applications, e.g. in motors and generators. In any rotating machine, however, the superconducting permanent magnet is subjected to variable (transient, or alternating) parasitic magnetic fields. These magnetic fields interact with the superconductor, which yields a reduction of the remnant magnetization. In the present work we quantify these effects by analysing selected experimental data on bulk melt-textured superconductors subjected to AC fields. Our results indicate that the non-uniformity of superconducting properties in rather large samples might lead to unusual features and need to be taken into account to analyse the experimental data. We also investigate the evolution of the DC remnant magnetization of the bulk sample when it is subjected to a large number of AC magnetic field cycles, and investigate the experimental errors that result from a misorientation of the sample or a mispositioning of the Hall probe. The time-dependence of the remnant magnetization over 100000 cycles of the AC field is shown to display distinct regimes which all differ strongly from the usual decay due to magnetic relaxation.

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

    PubMed Central

    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

    2016-01-01

    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. DOI: http://dx.doi.org/10.7554/eLife.09148.001 PMID:26952132

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

    SciTech Connect

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

    2015-06-15

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

  14. Automatic Reconstruction of Spacecraft 3D Shape from Imagery

    NASA Astrophysics Data System (ADS)

    Poelman, C.; Radtke, R.; Voorhees, H.

    We describe a system that computes the three-dimensional (3D) shape of a spacecraft from a sequence of uncalibrated, two-dimensional images. While the mathematics of multi-view geometry is well understood, building a system that accurately recovers 3D shape from real imagery remains an art. A novel aspect of our approach is the combination of algorithms from computer vision, photogrammetry, and computer graphics. We demonstrate our system by computing spacecraft models from imagery taken by the Air Force Research Laboratory's XSS-10 satellite and DARPA's Orbital Express satellite. Using feature tie points (each identified in two or more images), we compute the relative motion of each frame and the 3D location of each feature using iterative linear factorization followed by non-linear bundle adjustment. The "point cloud" that results from this traditional shape-from-motion approach is typically too sparse to generate a detailed 3D model. Therefore, we use the computed motion solution as input to a volumetric silhouette-carving algorithm, which constructs a solid 3D model based on viewpoint consistency with the image frames. The resulting voxel model is then converted to a facet-based surface representation and is texture-mapped, yielding realistic images from arbitrary viewpoints. We also illustrate other applications of the algorithm, including 3D mensuration and stereoscopic 3D movie generation.

  15. Counter-intuitive features of the dynamic topography unveiled by tectonically realistic 3D numerical models of mantle-lithosphere interactions

    NASA Astrophysics Data System (ADS)

    Burov, Evgueni; Gerya, Taras

    2013-04-01

    It has been long assumed that the dynamic topography associated with mantle-lithosphere interactions should be characterized by long-wavelength features (> 1000 km) correlating with morphology of mantle flow and expanding beyond the scale of tectonic processes. For example, debates on the existence of mantle plumes largely originate from interpretations of expected signatures of plume-induced topography that are compared to the predictions of analytical and numerical models of plume- or mantle-lithosphere interactions (MLI). Yet, most of the large-scale models treat the lithosphere as a homogeneous stagnant layer. We show that in continents, the dynamic topography is strongly affected by rheological properties and layered structure of the lithosphere. For that we reconcile mantle- and tectonic-scale models by introducing a tectonically realistic continental plate model in 3D large-scale plume-mantle-lithosphere interaction context. This model accounts for stratified structure of continental lithosphere, ductile and frictional (Mohr-Coulomb) plastic properties and thermodynamically consistent density variations. The experiments reveal a number of important differences from the predictions of the conventional models. In particular, plate bending, mechanical decoupling of crustal and mantle layers and intra-plate tension-compression instabilities result in transient topographic signatures such as alternating small-scale surface features that could be misinterpreted in terms of regional tectonics. Actually thick ductile lower crustal layer absorbs most of the "direct" dynamic topography and the features produced at surface are mostly controlled by the mechanical instabilities in the upper and intermediate crustal layers produced by MLI-induced shear and bending at Moho and LAB. Moreover, the 3D models predict anisotropic response of the lithosphere even in case of isotropic solicitations by axisymmetric mantle upwellings such as plumes. In particular, in presence of

  16. Analysis of breast CT lesions using computer-aided diagnosis: an application of neural networks on extracted morphologic and texture features

    NASA Astrophysics Data System (ADS)

    Ray, Shonket; Prionas, Nicolas D.; Lindfors, Karen K.; Boone, John M.

    2012-03-01

    Dedicated cone-beam breast CT (bCT) scanners have been developed as a potential alternative imaging modality to conventional X-ray mammography in breast cancer diagnosis. As with other modalities, quantitative imaging (QI) analysis can potentially be utilized as a tool to extract useful numeric information concerning diagnosed lesions from high quality 3D tomographic data sets. In this work, preliminary QI analysis was done by designing and implementing a computer-aided diagnosis (CADx) system consisting of image preprocessing, object(s) of interest (i.e. masses, microcalcifications) segmentation, structural analysis of the segmented object(s), and finally classification into benign or malignant disease. Image sets were acquired from bCT patient scans with diagnosed lesions. Iterative watershed segmentation (IWS), a hybridization of the watershed method using observer-set markers and a gradient vector flow (GVF) approach, was used as the lesion segmentation method in 3D. Eight morphologic parameters and six texture features based on gray level co-occurrence matrix (GLCM) calculations were obtained per segmented lesion and combined into multi-dimensional feature input data vectors. Artificial neural network (ANN) classifiers were used by performing cross validation and network parameter optimization to maximize area under the curve (AUC) values of the resulting receiver-operating characteristic (ROC) curves. Within these ANNs, biopsy-proven diagnoses of malignant and benign lesions were recorded as target data while the feature vectors were saved as raw input data. With the image data separated into post-contrast (n = 55) and pre-contrast sets (n = 39), a maximum AUC of 0.70 +/- 0.02 and 0.80 +/- 0.02 were achieved, respectively, for each data set after ANN application.

  17. 3D fingerprint imaging system based on full-field fringe projection profilometry

    NASA Astrophysics Data System (ADS)

    Huang, Shujun; Zhang, Zonghua; Zhao, Yan; Dai, Jie; Chen, Chao; Xu, Yongjia; Zhang, E.; Xie, Lili

    2014-01-01

    As an unique, unchangeable and easily acquired biometrics, fingerprint has been widely studied in academics and applied in many fields over the years. The traditional fingerprint recognition methods are based on the obtained 2D feature of fingerprint. However, fingerprint is a 3D biological characteristic. The mapping from 3D to 2D loses 1D information and causes nonlinear distortion of the captured fingerprint. Therefore, it is becoming more and more important to obtain 3D fingerprint information for recognition. In this paper, a novel 3D fingerprint imaging system is presented based on fringe projection technique to obtain 3D features and the corresponding color texture information. A series of color sinusoidal fringe patterns with optimum three-fringe numbers are projected onto a finger surface. From another viewpoint, the fringe patterns are deformed by the finger surface and captured by a CCD camera. 3D shape data of the finger can be obtained from the captured fringe pattern images. This paper studies the prototype of the 3D fingerprint imaging system, including principle of 3D fingerprint acquisition, hardware design of the 3D imaging system, 3D calibration of the system, and software development. Some experiments are carried out by acquiring several 3D fingerprint data. The experimental results demonstrate the feasibility of the proposed 3D fingerprint imaging system.

  18. Usefulness of texture features for segmentation of lungs with severe diffuse interstitial lung disease

    NASA Astrophysics Data System (ADS)

    Wang, Jiahui; Li, Feng; Li, Qiang

    2010-03-01

    We developed an automated method for the segmentation of lungs with severe diffuse interstitial lung disease (DILD) in multi-detector CT. In this study, we would like to compare the performance levels of this method and a thresholdingbased segmentation method for normal lungs, moderately abnormal lungs, severely abnormal lungs, and all lungs in our database. Our database includes 31 normal cases and 45 abnormal cases with severe DILD. The outlines of lungs were manually delineated by a medical physicist and confirmed by an experienced chest radiologist. These outlines were used as reference standards for the evaluation of the segmentation results. We first employed a thresholding technique for CT value to obtain initial lungs, which contain normal and mildly abnormal lung parenchyma. We then used texture-feature images derived from co-occurrence matrix to further segment lung regions with severe DILD. The segmented lung regions with severe DILD were combined with the initial lungs to generate the final segmentation results. We also identified and removed the airways to improve the accuracy of the segmentation results. We used three metrics, i.e., overlap, volume agreement, and mean absolute distance (MAD) between automatically segmented lung and reference lung to evaluate the performance of our segmentation method and the thresholding-based segmentation method. Our segmentation method achieved a mean overlap of 96.1%, a mean volume agreement of 98.1%, and a mean MAD of 0.96 mm for the 45 abnormal cases. On the other hand the thresholding-based segmentation method achieved a mean overlap of 94.2%, a mean volume agreement of 95.8%, and a mean MAD of 1.51 mm for the 45 abnormal cases. Our new method obtained higher performance level than the thresholding-based segmentation method.

  19. A common feature-based 3D-pharmacophore model generation and virtual screening: identification of potential PfDHFR inhibitors.

    PubMed

    Adane, Legesse; Bharatam, Prasad V; Sharma, Vikas

    2010-10-01

    A four-feature 3D-pharmacophore model was built from a set of 24 compounds whose activities were reported against the V1/S strain of the Plasmodium falciparum dihydrofolate reductase (PfDHFR) enzyme. This is an enzyme harboring Asn51Ile + Cys59Arg + Ser108Asn + Ile164Leu mutations. The HipHop module of the Catalyst program was used to generate the model. Selection of the best model among the 10 hypotheses generated by HipHop was carried out based on rank and best-fit values or alignments of the training set compounds onto a particular hypothesis. The best model (hypo1) consisted of two H-bond donors, one hydrophobic aromatic, and one hydrophobic aliphatic features. Hypo1 was used as a query to virtually screen Maybridge2004 and NCI2000 databases. The hits obtained from the search were subsequently subjected to FlexX and Glide docking studies. Based on the binding scores and interactions in the active site of quadruple-mutant PfDHFR, a set of nine hits were identified as potential inhibitors. PMID:19995305

  20. A common feature-based 3D-pharmacophore model generation and virtual screening: identification of potential PfDHFR inhibitors.

    PubMed

    Adane, Legesse; Bharatam, Prasad V; Sharma, Vikas

    2010-10-01

    A four-feature 3D-pharmacophore model was built from a set of 24 compounds whose activities were reported against the V1/S strain of the Plasmodium falciparum dihydrofolate reductase (PfDHFR) enzyme. This is an enzyme harboring Asn51Ile + Cys59Arg + Ser108Asn + Ile164Leu mutations. The HipHop module of the Catalyst program was used to generate the model. Selection of the best model among the 10 hypotheses generated by HipHop was carried out based on rank and best-fit values or alignments of the training set compounds onto a particular hypothesis. The best model (hypo1) consisted of two H-bond donors, one hydrophobic aromatic, and one hydrophobic aliphatic features. Hypo1 was used as a query to virtually screen Maybridge2004 and NCI2000 databases. The hits obtained from the search were subsequently subjected to FlexX and Glide docking studies. Based on the binding scores and interactions in the active site of quadruple-mutant PfDHFR, a set of nine hits were identified as potential inhibitors.

  1. Skin cancer texture analysis of OCT images based on Haralick, fractal dimension and the complex directional field features

    NASA Astrophysics Data System (ADS)

    Raupov, Dmitry S.; Myakinin, Oleg O.; Bratchenko, Ivan A.; Kornilin, Dmitry V.; Zakharov, Valery P.; Khramov, Alexander G.

    2016-04-01

    Optical coherence tomography (OCT) is usually employed for the measurement of tumor topology, which reflects structural changes of a tissue. We investigated the possibility of OCT in detecting changes using a computer texture analysis method based on Haralick texture features, fractal dimension and the complex directional field method from different tissues. These features were used to identify special spatial characteristics, which differ healthy tissue from various skin cancers in cross-section OCT images (B-scans). Speckle reduction is an important pre-processing stage for OCT image processing. In this paper, an interval type-II fuzzy anisotropic diffusion algorithm for speckle noise reduction in OCT images was used. The Haralick texture feature set includes contrast, correlation, energy, and homogeneity evaluated in different directions. A box-counting method is applied to compute fractal dimension of investigated tissues. Additionally, we used the complex directional field calculated by the local gradient methodology to increase of the assessment quality of the diagnosis method. The complex directional field (as well as the "classical" directional field) can help describe an image as set of directions. Considering to a fact that malignant tissue grows anisotropically, some principal grooves may be observed on dermoscopic images, which mean possible existence of principal directions on OCT images. Our results suggest that described texture features may provide useful information to differentiate pathological from healthy patients. The problem of recognition melanoma from nevi is decided in this work due to the big quantity of experimental data (143 OCT-images include tumors as Basal Cell Carcinoma (BCC), Malignant Melanoma (MM) and Nevi). We have sensitivity about 90% and specificity about 85%. Further research is warranted to determine how this approach may be used to select the regions of interest automatically.

  2. Prognosis classification in glioblastoma multiforme using multimodal MRI derived heterogeneity textural features: impact of pre-processing choices

    NASA Astrophysics Data System (ADS)

    Upadhaya, Taman; Morvan, Yannick; Stindel, Eric; Le Reste, Pierre-Jean; Hatt, Mathieu

    2016-03-01

    Heterogeneity image-derived features of Glioblastoma multiforme (GBM) tumors from multimodal MRI sequences may provide higher prognostic value than standard parameters used in routine clinical practice. We previously developed a framework for automatic extraction and combination of image-derived features (also called "Radiomics") through support vector machines (SVM) for predictive model building. The results we obtained in a cohort of 40 GBM suggested these features could be used to identify patients with poorer outcome. However, extraction of these features is a delicate multi-step process and their values may therefore depend on the pre-processing of images. The original developed workflow included skull removal, bias homogeneity correction, and multimodal tumor segmentation, followed by textural features computation, and lastly ranking, selection and combination through a SVM-based classifier. The goal of the present work was to specifically investigate the potential benefit and respective impact of the addition of several MRI pre-processing steps (spatial resampling for isotropic voxels, intensities quantization and normalization) before textural features computation, on the resulting accuracy of the classifier. Eighteen patients datasets were also added for the present work (58 patients in total). A classification accuracy of 83% (sensitivity 79%, specificity 85%) was obtained using the original framework. The addition of the new pre-processing steps increased it to 93% (sensitivity 93%, specificity 93%) in identifying patients with poorer survival (below the median of 12 months). Among the three considered pre-processing steps, spatial resampling was found to have the most important impact. This shows the crucial importance of investigating appropriate image pre-processing steps to be used for methodologies based on textural features extraction in medical imaging.

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

    SciTech Connect

    Masotti, Matteo; Lanconelli, Nico; Campanini, Renato

    2009-02-15

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

  4. An Approach to Diagnosis of Auto-Immune Diseases using HEP-2 Staining Pattern and Fractal Texture Features.

    PubMed

    Suganthi, S S; Pradhap, S Singh Allmin; Ramakrishnan, S

    2015-01-01

    Observing and classifying the indirect immunofluorescence patterns on HEp-2 cells can help in detecting Anti-Nuclear-Antibodies. A computer algorithm to perform this function can lead to a more standardized, faster and accurate diagnosis of auto-immune diseases such as systemic lupus erythematosus, sjogren’s syndrome, and rheumatoid arthritis. In this paper, HEp-2 staining patterns are classified using segmentation based fractal texture features. The images used for this experimentation are obtained from a publicly available database. The features extracted from a cell image is used to classify it into homogenous, fine speckled, coarse speckled, centromere and nucleolus. The cell images are segmented using the ground truth mask provided in the database. Adaptive histogram equalization is applied to the segmented images for contrast enhancement. Three features namely mean intensity, area and Hausdorff fractal dimension of the border are extracted for 8 different Otsu threshold levels. Finally, the 24 features thus extracted are fed to a support vector machine with Gaussian radial basis function kernel. It is observed that the overall accuracy of classification is 65.17%. The accuracy is greatly dependent on scaling and distribution of the features given to SVM. It appears that the segmentation based fractal texture features and SVM could help to build a robust automated diagnosis tool for auto-immune diseases. PMID:25996738

  5. Textural entropy as a potential feature for quantitative assessment of jaw bone healing process

    PubMed Central

    Kozakiewicz, Marcin; Materka, Andrzej

    2015-01-01

    Introduction The aim of the study was to propose and evaluate textural entropy as a parameter for bone healing assessment. Material and methods One hundred and twenty radiographs with loss of bone architecture were investigated (a bone defect was circumscribed – ROI DEF). A reference region (ROI REF) of the same surface area as the ROI DEF was placed in a field distant from the defect, where a normal, trabecular pattern of bone structure was well visualized. Data of three time points were investigated: T0 – immediately after the surgical procedure, T1 – 3 months post-op, and T2 – 12 months post-op. Results Textural entropy as a parameter describing bone structure regeneration was selected based on Fisher coefficient (F) evaluation. F was highest in T0 (3.4) and was decreasing later in T1 (1.7) and T2 (1.0 – means final lack of difference in the structure to reference bone). Textural entropy is a measure of structure disarrangement which in a bone defect region attains minimal value due to structural homogeneity, i.e. low complexity of the texture. The calculated parameter in the investigated material revealed a gradual increase inside the bone defect (p < 0.05), i.e. increase of complexity in a time-dependent manner starting from immediate post-op (T0 = 2.51; T1 = 2.68) up to most complex 1 year post-operational (T2 = 2.73), reaching the reference level of a normal bone. Conclusions Textural entropy may be useful for computer assisted evaluation of bone regeneration process. The complexity of the texture corresponds to mature trabecular bone formation. PMID:25861292

  6. Segmentation and detection of fluorescent 3D spots.

    PubMed

    Ram, Sundaresh; Rodríguez, Jeffrey J; Bosco, Giovanni

    2012-03-01

    The 3D spatial organization of genes and other genetic elements within the nucleus is important for regulating gene expression. Understanding how this spatial organization is established and maintained throughout the life of a cell is key to elucidating the many layers of gene regulation. Quantitative methods for studying nuclear organization will lead to insights into the molecular mechanisms that maintain gene organization as well as serve as diagnostic tools for pathologies caused by loss of nuclear structure. However, biologists currently lack automated and high throughput methods for quantitative and qualitative global analysis of 3D gene organization. In this study, we use confocal microscopy and fluorescence in-situ hybridization (FISH) as a cytogenetic technique to detect and localize the presence of specific DNA sequences in 3D. FISH uses probes that bind to specific targeted locations on the chromosomes, appearing as fluorescent spots in 3D images obtained using fluorescence microscopy. In this article, we propose an automated algorithm for segmentation and detection of 3D FISH spots. The algorithm is divided into two stages: spot segmentation and spot detection. Spot segmentation consists of 3D anisotropic smoothing to reduce the effect of noise, top-hat filtering, and intensity thresholding, followed by 3D region-growing. Spot detection uses a Bayesian classifier with spot features such as volume, average intensity, texture, and contrast to detect and classify the segmented spots as either true or false spots. Quantitative assessment of the proposed algorithm demonstrates improved segmentation and detection accuracy compared to other techniques.

  7. Texture features on T2-weighted magnetic resonance imaging: new potential biomarkers for prostate cancer aggressiveness

    NASA Astrophysics Data System (ADS)

    Vignati, A.; Mazzetti, S.; Giannini, V.; Russo, F.; Bollito, E.; Porpiglia, F.; Stasi, M.; Regge, D.

    2015-04-01

    To explore contrast (C) and homogeneity (H) gray-level co-occurrence matrix texture features on T2-weighted (T2w) Magnetic Resonance (MR) images and apparent diffusion coefficient (ADC) maps for predicting prostate cancer (PCa) aggressiveness, and to compare them with traditional ADC metrics for differentiating low- from intermediate/high-grade PCas. The local Ethics Committee approved this prospective study of 93 patients (median age, 65 years), who underwent 1.5 T multiparametric endorectal MR imaging before prostatectomy. Clinically significant (volume ≥0.5 ml) peripheral tumours were outlined on histological sections, contoured on T2w and ADC images, and their pathological Gleason Score (pGS) was recorded. C, H, and traditional ADC metrics (mean, median, 10th and 25th percentile) were calculated on the largest lesion slice, and correlated with the pGS through the Spearman correlation coefficient. The area under the receiver operating characteristic curve (AUC) assessed how parameters differentiate pGS = 6 from pGS ≥ 7. The dataset included 49 clinically significant PCas with a balanced distribution of pGS. The Spearman ρ and AUC values on ADC were: -0.489, 0.823 (mean) -0.522, 0.821 (median) -0.569, 0.854 (10th percentile) -0.556, 0.854 (25th percentile) -0.386, 0.871 (C); 0.533, 0.923 (H); while on T2w they were: -0.654, 0.945 (C); 0.645, 0.962 (H). AUC of H on ADC and T2w, and C on T2w were significantly higher than that of the mean ADC (p = 0.05). H and C calculated on T2w images outperform ADC parameters in correlating with pGS and differentiating low- from intermediate/high-risk PCas, supporting the role of T2w MR imaging in assessing PCa biological aggressiveness.

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

    PubMed

    Zyout, Imad; Czajkowska, Joanna; Grzegorzek, Marcin

    2015-12-01

    The high number of false positives and the resulting number of avoidable breast biopsies are the major problems faced by current mammography Computer Aided Detection (CAD) systems. False positive reduction is not only a requirement for mass but also for calcification CAD systems which are currently deployed for clinical use. This paper tackles two problems related to reducing the number of false positives in the detection of all lesions and masses, respectively. Firstly, textural patterns of breast tissue have been analyzed using several multi-scale textural descriptors based on wavelet and gray level co-occurrence matrix. The second problem addressed in this paper is the parameter selection and performance optimization. For this, we adopt a model selection procedure based on Particle Swarm Optimization (PSO) for selecting the most discriminative textural features and for strengthening the generalization capacity of the supervised learning stage based on a Support Vector Machine (SVM) classifier. For evaluating the proposed methods, two sets of suspicious mammogram regions have been used. The first one, obtained from Digital Database for Screening Mammography (DDSM), contains 1494 regions (1000 normal and 494 abnormal samples). The second set of suspicious regions was obtained from database of Mammographic Image Analysis Society (mini-MIAS) and contains 315 (207 normal and 108 abnormal) samples. Results from both datasets demonstrate the efficiency of using PSO based model selection for optimizing both classifier hyper-parameters and parameters, respectively. Furthermore, the obtained results indicate the promising performance of the proposed textural features and more specifically, those based on co-occurrence matrix of wavelet image representation technique. PMID:25795630

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

    PubMed

    Zyout, Imad; Czajkowska, Joanna; Grzegorzek, Marcin

    2015-12-01

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

  10. Computer extracted texture features on T2w MRI to predict biochemical recurrence following radiation therapy for prostate cancer

    NASA Astrophysics Data System (ADS)

    Ginsburg, Shoshana B.; Rusu, Mirabela; Kurhanewicz, John; Madabhushi, Anant

    2014-03-01

    In this study we explore the ability of a novel machine learning approach, in conjunction with computer-extracted features describing prostate cancer morphology on pre-treatment MRI, to predict whether a patient will develop biochemical recurrence within ten years of radiation therapy. Biochemical recurrence, which is characterized by a rise in serum prostate-specific antigen (PSA) of at least 2 ng/mL above the nadir PSA, is associated with increased risk of metastasis and prostate cancer-related mortality. Currently, risk of biochemical recurrence is predicted by the Kattan nomogram, which incorporates several clinical factors to predict the probability of recurrence-free survival following radiation therapy (but has limited prediction accuracy). Semantic attributes on T2w MRI, such as the presence of extracapsular extension and seminal vesicle invasion and surrogate measure- ments of tumor size, have also been shown to be predictive of biochemical recurrence risk. While the correlation between biochemical recurrence and factors like tumor stage, Gleason grade, and extracapsular spread are well- documented, it is less clear how to predict biochemical recurrence in the absence of extracapsular spread and for small tumors fully contained in the capsule. Computer{extracted texture features, which quantitatively de- scribe tumor micro-architecture and morphology on MRI, have been shown to provide clues about a tumor's aggressiveness. However, while computer{extracted features have been employed for predicting cancer presence and grade, they have not been evaluated in the context of predicting risk of biochemical recurrence. This work seeks to evaluate the role of computer-extracted texture features in predicting risk of biochemical recurrence on a cohort of sixteen patients who underwent pre{treatment 1.5 Tesla (T) T2w MRI. We extract a combination of first-order statistical, gradient, co-occurrence, and Gabor wavelet features from T2w MRI. To identify which of these

  11. Chemical and textural surface features of pyroclasts from hydrovolcanic eruption sequences

    SciTech Connect

    Wohletz, K.H.

    1983-01-01

    Hydrovolcanic pyroclasts are produced by the interaction of erupting magma with surface or near-surface water. Eruption energy determining pyroclast transport and depositional modes is dependent upon the amount of water interacting with magma. Grain morphologies, size distributions, surface textures, and chemical effects studied record the history of eruption cycles for volcanoes under consideration. Samples of crater-rim stratigraphic sequences from Crater Elegante and Cerro Colorado, Mexico, and from Panum Crater and Obsidian Dome, California, illustrate a basaltic tuff ring and tuff cone and two rhyolitic tuff rings respectively. Grain morphologies observed by scanning electron microscopy (SEM) reveal information on the process of melt fragmentation. Surface alteration and diagenesis have greater effect on pyroclasts from wet eruptions compared to dry ones. These textures are patchy overgrowths of microcrystalline and hydrated materials. Surface chemical characteristics observed with energy dispersive spectral analysis (EDS) show relative gains or losses of elements and an apparent enrichment of silica on altered surfaces.

  12. Texture analysis of terrain images: exploiting directional properties of a local-feature statistics operator using small masks

    NASA Astrophysics Data System (ADS)

    Telfer, Duncan J.; Wilson, Lionel

    1996-06-01

    The texture discrimination properties of a directional operator, using a window based histogram correlation technique, are described for test images and natural scene imagery. The natural image examples are drawn from digitized monochrome aerial photographs of volcanic terrain, and of coastal dune fields in the region of West Lancashire, England. The operator masks use directionally encoded local difference parameters and are of two sizes, 3 by 3 and 2 by 2 pixels, scanning over a window size of 25 by 25 pixels to create an autocorrelation map, normalized to the output gray-scale range. Comparisons of the outputs are discussed in terms of ability to detect specific types of texture feature associated with known lava flow regimes demonstrate the viability of the technique down to single pixel resolution, particularly for folded or striated topography. The vegetation cover of the volcanic terrain is also characterized in terms of its response to these texture operators. The output from the dune field images, which contain a wider variety of vegetation cover, also demonstrates the discrimination capability of the technique and its potential usefulness in environmental and conservation management.

  13. Variability in CT lung-nodule quantification: Effects of dose reduction and reconstruction methods on density and texture based features

    PubMed Central

    Lo, P.; Young, S.; Kim, H. J.; Brown, M. S.

    2016-01-01

    Purpose: To investigate the effects of dose level and reconstruction method on density and texture based features computed from CT lung nodules. Methods: This study had two major components. In the first component, a uniform water phantom was scanned at three dose levels and images were reconstructed using four conventional filtered backprojection (FBP) and four iterative reconstruction (IR) methods for a total of 24 different combinations of acquisition and reconstruction conditions. In the second component, raw projection (sinogram) data were obtained for 33 lung nodules from patients scanned as a part of their clinical practice, where low dose acquisitions were simulated by adding noise to sinograms acquired at clinical dose levels (a total of four dose levels) and reconstructed using one FBP kernel and two IR kernels for a total of 12 conditions. For the water phantom, spherical regions of interest (ROIs) were created at multiple locations within the water phantom on one reference image obtained at a reference condition. For the lung nodule cases, the ROI of each nodule was contoured semiautomatically (with manual editing) from images obtained at a reference condition. All ROIs were applied to their corresponding images reconstructed at different conditions. For 17 of the nodule cases, repeat contours were performed to assess repeatability. Histogram (eight features) and gray level co-occurrence matrix (GLCM) based texture features (34 features) were computed for all ROIs. For the lung nodule cases, the reference condition was selected to be 100% of clinical dose with FBP reconstruction using the B45f kernel; feature values calculated from other conditions were compared to this reference condition. A measure was introduced, which the authors refer to as Q, to assess the stability of features across different conditions, which is defined as the ratio of reproducibility (across conditions) to repeatability (across repeat contours) of each feature. Results: The

  14. Nanometer-scale features on micrometer-scale surface texturing: a bone histological, gene expression, and nanomechanical study.

    PubMed

    Coelho, Paulo G; Takayama, Tadahiro; Yoo, Daniel; Jimbo, Ryo; Karunagaran, Sanjay; Tovar, Nick; Janal, Malvin N; Yamano, Seiichi

    2014-08-01

    Micro- and nanoscale surface modifications have been the focus of multiple studies in the pursuit of accelerating bone apposition or osseointegration at the implant surface. Here, we evaluated histological and nanomechanical properties, and gene expression, for a microblasted surface presenting nanometer-scale texture within a micrometer-scale texture (MB) (Ossean Surface, Intra-Lock International, Boca Raton, FL) versus a dual-acid etched surface presenting texture at the micrometer-scale only (AA), in a rodent femur model for 1, 2, 4, and 8weeks in vivo. Following animal sacrifice, samples were evaluated in terms of histomorphometry, biomechanical properties through nanoindentation, and gene expression by real-time quantitative reverse transcription polymerase chain reaction analysis. Although the histomorphometric, and gene expression analysis results were not significantly different between MB and AA at 4 and 8 weeks, significant differences were seen at 1 and 2 weeks. The expression of the genes encoding collagen type I (COL-1), and osteopontin (OPN) was significantly higher for MB than for AA at 1 week, indicating up-regulated osteoprogenitor and osteoblast differentiation. At 2 weeks, significantly up-regulated expression of the genes for COL-1, runt-related transcription factor 2 (RUNX-2), osterix, and osteocalcin (OCN) indicated progressive mineralization in newly formed bone. The nanomechanical properties tested by the nanoindentation presented significantly higher-rank hardness and elastic modulus for the MB compared to AA at all time points tested. In conclusion, the nanotopographical featured surfaces presented an overall higher host-to-implant response compared to the microtextured only surfaces. The statistical differences observed in some of the osteogenic gene expression between the two groups may shed some insight into the role of surface texture and its extent in the observed bone healing mechanisms. PMID:24813260

  15. On the comparison of visual discomfort generated by S3D and 2D content based on eye-tracking features

    NASA Astrophysics Data System (ADS)

    Iatsun, Iana; Larabi, Mohamed-Chaker; Fernandez-Maloigne, Christine

    2014-03-01

    The changing of TV systems from 2D to 3D mode is the next expected step in the telecommunication world. Some works have already been done to perform this progress technically, but interaction of the third dimension with humans is not yet clear. Previously, it was found that any increased load of visual system can create visual fatigue, like prolonged TV watching, computer work or video gaming. But watching S3D can cause another nature of visual fatigue, since all S3D technologies creates illusion of the third dimension based on characteristics of binocular vision. In this work we propose to evaluate and compare the visual fatigue from watching 2D and S3D content. This work shows the difference in accumulation of visual fatigue and its assessment for two types of content. In order to perform this comparison eye-tracking experiments using six commercially available movies were conducted. Healthy naive participants took part into the test and gave their answers feeling the subjective evaluation. It was found that watching stereo 3D content induce stronger feeling of visual fatigue than conventional 2D, and the nature of video has an important effect on its increase. Visual characteristics obtained by using eye-tracking were investigated regarding their relation with visual fatigue.

  16. Predicting Ki67% expression from DCE-MR images of breast tumors using textural kinetic features in tumor habitats

    NASA Astrophysics Data System (ADS)

    Chaudhury, Baishali; Zhou, Mu; Farhidzadeh, Hamidreza; Goldgof, Dmitry B.; Hall, Lawrence O.; Gatenby, Robert A.; Gillies, Robert J.; Weinfurtner, Robert J.; Drukteinis, Jennifer S.

    2016-03-01

    The use of Ki67% expression, a cell proliferation marker, as a predictive and prognostic factor has been widely studied in the literature. Yet its usefulness is limited due to inconsistent cut off scores for Ki67% expression, subjective differences in its assessment in various studies, and spatial variation in expression, which makes it difficult to reproduce as a reliable independent prognostic factor. Previous studies have shown that there are significant spatial variations in Ki67% expression, which may limit its clinical prognostic utility after core biopsy. These variations are most evident when examining the periphery of the tumor vs. the core. To date, prediction of Ki67% expression from quantitative image analysis of DCE-MRI is very limited. This work presents a novel computer aided diagnosis framework to use textural kinetics to (i) predict the ratio of periphery Ki67% expression to core Ki67% expression, and (ii) predict Ki67% expression from individual tumor habitats. The pilot cohort consists of T1 weighted fat saturated DCE-MR images from 17 patients. Support vector regression with a radial basis function was used for predicting the Ki67% expression and ratios. The initial results show that texture features from individual tumor habitats are more predictive of the Ki67% expression ratio and spatial Ki67% expression than features from the whole tumor. The Ki67% expression ratio could be predicted with a root mean square error (RMSE) of 1.67%. Quantitative image analysis of DCE-MRI using textural kinetic habitats, has the potential to be used as a non-invasive method for predicting Ki67 percentage and ratio, thus more accurately reporting high KI-67 expression for patient prognosis.

  17. 3D textural evidence for the formation of ultra-high tenor precious metal bearing sulphide microdroplets in offset reefs: An extreme example from the Platinova Reef, Skaergaard Intrusion, Greenland

    NASA Astrophysics Data System (ADS)

    Holwell, David A.; Barnes, Stephen J.; Le Vaillant, Margaux; Keays, Reid R.; Fisher, Louise A.; Prasser, Richard

    2016-07-01

    larger ones that liquated from magma devoid of crystals, and that were able to grow and sink. This feature is common in all offset reef deposits, and is marked by the major enrichment in Au. Although the metal ratios of PGE to Au in the Pd- and Au-rich offset zones differ, the identical textures and comparable mineralogy show the physical mechanisms of concentration are the same, indicating a similar physical method of concentration. The relative position of the Pd, Au and Cu peaks in the Platinova Reef is essentially the same as that in numerous other offset reefs, suggesting that common overarching processes are responsible for the enrichment in metals, and relative offsets in peak metal concentrations in all such deposits. The most important of these processes are their relative Dsul/sil values and the diffusivities of the metals, which determine the order of offsets and the high tenors of the smallest sulphide droplets. The Platinova Reef therefore records the extreme enrichment via equilibrium and diffusive partitioning into sulphide liquid microdroplets very close to their point of nucleation.

  18. Association of computerized texture features on MRI with early treatment response following laser ablation for neuropathic cancer pain: preliminary findings.

    PubMed

    Tiwari, Pallavi; Danish, Shabbar F; Jiang, Benjamin; Madabhushi, Anant

    2015-10-01

    was considered. Our quantitative approach first involved intensity standardization to allow for grayscale MR intensities acquired pre- and post-LITT to have a fixed tissue-specific meaning within the same imaging protocol, the same body region, and within the same patient. An affine registration was then performed on individual post-LITT MRI protocols to a reference MRI protocol pre-LITT. A total of 78 computerized texture features (co-occurrence matrix homogeneity, neighboring gray-level dependence matrix, Gabor) are then extracted from pre- and post-LITT MP-MRI on a per-voxel basis. Quantitative, voxelwise comparison of the changes in MRI texture features between pre- and post-LITT MRI indicate that (a) Gabor texture features at specific orientations were highly sensitive as well as specific in predicting subtle microarchitectural changes within and around the ablation zone pre- and post-LITT, (b) FLAIR was identified as the most sensitive MRI protocol in identifying early treatment changes yielding a normalized percentage change of 360% within the ablation zone relative to its pre-LITT value, and (c) GRE was identified as the most sensitive MRI protocol in quantifying changes outside the ablation zone post-LITT. Our preliminary results thus indicate potential for noninvasive computerized MP-MRI features over volumetric features in determining localized microarchitectural early focal treatment changes post-LITT for neuropathic cancer pain treatment. PMID:26870745

  19. Structured Light-Based 3D Reconstruction System for Plants.

    PubMed

    Nguyen, Thuy Tuong; Slaughter, David C; Max, Nelson; Maloof, Julin N; Sinha, Neelima

    2015-07-29

    Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants. This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces) and software algorithms (including the proposed 3D point cloud registration and plant feature measurement). This paper demonstrates the ability to produce 3D models of whole plants created from multiple pairs of stereo images taken at different viewing angles, without the need to destructively cut away any parts of a plant. The ability to accurately predict phenotyping features, such as the number of leaves, plant height, leaf size and internode distances, is also demonstrated. Experimental results show that, for plants having a range of leaf sizes and a distance between leaves appropriate for the hardware design, the algorithms successfully predict phenotyping features in the target crops, with a recall of 0.97 and a precision of 0.89 for leaf detection and less than a 13-mm error for plant size, leaf size and internode distance.

  20. Structured Light-Based 3D Reconstruction System for Plants

    PubMed Central

    Nguyen, Thuy Tuong; Slaughter, David C.; Max, Nelson; Maloof, Julin N.; Sinha, Neelima

    2015-01-01

    Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants.This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces) and software algorithms (including the proposed 3D point cloud registration and plant feature measurement). This paper demonstrates the ability to produce 3D models of whole plants created from multiple pairs of stereo images taken at different viewing angles, without the need to destructively cut away any parts of a plant. The ability to accurately predict phenotyping features, such as the number of leaves, plant height, leaf size and internode distances, is also demonstrated. Experimental results show that, for plants having a range of leaf sizes and a distance between leaves appropriate for the hardware design, the algorithms successfully predict phenotyping features in the target crops, with a recall of 0.97 and a precision of 0.89 for leaf detection and less than a 13-mm error for plant size, leaf size and internode distance. PMID:26230701

  1. Visual texture for automated characterisation of geological features in borehole televiewer imagery

    NASA Astrophysics Data System (ADS)

    Al-Sit, Waleed; Al-Nuaimy, Waleed; Marelli, Matteo; Al-Ataby, Ali

    2015-08-01

    Detailed characterisation of the structure of subsurface fractures is greatly facilitated by digital borehole logging instruments, the interpretation of which is typically time-consuming and labour-intensive. Despite recent advances towards autonomy and automation, the final interpretation remains heavily dependent on the skill, experience, alertness and consistency of a human operator. Existing computational tools fail to detect layers between rocks that do not exhibit distinct fracture boundaries, and often struggle characterising cross-cutting layers and partial fractures. This paper presents a novel approach to the characterisation of planar rock discontinuities from digital images of borehole logs. Multi-resolution texture segmentation and pattern recognition techniques utilising Gabor filters are combined with an iterative adaptation of the Hough transform to enable non-distinct, partial, distorted and steep fractures and layers to be accurately identified and characterised in a fully automated fashion. This approach has successfully detected fractures and layers with high detection accuracy and at a relatively low computational cost.

  2. Image based 3D city modeling : Comparative study

    NASA Astrophysics Data System (ADS)

    Singh, S. P.; Jain, K.; Mandla, V. R.

    2014-06-01

    3D city model is a digital representation of the Earth's surface and it's related objects such as building, tree, vegetation, and some manmade feature belonging to urban area. The demand of 3D city modeling is increasing rapidly for various engineering and non-engineering applications. Generally four main image based approaches were used for virtual 3D city models generation. In first approach, researchers were used Sketch based modeling, second method is Procedural grammar based modeling, third approach is Close range photogrammetry based modeling and fourth approach is mainly based on Computer Vision techniques. SketchUp, CityEngine, Photomodeler and Agisoft Photoscan are the main softwares to represent these approaches respectively. These softwares have different approaches & methods suitable for image based 3D city modeling. Literature study shows that till date, there is no complete such type of comparative study available to create complete 3D city model by using images. This paper gives a comparative assessment of these four image based 3D modeling approaches. This comparative study is mainly based on data acquisition methods, data processing techniques and output 3D model products. For this research work, study area is the campus of civil engineering department, Indian Institute of Technology, Roorkee (India). This 3D campus acts as a prototype for city. This study also explains various governing parameters, factors and work experiences. This research work also gives a brief introduction, strengths and weakness of these four image based techniques. Some personal comment is also given as what can do or what can't do from these softwares. At the last, this study shows; it concluded that, each and every software has some advantages and limitations. Choice of software depends on user requirements of 3D project. For normal visualization project, SketchUp software is a good option. For 3D documentation record, Photomodeler gives good result. For Large city

  3. Virtual 3d City Modeling: Techniques and Applications

    NASA Astrophysics Data System (ADS)

    Singh, S. P.; Jain, K.; Mandla, V. R.

    2013-08-01

    3D city model is a digital representation of the Earth's surface and it's related objects such as Building, Tree, Vegetation, and some manmade feature belonging to urban area. There are various terms used for 3D city models such as "Cybertown", "Cybercity", "Virtual City", or "Digital City". 3D city models are basically a computerized or digital model of a city contains the graphic representation of buildings and other objects in 2.5 or 3D. Generally three main Geomatics approach are using for Virtual 3-D City models generation, in first approach, researcher are using Conventional techniques such as Vector Map data, DEM, Aerial images, second approach are based on High resolution satellite images with LASER scanning, In third method, many researcher are using Terrestrial images by using Close Range Photogrammetry with DSM & Texture mapping. We start this paper from the introduction of various Geomatics techniques for 3D City modeling. These techniques divided in to two main categories: one is based on Automation (Automatic, Semi-automatic and Manual methods), and another is Based on Data input techniques (one is Photogrammetry, another is Laser Techniques). After details study of this, finally in short, we are trying to give the conclusions of this study. In the last, we are trying to give the conclusions of this research paper and also giving a short view for justification and analysis, and present trend for 3D City modeling. This paper gives an overview about the Techniques related with "Generation of Virtual 3-D City models using Geomatics Techniques" and the Applications of Virtual 3D City models. Photogrammetry, (Close range, Aerial, Satellite), Lasergrammetry, GPS, or combination of these modern Geomatics techniques play a major role to create a virtual 3-D City model. Each and every techniques and method has some advantages and some drawbacks. Point cloud model is a modern trend for virtual 3-D city model. Photo-realistic, Scalable, Geo-referenced virtual 3

  4. Europeana and 3D

    NASA Astrophysics Data System (ADS)

    Pletinckx, D.

    2011-09-01

    The current 3D hype creates a lot of interest in 3D. People go to 3D movies, but are we ready to use 3D in our homes, in our offices, in our communication? Are we ready to deliver real 3D to a general public and use interactive 3D in a meaningful way to enjoy, learn, communicate? The CARARE project is realising this for the moment in the domain of monuments and archaeology, so that real 3D of archaeological sites and European monuments will be available to the general public by 2012. There are several aspects to this endeavour. First of all is the technical aspect of flawlessly delivering 3D content over all platforms and operating systems, without installing software. We have currently a working solution in PDF, but HTML5 will probably be the future. Secondly, there is still little knowledge on how to create 3D learning objects, 3D tourist information or 3D scholarly communication. We are still in a prototype phase when it comes to integrate 3D objects in physical or virtual museums. Nevertheless, Europeana has a tremendous potential as a multi-facetted virtual museum. Finally, 3D has a large potential to act as a hub of information, linking to related 2D imagery, texts, video, sound. We describe how to create such rich, explorable 3D objects that can be used intuitively by the generic Europeana user and what metadata is needed to support the semantic linking.

  5. Dynamics of magma supply at Mt. Etna volcano (Southern Italy) as revealed by textural and compositional features of plagioclase phenocrysts

    NASA Astrophysics Data System (ADS)

    Viccaro, Marco; Giacomoni, Pier Paolo; Ferlito, Carmelo; Cristofolini, Renato

    2010-04-01

    second, An decrease at effectively constant FeO contents may indicate crystallization at a high level of undercooling from already degassed magma, followed by rapid quenching; such a feature might be acquired during syn- or post-eruptive conditions. Although textures found in historic lavas are rather similar to those in the recent ones, some differences occur, such as lack of crystals with patchy cores in recent products and lower An contents in crystals of historic ones. The available data allowed us to obtain information on the dynamics of the feeding system, highlighting their possible modifications over time. In particular, historically erupted magmas, generally acknowledged to be volatile-poor, may have ascended through the deep portions of the plumbing system under H 2O-undersaturated conditions at lower rates than the recent ones, recognized as more volatile-rich. Eruption triggering mechanisms from closed reservoirs in the shallow portions of the feeding system are similar for both historic and recent events, and may be generally favoured by a recharging phase of more primitive, undegassed magma or by a few episodes of important fracture opening (e.g., in response to an earthquake swarm).

  6. 3D light scanning macrography.

    PubMed

    Huber, D; Keller, M; Robert, D

    2001-08-01

    The technique of 3D light scanning macrography permits the non-invasive surface scanning of small specimens at magnifications up to 200x. Obviating both the problem of limited depth of field inherent to conventional close-up macrophotography and the metallic coating required by scanning electron microscopy, 3D light scanning macrography provides three-dimensional digital images of intact specimens without the loss of colour, texture and transparency information. This newly developed technique offers a versatile, portable and cost-efficient method for the non-invasive digital and photographic documentation of small objects. Computer controlled device operation and digital image acquisition facilitate fast and accurate quantitative morphometric investigations, and the technique offers a broad field of research and educational applications in biological, medical and materials sciences. PMID:11489078

  7. PLOT3D/AMES, APOLLO UNIX VERSION USING GMR3D (WITHOUT TURB3D)

    NASA Technical Reports Server (NTRS)

    Buning, P.

    1994-01-01

    PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into

  8. PLOT3D/AMES, APOLLO UNIX VERSION USING GMR3D (WITH TURB3D)

    NASA Technical Reports Server (NTRS)

    Buning, P.

    1994-01-01

    PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into

  9. Unassisted 3D camera calibration

    NASA Astrophysics Data System (ADS)

    Atanassov, Kalin; Ramachandra, Vikas; Nash, James; Goma, Sergio R.

    2012-03-01

    With the rapid growth of 3D technology, 3D image capture has become a critical part of the 3D feature set on mobile phones. 3D image quality is affected by the scene geometry as well as on-the-device processing. An automatic 3D system usually assumes known camera poses accomplished by factory calibration using a special chart. In real life settings, pose parameters estimated by factory calibration can be negatively impacted by movements of the lens barrel due to shaking, focusing, or camera drop. If any of these factors displaces the optical axes of either or both cameras, vertical disparity might exceed the maximum tolerable margin and the 3D user may experience eye strain or headaches. To make 3D capture more practical, one needs to consider unassisted (on arbitrary scenes) calibration. In this paper, we propose an algorithm that relies on detection and matching of keypoints between left and right images. Frames containing erroneous matches, along with frames with insufficiently rich keypoint constellations, are detected and discarded. Roll, pitch yaw , and scale differences between left and right frames are then estimated. The algorithm performance is evaluated in terms of the remaining vertical disparity as compared to the maximum tolerable vertical disparity.

  10. Combining Spectral and Texture Features Using Random Forest Algorithm: Extracting Impervious Surface Area in Wuhan

    NASA Astrophysics Data System (ADS)

    Shao, Zhenfeng; Zhang, Yuan; Zhang, Lei; Song, Yang; Peng, Minjun

    2016-06-01

    Impervious surface area (ISA) is one of the most important indicators of urban environments. At present, based on multi-resolution remote sensing images, numerous approaches have been proposed to extract impervious surface, using statistical estimation, sub-pixel classification and spectral mixture analysis method of sub-pixel analysis. Through these methods, impervious surfaces can be effectively applied to regional-scale planning and management. However, for the large scale region, high resolution remote sensing images can provide more details, and therefore they will be more conducive to analysis environmental monitoring and urban management. Since the purpose of this study is to map impervious surfaces more effectively, three classification algorithms (random forests, decision trees, and artificial neural networks) were tested for their ability to map impervious surface. Random forests outperformed the decision trees, and artificial neural networks in precision. Combining the spectral indices and texture, random forests is applied to impervious surface extraction with a producer's accuracy of 0.98, a user's accuracy of 0.97, and an overall accuracy of 0.98 and a kappa coefficient of 0.97.

  11. Computer-aided diagnosis of interstitial lung disease: a texture feature extraction and classification approach

    NASA Astrophysics Data System (ADS)

    Vargas-Voracek, Rene; McAdams, H. Page; Floyd, Carey E., Jr.

    1998-06-01

    An approach for the classification of normal or abnormal lung parenchyma from selected regions of interest (ROIs) of chest radiographs is presented for computer aided diagnosis of interstitial lung disease (ILD). The proposed approach uses a feed-forward neural network to classify each ROI based on a set of isotropic texture measures obtained from the joint grey level distribution of pairs of pixels separated by a specific distance. Two hundred ROIs, each 64 X 64 pixels in size (11 X 11 mm), were extracted from digitized chest radiographs for testing. Diagnosis performance was evaluated with the leave-one-out method. Classification of independent ROIs achieved a sensitivity of 90% and a specificity of 84% with an area under the receiver operating characteristic curve of 0.85. The diagnosis for each patient was correct for all cases when a `majority vote' criterion for the classification of the corresponding ROIs was applied to issue a normal or ILD patient classification. The proposed approach is a simple, fast, and consistent method for computer aided diagnosis of ILD with a very good performance. Further research will include additional cases, including differential diagnosis among ILD manifestations.

  12. Automatic 3D video format detection

    NASA Astrophysics Data System (ADS)

    Zhang, Tao; Wang, Zhe; Zhai, Jiefu; Doyen, Didier

    2011-03-01

    Many 3D formats exist and will probably co-exist for a long time even if 3D standards are today under definition. The support for multiple 3D formats will be important for bringing 3D into home. In this paper, we propose a novel and effective method to detect whether a video is a 3D video or not, and to further identify the exact 3D format. First, we present how to detect those 3D formats that encode a pair of stereo images into a single image. The proposed method detects features and establishes correspondences between features in the left and right view images, and applies the statistics from the distribution of the positional differences between corresponding features to detect the existence of a 3D format and to identify the format. Second, we present how to detect the frame sequential 3D format. In the frame sequential 3D format, the feature points are oscillating from frame to frame. Similarly, the proposed method tracks feature points over consecutive frames, computes the positional differences between features, and makes a detection decision based on whether the features are oscillating. Experiments show the effectiveness of our method.

  13. Major structural features of the northern North Sea and adjacent areas of the continent according to lithosphere-scale 3D density and thermal modelling

    NASA Astrophysics Data System (ADS)

    Maystrenko, Y. P.; Olesen, O.; Ebbing, J.

    2013-12-01

    In order to analyse the regional configuration of the crystalline crust within the northern North Sea and adjacent areas of the continent, a lithosphere-scale 3D structural model has been constructed in the frame of the Crustal Onshore-Offshore Project (COOP project). Construction of the 3D model has been done by use of recently published/released structural data. For upper part of the model, all available data were merged into the following layers: sea water, the Cenozoic, the Upper Cretaceous, the Lower Cretaceous, the Jurassic, the Triassic, the Upper Permian (Zechstein) salt, Upper Permian clastics/carbonates and, finally, the Lower Permian-pre-Permian sedimentary rocks. Configuration of the crystalline crust and the Moho topography have been constrained by the published interpretations of deep seismic lines. The lithosphere-asthenosphere boundary has been compiled from previously published data. To evaluate the deep structure of the crystalline crust, a 3D density modelling has been carried out by use of the software IGMAS+ (the Interactive Gravity and Magnetic Application System). According to the 3D density modeling, the crystalline crust of the study area consists of several layers. Within the upper crystalline crust, gabbro to anorthositic rocks have been included into the 3D model along the western coast of Norway. In addition, a low-density (2627 kg/m3) upper crustal layer is modelled beneath the Horda Platform. The next upper crustal layer is characterized by regional distribution and has a density of 2670 kg/m3. The modelled middle crust of the study area contains four layers with similar densities around 2700 kg/m3. The lower crust consists of three layers. The deepest crustal layer is the high-density lower crustal layer (3060 kg/m3) which corresponds to the high-velocity layer. This layer thickens strongly beneath the Norwegian-Danish Basin and the eastern part of the East-Shetland platform. In addition to this high-density lower crustal layer, the

  14. 3d-3d correspondence revisited

    NASA Astrophysics Data System (ADS)

    Chung, Hee-Joong; Dimofte, Tudor; Gukov, Sergei; Sułkowski, Piotr

    2016-04-01

    In fivebrane compactifications on 3-manifolds, we point out the importance of all flat connections in the proper definition of the effective 3d {N}=2 theory. The Lagrangians of some theories with the desired properties can be constructed with the help of homological knot invariants that categorify colored Jones polynomials. Higgsing the full 3d theories constructed this way recovers theories found previously by Dimofte-Gaiotto-Gukov. We also consider the cutting and gluing of 3-manifolds along smooth boundaries and the role played by all flat connections in this operation.

  15. 3d-3d correspondence revisited

    DOE PAGES

    Chung, Hee -Joong; Dimofte, Tudor; Gukov, Sergei; Sułkowski, Piotr

    2016-04-21

    In fivebrane compactifications on 3-manifolds, we point out the importance of all flat connections in the proper definition of the effective 3d N = 2 theory. The Lagrangians of some theories with the desired properties can be constructed with the help of homological knot invariants that categorify colored Jones polynomials. Higgsing the full 3d theories constructed this way recovers theories found previously by Dimofte-Gaiotto-Gukov. As a result, we also consider the cutting and gluing of 3-manifolds along smooth boundaries and the role played by all flat connections in this operation.

  16. Identification of the Structural Features of Guanine Derivatives as MGMT Inhibitors Using 3D-QSAR Modeling Combined with Molecular Docking.

    PubMed

    Sun, Guohui; Fan, Tengjiao; Zhang, Na; Ren, Ting; Zhao, Lijiao; Zhong, Rugang

    2016-01-01

    DNA repair enzyme O⁶-methylguanine-DNA methyltransferase (MGMT), which plays an important role in inducing drug resistance against alkylating agents that modify the O⁶ position of guanine in DNA, is an attractive target for anti-tumor chemotherapy. A series of MGMT inhibitors have been synthesized over the past decades to improve the chemotherapeutic effects of O⁶-alkylating agents. In the present study, we performed a three-dimensional quantitative structure activity relationship (3D-QSAR) study on 97 guanine derivatives as MGMT inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Three different alignment methods (ligand-based, DFT optimization-based and docking-based alignment) were employed to develop reliable 3D-QSAR models. Statistical parameters derived from the models using the above three alignment methods showed that the ligand-based CoMFA (Qcv² = 0.672 and Rncv² = 0.997) and CoMSIA (Qcv² = 0.703 and Rncv² = 0.946) models were better than the other two alignment methods-based CoMFA and CoMSIA models. The two ligand-based models were further confirmed by an external test-set validation and a Y-randomization examination. The ligand-based CoMFA model (Qext² = 0.691, Rpred² = 0.738 and slope k = 0.91) was observed with acceptable external test-set validation values rather than the CoMSIA model (Qext² = 0.307, Rpred² = 0.4 and slope k = 0.719). Docking studies were carried out to predict the binding modes of the inhibitors with MGMT. The results indicated that the obtained binding interactions were consistent with the 3D contour maps. Overall, the combined results of the 3D-QSAR and the docking obtained in this study provide an insight into the understanding of the interactions between guanine derivatives and MGMT protein, which will assist in designing novel MGMT inhibitors with desired activity. PMID:27347909

  17. Identification of the Structural Features of Guanine Derivatives as MGMT Inhibitors Using 3D-QSAR Modeling Combined with Molecular Docking.

    PubMed

    Sun, Guohui; Fan, Tengjiao; Zhang, Na; Ren, Ting; Zhao, Lijiao; Zhong, Rugang

    2016-06-23

    DNA repair enzyme O⁶-methylguanine-DNA methyltransferase (MGMT), which plays an important role in inducing drug resistance against alkylating agents that modify the O⁶ position of guanine in DNA, is an attractive target for anti-tumor chemotherapy. A series of MGMT inhibitors have been synthesized over the past decades to improve the chemotherapeutic effects of O⁶-alkylating agents. In the present study, we performed a three-dimensional quantitative structure activity relationship (3D-QSAR) study on 97 guanine derivatives as MGMT inhibitors using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) methods. Three different alignment methods (ligand-based, DFT optimization-based and docking-based alignment) were employed to develop reliable 3D-QSAR models. Statistical parameters derived from the models using the above three alignment methods showed that the ligand-based CoMFA (Qcv² = 0.672 and Rncv² = 0.997) and CoMSIA (Qcv² = 0.703 and Rncv² = 0.946) models were better than the other two alignment methods-based CoMFA and CoMSIA models. The two ligand-based models were further confirmed by an external test-set validation and a Y-randomization examination. The ligand-based CoMFA model (Qext² = 0.691, Rpred² = 0.738 and slope k = 0.91) was observed with acceptable external test-set validation values rather than the CoMSIA model (Qext² = 0.307, Rpred² = 0.4 and slope k = 0.719). Docking studies were carried out to predict the binding modes of the inhibitors with MGMT. The results indicated that the obtained binding interactions were consistent with the 3D contour maps. Overall, the combined results of the 3D-QSAR and the docking obtained in this study provide an insight into the understanding of the interactions between guanine derivatives and MGMT protein, which will assist in designing novel MGMT inhibitors with desired activity.

  18. 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

  19. 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.

  20. 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.

  1. 3-D MAPPING TECHNOLOGIES FOR HIGH LEVEL WASTE TANKS

    SciTech Connect

    Marzolf, A.; Folsom, M.

    2010-08-31

    This research investigated four techniques that could be applicable for mapping of solids remaining in radioactive waste tanks at the Savannah River Site: stereo vision, LIDAR, flash LIDAR, and Structure from Motion (SfM). Stereo vision is the least appropriate technique for the solids mapping application. Although the equipment cost is low and repackaging would be fairly simple, the algorithms to create a 3D image from stereo vision would require significant further development and may not even be applicable since stereo vision works by finding disparity in feature point locations from the images taken by the cameras. When minimal variation in visual texture exists for an area of interest, it becomes difficult for the software to detect correspondences for that object. SfM appears to be appropriate for solids mapping in waste tanks. However, equipment development would be required for positioning and movement of the camera in the tank space to enable capturing a sequence of images of the scene. Since SfM requires the identification of distinctive features and associates those features to their corresponding instantiations in the other image frames, mockup testing would be required to determine the applicability of SfM technology for mapping of waste in tanks. There may be too few features to track between image frame sequences to employ the SfM technology since uniform appearance may exist when viewing the remaining solids in the interior of the waste tanks. Although scanning LIDAR appears to be an adequate solution, the expense of the equipment ($80,000-$120,000) and the need for further development to allow tank deployment may prohibit utilizing this technology. The development would include repackaging of equipment to permit deployment through the 4-inch access ports and to keep the equipment relatively uncontaminated to allow use in additional tanks. 3D flash LIDAR has a number of advantages over stereo vision, scanning LIDAR, and SfM, including full frame

  2. 3D and Education

    NASA Astrophysics Data System (ADS)

    Meulien Ohlmann, Odile

    2013-02-01

    Today the industry offers a chain of 3D products. Learning to "read" and to "create in 3D" becomes an issue of education of primary importance. 25 years professional experience in France, the United States and Germany, Odile Meulien set up a personal method of initiation to 3D creation that entails the spatial/temporal experience of the holographic visual. She will present some different tools and techniques used for this learning, their advantages and disadvantages, programs and issues of educational policies, constraints and expectations related to the development of new techniques for 3D imaging. Although the creation of display holograms is very much reduced compared to the creation of the 90ies, the holographic concept is spreading in all scientific, social, and artistic activities of our present time. She will also raise many questions: What means 3D? Is it communication? Is it perception? How the seeing and none seeing is interferes? What else has to be taken in consideration to communicate in 3D? How to handle the non visible relations of moving objects with subjects? Does this transform our model of exchange with others? What kind of interaction this has with our everyday life? Then come more practical questions: How to learn creating 3D visualization, to learn 3D grammar, 3D language, 3D thinking? What for? At what level? In which matter? for whom?

  3. Four-chamber heart modeling and automatic segmentation for 3-D cardiac CT volumes using marginal space learning and steerable features.

    PubMed

    Zheng, Yefeng; Barbu, Adrian; Georgescu, Bogdan; Scheuering, Michael; Comaniciu, Dorin

    2008-11-01

    We propose an automatic four-chamber heart segmentation system for the quantitative functional analysis of the heart from cardiac computed tomography (CT) volumes. Two topics are discussed: heart modeling and automatic model fitting to an unseen volume. Heart modeling is a nontrivial task since the heart is a complex nonrigid organ. The model must be anatomically accurate, allow manual editing, and provide sufficient information to guide automatic detection and segmentation. Unlike previous work, we explicitly represent important landmarks (such as the valves and the ventricular septum cusps) among the control points of the model. The control points can be detected reliably to guide the automatic model fitting process. Using this model, we develop an efficient and robust approach for automatic heart chamber segmentation in 3-D CT volumes. We formulate the segmentation as a two-step learning problem: anatomical structure localization and boundary delineation. In both steps, we exploit the recent advances in learning discriminative models. A novel algorithm, marginal space learning (MSL), is introduced to solve the 9-D similarity transformation search problem for localizing the heart chambers. After determining the pose of the heart chambers, we estimate the 3-D shape through learning-based boundary delineation. The proposed method has been extensively tested on the largest dataset (with 323 volumes from 137 patients) ever reported in the literature. To the best of our knowledge, our system is the fastest with a speed of 4.0 s per volume (on a dual-core 3.2-GHz processor) for the automatic segmentation of all four chambers.

  4. The 15 March 2007 paroxysm of Stromboli: video-image analysis, and textural and compositional features of the erupted deposit

    NASA Astrophysics Data System (ADS)

    Andronico, Daniele; Taddeucci, Jacopo; Cristaldi, Antonio; Miraglia, Lucia; Scarlato, Piergiorgio; Gaeta, Mario

    2013-07-01

    On 15 March 2007, a paroxysmal event occurred within the crater terrace of Stromboli, in the Aeolian Islands (Italy). Infrared and visible video recordings from the monitoring network reveal that there was a succession of highly explosive pulses, lasting about 5 min, from at least four eruptive vents. Initially, brief jets with low apparent temperature were simultaneously erupted from the three main vent regions, becoming hotter and transitioning to bomb-rich fountaining that lasted for 14 s. Field surveys estimate the corresponding fallout deposit to have a mass of ˜1.9 × 107 kg that, coupled with the video information on eruption duration, provides a mean mass eruption rate of ˜5.4 × 105 kg/s. Textural and chemical analyses of the erupted tephra reveal unexpected complexity, with grain-size bimodality in the samples associated with the different percentages of ash types (juvenile, lithics, and crystals) that reflects almost simultaneous deposition from multiple and evolving plumes. Juvenile glass chemistry ranges from a gas-rich, low porphyricity end member (typical of other paroxysmal events) to a gas-poor high porphyricity one usually associated with low-intensity Strombolian explosions. Integration of our diverse data sets reveals that (1) the 2007 event was a paroxysmal explosion driven by a magma sharing common features with large-scale paroxysms as well as with "ordinary" Strombolian explosions; (2) initial vent opening by the release of a pressurized gas slug and subsequent rapid magma vesiculation and ejection, which were recorded both by the infrared camera and in the texture of fallout products; and (3) lesser paroxysmal events can be highly dynamic and produce surprisingly complex fallout deposits, which would be difficult to interpret from the geological record alone.

  5. YouDash3D: exploring stereoscopic 3D gaming for 3D movie theaters

    NASA Astrophysics Data System (ADS)

    Schild, Jonas; Seele, Sven; Masuch, Maic

    2012-03-01

    Along with the success of the digitally revived stereoscopic cinema, events beyond 3D movies become attractive for movie theater operators, i.e. interactive 3D games. In this paper, we present a case that explores possible challenges and solutions for interactive 3D games to be played by a movie theater audience. We analyze the setting and showcase current issues related to lighting and interaction. Our second focus is to provide gameplay mechanics that make special use of stereoscopy, especially depth-based game design. Based on these results, we present YouDash3D, a game prototype that explores public stereoscopic gameplay in a reduced kiosk setup. It features live 3D HD video stream of a professional stereo camera rig rendered in a real-time game scene. We use the effect to place the stereoscopic effigies of players into the digital game. The game showcases how stereoscopic vision can provide for a novel depth-based game mechanic. Projected trigger zones and distributed clusters of the audience video allow for easy adaptation to larger audiences and 3D movie theater gaming.

  6. 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

  7. Texture based feature extraction methods for content based medical image retrieval systems.

    PubMed

    Ergen, Burhan; Baykara, Muhammet

    2014-01-01

    The developments of content based image retrieval (CBIR) systems used for image archiving are continued and one of the important research topics. Although some studies have been presented general image achieving, proposed CBIR systems for archiving of medical images are not very efficient. In presented study, it is examined the retrieval efficiency rate of spatial methods used for feature extraction for medical image retrieval systems. The investigated algorithms in this study depend on gray level co-occurrence matrix (GLCM), gray level run length matrix (GLRLM), and Gabor wavelet accepted as spatial methods. In the experiments, the database is built including hundreds of medical images such as brain, lung, sinus, and bone. The results obtained in this study shows that queries based on statistics obtained from GLCM are satisfied. However, it is observed that Gabor Wavelet has been the most effective and accurate method. PMID:25227014

  8. Texture based feature extraction methods for content based medical image retrieval systems.

    PubMed

    Ergen, Burhan; Baykara, Muhammet

    2014-01-01

    The developments of content based image retrieval (CBIR) systems used for image archiving are continued and one of the important research topics. Although some studies have been presented general image achieving, proposed CBIR systems for archiving of medical images are not very efficient. In presented study, it is examined the retrieval efficiency rate of spatial methods used for feature extraction for medical image retrieval systems. The investigated algorithms in this study depend on gray level co-occurrence matrix (GLCM), gray level run length matrix (GLRLM), and Gabor wavelet accepted as spatial methods. In the experiments, the database is built including hundreds of medical images such as brain, lung, sinus, and bone. The results obtained in this study shows that queries based on statistics obtained from GLCM are satisfied. However, it is observed that Gabor Wavelet has been the most effective and accurate method.

  9. Performance comparison of classifiers for differentiation among obstructive lung diseases based on features of texture analysis at HRCT

    NASA Astrophysics Data System (ADS)

    Lee, Youngjoo; Seo, Joon Beom; Kang, Bokyoung; Kim, Dongil; Lee, June Goo; Kim, Song Soo; Kim, Namkug; Kang, Suk Ho

    2007-03-01

    The performance of classification algorithms for differentiating among obstructive lung diseases based on features from texture analysis using HRCT (High Resolution Computerized Tomography) images was compared. HRCT can provide accurate information for the detection of various obstructive lung diseases, including centrilobular emphysema, panlobular emphysema and bronchiolitis obliterans. Features on HRCT images can be subtle, however, particularly in the early stages of disease, and image-based diagnosis is subject to inter-observer variation. To automate the diagnosis and improve the accuracy, we compared three types of automated classification systems, naÃve Bayesian classifier, ANN (Artificial Neural Net) and SVM (Support Vector Machine), based on their ability to differentiate among normal lung and three types of obstructive lung diseases. To assess the performance and cross-validation of these three classifiers, 5 folding methods with 5 randomly chosen groups were used. For a more robust result, each validation was repeated 100 times. SVM showed the best performance, with 86.5% overall sensitivity, significantly different from the other classifiers (one way ANOVA, p<0.01). We address the characteristics of each classifier affecting performance and the issue of which classifier is the most suitable for clinical applications, and propose an appropriate method to choose the best classifier and determine its optimal parameters for optimal disease discrimination. These results can be applied to classifiers for differentiation of other diseases.

  10. The SeqFEATURE library of 3D functional site models: comparison to existing methods and applications to protein function annotation

    PubMed Central

    Wu, Shirley; Liang, Mike P; Altman, Russ B

    2008-01-01

    Structural genomics efforts have led to increasing numbers of novel, uncharacterized protein structures with low sequence identity to known proteins, resulting in a growing need for structure-based function recognition tools. Our method, SeqFEATURE, robustly models protein functions described by sequence motifs using a structural representation. We built a library of models that shows good performance compared to other methods. In particular, SeqFEATURE demonstrates significant improvement over other methods when sequence and structural similarity are low. PMID:18197987

  11. Prominent rocks - 3D

    NASA Technical Reports Server (NTRS)

    1997-01-01

    Many prominent rocks near the Sagan Memorial Station are featured in this image, taken in stereo by the Imager for Mars Pathfinder (IMP) on Sol 3. 3D glasses are necessary to identify surface detail. Wedge is at lower left; Shark, Half-Dome, and Pumpkin are at center. Flat Top, about four inches high, is at lower right. The horizon in the distance is one to two kilometers away.

    Mars Pathfinder is the second in NASA's Discovery program of low-cost spacecraft with highly focused science goals. The Jet Propulsion Laboratory, Pasadena, CA, developed and manages the Mars Pathfinder mission for NASA's Office of Space Science, Washington, D.C. JPL is an operating division of the California Institute of Technology (Caltech). The Imager for Mars Pathfinder (IMP) was developed by the University of Arizona Lunar and Planetary Laboratory under contract to JPL. Peter Smith is the Principal Investigator.

    Click below to see the left and right views individually. [figure removed for brevity, see original site] Left [figure removed for brevity, see original site] Right

  12. Intelligent speckle reducing anisotropic diffusion algorithm for automated 3-D ultrasound images.

    PubMed

    Wu, Jun; Wang, Yuanyuan; Yu, Jinhua; Shi, Xinling; Zhang, Junhua; Chen, Yue; Pang, Yun

    2015-02-01

    A novel 3-D filtering method is presented for speckle reduction and detail preservation in automated 3-D ultrasound images. First, texture features of an image are analyzed by using the improved quadtree (QT) decomposition. Then, the optimal homogeneous and the obvious heterogeneous regions are selected from QT decomposition results. Finally, diffusion parameters and diffusion process are automatically decided based on the properties of these two selected regions. The computing time needed for 2-D speckle reduction is very short. However, the computing time required for 3-D speckle reduction is often hundreds of times longer than 2-D speckle reduction. This may limit its potential application in practice. Because this new filter can adaptively adjust the time step of iteration, the computation time is reduced effectively. Both synthetic and real 3-D ultrasound images are used to evaluate the proposed filter. It is shown that this filter is superior to other methods in both practicality and efficiency. PMID:26366596

  13. 3D Imaging.

    ERIC Educational Resources Information Center

    Hastings, S. K.

    2002-01-01

    Discusses 3 D imaging as it relates to digital representations in virtual library collections. Highlights include X-ray computed tomography (X-ray CT); the National Science Foundation (NSF) Digital Library Initiatives; output peripherals; image retrieval systems, including metadata; and applications of 3 D imaging for libraries and museums. (LRW)

  14. A new approach towards image based virtual 3D city modeling by using close range photogrammetry

    NASA Astrophysics Data System (ADS)

    Singh, S. P.; Jain, K.; Mandla, V. R.

    2014-05-01

    3D city model is a digital representation of the Earth's surface and it's related objects such as building, tree, vegetation, and some manmade feature belonging to urban area. The demand of 3D city modeling is increasing day to day for various engineering and non-engineering applications. Generally three main image based approaches are using for virtual 3D city models generation. In first approach, researchers used Sketch based modeling, second method is Procedural grammar based modeling and third approach is Close range photogrammetry based modeling. Literature study shows that till date, there is no complete solution available to create complete 3D city model by using images. These image based methods also have limitations This paper gives a new approach towards image based virtual 3D city modeling by using close range photogrammetry. This approach is divided into three sections. First, data acquisition process, second is 3D data processing, and third is data combination process. In data acquisition process, a multi-camera setup developed and used for video recording of an area. Image frames created from video data. Minimum required and suitable video image frame selected for 3D processing. In second section, based on close range photogrammetric principles and computer vision techniques, 3D model of area created. In third section, this 3D model exported to adding and merging of other pieces of large area. Scaling and alignment of 3D model was done. After applying the texturing and rendering on this model, a final photo-realistic textured 3D model created. This 3D model transferred into walk-through model or in movie form. Most of the processing steps are automatic. So this method is cost effective and less laborious. Accuracy of this model is good. For this research work, study area is the campus of department of civil engineering, Indian Institute of Technology, Roorkee. This campus acts as a prototype for city. Aerial photography is restricted in many country

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

    SciTech Connect

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

    2015-06-15

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

  16. Approach to Constructing 3d Virtual Scene of Irrigation Area Using Multi-Source Data

    NASA Astrophysics Data System (ADS)

    Cheng, S.; Dou, M.; Wang, J.; Zhang, S.; Chen, X.

    2015-10-01

    For an irrigation area that is often complicated by various 3D artificial ground features and natural environment, disadvantages of traditional 2D GIS in spatial data representation, management, query, analysis and visualization is becoming more and more evident. Building a more realistic 3D virtual scene is thus especially urgent for irrigation area managers and decision makers, so that they can carry out various irrigational operations lively and intuitively. Based on previous researchers' achievements, a simple, practical and cost-effective approach was proposed in this study, by adopting3D geographic information system (3D GIS), remote sensing (RS) technology. Based on multi-source data such as Google Earth (GE) high-resolution remote sensing image, ASTER G-DEM, hydrological facility maps and so on, 3D terrain model and ground feature models were created interactively. Both of the models were then rendered with texture data and integrated under ArcGIS platform. A vivid, realistic 3D virtual scene of irrigation area that has a good visual effect and possesses primary GIS functions about data query and analysis was constructed.Yet, there is still a long way to go for establishing a true 3D GIS for the irrigation are: issues of this study were deeply discussed and future research direction was pointed out in the end of the paper.

  17. Designing 3D Mesenchymal Stem Cell Sheets Merging Magnetic and Fluorescent Features: When Cell Sheet Technology Meets Image-Guided Cell Therapy

    PubMed Central

    Rahmi, Gabriel; Pidial, Laetitia; Silva, Amanda K. A.; Blondiaux, Eléonore; Meresse, Bertrand; Gazeau, Florence; Autret, Gwennhael; Balvay, Daniel; Cuenod, Charles André; Perretta, Silvana; Tavitian, Bertrand; Wilhelm, Claire; Cellier, Christophe; Clément, Olivier

    2016-01-01

    Cell sheet technology opens new perspectives in tissue regeneration therapy by providing readily implantable, scaffold-free 3D tissue constructs. Many studies have focused on the therapeutic effects of cell sheet implantation while relatively little attention has concerned the fate of the implanted cells in vivo. The aim of the present study was to track longitudinally the cells implanted in the cell sheets in vivo in target tissues. To this end we (i) endowed bone marrow-derived mesenchymal stem cells (BMMSCs) with imaging properties by double labeling with fluorescent and magnetic tracers, (ii) applied BMMSC cell sheets to a digestive fistula model in mice, (iii) tracked the BMMSC fate in vivo by MRI and probe-based confocal laser endomicroscopy (pCLE), and (iv) quantified healing of the fistula. We show that image-guided longitudinal follow-up can document both the fate of the cell sheet-derived BMMSCs and their healing capacity. Moreover, our theranostic approach informs on the mechanism of action, either directly by integration of cell sheet-derived BMMSCs into the host tissue or indirectly through the release of signaling molecules in the host tissue. Multimodal imaging and clinical evaluation converged to attest that cell sheet grafting resulted in minimal clinical inflammation, improved fistula healing, reduced tissue fibrosis and enhanced microvasculature density. At the molecular level, cell sheet transplantation induced an increase in the expression of anti-inflammatory cytokines (TGF-ß2 and IL-10) and host intestinal growth factors involved in tissue repair (EGF and VEGF). Multimodal imaging is useful for tracking cell sheets and for noninvasive follow-up of their regenerative properties. PMID:27022420

  18. Flow visualization using moving textures

    SciTech Connect

    Max, N.; Becker, B.

    1995-04-01

    An intuitive way to visualize a flow is to watch particles or textures move in the flow. In this paper, the authors show how texture mapping hardware can produce near-real-time texture motion, using a polygon grid, and one fixed texture. However, the authors make no attempt to indicate the flow direction in a still frame. As discussed here, any anisotropic stretching comes from the velocity gradient, not the velocity itself. The basic idea is to advect the texture by the flow field. In a cited paper, they gave an indication of the wind velocity by advecting the 3D texture coordinates on the polygon vertices of a cloudiness contour surface in a climate simulation. This was slow, because the 3D texture was rendered in software, and because advecting the texture was difficult for time-varying flows. In this paper, they replace the 3D textures by 2D texture maps compatible with hardware rendering, and give techniques for handling time-varying flows more efficiently. The next section gives their technique for the case of 2D steady flows, and the following one discusses the problems of texture distortion. Then they discuss the problems with extending method to time-varying flows, and two solutions. Next they develop compositing methods for visualizing 3D flows. The final section gives their results and conclusions.

  19. Complete 3D model reconstruction from multiple views

    NASA Astrophysics Data System (ADS)

    Lin, Huei-Yung; Subbarao, Murali; Park, Soon-Yong

    2002-02-01

    New algorithms are presented for automatically acquiring the complete 3D model of single and multiple objects using rotational stereo. The object is placed on a rotation stage. Stereo images for several viewing directions are taken by rotating the object by known angles. Partial 3D shapes and the corresponding texture maps are obtained using rotational stereo and shape from focus. First, for each view, shape from focus is used to obtain a rough 3D shape and the corresponding focused image. Then, the rough 3D shape and focused images are used in rotational stereo to obtain a more accurate measurement of 3D shape. The rotation axis is calibrated using three fixed points on a planar object and refined during surface integration. The complete 3D model is reconstructed by integrating partial 3D shapes and the corresponding texture maps of the object from multiple views. New algorithms for range image registration, surface integration and texture mapping are presented. Our method can generate 3D models very fast and preserve the texture of objects. A new prototype vision system named Stonybrook VIsion System 2 (SVIS-2) has been built and used in the experiments. In the experiments, 4 viewing directions at 90-degree intervals are used. SVIS-2 can acquire the 3D model of objects within a 250 mm x 250 mm x 250 mm cubic workspace placed about 750 mm from the camera. Both computational algorithms and experimental results on several objects are presented.

  20. Case study: Beauty and the Beast 3D: benefits of 3D viewing for 2D to 3D conversion

    NASA Astrophysics Data System (ADS)

    Handy Turner, Tara

    2010-02-01

    From the earliest stages of the Beauty and the Beast 3D conversion project, the advantages of accurate desk-side 3D viewing was evident. While designing and testing the 2D to 3D conversion process, the engineering team at Walt Disney Animation Studios proposed a 3D viewing configuration that not only allowed artists to "compose" stereoscopic 3D but also improved efficiency by allowing artists to instantly detect which image features were essential to the stereoscopic appeal of a shot and which features had minimal or even negative impact. At a time when few commercial 3D monitors were available and few software packages provided 3D desk-side output, the team designed their own prototype devices and collaborated with vendors to create a "3D composing" workstation. This paper outlines the display technologies explored, final choices made for Beauty and the Beast 3D, wish-lists for future development and a few rules of thumb for composing compelling 2D to 3D conversions.

  1. A Novel 3D Building Damage Detection Method Using Multiple Overlapping UAV Images

    NASA Astrophysics Data System (ADS)

    Sui, H.; Tu, J.; Song, Z.; Chen, G.; Li, Q.

    2014-09-01

    In this paper, a novel approach is presented that applies multiple overlapping UAV imagesto building damage detection. Traditional building damage detection method focus on 2D changes detection (i.e., those only in image appearance), whereas the 2D information delivered by the images is often not sufficient and accurate when dealing with building damage detection. Therefore the detection of building damage in 3D feature of scenes is desired. The key idea of 3D building damage detection is the 3D Change Detection using 3D point cloud obtained from aerial images through Structure from motion (SFM) techniques. The approach of building damage detection discussed in this paper not only uses the height changes of 3D feature of scene but also utilizes the image's shape and texture feature. Therefore, this method fully combines the 2D and 3D information of the real world to detect the building damage. The results, tested through field study, demonstrate that this method is feasible and effective in building damage detection. It has also shown that the proposed method is easily applicable and suited well for rapid damage assessment after natural disasters.

  2. Comments on the paper 'A novel 3D wavelet-based filter forvisualizing features in noisy biological data', by Moss et al.

    SciTech Connect

    Luengo Hendriks, Cris L.; Knowles, David W.

    2006-02-04

    Moss et al.(2005) describe, in a recent paper, a filter thatthey use to detect lines. We noticed that the wavelet on which thisfilter is based is a difference of uniform filters. This filter is anapproximation to the second derivative operator, which is commonlyimplemented as the Laplace of Gaussian (or Marr-Hildreth) operator (Marr&Hildreth, 1980; Jahne, 2002), Figure 1. We have compared Moss'filter with 1) the Laplace of Gaussian operator, 2) an approximation ofthe Laplace of Gaussian using uniform filters, and 3) a few common noisereduction filters. The Laplace-like operators detect lines by suppressingimage features both larger and smaller than the filter size. The noisereduction filters only suppress image features smaller than the filtersize. By estimating the signal to noise ratio (SNR) and mean squaredifference (MSD) of the filtered results, we found that the filterproposed by Moss et al. does not outperform the Laplace of Gaussianoperator. We also found that for images with extreme noise content, linedetection filters perform better than the noise reduction filters whentrying to enhance line structures. In less extreme cases of noise, thestandard noise reduction filters perform significantly better than boththe Laplace of Gaussian and Moss' filter.

  3. Robust 3D reconstruction with an RGB-D camera.

    PubMed

    Wang, Kangkan; Zhang, Guofeng; Bao, Hujun

    2014-11-01

    We present a novel 3D reconstruction approach using a low-cost RGB-D camera such as Microsoft Kinect. Compared with previous methods, our scanning system can work well in challenging cases where there are large repeated textures and significant depth missing problems. For robust registration, we propose to utilize both visual and geometry features and combine SFM technique to enhance the robustness of feature matching and camera pose estimation. In addition, a novel prior-based multicandidates RANSAC is introduced to efficiently estimate the model parameters and significantly speed up the camera pose estimation under multiple correspondence candidates. Even when serious depth missing occurs, our method still can successfully register all frames together. Loop closure also can be robustly detected and handled to eliminate the drift problem. The missing geometry can be completed by combining multiview stereo and mesh deformation techniques. A variety of challenging examples demonstrate the effectiveness of the proposed approach.

  4. 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.

  5. 3D PDF - a means of public access to geological 3D - objects, using the example of GTA3D

    NASA Astrophysics Data System (ADS)

    Slaby, Mark-Fabian; Reimann, Rüdiger

    2013-04-01

    In geology, 3D modeling has become very important. In the past, two-dimensional data such as isolines, drilling profiles, or cross-sections based on those, were used to illustrate the subsurface geology, whereas now, we can create complex digital 3D models. These models are produced with special software, such as GOCAD ®. The models can be viewed, only through the software used to create them, or through viewers available for free. The platform-independent PDF (Portable Document Format), enforced by Adobe, has found a wide distribution. This format has constantly evolved over time. Meanwhile, it is possible to display CAD data in an Adobe 3D PDF file with the free Adobe Reader (version 7). In a 3D PDF, a 3D model is freely rotatable and can be assembled from a plurality of objects, which can thus be viewed from all directions on their own. In addition, it is possible to create moveable cross-sections (profiles), and to assign transparency to the objects. Based on industry-standard CAD software, 3D PDFs can be generated from a large number of formats, or even be exported directly from this software. In geoinformatics, different approaches to creating 3D PDFs exist. The intent of the Authority for Mining, Energy and Geology to allow free access to the models of the Geotectonic Atlas (GTA3D), could not be realized with standard software solutions. A specially designed code converts the 3D objects to VRML (Virtual Reality Modeling Language). VRML is one of the few formats that allow using image files (maps) as textures, and to represent colors and shapes correctly. The files were merged in Acrobat X Pro, and a 3D PDF was generated subsequently. A topographic map, a display of geographic directions and horizontal and vertical scales help to facilitate the use.

  6. Specific features of insulator-metal transitions under high pressure in crystals with spin crossovers of 3d ions in tetrahedral environment

    SciTech Connect

    Lobach, K. A. Ovchinnikov, S. G.; Ovchinnikova, T. M.

    2015-01-15

    For Mott insulators with tetrahedral environment, the effective Hubbard parameter U{sub eff} is obtained as a function of pressure. This function is not universal. For crystals with d{sup 5} configuration, the spin crossover suppresses electron correlations, while for d{sup 4} configurations, the parameter U{sub eff} increases after a spin crossover. For d{sup 2} and d{sup 7} configurations, U{sub eff} increases with pressure in the high-spin (HS) state and is saturated after the spin crossover. Characteristic features of the insulator-metal transition are considered as pressure increases; it is shown that there may exist cascades of several transitions for various configurations.

  7. TACO3D. 3-D Finite Element Heat Transfer Code

    SciTech Connect

    Mason, W.E.

    1992-03-04

    TACO3D is a three-dimensional, finite-element program for heat transfer analysis. An extension of the two-dimensional TACO program, it can perform linear and nonlinear analyses and can be used to solve either transient or steady-state problems. The program accepts time-dependent or temperature-dependent material properties, and materials may be isotropic or orthotropic. A variety of time-dependent and temperature-dependent boundary conditions and loadings are available including temperature, flux, convection, and radiation boundary conditions and internal heat generation. Additional specialized features treat enclosure radiation, bulk nodes, and master/slave internal surface conditions (e.g., contact resistance). Data input via a free-field format is provided. A user subprogram feature allows for any type of functional representation of any independent variable. A profile (bandwidth) minimization option is available. The code is limited to implicit time integration for transient solutions. TACO3D has no general mesh generation capability. Rows of evenly-spaced nodes and rows of sequential elements may be generated, but the program relies on separate mesh generators for complex zoning. TACO3D does not have the ability to calculate view factors internally. Graphical representation of data in the form of time history and spatial plots is provided through links to the POSTACO and GRAPE postprocessor codes.

  8. Alignment of 3D Building Models and TIR Video Sequences with Line Tracking

    NASA Astrophysics Data System (ADS)

    Iwaszczuk, D.; Stilla, U.

    2014-11-01

    Thermal infrared imagery of urban areas became interesting for urban climate investigations and thermal building inspections. Using a flying platform such as UAV or a helicopter for the acquisition and combining the thermal data with the 3D building models via texturing delivers a valuable groundwork for large-area building inspections. However, such thermal textures are useful for further analysis if they are geometrically correctly extracted. This can be achieved with a good coregistrations between the 3D building models and thermal images, which cannot be achieved by direct georeferencing. Hence, this paper presents methodology for alignment of 3D building models and oblique TIR image sequences taken from a flying platform. In a single image line correspondences between model edges and image line segments are found using accumulator approach and based on these correspondences an optimal camera pose is calculated to ensure the best match between the projected model and the image structures. Among the sequence the linear features are tracked based on visibility prediction. The results of the proposed methodology are presented using a TIR image sequence taken from helicopter in a densely built-up urban area. The novelty of this work is given by employing the uncertainty of the 3D building models and by innovative tracking strategy based on a priori knowledge from the 3D building model and the visibility checking.

  9. Lung nodule detection using 3D convolutional neural networks trained on weakly labeled data

    NASA Astrophysics Data System (ADS)

    Anirudh, Rushil; Thiagarajan, Jayaraman J.; Bremer, Timo; Kim, Hyojin

    2016-03-01

    Early detection of lung nodules is currently the one of the most effective ways to predict and treat lung cancer. As a result, the past decade has seen a lot of focus on computer aided diagnosis (CAD) of lung nodules, whose goal is to efficiently detect, segment lung nodules and classify them as being benign or malignant. Effective detection of such nodules remains a challenge due to their arbitrariness in shape, size and texture. In this paper, we propose to employ 3D convolutional neural networks (CNN) to learn highly discriminative features for nodule detection in lieu of hand-engineered ones such as geometric shape or texture. While 3D CNNs are promising tools to model the spatio-temporal statistics of data, they are limited by their need for detailed 3D labels, which can be prohibitively expensive when compared obtaining 2D labels. Existing CAD methods rely on obtaining detailed labels for lung nodules, to train models, which is also unrealistic and time consuming. To alleviate this challenge, we propose a solution wherein the expert needs to provide only a point label, i.e., the central pixel of of the nodule, and its largest expected size. We use unsupervised segmentation to grow out a 3D region, which is used to train the CNN. Using experiments on the SPIE-LUNGx dataset, we show that the network trained using these weak labels can produce reasonably low false positive rates with a high sensitivity, even in the absence of accurate 3D labels.

  10. 3D photo mosaicing of Tagiri shallow vent field by an autonomous underwater vehicle (3rd report) - Mosaicing method based on navigation data and visual features -

    NASA Astrophysics Data System (ADS)

    Maki, Toshihiro; Ura, Tamaki; Singh, Hanumant; Sakamaki, Takashi

    Large-area seafloor imaging will bring significant benefits to various fields such as academics, resource survey, marine development, security, and search-and-rescue. The authors have proposed a navigation method of an autonomous underwater vehicle for seafloor imaging, and verified its performance through mapping tubeworm colonies with the area of 3,000 square meters using the AUV Tri-Dog 1 at Tagiri vent field, Kagoshima bay in Japan (Maki et al., 2008, 2009). This paper proposes a post-processing method to build a natural photo mosaic from a number of pictures taken by an underwater platform. The method firstly removes lens distortion, invariances of color and lighting from each image, and then ortho-rectification is performed based on camera pose and seafloor estimated by navigation data. The image alignment is based on both navigation data and visual characteristics, implemented as an expansion of the image based method (Pizarro et al., 2003). Using the two types of information realizes an image alignment that is consistent both globally and locally, as well as making the method applicable to data sets with little visual keys. The method was evaluated using a data set obtained by the AUV Tri-Dog 1 at the vent field in Sep. 2009. A seamless, uniformly illuminated photo mosaic covering the area of around 500 square meters was created from 391 pictures, which covers unique features of the field such as bacteria mats and tubeworm colonies.

  11. Identifying metastatic breast tumors using textural kinetic features of a contrast based habitat in DCE-MRI

    NASA Astrophysics Data System (ADS)

    Chaudhury, Baishali; Zhou, Mu; Goldgof, Dmitry B.; Hall, Lawrence O.; Gatenby, Robert A.; Gillies, Robert J.; Drukteinis, Jennifer S.

    2015-03-01

    The ability to identify aggressive tumors from indolent tumors using quantitative analysis on dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) would dramatically change the breast cancer treatment paradigm. With this prognostic information, patients with aggressive tumors that have the ability to spread to distant sites outside of the breast could be selected for more aggressive treatment and surveillance regimens. Conversely, patients with tumors that do not have the propensity to metastasize could be treated less aggressively, avoiding some of the morbidity associated with surgery, radiation and chemotherapy. We propose a computer aided detection framework to determine which breast cancers will metastasize to the loco-regional lymph nodes as well as which tumors will eventually go on to develop distant metastses using quantitative image analysis and radiomics. We defined a new contrast based tumor habitat and analyzed textural kinetic features from this habitat for classification purposes. The proposed tumor habitat, which we call combined-habitat, is derived from the intersection of two individual tumor sub-regions: one that exhibits rapid initial contrast uptake and the other that exhibits rapid delayed contrast washout. Hence the combined-habitat represents the tumor sub-region within which the pixels undergo both rapid initial uptake and rapid delayed washout. We analyzed a dataset of twenty-seven representative two dimensional (2D) images from volumetric DCE-MRI of breast tumors, for classification of tumors with no lymph nodes from tumors with positive number of axillary lymph nodes. For this classification an accuracy of 88.9% was achieved. Twenty of the twenty-seven patients were analyzed for classification of distant metastatic tumors from indolent cancers (tumors with no lymph nodes), for which the accuracy was 84.3%.

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

    PubMed Central

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

    2016-01-01

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

  13. Correlation Between Cerebral Atrophy and Texture Features in Alzheimer-type Dementia Brains: A 3-Year Follow-up MRI Study

    NASA Astrophysics Data System (ADS)

    Kodama, Naoki; Takeuchi, Hiroshi

    We assessed relationships between six texture features and changes in atrophy of the cerebral parenchyma, the hippocampus, and the parahippocampal gyrus in the Alzheimer-type dementia (ATD) brain to determine whether or not the features reflect cerebral atrophy in ATD patients. The subjects of this study were 10 ATD patients, and underwent an magnetic resonanse imaging test of the head annually for at least 3 consecutive years. They consisted of three men and seven women, with a mean age of 71.4 ± 6.7 years. The results of study, the mean run length nonuniformity (RLN), angular second moment (ASM), and contrast (CON) increased with time, whereas the mean gray level nonuniformity (GLN), run percentage (RPC), and entropy (ENT) decreased with time. There was a statistically significant correlation between brain-intracranial area ratio (BIR) and GLN (p = 0.039), between BIR and ASM (p = 0.011), and between BIR and ENT (p = 0.023) as well as between parahippocampal-intracranial area ratio and GLN (p = 0.049). These results indicate that the six texture features were shown to reflect gray matter atrophy associated with ATD and to change with the progress of the disease. Although the course of ATD can be followed up by measuring a hippocampal area or volume and determining a decrease in the area or volume, texture features should be a more effective instrument for identifying the progress of ATD.

  14. 3D velocity distribution of P- and S-waves in a biotite gneiss, measured in oil as the pressure medium: Comparison with velocity measurements in a multi-anvil pressure apparatus and with texture-based calculated data

    NASA Astrophysics Data System (ADS)

    Lokajíček, T.; Kern, H.; Svitek, T.; Ivankina, T.

    2014-06-01

    Ultrasonic measurements of the 3D velocity distribution of P- and S-waves were performed on a spherical sample of a biotite gneiss from the Outokumpu scientific drill hole. Measurements were done at room temperature and pressures up to 400 and 70 MPa, respectively, in a pressure vessel with oil as a pressure medium. A modified transducer/sample assembly and the installation of a new mechanical system allowed simultaneous measurements of P- and S-wave velocities in 132 independent directions of the sphere on a net in steps of 15°. Proper signals for P- and S-waves could be recorded by coating the sample surface with a high-viscosity shear wave gel and by temporal point contacting of the transmitter and receiver transducers with the sample surface during the measurements. The 3D seismic measurements revealed a strong foliation-related directional dependence (anisotropy) of P- and S-wave velocities, which is confirmed by measurements in a multi-anvil apparatus on a cube-shaped specimen of the same rock. Both experimental approaches show a marked pressure sensitivity of P- and S-wave velocities and velocity anisotropies. With increasing pressure, P- and S-wave velocities increase non-linearly due to progressive closure of micro-cracks. The reverse is true for velocity anisotropy. 3D velocity calculations based on neutron diffraction measurements of crystallographic preferred orientation (CPO) of major minerals show that the intrinsic bulk anisotropy is basically caused by the CPO of biotite constituting about 23 vol.% of the rock. Including the shape of biotite grains and oriented low-aspect ratio microcracks into the modelling increases bulk anisotropy. An important finding from this study is that the measurements on the sample sphere and on the sample cube displayed distinct differences, particularly in shear wave velocities. It is assumed that the differences are due to the different geometries of the samples and the configuration of the transducer-sample assembly

  15. Radiochromic 3D Detectors

    NASA Astrophysics Data System (ADS)

    Oldham, Mark

    2015-01-01

    Radiochromic materials exhibit a colour change when exposed to ionising radiation. Radiochromic film has been used for clinical dosimetry for many years and increasingly so recently, as films of higher sensitivities have become available. The two principle advantages of radiochromic dosimetry include greater tissue equivalence (radiologically) and the lack of requirement for development of the colour change. In a radiochromic material, the colour change arises direct from ionising interactions affecting dye molecules, without requiring any latent chemical, optical or thermal development, with important implications for increased accuracy and convenience. It is only relatively recently however, that 3D radiochromic dosimetry has become possible. In this article we review recent developments and the current state-of-the-art of 3D radiochromic dosimetry, and the potential for a more comprehensive solution for the verification of complex radiation therapy treatments, and 3D dose measurement in general.

  16. 3-D Seismic Interpretation

    NASA Astrophysics Data System (ADS)

    Moore, Gregory F.

    2009-05-01

    This volume is a brief introduction aimed at those who wish to gain a basic and relatively quick understanding of the interpretation of three-dimensional (3-D) seismic reflection data. The book is well written, clearly illustrated, and easy to follow. Enough elementary mathematics are presented for a basic understanding of seismic methods, but more complex mathematical derivations are avoided. References are listed for readers interested in more advanced explanations. After a brief introduction, the book logically begins with a succinct chapter on modern 3-D seismic data acquisition and processing. Standard 3-D acquisition methods are presented, and an appendix expands on more recent acquisition techniques, such as multiple-azimuth and wide-azimuth acquisition. Although this chapter covers the basics of standard time processing quite well, there is only a single sentence about prestack depth imaging, and anisotropic processing is not mentioned at all, even though both techniques are now becoming standard.

  17. An effective hyper-resolution pseudo-3D implementation of small scale hydrological features to improve regional and global climate studies

    NASA Astrophysics Data System (ADS)

    Hazenberg, P.; Broxton, P. D.; Gochis, D. J.; Niu, G.; Pelletier, J. D.; Troch, P. A.; Zeng, X.

    2013-12-01

    Global land surface processes play an important role in the land-atmosphere exchanges of energy, water, and trace gases. As such, correct representation of the different hydrological processes has long been an important research topic in climate modeling. Historically, these processes were presented at a relatively coarse horizontal resolution, focusing mainly on the vertical hydrological response, while lateral exchanges were either disregarded or implemented in a relatively crude manner. Increases in computational power have led to higher resolution regional and global land surface models. For the coming years, it is anticipated that these models will simulate the hydrological response of the earth surface at a 100-1000 meter pixel size, which is stated as hyper-resolution earth surface modeling. At these relatively high resolutions, correct representation of groundwater, including lateral interactions across pixels and with the channel network, becomes important. Next to that, at these high resolutions elevation differences have a larger impact on the hydrological response and therefore need to be represented properly. We will present a new hydrological framework specifically developed to operate at these hyper-resolutions. Our new approach discriminates between differences in the hydrological response of hillslopes, riparian zones, wetlands and flat regions within a given pixel, while interacting with the channel network and the atmosphere. Instead of applying the traditional conceptual approach, these interactions are incorporated using a physically-based approach. In order to be able to differentiate between these different hydrological features, globally available high-resolution 30 meter DEM data were analyzed using a state-of-the-art digital geomorphological identification method. Based on these techniques, local estimates of soil depth, hillslope width functions, channel network density, etc. were also obtained that are used as input to the model In the

  18. Photogrammetric measurement of 3D freeform millimetre-sized objects with micro features: an experimental validation of the close-range camera calibration model for narrow angles of view

    NASA Astrophysics Data System (ADS)

    Percoco, Gianluca; Sánchez Salmerón, Antonio J.

    2015-09-01

    The measurement of millimetre and micro-scale features is performed by high-cost systems based on technologies with narrow working ranges to accurately control the position of the sensors. Photogrammetry would lower the costs of 3D inspection of micro-features and would be applicable to the inspection of non-removable micro parts of large objects too. Unfortunately, the behaviour of photogrammetry is not known when photogrammetry is applied to micro-features. In this paper, the authors address these issues towards the application of digital close-range photogrammetry (DCRP) to the micro-scale, taking into account that in literature there are research papers stating that an angle of view (AOV) around 10° is the lower limit to the application of the traditional pinhole close-range calibration model (CRCM), which is the basis of DCRP. At first a general calibration procedure is introduced, with the aid of an open-source software library, to calibrate narrow AOV cameras with the CRCM. Subsequently the procedure is validated using a reflex camera with a 60 mm macro lens, equipped with extension tubes (20 and 32 mm) achieving magnification of up to 2 times approximately, to verify literature findings with experimental photogrammetric 3D measurements of millimetre-sized objects with micro-features. The limitation experienced by the laser printing technology, used to produce the bi-dimensional pattern on common paper, has been overcome using an accurate pattern manufactured with a photolithographic process. The results of the experimental activity prove that the CRCM is valid for AOVs down to 3.4° and that DCRP results are comparable with the results of existing and more expensive commercial techniques.

  19. Venus in 3D

    NASA Astrophysics Data System (ADS)

    Plaut, J. J.

    1993-08-01

    Stereographic images of the surface of Venus which enable geologists to reconstruct the details of the planet's evolution are discussed. The 120-meter resolution of these 3D images make it possible to construct digital topographic maps from which precise measurements can be made of the heights, depths, slopes, and volumes of geologic structures.

  20. 3D reservoir visualization

    SciTech Connect

    Van, B.T.; Pajon, J.L.; Joseph, P. )

    1991-11-01

    This paper shows how some simple 3D computer graphics tools can be combined to provide efficient software for visualizing and analyzing data obtained from reservoir simulators and geological simulations. The animation and interactive capabilities of the software quickly provide a deep understanding of the fluid-flow behavior and an accurate idea of the internal architecture of a reservoir.

  1. 3D Visualization for Phoenix Mars Lander Science Operations

    NASA Technical Reports Server (NTRS)

    Edwards, Laurence; Keely, Leslie; Lees, David; Stoker, Carol

    2012-01-01

    Planetary surface exploration missions present considerable operational challenges in the form of substantial communication delays, limited communication windows, and limited communication bandwidth. A 3D visualization software was developed and delivered to the 2008 Phoenix Mars Lander (PML) mission. The components of the system include an interactive 3D visualization environment called Mercator, terrain reconstruction software called the Ames Stereo Pipeline, and a server providing distributed access to terrain models. The software was successfully utilized during the mission for science analysis, site understanding, and science operations activity planning. A terrain server was implemented that provided distribution of terrain models from a central repository to clients running the Mercator software. The Ames Stereo Pipeline generates accurate, high-resolution, texture-mapped, 3D terrain models from stereo image pairs. These terrain models can then be visualized within the Mercator environment. The central cross-cutting goal for these tools is to provide an easy-to-use, high-quality, full-featured visualization environment that enhances the mission science team s ability to develop low-risk productive science activity plans. In addition, for the Mercator and Viz visualization environments, extensibility and adaptability to different missions and application areas are key design goals.

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

    SciTech Connect

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

    2014-06-15

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

  3. Remote measurement methods for 3-D modeling purposes using BAE Systems' Software

    NASA Astrophysics Data System (ADS)

    Walker, Stewart; Pietrzak, Arleta

    2015-06-01

    Efficient, accurate data collection from imagery is the key to an economical generation of useful geospatial products. Incremental developments of traditional geospatial data collection and the arrival of new image data sources cause new software packages to be created and existing ones to be adjusted to enable such data to be processed. In the past, BAE Systems' digital photogrammetric workstation, SOCET SET®, met fin de siècle expectations in data processing and feature extraction. Its successor, SOCET GXP®, addresses today's photogrammetric requirements and new data sources. SOCET GXP is an advanced workstation for mapping and photogrammetric tasks, with automated functionality for triangulation, Digital Elevation Model (DEM) extraction, orthorectification and mosaicking, feature extraction and creation of 3-D models with texturing. BAE Systems continues to add sensor models to accommodate new image sources, in response to customer demand. New capabilities added in the latest version of SOCET GXP facilitate modeling, visualization and analysis of 3-D features.

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

    PubMed

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

    2014-10-01

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

  5. a 3d Campus Information System - Initial Studies

    NASA Astrophysics Data System (ADS)

    Kahraman, I.; Karas, I. R.; Alizadehasharfi, B.; Abdul-Rahman, A.

    2013-08-01

    This paper discusses the method of developing Campus Information System. The system can handle 3D spatial data within desktop and web environment. The method consists of texturing of building facades for 3D building models and modeling 3D Campus Information System. In this paper, some of these steps are carried out; modelling 3D buildings, toggling these models on the terrain and ortho-photo, integration with a geo-database, transferring to the CityServer3D environment by using CityGML format and designing the service, etc. In addition to this, a simple but novel method of texturing of building façades for 3D city modeling that is based on Dynamic Pulse Function (DPF) is used for synthetic and procedural texturing. DPF is very fast compared to other photo realistic texturing methods. Last but not least, it is aimed to present this project on web using web mapping services. This makes 3D analysis easy for decision makers.

  6. 3D Feature Extraction for Unstructured Grids

    NASA Technical Reports Server (NTRS)

    Silver, Deborah

    1996-01-01

    Visualization techniques provide tools that help scientists identify observed phenomena in scientific simulation. To be useful, these tools must allow the user to extract regions, classify and visualize them, abstract them for simplified representations, and track their evolution. Object Segmentation provides a technique to extract and quantify regions of interest within these massive datasets. This article explores basic algorithms to extract coherent amorphous regions from two-dimensional and three-dimensional scalar unstructured grids. The techniques are applied to datasets from Computational Fluid Dynamics and those from Finite Element Analysis.

  7. 3D rapid mapping

    NASA Astrophysics Data System (ADS)

    Isaksson, Folke; Borg, Johan; Haglund, Leif

    2008-04-01

    In this paper the performance of passive range measurement imaging using stereo technique in real time applications is described. Stereo vision uses multiple images to get depth resolution in a similar way as Synthetic Aperture Radar (SAR) uses multiple measurements to obtain better spatial resolution. This technique has been used in photogrammetry for a long time but it will be shown that it is now possible to do the calculations, with carefully designed image processing algorithms, in e.g. a PC in real time. In order to get high resolution and quantitative data in the stereo estimation a mathematical camera model is used. The parameters to the camera model are settled in a calibration rig or in the case of a moving camera the scene itself can be used for calibration of most of the parameters. After calibration an ordinary TV camera has an angular resolution like a theodolite, but to a much lower price. The paper will present results from high resolution 3D imagery from air to ground. The 3D-results from stereo calculation of image pairs are stitched together into a large database to form a 3D-model of the area covered.

  8. Effect of Aqueous Extract of the Seaweed Gracilaria domingensis on the Physicochemical, Microbiological, and Textural Features of Fermented Milks.

    PubMed

    Tavares Estevam, Adriana Carneiro; Alonso Buriti, Flávia Carolina; de Oliveira, Tiago Almeida; Pereira, Elainy Virginia Dos Santos; Florentino, Eliane Rolim; Porto, Ana Lúcia Figueiredo

    2016-04-01

    The effects of the Gracilaria domingensis seaweed aqueous extract in comparison with gelatin on the physicochemical, microbial, and textural characteristics of fermented milks processed with the mixed culture SAB 440 A, composed of Streptococcus thermophilus, Lactobacillus acidophilus, and Bifidobacterium animalis ssp. lactis, were investigated. The addition of G. domingensis aqueous extract did not affect pH, titratable acidity, and microbial viability of fermented milks when compared with the control (with no texture modifier) and the products with added gelatin. Fermented milk with added the seaweed aqueous extract showed firmness, consistency, cohesiveness, and viscosity index at least 10% higher than those observed for the control product (P < 0.05). At 4 h of fermentation, the fermented milks with only G. domingensis extract showed a texture comparable to that observed for products containing only gelatin. At 5 h of fermentation, firmness and consistency increased significantly (P < 0.05) in products with only seaweed extract added, a behavior not observed in products with the full amount of gelatin, probably due to the differences between the interactions of these ingredients with casein during the development of the gel network throughout the acidification of milk. The G. domingensis aqueous extract appears as a promising gelatin alternative to be used as texture modifier in fermented milks and related dairy products. PMID:26989840

  9. Effect of Aqueous Extract of the Seaweed Gracilaria domingensis on the Physicochemical, Microbiological, and Textural Features of Fermented Milks.

    PubMed

    Tavares Estevam, Adriana Carneiro; Alonso Buriti, Flávia Carolina; de Oliveira, Tiago Almeida; Pereira, Elainy Virginia Dos Santos; Florentino, Eliane Rolim; Porto, Ana Lúcia Figueiredo

    2016-04-01

    The effects of the Gracilaria domingensis seaweed aqueous extract in comparison with gelatin on the physicochemical, microbial, and textural characteristics of fermented milks processed with the mixed culture SAB 440 A, composed of Streptococcus thermophilus, Lactobacillus acidophilus, and Bifidobacterium animalis ssp. lactis, were investigated. The addition of G. domingensis aqueous extract did not affect pH, titratable acidity, and microbial viability of fermented milks when compared with the control (with no texture modifier) and the products with added gelatin. Fermented milk with added the seaweed aqueous extract showed firmness, consistency, cohesiveness, and viscosity index at least 10% higher than those observed for the control product (P < 0.05). At 4 h of fermentation, the fermented milks with only G. domingensis extract showed a texture comparable to that observed for products containing only gelatin. At 5 h of fermentation, firmness and consistency increased significantly (P < 0.05) in products with only seaweed extract added, a behavior not observed in products with the full amount of gelatin, probably due to the differences between the interactions of these ingredients with casein during the development of the gel network throughout the acidification of milk. The G. domingensis aqueous extract appears as a promising gelatin alternative to be used as texture modifier in fermented milks and related dairy products.

  10. Dimensional accuracy of 3D printed vertebra

    NASA Astrophysics Data System (ADS)

    Ogden, Kent; Ordway, Nathaniel; Diallo, Dalanda; Tillapaugh-Fay, Gwen; Aslan, Can

    2014-03-01

    3D printer applications in the biomedical sciences and medical imaging are expanding and will have an increasing impact on the practice of medicine. Orthopedic and reconstructive surgery has been an obvious area for development of 3D printer applications as the segmentation of bony anatomy to generate printable models is relatively straightforward. There are important issues that should be addressed when using 3D printed models for applications that may affect patient care; in particular the dimensional accuracy of the printed parts needs to be high to avoid poor decisions being made prior to surgery or therapeutic procedures. In this work, the dimensional accuracy of 3D printed vertebral bodies derived from CT data for a cadaver spine is compared with direct measurements on the ex-vivo vertebra and with measurements made on the 3D rendered vertebra using commercial 3D image processing software. The vertebra was printed on a consumer grade 3D printer using an additive print process using PLA (polylactic acid) filament. Measurements were made for 15 different anatomic features of the vertebral body, including vertebral body height, endplate width and depth, pedicle height and width, and spinal canal width and depth, among others. It is shown that for the segmentation and printing process used, the results of measurements made on the 3D printed vertebral body are substantially the same as those produced by direct measurement on the vertebra and measurements made on the 3D rendered vertebra.

  11. Software for 3D radiotherapy dosimetry. Validation

    NASA Astrophysics Data System (ADS)

    Kozicki, Marek; Maras, Piotr; Karwowski, Andrzej C.

    2014-08-01

    The subject of this work is polyGeVero® software (GeVero Co., Poland), which has been developed to fill the requirements of fast calculations of 3D dosimetry data with the emphasis on polymer gel dosimetry for radiotherapy. This software comprises four workspaces that have been prepared for: (i) calculating calibration curves and calibration equations, (ii) storing the calibration characteristics of the 3D dosimeters, (iii) calculating 3D dose distributions in irradiated 3D dosimeters, and (iv) comparing 3D dose distributions obtained from measurements with the aid of 3D dosimeters and calculated with the aid of treatment planning systems (TPSs). The main features and functions of the software are described in this work. Moreover, the core algorithms were validated and the results are presented. The validation was performed using the data of the new PABIGnx polymer gel dosimeter. The polyGeVero® software simplifies and greatly accelerates the calculations of raw 3D dosimetry data. It is an effective tool for fast verification of TPS-generated plans for tumor irradiation when combined with a 3D dosimeter. Consequently, the software may facilitate calculations by the 3D dosimetry community. In this work, the calibration characteristics of the PABIGnx obtained through four calibration methods: multi vial, cross beam, depth dose, and brachytherapy, are discussed as well.

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

    PubMed Central

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

    2016-01-01

    In a secondary analysis of American College of Radiology Imaging Network (ACRIN) 6668/RTOG 0235, high pretreatment metabolic tumor volume (MTV) on 18F-FDG PET was found to be a poor prognostic factor for patients treated with chemoradiotherapy for locally advanced non–small cell lung cancer (NSCLC). Here we utilize the same dataset to explore whether heterogeneity metrics based on PET textural features can provide additional prognostic information. Methods Patients with locally advanced NSCLC underwent 18F-FDG PET prior to treatment. A gradient-based segmentation tool was used to contour each patient’s primary tumor. MTV, maximum SUV, and 43 textural features were extracted for each tumor. To address over-fitting and high collinearity among PET features, the least absolute shrinkage and selection operator (LASSO) method was applied to identify features that were independent predictors of overall survival (OS) after adjusting for MTV. Recursive binary partitioning in a conditional inference framework was utilized to identify optimal thresholds. Kaplan–Meier curves and log-rank testing were used to compare outcomes among patient groups. Results Two hundred one patients met inclusion criteria. The LASSO procedure identified 1 textural feature (SumMean) as an independent predictor of OS. The optimal cutpoint for MTV was 93.3 cm3, and the optimal Sum-Mean cutpoint for tumors above 93.3 cm3 was 0.018. This grouped patients into three categories: low tumor MTV (n = 155; median OS, 22.6 mo), high tumor MTV and high SumMean (n = 23; median OS, 20.0 mo), and high tumor MTV and low SumMean (n = 23; median OS, 6.2 mo; log-rank P < 0.001). Conclusion We have described an appropriate methodology to evaluate the prognostic value of textural PET features in the context of established prognostic factors. We have also identified a promising feature that may have prognostic value in locally advanced NSCLC patients with large tumors who are treated with chemoradiotherapy

  13. Lung Texture in Serial Thoracic Computed Tomography Scans: Correlation of Radiomics-based Features With Radiation Therapy Dose and Radiation Pneumonitis Development

    SciTech Connect

    Cunliffe, Alexandra; Armato, Samuel G.; Castillo, Richard; Pham, Ngoc; Guerrero, Thomas; Al-Hallaq, Hania A.

    2015-04-01

    Purpose: To assess the relationship between radiation dose and change in a set of mathematical intensity- and texture-based features and to determine the ability of texture analysis to identify patients who develop radiation pneumonitis (RP). Methods and Materials: A total of 106 patients who received radiation therapy (RT) for esophageal cancer were retrospectively identified under institutional review board approval. For each patient, diagnostic computed tomography (CT) scans were acquired before (0-168 days) and after (5-120 days) RT, and a treatment planning CT scan with an associated dose map was obtained. 32- × 32-pixel regions of interest (ROIs) were randomly identified in the lungs of each pre-RT scan. ROIs were subsequently mapped to the post-RT scan and the planning scan dose map by using deformable image registration. The changes in 20 feature values (ΔFV) between pre- and post-RT scan ROIs were calculated. Regression modeling and analysis of variance were used to test the relationships between ΔFV, mean ROI dose, and development of grade ≥2 RP. Area under the receiver operating characteristic curve (AUC) was calculated to determine each feature's ability to distinguish between patients with and those without RP. A classifier was constructed to determine whether 2- or 3-feature combinations could improve RP distinction. Results: For all 20 features, a significant ΔFV was observed with increasing radiation dose. Twelve features changed significantly for patients with RP. Individual texture features could discriminate between patients with and those without RP with moderate performance (AUCs from 0.49 to 0.78). Using multiple features in a classifier, AUC increased significantly (0.59-0.84). Conclusions: A relationship between dose and change in a set of image-based features was observed. For 12 features, ΔFV was significantly related to RP development. This study demonstrated the ability of radiomics to provide a quantitative, individualized

  14. Taming supersymmetric defects in 3d-3d correspondence

    NASA Astrophysics Data System (ADS)

    Gang, Dongmin; Kim, Nakwoo; Romo, Mauricio; Yamazaki, Masahito

    2016-07-01

    We study knots in 3d Chern-Simons theory with complex gauge group {SL}(N,{{C}}), in the context of its relation with 3d { N }=2 theory (the so-called 3d-3d correspondence). The defect has either co-dimension 2 or co-dimension 4 inside the 6d (2,0) theory, which is compactified on a 3-manifold \\hat{M}. We identify such defects in various corners of the 3d-3d correspondence, namely in 3d {SL}(N,{{C}}) CS theory, in 3d { N }=2 theory, in 5d { N }=2 super Yang-Mills theory, and in the M-theory holographic dual. We can make quantitative checks of the 3d-3d correspondence by computing partition functions at each of these theories. This Letter is a companion to a longer paper [1], which contains more details and more results.

  15. 3D Audio System

    NASA Technical Reports Server (NTRS)

    1992-01-01

    Ames Research Center research into virtual reality led to the development of the Convolvotron, a high speed digital audio processing system that delivers three-dimensional sound over headphones. It consists of a two-card set designed for use with a personal computer. The Convolvotron's primary application is presentation of 3D audio signals over headphones. Four independent sound sources are filtered with large time-varying filters that compensate for motion. The perceived location of the sound remains constant. Possible applications are in air traffic control towers or airplane cockpits, hearing and perception research and virtual reality development.

  16. 3D imaging: how to achieve highest accuracy

    NASA Astrophysics Data System (ADS)

    Luhmann, Thomas

    2011-07-01

    The generation of 3D information from images is a key technology in many different areas, e.g. in 3D modeling and representation of architectural or heritage objects, in human body motion tracking and scanning, in 3D scene analysis of traffic scenes, in industrial applications and many more. The basic concepts rely on mathematical representations of central perspective viewing as they are widely known from photogrammetry or computer vision approaches. The objectives of these methods differ, more or less, from high precision and well-structured measurements in (industrial) photogrammetry to fully-automated non-structured applications in computer vision. Accuracy and precision is a critical issue for the 3D measurement of industrial, engineering or medical objects. As state of the art, photogrammetric multi-view measurements achieve relative precisions in the order of 1:100000 to 1:200000, and relative accuracies with respect to retraceable lengths in the order of 1:50000 to 1:100000 of the largest object diameter. In order to obtain these figures a number of influencing parameters have to be optimized. These are, besides others: physical representation of object surface (targets, texture), illumination and light sources, imaging sensors, cameras and lenses, calibration strategies (camera model), orientation strategies (bundle adjustment), image processing of homologue features (target measurement, stereo and multi-image matching), representation of object or workpiece coordinate systems and object scale. The paper discusses the above mentioned parameters and offers strategies for obtaining highest accuracy in object space. Practical examples of high-quality stereo camera measurements and multi-image applications are used to prove the relevance of high accuracy in different applications, ranging from medical navigation to static and dynamic industrial measurements. In addition, standards for accuracy verifications are presented and demonstrated by practical examples

  17. Fast mode decision for 3D-HEVC depth intracoding.

    PubMed

    Zhang, Qiuwen; Li, Nana; Wu, Qinggang

    2014-01-01

    The emerging international standard of high efficiency video coding based 3D video coding (3D-HEVC) is a successor to multiview video coding (MVC). In 3D-HEVC depth intracoding, depth modeling mode (DMM) and high efficiency video coding (HEVC) intraprediction mode are both employed to select the best coding mode for each coding unit (CU). This technique achieves the highest possible coding efficiency, but it results in extremely large encoding time which obstructs the 3D-HEVC from practical application. In this paper, a fast mode decision algorithm based on the correlation between texture video and depth map is proposed to reduce 3D-HEVC depth intracoding computational complexity. Since the texture video and its associated depth map represent the same scene, there is a high correlation among the prediction mode from texture video and depth map. Therefore, we can skip some specific depth intraprediction modes rarely used in related texture CU. Experimental results show that the proposed algorithm can significantly reduce computational complexity of 3D-HEVC depth intracoding while maintaining coding efficiency. PMID:24963512

  18. 3D Shape Perception in Posterior Cortical Atrophy: A Visual Neuroscience Perspective

    PubMed Central

    Gillebert, Céline R.; Schaeverbeke, Jolien; Bastin, Christine; Neyens, Veerle; Bruffaerts, Rose; De Weer, An-Sofie; Seghers, Alexandra; Sunaert, Stefan; Van Laere, Koen; Versijpt, Jan; Vandenbulcke, Mathieu; Salmon, Eric; Todd, James T.; Orban, Guy A.

    2015-01-01

    Posterior cortical atrophy (PCA) is a rare focal neurodegenerative syndrome characterized by progressive visuoperceptual and visuospatial deficits, most often due to atypical Alzheimer's disease (AD). We applied insights from basic visual neuroscience to analyze 3D shape perception in humans affected by PCA. Thirteen PCA patients and 30 matched healthy controls participated, together with two patient control groups with diffuse Lewy body dementia (DLBD) and an amnestic-dominant phenotype of AD, respectively. The hierarchical study design consisted of 3D shape processing for 4 cues (shading, motion, texture, and binocular disparity) with corresponding 2D and elementary feature extraction control conditions. PCA and DLBD exhibited severe 3D shape-processing deficits and AD to a lesser degree. In PCA, deficient 3D shape-from-shading was associated with volume loss in the right posterior inferior temporal cortex. This region coincided with a region of functional activation during 3D shape-from-shading in healthy controls. In PCA patients who performed the same fMRI paradigm, response amplitude during 3D shape-from-shading was reduced in this region. Gray matter volume in this region also correlated with 3D shape-from-shading in AD. 3D shape-from-disparity in PCA was associated with volume loss slightly more anteriorly in posterior inferior temporal cortex as well as in ventral premotor cortex. The findings in right posterior inferior temporal cortex and right premotor cortex are consistent with neurophysiologically based models of the functional anatomy of 3D shape processing. However, in DLBD, 3D shape deficits rely on mechanisms distinct from inferior temporal structural integrity. SIGNIFICANCE STATEMENT Posterior cortical atrophy (PCA) is a neurodegenerative syndrome characterized by progressive visuoperceptual dysfunction and most often an atypical presentation of Alzheimer's disease (AD) affecting the ventral and dorsal visual streams rather than the medial

  19. Recording stereoscopic 3D neurosurgery with a head-mounted 3D camera system.

    PubMed

    Lee, Brian; Chen, Brian R; Chen, Beverly B; Lu, James Y; Giannotta, Steven L

    2015-06-01

    Stereoscopic three-dimensional (3D) imaging can present more information to the viewer and further enhance the learning experience over traditional two-dimensional (2D) video. Most 3D surgical videos are recorded from the operating microscope and only feature the crux, or the most important part of the surgery, leaving out other crucial parts of surgery including the opening, approach, and closing of the surgical site. In addition, many other surgeries including complex spine, trauma, and intensive care unit procedures are also rarely recorded. We describe and share our experience with a commercially available head-mounted stereoscopic 3D camera system to obtain stereoscopic 3D recordings of these seldom recorded aspects of neurosurgery. The strengths and limitations of using the GoPro(®) 3D system as a head-mounted stereoscopic 3D camera system in the operating room are reviewed in detail. Over the past several years, we have recorded in stereoscopic 3D over 50 cranial and spinal surgeries and created a library for education purposes. We have found the head-mounted stereoscopic 3D camera system to be a valuable asset to supplement 3D footage from a 3D microscope. We expect that these comprehensive 3D surgical videos will become an important facet of resident education and ultimately lead to improved patient care.

  20. Digital relief generation from 3D models

    NASA Astrophysics Data System (ADS)

    Wang, Meili; Sun, Yu; Zhang, Hongming; Qian, Kun; Chang, Jian; He, Dongjian

    2016-09-01

    It is difficult to extend image-based relief generation to high-relief generation, as the images contain insufficient height information. To generate reliefs from three-dimensional (3D) models, it is necessary to extract the height fields from the model, but this can only generate bas-reliefs. To overcome this problem, an efficient method is proposed to generate bas-reliefs and high-reliefs directly from 3D meshes. To produce relief features that are visually appropriate, the 3D meshes are first scaled. 3D unsharp masking is used to enhance the visual features in the 3D mesh, and average smoothing and Laplacian smoothing are implemented to achieve better smoothing results. A nonlinear variable scaling scheme is then employed to generate the final bas-reliefs and high-reliefs. Using the proposed method, relief models can be generated from arbitrary viewing positions with different gestures and combinations of multiple 3D models. The generated relief models can be printed by 3D printers. The proposed method provides a means of generating both high-reliefs and bas-reliefs in an efficient and effective way under the appropriate scaling factors.

  1. Computer-aided diagnosis of pulmonary nodules on CT scans: Segmentation and classification using 3D active contours

    PubMed Central

    Way, Ted W.; Hadjiiski, Lubomir M.; Sahiner, Berkman; Chan, Heang-Ping; Cascade, Philip N.; Kazerooni, Ella A.; Bogot, Naama; Zhou, Chuan

    2009-01-01

    We are developing a computer-aided diagnosis (CAD) system to classify malignant and benign lung nodules found on CT scans. A fully automated system was designed to segment the nodule from its surrounding structured background in a local volume of interest (VOI) and to extract image features for classification. Image segmentation was performed with a three-dimensional (3D) active contour (AC) method. A data set of 96 lung nodules (44 malignant, 52 benign) from 58 patients was used in this study. The 3D AC model is based on two-dimensional AC with the addition of three new energy components to take advantage of 3D information: (1) 3D gradient, which guides the active contour to seek the object surface, (2) 3D curvature, which imposes a smoothness constraint in the z direction, and (3) mask energy, which penalizes contours that grow beyond the pleura or thoracic wall. The search for the best energy weights in the 3D AC model was guided by a simplex optimization method. Morphological and gray-level features were extracted from the segmented nodule. The rubber band straightening transform (RBST) was applied to the shell of voxels surrounding the nodule. Texture features based on run-length statistics were extracted from the RBST image. A linear discriminant analysis classifier with stepwise feature selection was designed using a second simplex optimization to select the most effective features. Leave-one-case-out resampling was used to train and test the CAD system. The system achieved a test area under the receiver operating characteristic curve (Az) of 0.83±0.04. Our preliminary results indicate that use of the 3D AC model and the 3D texture features surrounding the nodule is a promising approach to the segmentation and classification of lung nodules with CAD. The segmentation performance of the 3D AC model trained with our data set was evaluated with 23 nodules available in the Lung Image Database Consortium (LIDC). The lung nodule volumes segmented by the 3D AC

  2. An Improved Version of TOPAZ 3D

    SciTech Connect

    Krasnykh, Anatoly

    2003-07-29

    An improved version of the TOPAZ 3D gun code is presented as a powerful tool for beam optics simulation. In contrast to the previous version of TOPAZ 3D, the geometry of the device under test is introduced into TOPAZ 3D directly from a CAD program, such as Solid Edge or AutoCAD. In order to have this new feature, an interface was developed, using the GiD software package as a meshing code. The article describes this method with two models to illustrate the results.

  3. Novel 3D ultrasound image-based biomarkers based on a feature selection from a 2D standardized vessel wall thickness map: a tool for sensitive assessment of therapies for carotid atherosclerosis

    NASA Astrophysics Data System (ADS)

    Chiu, Bernard; Li, Bing; Chow, Tommy W. S.

    2013-09-01

    With the advent of new therapies and management strategies for carotid atherosclerosis, there is a parallel need for measurement tools or biomarkers to evaluate the efficacy of these new strategies. 3D ultrasound has been shown to provide reproducible measurements of plaque area/volume and vessel wall volume. However, since carotid atherosclerosis is a focal disease that predominantly occurs at bifurcations, biomarkers based on local plaque change may be more sensitive than global volumetric measurements in demonstrating efficacy of new therapies. The ultimate goal of this paper is to develop a biomarker that is based on the local distribution of vessel-wall-plus-plaque thickness change (VWT-Change) that has occurred during the course of a clinical study. To allow comparison between different treatment groups, the VWT-Change distribution of each subject must first be mapped to a standardized domain. In this study, we developed a technique to map the 3D VWT-Change distribution to a 2D standardized template. We then applied a feature selection technique to identify regions on the 2D standardized map on which subjects in different treatment groups exhibit greater difference in VWT-Change. The proposed algorithm was applied to analyse the VWT-Change of 20 subjects in a placebo-controlled study of the effect of atorvastatin (Lipitor). The average VWT-Change for each subject was computed (i) over all points in the 2D map and (ii) over feature points only. For the average computed over all points, 97 subjects per group would be required to detect an effect size of 25% that of atorvastatin in a six-month study. The sample size is reduced to 25 subjects if the average were computed over feature points only. The introduction of this sensitive quantification technique for carotid atherosclerosis progression/regression would allow many proof-of-principle studies to be performed before a more costly and longer study involving a larger population is held to confirm the treatment

  4. Recent Advances in Visualizing 3D Flow with LIC

    NASA Technical Reports Server (NTRS)

    Interrante, Victoria; Grosch, Chester

    1998-01-01

    Line Integral Convolution (LIC), introduced by Cabral and Leedom in 1993, is an elegant and versatile technique for representing directional information via patterns of correlation in a texture. Although most commonly used to depict 2D flow, or flow over a surface in 3D, LIC methods can equivalently be used to portray 3D flow through a volume. However, the popularity of LIC as a device for illustrating 3D flow has historically been limited both by the computational expense of generating and rendering such a 3D texture and by the difficulties inherent in clearly and effectively conveying the directional information embodied in the volumetric output textures that are produced. In an earlier paper, we briefly discussed some of the factors that may underlie the perceptual difficulties that we can encounter with dense 3D displays and outlined several strategies for more effectively visualizing 3D flow with volume LIC. In this article, we review in more detail techniques for selectively emphasizing critical regions of interest in a flow and for facilitating the accurate perception of the 3D depth and orientation of overlapping streamlines, and we demonstrate new methods for efficiently incorporating an indication of orientation into a flow representation and for conveying additional information about related scalar quantities such as temperature or vorticity over a flow via subtle, continuous line width and color variations.

  5. Classification of JERS-1 Image Mosaic of Central Africa Using A Supervised Multiscale Classifier of Texture Features

    NASA Technical Reports Server (NTRS)

    Saatchi, Sassan; DeGrandi, Franco; Simard, Marc; Podest, Erika

    1999-01-01

    In this paper, a multiscale approach is introduced to classify the Japanese Research Satellite-1 (JERS-1) mosaic image over the Central African rainforest. A series of texture maps are generated from the 100 m mosaic image at various scales. Using a quadtree model and relating classes at each scale by a Markovian relationship, the multiscale images are classified from course to finer scale. The results are verified at various scales and the evolution of classification is monitored by calculating the error at each stage.

  6. 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

    SciTech Connect

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

    2015-06-15

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

  7. RAG-3D: A search tool for RNA 3D substructures

    DOE PAGES

    Zahran, Mai; Sevim Bayrak, Cigdem; Elmetwaly, Shereef; Schlick, Tamar

    2015-08-24

    In this study, to address many challenges in RNA structure/function prediction, the characterization of RNA's modular architectural units is required. Using the RNA-As-Graphs (RAG) database, we have previously explored the existence of secondary structure (2D) submotifs within larger RNA structures. Here we present RAG-3D—a dataset of RNA tertiary (3D) structures and substructures plus a web-based search tool—designed to exploit graph representations of RNAs for the goal of searching for similar 3D structural fragments. The objects in RAG-3D consist of 3D structures translated into 3D graphs, cataloged based on the connectivity between their secondary structure elements. Each graph is additionally describedmore » in terms of its subgraph building blocks. The RAG-3D search tool then compares a query RNA 3D structure to those in the database to obtain structurally similar structures and substructures. This comparison reveals conserved 3D RNA features and thus may suggest functional connections. Though RNA search programs based on similarity in sequence, 2D, and/or 3D structural elements are available, our graph-based search tool may be advantageous for illuminating similarities that are not obvious; using motifs rather than sequence space also reduces search times considerably. Ultimately, such substructuring could be useful for RNA 3D structure prediction, structure/function inference and inverse folding.« less

  8. RAG-3D: A search tool for RNA 3D substructures

    SciTech Connect

    Zahran, Mai; Sevim Bayrak, Cigdem; Elmetwaly, Shereef; Schlick, Tamar

    2015-08-24

    In this study, to address many challenges in RNA structure/function prediction, the characterization of RNA's modular architectural units is required. Using the RNA-As-Graphs (RAG) database, we have previously explored the existence of secondary structure (2D) submotifs within larger RNA structures. Here we present RAG-3D—a dataset of RNA tertiary (3D) structures and substructures plus a web-based search tool—designed to exploit graph representations of RNAs for the goal of searching for similar 3D structural fragments. The objects in RAG-3D consist of 3D structures translated into 3D graphs, cataloged based on the connectivity between their secondary structure elements. Each graph is additionally described in terms of its subgraph building blocks. The RAG-3D search tool then compares a query RNA 3D structure to those in the database to obtain structurally similar structures and substructures. This comparison reveals conserved 3D RNA features and thus may suggest functional connections. Though RNA search programs based on similarity in sequence, 2D, and/or 3D structural elements are available, our graph-based search tool may be advantageous for illuminating similarities that are not obvious; using motifs rather than sequence space also reduces search times considerably. Ultimately, such substructuring could be useful for RNA 3D structure prediction, structure/function inference and inverse folding.

  9. RAG-3D: a search tool for RNA 3D substructures

    PubMed Central

    Zahran, Mai; Sevim Bayrak, Cigdem; Elmetwaly, Shereef; Schlick, Tamar

    2015-01-01

    To address many challenges in RNA structure/function prediction, the characterization of RNA's modular architectural units is required. Using the RNA-As-Graphs (RAG) database, we have previously explored the existence of secondary structure (2D) submotifs within larger RNA structures. Here we present RAG-3D—a dataset of RNA tertiary (3D) structures and substructures plus a web-based search tool—designed to exploit graph representations of RNAs for the goal of searching for similar 3D structural fragments. The objects in RAG-3D consist of 3D structures translated into 3D graphs, cataloged based on the connectivity between their secondary structure elements. Each graph is additionally described in terms of its subgraph building blocks. The RAG-3D search tool then compares a query RNA 3D structure to those in the database to obtain structurally similar structures and substructures. This comparison reveals conserved 3D RNA features and thus may suggest functional connections. Though RNA search programs based on similarity in sequence, 2D, and/or 3D structural elements are available, our graph-based search tool may be advantageous for illuminating similarities that are not obvious; using motifs rather than sequence space also reduces search times considerably. Ultimately, such substructuring could be useful for RNA 3D structure prediction, structure/function inference and inverse folding. PMID:26304547

  10. Low-cost 3D rangefinder system

    NASA Astrophysics Data System (ADS)

    Chen, Bor-Tow; Lou, Wen-Shiou; Chen, Chia-Chen; Lin, Hsien-Chang

    1998-06-01

    Nowadays, 3D data are popularly performed in computer, and 3D browsers manipulate 3D model in the virtual world. Yet, till now, 3D digitizer is still a high-cost product and not a familiar equipment. In order to meet the requirement of 3D fancy world, in this paper, the concept of a low-cost 3D digitizer system is proposed to catch 3D range data from objects. The specified optical design of the 3D extraction is effective to depress the size, and the processing software of the system is compatible with PC to promote its portable capability. Both features contribute a low-cost system in PC environment in contrast to a large system bundled in an expensive workstation platform. In the structure of 3D extraction, laser beam and CCD camera are adopted to construct a 3D sensor. Instead of 2 CCD cameras for capturing laser lines twice before, a 2-in-1 system is proposed to merge 2 images in one CCD which still retains the information of two fields of views to inhibit occlusion problems. Besides, optical paths of two camera views are reflected by mirror in order that the volume of the system can be minified with one rotary axis only. It makes a portable system be more possible to work. Combined with the processing software executable in PC windows system, the proposed system not only saves hardware cost but also processing time of software. The system performance achieves 0.05 mm accuracy. It shows that a low- cost system is more possible to be high-performance.

  11. 3D grain boundary migration

    NASA Astrophysics Data System (ADS)

    Becker, J. K.; Bons, P. D.

    2009-04-01

    Microstructures of rocks play an important role in determining rheological properties and help to reveal the processes that lead to their formation. Some of these processes change the microstructure significantly and may thus have the opposite effect in obliterating any fabrics indicative of the previous history of the rocks. One of these processes is grain boundary migration (GBM). During static recrystallisation, GBM may produce a foam texture that completely overprints a pre-existing grain boundary network and GBM actively influences the rheology of a rock, via its influence on grain size and lattice defect concentration. We here present a new numerical simulation software that is capable of simulating a whole range of processes on the grain scale (it is not limited to grain boundary migration). The software is polyhedron-based, meaning that each grain (or phase) is represented by a polyhedron that has discrete boundaries. The boundary (the shell) of the polyhedron is defined by a set of facets which in turn is defined by a set of vertices. Each structural entity (polyhedron, facets and vertices) can have an unlimited number of parameters (depending on the process to be modeled) such as surface energy, concentration, etc. which can be used to calculate changes of the microstructre. We use the processes of grain boundary migration of a "regular" and a partially molten rock to demonstrate the software. Since this software is 3D, the formation of melt networks in a partially molten rock can also be studied. The interconnected melt network is of fundamental importance for melt segregation and migration in the crust and mantle and can help to understand the core-mantle differentiation of large terrestrial planets.

  12. Interactive 2D to 3D stereoscopic image synthesis

    NASA Astrophysics Data System (ADS)

    Feldman, Mark H.; Lipton, Lenny

    2005-03-01

    Advances in stereoscopic display technologies, graphic card devices, and digital imaging algorithms have opened up new possibilities in synthesizing stereoscopic images. The power of today"s DirectX/OpenGL optimized graphics cards together with adapting new and creative imaging tools found in software products such as Adobe Photoshop, provide a powerful environment for converting planar drawings and photographs into stereoscopic images. The basis for such a creative process is the focus of this paper. This article presents a novel technique, which uses advanced imaging features and custom Windows-based software that utilizes the Direct X 9 API to provide the user with an interactive stereo image synthesizer. By creating an accurate and interactive world scene with moveable and flexible depth map altered textured surfaces, perspective stereoscopic cameras with both visible frustums and zero parallax planes, a user can precisely model a virtual three-dimensional representation of a real-world scene. Current versions of Adobe Photoshop provide a creative user with a rich assortment of tools needed to highlight elements of a 2D image, simulate hidden areas, and creatively shape them for a 3D scene representation. The technique described has been implemented as a Photoshop plug-in and thus allows for a seamless transition of these 2D image elements into 3D surfaces, which are subsequently rendered to create stereoscopic views.

  13. 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.

  14. Diffractive optical element for creating visual 3D images.

    PubMed

    Goncharsky, Alexander; Goncharsky, Anton; Durlevich, Svyatoslav

    2016-05-01

    A method is proposed to compute and synthesize the microrelief of a diffractive optical element to produce a new visual security feature - the vertical 3D/3D switch effect. The security feature consists in the alternation of two 3D color images when the diffractive element is tilted up/down. Optical security elements that produce the new security feature are synthesized using electron-beam technology. Sample optical security elements are manufactured that produce 3D to 3D visual switch effect when illuminated by white light. Photos and video records of the vertical 3D/3D switch effect of real optical elements are presented. The optical elements developed can be replicated using standard equipment employed for manufacturing security holograms. The new optical security feature is easy to control visually, safely protected against counterfeit, and designed to protect banknotes, documents, ID cards, etc. PMID:27137530

  15. 'Diamond' in 3-D

    NASA Technical Reports Server (NTRS)

    2004-01-01

    This 3-D, microscopic imager mosaic of a target area on a rock called 'Diamond Jenness' was taken after NASA's Mars Exploration Rover Opportunity ground into the surface with its rock abrasion tool for a second time.

    Opportunity has bored nearly a dozen holes into the inner walls of 'Endurance Crater.' On sols 177 and 178 (July 23 and July 24, 2004), the rover worked double-duty on Diamond Jenness. Surface debris and the bumpy shape of the rock resulted in a shallow and irregular hole, only about 2 millimeters (0.08 inch) deep. The final depth was not enough to remove all the bumps and leave a neat hole with a smooth floor. This extremely shallow depression was then examined by the rover's alpha particle X-ray spectrometer.

    On Sol 178, Opportunity's 'robotic rodent' dined on Diamond Jenness once again, grinding almost an additional 5 millimeters (about 0.2 inch). The rover then applied its Moessbauer spectrometer to the deepened hole. This double dose of Diamond Jenness enabled the science team to examine the rock at varying layers. Results from those grindings are currently being analyzed.

    The image mosaic is about 6 centimeters (2.4 inches) across.

  16. Martian terrain - 3D

    NASA Technical Reports Server (NTRS)

    1997-01-01

    This area of terrain near the Sagan Memorial Station was taken on Sol 3 by the Imager for Mars Pathfinder (IMP). 3D glasses are necessary to identify surface detail.

    The IMP is a stereo imaging system with color capability provided by 24 selectable filters -- twelve filters per 'eye.' It stands 1.8 meters above the Martian surface, and has a resolution of two millimeters at a range of two meters.

    Mars Pathfinder is the second in NASA's Discovery program of low-cost spacecraft with highly focused science goals. The Jet Propulsion Laboratory, Pasadena, CA, developed and manages the Mars Pathfinder mission for NASA's Office of Space Science, Washington, D.C. JPL is an operating division of the California Institute of Technology (Caltech). The Imager for Mars Pathfinder (IMP) was developed by the University of Arizona Lunar and Planetary Laboratory under contract to JPL. Peter Smith is the Principal Investigator.

    Click below to see the left and right views individually. [figure removed for brevity, see original site] Left [figure removed for brevity, see original site] Right

  17. [3D virtual endoscopy of heart].

    PubMed

    Du, Aan; Yang, Xin; Xue, Haihong; Yao, Liping; Sun, Kun

    2012-10-01

    In this paper, we present a virtual endoscopy (VE) for diagnosis of heart diseases, which is proved efficient and affordable, easy to popularize for viewing the interior of the heart. The dual source CT (DSCT) data were used as primary data in our system. The 3D structure of virtual heart was reconstructed with 3D texture mapping technology based on graphics processing unit (GPU), and could be displayed dynamically in real time. When we displayed it in real time, we could not only observe the inside of the chambers of heart but also examine from the new angle of view by the 3D data which were already clipped according to doctor's desire. In the pattern of observation, we used both mutual interactive mode and auto mode. In the auto mode, we used Dijkstra Algorithm which treated the 3D Euler distance as weighting factor to find out the view path quickly, and, used view path to calculate the four chamber plane. PMID:23198444

  18. Benefits of Red-Edge Spectral Band and Texture Features for the Object-based Classification using RapidEye sSatellite Image data

    NASA Astrophysics Data System (ADS)

    Kim, H. O.; Yeom, J. M.

    2014-12-01

    Space-based remote sensing in agriculture is particularly relevant to issues such as global climate change, food security, and precision agriculture. Recent satellite missions have opened up new perspectives by offering high spatial resolution, various spectral properties, and fast revisit rates to the same regions. Here, we examine the utility of broadband red-edge spectral information in multispectral satellite image data for classifying paddy rice crops in South Korea. Additionally, we examine how object-based spectral features affect the classification of paddy rice growth stages. For the analysis, two seasons of RapidEye satellite image data were used. The results showed that the broadband red-edge information slightly improved the classification accuracy of the crop condition in heterogeneous paddy rice crop environments, particularly when single-season image data were used. This positive effect appeared to be offset by the multi-temporal image data. Additional texture information brought only a minor improvement or a slight decline, although it is well known to be advantageous for object-based classification in general. We conclude that broadband red-edge information derived from conventional multispectral satellite data has the potential to improve space-based crop monitoring. Because the positive or negative effects of texture features for object-based crop classification could barely be interpreted, the relationships between the textual properties and paddy rice crop parameters at the field scale should be further examined in depth.

  19. Assessing 3d Photogrammetry Techniques in Craniometrics

    NASA Astrophysics Data System (ADS)

    Moshobane, M. C.; de Bruyn, P. J. N.; Bester, M. N.

    2016-06-01

    Morphometrics (the measurement of morphological features) has been revolutionized by the creation of new techniques to study how organismal shape co-varies with several factors such as ecophenotypy. Ecophenotypy refers to the divergence of phenotypes due to developmental changes induced by local environmental conditions, producing distinct ecophenotypes. None of the techniques hitherto utilized could explicitly address organismal shape in a complete biological form, i.e. three-dimensionally. This study investigates the use of the commercial software, Photomodeler Scanner® (PMSc®) three-dimensional (3D) modelling software to produce accurate and high-resolution 3D models. Henceforth, the modelling of Subantarctic fur seal (Arctocephalus tropicalis) and Antarctic fur seal (Arctocephalus gazella) skulls which could allow for 3D measurements. Using this method, sixteen accurate 3D skull models were produced and five metrics were determined. The 3D linear measurements were compared to measurements taken manually with a digital caliper. In addition, repetitive measurements were recorded by varying researchers to determine repeatability. To allow for comparison straight line measurements were taken with the software, assuming that close accord with all manually measured features would illustrate the model's accurate replication of reality. Measurements were not significantly different demonstrating that realistic 3D skull models can be successfully produced to provide a consistent basis for craniometrics, with the additional benefit of allowing non-linear measurements if required.

  20. Isotropic 3D Nuclear Morphometry of Normal, Fibrocystic and Malignant Breast Epithelial Cells Reveals New Structural Alterations

    PubMed Central

    Nandakumar, Vivek; Kelbauskas, Laimonas; Hernandez, Kathryn F.; Lintecum, Kelly M.; Senechal, Patti; Bussey, Kimberly J.; Davies, Paul C. W.; Johnson, Roger H.; Meldrum, Deirdre R.

    2012-01-01

    Background Grading schemes for breast cancer diagnosis are predominantly based on pathologists' qualitative assessment of altered nuclear structure from 2D brightfield microscopy images. However, cells are three-dimensional (3D) objects with features that are inherently 3D and thus poorly characterized in 2D. Our goal is to quantitatively characterize nuclear structure in 3D, assess its variation with malignancy, and investigate whether such variation correlates with standard nuclear grading criteria. Methodology We applied micro-optical computed tomographic imaging and automated 3D nuclear morphometry to quantify and compare morphological variations between human cell lines derived from normal, benign fibrocystic or malignant breast epithelium. To reproduce the appearance and contrast in clinical cytopathology images, we stained cells with hematoxylin and eosin and obtained 3D images of 150 individual stained cells of each cell type at sub-micron, isotropic resolution. Applying volumetric image analyses, we computed 42 3D morphological and textural descriptors of cellular and nuclear structure. Principal Findings We observed four distinct nuclear shape categories, the predominant being a mushroom cap shape. Cell and nuclear volumes increased from normal to fibrocystic to metastatic type, but there was little difference in the volume ratio of nucleus to cytoplasm (N/C ratio) between the lines. Abnormal cell nuclei had more nucleoli, markedly higher density and clumpier chromatin organization compared to normal. Nuclei of non-tumorigenic, fibrocystic cells exhibited larger textural variations than metastatic cell nuclei. At p<0.0025 by ANOVA and Kruskal-Wallis tests, 90% of our computed descriptors statistically differentiated control from abnormal cell populations, but only 69% of these features statistically differentiated the fibrocystic from the metastatic cell populations. Conclusions Our results provide a new perspective on nuclear structure variations

  1. TU-A-12A-04: Quantitative Texture Features Calculated in Lung Tissue From CT Scans Demonstrate Consistency Between Two Databases From Different Institutions

    SciTech Connect

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

    2014-06-15

    Purpose: To evaluate the consistency of computed tomography (CT) scan texture features, previously identified as stable in a healthy patient cohort, in esophageal cancer patient CT scans. Methods: 116 patients receiving radiation therapy (median dose: 50.4Gy) for esophageal cancer were retrospectively identified. For each patient, diagnostic-quality pre-therapy (0-183 days) and post-therapy (5-120 days) scans (mean voxel size: 0.8mm×0.8mm×2.5mm) and a treatment planning scan and associated dose map were collected. An average of 501 32x32-pixel ROIs were placed randomly in the lungs of each pre-therapy scan. ROI centers were mapped to corresponding locations in post-therapy and planning scans using the displacement vector field output by demons deformable registration. Only ROIs with mean dose <5Gy were analyzed, as these were expected to contain minimal post-treatment damage. 140 texture features were calculated in pre-therapy and post-therapy scan ROIs and compared using Bland-Altman analysis. For each feature, the mean feature value change and the distance spanned by the 95% limits of agreement were normalized to the mean feature value, yielding normalized range of agreement (nRoA) and normalized bias (nBias). Using Wilcoxon signed rank tests, nRoA and nBias were compared with values computed previously in 27 healthy patient scans (mean voxel size: 0.67mm×0.67mm×1mm) acquired at a different institution. Results: nRoA was significantly (p<0.001) larger in cancer patients than healthy patients. Differences in nBias were not significant (p=0.23). The 20 features identified previously as having nRoA<20% for healthy patients had the lowest nRoA values in the current database, with an average increase of 5.6%. Conclusion: Despite differences in CT scanner type, scan resolution, and patient health status, the same 20 features remained stable (i.e., low variability and bias) in the absence of disease changes for databases from two institutions. Identification of

  2. Understanding Crystal Populations; Looking Towards 3D Quantitative Analysis

    NASA Astrophysics Data System (ADS)

    Jerram, D. A.; Morgan, D. J.

    2010-12-01

    In order to understand volcanic systems, the potential record held within crystal populations needs to be revealed. It is becoming increasingly clear, however, that the crystal populations that arrive at the surface in volcanic eruptions are commonly mixtures of crystals, which may be representative of simple crystallization, recycling of crystals and incorporation of alien crystals. If we can quantify the true 3D population within a sample then we will be able to separate crystals with different histories and begin to interrogate the true and complex plumbing within the volcanic system. Modeling crystal populations is one area where we can investigate the best methodologies to use when dealing with sections through 3D populations. By producing known 3D shapes and sizes with virtual textures and looking at the statistics of shape and size when such populations are sectioned, we are able to gain confidence about what our 2D information is telling us about the population. We can also use this approach to test the size of population we need to analyze. 3D imaging through serial sectioning or x-ray CT, provides a complete 3D quantification of a rocks texture. Individual phases can be identified and in principle the true 3D statistics of the population can be interrogated. In practice we need to develop strategies (as with 2D-3D transformations), that enable a true characterization of the 3D data, and an understanding of the errors and pitfalls that exist. Ultimately, the reproduction of true 3D textures and the wealth of information they hold, is now within our reach.

  3. 3D fast wavelet network model-assisted 3D face recognition

    NASA Astrophysics Data System (ADS)

    Said, Salwa; Jemai, Olfa; Zaied, Mourad; Ben Amar, Chokri

    2015-12-01

    In last years, the emergence of 3D shape in face recognition is due to its robustness to pose and illumination changes. These attractive benefits are not all the challenges to achieve satisfactory recognition rate. Other challenges such as facial expressions and computing time of matching algorithms remain to be explored. In this context, we propose our 3D face recognition approach using 3D wavelet networks. Our approach contains two stages: learning stage and recognition stage. For the training we propose a novel algorithm based on 3D fast wavelet transform. From 3D coordinates of the face (x,y,z), we proceed to voxelization to get a 3D volume which will be decomposed by 3D fast wavelet transform and modeled after that with a wavelet network, then their associated weights are considered as vector features to represent each training face . For the recognition stage, an unknown identity face is projected on all the training WN to obtain a new vector features after every projection. A similarity score is computed between the old and the obtained vector features. To show the efficiency of our approach, experimental results were performed on all the FRGC v.2 benchmark.

  4. 3-D Finite Element Heat Transfer

    1992-02-01

    TOPAZ3D is a three-dimensional implicit finite element computer code for heat transfer analysis. TOPAZ3D can be used to solve for the steady-state or transient temperature field on three-dimensional geometries. Material properties may be temperature-dependent and either isotropic or orthotropic. A variety of time-dependent and temperature-dependent boundary conditions can be specified including temperature, flux, convection, and radiation. By implementing the user subroutine feature, users can model chemical reaction kinetics and allow for any type of functionalmore » representation of boundary conditions and internal heat generation. TOPAZ3D can solve problems of diffuse and specular band radiation in an enclosure coupled with conduction in the material surrounding the enclosure. Additional features include thermal contact resistance across an interface, bulk fluids, phase change, and energy balances.« less

  5. Alignment of continuous video onto 3D point clouds.

    PubMed

    Zhao, Wenyi; Nister, David; Hsu, Steve

    2005-08-01

    We propose a general framework for aligning continuous (oblique) video onto 3D sensor data. We align a point cloud computed from the video onto the point cloud directly obtained from a 3D sensor. This is in contrast to existing techniques where the 2D images are aligned to a 3D model derived from the 3D sensor data. Using point clouds enables the alignment for scenes full of objects that are difficult to model; for example, trees. To compute 3D point clouds from video, motion stereo is used along with a state-of-the-art algorithm for camera pose estimation. Our experiments with real data demonstrate the advantages of the proposed registration algorithm for texturing models in large-scale semiurban environments. The capability to align video before a 3D model is built from the 3D sensor data offers new practical opportunities for 3D modeling. We introduce a novel modeling-through-registration approach that fuses 3D information from both the 3D sensor and the video. Initial experiments with real data illustrate the potential of the proposed approach.

  6. 3D face recognition based on matching of facial surfaces

    NASA Astrophysics Data System (ADS)

    Echeagaray-Patrón, Beatriz A.; Kober, Vitaly

    2015-09-01

    Face recognition is an important task in pattern recognition and computer vision. In this work a method for 3D face recognition in the presence of facial expression and poses variations is proposed. The method uses 3D shape data without color or texture information. A new matching algorithm based on conformal mapping of original facial surfaces onto a Riemannian manifold followed by comparison of conformal and isometric invariants computed in the manifold is suggested. Experimental results are presented using common 3D face databases that contain significant amount of expression and pose variations.

  7. Multi-view and 3D deformable part models.

    PubMed

    Pepik, Bojan; Stark, Michael; Gehler, Peter; Schiele, Bernt

    2015-11-01

    As objects are inherently 3D, they have been modeled in 3D in the early days of computer vision. Due to the ambiguities arising from mapping 2D features to 3D models, 3D object representations have been neglected and 2D feature-based models are the predominant paradigm in object detection nowadays. While such models have achieved outstanding bounding box detection performance, they come with limited expressiveness, as they are clearly limited in their capability of reasoning about 3D shape or viewpoints. In this work, we bring the worlds of 3D and 2D object representations closer, by building an object detector which leverages the expressive power of 3D object representations while at the same time can be robustly matched to image evidence. To that end, we gradually extend the successful deformable part model [1] to include viewpoint information and part-level 3D geometry information, resulting in several different models with different level of expressiveness. We end up with a 3D object model, consisting of multiple object parts represented in 3D and a continuous appearance model. We experimentally verify that our models, while providing richer object hypotheses than the 2D object models, provide consistently better joint object localization and viewpoint estimation than the state-of-the-art multi-view and 3D object detectors on various benchmarks (KITTI [2] , 3D object classes [3] , Pascal3D+ [4] , Pascal VOC 2007 [5] , EPFL multi-view cars[6] ). PMID:26440264

  8. Computerized analysis of interstitial lung diseases on chest radiographs based on lung texture, geometric-pattern features, and artificial neural networks

    NASA Astrophysics Data System (ADS)

    Ishida, Takayuki; Katsuragawa, Shigehiko; Nakamura, Katsumi; Ashizawa, Kazuto; MacMahon, Heber; Doi, Kunio

    2002-05-01

    For computerized detection of interstitial lung disease on chest radiographs, we developed three different methods: texture analysis based on the Fourier transform, geometric- pattern feature analysis, and artificial neural network (ANN) analysis of image data. With these computer-aided diagnostic methods, quantitative measures can be obtained. To improve the diagnostic accuracy, we investigated combined classification schemes by using the results obtained with the three methods for distinction between normal and abnormal chest radiographs with interstitial opacities. The sensitivities of texture analysis, geometric analysis, and ANN analysis were 88.0+/- 1.6%, 91.0+/- 2.6%, and 87.5+/- 1.9%, respectively, at a specificity of 90.0%, whereas the sensitivity of a combined classification scheme with the logical OR operation was improved to 97.1%+/- 1.5% at the same specificity of 90.0%. The combined scheme can achieve higher accuracy than the individual methods for distinction between normal and abnormal cases with interstitial opacities.

  9. Multi-resolution texture synthesis from turntable image sequences

    NASA Astrophysics Data System (ADS)

    Wang, Xuedong; Wu, Xiaojun; Zhang, Xiaorong

    2012-03-01

    Texture synthesis and texture mapping are important technologies for rendering realistic three-dimensional scene. It has been widely used in virtual reality, urban modeling, 3D animation, gaming and other areas. In this paper, we propose a fast method to construct high quality texture map for multi-resolution texture synthesis from turntable image sequences. Given a 3D mesh model, we first get the projection relationship between 3D mesh and image sequences. We then use image sequences to construct a texture triangle for each 3D triangle mesh and get a global rectangular texture map for the whole mesh. Another approach to construct a texture map is using Stretch-minimizing mesh parameterization. Finally, we map the texture to mesh model to verify the quality of these two methods. The high performance of this method has been demonstrated in many real object models.

  10. Exploring interaction with 3D volumetric displays

    NASA Astrophysics Data System (ADS)

    Grossman, Tovi; Wigdor, Daniel; Balakrishnan, Ravin

    2005-03-01

    Volumetric displays generate true volumetric 3D images by actually illuminating points in 3D space. As a result, viewing their contents is similar to viewing physical objects in the real world. These displays provide a 360 degree field of view, and do not require the user to wear hardware such as shutter glasses or head-trackers. These properties make them a promising alternative to traditional display systems for viewing imagery in 3D. Because these displays have only recently been made available commercially (e.g., www.actuality-systems.com), their current use tends to be limited to non-interactive output-only display devices. To take full advantage of the unique features of these displays, however, it would be desirable if the 3D data being displayed could be directly interacted with and manipulated. We investigate interaction techniques for volumetric display interfaces, through the development of an interactive 3D geometric model building application. While this application area itself presents many interesting challenges, our focus is on the interaction techniques that are likely generalizable to interactive applications for other domains. We explore a very direct style of interaction where the user interacts with the virtual data using direct finger manipulations on and around the enclosure surrounding the displayed 3D volumetric image.

  11. 3D Spray Droplet Distributions in Sneezes

    NASA Astrophysics Data System (ADS)

    Techet, Alexandra; Scharfman, Barry; Bourouiba, Lydia

    2015-11-01

    3D spray droplet clouds generated during human sneezing are investigated using the Synthetic Aperture Feature Extraction (SAFE) method, which relies on light field imaging (LFI) and synthetic aperture (SA) refocusing computational photographic techniques. An array of nine high-speed cameras are used to image sneeze droplets and tracked the droplets in 3D space and time (3D + T). An additional high-speed camera is utilized to track the motion of the head during sneezing. In the SAFE method, the raw images recorded by each camera in the array are preprocessed and binarized, simplifying post processing after image refocusing and enabling the extraction of feature sizes and positions in 3D + T. These binary images are refocused using either additive or multiplicative methods, combined with thresholding. Sneeze droplet centroids, radii, distributions and trajectories are determined and compared with existing data. The reconstructed 3D droplet centroids and radii enable a more complete understanding of the physical extent and fluid dynamics of sneeze ejecta. These measurements are important for understanding the infectious disease transmission potential of sneezes in various indoor environments.

  12. The 2003 phreatomagmatic eruptions of Anatahan volcano - Textural and petrologic features of deposits at an emergent island volcano

    USGS Publications Warehouse

    Pallister, J.S.; Trusdell, F.A.; Brownfield, I.K.; Siems, D.F.; Budahn, J.R.; Sutley, S.F.

    2005-01-01

    Stratigraphic and field data are used in conjunction with textural and chemical evidence (including data from scanning electron microscope, electron microprobe, X-ray fluorescence, X-ray diffraction, and instrumental neutron activation analysis) to establish that the 2003 eruption of Anatahan volcano was mainly phreatomagmatic, dominated by explosive interaction of homogeneous composition low-viscosity crystal-poor andesite magma with water. The hydromagmatic mode of eruption contributed to the significant height of initial eruptive columns and to the excavation and eruption of altered rock debris from the sub-volcanic hydrothermal system. Volatile contents of glass inclusions in equilibrium phenocrysts less abundances of these constituents in matrix glass times the estimated mass of juvenile magma indicate minimum emissions of 19 kt SO2 and 13 kt Cl. This petrologic estimate of SO2 emission is an order-of-magnitude less than an estimate from TOMS. Similarly, inferred magma volumes from the petrologic data are an order of magnitude greater than those modeled from deformation data. Both discrepancies indicate additional sources of volatiles, likely derived from a separate fluid phase in the magma. The paucity of near-source volcanic-tectonic earthquakes preceding the eruption, and the dominance of sustained long-period tremor are attributed to the ease of ascent of the hot low-viscosity andesite, followed by a shallow phreatomagmatic mode of eruption. Phreatomagmatic eruptions are probably more common at emergent tropical island volcanoes, where shallow fresh-water lenses occur at near-sea-level vents. These relations suggest that phreatomagmatic explosions contributed to the formation of many of the near-sea-level craters and possibly even to the small calderas at the other Mariana islands.

  13. 3D Elevation Program—Virtual USA in 3D

    USGS Publications Warehouse

    Lukas, Vicki; Stoker, J.M.

    2016-01-01

    The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) uses a laser system called ‘lidar’ (light detection and ranging) to create a virtual reality map of the Nation that is very accurate. 3D maps have many uses with new uses being discovered all the time.  

  14. 3D Elevation Program—Virtual USA in 3D

    USGS Publications Warehouse

    Lukas, Vicki; Stoker, J.M.

    2016-04-14

    The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) uses a laser system called ‘lidar’ (light detection and ranging) to create a virtual reality map of the Nation that is very accurate. 3D maps have many uses with new uses being discovered all the time.  

  15. 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.

  16. Quality of 3D Models Generated by SFM Technology

    NASA Astrophysics Data System (ADS)

    Marčiš, Marián

    2013-12-01

    Using various types of automation in digital photogrammetry is associated with questions such as the accuracy of a 3D model generated on various types of surfaces and textures, the financial costs of the equipment needed, and also the time costs of the processing. This topic deals with the actual technology of computer vision, which allows the automated exterior orientation of images, camera calibration, and the generation of 3D models directly from images of the object itself, based on the automatic detection of significant points. Detailed testing is done using the Agisoft PhotoScan system, and the camera configuration is solved with respect to the accuracy of the 3D model generated and the time consumption of the calculations for the different types of textures and the different settings for the processing.

  17. 3D printed diffractive terahertz lenses.

    PubMed

    Furlan, Walter D; Ferrando, Vicente; Monsoriu, Juan A; Zagrajek, Przemysław; Czerwińska, Elżbieta; Szustakowski, Mieczysław

    2016-04-15

    A 3D printer was used to realize custom-made diffractive THz lenses. After testing several materials, phase binary lenses with periodic and aperiodic radial profiles were designed and constructed in polyamide material to work at 0.625 THz. The nonconventional focusing properties of such lenses were assessed by computing and measuring their axial point spread function (PSF). Our results demonstrate that inexpensive 3D printed THz diffractive lenses can be reliably used in focusing and imaging THz systems. Diffractive THz lenses with unprecedented features, such as extended depth of focus or bifocalization, have been demonstrated. PMID:27082335

  18. 3D Wavelet-Based Filter and Method

    DOEpatents

    Moss, William C.; Haase, Sebastian; Sedat, John W.

    2008-08-12

    A 3D wavelet-based filter for visualizing and locating structural features of a user-specified linear size in 2D or 3D image data. The only input parameter is a characteristic linear size of the feature of interest, and the filter output contains only those regions that are correlated with the characteristic size, thus denoising the image.

  19. Contrast negation and texture synthesis differentially disrupt natural texture appearance.

    PubMed

    Balas, Benjamin

    2012-01-01

    Natural textures have characteristic image statistics that make them discriminable from unnatural textures. For example, both contrast negation and texture synthesis alter the appearance of natural textures even though each manipulation preserves some features while disrupting others. Here, we examined the extent to which contrast negation and texture synthesis each introduce or remove critical perceptual features for discriminating unnatural textures from natural textures. We find that both manipulations remove information that observers use for distinguishing natural textures from transformed versions of the same patterns, but do so in different ways. Texture synthesis removes information that is relevant for discrimination in both abstract patterns and ecologically valid textures, and we also observe a category-dependent asymmetry for identifying an "oddball" real texture among synthetic distractors. Contrast negation exhibits no such asymmetry, and also does not impact discrimination performance in abstract patterns. We discuss our results in the context of the visual system's tuning to ecologically relevant patterns and other results describing sensitivity to higher-order statistics in texture patterns.

  20. Fabrication of 3D tissue equivalent: an in vitro platform for understanding collagen evolution in healthy and diseased models

    NASA Astrophysics Data System (ADS)

    Urciuolo, F.; Imparato, G.; Casale, C.; Scamardella, S.; Netti, P.

    2013-04-01

    In this study we realized a three-dimensional human dermis equivalent (3D-HDE) and, by exploiting multi-photon microscopy (MPM) we validated its use as an in vitro model to study collagen network re-arrangement under simulated solar exposure. The realization of 3D-HDE has been pursed by means of a bottom-up tissue engineering strategy that comprises firstly the fabrication of micron sized tissue building blocks and then their assembly in a 3D tissue construct. The building blocks injected in a maturation chamber, and cultured under optimized culture condition, were able to fuse due to the establishment of cell-cell and cell-extra cellular matrix (ECM) interactions that induced a biological sintering process resulting in 3D-HDE production. The final 3D tissue was made-up by fibroblasts embedded in their own ECM rich in endogenous collagen type I, resembling the composition and the architecture of native human dermis. Second Harmonic Generation (SHG) and Two-Photon Excited Fluorescence (TPEF) imaging have been exploited to assess modification in collagen assembly before and after UV irradiation. Textural features and SHG to TPFE ratio of the endogenous ECM within 3D-HDE have been shown to vary after UVA irradiation, proving the hypothesis that the 3DHDE realized can be used as biological platform in vitro to study ECM modifications induced by photo-damage.

  1. Market study: 3-D eyetracker

    NASA Technical Reports Server (NTRS)

    1977-01-01

    A market study of a proposed version of a 3-D eyetracker for initial use at NASA's Ames Research Center was made. The commercialization potential of a simplified, less expensive 3-D eyetracker was ascertained. Primary focus on present and potential users of eyetrackers, as well as present and potential manufacturers has provided an effective means of analyzing the prospects for commercialization.

  2. LLNL-Earth3D

    SciTech Connect

    2013-10-01

    Earth3D is a computer code designed to allow fast calculation of seismic rays and travel times through a 3D model of the Earth. LLNL is using this for earthquake location and global tomography efforts and such codes are of great interest to the Earth Science community.

  3. [3-D ultrasound in gastroenterology].

    PubMed

    Zoller, W G; Liess, H

    1994-06-01

    Three-dimensional (3D) sonography represents a development of noninvasive diagnostic imaging by real-time two-dimensional (2D) sonography. The use of transparent rotating scans, comparable to a block of glass, generates a 3D effect. The objective of the present study was to optimate 3D presentation of abdominal findings. Additional investigations were made with a new volumetric program to determine the volume of selected findings of the liver. The results were compared with the estimated volumes of 2D sonography and 2D computer tomography (CT). For the processing of 3D images, typical parameter constellations were found for the different findings, which facilitated processing of 3D images. In more than 75% of the cases examined we found an optimal 3D presentation of sonographic findings with respect to the evaluation criteria developed by us for the 3D imaging of processed data. Great differences were found for the estimated volumes of the findings of the liver concerning the three different techniques applied. 3D ultrasound represents a valuable method to judge morphological appearance in abdominal findings. The possibility of volumetric measurements enlarges its potential diagnostic significance. Further clinical investigations are necessary to find out if definite differentiation between benign and malign findings is possible.

  4. Euro3D Science Conference

    NASA Astrophysics Data System (ADS)

    Walsh, J. R.

    2004-02-01

    The Euro3D RTN is an EU funded Research Training Network to foster the exploitation of 3D spectroscopy in Europe. 3D spectroscopy is a general term for spectroscopy of an area of the sky and derives its name from its two spatial + one spectral dimensions. There are an increasing number of instruments which use integral field devices to achieve spectroscopy of an area of the sky, either using lens arrays, optical fibres or image slicers, to pack spectra of multiple pixels on the sky (``spaxels'') onto a 2D detector. On account of the large volume of data and the special methods required to reduce and analyse 3D data, there are only a few centres of expertise and these are mostly involved with instrument developments. There is a perceived lack of expertise in 3D spectroscopy spread though the astronomical community and its use in the armoury of the observational astronomer is viewed as being highly specialised. For precisely this reason the Euro3D RTN was proposed to train young researchers in this area and develop user tools to widen the experience with this particular type of data in Europe. The Euro3D RTN is coordinated by Martin M. Roth (Astrophysikalisches Institut Potsdam) and has been running since July 2002. The first Euro3D science conference was held in Cambridge, UK from 22 to 23 May 2003. The main emphasis of the conference was, in keeping with the RTN, to expose the work of the young post-docs who are funded by the RTN. In addition the team members from the eleven European institutes involved in Euro3D also presented instrumental and observational developments. The conference was organized by Andy Bunker and held at the Institute of Astronomy. There were over thirty participants and 26 talks covered the whole range of application of 3D techniques. The science ranged from Galactic planetary nebulae and globular clusters to kinematics of nearby galaxies out to objects at high redshift. Several talks were devoted to reporting recent observations with newly

  5. Display of real-time 3D sensor data in a DVE system

    NASA Astrophysics Data System (ADS)

    Völschow, Philipp; Münsterer, Thomas; Strobel, Michael; Kuhn, Michael

    2016-05-01

    This paper describes the implementation of displaying real-time processed LiDAR 3D data in a DVE pilot assistance system. The goal is to display to the pilot a comprehensive image of the surrounding world without misleading or cluttering information. 3D data which can be attributed, i.e. classified, to terrain or predefined obstacle classes is depicted differently from data belonging to elevated objects which could not be classified. Display techniques may be different for head-down and head-up displays to avoid cluttering of the outside view in the latter case. While terrain is shown as shaded surfaces with grid structures or as grid structures alone, respectively, classified obstacles are typically displayed with obstacle symbols only. Data from objects elevated above ground are displayed as shaded 3D points in space. In addition the displayed 3D points are accumulated over a certain time frame allowing on the one hand side a cohesive structure being displayed and on the other hand displaying moving objects correctly. In addition color coding or texturing can be applied based on known terrain features like land use.

  6. 3D printing in dentistry.

    PubMed

    Dawood, A; Marti Marti, B; Sauret-Jackson, V; Darwood, A

    2015-12-01

    3D printing has been hailed as a disruptive technology which will change manufacturing. Used in aerospace, defence, art and design, 3D printing is becoming a subject of great interest in surgery. The technology has a particular resonance with dentistry, and with advances in 3D imaging and modelling technologies such as cone beam computed tomography and intraoral scanning, and with the relatively long history of the use of CAD CAM technologies in dentistry, it will become of increasing importance. Uses of 3D printing include the production of drill guides for dental implants, the production of physical models for prosthodontics, orthodontics and surgery, the manufacture of dental, craniomaxillofacial and orthopaedic implants, and the fabrication of copings and frameworks for implant and dental restorations. This paper reviews the types of 3D printing technologies available and their various applications in dentistry and in maxillofacial surgery. PMID:26657435

  7. PLOT3D user's manual

    NASA Technical Reports Server (NTRS)

    Walatka, Pamela P.; Buning, Pieter G.; Pierce, Larry; Elson, Patricia A.

    1990-01-01

    PLOT3D is a computer graphics program designed to visualize the grids and solutions of computational fluid dynamics. Seventy-four functions are available. Versions are available for many systems. PLOT3D can handle multiple grids with a million or more grid points, and can produce varieties of model renderings, such as wireframe or flat shaded. Output from PLOT3D can be used in animation programs. The first part of this manual is a tutorial that takes the reader, keystroke by keystroke, through a PLOT3D session. The second part of the manual contains reference chapters, including the helpfile, data file formats, advice on changing PLOT3D, and sample command files.

  8. 3D printing in dentistry.

    PubMed

    Dawood, A; Marti Marti, B; Sauret-Jackson, V; Darwood, A

    2015-12-01

    3D printing has been hailed as a disruptive technology which will change manufacturing. Used in aerospace, defence, art and design, 3D printing is becoming a subject of great interest in surgery. The technology has a particular resonance with dentistry, and with advances in 3D imaging and modelling technologies such as cone beam computed tomography and intraoral scanning, and with the relatively long history of the use of CAD CAM technologies in dentistry, it will become of increasing importance. Uses of 3D printing include the production of drill guides for dental implants, the production of physical models for prosthodontics, orthodontics and surgery, the manufacture of dental, craniomaxillofacial and orthopaedic implants, and the fabrication of copings and frameworks for implant and dental restorations. This paper reviews the types of 3D printing technologies available and their various applications in dentistry and in maxillofacial surgery.

  9. Mimicking human texture classification

    NASA Astrophysics Data System (ADS)

    van Rikxoort, Eva M.; van den Broek, Egon L.; Schouten, Theo E.

    2005-03-01

    In an attempt to mimic human (colorful) texture classification by a clustering algorithm three lines of research have been encountered, in which as test set 180 texture images (both their color and gray-scale equivalent) were drawn from the OuTex and VisTex databases. First, a k-means algorithm was applied with three feature vectors, based on color/gray values, four texture features, and their combination. Second, 18 participants clustered the images using a newly developed card sorting program. The mutual agreement between the participants was 57% and 56% and between the algorithm and the participants it was 47% and 45%, for respectively color and gray-scale texture images. Third, in a benchmark, 30 participants judged the algorithms' clusters with gray-scale textures as more homogeneous then those with colored textures. However, a high interpersonal variability was present for both the color and the gray-scale clusters. So, despite the promising results, it is questionable whether average human texture classification can be mimicked (if it exists at all).

  10. Use of sourdough made with quinoa (Chenopodium quinoa) flour and autochthonous selected lactic acid bacteria for enhancing the nutritional, textural and sensory features of white bread.

    PubMed

    Rizzello, Carlo Giuseppe; Lorusso, Anna; Montemurro, Marco; Gobbetti, Marco

    2016-06-01

    Lactic acid bacteria were isolated and identified from quinoa flour, spontaneously fermented quinoa dough, and type I quinoa sourdough. Strains were further selected based on acidification and proteolytic activities. Selected Lactobacillus plantarum T6B10 and Lactobacillus rossiae T0A16 were used as mixed starter to get quinoa sourdough. Compared to non-fermented flour, organic acids, free amino acids, soluble fibers, total phenols, phytase and antioxidant activities, and in vitro protein digestibility markedly increased during fermentation. A wheat bread was made using 20% (w/w) of quinoa sourdough, and compared to baker's yeast wheat breads manufactured with or without quinoa flour. The use of quinoa sourdough improved the chemical, textural, and sensory features of wheat bread, showing better performances compared to the use of quinoa flour. Protein digestibility and quality, and the rate of starch hydrolysis were also nutritional features that markedly improved using quinoa sourdough as an ingredient. This study exploited the potential of quinoa flour through sourdough fermentation. A number of advantages encouraged the manufacture of novel and healthy leavened baked goods.

  11. Use of sourdough made with quinoa (Chenopodium quinoa) flour and autochthonous selected lactic acid bacteria for enhancing the nutritional, textural and sensory features of white bread.

    PubMed

    Rizzello, Carlo Giuseppe; Lorusso, Anna; Montemurro, Marco; Gobbetti, Marco

    2016-06-01

    Lactic acid bacteria were isolated and identified from quinoa flour, spontaneously fermented quinoa dough, and type I quinoa sourdough. Strains were further selected based on acidification and proteolytic activities. Selected Lactobacillus plantarum T6B10 and Lactobacillus rossiae T0A16 were used as mixed starter to get quinoa sourdough. Compared to non-fermented flour, organic acids, free amino acids, soluble fibers, total phenols, phytase and antioxidant activities, and in vitro protein digestibility markedly increased during fermentation. A wheat bread was made using 20% (w/w) of quinoa sourdough, and compared to baker's yeast wheat breads manufactured with or without quinoa flour. The use of quinoa sourdough improved the chemical, textural, and sensory features of wheat bread, showing better performances compared to the use of quinoa flour. Protein digestibility and quality, and the rate of starch hydrolysis were also nutritional features that markedly improved using quinoa sourdough as an ingredient. This study exploited the potential of quinoa flour through sourdough fermentation. A number of advantages encouraged the manufacture of novel and healthy leavened baked goods. PMID:26919812

  12. Adaptive noise suppression technique for dense 3D point cloud reconstructions from monocular vision

    NASA Astrophysics Data System (ADS)

    Diskin, Yakov; Asari, Vijayan K.

    2012-10-01

    Mobile vision-based autonomous vehicles use video frames from multiple angles to construct a 3D model of their environment. In this paper, we present a post-processing adaptive noise suppression technique to enhance the quality of the computed 3D model. Our near real-time reconstruction algorithm uses each pair of frames to compute the disparities of tracked feature points to translate the distance a feature has traveled within the frame in pixels into real world depth values. As a result these tracked feature points are plotted to form a dense and colorful point cloud. Due to the inevitable small vibrations in the camera and the mismatches within the feature tracking algorithm, the point cloud model contains a significant amount of misplaced points appearing as noise. The proposed noise suppression technique utilizes the spatial information of each point to unify points of similar texture and color into objects while simultaneously removing noise dissociated with any nearby objects. The noise filter combines all the points of similar depth into 2D layers throughout the point cloud model. By applying erosion and dilation techniques we are able to eliminate the unwanted floating points while retaining points of larger objects. To reverse the compression process, we transform the 2D layer back into the 3D model allowing points to return to their original position without the attached noise components. We evaluate the resulting noiseless point cloud by utilizing an unmanned ground vehicle to perform obstacle avoidance tasks. The contribution of the noise suppression technique is measured by evaluating the accuracy of the 3D reconstruction.

  13. Voxel-based texture analysis of the brain.

    PubMed

    Maani, Rouzbeh; Yang, Yee Hong; Kalra, Sanjay

    2015-01-01

    This paper presents a novel voxel-based method for texture analysis of brain images. Texture analysis is a powerful quantitative approach for analyzing voxel intensities and their interrelationships, but has been thus far limited to analyzing regions of interest. The proposed method provides a 3D statistical map comparing texture features on a voxel-by-voxel basis. The validity of the method was examined on artificially generated effects as well as on real MRI data in Alzheimer's Disease (AD). The artificially generated effects included hyperintense and hypointense signals added to T1-weighted brain MRIs from 30 healthy subjects. The AD dataset included 30 patients with AD and 30 age/sex matched healthy control subjects. The proposed method detected artificial effects with high accuracy and revealed statistically significant differences between the AD and control groups. This paper extends the usage of texture analysis beyond the current region of interest analysis to voxel-by-voxel 3D statistical mapping and provides a hypothesis-free analysis tool to study cerebral pathology in neurological diseases.

  14. Voxel-Based Texture Analysis of the Brain

    PubMed Central

    Maani, Rouzbeh; Yang, Yee Hong; Kalra, Sanjay

    2015-01-01

    This paper presents a novel voxel-based method for texture analysis of brain images. Texture analysis is a powerful quantitative approach for analyzing voxel intensities and their interrelationships, but has been thus far limited to analyzing regions of interest. The proposed method provides a 3D statistical map comparing texture features on a voxel-by-voxel basis. The validity of the method was examined on artificially generated effects as well as on real MRI data in Alzheimer's Disease (AD). The artificially generated effects included hyperintense and hypointense signals added to T1-weighted brain MRIs from 30 healthy subjects. The AD dataset included 30 patients with AD and 30 age/sex matched healthy control subjects. The proposed method detected artificial effects with high accuracy and revealed statistically significant differences between the AD and control groups. This paper extends the usage of texture analysis beyond the current region of interest analysis to voxel-by-voxel 3D statistical mapping and provides a hypothesis-free analysis tool to study cerebral pathology in neurological diseases. PMID:25756621

  15. PLOT3D/AMES, DEC VAX VMS VERSION USING DISSPLA (WITH TURB3D)

    NASA Technical Reports Server (NTRS)

    Buning, P.

    1994-01-01

    PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into

  16. PLOT3D/AMES, DEC VAX VMS VERSION USING DISSPLA (WITHOUT TURB3D)

    NASA Technical Reports Server (NTRS)

    Buning, P. G.

    1994-01-01

    PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into

  17. ICER-3D Hyperspectral Image Compression Software

    NASA Technical Reports Server (NTRS)

    Xie, Hua; Kiely, Aaron; Klimesh, matthew; Aranki, Nazeeh

    2010-01-01

    Software has been developed to implement the ICER-3D algorithm. ICER-3D effects progressive, three-dimensional (3D), wavelet-based compression of hyperspectral images. If a compressed data stream is truncated, the progressive nature of the algorithm enables reconstruction of hyperspectral data at fidelity commensurate with the given data volume. The ICER-3D software is capable of providing either lossless or lossy compression, and incorporates an error-containment scheme to limit the effects of data loss during transmission. The compression algorithm, which was derived from the ICER image compression algorithm, includes wavelet-transform, context-modeling, and entropy coding subalgorithms. The 3D wavelet decomposition structure used by ICER-3D exploits correlations in all three dimensions of sets of hyperspectral image data, while facilitating elimination of spectral ringing artifacts, using a technique summarized in "Improving 3D Wavelet-Based Compression of Spectral Images" (NPO-41381), NASA Tech Briefs, Vol. 33, No. 3 (March 2009), page 7a. Correlation is further exploited by a context-modeling subalgorithm, which exploits spectral dependencies in the wavelet-transformed hyperspectral data, using an algorithm that is summarized in "Context Modeler for Wavelet Compression of Hyperspectral Images" (NPO-43239), which follows this article. An important feature of ICER-3D is a scheme for limiting the adverse effects of loss of data during transmission. In this scheme, as in the similar scheme used by ICER, the spatial-frequency domain is partitioned into rectangular error-containment regions. In ICER-3D, the partitions extend through all the wavelength bands. The data in each partition are compressed independently of those in the other partitions, so that loss or corruption of data from any partition does not affect the other partitions. Furthermore, because compression is progressive within each partition, when data are lost, any data from that partition received

  18. Handheld camera 3D modeling system using multiple reference panels

    NASA Astrophysics Data System (ADS)

    Fujimura, Kouta; Oue, Yasuhiro; Terauchi, Tomoya; Emi, Tetsuichi

    2002-03-01

    A novel 3D modeling system in which a target object is easily captured and modeled by using a hand-held camera with several reference panels is presented in this paper. The reference panels are designed to be able to obtain the camera position and discriminate between each other. A conventional 3D modeling system using a reference panel has several restrictions regarding the target object, specifically the size and its location. Our system uses multiple reference panels, which are set around the target object to remove these restrictions. The main features of this system are as follows: 1) The whole shape and photo-realistic textures of the target object can be digitized based on several still images or a movie captured by using a hand-held camera; as well as each location of the camera that can be calculated using the reference panels. 2) Our system can be provided as a software product only. That means there are no special requirements for hardware; even the reference panels , because they can be printed from image files or software. 3) This system can be applied to digitize a larger object. In the experiments, we developed and used an interactive region selection tool to detect the silhouette on each image instead of using the chroma -keying method. We have tested our system with a toy object. The calculation time is about 10 minutes (except for the capturing the images and extracting the silhouette by using our tool) on a personal computer with a Pentium-III processor (600MHz) and 320MB memory. However, it depends on how complex the images are and how many images you use. Our future plan is to evaluate the system with various kind of objects, specifically, large ones in outdoor environments.

  19. Texture mapping based on multiple aerial imageries in urban areas

    NASA Astrophysics Data System (ADS)

    Zhou, Guoqing; Ye, Siqi; Wang, Yuefeng; Han, Caiyun; Wang, Chenxi

    2015-12-01

    In the realistic 3D model reconstruction, the requirement of the texture is very high. Texture is one of the key factors that affecting realistic of the model and using texture mapping technology to realize. In this paper we present a practical approach of texture mapping based on photogrammetry theory from multiple aerial imageries in urban areas. By collinearity equation to matching the model and imageries, and in order to improving the quality of texture, we describe an automatic approach for select the optimal texture to realized 3D building from the aerial imageries of many strip. The texture of buildings can be automatically matching by the algorithm. The experimental results show that the platform of texture mapping process has a high degree of automation and improve the efficiency of the 3D modeling reconstruction.

  20. Sensing and compressing 3-D models

    SciTech Connect

    Krumm, J.

    1998-02-01

    The goal of this research project was to create a passive and robust computer vision system for producing 3-D computer models of arbitrary scenes. Although the authors were unsuccessful in achieving the overall goal, several components of this research have shown significant potential. Of particular interest is the application of parametric eigenspace methods for planar pose measurement of partially occluded objects in gray-level images. The techniques presented provide a simple, accurate, and robust solution to the planar pose measurement problem. In addition, the representational efficiency of eigenspace methods used with gray-level features were successfully extended to binary features, which are less sensitive to illumination changes. The results of this research are presented in two papers that were written during the course of this project. The papers are included in sections 2 and 3. The first section of this report summarizes the 3-D modeling efforts.

  1. Spatially resolved 3D noise

    NASA Astrophysics Data System (ADS)

    Haefner, David P.; Preece, Bradley L.; Doe, Joshua M.; Burks, Stephen D.

    2016-05-01

    When evaluated with a spatially uniform irradiance, an imaging sensor exhibits both spatial and temporal variations, which can be described as a three-dimensional (3D) random process considered as noise. In the 1990s, NVESD engineers developed an approximation to the 3D power spectral density (PSD) for noise in imaging systems known as 3D noise. In this correspondence, we describe how the confidence intervals for the 3D noise measurement allows for determination of the sampling necessary to reach a desired precision. We then apply that knowledge to create a smaller cube that can be evaluated spatially across the 2D image giving the noise as a function of position. The method presented here allows for both defective pixel identification and implements the finite sampling correction matrix. In support of the reproducible research effort, the Matlab functions associated with this work can be found on the Mathworks file exchange [1].

  2. Autofocus for 3D imaging

    NASA Astrophysics Data System (ADS)

    Lee-Elkin, Forest

    2008-04-01

    Three dimensional (3D) autofocus remains a significant challenge for the development of practical 3D multipass radar imaging. The current 2D radar autofocus methods are not readily extendable across sensor passes. We propose a general framework that allows a class of data adaptive solutions for 3D auto-focus across passes with minimal constraints on the scene contents. The key enabling assumption is that portions of the scene are sparse in elevation which reduces the number of free variables and results in a system that is simultaneously solved for scatterer heights and autofocus parameters. The proposed method extends 2-pass interferometric synthetic aperture radar (IFSAR) methods to an arbitrary number of passes allowing the consideration of scattering from multiple height locations. A specific case from the proposed autofocus framework is solved and demonstrates autofocus and coherent multipass 3D estimation across the 8 passes of the "Gotcha Volumetric SAR Data Set" X-Band radar data.

  3. Accepting the T3D

    SciTech Connect

    Rich, D.O.; Pope, S.C.; DeLapp, J.G.

    1994-10-01

    In April, a 128 PE Cray T3D was installed at Los Alamos National Laboratory`s Advanced Computing Laboratory as part of the DOE`s High-Performance Parallel Processor Program (H4P). In conjunction with CRI, the authors implemented a 30 day acceptance test. The test was constructed in part to help them understand the strengths and weaknesses of the T3D. In this paper, they briefly describe the H4P and its goals. They discuss the design and implementation of the T3D acceptance test and detail issues that arose during the test. They conclude with a set of system requirements that must be addressed as the T3D system evolves.

  4. Cue combination for 3D location judgements.

    PubMed

    Svarverud, Ellen; Gilson, Stuart J; Glennerster, Andrew

    2010-01-01

    Cue combination rules have often been applied to the perception of surface shape but not to judgements of object location. Here, we used immersive virtual reality to explore the relationship between different cues to distance. Participants viewed a virtual scene and judged the change in distance of an object presented in two intervals, where the scene changed in size between intervals (by a factor of between 0.25 and 4). We measured thresholds for detecting a change in object distance when there were only 'physical' (stereo and motion parallax) or 'texture-based' cues (independent of the scale of the scene) and used these to predict biases in a distance matching task. Under a range of conditions, in which the viewing distance and position of the target relative to other objects was varied, the ratio of 'physical' to 'texture-based' thresholds was a good predictor of biases in the distance matching task. The cue combination approach, which successfully accounts for our data, relies on quite different principles from those underlying traditional models of 3D reconstruction. PMID:20143898

  5. Cue combination for 3D location judgements

    PubMed Central

    Svarverud, Ellen; Gilson, Stuart J.; Glennerster, Andrew

    2010-01-01

    Cue combination rules have often been applied to the perception of surface shape but not to judgements of object location. Here, we used immersive virtual reality to explore the relationship between different cues to distance. Participants viewed a virtual scene and judged the change in distance of an object presented in two intervals, where the scene changed in size between intervals (by a factor of between 0.25 and 4). We measured thresholds for detecting a change in object distance when there were only ‘physical’ (stereo and motion parallax) or ‘texture-based’ cues (independent of the scale of the scene) and used these to predict biases in a distance matching task. Under a range of conditions, in which the viewing distance and position of the target relative to other objects was varied, the ratio of ‘physical’ to ‘texture-based’ thresholds was a good predictor of biases in the distance matching task. The cue combination approach, which successfully accounts for our data, relies on quite different principles from those underlying traditional models of 3D reconstruction. PMID:20143898

  6. PLOT3D/AMES, GENERIC UNIX VERSION USING DISSPLA (WITH TURB3D)

    NASA Technical Reports Server (NTRS)

    Buning, P.

    1994-01-01

    PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into

  7. PLOT3D/AMES, GENERIC UNIX VERSION USING DISSPLA (WITHOUT TURB3D)

    NASA Technical Reports Server (NTRS)

    Buning, P.

    1994-01-01

    PLOT3D is an interactive graphics program designed to help scientists visualize computational fluid dynamics (CFD) grids and solutions. Today, supercomputers and CFD algorithms can provide scientists with simulations of such highly complex phenomena that obtaining an understanding of the simulations has become a major problem. Tools which help the scientist visualize the simulations can be of tremendous aid. PLOT3D/AMES offers more functions and features, and has been adapted for more types of computers than any other CFD graphics program. Version 3.6b+ is supported for five computers and graphic libraries. Using PLOT3D, CFD physicists can view their computational models from any angle, observing the physics of problems and the quality of solutions. As an aid in designing aircraft, for example, PLOT3D's interactive computer graphics can show vortices, temperature, reverse flow, pressure, and dozens of other characteristics of air flow during flight. As critical areas become obvious, they can easily be studied more closely using a finer grid. PLOT3D is part of a computational fluid dynamics software cycle. First, a program such as 3DGRAPE (ARC-12620) helps the scientist generate computational grids to model an object and its surrounding space. Once the grids have been designed and parameters such as the angle of attack, Mach number, and Reynolds number have been specified, a "flow-solver" program such as INS3D (ARC-11794 or COS-10019) solves the system of equations governing fluid flow, usually on a supercomputer. Grids sometimes have as many as two million points, and the "flow-solver" produces a solution file which contains density, x- y- and z-momentum, and stagnation energy for each grid point. With such a solution file and a grid file containing up to 50 grids as input, PLOT3D can calculate and graphically display any one of 74 functions, including shock waves, surface pressure, velocity vectors, and particle traces. PLOT3D's 74 functions are organized into

  8. 3D printing of a multifunctional nanocomposite helical liquid sensor

    NASA Astrophysics Data System (ADS)

    Guo, Shuang-Zhuang; Yang, Xuelu; Heuzey, Marie-Claude; Therriault, Daniel

    2015-04-01

    A multifunctional 3D liquid sensor made of a PLA/MWCNT nanocomposite and shaped as a freeform helical structure was fabricated by solvent-cast 3D printing. The 3D liquid sensor featured a relatively high electrical conductivity, the functionality of liquid trapping due to its helical configuration, and an excellent sensitivity and selectivity even for a short immersion into solvents.A multifunctional 3D liquid sensor made of a PLA/MWCNT nanocomposite and shaped as a freeform helical structure was fabricated by solvent-cast 3D printing. The 3D liquid sensor featured a relatively high electrical conductivity, the functionality of liquid trapping due to its helical configuration, and an excellent sensitivity and selectivity even for a short immersion into solvents. Electronic supplementary information (ESI) available. See DOI: 10.1039/c5nr00278h