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Sample records for 3d texture features

  1. 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

  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. PMID:25942404

  3. Combination of 3D skin surface texture features and 2D ABCD features for improved melanoma diagnosis.

    PubMed

    Ding, Yi; John, Nigel W; Smith, Lyndon; Sun, Jiuai; Smith, Melvyn

    2015-10-01

    Two-dimensional asymmetry, border irregularity, colour variegation and diameter (ABCD) features are important indicators currently used for computer-assisted diagnosis of malignant melanoma (MM); however, they often prove to be insufficient to make a convincing diagnosis. Previous work has demonstrated that 3D skin surface normal features in the form of tilt and slant pattern disruptions are promising new features independent from the existing 2D ABCD features. This work investigates that whether improved lesion classification can be achieved by combining the 3D features with the 2D ABCD features. Experiments using a nonlinear support vector machine classifier show that many combinations of the 2D ABCD features and the 3D features can give substantially better classification accuracy than using (1) single features and (2) many combinations of the 2D ABCD features. The best 2D and 3D feature combination includes the overall 3D skin surface disruption, the asymmetry and all the three colour channel features. It gives an overall 87.8 % successful classification, which is better than the best single feature with 78.0 % and the best 2D feature combination with 83.1 %. These demonstrate that (1) the 3D features have additive values to improve the existing lesion classification and (2) combining the 3D feature with all the 2D features does not lead to the best lesion classification. The two ABCD features not selected by the best 2D and 3D combination, namely (1) the border feature and (2) the diameter feature, were also studied in separate experiments. It found that inclusion of either feature in the 2D and 3D combination can successfully classify 3 out of 4 lesion groups. The only one group not accurately classified by either feature can be classified satisfactorily by the other. In both cases, they have shown better classification performances than those without the 3D feature in the combinations. This further demonstrates that (1) the 3D feature can be used to

  4. Recognition methods for 3D textured surfaces

    NASA Astrophysics Data System (ADS)

    Cula, Oana G.; Dana, Kristin J.

    2001-06-01

    Texture as a surface representation is the subject of a wide body of computer vision and computer graphics literature. While texture is always associated with a form of repetition in the image, the repeating quantity may vary. The texture may be a color or albedo variation as in a checkerboard, a paisley print or zebra stripes. Very often in real-world scenes, texture is instead due to a surface height variation, e.g. pebbles, gravel, foliage and any rough surface. Such surfaces are referred to here as 3D textured surfaces. Standard texture recognition algorithms are not appropriate for 3D textured surfaces because the appearance of these surfaces changes in a complex manner with viewing direction and illumination direction. Recent methods have been developed for recognition of 3D textured surfaces using a database of surfaces observed under varied imaging parameters. One of these methods is based on 3D textons obtained using K-means clustering of multiscale feature vectors. Another method uses eigen-analysis originally developed for appearance-based object recognition. In this work we develop a hybrid approach that employs both feature grouping and dimensionality reduction. The method is tested using the Columbia-Utrecht texture database and provides excellent recognition rates. The method is compared with existing recognition methods for 3D textured surfaces. A direct comparison is facilitated by empirical recognition rates from the same texture data set. The current method has key advantages over existing methods including requiring less prior information on both the training and novel images.

  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. Texture splats for 3D vector and scalar field visualization

    SciTech Connect

    Crawfis, R.A.; Max, N.

    1993-04-06

    Volume Visualization is becoming an important tool for understanding large 3D datasets. A popular technique for volume rendering is known as splatting. With new hardware architectures offering substantial improvements in the performance of rendering texture mapped objects, we present textured splats. An ideal reconstruction function for 3D signals is developed which can be used as a texture map for a splat. Extensions to the basic splatting technique are then developed to additionally represent vector fields.

  9. 3D texture analysis of solitary pulmonary nodules using co-occurrence matrix from volumetric lung CT images

    NASA Astrophysics Data System (ADS)

    Dhara, Ashis Kumar; Mukhopadhyay, Sudipta; Khandelwal, Niranjan

    2013-02-01

    In this paper we have investigated a new approach for texture features extraction using co-occurrence matrix from volumetric lung CT image. Traditionally texture analysis is performed in 2D and is suitable for images collected from 2D imaging modality. The use of 3D imaging modalities provide the scope of texture analysis from 3D object and 3D texture feature are more realistic to represent 3D object. In this work, Haralick's texture features are extended in 3D and computed from volumetric data considering 26 neighbors. The optimal texture features to characterize the internal structure of Solitary Pulmonary Nodules (SPN) are selected based on area under curve (AUC) values of ROC curve and p values from 2-tailed Student's t-test. The selected texture feature in 3D to represent SPN can be used in efficient Computer Aided Diagnostic (CAD) design plays an important role in fast and accurate lung cancer screening. The reduced number of input features to the CAD system will decrease the computational time and classification errors caused by irrelevant features. In the present work, SPN are classified from Ground Glass Nodule (GGN) using Artificial Neural Network (ANN) classifier considering top five 3D texture features and top five 2D texture features separately. The classification is performed on 92 SPN and 25 GGN from Imaging Database Resources Initiative (IDRI) public database and classification accuracy using 3D texture features and 2D texture features provide 97.17% and 89.1% respectively.

  10. Texture blending on 3D models using casual images

    NASA Astrophysics Data System (ADS)

    Liu, Xingming; Liu, Xiaoli; Li, Ameng; Liu, Junyao; Wang, Huijing

    2013-12-01

    In this paper, a method for constructing photorealistic textured model using 3D structured light digitizer is presented. Our method acquisition of range images and texture images around object, and range images are registered and integrated to construct geometric model of object. System is calibrated and poses of texture-camera are determined so that the relationship between texture and geometric model is established. After that, a global optimization is applied to assign compatible texture to adjacent surface and followed with a level procedure to remove artifacts due to vary lighting, approximate geometric model and so on. Lastly, we demonstrate the effect of our method on constructing a real model of world.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. Compression of point-texture 3D motion sequences

    NASA Astrophysics Data System (ADS)

    Song, In-Wook; Kim, Chang-Su; Lee, Sang-Uk

    2005-10-01

    In this work, we propose two compression algorithms for PointTexture 3D sequences: the octree-based scheme and the motion-compensated prediction scheme. The first scheme represents each PointTexture frame hierarchically using an octree. The geometry information in the octree nodes is encoded by the predictive partial matching (PPM) method. The encoder supports the progressive transmission of the 3D frame by transmitting the octree nodes in a top-down manner. The second scheme adopts the motion-compensated prediction to exploit the temporal correlation in 3D sequences. It first divides each frame into blocks, and then estimates the motion of each block using the block matching algorithm. In contrast to the motion-compensated 2D video coding, the prediction residual may take more bits than the original signal. Thus, in our approach, the motion compensation is used only for the blocks that can be replaced by the matching blocks. The other blocks are PPM-encoded. Extensive simulation results demonstrate that the proposed algorithms provide excellent compression performances.

  17. Automatic 3D segmentation of ultrasound images using atlas registration and statistical texture prior

    NASA Astrophysics Data System (ADS)

    Yang, Xiaofeng; Schuster, David; Master, Viraj; Nieh, Peter; Fenster, Aaron; Fei, Baowei

    2011-03-01

    We are developing a molecular image-directed, 3D ultrasound-guided, targeted biopsy system for improved detection of prostate cancer. In this paper, we propose an automatic 3D segmentation method for transrectal ultrasound (TRUS) images, which is based on multi-atlas registration and statistical texture prior. The atlas database includes registered TRUS images from previous patients and their segmented prostate surfaces. Three orthogonal Gabor filter banks are used to extract texture features from each image in the database. Patient-specific Gabor features from the atlas database are used to train kernel support vector machines (KSVMs) and then to segment the prostate image from a new patient. The segmentation method was tested in TRUS data from 5 patients. The average surface distance between our method and manual segmentation is 1.61 +/- 0.35 mm, indicating that the atlas-based automatic segmentation method works well and could be used for 3D ultrasound-guided prostate biopsy.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. Textural features for image classification

    NASA Technical Reports Server (NTRS)

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

    1973-01-01

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

  3. 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…

  4. 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.

  5. 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.

  6. 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.

  7. Learning the spherical harmonic features for 3-D face recognition.

    PubMed

    Liu, Peijiang; Wang, Yunhong; Huang, Di; Zhang, Zhaoxiang; Chen, Liming

    2013-03-01

    In this paper, a competitive method for 3-D face recognition (FR) using spherical harmonic features (SHF) is proposed. With this solution, 3-D face models are characterized by the energies contained in spherical harmonics with different frequencies, thereby enabling the capture of both gross shape and fine surface details of a 3-D facial surface. This is in clear contrast to most 3-D FR techniques which are either holistic or feature based, using local features extracted from distinctive points. First, 3-D face models are represented in a canonical representation, namely, spherical depth map, by which SHF can be calculated. Then, considering the predictive contribution of each SHF feature, especially in the presence of facial expression and occlusion, feature selection methods are used to improve the predictive performance and provide faster and more cost-effective predictors. Experiments have been carried out on three public 3-D face datasets, SHREC2007, FRGC v2.0, and Bosphorus, with increasing difficulties in terms of facial expression, pose, and occlusion, and which demonstrate the effectiveness of the proposed method. PMID:23060332

  8. 3D Riesz-wavelet based Covariance descriptors for texture classification of lung nodule tissue in CT.

    PubMed

    Cirujeda, Pol; Muller, Henning; Rubin, Daniel; Aguilera, Todd A; Loo, Billy W; Diehn, Maximilian; Binefa, Xavier; Depeursinge, Adrien

    2015-08-01

    In this paper we present a novel technique for characterizing and classifying 3D textured volumes belonging to different lung tissue types in 3D CT images. We build a volume-based 3D descriptor, robust to changes of size, rigid spatial transformations and texture variability, thanks to the integration of Riesz-wavelet features within a Covariance-based descriptor formulation. 3D Riesz features characterize the morphology of tissue density due to their response to changes in intensity in CT images. These features are encoded in a Covariance-based descriptor formulation: this provides a compact and flexible representation thanks to the use of feature variations rather than dense features themselves and adds robustness to spatial changes. Furthermore, the particular symmetric definite positive matrix form of these descriptors causes them to lay in a Riemannian manifold. Thus, descriptors can be compared with analytical measures, and accurate techniques from machine learning and clustering can be adapted to their spatial domain. Additionally we present a classification model following a "Bag of Covariance Descriptors" paradigm in order to distinguish three different nodule tissue types in CT: solid, ground-glass opacity, and healthy lung. The method is evaluated on top of an acquired dataset of 95 patients with manually delineated ground truth by radiation oncology specialists in 3D, and quantitative sensitivity and specificity values are presented. PMID:26738126

  9. 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. PMID:26372206

  10. LV motion tracking from 3D echocardiography using textural and structural information.

    PubMed

    Myronenko, Andriy; Song, Xubo; Sahn, David J

    2007-01-01

    Automated motion reconstruction of the left ventricle (LV) from 3D echocardiography provides insight into myocardium architecture and function. Low image quality and artifacts make 3D ultrasound image processing a challenging problem. We introduce a LV tracking method, which combines textural and structural information to overcome the image quality limitations. Our method automatically reconstructs the motion of the LV contour (endocardium and epicardium) from a sequence of 3D ultrasound images. PMID:18044597

  11. Simulation studies of defect textures and dynamics in 3-d cholesteric droplets

    NASA Astrophysics Data System (ADS)

    Gimenez-Pinto, Vianney; Lu, Shin-Ying; Selinger, Jonathan; Selinger, Robin

    2010-03-01

    We model defect texture evolution in droplets of cholesteric liquid crystals by solving for the dynamics of the nematic director field. In order to accommodate defects in the simulated texture, we use a finite difference formulation that is explicitly independent of sign reversal of the director at any position in the sample. Textures are visualized using either the Berreman 4x4 matrix method or by mapping free energy density. We study both planar and focal conic cholesteric textures in 3-d spherical and cylindrical droplets, with the goal to optimize device geometries for bistable display applications.

  12. Simulation studies of dynamics and defect textures in 3-d cholesteric droplets

    NASA Astrophysics Data System (ADS)

    Gimenez-Pinto, Vianney; Lu, Shin-Ying; Selinger, Jonathan; Selinger, Robin

    2010-04-01

    We model defect texture evolution in droplets of cholesteric liquid crystals by solving for the dynamics of the nematic director field. In order to accommodate defects in the simulated texture, we use a finite difference formulation that is explicitly independent of sign reversal of the director at any position in the sample. Textures are visualized using either the Berreman 4x4 matrix method or by mapping free energy density. We study both planar and focal conic cholesteric textures in 3-d spherical and cylindrical droplets, with the goal to optimize device geometries for bistable display applications.

  13. 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.

  14. 2D virtual texture on 3D real object with coded structured light

    NASA Astrophysics Data System (ADS)

    Molinier, Thierry; Fofi, David; Salvi, Joaquim; Gorria, Patrick

    2008-02-01

    Augmented reality is used to improve color segmentation on human body or on precious no touch artifacts. We propose a technique to project a synthesized texture on real object without contact. Our technique can be used in medical or archaeological application. By projecting a suitable set of light patterns onto the surface of a 3D real object and by capturing images with a camera, a large number of correspondences can be found and the 3D points can be reconstructed. We aim to determine these points of correspondence between cameras and projector from a scene without explicit points and normals. We then project an adjusted texture onto the real object surface. We propose a global and automatic method to virtually texture a 3D real object.

  15. 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.

  16. 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

  17. Texture feature based liver lesion classification

    NASA Astrophysics Data System (ADS)

    Doron, Yeela; Mayer-Wolf, Nitzan; Diamant, Idit; Greenspan, Hayit

    2014-03-01

    Liver lesion classification is a difficult clinical task. Computerized analysis can support clinical workflow by enabling more objective and reproducible evaluation. In this paper, we evaluate the contribution of several types of texture features for a computer-aided diagnostic (CAD) system which automatically classifies liver lesions from CT images. Based on the assumption that liver lesions of various classes differ in their texture characteristics, a variety of texture features were examined as lesion descriptors. Although texture features are often used for this task, there is currently a lack of detailed research focusing on the comparison across different texture features, or their combinations, on a given dataset. In this work we investigated the performance of Gray Level Co-occurrence Matrix (GLCM), Local Binary Patterns (LBP), Gabor, gray level intensity values and Gabor-based LBP (GLBP), where the features are obtained from a given lesion`s region of interest (ROI). For the classification module, SVM and KNN classifiers were examined. Using a single type of texture feature, best result of 91% accuracy, was obtained with Gabor filtering and SVM classification. Combination of Gabor, LBP and Intensity features improved the results to a final accuracy of 97%.

  18. 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.

  19. 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

  20. 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

  1. Face recognition using transform domain texture features

    NASA Astrophysics Data System (ADS)

    Rangaswamy, Y.; S K, Ramya; Raja, K. B.; K. R., Venugopal; Patnaik, L. M.

    2013-12-01

    The face recognition is an efficient biometric system to identify a person. In this paper, we propose Face Recognition using Transform Domain Texture Features (FRTDTF). The face images are preprocessed and two sets of texture features are extracted. In first feature set, the Discrete Wavelet Transform (DWT) is applied on face image and considered only high frequency sub band coefficients to extract edge information efficiently. The Dual Tree Complex Wavelet Transform (DTCWT) is applied on high frequency sub bands of DWT to derive Low and High frequency DTCWT coefficients. The texture features of DTCWT coefficients are computed using Overlapping Local Binary Pattern (OLBP) to generate feature set 1. In second feature set, the DTCWT is applied on preprocessed face image and considered all frequency sub bands coefficients to extract significant information and edge information of face image. The texture features of DTCWT matrix are computed using OLBP to generate feature set 2. The final feature set is the concatenation of feature set 1 and set 2. The Euclidian distance (ED) is used to compare test image features with features of face images in the database. It is observed that, the performance parameter values are better in the case of proposed algorithm compared to existing algorithms.

  2. 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. PMID:10984701

  3. 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.

  4. The Extraction of 3D Shape from Texture and Shading in the Human Brain

    PubMed Central

    Georgieva, Svetlana S.; Todd, James T.; Peeters, Ronald

    2008-01-01

    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. PMID:18281304

  5. 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.

  6. Evaluation of textural features for multispectral images

    NASA Astrophysics Data System (ADS)

    Bayram, Ulya; Can, Gulcan; Duzgun, Sebnem; Yalabik, Nese

    2011-11-01

    Remote sensing is a field that has wide use, leading to the fact that it has a great importance. Therefore performance of selected features plays a great role. In order to gain some perspective on useful textural features, we have brought together state-of-art textural features in recent literature, yet to be applied in remote sensing field, as well as presenting a comparison with traditional ones. Therefore we selected most commonly used textural features in remote sensing that are grey-level co-occurrence matrix (GLCM) and Gabor features. Other selected features are local binary patterns (LBP), edge orientation features extracted after applying steerable filter, and histogram of oriented gradients (HOG) features. Color histogram feature is also used and compared. Since most of these features are histogram-based, we have compared performance of bin-by-bin comparison with a histogram comparison method named as diffusion distance method. During obtaining performance of each feature, k-nearest neighbor classification method (k-NN) is applied.

  7. 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.

  8. 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

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

    PubMed

    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

  10. Feature-Based Quality Evaluation of 3d Point Clouds - Study of the Performance of 3d Registration Algorithms

    NASA Astrophysics Data System (ADS)

    Ridene, T.; Goulette, F.; Chendeb, S.

    2013-08-01

    The production of realistic 3D map databases is continuously growing. We studied an approach of 3D mapping database producing based on the fusion of heterogeneous 3D data. In this term, a rigid registration process was performed. Before starting the modeling process, we need to validate the quality of the registration results, and this is one of the most difficult and open research problems. In this paper, we suggest a new method of evaluation of 3D point clouds based on feature extraction and comparison with a 2D reference model. This method is based on tow metrics: binary and fuzzy.

  11. 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

  12. Volume rendering segmented data using 3D textures: a practical approach for intra-operative visualization

    NASA Astrophysics Data System (ADS)

    Subramanian, Navneeth; Mullick, Rakesh; Vaidya, Vivek

    2006-03-01

    Volume rendering has high utility in visualization of segmented datasets. However, volume rendering of the segmented labels along with the original data causes undesirable intermixing/bleeding artifacts arising from interpolation at the sharp boundaries. This issue is further amplified in 3D textures based volume rendering due to the inaccessibility of the interpolation stage. We present an approach which helps minimize intermixing artifacts while maintaining the high performance of 3D texture based volume rendering - both of which are critical for intra-operative visualization. Our approach uses a 2D transfer function based classification scheme where label distinction is achieved through an encoding that generates unique gradient values for labels. This helps ensure that labelled voxels always map to distinct regions in the 2D transfer function, irrespective of interpolation. In contrast to previously reported algorithms, our algorithm does not require multiple passes for rendering and supports greater than 4 masks. It also allows for real-time modification of the colors/opacities of the segmented structures along with the original data. Additionally, these capabilities are available with minimal texture memory requirements amongst comparable algorithms. Results are presented on clinical and phantom data.

  13. 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.

  14. 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

  15. 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

  16. 3D quaternionic condensation and spin textures with Hopf invariants from synthetic spin-orbit coupling

    NASA Astrophysics Data System (ADS)

    Wu, Congjun; Li, Yi; Zhou, Xiangfa

    2013-03-01

    We study unconventional condensations of two-component bosons in a harmonic trap subject to the 3D σ --> . p --> -type spin-orbit (SO) coupling. The topology of condensate wavefunctions manifests in the quaternionic representation. The spatial distributions of the S3 quaternionic phase exhibit 3D skyrmion configurations, while those of the S2 spin orientation possess non-zero Hopf invariants. As increasing SO coupling strength, spin textures evolve from concentric distributions to lattice structures at weak interactions. Strong interactions change condensates into spin-polarized plane-wave states, or, superpositions of two plane-waves exhibiting helical spin spirals. This project is supported by AFOSR FA9550-11-1- 0067(YIP) and NSF-DMR-1105945.

  17. Fusing Passive and Active Sensed Images to Gain Infrared-Textured 3d Models

    NASA Astrophysics Data System (ADS)

    Weinmann, M.; Hoegner, L.; Leitloff, J.; Stilla, U.; Hinz, S.; Jutzi, B.

    2012-07-01

    Obtaining a 3D description of man-made and natural environments is a basic task in Computer Vision, Photogrammetry and Remote Sensing. New active sensors provide the possibility of capturing range information by images with a single measurement. With this new technique, image-based active ranging is possible which allows for capturing dynamic scenes, e.g. with moving pedestrians or moving vehicles. The currently available range imaging devices usually operate within the close-infrared domain to capture range and furthermore active and passive intensity images. Depending on the application, a 3D description with additional spectral information such as thermal-infrared data can be helpful and offers new opportunities for the detection and interpretation of human subjects and interactions. Therefore, thermal-infrared data combined with range information is promising. In this paper, an approach for mapping thermal-infrared data on range data is proposed. First, a camera calibration is carried out for the range imaging system (PMD[vision] CamCube 2.0) and the thermal-infrared system (InfraTec VarioCAM hr). Subsequently, a registration of close-infrared and thermal infrared intensity images derived from different sensor devices is performed. In this context, wavelength independent properties are selected in order to derive point correspondences between the different spectral domains. Finally, the thermal infrared images are enhanced with information derived from data acquired with the range imaging device and the enhanced IR texture is projected onto the respective 3D point cloud data for gaining appropriate infrared-textured 3D models. The feasibility of the proposed methodology is demonstrated for an experimental setup which is well-suited for investigating these proposed possibilities. Hence, the presented work is a first step towards the development of methods for combined thermal-infrared and range representation.

  18. 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

  19. Holographic measurement of wall stress distribution and 3D flow over a surface textured by microfibers

    NASA Astrophysics Data System (ADS)

    Bocanegra, Humberto; Gorumlu, Seder; Aksak, Burak; Castillo, Luciano; Sheng, Jian

    2015-11-01

    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. Existing methods, such as μPIV, suffers from low spatial resolution and fail to track tracer particle motion very close to a rough surface and within roughness elements. In this paper, we present a technique that combines high speed digital holographic microscopy (DHM) 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. It allows us to obtain a 3D velocity field with an uncertainty of 0.01% and 2D wall shear stress distribution at the resolution of ~ 65 μPa. Applying the technique to a microfluidics with a surface textured by microfibers, we find that the flow is three-dimensional and complex. While the microfibers affect the velocity flow field locally, their presence is felt globally in terms of wall shear stresses. The study of effect of microfiber patterns and flow characteristics on skin frictions are ongoing and will be reported.

  20. Texture analysis of the 3D collagen network and automatic classification of the physiology of articular cartilage.

    PubMed

    Duan, Xiaojuan; Wu, Jianping; Swift, Benjamin; Kirk, Thomas Brett

    2015-07-01

    A close relationship has been found between the 3D collagen structure and physiological condition of articular cartilage (AC). Studying the 3D collagen network in AC offers a way to determine the condition of the cartilage. However, traditional qualitative studies are time consuming and subjective. This study aims to develop a computer vision-based classifier to automatically determine the condition of AC tissue based on the structural characteristics of the collagen network. Texture analysis was applied to quantitatively characterise the 3D collagen structure in normal (International Cartilage Repair Society, ICRS, grade 0), aged (ICRS grade 1) and osteoarthritic cartilages (ICRS grade 2). Principle component techniques and linear discriminant analysis were then used to classify the microstructural characteristics of the 3D collagen meshwork and the condition of the AC. The 3D collagen meshwork in the three physiological condition groups displayed distinctive characteristics. Texture analysis indicated a significant difference in the mean texture parameters of the 3D collagen network between groups. The principle component and linear discriminant analysis of the texture data allowed for the development of a classifier for identifying the physiological status of the AC with an expected prediction error of 4.23%. An automatic image analysis classifier has been developed to predict the physiological condition of AC (from ICRS grade 0 to 2) based on texture data from the 3D collagen network in the tissue. PMID:24428581

  1. 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

  2. A PC-based high-quality and interactive virtual endoscopy navigating system using 3D texture based volume rendering.

    PubMed

    Hwang, Jin-Woo; Lee, Jong-Min; Kim, In-Young; Song, In-Ho; Lee, Yong-Hee; Kim, SunI

    2003-05-01

    As an alternative method to optical endoscopy, visual quality and interactivity are crucial for virtual endoscopy. One solution is to use the 3D texture map based volume rendering method that offers high rendering speed without reducing visual quality. However, it is difficult to apply the method to virtual endoscopy. First, 3D texture mapping requires a high-end graphic workstation. Second, texture memory limits reduce the frame-rate. Third, lack of shading reduces visual quality significantly. As 3D texture mapping has become available on personal computers recently, we developed an interactive navigation system using 3D texture mapping on a personal computer. We divided the volume data into small cubes and tested whether the cubes had meaningful data. Only the cubes that passed the test were loaded into the texture memory and rendered. With the amount of data to be rendered minimized, rendering speed increased remarkably. We also improved visual quality by implementing full Phong shading based on the iso-surface shading method without sacrificing interactivity. With the developed navigation system, 256 x 256 x 256 sized brain MRA data was interactively explored with good image quality. PMID:12725966

  3. 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

    , including skyscrapers and bridges, which were confounded and extracted as buildings. This can be attributed to low point density at building edges and on flat roofs or occlusions due to which LiDAR cannot give as much precise planimetric accuracy as photogrammetric techniques (in segmentation) and lack of optimum use of textural information as well as contextual information (especially at walls which are away from roof) in automatic extraction algorithm. In addition, there were no separate classes for bridges or the features lying inside the water and multiple water height levels were also not considered. Based on these inferences, we conclude that the LiDAR-based 3D feature extraction supplemented by high resolution satellite data is a potential application which can be used for understanding and characterization of urban setup.

  4. Context-based automatic reconstruction and texturing of 3D urban terrain for quick-response tasks

    NASA Astrophysics Data System (ADS)

    Bulatov, Dimitri; Häufel, Gisela; Meidow, Jochen; Pohl, Melanie; Solbrig, Peter; Wernerus, Peter

    2014-07-01

    Highly detailed 3D urban terrain models are the base for quick response tasks with indispensable human participation, e.g., disaster management. Thus, it is important to automate and accelerate the process of urban terrain modeling from sensor data such that the resulting 3D model is semantic, compact, recognizable, and easily usable for training and simulation purposes. To provide essential geometric attributes, buildings and trees must be identified among elevated objects in digital surface models. After building ground-plan estimation and roof details analysis, images from oblique airborne imagery are used to cover building faces with up-to-date texture thus achieving a better recognizability of the model. The three steps of the texturing procedure are sensor pose estimation, assessment of polygons projected into the images, and texture synthesis. Free geographic data, providing additional information about streets, forest areas, and other topographic object types, suppress false alarms and enrich the reconstruction results.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. Registration of 3-D images using weighted geometrical features

    SciTech Connect

    Maurer, C.R. Jr.; Aboutanos, G.B.; Dawant, B.M.; Maciunas, R.J.; Fitzpatrick, J.M.

    1996-12-01

    In this paper, the authors present a weighted geometrical features (WGF) registration algorithm. Its efficacy is demonstrated by combining points and a surface. The technique is an extension of Besl and McKay`s iterative closest point (ICP) algorithm. The authors use the WGF algorithm to register X-ray computed tomography (CT) and T2-weighted magnetic resonance (MR) volume head images acquired from eleven patients that underwent craniotomies in a neurosurgical clinical trial. Each patient had five external markers attached to transcutaneous posts screwed into the outer table of the skull. The authors define registration error as the distance between positions of corresponding markers that are not used for registration. The CT and MR images are registered using fiducial points (marker positions) only, a surface only, and various weighted combinations of points and a surface. The CT surface is derived from contours corresponding to the inner surface of the skull. The MR surface is derived from contours corresponding to the cerebrospinal fluid (CSF)-dura interface. Registration using points and a surface is found to be significantly more accurate than registration using only points or a surface.

  10. 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

  11. 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.

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

    PubMed

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

    2015-09-01

    The aim of this study was to assess the efficacy of three-dimensional texture analysis (3D TA) of conventional MR images for the classification of childhood brain tumours in a quantitative manner. The dataset comprised pre-contrast T1 - and T2-weighted MRI series obtained from 48 children diagnosed with brain tumours (medulloblastoma, pilocytic astrocytoma and ependymoma). 3D and 2D TA were carried out on the images using first-, second- and higher order statistical methods. Six supervised classification algorithms were trained with the most influential 3D and 2D textural features, and their performances in the classification of tumour types, using the two feature sets, were compared. Model validation was carried out using the leave-one-out cross-validation (LOOCV) approach, as well as stratified 10-fold cross-validation, in order to provide additional reassurance. McNemar's test was used to test the statistical significance of any improvements demonstrated by 3D-trained classifiers. Supervised learning models trained with 3D textural features showed improved classification performances to those trained with conventional 2D features. For instance, a neural network classifier showed 12% improvement in area under the receiver operator characteristics curve (AUC) and 19% in overall classification accuracy. These improvements were statistically significant for four of the tested classifiers, as per McNemar's tests. This study shows that 3D textural features extracted from conventional T1 - and T2-weighted images can improve the diagnostic classification of childhood brain tumours. Long-term benefits of accurate, yet non-invasive, diagnostic aids include a reduction in surgical procedures, improvement in surgical and therapy planning, and support of discussions with patients' families. It remains necessary, however, to extend the analysis to a multicentre cohort in order to assess the scalability of the techniques used. PMID:26256809

  13. Semantic 3D scene interpretation: A framework combining optimal neighborhood size selection with relevant features

    NASA Astrophysics Data System (ADS)

    Weinmann, M.; Jutzi, B.; Mallet, C.

    2014-08-01

    3D scene analysis by automatically assigning 3D points a semantic label has become an issue of major interest in recent years. Whereas the tasks of feature extraction and classification have been in the focus of research, the idea of using only relevant and more distinctive features extracted from optimal 3D neighborhoods has only rarely been addressed in 3D lidar data processing. In this paper, we focus on the interleaved issue of extracting relevant, but not redundant features and increasing their distinctiveness by considering the respective optimal 3D neighborhood of each individual 3D point. We present a new, fully automatic and versatile framework consisting of four successive steps: (i) optimal neighborhood size selection, (ii) feature extraction, (iii) feature selection, and (iv) classification. In a detailed evaluation which involves 5 different neighborhood definitions, 21 features, 6 approaches for feature subset selection and 2 different classifiers, we demonstrate that optimal neighborhoods for individual 3D points significantly improve the results of scene interpretation and that the selection of adequate feature subsets may even further increase the quality of the derived results.

  14. Active shape models with optimised texture features for radiotherapy

    NASA Astrophysics Data System (ADS)

    Cheng, K.; Montgomery, D.; Yang, F.; McLaren, D. B.; McLaughlin, S.; Nailon, W. H.

    2014-03-01

    There is now considerable interest in radiation oncology on the use of shape models of anatomy to improve target delineation and assess anatomical disparity at time of radiotherapy. In this paper a texture based active shape model (ASM) is presented for automatic delineation of the gross tumor volume (GTV), containing the prostate, on computed tomography (CT) images of prostate cancer patients. The model was trained on two-dimensional (2D) contours identified by a radiation oncologist on sequential CT image slices. A three-dimensional (3D) GTV shape was constructed from these and iteratively aligned using Procrustes analysis. To train the model the shape deformation variance was learnt using the Active Shape Model (ASM) approach. In a novel development to this approach a profile feature was selected from pre-computed texture features by minimizing the Mahalanobis distance to obtain the most distinct feature for each landmark. The interior of the GTV was modelled using quantile histograms to initialize the shape model on new cases. From the archive of 42 cases of contoured CT scans, 32 cases were randomly selected for training the model and 10 cases for evaluating performance. The gold standard was defined by the radiation oncologist. The shape model achieved an overall Dice coefficient of 0.81 for all test cases. Performance was found to increase, mean Dice coefficient of 0.87, when the volume size of the new case was similar to the mean shape of the model. With further work the approach has the potential to be used in real-time delineation of target volumes and improve segmentation accuracy.

  15. 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

  16. 3-D study of texture and elastic anisotropy on rocks from NW Italy Ivrea zone

    NASA Astrophysics Data System (ADS)

    Pros, Z.; Lokajicek, T.; Prikryl, R.; Klima, K.; Nikitin, A. N.; Ivankina, T. I.; Martinkova, M.

    2003-04-01

    The direct measurement of physical properties of lower crustal and upper mantle rocks, which can be found on the Earth's surface, could be used for the improving of our knowledge of deep rocks. These results could be used mainly for the correction of geological and geophysical models based on the indirect data. Elastic properties of rocks are one of the most important parameters studied and could be applied in many fields of Earth sciences. In this study several quite different methods were applied to determine elastic properties. P-wave ultrasonic sounding of mafic and ultrabasic rock samples in 132 independent directions at several levels of confining pressure enable to determine elastic anisotropy of P-wave velocity. The samples were collected in nearby of Balmuccia ultra basic massif (Ivrea zone, southern Alps, NW Italy). This method revealed large directional variance of maximum P-wave velocity and different symmetric (orthorhombic vs. transversal isotropic) of elastic waves 3-D distribution, that has not been found on these rocks before. Identical samples were studied by means of neutron diffraction. Neutron diffraction provide data on CPO orientation in identical spherical samples, on which was measured P-wave velocity. Laboratory 3-D measurement of P-wave velocity thus present powerful method for detection of magmatic fabric features not visible by naked eye. One dunite sample exhibits P-wave velocity approaching to that of olivine crystal 9.8 km/s due to the strong CPO of olivine in this sample. Such observation was not done before on the natural olivine-rich rocks. It follows from the comparison of measured and calculated P-wave velocities, that these values are more reliable than data obtained from measurement in few directions only. This project was supported by Grant Agency of the Czech Republic No.: 205/01/1430.

  17. Facial Features Detection Using Texture Hough Transform

    NASA Astrophysics Data System (ADS)

    Gorbatsevich, V. S.

    2015-05-01

    The paper presents an original method for object detection. The "texture" Hough transform is used as the main tool in the search. Unlike classical generalized Hough transform, this variation uses texture LBP descriptor as a primitive for voting. The voting weight of each primitive is assumed by learning at a training set. This paper gives an overview of an original method for weights learning, and a number of ways to get the maximum searching algorithm speed on practice.

  18. 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.

  19. 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.

  20. A practical salient region feature based 3D multi-modality registration method for medical images

    NASA Astrophysics Data System (ADS)

    Hahn, Dieter A.; Wolz, Gabriele; Sun, Yiyong; Hornegger, Joachim; Sauer, Frank; Kuwert, Torsten; Xu, Chenyang

    2006-03-01

    We present a novel representation of 3D salient region features and its integration into a hybrid rigid-body registration framework. We adopt scale, translation and rotation invariance properties of those intrinsic 3D features to estimate a transform between underlying mono- or multi-modal 3D medical images. Our method combines advantageous aspects of both feature- and intensity-based approaches and consists of three steps: an automatic extraction of a set of 3D salient region features on each image, a robust estimation of correspondences and their sub-pixel accurate refinement with outliers elimination. We propose a region-growing based approach for the extraction of 3D salient region features, a solution to the problem of feature clustering and a reduction of the correspondence search space complexity. Results of the developed algorithm are presented for both mono- and multi-modal intra-patient 3D image pairs (CT, PET and SPECT) that have been acquired for change detection, tumor localization, and time based intra-person studies. The accuracy of the method is clinically evaluated by a medical expert with an approach that measures the distance between a set of selected corresponding points consisting of both anatomical and functional structures or lesion sites. This demonstrates the robustness of the proposed method to image overlap, missing information and artefacts. We conclude by discussing potential medical applications and possibilities for integration into a non-rigid registration framework.

  1. 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

  2. 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.

  3. 3D-profile measurement of advanced semiconductor features by reference metrology

    NASA Astrophysics Data System (ADS)

    Takamasu, Kiyoshi; Iwaki, Yuuki; Takahashi, Satoru; Kawada, Hiroki; Ikota, Masami; Lorusso, Gian F.; Horiguchi, Naoto

    2016-03-01

    A method of sub-nanometer uncertainty for the 3D-profile measurement using TEM (Transmission Electron Microscope) images is proposed to standardize 3D-profile measurement through reference metrology. The proposed method has been validated for profiles of Si lines, photoresist features and advanced-FinFET (Fin-shaped Field-Effect Transistor) features in our previous investigations. However, efficiency of 3D-profile measurement using TEM is limited by measurement time including processing of the sample. In this article, we demonstrate a novel on-wafer 3D-profile metrology as "FIB-to-CDSEM method" with FIB (Focused Ion Beam) slope cut and CD-SEM (Critical Dimension Secondary Electron Microscope) measuring. Using the method, a few micrometer wide on a wafer is coated and cut by 45 degree slope using FIB tool. Then, the wafer is transferred to CD-SEM to measure the cross section image by top down CD-SEM measurement. We apply FIB-to-CDSEM method to CMOS sensor device. 3D-profile and 3D-profile parameters such as top line width and side wall angles of CMOS sensor device are evaluated. The 3D-profile parameters also are measured by TEM images as reference metrology. We compare the 3D-profile parameters by TEM method and FIB-to-CDSEM method. The average values and correlations on the wafer are agreed well between TEM and FIB-to- CDSEM methods.

  4. 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. PMID:26498516

  5. Feature extraction on local jet space for texture classification

    NASA Astrophysics Data System (ADS)

    Oliveira, Marcos William da Silva; da Silva, Núbia Rosa; Manzanera, Antoine; Bruno, Odemir Martinez

    2015-12-01

    The proposal of this study is to analyze the texture pattern recognition over the local jet space looking forward to improve the texture characterization. Local jets decompose the image based on partial derivatives allowing the texture feature extraction be exploited in different levels of geometrical structures. Each local jet component evidences a different local pattern, such as, flat regions, directional variations and concavity or convexity. Subsequently, a texture descriptor is used to extract features from 0th, 1st and 2nd-derivative components. Four well-known databases (Brodatz, Vistex, Usptex and Outex) and four texture descriptors (Fourier descriptors, Gabor filters, Local Binary Pattern and Local Binary Pattern Variance) were used to validate the idea, showing in most cases an increase of the success rates.

  6. 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.

  7. 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.

  8. Novel chromatin texture features for the classification of pap smears

    NASA Astrophysics Data System (ADS)

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

    2013-03-01

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

  9. Predicting beef tenderness using color and multispectral image texture features.

    PubMed

    Sun, X; Chen, K J; Maddock-Carlin, K R; Anderson, V L; Lepper, A N; Schwartz, C A; Keller, W L; Ilse, B R; Magolski, J D; Berg, E P

    2012-12-01

    The objective of this study was to investigate the usefulness of raw meat surface characteristics (texture) in predicting cooked beef tenderness. Color and multispectral texture features, including 4 different wavelengths and 217 image texture features, were extracted from 2 laboratory-based multispectral camera imaging systems. Steaks were segregated into tough and tender classification groups based on Warner-Bratzler shear force. The texture features were submitted to STEPWISE multiple regression and support vector machine (SVM) analyses to establish prediction models for beef tenderness. A subsample (80%) of tender or tough classified steaks were used to train models which were then validated on the remaining (20%) test steaks. For color images, the SVM model correctly identified tender steaks with 100% accurately while the STEPWISE equation identified 94.9% of the tender steaks correctly. For multispectral images, the SVM model predicted 91% and STEPWISE predicted 87% average accuracy of beef tender. PMID:22647652

  10. Feature relevance assessment for the semantic interpretation of 3D point cloud data

    NASA Astrophysics Data System (ADS)

    Weinmann, M.; Jutzi, B.; Mallet, C.

    2013-10-01

    The automatic analysis of large 3D point clouds represents a crucial task in photogrammetry, remote sensing and computer vision. In this paper, we propose a new methodology for the semantic interpretation of such point clouds which involves feature relevance assessment in order to reduce both processing time and memory consumption. Given a standard benchmark dataset with 1.3 million 3D points, we first extract a set of 21 geometric 3D and 2D features. Subsequently, we apply a classifier-independent ranking procedure which involves a general relevance metric in order to derive compact and robust subsets of versatile features which are generally applicable for a large variety of subsequent tasks. This metric is based on 7 different feature selection strategies and thus addresses different intrinsic properties of the given data. For the example of semantically interpreting 3D point cloud data, we demonstrate the great potential of smaller subsets consisting of only the most relevant features with 4 different state-of-the-art classifiers. The results reveal that, instead of including as many features as possible in order to compensate for lack of knowledge, a crucial task such as scene interpretation can be carried out with only few versatile features and even improved accuracy.

  11. 3D Palmprint Identification Using Block-Wise Features and Collaborative Representation.

    PubMed

    Zhang, Lin; Shen, Ying; Li, Hongyu; Lu, Jianwei

    2015-08-01

    Developing 3D palmprint recognition systems has recently begun to draw attention of researchers. Compared with its 2D counterpart, 3D palmprint has several unique merits. However, most of the existing 3D palmprint matching methods are designed for one-to-one verification and they are not efficient to cope with the one-to-many identification case. In this paper, we fill this gap by proposing a collaborative representation (CR) based framework with l1-norm or l2-norm regularizations for 3D palmprint identification. The effects of different regularization terms have been evaluated in experiments. To use the CR-based classification framework, one key issue is how to extract feature vectors. To this end, we propose a block-wise statistics based feature extraction scheme. We divide a 3D palmprint ROI into uniform blocks and extract a histogram of surface types from each block; histograms from all blocks are then concatenated to form a feature vector. Such feature vectors are highly discriminative and are robust to mere misalignment. Experiments demonstrate that the proposed CR-based framework with an l2-norm regularization term can achieve much better recognition accuracy than the other methods. More importantly, its computational complexity is extremely low, making it quite suitable for the large-scale identification application. Source codes are available at http://sse.tongji.edu.cn/linzhang/cr3dpalm/cr3dpalm.htm. PMID:26353008

  12. A very low-cost system for capturing 3D motion scans with color and texture data

    NASA Astrophysics Data System (ADS)

    Straub, Jeremy

    2015-05-01

    This paper presents a technique for capturing 3D motion scans using hardware that can be constructed for approximately $5,000 in cost. This hardware-software solution, in addition to capturing the movement of the physical structures also captures color and texture data. The scanner configuration developed at the University of North Dakota is sufficient in size for capturing scans of a group of humans. Scanning starts with synchronization and then requires modeling of each frame. For some applications linking structural elements from frame-to-frame may also be required. The efficacy of this scanning approach is discussed and prospective applications for it are considered.

  13. 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

  14. 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.

  15. gEMfitter: a highly parallel FFT-based 3D density fitting tool with GPU texture memory acceleration.

    PubMed

    Hoang, Thai V; Cavin, Xavier; Ritchie, David W

    2013-11-01

    Fitting high resolution protein structures into low resolution cryo-electron microscopy (cryo-EM) density maps is an important technique for modeling the atomic structures of very large macromolecular assemblies. This article presents "gEMfitter", a highly parallel fast Fourier transform (FFT) EM density fitting program which can exploit the special hardware properties of modern graphics processor units (GPUs) to accelerate both the translational and rotational parts of the correlation search. In particular, by using the GPU's special texture memory hardware to rotate 3D voxel grids, the cost of rotating large 3D density maps is almost completely eliminated. Compared to performing 3D correlations on one core of a contemporary central processor unit (CPU), running gEMfitter on a modern GPU gives up to 26-fold speed-up. Furthermore, using our parallel processing framework, this speed-up increases linearly with the number of CPUs or GPUs used. Thus, it is now possible to use routinely more robust but more expensive 3D correlation techniques. When tested on low resolution experimental cryo-EM data for the GroEL-GroES complex, we demonstrate the satisfactory fitting results that may be achieved by using a locally normalised cross-correlation with a Laplacian pre-filter, while still being up to three orders of magnitude faster than the well-known COLORES program. PMID:24060989

  16. 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

  17. Bone segmentation and fracture detection in ultrasound using 3D local phase features.

    PubMed

    Hacihaliloglu, Ilker; Abugharbieh, Rafeef; Hodgson, Antony; Rohling, Robert

    2008-01-01

    3D ultrasound (US) is increasingly considered as a viable alternative imaging modality in computer-assisted orthopaedic surgery (CAOS) applications. Automatic bone segmentation from US images, however, remains a challenge due to speckle noise and various other artifacts inherent to US. In this paper, we present intensity invariant three dimensional (3D) local image phase features, obtained using 3D Log-Gabor filter banks, for extracting ridge-like features similar to those that occur at soft tissue/bone interfaces. Our contributions include the novel extension of 2D phase symmetry features to 3D and their use in automatic extraction of bone surfaces and fractured fragments in 3D US. We validate our technique using phantom, in vitro, and in vivo experiments. Qualitative and quantitative results demonstrate remarkably clear segmentations results of bone surfaces with a localization accuracy of better than 0.62 mm and mean errors in estimating fracture displacements below 0.65 mm, which will likely be of strong clinical utility. PMID:18979759

  18. 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

  19. Building an accurate 3D model of a circular feature for robot vision

    NASA Astrophysics Data System (ADS)

    Li, L.

    2012-06-01

    In this paper, an accurate 3D model analysis of a circular feature is built with error compensation for robot vision. We propose an efficient method of fitting ellipses to data points by minimizing the algebraic distance subject to the constraint that a conic should be an ellipse and solving the ellipse parameters through a direct ellipse fitting method by analysing the 3D geometrical representation in a perspective projection scheme, the 3D position of a circular feature with known radius can be obtained. A set of identical circles, machined on a calibration board whose centres were known, was calibrated with a camera and did the model analysis that our method developed. Experimental results show that our method is more accurate than other methods.

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

    PubMed

    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

  1. 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

  2. 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.

  3. 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.

  4. Toward Automated FAÇADE Texture Generation for 3d Photorealistic City Modelling with Smartphones or Tablet Pcs

    NASA Astrophysics Data System (ADS)

    Wang, S.

    2012-07-01

    An automated model-image fitting algorithm is proposed in this paper for generating façade texture image from pictures taken by smartphones or tablet PCs. The façade texture generation requires tremendous labour work and thus, has been the bottleneck of 3D photo-realistic city modelling. With advanced developments of the micro electro mechanical system (MEMS), camera, global positioning system (GPS), and gyroscope (G-sensors) can all be integrated into a smartphone or a table PC. These sensors bring the possibility of direct-georeferencing for the pictures taken by smartphones or tablet PCs. Since the accuracy of these sensors cannot compared to the surveying instruments, the image position and orientation derived from these sensors are not capable of photogrammetric measurements. This paper adopted the least-squares model-image fitting (LSMIF) algorithm to iteratively improve the image's exterior orientation. The image position from GPS and the image orientation from gyroscope are treated as the initial values. By fitting the projection of the wireframe model to the extracted edge pixels on image, the image exterior orientation elements are solved when the optimal fitting achieved. With the exact exterior orientation elements, the wireframe model of the building can be correctly projected on the image and, therefore, the façade texture image can be extracted from the picture.

  5. Edge features extraction from 3D laser point cloud based on corresponding images

    NASA Astrophysics Data System (ADS)

    Li, Xin-feng; Zhao, Zi-ming; Xu, Guo-qing; Geng, Yan-long

    2013-09-01

    An extraction method of edge features from 3D laser point cloud based on corresponding images was proposed. After the registration of point cloud and corresponding image, the sub-pixel edge can be extracted from the image using gray moment algorithm. Then project the sub-pixel edge to the point cloud in fitting scan-lines. At last the edge features were achieved by linking the crossing points. The experimental results demonstrate that the method guarantees accurate fine extraction.

  6. 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.

  7. 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)

  8. 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.

  9. 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.

  10. 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

  11. 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

  12. 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

  13. Quantitative analysis and feature recognition in 3-D microstructural data sets

    NASA Astrophysics Data System (ADS)

    Lewis, A. C.; Suh, C.; Stukowski, M.; Geltmacher, A. B.; Spanos, G.; Rajan, K.

    2006-12-01

    A three-dimensional (3-D) reconstruction of an austenitic stainless-steel microstructure was used as input for an image-based finite-element model to simulate the anisotropic elastic mechanical response of the microstructure. The quantitative data-mining and data-warehousing techniques used to correlate regions of high stress with critical microstructural features are discussed. Initial analysis of elastic stresses near grain boundaries due to mechanical loading revealed low overall correlation with their location in the microstructure. However, the use of data-mining and feature-tracking techniques to identify high-stress outliers revealed that many of these high-stress points are generated near grain boundaries and grain edges (triple junctions). These techniques also allowed for the differentiation between high stresses due to boundary conditions of the finite volume reconstructed, and those due to 3-D microstructural features.

  14. 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

  15. 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.

  16. 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

  17. 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

  18. 3D Point Correspondence by Minimum Description Length in Feature Space.

    PubMed

    Chen, Jiun-Hung; Zheng, Ke Colin; Shapiro, Linda G

    2010-01-01

    Finding point correspondences plays an important role in automatically building statistical shape models from a training set of 3D surfaces. For the point correspondence problem, Davies et al. [1] proposed a minimum-description-length-based objective function to balance the training errors and generalization ability. A recent evaluation study [2] that compares several well-known 3D point correspondence methods for modeling purposes shows that the MDL-based approach [1] is the best method. We adapt the MDL-based objective function for a feature space that can exploit nonlinear properties in point correspondences, and propose an efficient optimization method to minimize the objective function directly in the feature space, given that the inner product of any vector pair can be computed in the feature space. We further employ a Mercer kernel [3] to define the feature space implicitly. A key aspect of our proposed framework is the generalization of the MDL-based objective function to kernel principal component analysis (KPCA) [4] spaces and the design of a gradient-descent approach to minimize such an objective function. We compare the generalized MDL objective function on KPCA spaces with the original one and evaluate their abilities in terms of reconstruction errors and specificity. From our experimental results on different sets of 3D shapes of human body organs, the proposed method performs significantly better than the original method. PMID:25328917

  19. 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.

  20. A new method of constructing a grid in the space of 3D rotations and its applications to texture analysis

    NASA Astrophysics Data System (ADS)

    Roşca, D.; Morawiec, A.; De Graef, M.

    2014-10-01

    In computational work, data sets must often be represented on the surface of a sphere or inside a ball, requiring uniform grids. We construct a new volume-preserving projection between a cube and the set of unit quaternions. The projection consists of two steps: an equal-volume mapping from the cube to the unit ball, followed by an inverse generalized Lambert projection to either of the two unit quaternion hemispheres. The new projection provides a one-to-one mapping between a grid in the cube and elements of the special orthogonal group SO(3), i.e., 3D rotations. We provide connections to other rotation representation schemes, including the Rodrigues-Frank vector and the homochoric parameterizations, and illustrate the new mapping through example applications relevant to texture analysis.

  1. 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

  2. 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

  3. Texture feature analysis for computer-aided diagnosis on pulmonary nodules.

    PubMed

    Han, Fangfang; Wang, Huafeng; Zhang, Guopeng; Han, Hao; Song, Bowen; Li, Lihong; Moore, William; Lu, Hongbing; Zhao, Hong; Liang, Zhengrong

    2015-02-01

    Differentiation of malignant and benign pulmonary nodules is of paramount clinical importance. Texture features of pulmonary nodules in CT images reflect a powerful character of the malignancy in addition to the geometry-related measures. This study first compared three well-known types of two-dimensional (2D) texture features (Haralick, Gabor, and local binary patterns or local binary pattern features) on CADx of lung nodules using the largest public database founded by Lung Image Database Consortium and Image Database Resource Initiative and then investigated extension from 2D to three-dimensional (3D) space. Quantitative comparison measures were made by the well-established support vector machine (SVM) classifier, the area under the receiver operating characteristic curves (AUC) and the p values from hypothesis t tests. While the three feature types showed about 90% differentiation rate, the Haralick features achieved the highest AUC value of 92.70% at an adequate image slice thickness, where a thinner or thicker thickness will deteriorate the performance due to excessive image noise or loss of axial details. Gain was observed when calculating 2D features on all image slices as compared to the single largest slice. The 3D extension revealed potential gain when an optimal number of directions can be found. All the observations from this systematic investigation study on the three feature types can lead to the conclusions that the Haralick feature type is a better choice, the use of the full 3D data is beneficial, and an adequate tradeoff between image thickness and noise is desired for an optimal CADx performance. These conclusions provide a guideline for further research on lung nodule differentiation using CT imaging. PMID:25117512

  4. 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.

  5. 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.

  6. Improved pulmonary nodule classification utilizing lung parenchyma texture features

    NASA Astrophysics Data System (ADS)

    Dilger, S. K.; Judisch, A.; Uthoff, J.; Hammond, E.; Newell, J. D.; Sieren, J. C.

    2015-03-01

    Current computer-aided diagnosis (CAD) models, developed to determine the malignancy of pulmonary nodules, characterize the nodule's shape, density, and border. Analyzing the lung parenchyma surrounding the nodule is an area that has been minimally explored. We hypothesize that improved classification of nodules can be achieved through the inclusion of features quantified from the surrounding lung tissue. From computed tomography (CT) data, feature extraction techniques were developed to quantify the parenchymal and nodule textures, including a three-dimensional application of Laws' Texture Energy Measures. Border irregularity was investigated using ray-casting and rubber-band straightening techniques, while histogram features characterized the densities of the nodule and parenchyma. The feature set was reduced by stepwise feature selection to a few independent features that best summarized the dataset. Using leave-one-out cross-validation, a neural network was used for classification. The CAD tool was applied to 50 nodules (22 malignant, 28 benign) from high-resolution CT scans. 47 features, including 39 parenchymal features, were statistically significant, with both nodule and parenchyma features selected for classification, yielding an area under the ROC curve (AUC) of 0.935. This was compared to classification solely based on the nodule yielding an AUC of 0.917. These preliminary results show an increase in performance when the surrounding parenchyma is included in analysis. While modest, the improvement and large number of significant parenchyma features supports our hypothesis that the parenchyma contains meaningful data that can assist in CAD development.

  7. 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

  8. 3D laser scanning microscopy of hypervelocity impact features in metal and aerogel targets

    NASA Astrophysics Data System (ADS)

    Hillier, J. K.; Postberg, F.; Price, M. C.; Trieloff, M.; Li, Y. W.; Srama, R.

    2012-09-01

    We present the results of a study into the mapping of hypervelocity impact features using a Keyence VK-X200 3D laser scanning microscope. The impact features observed are impact craters in a variety of different metal targets (Al, Au and Cu) and impact tracks in aerogel targets, similar to those used in the Stardust mission. Differences in crater morphology between different target materials and impact velocities, as well as differences in track depth and diameter in aerogel, for particles of known constant dimensions, are discussed.

  9. 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.

  10. Automatic detection of anatomical features on 3D ear impressions for canonical representation.

    PubMed

    Baloch, Sajjad; Melkisetoglu, Rupen; Flöry, Simon; Azernikov, Sergei; Slabaugh, Greg; Zouhar, Alexander; Fang, Tong

    2010-01-01

    We propose a shape descriptor for 3D ear impressions, derived from a comprehensive set of anatomical features. Motivated by hearing aid (HA) manufacturing, the selection of the anatomical features is carried out according to their uniqueness and importance in HA design. This leads to a canonical ear signature that is highly distinctive and potentially well suited for classification. First, the anatomical features are characterized into generic topological and geometric features, namely concavities, elbows, ridges, peaks, and bumps on the surface of the ear. Fast and robust algorithms are then developed for their detection. This indirect approach ensures the generality of the algorithms with potential applications in biomedicine, biometrics, and reverse engineering. PMID:20879444

  11. 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

  12. 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).

  13. Recognizing Objects in 3D Point Clouds with Multi-Scale Local Features

    PubMed Central

    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. PMID:25517694

  14. 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. PMID:25517694

  15. Study of texture stitching in 3D modeling of lidar point cloud based on per-pixel linear interpolation along loop line buffer

    NASA Astrophysics Data System (ADS)

    Xu, Jianxin; Liang, Hong

    2013-07-01

    Terrestrial laser scanning creates a point cloud composed of thousands or millions of 3D points. Through pre-processing, generating TINs, mapping texture, a 3D model of a real object is obtained. When the object is too large, the object is separated into some parts. This paper mainly focuses on problem of gray uneven of two adjacent textures' intersection. The new algorithm is presented in the paper, which is per-pixel linear interpolation along loop line buffer .The experiment data derives from point cloud of stone lion which is situated in front of west gate of Henan Polytechnic University. The model flow is composed of three parts. First, the large object is separated into two parts, and then each part is modeled, finally the whole 3D model of the stone lion is composed of two part models. When the two part models are combined, there is an obvious fissure line in the overlapping section of two adjacent textures for the two models. Some researchers decrease brightness value of all pixels for two adjacent textures by some algorithms. However, some algorithms are effect and the fissure line still exists. Gray uneven of two adjacent textures is dealt by the algorithm in the paper. The fissure line in overlapping section textures is eliminated. The gray transition in overlapping section become more smoothly.

  16. Unified Saliency Detection Model Using Color and Texture Features

    PubMed Central

    Luo, Tiejian

    2016-01-01

    Saliency detection attracted attention of many researchers and had become a very active area of research. Recently, many saliency detection models have been proposed and achieved excellent performance in various fields. However, most of these models only consider low-level features. This paper proposes a novel saliency detection model using both color and texture features and incorporating higher-level priors. The SLIC superpixel algorithm is applied to form an over-segmentation of the image. Color saliency map and texture saliency map are calculated based on the region contrast method and adaptive weight. Higher-level priors including location prior and color prior are incorporated into the model to achieve a better performance and full resolution saliency map is obtained by using the up-sampling method. Experimental results on three datasets demonstrate that the proposed saliency detection model outperforms the state-of-the-art models. PMID:26889826

  17. Characterizing mammographic images by using generic texture features

    PubMed Central

    2012-01-01

    Introduction Although mammographic density is an established risk factor for breast cancer, its use is limited in clinical practice because of a lack of automated and standardized measurement methods. The aims of this study were to evaluate a variety of automated texture features in mammograms as risk factors for breast cancer and to compare them with the percentage mammographic density (PMD) by using a case-control study design. Methods A case-control study including 864 cases and 418 controls was analyzed automatically. Four hundred seventy features were explored as possible risk factors for breast cancer. These included statistical features, moment-based features, spectral-energy features, and form-based features. An elaborate variable selection process using logistic regression analyses was performed to identify those features that were associated with case-control status. In addition, PMD was assessed and included in the regression model. Results Of the 470 image-analysis features explored, 46 remained in the final logistic regression model. An area under the curve of 0.79, with an odds ratio per standard deviation change of 2.88 (95% CI, 2.28 to 3.65), was obtained with validation data. Adding the PMD did not improve the final model. Conclusions Using texture features to predict the risk of breast cancer appears feasible. PMD did not show any additional value in this study. With regard to the features assessed, most of the analysis tools appeared to reflect mammographic density, although some features did not correlate with PMD. It remains to be investigated in larger case-control studies whether these features can contribute to increased prediction accuracy. PMID:22490545

  18. Texture of B-mode echograms: 3-D simulations and experiments of the effects of diffraction and scatterer density.

    PubMed

    Oosterveld, B J; Thijssen, J M; Verhoef, W A

    1985-04-01

    B-mode echograms were simulated by employing the impulse response method in transmission and reception using a discrete scatterer tissue model, with and without attenuation. The analytic signal approach was used for demodulation of the RF A-mode lines. The simulations were performed in 3-D space and compared to B-mode echograms obtained from experiments with scattering tissue phantoms. The average echo amplitude appeared to increase towards the focus and to decrease beyond it. In the focal zone, the average amplitude increased proportionally to the square root of the scatterer density. The signal to noise ratio (SNR) was found to be independent of depth, i.e., 1.91 as predicted for a Rayleigh distribution of gray levels, although a minimum was found in the focal zone at relatively low scatterer densities. The SNR continuously increased with increasing scatterer density and reached the limit of 1.91 at relatively high densities (greater than 10(4) cm-3). The lateral full width at half maximum (FWHM) of the two dimensional autocovariance function of the speckle increased continuously from the transducer face to far beyond the focus and decreased thereafter due to the diffraction effect. The lateral FWHM decreased proportionally to the logarithm of the scatterer density at low densities and reached a limit at high densities. Introduction of attenuation in the simulated tissue resulted in a much more pronounced depth dependence of the texture. The axial FWHM was independent of the distance to the transducer to a first approximation and decreased slightly with increasing scatterer density until a limit was reached at densities larger than 10(3) cm-3. This limit was in agreement with theory. The experiments confirmed the simulations and it can be concluded that the presented results are of great importance to the understanding of B-mode echograms and to the potential use of the analysis of B-mode texture for tissue characterization. PMID:3909602

  19. 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.

  20. 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

  1. 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

  2. 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

  3. 3D reconstruction for sinusoidal motion based on different feature detection algorithms

    NASA Astrophysics Data System (ADS)

    Zhang, Peng; Zhang, Jin; Deng, Huaxia; Yu, Liandong

    2015-02-01

    The dynamic testing of structures and components is an important area of research. Extensive researches on the methods of using sensors for vibration parameters have been studied for years. With the rapid development of industrial high-speed camera and computer hardware, the method of using stereo vision for dynamic testing has been the focus of the research since the advantages of non-contact, full-field, high resolution and high accuracy. But in the country there is not much research about the dynamic testing based on stereo vision, and yet few people publish articles about the three-dimensional (3D) reconstruction of feature points in the case of dynamic. It is essential to the following analysis whether it can obtain accurate movement of target objects. In this paper, an object with sinusoidal motion is detected by stereo vision and the accuracy with different feature detection algorithms is investigated. Three different marks including dot, square and circle are stuck on the object and the object is doing sinusoidal motion by vibration table. Then use feature detection algorithm speed-up robust feature (SURF) to detect point, detect square corners by Harris and position the center by Hough transform. After obtaining the pixel coordinate values of the feature point, the stereo calibration parameters are used to achieve three-dimensional reconstruction through triangulation principle. The trajectories of the specific direction according to the vibration frequency and the frequency camera acquisition are obtained. At last, the reconstruction accuracy of different feature detection algorithms is compared.

  4. 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.

  5. Texture Features from Mammographic Images and Risk of Breast Cancer

    PubMed Central

    Manduca, Armando; Carston, Michael J.; Heine, John J.; Scott, Christopher G.; Pankratz, V. Shane; Brandt, Kathy R.; Sellers, Thomas A.; Vachon, Celine M.; Cerhan, James R.

    2009-01-01

    Mammographic percent density (PD) is a strong risk factor for breast cancer, but there has been relatively little systematic evaluation of other features in mammographic images that might additionally predict breast cancer risk. We evaluated the association of a large number of image texture features with risk of breast cancer using a clinic-based case-control study of digitized film mammograms, all with screening mammograms prior to breast cancer diagnosis. The sample was split into training (123 cases, 258 controls) and validation (123 cases, 264 controls) datasets. Age and body mass index (BMI)-adjusted Odds Ratios (ORs) per standard deviation change in the feature, 95% confidence intervals, and the area under the receiver operator characteristic curve (AUC) were obtained using logistic regression. A bootstrap approach was used to identify the strongest features in the training dataset, and results for features that validated in the second half of the sample were reported using the full dataset. The mean age at mammography was 64.0 ± 10.2 years, and the mean time from mammography to breast cancer was 3.7 ± 1.0 (range 2.0-5.9 years). PD was associated with breast cancer risk (OR=1.49; 1.25-1.78). The strongest features that validated from each of several classes (Markovian, run-length, Laws, wavelet and Fourier) showed similar ORs as PD and predicted breast cancer at a similar magnitude (AUC=0.58-0.60) as PD (AUC=0.58). All of these features were automatically calculated (unlike PD), and measure texture at a coarse scale. These features were moderately correlated with PD (r = 0.39-0.64), and after adjustment for PD, each of the features attenuated only slightly and retained statistical significance. However, simultaneous inclusion of these features in a model with PD did not significantly improve the ability to predict breast cancer. PMID:19258482

  6. A 3D Feature Descriptor Recovered from a Single 2D Palmprint Image.

    PubMed

    Zheng, Qian; Kumar, Ajay; Pan, Gang

    2016-06-01

    Design and development of efficient and accurate feature descriptors is critical for the success of many computer vision applications. This paper proposes a new feature descriptor, referred to as DoN, for the 2D palmprint matching. The descriptor is extracted for each point on the palmprint. It is based on the ordinal measure which partially describes the difference of the neighboring points' normal vectors. DoN has at least two advantages: 1) it describes the 3D information, which is expected to be highly stable under commonly occurring illumination variations during contactless imaging; 2) the size of DoN for each point is only one bit, which is computationally simple to extract, easy to match, and efficient to storage. We show that such 3D information can be extracted from a single 2D palmprint image. The analysis for the effectiveness of ordinal measure for palmprint matching is also provided. Four publicly available 2D palmprint databases are used to evaluate the effectiveness of DoN, both for identification and the verification. Our method on all these databases achieves the state-of-the-art performance. PMID:27164564

  7. 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.

  8. 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.

  9. 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

  10. 3D Object Recognition using Gabor Feature Extraction and PCA-FLD Projections of Holographically Sensed Data

    NASA Astrophysics Data System (ADS)

    Yeom, Seokwon; Javidi, Bahram

    In this research, a 3D object classification technique using a single hologram has been presented. The PCA-FLD classifier with feature vectors based on Gabor wavelets has been utilized for this purpose. Training and test data of the 3D objects were obtained by computational holographic imaging. We were able to classify 3D objects used in the experiments with a few reconstructed planes of the hologram. The Gabor approach appears to be a good feature extractor for hologram-based 3D classification. The FLD combined with the PCA proved to be a very efficient classifier even with a few training data. Substantial dimensionality reduction was achieved by using the proposed technique for 3D classification problem using holographic imaging. As a consequence, we were able to classify different classes of 3D objects using computer-reconstructed holographic images.

  11. 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.

  12. 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

  13. 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…

  14. 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.

  15. 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.

  16. 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.

  17. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2001-06-01

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

  19. Non Destructive High-Resolution 3D Investigation of Vesicle Textures in Pumice and Scoria by Synchrotron X-Ray Computed Microtomography

    NASA Astrophysics Data System (ADS)

    Polacci, M.; Baker, D.; Mancini, L.; Tromba, G.; Zanini, F.

    2005-12-01

    High resolution X-ray computed microtomography was applied to investigate the 3D structure of pyroclastic material from different active, explosive, hazardous volcanic areas. The experiments were performed at the SYRMEP beamline of the ELETTRA synchrotron radiation facility in Trieste (Italy). The 2D image slices resulting from tomography of selected pumice and scoria samples were transformed into volume renderings via specific tomographic software. The reconstructed volumes allowed us to test the applicability of this technique, novel in the field of volcanology, to volcanic specimens with different textural characteristics. The use of a third generation synchrotron radiation facility allowed optimal visualization of vesicle and crystal geometry in the reconstructed volume where conventional X-ray methods are strongly limited. The BLOB3D software package was used to accomplish quantitative descriptions of vesicle textures in terms of vesicularity, number density, volume and connectivity. The results exhibited complex patterns of the vesicle content, size, shape and distribution within the different pyroclasts and allowed us to track the degassing history of each single clast. With this preliminary study we demonstrate that computed microtomography is a feasible tool complementary to conventional microscopy methods for the full 3D textural characterization of volcanic clasts, and that it may be used to provide further constraints to models of degassing at active volcanoes.

  20. Dielectrophoretic isolation of cells using 3D microelectrodes featuring castellated blocks.

    PubMed

    Xing, Xiaoxing; Yobas, Levent

    2015-05-21

    We present 3D microelectrodes featuring castellated blocks for dielectrophoretically isolating cells. These electrodes provide a more effective dielectrophoretic force field than thin-film surface electrodes and yet immobilize cells near stagnation points across a parabolic flow profile for enhanced cell viability and separation efficiency. Unlike known volumetric electrodes with linear profiles, the electrodes with structural variations introduced along their depth scale are versatile for constructing monolithic structures with readily integrated fluidic paths. This is exemplified here in the design of an interdigitated comb array wherein electrodes with castellated surfaces serve as building blocks and form digits with an array of fluidic pores. Activation of the design with low-voltage oscillations (±5 Vp, 400 kHz) is found adequate for retaining most viable cells (90.2% ± 3.5%) while removing nonviable cells (88.5% ± 5%) at an increased throughput (5 × 10(5) cells h(-1)). The electrodes, despite their intricate profile, are structured into single-crystal silicon through a self-aligned etching process without a precision layer-by-layer assembly. PMID:25857455

  1. 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

  2. Cost-effective and non-invasive automated benign and malignant thyroid lesion classification in 3D contrast-enhanced ultrasound using combination of wavelets and textures: a class of ThyroScan™ algorithms.

    PubMed

    Acharya, U R; Faust, O; Sree, S V; Molinari, F; Garberoglio, R; Suri, J S

    2011-08-01

    Ultrasound has great potential to aid in the differential diagnosis of malignant and benign thyroid lesions, but interpretative pitfalls exist and the accuracy is still poor. To overcome these difficulties, we developed and analyzed a range of knowledge representation techniques, which are a class of ThyroScan™ algorithms from Global Biomedical Technologies Inc., California, USA, for automatic classification of benign and malignant thyroid lesions. The analysis is based on data obtained from twenty nodules (ten benign and ten malignant) taken from 3D contrast-enhanced ultrasound images. Fine needle aspiration biopsy and histology confirmed malignancy. Discrete Wavelet Transform (DWT) and texture algorithms are used to extract relevant features from the thyroid images. The resulting feature vectors are fed to three different classifiers: K-Nearest Neighbor (K-NN), Probabilistic Neural Network (PNN), and Decision Tree (DeTr). The performance of these classifiers is compared using Receiver Operating Characteristic (ROC) curves. Our results show that combination of DWT and texture features coupled with K-NN resulted in good performance measures with the area of under the ROC curve of 0.987, a classification accuracy of 98.9%, a sensitivity of 98%, and a specificity of 99.8%. Finally, we have proposed a novel integrated index called Thyroid Malignancy Index (TMI), which is made up of texture features, to diagnose benign or malignant nodules using just one index. We hope that this TMI will help clinicians in a more objective detection of benign and malignant thyroid lesions. PMID:21728394

  3. 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

  4. 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

  5. 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.

  6. 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

  7. 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

  8. Automatic Texture Mapping with AN Omnidirectional Camera Mounted on a Vehicle Towards Large Scale 3d City Models

    NASA Astrophysics Data System (ADS)

    Deng, F.; Li, D.; Yan, L.; Fan, H.

    2012-07-01

    Today high resolution panoramic images with competitive quality have been widely used for rendering in some commercial systems. However the potential applications such as mapping, augmented reality and modelling which need accurate orientation information are still poorly studied. Urban models can be quickly obtained from aerial images or LIDAR, however with limited quality or efficiency due to low resolution textures and manual texture mapping work flow. We combine an Extended Kalman Filter (EKF) with the traditional Structure from Motion (SFM) method without any prior information based on a general camera model which can handle various kinds of omnidirectional and other kind of single perspective image sequences even with unconnected or weakly connected frames. The orientation results is then applied to mapping the textures from panoramas to the existing building models obtained from aerial photogrammetry. It turns out to largely improve the quality of the models and the efficiency of the modelling procedure.

  9. 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. PMID:24858457

  10. 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.

  11. 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.

  12. Comparing Shape and Texture Features for Pattern Recognition in Simulation Data

    SciTech Connect

    Newsam, S; Kamath, C

    2004-12-10

    Shape and texture features have been used for some time for pattern recognition in datasets such as remote sensed imagery, medical imagery, photographs, etc. In this paper, we investigate shape and texture features for pattern recognition in simulation data. In particular, we explore which features are suitable for characterizing regions of interest in images resulting from fluid mixing simulations. Three texture features--gray level co-occurrence matrices, wavelets, and Gabor filters--and two shape features--geometric moments and the angular radial transform--are compared. The features are evaluated using a similarity retrieval framework. Our preliminary results indicate that Gabor filters perform the best among the texture features and the angular radial transform performs the best among the shape features. The feature which performs the best overall is dependent on how the groundtruth dataset is created.

  13. Comparing shape and texture features for pattern recognition in simulation data

    NASA Astrophysics Data System (ADS)

    Newsam, Shawn D.; Kamath, Chandrika

    2005-03-01

    Shape and texture features have been used for some time for pattern recognition in datasets such as remote sensed imagery, medical imagery, photographs, etc. In this paper, we investigate shape and texture features for pattern recognition in simulation data. In particular, we explore which features are suitable for characterizing regions of interest in images resulting from fluid mixing simulations. Three texture features -- gray level co-occurrence matrices, wavelets, and Gabor filters -- and two shape features -- geometric moments and the angular radial transform -- are compared. The features are evaluated using a similarity retrieval framework. Our preliminary results indicate that Gabor filters perform the best among the texture features and the angular radial transform performs the best among the shape features. The feature which performs the best overall is dependent on how the groundtruth dataset is created.

  14. 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.

  15. 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

  16. 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.

  17. Wavelet-SVM classifier based on texture features for land cover classification

    NASA Astrophysics Data System (ADS)

    Zhang, Ning; Wu, Bingfang; Zhu, Jianjun; Zhou, Yuemin; Zhu, Liang

    2008-12-01

    Texture features are recognized to be a special hint in images, which represent the spatial relations of the gray pixels. Nowadays, the applications of the texture analysis in image classification spread abroad. Combined with wavelet multi-resolution analysis or support vector machine statistical learning theory, texture analysis could improve the quality of classification increasingly. In this paper, we focus on the land cover for the Three Gorges reservoir using remote sensing data SPOT-5, a new classification method, wavelet-SVM classifier based on texture features, is employed for this study. Compare to the traditional maximum likelihood classifier and SVM classifier only use spectrum feature, this method produces more accurate classification results. According to the real environment of the Three Gorges reservoir land cover, a best texture group is selected from several texture features. Decompose the image at different levels, which is one of the main advantage of wavelet, and then compute the texture features in every sub-image, and the next step is eliminating the redundant, every texture features are centralized on the first principal components using principal component analysis. Finally, with the first principal components inputted, we can get the classification result using SVM in every decomposition scale, but what the problem we couldn't overlook is how to select the best SVM parameters. So an iterative rule based on the classification accuracy is induced, the more accuracy, the proper parameters.

  18. 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.

  19. 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.

  20. Fully automatic detection of salient features in 3-d transesophageal images.

    PubMed

    Curiale, Ariel H; Haak, Alexander; Vegas-Sánchez-Ferrero, Gonzalo; Ren, Ben; Aja-Fernández, Santiago; Bosch, Johan G

    2014-12-01

    Most automated segmentation approaches to the mitral valve and left ventricle in 3-D echocardiography require a manual initialization. In this article, we propose a fully automatic scheme to initialize a multicavity segmentation approach in 3-D transesophageal echocardiography by detecting the left ventricle long axis, the mitral valve and the aortic valve location. Our approach uses a probabilistic and structural tissue classification to find structures such as the mitral and aortic valves; the Hough transform for circles to find the center of the left ventricle; and multidimensional dynamic programming to find the best position for the left ventricle long axis. For accuracy and agreement assessment, the proposed method was evaluated in 19 patients with respect to manual landmarks and as initialization of a multicavity segmentation approach for the left ventricle, the right ventricle, the left atrium, the right atrium and the aorta. The segmentation results revealed no statistically significant differences between manual and automated initialization in a paired t-test (p > 0.05). Additionally, small biases between manual and automated initialization were detected in the Bland-Altman analysis (bias, variance) for the left ventricle (-0.04, 0.10); right ventricle (-0.07, 0.18); left atrium (-0.01, 0.03); right atrium (-0.04, 0.13); and aorta (-0.05, 0.14). These results indicate that the proposed approach provides robust and accurate detection to initialize a multicavity segmentation approach without any user interaction. PMID:25308940

  1. Multi-view alignment with database of features for an improved usage of high-end 3D scanners

    NASA Astrophysics Data System (ADS)

    Bonarrigo, Francesco; Signoroni, Alberto; Leonardi, Riccardo

    2012-12-01

    The usability of high-precision and high-resolution 3D scanners is of crucial importance due to the increasing demand of 3D data in both professional and general-purpose applications. Simplified, intuitive and rapid object modeling requires effective and automated alignment pipelines capable to trace back each independently acquired range image of the scanned object into a common reference system. To this end, we propose a reliable and fast feature-based multiple-view alignment pipeline that allows interactive registration of multiple views according to an unchained acquisition procedure. A robust alignment of each new view is estimated with respect to the previously aligned data through fast extraction, representation and matching of feature points detected in overlapping areas from different views. The proposed pipeline guarantees a highly reliable alignment of dense range image datasets on a variety of objects in few seconds per million of points.

  2. 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.

  3. 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.

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

    PubMed

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

    2011-06-01

    Dynamic contrast-enhanced (DCE)-magnetic resonance imaging (MRI) of the breast has emerged as an adjunct imaging tool to conventional X-ray mammography due to its high detection sensitivity. Despite the increasing use of breast DCE-MRI, specificity in distinguishing malignant from benign breast lesions is low, and interobserver variability in lesion classification is high. The novel contribution of this paper is in the definition of a new DCE-MRI descriptor that we call textural kinetics, which attempts to capture spatiotemporal changes in breast lesion texture in order to distinguish malignant from benign lesions. We qualitatively and quantitatively demonstrated on 41 breast DCE-MRI studies that textural kinetic features outperform signal intensity kinetics and lesion morphology features in distinguishing benign from malignant lesions. A probabilistic boosting tree (PBT) classifier in conjunction with textural kinetic descriptors yielded an accuracy of 90%, sensitivity of 95%, specificity of 82%, and an area under the curve (AUC) of 0.92. Graph embedding, used for qualitative visualization of a low-dimensional representation of the data, showed the best separation between benign and malignant lesions when using textural kinetic features. The PBT classifier results and trends were also corroborated via a support vector machine classifier which showed that textural kinetic features outperformed the morphological, static texture, and signal intensity kinetics descriptors. When textural kinetic attributes were combined with morphologic descriptors, the resulting PBT classifier yielded 89% accuracy, 99% sensitivity, 76% specificity, and an AUC of 0.91. PMID:20508965

  5. Comparison of the predictive power of beef surface wavelet texture features at high and low magnification.

    PubMed

    Jackman, Patrick; Sun, Da-Wen; Allen, Paul

    2009-07-01

    Beef longissimus dorsi surface texture is an indicator used in predicting beef palatability by expert graders. Computer vision systems have previously used imaging at normal view to develop surface texture features with some success. Good models of beef overall acceptability using imaging at high magnification have been recently developed. As a comparison the same surface texture features were computed from the corresponding images at normal view and used to model overall acceptability. Both sets of texture features were also combined with muscle colour and marbling features and used to model overall acceptability. Models using texture features alone were more successful at normal modality. However colour and marbling features combined much better with texture features at high modality to yield the most accurate model of overall acceptability (r(2)=0.93). Accurate Partial Least Squares Regression (PLSR) models were computed at both modalities with and without inclusion of colour and marbling features. Addition of squared terms to the models failed to improve accuracy. PMID:20416713

  6. 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

  7. 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.

  8. Form feature and tolerance transfer from a 3D model to a setup planning system

    SciTech Connect

    Zhang, Hong-Chao; Zhou, Feng; Kuo, Tsai-Chi; Huang, S.H.

    1996-12-31

    Currently, most CAD systems, even the feature-based design systems which were developed for the need of CAPP, cannot provide exact information of an object (e.g., dimensions and tolerances). Some feature-based design systems can provide product data directly or indirectly; however, most CAPP systems still does not have interface with those CAD systems. The product data required by these CAPP systems usually has a specific format. In the CAPP system, it is essential for setup planning to ensure the precision of machining processes. Therefore, it is necessary to develop an interface with CAD models that the part data file can be obtained directly from CAD representation. This paper proposes an approach to integrate the setup planning system with a feature-based CAD system. By using an object-oriented approach - Product Data Translator (PDT), the compute-automated extraction of geometry and complete tolerance information is achieved; and the automated generation of tool approach direction was developed.

  9. Topology-based Simplification for Feature Extraction from 3D Scalar Fields

    SciTech Connect

    Gyulassy, A; Natarajan, V; Pascucci, V; Bremer, P; Hamann, B

    2005-10-13

    This paper describes a topological approach for simplifying continuous functions defined on volumetric domains. We present a combinatorial algorithm that simplifies the Morse-Smale complex by repeated application of two atomic operations that removes pairs of critical points. The Morse-Smale complex is a topological data structure that provides a compact representation of gradient flows between critical points of a function. Critical points paired by the Morse-Smale complex identify topological features and their importance. The simplification procedure leaves important critical points untouched, and is therefore useful for extracting desirable features. We also present a visualization of the simplified topology.

  10. 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.

  11. 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.

  12. 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.

  13. 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

  14. A cosmic microwave background feature consistent with a cosmic texture.

    PubMed

    Cruz, M; Turok, N; Vielva, P; Martínez-González, E; Hobson, M

    2007-12-01

    The Cosmic Microwave Background provides our most ancient image of the universe and our best tool for studying its early evolution. Theories of high-energy physics predict the formation of various types of topological defects in the very early universe, including cosmic texture, which would generate hot and cold spots in the Cosmic Microwave Background. We show through a Bayesian statistical analysis that the most prominent 5 degrees -radius cold spot observed in all-sky images, which is otherwise hard to explain, is compatible with having being caused by a texture. From this model, we constrain the fundamental symmetry-breaking energy scale to be (0) approximately 8.7 x 10(15) gigaelectron volts. If confirmed, this detection of a cosmic defect will probe physics at energies exceeding any conceivable terrestrial experiment. PMID:17962521

  15. 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.

  16. Learning How to Extract Rotation-Invariant and Scale-Invariant Features from Texture Images

    NASA Astrophysics Data System (ADS)

    Montoya-Zegarra, Javier A.; Papa, João Paulo; Leite, Neucimar J.; da Silva Torres, Ricardo; Falcão, Alexandre

    2008-12-01

    Learning how to extract texture features from noncontrolled environments characterized by distorted images is a still-open task. By using a new rotation-invariant and scale-invariant image descriptor based on steerable pyramid decomposition, and a novel multiclass recognition method based on optimum-path forest, a new texture recognition system is proposed. By combining the discriminating power of our image descriptor and classifier, our system uses small-size feature vectors to characterize texture images without compromising overall classification rates. State-of-the-art recognition results are further presented on the Brodatz data set. High classification rates demonstrate the superiority of the proposed system.

  17. 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

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

    PubMed Central

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

    2007-01-01

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

  19. 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.

  20. 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…

  1. 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. PMID:23559545

  2. 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

  3. Texture Feature Extraction and Analysis for Polyp Differentiation via Computed Tomography Colonography.

    PubMed

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

    2016-06-01

    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 with diagnostic capability. However, image textures are frequently compromised, particularly in low-dose CT imaging. Furthermore, texture feature extraction may vary, depending on the polyp spatial orientation variation, 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 (e.g. gradient and curvature) operations are performed on the CT intensity image to amplify the textures with adequate noise control. Then Haralick co-occurrence matrix (CM) is used to calculate texture measures along each of the 13 directions (defined by the first and second 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, Karhunen-Loeve transform is performed to map the 13 directions into an orthogonal coordinate system so that the resulted texture features are less dependent on the polyp orientation variation. These simple ideas for amplifying textures and stabilizing spatial variation demonstrated a significant impact for the differentiating task 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 achieved differentiation capability of 0.8016, indicating the CTC diagnostic feasibility. PMID:26800530

  4. Stereo 3-D Imagery Uses for Definition of Geologic Structures and Geomorphic Features (Anaglyph colored glasses employed)

    NASA Astrophysics Data System (ADS)

    Hicks, B. G.; Fuente, J. D.

    2008-12-01

    Recently completed projects incorporating TopoMorpher* digital images as adjuncts to commonly employed tools has emphasized the distinct advantage gained with STEREO 3-D DIGITAL IMAGERY. By manipulating scale, relief (four types of digital shading), sun angle, direction of viewing and tilt of scene, etc. -- to produce differing views of the same terrain -- aids in identifying, tracing, and interpreting ground surface anomalies. *TopoMorpher is a digital software product of Eighteen Software (18 software.com). The advantage of Stereo 3-D views combined with digital removal of vegetation which blocked interpretation (commonly called 'bare earth/naked' views) cannot be over-emphasized. The TopoMorpher program creates scenes transferable to disk for printing at any size. Included is with computer projector which allows large display and discussion ease for groups. The examples include (1) fault systems for targeting water well locations in bedrock and (2) delineation of debris slide and avalanche terrain. Combining geologic mapping and spring locations with Stereo 3-D TopoMorpher tracing of fault lineaments has allowed targeting of water well drilling sites. Selection of geophysical study areas for well siting has been simplified. Stereo 3-D TopoMorpher has a specific "relief/terrain setting" to define potential failure sites by producing detailed colored slope maps keyed to field-data derived parameters. Posters display individual project images and large scale overviews for identifying unusual major terrain features. Images at scales using 10 and 30 meter digital data as well as Lidar (< 1 meter) will be shown.

  5. 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

  6. Feature extraction algorithm for 3D scene modeling and visualization using monostatic SAR

    NASA Astrophysics Data System (ADS)

    Jackson, Julie A.; Moses, Randolph L.

    2006-05-01

    We present a feature extraction algorithm to detect scattering centers in three dimensions using monostatic synthetic aperture radar imagery. We develop attributed scattering center models that describe the radar response of canonical shapes. We employ these models to characterize a complex target geometry as a superposition of simpler, low-dimensional structures. Such a characterization provides a means for target visualization. Fitting an attributed scattering model to sensed radar data is comprised of two problems: detection and estimation. The detection problem is to find canonical targets in clutter. The estimation problem then fits the detected canonical shape model with parameters, such as size and orientation, that correspond to the measured target response. We present an algorithm to detect canonical scattering structures amidst clutter and to estimate the corresponding model parameters. We employ full-polarimetric imagery to accurately classify canonical shapes. Interformetric processing allows us to estimate scattering center locations in three-dimensions. We apply the algorithm to scattering prediction data of a simple scene comprised of canonical scatterers and to scattering predictions of a backhoe.

  7. High Resolution Prediction of Calcium-Binding Sites in 3D Protein Structures Using FEATURE

    PubMed Central

    2015-01-01

    Metal-binding proteins are ubiquitous in biological systems ranging from enzymes to cell surface receptors. Among the various biologically active metal ions, calcium plays a large role in regulating cellular and physiological changes. With the increasing number of high-quality crystal structures of proteins associated with their metal ion ligands, many groups have built models to identify Ca2+ sites in proteins, utilizing information such as structure, geometry, or homology to do the inference. We present a FEATURE-based approach in building such a model and show that our model is able to discriminate between nonsites and calcium-binding sites with a very high precision of more than 98%. We demonstrate the high specificity of our model by applying it to test sets constructed from other ions. We also introduce an algorithm to convert high scoring regions into specific site predictions and demonstrate the usage by scanning a test set of 91 calcium-binding protein structures (190 calcium sites). The algorithm has a recall of more than 93% on the test set with predictions found within 3 Å of the actual sites. PMID:26226489

  8. 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

  9. 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

  10. 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

  11. 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.

  12. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  14. 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.

  15. Sub-100 nm biodegradable nanoparticles: in vitro release features and toxicity testing in 2D and 3D cell cultures

    NASA Astrophysics Data System (ADS)

    Biondi, Marco; Guarnieri, Daniela; Yu, Hui; Belli, Valentina; Netti, Paolo Antonio

    2013-02-01

    A big challenge in tumor targeting by nanoparticles (NPs), taking advantage of the enhanced permeability and retention effect, is the fabrication of small size devices for enhanced tumor penetration, which is considered fundamental to improve chemotherapy efficacy. The purposes of this study are (i) to engineer the formulation of doxorubicin-loaded poly(d,l-lactic-co-glycolic acid) (PLGA)-block-poly(ethylene glycol) (PEG) NPs to obtain <100 nm devices and (ii) to translate standard 2D cytotoxicity studies to 3D collagen systems in which an initial step gradient of the NPs is present. Doxorubicin release can be prolonged for days to weeks depending on the NP formulation and the pH of the release medium. Sub-100 nm NPs are effectively internalized by HeLa cells in 2D and are less cytotoxic than free doxorubicin. In 3D, <100 nm NPs are significantly more toxic than larger ones towards HeLa cells, and the cell death rate is affected by the contributions of drug release and device transport through collagen. Thus, the reduction of NP size is a fundamental feature from both a technological and a biological point of view and must be properly engineered to optimize the tumor response to the NPs.

  16. The Radiological Feature of Anterior Occiput-to-Axis Screw Fixation as it Guides the Screw Trajectory on 3D Printed Models: A Feasibility Study on 3D Images and 3D Printed Models

    PubMed Central

    Wu, Ai-Min; Wang, Sheng; Weng, Wan-Qing; Shao, Zhen-Xuan; Yang, Xin-Dong; Wang, Jian-Shun; Xu, Hua-Zi; Chi, Yong-Long

    2014-01-01

    Abstract Anterior occiput-to-axis screw fixation is more suitable than a posterior approach for some patients with a history of posterior surgery. The complex osseous anatomy between the occiput and the axis causes a high risk of injury to neurological and vascular structures, and it is important to have an accurate screw trajectory to guide anterior occiput-to-axis screw fixation. Thirty computed tomography (CT) scans of upper cervical spines were obtained for three-dimensional (3D) reconstruction. Cylinders (1.75 mm radius) were drawn to simulate the trajectory of an anterior occiput-to-axis screw. The imitation screw was adjusted to 4 different angles and measured, as were the values of the maximized anteroposterior width and the left-right width of the occiput (C0) to the C1 and C1 to C2 joints. Then, the 3D models were printed, and an angle guide device was used to introduce the screws into the 3D models referring to the angles calculated from the 3D images. We found the screw angle ranged from α1 (left: 4.99 ± 4.59°; right: 4.28 ± 5.45°) to α2 (left: 20.22 ± 3.61°; right: 19.63 ± 4.94°); on the lateral view, the screw angle ranged from β1 (left: 13.13 ± 4.93°; right: 11.82 ± 5.64°) to β2 (left: 34.86 ± 6.00°; right: 35.01 ± 5.77°). No statistically significant difference was found between the data of the left and right sides. On the 3D printed models, all of the anterior occiput-to-axis screws were successfully introduced, and none of them penetrated outside of the cortex; the mean α4 was 12.00 ± 4.11 (left) and 12.25 ± 4.05 (right), and the mean β4 was 23.44 ± 4.21 (left) and 22.75 ± 4.41 (right). No significant difference was found between α4 and β4 on the 3D printed models and α3 and β3 calculated from the 3D digital images of the left and right sides. Aided with the angle guide device, we could achieve an optimal screw trajectory for anterior occiput-to-axis screw fixation on

  17. 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.

  18. 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. PMID:24801517

  19. Automatic segmentation of solitary pulmonary nodules based on local intensity structure analysis and 3D neighborhood features in 3D chest CT images

    NASA Astrophysics Data System (ADS)

    Chen, Bin; Kitasaka, Takayuki; Honma, Hirotoshi; Takabatake, Hirotsugu; Mori, Masaki; Natori, Hiroshi; Mori, Kensaku

    2012-03-01

    This paper presents a solitary pulmonary nodule (SPN) segmentation method based on local intensity structure analysis and neighborhood feature analysis in chest CT images. Automated segmentation of SPNs is desirable for a chest computer-aided detection/diagnosis (CAS) system since a SPN may indicate early stage of lung cancer. Due to the similar intensities of SPNs and other chest structures such as blood vessels, many false positives (FPs) are generated by nodule detection methods. To reduce such FPs, we introduce two features that analyze the relation between each segmented nodule candidate and it neighborhood region. The proposed method utilizes a blob-like structure enhancement (BSE) filter based on Hessian analysis to augment the blob-like structures as initial nodule candidates. Then a fine segmentation is performed to segment much more accurate region of each nodule candidate. FP reduction is mainly addressed by investigating two neighborhood features based on volume ratio and eigenvector of Hessian that are calculates from the neighborhood region of each nodule candidate. We evaluated the proposed method by using 40 chest CT images, include 20 standard-dose CT images that we randomly chosen from a local database and 20 low-dose CT images that were randomly chosen from a public database: LIDC. The experimental results revealed that the average TP rate of proposed method was 93.6% with 12.3 FPs/case.

  20. 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.

  1. 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

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

    PubMed Central

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

    2016-01-01

    Purpose: Imaging biomarker research focuses on discovering relationships between radiological features and histological findings. In glioblastoma patients, methylation of the O6-methylguanine methyltransferase (MGMT) gene promoter is positively correlated with an increased effectiveness of current standard of care. In this paper, the authors investigate texture features as potential imaging biomarkers for capturing the MGMT methylation status of glioblastoma multiforme (GBM) tumors when combined with supervised classification schemes. Methods: A retrospective study of 155 GBM patients with known MGMT methylation status was conducted. Co-occurrence and run length texture features were calculated, and both support vector machines (SVMs) and random forest classifiers were used to predict MGMT methylation status. Results: The best classification system (an SVM-based classifier) had a maximum area under the receiver-operating characteristic (ROC) curve of 0.85 (95% CI: 0.78–0.91) using four texture features (correlation, energy, entropy, and local intensity) originating from the T2-weighted images, yielding at the optimal threshold of the ROC curve, a sensitivity of 0.803 and a specificity of 0.813. Conclusions: Results show that supervised machine learning of MRI texture features can predict MGMT methylation status in preoperative GBM tumors, thus providing a new noninvasive imaging biomarker. PMID:27277032

  3. 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

  4. 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

  5. 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

  6. 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

  7. 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.

  8. 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

  9. Characterizing the textural features of gold ores for optimizing gold extraction

    NASA Astrophysics Data System (ADS)

    Hausen, Donald M.

    2000-04-01

    The beneficiation of gold ores begins with an examination and classification of the types of gold occurrences and recovery methods. Measurements can provide the necessary grind size for liberation and determine the sizes and associations of gold with gangue materials. In this article, the textural features several gold occurrences are described and compared.

  10. Analyzing fine-scale wetland composition using high resolution imagery and texture features

    NASA Astrophysics Data System (ADS)

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

    2013-08-01

    In order to monitor natural and anthropogenic disturbance effects to wetland ecosystems, it is necessary to employ both accurate and rapid mapping of wet graminoid/sedge communities. Thus, it is desirable to utilize automated classification algorithms so that the monitoring can be done regularly and in an efficient manner. This study developed a classification and accuracy assessment method for wetland mapping of at-risk plant communities in marl prairie and marsh areas of the Everglades National Park. Maximum likelihood (ML) and Support Vector Machine (SVM) classifiers were tested using 30.5 cm aerial imagery, the normalized difference vegetation index (NDVI), first and second order texture features and ancillary data. Additionally, appropriate window sizes for different texture features were estimated using semivariogram analysis. Findings show that the addition of NDVI and texture features increased classification accuracy from 66.2% using the ML classifier (spectral bands only) to 83.71% using the SVM classifier (spectral bands, NDVI and first order texture features).

  11. 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

  12. A statistical-textural-features based approach for classification of solid drugs using surface microscopic images.

    PubMed

    Tahir, Fahima; Fahiem, Muhammad Abuzar

    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

  13. 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. PMID:25537575

  14. Detection of Focal Cortical Dysplasia Lesions in MRI Using Textural Features

    NASA Astrophysics Data System (ADS)

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

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

  15. 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.

  16. 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

  17. 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.

  18. 3D SMoSIFT: three-dimensional sparse motion scale invariant feature transform for activity recognition from RGB-D videos

    NASA Astrophysics Data System (ADS)

    Wan, Jun; Ruan, Qiuqi; Li, Wei; An, Gaoyun; Zhao, Ruizhen

    2014-03-01

    Human activity recognition based on RGB-D data has received more attention in recent years. We propose a spatiotemporal feature named three-dimensional (3D) sparse motion scale-invariant feature transform (SIFT) from RGB-D data for activity recognition. First, we build pyramids as scale space for each RGB and depth frame, and then use Shi-Tomasi corner detector and sparse optical flow to quickly detect and track robust keypoints around the motion pattern in the scale space. Subsequently, local patches around keypoints, which are extracted from RGB-D data, are used to build 3D gradient and motion spaces. Then SIFT-like descriptors are calculated on both 3D spaces, respectively. The proposed feature is invariant to scale, transition, and partial occlusions. More importantly, the running time of the proposed feature is fast so that it is well-suited for real-time applications. We have evaluated the proposed feature under a bag of words model on three public RGB-D datasets: one-shot learning Chalearn Gesture Dataset, Cornell Activity Dataset-60, and MSR Daily Activity 3D dataset. Experimental results show that the proposed feature outperforms other spatiotemporal features and are comparative to other state-of-the-art approaches, even though there is only one training sample for each class.

  19. 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

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

    PubMed Central

    Wang, Kun-Ching

    2014-01-01

    In this paper, we present a novel texture image feature for Emotion Sensing in Speech (ESS). This idea is based on the fact that the texture images carry emotion-related information. The feature extraction is derived from time-frequency representation of spectrogram images. First, we transform the spectrogram as a recognizable image. Next, we use a cubic curve to enhance the image contrast. Then, the texture image information (TII) derived from the spectrogram image can be extracted by using Laws' masks to characterize emotional state. In order to evaluate the effectiveness of the proposed emotion recognition in different languages, we use two open emotional databases including the Berlin Emotional Speech Database (EMO-DB) and eNTERFACE corpus and one self-recorded database (KHUSC-EmoDB), to evaluate the performance cross-corpora. The results of the proposed ESS system are presented using support vector machine (SVM) as a classifier. Experimental results show that the proposed TII-based feature extraction inspired by visual perception can provide significant classification for ESS systems. The two-dimensional (2-D) TII feature can provide the discrimination between different emotions in visual expressions except for the conveyance pitch and formant tracks. In addition, the de-noising in 2-D images can be more easily completed than de-noising in 1-D speech. PMID:25207869

  1. The feature extraction based on texture image information for emotion sensing in speech.

    PubMed

    Wang, Kun-Ching

    2014-01-01

    In this paper, we present a novel texture image feature for Emotion Sensing in Speech (ESS). This idea is based on the fact that the texture images carry emotion-related information. The feature extraction is derived from time-frequency representation of spectrogram images. First, we transform the spectrogram as a recognizable image. Next, we use a cubic curve to enhance the image contrast. Then, the texture image information (TII) derived from the spectrogram image can be extracted by using Laws' masks to characterize emotional state. In order to evaluate the effectiveness of the proposed emotion recognition in different languages, we use two open emotional databases including the Berlin Emotional Speech Database (EMO-DB) and eNTERFACE corpus and one self-recorded database (KHUSC-EmoDB), to evaluate the performance cross-corpora. The results of the proposed ESS system are presented using support vector machine (SVM) as a classifier. Experimental results show that the proposed TII-based feature extraction inspired by visual perception can provide significant classification for ESS systems. The two-dimensional (2-D) TII feature can provide the discrimination between different emotions in visual expressions except for the conveyance pitch and formant tracks. In addition, the de-noising in 2-D images can be more easily completed than de-noising in 1-D speech. PMID:25207869

  2. 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

  3. Analysis of Shot Boundary Based on Color and Texture Features of Frame

    NASA Astrophysics Data System (ADS)

    Lin, Chuen-Horng; Hsiao, Muh-Don; Fu, Li-Jung

    2013-12-01

    This paper proposed a shot boundary detection method based on color and texture features of frames. The shot boundary detection is employed in order to build a highly efficient method for video description. The research methods include feature extraction using color and texture feature, and shot boundary detection offering an adaptive measuring method. In this paper, the color and texture features are Traditional Color Histogram (TCH) and Histogram of Gradient Directions (HGD), respectively. The adaptive measuring method was proposed for the threshold of distance as the basis of identifying shot changes between frames. In order to validate the shot boundary detection method proposed herein, the video database provided by Carleton University website was used for the experiment. The experimental and comparison results of shot boundary detection were validated, and the experimental results were analyzed. This study carried out a series of comparisons and analyses for the above video database, and proved that the shot boundary detection method proposed could effectively detect the shot boundary.

  4. 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

  5. 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

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

    PubMed

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

    2014-07-01

    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 ([Formula: see text]). PMID:26158036

  7. 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

  8. 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

  9. 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.

  10. 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.

  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. 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.

  13. Computer-aided diagnosis in CT colonography: detection of polyps based on geometric and texture features

    NASA Astrophysics Data System (ADS)

    Yoshida, Hiroyuki; Naeppi, Janne J.; Frimmel, Hans; Dachman, Abraham H.

    2002-05-01

    A computer-aided diagnosis scheme for the detection of colonic polyps in CT colonography has been developed, and its performance has been assessed based on clinical cases with colonoscopy-confirmed polyps. In the scheme, the colon was automatically segmented by use of knowledge-guided segmentation from 3-dimensional isotropic volumes reconstructed from axial CT slices in CT colonography. Polyp candidates are detected by first computing of 3-dimensional geometric features that characterize polyps, and then segmenting of connected components corresponding to suspicious regions by hysteresis thresholding and fuzzy clustering based on these geometric features. False-positive detections are reduced by computation of 3-dimensional texture features characterizing the internal structures of the polyp candidates, followed by application of discriminant analysis to the feature space generated by the geometric and texture features. We applied our scheme to 43 CT colonographic cases with cleansed colon, including 12 polyps larger than 5 mm. In a by-dataset analysis, the CAD scheme yielded a sensitivity of 95% with 1.2 false positives per data set. The false negative was one of the two polyps in a single patient. Consequently, in by-patient analysis, our method yielded 100% sensitivity with 2.0 false positives per patient. The results indicate that our CAD scheme has the potential to detect clinically important polyp cases with a high sensitivity and a relatively low false-positive rate.

  14. 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.

  15. A study of selected textural features usefulness for impervious surface coverage estimation using Landsat images

    NASA Astrophysics Data System (ADS)

    Bernat, Katarzyna; Drzewiecki, Wojciech

    2015-10-01

    The aim of our research was to evaluate the applicability of textural measures for sub-pixel impervious surfaces estimation using Landsat TM images based on machine learning algorithms. We put the particular focus on determining usefulness of five textural features groups in respect to pixel- and sub-pixel level. However, the two-stage approach to impervious surfaces coverage estimation was also tested. We compared the accuracy of impervious surfaces estimation using spectral bands only with results of imperviousness index estimation based on extended classification features sets (spectral band values supplemented with measures derived from various textural characteristics groups). Impervious surfaces coverage estimation was done using decision and regression trees based on C5.0 and Cubist algorithms. At the stage of classification the research area was divided into two categories: i) completely permeable (imperviousness index less than 1%) and ii) fully or partially impervious areas. At the stage of sub-pixel classification evaluation of percentage impervious surfaces coverage within single pixel was done. Based on the results of cross-validation, we selected the approaches guaranteeing the lowest means errors in terms of training set. Accuracy of the imperviousness index estimation was checked based on validation data set. The average error of hard classification using spectral features only was 6.5% and about 4.4% for spectral features combining with absolute gradient-based characteristics. The root mean square error (RMSE) of determination of the percentage impervious surfaces coverage within a single pixel was equal to 9.46% for the best tested classification features sets. The two-stage procedure was utilized for the primary approach involving spectral bands as the classification features set and for the approach guaranteeing the best accuracy for classification and regression stage. The results have shown that inclusion of textural measures into

  16. 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.

  17. Classification of benign and malignant breast masses based on shape and texture features in sonography images.

    PubMed

    Zakeri, Fahimeh Sadat; Behnam, Hamid; Ahmadinejad, Nasrin

    2012-06-01

    The purpose of this research was evaluating novel shape and texture feature' efficiency in classification of benign and malignant breast masses in sonography images. First, mass regions were extracted from the region of interest (ROI) sub-image by implementing a new hybrid segmentation approach based on level set algorithms. Then two left and right side areas of the masses are elicited. After that, six features (Eccentricity_feature, Solidity_feature, DeferenceArea_Hull_Rectangular, DeferenceArea_Mass_Rectangular, Cross-correlation-left and Cross-correlation-right) based on shape, texture and region characteristics of the masses were extracted for further classification. Finally a support vector machine (SVM) classifier was utilized to classify breast masses. The leave-one-case-out protocol was utilized on a database of eighty pathologically-proven breast sonographic images of patients (forty-seven benign cases and thirty-three malignant cases) to evaluate our method. The classification results showed an overall accuracy of 95.00%, sensitivity of 90.91%, specificity of 97.87%, positive predictive value of 96.77%, negative predictive value of 93.88%, and Matthew's correlation coefficient of 89.71%. The experimental results declare that our proposed method is actually a beneficial tool for the diagnosis of the breast cancer and can provide a second opinion for a physician's decision or can be used for the medicine training especially when coupled with other modalities. PMID:21082222

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

    PubMed

    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 (18)F-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

  19. 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

  20. 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.

  1. 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.

  2. 3D World Building System

    ScienceCinema

    None

    2014-02-26

    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.

  3. A method of detecting land use change of remote sensing images based on texture features and DEM

    NASA Astrophysics Data System (ADS)

    Huang, Dong-ming; Wei, Chun-tao; Yu, Jun-chen; Wang, Jian-lin

    2015-12-01

    In this paper, a combination method, between the neural network and textures information, is proposed to remote sensing images classification. The methodology involves an extraction of texture features using the gray level co-occurrence matrix and image classification with BP artificial neural network. The combination of texture features and the digital elevation model (DEM) as classified bands to neural network were used to recognized different classes. This scheme shows high recognition accuracy in the classification of remote sensing images. In the experiments, the proposed method was successfully applied to remote sensing image classification and Land Use Change Detection, in the meanwhile, the effectiveness of the proposed method was verified.

  4. Object Tracking in Crowded Video Scenes Based on the Undecimated Wavelet Features and Texture Analysis

    NASA Astrophysics Data System (ADS)

    Khansari, M.; Rabiee, H. R.; Asadi, M.; Ghanbari, M.

    2007-12-01

    We propose a new algorithm for object tracking in crowded video scenes by exploiting the properties of undecimated wavelet packet transform (UWPT) and interframe texture analysis. The algorithm is initialized by the user through specifying a region around the object of interest at the reference frame. Then, coefficients of the UWPT of the region are used to construct a feature vector (FV) for every pixel in that region. Optimal search for the best match is then performed by using the generated FVs inside an adaptive search window. Adaptation of the search window is achieved by interframe texture analysis to find the direction and speed of the object motion. This temporal texture analysis also assists in tracking of the object under partial or short-term full occlusion. Moreover, the tracking algorithm is robust to Gaussian and quantization noise processes. Experimental results show that the proposed algorithm has good performance for object tracking in crowded scenes on stairs, in airports, or at train stations in the presence of object translation, rotation, small scaling, and occlusion.

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. Atherosclerotic risk stratification strategy for carotid arteries using texture-based features.

    PubMed

    Acharya, U Rajendra; Sree, S Vinitha; Krishnan, M Muthu Rama; Molinari, Filippo; Saba, Luca; Ho, Sin Yee Stella; Ahuja, Anil T; Ho, Suzanne C; Nicolaides, Andrew; Suri, Jasjit S

    2012-06-01

    Plaques in the carotid artery result in stenosis, which is one of the main causes for stroke. Patients have to be carefully selected for stenosis treatments as they carry some risk. Since patients with symptomatic plaques have greater risk for strokes, an objective classification technique that classifies the plaques into symptomatic and asymptomatic classes is needed. We present a computer aided diagnostic (CAD) based ultrasound characterization methodology (a class of Atheromatic systems) that classifies the patient into symptomatic and asymptomatic classes using two kinds of datasets: (1) plaque regions in ultrasound carotids segmented semi-automatically and (2) far wall gray-scale intima-media thickness (IMT) regions along the common carotid artery segmented automatically. For both kinds of datasets, the protocol consists of estimating texture-based features in frameworks of local binary patterns (LBP) and Law's texture energy (LTE) and applying these features for obtaining the training parameters, which are then used for classification. Our database consists of 150 asymptomatic and 196 symptomatic plaque regions and 342 IMT wall regions. When using the Atheromatic-based system on semiautomatically determined plaque regions, support vector machine (SVM) classifier was adapted with highest accuracy of 83%. The accuracy registered was 89.5% on the far wall gray-scale IMT regions when using SVM, K-nearest neighbor (KNN) or radial basis probabilistic neural network (RBPNN) classifiers. LBP/LTE-based techniques on both kinds of carotid datasets are noninvasive, fast, objective and cost-effective for plaque characterization and, hence, will add more value to the existing carotid plaque diagnostics protocol. We have also proposed an index for each type of datasets: AtheromaticPi, for carotid plaque region, and AtheromaticWi, for IMT carotid wall region, based on the combination of the respective significant features. These indices show a separation between symptomatic

  10. 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

  11. 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

  12. 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.

  13. 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. PMID:26758780

  14. 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.

  15. Studying the effect of noise on the performance of 2D and 3D texture measures for quantifying the trabecular bone structure as obtained with high resolution MR imaging at 3 tesla

    NASA Astrophysics Data System (ADS)

    Monetti, Roberto; Bauer, Jan; Mueller, Dirk; Rummeny, Ernst J.; Link, Thomas M.; Majumdar, Sharmila; Matsuura, Maiko; Eckstein, Felix; Sidorenko, Irina; Raeth, Christoph W.

    2008-03-01

    3.0 Tesla MRI devices are becoming popular in clinical applications since they render images with a higher signal-tonoise ratio than the former 1.5 Tesla MRI devices. Here, we investigate if higher signal-to-noise ratio can be beneficial for a quantitative image analysis in the context of bone research. We performed a detailed analysis of the effect of noise on the performance of 2D morphometric linear measures and a 3D nonlinear measure with respect to their correlation with biomechanical properties of the bone expressed by the maximum compressive strength. The performance of both 2D and 3D texture measures was relatively insensitive to superimposed artificial noise. This finding suggests that MR sequences for visualizing bone structures at 3T should rather be optimized to spatial resolution (or scanning time) than to signal-to-noise ratio.

  16. Scaling properties of the anisotropic critical current density in bulk textured YBaCuO. Evidence toward a 3D flux line lattice

    SciTech Connect

    Braithwaite, D.; Bourgault, D.; Sulpice, A.; Barbut, J.M.; Tournier, R. l'Universite Joseph Fourier, Grenoble ); Monot, I.; Lepropre, M.; Provost, J.; Desgardin, G. )

    1993-04-01

    The dc transport critical current densities of melt texture grown and magnetically melt textured bulk YBaCuO have been measured at 77 K and in magnetic fields. A maximum value of over 31,000 A/cm[sup 2] is obtained with a field of 7 teslas applied parallel to the (a,b) planes. Over the rest of the angular range the critical current is shown to be determined mainly by the c-axis component of the applied field. Although this dependency is expected in the presence of two-dimensional vortices, in fact the data are shown to correspond better to the behavior expected of an anisotropic three-dimensional superconductor. These results are compared to magnetization measurements on the same samples. Results show that when the field is directed close to the c-axis, superconducting transport currents flow at fields well above the field at which the irreversible magnetization disappears.

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

    PubMed Central

    Chalkidou, Anastasia; O’Doherty, Michael J.; Marsden, Paul K.

    2015-01-01

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

  18. Breast tissue classification in digital tomosynthesis images based on global gradient minimization and texture features

    NASA Astrophysics Data System (ADS)

    Qin, Xulei; Lu, Guolan; Sechopoulos, Ioannis; Fei, Baowei

    2014-03-01

    Digital breast tomosynthesis (DBT) is a pseudo-three-dimensional x-ray imaging modality proposed to decrease the effect of tissue superposition present in mammography, potentially resulting in an increase in clinical performance for the detection and diagnosis of breast cancer. Tissue classification in DBT images can be useful in risk assessment, computer-aided detection and radiation dosimetry, among other aspects. However, classifying breast tissue in DBT is a challenging problem because DBT images include complicated structures, image noise, and out-of-plane artifacts due to limited angular tomographic sampling. In this project, we propose an automatic method to classify fatty and glandular tissue in DBT images. First, the DBT images are pre-processed to enhance the tissue structures and to decrease image noise and artifacts. Second, a global smooth filter based on L0 gradient minimization is applied to eliminate detailed structures and enhance large-scale ones. Third, the similar structure regions are extracted and labeled by fuzzy C-means (FCM) classification. At the same time, the texture features are also calculated. Finally, each region is classified into different tissue types based on both intensity and texture features. The proposed method is validated using five patient DBT images using manual segmentation as the gold standard. The Dice scores and the confusion matrix are utilized to evaluate the classified results. The evaluation results demonstrated the feasibility of the proposed method for classifying breast glandular and fat tissue on DBT images.

  19. 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.

  20. 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.

  1. Automatic organ localizations on 3D CT images by using majority-voting of multiple 2D detections based on local binary patterns and Haar-like features

    NASA Astrophysics Data System (ADS)

    Zhou, Xiangrong; Yamaguchi, Shoutarou; Zhou, Xinxin; Chen, Huayue; Hara, Takeshi; Yokoyama, Ryujiro; Kanematsu, Masayuki; Fujita, Hiroshi

    2013-02-01

    This paper describes an approach to accomplish the fast and automatic localization of the different inner organ regions on 3D CT scans. The proposed approach combines object detections and the majority voting technique to achieve the robust and quick organ localization. The basic idea of proposed method is to detect a number of 2D partial appearances of a 3D target region on CT images from multiple body directions, on multiple image scales, by using multiple feature spaces, and vote all the 2D detecting results back to the 3D image space to statistically decide one 3D bounding rectangle of the target organ. Ensemble learning was used to train the multiple 2D detectors based on template matching on local binary patterns and Haar-like feature spaces. A collaborative voting was used to decide the corner coordinates of the 3D bounding rectangle of the target organ region based on the coordinate histograms from detection results in three body directions. Since the architecture of the proposed method (multiple independent detections connected to a majority voting) naturally fits the parallel computing paradigm and multi-core CPU hardware, the proposed algorithm was easy to achieve a high computational efficiently for the organ localizations on a whole body CT scan by using general-purpose computers. We applied this approach to localization of 12 kinds of major organ regions independently on 1,300 torso CT scans. In our experiments, we randomly selected 300 CT scans (with human indicated organ and tissue locations) for training, and then, applied the proposed approach with the training results to localize each of the target regions on the other 1,000 CT scans for the performance testing. The experimental results showed the possibility of the proposed approach to automatically locate different kinds of organs on the whole body CT scans.

  2. Combining texture features from the MLO and CC views for mammographic CAD x

    NASA Astrophysics Data System (ADS)

    Gupta, Shalini; Zhang, David; Sampat, Mehul P.; Markey, Mia K.

    2006-03-01

    The purpose of this study was to investigate approaches for combining information from the MLO and CC mammographic views for Computer-aided Diagnosis (CADx) algorithms. Feature level and classifier output level combinations were explored. Linear discriminant analysis (LDA) with step-wise feature selection from a set of Haralick's texture features was used to develop classifiers for distinguishing between benign and malignant mammographic lesions. The effect of correlation between features from the two views on the performance of classifiers was investigated. The single view models included: (a) an LDA model with stepwise selection based on the MLO view only (MLO-Only) and similarly (b) a CC-Only LDA model. The feature-level combination models included: (a) LDA based on concatenation of feature sets selected independently from the two views (FEAT_CON), (b) LDA based on the concatenated feature sets along with the corresponding value of each feature from the opposite view (FEAT_COR_CON) if the correlation was below a threshold, (c) LDA based on the average of the MLO and CC feature values (FEAT_AVG). The classifier output level combination models investigated included: (a) average of the outputs of the MLO-Only and CC-Only classifiers (OUTPUT_AVG), (b) maximum of the outputs of the MLO-Only and CC-Only classifiers (OUTPUT_MAX), (c) minimum of the outputs of the MLO-Only and CC-Only classifiers (OUTPUT_MIN), (d) a second level LDA classifier on the outputs of the MLO-Only and CC-Only classifiers (OUTPUT_LDA), (e) product of the output values of the two classifiers (OUTPUT_PROD). The performance of the models was assessed and compared using the ROC methodology to determine if combination models performed better than the single-view models.

  3. Thermography based breast cancer detection using texture features and minimum variance quantization

    PubMed Central

    Milosevic, Marina; Jankovic, Dragan; Peulic, Aleksandar

    2014-01-01

    In this paper, we present a system based on feature extraction techniques and image segmentation techniques for detecting and diagnosing abnormal patterns in breast thermograms. The proposed system consists of three major steps: feature extraction, classification into normal and abnormal pattern and segmentation of abnormal pattern. Computed features based on gray-level co-occurrence matrices are used to evaluate the effectiveness of textural information possessed by mass regions. A total of 20 GLCM features are extracted from thermograms. The ability of feature set in differentiating abnormal from normal tissue is investigated using a Support Vector Machine classifier, Naive Bayes classifier and K-Nearest Neighbor classifier. To evaluate the classification performance, five-fold cross validation method and Receiver operating characteristic analysis was performed. The verification results show that the proposed algorithm gives the best classification results using K-Nearest Neighbor classifier and a accuracy of 92.5%. Image segmentation techniques can play an important role to segment and extract suspected hot regions of interests in the breast infrared images. Three image segmentation techniques: minimum variance quantization, dilation of image and erosion of image are discussed. The hottest regions of thermal breast images are extracted and compared to the original images. According to the results, the proposed method has potential to extract almost exact shape of tumors. PMID:26417334

  4. 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.

  5. 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

  6. 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. PMID:25893753

  7. 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.

  8. A study of cloud classification with neural networks using spectral and textural features.

    PubMed

    Tian, B; Shaikh, M A; Azimi-Sadjadi, M R; Haar, T V; Reinke, D L

    1999-01-01

    The problem of cloud data classification from satellite imagery using neural networks is considered in this paper. Several image transformations such as singular value decomposition (SVD) and wavelet packet (WP) were used to extract the salient spectral and textural features attributed to satellite cloud data in both visible and infrared (IR) channels. In addition, the well-known gray-level cooccurrence matrix (GLCM) method and spectral features were examined for the sake of comparison. Two different neural-network paradigms namely probability neural network (PNN) and unsupervised Kohonen self-organized feature map (SOM) were examined and their performance were also benchmarked on the geostationary operational environmental satellite (GOES) 8 data. Additionally, a postprocessing scheme was developed which utilizes the contextual information in the satellite images to improve the final classification accuracy. Overall, the performance of the PNN when used in conjunction with these feature extraction and postprocessing schemes showed the potential of this neural-network-based cloud classification system. PMID:18252510

  9. 3-D flexible nano-textured high-density microelectrode arrays for high-performance neuro-monitoring and neuro-stimulation.

    PubMed

    Gabran, S R I; Salam, Muhammad Tariqus; Dian, Joshua; El-Hayek, Youssef; Perez Velazquez, J L; Genov, Roman; Carlen, Peter L; Salama, M M A; Mansour, Raafat R

    2014-09-01

    We introduce a new 3-D flexible microelectrode array for high performance electrographic neural signal recording and stimulation. The microelectrode architecture maximizes the number of channels on each shank and minimizes its footprint. The electrode was implemented on flexible polyimide substrate using microfabrication and thin-film processing. The electrode has a planar layout and comprises multiple shanks. Each shank is three mm in length and carries six gold pads representing the neuro-interfacing channels. The channels are used in recording important precursors with potential clinical relevance and consequent electrical stimulation to perturb the clinical condition. The polyimide structure satisfied the mechanical characteristics required for the proper electrode implantation and operation. Pad postprocessing technique was developed to improve the electrode electrical performance. The planar electrodes were used for creating 3-D "Waterloo Array" microelectrode with controlled gaps using custom designed stackers. Electrode characterization and benchmarking against commercial equivalents demonstrated the superiority of the Flex electrodes. The Flex and commercial electrodes were associated with low-power implantable responsive neuro-stimulation system. The electrodes performance in recording and stimulation application was quantified through in vitro and in vivo acute and chronic experiments on human brain slices and freely-moving rodents. The Flex electrodes exhibited remarkable drop in the electric impedance (100 times at 100 Hz), improved electrode-electrolyte interface noise (dropped by four times) and higher signal-to-noise ratio (3.3 times). PMID:24876130

  10. 3D Non-Woven Polyvinylidene Fluoride Scaffolds: Fibre Cross Section and Texturizing Patterns Have Impact on Growth of Mesenchymal Stromal Cells

    PubMed Central

    Schellenberg, Anne; Ross, Robin; Abagnale, Giulio; Joussen, Sylvia; Schuster, Philipp; Arshi, Annahit; Pallua, Norbert; Jockenhoevel, Stefan; Gries, Thomas; Wagner, Wolfgang

    2014-01-01

    Several applications in tissue engineering require transplantation of cells embedded in appropriate biomaterial scaffolds. Such structures may consist of 3D non-woven fibrous materials whereas little is known about the impact of mesh size, pore architecture and fibre morphology on cellular behavior. In this study, we have developed polyvinylidene fluoride (PVDF) non-woven scaffolds with round, trilobal, or snowflake fibre cross section and different fibre crimp patterns (10, 16, or 28 needles per inch). Human mesenchymal stromal cells (MSCs) from adipose tissue were seeded in parallel on these scaffolds and their growth was compared. Initial cell adhesion during the seeding procedure was higher on non-wovens with round fibres than on those with snowflake or trilobal cross sections. All PVDF non-woven fabrics facilitated cell growth over a time course of 15 days. Interestingly, proliferation was significantly higher on non-wovens with round or trilobal fibres as compared to those with snowflake profile. Furthermore, proliferation increased in a wider, less dense network. Scanning electron microscopy (SEM) revealed that the MSCs aligned along the fibres and formed cellular layers spanning over the pores. 3D PVDF non-woven scaffolds support growth of MSCs, however fibre morphology and mesh size are relevant: proliferation is enhanced by round fibre cross sections and in rather wide-meshed scaffolds. PMID:24728045

  11. 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

  12. 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

  13. 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

  14. Quality Assessment of Mapping Building Textures from Infrared Image Sequences

    NASA Astrophysics Data System (ADS)

    Hoegner, L.; Iwaszczuk, D.; Stilla, U.

    2012-07-01

    Generation and texturing of building models is a fast developing field of research. Several techniques have been developed to extract building geometry and textures from multiple images and image sequences. In this paper, these techniques are discussed and extended to automatically add new textures from infrared (IR) image sequences to existing building models. In contrast to existing work, geometry and textures are not generated together from the same dataset but the textures are extracted from the image sequence and matched to an existing geo-referenced 3D building model. The texture generation is divided in two main parts. The first part deals with the estimation and refinement of the exterior camera orientation. Feature points are extracted in the images and used as tie points in the sequence. A recorded exterior orientation of the camera s added to these homologous points and a bundle adjustment is performed starting on image pairs and combining the hole sequence. A given 3d model of the observed building is additionally added to introduce further constraint as ground control points in the bundle adjustment. The second part includes the extraction of textures from the images and the combination of textures from different images of the sequence. Using the reconstructed exterior camera orientation for every image of the sequence, the visible facades are projected into the image and texture is extracted. These textures normally contain only parts of the facade. The partial textures extracted from all images are combined to one facade texture. This texture is stored with a 3D reference to the corresponding facade. This allows searching for features in textures and localising those features in 3D space. It will be shown, that the proposed strategy allows texture extraction and mapping even for big building complexes with restricted viewing possibilities and for images with low optical resolution.

  15. A Combination of Shape and Texture Features for Classification of Pulmonary Nodules in Lung CT Images.

    PubMed

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

    2016-08-01

    Classification of malignant and benign pulmonary nodules is important for further treatment plan. The present work focuses on the classification of benign and malignant pulmonary nodules using support vector machine. The pulmonary nodules are segmented using a semi-automated technique, which requires only a seed point from the end user. Several shape-based, margin-based, and texture-based features are computed to represent the pulmonary nodules. A set of relevant features is determined for the efficient representation of nodules in the feature space. The proposed classification scheme is validated on a data set of 891 nodules of Lung Image Database Consortium and Image Database Resource Initiative public database. The proposed classification scheme is evaluated for three configurations such as configuration 1 (composite rank of malignancy "1" and "2" as benign and "4" and "5" as malignant), configuration 2 (composite rank of malignancy "1","2", and "3" as benign and "4" and "5" as malignant), and configuration 3 (composite rank of malignancy "1" and "2" as benign and "3","4" and "5" as malignant). The performance of the classification is evaluated in terms of area (A z) under the receiver operating characteristic curve. The A z achieved by the proposed method for configuration-1, configuration-2, and configuration-3 are 0.9505, 0.8822, and 0.8488, respectively. The proposed method outperforms the most recent technique, which depends on the manual segmentation of pulmonary nodules by a trained radiologist. PMID:26738871

  16. 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.

  17. Surface textural features and its formation process of AISI 304 stainless steel subjected to massive LSP impacts

    NASA Astrophysics Data System (ADS)

    Luo, K. Y.; Yao, H. X.; Dai, F. Z.; Lu, J. Z.

    2014-04-01

    The effects of massive laser shock peening (LSP) impacts on surface textural feature of AISI 304 stainless steel (AISI 304 SS), including surface waviness, surface roughness, and machining texture and direction, have been investigated by using WKYO-NT1100 surface profiler and TR300 stylus roughness shape measuring instrument. Experimental results show that massive LSP impacts have an important influence on the surface waviness of the AISI 304 SS sample, but do not have a measurable impact on the surface roughness. Moreover, massive LSP impacts with constraint and ablation mode generate a novel compound texture on the surface of the AISI 304 SS sample. In addition, the formation process of surface compound texture in AISI 304 SS by massive LSP impacts is also entirely revealed.

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

    PubMed

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

    2014-01-01

    Osteosarcoma is the most common malignant bone tumor among children and adolescents. In this study, image texture analysis was made to extract texture features from bone CR images to evaluate the recognition rate of osteosarcoma. To obtain the optimal set of features, Sym4 and Db4 wavelet transforms and gray-level co-occurrence matrices were applied to the image, with statistical methods being used to maximize the feature selection. To evaluate the performance of these methods, a support vector machine algorithm was used. The experimental results demonstrated that the Sym4 wavelet had a higher classification accuracy (93.44%) than the Db4 wavelet with respect to osteosarcoma occurrence in the epiphysis, whereas the Db4 wavelet had a higher classification accuracy (96.25%) for osteosarcoma occurrence in the diaphysis. Results including accuracy, sensitivity, specificity and ROC curves obtained using the wavelets were all higher than those obtained using the features derived from the GLCM method. It is concluded that, a set of texture features can be extracted from the wavelets and used in computer-aided osteosarcoma diagnosis systems. In addition, this study also confirms that multi-resolution analysis is a useful tool for texture feature extraction during bone CR image processing. PMID:24211892

  19. 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.

  20. 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.

  1. Definition of a comprehensive set of texture semivariogram features and their evaluation for object-oriented image classification

    NASA Astrophysics Data System (ADS)

    Balaguer, A.; Ruiz, L. A.; Hermosilla, T.; Recio, J. A.

    2010-02-01

    In this paper, a comprehensive set of texture features extracted from the experimental semivariogram of specific image objects is proposed and described, and their usefulness for land use classification of high resolution images is evaluated. Fourteen features are defined and categorized into three different groups, according to the location of their respective parameters in the semivariogram curve: (i) features that use parameters close to the origin of the semivariogram, (ii) the parameters employed extend to the first maximum, and (iii) the parameters employed are extracted from the first to the second maximum. A selection of the most relevant features has been performed, combining the analysis and interpretation of redundancies, and using statistical discriminant analysis methods. The suitability of the proposed features for object-based image classification has been evaluated using digital aerial images from an agricultural area on the Mediterranean coast of Spain. The performance of the selected semivariogram features has been compared with two different sets of texture features: those derived from the grey level co-occurrence matrix, and the values of raw semivariance directly extracted from the semivariogram at different positions. As a result of the tests, the classification accuracies obtained using the proposed semivariogram features are, in general, higher and more balanced than those obtained using the other two sets of standard texture features.

  2. Bootstrapping 3D fermions

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

    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 C T . We observe features in our bounds that coincide with scaling dimensions in the GrossNeveu models at large N . We also speculate that other features could coincide with a fermionic CFT containing no relevant scalar operators.

  3. Automatic assessment of mitral regurgitation severity based on extensive textural features on 2D echocardiography videos.

    PubMed

    Moghaddasi, Hanie; Nourian, Saeed

    2016-06-01

    Heart disease is the major cause of death as well as a leading cause of disability in the developed countries. Mitral Regurgitation (MR) is a common heart disease which does not cause symptoms until its end stage. Therefore, early diagnosis of the disease is of crucial importance in the treatment process. Echocardiography is a common method of diagnosis in the severity of MR. Hence, a method which is based on echocardiography videos, image processing techniques and artificial intelligence could be helpful for clinicians, especially in borderline cases. In this paper, we introduce novel features to detect micro-patterns of echocardiography images in order to determine the severity of MR. Extensive Local Binary Pattern (ELBP) and Extensive Volume Local Binary Pattern (EVLBP) are presented as image descriptors which include details from different viewpoints of the heart in feature vectors. Support Vector Machine (SVM), Linear Discriminant Analysis (LDA) and Template Matching techniques are used as classifiers to determine the severity of MR based on textural descriptors. The SVM classifier with Extensive Uniform Local Binary Pattern (ELBPU) and Extensive Volume Local Binary Pattern (EVLBP) have the best accuracy with 99.52%, 99.38%, 99.31% and 99.59%, respectively, for the detection of Normal, Mild MR, Moderate MR and Severe MR subjects among echocardiography videos. The proposed method achieves 99.38% sensitivity and 99.63% specificity for the detection of the severity of MR and normal subjects. PMID:27082766

  4. Optimum feature size of randomly textured glass substrates for maximum scattering inside thin-film silicon solar cells

    NASA Astrophysics Data System (ADS)

    Sahraei, Nasim; Venkataraj, Selvaraj; Aberle, Armin G.; Peters, Marius

    2014-03-01

    Optimization of light scattering by designing proper randomly textured surfaces is one of the important issues when designing thin-film silicon solar cell structures. The wavelength region that needs to be scattered depends on the absorber material and the thickness of the solar cell. The optimum morphology of the textured substrate can be defined regarding the wavelength range intended for scattering. Good scattering is experimentally achieved by optimizing the fabrication process of the randomly textured substrate. However, optimum morphological parameters have not been analytically formulated. In this work we develop the morphological criteria for optimum light scattering in a-Si:H solar cells using Aluminum Induced Texture (AIT) glass superstrates. Transmission haze is widely used as an evaluating factor for scattering properties. Haze can be easily measured for the substrate/air interface. However, the relevant scattering properties are those in the absorber material. These properties cannot be measured directly, but can be predicted by an appropriate model. The simple model for haze calculation based on scalar scattering theory cannot correctly estimate the haze value because it only considers the root mean square (RMS) roughness of the textured surface, which does not contain information about lateral feature size. In addition, the opening angel of the haze measurement is not considered in the equation. In this work, we demonstrate that the power spectral density (PSD) function of the randomly textured surface can provide the missing information in the haze equation. A general formulation for calculating the lateral feature size based on the PSD function is presented. We use this calculated haze value based on PSD to find the optimum lateral feature size for scattering a specific wavelength into the desired material. The optimum lateral feature size for scattering 620-nm light, which is weakly absorbed in a-Si:H, is shown to be 100 nm.

  5. 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,…

  6. 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.

  7. 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

  8. Machine vision: an incremental learning system based on features derived using fast Gabor transforms for the identification of textural objects

    NASA Astrophysics Data System (ADS)

    Clark, Richard M.; Adjei, Osei; Johal, Harpal

    2001-11-01

    This paper proposes a fast, effective and also very adaptable incremental learning system for identifying textures based on features extracted from Gabor space. The Gabor transform is a useful technique for feature extraction since it exhibits properties that are similar to biologically visual sensory systems such as those found in the mammalian visual cortex. Although two-dimensional Gabor filters have been applied successfully to a variety of tasks such as text segmentation, object detection and fingerprint analysis, the work of this paper extends previous work by incorporating incremental learning to facilitate easier training. The proposed system transforms textural images into Gabor space and a non-linear threshold function is then applied to extract feature vectors that bear signatures of the textural images. The mean and variance of each training group is computed followed by a technique that uses the Kohonen network to cluster these features. The centers of these clusters form the basis of an incremental learning paradigm that allows new information to be integrated into the existing knowledge. A number of experiments are conducted for real-time identification or discrimination of textural images.

  9. 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.

  10. 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.

  11. 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

  12. 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

  13. 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.

  14. Geometry and Texture Measures for Interactive Virtualized Reality Indoor Modeler

    NASA Astrophysics Data System (ADS)

    Thangamania, K.; Ichikari, R.; Okuma, T.; Ishikawa, T.; Kurata, T.

    2015-05-01

    This paper discusses the algorithm to detect the distorted textures in the virtualized reality indoor models and automatically generate the necessary 3D planes to hold the undistorted textures. Virtualized reality (VR) interactive indoor modeler, our previous contribution enables the user to interactively create their desired indoor VR model from a single 2D image. The interactive modeler uses the projective texture mapping for mapping the textures over the manually created 3D planes. If the user has not created the necessary 3D planes, then the texture that belong to various objects are projected to the available 3D planes, which leads to the presence of distorted textures. In this paper, those distorted textures are detected automatically by the suitable principles from the shape from texture research. The texture distortion features such as the slant, tilt and the curvature parameters are calculated from the 2D image by means of affine transformation measured between the neighboring texture patches within the single image. This kind of affine transform calculation from a single image is useful in the case of deficient multiple view images. The usage of superpixels in clustering the textures corresponding to different objects, reduces the modeling labor cost. A standby database also stores the repeated basic textures that are found in the indoor model, and provides texture choices for the distorted floor, wall and other regions. Finally, this paper documents the prototype implementation and experiments with the automatic 3D plane creation and distortion detection with the above mentioned principles in the virtualized reality indoor environment.

  15. 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.

  16. 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

  17. Self-assembled 3D heterometallic Cu(II)/Fe(II) coordination polymers with octahedral net skeletons: structural features, molecular magnetism, thermal and oxidation catalytic properties.

    PubMed

    Karabach, Yauhen Y; Guedes da Silva, M Fátima C; Kopylovich, Maximilian N; Gil-Hernández, Beatriz; Sanchiz, Joaquin; Kirillov, Alexander M; Pombeiro, Armando J L

    2010-12-01

    The new three-dimensional (3D) heterometallic Cu(II)/Fe(II) coordination polymers [Cu(6)(H(2)tea)(6)Fe(CN)(6)](n)(NO(3))(2n)·6nH(2)O (1) and [Cu(6)(Hmdea)(6)Fe(CN)(6)](n)(NO(3))(2n)·7nH(2)O (2) have been easily generated by aqueous-medium self-assembly reactions of copper(II) nitrate with triethanolamine or N-methyldiethanolamine (H(3)tea or H(2)mdea, respectively), in the presence of potassium ferricyanide and sodium hydroxide. They have been isolated as air-stable crystalline solids and fully characterized including by single-crystal X-ray diffraction analyses. The latter reveal the formation of 3D metal-organic frameworks that are constructed from the [Cu(2)(μ-H(2)tea)(2)](2+) or [Cu(2)(μ-Hmdea)(2)](2+) nodes and the octahedral [Fe(CN)(6)](4-) linkers, featuring regular (1) or distorted (2) octahedral net skeletons. Upon dehydration, both compounds show reversible escape and binding processes toward water or methanol molecules. Magnetic susceptibility measurements of 1 and 2 reveal strong antiferromagnetic [J = -199(1) cm(-1)] or strong ferromagnetic [J = +153(1) cm(-1)] couplings between the copper(II) ions through the μ-O-alkoxo atoms in 1 or 2, respectively. The differences in magnetic behavior are explained in terms of the dependence of the magnetic coupling constant on the Cu-O-Cu bridging angle. Compounds 1 and 2 also act as efficient catalyst precursors for the mild oxidation of cyclohexane by aqueous hydrogen peroxide to cyclohexanol and cyclohexanone (homogeneous catalytic system), leading to maximum total yields (based on cyclohexane) and turnover numbers (TONs) up to about 22% and 470, respectively. PMID:21028781

  18. 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.

  19. 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.

  20. 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

  1. 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

  2. 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

  3. 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.

  4. Separable and non-separable discrete wavelet transform based texture features and image classification of breast thermograms

    NASA Astrophysics Data System (ADS)

    Etehadtavakol, Mahnaz; Ng, E. Y. K.; Chandran, Vinod; Rabbani, Hossien

    2013-11-01

    Highly sensitive infrared cameras can produce high-resolution diagnostic images of the temperature and vascular changes of breasts. Wavelet transform based features are suitable in extracting the texture difference information of these images due to their scale-space decomposition. The objective of this study is to investigate the potential of extracted features in differentiating between breast lesions by comparing the two corresponding pectoral regions of two breast thermograms. The pectoral regions of breastsare important because near 50% of all breast cancer is located in this region. In this study, the pectoral region of the left breast is selected. Then the corresponding pectoral region of the right breast is identified. Texture features based on the first and the second sets of statistics are extracted from wavelet decomposed images of the pectoral regions of two breast thermograms. Principal component analysis is used to reduce dimension and an Adaboost classifier to evaluate classification performance. A number of different wavelet features are compared and it is shown that complex non-separable 2D discrete wavelet transform features perform better than their real separable counterparts.

  5. 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

  6. 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

  7. 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.

  8. Classification of Weed Species Using Artificial Neural Networks Based on Color Leaf Texture Feature

    NASA Astrophysics Data System (ADS)

    Li, Zhichen; An, Qiu; Ji, Changying

    The potential impact of herbicide utilization compel people to use new method of weed control. Selective herbicide application is optimal method to reduce herbicide usage while maintain weed control. The key of selective herbicide is how to discriminate weed exactly. The HIS color co-occurrence method (CCM) texture analysis techniques was used to extract four texture parameters: Angular second moment (ASM), Entropy(E), Inertia quadrature (IQ), and Inverse difference moment or local homogeneity (IDM).The weed species selected for studying were Arthraxon hispidus, Digitaria sanguinalis, Petunia, Cyperus, Alternanthera Philoxeroides and Corchoropsis psilocarpa. The software of neuroshell2 was used for designing the structure of the neural network, training and test the data. It was found that the 8-40-1 artificial neural network provided the best classification performance and was capable of classification accuracies of 78%.

  9. 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

  10. Classification of convective and stratiform rain based on the spectral and textural features of Meteosat Second Generation infrared data

    NASA Astrophysics Data System (ADS)

    Giannakos, Apostolos; Feidas, Haralambos

    2013-08-01

    This paper aimed to investigate the potential of using spectral and textural features in the Meteosat Second Generation—Spinning Enhanced Visible and Infrared Imager (MSG-SEVIRI) data for developing techniques capable of classifying convective and stratiform rain areas in the satellite image. Two different classification methods were introduced that use the brightness temperature (BT) T 10.8 and brightness temperature differences T 10.8- T 12.1, T 8.7- T 10.8, T 6.2- T 10.8, T 6.2- T 7.3, T 13.4- T 10.8, T 8.7- T 12.1, and T 9.7- T 13.4 as spectral parameters, along with textural parameters derived from the thermal infrared MSG-SEVIRI channel to discriminate between convective and stratiform rainy clouds. The first is an algorithm based on the probability of convective rainfall (PCR) for each pixel of the MSG satellite data and the second is an artificial neural network multilayer perceptron (MLP) model that relies on the correlation of satellite data with convective and stratiform rain. Both schemes were trained using as reference convective/stratiform classification data from 88 stations in Greece for 20 rainy days with high convective activity and evaluated against an independent dataset of gauge data for six rainy days. Two PCR and two MLP algorithms were constructed based on the previous results: the PCR1 and MLP1 algorithms that use only spectral measures and the PCR2 and MLP2 algorithms based on both spectral and textural measures. It was found that the introduction of textural parameters as additional information to a technique (PCR2 and MLP2 ) works in improving the delineation between convective and stratiform rainy pixels compared to the techniques based only on spectral information (PCR1 and MLP1). The comparison of the two schemes revealed a clear outperformance of the MLP techniques over the PCR techniques. Best skill is provided by MLP2 (POD = 74.5 %, FAR = 44.3 %, POFD = 22.5 %, CSI = 0.47, ETS = 0.31, bias = 1.34) followed by MLP1 and the two PCR

  11. 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

  12. 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.

  13. 3D ultrasound image segmentation using wavelet support vector machines

    PubMed Central

    Akbari, Hamed; Fei, Baowei

    2012-01-01

    Purpose: Transrectal ultrasound (TRUS) imaging is clinically used in prostate biopsy and therapy. Segmentation of the prostate on TRUS images has many applications. In this study, a three-dimensional (3D) segmentation method for TRUS images of the prostate is presented for 3D ultrasound-guided biopsy. Methods: This segmentation method utilizes a statistical shape, texture information, and intensity profiles. A set of wavelet support vector machines (W-SVMs) is applied to the images at various subregions of the prostate. The W-SVMs are trained to adaptively capture the features of the ultrasound images in order to differentiate the prostate and nonprostate tissue. This method consists of a set of wavelet transforms for extraction of prostate texture features and a kernel-based support vector machine to classify the textures. The voxels around the surface of the prostate are labeled in sagittal, coronal, and transverse planes. The weight functions are defined for each labeled voxel on each plane and on the model at each region. In the 3D segmentation procedure, the intensity profiles around the boundary between the tentatively labeled prostate and nonprostate tissue are compared to the prostate model. Consequently, the surfaces are modified based on the model intensity profiles. The segmented prostate is updated and compared to the shape model. These two steps are repeated until they converge. Manual segmentation of the prostate serves as the gold standard and a variety of methods are used to evaluate the performance of the segmentation method. Results: The results from 40 TRUS image volumes of 20 patients show that the Dice overlap ratio is 90.3% ± 2.3% and that the sensitivity is 87.7% ± 4.9%. Conclusions: The proposed method provides a useful tool in our 3D ultrasound image-guided prostate biopsy and can also be applied to other applications in the prostate. PMID:22755682

  14. 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

  15. 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.

  16. 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

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

    PubMed

    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

  18. 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.

  19. Supernova Spectrum Synthesis for 3D Composition Models with the Monte Carlo Method

    NASA Astrophysics Data System (ADS)

    Thomas, Rollin

    2002-07-01

    newcommandBruteextttBrute Relying on spherical symmetry when modelling supernova spectra is clearly at best a good approximation. Recent polarization measurements, interesting features in flux spectra, and the clumpy textures of supernova remnants suggest that supernova envelopes are rife with fine structure. To account for this fine structure and create a complete picture of supernovae, new 3D explosion models will be forthcoming. To reconcile these models with observed spectra, 3D radiative transfer will be necessary. We propose a 3D Monte Carlo radiative transfer code, Brute, and improvements that will move it toward a fully self-consistent 3D transfer code. Spectroscopic HST observations of supernovae past, present and future will definitely benefit. Other 3D transfer problems of interest to HST users like AGNs will benefit from the techniques developed.

  20. 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

  1. 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

  2. New insights into alkylammonium-functionalized clinoptilolite and Na-P1 zeolite: Structural and textural features

    NASA Astrophysics Data System (ADS)

    Muir, Barbara; Matusik, Jakub; Bajda, Tomasz

    2016-01-01

    The area of zeolites' application could be expanded by utilizing their surfaces. Zeolites are frequently modified to increase their hydrophobicity and to generate the negative charge of the surface. The main objective of the study was to investigate and compare the features of natural clinoptilolite and synthetic zeolite Na-P1 modified by selected surfactants involving quaternary ammonium salts. The FTIR study indicates that with increasing carbon chain length in the surfactant attached to the zeolites surface the molecules adopt a more disordered structure. FTIR was also used to determine the efficiency of surface modification. Thermal analysis revealed that the presence of surfactant results in additional exothermic effects associated with the breaking of electrostatic bonds between zeolites and surfactants. The mass losses are in line with ECEC and CHN data. The textural study indicates that the synthetic zeolite Na-P1 has better sorption properties than natural clinoptilolite. The modification process always reduces the SBET and porosity of the material. With an increasing carbon chain length of surfactants all the texture parameters decrease.

  3. Classification of focal liver lesions on ultrasound images by extracting hybrid textural features and using an artificial neural network.

    PubMed

    Hwang, Yoo Na; Lee, Ju Hwan; Kim, Ga Young; Jiang, Yuan Yuan; Kim, Sung Min

    2015-01-01

    This paper focuses on the improvement of the diagnostic accuracy of focal liver lesions by quantifying the key features of cysts, hemangiomas, and malignant lesions on ultrasound images. The focal liver lesions were divided into 29 cysts, 37 hemangiomas, and 33 malignancies. A total of 42 hybrid textural features that composed of 5 first order statistics, 18 gray level co-occurrence matrices, 18 Law's, and echogenicity were extracted. A total of 29 key features that were selected by principal component analysis were used as a set of inputs for a feed-forward neural network. For each lesion, the performance of the diagnosis was evaluated by using the positive predictive value, negative predictive value, sensitivity, specificity, and accuracy. The results of the experiment indicate that the proposed method exhibits great performance, a high diagnosis accuracy of over 96% among all focal liver lesion groups (cyst vs. hemangioma, cyst vs. malignant, and hemangioma vs. malignant) on ultrasound images. The accuracy was slightly increased when echogenicity was included in the optimal feature set. These results indicate that it is possible for the proposed method to be applied clinically. PMID:26405925

  4. Using combination of color, texture, and shape features for image retrieval in melanomas databases

    NASA Astrophysics Data System (ADS)

    Larabi, Mohamed-Chaker; Richard, Noel; Fernandez-Maloigne, Christine

    2001-12-01

    This paper deals with Computer Aided Diagnosis for skin cancers (melanomas). The diagnosis is based on some rules called the ABCD mnemonics. They take into account color distribution, lesion's diameter, etc. The goal isn't to classify the lesion but to find those, which are the most similar, in order to help the expert to confirm his diagnosis and to avoid any useless excision. This is done thanks to an indexation system, which compare the signatures of previously diagnosed lesions contained in a database and patient's lesion signature. This last is constructed by translating the rules into image processing attributes. We have divided then into three families: Color attributes (color and fuzzy histograms), Texture attributes (co-occurrence matrix and Haralick indices) and Shape attributes (lesion surface and maximum included circle). Image quantization permits us to keep only the most significant colors, thus giving a light structure. Finally, we define a distance for each attribute and use weighted combination for the similarity measure.

  5. 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.

  6. 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.

  7. 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

  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. 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

  10. 3D face reconstruction from limited images based on differential evolution

    NASA Astrophysics Data System (ADS)

    Wang, Qun; Li, Jiang; Asari, Vijayan K.; Karim, Mohammad A.

    2011-09-01

    3D face modeling has been one of the greatest challenges for researchers in computer graphics for many years. Various methods have been used to model the shape and texture of faces under varying illumination and pose conditions from a single given image. In this paper, we propose a novel method for the 3D face synthesis and reconstruction by using a simple and efficient global optimizer. A 3D-2D matching algorithm which employs the integration of the 3D morphable model (3DMM) and the differential evolution (DE) algorithm is addressed. In 3DMM, the estimation process of fitting shape and texture information into 2D images is considered as the problem of searching for the global minimum in a high dimensional feature space, in which optimization is apt to have local convergence. Unlike the traditional scheme used in 3DMM, DE appears to be robust against stagnation in local minima and sensitiveness to initial values in face reconstruction. Benefitting from DE's successful performance, 3D face models can be created based on a single 2D image with respect to various illuminating and pose contexts. Preliminary results demonstrate that we are able to automatically create a virtual 3D face from a single 2D image with high performance. The validation process shows that there is only an insignificant difference between the input image and the 2D face image projected by the 3D model.

  11. 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.

  12. 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

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

    PubMed

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

    2015-07-21

    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

  14. 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. PMID:20374810

  15. 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

  16. 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.

  17. MaZda--a software package for image texture analysis.

    PubMed

    Szczypiński, Piotr M; Strzelecki, Michał; Materka, Andrzej; Klepaczko, Artur

    2009-04-01

    MaZda, a software package for 2D and 3D image texture analysis is presented. It provides a complete path for quantitative analysis of image textures, including computation of texture features, procedures for feature selection and extraction, algorithms for data classification, various data visualization and image segmentation tools. Initially, MaZda was aimed at analysis of magnetic resonance image textures. However, it revealed its effectiveness in analysis of other types of textured images, including X-ray and camera images. The software was utilized by numerous researchers in diverse applications. It was proven to be an efficient and reliable tool for quantitative image analysis, even in more accurate and objective medical diagnosis. MaZda was also successfully used in food industry to assess food product quality. MaZda can be downloaded for public use from the Institute of Electronics, Technical University of Lodz webpage. PMID:18922598

  18. Simulation of 3D infrared scenes using random fields model

    NASA Astrophysics Data System (ADS)

    Shao, Xiaopeng; Zhang, Jianqi

    2001-09-01

    Analysis and simulation of smart munitions requires imagery for the munition's sensor to view. The traditional infrared background simulations are always limited in the plane scene studies. A new method is described to synthesize the images in 3D view and with various terrains texture. We develop the random fields model and temperature fields to simulate 3D infrared scenes. Generalized long-correlation (GLC) model, one of random field models, will generate both the 3D terrains skeleton data and the terrains texture in this work. To build the terrain mesh with the random fields, digital elevation models (DEM) are introduced in the paper. And texture mapping technology will perform the task of pasting the texture in the concavo-convex surfaces of the 3D scene. The simulation using random fields model is a very available method to produce 3D infrared scene with great randomicity and reality.

  19. 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

  20. 3D features of delayed thermal convection in fault zones: consequences for deep fluid processes in the Tiberias Basin, Jordan Rift Valley

    NASA Astrophysics Data System (ADS)

    Magri, Fabien; Möller, Sebastian; Inbar, Nimrod; Siebert, Christian; Möller, Peter; Rosenthal, Eliyahu; Kühn, Michael

    2015-04-01

    It has been shown that thermal convection in faults can also occur for subcritical Rayleigh conditions. This type of convection develops after a certain period and is referred to as "delayed convection" (Murphy, 1979). The delay in the onset is due to the heat exchange between the damage zone and the surrounding units that adds a thermal buffer along the fault walls. Few numerical studies investigated delayed thermal convection in fractured zones, despite it has the potential to transport energy and minerals over large spatial scales (Tournier, 2000). Here 3D numerical simulations of thermally driven flow in faults are presented in order to investigate the impact of delayed convection on deep fluid processes at basin-scale. The Tiberias Basin (TB), in the Jordan Rift Valley, serves as study area. The TB is characterized by upsurge of deep-seated hot waters along the faulted shores of Lake Tiberias and high temperature gradient that can locally reach 46 °C/km, as in the Lower Yarmouk Gorge (LYG). 3D simulations show that buoyant flow ascend in permeable faults which hydraulic conductivity is estimated to vary between 30 m/yr and 140 m/yr. Delayed convection starts respectively at 46 and 200 kyrs and generate temperature anomalies in agreement with observations. It turned out that delayed convective cells are transient. Cellular patterns that initially develop in permeable units surrounding the faults can trigger convection also within the fault plane. The combination of these two convective modes lead to helicoidal-like flow patterns. This complex flow can explain the location of springs along different fault traces of the TB. Besides being of importance for understanding the hydrogeological processes of the TB (Magri et al., 2015), the presented simulations provide a scenario illustrating fault-induced 3D cells that could develop in any geothermal system. References Magri, F., Inbar, N., Siebert, C., Rosenthal, E., Guttman, J., Möller, P., 2015. Transient

  1. 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

  2. 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.

  3. 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

  4. 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?

  5. Methods for comparing 3D surface attributes

    NASA Astrophysics Data System (ADS)

    Pang, Alex; Freeman, Adam

    1996-03-01

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

  6. 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.

  7. 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

  8. 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

  9. Computer-aided diagnosis of psoriasis skin images with HOS, texture and color features: A first comparative study of its kind.

    PubMed

    Shrivastava, Vimal K; Londhe, Narendra D; Sonawane, Rajendra S; Suri, Jasjit S

    2016-04-01

    Psoriasis is an autoimmune skin disease with red and scaly plaques on skin and affecting about 125 million people worldwide. Currently, dermatologist use visual and haptic methods for diagnosis the disease severity. This does not help them in stratification and risk assessment of the lesion stage and grade. Further, current methods add complexity during monitoring and follow-up phase. The current diagnostic tools lead to subjectivity in decision making and are unreliable and laborious. This paper presents a first comparative performance study of its kind using principal component analysis (PCA) based CADx system for psoriasis risk stratification and image classification utilizing: (i) 11 higher order spectra (HOS) features, (ii) 60 texture features, and (iii) 86 color feature sets and their seven combinations. Aggregate 540 image samples (270 healthy and 270 diseased) from 30 psoriasis patients of Indian ethnic origin are used in our database. Machine learning using PCA is used for dominant feature selection which is then fed to support vector machine classifier (SVM) to obtain optimized performance. Three different protocols are implemented using three kinds of feature sets. Reliability index of the CADx is computed. Among all feature combinations, the CADx system shows optimal performance of 100% accuracy, 100% sensitivity and specificity, when all three sets of feature are combined. Further, our experimental result with increasing data size shows that all feature combinations yield high reliability index throughout the PCA-cutoffs except color feature set and combination of color and texture feature sets. HOS features are powerful in psoriasis disease classification and stratification. Even though, independently, all three set of features HOS, texture, and color perform competitively, but when combined, the machine learning system performs the best. The system is fully automated, reliable and accurate. PMID:26830378

  10. 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

  11. 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

  12. 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

  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. 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.

  15. Remote sensing based improvement of the geological map of the Neoproterozoic Ras Gharib segment in the Eastern Desert (NE-Egypt) using texture features

    NASA Astrophysics Data System (ADS)

    Jakob, Sandra; Bühler, Benjamin; Gloaguen, Richard; Breitkreuz, Christoph; Eliwa, Hassan Ali; El Gameel, Khaled

    2015-11-01

    Geological mapping in the Eastern Desert is impeded by difficult accessibility. We improve the existing geological maps by including texture features in a classification scheme of ASTER and Landsat 8 data. We tested the improvement of support vector machine classification using band ratios, principal component analysis (PCA) and texture analysis in the Ras Gharib segment (NE Egypt). A very high classification overall accuracy of 99.85% was achieved. We demonstrate that the input of textures provide valuable additional data for lithological mapping. With the gained information, the existing geological map of the study area was improved distinctly in precision and resolution, but also in terms of correction of yet wrong or inaccurate locations and of lithological unit extents.

  16. Texture-based segmentation with Gabor filters, wavelet and pyramid decompositions for extracting individual surface features from areal surface topography maps

    NASA Astrophysics Data System (ADS)

    Senin, Nicola; Leach, Richard K.; Pini, Stefano; Blunt, Liam A.

    2015-09-01

    Areal topography segmentation plays a fundamental role in those surface metrology applications concerned with the characterisation of individual topography features. Typical scenarios include the dimensional inspection and verification of micro-structured surface features, and the identification and characterisation of localised defects and other random singularities. While morphological segmentation into hills or dales is the only partitioning operation currently endorsed by the ISO specification standards on surface texture metrology, many other approaches are possible, in particular adapted from the literature on digital image segmentation. In this work an original segmentation approach is introduced and discussed, where topography partitioning is driven by information collected through the application of texture characterisation transforms popular in digital image processing. Gabor filters, wavelets and pyramid decompositions are investigated and applied to a selected set of test cases. The behaviour, performance and limitations of the proposed approach are discussed from the viewpoint of the identification and extraction of individual surface topography features.

  17. 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.

  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. 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.

  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. TRACE 3-D documentation

    SciTech Connect

    Crandall, K.R.

    1987-08-01

    TRACE 3-D is an interactive beam-dynamics program that calculates the envelopes of a bunched beam, including linear space-charge forces, through a user-defined transport system. TRACE 3-D provides an immediate graphics display of the envelopes and the phase-space ellipses and allows nine types of beam-matching options. This report describes the beam-dynamics calculations and gives detailed instruction for using the code. Several examples are described in detail.

  2. 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.

  3. 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%.

  4. 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

  5. Enantioselective synthesis and olfactory evaluation of bicyclic alpha- and gamma-ionone derivatives: the 3D arrangement of key molecular features relevant to the violet odor of ionones.

    PubMed

    Luparia, Marco; Legnani, Laura; Porta, Alessio; Zanoni, Giuseppe; Toma, Lucio; Vidari, Giovanni

    2009-09-18

    Violet smelling ionones 1-3, occurring in the headspace of different flowers, are well-known perfumery raw materials. With the goal to recognize the still ill-defined spatial arrangement of structural features relevant to the binding of ionones to olfactory G-protein coupled receptors, through B3LYP/6-31G(d) modeling studies we identified bicyclic compounds 7-9 as conformationally constrained 13-alkyl-substituted analogues of monocyclic alpha- and gamma-ionones. They were thus synthesized to evaluate the olfactory properties. The enantioselective syntheses of 7-9 entailed two common key steps: (i) a Diels-Alder reaction to construct the octalinic core and (ii) a Julia-Lythgoe olefination to install the alpha,beta-enone side chain. The odor thresholds of synthetic 7 and 9 were significantly lower than the corresponding parent ionones, and 9 showed the lowest threshold value among violet-smelling odorants examined so far. Modeling studies suggested a nearly identical spatial orientation of key hydrophobic and polar moieties of compounds 1, 3, and 4-9. Presumably, interaction of these moieties with ionone olfactory receptors (ORs) triggers a similar receptor code that is ultimately interpreted by the human brain as a pleasant woody-violet smell. These results open the way to studies aimed at identifying and modeling complementary binding sites on alpha-helical domains of ionone receptor proteins. PMID:19743882

  6. 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.

  7. 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.

  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. 3D segmentation of prostate ultrasound images using wavelet transform

    NASA Astrophysics Data System (ADS)

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

    2011-03-01

    The current definitive diagnosis of prostate cancer is transrectal ultrasound (TRUS) guided biopsy. However, the current procedure is limited by using 2D biopsy tools to target 3D biopsy locations. This paper presents a new method for automatic segmentation of the prostate in three-dimensional transrectal ultrasound images, by extracting texture features and by statistically matching geometrical shape of the prostate. A set of Wavelet-based support vector machines (WSVMs) are located and trained at different regions of the prostate surface. The WSVMs capture texture priors of ultrasound images for classification of the prostate and non-prostate tissues in different zones around the prostate boundary. In the segmentation procedure, these W-SVMs are trained in three sagittal, coronal, and transverse planes. The pre-trained W-SVMs are employed to tentatively label each voxel around the surface of the model as a prostate or non-prostate voxel by the texture matching. The labeled voxels in three planes after post-processing is overlaid on a prostate probability model. The probability prostate model is created using 10 segmented prostate data. Consequently, each voxel has four labels: sagittal, coronal, and transverse planes and one probability label. By defining a weight function for each labeling in each region, each voxel is labeled as a prostate or non-prostate voxel. Experimental results by using real patient data show the good performance of the proposed model in segmenting the prostate from ultrasound images.

  10. 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.

  11. 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.

  12. 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

  13. Large bulk-yard 3D measurement based on videogrammetry and projected contour aiding

    NASA Astrophysics Data System (ADS)

    Ou, Jianliang; Zhang, Xiaohu; Yuan, Yun; Zhu, Xianwei

    2011-07-01

    Fast and accurate 3D measurement of large stack-yard is important job in bulk load-and-unload and logistics management. Stack-yard holds its special characteristics as: complex and irregular shape, single surface texture and low material reflectivity, thus its 3D measurement is quite difficult to be realized by traditional non-contacting methods, such as LiDAR(LIght Detecting And Ranging) and photogrammetry. Light-section is good at the measurement of small bulk-flow but not suitable for large-scale bulk-yard yet. In the paper, an improved method based on stereo cameras and laser-line projector is proposed. The due theoretical model is composed from such three key points: corresponding point of contour edge matching in stereo imagery based on gradient and epipolar-line constraint, 3D point-set calculating for stereo imagery projected-contour edge with least square adjustment and forward intersection, then the projected 3D-contour reconstructed by RANSAC(RANdom SAmpling Consensus) and contour spatial features from 3D point-set of single contour edge. In this way, stack-yard surface can be scanned easily by the laser-line projector, and certain region's 3D shape can be reconstructed automatically by stereo cameras on an observing position. Experiment proved the proposed method is effective for bulk-yard 3D measurement in fast, automatic, reliable and accurate way.

  14. Output-sensitive 3D line integral convolution.

    PubMed

    Falk, Martin; Weiskopf, Daniel

    2008-01-01

    We propose an output-sensitive visualization method for 3D line integral convolution (LIC) whose rendering speed is largely independent of the data set size and mostly governed by the complexity of the output on the image plane. Our approach of view-dependent visualization tightly links the LIC generation with the volume rendering of the LIC result in order to avoid the computation of unnecessary LIC points: early-ray termination and empty-space leaping techniques are used to skip the computation of the LIC integral in a lazy-evaluation approach; both ray casting and texture slicing can be used as volume-rendering techniques. The input noise is modeled in object space to allow for temporal coherence under object and camera motion. Different noise models are discussed, covering dense representations based on filtered white noise all the way to sparse representations similar to oriented LIC. Aliasing artifacts are avoided by frequency control over the 3D noise and by employing a 3D variant of MIPmapping. A range of illumination models is applied to the LIC streamlines: different codimension-2 lighting models and a novel gradient-based illumination model that relies on precomputed gradients and does not require any direct calculation of gradients after the LIC integral is evaluated. We discuss the issue of proper sampling of the LIC and volume-rendering integrals by employing a frequency-space analysis of the noise model and the precomputed gradients. Finally, we demonstrate that our visualization approach lends itself to a fast graphics processing unit (GPU) implementation that supports both steady and unsteady flow. Therefore, this 3D LIC method allows users to interactively explore 3D flow by means of high-quality, view-dependent, and adaptive LIC volume visualization. Applications to flow visualization in combination with feature extraction and focus-and-context visualization are described, a comparison to previous methods is provided, and a detailed performance

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

    PubMed Central

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

    2014-01-01

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

  16. 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.

  17. 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

  18. 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.

  19. An RBF-based reparameterization method for constrained texture mapping.

    PubMed

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

    2012-07-01

    Texture mapping has long been used in computer graphics to enhance the realism of virtual scenes. However, to match the 3D model feature points with the corresponding pixels in a texture image, surface parameterization must satisfy specific positional constraints. However, despite numerous research efforts, the construction of a mathematically robust, foldover-free parameterization that is subject to positional constraints continues to be a challenge. In the present paper, this foldover problem is addressed by developing radial basis function (RBF)-based reparameterization. Given initial 2D embedding of a 3D surface, the proposed method can reparameterize 2D embedding into a foldover-free 2D mesh, satisfying a set of user-specified constraint points. In addition, this approach is mesh free. Therefore, generating smooth texture mapping results is possible without extra smoothing optimization. PMID:21690643

  20. 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.

  1. Fusion of multisensor passive and active 3D imagery

    NASA Astrophysics Data System (ADS)

    Fay, David A.; Verly, Jacques G.; Braun, Michael I.; Frost, Carl E.; Racamato, Joseph P.; Waxman, Allen M.

    2001-08-01

    We have extended our previous capabilities for fusion of multiple passive imaging sensors to now include 3D imagery obtained from a prototype flash ladar. Real-time fusion of low-light visible + uncooled LWIR + 3D LADAR, and SWIR + LWIR + 3D LADAR is demonstrated. Fused visualization is achieved by opponent-color neural networks for passive image fusion, which is then textured upon segmented object surfaces derived from the 3D data. An interactive viewer, coded in Java3D, is used to examine the 3D fused scene in stereo. Interactive designation, learning, recognition and search for targets, based on fused passive + 3D signatures, is achieved using Fuzzy ARTMAP neural networks with a Java-coded GUI. A client-server web-based architecture enables remote users to interact with fused 3D imagery via a wireless palmtop computer.

  2. 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.

  3. 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

  4. 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

  5. Depth image enhancement using perceptual texture priors

    NASA Astrophysics Data System (ADS)

    Bang, Duhyeon; Shim, Hyunjung

    2015-03-01

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

  6. 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

  7. 3D microscope

    NASA Astrophysics Data System (ADS)

    Iizuka, Keigo

    2008-02-01

    In order to circumvent the fact that only one observer can view the image from a stereoscopic microscope, an attachment was devised for displaying the 3D microscopic image on a large LCD monitor for viewing by multiple observers in real time. The principle of operation, design, fabrication, and performance are presented, along with tolerance measurements relating to the properties of the cellophane half-wave plate used in the design.

  8. Lung Texture in Serial Thoracic Computed Tomography Scans: Correlation of Radiomics-based Features With Radiation Therapy Dose and Radiation Pneumonitis Development

    PubMed Central

    Cunliffe, Alexandra; Armato, Samuel G.; Castillo, Richard; Pham, Ngoc; Guerrero, Thomas; Al-Hallaq, Hania A.

    2015-01-01

    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

  9. 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.

  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. Angular description for 3D scattering centers

    NASA Astrophysics Data System (ADS)

    Bhalla, Rajan; Raynal, Ann Marie; Ling, Hao; Moore, John; Velten, Vincent J.

    2006-05-01

    The electromagnetic scattered field from an electrically large target can often be well modeled as if it is emanating from a discrete set of scattering centers (see Fig. 1). In the scattering center extraction tool we developed previously based on the shooting and bouncing ray technique, no correspondence is maintained amongst the 3D scattering center extracted at adjacent angles. In this paper we present a multi-dimensional clustering algorithm to track the angular and spatial behaviors of 3D scattering centers and group them into features. The extracted features for the Slicy and backhoe targets are presented. We also describe two metrics for measuring the angular persistence and spatial mobility of the 3D scattering centers that make up these features in order to gather insights into target physics and feature stability. We find that features that are most persistent are also the most mobile and discuss implications for optimal SAR imaging.

  12. Reconstruction of 3D scenes from sequences of images

    NASA Astrophysics Data System (ADS)

    Niu, Bei; Sang, Xinzhu; Chen, Duo; Cai, Yuanfa

    2013-08-01

    Reconstruction of three-dimensional (3D) scenes is an active research topic in the field of computer vision and 3D display. It's a challenge to model 3D objects rapidly and effectively. A 3D model can be extracted from multiple images. The system only requires a sequence of images taken with cameras without knowing the parameters of camera, which provide flexibility to a high degree. We focus on quickly merging point cloud of the object from depth map sequences. The whole system combines algorithms of different areas in computer vision, such as camera calibration, stereo correspondence, point cloud splicing and surface reconstruction. The procedure of 3D reconstruction is decomposed into a number of successive steps. Firstly, image sequences are received by the camera freely moving around the object. Secondly, the scene depth is obtained by a non-local stereo matching algorithm. The pairwise is realized with the Scale Invariant Feature Transform (SIFT) algorithm. An initial matching is then made for the first two images of the sequence. For the subsequent image that is processed with previous image, the point of interest corresponding to ones in previous images are refined or corrected. The vertical parallax between the images is eliminated. The next step is to calibrate camera, and intrinsic parameters and external parameters of the camera are calculated. Therefore, The relative position and orientation of camera are gotten. A sequence of depth maps are acquired by using a non-local cost aggregation method for stereo matching. Then point cloud sequence is achieved by the scene depths, which consists of point cloud model using the external parameters of camera and the point cloud sequence. The point cloud model is then approximated by a triangular wire-frame mesh to reduce geometric complexity and to tailor the model to the requirements of computer graphics visualization systems. Finally, the texture is mapped onto the wire-frame model, which can also be used for 3

  13. Textural segmentation, second-order statistics, and textural elements.

    PubMed

    Beck, J

    1983-01-01

    Beck (1972, 1973) hypothesized that textural segmentation occurs strongly on the basis of simple properties such as brightness, color, size, and the slopes of contours and lines of the elemental descriptors of a texture or textural elements. The experiment reported supports the hypothesis that specific stimulus features, rather than second-order statistics, account for textural segmentation. The results agree with Julesz (1981a,b) who has reported evidence disproving his original conjecture of the importance of second-order statistics. Julesz (1981a,b) now hypothesizes textural segmentation to be a function of local features which he called textons. Textons are features that give textural segmentation when textures have identical second-order statistics. The two hypotheses are to date in complete agreement on the stimulus features producing textural segmentation, and the experiment reported is consistent with both. PMID:6626590

  14. 3D city models completion by fusing lidar and image data

    NASA Astrophysics Data System (ADS)

    Grammatikopoulos, L.; Kalisperakis, I.; Petsa, E.; Stentoumis, C.

    2015-05-01

    A fundamental step in the generation of visually detailed 3D city models is the acquisition of high fidelity 3D data. Typical approaches employ DSM representations usually derived from Lidar (Light Detection and Ranging) airborne scanning or image based procedures. In this contribution, we focus on the fusion of data from both these methods in order to enhance or complete them. Particularly, we combine an existing Lidar and orthomosaic dataset (used as reference), with a new aerial image acquisition (including both vertical and oblique imagery) of higher resolution, which was carried out in the area of Kallithea, in Athens, Greece. In a preliminary step, a digital orthophoto and a DSM is generated from the aerial images in an arbitrary reference system, by employing a Structure from Motion and dense stereo matching framework. The image-to-Lidar registration is performed by 2D feature (SIFT and SURF) extraction and matching among the two orthophotos. The established point correspondences are assigned with 3D coordinates through interpolation on the reference Lidar surface, are then backprojected onto the aerial images, and finally matched with 2D image features located in the vicinity of the backprojected 3D points. Consequently, these points serve as Ground Control Points with appropriate weights for final orientation and calibration of the images through a bundle adjustment solution. By these means, the aerial imagery which is optimally aligned to the reference dataset can be used for the generation of an enhanced and more accurately textured 3D city model.

  15. Fast Mode Decision for 3D-HEVC Depth Intracoding

    PubMed Central

    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

  16. 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

  17. Multiviewer 3D monitor

    NASA Astrophysics Data System (ADS)

    Kostrzewski, Andrew A.; Aye, Tin M.; Kim, Dai Hyun; Esterkin, Vladimir; Savant, Gajendra D.

    1998-09-01

    Physical Optics Corporation has developed an advanced 3-D virtual reality system for use with simulation tools for training technical and military personnel. This system avoids such drawbacks of other virtual reality (VR) systems as eye fatigue, headaches, and alignment for each viewer, all of which are due to the need to wear special VR goggles. The new system is based on direct viewing of an interactive environment. This innovative holographic multiplexed screen technology makes it unnecessary for the viewer to wear special goggles.

  18. 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.

  19. 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

  20. Using outcrop observations, 3D discrete feature network (DFN) fluid-flow simulations, and subsurface data to constrain the impact of normal faults and opening mode fractures on fluid flow in an active asphalt mine

    NASA Astrophysics Data System (ADS)

    Wilson, C. E.; Aydin, A.; Durlofsky, L.; Karimi-Fard, M.; Brownlow, D. T.

    2008-12-01

    An active quarry near Uvalde, TX which mines asphaltic limestone from the Anacacho Formation offers an ideal setting to study fluid-flow in fractured and faulted carbonate rocks. Semi-3D exposures of normal faults and fractures in addition to visual evidence of asphalt concentrations in the quarry help constrain relationships between geologic structures and the flow and transport of hydrocarbons. Furthermore, a subsurface dataset which includes thin sections and measured asphalt concentration from the surrounding region provides a basis to estimate asphalt concentrations and constrain the depositional architecture of both the previously mined portions of the quarry and the un-mined surrounding rock volume. We characterized a series of normal faults and opening mode fractures at the quarry and documented a correlation between the intensity and distribution of these structures with increased concentrations of asphalt. The three-dimensional depositional architecture of the Anacacho Formation was characterized using the subsurface thin sections. Then outcrop exposures of faults, fractured beds, and stratigraphic contacts were mapped and their three-dimensional positions were recorded with differential gps devices. These two datasets were assimilated and a quarry-scale, geologically realistic, three-dimensional Discrete Feature Network (DFN) which represents the geometries and material properties of the matrix, normal faults, and fractures within the quarry was constructed. We then performed two-point flux, control-volume finite- difference fluid-flow simulations with the DFN to investigate the 3D flow and transport of fluids. The results were compared and contrasted with available asphalt concentration estimates from the mine and the aforementioned data from the surrounding drill cores.

  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. 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. PMID:25620087

  3. RAG-3D: a search tool for RNA 3D substructures.

    PubMed

    Zahran, Mai; Sevim Bayrak, Cigdem; Elmetwaly, Shereef; Schlick, Tamar

    2015-10-30

    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

  4. 3D Surgical Simulation

    PubMed Central

    Cevidanes, Lucia; Tucker, Scott; Styner, Martin; Kim, Hyungmin; Chapuis, Jonas; Reyes, Mauricio; Proffit, William; Turvey, Timothy; Jaskolka, Michael

    2009-01-01

    This paper discusses the development of methods for computer-aided jaw surgery. Computer-aided jaw surgery allows us to incorporate the high level of precision necessary for transferring virtual plans into the operating room. We also present a complete computer-aided surgery (CAS) system developed in close collaboration with surgeons. Surgery planning and simulation include construction of 3D surface models from Cone-beam CT (CBCT), dynamic cephalometry, semi-automatic mirroring, interactive cutting of bone and bony segment repositioning. A virtual setup can be used to manufacture positioning splints for intra-operative guidance. The system provides further intra-operative assistance with the help of a computer display showing jaw positions and 3D positioning guides updated in real-time during the surgical procedure. The CAS system aids in dealing with complex cases with benefits for the patient, with surgical practice, and for orthodontic finishing. Advanced software tools for diagnosis and treatment planning allow preparation of detailed operative plans, osteotomy repositioning, bone reconstructions, surgical resident training and assessing the difficulties of the surgical procedures prior to the surgery. CAS has the potential to make the elaboration of the surgical plan a more flexible process, increase the level of detail and accuracy of the plan, yield higher operative precision and control, and enhance documentation of cases. Supported by NIDCR DE017727, and DE018962 PMID:20816308

  5. 3D-patterned polymer brush surfaces

    NASA Astrophysics Data System (ADS)

    Zhou, Xuechang; Liu, Xuqing; Xie, Zhuang; Zheng, Zijian

    2011-12-01

    Polymer brush-based three-dimensional (3D) structures are emerging as a powerful platform to engineer a surface by providing abundant spatially distributed chemical and physical properties. In this feature article, we aim to give a summary of the recent progress on the fabrication of 3D structures with polymer brushes, with a particular focus on the micro- and nanoscale. We start with a brief introduction on polymer brushes and the challenges to prepare their 3D structures. Then, we highlight the recent advances of the fabrication approaches on the basis of traditional polymerization time and grafting density strategies, and a recently developed feature density strategy. Finally, we provide some perspective outlooks on the future directions of engineering the 3D structures with polymer brushes.

  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. 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.

  8. 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.

  9. Scalable Multi-Platform Distribution of Spatial 3d Contents

    NASA Astrophysics Data System (ADS)

    Klimke, J.; Hagedorn, B.; Döllner, J.

    2013-09-01

    Virtual 3D city models provide powerful user interfaces for communication of 2D and 3D geoinformation. Providing high quality visualization of massive 3D geoinformation in a scalable, fast, and cost efficient manner is still a challenging task. Especially for mobile and web-based system environments, software and hardware configurations of target systems differ significantly. This makes it hard to provide fast, visually appealing renderings of 3D data throughout a variety of platforms and devices. Current mobile or web-based solutions for 3D visualization usually require raw 3D scene data such as triangle meshes together with textures delivered from server to client, what makes them strongly limited in terms of size and complexity of the models they can handle. In this paper, we introduce a new approach for provisioning of massive, virtual 3D city models on different platforms namely web browsers, smartphones or tablets, by means of an interactive map assembled from artificial oblique image tiles. The key concept is to synthesize such images of a virtual 3D city model by a 3D rendering service in a preprocessing step. This service encapsulates model handling and 3D rendering techniques for high quality visualization of massive 3D models. By generating image tiles using this service, the 3D rendering process is shifted from the client side, which provides major advantages: (a) The complexity of the 3D city model data is decoupled from data transfer complexity (b) the implementation of client applications is simplified significantly as 3D rendering is encapsulated on server side (c) 3D city models can be easily deployed for and used by a large number of concurrent users, leading to a high degree of scalability of the overall approach. All core 3D rendering techniques are performed on a dedicated 3D rendering server, and thin-client applications can be compactly implemented for various devices and platforms.

  10. 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.

  11. Laser point cloud diluting and refined 3D reconstruction fusing with digital images

    NASA Astrophysics Data System (ADS)

    Liu, Jie; Zhang, Jianqing

    2007-06-01

    This paper shows a method to combine the imaged-based modeling technique and Laser scanning data to rebuild a realistic 3D model. Firstly use the image pair to build a relative 3D model of the object, and then register the relative model to the Laser coordinate system. Project the Laser points to one of the images and extract the feature lines from that image. After that fit the 2D projected Laser points to lines in the image and constrain their corresponding 3D points to lines in the 3D Laser space to keep the features of the model. Build TIN and cancel the redundant points, which don't impact the curvature of their neighborhood areas. Use the diluting Laser point cloud to reconstruct the geometry model of the object, and then project the texture of corresponding image onto it. The process is shown to be feasible and progressive proved by experimental results. The final model is quite similar with the real object. This method cuts down the quantity of data in the precondition of keeping the features of model. The effect of it is manifest.

  12. 3D polarimetric purity

    NASA Astrophysics Data System (ADS)

    Gil, José J.; San José, Ignacio

    2010-11-01

    From our previous definition of the indices of polarimetric purity for 3D light beams [J.J. Gil, J.M. Correas, P.A. Melero and C. Ferreira, Monogr. Semin. Mat. G. de Galdeano 31, 161 (2004)], an analysis of their geometric and physical interpretation is presented. It is found that, in agreement with previous results, the first parameter is a measure of the degree of polarization, whereas the second parameter (called the degree of directionality) is a measure of the mean angular aperture of the direction of propagation of the corresponding light beam. This pair of invariant, non-dimensional, indices of polarimetric purity contains complete information about the polarimetric purity of a light beam. The overall degree of polarimetric purity is obtained as a weighted quadratic average of the degree of polarization and the degree of directionality.

  13. 3D field harmonics

    SciTech Connect

    Caspi, S.; Helm, M.; Laslett, L.J.

    1991-03-30

    We have developed an harmonic representation for the three dimensional field components within the windings of accelerator magnets. The form by which the field is presented is suitable for interfacing with other codes that make use of the 3D field components (particle tracking and stability). The field components can be calculated with high precision and reduced cup time at any location (r,{theta},z) inside the magnet bore. The same conductor geometry which is used to simulate line currents is also used in CAD with modifications more readily available. It is our hope that the format used here for magnetic fields can be used not only as a means of delivering fields but also as a way by which beam dynamics can suggest correction to the conductor geometry. 5 refs., 70 figs.

  14. 'Bonneville' in 3-D!

    NASA Technical Reports Server (NTRS)

    2004-01-01

    The Mars Exploration Rover Spirit took this 3-D navigation camera mosaic of the crater called 'Bonneville' after driving approximately 13 meters (42.7 feet) to get a better vantage point. Spirit's current position is close enough to the edge to see the interior of the crater, but high enough and far enough back to get a view of all of the walls. Because scientists and rover controllers are so pleased with this location, they will stay here for at least two more martian days, or sols, to take high resolution panoramic camera images of 'Bonneville' in its entirety. Just above the far crater rim, on the left side, is the rover's heatshield, which is visible as a tiny reflective speck.

  15. 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.

  16. RAG-3D: A search tool for RNA 3D substructures

    DOE PAGESBeta

    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

  17. 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.

  18. 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

  19. Illustrative visualization of 3D city models

    NASA Astrophysics Data System (ADS)

    Doellner, Juergen; Buchholz, Henrik; Nienhaus, Marc; Kirsch, Florian

    2005-03-01

    This paper presents an illustrative visualization technique that provides expressive representations of large-scale 3D city models, inspired by the tradition of artistic and cartographic visualizations typically found in bird"s-eye view and panoramic maps. We define a collection of city model components and a real-time multi-pass rendering algorithm that achieves comprehensible, abstract 3D city model depictions based on edge enhancement, color-based and shadow-based depth cues, and procedural facade texturing. Illustrative visualization provides an effective visual interface to urban spatial information and associated thematic information complementing visual interfaces based on the Virtual Reality paradigm, offering a huge potential for graphics design. Primary application areas include city and landscape planning, cartoon worlds in computer games, and tourist information systems.

  20. 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

  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. 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

  3. [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

  4. '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.

  5. 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.

  6. 3D steerable wavelets in practice.

    PubMed

    Chenouard, Nicolas; Unser, Michael

    2012-11-01

    We introduce a systematic and practical design for steerable wavelet frames in 3D. Our steerable wavelets are obtained by applying a 3D version of the generalized Riesz transform to a primary isotropic wavelet frame. The novel transform is self-reversible (tight frame) and its elementary constituents (Riesz wavelets) can be efficiently rotated in any 3D direction by forming appropriate linear combinations. Moreover, the basis functions at a given location can be linearly combined to design custom (and adaptive) steerable wavelets. The features of the proposed method are illustrated with the processing and analysis of 3D biomedical data. In particular, we show how those wavelets can be used to characterize directional patterns and to detect edges by means of a 3D monogenic analysis. We also propose a new inverse-problem formalism along with an optimization algorithm for reconstructing 3D images from a sparse set of wavelet-domain edges. The scheme results in high-quality image reconstructions which demonstrate the feature-reduction ability of the steerable wavelets as well as their potential for solving inverse problems. PMID:22752138

  7. 3D palmprint and hand imaging system based on full-field composite color sinusoidal fringe projection technique.

    PubMed

    Zhang, Zonghua; Huang, Shujun; Xu, Yongjia; Chen, Chao; Zhao, Yan; Gao, Nan; Xiao, Yanjun

    2013-09-01

    Palmprint and hand shape, as two kinds of important biometric characteristics, have been widely studied and applied to human identity recognition. The existing research is based mainly on 2D images, which lose the third-dimensional infor