WorldWideScience

Sample records for quakesim model image

  1. QuakeSim 2.0

    Science.gov (United States)

    Donnellan, Andrea; Parker, Jay W.; Lyzenga, Gregory A.; Granat, Robert A.; Norton, Charles D.; Rundle, John B.; Pierce, Marlon E.; Fox, Geoffrey C.; McLeod, Dennis; Ludwig, Lisa Grant

    2012-01-01

    QuakeSim 2.0 improves understanding of earthquake processes by providing modeling tools and integrating model applications and various heterogeneous data sources within a Web services environment. QuakeSim is a multisource, synergistic, data-intensive environment for modeling the behavior of earthquake faults individually, and as part of complex interacting systems. Remotely sensed geodetic data products may be explored, compared with faults and landscape features, mined by pattern analysis applications, and integrated with models and pattern analysis applications in a rich Web-based and visualization environment. Integration of heterogeneous data products with pattern informatics tools enables efficient development of models. Federated database components and visualization tools allow rapid exploration of large datasets, while pattern informatics enables identification of subtle, but important, features in large data sets. QuakeSim is valuable for earthquake investigations and modeling in its current state, and also serves as a prototype and nucleus for broader systems under development. The framework provides access to physics-based simulation tools that model the earthquake cycle and related crustal deformation. Spaceborne GPS and Inter ferometric Synthetic Aperture (InSAR) data provide information on near-term crustal deformation, while paleoseismic geologic data provide longerterm information on earthquake fault processes. These data sources are integrated into QuakeSim's QuakeTables database system, and are accessible by users or various model applications. UAVSAR repeat pass interferometry data products are added to the QuakeTables database, and are available through a browseable map interface or Representational State Transfer (REST) interfaces. Model applications can retrieve data from Quake Tables, or from third-party GPS velocity data services; alternatively, users can manually input parameters into the models. Pattern analysis of GPS and seismicity data

  2. QuakeSim: Multi-Source Synergistic Data Intensive Computing for Earth Science

    Data.gov (United States)

    National Aeronautics and Space Administration — Update QuakeSim services to integrate and rapidly fuse data from multiple sources to support comprehensive efforts in data mining, analysis, simulation, and...

  3. QuakeSim: a Web Service Environment for Productive Investigations with Earth Surface Sensor Data

    Science.gov (United States)

    Parker, J. W.; Donnellan, A.; Granat, R. A.; Lyzenga, G. A.; Glasscoe, M. T.; McLeod, D.; Al-Ghanmi, R.; Pierce, M.; Fox, G.; Grant Ludwig, L.; Rundle, J. B.

    2011-12-01

    The QuakeSim science gateway environment includes a visually rich portal interface, web service access to data and data processing operations, and the QuakeTables ontology-based database of fault models and sensor data. The integrated tools and services are designed to assist investigators by covering the entire earthquake cycle of strain accumulation and release. The Web interface now includes Drupal-based access to diverse and changing content, with new ability to access data and data processing directly from the public page, as well as the traditional project management areas that require password access. The system is designed to make initial browsing of fault models and deformation data particularly engaging for new users. Popular data and data processing include GPS time series with data mining techniques to find anomalies in time and space, experimental forecasting methods based on catalogue seismicity, faulted deformation models (both half-space and finite element), and model-based inversion of sensor data. The fault models include the CGS and UCERF 2.0 faults of California and are easily augmented with self-consistent fault models from other regions. The QuakeTables deformation data include the comprehensive set of UAVSAR interferograms as well as a growing collection of satellite InSAR data.. Fault interaction simulations are also being incorporated in the web environment based on Virtual California. A sample usage scenario is presented which follows an investigation of UAVSAR data from viewing as an overlay in Google Maps, to selection of an area of interest via a polygon tool, to fast extraction of the relevant correlation and phase information from large data files, to a model inversion of fault slip followed by calculation and display of a synthetic model interferogram.

  4. The QuakeSim Project: Web Services for Managing Geophysical Data and Applications

    Science.gov (United States)

    Pierce, Marlon E.; Fox, Geoffrey C.; Aktas, Mehmet S.; Aydin, Galip; Gadgil, Harshawardhan; Qi, Zhigang; Sayar, Ahmet

    2008-04-01

    We describe our distributed systems research efforts to build the “cyberinfrastructure” components that constitute a geophysical Grid, or more accurately, a Grid of Grids. Service-oriented computing principles are used to build a distributed infrastructure of Web accessible components for accessing data and scientific applications. Our data services fall into two major categories: Archival, database-backed services based around Geographical Information System (GIS) standards from the Open Geospatial Consortium, and streaming services that can be used to filter and route real-time data sources such as Global Positioning System data streams. Execution support services include application execution management services and services for transferring remote files. These data and execution service families are bound together through metadata information and workflow services for service orchestration. Users may access the system through the QuakeSim scientific Web portal, which is built using a portlet component approach.

  5. The QuakeSim Project: Numerical Simulations for Active Tectonic Processes

    Science.gov (United States)

    Donnellan, Andrea; Parker, Jay; Lyzenga, Greg; Granat, Robert; Fox, Geoffrey; Pierce, Marlon; Rundle, John; McLeod, Dennis; Grant, Lisa; Tullis, Terry

    2004-01-01

    In order to develop a solid earth science framework for understanding and studying of active tectonic and earthquake processes, this task develops simulation and analysis tools to study the physics of earthquakes using state-of-the art modeling, data manipulation, and pattern recognition technologies. We develop clearly defined accessible data formats and code protocols as inputs to the simulations. these are adapted to high-performance computers because the solid earth system is extremely complex and nonlinear resulting in computationally intensive problems with millions of unknowns. With these tools it will be possible to construct the more complex models and simulations necessary to develop hazard assessment systems critical for reducing future losses from major earthquakes.

  6. Ultrasound Imaging and its modeling

    DEFF Research Database (Denmark)

    Jensen, Jørgen Arendt

    2002-01-01

    Modern medical ultrasound scanners are used for imaging nearly all soft tissue structures in the body. The anatomy can be studied from gray-scale B-mode images, where the reflectivity and scattering strength of the tissues are displayed. The imaging is performed in real time with 20 to 100 images...

  7. Biomedical Imaging and Computational Modeling in Biomechanics

    CERN Document Server

    Iacoviello, Daniela

    2013-01-01

    This book collects the state-of-art and new trends in image analysis and biomechanics. It covers a wide field of scientific and cultural topics, ranging from remodeling of bone tissue under the mechanical stimulus up to optimizing the performance of sports equipment, through the patient-specific modeling in orthopedics, microtomography and its application in oral and implant research, computational modeling in the field of hip prostheses, image based model development and analysis of the human knee joint, kinematics of the hip joint, micro-scale analysis of compositional and mechanical properties of dentin, automated techniques for cervical cell image analysis, and iomedical imaging and computational modeling in cardiovascular disease.   The book will be of interest to researchers, Ph.D students, and graduate students with multidisciplinary interests related to image analysis and understanding, medical imaging, biomechanics, simulation and modeling, experimental analysis.

  8. Modeling and interpretation of images*

    Directory of Open Access Journals (Sweden)

    Min Michiel

    2015-01-01

    Full Text Available Imaging protoplanetary disks is a challenging but rewarding task. It is challenging because of the glare of the central star outshining the weak signal from the disk at shorter wavelengths and because of the limited spatial resolution at longer wavelengths. It is rewarding because it contains a wealth of information on the structure of the disks and can (directly probe things like gaps and spiral structure. Because it is so challenging, telescopes are often pushed to their limitations to get a signal. Proper interpretation of these images therefore requires intimate knowledge of the instrumentation, the detection method, and the image processing steps. In this chapter I will give some examples and stress some issues that are important when interpreting images from protoplanetary disks.

  9. Image-Optimized Coronal Magnetic Field Models

    Science.gov (United States)

    Jones, Shaela I.; Uritsky, Vadim; Davila, Joseph M.

    2017-01-01

    We have reported previously on a new method we are developing for using image-based information to improve global coronal magnetic field models. In that work we presented early tests of the method which proved its capability to improve global models based on flawed synoptic magnetograms, given excellent constraints on the field in the model volume. In this follow-up paper we present the results of similar tests given field constraints of a nature that could realistically be obtained from quality white-light coronagraph images of the lower corona. We pay particular attention to difficulties associated with the line-of-sight projection of features outside of the assumed coronagraph image plane, and the effect on the outcome of the optimization of errors in localization of constraints. We find that substantial improvement in the model field can be achieved with this type of constraints, even when magnetic features in the images are located outside of the image plane.

  10. Image-optimized Coronal Magnetic Field Models

    Energy Technology Data Exchange (ETDEWEB)

    Jones, Shaela I.; Uritsky, Vadim; Davila, Joseph M., E-mail: shaela.i.jones-mecholsky@nasa.gov, E-mail: shaela.i.jonesmecholsky@nasa.gov [NASA Goddard Space Flight Center, Code 670, Greenbelt, MD 20771 (United States)

    2017-08-01

    We have reported previously on a new method we are developing for using image-based information to improve global coronal magnetic field models. In that work, we presented early tests of the method, which proved its capability to improve global models based on flawed synoptic magnetograms, given excellent constraints on the field in the model volume. In this follow-up paper, we present the results of similar tests given field constraints of a nature that could realistically be obtained from quality white-light coronagraph images of the lower corona. We pay particular attention to difficulties associated with the line-of-sight projection of features outside of the assumed coronagraph image plane and the effect on the outcome of the optimization of errors in the localization of constraints. We find that substantial improvement in the model field can be achieved with these types of constraints, even when magnetic features in the images are located outside of the image plane.

  11. Computer model for harmonic ultrasound imaging.

    Science.gov (United States)

    Li, Y; Zagzebski, J A

    2000-01-01

    Harmonic ultrasound imaging has received great attention from ultrasound scanner manufacturers and researchers. In this paper, we present a computer model that can generate realistic harmonic images. In this model, the incident ultrasound is modeled after the "KZK" equation, and the echo signal is modeled using linear propagation theory because the echo signal is much weaker than the incident pulse. Both time domain and frequency domain numerical solutions to the "KZK" equation were studied. Realistic harmonic images of spherical lesion phantoms were generated for scans by a circular transducer. This model can be a very useful tool for studying the harmonic buildup and dissipation processes in a nonlinear medium, and it can be used to investigate a wide variety of topics related to B-mode harmonic imaging.

  12. Models for Patch-Based Image Restoration

    Directory of Open Access Journals (Sweden)

    Petrovic Nemanja

    2009-01-01

    Full Text Available Abstract We present a supervised learning approach for object-category specific restoration, recognition, and segmentation of images which are blurred using an unknown kernel. The novelty of this work is a multilayer graphical model which unifies the low-level vision task of restoration and the high-level vision task of recognition in a cooperative framework. The graphical model is an interconnected two-layer Markov random field. The restoration layer accounts for the compatibility between sharp and blurred images and models the association between adjacent patches in the sharp image. The recognition layer encodes the entity class and its location in the underlying scene. The potentials are represented using nonparametric kernel densities and are learnt from training data. Inference is performed using nonparametric belief propagation. Experiments demonstrate the effectiveness of our model for the restoration and recognition of blurred license plates as well as face images.

  13. Models for Patch-Based Image Restoration

    Directory of Open Access Journals (Sweden)

    Mithun Das Gupta

    2009-01-01

    Full Text Available We present a supervised learning approach for object-category specific restoration, recognition, and segmentation of images which are blurred using an unknown kernel. The novelty of this work is a multilayer graphical model which unifies the low-level vision task of restoration and the high-level vision task of recognition in a cooperative framework. The graphical model is an interconnected two-layer Markov random field. The restoration layer accounts for the compatibility between sharp and blurred images and models the association between adjacent patches in the sharp image. The recognition layer encodes the entity class and its location in the underlying scene. The potentials are represented using nonparametric kernel densities and are learnt from training data. Inference is performed using nonparametric belief propagation. Experiments demonstrate the effectiveness of our model for the restoration and recognition of blurred license plates as well as face images.

  14. The Halo Model of Origin Images

    DEFF Research Database (Denmark)

    Josiassen, Alexander; Lukas, Bryan A.; Whitwell, Gregory J.

    2013-01-01

    National origin has gained importance as a marketing tool for practitioners to sell their goods and services. However, because origin-image research has been troubled by several fundamental limitations, academia has become sceptical of the current status and strategic implications of the concept....... The aim of this paper was threefold, namely, to provide a state-of-the-art review of origin-image research in marketing, develop and empirically test a new origin-image model and, present the implications of the study....

  15. Model-based satellite image fusion

    DEFF Research Database (Denmark)

    Aanæs, Henrik; Sveinsson, J. R.; Nielsen, Allan Aasbjerg

    2008-01-01

    A method is proposed for pixel-level satellite image fusion derived directly from a model of the imaging sensor. By design, the proposed method is spectrally consistent. It is argued that the proposed method needs regularization, as is the case for any method for this problem. A framework for pixel...... neighborhood regularization is presented. This framework enables the formulation of the regularization in a way that corresponds well with our prior assumptions of the image data. The proposed method is validated and compared with other approaches on several data sets. Lastly, the intensity......-hue-saturation method is revisited in order to gain additional insight of what implications the spectral consistency has for an image fusion method....

  16. Ultrasonic modelling and imaging in dissimilar welds

    International Nuclear Information System (INIS)

    Shlivinski, A.; Langenberg, K.J.; Marklein, R.

    2004-01-01

    Non-destructive testing of defects in nuclear power plant dissimilar pipe weldings play an important part in safety inspections. Traditionally the imaging of such defects is performed using the synthetic aperture focusing technique (SAFT) algorithm, however since parts of the dissimilar welded structure are made of an anisotropic material, this algorithm may fail to produce correct results. Here we present a modified algorithm that enables a correct imaging of cracks in anisotropic and inhomogeneous complex structures by accounting for the true nature of the wave propagation in such structures, this algorithm is called inhomogeneous anisotropic SAFT (InASAFT). In InASAFT algorithm is shown to yield better results over the SAFT algorithm for complex environments. The InASAFT suffers, though, from the same difficulties of the SAFT algorithm, i.e. ''ghost'' images and lack of clear focused images. However these artefacts can be identified through numerical modelling of the wave propagation in the structure. (orig.)

  17. Nonparametric Mixture Models for Supervised Image Parcellation.

    Science.gov (United States)

    Sabuncu, Mert R; Yeo, B T Thomas; Van Leemput, Koen; Fischl, Bruce; Golland, Polina

    2009-09-01

    We present a nonparametric, probabilistic mixture model for the supervised parcellation of images. The proposed model yields segmentation algorithms conceptually similar to the recently developed label fusion methods, which register a new image with each training image separately. Segmentation is achieved via the fusion of transferred manual labels. We show that in our framework various settings of a model parameter yield algorithms that use image intensity information differently in determining the weight of a training subject during fusion. One particular setting computes a single, global weight per training subject, whereas another setting uses locally varying weights when fusing the training data. The proposed nonparametric parcellation approach capitalizes on recently developed fast and robust pairwise image alignment tools. The use of multiple registrations allows the algorithm to be robust to occasional registration failures. We report experiments on 39 volumetric brain MRI scans with expert manual labels for the white matter, cerebral cortex, ventricles and subcortical structures. The results demonstrate that the proposed nonparametric segmentation framework yields significantly better segmentation than state-of-the-art algorithms.

  18. Modelling land degradation in IMAGE 2

    NARCIS (Netherlands)

    Hootsmans RM; Bouwman AF; Leemans R; Kreileman GJJ; MNV

    2001-01-01

    Food security may be threatened by loss of soil productivity as a result of human-induced land degradation. Water erosion is the most important cause of land degradation, and its effects are irreversible. This report describes the IMAGE land degradation model developed for describing current and

  19. Parametric uncertainty in optical image modeling

    Science.gov (United States)

    Potzick, James; Marx, Egon; Davidson, Mark

    2006-10-01

    Optical photomask feature metrology and wafer exposure process simulation both rely on optical image modeling for accurate results. While it is fair to question the accuracies of the available models, model results also depend on several input parameters describing the object and imaging system. Errors in these parameter values can lead to significant errors in the modeled image. These parameters include wavelength, illumination and objective NA's, magnification, focus, etc. for the optical system, and topography, complex index of refraction n and k, etc. for the object. In this paper each input parameter is varied over a range about its nominal value and the corresponding images simulated. Second order parameter interactions are not explored. Using the scenario of the optical measurement of photomask features, these parametric sensitivities are quantified by calculating the apparent change of the measured linewidth for a small change in the relevant parameter. Then, using reasonable values for the estimated uncertainties of these parameters, the parametric linewidth uncertainties can be calculated and combined to give a lower limit to the linewidth measurement uncertainty for those parameter uncertainties.

  20. Statistical model for OCT image denoising

    KAUST Repository

    Li, Muxingzi

    2017-08-01

    Optical coherence tomography (OCT) is a non-invasive technique with a large array of applications in clinical imaging and biological tissue visualization. However, the presence of speckle noise affects the analysis of OCT images and their diagnostic utility. In this article, we introduce a new OCT denoising algorithm. The proposed method is founded on a numerical optimization framework based on maximum-a-posteriori estimate of the noise-free OCT image. It combines a novel speckle noise model, derived from local statistics of empirical spectral domain OCT (SD-OCT) data, with a Huber variant of total variation regularization for edge preservation. The proposed approach exhibits satisfying results in terms of speckle noise reduction as well as edge preservation, at reduced computational cost.

  1. Image analysis and modeling in medical image computing. Recent developments and advances.

    Science.gov (United States)

    Handels, H; Deserno, T M; Meinzer, H-P; Tolxdorff, T

    2012-01-01

    Medical image computing is of growing importance in medical diagnostics and image-guided therapy. Nowadays, image analysis systems integrating advanced image computing methods are used in practice e.g. to extract quantitative image parameters or to support the surgeon during a navigated intervention. However, the grade of automation, accuracy, reproducibility and robustness of medical image computing methods has to be increased to meet the requirements in clinical routine. In the focus theme, recent developments and advances in the field of modeling and model-based image analysis are described. The introduction of models in the image analysis process enables improvements of image analysis algorithms in terms of automation, accuracy, reproducibility and robustness. Furthermore, model-based image computing techniques open up new perspectives for prediction of organ changes and risk analysis of patients. Selected contributions are assembled to present latest advances in the field. The authors were invited to present their recent work and results based on their outstanding contributions to the Conference on Medical Image Computing BVM 2011 held at the University of Lübeck, Germany. All manuscripts had to pass a comprehensive peer review. Modeling approaches and model-based image analysis methods showing new trends and perspectives in model-based medical image computing are described. Complex models are used in different medical applications and medical images like radiographic images, dual-energy CT images, MR images, diffusion tensor images as well as microscopic images are analyzed. The applications emphasize the high potential and the wide application range of these methods. The use of model-based image analysis methods can improve segmentation quality as well as the accuracy and reproducibility of quantitative image analysis. Furthermore, image-based models enable new insights and can lead to a deeper understanding of complex dynamic mechanisms in the human body

  2. Image-Based Models Using Crowdsourcing Strategy

    Directory of Open Access Journals (Sweden)

    Antonia Spanò

    2016-12-01

    Full Text Available The conservation and valorization of Cultural Heritage require an extensive documentation, both in properly historic-artistic terms and regarding the physical characteristics of position, shape, color, and geometry. With the use of digital photogrammetry that make acquisition of overlapping images for 3D photo modeling and with the development of dense and accurate 3D point models, it is possible to obtain high-resolution orthoprojections of surfaces.Recent years have seen a growing interest in crowdsourcing that holds in the field of the protection and dissemination of cultural heritage, in parallel there is an increasing awareness for contributing the generation of digital models with the immense wealth of images available on the web which are useful for documentation heritage.In this way, the availability and ease the automation of SfM (Structure from Motion algorithm enables the generation of digital models of the built heritage, which can be inserted positively in crowdsourcing processes. In fact, non-expert users can handle the technology in the process of acquisition, which today is one of the fundamental points to involve the wider public to the cultural heritage protection. To present the image based models and their derivatives that can be made from a great digital resource; the current approach is useful for the little-known heritage or not easily accessible buildings as an emblematic case study that was selected. It is the Vank Cathedral in Isfahan in Iran: the availability of accurate point clouds and reliable orthophotos are very convenient since the building of the Safavid epoch (cent. XVII-XVIII completely frescoed with the internal surfaces, which the architecture and especially the architectural decoration reach their peak.The experimental part of the paper explores also some aspects of usability of the digital output from the image based modeling methods. The availability of orthophotos allows and facilitates the iconographic

  3. Image sequence analysis in nuclear medicine: (1) Parametric imaging using statistical modelling

    International Nuclear Information System (INIS)

    Liehn, J.C.; Hannequin, P.; Valeyre, J.

    1989-01-01

    This is a review of parametric imaging methods on Nuclear Medicine. A Parametric Image is an image in which each pixel value is a function of the value of the same pixel of an image sequence. The Local Model Method is the fitting of each pixel time activity curve by a model which parameter values form the Parametric Images. The Global Model Method is the modelling of the changes between two images. It is applied to image comparison. For both methods, the different models, the identification criterion, the optimization methods and the statistical properties of the images are discussed. The analysis of one or more Parametric Images is performed using 1D or 2D histograms. The statistically significant Parametric Images, (Images of significant Variances, Amplitudes and Differences) are also proposed [fr

  4. Ultrasonic modelling and imaging in dissimilar welds

    Energy Technology Data Exchange (ETDEWEB)

    Shlivinski, A.; Langenberg, K.J.; Marklein, R. [Dept. of Electrical Engineering, Univ. of Kassel, Kassel (Germany)

    2004-07-01

    Non-destructive testing of defects in nuclear power plant dissimilar pipe weldings play an important part in safety inspections. Traditionally the imaging of such defects is performed using the synthetic aperture focusing technique (SAFT) algorithm, however since parts of the dissimilar welded structure are made of an anisotropic material, this algorithm may fail to produce correct results. Here we present a modified algorithm that enables a correct imaging of cracks in anisotropic and inhomogeneous complex structures by accounting for the true nature of the wave propagation in such structures, this algorithm is called inhomogeneous anisotropic SAFT (InASAFT). In InASAFT algorithm is shown to yield better results over the SAFT algorithm for complex environments. The InASAFT suffers, though, from the same difficulties of the SAFT algorithm, i.e. ''ghost'' images and lack of clear focused images. However these artefacts can be identified through numerical modelling of the wave propagation in the structure. (orig.)

  5. Properties of Brownian Image Models in Scale-Space

    DEFF Research Database (Denmark)

    Pedersen, Kim Steenstrup

    2003-01-01

    Brownian images) will be discussed in relation to linear scale-space theory, and it will be shown empirically that the second order statistics of natural images mapped into jet space may, within some scale interval, be modeled by the Brownian image model. This is consistent with the 1/f 2 power spectrum...... law that apparently governs natural images. Furthermore, the distribution of Brownian images mapped into jet space is Gaussian and an analytical expression can be derived for the covariance matrix of Brownian images in jet space. This matrix is also a good approximation of the covariance matrix......In this paper it is argued that the Brownian image model is the least committed, scale invariant, statistical image model which describes the second order statistics of natural images. Various properties of three different types of Gaussian image models (white noise, Brownian and fractional...

  6. Reconstructing building mass models from UAV images

    KAUST Repository

    Li, Minglei

    2015-07-26

    We present an automatic reconstruction pipeline for large scale urban scenes from aerial images captured by a camera mounted on an unmanned aerial vehicle. Using state-of-the-art Structure from Motion and Multi-View Stereo algorithms, we first generate a dense point cloud from the aerial images. Based on the statistical analysis of the footprint grid of the buildings, the point cloud is classified into different categories (i.e., buildings, ground, trees, and others). Roof structures are extracted for each individual building using Markov random field optimization. Then, a contour refinement algorithm based on pivot point detection is utilized to refine the contour of patches. Finally, polygonal mesh models are extracted from the refined contours. Experiments on various scenes as well as comparisons with state-of-the-art reconstruction methods demonstrate the effectiveness and robustness of the proposed method.

  7. Modeling of skin cancer dermatoscopy images

    Science.gov (United States)

    Iralieva, Malica B.; Myakinin, Oleg O.; Bratchenko, Ivan A.; Zakharov, Valery P.

    2018-04-01

    An early identified cancer is more likely to effective respond to treatment and has a less expensive treatment as well. Dermatoscopy is one of general diagnostic techniques for skin cancer early detection that allows us in vivo evaluation of colors and microstructures on skin lesions. Digital phantoms with known properties are required during new instrument developing to compare sample's features with data from the instrument. An algorithm for image modeling of skin cancer is proposed in the paper. Steps of the algorithm include setting shape, texture generation, adding texture and normal skin background setting. The Gaussian represents the shape, and then the texture generation based on a fractal noise algorithm is responsible for spatial chromophores distributions, while the colormap applied to the values corresponds to spectral properties. Finally, a normal skin image simulated by mixed Monte Carlo method using a special online tool is added as a background. Varying of Asymmetry, Borders, Colors and Diameter settings is shown to be fully matched to the ABCD clinical recognition algorithm. The asymmetry is specified by setting different standard deviation values of Gaussian in different parts of image. The noise amplitude is increased to set the irregular borders score. Standard deviation is changed to determine size of the lesion. Colors are set by colormap changing. The algorithm for simulating different structural elements is required to match with others recognition algorithms.

  8. Variational PDE Models in Image Processing

    National Research Council Canada - National Science Library

    Chan, Tony F; Shen, Jianhong; Vese, Luminita

    2002-01-01

    .... These include astronomy and aerospace exploration, medical imaging, molecular imaging, computer graphics, human and machine vision, telecommunication, auto-piloting, surveillance video, and biometric...

  9. Statistical image processing and multidimensional modeling

    CERN Document Server

    Fieguth, Paul

    2010-01-01

    Images are all around us! The proliferation of low-cost, high-quality imaging devices has led to an explosion in acquired images. When these images are acquired from a microscope, telescope, satellite, or medical imaging device, there is a statistical image processing task: the inference of something - an artery, a road, a DNA marker, an oil spill - from imagery, possibly noisy, blurry, or incomplete. A great many textbooks have been written on image processing. However this book does not so much focus on images, per se, but rather on spatial data sets, with one or more measurements taken over

  10. The model of illumination-transillumination for image enhancement of X-ray images

    Energy Technology Data Exchange (ETDEWEB)

    Lyu, Kwang Yeul [Shingu College, Sungnam (Korea, Republic of); Rhee, Sang Min [Kangwon National Univ., Chuncheon (Korea, Republic of)

    2001-06-01

    In digital image processing, the homomorphic filtering approach is derived from an illumination - reflectance model of the image. It can also be used with an illumination-transillumination model X-ray film. Several X-ray images were applied to enhancement with histogram equalization and homomorphic filter based on an illumination-transillumination model. The homomorphic filter has proven theoretical claim of image density range compression and balanced contrast enhancement, and also was found a valuable tool to process analog X-ray images to digital images.

  11. Elastic models application for thorax image registration

    International Nuclear Information System (INIS)

    Correa Prado, Lorena S; Diaz, E Andres Valdez; Romo, Raul

    2007-01-01

    This work consist of the implementation and evaluation of elastic alignment algorithms of biomedical images, which were taken at thorax level and simulated with the 4D NCAT digital phantom. Radial Basis Functions spatial transformations (RBF), a kind of spline, which allows carrying out not only global rigid deformations but also local elastic ones were applied, using a point-matching method. The applied functions were: Thin Plate Spline (TPS), Multiquadric (MQ) Gaussian and B-Spline, which were evaluated and compared by means of calculating the Target Registration Error and similarity measures between the registered images (the squared sum of intensity differences (SSD) and correlation coefficient (CC)). In order to value the user incurred error in the point-matching and segmentation tasks, two algorithms were also designed that calculate the Fiduciary Localization Error. TPS and MQ were demonstrated to have better performance than the others. It was proved RBF represent an adequate model for approximating the thorax deformable behaviour. Validation algorithms showed the user error was not significant

  12. Modelling Brain Tissue using Magnetic Resonance Imaging

    DEFF Research Database (Denmark)

    Dyrby, Tim Bjørn

    2008-01-01

    Diffusion MRI, or diffusion weighted imaging (DWI), is a technique that measures the restricted diffusion of water molecules within brain tissue. Different reconstruction methods quantify water-diffusion anisotropy in the intra- and extra-cellular spaces of the neural environment. Fibre tracking...... models then use the directions of greatest diffusion as estimates of white matter fibre orientation. Several fibre tracking algorithms have emerged in the last few years that provide reproducible visualizations of three-dimensional fibre bundles. One class of these algorithms is probabilistic...... the possibility of using high-field experimental MR scanners and long scanning times, thereby significantly improving the signal-to-noise ratio (SNR) and anatomical resolution. Moreover, many of the degrading effects observed in vivo, such as physiological noise, are no longer present. However, the post mortem...

  13. Kinetic modeling in PET imaging of hypoxia

    Science.gov (United States)

    Li, Fan; Joergensen, Jesper T; Hansen, Anders E; Kjaer, Andreas

    2014-01-01

    Tumor hypoxia is associated with increased therapeutic resistance leading to poor treatment outcome. Therefore the ability to detect and quantify intratumoral oxygenation could play an important role in future individual personalized treatment strategies. Positron Emission Tomography (PET) can be used for non-invasive mapping of tissue oxygenation in vivo and several hypoxia specific PET tracers have been developed. Evaluation of PET data in the clinic is commonly based on visual assessment together with semiquantitative measurements e.g. standard uptake value (SUV). However, dynamic PET contains additional valuable information on the temporal changes in tracer distribution. Kinetic modeling can be used to extract relevant pharmacokinetic parameters of tracer behavior in vivo that reflects relevant physiological processes. In this paper, we review the potential contribution of kinetic analysis for PET imaging of hypoxia. PMID:25250200

  14. A new level set model for cell image segmentation

    Science.gov (United States)

    Ma, Jing-Feng; Hou, Kai; Bao, Shang-Lian; Chen, Chun

    2011-02-01

    In this paper we first determine three phases of cell images: background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing.

  15. Statistical model for OCT image denoising

    KAUST Repository

    Li, Muxingzi; Idoughi, Ramzi; Choudhury, Biswarup; Heidrich, Wolfgang

    2017-01-01

    Optical coherence tomography (OCT) is a non-invasive technique with a large array of applications in clinical imaging and biological tissue visualization. However, the presence of speckle noise affects the analysis of OCT images and their diagnostic

  16. Single image interpolation via adaptive nonlocal sparsity-based modeling.

    Science.gov (United States)

    Romano, Yaniv; Protter, Matan; Elad, Michael

    2014-07-01

    Single image interpolation is a central and extensively studied problem in image processing. A common approach toward the treatment of this problem in recent years is to divide the given image into overlapping patches and process each of them based on a model for natural image patches. Adaptive sparse representation modeling is one such promising image prior, which has been shown to be powerful in filling-in missing pixels in an image. Another force that such algorithms may use is the self-similarity that exists within natural images. Processing groups of related patches together exploits their correspondence, leading often times to improved results. In this paper, we propose a novel image interpolation method, which combines these two forces-nonlocal self-similarities and sparse representation modeling. The proposed method is contrasted with competitive and related algorithms, and demonstrated to achieve state-of-the-art results.

  17. POLARIZATION IMAGING AND SCATTERING MODEL OF CANCEROUS LIVER TISSUES

    Directory of Open Access Journals (Sweden)

    DONGZHI LI

    2013-07-01

    Full Text Available We apply different polarization imaging techniques for cancerous liver tissues, and compare the relative contrasts for difference polarization imaging (DPI, degree of polarization imaging (DOPI and rotating linear polarization imaging (RLPI. Experimental results show that a number of polarization imaging parameters are capable of differentiating cancerous cells in isotropic liver tissues. To analyze the contrast mechanism of the cancer-sensitive polarization imaging parameters, we propose a scattering model containing two types of spherical scatterers and carry on Monte Carlo simulations based on this bi-component model. Both the experimental and Monte Carlo simulated results show that the RLPI technique can provide a good imaging contrast of cancerous tissues. The bi-component scattering model provides a useful tool to analyze the contrast mechanism of polarization imaging of cancerous tissues.

  18. PET imaging using parkinsonian primate model

    International Nuclear Information System (INIS)

    Nagai, Yuji

    2004-01-01

    Many animal models have been for studying neutrodegenerative diseases in humans. Among them, Parkinson's disease (PD) model in primates treated with 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) is expected to be valid and useful in the field of regenerative medicine. MPTP-treated monkeys demonstrate parkinsonian syndrome, such as tremor, dyskinesia, rigidity, immobility, caused by the degeneration of dopamine neurons at the nigrostriatal pathway. In this model, investigation of cognitive impairment that is one of the important aspects of PD could be possible. We evaluated the degeneration process of nigrostriatal dopamine neurons with positron emission tomography (PET) using unanesthetized MPTP-treated two cynomolgus monkeys (Macaca fascicularis). The tracers used were [11C]PE2I, [11C]DOPA, [11C]raclopride for monitoring dopamine transporter (DAT) densities, dopamine (DA) turnover, dopamine D2-receptor (D2R) densities, respectively. The gross behavioral observation was also performed referring to the criteria of the PD symptoms. The motor dysfunction was not clearly observed up to the cumulative doses of 3 mg/kg MPTP. This period was called 'asymptomatic period'. As a result of PET scans in the asymptomatic period, DAT densities and DA turnover had already decreased greatly, but D2R densities had not changed clearly. These findings suggest that PET imaging can delineate the dopaminergic dysfunction in vivo even in the asymptomatic period. In human study of PD, it is reported that parkinsonism is shown after great loss of dopaminergic neutrons as well as pre-synaptic dysfunction. MPTP-treated monkeys demonstrate the parkinsonian syndrome with the similar mechanism as human PD. It can be expected that PET study with MPTP-monkeys would provide important clues relevant to the underlying cause of PD and be useful for preclinical study of regenerative medicine in this disease. (author)

  19. A Drosophila Model to Image Phagosome Maturation

    Directory of Open Access Journals (Sweden)

    Douglas A. Brooks

    2013-03-01

    Full Text Available Phagocytosis involves the internalization of extracellular material by invagination of the plasma membrane to form intracellular vesicles called phagosomes, which have functions that include pathogen degradation. The degradative properties of phagosomes are thought to be conferred by sequential fusion with endosomes and lysosomes; however, this maturation process has not been studied in vivo. We employed Drosophila hemocytes, which are similar to mammalian professional macrophages, to establish a model of phagosome maturation. Adult Drosophila females, carrying transgenic Rab7-GFP endosome and Lamp1-GFP lysosome markers, were injected with E. coli DH5α and the hemocytes were collected at 15, 30, 45 and 60 minutes after infection. In wild-type females, E. coli were detected within enlarged Rab7-GFP positive phagosomes at 15 to 45 minutes after infection; and were also observed in enlarged Lamp1-GFP positive phagolysosomes at 45 minutes. Two-photon imaging of hemocytes in vivo confirmed this vesicle morphology, including enlargement of Rab7-GFP and Lamp1-GFP structures that often appeared to protrude from hemocytes. The interaction of endosomes and lysosomes with E. coli phagosomes observed in Drosophila hemocytes was consistent with that previously described for phagosome maturation in human ex vivo macrophages. We also tested our model as a tool for genetic analysis using 14-3-3e mutants, and demonstrated altered phagosome maturation with delayed E. coli internalization, trafficking and/or degradation. These findings demonstrate that Drosophila hemocytes provide an appropriate, genetically amenable, model for analyzing phagosome maturation ex vivo and in vivo.

  20. Mathematical models for correction of images, obtained at radioisotope scan

    International Nuclear Information System (INIS)

    Glaz, A.; Lubans, A.

    2002-01-01

    The images, which obtained at radioisotope scintigraphy, contain distortions. Distortions appear as a result of absorption of radiation by patient's body's tissues. Two mathematical models for reducing of such distortions are proposed. Image obtained by only one gamma camera is used in the first mathematical model. Unfortunately, this model allows processing of the images only in case, when it can be assumed, that the investigated organ has a symmetric form. The images obtained by two gamma cameras are used in the second model. It gives possibility to assume that the investigated organ has non-symmetric form and to acquire more precise results. (authors)

  1. Joint model of motion and anatomy for PET image reconstruction

    International Nuclear Information System (INIS)

    Qiao Feng; Pan Tinsu; Clark, John W. Jr.; Mawlawi, Osama

    2007-01-01

    Anatomy-based positron emission tomography (PET) image enhancement techniques have been shown to have the potential for improving PET image quality. However, these techniques assume an accurate alignment between the anatomical and the functional images, which is not always valid when imaging the chest due to respiratory motion. In this article, we present a joint model of both motion and anatomical information by integrating a motion-incorporated PET imaging system model with an anatomy-based maximum a posteriori image reconstruction algorithm. The mismatched anatomical information due to motion can thus be effectively utilized through this joint model. A computer simulation and a phantom study were conducted to assess the efficacy of the joint model, whereby motion and anatomical information were either modeled separately or combined. The reconstructed images in each case were compared to corresponding reference images obtained using a quadratic image prior based maximum a posteriori reconstruction algorithm for quantitative accuracy. Results of these studies indicated that while modeling anatomical information or motion alone improved the PET image quantitation accuracy, a larger improvement in accuracy was achieved when using the joint model. In the computer simulation study and using similar image noise levels, the improvement in quantitation accuracy compared to the reference images was 5.3% and 19.8% when using anatomical or motion information alone, respectively, and 35.5% when using the joint model. In the phantom study, these results were 5.6%, 5.8%, and 19.8%, respectively. These results suggest that motion compensation is important in order to effectively utilize anatomical information in chest imaging using PET. The joint motion-anatomy model presented in this paper provides a promising solution to this problem

  2. A Learning State-Space Model for Image Retrieval

    Directory of Open Access Journals (Sweden)

    Lee Greg C

    2007-01-01

    Full Text Available This paper proposes an approach based on a state-space model for learning the user concepts in image retrieval. We first design a scheme of region-based image representation based on concept units, which are integrated with different types of feature spaces and with different region scales of image segmentation. The design of the concept units aims at describing similar characteristics at a certain perspective among relevant images. We present the details of our proposed approach based on a state-space model for interactive image retrieval, including likelihood and transition models, and we also describe some experiments that show the efficacy of our proposed model. This work demonstrates the feasibility of using a state-space model to estimate the user intuition in image retrieval.

  3. Non-rigid image registration using bone growth model

    DEFF Research Database (Denmark)

    Bro-Nielsen, Morten; Gramkow, Claus; Kreiborg, Sven

    1997-01-01

    Non-rigid registration has traditionally used physical models like elasticity and fluids. These models are very seldom valid models of the difference between the registered images. This paper presents a non-rigid registration algorithm, which uses a model of bone growth as a model of the change...... between time sequence images of the human mandible. By being able to register the images, this paper at the same time contributes to the validation of the growth model, which is based on the currently available medical theories and knowledge...

  4. Diffraction enhanced imaging: a simple model

    International Nuclear Information System (INIS)

    Zhu Peiping; Yuan Qingxi; Huang Wanxia; Wang Junyue; Shu Hang; Chen Bo; Liu Yijin; Li Enrong; Wu Ziyu

    2006-01-01

    Based on pinhole imaging and conventional x-ray projection imaging, a more general DEI (diffraction enhanced imaging) equation is derived using simple concepts in this paper. Not only can the new DEI equation explain all the same problems as with the DEI equation proposed by Chapman, but also some problems that cannot be explained with the old DEI equation, such as the noise background caused by small angle scattering diffracted by the analyser

  5. Diffraction enhanced imaging: a simple model

    Energy Technology Data Exchange (ETDEWEB)

    Zhu Peiping; Yuan Qingxi; Huang Wanxia; Wang Junyue; Shu Hang; Chen Bo; Liu Yijin; Li Enrong; Wu Ziyu [Beijing Synchrotron Radiation Facility, Institute of High Energy Physics, Chinese Academy of Sciences, Beijing 100049 (China)

    2006-10-07

    Based on pinhole imaging and conventional x-ray projection imaging, a more general DEI (diffraction enhanced imaging) equation is derived using simple concepts in this paper. Not only can the new DEI equation explain all the same problems as with the DEI equation proposed by Chapman, but also some problems that cannot be explained with the old DEI equation, such as the noise background caused by small angle scattering diffracted by the analyser.

  6. Optical Imaging and Radiometric Modeling and Simulation

    Science.gov (United States)

    Ha, Kong Q.; Fitzmaurice, Michael W.; Moiser, Gary E.; Howard, Joseph M.; Le, Chi M.

    2010-01-01

    OPTOOL software is a general-purpose optical systems analysis tool that was developed to offer a solution to problems associated with computational programs written for the James Webb Space Telescope optical system. It integrates existing routines into coherent processes, and provides a structure with reusable capabilities that allow additional processes to be quickly developed and integrated. It has an extensive graphical user interface, which makes the tool more intuitive and friendly. OPTOOL is implemented using MATLAB with a Fourier optics-based approach for point spread function (PSF) calculations. It features parametric and Monte Carlo simulation capabilities, and uses a direct integration calculation to permit high spatial sampling of the PSF. Exit pupil optical path difference (OPD) maps can be generated using combinations of Zernike polynomials or shaped power spectral densities. The graphical user interface allows rapid creation of arbitrary pupil geometries, and entry of all other modeling parameters to support basic imaging and radiometric analyses. OPTOOL provides the capability to generate wavefront-error (WFE) maps for arbitrary grid sizes. These maps are 2D arrays containing digital sampled versions of functions ranging from Zernike polynomials to combination of sinusoidal wave functions in 2D, to functions generated from a spatial frequency power spectral distribution (PSD). It also can generate optical transfer functions (OTFs), which are incorporated into the PSF calculation. The user can specify radiometrics for the target and sky background, and key performance parameters for the instrument s focal plane array (FPA). This radiometric and detector model setup is fairly extensive, and includes parameters such as zodiacal background, thermal emission noise, read noise, and dark current. The setup also includes target spectral energy distribution as a function of wavelength for polychromatic sources, detector pixel size, and the FPA s charge

  7. A statistical model for radar images of agricultural scenes

    Science.gov (United States)

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

    1982-01-01

    The presently derived and validated statistical model for radar images containing many different homogeneous fields predicts the probability density functions of radar images of entire agricultural scenes, thereby allowing histograms of large scenes composed of a variety of crops to be described. Seasat-A SAR images of agricultural scenes are accurately predicted by the model on the basis of three assumptions: each field has the same SNR, all target classes cover approximately the same area, and the true reflectivity characterizing each individual target class is a uniformly distributed random variable. The model is expected to be useful in the design of data processing algorithms and for scene analysis using radar images.

  8. New variational image decomposition model for simultaneously denoising and segmenting optical coherence tomography images

    International Nuclear Information System (INIS)

    Duan, Jinming; Bai, Li; Tench, Christopher; Gottlob, Irene; Proudlock, Frank

    2015-01-01

    Optical coherence tomography (OCT) imaging plays an important role in clinical diagnosis and monitoring of diseases of the human retina. Automated analysis of optical coherence tomography images is a challenging task as the images are inherently noisy. In this paper, a novel variational image decomposition model is proposed to decompose an OCT image into three components: the first component is the original image but with the noise completely removed; the second contains the set of edges representing the retinal layer boundaries present in the image; and the third is an image of noise, or in image decomposition terms, the texture, or oscillatory patterns of the original image. In addition, a fast Fourier transform based split Bregman algorithm is developed to improve computational efficiency of solving the proposed model. Extensive experiments are conducted on both synthesised and real OCT images to demonstrate that the proposed model outperforms the state-of-the-art speckle noise reduction methods and leads to accurate retinal layer segmentation. (paper)

  9. Sparse representation based image interpolation with nonlocal autoregressive modeling.

    Science.gov (United States)

    Dong, Weisheng; Zhang, Lei; Lukac, Rastislav; Shi, Guangming

    2013-04-01

    Sparse representation is proven to be a promising approach to image super-resolution, where the low-resolution (LR) image is usually modeled as the down-sampled version of its high-resolution (HR) counterpart after blurring. When the blurring kernel is the Dirac delta function, i.e., the LR image is directly down-sampled from its HR counterpart without blurring, the super-resolution problem becomes an image interpolation problem. In such cases, however, the conventional sparse representation models (SRM) become less effective, because the data fidelity term fails to constrain the image local structures. In natural images, fortunately, many nonlocal similar patches to a given patch could provide nonlocal constraint to the local structure. In this paper, we incorporate the image nonlocal self-similarity into SRM for image interpolation. More specifically, a nonlocal autoregressive model (NARM) is proposed and taken as the data fidelity term in SRM. We show that the NARM-induced sampling matrix is less coherent with the representation dictionary, and consequently makes SRM more effective for image interpolation. Our extensive experimental results demonstrate that the proposed NARM-based image interpolation method can effectively reconstruct the edge structures and suppress the jaggy/ringing artifacts, achieving the best image interpolation results so far in terms of PSNR as well as perceptual quality metrics such as SSIM and FSIM.

  10. Interpretation of medical images by model guided analysis

    International Nuclear Information System (INIS)

    Karssemeijer, N.

    1989-01-01

    Progress in the development of digital pictorial information systems stimulates a growing interest in the use of image analysis techniques in medicine. Especially when precise quantitative information is required the use of fast and reproducable computer analysis may be more appropriate than relying on visual judgement only. Such quantitative information can be valuable, for instance, in diagnostics or in irradiation therapy planning. As medical images are mostly recorded in a prescribed way, human anatomy guarantees a common image structure for each particular type of exam. In this thesis it is investigated how to make use of this a priori knowledge to guide image analysis. For that purpose models are developed which are suited to capture common image structure. The first part of this study is devoted to an analysis of nuclear medicine images of myocardial perfusion. In ch. 2 a model of these images is designed in order to represent characteristic image properties. It is shown that for these relatively simple images a compact symbolic description can be achieved, without significant loss of diagnostically importance of several image properties. Possibilities for automatic interpretation of more complex images is investigated in the following chapters. The central topic is segmentation of organs. Two methods are proposed and tested on a set of abdominal X-ray CT scans. Ch. 3 describes a serial approach based on a semantic network and the use of search areas. Relational constraints are used to guide the image processing and to classify detected image segments. In teh ch.'s 4 and 5 a more general parallel approach is utilized, based on a markov random field image model. A stochastic model used to represent prior knowledge about the spatial arrangement of organs is implemented as an external field. (author). 66 refs.; 27 figs.; 6 tabs

  11. Model-Based Reconstructive Elasticity Imaging Using Ultrasound

    Directory of Open Access Journals (Sweden)

    Salavat R. Aglyamov

    2007-01-01

    Full Text Available Elasticity imaging is a reconstructive imaging technique where tissue motion in response to mechanical excitation is measured using modern imaging systems, and the estimated displacements are then used to reconstruct the spatial distribution of Young's modulus. Here we present an ultrasound elasticity imaging method that utilizes the model-based technique for Young's modulus reconstruction. Based on the geometry of the imaged object, only one axial component of the strain tensor is used. The numerical implementation of the method is highly efficient because the reconstruction is based on an analytic solution of the forward elastic problem. The model-based approach is illustrated using two potential clinical applications: differentiation of liver hemangioma and staging of deep venous thrombosis. Overall, these studies demonstrate that model-based reconstructive elasticity imaging can be used in applications where the geometry of the object and the surrounding tissue is somewhat known and certain assumptions about the pathology can be made.

  12. A new level set model for cell image segmentation

    International Nuclear Information System (INIS)

    Ma Jing-Feng; Chen Chun; Hou Kai; Bao Shang-Lian

    2011-01-01

    In this paper we first determine three phases of cell images: background, cytoplasm and nucleolus according to the general physical characteristics of cell images, and then develop a variational model, based on these characteristics, to segment nucleolus and cytoplasm from their relatively complicated backgrounds. In the meantime, the preprocessing obtained information of cell images using the OTSU algorithm is used to initialize the level set function in the model, which can speed up the segmentation and present satisfactory results in cell image processing. (cross-disciplinary physics and related areas of science and technology)

  13. Software for medical image based phantom modelling

    International Nuclear Information System (INIS)

    Possani, R.G.; Massicano, F.; Coelho, T.S.; Yoriyaz, H.

    2011-01-01

    Latest treatment planning systems depends strongly on CT images, so the tendency is that the dosimetry procedures in nuclear medicine therapy be also based on images, such as magnetic resonance imaging (MRI) or computed tomography (CT), to extract anatomical and histological information, as well as, functional imaging or activities map as PET or SPECT. This information associated with the simulation of radiation transport software is used to estimate internal dose in patients undergoing treatment in nuclear medicine. This work aims to re-engineer the software SCMS, which is an interface software between the Monte Carlo code MCNP, and the medical images, that carry information from the patient in treatment. In other words, the necessary information contained in the images are interpreted and presented in a specific format to the Monte Carlo MCNP code to perform the simulation of radiation transport. Therefore, the user does not need to understand complex process of inputting data on MCNP, as the SCMS is responsible for automatically constructing anatomical data from the patient, as well as the radioactive source data. The SCMS was originally developed in Fortran- 77. In this work it was rewritten in an object-oriented language (JAVA). New features and data options have also been incorporated into the software. Thus, the new software has a number of improvements, such as intuitive GUI and a menu for the selection of the energy spectra correspondent to a specific radioisotope stored in a XML data bank. The new version also supports new materials and the user can specify an image region of interest for the calculation of absorbed dose. (author)

  14. Fisheye image rectification using spherical and digital distortion models

    Science.gov (United States)

    Li, Xin; Pi, Yingdong; Jia, Yanling; Yang, Yuhui; Chen, Zhiyong; Hou, Wenguang

    2018-02-01

    Fisheye cameras have been widely used in many applications including close range visual navigation and observation and cyber city reconstruction because its field of view is much larger than that of a common pinhole camera. This means that a fisheye camera can capture more information than a pinhole camera in the same scenario. However, the fisheye image contains serious distortion, which may cause trouble for human observers in recognizing the objects within. Therefore, in most practical applications, the fisheye image should be rectified to a pinhole perspective projection image to conform to human cognitive habits. The traditional mathematical model-based methods cannot effectively remove the distortion, but the digital distortion model can reduce the image resolution to some extent. Considering these defects, this paper proposes a new method that combines the physical spherical model and the digital distortion model. The distortion of fisheye images can be effectively removed according to the proposed approach. Many experiments validate its feasibility and effectiveness.

  15. Improved Denoising via Poisson Mixture Modeling of Image Sensor Noise.

    Science.gov (United States)

    Zhang, Jiachao; Hirakawa, Keigo

    2017-04-01

    This paper describes a study aimed at comparing the real image sensor noise distribution to the models of noise often assumed in image denoising designs. A quantile analysis in pixel, wavelet transform, and variance stabilization domains reveal that the tails of Poisson, signal-dependent Gaussian, and Poisson-Gaussian models are too short to capture real sensor noise behavior. A new Poisson mixture noise model is proposed to correct the mismatch of tail behavior. Based on the fact that noise model mismatch results in image denoising that undersmoothes real sensor data, we propose a mixture of Poisson denoising method to remove the denoising artifacts without affecting image details, such as edge and textures. Experiments with real sensor data verify that denoising for real image sensor data is indeed improved by this new technique.

  16. pyBSM: A Python package for modeling imaging systems

    Science.gov (United States)

    LeMaster, Daniel A.; Eismann, Michael T.

    2017-05-01

    There are components that are common to all electro-optical and infrared imaging system performance models. The purpose of the Python Based Sensor Model (pyBSM) is to provide open source access to these functions for other researchers to build upon. Specifically, pyBSM implements much of the capability found in the ERIM Image Based Sensor Model (IBSM) V2.0 along with some improvements. The paper also includes two use-case examples. First, performance of an airborne imaging system is modeled using the General Image Quality Equation (GIQE). The results are then decomposed into factors affecting noise and resolution. Second, pyBSM is paired with openCV to evaluate performance of an algorithm used to detect objects in an image.

  17. Correlation of breast image alignment using biomechanical modelling

    Science.gov (United States)

    Lee, Angela; Rajagopal, Vijay; Bier, Peter; Nielsen, Poul M. F.; Nash, Martyn P.

    2009-02-01

    Breast cancer is one of the most common causes of cancer death among women around the world. Researchers have found that a combination of imaging modalities (such as x-ray mammography, magnetic resonance, and ultrasound) leads to more effective diagnosis and management of breast cancers because each imaging modality displays different information about the breast tissues. In order to aid clinicians in interpreting the breast images from different modalities, we have developed a computational framework for generating individual-specific, 3D, finite element (FE) models of the breast. Medical images are embedded into this model, which is subsequently used to simulate the large deformations that the breasts undergo during different imaging procedures, thus warping the medical images to the deformed views of the breast in the different modalities. In this way, medical images of the breast taken in different geometric configurations (compression, gravity, etc.) can be aligned according to physically feasible transformations. In order to analyse the accuracy of the biomechanical model predictions, squared normalised cross correlation (NCC2) was used to provide both local and global comparisons of the model-warped images with clinical images of the breast subject to different gravity loaded states. The local comparison results were helpful in indicating the areas for improvement in the biomechanical model. To improve the modelling accuracy, we will need to investigate the incorporation of breast tissue heterogeneity into the model and altering the boundary conditions for the breast model. A biomechanical image registration tool of this kind will help radiologists to provide more reliable diagnosis and localisation of breast cancer.

  18. IMAGE TO POINT CLOUD METHOD OF 3D-MODELING

    Directory of Open Access Journals (Sweden)

    A. G. Chibunichev

    2012-07-01

    Full Text Available This article describes the method of constructing 3D models of objects (buildings, monuments based on digital images and a point cloud obtained by terrestrial laser scanner. The first step is the automated determination of exterior orientation parameters of digital image. We have to find the corresponding points of the image and point cloud to provide this operation. Before the corresponding points searching quasi image of point cloud is generated. After that SIFT algorithm is applied to quasi image and real image. SIFT algorithm allows to find corresponding points. Exterior orientation parameters of image are calculated from corresponding points. The second step is construction of the vector object model. Vectorization is performed by operator of PC in an interactive mode using single image. Spatial coordinates of the model are calculated automatically by cloud points. In addition, there is automatic edge detection with interactive editing available. Edge detection is performed on point cloud and on image with subsequent identification of correct edges. Experimental studies of the method have demonstrated its efficiency in case of building facade modeling.

  19. The Imagery–Image Duality Model

    DEFF Research Database (Denmark)

    Josiassen, Alexander; Woo, Linda; Kock, Florian

    2016-01-01

    A central research topic in tourism management concerns tourists’ choice of specific destinations. The present article reviews and advances the extant literature on destination image. From this review, we suggest that individuals have a multitude of destination associations, the total imagery...... the literature. The article further provides an extensive review of the literature with regard to the definitions, dimensionality, antecedents, and outcomes of the focal concepts as well as geographical scope of destination imagery and image studies and methodologies. This review has led to a novel understanding...

  20. Fuzzy object models for newborn brain MR image segmentation

    Science.gov (United States)

    Kobashi, Syoji; Udupa, Jayaram K.

    2013-03-01

    Newborn brain MR image segmentation is a challenging problem because of variety of size, shape and MR signal although it is the fundamental study for quantitative radiology in brain MR images. Because of the large difference between the adult brain and the newborn brain, it is difficult to directly apply the conventional methods for the newborn brain. Inspired by the original fuzzy object model introduced by Udupa et al. at SPIE Medical Imaging 2011, called fuzzy shape object model (FSOM) here, this paper introduces fuzzy intensity object model (FIOM), and proposes a new image segmentation method which combines the FSOM and FIOM into fuzzy connected (FC) image segmentation. The fuzzy object models are built from training datasets in which the cerebral parenchyma is delineated by experts. After registering FSOM with the evaluating image, the proposed method roughly recognizes the cerebral parenchyma region based on a prior knowledge of location, shape, and the MR signal given by the registered FSOM and FIOM. Then, FC image segmentation delineates the cerebral parenchyma using the fuzzy object models. The proposed method has been evaluated using 9 newborn brain MR images using the leave-one-out strategy. The revised age was between -1 and 2 months. Quantitative evaluation using false positive volume fraction (FPVF) and false negative volume fraction (FNVF) has been conducted. Using the evaluation data, a FPVF of 0.75% and FNVF of 3.75% were achieved. More data collection and testing are underway.

  1. Fuzzy modeling of electrical impedance tomography images of the lungs

    International Nuclear Information System (INIS)

    Tanaka, Harki; Ortega, Neli Regina Siqueira; Galizia, Mauricio Stanzione; Borges, Joao Batista; Amato, Marcelo Britto Passos

    2008-01-01

    Objectives: Aiming to improve the anatomical resolution of electrical impedance tomography images, we developed a fuzzy model based on electrical impedance tomography's high temporal resolution and on the functional pulmonary signals of perfusion and ventilation. Introduction: Electrical impedance tomography images carry information about both ventilation and perfusion. However, these images are difficult to interpret because of insufficient anatomical resolution, such that it becomes almost impossible to distinguish the heart from the lungs. Methods: Electrical impedance tomography data from an experimental animal model were collected during normal ventilation and apnoea while an injection of hypertonic saline was administered. The fuzzy model was elaborated in three parts: a modeling of the heart, the pulmonary ventilation map and the pulmonary perfusion map. Image segmentation was performed using a threshold method, and a ventilation/perfusion map was generated. Results: Electrical impedance tomography images treated by the fuzzy model were compared with the hypertonic saline injection method and computed tomography scan images, presenting good results. The average accuracy index was 0.80 when comparing the fuzzy modeled lung maps and the computed tomography scan lung mask. The average ROC curve area comparing a saline injection image and a fuzzy modeled pulmonary perfusion image was 0.77. Discussion: The innovative aspects of our work are the use of temporal information for the delineation of the heart structure and the use of two pulmonary functions for lung structure delineation. However, robustness of the method should be tested for the imaging of abnormal lung conditions. Conclusions: These results showed the adequacy of the fuzzy approach in treating the anatomical resolution uncertainties in electrical impedance tomography images. (author)

  2. Modelling of chromatic contrast for retrieval of wallpaper images

    OpenAIRE

    Gao, Xiaohong W.; Wang, Yuanlei; Qian, Yu; Gao, Alice

    2015-01-01

    Colour remains one of the key factors in presenting an object and consequently has been widely applied in retrieval of images based on their visual contents. However, a colour appearance changes with the change of viewing surroundings, the phenomenon that has not been paid attention yet while performing colour-based image retrieval. To comprehend this effect, in this paper, a chromatic contrast model, CAMcc, is developed for the application of retrieval of colour intensive images, cementing t...

  3. Reconstructing building mass models from UAV images

    KAUST Repository

    Li, Minglei; Nan, Liangliang; Smith, Neil; Wonka, Peter

    2015-01-01

    We present an automatic reconstruction pipeline for large scale urban scenes from aerial images captured by a camera mounted on an unmanned aerial vehicle. Using state-of-the-art Structure from Motion and Multi-View Stereo algorithms, we first

  4. Connections model for tomographic images reconstruction

    International Nuclear Information System (INIS)

    Rodrigues, R.G.S.; Pela, C.A.; Roque, S.F. A.C.

    1998-01-01

    This paper shows an artificial neural network with an adequately topology for tomographic image reconstruction. The associated error function is derived and the learning algorithm is make. The simulated results are presented and demonstrate the existence of a generalized solution for nets with linear activation function. (Author)

  5. Evaluation of multimodality imaging using image fusion with ultrasound tissue elasticity imaging in an experimental animal model.

    Science.gov (United States)

    Paprottka, P M; Zengel, P; Cyran, C C; Ingrisch, M; Nikolaou, K; Reiser, M F; Clevert, D A

    2014-01-01

    To evaluate the ultrasound tissue elasticity imaging by comparison to multimodality imaging using image fusion with Magnetic Resonance Imaging (MRI) and conventional grey scale imaging with additional elasticity-ultrasound in an experimental small-animal-squamous-cell carcinoma-model for the assessment of tissue morphology. Human hypopharynx carcinoma cells were subcutaneously injected into the left flank of 12 female athymic nude rats. After 10 days (SD ± 2) of subcutaneous tumor growth, sonographic grey scale including elasticity imaging and MRI measurements were performed using a high-end ultrasound system and a 3T MR. For image fusion the contrast-enhanced MRI DICOM data set was uploaded in the ultrasonic device which has a magnetic field generator, a linear array transducer (6-15 MHz) and a dedicated software package (GE Logic E9), that can detect transducers by means of a positioning system. Conventional grey scale and elasticity imaging were integrated in the image fusion examination. After successful registration and image fusion the registered MR-images were simultaneously shown with the respective ultrasound sectional plane. Data evaluation was performed using the digitally stored video sequence data sets by two experienced radiologist using a modified Tsukuba Elasticity score. The colors "red and green" are assigned for an area of soft tissue, "blue" indicates hard tissue. In all cases a successful image fusion and plan registration with MRI and ultrasound imaging including grey scale and elasticity imaging was possible. The mean tumor volume based on caliper measurements in 3 dimensions was ~323 mm3. 4/12 rats were evaluated with Score I, 5/12 rates were evaluated with Score II, 3/12 rates were evaluated with Score III. There was a close correlation in the fused MRI with existing small necrosis in the tumor. None of the scored II or III lesions was visible by conventional grey scale. The comparison of ultrasound tissue elasticity imaging enables a

  6. Modelling of classical ghost images obtained using scattered light

    International Nuclear Information System (INIS)

    Crosby, S; Castelletto, S; Aruldoss, C; Scholten, R E; Roberts, A

    2007-01-01

    The images obtained in ghost imaging with pseudo-thermal light sources are highly dependent on the spatial coherence properties of the incident light. Pseudo-thermal light is often created by reducing the coherence length of a coherent source by passing it through a turbid mixture of scattering spheres. We describe a model for simulating ghost images obtained with such partially coherent light, using a wave-transport model to calculate the influence of the scattering on initially coherent light. The model is able to predict important properties of the pseudo-thermal source, such as the coherence length and the amplitude of the residual unscattered component of the light which influence the resolution and visibility of the final ghost image. We show that the residual ballistic component introduces an additional background in the reconstructed image, and the spatial resolution obtainable depends on the size of the scattering spheres

  7. Modelling of classical ghost images obtained using scattered light

    Energy Technology Data Exchange (ETDEWEB)

    Crosby, S; Castelletto, S; Aruldoss, C; Scholten, R E; Roberts, A [School of Physics, University of Melbourne, Victoria, 3010 (Australia)

    2007-08-15

    The images obtained in ghost imaging with pseudo-thermal light sources are highly dependent on the spatial coherence properties of the incident light. Pseudo-thermal light is often created by reducing the coherence length of a coherent source by passing it through a turbid mixture of scattering spheres. We describe a model for simulating ghost images obtained with such partially coherent light, using a wave-transport model to calculate the influence of the scattering on initially coherent light. The model is able to predict important properties of the pseudo-thermal source, such as the coherence length and the amplitude of the residual unscattered component of the light which influence the resolution and visibility of the final ghost image. We show that the residual ballistic component introduces an additional background in the reconstructed image, and the spatial resolution obtainable depends on the size of the scattering spheres.

  8. Bas-Relief Modeling from Normal Images with Intuitive Styles.

    Science.gov (United States)

    Ji, Zhongping; Ma, Weiyin; Sun, Xianfang

    2014-05-01

    Traditional 3D model-based bas-relief modeling methods are often limited to model-dependent and monotonic relief styles. This paper presents a novel method for digital bas-relief modeling with intuitive style control. Given a composite normal image, the problem discussed in this paper involves generating a discontinuity-free depth field with high compression of depth data while preserving or even enhancing fine details. In our framework, several layers of normal images are composed into a single normal image. The original normal image on each layer is usually generated from 3D models or through other techniques as described in this paper. The bas-relief style is controlled by choosing a parameter and setting a targeted height for them. Bas-relief modeling and stylization are achieved simultaneously by solving a sparse linear system. Different from previous work, our method can be used to freely design bas-reliefs in normal image space instead of in object space, which makes it possible to use any popular image editing tools for bas-relief modeling. Experiments with a wide range of 3D models and scenes show that our method can effectively generate digital bas-reliefs.

  9. Digital image technology and a measurement tool in physical models

    CSIR Research Space (South Africa)

    Phelp, David

    2006-05-01

    Full Text Available Advances in digital image technology has allowed us to use accurate, but relatively cost effective technology to measure a number of varied activities in physical models. The capturing and manipulation of high resolution digital images can be used...

  10. A generalized logarithmic image processing model based on the gigavision sensor model.

    Science.gov (United States)

    Deng, Guang

    2012-03-01

    The logarithmic image processing (LIP) model is a mathematical theory providing generalized linear operations for image processing. The gigavision sensor (GVS) is a new imaging device that can be described by a statistical model. In this paper, by studying these two seemingly unrelated models, we develop a generalized LIP (GLIP) model. With the LIP model being its special case, the GLIP model not only provides new insights into the LIP model but also defines new image representations and operations for solving general image processing problems that are not necessarily related to the GVS. A new parametric LIP model is also developed. To illustrate the application of the new scalar multiplication operation, we propose an energy-preserving algorithm for tone mapping, which is a necessary step in image dehazing. By comparing with results using two state-of-the-art algorithms, we show that the new scalar multiplication operation is an effective tool for tone mapping.

  11. Monte Carlo modeling of human tooth optical coherence tomography imaging

    International Nuclear Information System (INIS)

    Shi, Boya; Meng, Zhuo; Wang, Longzhi; Liu, Tiegen

    2013-01-01

    We present a Monte Carlo model for optical coherence tomography (OCT) imaging of human tooth. The model is implemented by combining the simulation of a Gaussian beam with simulation for photon propagation in a two-layer human tooth model with non-parallel surfaces through a Monte Carlo method. The geometry and the optical parameters of the human tooth model are chosen on the basis of the experimental OCT images. The results show that the simulated OCT images are qualitatively consistent with the experimental ones. Using the model, we demonstrate the following: firstly, two types of photons contribute to the information of morphological features and noise in the OCT image of a human tooth, respectively. Secondly, the critical imaging depth of the tooth model is obtained, and it is found to decrease significantly with increasing mineral loss, simulated as different enamel scattering coefficients. Finally, the best focus position is located below and close to the dental surface by analysis of the effect of focus positions on the OCT signal and critical imaging depth. We anticipate that this modeling will become a powerful and accurate tool for a preliminary numerical study of the OCT technique on diseases of dental hard tissue in human teeth. (paper)

  12. Cardiovascular Imaging: What Have We Learned From Animal Models?

    Directory of Open Access Journals (Sweden)

    Arnoldo eSantos

    2015-10-01

    Full Text Available Cardiovascular imaging has become an indispensable tool for patient diagnosis and follow up. Probably the wide clinical applications of imaging are due to the possibility of a detailed and high quality description and quantification of cardiovascular system structure and function. Also phenomena that involve complex physiological mechanisms and biochemical pathways, such as inflammation and ischemia, can be visualized in a nondestructive way. The widespread use and evolution of imaging would not have been possible without animal studies. Animal models have allowed for instance, i the technical development of different imaging tools, ii to test hypothesis generated from human studies and finally, iii to evaluate the translational relevance assessment of in vitro and ex-vivo results. In this review, we will critically describe the contribution of animal models to the use of biomedical imaging in cardiovascular medicine. We will discuss the characteristics of the most frequent models used in/for imaging studies. We will cover the major findings of animal studies focused in the cardiovascular use of the repeatedly used imaging techniques in clinical practice and experimental studies. We will also describe the physiological findings and/or learning processes for imaging applications coming from models of the most common cardiovascular diseases. In these diseases, imaging research using animals has allowed the study of aspects such as: ventricular size, shape, global function and wall thickening, local myocardial function, myocardial perfusion, metabolism and energetic assessment, infarct quantification, vascular lesion characterization, myocardial fiber structure, and myocardial calcium uptake. Finally we will discuss the limitations and future of imaging research with animal models.

  13. Human visual modeling and image deconvolution by linear filtering

    International Nuclear Information System (INIS)

    Larminat, P. de; Barba, D.; Gerber, R.; Ronsin, J.

    1978-01-01

    The problem is the numerical restoration of images degraded by passing through a known and spatially invariant linear system, and by the addition of a stationary noise. We propose an improvement of the Wiener's filter to allow the restoration of such images. This improvement allows to reduce the important drawbacks of classical Wiener's filter: the voluminous data processing, the lack of consideration of the vision's characteristivs which condition the perception by the observer of the restored image. In a first paragraph, we describe the structure of the visual detection system and a modelling method of this system. In the second paragraph we explain a restoration method by Wiener filtering that takes the visual properties into account and that can be adapted to the local properties of the image. Then the results obtained on TV images or scintigrams (images obtained by a gamma-camera) are commented [fr

  14. Image-Based Geometric Modeling and Mesh Generation

    CERN Document Server

    2013-01-01

    As a new interdisciplinary research area, “image-based geometric modeling and mesh generation” integrates image processing, geometric modeling and mesh generation with finite element method (FEM) to solve problems in computational biomedicine, materials sciences and engineering. It is well known that FEM is currently well-developed and efficient, but mesh generation for complex geometries (e.g., the human body) still takes about 80% of the total analysis time and is the major obstacle to reduce the total computation time. It is mainly because none of the traditional approaches is sufficient to effectively construct finite element meshes for arbitrarily complicated domains, and generally a great deal of manual interaction is involved in mesh generation. This contributed volume, the first for such an interdisciplinary topic, collects the latest research by experts in this area. These papers cover a broad range of topics, including medical imaging, image alignment and segmentation, image-to-mesh conversion,...

  15. Validation of Diagnostic Imaging Based on Repeat Examinations. An Image Interpretation Model

    International Nuclear Information System (INIS)

    Isberg, B.; Jorulf, H.; Thorstensen, Oe.

    2004-01-01

    Purpose: To develop an interpretation model, based on repeatedly acquired images, aimed at improving assessments of technical efficacy and diagnostic accuracy in the detection of small lesions. Material and Methods: A theoretical model is proposed. The studied population consists of subjects that develop focal lesions which increase in size in organs of interest during the study period. The imaging modality produces images that can be re-interpreted with high precision, e.g. conventional radiography, computed tomography, and magnetic resonance imaging. At least four repeat examinations are carried out. Results: The interpretation is performed in four or five steps: 1. Independent readers interpret the examinations chronologically without access to previous or subsequent films. 2. Lesions found on images at the last examination are included in the analysis, with interpretation in consensus. 3. By concurrent back-reading in consensus, the lesions are identified on previous images until they are so small that even in retrospect they are undetectable. The earliest examination at which included lesions appear is recorded, and the lesions are verified by their growth (imaging reference standard). Lesion size and other characteristics may be recorded. 4. Records made at step 1 are corrected to those of steps 2 and 3. False positives are recorded. 5. (Optional) Lesion type is confirmed by another diagnostic test. Conclusion: Applied on subjects with progressive disease, the proposed image interpretation model may improve assessments of technical efficacy and diagnostic accuracy in the detection of small focal lesions. The model may provide an accurate imaging reference standard as well as repeated detection rates and false-positive rates for tested imaging modalities. However, potential review bias necessitates a strict protocol

  16. Gallbladder shape extraction from ultrasound images using active contour models.

    Science.gov (United States)

    Ciecholewski, Marcin; Chochołowicz, Jakub

    2013-12-01

    Gallbladder function is routinely assessed using ultrasonographic (USG) examinations. In clinical practice, doctors very often analyse the gallbladder shape when diagnosing selected disorders, e.g. if there are turns or folds of the gallbladder, so extracting its shape from USG images using supporting software can simplify a diagnosis that is often difficult to make. The paper describes two active contour models: the edge-based model and the region-based model making use of a morphological approach, both designed for extracting the gallbladder shape from USG images. The active contour models were applied to USG images without lesions and to those showing specific disease units, namely, anatomical changes like folds and turns of the gallbladder as well as polyps and gallstones. This paper also presents modifications of the edge-based model, such as the method for removing self-crossings and loops or the method of dampening the inflation force which moves nodes if they approach the edge being determined. The user is also able to add a fragment of the approximated edge beyond which neither active contour model will move if this edge is incomplete in the USG image. The modifications of the edge-based model presented here allow more precise results to be obtained when extracting the shape of the gallbladder from USG images than if the morphological model is used. © 2013 Elsevier Ltd. Published by Elsevier Ltd. All rights reserved.

  17. Filtering adult image content with topic models

    OpenAIRE

    Lienhart, Rainer (Prof. Dr.); Hauke, Rudolf

    2009-01-01

    Protecting children from exposure to adult content has become a serious problem in the real world. Current statistics show that, for instance, the average age of first Internet exposure to pornography is 11 years, that the largest consumer group of Internet pornography is the age group of 12-to-17-year-olds and that 90% of the 8-to-16-year-olds have viewed porn online. To protect our children, effective algorithms for detecting adult images are needed. In this research we evaluate the use of ...

  18. Kinetic modeling in PET imaging of hypoxia

    DEFF Research Database (Denmark)

    Li, Fan; Jørgensen, Jesper Tranekjær; Hansen, Anders E

    2014-01-01

    be used for non-invasive mapping of tissue oxygenation in vivo and several hypoxia specific PET tracers have been developed. Evaluation of PET data in the clinic is commonly based on visual assessment together with semiquantitative measurements e.g. standard uptake value (SUV). However, dynamic PET......Tumor hypoxia is associated with increased therapeutic resistance leading to poor treatment outcome. Therefore the ability to detect and quantify intratumoral oxygenation could play an important role in future individual personalized treatment strategies. Positron Emission Tomography (PET) can...... analysis for PET imaging of hypoxia....

  19. Modelling Strategies for Functional Magnetic Resonance Imaging

    DEFF Research Database (Denmark)

    Madsen, Kristoffer Hougaard

    2009-01-01

    and generalisations to higher order arrays are considered. Additionally, an application of the natural conjugate prior for supervised learning in the general linear model to efficiently incorporate prior information for supervised analysis is presented. Further extensions include methods to model nuisance effects...... in fMIR data thereby suppressing noise for both supervised and unsupervised analysis techniques....

  20. The Research of Optical Turbulence Model in Underwater Imaging System

    Directory of Open Access Journals (Sweden)

    Liying Sun

    2014-01-01

    Full Text Available In order to research the effect of turbulence on underwater imaging system and image restoration, the underwater turbulence model is simulated by computer fluid dynamics. This model is obtained in different underwater turbulence intensity, which contains the pressure data that influences refractive index distribution. When the pressure value is conversed to refractive index, the refractive index distribution can be received with the refraction formula. In the condition of same turbulent intensity, the distribution of refractive index presents gradient in the whole region, with disorder and mutations in the local region. With the turbulence intensity increase, the holistic variation of the refractive index in the image is larger, and the refractive index change more tempestuously in the local region. All the above are illustrated by the simulation results with he ray tracing method and turbulent refractive index model. According to different turbulence intensity analysis, it is proved that turbulence causes image distortion and increases noise.

  1. Color correction with blind image restoration based on multiple images using a low-rank model

    Science.gov (United States)

    Li, Dong; Xie, Xudong; Lam, Kin-Man

    2014-03-01

    We present a method that can handle the color correction of multiple photographs with blind image restoration simultaneously and automatically. We prove that the local colors of a set of images of the same scene exhibit the low-rank property locally both before and after a color-correction operation. This property allows us to correct all kinds of errors in an image under a low-rank matrix model without particular priors or assumptions. The possible errors may be caused by changes of viewpoint, large illumination variations, gross pixel corruptions, partial occlusions, etc. Furthermore, a new iterative soft-segmentation method is proposed for local color transfer using color influence maps. Due to the fact that the correct color information and the spatial information of images can be recovered using the low-rank model, more precise color correction and many other image-restoration tasks-including image denoising, image deblurring, and gray-scale image colorizing-can be performed simultaneously. Experiments have verified that our method can achieve consistent and promising results on uncontrolled real photographs acquired from the Internet and that it outperforms current state-of-the-art methods.

  2. Superresolving Black Hole Images with Full-Closure Sparse Modeling

    Science.gov (United States)

    Crowley, Chelsea; Akiyama, Kazunori; Fish, Vincent

    2018-01-01

    It is believed that almost all galaxies have black holes at their centers. Imaging a black hole is a primary objective to answer scientific questions relating to relativistic accretion and jet formation. The Event Horizon Telescope (EHT) is set to capture images of two nearby black holes, Sagittarius A* at the center of the Milky Way galaxy roughly 26,000 light years away and the other M87 which is in Virgo A, a large elliptical galaxy that is 50 million light years away. Sparse imaging techniques have shown great promise for reconstructing high-fidelity superresolved images of black holes from simulated data. Previous work has included the effects of atmospheric phase errors and thermal noise, but not systematic amplitude errors that arise due to miscalibration. We explore a full-closure imaging technique with sparse modeling that uses closure amplitudes and closure phases to improve the imaging process. This new technique can successfully handle data with systematic amplitude errors. Applying our technique to synthetic EHT data of M87, we find that full-closure sparse modeling can reconstruct images better than traditional methods and recover key structural information on the source, such as the shape and size of the predicted photon ring. These results suggest that our new approach will provide superior imaging performance for data from the EHT and other interferometric arrays.

  3. BOREAS TE-17 Production Efficiency Model Images

    Data.gov (United States)

    National Aeronautics and Space Administration — A BOREAS version of the Global Production Efficiency Model(www.inform.umd.edu/glopem) was developed by TE-17 to generate maps of gross and net primary production,...

  4. NEPR Bathymetry Model - NOAA TIFF Image

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This GeoTiff is a bathymetry model of the seafloor of Northeast Puerto Rico that contains the shallow water area (0-35m deep) of the Northeast Ecological Reserve:...

  5. Infrared image background modeling based on improved Susan filtering

    Science.gov (United States)

    Yuehua, Xia

    2018-02-01

    When SUSAN filter is used to model the infrared image, the Gaussian filter lacks the ability of direction filtering. After filtering, the edge information of the image cannot be preserved well, so that there are a lot of edge singular points in the difference graph, increase the difficulties of target detection. To solve the above problems, the anisotropy algorithm is introduced in this paper, and the anisotropic Gauss filter is used instead of the Gauss filter in the SUSAN filter operator. Firstly, using anisotropic gradient operator to calculate a point of image's horizontal and vertical gradient, to determine the long axis direction of the filter; Secondly, use the local area of the point and the neighborhood smoothness to calculate the filter length and short axis variance; And then calculate the first-order norm of the difference between the local area of the point's gray-scale and mean, to determine the threshold of the SUSAN filter; Finally, the built SUSAN filter is used to convolution the image to obtain the background image, at the same time, the difference between the background image and the original image is obtained. The experimental results show that the background modeling effect of infrared image is evaluated by Mean Squared Error (MSE), Structural Similarity (SSIM) and local Signal-to-noise Ratio Gain (GSNR). Compared with the traditional filtering algorithm, the improved SUSAN filter has achieved better background modeling effect, which can effectively preserve the edge information in the image, and the dim small target is effectively enhanced in the difference graph, which greatly reduces the false alarm rate of the image.

  6. Cancer imaging phenomics toolkit: quantitative imaging analytics for precision diagnostics and predictive modeling of clinical outcome.

    Science.gov (United States)

    Davatzikos, Christos; Rathore, Saima; Bakas, Spyridon; Pati, Sarthak; Bergman, Mark; Kalarot, Ratheesh; Sridharan, Patmaa; Gastounioti, Aimilia; Jahani, Nariman; Cohen, Eric; Akbari, Hamed; Tunc, Birkan; Doshi, Jimit; Parker, Drew; Hsieh, Michael; Sotiras, Aristeidis; Li, Hongming; Ou, Yangming; Doot, Robert K; Bilello, Michel; Fan, Yong; Shinohara, Russell T; Yushkevich, Paul; Verma, Ragini; Kontos, Despina

    2018-01-01

    The growth of multiparametric imaging protocols has paved the way for quantitative imaging phenotypes that predict treatment response and clinical outcome, reflect underlying cancer molecular characteristics and spatiotemporal heterogeneity, and can guide personalized treatment planning. This growth has underlined the need for efficient quantitative analytics to derive high-dimensional imaging signatures of diagnostic and predictive value in this emerging era of integrated precision diagnostics. This paper presents cancer imaging phenomics toolkit (CaPTk), a new and dynamically growing software platform for analysis of radiographic images of cancer, currently focusing on brain, breast, and lung cancer. CaPTk leverages the value of quantitative imaging analytics along with machine learning to derive phenotypic imaging signatures, based on two-level functionality. First, image analysis algorithms are used to extract comprehensive panels of diverse and complementary features, such as multiparametric intensity histogram distributions, texture, shape, kinetics, connectomics, and spatial patterns. At the second level, these quantitative imaging signatures are fed into multivariate machine learning models to produce diagnostic, prognostic, and predictive biomarkers. Results from clinical studies in three areas are shown: (i) computational neuro-oncology of brain gliomas for precision diagnostics, prediction of outcome, and treatment planning; (ii) prediction of treatment response for breast and lung cancer, and (iii) risk assessment for breast cancer.

  7. EVALUATION OF RATIONAL FUNCTION MODEL FOR GEOMETRIC MODELING OF CHANG'E-1 CCD IMAGES

    Directory of Open Access Journals (Sweden)

    Y. Liu

    2012-08-01

    Full Text Available Rational Function Model (RFM is a generic geometric model that has been widely used in geometric processing of high-resolution earth-observation satellite images, due to its generality and excellent capability of fitting complex rigorous sensor models. In this paper, the feasibility and precision of RFM for geometric modeling of China's Chang'E-1 (CE-1 lunar orbiter images is presented. The RFM parameters of forward-, nadir- and backward-looking CE-1 images are generated though least squares solution using virtual control points derived from the rigorous sensor model. The precision of the RFM is evaluated by comparing with the rigorous sensor model in both image space and object space. Experimental results using nine images from three orbits show that RFM can precisely fit the rigorous sensor model of CE-1 CCD images with a RMS residual error of 1/100 pixel level in image space and less than 5 meters in object space. This indicates that it is feasible to use RFM to describe the imaging geometry of CE-1 CCD images and spacecraft position and orientation. RFM will enable planetary data centers to have an option to supply RFM parameters of orbital images while keeping the original orbit trajectory data confidential.

  8. From medical imaging data to 3D printed anatomical models.

    Directory of Open Access Journals (Sweden)

    Thore M Bücking

    Full Text Available Anatomical models are important training and teaching tools in the clinical environment and are routinely used in medical imaging research. Advances in segmentation algorithms and increased availability of three-dimensional (3D printers have made it possible to create cost-efficient patient-specific models without expert knowledge. We introduce a general workflow that can be used to convert volumetric medical imaging data (as generated by Computer Tomography (CT to 3D printed physical models. This process is broken up into three steps: image segmentation, mesh refinement and 3D printing. To lower the barrier to entry and provide the best options when aiming to 3D print an anatomical model from medical images, we provide an overview of relevant free and open-source image segmentation tools as well as 3D printing technologies. We demonstrate the utility of this streamlined workflow by creating models of ribs, liver, and lung using a Fused Deposition Modelling 3D printer.

  9. Probabilistic mixture-based image modelling

    Czech Academy of Sciences Publication Activity Database

    Haindl, Michal; Havlíček, Vojtěch; Grim, Jiří

    2011-01-01

    Roč. 47, č. 3 (2011), s. 482-500 ISSN 0023-5954 R&D Projects: GA MŠk 1M0572; GA ČR GA102/08/0593 Grant - others:CESNET(CZ) 387/2010; GA MŠk(CZ) 2C06019; GA ČR(CZ) GA103/11/0335 Institutional research plan: CEZ:AV0Z10750506 Keywords : BTF texture modelling * discrete distribution mixtures * Bernoulli mixture * Gaussian mixture * multi-spectral texture modelling Subject RIV: BD - Theory of Information Impact factor: 0.454, year: 2011 http://library.utia.cas.cz/separaty/2011/RO/haindl-0360244.pdf

  10. Projection model for flame chemiluminescence tomography based on lens imaging

    Science.gov (United States)

    Wan, Minggang; Zhuang, Jihui

    2018-04-01

    For flame chemiluminescence tomography (FCT) based on lens imaging, the projection model is essential because it formulates the mathematical relation between the flame projections captured by cameras and the chemiluminescence field, and, through this relation, the field is reconstructed. This work proposed the blurry-spot (BS) model, which takes more universal assumptions and has higher accuracy than the widely applied line-of-sight model. By combining the geometrical camera model and the thin-lens equation, the BS model takes into account perspective effect of the camera lens; by combining ray-tracing technique and Monte Carlo simulation, it also considers inhomogeneous distribution of captured radiance on the image plane. Performance of these two models in FCT was numerically compared, and results showed that using the BS model could lead to better reconstruction quality in wider application ranges.

  11. Parallel imaging enhanced MR colonography using a phantom model.

    LENUS (Irish Health Repository)

    Morrin, Martina M

    2008-09-01

    To compare various Array Spatial and Sensitivity Encoding Technique (ASSET)-enhanced T2W SSFSE (single shot fast spin echo) and T1-weighted (T1W) 3D SPGR (spoiled gradient recalled echo) sequences for polyp detection and image quality at MR colonography (MRC) in a phantom model. Limitations of MRC using standard 3D SPGR T1W imaging include the long breath-hold required to cover the entire colon within one acquisition and the relatively low spatial resolution due to the long acquisition time. Parallel imaging using ASSET-enhanced T2W SSFSE and 3D T1W SPGR imaging results in much shorter imaging times, which allows for increased spatial resolution.

  12. Generative Topic Modeling in Image Data Mining and Bioinformatics Studies

    Science.gov (United States)

    Chen, Xin

    2012-01-01

    Probabilistic topic models have been developed for applications in various domains such as text mining, information retrieval and computer vision and bioinformatics domain. In this thesis, we focus on developing novel probabilistic topic models for image mining and bioinformatics studies. Specifically, a probabilistic topic-connection (PTC) model…

  13. Use of a model for 3D image reconstruction

    International Nuclear Information System (INIS)

    Delageniere, S.; Grangeat, P.

    1991-01-01

    We propose a software for 3D image reconstruction in transmission tomography. This software is based on the use of a model and of the RADON algorithm developed at LETI. The introduction of a markovian model helps us to enhance contrast and straitened the natural transitions existing in the objects studied, whereas standard transform methods smoothe them

  14. Supervised Gaussian mixture model based remote sensing image ...

    African Journals Online (AJOL)

    Using the supervised classification technique, both simulated and empirical satellite remote sensing data are used to train and test the Gaussian mixture model algorithm. For the purpose of validating the experiment, the resulting classified satellite image is compared with the ground truth data. For the simulated modelling, ...

  15. On use of image quality metrics for perceptual blur modeling: image/video compression case

    Science.gov (United States)

    Cha, Jae H.; Olson, Jeffrey T.; Preece, Bradley L.; Espinola, Richard L.; Abbott, A. Lynn

    2018-02-01

    Linear system theory is employed to make target acquisition performance predictions for electro-optical/infrared imaging systems where the modulation transfer function (MTF) may be imposed from a nonlinear degradation process. Previous research relying on image quality metrics (IQM) methods, which heuristically estimate perceived MTF has supported that an average perceived MTF can be used to model some types of degradation such as image compression. Here, we discuss the validity of the IQM approach by mathematically analyzing the associated heuristics from the perspective of reliability, robustness, and tractability. Experiments with standard images compressed by x.264 encoding suggest that the compression degradation can be estimated by a perceived MTF within boundaries defined by well-behaved curves with marginal error. Our results confirm that the IQM linearizer methodology provides a credible tool for sensor performance modeling.

  16. IMAGE ANALYSIS FOR MODELLING SHEAR BEHAVIOUR

    Directory of Open Access Journals (Sweden)

    Philippe Lopez

    2011-05-01

    Full Text Available Through laboratory research performed over the past ten years, many of the critical links between fracture characteristics and hydromechanical and mechanical behaviour have been made for individual fractures. One of the remaining challenges at the laboratory scale is to directly link fracture morphology of shear behaviour with changes in stress and shear direction. A series of laboratory experiments were performed on cement mortar replicas of a granite sample with a natural fracture perpendicular to the axis of the core. Results show that there is a strong relationship between the fracture's geometry and its mechanical behaviour under shear stress and the resulting damage. Image analysis, geostatistical, stereological and directional data techniques are applied in combination to experimental data. The results highlight the role of geometric characteristics of the fracture surfaces (surface roughness, size, shape, locations and orientations of asperities to be damaged in shear behaviour. A notable improvement in shear understanding is that shear behaviour is controlled by the apparent dip in the shear direction of elementary facets forming the fracture.

  17. Discrete gradient methods for solving variational image regularisation models

    International Nuclear Information System (INIS)

    Grimm, V; McLachlan, Robert I; McLaren, David I; Quispel, G R W; Schönlieb, C-B

    2017-01-01

    Discrete gradient methods are well-known methods of geometric numerical integration, which preserve the dissipation of gradient systems. In this paper we show that this property of discrete gradient methods can be interesting in the context of variational models for image processing, that is where the processed image is computed as a minimiser of an energy functional. Numerical schemes for computing minimisers of such energies are desired to inherit the dissipative property of the gradient system associated to the energy and consequently guarantee a monotonic decrease of the energy along iterations, avoiding situations in which more computational work might lead to less optimal solutions. Under appropriate smoothness assumptions on the energy functional we prove that discrete gradient methods guarantee a monotonic decrease of the energy towards stationary states, and we promote their use in image processing by exhibiting experiments with convex and non-convex variational models for image deblurring, denoising, and inpainting. (paper)

  18. Efficient image duplicated region detection model using sequential block clustering

    Czech Academy of Sciences Publication Activity Database

    Sekeh, M. A.; Maarof, M. A.; Rohani, M. F.; Mahdian, Babak

    2013-01-01

    Roč. 10, č. 1 (2013), s. 73-84 ISSN 1742-2876 Institutional support: RVO:67985556 Keywords : Image forensic * Copy–paste forgery * Local block matching Subject RIV: IN - Informatics, Computer Science Impact factor: 0.986, year: 2013 http://library.utia.cas.cz/separaty/2013/ZOI/mahdian-efficient image duplicated region detection model using sequential block clustering.pdf

  19. Modeling the National Ignition Facility neutron imaging system.

    Science.gov (United States)

    Wilson, D C; Grim, G P; Tregillis, I L; Wilke, M D; Patel, M V; Sepke, S M; Morgan, G L; Hatarik, R; Loomis, E N; Wilde, C H; Oertel, J A; Fatherley, V E; Clark, D D; Fittinghoff, D N; Bower, D E; Schmitt, M J; Marinak, M M; Munro, D H; Merrill, F E; Moran, M J; Wang, T-S F; Danly, C R; Hilko, R A; Batha, S H; Frank, M; Buckles, R

    2010-10-01

    Numerical modeling of the neutron imaging system for the National Ignition Facility (NIF), forward from calculated target neutron emission to a camera image, will guide both the reduction of data and the future development of the system. Located 28 m from target chamber center, the system can produce two images at different neutron energies by gating on neutron arrival time. The brighter image, using neutrons near 14 MeV, reflects the size and symmetry of the implosion "hot spot." A second image in scattered neutrons, 10-12 MeV, reflects the size and symmetry of colder, denser fuel, but with only ∼1%-7% of the neutrons. A misalignment of the pinhole assembly up to ±175 μm is covered by a set of 37 subapertures with different pointings. The model includes the variability of the pinhole point spread function across the field of view. Omega experiments provided absolute calibration, scintillator spatial broadening, and the level of residual light in the down-scattered image from the primary neutrons. Application of the model to light decay measurements of EJ399, BC422, BCF99-55, Xylene, DPAC-30, and Liquid A suggests that DPAC-30 and Liquid A would be preferred over the BCF99-55 scintillator chosen for the first NIF system, if they could be fabricated into detectors with sufficient resolution.

  20. Image based Monte Carlo modeling for computational phantom

    International Nuclear Information System (INIS)

    Cheng, M.; Wang, W.; Zhao, K.; Fan, Y.; Long, P.; Wu, Y.

    2013-01-01

    Full text of the publication follows. The evaluation on the effects of ionizing radiation and the risk of radiation exposure on human body has been becoming one of the most important issues for radiation protection and radiotherapy fields, which is helpful to avoid unnecessary radiation and decrease harm to human body. In order to accurately evaluate the dose on human body, it is necessary to construct more realistic computational phantom. However, manual description and verification of the models for Monte Carlo (MC) simulation are very tedious, error-prone and time-consuming. In addition, it is difficult to locate and fix the geometry error, and difficult to describe material information and assign it to cells. MCAM (CAD/Image-based Automatic Modeling Program for Neutronics and Radiation Transport Simulation) was developed as an interface program to achieve both CAD- and image-based automatic modeling. The advanced version (Version 6) of MCAM can achieve automatic conversion from CT/segmented sectioned images to computational phantoms such as MCNP models. Imaged-based automatic modeling program(MCAM6.0) has been tested by several medical images and sectioned images. And it has been applied in the construction of Rad-HUMAN. Following manual segmentation and 3D reconstruction, a whole-body computational phantom of Chinese adult female called Rad-HUMAN was created by using MCAM6.0 from sectioned images of a Chinese visible human dataset. Rad-HUMAN contains 46 organs/tissues, which faithfully represented the average anatomical characteristics of the Chinese female. The dose conversion coefficients (Dt/Ka) from kerma free-in-air to absorbed dose of Rad-HUMAN were calculated. Rad-HUMAN can be applied to predict and evaluate dose distributions in the Treatment Plan System (TPS), as well as radiation exposure for human body in radiation protection. (authors)

  1. Image based 3D city modeling : Comparative study

    Directory of Open Access Journals (Sweden)

    S. P. Singh

    2014-06-01

    Full Text Available 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

  2. Gallbladder Boundary Segmentation from Ultrasound Images Using Active Contour Model

    Science.gov (United States)

    Ciecholewski, Marcin

    Extracting the shape of the gallbladder from an ultrasonography (US) image allows superfluous information which is immaterial in the diagnostic process to be eliminated. In this project an active contour model was used to extract the shape of the gallbladder, both for cases free of lesions, and for those showing specific disease units, namely: lithiasis, polyps and changes in the shape of the organ, such as folds or turns of the gallbladder. The approximate shape of the gallbladder was found by applying the motion equation model. The tests conducted have shown that for the 220 US images of the gallbladder, the area error rate (AER) amounted to 18.15%.

  3. Photometric Modeling of Simulated Surace-Resolved Bennu Images

    Science.gov (United States)

    Golish, D.; DellaGiustina, D. N.; Clark, B.; Li, J. Y.; Zou, X. D.; Bennett, C. A.; Lauretta, D. S.

    2017-12-01

    The Origins, Spectral Interpretation, Resource Identification, Security, Regolith Explorer (OSIRIS-REx) is a NASA mission to study and return a sample of asteroid (101955) Bennu. Imaging data from the mission will be used to develop empirical surface-resolved photometric models of Bennu at a series of wavelengths. These models will be used to photometrically correct panchromatic and color base maps of Bennu, compensating for variations due to shadows and photometric angle differences, thereby minimizing seams in mosaicked images. Well-corrected mosaics are critical to the generation of a global hazard map and a global 1064-nm reflectance map which predicts LIDAR response. These data products directly feed into the selection of a site from which to safely acquire a sample. We also require photometric correction for the creation of color ratio maps of Bennu. Color ratios maps provide insight into the composition and geological history of the surface and allow for comparison to other Solar System small bodies. In advance of OSIRIS-REx's arrival at Bennu, we use simulated images to judge the efficacy of both the photometric modeling software and the mission observation plan. Our simulation software is based on USGS's Integrated Software for Imagers and Spectrometers (ISIS) and uses a synthetic shape model, a camera model, and an empirical photometric model to generate simulated images. This approach gives us the flexibility to create simulated images of Bennu based on analog surfaces from other small Solar System bodies and to test our modeling software under those conditions. Our photometric modeling software fits image data to several conventional empirical photometric models and produces the best fit model parameters. The process is largely automated, which is crucial to the efficient production of data products during proximity operations. The software also produces several metrics on the quality of the observations themselves, such as surface coverage and the

  4. Modeling digital breast tomosynthesis imaging systems for optimization studies

    Science.gov (United States)

    Lau, Beverly Amy

    Digital breast tomosynthesis (DBT) is a new imaging modality for breast imaging. In tomosynthesis, multiple images of the compressed breast are acquired at different angles, and the projection view images are reconstructed to yield images of slices through the breast. One of the main problems to be addressed in the development of DBT is the optimal parameter settings to obtain images ideal for detection of cancer. Since it would be unethical to irradiate women multiple times to explore potentially optimum geometries for tomosynthesis, it is ideal to use a computer simulation to generate projection images. Existing tomosynthesis models have modeled scatter and detector without accounting for oblique angles of incidence that tomosynthesis introduces. Moreover, these models frequently use geometry-specific physical factors measured from real systems, which severely limits the robustness of their algorithms for optimization. The goal of this dissertation was to design the framework for a computer simulation of tomosynthesis that would produce images that are sensitive to changes in acquisition parameters, so an optimization study would be feasible. A computer physics simulation of the tomosynthesis system was developed. The x-ray source was modeled as a polychromatic spectrum based on published spectral data, and inverse-square law was applied. Scatter was applied using a convolution method with angle-dependent scatter point spread functions (sPSFs), followed by scaling using an angle-dependent scatter-to-primary ratio (SPR). Monte Carlo simulations were used to generate sPSFs for a 5-cm breast with a 1-cm air gap. Detector effects were included through geometric propagation of the image onto layers of the detector, which were blurred using depth-dependent detector point-spread functions (PRFs). Depth-dependent PRFs were calculated every 5-microns through a 200-micron thick CsI detector using Monte Carlo simulations. Electronic noise was added as Gaussian noise as a

  5. Model-Based Referenceless Quality Metric of 3D Synthesized Images Using Local Image Description.

    Science.gov (United States)

    Gu, Ke; Jakhetiya, Vinit; Qiao, Jun-Fei; Li, Xiaoli; Lin, Weisi; Thalmann, Daniel

    2017-07-28

    New challenges have been brought out along with the emerging of 3D-related technologies such as virtual reality (VR), augmented reality (AR), and mixed reality (MR). Free viewpoint video (FVV), due to its applications in remote surveillance, remote education, etc, based on the flexible selection of direction and viewpoint, has been perceived as the development direction of next-generation video technologies and has drawn a wide range of researchers' attention. Since FVV images are synthesized via a depth image-based rendering (DIBR) procedure in the "blind" environment (without reference images), a reliable real-time blind quality evaluation and monitoring system is urgently required. But existing assessment metrics do not render human judgments faithfully mainly because geometric distortions are generated by DIBR. To this end, this paper proposes a novel referenceless quality metric of DIBR-synthesized images using the autoregression (AR)-based local image description. It was found that, after the AR prediction, the reconstructed error between a DIBR-synthesized image and its AR-predicted image can accurately capture the geometry distortion. The visual saliency is then leveraged to modify the proposed blind quality metric to a sizable margin. Experiments validate the superiority of our no-reference quality method as compared with prevailing full-, reduced- and no-reference models.

  6. Software to model AXAF image quality

    Science.gov (United States)

    Ahmad, Anees

    1993-01-01

    This draft final report describes the work performed under this delivery order from May 1992 through June 1993. The purpose of this contract was to enhance and develop an integrated optical performance modeling software for complex x-ray optical systems such as AXAF. The GRAZTRACE program developed by the MSFC Optical Systems Branch for modeling VETA-I was used as the starting baseline program. The original program was a large single file program and, therefore, could not be modified very efficiently. The original source code has been reorganized, and a 'Make Utility' has been written to update the original program. The new version of the source code consists of 36 small source files to make it easier for the code developer to manage and modify the program. A user library has also been built and a 'Makelib' utility has been furnished to update the library. With the user library, the users can easily access the GRAZTRACE source files and build a custom library. A user manual for the new version of GRAZTRACE has been compiled. The plotting capability for the 3-D point spread functions and contour plots has been provided in the GRAZTRACE using the graphics package DISPLAY. The Graphics emulator over the network has been set up for programming the graphics routine. The point spread function and the contour plot routines have also been modified to display the plot centroid, and to allow the user to specify the plot range, and the viewing angle options. A Command Mode version of GRAZTRACE has also been developed. More than 60 commands have been implemented in a Code-V like format. The functions covered in this version include data manipulation, performance evaluation, and inquiry and setting of internal parameters. The user manual for these commands has been formatted as in Code-V, showing the command syntax, synopsis, and options. An interactive on-line help system for the command mode has also been accomplished to allow the user to find valid commands, command syntax

  7. Image contrast enhancement based on a local standard deviation model

    International Nuclear Information System (INIS)

    Chang, Dah-Chung; Wu, Wen-Rong

    1996-01-01

    The adaptive contrast enhancement (ACE) algorithm is a widely used image enhancement method, which needs a contrast gain to adjust high frequency components of an image. In the literature, the gain is usually inversely proportional to the local standard deviation (LSD) or is a constant. But these cause two problems in practical applications, i.e., noise overenhancement and ringing artifact. In this paper a new gain is developed based on Hunt's Gaussian image model to prevent the two defects. The new gain is a nonlinear function of LSD and has the desired characteristic emphasizing the LSD regions in which details are concentrated. We have applied the new ACE algorithm to chest x-ray images and the simulations show the effectiveness of the proposed algorithm

  8. Computational model of lightness perception in high dynamic range imaging

    Science.gov (United States)

    Krawczyk, Grzegorz; Myszkowski, Karol; Seidel, Hans-Peter

    2006-02-01

    An anchoring theory of lightness perception by Gilchrist et al. [1999] explains many characteristics of human visual system such as lightness constancy and its spectacular failures which are important in the perception of images. The principal concept of this theory is the perception of complex scenes in terms of groups of consistent areas (frameworks). Such areas, following the gestalt theorists, are defined by the regions of common illumination. The key aspect of the image perception is the estimation of lightness within each framework through the anchoring to the luminance perceived as white, followed by the computation of the global lightness. In this paper we provide a computational model for automatic decomposition of HDR images into frameworks. We derive a tone mapping operator which predicts lightness perception of the real world scenes and aims at its accurate reproduction on low dynamic range displays. Furthermore, such a decomposition into frameworks opens new grounds for local image analysis in view of human perception.

  9. Image decomposition as a tool for validating stress analysis models

    Directory of Open Access Journals (Sweden)

    Mottershead J.

    2010-06-01

    Full Text Available It is good practice to validate analytical and numerical models used in stress analysis for engineering design by comparison with measurements obtained from real components either in-service or in the laboratory. In reality, this critical step is often neglected or reduced to placing a single strain gage at the predicted hot-spot of stress. Modern techniques of optical analysis allow full-field maps of displacement, strain and, or stress to be obtained from real components with relative ease and at modest cost. However, validations continued to be performed only at predicted and, or observed hot-spots and most of the wealth of data is ignored. It is proposed that image decomposition methods, commonly employed in techniques such as fingerprinting and iris recognition, can be employed to validate stress analysis models by comparing all of the key features in the data from the experiment and the model. Image decomposition techniques such as Zernike moments and Fourier transforms have been used to decompose full-field distributions for strain generated from optical techniques such as digital image correlation and thermoelastic stress analysis as well as from analytical and numerical models by treating the strain distributions as images. The result of the decomposition is 101 to 102 image descriptors instead of the 105 or 106 pixels in the original data. As a consequence, it is relatively easy to make a statistical comparison of the image descriptors from the experiment and from the analytical/numerical model and to provide a quantitative assessment of the stress analysis.

  10. Functional Brain Imaging Synthesis Based on Image Decomposition and Kernel Modeling: Application to Neurodegenerative Diseases

    Directory of Open Access Journals (Sweden)

    Francisco J. Martinez-Murcia

    2017-11-01

    Full Text Available The rise of neuroimaging in research and clinical practice, together with the development of new machine learning techniques has strongly encouraged the Computer Aided Diagnosis (CAD of different diseases and disorders. However, these algorithms are often tested in proprietary datasets to which the access is limited and, therefore, a direct comparison between CAD procedures is not possible. Furthermore, the sample size is often small for developing accurate machine learning methods. Multi-center initiatives are currently a very useful, although limited, tool in the recruitment of large populations and standardization of CAD evaluation. Conversely, we propose a brain image synthesis procedure intended to generate a new image set that share characteristics with an original one. Our system focuses on nuclear imaging modalities such as PET or SPECT brain images. We analyze the dataset by applying PCA to the original dataset, and then model the distribution of samples in the projected eigenbrain space using a Probability Density Function (PDF estimator. Once the model has been built, we can generate new coordinates on the eigenbrain space belonging to the same class, which can be then projected back to the image space. The system has been evaluated on different functional neuroimaging datasets assessing the: resemblance of the synthetic images with the original ones, the differences between them, their generalization ability and the independence of the synthetic dataset with respect to the original. The synthetic images maintain the differences between groups found at the original dataset, with no significant differences when comparing them to real-world samples. Furthermore, they featured a similar performance and generalization capability to that of the original dataset. These results prove that these images are suitable for standardizing the evaluation of CAD pipelines, and providing data augmentation in machine learning systems -e.g. in deep

  11. Comprehensive fluence model for absolute portal dose image prediction

    International Nuclear Information System (INIS)

    Chytyk, K.; McCurdy, B. M. C.

    2009-01-01

    Amorphous silicon (a-Si) electronic portal imaging devices (EPIDs) continue to be investigated as treatment verification tools, with a particular focus on intensity modulated radiation therapy (IMRT). This verification could be accomplished through a comparison of measured portal images to predicted portal dose images. A general fluence determination tailored to portal dose image prediction would be a great asset in order to model the complex modulation of IMRT. A proposed physics-based parameter fluence model was commissioned by matching predicted EPID images to corresponding measured EPID images of multileaf collimator (MLC) defined fields. The two-source fluence model was composed of a focal Gaussian and an extrafocal Gaussian-like source. Specific aspects of the MLC and secondary collimators were also modeled (e.g., jaw and MLC transmission factors, MLC rounded leaf tips, tongue and groove effect, interleaf leakage, and leaf offsets). Several unique aspects of the model were developed based on the results of detailed Monte Carlo simulations of the linear accelerator including (1) use of a non-Gaussian extrafocal fluence source function, (2) separate energy spectra used for focal and extrafocal fluence, and (3) different off-axis energy spectra softening used for focal and extrafocal fluences. The predicted energy fluence was then convolved with Monte Carlo generated, EPID-specific dose kernels to convert incident fluence to dose delivered to the EPID. Measured EPID data were obtained with an a-Si EPID for various MLC-defined fields (from 1x1 to 20x20 cm 2 ) over a range of source-to-detector distances. These measured profiles were used to determine the fluence model parameters in a process analogous to the commissioning of a treatment planning system. The resulting model was tested on 20 clinical IMRT plans, including ten prostate and ten oropharyngeal cases. The model predicted the open-field profiles within 2%, 2 mm, while a mean of 96.6% of pixels over all

  12. Modeling human faces with multi-image photogrammetry

    Science.gov (United States)

    D'Apuzzo, Nicola

    2002-03-01

    Modeling and measurement of the human face have been increasing by importance for various purposes. Laser scanning, coded light range digitizers, image-based approaches and digital stereo photogrammetry are the used methods currently employed in medical applications, computer animation, video surveillance, teleconferencing and virtual reality to produce three dimensional computer models of the human face. Depending on the application, different are the requirements. Ours are primarily high accuracy of the measurement and automation in the process. The method presented in this paper is based on multi-image photogrammetry. The equipment, the method and results achieved with this technique are here depicted. The process is composed of five steps: acquisition of multi-images, calibration of the system, establishment of corresponding points in the images, computation of their 3-D coordinates and generation of a surface model. The images captured by five CCD cameras arranged in front of the subject are digitized by a frame grabber. The complete system is calibrated using a reference object with coded target points, which can be measured fully automatically. To facilitate the establishment of correspondences in the images, texture in the form of random patterns can be projected from two directions onto the face. The multi-image matching process, based on a geometrical constrained least squares matching algorithm, produces a dense set of corresponding points in the five images. Neighborhood filters are then applied on the matching results to remove the errors. After filtering the data, the three-dimensional coordinates of the matched points are computed by forward intersection using the results of the calibration process; the achieved mean accuracy is about 0.2 mm in the sagittal direction and about 0.1 mm in the lateral direction. The last step of data processing is the generation of a surface model from the point cloud and the application of smooth filters. Moreover, a

  13. Modelling of microcracks image treated with fluorescent dye

    Science.gov (United States)

    Glebov, Victor; Lashmanov, Oleg U.

    2015-06-01

    The main reasons of catastrophes and accidents are high level of wear of equipment and violation of the production technology. The methods of nondestructive testing are designed to find out defects timely and to prevent break down of aggregates. These methods allow determining compliance of object parameters with technical requirements without destroying it. This work will discuss dye penetrant inspection or liquid penetrant inspection (DPI or LPI) methods and computer model of microcracks image treated with fluorescent dye. Usually cracks on image look like broken extended lines with small width (about 1 to 10 pixels) and ragged edges. The used method of inspection allows to detect microcracks with depth about 10 or more micrometers. During the work the mathematical model of image of randomly located microcracks treated with fluorescent dye was created in MATLAB environment. Background noises and distortions introduced by the optical systems are considered in the model. The factors that have influence on the image are listed below: 1. Background noise. Background noise is caused by the bright light from external sources and it reduces contrast on the objects edges. 2. Noises on the image sensor. Digital noise manifests itself in the form of randomly located points that are differing in their brightness and color. 3. Distortions caused by aberrations of optical system. After passing through the real optical system the homocentricity of the bundle of rays is violated or homocentricity remains but rays intersect at the point that doesn't coincide with the point of the ideal image. The stronger the influence of the above-listed factors, the worse the image quality and therefore the analysis of the image for control of the item finds difficulty. The mathematical model is created using the following algorithm: at the beginning the number of cracks that will be modeled is entered from keyboard. Then the point with random position is choosing on the matrix whose size is

  14. Image-Based 3D Face Modeling System

    Directory of Open Access Journals (Sweden)

    Vladimir Vezhnevets

    2005-08-01

    Full Text Available This paper describes an automatic system for 3D face modeling using frontal and profile images taken by an ordinary digital camera. The system consists of four subsystems including frontal feature detection, profile feature detection, shape deformation, and texture generation modules. The frontal and profile feature detection modules automatically extract the facial parts such as the eye, nose, mouth, and ear. The shape deformation module utilizes the detected features to deform the generic head mesh model such that the deformed model coincides with the detected features. A texture is created by combining the facial textures augmented from the input images and the synthesized texture and mapped onto the deformed generic head model. This paper provides a practical system for 3D face modeling, which is highly automated by aggregating, customizing, and optimizing a bunch of individual computer vision algorithms. The experimental results show a highly automated process of modeling, which is sufficiently robust to various imaging conditions. The whole model creation including all the optional manual corrections takes only 2∼3 minutes.

  15. Polarimetric SAR image classification based on discriminative dictionary learning model

    Science.gov (United States)

    Sang, Cheng Wei; Sun, Hong

    2018-03-01

    Polarimetric SAR (PolSAR) image classification is one of the important applications of PolSAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in PolSAR image classification, however for PolSAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for PolSAR classification.

  16. Generalized PSF modeling for optimized quantitation in PET imaging.

    Science.gov (United States)

    Ashrafinia, Saeed; Mohy-Ud-Din, Hassan; Karakatsanis, Nicolas A; Jha, Abhinav K; Casey, Michael E; Kadrmas, Dan J; Rahmim, Arman

    2017-06-21

    Point-spread function (PSF) modeling offers the ability to account for resolution degrading phenomena within the PET image generation framework. PSF modeling improves resolution and enhances contrast, but at the same time significantly alters image noise properties and induces edge overshoot effect. Thus, studying the effect of PSF modeling on quantitation task performance can be very important. Frameworks explored in the past involved a dichotomy of PSF versus no-PSF modeling. By contrast, the present work focuses on quantitative performance evaluation of standard uptake value (SUV) PET images, while incorporating a wide spectrum of PSF models, including those that under- and over-estimate the true PSF, for the potential of enhanced quantitation of SUVs. The developed framework first analytically models the true PSF, considering a range of resolution degradation phenomena (including photon non-collinearity, inter-crystal penetration and scattering) as present in data acquisitions with modern commercial PET systems. In the context of oncologic liver FDG PET imaging, we generated 200 noisy datasets per image-set (with clinically realistic noise levels) using an XCAT anthropomorphic phantom with liver tumours of varying sizes. These were subsequently reconstructed using the OS-EM algorithm with varying PSF modelled kernels. We focused on quantitation of both SUV mean and SUV max , including assessment of contrast recovery coefficients, as well as noise-bias characteristics (including both image roughness and coefficient of-variability), for different tumours/iterations/PSF kernels. It was observed that overestimated PSF yielded more accurate contrast recovery for a range of tumours, and typically improved quantitative performance. For a clinically reasonable number of iterations, edge enhancement due to PSF modeling (especially due to over-estimated PSF) was in fact seen to lower SUV mean bias in small tumours. Overall, the results indicate that exactly matched PSF

  17. Modelling the Image Research of a Tourism Destination

    Directory of Open Access Journals (Sweden)

    Nicolae Teodorescu

    2014-11-01

    Full Text Available The problematic area of the tourism destination image has a high expansion in marketing, the efforts of its conceptualization and phenomenalism being remarkable among specialists. In this context, the authors propose a systemic approach, the result of which refers to a model regarding the image research of a tourism destination, whose validation has been attained using Transalpina destination. The model created by the authors envisages morphological features and specific functional relationships, which are consistent with the marketing theory, and, in context, with the consumer behaviour theory. The conceptualmethodological solutions are magnified by applicative-experimental validations, which enhance the theoretical and practical valences of the created model. The main direction of developing the elaborated model consists in efforts of formalization and abstracting, in the perspective offered by several scientific disciplines.

  18. Uncertainty management in integrated modelling, the IMAGE case

    International Nuclear Information System (INIS)

    Van der Sluijs, J.P.

    1995-01-01

    Integrated assessment models of global environmental problems play an increasingly important role in decision making. This use demands a good insight regarding the reliability of these models. In this paper we analyze uncertainty management in the IMAGE-project (Integrated Model to Assess the Greenhouse Effect). We use a classification scheme comprising type and source of uncertainty. Our analysis shows reliability analysis as main area for improvement. We briefly review a recently developed methodology, NUSAP (Numerical, Unit, Spread, Assessment and Pedigree), that systematically addresses the strength of data in terms of spread, reliability and scientific status (pedigree) of information. This approach is being tested through interviews with model builders. 3 tabs., 20 refs

  19. RECONSTRUCTION OF HUMAN LUNG MORPHOLOGY MODELS FROM MAGNETIC RESONANCE IMAGES

    Science.gov (United States)

    Reconstruction of Human Lung Morphology Models from Magnetic Resonance ImagesT. B. Martonen (Experimental Toxicology Division, U.S. EPA, Research Triangle Park, NC 27709) and K. K. Isaacs (School of Public Health, University of North Carolina, Chapel Hill, NC 27514)

  20. Lévy-based modelling in brain imaging

    DEFF Research Database (Denmark)

    Jónsdóttir, Kristjana Ýr; Rønn-Nielsen, Anders; Mouridsen, Kim

    2013-01-01

    example of magnetic resonance imaging scans that are non-Gaussian. For these data, simulations under the fitted models show that traditional methods based on Gaussian random field theory may leave small, but significant changes in signal level undetected, while these changes are detectable under a non...

  1. Robotic needle steering: design, modeling, planning, and image guidance

    NARCIS (Netherlands)

    Cowan, Noah J.; Goldberg, Ken; Chirikjian, Gregory S.; Fichtinger, Gabor; Alterovitz, Ron; Reed, Kyle B.; Kallem, Vinutha; Misra, Sarthak; Park, Wooram; Okamura, Allison M.; Rosen, Jacob; Hannaford, Blake; Satava, Richard M.

    2010-01-01

    This chapter describes how advances in needle design, modeling, planning, and image guidance make it possible to steer flexible needles from outside the body to reach specified anatomical targets not accessible using traditional needle insertion methods. Steering can be achieved using a variety of

  2. A generalized framework unifying image registration and respiratory motion models and incorporating image reconstruction, for partial image data or full images

    Science.gov (United States)

    McClelland, Jamie R.; Modat, Marc; Arridge, Simon; Grimes, Helen; D'Souza, Derek; Thomas, David; O' Connell, Dylan; Low, Daniel A.; Kaza, Evangelia; Collins, David J.; Leach, Martin O.; Hawkes, David J.

    2017-06-01

    Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of ‘partial’ imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated.

  3. Automatic relative RPC image model bias compensation through hierarchical image matching for improving DEM quality

    Science.gov (United States)

    Noh, Myoung-Jong; Howat, Ian M.

    2018-02-01

    The quality and efficiency of automated Digital Elevation Model (DEM) extraction from stereoscopic satellite imagery is critically dependent on the accuracy of the sensor model used for co-locating pixels between stereo-pair images. In the absence of ground control or manual tie point selection, errors in the sensor models must be compensated with increased matching search-spaces, increasing both the computation time and the likelihood of spurious matches. Here we present an algorithm for automatically determining and compensating the relative bias in Rational Polynomial Coefficients (RPCs) between stereo-pairs utilizing hierarchical, sub-pixel image matching in object space. We demonstrate the algorithm using a suite of image stereo-pairs from multiple satellites over a range stereo-photogrammetrically challenging polar terrains. Besides providing a validation of the effectiveness of the algorithm for improving DEM quality, experiments with prescribed sensor model errors yield insight into the dependence of DEM characteristics and quality on relative sensor model bias. This algorithm is included in the Surface Extraction through TIN-based Search-space Minimization (SETSM) DEM extraction software package, which is the primary software used for the U.S. National Science Foundation ArcticDEM and Reference Elevation Model of Antarctica (REMA) products.

  4. Edge Detection on Images of Pseudoimpedance Section Supported by Context and Adaptive Transformation Model Images

    Directory of Open Access Journals (Sweden)

    Kawalec-Latała Ewa

    2014-03-01

    Full Text Available Most of underground hydrocarbon storage are located in depleted natural gas reservoirs. Seismic survey is the most economical source of detailed subsurface information. The inversion of seismic section for obtaining pseudoacoustic impedance section gives the possibility to extract detailed subsurface information. The seismic wavelet parameters and noise briefly influence the resolution. Low signal parameters, especially long signal duration time and the presence of noise decrease pseudoimpedance resolution. Drawing out from measurement or modelled seismic data approximation of distribution of acoustic pseuoimpedance leads us to visualisation and images useful to stratum homogeneity identification goal. In this paper, the improvement of geologic section image resolution by use of minimum entropy deconvolution method before inversion is applied. The author proposes context and adaptive transformation of images and edge detection methods as a way to increase the effectiveness of correct interpretation of simulated images. In the paper, the edge detection algorithms using Sobel, Prewitt, Robert, Canny operators as well as Laplacian of Gaussian method are emphasised. Wiener filtering of image transformation improving rock section structure interpretation pseudoimpedance matrix on proper acoustic pseudoimpedance value, corresponding to selected geologic stratum. The goal of the study is to develop applications of image transformation tools to inhomogeneity detection in salt deposits.

  5. Skin image illumination modeling and chromophore identification for melanoma diagnosis

    Science.gov (United States)

    Liu, Zhao; Zerubia, Josiane

    2015-05-01

    The presence of illumination variation in dermatological images has a negative impact on the automatic detection and analysis of cutaneous lesions. This paper proposes a new illumination modeling and chromophore identification method to correct lighting variation in skin lesion images, as well as to extract melanin and hemoglobin concentrations of human skin, based on an adaptive bilateral decomposition and a weighted polynomial curve fitting, with the knowledge of a multi-layered skin model. Different from state-of-the-art approaches based on the Lambert law, the proposed method, considering both specular reflection and diffuse reflection of the skin, enables us to address highlight and strong shading effects usually existing in skin color images captured in an uncontrolled environment. The derived melanin and hemoglobin indices, directly relating to the pathological tissue conditions, tend to be less influenced by external imaging factors and are more efficient in describing pigmentation distributions. Experiments show that the proposed method gave better visual results and superior lesion segmentation, when compared to two other illumination correction algorithms, both designed specifically for dermatological images. For computer-aided diagnosis of melanoma, sensitivity achieves 85.52% when using our chromophore descriptors, which is 8~20% higher than those derived from other color descriptors. This demonstrates the benefit of the proposed method for automatic skin disease analysis.

  6. FITTING OF PARAMETRIC BUILDING MODELS TO OBLIQUE AERIAL IMAGES

    Directory of Open Access Journals (Sweden)

    U. S. Panday

    2012-09-01

    Full Text Available In literature and in photogrammetric workstations many approaches and systems to automatically reconstruct buildings from remote sensing data are described and available. Those building models are being used for instance in city modeling or in cadastre context. If a roof overhang is present, the building walls cannot be estimated correctly from nadir-view aerial images or airborne laser scanning (ALS data. This leads to inconsistent building outlines, which has a negative influence on visual impression, but more seriously also represents a wrong legal boundary in the cadaster. Oblique aerial images as opposed to nadir-view images reveal greater detail, enabling to see different views of an object taken from different directions. Building walls are visible from oblique images directly and those images are used for automated roof overhang estimation in this research. A fitting algorithm is employed to find roof parameters of simple buildings. It uses a least squares algorithm to fit projected wire frames to their corresponding edge lines extracted from the images. Self-occlusion is detected based on intersection result of viewing ray and the planes formed by the building whereas occlusion from other objects is detected using an ALS point cloud. Overhang and ground height are obtained by sweeping vertical and horizontal planes respectively. Experimental results are verified with high resolution ortho-images, field survey, and ALS data. Planimetric accuracy of 1cm mean and 5cm standard deviation was obtained, while buildings' orientation were accurate to mean of 0.23° and standard deviation of 0.96° with ortho-image. Overhang parameters were aligned to approximately 10cm with field survey. The ground and roof heights were accurate to mean of – 9cm and 8cm with standard deviations of 16cm and 8cm with ALS respectively. The developed approach reconstructs 3D building models well in cases of sufficient texture. More images should be acquired for

  7. Modeling & imaging of bioelectrical activity principles and applications

    CERN Document Server

    He, Bin

    2010-01-01

    Over the past several decades, much progress has been made in understanding the mechanisms of electrical activity in biological tissues and systems, and for developing non-invasive functional imaging technologies to aid clinical diagnosis of dysfunction in the human body. The book will provide full basic coverage of the fundamentals of modeling of electrical activity in various human organs, such as heart and brain. It will include details of bioelectromagnetic measurements and source imaging technologies, as well as biomedical applications. The book will review the latest trends in

  8. Terrestrial magnetospheric imaging: Numerical modeling of low energy neutral atoms

    International Nuclear Information System (INIS)

    Moore, K.R.; Funsten, H.O.; McComas, D.J.; Scime, E.E.; Thomsen, M.F.

    1993-01-01

    Imaging of the terrestrial magnetosphere can be performed by detection of low energy neutral atoms (LENAs) that are produced by charge exchange between magnetospheric plasma ions and cold neutral atoms of the Earth's geocorona. As a result of recent instrumentation advances it is now feasible to make energy-resolved measurements of LENAs from less than I key to greater than 30 key. To model expected LENA fluxes at a spacecraft, we initially used a simplistic, spherically symmetric magnetospheric plasma model. 6 We now present improved calculations of both hydrogen and oxygen line-of-sight LENA fluxes expected on orbit for various plasma regimes as predicted by the Rice University Magnetospheric Specification Model. We also estimate expected image count rates based on realistic instrument geometric factors, energy passbands, and image accumulation intervals. The results indicate that presently proposed LENA instruments are capable of imaging of storm time ring current and potentially even quiet time ring current fluxes, and that phenomena such as ion injections from the tail and subsequent drifts toward the dayside magnetopause may also be deduced

  9. Muscles of mastication model-based MR image segmentation

    Energy Technology Data Exchange (ETDEWEB)

    Ng, H.P. [NUS Graduate School for Integrative Sciences and Engineering, Singapore (Singapore); Agency for Science Technology and Research, Singapore (Singapore). Biomedical Imaging Lab.; Ong, S.H. [National Univ. of Singapore (Singapore). Dept. of Electrical and Computer Engineering; National Univ. of Singapore (Singapore). Div. of Bioengineering; Hu, Q.; Nowinski, W.L. [Agency for Science Technology and Research, Singapore (Singapore). Biomedical Imaging Lab.; Foong, K.W.C. [NUS Graduate School for Integrative Sciences and Engineering, Singapore (Singapore); National Univ. of Singapore (Singapore). Dept. of Preventive Dentistry; Goh, P.S. [National Univ. of Singapore (Singapore). Dept. of Diagnostic Radiology

    2006-11-15

    Objective: The muscles of mastication play a major role in the orodigestive system as the principal motive force for the mandible. An algorithm for segmenting these muscles from magnetic resonance (MR) images was developed and tested. Materials and methods: Anatomical information about the muscles of mastication in MR images is used to obtain the spatial relationships relating the muscle region of interest (ROI) and head ROI. A model-based technique that involves the spatial relationships between head and muscle ROIs as well as muscle templates is developed. In the segmentation stage, the muscle ROI is derived from the model. Within the muscle ROI, anisotropic diffusion is applied to smooth the texture, followed by thresholding to exclude bone and fat. The muscle template and morphological operators are employed to obtain an initial estimate of the muscle boundary, which then serves as the input contour to the gradient vector flow snake that iterates to the final segmentation. Results: The method was applied to segmentation of the masseter, lateral pterygoid and medial pterygoid in 75 images. The overlap indices (K) achieved are 91.4, 92.1 and 91.2%, respectively. Conclusion: A model-based method for segmenting the muscles of mastication from MR images was developed and tested. The results show good agreement between manual and automatic segmentations. (orig.)

  10. Evaluation of a Mathematical Model for Digital Image Enhancement.

    Science.gov (United States)

    Geha, Hassem; Nasseh, Ibrahim; Noujeim, Marcel

    2015-01-01

    The purpose of this study is to compare the detected number of holes on a stepwedge on images resulting from the application of the 5th degree polynomial model compared to the images resulting from the application of linear enhancement. Material and Methods : A 10-step aluminum step wedge with holes randomly drilled on each step was exposed with three different kVp and five exposure times per kVp on a Schick33(®) sensor. The images were enhanced by brightness/contrast adjustment, histogram equalization and with the 5th degree polynomial model and compared to the original non-enhanced images by six observers in two separate readings. Results : There was no significant difference between the readers and between the first and second reading. There was a significant three-factor interaction among Method, Exposure time, and kVp in detecting holes. The overall pattern was: "Poly" results in the highest counts, "Original" in the lowest counts, with "B/C" and "Equalized" intermediate. Conclusion : The 5th degree polynomial model showed more holes when compared to the other modalities.

  11. Muscles of mastication model-based MR image segmentation

    International Nuclear Information System (INIS)

    Ng, H.P.; Agency for Science Technology and Research, Singapore; Ong, S.H.; National Univ. of Singapore; Hu, Q.; Nowinski, W.L.; Foong, K.W.C.; National Univ. of Singapore; Goh, P.S.

    2006-01-01

    Objective: The muscles of mastication play a major role in the orodigestive system as the principal motive force for the mandible. An algorithm for segmenting these muscles from magnetic resonance (MR) images was developed and tested. Materials and methods: Anatomical information about the muscles of mastication in MR images is used to obtain the spatial relationships relating the muscle region of interest (ROI) and head ROI. A model-based technique that involves the spatial relationships between head and muscle ROIs as well as muscle templates is developed. In the segmentation stage, the muscle ROI is derived from the model. Within the muscle ROI, anisotropic diffusion is applied to smooth the texture, followed by thresholding to exclude bone and fat. The muscle template and morphological operators are employed to obtain an initial estimate of the muscle boundary, which then serves as the input contour to the gradient vector flow snake that iterates to the final segmentation. Results: The method was applied to segmentation of the masseter, lateral pterygoid and medial pterygoid in 75 images. The overlap indices (K) achieved are 91.4, 92.1 and 91.2%, respectively. Conclusion: A model-based method for segmenting the muscles of mastication from MR images was developed and tested. The results show good agreement between manual and automatic segmentations. (orig.)

  12. Solid models for CT/MR image display

    International Nuclear Information System (INIS)

    ManKovich, N.J.; Yue, A.; Kioumehr, F.; Ammirati, M.; Turner, S.

    1991-01-01

    Medical imaging can now take wider advantage of Computer-Aided-Manufacturing through rapid prototyping technologies (RPT) such as stereolithography, laser sintering, and laminated object manufacturing to directly produce solid models of patient anatomy from processed CT and MR images. While conventional surgical planning relies on consultation with the radiologist combined with direct reading and measurement of CT and MR studies, 3-D surface and volumetric display workstations are providing a more easily interpretable view of patient anatomy. RPT can provide the surgeon with a life size model of patient anatomy constructed layer by layer with full internal detail. The authors have developed a prototype image processing and model fabrication system based on stereolithography, which provides the neurosurgeon with models of the skull base. Parallel comparison of the mode with the original thresholded CT data and with a CRT displayed surface rendering showed that both have an accuracy of >99.6 percent. The measurements on the surface rendered display proved more difficult to exactly locate and yielded a standard deviation of 2.37 percent. This paper presents an accuracy study and discusses ways of assessing the quality of neurosurgical plans when 3-D models re made available as planning tools

  13. Cognitive model of image interpretation for artificial intelligence applications

    International Nuclear Information System (INIS)

    Raju, S.

    1988-01-01

    A cognitive model of imaging diagnosis was devised to aid in the development of expert systems that assist in the interpretation of diagnostic images. In this cognitive model, a small set of observations that are strongly predictive of a particular diagnosis lead to a search for other observations that would support this diagnosis but are not necessarily specific for it. Then a set of alternative diagnoses is considered. This is followed by a search for observations that might allow differentiation of the primary diagnostic consideration from the alternatives. The production rules needed to implement this model can be classified into three major categories, each of which have certain general characteristics. Knowledge of these characteristics simplifies the development of these expert systems

  14. Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction

    Science.gov (United States)

    Su, X.

    2017-12-01

    A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.

  15. Numerical modeling of Harmonic Imaging and Pulse Inversion fields

    Science.gov (United States)

    Humphrey, Victor F.; Duncan, Tracy M.; Duck, Francis

    2003-10-01

    Tissue Harmonic Imaging (THI) and Pulse Inversion (PI) Harmonic Imaging exploit the harmonics generated as a result of nonlinear propagation through tissue to improve the performance of imaging systems. A 3D finite difference model, that solves the KZK equation in the frequency domain, is used to investigate the finite amplitude fields produced by rectangular transducers driven with short pulses and their inverses, in water and homogeneous tissue. This enables the characteristic of the fields and the effective PI field to be calculated. The suppression of the fundamental field in PI is monitored, and the suppression of side lobes and a reduction in the effective beamwidth for each field are calculated. In addition, the differences between the pulse and inverse pulse spectra resulting from the use of very short pulses are noted, and the differences in the location of the fundamental and second harmonic spectral peaks observed.

  16. Methods for modeling and quantification in functional imaging by positron emissions tomography and magnetic resonance imaging

    International Nuclear Information System (INIS)

    Costes, Nicolas

    2017-01-01

    This report presents experiences and researches in the field of in vivo medical imaging by positron emission tomography (PET) and magnetic resonance imaging (MRI). In particular, advances in terms of reconstruction, quantification and modeling in PET are described. The validation of processing and analysis methods is supported by the creation of data by simulation of the imaging process in PET. The recent advances of combined PET/MRI clinical cameras, allowing simultaneous acquisition of molecular/metabolic PET information, and functional/structural MRI information opens the door to unique methodological innovations, exploiting spatial alignment and simultaneity of the PET and MRI signals. It will lead to an increase in accuracy and sensitivity in the measurement of biological phenomena. In this context, the developed projects address new methodological issues related to quantification, and to the respective contributions of MRI or PET information for a reciprocal improvement of the signals of the two modalities. They open perspectives for combined analysis of the two imaging techniques, allowing optimal use of synchronous, anatomical, molecular and functional information for brain imaging. These innovative concepts, as well as data correction and analysis methods, will be easily translated into other areas of investigation using combined PET/MRI. (author) [fr

  17. BUILDING DETECTION USING AERIAL IMAGES AND DIGITAL SURFACE MODELS

    Directory of Open Access Journals (Sweden)

    J. Mu

    2017-05-01

    Full Text Available In this paper a method for building detection in aerial images based on variational inference of logistic regression is proposed. It consists of three steps. In order to characterize the appearances of buildings in aerial images, an effective bag-of-Words (BoW method is applied for feature extraction in the first step. In the second step, a classifier of logistic regression is learned using these local features. The logistic regression can be trained using different methods. In this paper we adopt a fully Bayesian treatment for learning the classifier, which has a number of obvious advantages over other learning methods. Due to the presence of hyper prior in the probabilistic model of logistic regression, approximate inference methods have to be applied for prediction. In order to speed up the inference, a variational inference method based on mean field instead of stochastic approximation such as Markov Chain Monte Carlo is applied. After the prediction, a probabilistic map is obtained. In the third step, a fully connected conditional random field model is formulated and the probabilistic map is used as the data term in the model. A mean field inference is utilized in order to obtain a binary building mask. A benchmark data set consisting of aerial images and digital surfaced model (DSM released by ISPRS for 2D semantic labeling is used for performance evaluation. The results demonstrate the effectiveness of the proposed method.

  18. Heterogeneous Breast Phantom Development for Microwave Imaging Using Regression Models

    Directory of Open Access Journals (Sweden)

    Camerin Hahn

    2012-01-01

    Full Text Available As new algorithms for microwave imaging emerge, it is important to have standard accurate benchmarking tests. Currently, most researchers use homogeneous phantoms for testing new algorithms. These simple structures lack the heterogeneity of the dielectric properties of human tissue and are inadequate for testing these algorithms for medical imaging. To adequately test breast microwave imaging algorithms, the phantom has to resemble different breast tissues physically and in terms of dielectric properties. We propose a systematic approach in designing phantoms that not only have dielectric properties close to breast tissues but also can be easily shaped to realistic physical models. The approach is based on regression model to match phantom's dielectric properties with the breast tissue dielectric properties found in Lazebnik et al. (2007. However, the methodology proposed here can be used to create phantoms for any tissue type as long as ex vivo, in vitro, or in vivo tissue dielectric properties are measured and available. Therefore, using this method, accurate benchmarking phantoms for testing emerging microwave imaging algorithms can be developed.

  19. A Frequency Matching Method for Generation of a Priori Sample Models from Training Images

    DEFF Research Database (Denmark)

    Lange, Katrine; Cordua, Knud Skou; Frydendall, Jan

    2011-01-01

    This paper presents a Frequency Matching Method (FMM) for generation of a priori sample models based on training images and illustrates its use by an example. In geostatistics, training images are used to represent a priori knowledge or expectations of models, and the FMM can be used to generate...... new images that share the same multi-point statistics as a given training image. The FMM proceeds by iteratively updating voxel values of an image until the frequency of patterns in the image matches the frequency of patterns in the training image; making the resulting image statistically...... indistinguishable from the training image....

  20. Software to model AXAF-I image quality

    Science.gov (United States)

    Ahmad, Anees; Feng, Chen

    1995-01-01

    A modular user-friendly computer program for the modeling of grazing-incidence type x-ray optical systems has been developed. This comprehensive computer software GRAZTRACE covers the manipulation of input data, ray tracing with reflectivity and surface deformation effects, convolution with x-ray source shape, and x-ray scattering. The program also includes the capabilities for image analysis, detector scan modeling, and graphical presentation of the results. A number of utilities have been developed to interface the predicted Advanced X-ray Astrophysics Facility-Imaging (AXAF-I) mirror structural and thermal distortions with the ray-trace. This software is written in FORTRAN 77 and runs on a SUN/SPARC station. An interactive command mode version and a batch mode version of the software have been developed.

  1. GPU based Monte Carlo for PET image reconstruction: detector modeling

    International Nuclear Information System (INIS)

    Légrády; Cserkaszky, Á; Lantos, J.; Patay, G.; Bükki, T.

    2011-01-01

    Monte Carlo (MC) calculations and Graphical Processing Units (GPUs) are almost like the dedicated hardware designed for the specific task given the similarities between visible light transport and neutral particle trajectories. A GPU based MC gamma transport code has been developed for Positron Emission Tomography iterative image reconstruction calculating the projection from unknowns to data at each iteration step taking into account the full physics of the system. This paper describes the simplified scintillation detector modeling and its effect on convergence. (author)

  2. Deformation Measurements of Gabion Walls Using Image Based Modeling

    Directory of Open Access Journals (Sweden)

    Marek Fraštia

    2014-06-01

    Full Text Available The image based modeling finds use in applications where it is necessary to reconstructthe 3D surface of the observed object with a high level of detail. Previous experiments showrelatively high variability of the results depending on the camera type used, the processingsoftware, or the process evaluation. The authors tested the method of SFM (Structure fromMotion to determine the stability of gabion walls. The results of photogrammetricmeasurements were compared to precise geodetic point measurements.

  3. Autoradiographic images in the hamster cheek pouch oral cancer model

    International Nuclear Information System (INIS)

    Portu, A.; Molinari, A.J.; Schwint, A.; Saint Martin, G.; Thorp, S.; Pozzi, E.C.C.; Curotto, P.

    2013-01-01

    The aim of this work is to summarize the autoradiographic study performed to samples from different protocols of the hamster cheek pouch oral cancer model. The qualitative analysis of histological and autoradiographic images, together with the determination of the boron concentration in the different structures of tumor, premalignant tissue and normal tissue contributed to the knowledge of the microdistribution of boron compounds. Besides, the study led to the optimization of the autoradiography technique applied to BNCT (Boron Neutron Capture Therapy). (author)

  4. Model-Based Photoacoustic Image Reconstruction using Compressed Sensing and Smoothed L0 Norm

    OpenAIRE

    Mozaffarzadeh, Moein; Mahloojifar, Ali; Nasiriavanaki, Mohammadreza; Orooji, Mahdi

    2018-01-01

    Photoacoustic imaging (PAI) is a novel medical imaging modality that uses the advantages of the spatial resolution of ultrasound imaging and the high contrast of pure optical imaging. Analytical algorithms are usually employed to reconstruct the photoacoustic (PA) images as a result of their simple implementation. However, they provide a low accurate image. Model-based (MB) algorithms are used to improve the image quality and accuracy while a large number of transducers and data acquisition a...

  5. Cardiac magnetic source imaging based on current multipole model

    International Nuclear Information System (INIS)

    Tang Fa-Kuan; Wang Qian; Hua Ning; Lu Hong; Tang Xue-Zheng; Ma Ping

    2011-01-01

    It is widely accepted that the heart current source can be reduced into a current multipole. By adopting three linear inverse methods, the cardiac magnetic imaging is achieved in this article based on the current multipole model expanded to the first order terms. This magnetic imaging is realized in a reconstruction plane in the centre of human heart, where the current dipole array is employed to represent realistic cardiac current distribution. The current multipole as testing source generates magnetic fields in the measuring plane, serving as inputs of cardiac magnetic inverse problem. In the heart-torso model constructed by boundary element method, the current multipole magnetic field distribution is compared with that in the homogeneous infinite space, and also with the single current dipole magnetic field distribution. Then the minimum-norm least-squares (MNLS) method, the optimal weighted pseudoinverse method (OWPIM), and the optimal constrained linear inverse method (OCLIM) are selected as the algorithms for inverse computation based on current multipole model innovatively, and the imaging effects of these three inverse methods are compared. Besides, two reconstructing parameters, residual and mean residual, are also discussed, and their trends under MNLS, OWPIM and OCLIM each as a function of SNR are obtained and compared. (general)

  6. Computer-aided pulmonary image analysis in small animal models

    Energy Technology Data Exchange (ETDEWEB)

    Xu, Ziyue; Mansoor, Awais; Mollura, Daniel J. [Center for Infectious Disease Imaging (CIDI), Radiology and Imaging Sciences, National Institutes of Health (NIH), Bethesda, Maryland 32892 (United States); Bagci, Ulas, E-mail: ulasbagci@gmail.com [Center for Research in Computer Vision (CRCV), University of Central Florida (UCF), Orlando, Florida 32816 (United States); Kramer-Marek, Gabriela [The Institute of Cancer Research, London SW7 3RP (United Kingdom); Luna, Brian [Microfluidic Laboratory Automation, University of California-Irvine, Irvine, California 92697-2715 (United States); Kubler, Andre [Department of Medicine, Imperial College London, London SW7 2AZ (United Kingdom); Dey, Bappaditya; Jain, Sanjay [Center for Tuberculosis Research, Johns Hopkins University School of Medicine, Baltimore, Maryland 21231 (United States); Foster, Brent [Department of Biomedical Engineering, University of California-Davis, Davis, California 95817 (United States); Papadakis, Georgios Z. [Radiology and Imaging Sciences, National Institutes of Health (NIH), Bethesda, Maryland 32892 (United States); Camp, Jeremy V. [Department of Microbiology and Immunology, University of Louisville, Louisville, Kentucky 40202 (United States); Jonsson, Colleen B. [National Institute for Mathematical and Biological Synthesis, University of Tennessee, Knoxville, Tennessee 37996 (United States); Bishai, William R. [Howard Hughes Medical Institute, Chevy Chase, Maryland 20815 and Center for Tuberculosis Research, Johns Hopkins University School of Medicine, Baltimore, Maryland 21231 (United States); Udupa, Jayaram K. [Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania 19104 (United States)

    2015-07-15

    Purpose: To develop an automated pulmonary image analysis framework for infectious lung diseases in small animal models. Methods: The authors describe a novel pathological lung and airway segmentation method for small animals. The proposed framework includes identification of abnormal imaging patterns pertaining to infectious lung diseases. First, the authors’ system estimates an expected lung volume by utilizing a regression function between total lung capacity and approximated rib cage volume. A significant difference between the expected lung volume and the initial lung segmentation indicates the presence of severe pathology, and invokes a machine learning based abnormal imaging pattern detection system next. The final stage of the proposed framework is the automatic extraction of airway tree for which new affinity relationships within the fuzzy connectedness image segmentation framework are proposed by combining Hessian and gray-scale morphological reconstruction filters. Results: 133 CT scans were collected from four different studies encompassing a wide spectrum of pulmonary abnormalities pertaining to two commonly used small animal models (ferret and rabbit). Sensitivity and specificity were greater than 90% for pathological lung segmentation (average dice similarity coefficient > 0.9). While qualitative visual assessments of airway tree extraction were performed by the participating expert radiologists, for quantitative evaluation the authors validated the proposed airway extraction method by using publicly available EXACT’09 data set. Conclusions: The authors developed a comprehensive computer-aided pulmonary image analysis framework for preclinical research applications. The proposed framework consists of automatic pathological lung segmentation and accurate airway tree extraction. The framework has high sensitivity and specificity; therefore, it can contribute advances in preclinical research in pulmonary diseases.

  7. Application of object modeling technique to medical image retrieval system

    International Nuclear Information System (INIS)

    Teshima, Fumiaki; Abe, Takeshi

    1993-01-01

    This report describes the results of discussions on the object-oriented analysis methodology, which is one of the object-oriented paradigms. In particular, we considered application of the object modeling technique (OMT) to the analysis of a medical image retrieval system. The object-oriented methodology places emphasis on the construction of an abstract model from real-world entities. The effectiveness of and future improvements to OMT are discussed from the standpoint of the system's expandability. These discussions have elucidated that the methodology is sufficiently well-organized and practical to be applied to commercial products, provided that it is applied to the appropriate problem domain. (author)

  8. Image-Based Models for Specularity Propagation in Diminished Reality.

    Science.gov (United States)

    Said, Souheil Hadj; Tamaazousti, Mohamed; Bartoli, Adrien

    2018-07-01

    The aim of Diminished Reality (DR) is to remove a target object in a live video stream seamlessly. In our approach, the area of the target object is replaced with new texture that blends with the rest of the image. The result is then propagated to the next frames of the video. One of the important stages of this technique is to update the target region with respect to the illumination change. This is a complex and recurrent problem when the viewpoint changes. We show that the state-of-the-art in DR fails in solving this problem, even under simple scenarios. We then use local illumination models to address this problem. According to these models, the variation in illumination only affects the specular component of the image. In the context of DR, the problem is therefore solved by propagating the specularities in the target area. We list a set of structural properties of specularities which we incorporate in two new models for specularity propagation. Our first model includes the same property as the previous approaches, which is the smoothness of illumination variation, but has a different estimation method based on the Thin-Plate Spline. Our second model incorporates more properties of the specularity's shape on planar surfaces. Experimental results on synthetic and real data show that our strategy substantially improves the rendering quality compared to the state-of-the-art in DR.

  9. Seismic Full Waveform Modeling & Imaging in Attenuating Media

    Science.gov (United States)

    Guo, Peng

    Seismic attenuation strongly affects seismic waveforms by amplitude loss and velocity dispersion. Without proper inclusion of Q parameters, errors can be introduced for seismic full waveform modeling and imaging. Three different (Carcione's, Robertsson's, and the generalized Robertsson's) isotropic viscoelastic wave equations based on the generalized standard linear solid (GSLS) are evaluated. The second-order displacement equations are derived, and used to demonstrate that, with the same stress relaxation times, these viscoelastic formulations are equivalent. By introducing separate memory variables for P and S relaxation functions, Robertsson's formulation is generalized to allow different P and S wave stress relaxation times, which improves the physical consistency of the Qp and Qs modelled in the seismograms.The three formulations have comparable computational cost. 3D seismic finite-difference forward modeling is applied to anisotropic viscoelastic media. The viscoelastic T-matrix (a dynamic effective medium theory) relates frequency-dependent anisotropic attenuation and velocity to reservoir properties in fractured HTI media, based on the meso-scale fluid flow attenuation mechanism. The seismic signatures resulting from changing viscoelastic reservoir properties are easily visible. Analysis of 3D viscoelastic seismograms suggests that anisotropic attenuation is a potential tool for reservoir characterization. To compensate the Q effects during reverse-time migration (RTM) in viscoacoustic and viscoelastic media, amplitudes need to be compensated during wave propagation; the propagation velocity of the Q-compensated wavefield needs to be the same as in the attenuating wavefield, to restore the phase information. Both amplitude and phase can be compensated when the velocity dispersion and the amplitude loss are decoupled. For wave equations based on the GSLS, because Q effects are coupled in the memory variables, Q-compensated wavefield propagates faster than

  10. Theoretical performance model for single image depth from defocus.

    Science.gov (United States)

    Trouvé-Peloux, Pauline; Champagnat, Frédéric; Le Besnerais, Guy; Idier, Jérôme

    2014-12-01

    In this paper we present a performance model for depth estimation using single image depth from defocus (SIDFD). Our model is based on an original expression of the Cramér-Rao bound (CRB) in this context. We show that this model is consistent with the expected behavior of SIDFD. We then study the influence on the performance of the optical parameters of a conventional camera such as the focal length, the aperture, and the position of the in-focus plane (IFP). We derive an approximate analytical expression of the CRB away from the IFP, and we propose an interpretation of the SIDFD performance in this domain. Finally, we illustrate the predictive capacity of our performance model on experimental data comparing several settings of a consumer camera.

  11. Object recognition in images via a factor graph model

    Science.gov (United States)

    He, Yong; Wang, Long; Wu, Zhaolin; Zhang, Haisu

    2018-04-01

    Object recognition in images suffered from huge search space and uncertain object profile. Recently, the Bag-of- Words methods are utilized to solve these problems, especially the 2-dimension CRF(Conditional Random Field) model. In this paper we suggest the method based on a general and flexible fact graph model, which can catch the long-range correlation in Bag-of-Words by constructing a network learning framework contrasted from lattice in CRF. Furthermore, we explore a parameter learning algorithm based on the gradient descent and Loopy Sum-Product algorithms for the factor graph model. Experimental results on Graz 02 dataset show that, the recognition performance of our method in precision and recall is better than a state-of-art method and the original CRF model, demonstrating the effectiveness of the proposed method.

  12. Imaging cerebral haemorrhage with magnetic induction tomography: numerical modelling.

    Science.gov (United States)

    Zolgharni, M; Ledger, P D; Armitage, D W; Holder, D S; Griffiths, H

    2009-06-01

    Magnetic induction tomography (MIT) is a new electromagnetic imaging modality which has the potential to image changes in the electrical conductivity of the brain due to different pathologies. In this study the feasibility of detecting haemorrhagic cerebral stroke with a 16-channel MIT system operating at 10 MHz was investigated. The finite-element method combined with a realistic, multi-layer, head model comprising 12 different tissues, was used for the simulations in the commercial FE package, Comsol Multiphysics. The eddy-current problem was solved and the MIT signals computed for strokes of different volumes occurring at different locations in the brain. The results revealed that a large, peripheral stroke (volume 49 cm(3)) produced phase changes that would be detectable with our currently achievable instrumentation phase noise level (17 m degrees ) in 70 (27%) of the 256 exciter/sensor channel combinations. However, reconstructed images showed that a lower noise level than this, of 1 m degrees , was necessary to obtain good visualization of the strokes. The simulated MIT measurements were compared with those from an independent transmission-line-matrix model in order to give confidence in the results.

  13. Dynamic Chest Image Analysis: Model-Based Perfusion Analysis in Dynamic Pulmonary Imaging

    Directory of Open Access Journals (Sweden)

    Kiuru Aaro

    2003-01-01

    Full Text Available The "Dynamic Chest Image Analysis" project aims to develop model-based computer analysis and visualization methods for showing focal and general abnormalities of lung ventilation and perfusion based on a sequence of digital chest fluoroscopy frames collected with the dynamic pulmonary imaging technique. We have proposed and evaluated a multiresolutional method with an explicit ventilation model for ventilation analysis. This paper presents a new model-based method for pulmonary perfusion analysis. According to perfusion properties, we first devise a novel mathematical function to form a perfusion model. A simple yet accurate approach is further introduced to extract cardiac systolic and diastolic phases from the heart, so that this cardiac information may be utilized to accelerate the perfusion analysis and improve its sensitivity in detecting pulmonary perfusion abnormalities. This makes perfusion analysis not only fast but also robust in computation; consequently, perfusion analysis becomes computationally feasible without using contrast media. Our clinical case studies with 52 patients show that this technique is effective for pulmonary embolism even without using contrast media, demonstrating consistent correlations with computed tomography (CT and nuclear medicine (NM studies. This fluoroscopical examination takes only about 2 seconds for perfusion study with only low radiation dose to patient, involving no preparation, no radioactive isotopes, and no contrast media.

  14. Analysis and modeling of electronic portal imaging exit dose measurements

    International Nuclear Information System (INIS)

    Pistorius, S.; Yeboah, C.

    1995-01-01

    In spite of the technical advances in treatment planning and delivery in recent years, it is still unclear whether the recommended accuracy in dose delivery is being achieved. Electronic portal imaging devices, now in routine use in many centres, have the potential for quantitative dosimetry. As part of a project which aims to develop an expert-system based On-line Dosimetric Verification (ODV) system we have investigated and modelled the dose deposited in the detector of a video based portal imaging system. Monte Carlo techniques were used to simulate gamma and x-ray beams in homogeneous slab phantom geometries. Exit doses and energy spectra were scored as a function of (i) slab thickness, (ii) field size and (iii) the air gap between the exit surface and the detector. The results confirm that in order to accurately calculate the dose in the high atomic number Gd 2 O 2 S detector for a range of air gaps, field sizes and slab thicknesses both the magnitude of the primary and scattered components and their effective energy need to be considered. An analytic, convolution based model which attempts to do this is proposed. The results of the simulation and the ability of the model to represent these data will be presented and discussed. This model is used to show that, after training, a back-propagation feed-forward cascade correlation neural network has the ability to identify and recognise the cause of, significant dosimetric errors

  15. Use of an object model in three dimensional image reconstruction. Application in medical imaging

    International Nuclear Information System (INIS)

    Delageniere-Guillot, S.

    1993-02-01

    Threedimensional image reconstruction from projections corresponds to a set of techniques which give information on the inner structure of the studied object. These techniques are mainly used in medical imaging or in non destructive evaluation. Image reconstruction is an ill-posed problem. So the inversion has to be regularized. This thesis deals with the introduction of a priori information within the reconstruction algorithm. The knowledge is introduced through an object model. The proposed scheme is applied to the medical domain for cone beam geometry. We address two specific problems. First, we study the reconstruction of high contrast objects. This can be applied to bony morphology (bone/soft tissue) or to angiography (vascular structures opacified by injection of contrast agent). With noisy projections, the filtering steps of standard methods tend to smooth the natural transitions of the investigated object. In order to regularize the reconstruction but to keep contrast, we introduce a model of classes which involves the Markov random fields theory. We develop a reconstruction scheme: analytic reconstruction-reprojection. Then, we address the case of an object changing during the acquisition. This can be applied to angiography when the contrast agent is moving through the vascular tree. The problem is then stated as a dynamic reconstruction. We define an evolution AR model and we use an algebraic reconstruction method. We represent the object at a particular moment as an intermediary state between the state of the object at the beginning and at the end of the acquisition. We test both methods on simulated and real data, and we prove how the use of an a priori model can improve the results. (author)

  16. Imaging infrared: Scene simulation, modeling, and real image tracking; Proceedings of the Meeting, Orlando, FL, Mar. 30, 31, 1989

    Science.gov (United States)

    Triplett, Milton J.; Wolverton, James R.; Hubert, August J.

    1989-09-01

    Various papers on scene simulation, modeling, and real image tracking using IR imaging are presented. Individual topics addressed include: tactical IR scene generator, dynamic FLIR simulation in flight training research, high-speed dynamic scene simulation in UV to IR spectra, development of an IR sensor calibration facility, IR celestial background scene description, transmission measurement of optical components at cryogenic temperatures, diffraction model for a point-source generator, silhouette-based tracking for tactical IR systems, use of knowledge in electrooptical trackers, detection and classification of target formations in IR image sequences, SMPRAD: simplified three-dimensional cloud radiance model, IR target generator, recent advances in testing of thermal imagers, generic IR system models with dynamic image generation, modeling realistic target acquisition using IR sensors in multiple-observer scenarios, and novel concept of scene generation and comprehensive dynamic sensor test.

  17. 3D MODEL GENERATION USING OBLIQUE IMAGES ACQUIRED BY UAV

    Directory of Open Access Journals (Sweden)

    A. Lingua

    2017-07-01

    Full Text Available In recent years, many studies revealed the advantages of using airborne oblique images for obtaining improved 3D city models (including façades and building footprints. Here the acquisition and use of oblique images from a low cost and open source Unmanned Aerial Vehicle (UAV for the 3D high-level-of-detail reconstruction of historical architectures is evaluated. The critical issues of such acquisitions (flight planning strategies, ground control points distribution, etc. are described. Several problems should be considered in the flight planning: best approach to cover the whole object with the minimum time of flight; visibility of vertical structures; occlusions due to the context; acquisition of all the parts of the objects (the closest and the farthest with similar resolution; suitable camera inclination, and so on. In this paper a solution is proposed in order to acquire oblique images with one only flight. The data processing was realized using Structure-from-Motion-based approach for point cloud generation using dense image-matching algorithms implemented in an open source software. The achieved results are analysed considering some check points and some reference LiDAR data. The system was tested for surveying a historical architectonical complex: the “Sacro Mo nte di Varallo Sesia” in north-west of Italy. This study demonstrates that the use of oblique images acquired from a low cost UAV system and processed through an open source software is an effective methodology to survey cultural heritage, characterized by limited accessibility, need for detail and rapidity of the acquisition phase, and often reduced budgets.

  18. Hemispherical reflectance model for passive images in an outdoor environment.

    Science.gov (United States)

    Kim, Charles C; Thai, Bea; Yamaoka, Neil; Aboutalib, Omar

    2015-05-01

    We present a hemispherical reflectance model for simulating passive images in an outdoor environment where illumination is provided by natural sources such as the sun and the clouds. While the bidirectional reflectance distribution function (BRDF) accurately produces radiance from any objects after the illumination, using the BRDF in calculating radiance requires double integration. Replacing the BRDF by hemispherical reflectance under the natural sources transforms the double integration into a multiplication. This reduces both storage space and computation time. We present the formalism for the radiance of the scene using hemispherical reflectance instead of BRDF. This enables us to generate passive images in an outdoor environment taking advantage of the computational and storage efficiencies. We show some examples for illustration.

  19. Objective and expert-independent validation of retinal image registration algorithms by a projective imaging distortion model.

    Science.gov (United States)

    Lee, Sangyeol; Reinhardt, Joseph M; Cattin, Philippe C; Abràmoff, Michael D

    2010-08-01

    Fundus camera imaging of the retina is widely used to diagnose and manage ophthalmologic disorders including diabetic retinopathy, glaucoma, and age-related macular degeneration. Retinal images typically have a limited field of view, and multiple images can be joined together using an image registration technique to form a montage with a larger field of view. A variety of methods for retinal image registration have been proposed, but evaluating such methods objectively is difficult due to the lack of a reference standard for the true alignment of the individual images that make up the montage. A method of generating simulated retinal images by modeling the geometric distortions due to the eye geometry and the image acquisition process is described in this paper. We also present a validation process that can be used for any retinal image registration method by tracing through the distortion path and assessing the geometric misalignment in the coordinate system of the reference standard. The proposed method can be used to perform an accuracy evaluation over the whole image, so that distortion in the non-overlapping regions of the montage components can be easily assessed. We demonstrate the technique by generating test image sets with a variety of overlap conditions and compare the accuracy of several retinal image registration models. Copyright 2010 Elsevier B.V. All rights reserved.

  20. Automated drusen detection in retinal images using analytical modelling algorithms

    Directory of Open Access Journals (Sweden)

    Manivannan Ayyakkannu

    2011-07-01

    Full Text Available Abstract Background Drusen are common features in the ageing macula associated with exudative Age-Related Macular Degeneration (ARMD. They are visible in retinal images and their quantitative analysis is important in the follow up of the ARMD. However, their evaluation is fastidious and difficult to reproduce when performed manually. Methods This article proposes a methodology for Automatic Drusen Deposits Detection and quantification in Retinal Images (AD3RI by using digital image processing techniques. It includes an image pre-processing method to correct the uneven illumination and to normalize the intensity contrast with smoothing splines. The drusen detection uses a gradient based segmentation algorithm that isolates drusen and provides basic drusen characterization to the modelling stage. The detected drusen are then fitted by Modified Gaussian functions, producing a model of the image that is used to evaluate the affected area. Twenty two images were graded by eight experts, with the aid of a custom made software and compared with AD3RI. This comparison was based both on the total area and on the pixel-to-pixel analysis. The coefficient of variation, the intraclass correlation coefficient, the sensitivity, the specificity and the kappa coefficient were calculated. Results The ground truth used in this study was the experts' average grading. In order to evaluate the proposed methodology three indicators were defined: AD3RI compared to the ground truth (A2G; each expert compared to the other experts (E2E and a standard Global Threshold method compared to the ground truth (T2G. The results obtained for the three indicators, A2G, E2E and T2G, were: coefficient of variation 28.8 %, 22.5 % and 41.1 %, intraclass correlation coefficient 0.92, 0.88 and 0.67, sensitivity 0.68, 0.67 and 0.74, specificity 0.96, 0.97 and 0.94, and kappa coefficient 0.58, 0.60 and 0.49, respectively. Conclusions The gradings produced by AD3RI obtained an agreement

  1. Data-driven forward model inference for EEG brain imaging

    DEFF Research Database (Denmark)

    Hansen, Sofie Therese; Hauberg, Søren; Hansen, Lars Kai

    2016-01-01

    Electroencephalography (EEG) is a flexible and accessible tool with excellent temporal resolution but with a spatial resolution hampered by volume conduction. Reconstruction of the cortical sources of measured EEG activity partly alleviates this problem and effectively turns EEG into a brain......-of-concept study, we show that, even when anatomical knowledge is unavailable, a suitable forward model can be estimated directly from the EEG. We propose a data-driven approach that provides a low-dimensional parametrization of head geometry and compartment conductivities, built using a corpus of forward models....... Combined with only a recorded EEG signal, we are able to estimate both the brain sources and a person-specific forward model by optimizing this parametrization. We thus not only solve an inverse problem, but also optimize over its specification. Our work demonstrates that personalized EEG brain imaging...

  2. FDTD Modeling of Nano- and Bio-Photonic Imaging

    DEFF Research Database (Denmark)

    Tanev, Stoyan; Tuchin, Valery; Pond, James

    2010-01-01

    to address newly emerging problems and not so much on its mathematical formulation. We will first discuss the application of a traditional formulation of the FDTD approach to the modeling of sub-wavelength photonics structures. Next, a modified total/scattered field FDTD approach will be applied...... to the modeling of biophotonics applications including Optical Phase Contrast Microscope (OPCM) imaging of cells containing gold nanoparticles (NPs) as well as its potential application as a modality for in vivo flow cytometry configurations.......In this paper we focus on the discussion of two recent unique applications of the Finite-Difference Time-Domain (FDTD) simulation method to the design and modeling of advanced nano- and bio-photonic problems. The approach that is adopted here focuses on the potential of the FDTD methodology...

  3. Mapping from Speech to Images Using Continuous State Space Models

    DEFF Research Database (Denmark)

    Lehn-Schiøler, Tue; Hansen, Lars Kai; Larsen, Jan

    2005-01-01

    In this paper a system that transforms speech waveforms to animated faces are proposed. The system relies on continuous state space models to perform the mapping, this makes it possible to ensure video with no sudden jumps and allows continuous control of the parameters in 'face space...... a subjective point of view the model is able to construct an image sequence from an unknown noisy speech sequence even though the number of training examples are limited.......'. The performance of the system is critically dependent on the number of hidden variables, with too few variables the model cannot represent data, and with too many overfitting is noticed. Simulations are performed on recordings of 3-5 sec.\\$\\backslash\\$ video sequences with sentences from the Timit database. From...

  4. [Evaluating the maturity of IT-supported clinical imaging and diagnosis using the Digital Imaging Adoption Model : Are your clinical imaging processes ready for the digital era?

    Science.gov (United States)

    Studzinski, J

    2017-06-01

    The Digital Imaging Adoption Model (DIAM) has been jointly developed by HIMSS Analytics and the European Society of Radiology (ESR). It helps evaluate the maturity of IT-supported processes in medical imaging, particularly in radiology. This eight-stage maturity model drives your organisational, strategic and tactical alignment towards imaging-IT planning. The key audience for the model comprises hospitals with imaging centers, as well as external imaging centers that collaborate with hospitals. The assessment focuses on different dimensions relevant to digital imaging, such as software infrastructure and usage, workflow security, clinical documentation and decision support, data exchange and analytical capabilities. With its standardised approach, it enables regional, national and international benchmarking. All DIAM participants receive a structured report that can be used as a basis for presenting, e.g. budget planning and investment decisions at management level.

  5. Geometric modelling of a make mandible utilising CT imaging

    International Nuclear Information System (INIS)

    Baker, N.; Basu, A.; McLean, A.G.; Jamieson, D.; Jonkman, M.

    1996-01-01

    Full text: The mandible is one of the most important and frequently used bones in the human body. It is responsible for basic actions such as mastication, communication and swallowing. It houses and provides protection for the tongue, teeth and salivary glands. The mandible is unique in that it has two anatomically identical articulations, each providing the same function. Both articulations, however, rarely have synchronous force and motion characteristics. The mandible is the only moveable bone in the skull and is capable of the following motions: depression - lowering the mandible, as in yawning, elevation - raising the mandible, protraction - thrusting the jaw forward, retraction - withdrawing the jaw posteriorly, and lateral deviation - sideways displacement in the transverse plane. The mandible is an irregular bone comprising a broad U shaped body with two ascending rami. The rami are quadrilateral plate like structures with lateral sides which are nearly flat. The mandible is subjected to repetitive loading and is susceptible to wear at its articulations, cyclic fatigue and dislocation. Despite the importance of the mandible little is understood about its mechanical properties and loading parameters. The purpose of this study was to create a three dimensional geometric model of a human mandible based on anatomical data. A 21 year old male with no history of mandible fracture or temporomandibular joint dysfunction was selected. The mandible was non-invasively imaged by Computed Tomography (CT). The subject was imaged lying on his back with the head supported and immobilised by a U shaped head rest. Seventeen parallel cross-sectional images oblique to the transverse plane were constructed. Cortical and cancellous bone boundaries were manually digitised for every image using a Science Accessories Corporation GP-9 digitiser linked to an IBM 286 SX personal computer. The data was transferred to a global coordinate system and entered into MSC/PATRAN finite element

  6. Elastic models: a comparative study applied to retinal images.

    Science.gov (United States)

    Karali, E; Lambropoulou, S; Koutsouris, D

    2011-01-01

    In this work various methods of parametric elastic models are compared, namely the classical snake, the gradient vector field snake (GVF snake) and the topology-adaptive snake (t-snake), as well as the method of self-affine mapping system as an alternative to elastic models. We also give a brief overview of the methods used. The self-affine mapping system is implemented using an adapting scheme and minimum distance as optimization criterion, which is more suitable for weak edges detection. All methods are applied to glaucomatic retinal images with the purpose of segmenting the optical disk. The methods are compared in terms of segmentation accuracy and speed, as these are derived from cross-correlation coefficients between real and algorithm extracted contours and segmentation time, respectively. As a result, the method of self-affine mapping system presents adequate segmentation time and segmentation accuracy, and significant independence from initialization.

  7. Development of Software to Model AXAF-I Image Quality

    Science.gov (United States)

    Ahmad, Anees; Hawkins, Lamar

    1996-01-01

    This draft final report describes the work performed under the delivery order number 145 from May 1995 through August 1996. The scope of work included a number of software development tasks for the performance modeling of AXAF-I. A number of new capabilities and functions have been added to the GT software, which is the command mode version of the GRAZTRACE software, originally developed by MSFC. A structural data interface has been developed for the EAL (old SPAR) finite element analysis FEA program, which is being used by MSFC Structural Analysis group for the analysis of AXAF-I. This interface utility can read the structural deformation file from the EAL and other finite element analysis programs such as NASTRAN and COSMOS/M, and convert the data to a suitable format that can be used for the deformation ray-tracing to predict the image quality for a distorted mirror. There is a provision in this utility to expand the data from finite element models assuming 180 degrees symmetry. This utility has been used to predict image characteristics for the AXAF-I HRMA, when subjected to gravity effects in the horizontal x-ray ground test configuration. The development of the metrology data processing interface software has also been completed. It can read the HDOS FITS format surface map files, manipulate and filter the metrology data, and produce a deformation file, which can be used by GT for ray tracing for the mirror surface figure errors. This utility has been used to determine the optimum alignment (axial spacing and clocking) for the four pairs of AXAF-I mirrors. Based on this optimized alignment, the geometric images and effective focal lengths for the as built mirrors were predicted to cross check the results obtained by Kodak.

  8. Reconstruction of hyperspectral image using matting model for classification

    Science.gov (United States)

    Xie, Weiying; Li, Yunsong; Ge, Chiru

    2016-05-01

    Although hyperspectral images (HSIs) captured by satellites provide much information in spectral regions, some bands are redundant or have large amounts of noise, which are not suitable for image analysis. To address this problem, we introduce a method for reconstructing the HSI with noise reduction and contrast enhancement using a matting model for the first time. The matting model refers to each spectral band of an HSI that can be decomposed into three components, i.e., alpha channel, spectral foreground, and spectral background. First, one spectral band of an HSI with more refined information than most other bands is selected, and is referred to as an alpha channel of the HSI to estimate the hyperspectral foreground and hyperspectral background. Finally, a combination operation is applied to reconstruct the HSI. In addition, the support vector machine (SVM) classifier and three sparsity-based classifiers, i.e., orthogonal matching pursuit (OMP), simultaneous OMP, and OMP based on first-order neighborhood system weighted classifiers, are utilized on the reconstructed HSI and the original HSI to verify the effectiveness of the proposed method. Specifically, using the reconstructed HSI, the average accuracy of the SVM classifier can be improved by as much as 19%.

  9. Model-based magnetization retrieval from holographic phase images

    Energy Technology Data Exchange (ETDEWEB)

    Röder, Falk, E-mail: f.roeder@hzdr.de [Helmholtz-Zentrum Dresden-Rossendorf, Institut für Ionenstrahlphysik und Materialforschung, Bautzner Landstr. 400, D-01328 Dresden (Germany); Triebenberg Labor, Institut für Strukturphysik, Technische Universität Dresden, D-01062 Dresden (Germany); Vogel, Karin [Triebenberg Labor, Institut für Strukturphysik, Technische Universität Dresden, D-01062 Dresden (Germany); Wolf, Daniel [Helmholtz-Zentrum Dresden-Rossendorf, Institut für Ionenstrahlphysik und Materialforschung, Bautzner Landstr. 400, D-01328 Dresden (Germany); Triebenberg Labor, Institut für Strukturphysik, Technische Universität Dresden, D-01062 Dresden (Germany); Hellwig, Olav [Helmholtz-Zentrum Dresden-Rossendorf, Institut für Ionenstrahlphysik und Materialforschung, Bautzner Landstr. 400, D-01328 Dresden (Germany); AG Magnetische Funktionsmaterialien, Institut für Physik, Technische Universität Chemnitz, D-09126 Chemnitz (Germany); HGST, A Western Digital Company, 3403 Yerba Buena Rd., San Jose, CA 95135 (United States); Wee, Sung Hun [HGST, A Western Digital Company, 3403 Yerba Buena Rd., San Jose, CA 95135 (United States); Wicht, Sebastian; Rellinghaus, Bernd [IFW Dresden, Institute for Metallic Materials, P.O. Box 270116, D-01171 Dresden (Germany)

    2017-05-15

    The phase shift of the electron wave is a useful measure for the projected magnetic flux density of magnetic objects at the nanometer scale. More important for materials science, however, is the knowledge about the magnetization in a magnetic nano-structure. As demonstrated here, a dominating presence of stray fields prohibits a direct interpretation of the phase in terms of magnetization modulus and direction. We therefore present a model-based approach for retrieving the magnetization by considering the projected shape of the nano-structure and assuming a homogeneous magnetization therein. We apply this method to FePt nano-islands epitaxially grown on a SrTiO{sub 3} substrate, which indicates an inclination of their magnetization direction relative to the structural easy magnetic [001] axis. By means of this real-world example, we discuss prospects and limits of this approach. - Highlights: • Retrieval of the magnetization from holographic phase images. • Magnetostatic model constructed for a magnetic nano-structure. • Decomposition into homogeneously magnetized components. • Discretization of a each component by elementary cuboids. • Analytic solution for the phase of a magnetized cuboid considered. • Fitting a set of magnetization vectors to experimental phase images.

  10. A biometric authentication model using hand gesture images.

    Science.gov (United States)

    Fong, Simon; Zhuang, Yan; Fister, Iztok; Fister, Iztok

    2013-10-30

    A novel hand biometric authentication method based on measurements of the user's stationary hand gesture of hand sign language is proposed. The measurement of hand gestures could be sequentially acquired by a low-cost video camera. There could possibly be another level of contextual information, associated with these hand signs to be used in biometric authentication. As an analogue, instead of typing a password 'iloveu' in text which is relatively vulnerable over a communication network, a signer can encode a biometric password using a sequence of hand signs, 'i' , 'l' , 'o' , 'v' , 'e' , and 'u'. Subsequently the features from the hand gesture images are extracted which are integrally fuzzy in nature, to be recognized by a classification model for telling if this signer is who he claimed himself to be, by examining over his hand shape and the postures in doing those signs. It is believed that everybody has certain slight but unique behavioral characteristics in sign language, so are the different hand shape compositions. Simple and efficient image processing algorithms are used in hand sign recognition, including intensity profiling, color histogram and dimensionality analysis, coupled with several popular machine learning algorithms. Computer simulation is conducted for investigating the efficacy of this novel biometric authentication model which shows up to 93.75% recognition accuracy.

  11. Joint Probability Models of Radiology Images and Clinical Annotations

    Science.gov (United States)

    Arnold, Corey Wells

    2009-01-01

    Radiology data, in the form of images and reports, is growing at a high rate due to the introduction of new imaging modalities, new uses of existing modalities, and the growing importance of objective image information in the diagnosis and treatment of patients. This increase has resulted in an enormous set of image data that is richly annotated…

  12. Imaging noradrenergic influence on amyloid pathology in mouse models of Alzheimer's disease

    International Nuclear Information System (INIS)

    Winkeler, A.; Waerzeggers, Y.; Klose, A.; Monfared, P.; Thomas, A.V.; Jacobs, A.H.; Schubert, M.; Heneka, M.T.

    2008-01-01

    Molecular imaging aims towards the non-invasive characterization of disease-specific molecular alterations in the living organism in vivo. In that, molecular imaging opens a new dimension in our understanding of disease pathogenesis, as it allows the non-invasive determination of the dynamics of changes on the molecular level. The imaging technology being employed includes magnetic resonance imaging (MRI) and nuclear imaging as well as optical-based imaging technologies. These imaging modalities are employed together or alone for disease phenotyping, development of imaging-guided therapeutic strategies and in basic and translational research. In this study, we review recent investigations employing positron emission tomography and MRI for phenotyping mouse models of Alzheimers' disease by imaging. We demonstrate that imaging has an important role in the characterization of mouse models of neurodegenerative diseases. (orig.)

  13. VERIFICATION OF 3D BUILDING MODELS USING MUTUAL INFORMATION IN AIRBORNE OBLIQUE IMAGES

    Directory of Open Access Journals (Sweden)

    A. P. Nyaruhuma

    2012-07-01

    Full Text Available This paper describes a method for automatic verification of 3D building models using airborne oblique images. The problem being tackled is identifying buildings that are demolished or changed since the models were constructed or identifying wrong models using the images. The models verified are of CityGML LOD2 or higher since their edges are expected to coincide with actual building edges. The verification approach is based on information theory. Corresponding variables between building models and oblique images are used for deriving mutual information for individual edges, faces or whole buildings, and combined for all perspective images available for the building. The wireframe model edges are projected to images and verified using low level image features – the image pixel gradient directions. A building part is only checked against images in which it may be visible. The method has been tested with models constructed using laser points against Pictometry images that are available for most cities of Europe and may be publically viewed in the so called Birds Eye view of the Microsoft Bing Maps. Results are that nearly all buildings are correctly categorised as existing or demolished. Because we now concentrate only on roofs we also used the method to test and compare results from nadir images. This comparison made clear that especially height errors in models can be more reliably detected in oblique images because of the tilted view. Besides overall building verification, results per individual edges can be used for improving the 3D building models.

  14. Remote Sensing Image Enhancement Based on Non-subsampled Shearlet Transform and Parameterized Logarithmic Image Processing Model

    Directory of Open Access Journals (Sweden)

    TAO Feixiang

    2015-08-01

    Full Text Available Aiming at parts of remote sensing images with dark brightness and low contrast, a remote sensing image enhancement method based on non-subsampled Shearlet transform and parameterized logarithmic image processing model is proposed in this paper to improve the visual effects and interpretability of remote sensing images. Firstly, a remote sensing image is decomposed into a low-frequency component and high frequency components by non-subsampled Shearlet transform.Then the low frequency component is enhanced according to PLIP (parameterized logarithmic image processing model, which can improve the contrast of image, while the improved fuzzy enhancement method is used to enhance the high frequency components in order to highlight the information of edges and details. A large number of experimental results show that, compared with five kinds of image enhancement methods such as bidirectional histogram equalization method, the method based on stationary wavelet transform and the method based on non-subsampled contourlet transform, the proposed method has advantages in both subjective visual effects and objective quantitative evaluation indexes such as contrast and definition, which can more effectively improve the contrast of remote sensing image and enhance edges and texture details with better visual effects.

  15. [Application of GVF snake model in segmentation of whole body bone SPECT image].

    Science.gov (United States)

    Zhu, Chunmei; Tian, Lianfang; Chen, Ping; Wang, Lifei; Ye, Guangchun; Mao, Zongyuan

    2008-02-01

    Limited by the imaging principle of whole body bone SPECT image, the gray value of bladder area is quite high, which affects the image's brightness, contrast and readability. In the meantime, the similarity between bladder area and focus makes it difficult for some images to be segmented automatically. In this paper, an improved Snake model, GVF Snake, is adopted to automatically segment bladder area, preparing for further processing of whole body bone SPECT images.

  16. The design of a new model circuit for image acquisition from nuclear medicine

    International Nuclear Information System (INIS)

    Zhang Nan; Jin Yongjie

    1995-01-01

    A new practical model of image acquisition circuit is given. It can be applied to data acquisition system of γ camera from nuclear medicine directly. Its idea also can be applied to some image acquisition system of nuclear event

  17. Computational biomechanics for medicine imaging, modeling and computing

    CERN Document Server

    Doyle, Barry; Wittek, Adam; Nielsen, Poul; Miller, Karol

    2016-01-01

    The Computational Biomechanics for Medicine titles provide an opportunity for specialists in computational biomechanics to present their latest methodologies and advancements. This volume comprises eighteen of the newest approaches and applications of computational biomechanics, from researchers in Australia, New Zealand, USA, UK, Switzerland, Scotland, France and Russia. Some of the interesting topics discussed are: tailored computational models; traumatic brain injury; soft-tissue mechanics; medical image analysis; and clinically-relevant simulations. One of the greatest challenges facing the computational engineering community is to extend the success of computational mechanics to fields outside traditional engineering, in particular to biology, the biomedical sciences, and medicine. We hope the research presented within this book series will contribute to overcoming this grand challenge.

  18. Model-based normalization for iterative 3D PET image

    International Nuclear Information System (INIS)

    Bai, B.; Li, Q.; Asma, E.; Leahy, R.M.; Holdsworth, C.H.; Chatziioannou, A.; Tai, Y.C.

    2002-01-01

    We describe a method for normalization in 3D PET for use with maximum a posteriori (MAP) or other iterative model-based image reconstruction methods. This approach is an extension of previous factored normalization methods in which we include separate factors for detector sensitivity, geometric response, block effects and deadtime. Since our MAP reconstruction approach already models some of the geometric factors in the forward projection, the normalization factors must be modified to account only for effects not already included in the model. We describe a maximum likelihood approach to joint estimation of the count-rate independent normalization factors, which we apply to data from a uniform cylindrical source. We then compute block-wise and block-profile deadtime correction factors using singles and coincidence data, respectively, from a multiframe cylindrical source. We have applied this method for reconstruction of data from the Concorde microPET P4 scanner. Quantitative evaluation of this method using well-counter measurements of activity in a multicompartment phantom compares favourably with normalization based directly on cylindrical source measurements. (author)

  19. Design Considerations, Modeling and Analysis for the Multispectral Thermal Imager

    International Nuclear Information System (INIS)

    Borel, C.C.; Clodius, W.B.; Cooke, B.J.; Smith, B.W.; Weber, P.G.

    1999-01-01

    The design of remote sensing systems is driven by the need to provide cost-effective, substantive answers to questions posed by our customers. This is especially important for space-based systems, which tend to be expensive, and which generally cannot be changed after they are launched. We report here on the approach we employed in developing the desired attributes of a satellite mission, namely the Multispectral Thermal Imager. After an initial scoping study, we applied a procedure which we call: ''End-to-end modeling and analysis (EEM).'' We began with target attributes, translated to observable signatures and then propagated the signatures through the atmosphere to the sensor location. We modeled the sensor attributes to yield a simulated data stream, which was then analyzed to retrieve information about the original target. The retrieved signature was then compared to the original to obtain a figure of merit: hence the term ''end-to-end modeling and analysis.'' We base the EEM in physics to ensure high fidelity and to permit scaling. As the actual design of the payload evolves, and as real hardware is tested, we can update the EEM to facilitate trade studies, and to judge, for example, whether components that deviate from specifications are acceptable

  20. Fat segmentation on chest CT images via fuzzy models

    Science.gov (United States)

    Tong, Yubing; Udupa, Jayaram K.; Wu, Caiyun; Pednekar, Gargi; Subramanian, Janani Rajan; Lederer, David J.; Christie, Jason; Torigian, Drew A.

    2016-03-01

    Quantification of fat throughout the body is vital for the study of many diseases. In the thorax, it is important for lung transplant candidates since obesity and being underweight are contraindications to lung transplantation given their associations with increased mortality. Common approaches for thoracic fat segmentation are all interactive in nature, requiring significant manual effort to draw the interfaces between fat and muscle with low efficiency and questionable repeatability. The goal of this paper is to explore a practical way for the segmentation of subcutaneous adipose tissue (SAT) and visceral adipose tissue (VAT) components of chest fat based on a recently developed body-wide automatic anatomy recognition (AAR) methodology. The AAR approach involves 3 main steps: building a fuzzy anatomy model of the body region involving all its major representative objects, recognizing objects in any given test image, and delineating the objects. We made several modifications to these steps to develop an effective solution to delineate SAT/VAT components of fat. Two new objects representing interfaces of SAT and VAT regions with other tissues, SatIn and VatIn are defined, rather than using directly the SAT and VAT components as objects for constructing the models. A hierarchical arrangement of these new and other reference objects is built to facilitate their recognition in the hierarchical order. Subsequently, accurate delineations of the SAT/VAT components are derived from these objects. Unenhanced CT images from 40 lung transplant candidates were utilized in experimentally evaluating this new strategy. Mean object location error achieved was about 2 voxels and delineation error in terms of false positive and false negative volume fractions were, respectively, 0.07 and 0.1 for SAT and 0.04 and 0.2 for VAT.

  1. Model-based image reconstruction for four-dimensional PET

    International Nuclear Information System (INIS)

    Li Tianfang; Thorndyke, Brian; Schreibmann, Eduard; Yang Yong; Xing Lei

    2006-01-01

    Positron emission tonography (PET) is useful in diagnosis and radiation treatment planning for a variety of cancers. For patients with cancers in thoracic or upper abdominal region, the respiratory motion produces large distortions in the tumor shape and size, affecting the accuracy in both diagnosis and treatment. Four-dimensional (4D) (gated) PET aims to reduce the motion artifacts and to provide accurate measurement of the tumor volume and the tracer concentration. A major issue in 4D PET is the lack of statistics. Since the collected photons are divided into several frames in the 4D PET scan, the quality of each reconstructed frame degrades as the number of frames increases. The increased noise in each frame heavily degrades the quantitative accuracy of the PET imaging. In this work, we propose a method to enhance the performance of 4D PET by developing a new technique of 4D PET reconstruction with incorporation of an organ motion model derived from 4D-CT images. The method is based on the well-known maximum-likelihood expectation-maximization (ML-EM) algorithm. During the processes of forward- and backward-projection in the ML-EM iterations, all projection data acquired at different phases are combined together to update the emission map with the aid of deformable model, the statistics is therefore greatly improved. The proposed algorithm was first evaluated with computer simulations using a mathematical dynamic phantom. Experiment with a moving physical phantom was then carried out to demonstrate the accuracy of the proposed method and the increase of signal-to-noise ratio over three-dimensional PET. Finally, the 4D PET reconstruction was applied to a patient case

  2. Model-based estimation of breast percent density in raw and processed full-field digital mammography images from image-acquisition physics and patient-image characteristics

    Science.gov (United States)

    Keller, Brad M.; Nathan, Diane L.; Conant, Emily F.; Kontos, Despina

    2012-03-01

    Breast percent density (PD%), as measured mammographically, is one of the strongest known risk factors for breast cancer. While the majority of studies to date have focused on PD% assessment from digitized film mammograms, digital mammography (DM) is becoming increasingly common, and allows for direct PD% assessment at the time of imaging. This work investigates the accuracy of a generalized linear model-based (GLM) estimation of PD% from raw and postprocessed digital mammograms, utilizing image acquisition physics, patient characteristics and gray-level intensity features of the specific image. The model is trained in a leave-one-woman-out fashion on a series of 81 cases for which bilateral, mediolateral-oblique DM images were available in both raw and post-processed format. Baseline continuous and categorical density estimates were provided by a trained breast-imaging radiologist. Regression analysis is performed and Pearson's correlation, r, and Cohen's kappa, κ, are computed. The GLM PD% estimation model performed well on both processed (r=0.89, p<0.001) and raw (r=0.75, p<0.001) images. Model agreement with radiologist assigned density categories was also high for processed (κ=0.79, p<0.001) and raw (κ=0.76, p<0.001) images. Model-based prediction of breast PD% could allow for a reproducible estimation of breast density, providing a rapid risk assessment tool for clinical practice.

  3. 2-D Fused Image Reconstruction approach for Microwave Tomography: a theoretical assessment using FDTD Model.

    Science.gov (United States)

    Bindu, G; Semenov, S

    2013-01-01

    This paper describes an efficient two-dimensional fused image reconstruction approach for Microwave Tomography (MWT). Finite Difference Time Domain (FDTD) models were created for a viable MWT experimental system having the transceivers modelled using thin wire approximation with resistive voltage sources. Born Iterative and Distorted Born Iterative methods have been employed for image reconstruction with the extremity imaging being done using a differential imaging technique. The forward solver in the imaging algorithm employs the FDTD method of solving the time domain Maxwell's equations with the regularisation parameter computed using a stochastic approach. The algorithm is tested with 10% noise inclusion and successful image reconstruction has been shown implying its robustness.

  4. Mineral Precipitation in Fractures: Multiscale Imaging and Geochemical Modeling

    Science.gov (United States)

    Hajirezaie, S.; Peters, C. A.; Swift, A.; Sheets, J. M.; Cole, D. R.; Crandall, D.; Cheshire, M.; Stack, A. G.; Anovitz, L. M.

    2017-12-01

    For subsurface energy technologies such as geologic carbon sequestration, fractures are potential pathways for fluid migration from target formations. Highly permeable fractures may become sealed by mineral precipitation. In this study, we examined shale specimens with existing cemented fractures as natural analogues, using an array of imaging methods to characterize mineralogy and porosity at several spatial scales. In addition, we used reactive transport modeling to investigate geochemical conditions that can lead to extensive mineral precipitation and to simulate the impacts on fracture hydraulic properties. The naturally-cemented fractured rock specimens were from the Upper Wolfcamp formation in Texas, at 10,000 ft depth. The specimens were scanned using x-ray computed tomography (xCT) at resolution of 13 microns. The xCT images revealed an original fracture aperture of 1.9 mm filled with several distinct mineral phases and vuggy void regions, and the mineral phase volumes and surface areas were quantified and mapped in 3D. Specimens were thin-sectioned and examined at micron- and submicron-scales using petrographic microscopy (PM), scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), and small angle X-ray scattering (SAXS). Collectively these methods revealed crystals of dolomite as large as 900 microns in length overlain with a heterogeneous mixture of carbonate minerals including calcite, dolomite, and Fe-rich dolomite, interspersed at spatial scales as small as 5 microns. In addition, secondary precipitation of SiO2 was found to fill some of the void space. This multiscale imaging was used to inform the reactive transport modeling employed to examine the conditions that can cause the observed mineral precipitation in fractures at a larger scale. Two brines containing solutions that when mixed would lead to precipitation of various carbonate minerals were simulated as injectants into a fracture domain. In particular, the competing

  5. FWFusion: Fuzzy Whale Fusion model for MRI multimodal image ...

    Indian Academy of Sciences (India)

    Hanmant Venketrao Patil

    2018-03-14

    Mar 14, 2018 ... consider multi-modality medical images other than PET and MRI images. ... cipal component averaging based on DWT for fusing CT-. MRI and MRI ..... sub-band LH of the fused image, the distance measure is given based on the ...... sustainable integrated dynamic ship routing and scheduling optimization.

  6. Discrete imaging models for three-dimensional optoacoustic tomography using radially symmetric expansion functions.

    Science.gov (United States)

    Wang, Kun; Schoonover, Robert W; Su, Richard; Oraevsky, Alexander; Anastasio, Mark A

    2014-05-01

    Optoacoustic tomography (OAT), also known as photoacoustic tomography, is an emerging computed biomedical imaging modality that exploits optical contrast and ultrasonic detection principles. Iterative image reconstruction algorithms that are based on discrete imaging models are actively being developed for OAT due to their ability to improve image quality by incorporating accurate models of the imaging physics, instrument response, and measurement noise. In this work, we investigate the use of discrete imaging models based on Kaiser-Bessel window functions for iterative image reconstruction in OAT. A closed-form expression for the pressure produced by a Kaiser-Bessel function is calculated, which facilitates accurate computation of the system matrix. Computer-simulation and experimental studies are employed to demonstrate the potential advantages of Kaiser-Bessel function-based iterative image reconstruction in OAT.

  7. Sparse Representation Based Binary Hypothesis Model for Hyperspectral Image Classification

    Directory of Open Access Journals (Sweden)

    Yidong Tang

    2016-01-01

    Full Text Available The sparse representation based classifier (SRC and its kernel version (KSRC have been employed for hyperspectral image (HSI classification. However, the state-of-the-art SRC often aims at extended surface objects with linear mixture in smooth scene and assumes that the number of classes is given. Considering the small target with complex background, a sparse representation based binary hypothesis (SRBBH model is established in this paper. In this model, a query pixel is represented in two ways, which are, respectively, by background dictionary and by union dictionary. The background dictionary is composed of samples selected from the local dual concentric window centered at the query pixel. Thus, for each pixel the classification issue becomes an adaptive multiclass classification problem, where only the number of desired classes is required. Furthermore, the kernel method is employed to improve the interclass separability. In kernel space, the coding vector is obtained by using kernel-based orthogonal matching pursuit (KOMP algorithm. Then the query pixel can be labeled by the characteristics of the coding vectors. Instead of directly using the reconstruction residuals, the different impacts the background dictionary and union dictionary have on reconstruction are used for validation and classification. It enhances the discrimination and hence improves the performance.

  8. Lunar photometric modelling with SMART-1/AMIE imaging data

    International Nuclear Information System (INIS)

    Wilkman, O.; Muinonen, K.; Videen, G.; Josset, J.-L.; Souchon, A.

    2014-01-01

    We investigate the light-scattering properties of the lunar mare areas. A large photometric dataset was extracted from images taken by the AMIE camera on board the SMART-1 spacecraft. Inter-particle shadowing effects in the regolith are modelled using ray-tracing simulations, and then a phase function is fit to the data using Bayesian techniques and Markov chain Monte Carlo. Additionally, the data are fit with phase functions computed from radiative-transfer coherent-backscatter (RT-CB) simulations. The results indicate that the lunar photometry, including both the opposition effect and azimuthal effects, can be explained well with a combination of inter-particle shadowing and coherent backscattering. Our results produce loose constraints on the mare physical properties. The RT-CB results indicate that the scattering volume element is optically thick. In both the Bayesian analysis and the RT-CB fit, models with lower packing density and/or higher surface roughness always produce better fits to the data than densely packed, smoother ones

  9. Median Filter Noise Reduction of Image and Backpropagation Neural Network Model for Cervical Cancer Classification

    Science.gov (United States)

    Wutsqa, D. U.; Marwah, M.

    2017-06-01

    In this paper, we consider spatial operation median filter to reduce the noise in the cervical images yielded by colposcopy tool. The backpropagation neural network (BPNN) model is applied to the colposcopy images to classify cervical cancer. The classification process requires an image extraction by using a gray level co-occurrence matrix (GLCM) method to obtain image features that are used as inputs of BPNN model. The advantage of noise reduction is evaluated by comparing the performances of BPNN models with and without spatial operation median filter. The experimental result shows that the spatial operation median filter can improve the accuracy of the BPNN model for cervical cancer classification.

  10. A Hybrid Probabilistic Model for Unified Collaborative and Content-Based Image Tagging.

    Science.gov (United States)

    Zhou, Ning; Cheung, William K; Qiu, Guoping; Xue, Xiangyang

    2011-07-01

    The increasing availability of large quantities of user contributed images with labels has provided opportunities to develop automatic tools to tag images to facilitate image search and retrieval. In this paper, we present a novel hybrid probabilistic model (HPM) which integrates low-level image features and high-level user provided tags to automatically tag images. For images without any tags, HPM predicts new tags based solely on the low-level image features. For images with user provided tags, HPM jointly exploits both the image features and the tags in a unified probabilistic framework to recommend additional tags to label the images. The HPM framework makes use of the tag-image association matrix (TIAM). However, since the number of images is usually very large and user-provided tags are diverse, TIAM is very sparse, thus making it difficult to reliably estimate tag-to-tag co-occurrence probabilities. We developed a collaborative filtering method based on nonnegative matrix factorization (NMF) for tackling this data sparsity issue. Also, an L1 norm kernel method is used to estimate the correlations between image features and semantic concepts. The effectiveness of the proposed approach has been evaluated using three databases containing 5,000 images with 371 tags, 31,695 images with 5,587 tags, and 269,648 images with 5,018 tags, respectively.

  11. Integral equation models for image restoration: high accuracy methods and fast algorithms

    International Nuclear Information System (INIS)

    Lu, Yao; Shen, Lixin; Xu, Yuesheng

    2010-01-01

    Discrete models are consistently used as practical models for image restoration. They are piecewise constant approximations of true physical (continuous) models, and hence, inevitably impose bottleneck model errors. We propose to work directly with continuous models for image restoration aiming at suppressing the model errors caused by the discrete models. A systematic study is conducted in this paper for the continuous out-of-focus image models which can be formulated as an integral equation of the first kind. The resulting integral equation is regularized by the Lavrentiev method and the Tikhonov method. We develop fast multiscale algorithms having high accuracy to solve the regularized integral equations of the second kind. Numerical experiments show that the methods based on the continuous model perform much better than those based on discrete models, in terms of PSNR values and visual quality of the reconstructed images

  12. A model of destination image promotion with a case study of Nanjing, P. R. China

    Science.gov (United States)

    Xiang Li; Hans Vogelsong

    2003-01-01

    Destination image has long been a popular research topic in tourism studies. However, methods used to integrate image in real marketing practice and evaluating the market performance in a systematic way are still puzzling to practitioners. A destination image promotion model is proposed in this paper as an effort to solve the problem. The roles of some major factors...

  13. Generation of synthetic Kinect depth images based on empirical noise model

    DEFF Research Database (Denmark)

    Iversen, Thorbjørn Mosekjær; Kraft, Dirk

    2017-01-01

    The development, training and evaluation of computer vision algorithms rely on the availability of a large number of images. The acquisition of these images can be time-consuming if they are recorded using real sensors. An alternative is to rely on synthetic images which can be rapidly generated....... This Letter describes a novel method for the simulation of Kinect v1 depth images. The method is based on an existing empirical noise model from the literature. The authors show that their relatively simple method is able to provide depth images which have a high similarity with real depth images....

  14. "Big Data" in Rheumatology: Intelligent Data Modeling Improves the Quality of Imaging Data.

    Science.gov (United States)

    Landewé, Robert B M; van der Heijde, Désirée

    2018-05-01

    Analysis of imaging data in rheumatology is a challenge. Reliability of scores is an issue for several reasons. Signal-to-noise ratio of most imaging techniques is rather unfavorable (too little signal in relation to too much noise). Optimal use of all available data may help to increase credibility of imaging data, but knowledge of complicated statistical methodology and the help of skilled statisticians are required. Clinicians should appreciate the merits of sophisticated data modeling and liaise with statisticians to increase the quality of imaging results, as proper imaging studies in rheumatology imply more than a supersensitive imaging technique alone. Copyright © 2018 Elsevier Inc. All rights reserved.

  15. Despeckling Polsar Images Based on Relative Total Variation Model

    Science.gov (United States)

    Jiang, C.; He, X. F.; Yang, L. J.; Jiang, J.; Wang, D. Y.; Yuan, Y.

    2018-04-01

    Relatively total variation (RTV) algorithm, which can effectively decompose structure information and texture in image, is employed in extracting main structures of the image. However, applying the RTV directly to polarimetric SAR (PolSAR) image filtering will not preserve polarimetric information. A new RTV approach based on the complex Wishart distribution is proposed considering the polarimetric properties of PolSAR. The proposed polarization RTV (PolRTV) algorithm can be used for PolSAR image filtering. The L-band Airborne SAR (AIRSAR) San Francisco data is used to demonstrate the effectiveness of the proposed algorithm in speckle suppression, structural information preservation, and polarimetric property preservation.

  16. Balanced sparse model for tight frames in compressed sensing magnetic resonance imaging.

    Directory of Open Access Journals (Sweden)

    Yunsong Liu

    Full Text Available Compressed sensing has shown to be promising to accelerate magnetic resonance imaging. In this new technology, magnetic resonance images are usually reconstructed by enforcing its sparsity in sparse image reconstruction models, including both synthesis and analysis models. The synthesis model assumes that an image is a sparse combination of atom signals while the analysis model assumes that an image is sparse after the application of an analysis operator. Balanced model is a new sparse model that bridges analysis and synthesis models by introducing a penalty term on the distance of frame coefficients to the range of the analysis operator. In this paper, we study the performance of the balanced model in tight frame based compressed sensing magnetic resonance imaging and propose a new efficient numerical algorithm to solve the optimization problem. By tuning the balancing parameter, the new model achieves solutions of three models. It is found that the balanced model has a comparable performance with the analysis model. Besides, both of them achieve better results than the synthesis model no matter what value the balancing parameter is. Experiment shows that our proposed numerical algorithm constrained split augmented Lagrangian shrinkage algorithm for balanced model (C-SALSA-B converges faster than previously proposed algorithms accelerated proximal algorithm (APG and alternating directional method of multipliers for balanced model (ADMM-B.

  17. In vivo 3-dimensional photoacoustic imaging of the renal vasculature in preclinical rodent models

    OpenAIRE

    Ogunlade, O.; Connell, J. J.; Huang, J. L.; Zhang, E.; Lythgoe, M. F.; Long, D. A.; Beard, P.

    2017-01-01

    Non-invasive imaging of the kidney vasculature in preclinical murine models is important for studying renal development, diseases and evaluating new therapies, but is challenging to achieve using existing imaging modalities. Photoacoustic imaging is a promising new technique that is particularly well suited to visualising the vasculature and could provide an alternative to existing preclinical imaging methods for studying renal vascular anatomy and function. To investigate this, an all-optica...

  18. Multi-Modal Imaging in a Mouse Model of Orthotopic Lung Cancer

    OpenAIRE

    Patel, Priya; Kato, Tatsuya; Ujiie, Hideki; Wada, Hironobu; Lee, Daiyoon; Hu, Hsin-pei; Hirohashi, Kentaro; Ahn, Jin Young; Zheng, Jinzi; Yasufuku, Kazuhiro

    2016-01-01

    Background Investigation of CF800, a novel PEGylated nano-liposomal imaging agent containing indocyanine green (ICG) and iohexol, for real-time near infrared (NIR) fluorescence and computed tomography (CT) image-guided surgery in an orthotopic lung cancer model in nude mice. Methods CF800 was intravenously administered into 13 mice bearing the H460 orthotopic human lung cancer. At 48 h post-injection (peak imaging agent accumulation time point), ex vivo NIR and CT imaging was performed. A cli...

  19. Comprehensive model for predicting perceptual image quality of smart mobile devices.

    Science.gov (United States)

    Gong, Rui; Xu, Haisong; Luo, M R; Li, Haifeng

    2015-01-01

    An image quality model for smart mobile devices was proposed based on visual assessments of several image quality attributes. A series of psychophysical experiments were carried out on two kinds of smart mobile devices, i.e., smart phones and tablet computers, in which naturalness, colorfulness, brightness, contrast, sharpness, clearness, and overall image quality were visually evaluated under three lighting environments via categorical judgment method for various application types of test images. On the basis of Pearson correlation coefficients and factor analysis, the overall image quality could first be predicted by its two constituent attributes with multiple linear regression functions for different types of images, respectively, and then the mathematical expressions were built to link the constituent image quality attributes with the physical parameters of smart mobile devices and image appearance factors. The procedure and algorithms were applicable to various smart mobile devices, different lighting conditions, and multiple types of images, and performance was verified by the visual data.

  20. MO-C-18A-01: Advances in Model-Based 3D Image Reconstruction

    International Nuclear Information System (INIS)

    Chen, G; Pan, X; Stayman, J; Samei, E

    2014-01-01

    Recent years have seen the emergence of CT image reconstruction techniques that exploit physical models of the imaging system, photon statistics, and even the patient to achieve improved 3D image quality and/or reduction of radiation dose. With numerous advantages in comparison to conventional 3D filtered backprojection, such techniques bring a variety of challenges as well, including: a demanding computational load associated with sophisticated forward models and iterative optimization methods; nonlinearity and nonstationarity in image quality characteristics; a complex dependency on multiple free parameters; and the need to understand how best to incorporate prior information (including patient-specific prior images) within the reconstruction process. The advantages, however, are even greater – for example: improved image quality; reduced dose; robustness to noise and artifacts; task-specific reconstruction protocols; suitability to novel CT imaging platforms and noncircular orbits; and incorporation of known characteristics of the imager and patient that are conventionally discarded. This symposium features experts in 3D image reconstruction, image quality assessment, and the translation of such methods to emerging clinical applications. Dr. Chen will address novel methods for the incorporation of prior information in 3D and 4D CT reconstruction techniques. Dr. Pan will show recent advances in optimization-based reconstruction that enable potential reduction of dose and sampling requirements. Dr. Stayman will describe a “task-based imaging” approach that leverages models of the imaging system and patient in combination with a specification of the imaging task to optimize both the acquisition and reconstruction process. Dr. Samei will describe the development of methods for image quality assessment in such nonlinear reconstruction techniques and the use of these methods to characterize and optimize image quality and dose in a spectrum of clinical

  1. Superresolution Interferometric Imaging with Sparse Modeling Using Total Squared Variation: Application to Imaging the Black Hole Shadow

    Science.gov (United States)

    Kuramochi, Kazuki; Akiyama, Kazunori; Ikeda, Shiro; Tazaki, Fumie; Fish, Vincent L.; Pu, Hung-Yi; Asada, Keiichi; Honma, Mareki

    2018-05-01

    We propose a new imaging technique for interferometry using sparse modeling, utilizing two regularization terms: the ℓ 1-norm and a new function named total squared variation (TSV) of the brightness distribution. First, we demonstrate that our technique may achieve a superresolution of ∼30% compared with the traditional CLEAN beam size using synthetic observations of two point sources. Second, we present simulated observations of three physically motivated static models of Sgr A* with the Event Horizon Telescope (EHT) to show the performance of proposed techniques in greater detail. Remarkably, in both the image and gradient domains, the optimal beam size minimizing root-mean-squared errors is ≲10% of the traditional CLEAN beam size for ℓ 1+TSV regularization, and non-convolved reconstructed images have smaller errors than beam-convolved reconstructed images. This indicates that TSV is well matched to the expected physical properties of the astronomical images and the traditional post-processing technique of Gaussian convolution in interferometric imaging may not be required. We also propose a feature-extraction method to detect circular features from the image of a black hole shadow and use it to evaluate the performance of the image reconstruction. With this method and reconstructed images, the EHT can constrain the radius of the black hole shadow with an accuracy of ∼10%–20% in present simulations for Sgr A*, suggesting that the EHT would be able to provide useful independent measurements of the mass of the supermassive black holes in Sgr A* and also another primary target, M87.

  2. An three-dimensional imaging algorithm based on the radiation model of electric dipole

    International Nuclear Information System (INIS)

    Tian Bo; Zhong Weijun; Tong Chuangming

    2011-01-01

    A three-dimensional imaging algorithm based on the radiation model of dipole (DBP) is presented. On the foundation of researching the principle of the back projection (BP) algorithm, the relationship between the near field imaging model and far field imaging model is analyzed based on the scattering model. Firstly, the far field sampling data is transferred to the near field sampling data through applying the radiation theory of dipole. Then the dealt sampling data was projected to the imaging region to obtain the images of targets. The capability of the new algorithm to detect targets is verified by using finite-difference time-domain method (FDTD), and the coupling effect for imaging is analyzed. (authors)

  3. Synthetic SAR Image Generation using Sensor, Terrain and Target Models

    DEFF Research Database (Denmark)

    Kusk, Anders; Abulaitijiang, Adili; Dall, Jørgen

    2016-01-01

    A tool to generate synthetic SAR images of objects set on a clutter background is described. The purpose is to generate images for training Automatic Target Recognition and Identification algorithms. The tool employs a commercial electromagnetic simulation program to calculate radar cross section...

  4. Probabilistic image processing by means of the Bethe approximation for the Q-Ising model

    International Nuclear Information System (INIS)

    Tanaka, Kazuyuki; Inoue, Jun-ichi; Titterington, D M

    2003-01-01

    The framework of Bayesian image restoration for multi-valued images by means of the Q-Ising model with nearest-neighbour interactions is presented. Hyperparameters in the probabilistic model are determined so as to maximize the marginal likelihood. A practical algorithm is described for multi-valued image restoration based on the Bethe approximation. The algorithm corresponds to loopy belief propagation in artificial intelligence. We conclude that, in real world grey-level images, the Q-Ising model can give us good results

  5. Matching Images to Models: Camera Calibration for 3-D Surface Reconstruction

    Science.gov (United States)

    Morris, Robin D.; Smelyanskiy, Vadim N.; Cheeseman. Peter C.; Norvig, Peter (Technical Monitor)

    2001-01-01

    In a previous paper we described a system which recursively recovers a super-resolved three dimensional surface model from a set of images of the surface. In that paper we assumed that the camera calibration for each image was known. In this paper we solve two problems. Firstly, if an estimate of the surface is already known, the problem is to calibrate a new image relative to the existing surface model. Secondly, if no surface estimate is available, the relative camera calibration between the images in the set must be estimated. This will allow an initial surface model to be estimated. Results of both types of estimation are given.

  6. Microscopic imaging through turbid media Monte Carlo modeling and applications

    CERN Document Server

    Gu, Min; Deng, Xiaoyuan

    2015-01-01

    This book provides a systematic introduction to the principles of microscopic imaging through tissue-like turbid media in terms of Monte-Carlo simulation. It describes various gating mechanisms based on the physical differences between the unscattered and scattered photons and method for microscopic image reconstruction, using the concept of the effective point spread function. Imaging an object embedded in a turbid medium is a challenging problem in physics as well as in biophotonics. A turbid medium surrounding an object under inspection causes multiple scattering, which degrades the contrast, resolution and signal-to-noise ratio. Biological tissues are typically turbid media. Microscopic imaging through a tissue-like turbid medium can provide higher resolution than transillumination imaging in which no objective is used. This book serves as a valuable reference for engineers and scientists working on microscopy of tissue turbid media.

  7. Image Analysis of a Negatively Curved Graphitic Sheet Model for Amorphous Carbon

    Science.gov (United States)

    Bursill, L. A.; Bourgeois, Laure N.

    High-resolution electron micrographs are presented which show essentially curved single sheets of graphitic carbon. Image calculations are then presented for the random surface schwarzite-related model of Townsend et al. (Phys. Rev. Lett. 69, 921-924, 1992). Comparison with experimental images does not rule out the contention that such models, containing surfaces of negative curvature, may be useful for predicting some physical properties of specific forms of nanoporous carbon. Some difficulties of the model predictions, when compared with the experimental images, are pointed out. The range of application of this model, as well as competing models, is discussed briefly.

  8. Relationship model among sport event image, destination image, and tourist satisfaction of Tour de Singkarak in West Sumatera

    Directory of Open Access Journals (Sweden)

    Ratni Prima Lita

    2015-06-01

    Full Text Available Sport events Tour de Singkarak (TDS can increase tourist arrivals to West Sumatera. At least at the time of execution, the majority of participants and team supporters (sports tourist brings the families. Although there are claims about the arrival of tourists, it requires to see the impact of sports events TDS and comprehensive long-term basis to the West Sumatera image as a tourist destination (destination image and its impact on tourist satisfaction. This study re-conceptualizes the interconnec-tedness among sport event image, tourist destination image, perception and the effect on tourists satisfaction. The investigation on this interconnection is expected to reveal empirically tested model. As an explanatory in nature, this study uses explanatory survey and cross sectional data. In total of 100 spectators of Tour de Singkarak in West Sumatera, they got involved in survey and they were taken by convenience sam-pling technique. Analysis of this data was done by using variance based structural equation modeling. It was found that sport event image and destination image signifi-cantly affect the satisfaction of spectators of Tour de Singkarak.

  9. Waif goodbye! Average-size female models promote positive body image and appeal to consumers.

    Science.gov (United States)

    Diedrichs, Phillippa C; Lee, Christina

    2011-10-01

    Despite consensus that exposure to media images of thin fashion models is associated with poor body image and disordered eating behaviours, few attempts have been made to enact change in the media. This study sought to investigate an effective alternative to current media imagery, by exploring the advertising effectiveness of average-size female fashion models, and their impact on the body image of both women and men. A sample of 171 women and 120 men were assigned to one of three advertisement conditions: no models, thin models and average-size models. Women and men rated average-size models as equally effective in advertisements as thin and no models. For women with average and high levels of internalisation of cultural beauty ideals, exposure to average-size female models was associated with a significantly more positive body image state in comparison to exposure to thin models and no models. For men reporting high levels of internalisation, exposure to average-size models was also associated with a more positive body image state in comparison to viewing thin models. These findings suggest that average-size female models can promote positive body image and appeal to consumers.

  10. Pseudorandom numbers: evolutionary models in image processing, biology, and nonlinear dynamic systems

    Science.gov (United States)

    Yaroslavsky, Leonid P.

    1996-11-01

    We show that one can treat pseudo-random generators, evolutionary models of texture images, iterative local adaptive filters for image restoration and enhancement and growth models in biology and material sciences in a unified way as special cases of dynamic systems with a nonlinear feedback.

  11. Thermal analysis of fused deposition modeling process using infrared thermography imaging and finite element modeling

    Science.gov (United States)

    Zhou, Xunfei; Hsieh, Sheng-Jen

    2017-05-01

    After years of development, Fused Deposition Modeling (FDM) has become the most popular technique in commercial 3D printing due to its cost effectiveness and easy-to-operate fabrication process. Mechanical strength and dimensional accuracy are two of the most important factors for reliability of FDM products. However, the solid-liquid-solid state changes of material in the FDM process make it difficult to monitor and model. In this paper, an experimental model was developed to apply cost-effective infrared thermography imaging method to acquire temperature history of filaments at the interface and their corresponding cooling mechanism. A three-dimensional finite element model was constructed to simulate the same process using element "birth and death" feature and validated with the thermal response from the experimental model. In 6 of 9 experimental conditions, a maximum of 13% difference existed between the experimental and numerical models. This work suggests that numerical modeling of FDM process is reliable and can facilitate better understanding of bead spreading and road-to-road bonding mechanics during fabrication.

  12. Metal artifact reduction algorithm based on model images and spatial information

    Energy Technology Data Exchange (ETDEWEB)

    Wu, Jay [Institute of Radiological Science, Central Taiwan University of Science and Technology, Taichung, Taiwan (China); Shih, Cheng-Ting [Department of Biomedical Engineering and Environmental Sciences, National Tsing-Hua University, Hsinchu, Taiwan (China); Chang, Shu-Jun [Health Physics Division, Institute of Nuclear Energy Research, Taoyuan, Taiwan (China); Huang, Tzung-Chi [Department of Biomedical Imaging and Radiological Science, China Medical University, Taichung, Taiwan (China); Sun, Jing-Yi [Institute of Radiological Science, Central Taiwan University of Science and Technology, Taichung, Taiwan (China); Wu, Tung-Hsin, E-mail: tung@ym.edu.tw [Department of Biomedical Imaging and Radiological Sciences, National Yang-Ming University, No.155, Sec. 2, Linong Street, Taipei 112, Taiwan (China)

    2011-10-01

    Computed tomography (CT) has become one of the most favorable choices for diagnosis of trauma. However, high-density metal implants can induce metal artifacts in CT images, compromising image quality. In this study, we proposed a model-based metal artifact reduction (MAR) algorithm. First, we built a model image using the k-means clustering technique with spatial information and calculated the difference between the original image and the model image. Then, the projection data of these two images were combined using an exponential weighting function. At last, the corrected image was reconstructed using the filter back-projection algorithm. Two metal-artifact contaminated images were studied. For the cylindrical water phantom image, the metal artifact was effectively removed. The mean CT number of water was improved from -28.95{+-}97.97 to -4.76{+-}4.28. For the clinical pelvic CT image, the dark band and the metal line were removed, and the continuity and uniformity of the soft tissue were recovered as well. These results indicate that the proposed MAR algorithm is useful for reducing metal artifact and could improve the diagnostic value of metal-artifact contaminated CT images.

  13. High-Resolution Longitudinal Screening with Magnetic Resonance Imaging in a Murine Brain Cancer Model

    Directory of Open Access Journals (Sweden)

    Nicholas A. Bock

    2003-11-01

    Full Text Available One of the main limitations of intracranial models of diseases is our present inability to monitor and evaluate the intracranial compartment noninvasively over time. Therefore, there is a growing need for imaging modalities that provide thorough neuropathological evaluations of xenograft and transgenic models of intracranial pathology. In this study, we have established protocols for multiple-mouse magnetic resonance imaging (MRI to follow the growth and behavior of intracranial xenografts of gliomas longitudinally. We successfully obtained weekly images on 16 mice for a total of 5 weeks on a 7-T multiple-mouse MRI. T2- and Ti-weighted imaging with gadolinium enhancement of vascularity was used to detect tumor margins, tumor size, and growth. These experiments, using 3D whole brain images obtained in four mice at once, demonstrate the feasibility of obtaining repeat radiological images in intracranial tumor models and suggest that MRI should be incorporated as a research modality for the investigation of intracranial pathobiology.

  14. Imaging and Modeling Laboratory in Neurobiology and Oncology - IMNC. Activity report 2008-2012

    International Nuclear Information System (INIS)

    Charon, Yves; Arlaud, Nathalie; Mastrippolito, Roland

    2014-09-01

    The Imaging and Modeling Laboratory in Neurobiology and Oncology (IMNC) is an interdisciplinary unit shared between the Paris-Sud and Paris-Diderot universities and the National Institute of Nuclear and particle physics (IN2P3). Created in January 2006, the laboratory activities are structured around three main topics: the clinical and pre-clinical multi-modal imaging (optical and isotopic), the modeling of tumoral processes, and radiotherapy. This report presents the activities of the laboratory during the years 2008-2012: 1 - Forewords; 2 - Highlights; 3 - Research teams: Small animal imaging; Metabolism, imaging and olfaction; Surgery imaging in oncology; Quantification in molecular imaging; Modeling of biological systems; 4 - Technical innovations: Instrumentation, Scientific calculation, Biology department, valorisation and open-source softwares; 5 - Publications; 6 - Scientific life, communication and teaching activities; 7 - Laboratory operation; 8 - Perspectives

  15. 3D fluoroscopic image estimation using patient-specific 4DCBCT-based motion models

    International Nuclear Information System (INIS)

    Dhou, S; Hurwitz, M; Cai, W; Rottmann, J; Williams, C; Wagar, M; Berbeco, R; Lewis, J H; Mishra, P; Li, R; Ionascu, D

    2015-01-01

    3D fluoroscopic images represent volumetric patient anatomy during treatment with high spatial and temporal resolution. 3D fluoroscopic images estimated using motion models built using 4DCT images, taken days or weeks prior to treatment, do not reliably represent patient anatomy during treatment. In this study we developed and performed initial evaluation of techniques to develop patient-specific motion models from 4D cone-beam CT (4DCBCT) images, taken immediately before treatment, and used these models to estimate 3D fluoroscopic images based on 2D kV projections captured during treatment. We evaluate the accuracy of 3D fluoroscopic images by comparison to ground truth digital and physical phantom images. The performance of 4DCBCT-based and 4DCT-based motion models are compared in simulated clinical situations representing tumor baseline shift or initial patient positioning errors. The results of this study demonstrate the ability for 4DCBCT imaging to generate motion models that can account for changes that cannot be accounted for with 4DCT-based motion models. When simulating tumor baseline shift and patient positioning errors of up to 5 mm, the average tumor localization error and the 95th percentile error in six datasets were 1.20 and 2.2 mm, respectively, for 4DCBCT-based motion models. 4DCT-based motion models applied to the same six datasets resulted in average tumor localization error and the 95th percentile error of 4.18 and 5.4 mm, respectively. Analysis of voxel-wise intensity differences was also conducted for all experiments. In summary, this study demonstrates the feasibility of 4DCBCT-based 3D fluoroscopic image generation in digital and physical phantoms and shows the potential advantage of 4DCBCT-based 3D fluoroscopic image estimation when there are changes in anatomy between the time of 4DCT imaging and the time of treatment delivery. (paper)

  16. Automated image analysis of lateral lumber X-rays by a form model

    International Nuclear Information System (INIS)

    Mahnken, A.H.; Kohnen, M.; Steinberg, S.; Wein, B.B.; Guenther, R.W.

    2001-01-01

    Development of a software for fully automated image analysis of lateral lumbar spine X-rays. Material and method: Using the concept of active shape models, we developed a software that produces a form model of the lumbar spine from lateral lumbar spine radiographs and runs an automated image segmentation. This model is able to detect lumbar vertebrae automatically after the filtering of digitized X-ray images. The model was trained with 20 lateral lumbar spine radiographs with no pathological findings before we evaluated the software with 30 further X-ray images which were sorted by image quality ranging from one (best) to three (worst). There were 10 images for each quality. Results: Image recognition strongly depended on image quality. In group one 52 and in group two 51 out of 60 vertebral bodies including the sacrum were recognized, but in group three only 18 vertebral bodies were properly identified. Conclusion: Fully automated and reliable recognition of vertebral bodies from lateral spine radiographs using the concept of active shape models is possible. The precision of this technique is limited by the superposition of different structures. Further improvements are necessary. Therefore standardized image quality and enlargement of the training data set are required. (orig.) [de

  17. A spinal cord window chamber model for in vivo longitudinal multimodal optical and acoustic imaging in a murine model.

    Directory of Open Access Journals (Sweden)

    Sarah A Figley

    Full Text Available In vivo and direct imaging of the murine spinal cord and its vasculature using multimodal (optical and acoustic imaging techniques could significantly advance preclinical studies of the spinal cord. Such intrinsically high resolution and complementary imaging technologies could provide a powerful means of quantitatively monitoring changes in anatomy, structure, physiology and function of the living cord over time after traumatic injury, onset of disease, or therapeutic intervention. However, longitudinal in vivo imaging of the intact spinal cord in rodent models has been challenging, requiring repeated surgeries to expose the cord for imaging or sacrifice of animals at various time points for ex vivo tissue analysis. To address these limitations, we have developed an implantable spinal cord window chamber (SCWC device and procedures in mice for repeated multimodal intravital microscopic imaging of the cord and its vasculature in situ. We present methodology for using our SCWC to achieve spatially co-registered optical-acoustic imaging performed serially for up to four weeks, without damaging the cord or induction of locomotor deficits in implanted animals. To demonstrate the feasibility, we used the SCWC model to study the response of the normal spinal cord vasculature to ionizing radiation over time using white light and fluorescence microscopy combined with optical coherence tomography (OCT in vivo. In vivo power Doppler ultrasound and photoacoustics were used to directly visualize the cord and vascular structures and to measure hemoglobin oxygen saturation through the complete spinal cord, respectively. The model was also used for intravital imaging of spinal micrometastases resulting from primary brain tumor using fluorescence and bioluminescence imaging. Our SCWC model overcomes previous in vivo imaging challenges, and our data provide evidence of the broader utility of hybridized optical-acoustic imaging methods for obtaining

  18. A 4DCT imaging-based breathing lung model with relative hysteresis

    Energy Technology Data Exchange (ETDEWEB)

    Miyawaki, Shinjiro; Choi, Sanghun [IIHR – Hydroscience & Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Hoffman, Eric A. [Department of Biomedical Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Medicine, The University of Iowa, Iowa City, IA 52242 (United States); Department of Radiology, The University of Iowa, Iowa City, IA 52242 (United States); Lin, Ching-Long, E-mail: ching-long-lin@uiowa.edu [IIHR – Hydroscience & Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Mechanical and Industrial Engineering, The University of Iowa, 3131 Seamans Center, Iowa City, IA 52242 (United States)

    2016-12-01

    To reproduce realistic airway motion and airflow, the authors developed a deforming lung computational fluid dynamics (CFD) model based on four-dimensional (4D, space and time) dynamic computed tomography (CT) images. A total of 13 time points within controlled tidal volume respiration were used to account for realistic and irregular lung motion in human volunteers. Because of the irregular motion of 4DCT-based airways, we identified an optimal interpolation method for airway surface deformation during respiration, and implemented a computational solid mechanics-based moving mesh algorithm to produce smooth deforming airway mesh. In addition, we developed physiologically realistic airflow boundary conditions for both models based on multiple images and a single image. Furthermore, we examined simplified models based on one or two dynamic or static images. By comparing these simplified models with the model based on 13 dynamic images, we investigated the effects of relative hysteresis of lung structure with respect to lung volume, lung deformation, and imaging methods, i.e., dynamic vs. static scans, on CFD-predicted pressure drop. The effect of imaging method on pressure drop was 24 percentage points due to the differences in airflow distribution and airway geometry. - Highlights: • We developed a breathing human lung CFD model based on 4D-dynamic CT images. • The 4DCT-based breathing lung model is able to capture lung relative hysteresis. • A new boundary condition for lung model based on one static CT image was proposed. • The difference between lung models based on 4D and static CT images was quantified.

  19. William, a voxel model of child anatomy from tomographic images for Monte Carlo dosimetry calculations

    International Nuclear Information System (INIS)

    Caon, M.

    2010-01-01

    Full text: Medical imaging provides two-dimensional pictures of the human internal anatomy from which may be constructed a three-dimensional model of organs and tissues suitable for calculation of dose from radiation. Diagnostic CT provides the greatest exposure to radiation per examination and the frequency of CT examination is high. Esti mates of dose from diagnostic radiography are still determined from data derived from geometric models (rather than anatomical models), models scaled from adult bodies (rather than bodies of children) and CT scanner hardware that is no longer used. The aim of anatomical modelling is to produce a mathematical representation of internal anatomy that has organs of realistic size, shape and positioning. The organs and tissues are represented by a great many cuboidal volumes (voxels). The conversion of medical images to voxels is called segmentation and on completion every pixel in an image is assigned to a tissue or organ. Segmentation is time consuming. An image processing pack age is used to identify organ boundaries in each image. Thirty to forty tomographic voxel models of anatomy have been reported in the literature. Each model is of an individual, or a composite from several individuals. Images of children are particularly scarce. So there remains a need for more paediatric anatomical models. I am working on segmenting ''William'' who is 368 PET-CT images from head to toe of a seven year old boy. William will be used for Monte Carlo dose calculations of dose from CT examination using a simulated modern CT scanner.

  20. Unified and Modular Modeling and Functional Verification Framework of Real-Time Image Signal Processors

    Directory of Open Access Journals (Sweden)

    Abhishek Jain

    2016-01-01

    Full Text Available In VLSI industry, image signal processing algorithms are developed and evaluated using software models before implementation of RTL and firmware. After the finalization of the algorithm, software models are used as a golden reference model for the image signal processor (ISP RTL and firmware development. In this paper, we are describing the unified and modular modeling framework of image signal processing algorithms used for different applications such as ISP algorithms development, reference for hardware (HW implementation, reference for firmware (FW implementation, and bit-true certification. The universal verification methodology- (UVM- based functional verification framework of image signal processors using software reference models is described. Further, IP-XACT based tools for automatic generation of functional verification environment files and model map files are described. The proposed framework is developed both with host interface and with core using virtual register interface (VRI approach. This modeling and functional verification framework is used in real-time image signal processing applications including cellphone, smart cameras, and image compression. The main motivation behind this work is to propose the best efficient, reusable, and automated framework for modeling and verification of image signal processor (ISP designs. The proposed framework shows better results and significant improvement is observed in product verification time, verification cost, and quality of the designs.

  1. AUTOMATED ANALYSIS OF QUANTITATIVE IMAGE DATA USING ISOMORPHIC FUNCTIONAL MIXED MODELS, WITH APPLICATION TO PROTEOMICS DATA.

    Science.gov (United States)

    Morris, Jeffrey S; Baladandayuthapani, Veerabhadran; Herrick, Richard C; Sanna, Pietro; Gutstein, Howard

    2011-01-01

    Image data are increasingly encountered and are of growing importance in many areas of science. Much of these data are quantitative image data, which are characterized by intensities that represent some measurement of interest in the scanned images. The data typically consist of multiple images on the same domain and the goal of the research is to combine the quantitative information across images to make inference about populations or interventions. In this paper, we present a unified analysis framework for the analysis of quantitative image data using a Bayesian functional mixed model approach. This framework is flexible enough to handle complex, irregular images with many local features, and can model the simultaneous effects of multiple factors on the image intensities and account for the correlation between images induced by the design. We introduce a general isomorphic modeling approach to fitting the functional mixed model, of which the wavelet-based functional mixed model is one special case. With suitable modeling choices, this approach leads to efficient calculations and can result in flexible modeling and adaptive smoothing of the salient features in the data. The proposed method has the following advantages: it can be run automatically, it produces inferential plots indicating which regions of the image are associated with each factor, it simultaneously considers the practical and statistical significance of findings, and it controls the false discovery rate. Although the method we present is general and can be applied to quantitative image data from any application, in this paper we focus on image-based proteomic data. We apply our method to an animal study investigating the effects of opiate addiction on the brain proteome. Our image-based functional mixed model approach finds results that are missed with conventional spot-based analysis approaches. In particular, we find that the significant regions of the image identified by the proposed method

  2. Validation of models in an imaging infrared simulation

    CSIR Research Space (South Africa)

    Willers, C

    2007-10-01

    Full Text Available threeprocessesfortransformingtheinformationbetweentheentities. Reality/ Problem Entity Conceptual Model Computerized Model Model Validation ModelVerification Model Qualification Computer Implementation Analysisand Modelling Simulationand Experimentation “Substantiationthata....C.Refsgaard ,ModellingGuidelines-terminology andguidingprinciples, AdvancesinWaterResources, Vol27,No1,January2004,?pp.71-82(12),Elsevier. et.al. [5]N.Oreskes,et.al.,Verification,Validation,andConfirmationof NumericalModelsintheEarthSciences,Science,Vol263, Number...

  3. The National Cancer Informatics Program (NCIP) Annotation and Image Markup (AIM) Foundation model.

    Science.gov (United States)

    Mongkolwat, Pattanasak; Kleper, Vladimir; Talbot, Skip; Rubin, Daniel

    2014-12-01

    Knowledge contained within in vivo imaging annotated by human experts or computer programs is typically stored as unstructured text and separated from other associated information. The National Cancer Informatics Program (NCIP) Annotation and Image Markup (AIM) Foundation information model is an evolution of the National Institute of Health's (NIH) National Cancer Institute's (NCI) Cancer Bioinformatics Grid (caBIG®) AIM model. The model applies to various image types created by various techniques and disciplines. It has evolved in response to the feedback and changing demands from the imaging community at NCI. The foundation model serves as a base for other imaging disciplines that want to extend the type of information the model collects. The model captures physical entities and their characteristics, imaging observation entities and their characteristics, markups (two- and three-dimensional), AIM statements, calculations, image source, inferences, annotation role, task context or workflow, audit trail, AIM creator details, equipment used to create AIM instances, subject demographics, and adjudication observations. An AIM instance can be stored as a Digital Imaging and Communications in Medicine (DICOM) structured reporting (SR) object or Extensible Markup Language (XML) document for further processing and analysis. An AIM instance consists of one or more annotations and associated markups of a single finding along with other ancillary information in the AIM model. An annotation describes information about the meaning of pixel data in an image. A markup is a graphical drawing placed on the image that depicts a region of interest. This paper describes fundamental AIM concepts and how to use and extend AIM for various imaging disciplines.

  4. Development and practice for a PACS-based interactive teaching model for CT image

    International Nuclear Information System (INIS)

    Tian Junzhang; Jiang Guihua; Zheng Liyin; Wang Ling; Wenhua; Liang Lianbao

    2002-01-01

    Objective: To explore the interactive teaching model for CT imaging based on PACS, and provide the clinician and young radiologist with continued medical education. Methods: 100 M trunk net was adopted in PACS and 10 M was exchanged on desktop. Teaching model was installed in browse and diagnosis workstation. Teaching contents were classified according to region and managed according to branch model. Text data derived from authoritative textbooks, monograph, and periodicals. Imaging data derived from cases proved by pathology and clinic. The data were obtained through digital camera and scanner or from PACS. After edited and transformed into standard digital image through DICOM server, they were saved in HD of PACS image server with file form. Results: Teaching model for CT imaging provided kinds of cases of CT sign, clinic characteristics, pathology and distinguishing diagnosis. Normal section anatomy, typical image, and its notation could be browsed real time. Teaching model for CT imaging could provide reference to teaching, diagnosis and report. Conclusion: PACS-based teaching model for CT imaging could provide interactive teaching and scientific research tool and improve work quality and efficiency

  5. Modulation transfer function cascade model for a sampled IR imaging system.

    Science.gov (United States)

    de Luca, L; Cardone, G

    1991-05-01

    The performance of the infrared scanning radiometer (IRSR) is strongly stressed in convective heat transfer applications where high spatial frequencies in the signal that describes the thermal image are present. The need to characterize more deeply the system spatial resolution has led to the formulation of a cascade model for the evaluation of the actual modulation transfer function of a sampled IR imaging system. The model can yield both the aliasing band and the averaged modulation response for a general sampling subsystem. For a line scan imaging system, which is the case of a typical IRSR, a rule of thumb that states whether the combined sampling-imaging system is either imaging-dependent or sampling-dependent is proposed. The model is tested by comparing it with other noncascade models as well as by ad hoc measurements performed on a commercial digitized IRSR.

  6. Improving Sediment Transport Prediction by Assimilating Satellite Images in a Tidal Bay Model of Hong Kong

    Directory of Open Access Journals (Sweden)

    Peng Zhang

    2014-03-01

    Full Text Available Numerical models being one of the major tools for sediment dynamic studies in complex coastal waters are now benefitting from remote sensing images that are easily available for model inputs. The present study explored various methods of integrating remote sensing ocean color data into a numerical model to improve sediment transport prediction in a tide-dominated bay in Hong Kong, Deep Bay. Two sea surface sediment datasets delineated from satellite images from the Moderate Resolution Imaging Spectra-radiometer (MODIS were assimilated into a coastal ocean model of the bay for one tidal cycle. It was found that remote sensing sediment information enhanced the sediment transport model ability by validating the model results with in situ measurements. Model results showed that root mean square errors of forecast sediment both at the surface layer and the vertical layers from the model with satellite sediment assimilation are reduced by at least 36% over the model without assimilation.

  7. Mammogram synthesis using a 3D simulation. I. Breast tissue model and image acquisition simulation

    International Nuclear Information System (INIS)

    Bakic, Predrag R.; Albert, Michael; Brzakovic, Dragana; Maidment, Andrew D. A.

    2002-01-01

    A method is proposed for generating synthetic mammograms based upon simulations of breast tissue and the mammographic imaging process. A computer breast model has been designed with a realistic distribution of large and medium scale tissue structures. Parameters controlling the size and placement of simulated structures (adipose compartments and ducts) provide a method for consistently modeling images of the same simulated breast with modified position or acquisition parameters. The mammographic imaging process is simulated using a compression model and a model of the x-ray image acquisition process. The compression model estimates breast deformation using tissue elasticity parameters found in the literature and clinical force values. The synthetic mammograms were generated by a mammogram acquisition model using a monoenergetic parallel beam approximation applied to the synthetically compressed breast phantom

  8. A singular K-space model for fast reconstruction of magnetic resonance images from undersampled data.

    Science.gov (United States)

    Luo, Jianhua; Mou, Zhiying; Qin, Binjie; Li, Wanqing; Ogunbona, Philip; Robini, Marc C; Zhu, Yuemin

    2017-12-09

    Reconstructing magnetic resonance images from undersampled k-space data is a challenging problem. This paper introduces a novel method of image reconstruction from undersampled k-space data based on the concept of singularizing operators and a novel singular k-space model. Exploring the sparsity of an image in the k-space, the singular k-space model (SKM) is proposed in terms of the k-space functions of a singularizing operator. The singularizing operator is constructed by combining basic difference operators. An algorithm is developed to reliably estimate the model parameters from undersampled k-space data. The estimated parameters are then used to recover the missing k-space data through the model, subsequently achieving high-quality reconstruction of the image using inverse Fourier transform. Experiments on physical phantom and real brain MR images have shown that the proposed SKM method constantly outperforms the popular total variation (TV) and the classical zero-filling (ZF) methods regardless of the undersampling rates, the noise levels, and the image structures. For the same objective quality of the reconstructed images, the proposed method requires much less k-space data than the TV method. The SKM method is an effective method for fast MRI reconstruction from the undersampled k-space data. Graphical abstract Two Real Images and their sparsified images by singularizing operator.

  9. Single-shot spiral imaging enabled by an expanded encoding model: Demonstration in diffusion MRI.

    Science.gov (United States)

    Wilm, Bertram J; Barmet, Christoph; Gross, Simon; Kasper, Lars; Vannesjo, S Johanna; Haeberlin, Max; Dietrich, Benjamin E; Brunner, David O; Schmid, Thomas; Pruessmann, Klaas P

    2017-01-01

    The purpose of this work was to improve the quality of single-shot spiral MRI and demonstrate its application for diffusion-weighted imaging. Image formation is based on an expanded encoding model that accounts for dynamic magnetic fields up to third order in space, nonuniform static B 0 , and coil sensitivity encoding. The encoding model is determined by B 0 mapping, sensitivity mapping, and concurrent field monitoring. Reconstruction is performed by iterative inversion of the expanded signal equations. Diffusion-tensor imaging with single-shot spiral readouts is performed in a phantom and in vivo, using a clinical 3T instrument. Image quality is assessed in terms of artefact levels, image congruence, and the influence of the different encoding factors. Using the full encoding model, diffusion-weighted single-shot spiral imaging of high quality is accomplished both in vitro and in vivo. Accounting for actual field dynamics, including higher orders, is found to be critical to suppress blurring, aliasing, and distortion. Enhanced image congruence permitted data fusion and diffusion tensor analysis without coregistration. Use of an expanded signal model largely overcomes the traditional vulnerability of spiral imaging with long readouts. It renders single-shot spirals competitive with echo-planar readouts and thus deploys shorter echo times and superior readout efficiency for diffusion imaging and further prospective applications. Magn Reson Med 77:83-91, 2017. © 2016 International Society for Magnetic Resonance in Medicine. © 2016 International Society for Magnetic Resonance in Medicine.

  10. Mixed Higher Order Variational Model for Image Recovery

    Directory of Open Access Journals (Sweden)

    Pengfei Liu

    2014-01-01

    Full Text Available A novel mixed higher order regularizer involving the first and second degree image derivatives is proposed in this paper. Using spectral decomposition, we reformulate the new regularizer as a weighted L1-L2 mixed norm of image derivatives. Due to the equivalent formulation of the proposed regularizer, an efficient fast projected gradient algorithm combined with monotone fast iterative shrinkage thresholding, called, FPG-MFISTA, is designed to solve the resulting variational image recovery problems under majorization-minimization framework. Finally, we demonstrate the effectiveness of the proposed regularization scheme by the experimental comparisons with total variation (TV scheme, nonlocal TV scheme, and current second degree methods. Specifically, the proposed approach achieves better results than related state-of-the-art methods in terms of peak signal to ratio (PSNR and restoration quality.

  11. Myocardial imaging with thallium-201: an experimental model for analysis of the true myocardial and background image components

    International Nuclear Information System (INIS)

    Narahara, K.A.; Hamilton, G.W.; Williams, D.L.; Gould, K.L.

    1977-01-01

    The true myocardial and background components of a resting thallium-201 myocardial image were determined in an experimental dog model. True background was determined by imaging after the heart had been removed and replaced with a water-filled balloon of equal size and shape. In all studies, the background estimated from the region surrounding the heart exceeded true background activity. Furthermore, the relationship between true myocardial background and that estimated from the pericardiac region was inconsistent. Background estimates based on the activity surrounding the heart were not accurate predictors of true background activity

  12. A Variational Level Set Model Combined with FCMS for Image Clustering Segmentation

    Directory of Open Access Journals (Sweden)

    Liming Tang

    2014-01-01

    Full Text Available The fuzzy C means clustering algorithm with spatial constraint (FCMS is effective for image segmentation. However, it lacks essential smoothing constraints to the cluster boundaries and enough robustness to the noise. Samson et al. proposed a variational level set model for image clustering segmentation, which can get the smooth cluster boundaries and closed cluster regions due to the use of level set scheme. However it is very sensitive to the noise since it is actually a hard C means clustering model. In this paper, based on Samson’s work, we propose a new variational level set model combined with FCMS for image clustering segmentation. Compared with FCMS clustering, the proposed model can get smooth cluster boundaries and closed cluster regions due to the use of level set scheme. In addition, a block-based energy is incorporated into the energy functional, which enables the proposed model to be more robust to the noise than FCMS clustering and Samson’s model. Some experiments on the synthetic and real images are performed to assess the performance of the proposed model. Compared with some classical image segmentation models, the proposed model has a better performance for the images contaminated by different noise levels.

  13. Range and Image Based Modelling: a way for Frescoed Vault Texturing Optimization

    Science.gov (United States)

    Caroti, G.; Martínez-Espejo Zaragoza, I.; Piemonte, A.

    2015-02-01

    In the restoration of the frescoed vaults it is not only important to know the geometric shape of the painted surface, but it is essential to document its chromatic characterization and conservation status. The new techniques of range-based and image-based modelling, each with its limitations and advantages, offer a wide range of methods to obtain the geometric shape. In fact, several studies widely document that laser scanning enable obtaining three-dimensional models with high morphological precision. However, the quality level of the colour obtained with built-in laser scanner cameras is not comparable to that obtained for the shape. It is possible to improve the texture quality by means of a dedicated photographic campaign. This procedure, however, requires to calculate the external orientation of each image identifying the control points on it and on the model through a costly step of post processing. With image-based modelling techniques it is possible to obtain models that maintain the colour quality of the original images, but with variable geometric precision, locally lower than the laser scanning model. This paper presents a methodology that uses the camera external orientation parameters calculated by image based modelling techniques to project the same image on the model obtained from the laser scan. This methodology is tested on an Italian mirror (a schifo) frescoed vault. In the paper the different models, the analysis of precision and the efficiency evaluation of proposed methodology are presented.

  14. Bayesian inference on multiscale models for poisson intensity estimation: applications to photon-limited image denoising.

    Science.gov (United States)

    Lefkimmiatis, Stamatios; Maragos, Petros; Papandreou, George

    2009-08-01

    We present an improved statistical model for analyzing Poisson processes, with applications to photon-limited imaging. We build on previous work, adopting a multiscale representation of the Poisson process in which the ratios of the underlying Poisson intensities (rates) in adjacent scales are modeled as mixtures of conjugate parametric distributions. Our main contributions include: 1) a rigorous and robust regularized expectation-maximization (EM) algorithm for maximum-likelihood estimation of the rate-ratio density parameters directly from the noisy observed Poisson data (counts); 2) extension of the method to work under a multiscale hidden Markov tree model (HMT) which couples the mixture label assignments in consecutive scales, thus modeling interscale coefficient dependencies in the vicinity of image edges; 3) exploration of a 2-D recursive quad-tree image representation, involving Dirichlet-mixture rate-ratio densities, instead of the conventional separable binary-tree image representation involving beta-mixture rate-ratio densities; and 4) a novel multiscale image representation, which we term Poisson-Haar decomposition, that better models the image edge structure, thus yielding improved performance. Experimental results on standard images with artificially simulated Poisson noise and on real photon-limited images demonstrate the effectiveness of the proposed techniques.

  15. A Space-Time Periodic Task Model for Recommendation of Remote Sensing Images

    Directory of Open Access Journals (Sweden)

    Xiuhong Zhang

    2018-01-01

    Full Text Available With the rapid development of remote sensing technology, the quantity and variety of remote sensing images are growing so quickly that proactive and personalized access to data has become an inevitable trend. One of the active approaches is remote sensing image recommendation, which can offer related image products to users according to their preference. Although multiple studies on remote sensing retrieval and recommendation have been performed, most of these studies model the user profiles only from the perspective of spatial area or image features. In this paper, we propose a spatiotemporal recommendation method for remote sensing data based on the probabilistic latent topic model, which is named the Space-Time Periodic Task model (STPT. User retrieval behaviors of remote sensing images are represented as mixtures of latent tasks, which act as links between users and images. Each task is associated with the joint probability distribution of space, time and image characteristics. Meanwhile, the von Mises distribution is introduced to fit the distribution of tasks over time. Then, we adopt Gibbs sampling to learn the random variables and parameters and present the inference algorithm for our model. Experiments show that the proposed STPT model can improve the capability and efficiency of remote sensing image data services.

  16. Perona Malik anisotropic diffusion model using Peaceman Rachford scheme on digital radiographic image

    International Nuclear Information System (INIS)

    Halim, Suhaila Abd; Razak, Rohayu Abd; Ibrahim, Arsmah; Manurung, Yupiter HP

    2014-01-01

    In image processing, it is important to remove noise without affecting the image structure as well as preserving all the edges. Perona Malik Anisotropic Diffusion (PMAD) is a PDE-based model which is suitable for image denoising and edge detection problems. In this paper, the Peaceman Rachford scheme is applied on PMAD to remove unwanted noise as the scheme is efficient and unconditionally stable. The capability of the scheme to remove noise is evaluated on several digital radiography weld defect images computed using MATLAB R2009a. Experimental results obtained show that the Peaceman Rachford scheme improves the image quality substantially well based on the Peak Signal to Noise Ratio (PSNR). The Peaceman Rachford scheme used in solving the PMAD model successfully removes unwanted noise in digital radiographic image

  17. Perona Malik anisotropic diffusion model using Peaceman Rachford scheme on digital radiographic image

    Energy Technology Data Exchange (ETDEWEB)

    Halim, Suhaila Abd; Razak, Rohayu Abd; Ibrahim, Arsmah [Center of Mathematics Studies, Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, 40450 Shah Alam. Selangor DE (Malaysia); Manurung, Yupiter HP [Advanced Manufacturing Technology Excellence Center (AMTEx), Faculty of Mechanical Engineering, Universiti Teknologi MARA, 40450 Shah Alam. Selangor DE (Malaysia)

    2014-06-19

    In image processing, it is important to remove noise without affecting the image structure as well as preserving all the edges. Perona Malik Anisotropic Diffusion (PMAD) is a PDE-based model which is suitable for image denoising and edge detection problems. In this paper, the Peaceman Rachford scheme is applied on PMAD to remove unwanted noise as the scheme is efficient and unconditionally stable. The capability of the scheme to remove noise is evaluated on several digital radiography weld defect images computed using MATLAB R2009a. Experimental results obtained show that the Peaceman Rachford scheme improves the image quality substantially well based on the Peak Signal to Noise Ratio (PSNR). The Peaceman Rachford scheme used in solving the PMAD model successfully removes unwanted noise in digital radiographic image.

  18. Depth Reconstruction from Single Images Using a Convolutional Neural Network and a Condition Random Field Model.

    Science.gov (United States)

    Liu, Dan; Liu, Xuejun; Wu, Yiguang

    2018-04-24

    This paper presents an effective approach for depth reconstruction from a single image through the incorporation of semantic information and local details from the image. A unified framework for depth acquisition is constructed by joining a deep Convolutional Neural Network (CNN) and a continuous pairwise Conditional Random Field (CRF) model. Semantic information and relative depth trends of local regions inside the image are integrated into the framework. A deep CNN network is firstly used to automatically learn a hierarchical feature representation of the image. To get more local details in the image, the relative depth trends of local regions are incorporated into the network. Combined with semantic information of the image, a continuous pairwise CRF is then established and is used as the loss function of the unified model. Experiments on real scenes demonstrate that the proposed approach is effective and that the approach obtains satisfactory results.

  19. Innovative biomagnetic imaging sensors for breast cancer: A model-based study

    International Nuclear Information System (INIS)

    Deng, Y.; Golkowski, M.

    2012-01-01

    Breast cancer is a serious potential health problem for all women and is the second leading cause of cancer deaths in the United States. The current screening procedures and imaging techniques, including x-ray mammography, clinical biopsy, ultrasound imaging, and magnetic resonance imaging, provide only 73% accuracy in detecting breast cancer. This gives the impetus to explore alternate techniques for imaging the breast and detecting early stage tumors. Among the complementary methods, the noninvasive biomagnetic breast imaging is attractive and promising, because both ionizing radiation and breast compressions that the prevalent x-ray mammography suffers from are avoided. It furthermore offers very high contrast because of the significant electromagnetic properties' differences between the cancerous, benign, and normal breast tissues. In this paper, a hybrid and accurate modeling tool for biomagnetic breast imaging is developed, which couples the electromagnetic and ultrasonic energies, and initial validations between the model predication and experimental findings are conducted.

  20. New deconvolution method for microscopic images based on the continuous Gaussian radial basis function interpolation model.

    Science.gov (United States)

    Chen, Zhaoxue; Chen, Hao

    2014-01-01

    A deconvolution method based on the Gaussian radial basis function (GRBF) interpolation is proposed. Both the original image and Gaussian point spread function are expressed as the same continuous GRBF model, thus image degradation is simplified as convolution of two continuous Gaussian functions, and image deconvolution is converted to calculate the weighted coefficients of two-dimensional control points. Compared with Wiener filter and Lucy-Richardson algorithm, the GRBF method has an obvious advantage in the quality of restored images. In order to overcome such a defect of long-time computing, the method of graphic processing unit multithreading or increasing space interval of control points is adopted, respectively, to speed up the implementation of GRBF method. The experiments show that based on the continuous GRBF model, the image deconvolution can be efficiently implemented by the method, which also has a considerable reference value for the study of three-dimensional microscopic image deconvolution.

  1. Depth Reconstruction from Single Images Using a Convolutional Neural Network and a Condition Random Field Model

    Directory of Open Access Journals (Sweden)

    Dan Liu

    2018-04-01

    Full Text Available This paper presents an effective approach for depth reconstruction from a single image through the incorporation of semantic information and local details from the image. A unified framework for depth acquisition is constructed by joining a deep Convolutional Neural Network (CNN and a continuous pairwise Conditional Random Field (CRF model. Semantic information and relative depth trends of local regions inside the image are integrated into the framework. A deep CNN network is firstly used to automatically learn a hierarchical feature representation of the image. To get more local details in the image, the relative depth trends of local regions are incorporated into the network. Combined with semantic information of the image, a continuous pairwise CRF is then established and is used as the loss function of the unified model. Experiments on real scenes demonstrate that the proposed approach is effective and that the approach obtains satisfactory results.

  2. Rapid anatomical brain imaging using spiral acquisition and an expanded signal model.

    Science.gov (United States)

    Kasper, Lars; Engel, Maria; Barmet, Christoph; Haeberlin, Maximilian; Wilm, Bertram J; Dietrich, Benjamin E; Schmid, Thomas; Gross, Simon; Brunner, David O; Stephan, Klaas E; Pruessmann, Klaas P

    2018-03-01

    We report the deployment of spiral acquisition for high-resolution structural imaging at 7T. Long spiral readouts are rendered manageable by an expanded signal model including static off-resonance and B 0 dynamics along with k-space trajectories and coil sensitivity maps. Image reconstruction is accomplished by inversion of the signal model using an extension of the iterative non-Cartesian SENSE algorithm. Spiral readouts up to 25 ms are shown to permit whole-brain 2D imaging at 0.5 mm in-plane resolution in less than a minute. A range of options is explored, including proton-density and T 2 * contrast, acceleration by parallel imaging, different readout orientations, and the extraction of phase images. Results are shown to exhibit competitive image quality along with high geometric consistency. Copyright © 2017 Elsevier Inc. All rights reserved.

  3. Learning a generative model of images by factoring appearance and shape.

    Science.gov (United States)

    Le Roux, Nicolas; Heess, Nicolas; Shotton, Jamie; Winn, John

    2011-03-01

    Computer vision has grown tremendously in the past two decades. Despite all efforts, existing attempts at matching parts of the human visual system's extraordinary ability to understand visual scenes lack either scope or power. By combining the advantages of general low-level generative models and powerful layer-based and hierarchical models, this work aims at being a first step toward richer, more flexible models of images. After comparing various types of restricted Boltzmann machines (RBMs) able to model continuous-valued data, we introduce our basic model, the masked RBM, which explicitly models occlusion boundaries in image patches by factoring the appearance of any patch region from its shape. We then propose a generative model of larger images using a field of such RBMs. Finally, we discuss how masked RBMs could be stacked to form a deep model able to generate more complicated structures and suitable for various tasks such as segmentation or object recognition.

  4. Spiking cortical model-based nonlocal means method for speckle reduction in optical coherence tomography images

    Science.gov (United States)

    Zhang, Xuming; Li, Liu; Zhu, Fei; Hou, Wenguang; Chen, Xinjian

    2014-06-01

    Optical coherence tomography (OCT) images are usually degraded by significant speckle noise, which will strongly hamper their quantitative analysis. However, speckle noise reduction in OCT images is particularly challenging because of the difficulty in differentiating between noise and the information components of the speckle pattern. To address this problem, the spiking cortical model (SCM)-based nonlocal means method is presented. The proposed method explores self-similarities of OCT images based on rotation-invariant features of image patches extracted by SCM and then restores the speckled images by averaging the similar patches. This method can provide sufficient speckle reduction while preserving image details very well due to its effectiveness in finding reliable similar patches under high speckle noise contamination. When applied to the retinal OCT image, this method provides signal-to-noise ratio improvements of >16 dB with a small 5.4% loss of similarity.

  5. Design of a practical model-observer-based image quality assessment method for CT imaging systems

    Science.gov (United States)

    Tseng, Hsin-Wu; Fan, Jiahua; Cao, Guangzhi; Kupinski, Matthew A.; Sainath, Paavana

    2014-03-01

    The channelized Hotelling observer (CHO) is a powerful method for quantitative image quality evaluations of CT systems and their image reconstruction algorithms. It has recently been used to validate the dose reduction capability of iterative image-reconstruction algorithms implemented on CT imaging systems. The use of the CHO for routine and frequent system evaluations is desirable both for quality assurance evaluations as well as further system optimizations. The use of channels substantially reduces the amount of data required to achieve accurate estimates of observer performance. However, the number of scans required is still large even with the use of channels. This work explores different data reduction schemes and designs a new approach that requires only a few CT scans of a phantom. For this work, the leave-one-out likelihood (LOOL) method developed by Hoffbeck and Landgrebe is studied as an efficient method of estimating the covariance matrices needed to compute CHO performance. Three different kinds of approaches are included in the study: a conventional CHO estimation technique with a large sample size, a conventional technique with fewer samples, and the new LOOL-based approach with fewer samples. The mean value and standard deviation of area under ROC curve (AUC) is estimated by shuffle method. Both simulation and real data results indicate that an 80% data reduction can be achieved without loss of accuracy. This data reduction makes the proposed approach a practical tool for routine CT system assessment.

  6. Comparing planar image quality of rotating slat and parallel hole collimation: influence of system modeling

    International Nuclear Information System (INIS)

    Holen, Roel van; Vandenberghe, Stefaan; Staelens, Steven; Lemahieu, Ignace

    2008-01-01

    The main remaining challenge for a gamma camera is to overcome the existing trade-off between collimator spatial resolution and system sensitivity. This problem, strongly limiting the performance of parallel hole collimated gamma cameras, can be overcome by applying new collimator designs such as rotating slat (RS) collimators which have a much higher photon collection efficiency. The drawback of a RS collimated gamma camera is that, even for obtaining planar images, image reconstruction is needed, resulting in noise accumulation. However, nowadays iterative reconstruction techniques with accurate system modeling can provide better image quality. Because the impact of this modeling on image quality differs from one system to another, an objective assessment of the image quality obtained with a RS collimator is needed in comparison to classical projection images obtained using a parallel hole (PH) collimator. In this paper, a comparative study of image quality, achieved with system modeling, is presented. RS data are reconstructed to planar images using maximum likelihood expectation maximization (MLEM) with an accurate Monte Carlo derived system matrix while PH projections are deconvolved using a Monte Carlo derived point-spread function. Contrast-to-noise characteristics are used to show image quality for cold and hot spots of varying size. Influence of the object size and contrast is investigated using the optimal contrast-to-noise ratio (CNR o ). For a typical phantom setup, results show that cold spot imaging is slightly better for a PH collimator. For hot spot imaging, the CNR o of the RS images is found to increase with increasing lesion diameter and lesion contrast while it decreases when background dimensions become larger. Only for very large background dimensions in combination with low contrast lesions, the use of a PH collimator could be beneficial for hot spot imaging. In all other cases, the RS collimator scores better. Finally, the simulation of a

  7. Registered error between PET and CT images confirmed by a water model

    International Nuclear Information System (INIS)

    Chen Yangchun; Fan Mingwu; Xu Hao; Chen Ping; Zhang Chunlin

    2012-01-01

    The registered error between PET and CT imaging system was confirmed by a water model simulating clinical cases. A barrel of 6750 mL was filled with 59.2 MBq [ 18 F]-FDG and scanned after 80 min by 2 dimension model PET/CT. The CT images were used to attenuate the PET images. The CT/PET images were obtained by image morphological processing analyses without barrel wall. The relationship of the water image centroids of CT and PET images was established by linear regression analysis, and the registered error between PET and CT image could be computed one slice by one slice. The alignment program was done 4 times following the protocol given by GE Healthcare. Compared with centroids of water CT images, centroids of PET images were shifted to X-axis (0.011slice+0.63) mm, to Y-axis (0.022×slice+1.35) mm. To match CT images, PET images should be translated along X-axis (-2.69±0.15) mm, Y-axis (0.43±0.11) mm, Z-axis (0.86±0.23) mm, and X-axis be rotated by (0.06±0.07)°, Y-axis by (-0.01±0.08)°, and Z-axis by (0.11±0.07)°. So, the systematic registered error was not affected by load and its distribution. By finding the registered error between PET and CT images for coordinate rotation random error, the water model could confirm the registered results of PET-CT system corrected by Alignment parameters. (authors)

  8. Edge detection of solid motor' CT image based on gravitation model

    International Nuclear Information System (INIS)

    Yu Guanghui; Lu Hongyi; Zhu Min; Liu Xudong; Hou Zhiqiang

    2012-01-01

    In order to detect the edge of solid motor' CT image much better, a new edge detection operator base on gravitation model was put forward. The edge of CT image is got by the new operator. The superiority turned out by comparing the edge got by ordinary operator. The comparison among operators with different size shows that higher quality CT images need smaller size operator while the lower need the larger. (authors)

  9. Recent Advances in Translational Magnetic Resonance Imaging in Animal Models of Stress and Depression.

    Science.gov (United States)

    McIntosh, Allison L; Gormley, Shane; Tozzi, Leonardo; Frodl, Thomas; Harkin, Andrew

    2017-01-01

    Magnetic resonance imaging (MRI) is a valuable translational tool that can be used to investigate alterations in brain structure and function in both patients and animal models of disease. Regional changes in brain structure, functional connectivity, and metabolite concentrations have been reported in depressed patients, giving insight into the networks and brain regions involved, however preclinical models are less well characterized. The development of more effective treatments depends upon animal models that best translate to the human condition and animal models may be exploited to assess the molecular and cellular alterations that accompany neuroimaging changes. Recent advances in preclinical imaging have facilitated significant developments within the field, particularly relating to high resolution structural imaging and resting-state functional imaging which are emerging techniques in clinical research. This review aims to bring together the current literature on preclinical neuroimaging in animal models of stress and depression, highlighting promising avenues of research toward understanding the pathological basis of this hugely prevalent disorder.

  10. Unified Probabilistic Models for Face Recognition from a Single Example Image per Person

    Institute of Scientific and Technical Information of China (English)

    Pin Liao; Li Shen

    2004-01-01

    This paper presents a new technique of unified probabilistic models for face recognition from only one single example image per person. The unified models, trained on an obtained training set with multiple samples per person, are used to recognize facial images from another disjoint database with a single sample per person. Variations between facial images are modeled as two unified probabilistic models: within-class variations and between-class variations. Gaussian Mixture Models are used to approximate the distributions of the two variations and exploit a classifier combination method to improve the performance. Extensive experimental results on the ORL face database and the authors' database (the ICT-JDL database) including totally 1,750facial images of 350 individuals demonstrate that the proposed technique, compared with traditional eigenface method and some well-known traditional algorithms, is a significantly more effective and robust approach for face recognition.

  11. Automating the segmentation of medical images for the production of voxel tomographic computational models

    International Nuclear Information System (INIS)

    Caon, M.

    2001-01-01

    Radiation dosimetry for the diagnostic medical imaging procedures performed on humans requires anatomically accurate, computational models. These may be constructed from medical images as voxel-based tomographic models. However, they are time consuming to produce and as a consequence, there are few available. This paper discusses the emergence of semi-automatic segmentation techniques and describes an application (iRAD) written in Microsoft Visual Basic that allows the bitmap of a medical image to be segmented interactively and semi-automatically while displayed in Microsoft Excel. iRAD will decrease the time required to construct voxel models. Copyright (2001) Australasian College of Physical Scientists and Engineers in Medicine

  12. AMARSI: Aerosol modeling and retrieval from multi-spectral imagers

    NARCIS (Netherlands)

    Leeuw, G. de; Curier, R.L.; Staroverova, A.; Kokhanovsky, A.; Hoyningen-Huene, W. van; Rozanov, V.V.; Burrows, J.P.; Hesselmans, G.; Gale, L.; Bouvet, M.

    2008-01-01

    The AMARSI project aims at the development and validation of aerosol retrieval algorithms over ocean. One algorithm will be developed for application with data from the Multi Spectral Imager (MSI) on EarthCARE. A second algorithm will be developed using the combined information from AATSR and MERIS,

  13. AUGUSTO'S Sundial: Image-Based Modeling for Reverse Engeneering Purposes

    Science.gov (United States)

    Baiocchi, V.; Barbarella, M.; Del Pizzo, S.; Giannone, F.; Troisi, S.; Piccaro, C.; Marcantonio, D.

    2017-02-01

    A photogrammetric survey of a unique archaeological site is reported in this paper. The survey was performed using both a panoramic image-based solution and by classical procedure. The panoramic image-based solution was carried out employing a commercial solution: the Trimble V10 Imaging Rover (IR). Such instrument is an integrated cameras system that captures 360 degrees digital panoramas, composed of 12 images, with a single push. The direct comparison of the point clouds obtained with traditional photogrammetric procedure and V10 stations, using the same GCP coordinates has been carried out in Cloud Compare, open source software that can provide the comparison between two point clouds supplied by all the main statistical data. The site is a portion of the dial plate of the "Horologium Augusti" inaugurated in 9 B.C.E. in the area of Campo Marzio and still present intact in the same position, in a cellar of a building in Rome, around 7 meter below the present ground level.

  14. Missing data reconstruction using Gaussian mixture models for fingerprint images

    Science.gov (United States)

    Agaian, Sos S.; Yeole, Rushikesh D.; Rao, Shishir P.; Mulawka, Marzena; Troy, Mike; Reinecke, Gary

    2016-05-01

    Publisher's Note: This paper, originally published on 25 May 2016, was replaced with a revised version on 16 June 2016. If you downloaded the original PDF, but are unable to access the revision, please contact SPIE Digital Library Customer Service for assistance. One of the most important areas in biometrics is matching partial fingerprints in fingerprint databases. Recently, significant progress has been made in designing fingerprint identification systems for missing fingerprint information. However, a dependable reconstruction of fingerprint images still remains challenging due to the complexity and the ill-posed nature of the problem. In this article, both binary and gray-level images are reconstructed. This paper also presents a new similarity score to evaluate the performance of the reconstructed binary image. The offered fingerprint image identification system can be automated and extended to numerous other security applications such as postmortem fingerprints, forensic science, investigations, artificial intelligence, robotics, all-access control, and financial security, as well as for the verification of firearm purchasers, driver license applicants, etc.

  15. 3-Dimensional Iterative Forward Model for Microwave Imaging

    DEFF Research Database (Denmark)

    Kim, Oleksiy S.; Meincke, Peter

    2006-01-01

    The efficient solution of a forward scattering problem is the key point in nonlinear inversion schemes associated with microwave imaging. In this paper the solution is presented for the volume integral equation based on the method of moments (MoM) and accelerated with the adaptive integral method...

  16. Contourlet-based active contour model for PET image segmentation

    NARCIS (Netherlands)

    Abdoli, M.; Dierckx, R. A. J. O.; Zaidi, H.

    Purpose: PET-guided radiation therapy treatment planning, clinical diagnosis, assessment of tumor growth, and therapy response rely on the accurate delineation of the tumor volume and quantification of tracer uptake. Most PET image segmentation techniques proposed thus far are suboptimal in the

  17. Tarot Images and Spiritual Education: The Three I's Model

    Science.gov (United States)

    Semetsky, Inna

    2011-01-01

    The paper presents education as a process of human development toward becoming our authentic Selves and posits the Tarot hermeneutic as one of the means of holistic, spiritual education. As a system of images and symbols, Tarot encompasses the three I's represented by intuition, insight and imagination in contrast to the three R's of traditional…

  18. Infrared Radiography: Modeling X-ray Imaging without Harmful Radiation

    Science.gov (United States)

    Zietz, Otto; Mylott, Elliot; Widenhorn, Ralf

    2015-01-01

    Planar x-ray imaging is a ubiquitous diagnostic tool and is routinely performed to diagnose conditions as varied as bone fractures and pneumonia. The underlying principle is that the varying attenuation coefficients of air, water, tissue, bone, or metal implants within the body result in non-uniform transmission of x-ray radiation. Through the…

  19. Magnetic Resonance Imaging of Heart Failure Using a Swine Model

    Science.gov (United States)

    2011-03-21

    Suppl):I437-442. 36. McAlister FA, Teo KK, Taher M, Montague TJ, Humen D, Cheung L, Kiaii M, Yim R, Armstrong PW. Insights into the contemporary...Imaging 2001;13:714-721. 8. Ho VB, Meaney JF, Kent KC , Choyke PL, Watts R, Hood MN, Wang Y, Winchester P, Dong Q, Prince MR. Bolus-chase peripheral MR

  20. CT radiation dose and image quality optimization using a porcine model.

    Science.gov (United States)

    Zarb, Francis; McEntee, Mark F; Rainford, Louise

    2013-01-01

    To evaluate potential radiation dose savings and resultant image quality effects with regard to optimization of commonly performed computed tomography (CT) studies derived from imaging a porcine (pig) model. Imaging protocols for 4 clinical CT suites were developed based on the lowest milliamperage and kilovoltage, the highest pitch that could be set from current imaging protocol parameters, or both. This occurred before significant changes in noise, contrast, and spatial resolution were measured objectively on images produced from a quality assurance CT phantom. The current and derived phantom protocols were then applied to scan a porcine model for head, abdomen, and chest CT studies. Further optimized protocols were developed based on the same methodology as in the phantom study. The optimization achieved with respect to radiation dose and image quality was evaluated following data collection of radiation dose recordings and image quality review. Relative visual grading analysis of image quality criteria adapted from the European guidelines on radiology quality criteria for CT were used for studies completed with both the phantom-based or porcine-derived imaging protocols. In 5 out of 16 experimental combinations, the current clinical protocol was maintained. In 2 instances, the phantom protocol reduced radiation dose by 19% to 38%. In the remaining 9 instances, the optimization based on the porcine model further reduced radiation dose by 17% to 38%. The porcine model closely reflects anatomical structures in humans, allowing the grading of anatomical criteria as part of image quality review without radiation risks to human subjects. This study demonstrates that using a porcine model to evaluate CT optimization resulted in more radiation dose reduction than when imaging protocols were tested solely on quality assurance phantoms.

  1. Modeling decision-making in single- and multi-modal medical images

    Science.gov (United States)

    Canosa, R. L.; Baum, K. G.

    2009-02-01

    This research introduces a mode-specific model of visual saliency that can be used to highlight likely lesion locations and potential errors (false positives and false negatives) in single-mode PET and MRI images and multi-modal fused PET/MRI images. Fused-modality digital images are a relatively recent technological improvement in medical imaging; therefore, a novel component of this research is to characterize the perceptual response to these fused images. Three different fusion techniques were compared to single-mode displays in terms of observer error rates using synthetic human brain images generated from an anthropomorphic phantom. An eye-tracking experiment was performed with naÃve (non-radiologist) observers who viewed the single- and multi-modal images. The eye-tracking data allowed the errors to be classified into four categories: false positives, search errors (false negatives never fixated), recognition errors (false negatives fixated less than 350 milliseconds), and decision errors (false negatives fixated greater than 350 milliseconds). A saliency model consisting of a set of differentially weighted low-level feature maps is derived from the known error and ground truth locations extracted from a subset of the test images for each modality. The saliency model shows that lesion and error locations attract visual attention according to low-level image features such as color, luminance, and texture.

  2. Thick tissue diffusion model with binding to optimize topical staining in fluorescence breast cancer margin imaging

    Science.gov (United States)

    Xu, Xiaochun; Kang, Soyoung; Navarro-Comes, Eric; Wang, Yu; Liu, Jonathan T. C.; Tichauer, Kenneth M.

    2018-03-01

    Intraoperative tumor/surgical margin assessment is required to achieve higher tumor resection rate in breast-conserving surgery. Though current histology provides incomparable accuracy in margin assessment, thin tissue sectioning and the limited field of view of microscopy makes histology too time-consuming for intraoperative applications. If thick tissue, wide-field imaging can provide an acceptable assessment of tumor cells at the surface of resected tissues, an intraoperative protocol can be developed to guide the surgery and provide immediate feedback for surgeons. Topical staining of margins with cancer-targeted molecular imaging agents has the potential to provide the sensitivity needed to see microscopic cancer on a wide-field image; however, diffusion and nonspecific retention of imaging agents in thick tissue can significantly diminish tumor contrast with conventional methods. Here, we present a mathematical model to accurately simulate nonspecific retention, binding, and diffusion of imaging agents in thick tissue topical staining to guide and optimize future thick tissue staining and imaging protocol. In order to verify the accuracy and applicability of the model, diffusion profiles of cancer targeted and untargeted (control) nanoparticles at different staining times in A431 tumor xenografts were acquired for model comparison and tuning. The initial findings suggest the existence of nonspecific retention in the tissue, especially at the tissue surface. The simulator can be used to compare the effect of nonspecific retention, receptor binding and diffusion under various conditions (tissue type, imaging agent) and provides optimal staining and imaging protocols for targeted and control imaging agent.

  3. Using Image Modelling to Teach Newton's Laws with the Ollie Trick

    Science.gov (United States)

    Dias, Marco Adriano; Carvalho, Paulo Simeão; Vianna, Deise Miranda

    2016-01-01

    Image modelling is a video-based teaching tool that is a combination of strobe images and video analysis. This tool can enable a qualitative and a quantitative approach to the teaching of physics, in a much more engaging and appealling way than the traditional expositive practice. In a specific scenario shown in this paper, the Ollie trick, we…

  4. Modeling Image Patches with a Generic Dictionary of Mini-Epitomes

    Science.gov (United States)

    Papandreou, George; Chen, Liang-Chieh; Yuille, Alan L.

    2015-01-01

    The goal of this paper is to question the necessity of features like SIFT in categorical visual recognition tasks. As an alternative, we develop a generative model for the raw intensity of image patches and show that it can support image classification performance on par with optimized SIFT-based techniques in a bag-of-visual-words setting. Key ingredient of the proposed model is a compact dictionary of mini-epitomes, learned in an unsupervised fashion on a large collection of images. The use of epitomes allows us to explicitly account for photometric and position variability in image appearance. We show that this flexibility considerably increases the capacity of the dictionary to accurately approximate the appearance of image patches and support recognition tasks. For image classification, we develop histogram-based image encoding methods tailored to the epitomic representation, as well as an “epitomic footprint” encoding which is easy to visualize and highlights the generative nature of our model. We discuss in detail computational aspects and develop efficient algorithms to make the model scalable to large tasks. The proposed techniques are evaluated with experiments on the challenging PASCAL VOC 2007 image classification benchmark. PMID:26321859

  5. Fusing range and intensity images for generating dense models of three-dimensional environments

    DEFF Research Database (Denmark)

    Ellekilde, Lars-Peter; Miró, Jaime Valls; Dissanayake., Gamini

    This paper presents a novel strategy for the construction of dense three-dimensional environment models by combining images from a conventional camera and a range imager. Ro- bust data association is ?rst accomplished by exploiting the Scale Invariant Feature Transformation (SIFT) technique...

  6. Dynamic PET simulator via tomographic emission projection for kinetic modeling and parametric image studies.

    Science.gov (United States)

    Häggström, Ida; Beattie, Bradley J; Schmidtlein, C Ross

    2016-06-01

    To develop and evaluate a fast and simple tool called dpetstep (Dynamic PET Simulator of Tracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment, postprocessing choices, etc., on dynamic and parametric images. The tool was developed in matlab using both new and previously reported modules of petstep (PET Simulator of Tracers via Emission Projection). Time activity curves are generated for each voxel of the input parametric image, whereby effects of imaging system blurring, counting noise, scatters, randoms, and attenuation are simulated for each frame. Each frame is then reconstructed into images according to the user specified method, settings, and corrections. Reconstructed images were compared to MC data, and simple Gaussian noised time activity curves (GAUSS). dpetstep was 8000 times faster than MC. Dynamic images from dpetstep had a root mean square error that was within 4% on average of that of MC images, whereas the GAUSS images were within 11%. The average bias in dpetstep and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dpetstep images conformed well to MC images, confirmed visually by scatter plot histograms, and statistically by tumor region of interest histogram comparisons that showed no significant differences (p dynamic PET and parametric images, and demonstrated that it generates both images and subsequent parametric images with very similar noise properties to those of MC images, in a fraction of the time. They believe dpetstep to be very useful for generating fast, simple, and realistic results, however since it uses simple scatter and random models it may not be suitable for studies investigating these phenomena. dpetstep can be downloaded free of cost from https://github.com/CRossSchmidtlein/dPETSTEP.

  7. Model-based microwave image reconstruction: simulations and experiments

    International Nuclear Information System (INIS)

    Ciocan, Razvan; Jiang Huabei

    2004-01-01

    We describe an integrated microwave imaging system that can provide spatial maps of dielectric properties of heterogeneous media with tomographically collected data. The hardware system (800-1200 MHz) was built based on a lock-in amplifier with 16 fixed antennas. The reconstruction algorithm was implemented using a Newton iterative method with combined Marquardt-Tikhonov regularizations. System performance was evaluated using heterogeneous media mimicking human breast tissue. Finite element method coupled with the Bayliss and Turkel radiation boundary conditions were applied to compute the electric field distribution in the heterogeneous media of interest. The results show that inclusions embedded in a 76-diameter background medium can be quantitatively reconstructed from both simulated and experimental data. Quantitative analysis of the microwave images obtained suggests that an inclusion of 14 mm in diameter is the smallest object that can be fully characterized presently using experimental data, while objects as small as 10 mm in diameter can be quantitatively resolved with simulated data

  8. Development of computational small animal models and their applications in preclinical imaging and therapy research

    Energy Technology Data Exchange (ETDEWEB)

    Xie, Tianwu [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva 4 CH-1211 (Switzerland); Zaidi, Habib, E-mail: habib.zaidi@hcuge.ch [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, Geneva 4 CH-1211 (Switzerland); Geneva Neuroscience Center, Geneva University, Geneva CH-1205 (Switzerland); Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen 9700 RB (Netherlands)

    2016-01-15

    The development of multimodality preclinical imaging techniques and the rapid growth of realistic computer simulation tools have promoted the construction and application of computational laboratory animal models in preclinical research. Since the early 1990s, over 120 realistic computational animal models have been reported in the literature and used as surrogates to characterize the anatomy of actual animals for the simulation of preclinical studies involving the use of bioluminescence tomography, fluorescence molecular tomography, positron emission tomography, single-photon emission computed tomography, microcomputed tomography, magnetic resonance imaging, and optical imaging. Other applications include electromagnetic field simulation, ionizing and nonionizing radiation dosimetry, and the development and evaluation of new methodologies for multimodality image coregistration, segmentation, and reconstruction of small animal images. This paper provides a comprehensive review of the history and fundamental technologies used for the development of computational small animal models with a particular focus on their application in preclinical imaging as well as nonionizing and ionizing radiation dosimetry calculations. An overview of the overall process involved in the design of these models, including the fundamental elements used for the construction of different types of computational models, the identification of original anatomical data, the simulation tools used for solving various computational problems, and the applications of computational animal models in preclinical research. The authors also analyze the characteristics of categories of computational models (stylized, voxel-based, and boundary representation) and discuss the technical challenges faced at the present time as well as research needs in the future.

  9. Development of computational small animal models and their applications in preclinical imaging and therapy research.

    Science.gov (United States)

    Xie, Tianwu; Zaidi, Habib

    2016-01-01

    The development of multimodality preclinical imaging techniques and the rapid growth of realistic computer simulation tools have promoted the construction and application of computational laboratory animal models in preclinical research. Since the early 1990s, over 120 realistic computational animal models have been reported in the literature and used as surrogates to characterize the anatomy of actual animals for the simulation of preclinical studies involving the use of bioluminescence tomography, fluorescence molecular tomography, positron emission tomography, single-photon emission computed tomography, microcomputed tomography, magnetic resonance imaging, and optical imaging. Other applications include electromagnetic field simulation, ionizing and nonionizing radiation dosimetry, and the development and evaluation of new methodologies for multimodality image coregistration, segmentation, and reconstruction of small animal images. This paper provides a comprehensive review of the history and fundamental technologies used for the development of computational small animal models with a particular focus on their application in preclinical imaging as well as nonionizing and ionizing radiation dosimetry calculations. An overview of the overall process involved in the design of these models, including the fundamental elements used for the construction of different types of computational models, the identification of original anatomical data, the simulation tools used for solving various computational problems, and the applications of computational animal models in preclinical research. The authors also analyze the characteristics of categories of computational models (stylized, voxel-based, and boundary representation) and discuss the technical challenges faced at the present time as well as research needs in the future.

  10. Development of computational small animal models and their applications in preclinical imaging and therapy research

    International Nuclear Information System (INIS)

    Xie, Tianwu; Zaidi, Habib

    2016-01-01

    The development of multimodality preclinical imaging techniques and the rapid growth of realistic computer simulation tools have promoted the construction and application of computational laboratory animal models in preclinical research. Since the early 1990s, over 120 realistic computational animal models have been reported in the literature and used as surrogates to characterize the anatomy of actual animals for the simulation of preclinical studies involving the use of bioluminescence tomography, fluorescence molecular tomography, positron emission tomography, single-photon emission computed tomography, microcomputed tomography, magnetic resonance imaging, and optical imaging. Other applications include electromagnetic field simulation, ionizing and nonionizing radiation dosimetry, and the development and evaluation of new methodologies for multimodality image coregistration, segmentation, and reconstruction of small animal images. This paper provides a comprehensive review of the history and fundamental technologies used for the development of computational small animal models with a particular focus on their application in preclinical imaging as well as nonionizing and ionizing radiation dosimetry calculations. An overview of the overall process involved in the design of these models, including the fundamental elements used for the construction of different types of computational models, the identification of original anatomical data, the simulation tools used for solving various computational problems, and the applications of computational animal models in preclinical research. The authors also analyze the characteristics of categories of computational models (stylized, voxel-based, and boundary representation) and discuss the technical challenges faced at the present time as well as research needs in the future

  11. Aspergillus infection monitored by multimodal imaging in a rat model.

    Science.gov (United States)

    Pluhacek, Tomas; Petrik, Milos; Luptakova, Dominika; Benada, Oldrich; Palyzova, Andrea; Lemr, Karel; Havlicek, Vladimir

    2016-06-01

    Although myriads of experimental approaches have been published in the field of fungal infection diagnostics, interestingly, in 21st century there is no satisfactory early noninvasive tool for Aspergillus diagnostics with good sensitivity and specificity. In this work, we for the first time described the fungal burden in rat lungs by multimodal imaging approach. The Aspergillus infection was monitored by positron emission tomography and light microscopy employing modified Grocott's methenamine silver staining and eosin counterstaining. Laser ablation inductively coupled plasma mass spectrometry imaging has revealed a dramatic iron increase in fungi-affected areas, which can be presumably attributed to microbial siderophores. Quantitative elemental data were inferred from matrix-matched standards prepared from rat lungs. The iron, silver, and gold MS images collected with variable laser foci revealed that particularly silver or gold can be used as excellent elements useful for sensitively tracking the Aspergillus infection. The limit of detection was determined for both (107) Ag and (197) Au as 0.03 μg/g (5 μm laser focus). The selective incorporation of (107) Ag and (197) Au into fungal cell bodies and low background noise from both elements were confirmed by energy dispersive X-ray scattering utilizing the submicron lateral resolving power of scanning electron microscopy. The low limits of detection and quantitation of both gold and silver make ICP-MS imaging monitoring a viable alternative to standard optical evaluation used in current clinical settings. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  12. A theory of fine structure image models with an application to detection and classification of dementia.

    Science.gov (United States)

    O'Neill, William; Penn, Richard; Werner, Michael; Thomas, Justin

    2015-06-01

    Estimation of stochastic process models from data is a common application of time series analysis methods. Such system identification processes are often cast as hypothesis testing exercises whose intent is to estimate model parameters and test them for statistical significance. Ordinary least squares (OLS) regression and the Levenberg-Marquardt algorithm (LMA) have proven invaluable computational tools for models being described by non-homogeneous, linear, stationary, ordinary differential equations. In this paper we extend stochastic model identification to linear, stationary, partial differential equations in two independent variables (2D) and show that OLS and LMA apply equally well to these systems. The method employs an original nonparametric statistic as a test for the significance of estimated parameters. We show gray scale and color images are special cases of 2D systems satisfying a particular autoregressive partial difference equation which estimates an analogous partial differential equation. Several applications to medical image modeling and classification illustrate the method by correctly classifying demented and normal OLS models of axial magnetic resonance brain scans according to subject Mini Mental State Exam (MMSE) scores. Comparison with 13 image classifiers from the literature indicates our classifier is at least 14 times faster than any of them and has a classification accuracy better than all but one. Our modeling method applies to any linear, stationary, partial differential equation and the method is readily extended to 3D whole-organ systems. Further, in addition to being a robust image classifier, estimated image models offer insights into which parameters carry the most diagnostic image information and thereby suggest finer divisions could be made within a class. Image models can be estimated in milliseconds which translate to whole-organ models in seconds; such runtimes could make real-time medicine and surgery modeling possible.

  13. Voxel-based model construction from colored tomographic images

    International Nuclear Information System (INIS)

    Loureiro, Eduardo Cesar de Miranda

    2002-07-01

    This work presents a new approach in the construction of voxel-based phantoms that was implemented to simplify the segmentation process of organs and tissues reducing the time used in this procedure. The segmentation process is performed by painting tomographic images and attributing a different color for each organ or tissue. A voxel-based head and neck phantom was built using this new approach. The way as the data are stored allows an increasing in the performance of the radiation transport code. The program that calculates the radiation transport also works with image files. This capability allows image reconstruction showing isodose areas, under several points of view, increasing the information to the user. Virtual X-ray photographs can also be obtained allowing that studies could be accomplished looking for the radiographic techniques optimization assessing, at the same time, the doses in organs and tissues. The accuracy of the program here presented, called MCvoxEL, that implements this new approach, was tested by comparison to results from two modern and well-supported Monte Carlo codes. Dose conversion factors for parallel X-ray exposure were also calculated. (author)

  14. Novel radioiodinated sibutramine and fluoxetine as models for brain imaging

    International Nuclear Information System (INIS)

    Motaleb, M.A.; El-Kolaly, M.T.; Rashed, H.M.; Abd El-Bary, A.

    2011-01-01

    Brain imaging is a process which allows scientists and physicians to view and monitor the areas of the brain which allow diagnosis and following up different abnormalities in the brain. The aim of this study was to develop potential radiopharmaceuticals for the non-invasive brain imaging. Sibutramine and fluoxetine (two drugs that have the ability to cross blood-brain barrier) were successfully labeled with 125 I via direct electrophilic substitution reaction at ambient temperature. The reaction parameters studied were substrate concentration, oxidizing agent concentration, pH of the reaction mixture, reaction temperature, reaction time and in vitro stability of the iodocompounds. The iodocompounds gave maximum labeling yield of 92 ± 2.77 and 93 ± 2.1%, respectively, and maintained stability throughout working period (24 h). Biodistribution studies showed that maximum in vivo uptake of the iodocompounds in the brain was 5.7 ± 0.19 and 6.14 ± 0.26% injected activity/g tissue organ, respectively, at 15 and 5 min post-injection, whereas the clearance from the mice appeared to proceed via the hepatobiliary pathway. Brain uptake of 125 I-sibutramine and 125 I-fluoxetine is higher than that of 99m Tc-ECD and 99m Tc-HMPAO (currently used radiopharmaceuticals for brain imaging) and so radioiodinated sibutramine and fluoxetine could be used instead of 99m Tc-ECD and 99m Tc-HMPAO for brain SPECT. (author)

  15. Calibrationless Parallel Magnetic Resonance Imaging: A Joint Sparsity Model

    Directory of Open Access Journals (Sweden)

    Angshul Majumdar

    2013-12-01

    Full Text Available State-of-the-art parallel MRI techniques either explicitly or implicitly require certain parameters to be estimated, e.g., the sensitivity map for SENSE, SMASH and interpolation weights for GRAPPA, SPIRiT. Thus all these techniques are sensitive to the calibration (parameter estimation stage. In this work, we have proposed a parallel MRI technique that does not require any calibration but yields reconstruction results that are at par with (or even better than state-of-the-art methods in parallel MRI. Our proposed method required solving non-convex analysis and synthesis prior joint-sparsity problems. This work also derives the algorithms for solving them. Experimental validation was carried out on two datasets—eight channel brain and eight channel Shepp-Logan phantom. Two sampling methods were used—Variable Density Random sampling and non-Cartesian Radial sampling. For the brain data, acceleration factor of 4 was used and for the other an acceleration factor of 6 was used. The reconstruction results were quantitatively evaluated based on the Normalised Mean Squared Error between the reconstructed image and the originals. The qualitative evaluation was based on the actual reconstructed images. We compared our work with four state-of-the-art parallel imaging techniques; two calibrated methods—CS SENSE and l1SPIRiT and two calibration free techniques—Distributed CS and SAKE. Our method yields better reconstruction results than all of them.

  16. A generalized model for optimal transport of images including dissipation and density modulation

    KAUST Repository

    Maas, Jan; Rumpf, Martin; Schö nlieb, Carola; Simon, Stefan

    2015-01-01

    transport to strongly dissipative dynamics. For this model a robust and effective variational time discretization of geodesic paths is proposed. This requires to minimize a discrete path energy consisting of a sum of consecutive image matching functionals

  17. Diagnosing hypoxia in murine models of rheumatoid arthritis from reflectance multispectral images

    Science.gov (United States)

    Glinton, Sophie; Naylor, Amy J.; Claridge, Ela

    2017-07-01

    Spectra computed from multispectral images of murine models of Rheumatoid Arthritis show a characteristic decrease in reflectance within the 600-800nm region which is indicative of the reduction in blood oxygenation and is consistent with hypoxia.

  18. Development of computational small animal models and their applications in preclinical imaging and therapy research

    NARCIS (Netherlands)

    Xie, Tianwu; Zaidi, Habib

    The development of multimodality preclinical imaging techniques and the rapid growth of realistic computer simulation tools have promoted the construction and application of computational laboratory animal models in preclinical research. Since the early 1990s, over 120 realistic computational animal

  19. Development of Realistic Head Models for Electromagnetic Source Imaging of the Human Brain

    National Research Council Canada - National Science Library

    Akalin, Z

    2001-01-01

    In this work, a methodology is developed to solve the forward problem of electromagnetic source imaging using realistic head models, For this purpose, first segmentation of the 3 dimensional MR head...

  20. Automatic extraction of soft tissues from 3D MRI head images using model driven analysis

    International Nuclear Information System (INIS)

    Jiang, Hao; Yamamoto, Shinji; Imao, Masanao.

    1995-01-01

    This paper presents an automatic extraction system (called TOPS-3D : Top Down Parallel Pattern Recognition System for 3D Images) of soft tissues from 3D MRI head images by using model driven analysis algorithm. As the construction of system TOPS we developed, two concepts have been considered in the design of system TOPS-3D. One is the system having a hierarchical structure of reasoning using model information in higher level, and the other is a parallel image processing structure used to extract plural candidate regions for a destination entity. The new points of system TOPS-3D are as follows. (1) The TOPS-3D is a three-dimensional image analysis system including 3D model construction and 3D image processing techniques. (2) A technique is proposed to increase connectivity between knowledge processing in higher level and image processing in lower level. The technique is realized by applying opening operation of mathematical morphology, in which a structural model function defined in higher level by knowledge representation is immediately used to the filter function of opening operation as image processing in lower level. The system TOPS-3D applied to 3D MRI head images consists of three levels. First and second levels are reasoning part, and third level is image processing part. In experiments, we applied 5 samples of 3D MRI head images with size 128 x 128 x 128 pixels to the system TOPS-3D to extract the regions of soft tissues such as cerebrum, cerebellum and brain stem. From the experimental results, the system is robust for variation of input data by using model information, and the position and shape of soft tissues are extracted corresponding to anatomical structure. (author)

  1. Minimal Camera Networks for 3D Image Based Modeling of Cultural Heritage Objects

    Science.gov (United States)

    Alsadik, Bashar; Gerke, Markus; Vosselman, George; Daham, Afrah; Jasim, Luma

    2014-01-01

    3D modeling of cultural heritage objects like artifacts, statues and buildings is nowadays an important tool for virtual museums, preservation and restoration. In this paper, we introduce a method to automatically design a minimal imaging network for the 3D modeling of cultural heritage objects. This becomes important for reducing the image capture time and processing when documenting large and complex sites. Moreover, such a minimal camera network design is desirable for imaging non-digitally documented artifacts in museums and other archeological sites to avoid disturbing the visitors for a long time and/or moving delicate precious objects to complete the documentation task. The developed method is tested on the Iraqi famous statue “Lamassu”. Lamassu is a human-headed winged bull of over 4.25 m in height from the era of Ashurnasirpal II (883–859 BC). Close-range photogrammetry is used for the 3D modeling task where a dense ordered imaging network of 45 high resolution images were captured around Lamassu with an object sample distance of 1 mm. These images constitute a dense network and the aim of our study was to apply our method to reduce the number of images for the 3D modeling and at the same time preserve pre-defined point accuracy. Temporary control points were fixed evenly on the body of Lamassu and measured by using a total station for the external validation and scaling purpose. Two network filtering methods are implemented and three different software packages are used to investigate the efficiency of the image orientation and modeling of the statue in the filtered (reduced) image networks. Internal and external validation results prove that minimal image networks can provide highly accurate records and efficiency in terms of visualization, completeness, processing time (>60% reduction) and the final accuracy of 1 mm. PMID:24670718

  2. Minimal camera networks for 3D image based modeling of cultural heritage objects.

    Science.gov (United States)

    Alsadik, Bashar; Gerke, Markus; Vosselman, George; Daham, Afrah; Jasim, Luma

    2014-03-25

    3D modeling of cultural heritage objects like artifacts, statues and buildings is nowadays an important tool for virtual museums, preservation and restoration. In this paper, we introduce a method to automatically design a minimal imaging network for the 3D modeling of cultural heritage objects. This becomes important for reducing the image capture time and processing when documenting large and complex sites. Moreover, such a minimal camera network design is desirable for imaging non-digitally documented artifacts in museums and other archeological sites to avoid disturbing the visitors for a long time and/or moving delicate precious objects to complete the documentation task. The developed method is tested on the Iraqi famous statue "Lamassu". Lamassu is a human-headed winged bull of over 4.25 m in height from the era of Ashurnasirpal II (883-859 BC). Close-range photogrammetry is used for the 3D modeling task where a dense ordered imaging network of 45 high resolution images were captured around Lamassu with an object sample distance of 1 mm. These images constitute a dense network and the aim of our study was to apply our method to reduce the number of images for the 3D modeling and at the same time preserve pre-defined point accuracy. Temporary control points were fixed evenly on the body of Lamassu and measured by using a total station for the external validation and scaling purpose. Two network filtering methods are implemented and three different software packages are used to investigate the efficiency of the image orientation and modeling of the statue in the filtered (reduced) image networks. Internal and external validation results prove that minimal image networks can provide highly accurate records and efficiency in terms of visualization, completeness, processing time (>60% reduction) and the final accuracy of 1 mm.

  3. An Emphasis on Perception: Teaching Image Formation Using a Mechanistic Model of Vision.

    Science.gov (United States)

    Allen, Sue; And Others

    An effective way to teach the concept of image is to give students a model of human vision which incorporates a simple mechanism of depth perception. In this study two almost identical versions of a curriculum in geometrical optics were created. One used a mechanistic, interpretive eye model, and in the other the eye was modeled as a passive,…

  4. Software engineering methods for the visualization in the modeling of radiation imaging system

    International Nuclear Information System (INIS)

    Tang Jie; Zhang Li; Chen Zhiqiang; Zhao Ziran; XiaoYongshun

    2003-01-01

    This thesis has accomplished the research in visualization in the modeling of radiation imaging system, and a visualize software was developed using OpenGL and Visual C++ tools. It can load any model files, which are made by the user for every component of the radiation image system, and easily manages the module dynamic link library (DLL) designed by the user for possible movements of those components

  5. Constructing a Computer Model of the Human Eye Based on Tissue Slice Images

    OpenAIRE

    Dai, Peishan; Wang, Boliang; Bao, Chunbo; Ju, Ying

    2010-01-01

    Computer simulation of the biomechanical and biological heat transfer in ophthalmology greatly relies on having a reliable computer model of the human eye. This paper proposes a novel method on the construction of a geometric model of the human eye based on tissue slice images. Slice images were obtained from an in vitro Chinese human eye through an embryo specimen processing methods. A level set algorithm was used to extract contour points of eye tissues while a principle component analysi...

  6. Multiscale vision model for event detection and reconstruction in two-photon imaging data

    DEFF Research Database (Denmark)

    Brazhe, Alexey; Mathiesen, Claus; Lind, Barbara Lykke

    2014-01-01

    on a modified multiscale vision model, an object detection framework based on the thresholding of wavelet coefficients and hierarchical trees of significant coefficients followed by nonlinear iterative partial object reconstruction, for the analysis of two-photon calcium imaging data. The framework is discussed...... of the multiscale vision model is similar in the denoising, but provides a better segmenation of the image into meaningful objects, whereas other methods need to be combined with dedicated thresholding and segmentation utilities....

  7. Image Restoration Based on the Hybrid Total-Variation-Type Model

    OpenAIRE

    Shi, Baoli; Pang, Zhi-Feng; Yang, Yu-Fei

    2012-01-01

    We propose a hybrid total-variation-type model for the image restoration problem based on combining advantages of the ROF model with the LLT model. Since two ${L}^{1}$ -norm terms in the proposed model make it difficultly solved by using some classically numerical methods directly, we first employ the alternating direction method of multipliers (ADMM) to solve a general form of the proposed model. Then, based on the ADMM and the Moreau-Yosida decomposition theory, a more efficient method call...

  8. Learning a No-Reference Quality Assessment Model of Enhanced Images With Big Data.

    Science.gov (United States)

    Gu, Ke; Tao, Dacheng; Qiao, Jun-Fei; Lin, Weisi

    2018-04-01

    In this paper, we investigate into the problem of image quality assessment (IQA) and enhancement via machine learning. This issue has long attracted a wide range of attention in computational intelligence and image processing communities, since, for many practical applications, e.g., object detection and recognition, raw images are usually needed to be appropriately enhanced to raise the visual quality (e.g., visibility and contrast). In fact, proper enhancement can noticeably improve the quality of input images, even better than originally captured images, which are generally thought to be of the best quality. In this paper, we present two most important contributions. The first contribution is to develop a new no-reference (NR) IQA model. Given an image, our quality measure first extracts 17 features through analysis of contrast, sharpness, brightness and more, and then yields a measure of visual quality using a regression module, which is learned with big-data training samples that are much bigger than the size of relevant image data sets. The results of experiments on nine data sets validate the superiority and efficiency of our blind metric compared with typical state-of-the-art full-reference, reduced-reference and NA IQA methods. The second contribution is that a robust image enhancement framework is established based on quality optimization. For an input image, by the guidance of the proposed NR-IQA measure, we conduct histogram modification to successively rectify image brightness and contrast to a proper level. Thorough tests demonstrate that our framework can well enhance natural images, low-contrast images, low-light images, and dehazed images. The source code will be released at https://sites.google.com/site/guke198701/publications.

  9. Continuous monitoring of arthritis in animal models using optical imaging modalities

    Science.gov (United States)

    Son, Taeyoon; Yoon, Hyung-Ju; Lee, Saseong; Jang, Won Seuk; Jung, Byungjo; Kim, Wan-Uk

    2014-10-01

    Given the several difficulties associated with histology, including difficulty in continuous monitoring, this study aimed to investigate the feasibility of optical imaging modalities-cross-polarization color (CPC) imaging, erythema index (EI) imaging, and laser speckle contrast (LSC) imaging-for continuous evaluation and monitoring of arthritis in animal models. C57BL/6 mice, used for the evaluation of arthritis, were divided into three groups: arthritic mice group (AMG), positive control mice group (PCMG), and negative control mice group (NCMG). Complete Freund's adjuvant, mineral oil, and saline were injected into the footpad for AMG, PCMG, and NCMG, respectively. LSC and CPC images were acquired from 0 through 144 h after injection for all groups. EI images were calculated from CPC images. Variations in feet area, EI, and speckle index for each mice group over time were calculated for quantitative evaluation of arthritis. Histological examinations were performed, and the results were found to be consistent with those from optical imaging analysis. Thus, optical imaging modalities may be successfully applied for continuous evaluation and monitoring of arthritis in animal models.

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

    Science.gov (United States)

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

    2018-04-01

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

  11. Point spread function modeling and image restoration for cone-beam CT

    International Nuclear Information System (INIS)

    Zhang Hua; Shi Yikai; Huang Kuidong; Xu Zhe

    2015-01-01

    X-ray cone-beam computed tomography (CT) has such notable features as high efficiency and precision, and is widely used in the fields of medical imaging and industrial non-destructive testing, but the inherent imaging degradation reduces the quality of CT images. Aimed at the problems of projection image degradation and restoration in cone-beam CT, a point spread function (PSF) modeling method is proposed first. The general PSF model of cone-beam CT is established, and based on it, the PSF under arbitrary scanning conditions can be calculated directly for projection image restoration without the additional measurement, which greatly improved the application convenience of cone-beam CT. Secondly, a projection image restoration algorithm based on pre-filtering and pre-segmentation is proposed, which can make the edge contours in projection images and slice images clearer after restoration, and control the noise in the equivalent level to the original images. Finally, the experiments verified the feasibility and effectiveness of the proposed methods. (authors)

  12. Reconstructed image of human heart for total artificial heart implantation, based on MR image and cast silicone model of heart

    International Nuclear Information System (INIS)

    Komoda, Takashi; Maeta, Hajime; Uyama, Chikao.

    1991-01-01

    Based on transverse (TRN) and LV long axis (LAX) MR images of two cadaver hearts, three-dimensional (3-D) computer models of the connecting interface between remaining heart and total artificial heart, i.e., mitral and tricuspid valvular annuli (MVA and TVA), ascending aorta (Ao) and pulmonary artery (PA), were reconstructed to compare the shape and the size of MVA and those of TVA, the distance between the center of MVA and TVA (D G ), the angle between the plane of MVA and that of TVA (R T ), and the angles of Ao and PA, respectively, to the plane of MVA (R A , R P ), with those obtained in cast silicone models. It was found that based on LAX rather than TRN MR image, MVA and TVA might be more precisely reconstructed. The data obtained in 3-D images of MVA, TVA, Ao and PA based on silicone models of 32 hearts were as follows: D G (cm): 4.17±0.43, R T (degrees): 22.1±11.3, R A (degrees): 54.9±15.3, R P (degrees): 30.8±17.1. (author)

  13. Image fusion in craniofacial virtual reality modeling based on CT and 3dMD photogrammetry.

    Science.gov (United States)

    Xin, Pengfei; Yu, Hongbo; Cheng, Huanchong; Shen, Shunyao; Shen, Steve G F

    2013-09-01

    The aim of this study was to demonstrate the feasibility of building a craniofacial virtual reality model by image fusion of 3-dimensional (3D) CT models and 3 dMD stereophotogrammetric facial surface. A CT scan and stereophotography were performed. The 3D CT models were reconstructed by Materialise Mimics software, and the stereophotogrammetric facial surface was reconstructed by 3 dMD patient software. All 3D CT models were exported as Stereo Lithography file format, and the 3 dMD model was exported as Virtual Reality Modeling Language file format. Image registration and fusion were performed in Mimics software. Genetic algorithm was used for precise image fusion alignment with minimum error. The 3D CT models and the 3 dMD stereophotogrammetric facial surface were finally merged into a single file and displayed using Deep Exploration software. Errors between the CT soft tissue model and 3 dMD facial surface were also analyzed. Virtual model based on CT-3 dMD image fusion clearly showed the photorealistic face and bone structures. Image registration errors in virtual face are mainly located in bilateral cheeks and eyeballs, and the errors are more than 1.5 mm. However, the image fusion of whole point cloud sets of CT and 3 dMD is acceptable with a minimum error that is less than 1 mm. The ease of use and high reliability of CT-3 dMD image fusion allows the 3D virtual head to be an accurate, realistic, and widespread tool, and has a great benefit to virtual face model.

  14. Segmentation of laser range radar images using hidden Markov field models

    International Nuclear Information System (INIS)

    Pucar, P.

    1993-01-01

    Segmentation of images in the context of model based stochastic techniques is connected with high, very often unpracticle computational complexity. The objective with this thesis is to take the models used in model based image processing, simplify and use them in suboptimal, but not computationally demanding algorithms. Algorithms that are essentially one-dimensional, and their extensions to two dimensions are given. The model used in this thesis is the well known hidden Markov model. Estimation of the number of hidden states from observed data is a problem that is addressed. The state order estimation problem is of general interest and is not specifically connected to image processing. An investigation of three state order estimation techniques for hidden Markov models is given. 76 refs

  15. MATCHING AERIAL IMAGES TO 3D BUILDING MODELS BASED ON CONTEXT-BASED GEOMETRIC HASHING

    Directory of Open Access Journals (Sweden)

    J. Jung

    2016-06-01

    Full Text Available In this paper, a new model-to-image framework to automatically align a single airborne image with existing 3D building models using geometric hashing is proposed. As a prerequisite process for various applications such as data fusion, object tracking, change detection and texture mapping, the proposed registration method is used for determining accurate exterior orientation parameters (EOPs of a single image. This model-to-image matching process consists of three steps: 1 feature extraction, 2 similarity measure and matching, and 3 adjustment of EOPs of a single image. For feature extraction, we proposed two types of matching cues, edged corner points representing the saliency of building corner points with associated edges and contextual relations among the edged corner points within an individual roof. These matching features are extracted from both 3D building and a single airborne image. A set of matched corners are found with given proximity measure through geometric hashing and optimal matches are then finally determined by maximizing the matching cost encoding contextual similarity between matching candidates. Final matched corners are used for adjusting EOPs of the single airborne image by the least square method based on co-linearity equations. The result shows that acceptable accuracy of single image's EOP can be achievable by the proposed registration approach as an alternative to labour-intensive manual registration process.

  16. Beam-hardening correction in CT based on basis image and TV model

    International Nuclear Information System (INIS)

    Li Qingliang; Yan Bin; Li Lei; Sun Hongsheng; Zhang Feng

    2012-01-01

    In X-ray computed tomography, the beam hardening leads to artifacts and reduces the image quality. It analyzes how beam hardening influences on original projection. According, it puts forward a kind of new beam-hardening correction method based on the basis images and TV model. Firstly, according to physical characteristics of the beam hardening an preliminary correction model with adjustable parameters is set up. Secondly, using different parameters, original projections are operated by the correction model. Thirdly, the projections are reconstructed to obtain a series of basis images. Finally, the linear combination of basis images is the final reconstruction image. Here, with total variation for the final reconstruction image as the cost function, the linear combination coefficients for the basis images are determined according to iterative method. To verify the effectiveness of the proposed method, the experiments are carried out on real phantom and industrial part. The results show that the algorithm significantly inhibits cup and strip artifacts in CT image. (authors)

  17. Small Animal [18F]FDG PET Imaging for Tumor Model Study

    International Nuclear Information System (INIS)

    Woo, Sang Keun; Kim, Kyeong Min; Cheon, Gi Jeong

    2008-01-01

    PET allows non-invasive, quantitative and repetitive imaging of biological function in living animals. Small animal PET imaging with [ 18 F]FDG has been successfully applied to investigation of metabolism, receptor, ligand interactions, gene expression, adoptive cell therapy and somatic gene therapy. Experimental condition of animal handling impacts on the biodistribution of [ 18 F]FDG in small animal study. The small animal PET and CT images were registered using the hardware fiducial markers and small animal contour point. Tumor imaging in small animal with small animal [ 18 F]FDG PET should be considered fasting, warming, and isoflurane anesthesia level. Registered imaging with small animal PET and CT image could be useful for the detection of tumor. Small animal experimental condition of animal handling and registration method will be of most importance for small lesion detection of metastases tumor model

  18. Remote sensing image ship target detection method based on visual attention model

    Science.gov (United States)

    Sun, Yuejiao; Lei, Wuhu; Ren, Xiaodong

    2017-11-01

    The traditional methods of detecting ship targets in remote sensing images mostly use sliding window to search the whole image comprehensively. However, the target usually occupies only a small fraction of the image. This method has high computational complexity for large format visible image data. The bottom-up selective attention mechanism can selectively allocate computing resources according to visual stimuli, thus improving the computational efficiency and reducing the difficulty of analysis. Considering of that, a method of ship target detection in remote sensing images based on visual attention model was proposed in this paper. The experimental results show that the proposed method can reduce the computational complexity while improving the detection accuracy, and improve the detection efficiency of ship targets in remote sensing images.

  19. Brain MRI Tumor Detection using Active Contour Model and Local Image Fitting Energy

    Science.gov (United States)

    Nabizadeh, Nooshin; John, Nigel

    2014-03-01

    Automatic abnormality detection in Magnetic Resonance Imaging (MRI) is an important issue in many diagnostic and therapeutic applications. Here an automatic brain tumor detection method is introduced that uses T1-weighted images and K. Zhang et. al.'s active contour model driven by local image fitting (LIF) energy. Local image fitting energy obtains the local image information, which enables the algorithm to segment images with intensity inhomogeneities. Advantage of this method is that the LIF energy functional has less computational complexity than the local binary fitting (LBF) energy functional; moreover, it maintains the sub-pixel accuracy and boundary regularization properties. In Zhang's algorithm, a new level set method based on Gaussian filtering is used to implement the variational formulation, which is not only vigorous to prevent the energy functional from being trapped into local minimum, but also effective in keeping the level set function regular. Experiments show that the proposed method achieves high accuracy brain tumor segmentation results.

  20. A Mathematical Model for Storage and Recall of Images using Targeted Synchronization of Coupled Maps.

    Science.gov (United States)

    Palaniyandi, P; Rangarajan, Govindan

    2017-08-21

    We propose a mathematical model for storage and recall of images using coupled maps. We start by theoretically investigating targeted synchronization in coupled map systems wherein only a desired (partial) subset of the maps is made to synchronize. A simple method is introduced to specify coupling coefficients such that targeted synchronization is ensured. The principle of this method is extended to storage/recall of images using coupled Rulkov maps. The process of adjusting coupling coefficients between Rulkov maps (often used to model neurons) for the purpose of storing a desired image mimics the process of adjusting synaptic strengths between neurons to store memories. Our method uses both synchronisation and synaptic weight modification, as the human brain is thought to do. The stored image can be recalled by providing an initial random pattern to the dynamical system. The storage and recall of the standard image of Lena is explicitly demonstrated.

  1. Reconstruction of binary geological images using analytical edge and object models

    Science.gov (United States)

    Abdollahifard, Mohammad J.; Ahmadi, Sadegh

    2016-04-01

    Reconstruction of fields using partial measurements is of vital importance in different applications in geosciences. Solving such an ill-posed problem requires a well-chosen model. In recent years, training images (TI) are widely employed as strong prior models for solving these problems. However, in the absence of enough evidence it is difficult to find an adequate TI which is capable of describing the field behavior properly. In this paper a very simple and general model is introduced which is applicable to a fairly wide range of binary images without any modifications. The model is motivated by the fact that nearly all binary images are composed of simple linear edges in micro-scale. The analytic essence of this model allows us to formulate the template matching problem as a convex optimization problem having efficient and fast solutions. The model has the potential to incorporate the qualitative and quantitative information provided by geologists. The image reconstruction problem is also formulated as an optimization problem and solved using an iterative greedy approach. The proposed method is capable of recovering the image unknown values with accuracies about 90% given samples representing as few as 2% of the original image.

  2. Influence of Averaging Preprocessing on Image Analysis with a Markov Random Field Model

    Science.gov (United States)

    Sakamoto, Hirotaka; Nakanishi-Ohno, Yoshinori; Okada, Masato

    2018-02-01

    This paper describes our investigations into the influence of averaging preprocessing on the performance of image analysis. Averaging preprocessing involves a trade-off: image averaging is often undertaken to reduce noise while the number of image data available for image analysis is decreased. We formulated a process of generating image data by using a Markov random field (MRF) model to achieve image analysis tasks such as image restoration and hyper-parameter estimation by a Bayesian approach. According to the notions of Bayesian inference, posterior distributions were analyzed to evaluate the influence of averaging. There are three main results. First, we found that the performance of image restoration with a predetermined value for hyper-parameters is invariant regardless of whether averaging is conducted. We then found that the performance of hyper-parameter estimation deteriorates due to averaging. Our analysis of the negative logarithm of the posterior probability, which is called the free energy based on an analogy with statistical mechanics, indicated that the confidence of hyper-parameter estimation remains higher without averaging. Finally, we found that when the hyper-parameters are estimated from the data, the performance of image restoration worsens as averaging is undertaken. We conclude that averaging adversely influences the performance of image analysis through hyper-parameter estimation.

  3. [Research progress of multi-model medical image fusion and recognition].

    Science.gov (United States)

    Zhou, Tao; Lu, Huiling; Chen, Zhiqiang; Ma, Jingxian

    2013-10-01

    Medical image fusion and recognition has a wide range of applications, such as focal location, cancer staging and treatment effect assessment. Multi-model medical image fusion and recognition are analyzed and summarized in this paper. Firstly, the question of multi-model medical image fusion and recognition is discussed, and its advantage and key steps are discussed. Secondly, three fusion strategies are reviewed from the point of algorithm, and four fusion recognition structures are discussed. Thirdly, difficulties, challenges and possible future research direction are discussed.

  4. Modeling the Color Image and Video Quality on Liquid Crystal Displays with Backlight Dimming

    DEFF Research Database (Denmark)

    Korhonen, Jari; Mantel, Claire; Burini, Nino

    2013-01-01

    Objective image and video quality metrics focus mostly on the digital representation of the signal. However, the display characteristics are also essential for the overall Quality of Experience (QoE). In this paper, we use a model of a backlight dimming system for Liquid Crystal Display (LCD......) and show how the modeled image can be used as an input to quality assessment algorithms. For quality assessment, we propose an image quality metric, based on Peak Signal-to-Noise Ratio (PSNR) computation in the CIE L*a*b* color space. The metric takes luminance reduction, color distortion and loss...

  5. Detecting Weather Radar Clutter by Information Fusion With Satellite Images and Numerical Weather Prediction Model Output

    DEFF Research Database (Denmark)

    Bøvith, Thomas; Nielsen, Allan Aasbjerg; Hansen, Lars Kai

    2006-01-01

    A method for detecting clutter in weather radar images by information fusion is presented. Radar data, satellite images, and output from a numerical weather prediction model are combined and the radar echoes are classified using supervised classification. The presented method uses indirect...... information on precipitation in the atmosphere from Meteosat-8 multispectral images and near-surface temperature estimates from the DMI-HIRLAM-S05 numerical weather prediction model. Alternatively, an operational nowcasting product called 'Precipitating Clouds' based on Meteosat-8 input is used. A scale...

  6. Evaluation of HVS models in the application of medical image quality assessment

    Science.gov (United States)

    Zhang, L.; Cavaro-Menard, C.; Le Callet, P.

    2012-03-01

    In this study, four of the most widely used Human Visual System (HVS) models are applied on Magnetic Resonance (MR) images for signal detection task. Their performances are evaluated against gold standard derived from radiologists' majority decision. The task-based image quality assessment requires taking into account the human perception specificities, for which various HVS models have been proposed. However to our knowledge, no work was conducted to evaluate and compare the suitability of these models with respect to the assessment of medical image qualities. This pioneering study investigates the performances of different HVS models on medical images in terms of approximation to radiologist performance. We propose to score the performance of each HVS model using the AUC (Area Under the receiver operating characteristic Curve) and its variance estimate as the figure of merit. The radiologists' majority decision is used as gold standard so that the estimated AUC measures the distance between the HVS model and the radiologist perception. To calculate the variance estimate of AUC, we adopted the one-shot method that is independent of the HVS model's output range. The results of this study will help to provide arguments to the application of some HVS model on our future medical image quality assessment metric.

  7. An Effective Surface Modeling Method for Car Styling from a Side-View Image

    Institute of Scientific and Technical Information of China (English)

    LIBao-jun; ZHANGXue-fang; LVZhang-quan; QIYi-chao

    2014-01-01

    We introduce an almost-automatic technique for generating 3D car styling surface models based on a single side-view image. Our approach combines the prior knowledge of car styling and deformable curve network model to obtain an automatic modeling process. Firstly, we define the consistent parameterized curve template for 2D and 3D case respectivelyby analyzingthe characteristic lines for car styling. Then, a semi-automatic extraction from a side-view car image is adopted. Thirdly, statistic morphable model of 3D curve network isused to get the initial solution with sparse point constraints.Withonly afew post-processing operations, the optimized curve network models for creating surfaces are obtained. Finally, the styling surfaces are automatically generated using template-based parametric surface modeling method. More than 50 3D curve network models are constructed as the morphable database. We show that this intelligent modeling toolsimplifiesthe exhausted modeling task, and also demonstratemeaningful results of our approach.

  8. Remote sensing models and methods for image processing

    CERN Document Server

    Schowengerdt, Robert A

    2007-01-01

    Remote sensing is a technology that engages electromagnetic sensors to measure and monitor changes in the earth's surface and atmosphere. Normally this is accomplished through the use of a satellite or aircraft. This book, in its 3rd edition, seamlessly connects the art and science of earth remote sensing with the latest interpretative tools and techniques of computer-aided image processing. Newly expanded and updated, this edition delivers more of the applied scientific theory and practical results that helped the previous editions earn wide acclaim and become classroom and industry standa

  9. Textured digital elevation model formation from low-cost UAV LADAR/digital image data

    Science.gov (United States)

    Bybee, Taylor C.; Budge, Scott E.

    2015-05-01

    Textured digital elevation models (TDEMs) have valuable use in precision agriculture, situational awareness, and disaster response. However, scientific-quality models are expensive to obtain using conventional aircraft-based methods. The cost of creating an accurate textured terrain model can be reduced by using a low-cost (processing step and enables both 2D- and 3D-image registration techniques to be used. This paper describes formation of TDEMs using simulated data from a small UAV gathering swaths of texel images of the terrain below. Being a low-cost UAV, only a coarse knowledge of position and attitude is known, and thus both 2D- and 3D-image registration techniques must be used to register adjacent swaths of texel imagery to create a TDEM. The process of creating an aggregate texel image (a TDEM) from many smaller texel image swaths is described. The algorithm is seeded with the rough estimate of position and attitude of each capture. Details such as the required amount of texel image overlap, registration models, simulated flight patterns (level and turbulent), and texture image formation are presented. In addition, examples of such TDEMs are shown and analyzed for accuracy.

  10. Monte Carlo modeling of neutron imaging at the SINQ spallation source

    International Nuclear Information System (INIS)

    Lebenhaft, J.R.; Lehmann, E.H.; Pitcher, E.J.; McKinney, G.W.

    2003-01-01

    Modeling of the Swiss Spallation Neutron Source (SINQ) has been used to demonstrate the neutron radiography capability of the newly released MPI-version of the MCNPX Monte Carlo code. A detailed MCNPX model was developed of SINQ and its associated neutron transmission radiography (NEUTRA) facility. Preliminary validation of the model was performed by comparing the calculated and measured neutron fluxes in the NEUTRA beam line, and a simulated radiography image was generated for a sample consisting of steel tubes containing different materials. This paper describes the SINQ facility, provides details of the MCNPX model, and presents preliminary results of the neutron imaging. (authors)

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

    Science.gov (United States)

    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

  12. Comparison of Model Predictions of Image Quality with Results of Clinical Trials in Chest and Lumbar Spine Screen-film Imaging

    International Nuclear Information System (INIS)

    Sandborg, M.; McVey, G.; Dance, D.R.; Carlsson, G.A.

    2000-01-01

    The ability to predict image quality from known physical and technical parameters is a prerequisite for making successful dose optimisation. In this study, imaging systems have been simulated using a Monte Carlo model of the imaging systems. The model includes a voxelised human anatomy and quantifies image quality in terms of contrast and signal-to-noise ratio for 5-6 anatomical details included in the anatomy. The imaging systems used in clinical trials were simulated and the ranking of the systems by the model and radiologists compared. The model and the results of the trial for chest PA both show that using a high maximum optical density was significantly better than using a low one. The model predicts that a good system is characterised by a large dynamic range and a high contrast of the blood vessels in the retrocardiac area. The ranking by the radiologists and the model agreed for the lumbar spine AP. (author)

  13. 3D/2D model-to-image registration by imitation learning for cardiac procedures.

    Science.gov (United States)

    Toth, Daniel; Miao, Shun; Kurzendorfer, Tanja; Rinaldi, Christopher A; Liao, Rui; Mansi, Tommaso; Rhode, Kawal; Mountney, Peter

    2018-05-12

    In cardiac interventions, such as cardiac resynchronization therapy (CRT), image guidance can be enhanced by involving preoperative models. Multimodality 3D/2D registration for image guidance, however, remains a significant research challenge for fundamentally different image data, i.e., MR to X-ray. Registration methods must account for differences in intensity, contrast levels, resolution, dimensionality, field of view. Furthermore, same anatomical structures may not be visible in both modalities. Current approaches have focused on developing modality-specific solutions for individual clinical use cases, by introducing constraints, or identifying cross-modality information manually. Machine learning approaches have the potential to create more general registration platforms. However, training image to image methods would require large multimodal datasets and ground truth for each target application. This paper proposes a model-to-image registration approach instead, because it is common in image-guided interventions to create anatomical models for diagnosis, planning or guidance prior to procedures. An imitation learning-based method, trained on 702 datasets, is used to register preoperative models to intraoperative X-ray images. Accuracy is demonstrated on cardiac models and artificial X-rays generated from CTs. The registration error was [Formula: see text] on 1000 test cases, superior to that of manual ([Formula: see text]) and gradient-based ([Formula: see text]) registration. High robustness is shown in 19 clinical CRT cases. Besides the proposed methods feasibility in a clinical environment, evaluation has shown good accuracy and high robustness indicating that it could be applied in image-guided interventions.

  14. New second order Mumford-Shah model based on Γ-convergence approximation for image processing

    Science.gov (United States)

    Duan, Jinming; Lu, Wenqi; Pan, Zhenkuan; Bai, Li

    2016-05-01

    In this paper, a second order variational model named the Mumford-Shah total generalized variation (MSTGV) is proposed for simultaneously image denoising and segmentation, which combines the original Γ-convergence approximated Mumford-Shah model with the second order total generalized variation (TGV). For image denoising, the proposed MSTGV can eliminate both the staircase artefact associated with the first order total variation and the edge blurring effect associated with the quadratic H1 regularization or the second order bounded Hessian regularization. For image segmentation, the MSTGV can obtain clear and continuous boundaries of objects in the image. To improve computational efficiency, the implementation of the MSTGV does not directly solve its high order nonlinear partial differential equations and instead exploits the efficient split Bregman algorithm. The algorithm benefits from the fast Fourier transform, analytical generalized soft thresholding equation, and Gauss-Seidel iteration. Extensive experiments are conducted to demonstrate the effectiveness and efficiency of the proposed model.

  15. Color model comparative analysis for breast cancer diagnosis using H and E stained images

    Science.gov (United States)

    Li, Xingyu; Plataniotis, Konstantinos N.

    2015-03-01

    Digital cancer diagnosis is a research realm where signal processing techniques are used to analyze and to classify color histopathology images. Different from grayscale image analysis of magnetic resonance imaging or X-ray, colors in histopathology images convey large amount of histological information and thus play significant role in cancer diagnosis. Though color information is widely used in histopathology works, as today, there is few study on color model selections for feature extraction in cancer diagnosis schemes. This paper addresses the problem of color space selection for digital cancer classification using H and E stained images, and investigates the effectiveness of various color models (RGB, HSV, CIE L*a*b*, and stain-dependent H and E decomposition model) in breast cancer diagnosis. Particularly, we build a diagnosis framework as a comparison benchmark and take specific concerns of medical decision systems into account in evaluation. The evaluation methodologies include feature discriminate power evaluation and final diagnosis performance comparison. Experimentation on a publicly accessible histopathology image set suggests that the H and E decomposition model outperforms other assessed color spaces. For reasons behind various performance of color spaces, our analysis via mutual information estimation demonstrates that color components in the H and E model are less dependent, and thus most feature discriminate power is collected in one channel instead of spreading out among channels in other color spaces.

  16. OntoVIP: an ontology for the annotation of object models used for medical image simulation.

    Science.gov (United States)

    Gibaud, Bernard; Forestier, Germain; Benoit-Cattin, Hugues; Cervenansky, Frédéric; Clarysse, Patrick; Friboulet, Denis; Gaignard, Alban; Hugonnard, Patrick; Lartizien, Carole; Liebgott, Hervé; Montagnat, Johan; Tabary, Joachim; Glatard, Tristan

    2014-12-01

    This paper describes the creation of a comprehensive conceptualization of object models used in medical image simulation, suitable for major imaging modalities and simulators. The goal is to create an application ontology that can be used to annotate the models in a repository integrated in the Virtual Imaging Platform (VIP), to facilitate their sharing and reuse. Annotations make the anatomical, physiological and pathophysiological content of the object models explicit. In such an interdisciplinary context we chose to rely on a common integration framework provided by a foundational ontology, that facilitates the consistent integration of the various modules extracted from several existing ontologies, i.e. FMA, PATO, MPATH, RadLex and ChEBI. Emphasis is put on methodology for achieving this extraction and integration. The most salient aspects of the ontology are presented, especially the organization in model layers, as well as its use to browse and query the model repository. Copyright © 2014 Elsevier Inc. All rights reserved.

  17. Supervised variational model with statistical inference and its application in medical image segmentation.

    Science.gov (United States)

    Li, Changyang; Wang, Xiuying; Eberl, Stefan; Fulham, Michael; Yin, Yong; Dagan Feng, David

    2015-01-01

    Automated and general medical image segmentation can be challenging because the foreground and the background may have complicated and overlapping density distributions in medical imaging. Conventional region-based level set algorithms often assume piecewise constant or piecewise smooth for segments, which are implausible for general medical image segmentation. Furthermore, low contrast and noise make identification of the boundaries between foreground and background difficult for edge-based level set algorithms. Thus, to address these problems, we suggest a supervised variational level set segmentation model to harness the statistical region energy functional with a weighted probability approximation. Our approach models the region density distributions by using the mixture-of-mixtures Gaussian model to better approximate real intensity distributions and distinguish statistical intensity differences between foreground and background. The region-based statistical model in our algorithm can intuitively provide better performance on noisy images. We constructed a weighted probability map on graphs to incorporate spatial indications from user input with a contextual constraint based on the minimization of contextual graphs energy functional. We measured the performance of our approach on ten noisy synthetic images and 58 medical datasets with heterogeneous intensities and ill-defined boundaries and compared our technique to the Chan-Vese region-based level set model, the geodesic active contour model with distance regularization, and the random walker model. Our method consistently achieved the highest Dice similarity coefficient when compared to the other methods.

  18. Comparative Accuracy of Facial Models Fabricated Using Traditional and 3D Imaging Techniques.

    Science.gov (United States)

    Lincoln, Ketu P; Sun, Albert Y T; Prihoda, Thomas J; Sutton, Alan J

    2016-04-01

    The purpose of this investigation was to compare the accuracy of facial models fabricated using facial moulage impression methods to the three-dimensional printed (3DP) fabrication methods using soft tissue images obtained from cone beam computed tomography (CBCT) and 3D stereophotogrammetry (3D-SPG) scans. A reference phantom model was fabricated using a 3D-SPG image of a human control form with ten fiducial markers placed on common anthropometric landmarks. This image was converted into the investigation control phantom model (CPM) using 3DP methods. The CPM was attached to a camera tripod for ease of image capture. Three CBCT and three 3D-SPG images of the CPM were captured. The DICOM and STL files from the three 3dMD and three CBCT were imported to the 3DP, and six testing models were made. Reversible hydrocolloid and dental stone were used to make three facial moulages of the CPM, and the impressions/casts were poured in type IV gypsum dental stone. A coordinate measuring machine (CMM) was used to measure the distances between each of the ten fiducial markers. Each measurement was made using one point as a static reference to the other nine points. The same measuring procedures were accomplished on all specimens. All measurements were compared between specimens and the control. The data were analyzed using ANOVA and Tukey pairwise comparison of the raters, methods, and fiducial markers. The ANOVA multiple comparisons showed significant difference among the three methods (p 3D-SPG showed statistical difference in comparison to the models fabricated using the traditional method of facial moulage and 3DP models fabricated from CBCT imaging. 3DP models fabricated using 3D-SPG were less accurate than the CPM and models fabricated using facial moulage and CBCT imaging techniques. © 2015 by the American College of Prosthodontists.

  19. Image/video understanding systems based on network-symbolic models

    Science.gov (United States)

    Kuvich, Gary

    2004-03-01

    Vision is a part of a larger information system that converts visual information into knowledge structures. These structures drive vision process, resolve ambiguity and uncertainty via feedback projections, and provide image understanding that is an interpretation of visual information in terms of such knowledge models. Computer simulation models are built on the basis of graphs/networks. The ability of human brain to emulate similar graph/network models is found. Symbols, predicates and grammars naturally emerge in such networks, and logic is simply a way of restructuring such models. Brain analyzes an image as a graph-type relational structure created via multilevel hierarchical compression of visual information. Primary areas provide active fusion of image features on a spatial grid-like structure, where nodes are cortical columns. Spatial logic and topology naturally present in such structures. Mid-level vision processes like perceptual grouping, separation of figure from ground, are special kinds of network transformations. They convert primary image structure into the set of more abstract ones, which represent objects and visual scene, making them easy for analysis by higher-level knowledge structures. Higher-level vision phenomena are results of such analysis. Composition of network-symbolic models combines learning, classification, and analogy together with higher-level model-based reasoning into a single framework, and it works similar to frames and agents. Computational intelligence methods transform images into model-based knowledge representation. Based on such principles, an Image/Video Understanding system can convert images into the knowledge models, and resolve uncertainty and ambiguity. This allows creating intelligent computer vision systems for design and manufacturing.

  20. Diffraction enhanced imaging of a rat model of gastric acid aspiration pneumonitis.

    Science.gov (United States)

    Connor, Dean M; Zhong, Zhong; Foda, Hussein D; Wiebe, Sheldon; Parham, Christopher A; Dilmanian, F Avraham; Cole, Elodia B; Pisano, Etta D

    2011-12-01

    Diffraction-enhanced imaging (DEI) is a type of phase contrast x-ray imaging that has improved image contrast at a lower dose than conventional radiography for many imaging applications, but no studies have been done to determine if DEI might be useful for diagnosing lung injury. The goals of this study were to determine if DEI could differentiate between healthy and injured lungs for a rat model of gastric aspiration and to compare diffraction-enhanced images with chest radiographs. Radiographs and diffraction-enhanced chest images of adult Sprague Dawley rats were obtained before and 4 hours after the aspiration of 0.4 mL/kg of 0.1 mol/L hydrochloric acid. Lung damage was confirmed with histopathology. The radiographs and diffraction-enhanced peak images revealed regions of atelectasis in the injured rat lung. The diffraction-enhanced peak images revealed the full extent of the lung with improved clarity relative to the chest radiographs, especially in the portion of the lower lobe that extended behind the diaphragm on the anteroposterior projection. For a rat model of gastric acid aspiration, DEI is capable of distinguishing between a healthy and an injured lung and more clearly than radiography reveals the full extent of the lung and the lung damage. Copyright © 2011 AUR. All rights reserved.

  1. Just Noticeable Distortion Model and Its Application in Color Image Watermarking

    Science.gov (United States)

    Liu, Kuo-Cheng

    In this paper, a perceptually adaptive watermarking scheme for color images is proposed in order to achieve robustness and transparency. A new just noticeable distortion (JND) estimator for color images is first designed in the wavelet domain. The key issue of the JND model is to effectively integrate visual masking effects. The estimator is an extension to the perceptual model that is used in image coding for grayscale images. Except for the visual masking effects given coefficient by coefficient by taking into account the luminance content and the texture of grayscale images, the crossed masking effect given by the interaction between luminance and chrominance components and the effect given by the variance within the local region of the target coefficient are investigated such that the visibility threshold for the human visual system (HVS) can be evaluated. In a locally adaptive fashion based on the wavelet decomposition, the estimator applies to all subbands of luminance and chrominance components of color images and is used to measure the visibility of wavelet quantization errors. The subband JND profiles are then incorporated into the proposed color image watermarking scheme. Performance in terms of robustness and transparency of the watermarking scheme is obtained by means of the proposed approach to embed the maximum strength watermark while maintaining the perceptually lossless quality of the watermarked color image. Simulation results show that the proposed scheme with inserting watermarks into luminance and chrominance components is more robust than the existing scheme while retaining the watermark transparency.

  2. Registration of eye reflection and scene images using an aspherical eye model.

    Science.gov (United States)

    Nakazawa, Atsushi; Nitschke, Christian; Nishida, Toyoaki

    2016-11-01

    This paper introduces an image registration algorithm between an eye reflection and a scene image. Although there are currently a large number of image registration algorithms, this task remains difficult due to nonlinear distortions at the eye surface and large amounts of noise, such as iris texture, eyelids, eyelashes, and their shadows. To overcome this issue, we developed an image registration method combining an aspherical eye model that simulates nonlinear distortions considering eye geometry and a two-step iterative registration strategy that obtains dense correspondence of the feature points to achieve accurate image registrations for the entire image region. We obtained a database of eye reflection and scene images featuring four subjects in indoor and outdoor scenes and compared the registration performance with different asphericity conditions. Results showed that the proposed approach can perform accurate registration with an average accuracy of 1.05 deg by using the aspherical cornea model. This work is relevant for eye image analysis in general, enabling novel applications and scenarios.

  3. PACS for surgery and interventional radiology: Features of a Therapy Imaging and Model Management System (TIMMS)

    International Nuclear Information System (INIS)

    Lemke, Heinz U.; Berliner, Leonard

    2011-01-01

    Appropriate use of information and communication technology (ICT) and mechatronic (MT) systems is viewed by many experts as a means to improve workflow and quality of care in the operating room (OR). This will require a suitable information technology (IT) infrastructure, as well as communication and interface standards, such as specialized extensions of DICOM, to allow data interchange between surgical system components in the OR. A design of such an infrastructure, sometimes referred to as surgical PACS, but better defined as a Therapy Imaging and Model Management System (TIMMS), will be introduced in this article. A TIMMS should support the essential functions that enable and advance image guided therapy, and in the future, a more comprehensive form of patient-model guided therapy. Within this concept, the 'image-centric world view' of the classical PACS technology is complemented by an IT 'model-centric world view'. Such a view is founded in the special patient modelling needs of an increasing number of modern surgical interventions as compared to the imaging intensive working mode of diagnostic radiology, for which PACS was originally conceptualised and developed. The modelling aspects refer to both patient information and workflow modelling. Standards for creating and integrating information about patients, equipment, and procedures are vitally needed when planning for an efficient OR. The DICOM Working Group 24 (WG-24) has been established to develop DICOM objects and services related to image and model guided surgery. To determine these standards, it is important to define step-by-step surgical workflow practices and create interventional workflow models per procedures or per variable cases. As the boundaries between radiation therapy, surgery and interventional radiology are becoming less well-defined, precise patient models will become the greatest common denominator for all therapeutic disciplines. In addition to imaging, the focus of WG-24 is to serve

  4. PACS for surgery and interventional radiology: features of a Therapy Imaging and Model Management System (TIMMS).

    Science.gov (United States)

    Lemke, Heinz U; Berliner, Leonard

    2011-05-01

    Appropriate use of information and communication technology (ICT) and mechatronic (MT) systems is viewed by many experts as a means to improve workflow and quality of care in the operating room (OR). This will require a suitable information technology (IT) infrastructure, as well as communication and interface standards, such as specialized extensions of DICOM, to allow data interchange between surgical system components in the OR. A design of such an infrastructure, sometimes referred to as surgical PACS, but better defined as a Therapy Imaging and Model Management System (TIMMS), will be introduced in this article. A TIMMS should support the essential functions that enable and advance image guided therapy, and in the future, a more comprehensive form of patient-model guided therapy. Within this concept, the "image-centric world view" of the classical PACS technology is complemented by an IT "model-centric world view". Such a view is founded in the special patient modelling needs of an increasing number of modern surgical interventions as compared to the imaging intensive working mode of diagnostic radiology, for which PACS was originally conceptualised and developed. The modelling aspects refer to both patient information and workflow modelling. Standards for creating and integrating information about patients, equipment, and procedures are vitally needed when planning for an efficient OR. The DICOM Working Group 24 (WG-24) has been established to develop DICOM objects and services related to image and model guided surgery. To determine these standards, it is important to define step-by-step surgical workflow practices and create interventional workflow models per procedures or per variable cases. As the boundaries between radiation therapy, surgery and interventional radiology are becoming less well-defined, precise patient models will become the greatest common denominator for all therapeutic disciplines. In addition to imaging, the focus of WG-24 is to serve

  5. Nonlinear propagation in ultrasonic fields: measurements, modelling and harmonic imaging.

    Science.gov (United States)

    Humphrey, V F

    2000-03-01

    In high amplitude ultrasonic fields, such as those used in medical ultrasound, nonlinear propagation can result in waveform distortion and the generation of harmonics of the initial frequency. In the nearfield of a transducer this process is complicated by diffraction effects associated with the source. The results of a programme to study the nonlinear propagation in the fields of circular, focused and rectangular transducers are described, and comparisons made with numerical predictions obtained using a finite difference solution to the Khokhlov-Zabolotskaya-Kuznetsov (or KZK) equation. These results are extended to consider nonlinear propagation in tissue-like media and the implications for ultrasonic measurements and ultrasonic heating are discussed. The narrower beamwidths and reduced side-lobe levels of the harmonic beams are illustrated and the use of harmonics to form diagnostic images with improved resolution is described.

  6. Modelling the Cost and Quality of Preservation Imaging and Archiving

    DEFF Research Database (Denmark)

    Kejser, Ulla Bøgvad

    2009-01-01

    , fire and other risks. In this PhD thesis it is examined how one may evaluate the long‐term costs and benefits to cultural heritage institutions of different preservation strategies for digital copies. The investigated alternatives are preserving the copies in a digital repository, and printing...... the files out on microfilm and preserving them in a non‐digital repository. In order to obtain empirical data and to understand the decisive cost factors in preservation copying, a case study was set up in which degrading sheet‐film negatives were digitised. Requirements for image quality and metadata were...... systematic evaluation of the quality of repositories and the perceived benefits that different preservation strategies may bring. This also relates to a conducted investigation of preservation requirements for a shared bit preservation system, which describes how institutions with OAIS compliant repositories...

  7. A SEMIAUTOMATIC APPROACH FOR GENERATION OF SITE MODELS FROM CARTOSAT-2 MULTIVIEW IMAGES

    Directory of Open Access Journals (Sweden)

    A. Mahapatra

    2012-07-01

    Full Text Available In the last decade there has been a paradigm shift in creating, viewing and utilizing geospatial data for planning, navigation and traffic management of urban areas. Realistic, three-dimensional information is preferred over conventional two dimensional maps. The paper describes objectives, methodology and results of an operational system being developed for generation of site model from Cartosat-2 multiview images. The system is designed to work in operational mode with varying level of manual interactivity. A rigorous physical sensor model based on collinearity condition models the "step n stare" mode of image acquisition of the satellite. The relative orientation of the overlapping images is achieved using coplanarity condition and conjugate points. A procedure is developed to perform digitization in mono and stereo modes. A technique for refining manually digitized boundaries is developed. The conjugate points are generated by establishing a correspondence between the points obtained on refined edges to analogous points on the images obtained with view angles ±26 deg. It is achieved through geometrically constrained image matching method. The results are shown for a portion of multi-view images of Washington City obtained from Cartosat-2. The scheme is generic to accept very high resolution stereo images from other satellites as input.

  8. Thin Cloud Detection Method by Linear Combination Model of Cloud Image

    Science.gov (United States)

    Liu, L.; Li, J.; Wang, Y.; Xiao, Y.; Zhang, W.; Zhang, S.

    2018-04-01

    The existing cloud detection methods in photogrammetry often extract the image features from remote sensing images directly, and then use them to classify images into cloud or other things. But when the cloud is thin and small, these methods will be inaccurate. In this paper, a linear combination model of cloud images is proposed, by using this model, the underlying surface information of remote sensing images can be removed. So the cloud detection result can become more accurate. Firstly, the automatic cloud detection program in this paper uses the linear combination model to split the cloud information and surface information in the transparent cloud images, then uses different image features to recognize the cloud parts. In consideration of the computational efficiency, AdaBoost Classifier was introduced to combine the different features to establish a cloud classifier. AdaBoost Classifier can select the most effective features from many normal features, so the calculation time is largely reduced. Finally, we selected a cloud detection method based on tree structure and a multiple feature detection method using SVM classifier to compare with the proposed method, the experimental data shows that the proposed cloud detection program in this paper has high accuracy and fast calculation speed.

  9. Discrete Event Simulation Model of the Polaris 2.1 Gamma Ray Imaging Radiation Detection Device

    Science.gov (United States)

    2016-06-01

    release; distribution is unlimited DISCRETE EVENT SIMULATION MODEL OF THE POLARIS 2.1 GAMMA RAY IMAGING RADIATION DETECTION DEVICE by Andres T...ONLY (Leave blank) 2. REPORT DATE June 2016 3. REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE DISCRETE EVENT SIMULATION MODEL...modeled. The platform, Simkit, was utilized to create a discrete event simulation (DES) model of the Polaris. After carefully constructing the DES

  10. Edge Sharpness Assessment by Parametric Modeling: Application to Magnetic Resonance Imaging.

    Science.gov (United States)

    Ahmad, R; Ding, Y; Simonetti, O P

    2015-05-01

    In biomedical imaging, edge sharpness is an important yet often overlooked image quality metric. In this work, a semi-automatic method to quantify edge sharpness in the presence of significant noise is presented with application to magnetic resonance imaging (MRI). The method is based on parametric modeling of image edges. First, an edge map is automatically generated and one or more edges-of-interest (EOI) are manually selected using graphical user interface. Multiple exclusion criteria are then enforced to eliminate edge pixels that are potentially not suitable for sharpness assessment. Second, at each pixel of the EOI, an image intensity profile is read along a small line segment that runs locally normal to the EOI. Third, the profiles corresponding to all EOI pixels are individually fitted with a sigmoid function characterized by four parameters, including one that represents edge sharpness. Last, the distribution of the sharpness parameter is used to quantify edge sharpness. For validation, the method is applied to simulated data as well as MRI data from both phantom imaging and cine imaging experiments. This method allows for fast, quantitative evaluation of edge sharpness even in images with poor signal-to-noise ratio. Although the utility of this method is demonstrated for MRI, it can be adapted for other medical imaging applications.

  11. A Joint Land Cover Mapping and Image Registration Algorithm Based on a Markov Random Field Model

    Directory of Open Access Journals (Sweden)

    Apisit Eiumnoh

    2013-10-01

    Full Text Available Traditionally, image registration of multi-modal and multi-temporal images is performed satisfactorily before land cover mapping. However, since multi-modal and multi-temporal images are likely to be obtained from different satellite platforms and/or acquired at different times, perfect alignment is very difficult to achieve. As a result, a proper land cover mapping algorithm must be able to correct registration errors as well as perform an accurate classification. In this paper, we propose a joint classification and registration technique based on a Markov random field (MRF model to simultaneously align two or more images and obtain a land cover map (LCM of the scene. The expectation maximization (EM algorithm is employed to solve the joint image classification and registration problem by iteratively estimating the map parameters and approximate posterior probabilities. Then, the maximum a posteriori (MAP criterion is used to produce an optimum land cover map. We conducted experiments on a set of four simulated images and one pair of remotely sensed images to investigate the effectiveness and robustness of the proposed algorithm. Our results show that, with proper selection of a critical MRF parameter, the resulting LCMs derived from an unregistered image pair can achieve an accuracy that is as high as when images are perfectly aligned. Furthermore, the registration error can be greatly reduced.

  12. Feedforward Object-Vision Models Only Tolerate Small Image Variations Compared to Human

    Directory of Open Access Journals (Sweden)

    Masoud eGhodrati

    2014-07-01

    Full Text Available Invariant object recognition is a remarkable ability of primates' visual system that its underlying mechanism has constantly been under intense investigations. Computational modelling is a valuable tool toward understanding the processes involved in invariant object recognition. Although recent computational models have shown outstanding performances on challenging image databases, they fail to perform well when images with more complex variations of the same object are applied to them. Studies have shown that making sparse representation of objects by extracting more informative visual features through a feedforward sweep can lead to higher recognition performances. Here, however, we show that when the complexity of image variations is high, even this approach results in poor performance compared to humans. To assess the performance of models and humans in invariant object recognition tasks, we built a parametrically controlled image database consisting of several object categories varied in different dimensions and levels, rendered from 3D planes. Comparing the performance of several object recognition models with human observers shows that only in low-level image variations the models perform similar to humans in categorization tasks. Furthermore, the results of our behavioral experiments demonstrate that, even under difficult experimental conditions (i.e. briefly presented masked stimuli with complex image variations, human observers performed outstandingly well, suggesting that the models are still far from resembling humans in invariant object recognition. Taken together, we suggest that learning sparse informative visual features, although desirable, is not a complete solution for future progresses in object-vision modelling. We show that this approach is not of significant help in solving the computational crux of object recognition (that is invariant object recognition when the identity-preserving image variations become more complex.

  13. Matching Aerial Images to 3D Building Models Using Context-Based Geometric Hashing

    Directory of Open Access Journals (Sweden)

    Jaewook Jung

    2016-06-01

    Full Text Available A city is a dynamic entity, which environment is continuously changing over time. Accordingly, its virtual city models also need to be regularly updated to support accurate model-based decisions for various applications, including urban planning, emergency response and autonomous navigation. A concept of continuous city modeling is to progressively reconstruct city models by accommodating their changes recognized in spatio-temporal domain, while preserving unchanged structures. A first critical step for continuous city modeling is to coherently register remotely sensed data taken at different epochs with existing building models. This paper presents a new model-to-image registration method using a context-based geometric hashing (CGH method to align a single image with existing 3D building models. This model-to-image registration process consists of three steps: (1 feature extraction; (2 similarity measure; and matching, and (3 estimating exterior orientation parameters (EOPs of a single image. For feature extraction, we propose two types of matching cues: edged corner features representing the saliency of building corner points with associated edges, and contextual relations among the edged corner features within an individual roof. A set of matched corners are found with given proximity measure through geometric hashing, and optimal matches are then finally determined by maximizing the matching cost encoding contextual similarity between matching candidates. Final matched corners are used for adjusting EOPs of the single airborne image by the least square method based on collinearity equations. The result shows that acceptable accuracy of EOPs of a single image can be achievable using the proposed registration approach as an alternative to a labor-intensive manual registration process.

  14. Modeling susceptibility difference artifacts produced by metallic implants in magnetic resonance imaging with point-based thin-plate spline image registration.

    Science.gov (United States)

    Pauchard, Y; Smith, M; Mintchev, M

    2004-01-01

    Magnetic resonance imaging (MRI) suffers from geometric distortions arising from various sources. One such source are the non-linearities associated with the presence of metallic implants, which can profoundly distort the obtained images. These non-linearities result in pixel shifts and intensity changes in the vicinity of the implant, often precluding any meaningful assessment of the entire image. This paper presents a method for correcting these distortions based on non-rigid image registration techniques. Two images from a modelled three-dimensional (3D) grid phantom were subjected to point-based thin-plate spline registration. The reference image (without distortions) was obtained from a grid model including a spherical implant, and the corresponding test image containing the distortions was obtained using previously reported technique for spatial modelling of magnetic susceptibility artifacts. After identifying the nonrecoverable area in the distorted image, the calculated spline model was able to quantitatively account for the distortions, thus facilitating their compensation. Upon the completion of the compensation procedure, the non-recoverable area was removed from the reference image and the latter was compared to the compensated image. Quantitative assessment of the goodness of the proposed compensation technique is presented.

  15. Power laws and inverse motion modelling: application to turbulence measurements from satellite images

    Directory of Open Access Journals (Sweden)

    Pablo D. Mininni

    2012-01-01

    Full Text Available In the context of tackling the ill-posed inverse problem of motion estimation from image sequences, we propose to introduce prior knowledge on flow regularity given by turbulence statistical models. Prior regularity is formalised using turbulence power laws describing statistically self-similar structure of motion increments across scales. The motion estimation method minimises the error of an image observation model while constraining second-order structure function to behave as a power law within a prescribed range. Thanks to a Bayesian modelling framework, the motion estimation method is able to jointly infer the most likely power law directly from image data. The method is assessed on velocity fields of 2-D or quasi-2-D flows. Estimation accuracy is first evaluated on a synthetic image sequence of homogeneous and isotropic 2-D turbulence. Results obtained with the approach based on physics of fluids outperform state-of-the-art. Then, the method analyses atmospheric turbulence using a real meteorological image sequence. Selecting the most likely power law model enables the recovery of physical quantities, which are of major interest for turbulence atmospheric characterisation. In particular, from meteorological images we are able to estimate energy and enstrophy fluxes of turbulent cascades, which are in agreement with previous in situ measurements.

  16. Efficient fully 3D list-mode TOF PET image reconstruction using a factorized system matrix with an image domain resolution model

    International Nuclear Information System (INIS)

    Zhou, Jian; Qi, Jinyi

    2014-01-01

    A factorized system matrix utilizing an image domain resolution model is attractive in fully 3D time-of-flight PET image reconstruction using list-mode data. In this paper, we study a factored model based on sparse matrix factorization that is comprised primarily of a simplified geometrical projection matrix and an image blurring matrix. Beside the commonly-used Siddon’s ray-tracer, we propose another more simplified geometrical projector based on the Bresenham’s ray-tracer which further reduces the computational cost. We discuss in general how to obtain an image blurring matrix associated with a geometrical projector, and provide theoretical analysis that can be used to inspect the efficiency in model factorization. In simulation studies, we investigate the performance of the proposed sparse factorization model in terms of spatial resolution, noise properties and computational cost. The quantitative results reveal that the factorization model can be as efficient as a non-factored model, while its computational cost can be much lower. In addition we conduct Monte Carlo simulations to identify the conditions under which the image resolution model can become more efficient in terms of image contrast recovery. We verify our observations using the provided theoretical analysis. The result offers a general guide to achieve the optimal reconstruction performance based on a sparse factorization model with an image domain resolution model. (paper)

  17. A new method to calibrate Lagrangian model with ASAR images for oil slick trajectory.

    Science.gov (United States)

    Tian, Siyu; Huang, Xiaoxia; Li, Hongga

    2017-03-15

    Since Lagrangian model coefficients vary with different conditions, it is necessary to calibrate the model to obtain optimal coefficient combination for special oil spill accident. This paper focuses on proposing a new method to calibrate Lagrangian model with time series of Envisat ASAR images. Oil slicks extracted from time series images form a detected trajectory of special oil slick. Lagrangian model is calibrated by minimizing the difference between simulated trajectory and detected trajectory. mean center position distance difference (MCPD) and rotation difference (RD) of Oil slicks' or particles' standard deviational ellipses (SDEs) are calculated as two evaluations. The two parameters are taken to evaluate the performance of Lagrangian transport model with different coefficient combinations. This method is applied to Penglai 19-3 oil spill accident. The simulation result with calibrated model agrees well with related satellite observations. It is suggested the new method is effective to calibrate Lagrangian model. Copyright © 2016 Elsevier Ltd. All rights reserved.

  18. Image reconstruction method for electrical capacitance tomography based on the combined series and parallel normalization model

    International Nuclear Information System (INIS)

    Dong, Xiangyuan; Guo, Shuqing

    2008-01-01

    In this paper, a novel image reconstruction method for electrical capacitance tomography (ECT) based on the combined series and parallel model is presented. A regularization technique is used to obtain a stabilized solution of the inverse problem. Also, the adaptive coefficient of the combined model is deduced by numerical optimization. Simulation results indicate that it can produce higher quality images when compared to the algorithm based on the parallel or series models for the cases tested in this paper. It provides a new algorithm for ECT application

  19. Computational Modeling for Enhancing Soft Tissue Image Guided Surgery: An Application in Neurosurgery.

    Science.gov (United States)

    Miga, Michael I

    2016-01-01

    With the recent advances in computing, the opportunities to translate computational models to more integrated roles in patient treatment are expanding at an exciting rate. One area of considerable development has been directed towards correcting soft tissue deformation within image guided neurosurgery applications. This review captures the efforts that have been undertaken towards enhancing neuronavigation by the integration of soft tissue biomechanical models, imaging and sensing technologies, and algorithmic developments. In addition, the review speaks to the evolving role of modeling frameworks within surgery and concludes with some future directions beyond neurosurgical applications.

  20. A Novel Probability Model for Suppressing Multipath Ghosts in GPR and TWI Imaging: A Numerical Study

    Directory of Open Access Journals (Sweden)

    Tan Yun-hua

    2015-10-01

    Full Text Available A novel concept for suppressing the problem of multipath ghosts in Ground Penetrating Radar (GPR and Through-Wall Imaging (TWI is presented. Ghosts (i.e., false targets mainly arise from the use of the Born or single-scattering approximations that lead to linearized imaging algorithms; however, these approximations neglect the effect of multiple scattering (or multipath between the electromagnetic wavefield and the object under investigation. In contrast to existing methods of suppressing multipath ghosts, the proposed method models for the first time the reflectivity of the probed objects as a probability function up to a normalized factor and introduces the concept of random subaperture by randomly picking up measurement locations from the entire aperture. Thus, the final radar image is a joint probability distribution that corresponds to radar images derived from multiple random subapertures. Finally, numerical experiments are used to demonstrate the performance of the proposed methodology in GPR and TWI imaging.

  1. Imaging techniques for visualizing and phenotyping congenital heart defects in murine models.

    Science.gov (United States)

    Liu, Xiaoqin; Tobita, Kimimasa; Francis, Richard J B; Lo, Cecilia W

    2013-06-01

    Mouse model is ideal for investigating the genetic and developmental etiology of congenital heart disease. However, cardiovascular phenotyping for the precise diagnosis of structural heart defects in mice remain challenging. With rapid advances in imaging techniques, there are now high throughput phenotyping tools available for the diagnosis of structural heart defects. In this review, we discuss the efficacy of four different imaging modalities for congenital heart disease diagnosis in fetal/neonatal mice, including noninvasive fetal echocardiography, micro-computed tomography (micro-CT), micro-magnetic resonance imaging (micro-MRI), and episcopic fluorescence image capture (EFIC) histopathology. The experience we have gained in the use of these imaging modalities in a large-scale mouse mutagenesis screen have validated their efficacy for congenital heart defect diagnosis in the tiny hearts of fetal and newborn mice. These cutting edge phenotyping tools will be invaluable for furthering our understanding of the developmental etiology of congenital heart disease. Copyright © 2013 Wiley Periodicals, Inc.

  2. Medical imaging education in biomedical engineering curriculum: courseware development and application through a hybrid teaching model.

    Science.gov (United States)

    Zhao, Weizhao; Li, Xiping; Chen, Hairong; Manns, Fabrice

    2012-01-01

    Medical Imaging is a key training component in Biomedical Engineering programs. Medical imaging education is interdisciplinary training, involving physics, mathematics, chemistry, electrical engineering, computer engineering, and applications in biology and medicine. Seeking an efficient teaching method for instructors and an effective learning environment for students has long been a goal for medical imaging education. By the support of NSF grants, we developed the medical imaging teaching software (MITS) and associated dynamic assessment tracking system (DATS). The MITS/DATS system has been applied to junior and senior medical imaging classes through a hybrid teaching model. The results show that student's learning gain improved, particularly in concept understanding and simulation project completion. The results also indicate disparities in subjective perception between junior and senior classes. Three institutions are collaborating to expand the courseware system and plan to apply it to different class settings.

  3. Software phantom with realistic speckle modeling for validation of image analysis methods in echocardiography

    Science.gov (United States)

    Law, Yuen C.; Tenbrinck, Daniel; Jiang, Xiaoyi; Kuhlen, Torsten

    2014-03-01

    Computer-assisted processing and interpretation of medical ultrasound images is one of the most challenging tasks within image analysis. Physical phenomena in ultrasonographic images, e.g., the characteristic speckle noise and shadowing effects, make the majority of standard methods from image analysis non optimal. Furthermore, validation of adapted computer vision methods proves to be difficult due to missing ground truth information. There is no widely accepted software phantom in the community and existing software phantoms are not exible enough to support the use of specific speckle models for different tissue types, e.g., muscle and fat tissue. In this work we propose an anatomical software phantom with a realistic speckle pattern simulation to _ll this gap and provide a exible tool for validation purposes in medical ultrasound image analysis. We discuss the generation of speckle patterns and perform statistical analysis of the simulated textures to obtain quantitative measures of the realism and accuracy regarding the resulting textures.

  4. Modeling multiple visual words assignment for bag-of-features based medical image retrieval

    KAUST Repository

    Wang, Jim Jing-Yan

    2012-01-01

    In this paper, we investigate the bag-of-features based medical image retrieval methods, which represent an image as a collection of local features, such as image patch and key points with SIFT descriptor. To improve the bag-of-features method, we first model the assignment of local descriptor as contribution functions, and then propose a new multiple assignment strategy. By assuming the local feature can be reconstructed by its neighboring visual words in vocabulary, we solve the reconstruction weights as a QP problem and then use the solved weights as contribution functions, which results in a new assignment method called the QP assignment. We carry our experiments on ImageCLEFmed datasets. Experiments\\' results show that our proposed method exceeds the performances of traditional solutions and works well for the bag-of-features based medical image retrieval tasks.

  5. Modeling multiple visual words assignment for bag-of-features based medical image retrieval

    KAUST Repository

    Wang, Jim Jing-Yan; Almasri, Islam

    2012-01-01

    In this paper, we investigate the bag-of-features based medical image retrieval methods, which represent an image as a collection of local features, such as image patch and key points with SIFT descriptor. To improve the bag-of-features method, we first model the assignment of local descriptor as contribution functions, and then propose a new multiple assignment strategy. By assuming the local feature can be reconstructed by its neighboring visual words in vocabulary, we solve the reconstruction weights as a QP problem and then use the solved weights as contribution functions, which results in a new assignment method called the QP assignment. We carry our experiments on ImageCLEFmed datasets. Experiments' results show that our proposed method exceeds the performances of traditional solutions and works well for the bag-of-features based medical image retrieval tasks.

  6. A Convex Variational Model for Restoring Blurred Images with Multiplicative Noise

    DEFF Research Database (Denmark)

    Dong, Yiqiu; Tieyong Zeng

    2013-01-01

    In this paper, a new variational model for restoring blurred images with multiplicative noise is proposed. Based on the statistical property of the noise, a quadratic penalty function technique is utilized in order to obtain a strictly convex model under a mild condition, which guarantees...

  7. New Hybrid Variational Recovery Model for Blurred Images with Multiplicative Noise

    DEFF Research Database (Denmark)

    Dong, Yiqiu; Zeng, Tieyong

    2013-01-01

    A new hybrid variational model for recovering blurred images in the presence of multiplicative noise is proposed. Inspired by previous work on multiplicative noise removal, an I-divergence technique is used to build a strictly convex model under a condition that ensures the uniqueness...

  8. RECONSTRUCTION OF A HUMAN LUNG MORPHOLOGY MODEL FROM MAGNETIC RESONANCE IMAGES

    Science.gov (United States)

    RATIONALE A description of lung morphological structure is necessary for modeling the deposition and fate of inhaled therapeutic aerosols. A morphological model of the lung boundary was generated from magnetic resonance (MR) images with the goal of creating a framework for anato...

  9. COMPUTER RECONSTRUCTION OF A HUMAN LUNG MORPHOLOGY MODEL FROM MAGNETIC RESONANCE (MR) IMAGES

    Science.gov (United States)

    A mathematical description of the morphological structure of the lung is necessary for modeling and analysis of the deposition of inhaled aerosols. A morphological model of the lung boundary was generated from magnetic resonance (MR) images, with the goal of creating a frame...

  10. IMAGE: An Integrated Model for the Assessment of the Greenhouse Effect

    NARCIS (Netherlands)

    Rotmans J; Boois H de; Swart RJ

    1989-01-01

    In dit rapport wordt beschreven hoe het RIVM-simulatiemodel IMAGE (an Integrated Model for the Assessment of the Greenhouse Effect) is opgebouwd. Het model beoogt een geintegreerd overzicht te geven van de broeikasproblematiek alsmede inzicht te verschaffen in de wezenlijke drijfveren van het

  11. The IMAGE model suite used for the OECD Environmental Outlook to 2050

    Energy Technology Data Exchange (ETDEWEB)

    Kram, T.; Stehfest, E.

    2012-03-15

    In the Environmental Outlook to 2050 from the Organisation for Economic Co-operation and Development (OECD) a number of scenarios and projection are used which are calculated with the IMAGE model suite. This document describes the models and modules used and their interconnections.

  12. A generative Bezier curve model for surf-zone tracking in coastal image sequences

    CSIR Research Space (South Africa)

    Burke, Michael G

    2017-09-01

    Full Text Available This work introduces a generative Bezier curve model suitable for surf-zone curve tracking in coastal image sequences. The model combines an adaptive curve parametrised by control points governed by local random walks with a global sinusoidal motion...

  13. Background Report for the IMAGE 2.0 Energy-Economy Model

    NARCIS (Netherlands)

    Toet AMC; Vries HJM de; Wijngaart RA van den; MTV

    1994-01-01

    Dit rapport geeft achtergrond informatie over de structuur, historische invoergegevens (1970-1990) en calibratie van het Energy-Economy model van IMAGE 2.0. Ook worden de aannames voor het Energy-Economy model beschreven met betrekking tot het Conventional Wisdom scenario. Dit is het basis

  14. Modeling for the management of peak loads on a radiology image management network

    International Nuclear Information System (INIS)

    Dwyer, S.J.; Cox, G.G.; Templeton, A.W.; Cook, L.T.; Anderson, W.H.; Hensley, K.S.

    1987-01-01

    The design of a radiology image management network for a radiology department can now be assisted by a queueing model. The queueing model requires that the designers specify the following parameters: the number of tasks to be accomplished (acquisition of image data, transmission of data, archiving of data, displaying and manipulation of data, and generation of hard copies); the average times to complete each task; the patient scheduled arrival times; and the number/type of computer nodes interfaced to the network (acquisition nodes, interactive diagnostic display stations, archiving nodes, hard copy nodes, and gateways to hospital systems). The outcomes from the queuering model include mean throughput data rates and identified bottlenecks, and peak throughput data rates and identified bottlenecks. This exhibit presents the queueing model and illustrates its use in managing peak loads on an image management network

  15. Insights into Parkinson's disease models and neurotoxicity using non-invasive imaging

    International Nuclear Information System (INIS)

    Sanchez-Pernaute, Rosario; Brownell, Anna-Liisa; Jenkins, Bruce G.; Isacson, Ole

    2005-01-01

    Loss of dopamine in the nigrostriatal system causes a severe impairment in motor function in patients with Parkinson's disease and in experimental neurotoxic models of the disease. We have used non-invasive imaging techniques such as positron emission tomography (PET) and functional magnetic resonance imaging (MRI) to investigate in vivo the changes in the dopamine system in neurotoxic models of Parkinson's disease. In addition to classic neurotransmitter studies, in these models, it is also possible to characterize associated and perhaps pathogenic factors, such as the contribution of microglia activation and inflammatory responses to neuronal damage. Functional imaging techniques are instrumental to our understanding and modeling of disease mechanisms, which should in turn lead to development of new therapies for Parkinson's disease and other neurodegenerative disorders

  16. Structural assessment of aerospace components using image processing algorithms and Finite Element models

    DEFF Research Database (Denmark)

    Stamatelos, Dimtrios; Kappatos, Vassilios

    2017-01-01

    Purpose – This paper presents the development of an advanced structural assessment approach for aerospace components (metallic and composites). This work focuses on developing an automatic image processing methodology based on Non Destructive Testing (NDT) data and numerical models, for predicting...... the residual strength of these components. Design/methodology/approach – An image processing algorithm, based on the threshold method, has been developed to process and quantify the geometric characteristics of damages. Then, a parametric Finite Element (FE) model of the damaged component is developed based...... on the inputs acquired from the image processing algorithm. The analysis of the metallic structures is employing the Extended FE Method (XFEM), while for the composite structures the Cohesive Zone Model (CZM) technique with Progressive Damage Modelling (PDM) is used. Findings – The numerical analyses...

  17. Modeling an Optical and Infrared Search for Extraterrestrial Intelligence Survey with Exoplanet Direct Imaging

    Science.gov (United States)

    Vides, Christina; Macintosh, Bruce; Ruffio, Jean-Baptiste; Nielsen, Eric; Povich, Matthew Samuel

    2018-01-01

    Gemini Planet Imager (GPI) is a direct high contrast imaging instrument coupled to the Gemini South Telescope. Its purpose is to image extrasolar planets around young (~Intelligence), we modeled GPI’s capabilities to detect an extraterrestrial continuous wave (CW) laser broadcasted within the H-band have been modeled. By using sensitivity evaluated for actual GPI observations of young target stars, we produced models of the CW laser power as a function of distance from the star that could be detected if GPI were to observe nearby (~ 3-5 pc) planet-hosting G-type stars. We took a variety of transmitters into consideration in producing these modeled values. GPI is known to be sensitive to both pulsed and CW coherent electromagnetic radiation. The results were compared to similar studies and it was found that these values are competitive to other optical and infrared observations.

  18. Aspergillus infection monitored by multimodal imaging in a rat model

    Czech Academy of Sciences Publication Activity Database

    Pluháček, Tomáš; Petrík, M.; Luptáková, Dominika; Benada, Oldřich; Palyzová, Andrea; Lemr, Karel; Havlíček, Vladimír

    2016-01-01

    Roč. 16, 11-12 (2016), s. 1785-1792 ISSN 1615-9853 R&D Projects: GA MŠk LO1509; GA ČR GAP206/12/1150 Institutional support: RVO:61388971 Keywords : Animal model * Aspergillosis * Biomedicine Subject RIV: CE - Biochemistry Impact factor: 4.041, year: 2016

  19. Mathematical modeling of three-dimensional images in emission tomography

    International Nuclear Information System (INIS)

    Koblik, Yu.N.; Khugaev, A. V.; Mktchyan, G.A.; Ioannou, P.; Dimovasili, E.

    2002-01-01

    The model of processing results of three-dimensional measurements in positron-emissive tomograph is proposed in this work. The algorithm of construction and visualization of phantom objects of arbitrary shape was developed and its concrete realization in view of program packet for PC was carried out

  20. Fast Algorithms for Fitting Active Appearance Models to Unconstrained Images

    NARCIS (Netherlands)

    Tzimiropoulos, Georgios; Pantic, Maja

    2016-01-01

    Fitting algorithms for Active Appearance Models (AAMs) are usually considered to be robust but slow or fast but less able to generalize well to unseen variations. In this paper, we look into AAM fitting algorithms and make the following orthogonal contributions: We present a simple “project-out‿

  1. Modeling the diffusion magnetic resonance imaging signal inside neurons

    International Nuclear Information System (INIS)

    Nguyen, D V; Li, J R; Grebenkov, D S; Le Bihan, D

    2014-01-01

    The Bloch-Torrey partial differential equation (PDE) describes the complex transverse water proton magnetization due to diffusion-encoding magnetic field gradient pulses. The integral of the solution of this PDE yields the diffusion magnetic resonance imaging (dMRI) signal. In a complex medium such as cerebral tissue, it is difficult to explicitly link the dMRI signal to biological parameters such as the cellular geometry or the cellular volume fraction. Studying the dMRI signal arising from a single neuron can provide insight into how the geometrical structure of neurons influences the measured signal. We formulate the Bloch-Torrey PDE inside a single neuron, under no water exchange condition with the extracellular space, and show how to reduce the 3D simulation in the full neuron to a 3D simulation around the soma and 1D simulations in the neurites. We show that this latter approach is computationally much faster than full 3D simulation and still gives accurate results over a wide range of diffusion times

  2. DTPA: Bis benzimidazole as multi model imaging agent

    International Nuclear Information System (INIS)

    Srivastava, Vikas; Tiwari, A.K.; Sharma, H.; Sharma, R.; Mishra, A.K.

    2010-01-01

    Full text: The DTPA bis benzimidazole analogue has been tested for radiopharmaceutical efficacy. The radiolabelling was found more then 98% after 8 hrs and blood kinetics was fast. The compound was also tested for optical imaging agent. The Eu 3+ ion has an absorption band in the visible spectrum (578-582 nm) whose wavelength is very sensitive to even small changes in the coordination environment. Although the intensity of this 7F0 → 5D0 transition is low, the bands are relatively narrow, which allows distinguishing different coordination states of the metal. For Eu 3+ complexes which have two differently hydrated forms in aqueous solution, one observes two absorption bands belonging to the two species. High-resolution UV-visible spectra were recorded in aqueous solutions which show a temperature invariant absorption with two distinct, temperature-dependent absorption bands. The intensity ratio of these two bands changes with temperature: the band at shorter wavelengths is decreasing very slightly, while that at longer wavelengths is increasing with the temperature. The ratio of the integrals of the two bands is related to the equilibrium constant, and its temperature dependence yields the reaction enthalpy and entropy

  3. Imaging system models for small-bore DOI-PET scanners

    International Nuclear Information System (INIS)

    Takahashi, Hisashi; Kobayashi, Tetsuya; Yamaya, Taiga; Murayama, Hideo; Kitamura, Keishi; Hasegawa, Tomoyuki; Suga, Mikio

    2006-01-01

    Depth-of-interaction (DOI) information, which improves resolution uniformity in the field of view (FOV), is expected to lead to high-sensitivity PET scanners with small-bore detector rings. We are developing small-bore PET scanners with DOI detectors arranged in hexagonal or overlapped tetragonal patterns for small animal imaging or mammography. It is necessary to optimize the imaging system model because these scanners exhibit irregular detector sampling. In this work, we compared two imaging system models: (a) a parallel sub-LOR model in which the detector response functions (DRFs) are assumed to be uniform along the line of responses (LORs) and (b) a sub-crystal model in which each crystal is divided into a set of smaller volumes. These two models were applied to the overlapped tetragonal scanner (FOV 38.1 mm in diameter) and the hexagonal scanner (FOV 85.2 mm in diameter) simulated by GATE. We showed that the resolution non-uniformity of system model (b) was improved by 40% compared with that of system model (a) in the overlapped tetragonal scanner and that the resolution non-uniformity of system model (a) was improved by 18% compared with that of system model (b) in the hexagonal scanner. These results indicate that system model (b) should be applied to the overlapped tetragonal scanner and system model (a) should be applied to the hexagonal scanner. (author)

  4. Deep HST Imaging in 47 Tucanae: A Global Dynamical Model

    Science.gov (United States)

    Heyl, J.; Caiazzo, I.; Richer, H.; Anderson, J.; Kalirai, J.; Parada, J.

    2017-12-01

    Multi-epoch observations with the Advanced Camera Survey and WFC3 on the Hubble Space Telescope provide a unique and comprehensive probe of stellar dynamics within 47 Tucanae. We confront analytic models of the globular cluster with the observed stellar proper motions that probe along the main sequence from just above 0.8-0.1M ⊙ as well as white dwarfs younger than 1 Gyr. One field lies just beyond the half-light radius where dynamical models (e.g., lowered Maxwellian distributions) make robust predictions for the stellar proper motions. The observed proper motions in this outer field show evidence for anisotropy in the velocity distribution as well as skewness; the latter is evidence of rotation. The measured velocity dispersions and surface brightness distributions agree in detail with a rotating anisotropic model of the stellar distribution function with mild dependence of the proper-motion dispersion on mass. However, the best-fitting models underpredict the rotation and skewness of the stellar velocities. In the second field, centered on the core of the cluster, the mass segregation in proper motion is much stronger. Nevertheless the model developed in the outer field can be extended inward by taking this mass segregation into account in a heuristic fashion. The proper motions of the main-sequence stars yield a mass estimate of the cluster of 1.31+/- 0.02× {10}6{M}⊙ at a distance of 4.7 kpc. By comparing the proper motions of a sample of giant and subgiant stars with the observed radial velocities we estimate the distance to the cluster kinematically to be 4.29 ± 0.47 kpc.

  5. Multi-object segmentation framework using deformable models for medical imaging analysis.

    Science.gov (United States)

    Namías, Rafael; D'Amato, Juan Pablo; Del Fresno, Mariana; Vénere, Marcelo; Pirró, Nicola; Bellemare, Marc-Emmanuel

    2016-08-01

    Segmenting structures of interest in medical images is an important step in different tasks such as visualization, quantitative analysis, simulation, and image-guided surgery, among several other clinical applications. Numerous segmentation methods have been developed in the past three decades for extraction of anatomical or functional structures on medical imaging. Deformable models, which include the active contour models or snakes, are among the most popular methods for image segmentation combining several desirable features such as inherent connectivity and smoothness. Even though different approaches have been proposed and significant work has been dedicated to the improvement of such algorithms, there are still challenging research directions as the simultaneous extraction of multiple objects and the integration of individual techniques. This paper presents a novel open-source framework called deformable model array (DMA) for the segmentation of multiple and complex structures of interest in different imaging modalities. While most active contour algorithms can extract one region at a time, DMA allows integrating several deformable models to deal with multiple segmentation scenarios. Moreover, it is possible to consider any existing explicit deformable model formulation and even to incorporate new active contour methods, allowing to select a suitable combination in different conditions. The framework also introduces a control module that coordinates the cooperative evolution of the snakes and is able to solve interaction issues toward the segmentation goal. Thus, DMA can implement complex object and multi-object segmentations in both 2D and 3D using the contextual information derived from the model interaction. These are important features for several medical image analysis tasks in which different but related objects need to be simultaneously extracted. Experimental results on both computed tomography and magnetic resonance imaging show that the proposed

  6. New Parametric Imaging Algorithm for Quantification of Binding Parameter in non-reversible compartment model: MLAIR

    International Nuclear Information System (INIS)

    Kim, Su Jin; Lee, Jae Sung; Kim, Yu Kyeong; Lee, Dong Soo

    2007-01-01

    Parametric imaging allows us analysis of the entire brain or body image. Graphical approaches are commonly employed to generate parametric imaging through linear or multilinear regression. However, this linear regression method has limited accuracy due to bias in high level of noise data. Several methods have been proposed to reduce bias for linear regression estimation especially in reversible model. In this study, we focus on generating a net accumulation rate (K i ), which is related to binding parameter in brain receptor study, parametric imaging in an irreversible compartment model using multiple linear analysis. The reliability of a newly developed multiple linear analysis method (MLAIR) was assessed through the Monte Carlo simulation, and we applied it to a [ 11 C]MeNTI PET for opioid receptor

  7. In Vivo PET Imaging of HDL in Multiple Atherosclerosis Models

    DEFF Research Database (Denmark)

    Pérez-Medina, Carlos; Binderup, Tina; Lobatto, Mark E

    2016-01-01

    . Ex vivo validation was conducted by radioactivity counting, autoradiography, and near-infrared fluorescence imaging. Flow cytometric assessment of cellular specificity in different tissues was performed in the murine model. RESULTS: We observed distinct pharmacokinetic profiles for the two (89)Zr......OBJECTIVES: The goal of this study was to develop and validate a noninvasive imaging tool to visualize the in vivo behavior of high-density lipoprotein (HDL) by using positron emission tomography (PET), with an emphasis on its plaque-targeting abilities. BACKGROUND: HDL is a natural nanoparticle......,2-distearoyl-sn-glycero-3-phosphoethanolamine-deferoxamine B). Biodistribution and plaque targeting of radiolabeled HDL were studied in established murine, rabbit, and porcine atherosclerosis models by using PET combined with computed tomography (PET/CT) imaging or PET combined with magnetic resonance imaging...

  8. Spatiotemporal processing of gated cardiac SPECT images using deformable mesh modeling

    International Nuclear Information System (INIS)

    Brankov, Jovan G.; Yang Yongyi; Wernick, Miles N.

    2005-01-01

    In this paper we present a spatiotemporal processing approach, based on deformable mesh modeling, for noise reduction in gated cardiac single-photon emission computed tomography images. Because of the partial volume effect (PVE), clinical cardiac-gated perfusion images exhibit a phenomenon known as brightening--the myocardium appears to become brighter as the heart wall thickens. Although brightening is an artifact, it serves as an important diagnostic feature for assessment of wall thickening in clinical practice. Our proposed processing algorithm aims to preserve this important diagnostic feature while reducing the noise level in the images. The proposed algorithm is based on the use of a deformable mesh for modeling the cardiac motion in a gated cardiac sequence, based on which the images are processed by smoothing along space-time trajectories of object points while taking into account the PVE. Our experiments demonstrate that the proposed algorithm can yield significantly more-accurate results than several existing methods

  9. Phase aided 3D imaging and modeling: dedicated systems and case studies

    Science.gov (United States)

    Yin, Yongkai; He, Dong; Liu, Zeyi; Liu, Xiaoli; Peng, Xiang

    2014-05-01

    Dedicated prototype systems for 3D imaging and modeling (3DIM) are presented. The 3D imaging systems are based on the principle of phase-aided active stereo, which have been developed in our laboratory over the past few years. The reported 3D imaging prototypes range from single 3D sensor to a kind of optical measurement network composed of multiple node 3D-sensors. To enable these 3D imaging systems, we briefly discuss the corresponding calibration techniques for both single sensor and multi-sensor optical measurement network, allowing good performance of the 3DIM prototype systems in terms of measurement accuracy and repeatability. Furthermore, two case studies including the generation of high quality color model of movable cultural heritage and photo booth from body scanning are presented to demonstrate our approach.

  10. 3D Modeling from Multi-views Images for Cultural Heritage in Wat-Pho, Thailand

    Science.gov (United States)

    Soontranon, N.; Srestasathiern, P.; Lawawirojwong, S.

    2015-08-01

    In Thailand, there are several types of (tangible) cultural heritages. This work focuses on 3D modeling of the heritage objects from multi-views images. The images are acquired by using a DSLR camera which costs around 1,500 (camera and lens). Comparing with a 3D laser scanner, the camera is cheaper and lighter than the 3D scanner. Hence, the camera is available for public users and convenient for accessing narrow areas. The acquired images consist of various sculptures and architectures in Wat-Pho which is a Buddhist temple located behind the Grand Palace (Bangkok, Thailand). Wat-Pho is known as temple of the reclining Buddha and the birthplace of traditional Thai massage. To compute the 3D models, a diagram is separated into following steps; Data acquisition, Image matching, Image calibration and orientation, Dense matching and Point cloud processing. For the initial work, small heritages less than 3 meters height are considered for the experimental results. A set of multi-views images of an interested object is used as input data for 3D modeling. In our experiments, 3D models are obtained from MICMAC (open source) software developed by IGN, France. The output of 3D models will be represented by using standard formats of 3D point clouds and triangulated surfaces such as .ply, .off, .obj, etc. To compute for the efficient 3D models, post-processing techniques are required for the final results e.g. noise reduction, surface simplification and reconstruction. The reconstructed 3D models can be provided for public access such as website, DVD, printed materials. The high accurate 3D models can also be used as reference data of the heritage objects that must be restored due to deterioration of a lifetime, natural disasters, etc.

  11. Mathematical Foundation Based Inter-Connectivity modelling of Thermal Image processing technique for Fire Protection

    Directory of Open Access Journals (Sweden)

    Sayantan Nath

    2015-09-01

    Full Text Available In this paper, integration between multiple functions of image processing and its statistical parameters for intelligent alarming series based fire detection system is presented. The proper inter-connectivity mapping between processing elements of imagery based on classification factor for temperature monitoring and multilevel intelligent alarm sequence is introduced by abstractive canonical approach. The flow of image processing components between core implementation of intelligent alarming system with temperature wise area segmentation as well as boundary detection technique is not yet fully explored in the present era of thermal imaging. In the light of analytical perspective of convolutive functionalism in thermal imaging, the abstract algebra based inter-mapping model between event-calculus supported DAGSVM classification for step-by-step generation of alarm series with gradual monitoring technique and segmentation of regions with its affected boundaries in thermographic image of coal with respect to temperature distinctions is discussed. The connectedness of the multifunctional operations of image processing based compatible fire protection system with proper monitoring sequence is presently investigated here. The mathematical models representing the relation between the temperature affected areas and its boundary in the obtained thermal image defined in partial derivative fashion is the core contribution of this study. The thermal image of coal sample is obtained in real-life scenario by self-assembled thermographic camera in this study. The amalgamation between area segmentation, boundary detection and alarm series are described in abstract algebra. The principal objective of this paper is to understand the dependency pattern and the principles of working of image processing components and structure an inter-connected modelling technique also for those components with the help of mathematical foundation.

  12. Imaging

    International Nuclear Information System (INIS)

    Kellum, C.D.; Fisher, L.M.; Tegtmeyer, C.J.

    1987-01-01

    This paper examines the advantages of the use of excretory urography for diagnosis. According to the authors, excretory urography remains the basic radiologic examination of the urinary tract and is the foundation for the evaluation of suspected urologic disease. Despite development of the newer diagnostic modalities such as isotope scanning, ultrasonography, CT, and magnetic resonsance imaging (MRI), excretory urography has maintained a prominent role in ruorradiology. Some indications have been altered and will continue to change with the newer imaging modalities, but the initial evaluation of suspected urinary tract structural abnormalities; hematuria, pyuria, and calculus disease is best performed with excretory urography. The examination is relatively inexpensive and simple to perform, with few contraindictions. Excretory urography, when properly performed, can provide valuable information about the renal parenchyma, pelvicalyceal system, ureters, and urinary bladder

  13. Applications of Panoramic Images: from 720° Panorama to Interior 3d Models of Augmented Reality

    Science.gov (United States)

    Lee, I.-C.; Tsai, F.

    2015-05-01

    A series of panoramic images are usually used to generate a 720° panorama image. Although panoramic images are typically used for establishing tour guiding systems, in this research, we demonstrate the potential of using panoramic images acquired from multiple sites to create not only 720° panorama, but also three-dimensional (3D) point clouds and 3D indoor models. Since 3D modeling is one of the goals of this research, the location of the panoramic sites needed to be carefully planned in order to maintain a robust result for close-range photogrammetry. After the images are acquired, panoramic images are processed into 720° panoramas, and these panoramas which can be used directly as panorama guiding systems or other applications. In addition to these straightforward applications, interior orientation parameters can also be estimated while generating 720° panorama. These parameters are focal length, principle point, and lens radial distortion. The panoramic images can then be processed with closerange photogrammetry procedures to extract the exterior orientation parameters and generate 3D point clouds. In this research, VisaulSFM, a structure from motion software is used to estimate the exterior orientation, and CMVS toolkit is used to generate 3D point clouds. Next, the 3D point clouds are used as references to create building interior models. In this research, Trimble Sketchup was used to build the model, and the 3D point cloud was added to the determining of locations of building objects using plane finding procedure. In the texturing process, the panorama images are used as the data source for creating model textures. This 3D indoor model was used as an Augmented Reality model replacing a guide map or a floor plan commonly used in an on-line touring guide system. The 3D indoor model generating procedure has been utilized in two research projects: a cultural heritage site at Kinmen, and Taipei Main Station pedestrian zone guidance and navigation system. The

  14. Dynamic PET simulator via tomographic emission projection for kinetic modeling and parametric image studies

    Energy Technology Data Exchange (ETDEWEB)

    Häggström, Ida, E-mail: haeggsti@mskcc.org [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York 10065 and Department of Radiation Sciences, Umeå University, Umeå 90187 (Sweden); Beattie, Bradley J.; Schmidtlein, C. Ross [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York 10065 (United States)

    2016-06-15

    Purpose: To develop and evaluate a fast and simple tool called dPETSTEP (Dynamic PET Simulator of Tracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment, postprocessing choices, etc., on dynamic and parametric images. Methods: The tool was developed in MATLAB using both new and previously reported modules of PETSTEP (PET Simulator of Tracers via Emission Projection). Time activity curves are generated for each voxel of the input parametric image, whereby effects of imaging system blurring, counting noise, scatters, randoms, and attenuation are simulated for each frame. Each frame is then reconstructed into images according to the user specified method, settings, and corrections. Reconstructed images were compared to MC data, and simple Gaussian noised time activity curves (GAUSS). Results: dPETSTEP was 8000 times faster than MC. Dynamic images from dPETSTEP had a root mean square error that was within 4% on average of that of MC images, whereas the GAUSS images were within 11%. The average bias in dPETSTEP and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dPETSTEP images conformed well to MC images, confirmed visually by scatter plot histograms, and statistically by tumor region of interest histogram comparisons that showed no significant differences (p < 0.01). Compared to GAUSS, dPETSTEP images and noise properties agreed better with MC. Conclusions: The authors have developed a fast and easy one-stop solution for simulations of dynamic PET and parametric images, and demonstrated that it generates both images and subsequent parametric images with very similar noise properties to those of MC images, in a fraction of the time. They believe dPETSTEP to be very useful for generating fast, simple, and realistic results, however since it uses simple scatter and random models it may not be suitable for

  15. Dynamic PET simulator via tomographic emission projection for kinetic modeling and parametric image studies

    International Nuclear Information System (INIS)

    Häggström, Ida; Beattie, Bradley J.; Schmidtlein, C. Ross

    2016-01-01

    Purpose: To develop and evaluate a fast and simple tool called dPETSTEP (Dynamic PET Simulator of Tracers via Emission Projection), for dynamic PET simulations as an alternative to Monte Carlo (MC), useful for educational purposes and evaluation of the effects of the clinical environment, postprocessing choices, etc., on dynamic and parametric images. Methods: The tool was developed in MATLAB using both new and previously reported modules of PETSTEP (PET Simulator of Tracers via Emission Projection). Time activity curves are generated for each voxel of the input parametric image, whereby effects of imaging system blurring, counting noise, scatters, randoms, and attenuation are simulated for each frame. Each frame is then reconstructed into images according to the user specified method, settings, and corrections. Reconstructed images were compared to MC data, and simple Gaussian noised time activity curves (GAUSS). Results: dPETSTEP was 8000 times faster than MC. Dynamic images from dPETSTEP had a root mean square error that was within 4% on average of that of MC images, whereas the GAUSS images were within 11%. The average bias in dPETSTEP and MC images was the same, while GAUSS differed by 3% points. Noise profiles in dPETSTEP images conformed well to MC images, confirmed visually by scatter plot histograms, and statistically by tumor region of interest histogram comparisons that showed no significant differences (p < 0.01). Compared to GAUSS, dPETSTEP images and noise properties agreed better with MC. Conclusions: The authors have developed a fast and easy one-stop solution for simulations of dynamic PET and parametric images, and demonstrated that it generates both images and subsequent parametric images with very similar noise properties to those of MC images, in a fraction of the time. They believe dPETSTEP to be very useful for generating fast, simple, and realistic results, however since it uses simple scatter and random models it may not be suitable for

  16. Segmentation of Concealed Objects in Passive Millimeter-Wave Images Based on the Gaussian Mixture Model

    Science.gov (United States)

    Yu, Wangyang; Chen, Xiangguang; Wu, Lei

    2015-04-01

    Passive millimeter wave (PMMW) imaging has become one of the most effective means to detect the objects concealed under clothing. Due to the limitations of the available hardware and the inherent physical properties of PMMW imaging systems, images often exhibit poor contrast and low signal-to-noise ratios. Thus, it is difficult to achieve ideal results by using a general segmentation algorithm. In this paper, an advanced Gaussian Mixture Model (GMM) algorithm for the segmentation of concealed objects in PMMW images is presented. Our work is concerned with the fact that the GMM is a parametric statistical model, which is often used to characterize the statistical behavior of images. Our approach is three-fold: First, we remove the noise from the image using both a notch reject filter and a total variation filter. Next, we use an adaptive parameter initialization GMM algorithm (APIGMM) for simulating the histogram of images. The APIGMM provides an initial number of Gaussian components and start with more appropriate parameter. Bayesian decision is employed to separate the pixels of concealed objects from other areas. At last, the confidence interval (CI) method, alongside local gradient information, is used to extract the concealed objects. The proposed hybrid segmentation approach detects the concealed objects more accurately, even compared to two other state-of-the-art segmentation methods.

  17. 4D reconstruction of the past: the image retrieval and 3D model construction pipeline

    Science.gov (United States)

    Hadjiprocopis, Andreas; Ioannides, Marinos; Wenzel, Konrad; Rothermel, Mathias; Johnsons, Paul S.; Fritsch, Dieter; Doulamis, Anastasios; Protopapadakis, Eftychios; Kyriakaki, Georgia; Makantasis, Kostas; Weinlinger, Guenther; Klein, Michael; Fellner, Dieter; Stork, Andre; Santos, Pedro

    2014-08-01

    One of the main characteristics of the Internet era we are living in, is the free and online availability of a huge amount of data. This data is of varied reliability and accuracy and exists in various forms and formats. Often, it is cross-referenced and linked to other data, forming a nexus of text, images, animation and audio enabled by hypertext and, recently, by the Web3.0 standard. Our main goal is to enable historians, architects, archaeolo- gists, urban planners and affiliated professionals to reconstruct views of historical monuments from thousands of images floating around the web. This paper aims to provide an update of our progress in designing and imple- menting a pipeline for searching, filtering and retrieving photographs from Open Access Image Repositories and social media sites and using these images to build accurate 3D models of archaeological monuments as well as enriching multimedia of cultural / archaeological interest with metadata and harvesting the end products to EU- ROPEANA. We provide details of how our implemented software searches and retrieves images of archaeological sites from Flickr and Picasa repositories as well as strategies on how to filter the results, on two levels; a) based on their built-in metadata including geo-location information and b) based on image processing and clustering techniques. We also describe our implementation of a Structure from Motion pipeline designed for producing 3D models using the large collection of 2D input images (>1000) retrieved from Internet Repositories.

  18. A Novel Murine Model for Localized Radiation Necrosis and its Characterization Using Advanced Magnetic Resonance Imaging

    International Nuclear Information System (INIS)

    Jost, Sarah C.; Hope, Andrew; Kiehl, Erich; Perry, Arie; Travers, Sarah; Garbow, Joel R.

    2009-01-01

    Purpose: To develop a murine model of radiation necrosis using fractionated, subtotal cranial irradiation; and to investigate the imaging signature of radiation-induced tissue damage using advanced magnetic resonance imaging techniques. Methods and Materials: Twenty-four mice each received 60 Gy of hemispheric (left) irradiation in 10 equal fractions. Magnetic resonance images at 4.7 T were subsequently collected using T1-, T2-, and diffusion sequences at selected time points after irradiation. After imaging, animals were killed and their brains fixed for correlative histologic analysis. Results: Contrast-enhanced T1- and T2-weighted magnetic resonance images at months 2, 3, and 4 showed changes consistent with progressive radiation necrosis. Quantitatively, mean diffusivity was significantly higher (mean = 0.86, 1.13, and 1.24 μm 2 /ms at 2, 3, and 4 months, respectively) in radiated brain, compared with contralateral untreated brain tissue (mean = 0.78, 0.82, and 0.83 μm 2 /ms) (p < 0.0001). Histology reflected changes typically seen in radiation necrosis. Conclusions: This murine model of radiation necrosis will facilitate investigation of imaging biomarkers that distinguish between radiation necrosis and tumor recurrence. In addition, this preclinical study supports clinical data suggesting that diffusion-weighted imaging may be helpful in answering this diagnostic question in clinical settings.

  19. A multiscale MDCT image-based breathing lung model with time-varying regional ventilation

    Energy Technology Data Exchange (ETDEWEB)

    Yin, Youbing, E-mail: youbing-yin@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Radiology, The University of Iowa, Iowa City, IA 52242 (United States); Choi, Jiwoong, E-mail: jiwoong-choi@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Hoffman, Eric A., E-mail: eric-hoffman@uiowa.edu [Department of Radiology, The University of Iowa, Iowa City, IA 52242 (United States); Department of Biomedical Engineering, The University of Iowa, Iowa City, IA 52242 (United States); Department of Internal Medicine, The University of Iowa, Iowa City, IA 52242 (United States); Tawhai, Merryn H., E-mail: m.tawhai@auckland.ac.nz [Auckland Bioengineering Institute, The University of Auckland, Auckland (New Zealand); Lin, Ching-Long, E-mail: ching-long-lin@uiowa.edu [Department of Mechanical and Industrial Engineering, The University of Iowa, Iowa City, IA 52242 (United States); IIHR-Hydroscience and Engineering, The University of Iowa, Iowa City, IA 52242 (United States)

    2013-07-01

    A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C{sub 1} continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung.

  20. A multiscale MDCT image-based breathing lung model with time-varying regional ventilation

    Science.gov (United States)

    Yin, Youbing; Choi, Jiwoong; Hoffman, Eric A.; Tawhai, Merryn H.; Lin, Ching-Long

    2012-01-01

    A novel algorithm is presented that links local structural variables (regional ventilation and deforming central airways) to global function (total lung volume) in the lung over three imaged lung volumes, to derive a breathing lung model for computational fluid dynamics simulation. The algorithm constitutes the core of an integrative, image-based computational framework for subject-specific simulation of the breathing lung. For the first time, the algorithm is applied to three multi-detector row computed tomography (MDCT) volumetric lung images of the same individual. A key technique in linking global and local variables over multiple images is an in-house mass-preserving image registration method. Throughout breathing cycles, cubic interpolation is employed to ensure C1 continuity in constructing time-varying regional ventilation at the whole lung level, flow rate fractions exiting the terminal airways, and airway deformation. The imaged exit airway flow rate fractions are derived from regional ventilation with the aid of a three-dimensional (3D) and one-dimensional (1D) coupled airway tree that connects the airways to the alveolar tissue. An in-house parallel large-eddy simulation (LES) technique is adopted to capture turbulent-transitional-laminar flows in both normal and deep breathing conditions. The results obtained by the proposed algorithm when using three lung volume images are compared with those using only one or two volume images. The three-volume-based lung model produces physiologically-consistent time-varying pressure and ventilation distribution. The one-volume-based lung model under-predicts pressure drop and yields un-physiological lobar ventilation. The two-volume-based model can account for airway deformation and non-uniform regional ventilation to some extent, but does not capture the non-linear features of the lung. PMID:23794749

  1. Apoptosis imaging studies in various animal models using radio-iodinated peptide.

    Science.gov (United States)

    Kwak, Wonjung; Ha, Yeong Su; Soni, Nisarg; Lee, Woonghee; Park, Se-Il; Ahn, Heesu; An, Gwang Il; Kim, In-San; Lee, Byung-Heon; Yoo, Jeongsoo

    2015-01-01

    Apoptosis has a role in many medical disorders and treatments; hence, its non-invasive evaluation is one of the most riveting research topics. Currently annexin V is used as gold standard for imaging apoptosis. However, several drawbacks, including high background, slow body clearance, make it a suboptimum marker for apoptosis imaging. In this study, we radiolabeled the recently identified histone H1 targeting peptide (ApoPep-1) and evaluated its potential as a new apoptosis imaging agent in various animal models. ApoPep-1 (CQRPPR) was synthesized, and an extra tyrosine residue was added to its N-terminal end for radiolabeling. This peptide was radiolabeled with (124)I and (131)I and was tested for its serum stability. Surgery- and drug-induced apoptotic rat models were prepared for apoptosis evaluation, and PET imaging was performed. Doxorubicin was used for xenograft tumor treatment in mice, and the induced apoptosis was studied. Tumor metabolism and proliferation were assessed by [(18)F]FDG and [(18)F]FLT PET imaging and compared with ApoPep-1 after doxorubicin treatment. The peptide was radiolabeled at high purity, and it showed reasonably good stability in serum. Cell death was easily imaged by radiolabeled ApoPep-1 in an ischemia surgery model. And, liver apoptosis was more clearly identified by ApoPep-1 rather than [(124)I]annexin V in cycloheximide-treated models. Three doxorubicin doses inhibited tumor growth, which was evaluated by 30-40% decreases of [(18)F]FDG and [(18)F]FLT PET uptake in the tumor area. However, ApoPep-1 demonstrated more than 200% increase in tumor uptake after chemotherapy, while annexin V did not show any meaningful uptake in the tumor compared with the background. Biodistribution data were also in good agreement with the microPET imaging results. All of the experimental data clearly demonstrated high potential of the radiolabeled ApoPep-1 for in vivo apoptosis imaging.

  2. Analytic sensing for multi-layer spherical models with application to EEG source imaging

    OpenAIRE

    Kandaswamy, Djano; Blu, Thierry; Van De Ville, Dimitri

    2013-01-01

    Source imaging maps back boundary measurements to underlying generators within the domain; e. g., retrieving the parameters of the generating dipoles from electrical potential measurements on the scalp such as in electroencephalography (EEG). Fitting such a parametric source model is non-linear in the positions of the sources and renewed interest in mathematical imaging has led to several promising approaches. One important step in these methods is the application of a sensing principle that ...

  3. Establishment of imageable model of T-cell lymphoma growing in syngenic mice

    Czech Academy of Sciences Publication Activity Database

    Větvička, David; Hovorka, Ondřej; Kovář, Lubomír; Říhová, Blanka

    2009-01-01

    Roč. 29, č. 11 (2009), s. 4513-4518 ISSN 0250-7005 R&D Projects: GA AV ČR IAA400200702; GA AV ČR KAN200200651; GA ČR GD310/08/H077 Institutional research plan: CEZ:AV0Z50200510 Keywords : Imageable model * EL-4 T- cell lymphoma * whole body imaging Subject RIV: EC - Immunology Impact factor: 1.428, year: 2009

  4. Multimodality imaging and mathematical modelling of drug delivery to glioblastomas.

    Science.gov (United States)

    Boujelben, Ahmed; Watson, Michael; McDougall, Steven; Yen, Yi-Fen; Gerstner, Elizabeth R; Catana, Ciprian; Deisboeck, Thomas; Batchelor, Tracy T; Boas, David; Rosen, Bruce; Kalpathy-Cramer, Jayashree; Chaplain, Mark A J

    2016-10-06

    Patients diagnosed with glioblastoma, an aggressive brain tumour, have a poor prognosis, with a median overall survival of less than 15 months. Vasculature within these tumours is typically abnormal, with increased tortuosity, dilation and disorganization, and they typically exhibit a disrupted blood-brain barrier (BBB). Although it has been hypothesized that the 'normalization' of the vasculature resulting from anti-angiogenic therapies could improve drug delivery through improved blood flow, there is also evidence that suggests that the restoration of BBB integrity might limit the delivery of therapeutic agents and hence their effectiveness. In this paper, we apply mathematical models of blood flow, vascular permeability and diffusion within the tumour microenvironment to investigate the effect of these competing factors on drug delivery. Preliminary results from the modelling indicate that all three physiological parameters investigated-flow rate, vessel permeability and tissue diffusion coefficient-interact nonlinearly to produce the observed average drug concentration in the microenvironment.

  5. Factoring variations in natural images with deep Gaussian mixture models

    OpenAIRE

    van den Oord, Aäron; Schrauwen, Benjamin

    2014-01-01

    Generative models can be seen as the swiss army knives of machine learning, as many problems can be written probabilistically in terms of the distribution of the data, including prediction, reconstruction, imputation and simulation. One of the most promising directions for unsupervised learning may lie in Deep Learning methods, given their success in supervised learning. However, one of the cur- rent problems with deep unsupervised learning methods, is that they often are harder to scale. As ...

  6. Face Recognition for Access Control Systems Combining Image-Difference Features Based on a Probabilistic Model

    Science.gov (United States)

    Miwa, Shotaro; Kage, Hiroshi; Hirai, Takashi; Sumi, Kazuhiko

    We propose a probabilistic face recognition algorithm for Access Control System(ACS)s. Comparing with existing ACSs using low cost IC-cards, face recognition has advantages in usability and security that it doesn't require people to hold cards over scanners and doesn't accept imposters with authorized cards. Therefore face recognition attracts more interests in security markets than IC-cards. But in security markets where low cost ACSs exist, price competition is important, and there is a limitation on the quality of available cameras and image control. Therefore ACSs using face recognition are required to handle much lower quality images, such as defocused and poor gain-controlled images than high security systems, such as immigration control. To tackle with such image quality problems we developed a face recognition algorithm based on a probabilistic model which combines a variety of image-difference features trained by Real AdaBoost with their prior probability distributions. It enables to evaluate and utilize only reliable features among trained ones during each authentication, and achieve high recognition performance rates. The field evaluation using a pseudo Access Control System installed in our office shows that the proposed system achieves a constant high recognition performance rate independent on face image qualities, that is about four times lower EER (Equal Error Rate) under a variety of image conditions than one without any prior probability distributions. On the other hand using image difference features without any prior probabilities are sensitive to image qualities. We also evaluated PCA, and it has worse, but constant performance rates because of its general optimization on overall data. Comparing with PCA, Real AdaBoost without any prior distribution performs twice better under good image conditions, but degrades to a performance as good as PCA under poor image conditions.

  7. Three-dimensional modeler for animated images display system

    International Nuclear Information System (INIS)

    Boubekeur, Rania

    1987-01-01

    The mv3d software allows the modeling and display of three dimensional objects in interpretative mode with animation possibility in real time. This system is intended for a graphical extension of a FORTH interpreter (implemented by CEA/IRDI/D.LETI/DEIN) in order to control a specific hardware (3.D card designed and implemented by DEIN) allowing the generation of three dimensional objects. The object description is carried out with a specific graphical language integrated in the FORTH interpreter. Objects are modeled using elementary solids called basic forms (cube, cone, cylinder...) assembled with classical geometric transformations (rotation, translation and scaling). These basic forms are approximated by plane polygonal facets further divided in triangles. Coordinates of the summits of triangles constitute the geometrical data. These are sent to the 3.D. card for processing and display. Performed processing are: geometrical transformations on display, hidden surface elimination, shading and clipping. The mv3d software is not an entire modeler but a simple, modular and extensible tool, to which other specific functions may be easily added such as: robots motion, collisions... (author) [fr

  8. Eco Control of Agro Pests using Imaging, Modelling & Natural Predators

    Directory of Open Access Journals (Sweden)

    Fina Faithpraise

    2014-10-01

    Full Text Available Caterpillars in their various forms: size, shape, and colour cause significant harm to crops and humans. This paper offers a solution for the detection and control of caterpillars through the use of a sustainable pest control system that does not require the application of chemical pesticides, which damage human health and destroy the naturally beneficial insects within the environment. The proposed system is capable of controlling 80% of the population of caterpillars in less than 65 days by deploying a controlled number of larval parasitoid wasps (Cotesia Flavipes, Cameron into the crop environment. This is made possible by using a continuous time model of the interaction between the caterpillar and the Cotesia Flavipes (Cameron wasps using a set of simultaneous, non-linear, ordinary differential equations incorporating natural death rates based on the Weibull probability distribution function. A negative binomial distribution is used to model the efficiency and the probability that the wasp will find and parasitize a host larva. The caterpillar is presented in all its life-cycle stages of: egg, larva, pupa and adult and the Cotesia Flavipes (Cameron wasp is present as an adult larval parasitoid. Biological control modelling is used to estimate the quantity of the Cotesia Flavipes (Cameron wasps that should be introduced into the caterpillar infested environment to suppress its population density to an economically acceptable level within a prescribed number of days.

  9. Optical coherence tomography imaging of colonic crypts in a mouse model of colorectal cancer

    Science.gov (United States)

    Welge, Weston A.; Barton, Jennifer K.

    2016-03-01

    Aberrant crypt foci (ACF) are abnormal epithelial lesions that precede development of colonic polyps. As the earliest morphological change in the development of colorectal cancer, ACF is a highly studied phenomenon. The most common method of imaging ACF is chromoendoscopy using methylene blue as a contrast agent. Narrow- band imaging is a contrast-agent-free modality for imaging the colonic crypts. Optical coherence tomography (OCT) is an attractive alternative to chromoendoscopy and narrow-band imaging because it can resolve the crypt structure at sufficiently high sampling while simultaneously providing depth-resolved data. We imaged in vivo the distal 15 mm of colon in the azoxymethane (AOM) mouse model of colorectal cancer using a commercial swept-source OCT system and a miniature endoscope designed and built in-house. We present en face images of the colonic crypts and demonstrate that different patterns in healthy and adenoma tissue can be seen. These patterns correspond to those reported in the literature. We have previously demonstrated early detection of colon adenoma using OCT by detecting minute thickening of the mucosa. By combining mucosal thickness measurement with imaging of the crypt structure, OCT can be used to correlate ACF and adenoma development in space and time. These results suggest that OCT may be a superior imaging modality for studying the connection between ACF and colorectal cancer.

  10. Combining variational and model-based techniques to register PET and MR images in hand osteoarthritis

    International Nuclear Information System (INIS)

    Magee, Derek; Tanner, Steven F; Jeavons, Alan P; Waller, Michael; Tan, Ai Lyn; McGonagle, Dennis

    2010-01-01

    Co-registration of clinical images acquired using different imaging modalities and equipment is finding increasing use in patient studies. Here we present a method for registering high-resolution positron emission tomography (PET) data of the hand acquired using high-density avalanche chambers with magnetic resonance (MR) images of the finger obtained using a 'microscopy coil'. This allows the identification of the anatomical location of the PET radiotracer and thereby locates areas of active bone metabolism/'turnover'. Image fusion involving data acquired from the hand is demanding because rigid-body transformations cannot be employed to accurately register the images. The non-rigid registration technique that has been implemented in this study uses a variational approach to maximize the mutual information between images acquired using these different imaging modalities. A piecewise model of the fingers is employed to ensure that the methodology is robust and that it generates an accurate registration. Evaluation of the accuracy of the technique is tested using both synthetic data and PET and MR images acquired from patients with osteoarthritis. The method outperforms some established non-rigid registration techniques and results in a mean registration error that is less than approximately 1.5 mm in the vicinity of the finger joints.

  11. Conversion of a Surface Model of a Structure of Interest into a Volume Model for Medical Image Retrieval

    Directory of Open Access Journals (Sweden)

    Sarmad ISTEPHAN

    2015-06-01

    Full Text Available Volumetric medical image datasets contain vital information for noninvasive diagnosis, treatment planning and prognosis. However, direct and unlimited query of such datasets is hindered due to the unstructured nature of the imaging data. This study is a step towards the unlimited query of medical image datasets by focusing on specific Structures of Interest (SOI. A requirement in achieving this objective is having both the surface and volume models of the SOI. However, typically, only the surface model is available. Therefore, this study focuses on creating a fast method to convert a surface model to a volume model. Three methods (1D, 2D and 3D are proposed and evaluated using simulated and real data of Deep Perisylvian Area (DPSA within the human brain. The 1D method takes 80 msec for DPSA model; about 4 times faster than 2D method and 7.4 fold faster than 3D method, with over 97% accuracy. The proposed 1D method is feasible for surface to volume conversion in computer aided diagnosis, treatment planning and prognosis systems containing large amounts of unstructured medical images.

  12. Short-Term Solar Irradiance Forecasts Using Sky Images and Radiative Transfer Model

    Directory of Open Access Journals (Sweden)

    Juan Du

    2018-05-01

    Full Text Available In this paper, we propose a novel forecast method which addresses the difficulty in short-term solar irradiance forecasting that arises due to rapidly evolving environmental factors over short time periods. This involves the forecasting of Global Horizontal Irradiance (GHI that combines prediction sky images with a Radiative Transfer Model (RTM. The prediction images (up to 10 min ahead are produced by a non-local optical flow method, which is used to calculate the cloud motion for each pixel, with consecutive sky images at 1 min intervals. The Direct Normal Irradiance (DNI and the diffuse radiation intensity field under clear sky and overcast conditions obtained from the RTM are then mapped to the sky images. Through combining the cloud locations on the prediction image with the corresponding instance of image-based DNI and diffuse radiation intensity fields, the GHI can be quantitatively forecasted for time horizons of 1–10 min ahead. The solar forecasts are evaluated in terms of root mean square error (RMSE and mean absolute error (MAE in relation to in-situ measurements and compared to the performance of the persistence model. The results of our experiment show that GHI forecasts using the proposed method perform better than the persistence model.

  13. Efficient and robust model-to-image alignment using 3D scale-invariant features.

    Science.gov (United States)

    Toews, Matthew; Wells, William M

    2013-04-01

    This paper presents feature-based alignment (FBA), a general method for efficient and robust model-to-image alignment. Volumetric images, e.g. CT scans of the human body, are modeled probabilistically as a collage of 3D scale-invariant image features within a normalized reference space. Features are incorporated as a latent random variable and marginalized out in computing a maximum a posteriori alignment solution. The model is learned from features extracted in pre-aligned training images, then fit to features extracted from a new image to identify a globally optimal locally linear alignment solution. Novel techniques are presented for determining local feature orientation and efficiently encoding feature intensity in 3D. Experiments involving difficult magnetic resonance (MR) images of the human brain demonstrate FBA achieves alignment accuracy similar to widely-used registration methods, while requiring a fraction of the memory and computation resources and offering a more robust, globally optimal solution. Experiments on CT human body scans demonstrate FBA as an effective system for automatic human body alignment where other alignment methods break down. Copyright © 2012 Elsevier B.V. All rights reserved.

  14. Time series modeling of live-cell shape dynamics for image-based phenotypic profiling.

    Science.gov (United States)

    Gordonov, Simon; Hwang, Mun Kyung; Wells, Alan; Gertler, Frank B; Lauffenburger, Douglas A; Bathe, Mark

    2016-01-01

    Live-cell imaging can be used to capture spatio-temporal aspects of cellular responses that are not accessible to fixed-cell imaging. As the use of live-cell imaging continues to increase, new computational procedures are needed to characterize and classify the temporal dynamics of individual cells. For this purpose, here we present the general experimental-computational framework SAPHIRE (Stochastic Annotation of Phenotypic Individual-cell Responses) to characterize phenotypic cellular responses from time series imaging datasets. Hidden Markov modeling is used to infer and annotate morphological state and state-switching properties from image-derived cell shape measurements. Time series modeling is performed on each cell individually, making the approach broadly useful for analyzing asynchronous cell populations. Two-color fluorescent cells simultaneously expressing actin and nuclear reporters enabled us to profile temporal changes in cell shape following pharmacological inhibition of cytoskeleton-regulatory signaling pathways. Results are compared with existing approaches conventionally applied to fixed-cell imaging datasets, and indicate that time series modeling captures heterogeneous dynamic cellular responses that can improve drug classification and offer additional important insight into mechanisms of drug action. The software is available at http://saphire-hcs.org.

  15. Studies on diagnosis of lung emphysema by CT image using experimental models and clinical cases

    International Nuclear Information System (INIS)

    Nakatani, Seiki

    1998-01-01

    Since the detailed report between the degree of functional disorder in lung emphysema and the analysis of CT image is quite unknown, the present study was attempted to produce the experimental model of lung emphysema with various stages by the administration of papain to the focal lobe in canine lung. Using this model or clinical lung emphysema, the relationship between the degree of destruction of alveolar walls, clinical pulmonary functions and CT images was investigated. CT scan was performed at the level of 50% vital capacity in both experimental models and clinical subjects by using spirometric gating CT. CT density histogram was obtained from CT image which was produced by using the developed software for this purpose. Densitometric parameters, such as mean CT value, %LAA, the peak in the histogram and 5% tile were selected from CT image. Papain solution of 5 mg/kg body weight was cumulatively administered to the left lower lobe in canine lung, resulting in the destruction of lung alveolar walls in parallel to the increasing dosage of papain. There was a significant correlation between not only the increasing dosage of papain, but also %FEV 1.0 and CT densitometric parameters, indicating that the histological changes of alveolar walls and the lung function in lung emphysema could be estimated by analysis of CT image. These experimental and clinical studies suggest that the analysis of CT image can reflect the pathophysiological changes in the lung and be useful for precise clinical diagnosis of lung emphysema. (author)

  16. Multidirectional Scanning Model, MUSCLE, to Vectorize Raster Images with Straight Lines

    Directory of Open Access Journals (Sweden)

    Ibrahim Baz

    2008-04-01

    Full Text Available This paper presents a new model, MUSCLE (Multidirectional Scanning for Line Extraction, for automatic vectorization of raster images with straight lines. The algorithm of the model implements the line thinning and the simple neighborhood methods to perform vectorization. The model allows users to define specified criteria which are crucial for acquiring the vectorization process. In this model, various raster images can be vectorized such as township plans, maps, architectural drawings, and machine plans. The algorithm of the model was developed by implementing an appropriate computer programming and tested on a basic application. Results, verified by using two well known vectorization programs (WinTopo and Scan2CAD, indicated that the model can successfully vectorize the specified raster data quickly and accurately.

  17. Modeling and Prediction of Wildfire Hazard in Southern California, Integration of Models with Imaging Spectrometry

    Science.gov (United States)

    Roberts, Dar A.; Church, Richard; Ustin, Susan L.; Brass, James A. (Technical Monitor)

    2001-01-01

    Large urban wildfires throughout southern California have caused billions of dollars of damage and significant loss of life over the last few decades. Rapid urban growth along the wildland interface, high fuel loads and a potential increase in the frequency of large fires due to climatic change suggest that the problem will worsen in the future. Improved fire spread prediction and reduced uncertainty in assessing fire hazard would be significant, both economically and socially. Current problems in the modeling of fire spread include the role of plant community differences, spatial heterogeneity in fuels and spatio-temporal changes in fuels. In this research, we evaluated the potential of Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and Airborne Synthetic Aperture Radar (AIRSAR) data for providing improved maps of wildfire fuel properties. Analysis concentrated in two areas of Southern California, the Santa Monica Mountains and Santa Barbara Front Range. Wildfire fuel information can be divided into four basic categories: fuel type, fuel load (live green and woody biomass), fuel moisture and fuel condition (live vs senesced fuels). To map fuel type, AVIRIS data were used to map vegetation species using Multiple Endmember Spectral Mixture Analysis (MESMA) and Binary Decision Trees. Green live biomass and canopy moisture were mapped using AVIRIS through analysis of the 980 nm liquid water absorption feature and compared to alternate measures of moisture and field measurements. Woody biomass was mapped using L and P band cross polarimetric data acquired in 1998 and 1999. Fuel condition was mapped using spectral mixture analysis to map green vegetation (green leaves), nonphotosynthetic vegetation (NPV; stems, wood and litter), shade and soil. Summaries describing the potential of hyperspectral and SAR data for fuel mapping are provided by Roberts et al. and Dennison et al. To utilize remotely sensed data to assess fire hazard, fuel-type maps were translated

  18. Classification of bones from MR images in torso PET-MR imaging using a statistical shape model

    International Nuclear Information System (INIS)

    Reza Ay, Mohammad; Akbarzadeh, Afshin; Ahmadian, Alireza; Zaidi, Habib

    2014-01-01

    There have been exclusive features for hybrid PET/MRI systems in comparison with its PET/CT counterpart in terms of reduction of radiation exposure, improved soft-tissue contrast and truly simultaneous and multi-parametric imaging capabilities. However, quantitative imaging on PET/MR is challenged by attenuation of annihilation photons through their pathway. The correction for photon attenuation requires the availability of patient-specific attenuation map, which accounts for the spatial distribution of attenuation coefficients of biological tissues. However, the lack of information on electron density in the MR signal poses an inherent difficulty to the derivation of the attenuation map from MR images. In other words, the MR signal correlates with proton densities and tissue relaxation properties, rather than with electron density and, as such, it is not directly related to attenuation coefficients. In order to derive the attenuation map from MR images at 511 keV, various strategies have been proposed and implemented on prototype and commercial PET/MR systems. Segmentation-based methods generate an attenuation map by classification of T1-weighted or high resolution Dixon MR sequences followed by assignment of predefined attenuation coefficients to various tissue types. Intensity-based segmentation approaches fail to include bones in the attenuation map since the segmentation of bones from conventional MR sequences is a difficult task. Most MR-guided attenuation correction techniques ignore bones owing to the inherent difficulties associated with bone segmentation unless specialized MR sequences such as ultra-short echo (UTE) sequence are utilized. In this work, we introduce a new technique based on statistical shape modeling to segment bones and generate a four-class attenuation map. Our segmentation approach requires a torso bone shape model based on principle component analysis (PCA). A CT-based training set including clearly segmented bones of the torso region

  19. Mixed reality orthognathic surgical simulation by entity model manipulation and 3D-image display

    Science.gov (United States)

    Shimonagayoshi, Tatsunari; Aoki, Yoshimitsu; Fushima, Kenji; Kobayashi, Masaru

    2005-12-01

    In orthognathic surgery, the framing of 3D-surgical planning that considers the balance between the front and back positions and the symmetry of the jawbone, as well as the dental occlusion of teeth, is essential. In this study, a support system for orthodontic surgery to visualize the changes in the mandible and the occlusal condition and to determine the optimum position in mandibular osteotomy has been developed. By integrating the operating portion of a tooth model that is to determine the optimum occlusal position by manipulating the entity tooth model and the 3D-CT skeletal images (3D image display portion) that are simultaneously displayed in real-time, the determination of the mandibular position and posture in which the improvement of skeletal morphology and occlusal condition is considered, is possible. The realistic operation of the entity model and the virtual 3D image display enabled the construction of a surgical simulation system that involves augmented reality.

  20. A Model-Based Approach to Recovering the Structure of a Plant from Images

    KAUST Repository

    Ward, Ben

    2015-03-19

    We present a method for recovering the structure of a plant directly from a small set of widely-spaced images for automated analysis of phenotype. Structure recovery is more complex than shape estimation, but the resulting structure estimate is more closely related to phenotype than is a 3D geometric model. The method we propose is applicable to a wide variety of plants, but is demonstrated on wheat. Wheat is composed of thin elements with few identifiable features, making it difficult to analyse using standard feature matching techniques. Our method instead analyses the structure of plants using only their silhouettes. We employ a generate-and-test method, using a database of manually modelled leaves and a model for their composition to synthesise plausible plant structures which are evaluated against the images. The method is capable of efficiently recovering accurate estimates of plant structure in a wide variety of imaging scenarios, without manual intervention.

  1. Fog Density Estimation and Image Defogging Based on Surrogate Modeling for Optical Depth.

    Science.gov (United States)

    Jiang, Yutong; Sun, Changming; Zhao, Yu; Yang, Li

    2017-05-03

    In order to estimate fog density correctly and to remove fog from foggy images appropriately, a surrogate model for optical depth is presented in this paper. We comprehensively investigate various fog-relevant features and propose a novel feature based on the hue, saturation, and value color space which correlate well with the perception of fog density. We use a surrogate-based method to learn a refined polynomial regression model for optical depth with informative fog-relevant features such as dark-channel, saturation-value, and chroma which are selected on the basis of sensitivity analysis. Based on the obtained accurate surrogate model for optical depth, an effective method for fog density estimation and image defogging is proposed. The effectiveness of our proposed method is verified quantitatively and qualitatively by the experimental results on both synthetic and real-world foggy images.

  2. 3D Modeling of Vascular Pathologies from contrast enhanced magnetic resonance images (MRI)

    International Nuclear Information System (INIS)

    Cantor Rivera, Diego; Orkisz, Maciej; Arias, Julian; Uriza, Luis Felipe

    2007-01-01

    This paper presents a method for generating 3D vascular models from contrast enhanced magnetic resonance images (MRI) using a fast marching algorithm. The main contributions of this work are: the use of the original image for defining a speed function (which determines the movement of the interface) and the calculation of the time in which the interface identifies the artery. The proposed method was validated on pathologic carotid artery images of patients and vascular phantoms. A visual appraisal of vascular models obtained with the method shows a satisfactory extraction of the vascular wall. A quantitative assessment proved that the generated models depend on the values of algorithm parameters. The maximum induced error was equal to 1.34 voxels in the diameter of the measured stenoses.

  3. Experience of modeling relief of impact lunar crater Aitken based on high-resolution orbital images

    Science.gov (United States)

    Mukhametshin, Ch R.; Semenov, A. A.; Shpekin, M. I.

    2018-05-01

    The paper presents the author’s results of modeling the relief of lunar Aitken crater on the basis of high-resolution orbital images. The images were taken in the frame of the “Apollo” program in 1971-1972 and delivered to the Earth by crews of “Apollo-15” and “Apollo-17”. The authors used the images obtained by metric and panoramic cameras. The main result is the careful study of the unusual features of Aitken crater on models created by the authors with the computer program, developed by “Agisoft Photoscan”. The paper shows what possibilities are opened with 3D models in the study of the structure of impact craters on the Moon. In particular, for the first time, the authors managed to show the structure of the glacier-like tongue in Aitken crater, which is regarded as one of the promising areas of the Moon for the forthcoming expeditions.

  4. A Model-Based Approach to Recovering the Structure of a Plant from Images

    KAUST Repository

    Ward, Ben; Bastian, John; van den Hengel, Anton; Pooley, Daniel; Bari, Rajendra; Berger, Bettina; Tester, Mark A.

    2015-01-01

    We present a method for recovering the structure of a plant directly from a small set of widely-spaced images for automated analysis of phenotype. Structure recovery is more complex than shape estimation, but the resulting structure estimate is more closely related to phenotype than is a 3D geometric model. The method we propose is applicable to a wide variety of plants, but is demonstrated on wheat. Wheat is composed of thin elements with few identifiable features, making it difficult to analyse using standard feature matching techniques. Our method instead analyses the structure of plants using only their silhouettes. We employ a generate-and-test method, using a database of manually modelled leaves and a model for their composition to synthesise plausible plant structures which are evaluated against the images. The method is capable of efficiently recovering accurate estimates of plant structure in a wide variety of imaging scenarios, without manual intervention.

  5. Correlation between model observer and human observer performance in CT imaging when lesion location is uncertain

    Energy Technology Data Exchange (ETDEWEB)

    Leng, Shuai; Yu, Lifeng; Zhang, Yi; McCollough, Cynthia H. [Department of Radiology, Mayo Clinic, 200 First Street Southwest, Rochester, Minnesota 55905 (United States); Carter, Rickey [Department of Biostatistics, Mayo Clinic, 200 First Street Southwest, Rochester, Minnesota 55905 (United States); Toledano, Alicia Y. [Biostatistics Consulting, LLC, 10606 Wheatley Street, Kensington, Maryland 20895 (United States)

    2013-08-15

    Purpose: The purpose of this study was to investigate the correlation between model observer and human observer performance in CT imaging for the task of lesion detection and localization when the lesion location is uncertain.Methods: Two cylindrical rods (3-mm and 5-mm diameters) were placed in a 35 × 26 cm torso-shaped water phantom to simulate lesions with −15 HU contrast at 120 kV. The phantom was scanned 100 times on a 128-slice CT scanner at each of four dose levels (CTDIvol = 5.7, 11.4, 17.1, and 22.8 mGy). Regions of interest (ROIs) around each lesion were extracted to generate images with signal-present, with each ROI containing 128 × 128 pixels. Corresponding ROIs of signal-absent images were generated from images without lesion mimicking rods. The location of the lesion (rod) in each ROI was randomly distributed by moving the ROIs around each lesion. Human observer studies were performed by having three trained observers identify the presence or absence of lesions, indicating the lesion location in each image and scoring confidence for the detection task on a 6-point scale. The same image data were analyzed using a channelized Hotelling model observer (CHO) with Gabor channels. Internal noise was added to the decision variables for the model observer study. Area under the curve (AUC) of ROC and localization ROC (LROC) curves were calculated using a nonparametric approach. The Spearman's rank order correlation between the average performance of the human observers and the model observer performance was calculated for the AUC of both ROC and LROC curves for both the 3- and 5-mm diameter lesions.Results: In both ROC and LROC analyses, AUC values for the model observer agreed well with the average values across the three human observers. The Spearman's rank order correlation values for both ROC and LROC analyses for both the 3- and 5-mm diameter lesions were all 1.0, indicating perfect rank ordering agreement of the figures of merit (AUC

  6. A generalized model for optimal transport of images including dissipation and density modulation

    KAUST Repository

    Maas, Jan

    2015-11-01

    © EDP Sciences, SMAI 2015. In this paper the optimal transport and the metamorphosis perspectives are combined. For a pair of given input images geodesic paths in the space of images are defined as minimizers of a resulting path energy. To this end, the underlying Riemannian metric measures the rate of transport cost and the rate of viscous dissipation. Furthermore, the model is capable to deal with strongly varying image contrast and explicitly allows for sources and sinks in the transport equations which are incorporated in the metric related to the metamorphosis approach by Trouvé and Younes. In the non-viscous case with source term existence of geodesic paths is proven in the space of measures. The proposed model is explored on the range from merely optimal transport to strongly dissipative dynamics. For this model a robust and effective variational time discretization of geodesic paths is proposed. This requires to minimize a discrete path energy consisting of a sum of consecutive image matching functionals. These functionals are defined on corresponding pairs of intensity functions and on associated pairwise matching deformations. Existence of time discrete geodesics is demonstrated. Furthermore, a finite element implementation is proposed and applied to instructive test cases and to real images. In the non-viscous case this is compared to the algorithm proposed by Benamou and Brenier including a discretization of the source term. Finally, the model is generalized to define discrete weighted barycentres with applications to textures and objects.

  7. Regional SAR Image Segmentation Based on Fuzzy Clustering with Gamma Mixture Model

    Science.gov (United States)

    Li, X. L.; Zhao, Q. H.; Li, Y.

    2017-09-01

    Most of stochastic based fuzzy clustering algorithms are pixel-based, which can not effectively overcome the inherent speckle noise in SAR images. In order to deal with the problem, a regional SAR image segmentation algorithm based on fuzzy clustering with Gamma mixture model is proposed in this paper. First, initialize some generating points randomly on the image, the image domain is divided into many sub-regions using Voronoi tessellation technique. Each sub-region is regarded as a homogeneous area in which the pixels share the same cluster label. Then, assume the probability of the pixel to be a Gamma mixture model with the parameters respecting to the cluster which the pixel belongs to. The negative logarithm of the probability represents the dissimilarity measure between the pixel and the cluster. The regional dissimilarity measure of one sub-region is defined as the sum of the measures of pixels in the region. Furthermore, the Markov Random Field (MRF) model is extended from pixels level to Voronoi sub-regions, and then the regional objective function is established under the framework of fuzzy clustering. The optimal segmentation results can be obtained by the solution of model parameters and generating points. Finally, the effectiveness of the proposed algorithm can be proved by the qualitative and quantitative analysis from the segmentation results of the simulated and real SAR images.

  8. An Improved Physics-Based Model for Topographic Correction of Landsat TM Images

    Directory of Open Access Journals (Sweden)

    Ainong Li

    2015-05-01

    Full Text Available Optical remotely sensed images in mountainous areas are subject to radiometric distortions induced by topographic effects, which need to be corrected before quantitative applications. Based on Li model and Sandmeier model, this paper proposed an improved physics-based model for the topographic correction of Landsat Thematic Mapper (TM images. The model employed Normalized Difference Vegetation Index (NDVI thresholds to approximately divide land targets into eleven groups, due to NDVI’s lower sensitivity to topography and its significant role in indicating land cover type. Within each group of terrestrial targets, corresponding MODIS BRDF (Bidirectional Reflectance Distribution Function products were used to account for land surface’s BRDF effect, and topographic effects are corrected without Lambertian assumption. The methodology was tested with two TM scenes of severely rugged mountain areas acquired under different sun elevation angles. Results demonstrated that reflectance of sun-averted slopes was evidently enhanced, and the overall quality of images was improved with topographic effect being effectively suppressed. Correlation coefficients between Near Infra-Red band reflectance and illumination condition reduced almost to zero, and coefficients of variance also showed some reduction. By comparison with the other two physics-based models (Sandmeier model and Li model, the proposed model showed favorable results on two tested Landsat scenes. With the almost half-century accumulation of Landsat data and the successive launch and operation of Landsat 8, the improved model in this paper can be potentially helpful for the topographic correction of Landsat and Landsat-like data.

  9. Creating vascular models by postprocessing computed tomography angiography images: a guide for anatomical education.

    Science.gov (United States)

    Govsa, Figen; Ozer, Mehmet Asim; Sirinturk, Suzan; Eraslan, Cenk; Alagoz, Ahmet Kemal

    2017-08-01

    A new application of teaching anatomy includes the use of computed tomography angiography (CTA) images to create clinically relevant three-dimensional (3D) printed models. The purpose of this article is to review recent innovations on the process and the application of 3D printed models as a tool for using under and post-graduate medical education. Images of aortic arch pattern received by CTA were converted into 3D images using the Google SketchUp free software and were saved in stereolithography format. Using a 3D printer (Makerbot), a model mode polylactic acid material was printed. A two-vessel left aortic arch was identified consisting of the brachiocephalic trunk and left subclavian artery. The life-like 3D models were rotated 360° in all axes in hand. The early adopters in education and clinical practices have embraced the medical imaging-guided 3D printed anatomical models for their ability to provide tactile feedback and a superior appreciation of visuospatial relationship between the anatomical structures. Printed vascular models are used to assist in preoperative planning, develop intraoperative guidance tools, and to teach patients surgical trainees in surgical practice.

  10. A Bayesian Spatial Model to Predict Disease Status Using Imaging Data From Various Modalities

    Directory of Open Access Journals (Sweden)

    Wenqiong Xue

    2018-03-01

    Full Text Available Relating disease status to imaging data stands to increase the clinical significance of neuroimaging studies. Many neurological and psychiatric disorders involve complex, systems-level alterations that manifest in functional and structural properties of the brain and possibly other clinical and biologic measures. We propose a Bayesian hierarchical model to predict disease status, which is able to incorporate information from both functional and structural brain imaging scans. We consider a two-stage whole brain parcellation, partitioning the brain into 282 subregions, and our model accounts for correlations between voxels from different brain regions defined by the parcellations. Our approach models the imaging data and uses posterior predictive probabilities to perform prediction. The estimates of our model parameters are based on samples drawn from the joint posterior distribution using Markov Chain Monte Carlo (MCMC methods. We evaluate our method by examining the prediction accuracy rates based on leave-one-out cross validation, and we employ an importance sampling strategy to reduce the computation time. We conduct both whole-brain and voxel-level prediction and identify the brain regions that are highly associated with the disease based on the voxel-level prediction results. We apply our model to multimodal brain imaging data from a study of Parkinson's disease. We achieve extremely high accuracy, in general, and our model identifies key regions contributing to accurate prediction including caudate, putamen, and fusiform gyrus as well as several sensory system regions.

  11. A novel modeling method for manufacturing hearing aid using 3D medical images

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Hyeong Gyun [Dept of Radiological Science, Far East University, Eumseong (Korea, Republic of)

    2016-06-15

    This study aimed to suggest a novel method of modeling a hearing aid ear shell based on Digital Imaging and Communication in Medicine (DICOM) in the hearing aid ear shell manufacturing method using a 3D printer. In the experiment, a 3D external auditory meatus was extracted by using the critical values in the DICOM volume images, a nd t he modeling surface structures were compared in standard type STL (STereoLithography) files which could be recognized by a 3D printer. In this 3D modeling method, a conventional ear model was prepared, and the gaps between adjacent isograms produced by a 3D scanner were filled with 3D surface fragments to express the modeling structure. In this study, the same type of triangular surface structures were prepared by using the DICOM images. The result showed that the modeling surface structure based on the DICOM images provide the same environment that the conventional 3D printers may recognize, eventually enabling to print out the hearing aid ear shell shape.

  12. A novel modeling method for manufacturing hearing aid using 3D medical images

    International Nuclear Information System (INIS)

    Kim, Hyeong Gyun

    2016-01-01

    This study aimed to suggest a novel method of modeling a hearing aid ear shell based on Digital Imaging and Communication in Medicine (DICOM) in the hearing aid ear shell manufacturing method using a 3D printer. In the experiment, a 3D external auditory meatus was extracted by using the critical values in the DICOM volume images, a nd t he modeling surface structures were compared in standard type STL (STereoLithography) files which could be recognized by a 3D printer. In this 3D modeling method, a conventional ear model was prepared, and the gaps between adjacent isograms produced by a 3D scanner were filled with 3D surface fragments to express the modeling structure. In this study, the same type of triangular surface structures were prepared by using the DICOM images. The result showed that the modeling surface structure based on the DICOM images provide the same environment that the conventional 3D printers may recognize, eventually enabling to print out the hearing aid ear shell shape

  13. Maximizing entropy of image models for 2-D constrained coding

    DEFF Research Database (Denmark)

    Forchhammer, Søren; Danieli, Matteo; Burini, Nino

    2010-01-01

    This paper considers estimating and maximizing the entropy of two-dimensional (2-D) fields with application to 2-D constrained coding. We consider Markov random fields (MRF), which have a non-causal description, and the special case of Pickard random fields (PRF). The PRF are 2-D causal finite...... context models, which define stationary probability distributions on finite rectangles and thus allow for calculation of the entropy. We consider two binary constraints and revisit the hard square constraint given by forbidding neighboring 1s and provide novel results for the constraint that no uniform 2...... £ 2 squares contains all 0s or all 1s. The maximum values of the entropy for the constraints are estimated and binary PRF satisfying the constraint are characterized and optimized w.r.t. the entropy. The maximum binary PRF entropy is 0.839 bits/symbol for the no uniform squares constraint. The entropy...

  14. Imaging proteolytic activity in live cells and animal models.

    Directory of Open Access Journals (Sweden)

    Stefanie Galbán

    Full Text Available In addition to their degradative role in protein turnover, proteases play a key role as positive or negative regulators of signal transduction pathways and therefore their dysregulation contributes to many disease states. Regulatory roles of proteases include their hormone-like role in triggering G protein-coupled signaling (Protease-Activated-Receptors; their role in shedding of ligands such as EGF, Notch and Fas; and their role in signaling events that lead to apoptotic cell death. Dysregulated activation of apoptosis by the caspase family of proteases has been linked to diseases such as cancer, autoimmunity and inflammation. In an effort to better understand the role of proteases in health and disease, a luciferase biosensor is described which can quantitatively report proteolytic activity in live cells and mouse models. The biosensor, hereafter referred to as GloSensor Caspase 3/7 has a robust signal to noise (50-100 fold and dynamic range such that it can be used to screen for pharmacologically active compounds in high throughput campaigns as well as to study cell signaling in rare cell populations such as isolated cancer stem cells. The biosensor can also be used in the context of genetically engineered mouse models of human disease wherein conditional expression using the Cre/loxP technology can be implemented to investigate the role of a specific protease in living subjects. While the regulation of apoptosis by caspase's was used as an example in these studies, biosensors to study additional proteases involved in the regulation of normal and pathological cellular processes can be designed using the concepts presented herein.

  15. A Monte Carlo calculation model of electronic portal imaging device for transit dosimetry through heterogeneous media

    Energy Technology Data Exchange (ETDEWEB)

    Yoon, Jihyung; Jung, Jae Won, E-mail: jungj@ecu.edu [Department of Physics, East Carolina University, Greenville, North Carolina 27858 (United States); Kim, Jong Oh [Department of Radiation Oncology, University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania 15232 (United States); Yeo, Inhwan [Department of Radiation Medicine, Loma Linda University Medical Center, Loma Linda, California 92354 (United States)

    2016-05-15

    Purpose: To develop and evaluate a fast Monte Carlo (MC) dose calculation model of electronic portal imaging device (EPID) based on its effective atomic number modeling in the XVMC code. Methods: A previously developed EPID model, based on the XVMC code by density scaling of EPID structures, was modified by additionally considering effective atomic number (Z{sub eff}) of each structure and adopting a phase space file from the EGSnrc code. The model was tested under various homogeneous and heterogeneous phantoms and field sizes by comparing the calculations in the model with measurements in EPID. In order to better evaluate the model, the performance of the XVMC code was separately tested by comparing calculated dose to water with ion chamber (IC) array measurement in the plane of EPID. Results: In the EPID plane, calculated dose to water by the code showed agreement with IC measurements within 1.8%. The difference was averaged across the in-field regions of the acquired profiles for all field sizes and phantoms. The maximum point difference was 2.8%, affected by proximity of the maximum points to penumbra and MC noise. The EPID model showed agreement with measured EPID images within 1.3%. The maximum point difference was 1.9%. The difference dropped from the higher value of the code by employing the calibration that is dependent on field sizes and thicknesses for the conversion of calculated images to measured images. Thanks to the Z{sub eff} correction, the EPID model showed a linear trend of the calibration factors unlike those of the density-only-scaled model. The phase space file from the EGSnrc code sharpened penumbra profiles significantly, improving agreement of calculated profiles with measured profiles. Conclusions: Demonstrating high accuracy, the EPID model with the associated calibration system may be used for in vivo dosimetry of radiation therapy. Through this study, a MC model of EPID has been developed, and their performance has been rigorously

  16. Computationally-optimized bone mechanical modeling from high-resolution structural images.

    Directory of Open Access Journals (Sweden)

    Jeremy F Magland

    Full Text Available Image-based mechanical modeling of the complex micro-structure of human bone has shown promise as a non-invasive method for characterizing bone strength and fracture risk in vivo. In particular, elastic moduli obtained from image-derived micro-finite element (μFE simulations have been shown to correlate well with results obtained by mechanical testing of cadaveric bone. However, most existing large-scale finite-element simulation programs require significant computing resources, which hamper their use in common laboratory and clinical environments. In this work, we theoretically derive and computationally evaluate the resources needed to perform such simulations (in terms of computer memory and computation time, which are dependent on the number of finite elements in the image-derived bone model. A detailed description of our approach is provided, which is specifically optimized for μFE modeling of the complex three-dimensional architecture of trabecular bone. Our implementation includes domain decomposition for parallel computing, a novel stopping criterion, and a system for speeding up convergence by pre-iterating on coarser grids. The performance of the system is demonstrated on a dual quad-core Xeon 3.16 GHz CPUs equipped with 40 GB of RAM. Models of distal tibia derived from 3D in-vivo MR images in a patient comprising 200,000 elements required less than 30 seconds to converge (and 40 MB RAM. To illustrate the system's potential for large-scale μFE simulations, axial stiffness was estimated from high-resolution micro-CT images of a voxel array of 90 million elements comprising the human proximal femur in seven hours CPU time. In conclusion, the system described should enable image-based finite-element bone simulations in practical computation times on high-end desktop computers with applications to laboratory studies and clinical imaging.

  17. Sediment plume model-a comparison between use of measured turbidity data and satellite images for model calibration.

    Science.gov (United States)

    Sadeghian, Amir; Hudson, Jeff; Wheater, Howard; Lindenschmidt, Karl-Erich

    2017-08-01

    In this study, we built a two-dimensional sediment transport model of Lake Diefenbaker, Saskatchewan, Canada. It was calibrated by using measured turbidity data from stations along the reservoir and satellite images based on a flood event in 2013. In June 2013, there was heavy rainfall for two consecutive days on the frozen and snow-covered ground in the higher elevations of western Alberta, Canada. The runoff from the rainfall and the melted snow caused one of the largest recorded inflows to the headwaters of the South Saskatchewan River and Lake Diefenbaker downstream. An estimated discharge peak of over 5200 m 3 /s arrived at the reservoir inlet with a thick sediment front within a few days. The sediment plume moved quickly through the entire reservoir and remained visible from satellite images for over 2 weeks along most of the reservoir, leading to concerns regarding water quality. The aims of this study are to compare, quantitatively and qualitatively, the efficacy of using turbidity data and satellite images for sediment transport model calibration and to determine how accurately a sediment transport model can simulate sediment transport based on each of them. Both turbidity data and satellite images were very useful for calibrating the sediment transport model quantitatively and qualitatively. Model predictions and turbidity measurements show that the flood water and suspended sediments entered upstream fairly well mixed and moved downstream as overflow with a sharp gradient at the plume front. The model results suggest that the settling and resuspension rates of sediment are directly proportional to flow characteristics and that the use of constant coefficients leads to model underestimation or overestimation unless more data on sediment formation become available. Hence, this study reiterates the significance of the availability of data on sediment distribution and characteristics for building a robust and reliable sediment transport model.

  18. Multiple-point statistical simulation for hydrogeological models: 3-D training image development and conditioning strategies

    Science.gov (United States)

    Høyer, Anne-Sophie; Vignoli, Giulio; Mejer Hansen, Thomas; Thanh Vu, Le; Keefer, Donald A.; Jørgensen, Flemming

    2017-12-01

    Most studies on the application of geostatistical simulations based on multiple-point statistics (MPS) to hydrogeological modelling focus on relatively fine-scale models and concentrate on the estimation of facies-level structural uncertainty. Much less attention is paid to the use of input data and optimal construction of training images. For instance, even though the training image should capture a set of spatial geological characteristics to guide the simulations, the majority of the research still relies on 2-D or quasi-3-D training images. In the present study, we demonstrate a novel strategy for 3-D MPS modelling characterized by (i) realistic 3-D training images and (ii) an effective workflow for incorporating a diverse group of geological and geophysical data sets. The study covers an area of 2810 km2 in the southern part of Denmark. MPS simulations are performed on a subset of the geological succession (the lower to middle Miocene sediments) which is characterized by relatively uniform structures and dominated by sand and clay. The simulated domain is large and each of the geostatistical realizations contains approximately 45 million voxels with size 100 m × 100 m × 5 m. Data used for the modelling include water well logs, high-resolution seismic data, and a previously published 3-D geological model. We apply a series of different strategies for the simulations based on data quality, and develop a novel method to effectively create observed spatial trends. The training image is constructed as a relatively small 3-D voxel model covering an area of 90 km2. We use an iterative training image development strategy and find that even slight modifications in the training image create significant changes in simulations. Thus, this study shows how to include both the geological environment and the type and quality of input information in order to achieve optimal results from MPS modelling. We present a practical workflow to build the training image and

  19. Using optical remote sensing model to estimate oil slick thickness based on satellite image

    International Nuclear Information System (INIS)

    Lu, Y C; Tian, Q J; Lyu, C G; Fu, W X; Han, W C

    2014-01-01

    An optical remote sensing model has been established based on two-beam interference theory to estimate marine oil slick thickness. Extinction coefficient and normalized reflectance of oil are two important parts in this model. Extinction coefficient is an important inherent optical property and will not vary with the background reflectance changed. Normalized reflectance can be used to eliminate the background differences between in situ measured spectra and remotely sensing image. Therefore, marine oil slick thickness and area can be estimated and mapped based on optical remotely sensing image and extinction coefficient

  20. Image-based Modeling of PSF Deformation with Application to Limited Angle PET Data

    Science.gov (United States)

    Matej, Samuel; Li, Yusheng; Panetta, Joseph; Karp, Joel S.; Surti, Suleman

    2016-01-01

    The point-spread-functions (PSFs) of reconstructed images can be deformed due to detector effects such as resolution blurring and parallax error, data acquisition geometry such as insufficient sampling or limited angular coverage in dual-panel PET systems, or reconstruction imperfections/simplifications. PSF deformation decreases quantitative accuracy and its spatial variation lowers consistency of lesion uptake measurement across the imaging field-of-view (FOV). This can be a significant problem with dual panel PET systems even when using TOF data and image reconstruction models of the detector and data acquisition process. To correct for the spatially variant reconstructed PSF distortions we propose to use an image-based resolution model (IRM) that includes such image PSF deformation effects. Originally the IRM was mostly used for approximating data resolution effects of standard PET systems with full angular coverage in a computationally efficient way, but recently it was also used to mitigate effects of simplified geometric projectors. Our work goes beyond this by including into the IRM reconstruction imperfections caused by combination of the limited angle, parallax errors, and any other (residual) deformation effects and testing it for challenging dual panel data with strongly asymmetric and variable PSF deformations. We applied and tested these concepts using simulated data based on our design for a dedicated breast imaging geometry (B-PET) consisting of dual-panel, time-of-flight (TOF) detectors. We compared two image-based resolution models; i) a simple spatially invariant approximation to PSF deformation, which captures only the general PSF shape through an elongated 3D Gaussian function, and ii) a spatially variant model using a Gaussian mixture model (GMM) to more accurately capture the asymmetric PSF shape in images reconstructed from data acquired with the B-PET scanner geometry. Results demonstrate that while both IRMs decrease the overall uptake

  1. Comparison of Color Model in Cotton Image Under Conditions of Natural Light

    Science.gov (United States)

    Zhang, J. H.; Kong, F. T.; Wu, J. Z.; Wang, S. W.; Liu, J. J.; Zhao, P.

    Although the color images contain a large amount of information reflecting the species characteristics, different color models also get different information. The selection of color models is the key to separating crops from background effectively and rapidly. Taking the cotton images collected under natural light as the object, we convert the color components of RGB color model, HSL color model and YIQ color model respectively. Then, we use subjective evaluation and objective evaluation methods, evaluating the 9 color components of conversion. It is concluded that the Q component of the soil, straw and plastic film region gray values remain the same without larger fluctuation when using subjective evaluation method. In the objective evaluation, we use the variance method, average gradient method, gray prediction objective evaluation error statistics method and information entropy method respectively to find the minimum numerical of Q color component suitable for background segmentation.

  2. A data model and database for high-resolution pathology analytical image informatics

    Directory of Open Access Journals (Sweden)

    Fusheng Wang

    2011-01-01

    Full Text Available Background: The systematic analysis of imaged pathology specimens often results in a vast amount of morphological information at both the cellular and sub-cellular scales. While microscopy scanners and computerized analysis are capable of capturing and analyzing data rapidly, microscopy image data remain underutilized in research and clinical settings. One major obstacle which tends to reduce wider adoption of these new technologies throughout the clinical and scientific communities is the challenge of managing, querying, and integrating the vast amounts of data resulting from the analysis of large digital pathology datasets. This paper presents a data model, which addresses these challenges, and demonstrates its implementation in a relational database system. Context: This paper describes a data model, referred to as Pathology Analytic Imaging Standards (PAIS, and a database implementation, which are designed to support the data management and query requirements of detailed characterization of micro-anatomic morphology through many interrelated analysis pipelines on whole-slide images and tissue microarrays (TMAs. Aims: (1 Development of a data model capable of efficiently representing and storing virtual slide related image, annotation, markup, and feature information. (2 Development of a database, based on the data model, capable of supporting queries for data retrieval based on analysis and image metadata, queries for comparison of results from different analyses, and spatial queries on segmented regions, features, and classified objects. Settings and Design: The work described in this paper is motivated by the challenges associated with characterization of micro-scale features for comparative and correlative analyses involving whole-slides tissue images and TMAs. Technologies for digitizing tissues have advanced significantly in the past decade. Slide scanners are capable of producing high-magnification, high-resolution images from whole

  3. A data model and database for high-resolution pathology analytical image informatics.

    Science.gov (United States)

    Wang, Fusheng; Kong, Jun; Cooper, Lee; Pan, Tony; Kurc, Tahsin; Chen, Wenjin; Sharma, Ashish; Niedermayr, Cristobal; Oh, Tae W; Brat, Daniel; Farris, Alton B; Foran, David J; Saltz, Joel

    2011-01-01

    The systematic analysis of imaged pathology specimens often results in a vast amount of morphological information at both the cellular and sub-cellular scales. While microscopy scanners and computerized analysis are capable of capturing and analyzing data rapidly, microscopy image data remain underutilized in research and clinical settings. One major obstacle which tends to reduce wider adoption of these new technologies throughout the clinical and scientific communities is the challenge of managing, querying, and integrating the vast amounts of data resulting from the analysis of large digital pathology datasets. This paper presents a data model, which addresses these challenges, and demonstrates its implementation in a relational database system. This paper describes a data model, referred to as Pathology Analytic Imaging Standards (PAIS), and a database implementation, which are designed to support the data management and query requirements of detailed characterization of micro-anatomic morphology through many interrelated analysis pipelines on whole-slide images and tissue microarrays (TMAs). (1) Development of a data model capable of efficiently representing and storing virtual slide related image, annotation, markup, and feature information. (2) Development of a database, based on the data model, capable of supporting queries for data retrieval based on analysis and image metadata, queries for comparison of results from different analyses, and spatial queries on segmented regions, features, and classified objects. The work described in this paper is motivated by the challenges associated with characterization of micro-scale features for comparative and correlative analyses involving whole-slides tissue images and TMAs. Technologies for digitizing tissues have advanced significantly in the past decade. Slide scanners are capable of producing high-magnification, high-resolution images from whole slides and TMAs within several minutes. Hence, it is becoming

  4. A model of primate visual cortex based on category-specific redundancies in natural images

    Science.gov (United States)

    Malmir, Mohsen; Shiry Ghidary, S.

    2010-12-01

    Neurophysiological and computational studies have proposed that properties of natural images have a prominent role in shaping selectivity of neurons in the visual cortex. An important property of natural images that has been studied extensively is the inherent redundancy in these images. In this paper, the concept of category-specific redundancies is introduced to describe the complex pattern of dependencies between responses of linear filters to natural images. It is proposed that structural similarities between images of different object categories result in dependencies between responses of linear filters in different spatial scales. It is also proposed that the brain gradually removes these dependencies in different areas of the ventral visual hierarchy to provide a more efficient representation of its sensory input. The authors proposed a model to remove these redundancies and trained it with a set of natural images using general learning rules that are developed to remove dependencies between responses of neighbouring neurons. Results of experiments demonstrate the close resemblance of neuronal selectivity between different layers of the model and their corresponding visual areas.

  5. Automatic lung tumor segmentation on PET/CT images using fuzzy Markov random field model.

    Science.gov (United States)

    Guo, Yu; Feng, Yuanming; Sun, Jian; Zhang, Ning; Lin, Wang; Sa, Yu; Wang, Ping

    2014-01-01

    The combination of positron emission tomography (PET) and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF) model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC) patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice's similarity coefficient (DSC) was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.

  6. Automatic Lung Tumor Segmentation on PET/CT Images Using Fuzzy Markov Random Field Model

    Directory of Open Access Journals (Sweden)

    Yu Guo

    2014-01-01

    Full Text Available The combination of positron emission tomography (PET and CT images provides complementary functional and anatomical information of human tissues and it has been used for better tumor volume definition of lung cancer. This paper proposed a robust method for automatic lung tumor segmentation on PET/CT images. The new method is based on fuzzy Markov random field (MRF model. The combination of PET and CT image information is achieved by using a proper joint posterior probability distribution of observed features in the fuzzy MRF model which performs better than the commonly used Gaussian joint distribution. In this study, the PET and CT simulation images of 7 non-small cell lung cancer (NSCLC patients were used to evaluate the proposed method. Tumor segmentations with the proposed method and manual method by an experienced radiation oncologist on the fused images were performed, respectively. Segmentation results obtained with the two methods were similar and Dice’s similarity coefficient (DSC was 0.85 ± 0.013. It has been shown that effective and automatic segmentations can be achieved with this method for lung tumors which locate near other organs with similar intensities in PET and CT images, such as when the tumors extend into chest wall or mediastinum.

  7. Early magnetic resonance imaging and histologic findings in a model of avascular necrosis of femoral head

    Energy Technology Data Exchange (ETDEWEB)

    Nakamura, Takuya [Kanazawa Univ. (Japan). School of Medicine

    1997-12-01

    The present study was performed to examine early MR images and histologic findings using a canine model of avascular necrosis of femoral head (ANFH). The ANFH model was surgically induced. At three days, 1, 2 and 4 weeks after surgery, the proximal femurs were excised. MR images were obtained in 4 dogs at 3 days and 7 dogs at each of the other intervals. Histologic examinations were performed on 7 dogs at each interval. Three days after surgery, MR showed almost no abnormal findings. Histologic changes included edematous bone marrow and bleeding in the bone marrow in some regions. One week after surgery, empty lacunae in trabecular bones and immature fibrous tissues in the bone marrow were seen in some cases, but appositional bone was not yet apparent. In only one case, abnormal MR findings -a ringlike pattern- were seen. Two weeks after surgery, 4 cases showed appositional bones on histology and abnormalities on MR images. Four weeks after surgery, fibrous tissues had matured and appositional bones had increased. Therefore, all 7 cases showed MR imaging abnormalities. Abnormal MR images included a ringlike pattern, and homogeneous and inhomogeneous patterns. These results indicated that MR imaging shows abnormality 2 weeks after surgery at the latest. (author)

  8. High-Resolution Remote Sensing Image Building Extraction Based on Markov Model

    Science.gov (United States)

    Zhao, W.; Yan, L.; Chang, Y.; Gong, L.

    2018-04-01

    With the increase of resolution, remote sensing images have the characteristics of increased information load, increased noise, more complex feature geometry and texture information, which makes the extraction of building information more difficult. To solve this problem, this paper designs a high resolution remote sensing image building extraction method based on Markov model. This method introduces Contourlet domain map clustering and Markov model, captures and enhances the contour and texture information of high-resolution remote sensing image features in multiple directions, and further designs the spectral feature index that can characterize "pseudo-buildings" in the building area. Through the multi-scale segmentation and extraction of image features, the fine extraction from the building area to the building is realized. Experiments show that this method can restrain the noise of high-resolution remote sensing images, reduce the interference of non-target ground texture information, and remove the shadow, vegetation and other pseudo-building information, compared with the traditional pixel-level image information extraction, better performance in building extraction precision, accuracy and completeness.

  9. Improving fault image by determination of optimum seismic survey parameters using ray-based modeling

    Science.gov (United States)

    Saffarzadeh, Sadegh; Javaherian, Abdolrahim; Hasani, Hossein; Talebi, Mohammad Ali

    2018-06-01

    In complex structures such as faults, salt domes and reefs, specifying the survey parameters is more challenging and critical owing to the complicated wave field behavior involved in such structures. In the petroleum industry, detecting faults has become crucial for reservoir potential where faults can act as traps for hydrocarbon. In this regard, seismic survey modeling is employed to construct a model close to the real structure, and obtain very realistic synthetic seismic data. Seismic modeling software, the velocity model and parameters pre-determined by conventional methods enable a seismic survey designer to run a shot-by-shot virtual survey operation. A reliable velocity model of structures can be constructed by integrating the 2D seismic data, geological reports and the well information. The effects of various survey designs can be investigated by the analysis of illumination maps and flower plots. Also, seismic processing of the synthetic data output can describe the target image using different survey parameters. Therefore, seismic modeling is one of the most economical ways to establish and test the optimum acquisition parameters to obtain the best image when dealing with complex geological structures. The primary objective of this study is to design a proper 3D seismic survey orientation to achieve fault zone structures through ray-tracing seismic modeling. The results prove that a seismic survey designer can enhance the image of fault planes in a seismic section by utilizing the proposed modeling and processing approach.

  10. Body image concerns in professional fashion models: are they really an at-risk group?

    Science.gov (United States)

    Swami, Viren; Szmigielska, Emilia

    2013-05-15

    Although professional models are thought to be a high-risk group for body image concerns, only a handful of studies have empirically investigated this possibility. The present study sought to overcome this dearth of information by comparing professional models and a matched sample on key indices of body image and appeared-related concerns. A group of 52 professional fashion models was compared with a matched sample of 51 non-models from London, England, on indices of weight discrepancy, body appreciation, social physique anxiety, body dissatisfaction, drive for thinness, internalization of sociocultural messages about appearance, and dysfunctional investment in appearance. Results indicated that professional models only evidenced significantly higher drive for thinness and dysfunctional investment in appearance than the control group. Greater duration of engagement as a professional model was associated with more positive body appreciation but also greater drive for thinness. These results indicate that models, who are already underweight, have a strong desire to maintain their low body mass or become thinner. Taken together, the present results suggest that interventions aimed at promoting healthy body image among fashion models may require different strategies than those aimed at the general population. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

  11. Simulations, Imaging, and Modeling: A Unique Theme for an Undergraduate Research Program in Biomechanics.

    Science.gov (United States)

    George, Stephanie M; Domire, Zachary J

    2017-07-01

    As the reliance on computational models to inform experiments and evaluate medical devices grows, the demand for students with modeling experience will grow. In this paper, we report on the 3-yr experience of a National Science Foundation (NSF) funded Research Experiences for Undergraduates (REU) based on the theme simulations, imaging, and modeling in biomechanics. While directly applicable to REU sites, our findings also apply to those creating other types of summer undergraduate research programs. The objective of the paper is to examine if a theme of simulations, imaging, and modeling will improve students' understanding of the important topic of modeling, provide an overall positive research experience, and provide an interdisciplinary experience. The structure of the program and the evaluation plan are described. We report on the results from 25 students over three summers from 2014 to 2016. Overall, students reported significant gains in the knowledge of modeling, research process, and graduate school based on self-reported mastery levels and open-ended qualitative responses. This theme provides students with a skill set that is adaptable to other applications illustrating the interdisciplinary nature of modeling in biomechanics. Another advantage is that students may also be able to continue working on their project following the summer experience through network connections. In conclusion, we have described the successful implementation of the theme simulation, imaging, and modeling for an REU site and the overall positive response of the student participants.

  12. Hybrid 3D pregnant woman and fetus modeling from medical imaging for dosimetry studies

    Energy Technology Data Exchange (ETDEWEB)

    Bibin, Lazar; Anquez, Jeremie; Angelini, Elsa; Bloch, Isabelle [Telecom ParisTech, CNRS UMR 5141 LTCI, Institut TELECOM, Paris (France)

    2010-01-15

    Numerical simulations studying the interactions between radiations and biological tissues require the use of three-dimensional models of the human anatomy at various ages and in various positions. Several detailed and flexible models exist for adults and children and have been extensively used for dosimetry. On the other hand, progress of simulation studies focusing on pregnant women and the fetus have been limited by the fact that only a small number of models exist with rather coarse anatomical details and a poor representation of the anatomical variability of the fetus shape and its position over the entire gestation. In this paper, we propose a new computational framework to generate 3D hybrid models of pregnant women, composed of fetus shapes segmented from medical images and a generic maternal body envelope representing a synthetic woman scaled to the dimension of the uterus. The computational framework includes the following tasks: image segmentation, contour regularization, mesh-based surface reconstruction, and model integration. A series of models was created to represent pregnant women at different gestational stages and with the fetus in different positions, all including detailed tissues of the fetus and the utero-fetal unit, which play an important role in dosimetry. These models were anatomically validated by clinical obstetricians and radiologists who verified the accuracy and representativeness of the anatomical details, and the positioning of the fetus inside the maternal body. The computational framework enables the creation of detailed, realistic, and representative fetus models from medical images, directly exploitable for dosimetry simulations. (orig.)

  13. Hybrid 3D pregnant woman and fetus modeling from medical imaging for dosimetry studies

    International Nuclear Information System (INIS)

    Bibin, Lazar; Anquez, Jeremie; Angelini, Elsa; Bloch, Isabelle

    2010-01-01

    Numerical simulations studying the interactions between radiations and biological tissues require the use of three-dimensional models of the human anatomy at various ages and in various positions. Several detailed and flexible models exist for adults and children and have been extensively used for dosimetry. On the other hand, progress of simulation studies focusing on pregnant women and the fetus have been limited by the fact that only a small number of models exist with rather coarse anatomical details and a poor representation of the anatomical variability of the fetus shape and its position over the entire gestation. In this paper, we propose a new computational framework to generate 3D hybrid models of pregnant women, composed of fetus shapes segmented from medical images and a generic maternal body envelope representing a synthetic woman scaled to the dimension of the uterus. The computational framework includes the following tasks: image segmentation, contour regularization, mesh-based surface reconstruction, and model integration. A series of models was created to represent pregnant women at different gestational stages and with the fetus in different positions, all including detailed tissues of the fetus and the utero-fetal unit, which play an important role in dosimetry. These models were anatomically validated by clinical obstetricians and radiologists who verified the accuracy and representativeness of the anatomical details, and the positioning of the fetus inside the maternal body. The computational framework enables the creation of detailed, realistic, and representative fetus models from medical images, directly exploitable for dosimetry simulations. (orig.)

  14. Automatic thoracic anatomy segmentation on CT images using hierarchical fuzzy models and registration

    Science.gov (United States)

    Sun, Kaioqiong; Udupa, Jayaram K.; Odhner, Dewey; Tong, Yubing; Torigian, Drew A.

    2014-03-01

    This paper proposes a thoracic anatomy segmentation method based on hierarchical recognition and delineation guided by a built fuzzy model. Labeled binary samples for each organ are registered and aligned into a 3D fuzzy set representing the fuzzy shape model for the organ. The gray intensity distributions of the corresponding regions of the organ in the original image are recorded in the model. The hierarchical relation and mean location relation between different organs are also captured in the model. Following the hierarchical structure and location relation, the fuzzy shape model of different organs is registered to the given target image to achieve object recognition. A fuzzy connected delineation method is then used to obtain the final segmentation result of organs with seed points provided by recognition. The hierarchical structure and location relation integrated in the model provide the initial parameters for registration and make the recognition efficient and robust. The 3D fuzzy model combined with hierarchical affine registration ensures that accurate recognition can be obtained for both non-sparse and sparse organs. The results on real images are presented and shown to be better than a recently reported fuzzy model-based anatomy recognition strategy.

  15. Modelling the transport of optical photons in scintillation detectors for diagnostic and radiotherapy imaging

    Science.gov (United States)

    Roncali, Emilie; Mosleh-Shirazi, Mohammad Amin; Badano, Aldo

    2017-10-01

    Computational modelling of radiation transport can enhance the understanding of the relative importance of individual processes involved in imaging systems. Modelling is a powerful tool for improving detector designs in ways that are impractical or impossible to achieve through experimental measurements. Modelling of light transport in scintillation detectors used in radiology and radiotherapy imaging that rely on the detection of visible light plays an increasingly important role in detector design. Historically, researchers have invested heavily in modelling the transport of ionizing radiation while light transport is often ignored or coarsely modelled. Due to the complexity of existing light transport simulation tools and the breadth of custom codes developed by users, light transport studies are seldom fully exploited and have not reached their full potential. This topical review aims at providing an overview of the methods employed in freely available and other described optical Monte Carlo packages and analytical models and discussing their respective advantages and limitations. In particular, applications of optical transport modelling in nuclear medicine, diagnostic and radiotherapy imaging are described. A discussion on the evolution of these modelling tools into future developments and applications is presented. The authors declare equal leadership and contribution regarding this review.

  16. Analyzer-based imaging of spinal fusion in an animal model

    International Nuclear Information System (INIS)

    Kelly, M E; Beavis, R C; Allen, L A; Fiorella, David; Schueltke, E; Juurlink, B H; Chapman, L D; Zhong, Z

    2008-01-01

    Analyzer-based imaging (ABI) utilizes synchrotron radiation sources to create collimated monochromatic x-rays. In addition to x-ray absorption, this technique uses refraction and scatter rejection to create images. ABI provides dramatically improved contrast over standard imaging techniques. Twenty-one adult male Wistar rats were divided into four experimental groups to undergo the following interventions: (1) non-injured control, (2) decortication alone, (3) decortication with iliac crest bone grafting and (4) decortication with iliac crest bone grafting and interspinous wiring. Surgical procedures were performed at the L5-6 level. Animals were killed at 2, 4 and 6 weeks after the intervention and the spine muscle blocks were excised. Specimens were assessed for the presence of fusion by (1) manual testing, (2) conventional absorption radiography and (3) ABI. ABI showed no evidence of bone fusion in groups 1 and 2 and showed solid or possibly solid fusion in subjects from groups 3 and 4 at 6 weeks. Metal artifacts were not present in any of the ABI images. Conventional absorption radiographs did not provide diagnostic quality imaging of either the graft material or fusion masses in any of the specimens in any of the groups. Synchrotron-based ABI represents a novel imaging technique which can be used to assess spinal fusion in a small animal model. ABI produces superior image quality when compared to conventional radiographs

  17. TWO NOVEL ACM (ACTIVE CONTOUR MODEL) METHODS FOR INTRAVASCULAR ULTRASOUND IMAGE SEGMENTATION

    International Nuclear Information System (INIS)

    Chen, Chi Hau; Potdat, Labhesh; Chittineni, Rakesh

    2010-01-01

    One of the attractive image segmentation methods is the Active Contour Model (ACM) which has been widely used in medical imaging as it always produces sub-regions with continuous boundaries. Intravascular ultrasound (IVUS) is a catheter based medical imaging technique which is used for quantitative assessment of atherosclerotic disease. Two methods of ACM realizations are presented in this paper. The gradient descent flow based on minimizing energy functional can be used for segmentation of IVUS images. However this local operation alone may not be adequate to work with the complex IVUS images. The first method presented consists of basically combining the local geodesic active contours and global region-based active contours. The advantage of combining the local and global operations is to allow curves deforming under the energy to find only significant local minima and delineate object borders despite noise, poor edge information and heterogeneous intensity profiles. Results for this algorithm are compared to standard techniques to demonstrate the method's robustness and accuracy. In the second method, the energy function is appropriately modified and minimized using a Hopfield neural network. Proper modifications in the definition of the bias of the neurons have been introduced to incorporate image characteristics. The method overcomes distortions in the expected image pattern, such as due to the presence of calcium, and employs a specialized structure of the neural network and boundary correction schemes which are based on a priori knowledge about the vessel geometry. The presented method is very fast and has been evaluated using sequences of IVUS frames.

  18. Analyzer-based imaging of spinal fusion in an animal model

    Science.gov (United States)

    Kelly, M. E.; Beavis, R. C.; Fiorella, David; Schültke, E.; Allen, L. A.; Juurlink, B. H.; Zhong, Z.; Chapman, L. D.

    2008-05-01

    Analyzer-based imaging (ABI) utilizes synchrotron radiation sources to create collimated monochromatic x-rays. In addition to x-ray absorption, this technique uses refraction and scatter rejection to create images. ABI provides dramatically improved contrast over standard imaging techniques. Twenty-one adult male Wistar rats were divided into four experimental groups to undergo the following interventions: (1) non-injured control, (2) decortication alone, (3) decortication with iliac crest bone grafting and (4) decortication with iliac crest bone grafting and interspinous wiring. Surgical procedures were performed at the L5-6 level. Animals were killed at 2, 4 and 6 weeks after the intervention and the spine muscle blocks were excised. Specimens were assessed for the presence of fusion by (1) manual testing, (2) conventional absorption radiography and (3) ABI. ABI showed no evidence of bone fusion in groups 1 and 2 and showed solid or possibly solid fusion in subjects from groups 3 and 4 at 6 weeks. Metal artifacts were not present in any of the ABI images. Conventional absorption radiographs did not provide diagnostic quality imaging of either the graft material or fusion masses in any of the specimens in any of the groups. Synchrotron-based ABI represents a novel imaging technique which can be used to assess spinal fusion in a small animal model. ABI produces superior image quality when compared to conventional radiographs.

  19. Gaussian mixture models-based ship target recognition algorithm in remote sensing infrared images

    Science.gov (United States)

    Yao, Shoukui; Qin, Xiaojuan

    2018-02-01

    Since the resolution of remote sensing infrared images is low, the features of ship targets become unstable. The issue of how to recognize ships with fuzzy features is an open problem. In this paper, we propose a novel ship target recognition algorithm based on Gaussian mixture models (GMMs). In the proposed algorithm, there are mainly two steps. At the first step, the Hu moments of these ship target images are calculated, and the GMMs are trained on the moment features of ships. At the second step, the moment feature of each ship image is assigned to the trained GMMs for recognition. Because of the scale, rotation, translation invariance property of Hu moments and the power feature-space description ability of GMMs, the GMMs-based ship target recognition algorithm can recognize ship reliably. Experimental results of a large simulating image set show that our approach is effective in distinguishing different ship types, and obtains a satisfactory ship recognition performance.

  20. A model of selective visual attention for a stereo pair of images

    Science.gov (United States)

    Park, Min Chul; Kim, Sung Kyu; Son, Jung-Young

    2005-11-01

    Human visual attention system has a remarkable ability to interpret complex scenes with the ease and simplicity by selecting or focusing on a small region of visual field without scanning the whole images. In this paper, a novel selective visual attention model by using 3D image display system for a stereo pair of images is proposed. It is based on the feature integration theory and locates ROI(region of interest) or FOA(focus of attention). The disparity map obtained from a stereo pair of images is exploited as one of spatial visual features to form a set of topographic feature maps in our approach. Though the true human cognitive mechanism on the analysis and integration process might be different from our assumption the proposed attention system matches well with the results found by human observers.

  1. Modeling the Process of Color Image Recognition Using ART2 Neural Network

    Directory of Open Access Journals (Sweden)

    Todor Petkov

    2015-09-01

    Full Text Available This paper thoroughly describes the use of unsupervised adaptive resonance theory ART2 neural network for the purposes of image color recognition of x-ray images and images taken by nuclear magnetic resonance. In order to train the network, the pixel values of RGB colors are regarded as learning vectors with three values, one for red, one for green and one for blue were used. At the end the trained network was tested by the values of pictures and determines the design, or how to visualize the converted picture. As a result we had the same pictures with colors according to the network. Here we use the generalized net to prepare a model that describes the process of the color image recognition.

  2. Image mispositioning due to dipping TI media : a physical seismic modelling study

    Energy Technology Data Exchange (ETDEWEB)

    Isaac, J.H.; Lawton, D.C.

    1998-09-01

    Physical modelling experiments were performed to study mispositioning of targets imaged beneath a dipping anisotropic overburden. The significance of the study is that many hydrocarbon resource exploration and development plays in different tectonic settings involve dipping clastic sequences which lie above the reservoir or target zone. In many areas in the Alberta foothills, dipping panels of relatively undeformed Wapiabi shales are found in abundance, overlying deep carbonate reservoirs. These experiments demonstrated the magnitude of the image mispositioning incurred by the use of an inappropriate isotropic processing code when velocity anisotropy was present in the overburden. It was shown that the lateral shift of an imaged target beneath a 1500 m thick, 45 degree dipping anisotropic overburden is significant. Zero-offset data showed a shift in the imaged location of 320 m in the updip direction of the dipping beds, while the shift on stacked time and depth migrated multichannel data was 300 m. 2 refs., 2 figs.

  3. Historical Single Image-Based Modeling: The Case of Gobierna Tower, Zamora (Spain

    Directory of Open Access Journals (Sweden)

    Jesús Garcia-Gago

    2014-01-01

    Full Text Available Historical perspective images have been proved to be very useful to properly provide a dimensional analysis of buildings façades or even to generate a pseudo-3D reconstruction based on rectified images of the whole structure. In this paper, the case of Gobierna Tower (Zamora, Spain is analyzed from a historical single image-based modeling approach. In particular, a bottom-up approach, which takes advantage from the perspective of the image, the existence of the three vanishing points and the usual geometric constraints (i.e., planarity, orthogonality, and parallelism is applied for the dimensional analysis of a destroyed historical building. Results were compared with ground truth measurements existing in a historical topographical surveying obtaining deviations of about 1%.

  4. Imaging of oxygenation in 3D tissue models with multi-modal phosphorescent probes

    Science.gov (United States)

    Papkovsky, Dmitri B.; Dmitriev, Ruslan I.; Borisov, Sergei

    2015-03-01

    Cell-penetrating phosphorescence based probes allow real-time, high-resolution imaging of O2 concentration in respiring cells and 3D tissue models. We have developed a panel of such probes, small molecule and nanoparticle structures, which have different spectral characteristics, cell penetrating and tissue staining behavior. The probes are compatible with conventional live cell imaging platforms and can be used in different detection modalities, including ratiometric intensity and PLIM (Phosphorescence Lifetime IMaging) under one- or two-photon excitation. Analytical performance of these probes and utility of the O2 imaging method have been demonstrated with different types of samples: 2D cell cultures, multi-cellular spheroids from cancer cell lines and primary neurons, excised slices from mouse brain, colon and bladder tissue, and live animals. They are particularly useful for hypoxia research, ex-vivo studies of tissue physiology, cell metabolism, cancer, inflammation, and multiplexing with many conventional fluorophors and markers of cellular function.

  5. Imaging of structures in the high-latitude ionosphere: model comparisons

    Directory of Open Access Journals (Sweden)

    D. W. Idenden

    Full Text Available The tomographic reconstruction technique generates a two-dimensional latitude versus height electron density distribution from sets of slant total electron content measurements (TEC along ray paths between beacon satellites and ground-based radio receivers. In this note, the technique is applied to TEC values obtained from data simulated by the Sheffield/UCL/SEL Coupled Thermosphere/Ionosphere/Model (CTIM. A comparison of the resulting reconstructed image with the 'input' modelled data allows for verification of the reconstruction technique. All the features of the high-latitude ionosphere in the model data are reproduced well in the tomographic image. Reconstructed vertical TEC values follow closely the modelled values, with the F-layer maximum density (NmF2 agreeing generally within about 10%. The method has also been able successfully to reproduce underlying auroral-E ionisation over a restricted latitudinal range in part of the image. The height of the F2 peak is generally in agreement to within about the vertical image resolution (25 km.

    Key words. Ionosphere (modelling and forecasting; polar ionosphere · Radio Science (instruments and techniques

  6. The monocular visual imaging technology model applied in the airport surface surveillance

    Science.gov (United States)

    Qin, Zhe; Wang, Jian; Huang, Chao

    2013-08-01

    At present, the civil aviation airports use the surface surveillance radar monitoring and positioning systems to monitor the aircrafts, vehicles and the other moving objects. Surface surveillance radars can cover most of the airport scenes, but because of the terminals, covered bridges and other buildings geometry, surface surveillance radar systems inevitably have some small segment blind spots. This paper presents a monocular vision imaging technology model for airport surface surveillance, achieving the perception of scenes of moving objects such as aircrafts, vehicles and personnel location. This new model provides an important complement for airport surface surveillance, which is different from the traditional surface surveillance radar techniques. Such technique not only provides clear objects activities screen for the ATC, but also provides image recognition and positioning of moving targets in this area. Thereby it can improve the work efficiency of the airport operations and avoid the conflict between the aircrafts and vehicles. This paper first introduces the monocular visual imaging technology model applied in the airport surface surveillance and then the monocular vision measurement accuracy analysis of the model. The monocular visual imaging technology model is simple, low cost, and highly efficient. It is an advanced monitoring technique which can make up blind spot area of the surface surveillance radar monitoring and positioning systems.

  7. a Semi-Empirical Topographic Correction Model for Multi-Source Satellite Images

    Science.gov (United States)

    Xiao, Sa; Tian, Xinpeng; Liu, Qiang; Wen, Jianguang; Ma, Yushuang; Song, Zhenwei

    2018-04-01

    Topographic correction of surface reflectance in rugged terrain areas is the prerequisite for the quantitative application of remote sensing in mountainous areas. Physics-based radiative transfer model can be applied to correct the topographic effect and accurately retrieve the reflectance of the slope surface from high quality satellite image such as Landsat8 OLI. However, as more and more images data available from various of sensors, some times we can not get the accurate sensor calibration parameters and atmosphere conditions which are needed in the physics-based topographic correction model. This paper proposed a semi-empirical atmosphere and topographic corrction model for muti-source satellite images without accurate calibration parameters.Based on this model we can get the topographic corrected surface reflectance from DN data, and we tested and verified this model with image data from Chinese satellite HJ and GF. The result shows that the correlation factor was reduced almost 85 % for near infrared bands and the classification overall accuracy of classification increased 14 % after correction for HJ. The reflectance difference of slope face the sun and face away the sun have reduced after correction.

  8. The Application of Use Case Modeling in Designing Medical Imaging Information Systems

    International Nuclear Information System (INIS)

    Safdari, Reza; Farzi, Jebraeil; Ghazisaeidi, Marjan; Mirzaee, Mahboobeh; Goodini, Azadeh

    2013-01-01

    Introduction. The essay at hand is aimed at examining the application of use case modeling in analyzing and designing information systems to support Medical Imaging services. Methods. The application of use case modeling in analyzing and designing health information systems was examined using electronic databases (Pubmed, Google scholar) resources and the characteristics of the modeling system and its effect on the development and design of the health information systems were analyzed. Results. Analyzing the subject indicated that Provident modeling of health information systems should provide for quick access to many health data resources in a way that patients' data can be used in order to expand distant services and comprehensive Medical Imaging advices. Also these experiences show that progress in the infrastructure development stages through gradual and repeated evolution process of user requirements is stronger and this can lead to a decline in the cycle of requirements engineering process in the design of Medical Imaging information systems. Conclusion. Use case modeling approach can be effective in directing the problems of health and Medical Imaging information systems towards understanding, focusing on the start and analysis, better planning, repetition, and control

  9. Recent Advances in Translational Magnetic Resonance Imaging in Animal Models of Stress and Depression

    Directory of Open Access Journals (Sweden)

    Allison L. McIntosh

    2017-05-01

    Full Text Available Magnetic resonance imaging (MRI is a valuable translational tool that can be used to investigate alterations in brain structure and function in both patients and animal models of disease. Regional changes in brain structure, functional connectivity, and metabolite concentrations have been reported in depressed patients, giving insight into the networks and brain regions involved, however preclinical models are less well characterized. The development of more effective treatments depends upon animal models that best translate to the human condition and animal models may be exploited to assess the molecular and cellular alterations that accompany neuroimaging changes. Recent advances in preclinical imaging have facilitated significant developments within the field, particularly relating to high resolution structural imaging and resting-state functional imaging which are emerging techniques in clinical research. This review aims to bring together the current literature on preclinical neuroimaging in animal models of stress and depression, highlighting promising avenues of research toward understanding the pathological basis of this hugely prevalent disorder.

  10. Tracking boundary movement and exterior shape modelling in lung EIT imaging

    International Nuclear Information System (INIS)

    Biguri, A; Soleimani, M; Grychtol, B; Adler, A

    2015-01-01

    Electrical impedance tomography (EIT) has shown significant promise for lung imaging. One key challenge for EIT in this application is the movement of electrodes during breathing, which introduces artefacts in reconstructed images. Various approaches have been proposed to compensate for electrode movement, but no comparison of these approaches is available. This paper analyses boundary model mismatch and electrode movement in lung EIT. The aim is to evaluate the extent to which various algorithms tolerate movement, and to determine if a patient specific model is required for EIT lung imaging. Movement data are simulated from a CT-based model, and image analysis is performed using quantitative figures of merit. The electrode movement is modelled based on expected values of chest movement and an extended Jacobian method is proposed to make use of exterior boundary tracking. Results show that a dynamical boundary tracking is the most robust method against any movement, but is computationally more expensive. Simultaneous electrode movement and conductivity reconstruction algorithms show increased robustness compared to only conductivity reconstruction. The results of this comparative study can help develop a better understanding of the impact of shape model mismatch and electrode movement in lung EIT. (paper)

  11. Tracking boundary movement and exterior shape modelling in lung EIT imaging.

    Science.gov (United States)

    Biguri, A; Grychtol, B; Adler, A; Soleimani, M

    2015-06-01

    Electrical impedance tomography (EIT) has shown significant promise for lung imaging. One key challenge for EIT in this application is the movement of electrodes during breathing, which introduces artefacts in reconstructed images. Various approaches have been proposed to compensate for electrode movement, but no comparison of these approaches is available. This paper analyses boundary model mismatch and electrode movement in lung EIT. The aim is to evaluate the extent to which various algorithms tolerate movement, and to determine if a patient specific model is required for EIT lung imaging. Movement data are simulated from a CT-based model, and image analysis is performed using quantitative figures of merit. The electrode movement is modelled based on expected values of chest movement and an extended Jacobian method is proposed to make use of exterior boundary tracking. Results show that a dynamical boundary tracking is the most robust method against any movement, but is computationally more expensive. Simultaneous electrode movement and conductivity reconstruction algorithms show increased robustness compared to only conductivity reconstruction. The results of this comparative study can help develop a better understanding of the impact of shape model mismatch and electrode movement in lung EIT.

  12. In Vivo Bioluminescence Imaging for Longitudinal Monitoring of Inflammation in Animal Models of Uveitis.

    Science.gov (United States)

    Gutowski, Michal B; Wilson, Leslie; Van Gelder, Russell N; Pepple, Kathryn L

    2017-03-01

    We develop a quantitative bioluminescence assay for in vivo longitudinal monitoring of inflammation in animal models of uveitis. Three models of experimental uveitis were induced in C57BL/6 albino mice: primed mycobacterial uveitis (PMU), endotoxin-induced uveitis (EIU), and experimental autoimmune uveitis (EAU). Intraperitoneal injection of luminol sodium salt, which emits light when oxidized, provided the bioluminescence substrate. Bioluminescence images were captured by a PerkinElmer In Vivo Imaging System (IVIS) Spectrum and total bioluminescence was analyzed using Living Image software. Bioluminescence on day zero was compared to bioluminescence on the day of peak inflammation for each model. Longitudinal bioluminescence imaging was performed in EIU and EAU. In the presence of luminol, intraocular inflammation generates detectable bioluminescence in three mouse models of uveitis. Peak bioluminescence in inflamed PMU eyes (1.46 × 105 photons/second [p/s]) was significantly increased over baseline (1.47 × 104 p/s, P = 0.01). Peak bioluminescence in inflamed EIU eyes (3.18 × 104 p/s) also was significantly increased over baseline (1.09 × 104 p/s, P = 0.04), and returned to near baseline levels by 48 hours. In EAU, there was a nonsignificant increase in bioluminescence at peak inflammation. In vivo bioluminescence may be used as a noninvasive, quantitative measure of intraocular inflammation in animal models of uveitis. Primed mycobacterial uveitis and EIU are both acute models with robust anterior inflammation and demonstrated significant changes in bioluminescence corresponding with peak inflammation. Experimental autoimmune uveitis is a more indolent posterior uveitis and generated a more modest bioluminescent signal. In vivo imaging system bioluminescence is a nonlethal, quantifiable assay that can be used for monitoring inflammation in animal models of uveitis.

  13. Post-modelling of images from a laser-induced wavy boiling front

    Energy Technology Data Exchange (ETDEWEB)

    Matti, R.S., E-mail: ramiz.matti@ltu.se [Luleå University of Technology, Department of Engineering Sciences and Mathematics, SE-971 87 Luleå (Sweden); University of Mosul, College of Engineering, Department of Mechanical Engineering, Mosul (Iraq); Kaplan, A.F.H. [Luleå University of Technology, Department of Engineering Sciences and Mathematics, SE-971 87 Luleå (Sweden)

    2015-12-01

    Highlights: • New method: post-modelling of high speed images from a laser-induced front. • From the images a wavy cavity and its absorption distribution is calculated. • Histograms enable additional statistical analysis and understanding. • Despite the complex topology the absorptivity is bound to 35–43%. • The new method visualizes valuable complementary information. - Abstract: Processes like laser keyhole welding, remote fusion laser cutting or laser drilling are governed by a highly dynamic wavy boiling front that was recently recorded by ultra-high speed imaging. A new approach has now been established by post-modelling of the high speed images. Based on the image greyscale and on a cavity model the three-dimensional front topology is reconstructed. As a second step the Fresnel absorptivity modulation across the wavy front is calculated, combined with the local projection of the laser beam. Frequency polygons enable additional analysis of the statistical variations of the properties across the front. Trends like shadow formation and time dependency can be studied, locally and for the whole front. Despite strong topology modulation in space and time, for lasers with 1 μm wavelength and steel the absorptivity is bounded to a narrow range of 35–43%, owing to its Fresnel characteristics.

  14. Impact of Tourist Perceptions, Destination Image and Tourist Satisfaction on Destination Loyalty: A Conceptual Model

    Directory of Open Access Journals (Sweden)

    R Rajesh

    2013-07-01

    Full Text Available The objective this research paper is develops a destination loyalty theoretical model by using tourist perception, destination image and tourist satisfaction. These study analysis components, attributes, factor influencing the destination image and examine the tourist satisfaction and determinants of destination loyalty. This is a conceptual paper attempts at evaluating recent empirical on destination image, tourist satisfaction and loyalty. The conceptual framework model is developed on the basis of existing theoretical and empirical research in the field of destination marketing. The models include four constructs. Tourist Perception constructs has been influenced by factors like Historical and Cultural Attractions, Destination Affordability, Travel Environment, Natural Attractions, Entertainments and Infrastructure. Destination image construct has been influenced by factors like Infrastructure & Facilities, Heritage Attractions, Natural Made Attractions, Destination Safety & Cleanness, Friendly Local Community & Clam Atmosphere, Rejuvenation and Service Price and Affordability. The satisfaction construct has been influenced by factors like Entertainments, Destination Attractions and Atmosphere, Accommodation, Food, Transportation Services and Shopping. The destination loyalty construct has influenced by intentions to revisit, word of mouth promotion and recommending to others . The earlier study result reveals that tourist perception, destination image and tourist satisfaction directly influence destination loyalty. The outcomes of the study have significant managerial implications for destination marketing managers.

  15. Model-based VQ for image data archival, retrieval and distribution

    Science.gov (United States)

    Manohar, Mareboyana; Tilton, James C.

    1995-01-01

    An ideal image compression technique for image data archival, retrieval and distribution would be one with the asymmetrical computational requirements of Vector Quantization (VQ), but without the complications arising from VQ codebooks. Codebook generation and maintenance are stumbling blocks which have limited the use of VQ as a practical image compression algorithm. Model-based VQ (MVQ), a variant of VQ described here, has the computational properties of VQ but does not require explicit codebooks. The codebooks are internally generated using mean removed error and Human Visual System (HVS) models. The error model assumed is the Laplacian distribution with mean, lambda-computed from a sample of the input image. A Laplacian distribution with mean, lambda, is generated with uniform random number generator. These random numbers are grouped into vectors. These vectors are further conditioned to make them perceptually meaningful by filtering the DCT coefficients from each vector. The DCT coefficients are filtered by multiplying by a weight matrix that is found to be optimal for human perception. The inverse DCT is performed to produce the conditioned vectors for the codebook. The only image dependent parameter used in the generation of codebook is the mean, lambda, that is included in the coded file to repeat the codebook generation process for decoding.

  16. Objective and expert-independent validation of retinal image registration algorithms by a projective imaging distortion model

    NARCIS (Netherlands)

    Lee, Sangyeol; Reinhardt, Joseph M.; Cattin, Philippe C.; Abramoff, M.D.

    2010-01-01

    Fundus camera imaging of the retina is widely used to diagnose and manage ophthalmologic disorders including diabetic retinopathy, glaucoma, and age-related macular degeneration. Retinal images typically have a limited field of view, and multiple images can be joined together using an image

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

    International Nuclear Information System (INIS)

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

    2015-01-01

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

  18. SEMI-AUTOMATIC BUILDING MODELS AND FAÇADE TEXTURE MAPPING FROM MOBILE PHONE IMAGES

    Directory of Open Access Journals (Sweden)

    J. Jeong

    2016-06-01

    Full Text Available Research on 3D urban modelling has been actively carried out for a long time. Recently the need of 3D urban modelling research is increased rapidly due to improved geo-web services and popularized smart devices. Nowadays 3D urban models provided by, for example, Google Earth use aerial photos for 3D urban modelling but there are some limitations: immediate update for the change of building models is difficult, many buildings are without 3D model and texture, and large resources for maintaining and updating are inevitable. To resolve the limitations mentioned above, we propose a method for semi-automatic building modelling and façade texture mapping from mobile phone images and analyze the result of modelling with actual measurements. Our method consists of camera geometry estimation step, image matching step, and façade mapping step. Models generated from this method were compared with actual measurement value of real buildings. Ratios of edge length of models and measurements were compared. Result showed 5.8% average error of length ratio. Through this method, we could generate a simple building model with fine façade textures without expensive dedicated tools and dataset.

  19. Multimodality pH imaging in a mouse dorsal skin fold window chamber model

    Science.gov (United States)

    Leung, Hui Min; Schafer, Rachel; Pagel, Mark M.; Robey, Ian F.; Gmitro, Arthur F.

    2013-03-01

    Upregulate levels of expression and activity of membrane H+ ion pumps in cancer cells drives the extracellular pH (pHe,) to values lower than normal. Furthermore, disregulated pH is indicative of the changes in glycolytic metabolism in tumor cells and has been shown to facilitate extracellular tissue remodeling during metastasis Therefore, measurement of pHe could be a useful cancer biomarker for diagnostic and therapy monitoring evaluation. Multimodality in-vivo imaging of pHe in tumorous tissue in a mouse dorsal skin fold window chamber (DSFWC) model is described. A custom-made plastic window chamber structure was developed that is compatible with both imaging optical and MR imaging modalities and provides a model system for continuous study of the same tissue microenvironment on multiple imaging platforms over a 3-week period. For optical imaging of pHe, SNARF-1 carboxylic acid is injected intravenously into a SCID mouse with an implanted tumor. A ratiometric measurement of the fluorescence signal captured on a confocal microscope reveals the pHe of the tissue visible within the window chamber. This imaging method was used in a preliminary study to evaluate sodium bicarbonate as a potential drug treatment to reverse tissue acidosis. For MR imaging of pHe the chemical exchange saturation transfer (CEST) was used as an alternative way of measuring pHe in a DSFWC model. ULTRAVIST®, a FDA approved x-ray/CT contrast agent has been shown to have a CEST effect that is pH dependent. A ratiometric analysis of water saturation at 5.6 and 4.2 ppm chemical shift provides a means to estimate the local pHe.

  20. [A Method to Reconstruct Surface Reflectance Spectrum from Multispectral Image Based on Canopy Radiation Transfer Model].

    Science.gov (United States)

    Zhao, Yong-guang; Ma, Ling-ling; Li, Chuan-rong; Zhu, Xiao-hua; Tang, Ling-li

    2015-07-01

    Due to the lack of enough spectral bands for multi-spectral sensor, it is difficult to reconstruct surface retlectance spectrum from finite spectral information acquired by multi-spectral instrument. Here, taking into full account of the heterogeneity of pixel from remote sensing image, a method is proposed to simulate hyperspectral data from multispectral data based on canopy radiation transfer model. This method first assumes the mixed pixels contain two types of land cover, i.e., vegetation and soil. The sensitive parameters of Soil-Leaf-Canopy (SLC) model and a soil ratio factor were retrieved from multi-spectral data based on Look-Up Table (LUT) technology. Then, by combined with a soil ratio factor, all the parameters were input into the SLC model to simulate the surface reflectance spectrum from 400 to 2 400 nm. Taking Landsat Enhanced Thematic Mapper Plus (ETM+) image as reference image, the surface reflectance spectrum was simulated. The simulated reflectance spectrum revealed different feature information of different surface types. To test the performance of this method, the simulated reflectance spectrum was convolved with the Landsat ETM + spectral response curves and Moderate Resolution Imaging Spectrometer (MODIS) spectral response curves to obtain the simulated Landsat ETM+ and MODIS image. Finally, the simulated Landsat ETM+ and MODIS images were compared with the observed Landsat ETM+ and MODIS images. The results generally showed high correction coefficients (Landsat: 0.90-0.99, MODIS: 0.74-0.85) between most simulated bands and observed bands and indicated that the simulated reflectance spectrum was well simulated and reliable.

  1. Device model for pixelless infrared image up-converters based on polycrystalline graphene heterostructures

    Science.gov (United States)

    Ryzhii, V.; Shur, M. S.; Ryzhii, M.; Karasik, V. E.; Otsuji, T.

    2018-01-01

    We developed a device model for pixelless converters of far/mid-infrared radiation (FIR/MIR) images into near-infrared/visible (NIR/VIR) images. These converters use polycrystalline graphene layers (PGLs) immersed in the van der Waals materials integrated with a light emitting diode (LED). The PGL serves as an element of the PGL infrared photodetector (PGLIP) sensitive to the incoming FIR/MIR due to the interband absorption. The spatially non-uniform photocurrent generated in the PGLIP repeats (mimics) the non-uniform distribution (image) created by the incident FIR/MIR. The injection of the nonuniform photocurrent into the LED active layer results in the nonuniform NIR/VIR image reproducing the FIR/MIR image. The PGL and the entire layer structure are not deliberately partitioned into pixels. We analyze the characteristics of such pixelless PGLIP-LED up-converters and show that their image contrast transfer function and the up-conversion efficiency depend on the PGL lateral resistivity. The up-converter exhibits high photoconductive gain and conversion efficiency when the lateral resistivity is sufficiently high. Several teams have successfully demonstrated the large area PGLs with the resistivities varying in a wide range. Such layers can be used in the pixelless PGLIP-LED image up-converters. The PGLIP-LED image up-converters can substantially surpass the image up-converters based on the quantum-well infrared photodetector integrated with the LED. These advantages are due to the use of the interband FIR/NIR absorption and a high photoconductive gain in the GLIPs.

  2. Overview of IMAGE 2.0. An integrated model of climate change and the global environment

    International Nuclear Information System (INIS)

    Alcamo, J.; Battjes, C.; Van den Born, G.J.; Bouwman, A.F.; De Haan, B.J.; Klein Goldewijk, K.; Klepper, O.; Kreileman, G.J.J.; Krol, M.; Leemans, R.; Van Minnen, J.G.; Olivier, J.G.J.; De Vries, H.J.M.; Toet, A.M.C.; Van den Wijngaart, R.A.; Van der Woerd, H.J.; Zuidema, G.

    1995-01-01

    The IMAGE 2.0 model is a multi-disciplinary, integrated model, designed to simulate the dynamics of the global society-biosphere-climate system. In this paper the focus is on the scientific aspects of the model, while another paper in this volume emphasizes its political aspects. The objectives of IMAGE 2.0 are to investigate linkages and feedbacks in the global system, and to evaluate consequences of climate policies. Dynamic calculations are performed to the year 2100, with a spatial scale ranging from grid (0.5x0.5 latitude-longitude) to world political regions, depending on the sub-model. A total of 13 sub-models make up IMAGE 2.0, and they are organized into three fully linked sub-systems: Energy-Industry, Terrestrial Environment, and Atmosphere-Ocean. The fully linked model has been tested against data from 1970 to 1990, and after calibration it can reproduce the following observed trends: regional energy consumption and energy-related emissions, terrestrial flux of carbon dioxide and emissions of greenhouse gases, concentrations of greenhouse gases in the atmosphere, and transformation of land cover. The model can also simulate current zonal average surface and vertical temperatures. 1 fig., 10 refs

  3. Comparison of linear measurements and analyses taken from plaster models and three-dimensional images.

    Science.gov (United States)

    Porto, Betina Grehs; Porto, Thiago Soares; Silva, Monica Barros; Grehs, Renésio Armindo; Pinto, Ary dos Santos; Bhandi, Shilpa H; Tonetto, Mateus Rodrigues; Bandéca, Matheus Coelho; dos Santos-Pinto, Lourdes Aparecida Martins

    2014-11-01

    Digital models are an alternative for carrying out analyses and devising treatment plans in orthodontics. The objective of this study was to evaluate the accuracy and the reproducibility of measurements of tooth sizes, interdental distances and analyses of occlusion using plaster models and their digital images. Thirty pairs of plaster models were chosen at random, and the digital images of each plaster model were obtained using a laser scanner (3Shape R-700, 3Shape A/S). With the plaster models, the measurements were taken using a caliper (Mitutoyo Digimatic(®), Mitutoyo (UK) Ltd) and the MicroScribe (MS) 3DX (Immersion, San Jose, Calif). For the digital images, the measurement tools used were those from the O3d software (Widialabs, Brazil). The data obtained were compared statistically using the Dahlberg formula, analysis of variance and the Tukey test (p < 0.05). The majority of the measurements, obtained using the caliper and O3d were identical, and both were significantly different from those obtained using the MS. Intra-examiner agreement was lowest when using the MS. The results demonstrated that the accuracy and reproducibility of the tooth measurements and analyses from the plaster models using the caliper and from the digital models using O3d software were identical.

  4. Ultrasound imaging measurement of submerged topography in the muddy water physical model

    International Nuclear Information System (INIS)

    Xiao, Xiongwu; Guo, Bingxuan; Li, Deren; Zhang, Peng; Zang, Yu-fu; Zou, Xianjian; Liu, Jian-chen

    2015-01-01

    The real-time, accurate measurement of submerged topography is vital for the analysis of riverbed erosion and deposition. This paper describes a novel method of measuring submerged topography in the B-scan image obtained using an ultrasound imaging device. Results show the distribution of gray values in the image has a process of mutation. This mutation process can be used to adaptively track the topographic lines between riverbed and water, based on the continuity of topography in the horizontal direction. The extracted topographic lines, of one pixel width, are processed by a wavelet filtering method. Compared with the actual topography, the measurement accuracy is within 1 mm. It is suitable for the real-time measurement and analysis of all current model topographies with the advantage of good self-adaptation. In particular, it is visible and intuitive for muddy water in the movable-bed model experiment. (paper)

  5. Mid-IR Imaging of Orion BN/KL: Modeling of Physical Conditions and Energy Balance

    Science.gov (United States)

    Gezari, Daniel; Varosi, Frank; Dwek, Eli; Danchi, William C.; Tan, Jonathan; Okumura, Shin-ichiro

    2016-01-01

    We have modeled two mid-infrared imaging photometry data sets to determine the spatial distribution of physical conditions in the BN/KL (Becklin-Neugebauer / Kleinmann-Low) infrared complex. We observed the BN/KL region using the 10-meter Keck I telescope and the LWS (Living With a Star) in the direct imaging mode, over a 13 inch by 19 inch field . We also modeled images obtained with COMICS (Cooled Mid-Infrared Camera and Spectrometer, Kataza et al. 2000) at the 8.2-meter SUBARU telescope, over a total field of view [which] is 31 inches by 41 inches in a total of nine bands: 7.8, 8.8, 9.7, 10.5, 11.7, 12.4, 18.5, 20.8 and 24.8 microns with 1-micron bandwidth interference filters.

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

    International Nuclear Information System (INIS)

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

    2010-01-01

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

  7. Reconstruction of implanted marker trajectories from cone-beam CT projection images using interdimensional correlation modeling

    International Nuclear Information System (INIS)

    Chung, Hyekyun; Poulsen, Per Rugaard; Keall, Paul J.; Cho, Seungryong; Cho, Byungchul

    2016-01-01

    Purpose: Cone-beam CT (CBCT) is a widely used imaging modality for image-guided radiotherapy. Most vendors provide CBCT systems that are mounted on a linac gantry. Thus, CBCT can be used to estimate the actual 3-dimensional (3D) position of moving respiratory targets in the thoracic/abdominal region using 2D projection images. The authors have developed a method for estimating the 3D trajectory of respiratory-induced target motion from CBCT projection images using interdimensional correlation modeling. Methods: Because the superior–inferior (SI) motion of a target can be easily analyzed on projection images of a gantry-mounted CBCT system, the authors investigated the interdimensional correlation of the SI motion with left–right and anterior–posterior (AP) movements while the gantry is rotating. A simple linear model and a state-augmented model were implemented and applied to the interdimensional correlation analysis, and their performance was compared. The parameters of the interdimensional correlation models were determined by least-square estimation of the 2D error between the actual and estimated projected target position. The method was validated using 160 3D tumor trajectories from 46 thoracic/abdominal cancer patients obtained during CyberKnife treatment. The authors’ simulations assumed two application scenarios: (1) retrospective estimation for the purpose of moving tumor setup used just after volumetric matching with CBCT; and (2) on-the-fly estimation for the purpose of real-time target position estimation during gating or tracking delivery, either for full-rotation volumetric-modulated arc therapy (VMAT) in 60 s or a stationary six-field intensity-modulated radiation therapy (IMRT) with a beam delivery time of 20 s. Results: For the retrospective CBCT simulations, the mean 3D root-mean-square error (RMSE) for all 4893 trajectory segments was 0.41 mm (simple linear model) and 0.35 mm (state-augmented model). In the on-the-fly simulations, prior

  8. Reconstruction of implanted marker trajectories from cone-beam CT projection images using interdimensional correlation modeling

    Energy Technology Data Exchange (ETDEWEB)

    Chung, Hyekyun [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, South Korea and Department of Radiation Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul 138-736 (Korea, Republic of); Poulsen, Per Rugaard [Department of Oncology, Aarhus University Hospital, Nørrebrogade 44, 8000 Aarhus C (Denmark); Keall, Paul J. [Radiation Physics Laboratory, Sydney Medical School, University of Sydney, NSW 2006 (Australia); Cho, Seungryong [Department of Nuclear and Quantum Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141 (Korea, Republic of); Cho, Byungchul, E-mail: cho.byungchul@gmail.com, E-mail: bcho@amc.seoul.kr [Department of Radiation Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul 05505 (Korea, Republic of)

    2016-08-15

    Purpose: Cone-beam CT (CBCT) is a widely used imaging modality for image-guided radiotherapy. Most vendors provide CBCT systems that are mounted on a linac gantry. Thus, CBCT can be used to estimate the actual 3-dimensional (3D) position of moving respiratory targets in the thoracic/abdominal region using 2D projection images. The authors have developed a method for estimating the 3D trajectory of respiratory-induced target motion from CBCT projection images using interdimensional correlation modeling. Methods: Because the superior–inferior (SI) motion of a target can be easily analyzed on projection images of a gantry-mounted CBCT system, the authors investigated the interdimensional correlation of the SI motion with left–right and anterior–posterior (AP) movements while the gantry is rotating. A simple linear model and a state-augmented model were implemented and applied to the interdimensional correlation analysis, and their performance was compared. The parameters of the interdimensional correlation models were determined by least-square estimation of the 2D error between the actual and estimated projected target position. The method was validated using 160 3D tumor trajectories from 46 thoracic/abdominal cancer patients obtained during CyberKnife treatment. The authors’ simulations assumed two application scenarios: (1) retrospective estimation for the purpose of moving tumor setup used just after volumetric matching with CBCT; and (2) on-the-fly estimation for the purpose of real-time target position estimation during gating or tracking delivery, either for full-rotation volumetric-modulated arc therapy (VMAT) in 60 s or a stationary six-field intensity-modulated radiation therapy (IMRT) with a beam delivery time of 20 s. Results: For the retrospective CBCT simulations, the mean 3D root-mean-square error (RMSE) for all 4893 trajectory segments was 0.41 mm (simple linear model) and 0.35 mm (state-augmented model). In the on-the-fly simulations, prior

  9. Multi-component fiber track modelling of diffusion-weighted magnetic resonance imaging data

    Directory of Open Access Journals (Sweden)

    Yasser M. Kadah

    2010-01-01

    Full Text Available In conventional diffusion tensor imaging (DTI based on magnetic resonance data, each voxel is assumed to contain a single component having diffusion properties that can be fully represented by a single tensor. Even though this assumption can be valid in some cases, the general case involves the mixing of components, resulting in significant deviation from the single tensor model. Hence, a strategy that allows the decomposition of data based on a mixture model has the potential of enhancing the diagnostic value of DTI. This project aims to work towards the development and experimental verification of a robust method for solving the problem of multi-component modelling of diffusion tensor imaging data. The new method demonstrates significant error reduction from the single-component model while maintaining practicality for clinical applications, obtaining more accurate Fiber tracking results.

  10. Mouse Models of Breast Cancer: Platforms for Discovering Precision Imaging Diagnostics and Future Cancer Medicine.

    Science.gov (United States)

    Manning, H Charles; Buck, Jason R; Cook, Rebecca S

    2016-02-01

    Representing an enormous health care and socioeconomic challenge, breast cancer is the second most common cancer in the world and the second most common cause of cancer-related death. Although many of the challenges associated with preventing, treating, and ultimately curing breast cancer are addressable in the laboratory, successful translation of groundbreaking research to clinical populations remains an important barrier. Particularly when compared with research on other types of solid tumors, breast cancer research is hampered by a lack of tractable in vivo model systems that accurately recapitulate the relevant clinical features of the disease. A primary objective of this article was to provide a generalizable overview of the types of in vivo model systems, with an emphasis primarily on murine models, that are widely deployed in preclinical breast cancer research. Major opportunities to advance precision cancer medicine facilitated by molecular imaging of preclinical breast cancer models are discussed. © 2016 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

  11. Correction of electrode modelling errors in multi-frequency EIT imaging.

    Science.gov (United States)

    Jehl, Markus; Holder, David

    2016-06-01

    The differentiation of haemorrhagic from ischaemic stroke using electrical impedance tomography (EIT) requires measurements at multiple frequencies, since the general lack of healthy measurements on the same patient excludes time-difference imaging methods. It has previously been shown that the inaccurate modelling of electrodes constitutes one of the largest sources of image artefacts in non-linear multi-frequency EIT applications. To address this issue, we augmented the conductivity Jacobian matrix with a Jacobian matrix with respect to electrode movement. Using this new algorithm, simulated ischaemic and haemorrhagic strokes in a realistic head model were reconstructed for varying degrees of electrode position errors. The simultaneous recovery of conductivity spectra and electrode positions removed most artefacts caused by inaccurately modelled electrodes. Reconstructions were stable for electrode position errors of up to 1.5 mm standard deviation along both surface dimensions. We conclude that this method can be used for electrode model correction in multi-frequency EIT.

  12. Image-based modeling of tumor shrinkage in head and neck radiation therapy1

    Science.gov (United States)

    Chao, Ming; Xie, Yaoqin; Moros, Eduardo G.; Le, Quynh-Thu; Xing, Lei

    2010-01-01

    Purpose: Understanding the kinetics of tumor growth∕shrinkage represents a critical step in quantitative assessment of therapeutics and realization of adaptive radiation therapy. This article presents a novel framework for image-based modeling of tumor change and demonstrates its performance with synthetic images and clinical cases. Methods: Due to significant tumor tissue content changes, similarity-based models are not suitable for describing the process of tumor volume changes. Under the hypothesis that tissue features in a tumor volume or at the boundary region are partially preserved, the kinetic change was modeled in two steps: (1) Autodetection of homologous tissue features shared by two input images using the scale invariance feature transformation (SIFT) method; and (2) establishment of a voxel-to-voxel correspondence between the images for the remaining spatial points by interpolation. The correctness of the tissue feature correspondence was assured by a bidirectional association procedure, where SIFT features were mapped from template to target images and reversely. A series of digital phantom experiments and five head and neck clinical cases were used to assess the performance of the proposed technique. Results: The proposed technique can faithfully identify the known changes introduced when constructing the digital phantoms. The subsequent feature-guided thin plate spline calculation reproduced the “ground truth” with accuracy better than 1.5 mm. For the clinical cases, the new algorithm worked reliably for a volume change as large as 30%. Conclusions: An image-based tumor kinetic algorithm was developed to model the tumor response to radiation therapy. The technique provides a practical framework for future application in adaptive radiation therapy. PMID:20527569

  13. Image-based modeling of tumor shrinkage in head and neck radiation therapy

    International Nuclear Information System (INIS)

    Chao Ming; Xie Yaoqin; Moros, Eduardo G.; Le, Quynh-Thu; Xing Lei

    2010-01-01

    Purpose: Understanding the kinetics of tumor growth/shrinkage represents a critical step in quantitative assessment of therapeutics and realization of adaptive radiation therapy. This article presents a novel framework for image-based modeling of tumor change and demonstrates its performance with synthetic images and clinical cases. Methods: Due to significant tumor tissue content changes, similarity-based models are not suitable for describing the process of tumor volume changes. Under the hypothesis that tissue features in a tumor volume or at the boundary region are partially preserved, the kinetic change was modeled in two steps: (1) Autodetection of homologous tissue features shared by two input images using the scale invariance feature transformation (SIFT) method; and (2) establishment of a voxel-to-voxel correspondence between the images for the remaining spatial points by interpolation. The correctness of the tissue feature correspondence was assured by a bidirectional association procedure, where SIFT features were mapped from template to target images and reversely. A series of digital phantom experiments and five head and neck clinical cases were used to assess the performance of the proposed technique. Results: The proposed technique can faithfully identify the known changes introduced when constructing the digital phantoms. The subsequent feature-guided thin plate spline calculation reproduced the ''ground truth'' with accuracy better than 1.5 mm. For the clinical cases, the new algorithm worked reliably for a volume change as large as 30%. Conclusions: An image-based tumor kinetic algorithm was developed to model the tumor response to radiation therapy. The technique provides a practical framework for future application in adaptive radiation therapy.

  14. Image-based modeling of tumor shrinkage in head and neck radiation therapy

    Energy Technology Data Exchange (ETDEWEB)

    Chao Ming; Xie Yaoqin; Moros, Eduardo G.; Le, Quynh-Thu; Xing Lei [Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, California 94305-5847 and Department of Radiation Oncology, University of Arkansas for Medical Sciences, 4301 W. Markham Street, Little Rock, Arkansas 72205-1799 (United States); Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, California 94305-5847 (United States); Department of Radiation Oncology, University of Arkansas for Medical Sciences, 4301 W. Markham Street, Little Rock, Arkansas 72205-1799 (United States); Department of Radiation Oncology, Stanford University School of Medicine, 875 Blake Wilbur Drive, Stanford, California 94305-5847 (United States)

    2010-05-15

    Purpose: Understanding the kinetics of tumor growth/shrinkage represents a critical step in quantitative assessment of therapeutics and realization of adaptive radiation therapy. This article presents a novel framework for image-based modeling of tumor change and demonstrates its performance with synthetic images and clinical cases. Methods: Due to significant tumor tissue content changes, similarity-based models are not suitable for describing the process of tumor volume changes. Under the hypothesis that tissue features in a tumor volume or at the boundary region are partially preserved, the kinetic change was modeled in two steps: (1) Autodetection of homologous tissue features shared by two input images using the scale invariance feature transformation (SIFT) method; and (2) establishment of a voxel-to-voxel correspondence between the images for the remaining spatial points by interpolation. The correctness of the tissue feature correspondence was assured by a bidirectional association procedure, where SIFT features were mapped from template to target images and reversely. A series of digital phantom experiments and five head and neck clinical cases were used to assess the performance of the proposed technique. Results: The proposed technique can faithfully identify the known changes introduced when constructing the digital phantoms. The subsequent feature-guided thin plate spline calculation reproduced the ''ground truth'' with accuracy better than 1.5 mm. For the clinical cases, the new algorithm worked reliably for a volume change as large as 30%. Conclusions: An image-based tumor kinetic algorithm was developed to model the tumor response to radiation therapy. The technique provides a practical framework for future application in adaptive radiation therapy.

  15. Efficient methodologies for system matrix modelling in iterative image reconstruction for rotating high-resolution PET

    Energy Technology Data Exchange (ETDEWEB)

    Ortuno, J E; Kontaxakis, G; Rubio, J L; Santos, A [Departamento de Ingenieria Electronica (DIE), Universidad Politecnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid (Spain); Guerra, P [Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid (Spain)], E-mail: juanen@die.upm.es

    2010-04-07

    A fully 3D iterative image reconstruction algorithm has been developed for high-resolution PET cameras composed of pixelated scintillator crystal arrays and rotating planar detectors, based on the ordered subsets approach. The associated system matrix is precalculated with Monte Carlo methods that incorporate physical effects not included in analytical models, such as positron range effects and interaction of the incident gammas with the scintillator material. Custom Monte Carlo methodologies have been developed and optimized for modelling of system matrices for fast iterative image reconstruction adapted to specific scanner geometries, without redundant calculations. According to the methodology proposed here, only one-eighth of the voxels within two central transaxial slices need to be modelled in detail. The rest of the system matrix elements can be obtained with the aid of axial symmetries and redundancies, as well as in-plane symmetries within transaxial slices. Sparse matrix techniques for the non-zero system matrix elements are employed, allowing for fast execution of the image reconstruction process. This 3D image reconstruction scheme has been compared in terms of image quality to a 2D fast implementation of the OSEM algorithm combined with Fourier rebinning approaches. This work confirms the superiority of fully 3D OSEM in terms of spatial resolution, contrast recovery and noise reduction as compared to conventional 2D approaches based on rebinning schemes. At the same time it demonstrates that fully 3D methodologies can be efficiently applied to the image reconstruction problem for high-resolution rotational PET cameras by applying accurate pre-calculated system models and taking advantage of the system's symmetries.

  16. First test model of the optical microscope which images the whole vertical particle tracks without any depth scanning

    International Nuclear Information System (INIS)

    Soroko, L.M.

    2001-01-01

    The first test model of the optical microscope which produces the in focus image of the whole vertical particle track without depth scanning is described. The in focus image of the object consisting of the linear array of the point-like elements was obtained. A comparison with primary out of focus image of such an object has been made

  17. Quantitative analysis of CT brain images: a statistical model incorporating partial volume and beam hardening effects

    International Nuclear Information System (INIS)

    McLoughlin, R.F.; Ryan, M.V.; Heuston, P.M.; McCoy, C.T.; Masterson, J.B.

    1992-01-01

    The purpose of this study was to construct and evaluate a statistical model for the quantitative analysis of computed tomographic brain images. Data were derived from standard sections in 34 normal studies. A model representing the intercranial pure tissue and partial volume areas, with allowance for beam hardening, was developed. The average percentage error in estimation of areas, derived from phantom tests using the model, was 28.47%. We conclude that our model is not sufficiently accurate to be of clinical use, even though allowance was made for partial volume and beam hardening effects. (author)

  18. BrainK for Structural Image Processing: Creating Electrical Models of the Human Head

    Directory of Open Access Journals (Sweden)

    Kai Li

    2016-01-01

    Full Text Available BrainK is a set of automated procedures for characterizing the tissues of the human head from MRI, CT, and photogrammetry images. The tissue segmentation and cortical surface extraction support the primary goal of modeling the propagation of electrical currents through head tissues with a finite difference model (FDM or finite element model (FEM created from the BrainK geometries. The electrical head model is necessary for accurate source localization of dense array electroencephalographic (dEEG measures from head surface electrodes. It is also necessary for accurate targeting of cerebral structures with transcranial current injection from those surface electrodes. BrainK must achieve five major tasks: image segmentation, registration of the MRI, CT, and sensor photogrammetry images, cortical surface reconstruction, dipole tessellation of the cortical surface, and Talairach transformation. We describe the approach to each task, and we compare the accuracies for the key tasks of tissue segmentation and cortical surface extraction in relation to existing research tools (FreeSurfer, FSL, SPM, and BrainVisa. BrainK achieves good accuracy with minimal or no user intervention, it deals well with poor quality MR images and tissue abnormalities, and it provides improved computational efficiency over existing research packages.

  19. On Feature Relevance in Image-Based Prediction Models: An Empirical Study

    DEFF Research Database (Denmark)

    Konukoglu, E.; Ganz, Melanie; Van Leemput, Koen

    2013-01-01

    Determining disease-related variations of the anatomy and function is an important step in better understanding diseases and developing early diagnostic systems. In particular, image-based multivariate prediction models and the “relevant features” they produce are attracting attention from the co...

  20. Cylindrical SUV distribution model for detecting skin lesions in body trunk FDG-PET/CT images

    International Nuclear Information System (INIS)

    Nemoto, Mitsutaka; Nomura, Yukihiro; Masutani, Yoshitaka; Yoshikawa, Takeharu; Hayashi, Naoto; Yoshioka, Naoki; Ohtomo, Kuni; Hanaoka, Shouhei

    2010-01-01

    We have been developing a computerized detection method for skin lesions in body trunk fluorodeoxyglucose-positron emission tomography (FDG-PET)/CT images. Spots on the skin with a high standard uptake value (SUV) are due not only to glucose metabolism in skin lesions but also to the physiological metabolism of organs near the skin. The distribution pattern of regional SUV on the skin is important information for the differential diagnosis of such high-SUV spots. In this study, we have developed a new skin lesion detection method based on a cylindrical SUV distribution model of the skin. The shape of the SUV distribution model is an approximation of the body trunk, and the SUV distribution model includes standard values for regional skin SUV. Classifier ensembles based on CT image features, SUV features, and subtraction features between the SUVs in FDG-PET images and the values in the SUV distribution model are used to extract and classify candidate regions for skin lesions. In a study of skin lesion detection using FDG-PET/CT images in 36 clinical cases, the true-positive rate was 61.7%, with 11.7 false-positive regions per case. The training results of the classifier ensemble for extracting and classifying candidate regions showed the effective features for detecting skin lesions in the study. (author)

  1. Stratified spherical model for microwave imaging of the brain: Analysis and experimental validation of transmitted power

    DEFF Research Database (Denmark)

    Bjelogrlic, Mina; Volery, Maxime; Fuchs, Benjamin

    2018-01-01

    This work presents the analysis of power transmission of a radiating field inside the human head for microwave imaging applications. For this purpose, a spherical layered model composed of dispersive biological tissues is investigated in the range of (0.5–4) GHz and is confronted to experimental ...

  2. Model-based extraction of input and organ functions in dynamic scintigraphic imaging

    Czech Academy of Sciences Publication Activity Database

    Tichý, Ondřej; Šmídl, Václav; Šámal, M.

    2016-01-01

    Roč. 4, 3-4 (2016), s. 135-145 ISSN 2168-1171 R&D Projects: GA ČR GA13-29225S Institutional support: RVO:67985556 Keywords : blind source separation * convolution * dynamic medical imaging * compartment modelling Subject RIV: BB - Applied Statistics, Operational Research http://library.utia.cas.cz/separaty/2014/AS/tichy-0428540.pdf

  3. Construction of In Vivo Fluorescent Imaging of Echinococcus granulosus in a Mouse Model.

    Science.gov (United States)

    Wang, Sibo; Yang, Tao; Zhang, Xuyong; Xia, Jie; Guo, Jun; Wang, Xiaoyi; Hou, Jixue; Zhang, Hongwei; Chen, Xueling; Wu, Xiangwei

    2016-06-01

    Human hydatid disease (cystic echinococcosis, CE) is a chronic parasitic infection caused by the larval stage of the cestode Echinococcus granulosus. As the disease mainly affects the liver, approximately 70% of all identified CE cases are detected in this organ. Optical molecular imaging (OMI), a noninvasive imaging technique, has never been used in vivo with the specific molecular markers of CE. Thus, we aimed to construct an in vivo fluorescent imaging mouse model of CE to locate and quantify the presence of the parasites within the liver noninvasively. Drug-treated protoscolices were monitored after marking by JC-1 dye in in vitro and in vivo studies. This work describes for the first time the successful construction of an in vivo model of E. granulosus in a small living experimental animal to achieve dynamic monitoring and observation of multiple time points of the infection course. Using this model, we quantified and analyzed labeled protoscolices based on the intensities of their red and green fluorescence. Interestingly, the ratio of red to green fluorescence intensity not only revealed the location of protoscolices but also determined the viability of the parasites in vivo and in vivo tests. The noninvasive imaging model proposed in this work will be further studied for long-term detection and observation and may potentially be widely utilized in susceptibility testing and therapeutic effect evaluation.

  4. Explicit Foreground and Background Modeling in The Classification of Text Blocks in Scene Images

    NARCIS (Netherlands)

    Sriman, Bowornrat; Schomaker, Lambertus

    2015-01-01

    Achieving high accuracy for classifying foreground and background is an interesting challenge in the field of scene image analysis because of the wide range of illumination, complex background, and scale changes. Clas