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...
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)
Despeckling Polsar Images Based on Relative Total Variation Model
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.
Mixed Higher Order Variational Model for Image Recovery
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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.
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)
Feedforward Object-Vision Models Only Tolerate Small Image Variations Compared to Human
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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.
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...
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...
Image Restoration Based on the Hybrid Total-Variation-Type Model
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...
Factoring variations in natural images with deep Gaussian mixture models
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 ...
A Variational Level Set Model Combined with FCMS for Image Clustering Segmentation
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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.
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.
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.
Image Restoration Based on the Hybrid Total-Variation-Type Model
Directory of Open Access Journals (Sweden)
Baoli Shi
2012-01-01
Full Text Available 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 L1-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 called the proximal point method (PPM is proposed and the convergence of the proposed method is proved. Some numerical results demonstrate the viability and efficiency of the proposed model and methods.
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.
Zheng, Qiang; Li, Honglun; Fan, Baode; Wu, Shuanhu; Xu, Jindong
2017-12-01
Active contour model (ACM) has been one of the most widely utilized methods in magnetic resonance (MR) brain image segmentation because of its ability of capturing topology changes. However, most of the existing ACMs only consider single-slice information in MR brain image data, i.e., the information used in ACMs based segmentation method is extracted only from one slice of MR brain image, which cannot take full advantage of the adjacent slice images' information, and cannot satisfy the local segmentation of MR brain images. In this paper, a novel ACM is proposed to solve the problem discussed above, which is based on multi-variate local Gaussian distribution and combines the adjacent slice images' information in MR brain image data to satisfy segmentation. The segmentation is finally achieved through maximizing the likelihood estimation. Experiments demonstrate the advantages of the proposed ACM over the single-slice ACM in local segmentation of MR brain image series.
International Nuclear Information System (INIS)
Park, Kyung Joo; Park, Jae Hyung; Lee, Hak Jong; Won, Hyung Jin; Lee, Dong Hyuk; Min, Byung Goo; Chang, Kee Hyun
1997-01-01
The image quality of magnetic resonance angiography (MRA) varies according to the imaging techniques applied and the parameters affected by blood flow patterns, as well as by the shape of the blood vessels. This study was designed to assess the influence on signal intensity and its distribution of the geometry of these vessels, the imaging parameters, and the concentration of contrast media in MRA of stenosis and aneurysm models. MRA was performed in stenosis and aneurysm models made of glass tubes, using pulsatile flow with viscosity and flow profile similar to those of blood. Slice and maximum intensity projection (MIP) images were obtained using various imaging techniques and parameters;there was variation in repetition time, flip angle, imaging planes, and concentrations of contrast media. On slice images of three-dimensional (3D) time-of-flight (TOF) techniques, flow signal intensity was measured at five locations in the models, and contrast ratio was calculated as the difference between flow signal intensity (SI) and background signal intensity (SIb) divided by background signal intensity or (SI-SIb)/SIb. MIP images obtained by various techniques and using various parameters were also analyzed, with emphasis in the stenosis model on demonstrated degree of stenosis, severity of signal void and image distortion, and in the aneurysm model, on degree of visualization, distortion of contour and distribution of signals. In 3D TOF, the shortest TR (36 msec) and the largest FA (50 deg ) resulted in the highest contrast ratio, but larger flip angles did not effectively demonstrate the demonstration of the peripheral part of the aneurysm. Loss of signal was most prominent in images of the stenosis model obtained with parallel or oblique planes to the flow direction. The two-dimensional TOF technique also caused signal void in stenosis, but precisely demonstrated the aneurysm, with dense opacification of the peripheral part. The phase contrast technique showed some
A Total Variation Model Based on the Strictly Convex Modification for Image Denoising
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Boying Wu
2014-01-01
Full Text Available We propose a strictly convex functional in which the regular term consists of the total variation term and an adaptive logarithm based convex modification term. We prove the existence and uniqueness of the minimizer for the proposed variational problem. The existence, uniqueness, and long-time behavior of the solution of the associated evolution system is also established. Finally, we present experimental results to illustrate the effectiveness of the model in noise reduction, and a comparison is made in relation to the more classical methods of the traditional total variation (TV, the Perona-Malik (PM, and the more recent D-α-PM method. Additional distinction from the other methods is that the parameters, for manual manipulation, in the proposed algorithm are reduced to basically only one.
Imaging Tumor Variation in Response to Photodynamic Therapy in Pancreatic Cancer Xenograft Models
International Nuclear Information System (INIS)
Samkoe, Kimberley S.; Chen, Alina; Rizvi, Imran; O'Hara, Julia A.; Hoopes, P. Jack; Pereira, Stephen P.; Hasan, Tayyaba; Pogue, Brian W.
2010-01-01
Purpose: A treatment monitoring study investigated the differential effects of orthotopic pancreatic cancer models in response to interstitial photodynamic therapy (PDT), and the validity of using magnetic resonance imaging as a surrogate measure of response was assessed. Methods and Materials: Different orthotopic pancreatic cancer xenograft models (AsPC-1 and Panc-1) were used to represent the range of pathophysiology observed in human beings. Identical dose escalation studies (10, 20, and 40J/cm) using interstitial verteporfin PDT were performed, and magnetic resonance imaging with T2-weighted and T1-weighted contrast were used to monitor the total tumor volume and the vascular perfusion volume, respectively. Results: There was a significant amount of necrosis in the slower-growing Panc-1 tumor using high light dose, although complete necrosis was not observed. Lower doses were required for the same level of tumor kill in the faster-growing AsPC-1 cell line. Conclusions: The tumor growth rate and vascular pattern of the tumor affect the optimal PDT treatment regimen, with faster-growing tumors being relatively easier to treat. This highlights the fact that therapy in human beings shows a heterogeneous range of outcomes, and suggests a need for careful individualized treatment outcomes assessment in clinical work.
Image denoising by a direct variational minimization
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Pilipović Stevan
2011-01-01
Full Text Available Abstract In this article we introduce a novel method for the image de-noising which combines a mathematically well-posdenes of the variational modeling with the efficiency of a patch-based approach in the field of image processing. It based on a direct minimization of an energy functional containing a minimal surface regularizer that uses fractional gradient. The minimization is obtained on every predefined patch of the image, independently. By doing so, we avoid the use of an artificial time PDE model with its inherent problems of finding optimal stopping time, as well as the optimal time step. Moreover, we control the level of image smoothing on each patch (and thus on the whole image by adapting the Lagrange multiplier using the information on the level of discontinuities on a particular patch, which we obtain by pre-processing. In order to reduce the average number of vectors in the approximation generator and still to obtain the minimal degradation, we combine a Ritz variational method for the actual minimization on a patch, and a complementary fractional variational principle. Thus, the proposed method becomes computationally feasible and applicable for practical purposes. We confirm our claims with experimental results, by comparing the proposed method with a couple of PDE-based methods, where we get significantly better denoising results specially on the oscillatory regions.
DEFF Research Database (Denmark)
Khan, A.; Zunino, Andrea; Deschamps, F.
2013-01-01
Here we discuss the nature of velocity heterogeneities seen in seismic tomography images of Earth's mantle whose origins and relation to thermochemical variations are yet to be understood. We illustrate this by inverting fundamental-mode and higher-order surface-wave phase velocities for radial....../Fe and Mg/Si values relative to surrounding mantle. Correlated herewith are thermal variations that closely follow surface tectonics. We also observe a strong contribution to lateral variations in structure and topography across the “410 km” seismic discontinuity from thermochemically induced phase......-wave tomography models with other regional models is encouraging. Radial anisotropy is strongest at 150/200 km depth beneath oceanic/continental areas, respectively, and appears weak and homogeneous below. Finally, geoid anomalies are computed for a subset of sampled model and compared to observations....
Fast magnetic resonance imaging based on high degree total variation
Wang, Sujie; Lu, Liangliang; Zheng, Junbao; Jiang, Mingfeng
2018-04-01
In order to eliminating the artifacts and "staircase effect" of total variation in Compressive Sensing MRI, high degree total variation model is proposed for dynamic MRI reconstruction. the high degree total variation regularization term is used as a constraint to reconstruct the magnetic resonance image, and the iterative weighted MM algorithm is proposed to solve the convex optimization problem of the reconstructed MR image model, In addtion, one set of cardiac magnetic resonance data is used to verify the proposed algorithm for MRI. The results show that the high degree total variation method has a better reconstruction effect than the total variation and the total generalized variation, which can obtain higher reconstruction SNR and better structural similarity.
Chen, Bo; Bian, Zhaoying; Zhou, Xiaohui; Chen, Wensheng; Ma, Jianhua; Liang, Zhengrong
2018-04-12
Total variation (TV) minimization for the sparse-view x-ray computer tomography (CT) reconstruction has been widely explored to reduce radiation dose. However, due to the piecewise constant assumption for the TV model, the reconstructed images often suffer from over-smoothness on the image edges. To mitigate this drawback of TV minimization, we present a Mumford-Shah total variation (MSTV) minimization algorithm in this paper. The presented MSTV model is derived by integrating TV minimization and Mumford-Shah segmentation. Subsequently, a penalized weighted least-squares (PWLS) scheme with MSTV is developed for the sparse-view CT reconstruction. For simplicity, the proposed algorithm is named as 'PWLS-MSTV.' To evaluate the performance of the present PWLS-MSTV algorithm, both qualitative and quantitative studies were conducted by using a digital XCAT phantom and a physical phantom. Experimental results show that the present PWLS-MSTV algorithm has noticeable gains over the existing algorithms in terms of noise reduction, contrast-to-ratio measure and edge-preservation.
Variational segmentation problems using prior knowledge in imaging and vision
DEFF Research Database (Denmark)
Fundana, Ketut
This dissertation addresses variational formulation of segmentation problems using prior knowledge. Variational models are among the most successful approaches for solving many Computer Vision and Image Processing problems. The models aim at finding the solution to a given energy functional defined......, prior knowledge is needed to obtain the desired solution. The introduction of shape priors in particular, has proven to be an effective way to segment objects of interests. Firstly, we propose a prior-based variational segmentation model to segment objects of interest in image sequences, that can deal....... Many objects have high variability in shape and orientation. This often leads to unsatisfactory results, when using a segmentation model with single shape template. One way to solve this is by using more sophisticated shape models. We propose to incorporate shape priors from a shape sub...
Variational methods in molecular modeling
2017-01-01
This book presents tutorial overviews for many applications of variational methods to molecular modeling. Topics discussed include the Gibbs-Bogoliubov-Feynman variational principle, square-gradient models, classical density functional theories, self-consistent-field theories, phase-field methods, Ginzburg-Landau and Helfrich-type phenomenological models, dynamical density functional theory, and variational Monte Carlo methods. Illustrative examples are given to facilitate understanding of the basic concepts and quantitative prediction of the properties and rich behavior of diverse many-body systems ranging from inhomogeneous fluids, electrolytes and ionic liquids in micropores, colloidal dispersions, liquid crystals, polymer blends, lipid membranes, microemulsions, magnetic materials and high-temperature superconductors. All chapters are written by leading experts in the field and illustrated with tutorial examples for their practical applications to specific subjects. With emphasis placed on physical unders...
Equilibrium models and variational inequalities
Konnov, Igor
2007-01-01
The concept of equilibrium plays a central role in various applied sciences, such as physics (especially, mechanics), economics, engineering, transportation, sociology, chemistry, biology and other fields. If one can formulate the equilibrium problem in the form of a mathematical model, solutions of the corresponding problem can be used for forecasting the future behavior of very complex systems and, also, for correcting the the current state of the system under control. This book presents a unifying look on different equilibrium concepts in economics, including several models from related sciences.- Presents a unifying look on different equilibrium concepts and also the present state of investigations in this field- Describes static and dynamic input-output models, Walras, Cassel-Wald, spatial price, auction market, oligopolistic equilibrium models, transportation and migration equilibrium models- Covers the basics of theory and solution methods both for the complementarity and variational inequality probl...
Variational Histogram Equalization for Single Color Image Defogging
Directory of Open Access Journals (Sweden)
Li Zhou
2016-01-01
Full Text Available Foggy images taken in the bad weather inevitably suffer from contrast loss and color distortion. Existing defogging methods merely resort to digging out an accurate scene transmission in ignorance of their unpleasing distortion and high complexity. Different from previous works, we propose a simple but powerful method based on histogram equalization and the physical degradation model. By revising two constraints in a variational histogram equalization framework, the intensity component of a fog-free image can be estimated in HSI color space, since the airlight is inferred through a color attenuation prior in advance. To cut down the time consumption, a general variation filter is proposed to obtain a numerical solution from the revised framework. After getting the estimated intensity component, it is easy to infer the saturation component from the physical degradation model in saturation channel. Accordingly, the fog-free image can be restored with the estimated intensity and saturation components. In the end, the proposed method is tested on several foggy images and assessed by two no-reference indexes. Experimental results reveal that our method is relatively superior to three groups of relevant and state-of-the-art defogging methods.
Blind image fusion for hyperspectral imaging with the directional total variation
Bungert, Leon; Coomes, David A.; Ehrhardt, Matthias J.; Rasch, Jennifer; Reisenhofer, Rafael; Schönlieb, Carola-Bibiane
2018-04-01
Hyperspectral imaging is a cutting-edge type of remote sensing used for mapping vegetation properties, rock minerals and other materials. A major drawback of hyperspectral imaging devices is their intrinsic low spatial resolution. In this paper, we propose a method for increasing the spatial resolution of a hyperspectral image by fusing it with an image of higher spatial resolution that was obtained with a different imaging modality. This is accomplished by solving a variational problem in which the regularization functional is the directional total variation. To accommodate for possible mis-registrations between the two images, we consider a non-convex blind super-resolution problem where both a fused image and the corresponding convolution kernel are estimated. Using this approach, our model can realign the given images if needed. Our experimental results indicate that the non-convexity is negligible in practice and that reliable solutions can be computed using a variety of different optimization algorithms. Numerical results on real remote sensing data from plant sciences and urban monitoring show the potential of the proposed method and suggests that it is robust with respect to the regularization parameters, mis-registration and the shape of the kernel.
A Variational Approach to Simultaneous Image Segmentation and Bias Correction.
Zhang, Kaihua; Liu, Qingshan; Song, Huihui; Li, Xuelong
2015-08-01
This paper presents a novel variational approach for simultaneous estimation of bias field and segmentation of images with intensity inhomogeneity. We model intensity of inhomogeneous objects to be Gaussian distributed with different means and variances, and then introduce a sliding window to map the original image intensity onto another domain, where the intensity distribution of each object is still Gaussian but can be better separated. The means of the Gaussian distributions in the transformed domain can be adaptively estimated by multiplying the bias field with a piecewise constant signal within the sliding window. A maximum likelihood energy functional is then defined on each local region, which combines the bias field, the membership function of the object region, and the constant approximating the true signal from its corresponding object. The energy functional is then extended to the whole image domain by the Bayesian learning approach. An efficient iterative algorithm is proposed for energy minimization, via which the image segmentation and bias field correction are simultaneously achieved. Furthermore, the smoothness of the obtained optimal bias field is ensured by the normalized convolutions without extra cost. Experiments on real images demonstrated the superiority of the proposed algorithm to other state-of-the-art representative methods.
Fractional Regularization Term for Variational Image Registration
Directory of Open Access Journals (Sweden)
Rafael Verdú-Monedero
2009-01-01
Full Text Available Image registration is a widely used task of image analysis with applications in many fields. Its classical formulation and current improvements are given in the spatial domain. In this paper a regularization term based on fractional order derivatives is formulated. This term is defined and implemented in the frequency domain by translating the energy functional into the frequency domain and obtaining the Euler-Lagrange equations which minimize it. The new regularization term leads to a simple formulation and design, being applicable to higher dimensions by using the corresponding multidimensional Fourier transform. The proposed regularization term allows for a real gradual transition from a diffusion registration to a curvature registration which is best suited to some applications and it is not possible in the spatial domain. Results with 3D actual images show the validity of this approach.
Total variation regularization in measurement and image space for PET reconstruction
Burger, M
2014-09-18
© 2014 IOP Publishing Ltd. The aim of this paper is to test and analyse a novel technique for image reconstruction in positron emission tomography, which is based on (total variation) regularization on both the image space and the projection space. We formulate our variational problem considering both total variation penalty terms on the image and on an idealized sinogram to be reconstructed from a given Poisson distributed noisy sinogram. We prove existence, uniqueness and stability results for the proposed model and provide some analytical insight into the structures favoured by joint regularization. For the numerical solution of the corresponding discretized problem we employ the split Bregman algorithm and extensively test the approach in comparison to standard total variation regularization on the image. The numerical results show that an additional penalty on the sinogram performs better on reconstructing images with thin structures.
Li, Chen; Yin, Xiaokang; Li, Zhen; Li, Wei; Chen, Guoming
2018-04-01
Capacitive imaging (CI) technique is a novel electromagnetic NDE technique. The Quasi-static electromagnetic field from the carefully designed electrode pair will vary when the electrical properties of the sample change, leading to the possibility of imaging. It is observed that for a given specimen, the targeted features appear as different variations in capacitive images under different experimental conditions. In some cases, even opposite variations occur, which brings confusion to indication interpretation. It is thus thought interesting to embark on investigations into the cause and effects of the negative variation phenomenon. In this work, the positive and negative variations were first explained from the measurement sensitivity distribution perspective. This was then followed by a detailed analysis using finite element models in COMSOL. A parametric experimental study on a glass fiber composite plate with artificial defects was then carried out to investigate how the experimental conditions affect the variation.
Modeling Per Capita State Health Expenditure Variat...
U.S. Department of Health & Human Services — Modeling Per Capita State Health Expenditure Variation State-Level Characteristics Matter, published in Volume 3, Issue 4, of the Medicare and Medicaid Research...
Total Variation and Tomographic Imaging from Projections
DEFF Research Database (Denmark)
Hansen, Per Christian; Jørgensen, Jakob Heide
2011-01-01
or 3D reconstruction from noisy projections. We demonstrate that for a small signal-to-noise ratio, this new approach allows us to compute better (i.e., more reliable) reconstructions than those obtained by classical methods. This is possible due to the use of the TV reconstruction model, which...
Efficient Variational Approaches for Deformable Registration of Images
Directory of Open Access Journals (Sweden)
Mehmet Ali Akinlar
2012-01-01
Full Text Available Dirichlet, anisotropic, and Huber regularization terms are presented for efficient registration of deformable images. Image registration, an ill-posed optimization problem, is solved using a gradient-descent-based method and some fundamental theorems in calculus of variations. Euler-Lagrange equations with homogeneous Neumann boundary conditions are obtained. These equations are discretized by multigrid and finite difference numerical techniques. The method is applied to the registration of brain MR images of size 65×65. Computational results indicate that the presented method is quite fast and efficient in the registration of deformable medical images.
Fractional-Order Total Variation Image Restoration Based on Primal-Dual Algorithm
Chen, Dali; Chen, YangQuan; Xue, Dingyu
2013-01-01
This paper proposes a fractional-order total variation image denoising algorithm based on the primal-dual method, which provides a much more elegant and effective way of treating problems of the algorithm implementation, ill-posed inverse, convergence rate, and blocky effect. The fractional-order total variation model is introduced by generalizing the first-order model, and the corresponding saddle-point and dual formulation are constructed in theory. In order to guarantee $O(1/{N}^{2})$ conv...
Adaptive Proximal Point Algorithms for Total Variation Image Restoration
Directory of Open Access Journals (Sweden)
Ying Chen
2015-02-01
Full Text Available Image restoration is a fundamental problem in various areas of imaging sciences. This paper presents a class of adaptive proximal point algorithms (APPA with contraction strategy for total variational image restoration. In each iteration, the proposed methods choose an adaptive proximal parameter matrix which is not necessary symmetric. In fact, there is an inner extrapolation in the prediction step, which is followed by a correction step for contraction. And the inner extrapolation is implemented by an adaptive scheme. By using the framework of contraction method, global convergence result and a convergence rate of O(1/N could be established for the proposed methods. Numerical results are reported to illustrate the efficiency of the APPA methods for solving total variation image restoration problems. Comparisons with the state-of-the-art algorithms demonstrate that the proposed methods are comparable and promising.
Modeling of Craniofacial Anatomy, Variation, and Growth
DEFF Research Database (Denmark)
Thorup, Signe Strann
The topic of this thesis is automatic analysis of craniofacial images with respect to changes due to growth and surgery, inter-subject variation and intracranial volume estimation. The methods proposed contribute to the knowledge about specific craniofacial anomalies, as well as provide a tool...... for detailed analyses for clinical and research purposes. Most of the applications in this thesis rely on non-rigid image registration by the means of warping one image into the coordinate system of another image. This warping results in a deformation field that describes the anatomical correspondence between......, thus creating a personalized atlas. The knowledge built into the atlas is e.g. location of anatomical regions and landmarks of importance to surgery planning and evaluation or population studies. With these correspondences, various analyses could be carried out e.g. quantification of growth, inter...
Naturalness and image quality : chroma and hue variation in color images of natural scenes
Ridder, de H.; Blommaert, F.J.J.; Fedorovskaya, E.A.; Rogowitz, B.E.; Allebach, J.P.
1995-01-01
The relation between perceptual image quality and naturalness was investigated by varying the colorfulness and hue of color images of natural scenes. These variations were created by digitizing the images, subsequently determining their color point distributions in the CIELUV color space and finally
Naturalness and image quality: Chroma and hue variation in color images of natural scenes
Ridder, de H.; Blommaert, F.J.J.; Fedorovskaya, E.A.; Eschbach, R.; Braun, K.
1997-01-01
The relation between perceptual image quality and natural ness was investigated by varying the colorfulness and hue of color images of natural scenes. These variations were created by digitizing the images, subsequently determining their color point distributions in the CIELUV color space and
Mixed Gaussian-Impulse Noise Image Restoration Via Total Variation
2012-05-01
deblurring under impulse noise ,” J. Math. Imaging Vis., vol. 36, pp. 46–53, January 2010. [5] B. Li, Q. Liu, J. Xu, and X. Luo, “A new method for removing......Several Total Variation (TV) regularization methods have recently been proposed to address denoising under mixed Gaussian and impulse noise . While
Li, Biyuan; Tang, Chen; Gao, Guannan; Chen, Mingming; Tang, Shuwei; Lei, Zhenkun
2017-06-01
Filtering off speckle noise from a fringe image is one of the key tasks in electronic speckle pattern interferometry (ESPI). In general, ESPI fringe images can be divided into three categories: low-density fringe images, high-density fringe images, and variable-density fringe images. In this paper, we first present a general filtering method based on variational image decomposition that can filter speckle noise for ESPI fringe images with various densities. In our method, a variable-density ESPI fringe image is decomposed into low-density fringes, high-density fringes, and noise. A low-density fringe image is decomposed into low-density fringes and noise. A high-density fringe image is decomposed into high-density fringes and noise. We give some suitable function spaces to describe low-density fringes, high-density fringes, and noise, respectively. Then we construct several models and numerical algorithms for ESPI fringe images with various densities. And we investigate the performance of these models via our extensive experiments. Finally, we compare our proposed models with the windowed Fourier transform method and coherence enhancing diffusion partial differential equation filter. These two methods may be the most effective filtering methods at present. Furthermore, we use the proposed method to filter a collection of the experimentally obtained ESPI fringe images with poor quality. The experimental results demonstrate the performance of our proposed method.
A Combined First and Second Order Variational Approach for Image Reconstruction
Papafitsoros, K.
2013-05-10
In this paper we study a variational problem in the space of functions of bounded Hessian. Our model constitutes a straightforward higher-order extension of the well known ROF functional (total variation minimisation) to which we add a non-smooth second order regulariser. It combines convex functions of the total variation and the total variation of the first derivatives. In what follows, we prove existence and uniqueness of minimisers of the combined model and present the numerical solution of the corresponding discretised problem by employing the split Bregman method. The paper is furnished with applications of our model to image denoising, deblurring as well as image inpainting. The obtained numerical results are compared with results obtained from total generalised variation (TGV), infimal convolution and Euler\\'s elastica, three other state of the art higher-order models. The numerical discussion confirms that the proposed higher-order model competes with models of its kind in avoiding the creation of undesirable artifacts and blocky-like structures in the reconstructed images-a known disadvantage of the ROF model-while being simple and efficiently numerically solvable. ©Springer Science+Business Media New York 2013.
Delay Variation Model with Two Service Queues
Directory of Open Access Journals (Sweden)
Filip Rezac
2010-01-01
Full Text Available Delay in VoIP technology is very unpleasant issue and therefore a voice packets prioritization must be ensured. To maintain the high call quality a maximum information delivery time from the sender to the recipient is set to 150 ms. This paper focuses on the design of a mathematical model of end-to-end delay of a VoIP connection, in particular on a delay variation. It describes all partial delay components and mechanisms, their generation, facilities and mathematical formulations. A new approach to the delay variation model is presented and its validation has been done by experimention.
Variational approach to chiral quark models
Energy Technology Data Exchange (ETDEWEB)
Futami, Yasuhiko; Odajima, Yasuhiko; Suzuki, Akira
1987-03-01
A variational approach is applied to a chiral quark model to test the validity of the perturbative treatment of the pion-quark interaction based on the chiral symmetry principle. It is indispensably related to the chiral symmetry breaking radius if the pion-quark interaction can be regarded as a perturbation.
A variational approach to chiral quark models
International Nuclear Information System (INIS)
Futami, Yasuhiko; Odajima, Yasuhiko; Suzuki, Akira.
1987-01-01
A variational approach is applied to a chiral quark model to test the validity of the perturbative treatment of the pion-quark interaction based on the chiral symmetry principle. It is indispensably related to the chiral symmetry breaking radius if the pion-quark interaction can be regarded as a perturbation. (author)
An algorithm for total variation regularized photoacoustic imaging
DEFF Research Database (Denmark)
Dong, Yiqiu; Görner, Torsten; Kunis, Stefan
2014-01-01
Recovery of image data from photoacoustic measurements asks for the inversion of the spherical mean value operator. In contrast to direct inversion methods for specific geometries, we consider a semismooth Newton scheme to solve a total variation regularized least squares problem. During the iter......Recovery of image data from photoacoustic measurements asks for the inversion of the spherical mean value operator. In contrast to direct inversion methods for specific geometries, we consider a semismooth Newton scheme to solve a total variation regularized least squares problem. During...... the iteration, each matrix vector multiplication is realized in an efficient way using a recently proposed spectral discretization of the spherical mean value operator. All theoretical results are illustrated by numerical experiments....
Learning-based stochastic object models for characterizing anatomical variations
Dolly, Steven R.; Lou, Yang; Anastasio, Mark A.; Li, Hua
2018-03-01
It is widely known that the optimization of imaging systems based on objective, task-based measures of image quality via computer-simulation requires the use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in human anatomy within a specified ensemble of patients remains a challenging task. Previously reported numerical anatomic models lack the ability to accurately model inter-patient and inter-organ variations in human anatomy among a broad patient population, mainly because they are established on image data corresponding to a few of patients and individual anatomic organs. This may introduce phantom-specific bias into computer-simulation studies, where the study result is heavily dependent on which phantom is used. In certain applications, however, databases of high-quality volumetric images and organ contours are available that can facilitate this SOM development. In this work, a novel and tractable methodology for learning a SOM and generating numerical phantoms from a set of volumetric training images is developed. The proposed methodology learns geometric attribute distributions (GAD) of human anatomic organs from a broad patient population, which characterize both centroid relationships between neighboring organs and anatomic shape similarity of individual organs among patients. By randomly sampling the learned centroid and shape GADs with the constraints of the respective principal attribute variations learned from the training data, an ensemble of stochastic objects can be created. The randomness in organ shape and position reflects the learned variability of human anatomy. To demonstrate the methodology, a SOM of an adult male pelvis is computed and examples of corresponding numerical phantoms are created.
Modeling response variation for radiometric calorimeters
International Nuclear Information System (INIS)
Mayer, R.L. II.
1986-01-01
Radiometric calorimeters are widely used in the DOE complex for accountability measurements of plutonium and tritium. Proper characterization of response variation for these instruments is, therefore, vital for accurate assessment of measurement control as well as for propagation of error calculations. This is not difficult for instruments used to measure items within a narrow range of power values; however, when a single instrument is used to measure items over a wide range of power values, improper estimates of uncertainty can result since traditional error models for radiometric calorimeters assume that uncertainty is not a function of sample power. This paper describes methods which can be used to accurately estimate random response variation for calorimeters used to measure items over a wide range of sample powers. The model is applicable to the two most common modes of calorimeter operation: heater replacement and servo control. 5 refs., 4 figs., 1 tab
Variational multiscale models for charge transport.
Wei, Guo-Wei; Zheng, Qiong; Chen, Zhan; Xia, Kelin
2012-01-01
This work presents a few variational multiscale models for charge transport in complex physical, chemical and biological systems and engineering devices, such as fuel cells, solar cells, battery cells, nanofluidics, transistors and ion channels. An essential ingredient of the present models, introduced in an earlier paper (Bulletin of Mathematical Biology, 72, 1562-1622, 2010), is the use of differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain from the microscopic domain, meanwhile, dynamically couple discrete and continuum descriptions. Our main strategy is to construct the total energy functional of a charge transport system to encompass the polar and nonpolar free energies of solvation, and chemical potential related energy. By using the Euler-Lagrange variation, coupled Laplace-Beltrami and Poisson-Nernst-Planck (LB-PNP) equations are derived. The solution of the LB-PNP equations leads to the minimization of the total free energy, and explicit profiles of electrostatic potential and densities of charge species. To further reduce the computational complexity, the Boltzmann distribution obtained from the Poisson-Boltzmann (PB) equation is utilized to represent the densities of certain charge species so as to avoid the computationally expensive solution of some Nernst-Planck (NP) equations. Consequently, the coupled Laplace-Beltrami and Poisson-Boltzmann-Nernst-Planck (LB-PBNP) equations are proposed for charge transport in heterogeneous systems. A major emphasis of the present formulation is the consistency between equilibrium LB-PB theory and non-equilibrium LB-PNP theory at equilibrium. Another major emphasis is the capability of the reduced LB-PBNP model to fully recover the prediction of the LB-PNP model at non-equilibrium settings. To account for the fluid impact on the charge transport, we derive coupled Laplace-Beltrami, Poisson-Nernst-Planck and Navier-Stokes equations from the variational principle
Variational multiscale models for charge transport
Wei, Guo-Wei; Zheng, Qiong; Chen, Zhan; Xia, Kelin
2012-01-01
This work presents a few variational multiscale models for charge transport in complex physical, chemical and biological systems and engineering devices, such as fuel cells, solar cells, battery cells, nanofluidics, transistors and ion channels. An essential ingredient of the present models, introduced in an earlier paper (Bulletin of Mathematical Biology, 72, 1562-1622, 2010), is the use of differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain from the microscopic domain, meanwhile, dynamically couple discrete and continuum descriptions. Our main strategy is to construct the total energy functional of a charge transport system to encompass the polar and nonpolar free energies of solvation, and chemical potential related energy. By using the Euler-Lagrange variation, coupled Laplace-Beltrami and Poisson-Nernst-Planck (LB-PNP) equations are derived. The solution of the LB-PNP equations leads to the minimization of the total free energy, and explicit profiles of electrostatic potential and densities of charge species. To further reduce the computational complexity, the Boltzmann distribution obtained from the Poisson-Boltzmann (PB) equation is utilized to represent the densities of certain charge species so as to avoid the computationally expensive solution of some Nernst-Planck (NP) equations. Consequently, the coupled Laplace-Beltrami and Poisson-Boltzmann-Nernst-Planck (LB-PBNP) equations are proposed for charge transport in heterogeneous systems. A major emphasis of the present formulation is the consistency between equilibrium LB-PB theory and non-equilibrium LB-PNP theory at equilibrium. Another major emphasis is the capability of the reduced LB-PBNP model to fully recover the prediction of the LB-PNP model at non-equilibrium settings. To account for the fluid impact on the charge transport, we derive coupled Laplace-Beltrami, Poisson-Nernst-Planck and Navier-Stokes equations from the variational principle
Rosenkrantz, Andrew B; Hughes, Danny R; Duszak, Richard
2015-10-01
The purpose of this study was to assess state-level trends in per beneficiary Medicare spending on medical imaging. Medicare part B 5% research identifiable files from 2004 through 2012 were used to compute national and state-by-state annual average per beneficiary spending on imaging. State-to-state geographic variation and temporal trends were analyzed. National average per beneficiary Medicare part B spending on imaging increased 7.8% annually between 2004 ($350.54) and its peak in 2006 ($405.41) then decreased 4.4% annually between 2006 and 2012 ($298.63). In 2012, annual per beneficiary spending was highest in Florida ($367.25) and New York ($355.67) and lowest in Ohio ($67.08) and Vermont ($72.78). Maximum state-to-state geographic variation increased over time, with the ratio of highest-spending state to lowest-spending state increasing from 4.0 in 2004 to 5.5 in 2012. Spending in nearly all states decreased since peaks in 2005 (six states) or 2006 (43 states). The average annual decrease among states was 5.1% ± 1.8% (range, 1.2-12.2%) The largest decrease was in Ohio. In only two states did per beneficiary spending increase (Maryland, 12.5% average annual increase since 2005; Oregon, 4.8% average annual increase since 2008). Medicare part B average per beneficiary spending on medical imaging declined in nearly every state since 2005 and 2006 peaks, abruptly reversing previously reported trends. Spending continued to increase, however, in Maryland and Oregon. Identification of state-level variation may facilitate future investigation of the potential effect of specific and regional changes in spending on patient access and outcomes.
Variational approach for restoring blurred images with cauchy noise
DEFF Research Database (Denmark)
Sciacchitano, Federica; Dong, Yiqiu; Zeng, Tieyong
2015-01-01
model, we add a quadratic penalty term, which guarantees the uniqueness of the solution. Due to the convexity of our model, the primal dual algorithm is employed to solve the minimization problem. Experimental results show the effectiveness of the proposed method for simultaneously deblurring...... and denoising images corrupted by Cauchy noise. Comparison with other existing and well-known methods is provided as well....
Total variation superiorized conjugate gradient method for image reconstruction
Zibetti, Marcelo V. W.; Lin, Chuan; Herman, Gabor T.
2018-03-01
The conjugate gradient (CG) method is commonly used for the relatively-rapid solution of least squares problems. In image reconstruction, the problem can be ill-posed and also contaminated by noise; due to this, approaches such as regularization should be utilized. Total variation (TV) is a useful regularization penalty, frequently utilized in image reconstruction for generating images with sharp edges. When a non-quadratic norm is selected for regularization, as is the case for TV, then it is no longer possible to use CG. Non-linear CG is an alternative, but it does not share the efficiency that CG shows with least squares and methods such as fast iterative shrinkage-thresholding algorithms (FISTA) are preferred for problems with TV norm. A different approach to including prior information is superiorization. In this paper it is shown that the conjugate gradient method can be superiorized. Five different CG variants are proposed, including preconditioned CG. The CG methods superiorized by the total variation norm are presented and their performance in image reconstruction is demonstrated. It is illustrated that some of the proposed variants of the superiorized CG method can produce reconstructions of superior quality to those produced by FISTA and in less computational time, due to the speed of the original CG for least squares problems. In the Appendix we examine the behavior of one of the superiorized CG methods (we call it S-CG); one of its input parameters is a positive number ɛ. It is proved that, for any given ɛ that is greater than the half-squared-residual for the least squares solution, S-CG terminates in a finite number of steps with an output for which the half-squared-residual is less than or equal to ɛ. Importantly, it is also the case that the output will have a lower value of TV than what would be provided by unsuperiorized CG for the same value ɛ of the half-squared residual.
Parallel algorithm of real-time infrared image restoration based on total variation theory
Zhu, Ran; Li, Miao; Long, Yunli; Zeng, Yaoyuan; An, Wei
2015-10-01
Image restoration is a necessary preprocessing step for infrared remote sensing applications. Traditional methods allow us to remove the noise but penalize too much the gradients corresponding to edges. Image restoration techniques based on variational approaches can solve this over-smoothing problem for the merits of their well-defined mathematical modeling of the restore procedure. The total variation (TV) of infrared image is introduced as a L1 regularization term added to the objective energy functional. It converts the restoration process to an optimization problem of functional involving a fidelity term to the image data plus a regularization term. Infrared image restoration technology with TV-L1 model exploits the remote sensing data obtained sufficiently and preserves information at edges caused by clouds. Numerical implementation algorithm is presented in detail. Analysis indicates that the structure of this algorithm can be easily implemented in parallelization. Therefore a parallel implementation of the TV-L1 filter based on multicore architecture with shared memory is proposed for infrared real-time remote sensing systems. Massive computation of image data is performed in parallel by cooperating threads running simultaneously on multiple cores. Several groups of synthetic infrared image data are used to validate the feasibility and effectiveness of the proposed parallel algorithm. Quantitative analysis of measuring the restored image quality compared to input image is presented. Experiment results show that the TV-L1 filter can restore the varying background image reasonably, and that its performance can achieve the requirement of real-time image processing.
Variational study of the pair hopping model
International Nuclear Information System (INIS)
Fazekas, P.
1990-01-01
We study the ground state of a Hamiltonian introduced by Kolb and Penson for modelling situations in which small electron pairs are formed. The Hamiltonian consists of a tight binding band term, and a term describing the nearest neighbour hopping of electron pairs. We give a Gutzwiller-type variational treatment, first with a single-parameter Ansatz treated in the single site Gutzwiller approximation, and then with more complicated trial wave functions, and an improved Gutzwiller approximation. The calculation yields a transition from a partially paired normal state, in which the spin susceptibility has a diminished value, into a fully paired state. (author). 16 refs, 2 figs
A new level set model for cell image segmentation
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.
Modeling Individual Cyclic Variation in Human Behavior.
Pierson, Emma; Althoff, Tim; Leskovec, Jure
2018-04-01
Cycles are fundamental to human health and behavior. Examples include mood cycles, circadian rhythms, and the menstrual cycle. However, modeling cycles in time series data is challenging because in most cases the cycles are not labeled or directly observed and need to be inferred from multidimensional measurements taken over time. Here, we present Cyclic Hidden Markov Models (CyH-MMs) for detecting and modeling cycles in a collection of multidimensional heterogeneous time series data. In contrast to previous cycle modeling methods, CyHMMs deal with a number of challenges encountered in modeling real-world cycles: they can model multivariate data with both discrete and continuous dimensions; they explicitly model and are robust to missing data; and they can share information across individuals to accommodate variation both within and between individual time series. Experiments on synthetic and real-world health-tracking data demonstrate that CyHMMs infer cycle lengths more accurately than existing methods, with 58% lower error on simulated data and 63% lower error on real-world data compared to the best-performing baseline. CyHMMs can also perform functions which baselines cannot: they can model the progression of individual features/symptoms over the course of the cycle, identify the most variable features, and cluster individual time series into groups with distinct characteristics. Applying CyHMMs to two real-world health-tracking datasets-of human menstrual cycle symptoms and physical activity tracking data-yields important insights including which symptoms to expect at each point during the cycle. We also find that people fall into several groups with distinct cycle patterns, and that these groups differ along dimensions not provided to the model. For example, by modeling missing data in the menstrual cycles dataset, we are able to discover a medically relevant group of birth control users even though information on birth control is not given to the model.
Durand, Sylvain; Frapart, Yves-Michel; Kerebel, Maud
2017-11-01
Spatial electron paramagnetic resonance imaging (EPRI) is a recent method to localize and characterize free radicals in vivo or in vitro, leading to applications in material and biomedical sciences. To improve the quality of the reconstruction obtained by EPRI, a variational method is proposed to inverse the image formation model. It is based on a least-square data-fidelity term and the total variation and Besov seminorm for the regularization term. To fully comprehend the Besov seminorm, an implementation using the curvelet transform and the L 1 norm enforcing the sparsity is proposed. It allows our model to reconstruct both image where acquisition information are missing and image with details in textured areas, thus opening possibilities to reduce acquisition times. To implement the minimization problem using the algorithm developed by Chambolle and Pock, a thorough analysis of the direct model is undertaken and the latter is inverted while avoiding the use of filtered backprojection (FBP) and of non-uniform Fourier transform. Numerical experiments are carried out on simulated data, where the proposed model outperforms both visually and quantitatively the classical model using deconvolution and FBP. Improved reconstructions on real data, acquired on an irradiated distal phalanx, were successfully obtained.
Bayesian Image Restoration Using a Large-Scale Total Patch Variation Prior
Directory of Open Access Journals (Sweden)
Yang Chen
2011-01-01
Full Text Available Edge-preserving Bayesian restorations using nonquadratic priors are often inefficient in restoring continuous variations and tend to produce block artifacts around edges in ill-posed inverse image restorations. To overcome this, we have proposed a spatial adaptive (SA prior with improved performance. However, this SA prior restoration suffers from high computational cost and the unguaranteed convergence problem. Concerning these issues, this paper proposes a Large-scale Total Patch Variation (LS-TPV Prior model for Bayesian image restoration. In this model, the prior for each pixel is defined as a singleton conditional probability, which is in a mixture prior form of one patch similarity prior and one weight entropy prior. A joint MAP estimation is thus built to ensure the iteration monotonicity. The intensive calculation of patch distances is greatly alleviated by the parallelization of Compute Unified Device Architecture(CUDA. Experiments with both simulated and real data validate the good performance of the proposed restoration.
Zhou, Li; Bi, Du-Yan; He, Lin-Yuan
2015-01-01
The visibility of images captured in foggy conditions is impaired severely by a decrease in the contrasts of objects and veiling with a characteristic gray hue, which may limit the performance of visual applications out of doors. Contrast enhancement together with color restoration is a challenging mission for conventional fog-removal methods, as the degrading effect of fog is largely dependent on scene depth information. Nowadays, people change their minds by establishing a variational framework for contrast enhancement based on a physically based analytical model, unexpectedly resulting in color distortion, dark-patch distortion, or fuzzy features of local regions. Unlike previous work, our method treats an atmospheric veil as a scattering disturbance and formulates a foggy image as an energy functional minimization to estimate direct attenuation, originating from the work of image denoising. In addition to a global contrast measurement based on a total variation norm, an additional local measurement is designed in that optimal problem for the purpose of digging out more local details as well as suppressing dark-patch distortion. Moreover, we estimate the airlight precisely by maximization with a geometric constraint and a natural image prior in order to protect the faithfulness of the scene color. With the estimated direct attenuation and airlight, the fog-free image can be restored. Finally, our method is tested on several benchmark and realistic images evaluated by two assessment approaches. The experimental results imply that our proposed method works well compared with the state-of-the-art defogging methods.
Diagnostic difficulties resulting from morphological image variation in spondylodiscitis MR imaging
International Nuclear Information System (INIS)
Dziurzyńska-Białek, Ewa; Kruk-Bachonko, Joanna; Guz, Wiesław; Łosicki, Marek; Krupski, Witold
2012-01-01
Spinal infection (discitis; spondylodiscitis) presents a wide spectrum of pathologies. The method of choice for spondylodiscitis imaging is magnetic resonance (MR). It provides detailed anatomical information, especially concerning epidural space and spinal cord. The main aim of this article is the description and evaluation of spondylodiscitis morphological variation visible in magnetic resonance imaging. In this article we retrospectively analysed the patients diagnosed at the Department of Radiology of the Provincial Hospital No 2 in Rzeszów between October 2009 and October 2011. The subjects involved a group of five women aged 41–74 (mean 56.3 years) and eight men aged 46–69 (mean 61,3 years). All patients had spondylodiscitis symptoms. All patients underwent MRI examination before and after the contrast enhancement. In three patients additional CT examination was performed. Following the MRI procedure all patients were diagnosed with typical symptoms of spondylodiscitis. It also revealed a number of pathologies resulting from morphological spondylodiscitis variation. Other pathologies found on the MR images of the study group patients involved epidural intra-canal spinal pathological masses causing spinal cord compression, lung abscess, pyothorax, paravertebral abscesses and epidural empyemas, abscess between adjacent vertebral bodies, abscesses beneath anterior longitudinal ligament, and iliopsoas muscle abscesses. In all cases a destruction of vertebral bodies with end plates loss restriction and cortical layer discontinuity was observed. Moreover, one person was diagnosed with pathological vertebral body fractures and liquefactive necrosis of the vertebral body. Spondylodiscitis manifests itself in a great number of morphological variations visible on the radiological images. Apart from ordinary features of vertebral bodies and discs, progressive spinal destruction is observed together with reactive bone changes and soft tissue infiltration. The latter
Regional variation in Medicare payments for medical imaging: radiologists versus nonradiologists.
Rosman, David A; Nsiah, Eugene; Hughes, Danny R; Duszak, Richard
2015-05-01
The purpose of this article was to study regional variation in Medicare Physician Fee Schedule (MPFS) payments for medical imaging to radiologists compared with nonradiologists. Using a 5% random sample of all Medicare enrollees, which covered approximately 2.5 million Part B beneficiaries in 2011, total professional-only, technical-only, and global MPFS spending was calculated on a state-by-state and United States Census Bureau regional basis for all Medicare Berenson-Eggers Type of Service-defined medical imaging services. Payments to radiologists versus nonradiologists were identified and variation was analyzed. Nationally, mean MPFS medical imaging spending per Medicare beneficiary was $207.17 ($95.71 [46.2%] to radiologists vs $111.46 [53.8%] to nonradiologists). Of professional-only (typically interpretation) payments, 20.6% went to nonradiologists. Of technical-only (typically owned equipment) payments, 84.9% went to nonradiologists. Of global (both professional and technical) payments, 70.1% went to nonradiologists. The percentage of MPFS medical imaging spending on nonradiologists ranged from 32% (Minnesota) to 69.5% (South Carolina). The percentage of MPFS payments for medical imaging to nonradiologists exceeded those to radiologists in 58.8% of states. The relative percentage of MPFS payments to nonradiologists was highest in the South (58.5%) and lowest in the Northeast (48.0%). Nationally, 53.8% of MPFS payments for medical imaging services are made to nonradiologists, who claim a majority of MPFS payments in most states dominated by noninterpretive payments. This majority spending on nonradiologists may have implications in bundled and capitated payment models for radiology services. Medical imaging payment policy initiatives must consider the roles of all provider groups and associated regional variation.
Variational Level Set Method for Two-Stage Image Segmentation Based on Morphological Gradients
Directory of Open Access Journals (Sweden)
Zemin Ren
2014-01-01
Full Text Available We use variational level set method and transition region extraction techniques to achieve image segmentation task. The proposed scheme is done by two steps. We first develop a novel algorithm to extract transition region based on the morphological gradient. After this, we integrate the transition region into a variational level set framework and develop a novel geometric active contour model, which include an external energy based on transition region and fractional order edge indicator function. The external energy is used to drive the zero level set toward the desired image features, such as object boundaries. Due to this external energy, the proposed model allows for more flexible initialization. The fractional order edge indicator function is incorporated into the length regularization term to diminish the influence of noise. Moreover, internal energy is added into the proposed model to penalize the deviation of the level set function from a signed distance function. The results evolution of the level set function is the gradient flow that minimizes the overall energy functional. The proposed model has been applied to both synthetic and real images with promising results.
Glomus Tumors: Symptom Variations and Magnetic Resonance Imaging for Diagnosis
Directory of Open Access Journals (Sweden)
Ki Weon Ham
2013-07-01
Full Text Available Background The typical clinical symptoms of glomus tumors are pain, tenderness, and sensitivity to temperature change, and the presence of these clinical findings is helpful in diagnosis. However, the tumors often pose diagnostic difficulty because of variations in presentation and the nonspecific symptoms of glomus tumors. To the best of our knowledge, few studies have reported on the usefulness of magnetic resonance imaging (MRI in diagnosing glomus tumors in patients with unspecific symptoms.Methods The inclusion criteria of this study were: having undergone surgery for subungual glomus tumor of the hand, histopathologic confirmation of glomus tumor, and having undergone preoperative MRI. Twenty-one patients were enrolled. The characteristics of the tumors and the presenting symptoms including pain, tenderness, and sensitivity to temperature change were retrospectively reviewed.Results Five out of 21 patients (23% did not show the typical glomus tumor symptom triad because they did not complain of pain provoked by coldness. Nevertheless, preoperative MRI showed well-defined small soft-tissue lesions on T1- and T2-weighted images, which are typical findings of glomus tumors. The tumors were completely resected and confirmed as glomus tumor histopathologically.Conclusions Early occult lesions of glomus tumor in the hand may not be revealed by physical examination because of their barely detectable symptoms. Moreover, subungual lesions may be particularly difficult to evaluate on physical examination. Our cases showed that MRI offers excellent diagnostic information in clinically undiagnosed or misdiagnosed patients. Preoperative MRI can accurately define the character and extent of glomus tumor, even though it is impalpable and invisible.
Glomus Tumors: Symptom Variations and Magnetic Resonance Imaging for Diagnosis
Directory of Open Access Journals (Sweden)
Ki Weon Ham
2013-07-01
Full Text Available BackgroundThe typical clinical symptoms of glomus tumors are pain, tenderness, and sensitivity to temperature change, and the presence of these clinical findings is helpful in diagnosis. However, the tumors often pose diagnostic difficulty because of variations in presentation and the nonspecific symptoms of glomus tumors. To the best of our knowledge, few studies have reported on the usefulness of magnetic resonance imaging (MRI in diagnosing glomus tumors in patients with unspecific symptoms.MethodsThe inclusion criteria of this study were: having undergone surgery for subungual glomus tumor of the hand, histopathologic confirmation of glomus tumor, and having undergone preoperative MRI. Twenty-one patients were enrolled. The characteristics of the tumors and the presenting symptoms including pain, tenderness, and sensitivity to temperature change were retrospectively reviewed.ResultsFive out of 21 patients (23% did not show the typical glomus tumor symptom triad because they did not complain of pain provoked by coldness. Nevertheless, preoperative MRI showed well-defined small soft-tissue lesions on T1- and T2-weighted images, which are typical findings of glomus tumors. The tumors were completely resected and confirmed as glomus tumor histopathologically.ConclusionsEarly occult lesions of glomus tumor in the hand may not be revealed by physical examination because of their barely detectable symptoms. Moreover, subungual lesions may be particularly difficult to evaluate on physical examination. Our cases showed that MRI offers excellent diagnostic information in clinically undiagnosed or misdiagnosed patients. Preoperative MRI can accurately define the character and extent of glomus tumor, even though it is impalpable and invisible.
2016-05-01
norm does not cap - ture the geometry completely. The L1−L2 in (c) does a better job than TV while L1 in (b) and L1−0.5L2 in (d) capture the squares most...and isotropic total variation (TV) norms into a relaxed formu- lation of the two phase Mumford-Shah (MS) model for image segmentation. We show...results exceeding those obtained by the MS model when using the standard TV norm to regular- ize partition boundaries. In particular, examples illustrating
Statistical model for OCT image denoising
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.
Directory of Open Access Journals (Sweden)
Rubing Xi
2014-01-01
Full Text Available The variational models with nonlocal regularization offer superior image restoration quality over traditional method. But the processing speed remains a bottleneck due to the calculation quantity brought by the recent iterative algorithms. In this paper, a fast algorithm is proposed to restore the multichannel image in the presence of additive Gaussian noise by minimizing an energy function consisting of an l2-norm fidelity term and a nonlocal vectorial total variational regularization term. This algorithm is based on the variable splitting and penalty techniques in optimization. Following our previous work on the proof of the existence and the uniqueness of the solution of the model, we establish and prove the convergence properties of this algorithm, which are the finite convergence for some variables and the q-linear convergence for the rest. Experiments show that this model has a fabulous texture-preserving property in restoring color images. Both the theoretical derivation of the computation complexity analysis and the experimental results show that the proposed algorithm performs favorably in comparison to the widely used fixed point algorithm.
A variational void coalescence model for ductile metals
Siddiq, Amir; Arciniega, Roman; El Sayed, Tamer
2011-01-01
We present a variational void coalescence model that includes all the essential ingredients of failure in ductile porous metals. The model is an extension of the variational void growth model by Weinberg et al. (Comput Mech 37:142-152, 2006
Directory of Open Access Journals (Sweden)
Kweon-Ho Nam
Full Text Available Despite considerable research efforts on the relationship between arterial geometry and cardiovascular pathology, information is lacking on the pulsatile geometrical variation caused by arterial distensibility and cardiomotility because of the lack of suitable in vivo experimental models and the methodological difficulties in examining the arterial dynamics. We aimed to investigate the feasibility of using a chick embryo system as an experimental model for basic research on the pulsatile variation of arterial geometry. Optical microscope video images of various arterial shapes in chick chorioallantoic circulation were recorded from different locations and different embryo samples. The high optical transparency of the chorioallantoic membrane (CAM allowed clear observation of tiny vessels and their movements. Systolic and diastolic changes in arterial geometry were visualized by detecting the wall boundaries from binary images. Several to hundreds of microns of wall displacement variations were recognized during a pulsatile cycle. The spatial maps of the wall motion harmonics and magnitude ratio of harmonic components were obtained by analyzing the temporal brightness variation at each pixel in sequential grayscale images using spectral analysis techniques. The local variations in the spectral characteristics of the arterial wall motion were reflected well in the analysis results. In addition, mapping the phase angle of the fundamental frequency identified the regional variations in the wall motion directivity and phase shift. Regional variations in wall motion phase angle and fundamental-to-second harmonic ratio were remarkable near the bifurcation area. In summary, wall motion in various arterial geometry including straight, curved and bifurcated shapes was well observed in the CAM artery model, and their local and cyclic variations could be characterized by Fourier and wavelet transforms of the acquired video images. The CAM artery model with
Sparse linear models: Variational approximate inference and Bayesian experimental design
International Nuclear Information System (INIS)
Seeger, Matthias W
2009-01-01
A wide range of problems such as signal reconstruction, denoising, source separation, feature selection, and graphical model search are addressed today by posterior maximization for linear models with sparsity-favouring prior distributions. The Bayesian posterior contains useful information far beyond its mode, which can be used to drive methods for sampling optimization (active learning), feature relevance ranking, or hyperparameter estimation, if only this representation of uncertainty can be approximated in a tractable manner. In this paper, we review recent results for variational sparse inference, and show that they share underlying computational primitives. We discuss how sampling optimization can be implemented as sequential Bayesian experimental design. While there has been tremendous recent activity to develop sparse estimation, little attendance has been given to sparse approximate inference. In this paper, we argue that many problems in practice, such as compressive sensing for real-world image reconstruction, are served much better by proper uncertainty approximations than by ever more aggressive sparse estimation algorithms. Moreover, since some variational inference methods have been given strong convex optimization characterizations recently, theoretical analysis may become possible, promising new insights into nonlinear experimental design.
Sparse linear models: Variational approximate inference and Bayesian experimental design
Energy Technology Data Exchange (ETDEWEB)
Seeger, Matthias W [Saarland University and Max Planck Institute for Informatics, Campus E1.4, 66123 Saarbruecken (Germany)
2009-12-01
A wide range of problems such as signal reconstruction, denoising, source separation, feature selection, and graphical model search are addressed today by posterior maximization for linear models with sparsity-favouring prior distributions. The Bayesian posterior contains useful information far beyond its mode, which can be used to drive methods for sampling optimization (active learning), feature relevance ranking, or hyperparameter estimation, if only this representation of uncertainty can be approximated in a tractable manner. In this paper, we review recent results for variational sparse inference, and show that they share underlying computational primitives. We discuss how sampling optimization can be implemented as sequential Bayesian experimental design. While there has been tremendous recent activity to develop sparse estimation, little attendance has been given to sparse approximate inference. In this paper, we argue that many problems in practice, such as compressive sensing for real-world image reconstruction, are served much better by proper uncertainty approximations than by ever more aggressive sparse estimation algorithms. Moreover, since some variational inference methods have been given strong convex optimization characterizations recently, theoretical analysis may become possible, promising new insights into nonlinear experimental design.
A variational ensemble scheme for noisy image data assimilation
Yang, Yin; Robinson, Cordelia; Heitz, Dominique; Mémin, Etienne
2014-05-01
Data assimilation techniques aim at recovering a system state variables trajectory denoted as X, along time from partially observed noisy measurements of the system denoted as Y. These procedures, which couple dynamics and noisy measurements of the system, fulfill indeed a twofold objective. On one hand, they provide a denoising - or reconstruction - procedure of the data through a given model framework and on the other hand, they provide estimation procedures for unknown parameters of the dynamics. A standard variational data assimilation problem can be formulated as the minimization of the following objective function with respect to the initial discrepancy, η, from the background initial guess: δ« J(η(x)) = 1∥Xb (x) - X (t ,x)∥2 + 1 tf∥H(X (t,x ))- Y (t,x)∥2dt. 2 0 0 B 2 t0 R (1) where the observation operator H links the state variable and the measurements. The cost function can be interpreted as the log likelihood function associated to the a posteriori distribution of the state given the past history of measurements and the background. In this work, we aim at studying ensemble based optimal control strategies for data assimilation. Such formulation nicely combines the ingredients of ensemble Kalman filters and variational data assimilation (4DVar). It is also formulated as the minimization of the objective function (1), but similarly to ensemble filter, it introduces in its objective function an empirical ensemble-based background-error covariance defined as: B ≡ )(Xb - )T>. (2) Thus, it works in an off-line smoothing mode rather than on the fly like sequential filters. Such resulting ensemble variational data assimilation technique corresponds to a relatively new family of methods [1,2,3]. It presents two main advantages: first, it does not require anymore to construct the adjoint of the dynamics tangent linear operator, which is a considerable advantage with respect to the method's implementation, and second, it enables the handling of a flow
Luo, Lei; Yang, Jian; Qian, Jianjun; Tai, Ying; Lu, Gui-Fu
2017-09-01
Dealing with partial occlusion or illumination is one of the most challenging problems in image representation and classification. In this problem, the characterization of the representation error plays a crucial role. In most current approaches, the error matrix needs to be stretched into a vector and each element is assumed to be independently corrupted. This ignores the dependence between the elements of error. In this paper, it is assumed that the error image caused by partial occlusion or illumination changes is a random matrix variate and follows the extended matrix variate power exponential distribution. This has the heavy tailed regions and can be used to describe a matrix pattern of l×m dimensional observations that are not independent. This paper reveals the essence of the proposed distribution: it actually alleviates the correlations between pixels in an error matrix E and makes E approximately Gaussian. On the basis of this distribution, we derive a Schatten p -norm-based matrix regression model with L q regularization. Alternating direction method of multipliers is applied to solve this model. To get a closed-form solution in each step of the algorithm, two singular value function thresholding operators are introduced. In addition, the extended Schatten p -norm is utilized to characterize the distance between the test samples and classes in the design of the classifier. Extensive experimental results for image reconstruction and classification with structural noise demonstrate that the proposed algorithm works much more robustly than some existing regression-based methods.
Low contrast detectability for color patterns variation of display images
International Nuclear Information System (INIS)
Ogura, Akio
1998-01-01
In recent years, the radionuclide images are acquired in digital form and displayed with false colors for signal intensity. This color scales for signal intensity have various patterns. In this study, low contrast detectability was compared the performance of gray scale cording with three color scales: the hot color scale, prism color scale and stripe color scale. SPECT images of brain phantom were displayed using four color patterns. These printed images and display images were evaluated with ROC analysis. Display images were indicated higher detectability than printed images. The hot scale and gray scale images indicated better Az of ROC than prism scale images because the prism scale images showed higher false positive rate. (author)
Geomagnetic Core Field Secular Variation Models
DEFF Research Database (Denmark)
Gillet, N.; Lesur, V.; Olsen, Nils
2010-01-01
highlight the difficulty of resolving the time variability of the high degree secular variation coefficients (i.e. the secular acceleration), arising for instance from the challenge to properly separate sources of internal and of external origin. In addition, the regularisation process may also result...
Accelerating cross-validation with total variation and its application to super-resolution imaging.
Directory of Open Access Journals (Sweden)
Tomoyuki Obuchi
Full Text Available We develop an approximation formula for the cross-validation error (CVE of a sparse linear regression penalized by ℓ1-norm and total variation terms, which is based on a perturbative expansion utilizing the largeness of both the data dimensionality and the model. The developed formula allows us to reduce the necessary computational cost of the CVE evaluation significantly. The practicality of the formula is tested through application to simulated black-hole image reconstruction on the event-horizon scale with super resolution. The results demonstrate that our approximation reproduces the CVE values obtained via literally conducted cross-validation with reasonably good precision.
International Nuclear Information System (INIS)
Tingberg, A.; Eriksson, F.; Medin, J.; Besjakov, J.; Baarth, M.; Haakansson, M.; Sandborg, M.; Almen, A.; Lanhede, B.; Alm-Carlsson, G.; Mattsson, S.; Maansson, L. G.
2005-01-01
Purpose: To investigate the influence of masking on the inter-observer variation in image quality evaluation of clinical radiographs of chest and lumbar spine. Background: Inter-observer variation is a big problem in image quality evaluation since this variation is often much bigger than the variation in image quality between, for example, two radiographic systems. In this study, we have evaluated the effect of masking on the inter-observer variation. The idea of the masking was to force every observer to view exactly the same part of the image and to avoid the effect of the overall 'first impression' of the image. A discussion with a group of European expert radiologists before the study indicated that masking might be a good way to reduce the inter-observer variation. Methods: Five chest and five lumbar spine radiographs were collected together with detailed information regarding exposure conditions. The radiographs were digitised with a high-performance scanner and five different manipulations were performed, simulating five different exposure conditions. The contrast, noise and spatial resolution were manipulated by this method. The images were printed onto the film and the individual masks were produced for each film, showing only the parts of the images that were necessary for the image quality evaluation. The quality of the images was evaluated on ordinary viewing boxes by a large group of experienced radiologists. The images were examined with and without the masks with a set of image criteria (if fulfilled, 1 point; and not fulfilled, 0 point), and the mean score was calculated for each simulated exposure condition. Results: The results of this study indicate that - contrary to what was supposed - the inter-observer variation increased when the images were masked. In some cases, especially for chest, this increase was statistically significant. Conclusions: Based on the results of this study, image masking in studies of fulfilment of image criteria cannot
Motion estimation of tagged cardiac magnetic resonance images using variational techniques
Czech Academy of Sciences Publication Activity Database
Carranza-Herrezuelo, N.; Bajo, A.; Šroubek, Filip; Santamarta, C.; Cristóbal, G.; Santos, A.; Ledesma-Carbayo, M.J.
2010-01-01
Roč. 34, č. 6 (2010), s. 514-522 ISSN 0895-6111 Institutional research plan: CEZ:AV0Z10750506 Keywords : medical imaging processing * motion estimation * variational techniques * tagged cardiac magnetic resonance images * optical flow Subject RIV: JD - Computer Applications, Robotics Impact factor: 1.110, year: 2010 http://library.utia.cas.cz/separaty/2010/ZOI/sroubek- motion estimation of tagged cardiac magnetic resonance images using variational techniques.pdf
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)
Robust bladder image registration by redefining data-term in total variational approach
Ali, Sharib; Daul, Christian; Galbrun, Ernest; Amouroux, Marine; Guillemin, François; Blondel, Walter
2015-03-01
Cystoscopy is the standard procedure for clinical diagnosis of bladder cancer diagnosis. Bladder carcinoma in situ are often multifocal and spread over large areas. In vivo, localization and follow-up of these tumors and their nearby sites is necessary. But, due to the small field of view (FOV) of the cystoscopic video images, urologists cannot easily interpret the scene. Bladder mosaicing using image registration facilitates this interpretation through the visualization of entire lesions with respect to anatomical landmarks. The reference white light (WL) modality is affected by a strong variability in terms of texture, illumination conditions and motion blur. Moreover, in the complementary fluorescence light (FL) modality, the texture is visually different from that of the WL. Existing algorithms were developed for a particular modality and scene conditions. This paper proposes a more general on fly image registration approach for dealing with these variability issues in cystoscopy. To do so, we present a novel, robust and accurate image registration scheme by redefining the data-term of the classical total variational (TV) approach. Quantitative results on realistic bladder phantom images are used for verifying accuracy and robustness of the proposed model. This method is also qualitatively assessed with patient data mosaicing for both WL and FL modalities.
Bohlman, S.; Park, J.; Muller-Landau, H. C.; Rifai, S. W.; Dandois, J. P.
2017-12-01
Phenology is a critical driver of ecosystem processes. There is strong evidence that phenology is shifting in temperate ecosystems in response to climate change, but tropical tree and liana phenology remains poorly quantified and understood. A key challenge is that tropical forests contain hundreds of plant species with a wide variety of phenological patterns. Satellite-based observations, an important source of phenology data in northern latitudes, are hindered by frequent cloud cover in the tropics. To quantify phenology over a large number of individuals and species, we collected bi-weekly images from unmanned aerial vehicles (UAVs) in the well-studied 50-ha forest inventory plot on Barro Colorado Island, Panama. Between October 2014 and December 2015 and again in May 2015, we collected a total of 35 sets of UAV images, each with continuous coverage of the 50-ha plot, where every tree ≥ 1 cm DBH is mapped. Spectral, texture, and image information was extracted from the UAV images for individual tree crowns, which was then used as inputs for a machine learning algorithm to predict percent leaf and branch cover. We obtained the species identities of 2000 crowns in the images via field mapping. The objectives of this study are to (1) determined if machine learning algorithms, applied to UAV images, can effectively quantify changes in leaf cover, which we term "deciduousness; (2) determine how liana cover effects deciduousness and (3) test how well UAV-derived deciduousness patterns match satellite-derived temporal patterns. Machine learning algorithms trained on a variety of image parameters could effectively determine leaf cover, despite variation in lighting and viewing angles. Crowns with higher liana cover have less overall deciduousness (tree + liana together) than crowns with lower liana cover. Individual crown deciduousness, summed over all crowns measured in the 50-ha plot, showed a similar seasonal pattern as MODIS EVI composited over 10 years. However
Automatic Fontanel Extraction from Newborns' CT Images Using Variational Level Set
Kazemi, Kamran; Ghadimi, Sona; Lyaghat, Alireza; Tarighati, Alla; Golshaeyan, Narjes; Abrishami-Moghaddam, Hamid; Grebe, Reinhard; Gondary-Jouet, Catherine; Wallois, Fabrice
A realistic head model is needed for source localization methods used for the study of epilepsy in neonates applying Electroencephalographic (EEG) measurements from the scalp. The earliest models consider the head as a series of concentric spheres, each layer corresponding to a different tissue whose conductivity is assumed to be homogeneous. The results of the source reconstruction depend highly on the electric conductivities of the tissues forming the head.The most used model is constituted of three layers (scalp, skull, and intracranial). Most of the major bones of the neonates’ skull are ossified at birth but can slightly move relative to each other. This is due to the sutures, fibrous membranes that at this stage of development connect the already ossified flat bones of the neurocranium. These weak parts of the neurocranium are called fontanels. Thus it is important to enter the exact geometry of fontaneles and flat bone in a source reconstruction because they show pronounced in conductivity. Computer Tomography (CT) imaging provides an excellent tool for non-invasive investigation of the skull which expresses itself in high contrast to all other tissues while the fontanels only can be identified as absence of bone, gaps in the skull formed by flat bone. Therefore, the aim of this paper is to extract the fontanels from CT images applying a variational level set method. We applied the proposed method to CT-images of five different subjects. The automatically extracted fontanels show good agreement with the manually extracted ones.
Modeling Cyclic Variation of Intracranial Pressure
National Research Council Canada - National Science Library
Daley, M
2001-01-01
...) recording during mechanical ventilation are due to cyclic extravascular compressional modulation primarily of the cerebral venous bed, an established isovolumetric model of cerebrospinal fluid...
A population based statistical model for daily geometric variations in the thorax
Szeto, Yenny Z.; Witte, Marnix G.; van Herk, Marcel; Sonke, Jan-Jakob
2017-01-01
To develop a population based statistical model of the systematic interfraction geometric variations between the planning CT and first treatment week of lung cancer patients for inclusion as uncertainty term in future probabilistic planning. Deformable image registrations between the planning CT and
Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets
Lenzen, F.; Lellmann, J.; Becker, F.; Schnö rr, C.
2014-01-01
© 2014 Society for Industrial and Applied Mathematics. We consider a class of quasi-variational inequalities (QVIs) for adaptive image restoration, where the adaptivity is described via solution-dependent constraint sets. In previous work we studied
Variational Ridging in Sea Ice Models
Roberts, A.; Hunke, E. C.; Lipscomb, W. H.; Maslowski, W.; Kamal, S.
2017-12-01
This work presents the results of a new development to make basin-scale sea ice models aware of the shape, porosity and extent of individual ridges within the pack. We have derived an analytic solution for the Euler-Lagrange equation of individual ridges that accounts for non-conservative forces, and therefore the compressive strength of individual ridges. Because a region of the pack is simply a collection of paths of individual ridges, we are able to solve the Euler-Lagrange equation for a large-scale sea ice field also, and therefore the compressive strength of a region of the pack that explicitly accounts for the macro-porosity of ridged debris. We make a number of assumptions that have simplified the problem, such as treating sea ice as a granular material in ridges, and assuming that bending moments associated with ridging are perturbations around an isostatic state. Regardless of these simplifications, the ridge model is remarkably predictive of macro-porosity and ridge shape, and, because our equations are analytic, they do not require costly computations to solve the Euler-Lagrange equation of ridges on the large scale. The new ridge model is therefore applicable to large-scale sea ice models. We present results from this theoretical development, as well as plans to apply it to the Regional Arctic System Model and a community sea ice code. Most importantly, the new ridging model is particularly useful for pinpointing gaps in our observational record of sea ice ridges, and points to the need for improved measurements of the evolution of porosity of deformed ice in the Arctic and Antarctic. Such knowledge is not only useful for improving models, but also for improving estimates of sea ice volume derived from altimetric measurements of sea ice freeboard.
A Proposed Conceptual Model to Measure Unwarranted Practice Variation
National Research Council Canada - National Science Library
Barr, Andrew M
2007-01-01
.... Employing a unit of analysis of the U.S. Army healthcare system and utilizing research by Wennberg and the Institute of Medicine, a model describing healthcare quality in terms of unwarranted practice variation and healthcare outcomes...
Target Selection Models with Preference Variation Between Offenders
Townsley, Michael; Birks, Daniel; Ruiter, Stijn; Bernasco, Wim; White, Gentry
2016-01-01
Objectives: This study explores preference variation in location choice strategies of residential burglars. Applying a model of offender target selection that is grounded in assertions of the routine activity approach, rational choice perspective, crime pattern and social disorganization theories,
Ultrasonic-assisted manufacturing processes: Variational model and numerical simulations
Siddiq, Amir; El Sayed, Tamer
2012-01-01
We present a computational study of ultrasonic assisted manufacturing processes including sheet metal forming, upsetting, and wire drawing. A fully variational porous plasticity model is modified to include ultrasonic softening effects
A variational approach to the Gross-Neveu model
International Nuclear Information System (INIS)
Mishra, H.; Misra, P.; Mishra, A.
1988-01-01
The authors solve the instability of perturbative vacuum of Gross-Neveu model. They use a variational method. The analysis is nonperturbative as it uses only equal time commmutator/anticommutator algebra
Meacham, K.; Montes, C.; Pederson, T.; Wu, J.; Guan, K.; Bernacchi, C.
2017-12-01
Improved photosynthetic rates have been shown to increase crop biomass, making improved photosynthesis a focus for driving future grain yield increases. Improving the photosynthetic pathway offers opportunity to meet food demand, but requires high throughput measurement techniques to detect photosynthetic variation in natural accessions and transgenically modified plants. Gas exchange measurements are the most widely used method of measuring photosynthesis in field trials but this process is laborious and slow, and requires further modeling to estimate meaningful parameters and to upscale to the plot or canopy level. In field trials of tobacco with modifications made to the photosynthetic pathway, we infer the maximum carboxylation rate of Rubisco (Vcmax) and maximum electron transport rate (Jmax) and detect photosynthetic variation from hyperspectral imaging with a partial least squares regression technique. Ground-truth measurements from photosynthetic gas exchange, a full-range (400-2500nm) handheld spectroadiometer with leaf clip, hyperspectral indices, and extractions of leaf pigments support the model. The results from a range of wild-type cultivars and from genetically modified germplasm suggest that the opportunity for rapid selection of top performing genotypes from among thousands of plots. This research creates the opportunity to extend agroecosystem models from simplified "one-cultivar" generic parameterization to better represent a full suite of current and future crop cultivars for a wider range of environmental conditions.
Validity of covariance models for the analysis of geographical variation
DEFF Research Database (Denmark)
Guillot, Gilles; Schilling, Rene L.; Porcu, Emilio
2014-01-01
1. Due to the availability of large molecular data-sets, covariance models are increasingly used to describe the structure of genetic variation as an alternative to more heavily parametrised biological models. 2. We focus here on a class of parametric covariance models that received sustained att...
Sparse Source EEG Imaging with the Variational Garrote
DEFF Research Database (Denmark)
Hansen, Sofie Therese; Stahlhut, Carsten; Hansen, Lars Kai
2013-01-01
EEG imaging, the estimation of the cortical source distribution from scalp electrode measurements, poses an extremely ill-posed inverse problem. Recent work by Delorme et al. (2012) supports the hypothesis that distributed source solutions are sparse. We show that direct search for sparse solutions...
Focus-variation image reconstruction in field-emission TEM
Coene, W.M.J.; Janssen, A.J.E.M.; Op de Beeck, M.; Van Dyck, D.; Van Zwet, E.J.; Zandbergen, H.W.; Bailey, G.W.; Rieder, C.L.
1993-01-01
The use of a field emission gun (FEG) in high resolution TEM (HRTEM) improves the information limit much below the point resolution. In the area between point and information resolution of the FEG-TEM, image interpretation is complicated by the lens aberrations and focus effects. Different
A variational void coalescence model for ductile metals
Siddiq, Amir
2011-08-17
We present a variational void coalescence model that includes all the essential ingredients of failure in ductile porous metals. The model is an extension of the variational void growth model by Weinberg et al. (Comput Mech 37:142-152, 2006). The extended model contains all the deformation phases in ductile porous materials, i.e. elastic deformation, plastic deformation including deviatoric and volumetric (void growth) plasticity followed by damage initiation and evolution due to void coalescence. Parametric studies have been performed to assess the model\\'s dependence on the different input parameters. The model is then validated against uniaxial loading experiments for different materials. We finally show the model\\'s ability to predict the damage mechanisms and fracture surface profile of a notched round bar under tension as observed in experiments. © Springer-Verlag 2011.
Qian, Tingting; Wang, Lianlian; Lu, Guanghua
2017-07-01
Radar correlated imaging (RCI) introduces the optical correlated imaging technology to traditional microwave imaging, which has raised widespread concern recently. Conventional RCI methods neglect the structural information of complex extended target, which makes the quality of recovery result not really perfect, thus a novel combination of negative exponential restraint and total variation (NER-TV) algorithm for extended target imaging is proposed in this paper. The sparsity is measured by a sequential order one negative exponential function, then the 2D total variation technique is introduced to design a novel optimization problem for extended target imaging. And the proven alternating direction method of multipliers is applied to solve the new problem. Experimental results show that the proposed algorithm could realize high resolution imaging efficiently for extended target.
Effects of small variations of speed of sound in optoacoustic tomographic imaging
International Nuclear Information System (INIS)
Deán-Ben, X. Luís; Ntziachristos, Vasilis; Razansky, Daniel
2014-01-01
Purpose: Speed of sound difference in the imaged object and surrounding coupling medium may reduce the resolution and overall quality of optoacoustic tomographic reconstructions obtained by assuming a uniform acoustic medium. In this work, the authors investigate the effects of acoustic heterogeneities and discuss potential benefits of accounting for those during the reconstruction procedure. Methods: The time shift of optoacoustic signals in an acoustically heterogeneous medium is studied theoretically by comparing different continuous and discrete wave propagation models. A modification of filtered back-projection reconstruction is subsequently implemented by considering a straight acoustic rays model for ultrasound propagation. The results obtained with this reconstruction procedure are compared numerically and experimentally to those obtained assuming a heuristically fitted uniform speed of sound in both full-view and limited-view optoacoustic tomography scenarios. Results: The theoretical analysis showcases that the errors in the time-of-flight of the signals predicted by considering the straight acoustic rays model tend to be generally small. When using this model for reconstructing simulated data, the resulting images accurately represent the theoretical ones. On the other hand, significant deviations in the location of the absorbing structures are found when using a uniform speed of sound assumption. The experimental results obtained with tissue-mimicking phantoms and a mouse postmortem are found to be consistent with the numerical simulations. Conclusions: Accurate analysis of effects of small speed of sound variations demonstrates that accounting for differences in the speed of sound allows improving optoacoustic reconstruction results in realistic imaging scenarios involving acoustic heterogeneities in tissues and surrounding media
Omics approaches to individual variation: modeling networks and the virtual patient
Lehrach, Hans
2016-01-01
Every human is unique. We differ in our genomes, environment, behavior, disease history, and past and current medical treatment?a complex catalog of differences that often leads to variations in the way each of us responds to a particular therapy. We argue here that true personalization of drug therapies will rely on ?virtual patient? models based on a detailed characterization of the individual patient by molecular, imaging, and sensor techniques. The models will be based, wherever possible,...
Bai, Bing
2012-03-01
There has been a lot of work on total variation (TV) regularized tomographic image reconstruction recently. Many of them use gradient-based optimization algorithms with a differentiable approximation of the TV functional. In this paper we apply TV regularization in Positron Emission Tomography (PET) image reconstruction. We reconstruct the PET image in a Bayesian framework, using Poisson noise model and TV prior functional. The original optimization problem is transformed to an equivalent problem with inequality constraints by adding auxiliary variables. Then we use an interior point method with logarithmic barrier functions to solve the constrained optimization problem. In this method, a series of points approaching the solution from inside the feasible region are found by solving a sequence of subproblems characterized by an increasing positive parameter. We use preconditioned conjugate gradient (PCG) algorithm to solve the subproblems directly. The nonnegativity constraint is enforced by bend line search. The exact expression of the TV functional is used in our calculations. Simulation results show that the algorithm converges fast and the convergence is insensitive to the values of the regularization and reconstruction parameters.
Research on compressive sensing reconstruction algorithm based on total variation model
Gao, Yu-xuan; Sun, Huayan; Zhang, Tinghua; Du, Lin
2017-12-01
Compressed sensing for breakthrough Nyquist sampling theorem provides a strong theoretical , making compressive sampling for image signals be carried out simultaneously. In traditional imaging procedures using compressed sensing theory, not only can it reduces the storage space, but also can reduce the demand for detector resolution greatly. Using the sparsity of image signal, by solving the mathematical model of inverse reconfiguration, realize the super-resolution imaging. Reconstruction algorithm is the most critical part of compression perception, to a large extent determine the accuracy of the reconstruction of the image.The reconstruction algorithm based on the total variation (TV) model is more suitable for the compression reconstruction of the two-dimensional image, and the better edge information can be obtained. In order to verify the performance of the algorithm, Simulation Analysis the reconstruction result in different coding mode of the reconstruction algorithm based on the TV reconstruction algorithm. The reconstruction effect of the reconfigurable algorithm based on TV based on the different coding methods is analyzed to verify the stability of the algorithm. This paper compares and analyzes the typical reconstruction algorithm in the same coding mode. On the basis of the minimum total variation algorithm, the Augmented Lagrangian function term is added and the optimal value is solved by the alternating direction method.Experimental results show that the reconstruction algorithm is compared with the traditional classical algorithm based on TV has great advantages, under the low measurement rate can be quickly and accurately recovers target image.
Huang, Z.; Chen, Q.; Shen, Y.; Chen, Q.; Liu, X.
2017-09-01
Variational pansharpening can enhance the spatial resolution of a hyperspectral (HS) image using a high-resolution panchromatic (PAN) image. However, this technology may lead to spectral distortion that obviously affect the accuracy of data analysis. In this article, we propose an improved variational method for HS image pansharpening with the constraint of spectral difference minimization. We extend the energy function of the classic variational pansharpening method by adding a new spectral fidelity term. This fidelity term is designed following the definition of spectral angle mapper, which means that for every pixel, the spectral difference value of any two bands in the HS image is in equal proportion to that of the two corresponding bands in the pansharpened image. Gradient descent method is adopted to find the optimal solution of the modified energy function, and the pansharpened image can be reconstructed. Experimental results demonstrate that the constraint of spectral difference minimization is able to preserve the original spectral information well in HS images, and reduce the spectral distortion effectively. Compared to original variational method, our method performs better in both visual and quantitative evaluation, and achieves a good trade-off between spatial and spectral information.
Limited data tomographic image reconstruction via dual formulation of total variation minimization
Jang, Kwang Eun; Sung, Younghun; Lee, Kangeui; Lee, Jongha; Cho, Seungryong
2011-03-01
The X-ray mammography is the primary imaging modality for breast cancer screening. For the dense breast, however, the mammogram is usually difficult to read due to tissue overlap problem caused by the superposition of normal tissues. The digital breast tomosynthesis (DBT) that measures several low dose projections over a limited angle range may be an alternative modality for breast imaging, since it allows the visualization of the cross-sectional information of breast. The DBT, however, may suffer from the aliasing artifact and the severe noise corruption. To overcome these problems, a total variation (TV) regularized statistical reconstruction algorithm is presented. Inspired by the dual formulation of TV minimization in denoising and deblurring problems, we derived a gradient-type algorithm based on statistical model of X-ray tomography. The objective function is comprised of a data fidelity term derived from the statistical model and a TV regularization term. The gradient of the objective function can be easily calculated using simple operations in terms of auxiliary variables. After a descending step, the data fidelity term is renewed in each iteration. Since the proposed algorithm can be implemented without sophisticated operations such as matrix inverse, it provides an efficient way to include the TV regularization in the statistical reconstruction method, which results in a fast and robust estimation for low dose projections over the limited angle range. Initial tests with an experimental DBT system confirmed our finding.
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...
Bilinear models for inter- and intra-patient variation of the prostate
International Nuclear Information System (INIS)
Jeong, Y; Radke, R J; Lovelock, D M
2010-01-01
We propose bilinear models for capturing and effectively decoupling the expected shape variations of an organ both across the patient population and within a specific patient. Bilinear models have been successfully introduced in other areas of computer vision, but they have rarely been used in medical imaging applications. Our particular interest is in modeling the shape variation of the prostate for potential use in radiation therapy treatment planning. Using a dataset of 204 prostate shapes contoured from CT imagery of 12 different patients, we build bilinear models and show that they can fit both training and testing shapes accurately. We also show how the bilinear model can adapt to a new patient using only a few example shapes, producing a patient-specific model that also reflects expected content variation learnt from a broader population. Finally, we evaluate the training and testing projection error, adaptation performance and image segmentation accuracy of the bilinear model compared to linear principal component analysis and hierarchical point distribution models with the same number of parameters.
A variational formulation for linear models in coupled dynamic thermoelasticity
International Nuclear Information System (INIS)
Feijoo, R.A.; Moura, C.A. de.
1981-07-01
A variational formulation for linear models in coupled dynamic thermoelasticity which quite naturally motivates the design of a numerical scheme for the problem, is studied. When linked to regularization or penalization techniques, this algorithm may be applied to more general models, namely, the ones that consider non-linear constraints associated to variational inequalities. The basic postulates of Mechanics and Thermodynamics as well as some well-known mathematical techniques are described. A thorough description of the algorithm implementation with the finite-element method is also provided. Proofs for existence and uniqueness of solutions and for convergence of the approximations are presented, and some numerical results are exhibited. (Author) [pt
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.
Dynamic contrast-enhanced MR imaging to assess physiologic variations of myometrial perfusion
International Nuclear Information System (INIS)
Thomassin-Naggara, Isabelle; Balvay, Daniel; Cuenod, Charles A.; Darai, Emile; Marsault, Claude; Bazot, Marc
2010-01-01
To prospectively evaluate the ability of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to assess physiological microvascular states in normal myometrium. Eighty-five women (62 women of reproductive age, 23 postmenopausal) undergoing DCE-MRI of the pelvis were included. Microvascular parameters for the inner and outer myometrium were analysed using a pharmacokinetic model. These parameters were tissue blood flow (F), blood volume fraction (V b ), permeability-surface area product (PS), interstitial volume fraction (V e ) and lag time (Dt). In the women of reproductive age, the inner myometrium displayed higher F and PS, lower V b and V e , and longer Dt than the outer myometrium (p = 0.02, p = 0.01, p = 0.005, p = 0.03 and p = 0.01, respectively). The inner myometrium presented microvascular variations during the menstrual cycle with a pre-ovulatory peak followed by a fall reaching a nadir of F and V b about 4 days after ovulation. Compared with women of reproductive age, in the postmenopausal state, F and V b decreased in the outer myometrium, while PS, V e and Dt increased (p < 0.0001, p = 0.001, p = 0.001, p = 0.03 and p = 0.0004, respectively). DCE-MRI is a non-invasive technique that can measure variations of myometrial microcirculation, and thereby be potentially useful to help characterize the role and states of the myometrium in assisted reproductive therapy. (orig.)
Comparison of computerized digital and film-screen radiography: response to variation in imaging kVp
Energy Technology Data Exchange (ETDEWEB)
Broderick, N J; Long, B; Dreesen, R G; Cohen, M D; Cory, D A [Riley Hospital for Children, Indiana Univ. School of Medicine, Indianapolis, IN (United States). Dept. of Radiology; Katz, B P; Kalasinski, L A [Regenstreif Inst., Indiana Univ. School of Medicine, Indianapolis, IN (United States). Dept. of Medicine
1992-09-01
A controlled prospective study, in an animal model chosen to simulate portable neonatal radiography, was performed to compare the response of the Philips Computed Radiography (CR) system and conventional 200 speed film-screen (FS) to variation in imaging kVp. Acceptable images were obtained on the CR system over a very wide kVp range. In contrast the FS system produced acceptable images over a narrow kVp range. This ability suggests that the CR system should eliminate the need for repeat examinations in cases where a suboptimal kVp setting would have resulted in an unacceptable FS image. CR technology should therefore be ideally suited to portable radiography especially in situations where selection of correct exposure factors is difficult as in the neonatal nursery. (orig.).
Comparison of computerized digital and film-screen radiography: response to variation in imaging kVp
International Nuclear Information System (INIS)
Broderick, N.J.; Long, B.; Dreesen, R.G.; Cohen, M.D.; Cory, D.A.; Katz, B.P.; Kalasinski, L.A.
1992-01-01
A controlled prospective study, in an animal model chosen to simulate portable neonatal radiography, was performed to compare the response of the Philips Computed Radiography (CR) system and conventional 200 speed film-screen (FS) to variation in imaging kVp. Acceptable images were obtained on the CR system over a very wide kVp range. In contrast the FS system produced acceptable images over a narrow kVp range. This ability suggests that the CR system should eliminate the need for repeat examinations in cases where a suboptimal kVp setting would have resulted in an unacceptable FS image. CR technology should therefore be ideally suited to portable radiography especially in situations where selection of correct exposure factors is difficult as in the neonatal nursery. (orig.)
Variations in the size of focal nodular hyperplasia on magnetic resonance imaging.
Ramírez-Fuentes, C; Martí-Bonmatí, L; Torregrosa, A; Del Val, A; Martínez, C
2013-01-01
To evaluate the changes in the size of focal nodular hyperplasia (FNH) during long-term magnetic resonance imaging (MRI) follow-up. We reviewed 44 FNHs in 30 patients studied with MRI with at least two MRI studies at least 12 months apart. We measured the largest diameter of the lesion (inmm) in contrast-enhanced axial images and calculated the percentage of variation as the difference between the maximum diameter in the follow-up and the maximum diameter in the initial study. We defined significant variation in size as variation greater than 20%. We also analyzed predisposing hormonal factors. The mean interval between the two imaging studies was 35±2 months (range: 12-94). Most lesions (80%) remained stable during follow-up. Only 9 of the 44 lesions (20%) showed a significant variation in diameter: 7 (16%) decreased in size and 2 (4%) increased, with variations that reached the double of the initial size. The change in size was not related to pregnancy, menopause, or the use of birth control pills or corticoids. Changes in the size of FNHs during follow-up are relatively common and should not lead to a change in the diagnosis. These variations in size seem to be independent of hormonal factors that are considered to predispose. Copyright © 2011 SERAM. Published by Elsevier Espana. All rights reserved.
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.
Regularization by Functions of Bounded Variation and Applications to Image Enhancement
International Nuclear Information System (INIS)
Casas, E.; Kunisch, K.; Pola, C.
1999-01-01
Optimization problems regularized by bounded variation seminorms are analyzed. The optimality system is obtained and finite-dimensional approximations of bounded variation function spaces as well as of the optimization problems are studied. It is demonstrated that the choice of the vector norm in the definition of the bounded variation seminorm is of special importance for approximating subspaces consisting of piecewise constant functions. Algorithms based on a primal-dual framework that exploit the structure of these nondifferentiable optimization problems are proposed. Numerical examples are given for denoising of blocky images with very high noise
Zhang, Hanming; Wang, Linyuan; Yan, Bin; Li, Lei; Cai, Ailong; Hu, Guoen
2016-01-01
Total generalized variation (TGV)-based computed tomography (CT) image reconstruction, which utilizes high-order image derivatives, is superior to total variation-based methods in terms of the preservation of edge information and the suppression of unfavorable staircase effects. However, conventional TGV regularization employs l1-based form, which is not the most direct method for maximizing sparsity prior. In this study, we propose a total generalized p-variation (TGpV) regularization model to improve the sparsity exploitation of TGV and offer efficient solutions to few-view CT image reconstruction problems. To solve the nonconvex optimization problem of the TGpV minimization model, we then present an efficient iterative algorithm based on the alternating minimization of augmented Lagrangian function. All of the resulting subproblems decoupled by variable splitting admit explicit solutions by applying alternating minimization method and generalized p-shrinkage mapping. In addition, approximate solutions that can be easily performed and quickly calculated through fast Fourier transform are derived using the proximal point method to reduce the cost of inner subproblems. The accuracy and efficiency of the simulated and real data are qualitatively and quantitatively evaluated to validate the efficiency and feasibility of the proposed method. Overall, the proposed method exhibits reasonable performance and outperforms the original TGV-based method when applied to few-view problems.
Variational Boussinesq model for simulation of coastal waves and tsunamis
Adytia, D.; Adytia, Didit; van Groesen, Embrecht W.C.; Tan, Soon Keat; Huang, Zhenhua
2009-01-01
In this paper we describe the basic ideas of a so-called Variational Boussinesq Model which is based on the Hamiltonian structure of gravity surface waves. By using a rather simple approach to prescribe the profile of vertical fluid potential in the expression for the kinetic energy, we obtain a set
Variational Boussinesq model for strongly nonlinear dispersive waves
Lawrence, C.; Adytia, D.; van Groesen, E.
2018-01-01
For wave tank, coastal and oceanic applications, a fully nonlinear Variational Boussinesq model with optimized dispersion is derived and a simple Finite Element implementation is described. Improving a previous weakly nonlinear version, high waves over flat and varying bottom are shown to be
Analysis of spin and gauge models with variational methods
International Nuclear Information System (INIS)
Dagotto, E.; Masperi, L.; Moreo, A.; Della Selva, A.; Fiore, R.
1985-01-01
Since independent-site (link) or independent-link (plaquette) variational states enhance the order or the disorder, respectively, in the treatment of spin (gauge) models, we prove that mixed states are able to improve the critical coupling while giving the qualitatively correct behavior of the relevant parameters
The variational approach to the Glashow-Weinberg-Salam model
International Nuclear Information System (INIS)
Manka, R.; Sladkowski, J.
1987-01-01
The variational approach to the Glashow-Weinberg-Salam model, based on canonical quantization, is presented. It is shown that taking into consideration the Becchi-Rouet-Stora symmetry leads to the correct, temperature-dependent, effective potential. This generalization of the Weinberg-Coleman potential leads to a phase transition of the first kind
Modeling stimulus variation in three common implicit attitude tasks.
Wolsiefer, Katie; Westfall, Jacob; Judd, Charles M
2017-08-01
We explored the consequences of ignoring the sampling variation due to stimuli in the domain of implicit attitudes. A large literature in psycholinguistics has examined the statistical treatment of random stimulus materials, but the recommendations from this literature have not been applied to the social psychological literature on implicit attitudes. This is partly because of inherent complications in applying crossed random-effect models to some of the most common implicit attitude tasks, and partly because no work to date has demonstrated that random stimulus variation is in fact consequential in implicit attitude measurement. We addressed this problem by laying out statistically appropriate and practically feasible crossed random-effect models for three of the most commonly used implicit attitude measures-the Implicit Association Test, affect misattribution procedure, and evaluative priming task-and then applying these models to large datasets (average N = 3,206) that assess participants' implicit attitudes toward race, politics, and self-esteem. We showed that the test statistics from the traditional analyses are substantially (about 60 %) inflated relative to the more-appropriate analyses that incorporate stimulus variation. Because all three tasks used the same stimulus words and faces, we could also meaningfully compare the relative contributions of stimulus variation across the tasks. In an appendix, we give syntax in R, SAS, and SPSS for fitting the recommended crossed random-effects models to data from all three tasks, as well as instructions on how to structure the data file.
Perz, Rafał; Toczyski, Jacek; Subit, Damien
2015-01-01
Computational models of the human body are commonly used for injury prediction in automobile safety research. To create these models, the geometry of the human body is typically obtained from segmentation of medical images such as computed tomography (CT) images that have a resolution between 0.2 and 1mm/pixel. While the accuracy of the geometrical and structural information obtained from these images depend greatly on their resolution, the effect of image resolution on the estimation of the ribs geometrical properties has yet to be established. To do so, each of the thirty-four sections of ribs obtained from a Post Mortem Human Surrogate (PMHS) was imaged using three different CT modalities: standard clinical CT (clinCT), high resolution clinical CT (HRclinCT), and microCT. The images were processed to estimate the rib cross-section geometry and mechanical properties, and the results were compared to those obtained from the microCT images by computing the 'deviation factor', a metric that quantifies the relative difference between results obtained from clinCT and HRclinCT to those obtained from microCT. Overall, clinCT images gave a deviation greater than 100%, and were therefore deemed inadequate for the purpose of this study. HRclinCT overestimated the rib cross-sectional area by 7.6%, the moments of inertia by about 50%, and the cortical shell area by 40.2%, while underestimating the trabecular area by 14.7%. Next, a parametric analysis was performed to quantify how the variations in the estimate of the geometrical properties affected the rib predicted mechanical response under antero-posterior loading. A variation of up to 45% for the predicted peak force and up to 50% for the predicted stiffness was observed. These results provide a quantitative estimate of the sensitivity of the response of the FE model to the resolution of the images used to generate it. They also suggest that a correction factor could be derived from the comparison between microCT and
Storm surge model based on variational data assimilation method
Directory of Open Access Journals (Sweden)
Shi-li Huang
2010-06-01
Full Text Available By combining computation and observation information, the variational data assimilation method has the ability to eliminate errors caused by the uncertainty of parameters in practical forecasting. It was applied to a storm surge model based on unstructured grids with high spatial resolution meant for improving the forecasting accuracy of the storm surge. By controlling the wind stress drag coefficient, the variation-based model was developed and validated through data assimilation tests in an actual storm surge induced by a typhoon. In the data assimilation tests, the model accurately identified the wind stress drag coefficient and obtained results close to the true state. Then, the actual storm surge induced by Typhoon 0515 was forecast by the developed model, and the results demonstrate its efficiency in practical application.
Insights into pre-reversal paleosecular variation from stochastic models
Directory of Open Access Journals (Sweden)
Klaudio ePeqini
2015-09-01
Full Text Available To provide insights on the paleosecular variation of the geomagnetic field and the mechanism of reversals, long time series of the dipolar magnetic moment are generated by two different stochastic models, known as the domino model and the inhomogeneous Lebovitz disk dynamo model, with initial values taken from the from paleomagnetic data. The former model considers mutual interactions of N macrospins embedded in a uniformly rotating medium, where random forcing and dissipation act on each macrospin. With an appropriate set of the model’s parameters values, the series generated by this model have similar statistical behaviour to the time series of the SHA.DIF.14K model. The latter model is an extension of the classical two-disk Rikitake model, considering N dynamo elements with appropriate interactions between them.We varied the parameters set of both models aiming at generating suitable time series with behaviour similar to the long time series of recent secular variation (SV. Such series are then extended to the near future, obtaining reversals in both cases of models. The analysis of the time series generated by simulating the models show that the reversals appears after a persistent period of low intensity geomagnetic field, as it is occurring in the present times.
Decision-Based Marginal Total Variation Diffusion for Impulsive Noise Removal in Color Images
Directory of Open Access Journals (Sweden)
Hongyao Deng
2017-01-01
Full Text Available Impulsive noise removal for color images usually employs vector median filter, switching median filter, the total variation L1 method, and variants. These approaches, however, often introduce excessive smoothing and can result in extensive visual feature blurring and thus are suitable only for images with low density noise. A marginal method to reduce impulsive noise is proposed in this paper that overcomes this limitation that is based on the following facts: (i each channel in a color image is contaminated independently, and contaminative components are independent and identically distributed; (ii in a natural image the gradients of different components of a pixel are similar to one another. This method divides components into different categories based on different noise characteristics. If an image is corrupted by salt-and-pepper noise, the components are divided into the corrupted and the noise-free components; if the image is corrupted by random-valued impulses, the components are divided into the corrupted, noise-free, and the possibly corrupted components. Components falling into different categories are processed differently. If a component is corrupted, modified total variation diffusion is applied; if it is possibly corrupted, scaled total variation diffusion is applied; otherwise, the component is left unchanged. Simulation results demonstrate its effectiveness.
Biomedical Imaging and Computational Modeling in Biomechanics
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.
Ultrasonic-assisted manufacturing processes: Variational model and numerical simulations
Siddiq, Amir
2012-04-01
We present a computational study of ultrasonic assisted manufacturing processes including sheet metal forming, upsetting, and wire drawing. A fully variational porous plasticity model is modified to include ultrasonic softening effects and then utilized to account for instantaneous softening when ultrasonic energy is applied during deformation. Material model parameters are identified via inverse modeling, i.e. by using experimental data. The versatility and predictive ability of the model are demonstrated and the effect of ultrasonic intensity on the manufacturing process at hand is investigated and compared qualitatively with experimental results reported in the literature. © 2011 Elsevier B.V. All rights reserved.
Energy Technology Data Exchange (ETDEWEB)
Kim, Jong Woo; Lee, Sang Hoon; Kim, Nam Kug; Cho, Kyung Sik; Lee, Jin Seong [Dept. of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul (Korea, Republic of)
2013-04-15
To evaluate the effects of the key imaging-parameter alterations on the four MR sequences in a phantom study. Magnetic resonance (MR) imaging was performed on a MR phantom with an 8-channel head coil by using a 3 T MR system. The images were obtained in the axial plane on four MR sequences [T1-weighted, T2-weighted, Proton-density, and 3 dimensional (3D) fast spin echo (FSE)] with controlled variations in the following key parameters: 1) echo train length (ETL), 2) repetition time (TR), and 3) echo time (TE). The image blurring was determined by the degree of the gradient angle; i.e., the blurring increased as the gradient angle decreases. The increasing ETL was observed to cause an increase in the image blurring on all pulse sequences with a statistical significance (p = 0.004) on the 3D FSE. Increasing the TR appeared to have no effect except a statistically significant decrease on the T1-weighted images (p = 0.011). Increasing TE showed no effect on the T1-weighted images (p = 0.932); however, it caused an increase of blurring on the proton density images (p = 0.016) as well as the T2-weighted images (p < 0.001), and a decrease on the 3D FSE (p = 0.001). To reduce the image blurring, short ETL and long TE for 3D FSE, long TR for T1-weighted images and short TE for proton-density and T2-weighted images should be applied.
A generalized model for optimal transport of images including dissipation and density modulation
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
Kelly, C. L.; Lawrence, J. F.
2014-12-01
During October 2012, 51 geophones and 6 broadband seismometers were deployed in an ~50x50m region surrounding a periodically erupting columnar geyser in the El Tatio Geyser Field, Chile. The dense array served as the seismic framework for a collaborative project to study the mechanics of complex hydrothermal systems. Contemporaneously, complementary geophysical measurements (including down-hole temperature and pressure, discharge rates, thermal imaging, water chemistry, and video) were also collected. Located on the western flanks of the Andes Mountains at an elevation of 4200m, El Tatio is the third largest geyser field in the world. Its non-pristine condition makes it an ideal location to perform minutely invasive geophysical studies. The El Jefe Geyser was chosen for its easily accessible conduit and extremely periodic eruption cycle (~120s). During approximately 2 weeks of continuous recording, we recorded ~2500 nighttime eruptions which lack cultural noise from tourism. With ample data, we aim to study how the source varies spatially and temporally during each phase of the geyser's eruption cycle. We are developing a new back-projection processing technique to improve source imaging for diffuse signals. Our method was previously applied to the Sierra Negra Volcano system, which also exhibits repeating harmonic and diffuse seismic sources. We back-project correlated seismic signals from the receivers back to their sources, assuming linear source to receiver paths and a known velocity model (obtained from ambient noise tomography). We apply polarization filters to isolate individual and concurrent geyser energy associated with P and S phases. We generate 4D, time-lapsed images of the geyser source field that illustrate how the source distribution changes through the eruption cycle. We compare images for pre-eruption, co-eruption, post-eruption and quiescent periods. We use our images to assess eruption mechanics in the system (i.e. top-down vs. bottom-up) and
International Nuclear Information System (INIS)
Smith, Ryan P.; Bloch, Peter; Harris, Eleanor E.; McDonough, James; Sarkar, Abhirup; Kassaee, Alireza; Avery, Steven; Solin, Lawrence J.
2005-01-01
Purpose: To evaluate the daily setup variation and the anatomic movement of the heart and lungs during breast irradiation with tangential photon beams, as measured with an electronic portal imaging device. Methods and materials: Analysis of 1,709 portal images determined changes in the radiation field during a treatment course in 8 patients. Values obtained for every image included central lung distance (CLD) and area of lung and heart within the irradiated field. The data from these measurements were used to evaluate variation from setup between treatment days and motion due to respiration and/or patient movement during treatment delivery. Results: The effect of respiratory motion and movement during treatment was minimal: the maximum range in CLD for any patient on any day was 0.25 cm. The variation caused by day-to-day setup variation was greater, with CLD values for patients ranging from 0.59 cm to 2.94 cm. Similar findings were found for heart and lung areas. Conclusions: There is very little change in CLD and corresponding lung and heart area during individual radiation treatment fractions in breast tangential fields, compared with a relatively greater amount of variation that occurs between days
Inter-fraction variations in respiratory motion models
Energy Technology Data Exchange (ETDEWEB)
McClelland, J R; Modat, M; Ourselin, S; Hawkes, D J [Centre for Medical Image Computing, University College London (United Kingdom); Hughes, S; Qureshi, A; Ahmad, S; Landau, D B, E-mail: j.mcclelland@cs.ucl.ac.uk [Department of Oncology, Guy' s and St Thomas' s Hospitals NHS Trust, London (United Kingdom)
2011-01-07
Respiratory motion can vary dramatically between the planning stage and the different fractions of radiotherapy treatment. Motion predictions used when constructing the radiotherapy plan may be unsuitable for later fractions of treatment. This paper presents a methodology for constructing patient-specific respiratory motion models and uses these models to evaluate and analyse the inter-fraction variations in the respiratory motion. The internal respiratory motion is determined from the deformable registration of Cine CT data and related to a respiratory surrogate signal derived from 3D skin surface data. Three different models for relating the internal motion to the surrogate signal have been investigated in this work. Data were acquired from six lung cancer patients. Two full datasets were acquired for each patient, one before the course of radiotherapy treatment and one at the end (approximately 6 weeks later). Separate models were built for each dataset. All models could accurately predict the respiratory motion in the same dataset, but had large errors when predicting the motion in the other dataset. Analysis of the inter-fraction variations revealed that most variations were spatially varying base-line shifts, but changes to the anatomy and the motion trajectories were also observed.
4D segmentation of brain MR images with constrained cortical thickness variation.
Directory of Open Access Journals (Sweden)
Li Wang
Full Text Available Segmentation of brain MR images plays an important role in longitudinal investigation of developmental, aging, disease progression changes in the cerebral cortex. However, most existing brain segmentation methods consider multiple time-point images individually and thus cannot achieve longitudinal consistency. For example, cortical thickness measured from the segmented image will contain unnecessary temporal variations, which will affect the time related change pattern and eventually reduce the statistical power of analysis. In this paper, we propose a 4D segmentation framework for the adult brain MR images with the constraint of cortical thickness variations. Specifically, we utilize local intensity information to address the intensity inhomogeneity, spatial cortical thickness constraint to maintain the cortical thickness being within a reasonable range, and temporal cortical thickness variation constraint in neighboring time-points to suppress the artificial variations. The proposed method has been tested on BLSA dataset and ADNI dataset with promising results. Both qualitative and quantitative experimental results demonstrate the advantage of the proposed method, in comparison to other state-of-the-art 4D segmentation methods.
Spacial Variation in SAR Images of Different Resolution for Agricultural Fields
DEFF Research Database (Denmark)
Sandholt, Inge; Skriver, Henning
1999-01-01
The spatial variation in two types of Synthetic Aperture Radar (SAR) images covering agricultural fields is analysed. C-band polarimetric SAR data from the Danish airborne SAR, EMISAR, have been compared to space based ERS-1 C-band SAR with respect to scale and effect of polarization. The general...
Image Size Variation Influence on Corrupted and Non-viewable BMP Image
Azmi, Tengku Norsuhaila T.; Azma Abdullah, Nurul; Rahman, Nurul Hidayah Ab; Hamid, Isredza Rahmi A.; Chai Wen, Chuah
2017-08-01
Image is one of the evidence component seek in digital forensics. Joint Photographic Experts Group (JPEG) format is most popular used in the Internet because JPEG files are very lossy and easy to compress that can speed up Internet transmitting processes. However, corrupted JPEG images are hard to recover due to the complexities of determining corruption point. Nowadays Bitmap (BMP) images are preferred in image processing compared to another formats because BMP image contain all the image information in a simple format. Therefore, in order to investigate the corruption point in JPEG, the file is required to be converted into BMP format. Nevertheless, there are many things that can influence the corrupting of BMP image such as the changes of image size that make the file non-viewable. In this paper, the experiment indicates that the size of BMP file influences the changes in the image itself through three conditions, deleting, replacing and insertion. From the experiment, we learnt by correcting the file size, it can able to produce a viewable file though partially. Then, it can be investigated further to identify the corruption point.
Liu, Yan; Ma, Jianhua; Fan, Yi; Liang, Zhengrong
2012-12-07
Previous studies have shown that by minimizing the total variation (TV) of the to-be-estimated image with some data and other constraints, piecewise-smooth x-ray computed tomography (CT) can be reconstructed from sparse-view projection data without introducing notable artifacts. However, due to the piecewise constant assumption for the image, a conventional TV minimization algorithm often suffers from over-smoothness on the edges of the resulting image. To mitigate this drawback, we present an adaptive-weighted TV (AwTV) minimization algorithm in this paper. The presented AwTV model is derived by considering the anisotropic edge property among neighboring image voxels, where the associated weights are expressed as an exponential function and can be adaptively adjusted by the local image-intensity gradient for the purpose of preserving the edge details. Inspired by the previously reported TV-POCS (projection onto convex sets) implementation, a similar AwTV-POCS implementation was developed to minimize the AwTV subject to data and other constraints for the purpose of sparse-view low-dose CT image reconstruction. To evaluate the presented AwTV-POCS algorithm, both qualitative and quantitative studies were performed by computer simulations and phantom experiments. The results show that the presented AwTV-POCS algorithm can yield images with several notable gains, in terms of noise-resolution tradeoff plots and full-width at half-maximum values, as compared to the corresponding conventional TV-POCS algorithm.
Global manipulation of digital images can lead to variation in cytological diagnosis.
Prasad, H; Wanjari, Sangeeta; Parwani, Rajkumar
2011-03-31
With the adoption of a completely electronic workflow by several journals and the advent of telepathology, digital imaging has become an integral part of every scientific research. However, manipulating digital images is very easy, and it can lead to misinterpretations. To analyse the impact of manipulating digital images on their diagnosis. Digital images were obtained from Papanicolaou-stained smears of dysplastic and normal oral epithelium. They were manipulated using GNU Image Manipulation Program (GIMP) to alter their brightness and contrast and color levels. A Power Point presentation composed of slides of these manipulated images along with the unaltered originals arranged randomly was created. The presentation was shown to five observers individually who rated the images as normal, mild, moderate or severe dysplasia. Weighted κ statistics was used to measure and assess the levels of agreement between observers. Levels of agreement between manipulated images and original images varied greatly among observers. Variation in diagnosis was in the form of overdiagnosis or under-diagnosis, usually by one grade. Global manipulations of digital images of cytological slides can significantly affect their interpretation. Such manipulations should therefore be kept to a minimum, and avoided wherever possible.
Global manipulation of digital images can lead to variation in cytological diagnosis
Directory of Open Access Journals (Sweden)
H Prasad
2011-01-01
Full Text Available Background: With the adoption of a completely electronic workflow by several journals and the advent of telepathology, digital imaging has become an integral part of every scientific research. However, manipulating digital images is very easy, and it can lead to misinterpretations. Aim: To analyse the impact of manipulating digital images on their diagnosis. Design: Digital images were obtained from Papanicolaou-stained smears of dysplastic and normal oral epithelium. They were manipulated using GNU Image Manipulation Program (GIMP to alter their brightness and contrast and color levels. A Power Point presentation composed of slides of these manipulated images along with the unaltered originals arranged randomly was created. The presentation was shown to five observers individually who rated the images as normal, mild, moderate or severe dysplasia. Weighted k statistics was used to measure and assess the levels of agreement between observers. Results: Levels of agreement between manipulated images and original images varied greatly among observers. Variation in diagnosis was in the form of overdiagnosis or under-diagnosis, usually by one grade. Conclusion: Global manipulations of digital images of cytological slides can significantly affect their interpretation. Such manipulations should therefore be kept to a minimum, and avoided wherever possible.
Directory of Open Access Journals (Sweden)
Yongle Li
2014-01-01
Full Text Available We propose a new method of image restoration for catadioptric defocus blur using omnitotal variation (Omni-TV minimization based on omnigradient. Catadioptric omnidirectional imaging systems usually consist of conventional cameras and curved mirrors for capturing 360° field of view. The problem of catadioptric omnidirectional imaging defocus blur, which is caused by lens aperture and mirror curvature, becomes more severe when high resolution sensors and large apertures are used. In an omnidirectional image, two points near each other may not be close to one another in the 3D scene. Traditional gradient computation cannot be directly applied to omnidirectional image processing. Thus, omnigradient computing method combined with the characteristics of catadioptric omnidirectional imaging is proposed. Following this Omni-TV minimization is used as the constraint for deconvolution regularization, leading to the restoration of defocus blur in an omnidirectional image to obtain all sharp omnidirectional images. The proposed method is important for improving catadioptric omnidirectional imaging quality and promoting applications in related fields like omnidirectional video and image processing.
Naturalness and image quality : saturation and lightness variation in color images of natural scenes
Ridder, de H.
1996-01-01
The relation between perceived image quality and naturalness was investigated by varying the colorfulness of natural images at various lightness levels. At each lightness level, subjects assessed perceived colorfulness, naturalness, and quality as a function of average saturation by means of direct
Seasonal Gravity Field Variations from GRACE and Hydrological Models
DEFF Research Database (Denmark)
Andersen, Ole Baltazar; Hinderer, Jacques; Lemoine, Frank G.
2004-01-01
. Four global hydrological models covering the same period in 2002–2003 as the GRACE observations were investigated to for their mutual consistency in estimates of annual variation in terrestrial water storage and related temporal changes in gravity field. The hydrological models differ by a maximum of 2...... µGal or nearly 5 cm equivalent water storage in selected regions. Integrated over all land masses the standard deviation among the annual signal from the four hydrological models are 0.6 µGal equivalent to around 1.4 cm in equivalent water layer thickness. The estimated accuracy of the annual...
Color correction with blind image restoration based on multiple images using a low-rank model
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.
Biosphere modelling for a HLW repository - scenario and parameter variations
International Nuclear Information System (INIS)
Grogan, H.
1985-03-01
In Switzerland high-level radioactive wastes have been considered for disposal in deep-lying crystalline formations. The individual doses to man resulting from radionuclides entering the biosphere via groundwater transport are calculated. The main recipient area modelled, which constitutes the base case, is a broad gravel terrace sited along the south bank of the river Rhine. An alternative recipient region, a small valley with a well, is also modelled. A number of parameter variations are performed in order to ascertain their impact on the doses. Finally two scenario changes are modelled somewhat simplistically, these consider different prevailing climates, namely tundra and a warmer climate than present. In the base case negligibly low doses to man in the long term, resulting from the existence of a HLW repository have been calculated. Cs-135 results in the largest dose (8.4E-7 mrem/y at 6.1E+6 y) while Np-237 gives the largest dose from the actinides (3.6E-8 mrem/y). The response of the model to parameter variations cannot be easily predicted due to non-linear coupling of many of the parameters. However, the calculated doses were negligibly low in all cases as were those resulting from the two scenario variations. (author)
The numerical solution of total variation minimization problems in image processing
Energy Technology Data Exchange (ETDEWEB)
Vogel, C.R.; Oman, M.E. [Montana State Univ., Bozeman, MT (United States)
1994-12-31
Consider the minimization of penalized least squares functionals of the form: f(u) = 1/2 ({parallel}Au {minus} z{parallel}){sup 2} + {alpha}{integral}{sub {Omega}}{vert_bar}{del}u{vert_bar}dx. Here A is a bounded linear operator, z represents data, {parallel} {center_dot} {parallel} is a Hilbert space norm, {alpha} is a positive parameter, {integral}{sub {Omega}}{vert_bar}{del}u{vert_bar} dx represents the total variation (TV) of a function u {element_of} BV ({Omega}), the class of functions of bounded variation on a bounded region {Omega}, and {vert_bar} {center_dot} {vert_bar} denotes Euclidean norm. In image processing, u represents an image which is to be recovered from noisy data z. Certain {open_quotes}blurring processes{close_quotes} may be represented by the action of an operator A on the image u.
Menu variations for diabetes mellitus patients using Goal Programming model
Dhoruri, Atmini; Lestari, Dwi; Ratnasari, Eminugroho
2017-08-01
Diabetes mellitus (DM) was a chronic metabolic disease characterized by higher than normal blood glucose level (normal blood glucose level = = 80 -120 mg/dl). In this study, type 2 DM which mostly caused by unhealthy eating habits would be investigated. Related to eating habit, DM patients needed dietary menu planning with an extracare regarding their nutrients intake (energy, protein, fat and carbohydrate). Therefore, the measures taken were by organizing nutritious dietary menu for diabetes mellitus patients. Dietary menu with appropriate amount of nutrients was organized by considering the amount of calories, proteins, fats and carbohydrates. In this study, Goal Programming model was employed to determine optimal dietary menu variations for diabetes mellitus patients by paying attention to optimal expenses. According to the data obtained from hospitals in Yogyakarta, optimal menu variations would be analyzed by using Goal Programming model and would be completed by using LINGO computer program.
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.
Dynamic contrast-enhanced MR imaging to assess physiologic variations of myometrial perfusion
Energy Technology Data Exchange (ETDEWEB)
Thomassin-Naggara, Isabelle [Assistance Publique-Hopitaux de Paris, Department of Radiology, Hopital Tenon, Paris (France); Universite Rene Descartes, Laboratoire de Recherche en Imagerie-INSERM U970, Paris (France); Hopital Tenon, Service de Radiologie, Paris (France); Balvay, Daniel [Universite Rene Descartes, Laboratoire de Recherche en Imagerie-INSERM U970, Paris (France); Cuenod, Charles A. [Universite Rene Descartes, Laboratoire de Recherche en Imagerie-INSERM U970, Paris (France); Hopital Europeen Georges Pompidou (HEGP), Department of Radiology, Paris (France); Darai, Emile [Assistance Publique-Hopitaux de Paris, Department of Gynaecology-Obstetrics, Hopital Tenon, Paris (France); Marsault, Claude; Bazot, Marc [Assistance Publique-Hopitaux de Paris, Department of Radiology, Hopital Tenon, Paris (France)
2010-04-15
To prospectively evaluate the ability of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to assess physiological microvascular states in normal myometrium. Eighty-five women (62 women of reproductive age, 23 postmenopausal) undergoing DCE-MRI of the pelvis were included. Microvascular parameters for the inner and outer myometrium were analysed using a pharmacokinetic model. These parameters were tissue blood flow (F), blood volume fraction (V{sub b}), permeability-surface area product (PS), interstitial volume fraction (V{sub e}) and lag time (Dt). In the women of reproductive age, the inner myometrium displayed higher F and PS, lower V{sub b} and V{sub e}, and longer Dt than the outer myometrium (p = 0.02, p = 0.01, p = 0.005, p = 0.03 and p = 0.01, respectively). The inner myometrium presented microvascular variations during the menstrual cycle with a pre-ovulatory peak followed by a fall reaching a nadir of F and V{sub b} about 4 days after ovulation. Compared with women of reproductive age, in the postmenopausal state, F and V{sub b} decreased in the outer myometrium, while PS, V{sub e} and Dt increased (p < 0.0001, p = 0.001, p = 0.001, p = 0.03 and p = 0.0004, respectively). DCE-MRI is a non-invasive technique that can measure variations of myometrial microcirculation, and thereby be potentially useful to help characterize the role and states of the myometrium in assisted reproductive therapy. (orig.)
New second order Mumford-Shah model based on Γ-convergence approximation for image processing
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.
Bohlman, Stephanie; Rifai, Sami; Park, John; Dandois, Jonathan; Muller-Landau, Helene
2017-04-01
identities of 2000 crowns in the images by linking the crowns to stem tags in the field, thus producing a time series of cumulative annual deciduousness for 65 species. Deciduousness showed continuous variation among species rather than distinct phenological categories (ie evergreen and deciduous) that are commonly used in physiological, ecosystem and modeling studies. Some species labelled as evergreen by expert-based classification had annual deciduousness higher than those labelled as deciduous. We found significant, positive relationships between species mean deciduousness and species' leaf phosphorous, photosynthetic capacity and adult relative growth rate, suggesting that higher deciduousness is associated with greater resource acquisition. Comparing May 2015 (during an El Nino drought) and May 2014 (an non El Nino year with normal rainfall), mean deciduousness values for nearly all species was greater in 2015 but with differing levels of intraspecific variation. We discuss how the variation in deciduousness among species, its relationship with plant traits and response to the drought might be incorporated into terrestrial biosphere models of tropical forests to more accurately represent phenology and understand the consequences of community-level variation in phenology for ecosystem processes.
Skin image illumination modeling and chromophore identification for melanoma diagnosis
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.
Image-Optimized Coronal Magnetic Field Models
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.
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.
Lahmiri, Salim; Shmuel, Amir
2017-11-01
Diabetic retinopathy is a disease that can cause a loss of vision. An early and accurate diagnosis helps to improve treatment of the disease and prognosis. One of the earliest characteristics of diabetic retinopathy is the appearance of retinal hemorrhages. The purpose of this study is to design a fully automated system for the detection of hemorrhages in a retinal image. In the first stage of our proposed system, a retinal image is processed with variational mode decomposition (VMD) to obtain the first variational mode, which captures the high frequency components of the original image. In the second stage, four texture descriptors are extracted from the first variational mode. Finally, a classifier trained with all computed texture descriptors is used to distinguish between images of healthy and unhealthy retinas with hemorrhages. Experimental results showed evidence of the effectiveness of the proposed system for detection of hemorrhages in the retina, since a perfect detection rate was achieved. Our proposed system for detecting diabetic retinopathy is simple and easy to implement. It requires only short processing time, and it yields higher accuracy in comparison with previously proposed methods for detecting diabetic retinopathy.
Small velocity and finite temperature variations in kinetic relaxation models
Markowich, Peter; Jü ngel, Ansgar; Aoki, Kazuo
2010-01-01
A small Knuden number analysis of a kinetic equation in the diffusive scaling is performed. The collision kernel is of BGK type with a general local Gibbs state. Assuming that the flow velocity is of the order of the Knudsen number, a Hilbert expansion yields a macroscopic model with finite temperature variations, whose complexity lies in between the hydrodynamic and the energy-transport equations. Its mathematical structure is explored and macroscopic models for specific examples of the global Gibbs state are presented. © American Institute of Mathematical Sciences.
Variational approach to thermal masses in compactified models
Energy Technology Data Exchange (ETDEWEB)
Dominici, Daniele [Dipartimento di Fisica e Astronomia Università di Firenze and INFN - Sezione di Firenze,Via G. Sansone 1, 50019 Sesto Fiorentino (Italy); Roditi, Itzhak [Centro Brasileiro de Pesquisas Físicas - CBPF/MCT,Rua Dr. Xavier Sigaud 150, 22290-180, Rio de Janeiro, RJ (Brazil)
2015-08-20
We investigate by means of a variational approach the effective potential of a 5DU(1) scalar model at finite temperature and compactified on S{sup 1} and S{sup 1}/Z{sub 2} as well as the corresponding 4D model obtained through a trivial dimensional reduction. We are particularly interested in the behavior of the thermal masses of the scalar field with respect to the Wilson line phase and the results obtained are compared with those coming from a one-loop effective potential calculation. We also explore the nature of the phase transition.
Diurnal, Seasonal, and Interannual Variations of Cloud Properties Derived for CERES From Imager Data
Minnis, Patrick; Young, David F.; Sun-Mack, Sunny; Trepte, Qing Z.; Chen, Yan; Brown, Richard R.; Gibson, Sharon; Heck, Patrick W.
2004-01-01
Simultaneous measurement of the radiation and cloud fields on a global basis is a key component in the effort to understand and model the interaction between clouds and radiation at the top of the atmosphere, at the surface, and within the atmosphere. The NASA Clouds and Earth s Radiant Energy System (CERES) Project, begun in 1998, is meeting this need. Broadband shortwave (SW) and longwave radiance measurements taken by the CERES scanners at resolutions between 10 and 20 km on the Tropical Rainfall Measuring Mission (TRMM), Terra, and Aqua satellites are matched to simultaneous retrievals of cloud height, phase, particle size, water path, and optical depth OD from the TRMM Visible Infrared Scanner (VIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua. Besides aiding the interpretation of the broadband radiances, the CERES cloud properties are valuable for understanding cloud variations at a variety of scales. In this paper, the resulting CERES cloud data taken to date are averaged at several temporal scales to examine the temporal and spatial variability of the cloud properties on a global scale at a 1 resolution.
Directory of Open Access Journals (Sweden)
Haiqing He
2018-02-01
Full Text Available Feature-based matching methods have been widely used in remote sensing image matching given their capability to achieve excellent performance despite image geometric and radiometric distortions. However, most of the feature-based methods are unreliable for complex background variations, because the gradient or other image grayscale information used to construct the feature descriptor is sensitive to image background variations. Recently, deep learning-based methods have been proven suitable for high-level feature representation and comparison in image matching. Inspired by the progresses made in deep learning, a new technical framework for remote sensing image matching based on the Siamese convolutional neural network is presented in this paper. First, a Siamese-type network architecture is designed to simultaneously learn the features and the corresponding similarity metric from labeled training examples of matching and non-matching true-color patch pairs. In the proposed network, two streams of convolutional and pooling layers sharing identical weights are arranged without the manually designed features. The number of convolutional layers is determined based on the factors that affect image matching. The sigmoid function is employed to compute the matching and non-matching probabilities in the output layer. Second, a gridding sub-pixel Harris algorithm is used to obtain the accurate localization of candidate matches. Third, a Gaussian pyramid coupling quadtree is adopted to gradually narrow down the searching space of the candidate matches, and multiscale patches are compared synchronously. Subsequently, a similarity measure based on the output of the sigmoid is adopted to find the initial matches. Finally, the random sample consensus algorithm and the whole-to-local quadratic polynomial constraints are used to remove false matches. In the experiments, different types of satellite datasets, such as ZY3, GF1, IKONOS, and Google Earth images
Computer model for harmonic ultrasound imaging.
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.
Variational cluster perturbation theory for Bose-Hubbard models
International Nuclear Information System (INIS)
Koller, W; Dupuis, N
2006-01-01
We discuss the application of the variational cluster perturbation theory (VCPT) to the Mott-insulator-to-superfluid transition in the Bose-Hubbard model. We show how the VCPT can be formulated in such a way that it gives a translation invariant excitation spectrum-free of spurious gaps-despite the fact that it formally breaks translation invariance. The phase diagram and the single-particle Green function in the insulating phase are obtained for one-dimensional systems. When the chemical potential of the cluster is taken as a variational parameter, the VCPT reproduces the dimensional dependence of the phase diagram even for one-site clusters. We find a good quantitative agreement with the results of the density-matrix renormalization group when the number of sites in the cluster becomes of order 10. The extension of the method to the superfluid phase is discussed
Rectal dose variation during the course of image-guided radiation therapy of prostate cancer
International Nuclear Information System (INIS)
Chen Lili; Paskalev, Kamen; Xu Xiu; Zhu, Jennifer; Wang Lu; Price, Robert A.; Hu Wei; Feigenberg, Steven J.; Horwitz, Eric M.; Pollack, Alan; Charlie Ma, C.M.
2010-01-01
Background and purpose: To investigate the change in rectal dose during the treatment course for intensity-modulated radiotherapy (IMRT) of prostate cancer with image-guidance. Materials and methods: Twenty prostate cancer patients were recruited for this retrospective study. All patients have been treated with IMRT. For each patient, MR and CT images were fused for target and critical structure delineation. IMRT treatment planning was performed on the simulation CT images. Inter-fractional motion during the course of treatment was corrected using a CT-on-rails system. The rectum was outlined on both the original treatment plan and the subsequent daily CT images from the CT-on-rails by the same investigator. Dose distributions on these daily CT images were recalculated with the isocenter shifts relative to the simulation CT images using the leaf sequences/MUs based on the original treatment plan. The rectal doses from the subsequent daily CTs were compared with the original doses planned on the simulation CT using our clinical acceptance criteria. Results: Based on 20 patients with 139 daily CT sets, 28% of the subsequent treatment dose distributions did not meet our criterion of V 40 65 < 17%. The inter-fractional rectal volume variation is significant for some patients. Conclusions: Due to the large inter-fractional variation of the rectal volume, it is more favorable to plan prostate IMRT based on an empty rectum and deliver treatment to patients with an empty rectum. Over 70% of actual treatments showed better rectal doses than our clinical acceptance criteria. A significant fraction (27%) of the actual treatments would benefit from adaptive image-guided radiotherapy based on daily CT images.
Total Variation Based Parameter-Free Model for Impulse Noise Removal
DEFF Research Database (Denmark)
Sciacchitano, Federica; Dong, Yiqiu; Andersen, Martin Skovgaard
2017-01-01
We propose a new two-phase method for reconstruction of blurred images corrupted by impulse noise. In the first phase, we use a noise detector to identify the pixels that are contaminated by noise, and then, in the second phase, we reconstruct the noisy pixels by solving an equality constrained...... total variation minimization problem that preserves the exact values of the noise-free pixels. For images that are only corrupted by impulse noise (i. e., not blurred) we apply the semismooth Newton's method to a reduced problem, and if the images are also blurred, we solve the equality constrained...... reconstruction problem using a first-order primal-dual algorithm. The proposed model improves the computational efficiency (in the denoising case) and has the advantage of being regularization parameter-free. Our numerical results suggest that the method is competitive in terms of its restoration capabilities...
Viale, Alberto; Villa, Dario
2011-03-01
Recently stereoscopy has increased a lot its popularity and various technologies are spreading in theaters and homes allowing observation of stereoscopic images and movies, becoming affordable even for home users. However there are some golden rules that users should follow to ensure a better enjoyment of stereoscopic images, first of all the viewing condition should not be too different from the ideal ones, which were assumed during the production process. To allow the user to perceive stereo depth instead of a flat image, two different views of the same scene are shown to the subject, one is seen just through his left eye and the other just through the right one; the vision process is making the work of merging the two images in a virtual three-dimensional scene, giving to the user the perception of depth. The two images presented to the user were created, either from image synthesis or from more traditional techniques, following the rules of perspective. These rules need some boundary conditions to be explicit, such as eye separation, field of view, parallax distance, viewer position and orientation. In this paper we are interested in studying how the variation of the viewer position and orientation from the ideal ones expressed as specified parameters in the image creation process, is affecting the correctness of the reconstruction of the three-dimensional virtual scene.
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.
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.
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.
Human cerebral cortices: signal variation on diffusion-weighted MR imaging
Energy Technology Data Exchange (ETDEWEB)
Asao, Chiaki [Kumamoto Regional Medical Center, Department of Radiology, Kumamoto (Japan); National Hospital Organization Kumamoto Medical Center, Department of Radiology, Kumamoto (Japan); Hirai, Toshinori; Yamashita, Yasuyuki [Kumamoto University Graduate School of Medical Sciences, Department of Diagnostic Radiology, Kumamoto (Japan); Yoshimatsu, Shunji [National Hospital Organization Kumamoto Medical Center, Department of Radiology, Kumamoto (Japan); Matsukawa, Tetsuya; Imuta, Masanori [Kumamoto Regional Medical Center, Department of Radiology, Kumamoto (Japan); Sagara, Katsuro [Kumamoto Regional Medical Center, Department of Internal Medicine, Kumamoto (Japan)
2008-03-15
We have often encountered high signal intensity (SI) of the cingulate gyrus and insula during diffusion-weighted magnetic resonance imaging (DW-MRI) on neurologically healthy adults. To date, cortical signal heterogeneity on DW images has not been investigated systematically. The purpose of our study was to determine whether there is regional signal variation in the brain cortices of neurologically healthy adults on DW-MR images. The SI of the cerebral cortices on DW-MR images at 1.5 T was evaluated in 50 neurologically healthy subjects (34 men, 16 women; age range 33-84 years; mean age 57.6 years). The cortical SI in the cingulate gyrus, insula, and temporal, occipital, and parietal lobes was graded relative to the SI of the frontal lobe. Contrast-to-noise ratios (CNRs) on DW-MR images were compared for each cortical area. Diffusion changes were analyzed by visually assessment of the differences in appearance among the cortices on apparent diffusion coefficient (ADC) maps. Increased SI was frequently seen in the cingulate gyrus and insula regardless of patient age. There were no significant gender- or laterality-related differences. The CNR was significantly higher in the cingulate gyrus and insula than in the other cortices (p <.01), and significant differences existed among the cortical regions (p <.001). There were no apparent ADC differences among the cortices on ADC maps. Regional signal variation of the brain cortices was observed on DW-MR images of healthy subjects, and the cingulate gyrus and insula frequently manifested high SI. These findings may help in the recognition of cortical signal abnormalities as visualized on DW-MR images. (orig.)
Human cerebral cortices: signal variation on diffusion-weighted MR imaging
International Nuclear Information System (INIS)
Asao, Chiaki; Hirai, Toshinori; Yamashita, Yasuyuki; Yoshimatsu, Shunji; Matsukawa, Tetsuya; Imuta, Masanori; Sagara, Katsuro
2008-01-01
We have often encountered high signal intensity (SI) of the cingulate gyrus and insula during diffusion-weighted magnetic resonance imaging (DW-MRI) on neurologically healthy adults. To date, cortical signal heterogeneity on DW images has not been investigated systematically. The purpose of our study was to determine whether there is regional signal variation in the brain cortices of neurologically healthy adults on DW-MR images. The SI of the cerebral cortices on DW-MR images at 1.5 T was evaluated in 50 neurologically healthy subjects (34 men, 16 women; age range 33-84 years; mean age 57.6 years). The cortical SI in the cingulate gyrus, insula, and temporal, occipital, and parietal lobes was graded relative to the SI of the frontal lobe. Contrast-to-noise ratios (CNRs) on DW-MR images were compared for each cortical area. Diffusion changes were analyzed by visually assessment of the differences in appearance among the cortices on apparent diffusion coefficient (ADC) maps. Increased SI was frequently seen in the cingulate gyrus and insula regardless of patient age. There were no significant gender- or laterality-related differences. The CNR was significantly higher in the cingulate gyrus and insula than in the other cortices (p <.01), and significant differences existed among the cortical regions (p <.001). There were no apparent ADC differences among the cortices on ADC maps. Regional signal variation of the brain cortices was observed on DW-MR images of healthy subjects, and the cingulate gyrus and insula frequently manifested high SI. These findings may help in the recognition of cortical signal abnormalities as visualized on DW-MR images. (orig.)
Modeling of electron time variations in the radiation belts
International Nuclear Information System (INIS)
Chan, K.W.; Teague, M.J.; Schofield, N.J.; Vette, J.I.
1979-01-01
A review of the temporal variation in the trapped electron population of the inner and outer radiation zones is presented. Techniques presently used for modeling these zones are discussed and their deficiencies identified. An intermediate region is indicated between the zones in which the present modeling techniques are inadequate due to the magnitude and frequency of magnetic storms. Future trends are examined, and it is suggested that modeling of individual magnetic storms may be required in certain L bands. An analysis of seven magnetic storms is presented, establishing the independence of the depletion time of the storm flux and the storm magnitude. Provisional correlation between the storm magnitude and the Dst index is demonstrated
Variations of little Higgs models and their electroweak constraints
International Nuclear Information System (INIS)
Csaki, Csaba; Hubisz, Jay; Meade, Patrick; Kribs, Graham D.; Terning, John
2003-01-01
We calculate the tree-level electroweak precision constraints on a wide class of little Higgs models including variations of the littlest Higgs SU(5)/SO(5), SU(6)/Sp(6), and SU(4) 4 /SU(3) 4 models. By performing a global fit to the precision data we find that for generic regions of the parameter space the bound on the symmetry breaking scale f is several TeV, where we have kept the normalization of f constant in the different models. For example, the 'minimal' implementation of SU(6)/Sp(6) is bounded by f>3.0 TeV throughout most of the parameter space, and SU(4) 4 /SU(3) 4 is bounded by f 2 ≡f 1 2 +f 2 2 >(4.2 TeV) 2 . In certain models, such as SU(4) 4 /SU(3) 4 , a large f does not directly imply a large amount of fine-tuning since the heavy-fermion masses that contribute to the Higgs boson mass can be lowered below f for a carefully chosen set of parameters. We also find that for certain models (or variations) there exist regions of parameter space in which the bound on f can be lowered into the range 1-2 TeV. These regions are typically characterized by a small mixing between heavy and standard model gauge bosons and a small (or vanishing) coupling between heavy U(1) gauge bosons and light fermions. Whether such a region of parameter space is natural or not is ultimately contingent on the UV completion
Residential radon in Finland: sources, variation, modelling and dose comparisons
Energy Technology Data Exchange (ETDEWEB)
Arvela, H
1995-09-01
The study deals with sources of indoor radon in Finland, seasonal variations in radon concentration, the effect of house construction and ventilation and also with the radiation dose from indoor radon and terrestrial gamma radiation. The results are based on radon measurements in approximately 4000 dwellings and on air exchange measurements in 250 dwellings as well as on model calculations. The results confirm that convective soil air flow is by far the most important source of indoor radon in Finnish low-rise residential housing. (97 refs., 61 figs., 30 tabs.).
Residential radon in Finland: sources, variation, modelling and dose comparisons
International Nuclear Information System (INIS)
Arvela, H.
1995-09-01
The study deals with sources of indoor radon in Finland, seasonal variations in radon concentration, the effect of house construction and ventilation and also with the radiation dose from indoor radon and terrestrial gamma radiation. The results are based on radon measurements in approximately 4000 dwellings and on air exchange measurements in 250 dwellings as well as on model calculations. The results confirm that convective soil air flow is by far the most important source of indoor radon in Finnish low-rise residential housing. (97 refs., 61 figs., 30 tabs.)
A Combined First and Second Order Variational Approach for Image Reconstruction
Papafitsoros, K.; Schö nlieb, C. B.
2013-01-01
the creation of undesirable artifacts and blocky-like structures in the reconstructed images-a known disadvantage of the ROF model-while being simple and efficiently numerically solvable. ©Springer Science+Business Media New York 2013.
A variational multiscale constitutive model for nanocrystalline materials
Gurses, Ercan
2011-03-01
This paper presents a variational multi-scale constitutive model in the finite deformation regime capable of capturing the mechanical behavior of nanocrystalline (nc) fcc metals. The nc-material is modeled as a two-phase material consisting of a grain interior phase and a grain boundary effected zone (GBAZ). A rate-independent isotropic porous plasticity model is employed to describe the GBAZ, whereas a crystal-plasticity model which accounts for the transition from partial dislocation to full dislocation mediated plasticity is employed for the grain interior. The constitutive models of both phases are formulated in a small strain framework and extended to finite deformation by use of logarithmic and exponential mappings. Assuming the rule of mixtures, the overall behavior of a given grain is obtained via volume averaging. The scale transition from a single grain to a polycrystal is achieved by Taylor-type homogenization where a log-normal grain size distribution is assumed. It is shown that the proposed model is able to capture the inverse HallPetch effect, i.e., loss of strength with grain size refinement. Finally, the predictive capability of the model is validated against experimental results on nanocrystalline copper and nickel. © 2010 Elsevier Ltd. All rights reserved.
High-resolution magnetic resonance imaging of diurnal variations in rheumatoid arthritis
International Nuclear Information System (INIS)
Nicholas, R.S.
2000-09-01
This thesis describes work that uses high-resolution magnetic resonance imaging (MRI) to give an insight into the aetiology of rheumatoid arthritis (RA) with particular reference to characterising diurnal changes in joint stiffness in the metacarpophalangeal (MCP) joints. The study was performed on a targeted 1.1 T MRI scanner using specialised sequences, including 3-dimensional gradient-echo, magnetisation transfer (MT) and multiple gradient-echo. These enabled tissue-dependent parameters such as MT ratio, effective transverse relaxation time (T 2 *) and proton density (ρ) to be made. Preliminary reproducibility studies of the MRI measurements showed that MT ratio could be measured in vivo to an accuracy of better than 8%. This variation is due to repositioning errors and physiological changes. Equivalent variations in T 2 * and p were 23% and 16% respectively; these poorer figures were contributed to errors in fitting the data to an exponential curve. An MRI study monitoring the diurnal variation of stiffness in RA demonstrated better characterisation of the disease state using MT and T 2 * maps compared to standard gradient-echo imaging. Features associated with arthritis such as bone erosions and cysts were found in the control group and an MT age dependence was measured in the soft tissue on the superior margin of the joint. This region also exhibited a diurnal variation in MT ratio for the patient group. The interaction between this region of tissue and other structures (e.g. the sheath of extensor tendon) within the joint could be a possible cause of joint stiffness. An incidental finding of this study was that Ritchie joint score also showed a diurnal variation. This study has demonstrated that MRI can be used to make reproducible measurements of the diurnal variations in RA. The indication is that the soft tissues in the superior aspect of the joint may be responsible for the symptom of joint stiffness in the MCP joints and future studies should be
Tang, Jian; Jiang, Xiaoliang
2017-01-01
Image segmentation has always been a considerable challenge in image analysis and understanding due to the intensity inhomogeneity, which is also commonly known as bias field. In this paper, we present a novel region-based approach based on local entropy for segmenting images and estimating the bias field simultaneously. Firstly, a local Gaussian distribution fitting (LGDF) energy function is defined as a weighted energy integral, where the weight is local entropy derived from a grey level distribution of local image. The means of this objective function have a multiplicative factor that estimates the bias field in the transformed domain. Then, the bias field prior is fully used. Therefore, our model can estimate the bias field more accurately. Finally, minimization of this energy function with a level set regularization term, image segmentation, and bias field estimation can be achieved. Experiments on images of various modalities demonstrated the superior performance of the proposed method when compared with other state-of-the-art approaches.
Solving Quasi-Variational Inequalities for Image Restoration with Adaptive Constraint Sets
Lenzen, F.
2014-01-01
© 2014 Society for Industrial and Applied Mathematics. We consider a class of quasi-variational inequalities (QVIs) for adaptive image restoration, where the adaptivity is described via solution-dependent constraint sets. In previous work we studied both theoretical and numerical issues. While we were able to show the existence of solutions for a relatively broad class of problems, we encountered difficulties concerning uniqueness of the solution as well as convergence of existing algorithms for solving QVIs. In particular, it seemed that with increasing image size the growing condition number of the involved differential operator posed severe problems. In the present paper we prove uniqueness for a larger class of problems, particularly independent of the image size. Moreover, we provide a numerical algorithm with proved convergence. Experimental results support our theoretical findings.
Gamma-variate modeling of indicator dilution curves in electrical impedance tomography.
Hentze, Benjamin; Muders, Thomas; Luepschen, Henning; Leonhardt, Steffen; Putensen, Christian; Walter, Marian
2017-07-01
Electrical impedance tomography (EIT) is a non-invasive imaging technique, that can be used to monitor regional lung ventilation (V̇) in intensive care units (ICU) at bedside. This work introduces a method to extract regional lung perfusion (Q̇) from EIT image streams in order to quantify regional gas exchange in the lungs. EIT data from a single porcine animal trial, recorded during injection of a contrast agent (NaCl 10%) into a central venous catheter (CVC), are used for evaluation. Using semi-negative matrix factorization (Semi-NMF) a set of source signals is extracted from the data. A subsequent non-linear fit of a gamma-variate model to the source signals results in model signals, describing contrast agent flow through the cardio-pulmonary system. A linear fit of the model signals to the EIT image stream then yields functional images ofQ̇. Additionally, a pulmonary transit function (PTF) and parameters, such as mean transit time (MTT), time to peak (TTP) and area under curve (AUC) are derived. In result, EIT was used to track changes of regional lung ventilation to perfusion ratio (V̇/Q̇) during changes of positive end-expiratory pressure (PEEP). Furthermore, correlations of MTT and AUC with cardiac output (CO) indicate that CO measurement by EIT might be possible.
A Variational Approach to the Modeling of MIMO Systems
Directory of Open Access Journals (Sweden)
Jraifi A
2007-01-01
Full Text Available Motivated by the study of the optimization of the quality of service for multiple input multiple output (MIMO systems in 3G (third generation, we develop a method for modeling MIMO channel . This method, which uses a statistical approach, is based on a variational form of the usual channel equation. The proposed equation is given by with scalar variable . Minimum distance of received vectors is used as the random variable to model MIMO channel. This variable is of crucial importance for the performance of the transmission system as it captures the degree of interference between neighbors vectors. Then, we use this approach to compute numerically the total probability of errors with respect to signal-to-noise ratio (SNR and then predict the numbers of antennas. By fixing SNR variable to a specific value, we extract informations on the optimal numbers of MIMO antennas.
Image-Based Models for Specularity Propagation in Diminished Reality.
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.
Directory of Open Access Journals (Sweden)
Shi Jun
2015-02-01
Full Text Available Downward-looking Linear Array Synthetic Aperture Radar (LASAR has many potential applications in the topographic mapping, disaster monitoring and reconnaissance applications, especially in the mountainous area. However, limited by the sizes of platforms, its resolution in the linear array direction is always far lower than those in the range and azimuth directions. This disadvantage leads to the blurring of Three-Dimensional (3D images in the linear array direction, and restricts the application of LASAR. To date, the research on 3D SAR image enhancement has focused on the sparse recovery technique. In this case, the one-to-one mapping of Digital Elevation Model (DEM brakes down. To overcome this, an optimal DEM reconstruction method for LASAR based on the variational model is discussed in an effort to optimize the DEM and the associated scattering coefficient map, and to minimize the Mean Square Error (MSE. Using simulation experiments, it is found that the variational model is more suitable for DEM enhancement applications to all kinds of terrains compared with the Orthogonal Matching Pursuit (OMPand Least Absolute Shrinkage and Selection Operator (LASSO methods.
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....
Effect of camera temperature variations on stereo-digital image correlation measurements
Pan, Bing
2015-11-25
In laboratory and especially non-laboratory stereo-digital image correlation (stereo-DIC) applications, the extrinsic and intrinsic parameters of the cameras used in the system may change slightly due to the camera warm-up effect and possible variations in ambient temperature. Because these camera parameters are generally calibrated once prior to measurements and considered to be unaltered during the whole measurement period, the changes in these parameters unavoidably induce displacement/strain errors. In this study, the effect of temperature variations on stereo-DIC measurements is investigated experimentally. To quantify the errors associated with camera or ambient temperature changes, surface displacements and strains of a stationary optical quartz glass plate with near-zero thermal expansion were continuously measured using a regular stereo-DIC system. The results confirm that (1) temperature variations in the cameras and ambient environment have a considerable influence on the displacements and strains measured by stereo-DIC due to the slightly altered extrinsic and intrinsic camera parameters; and (2) the corresponding displacement and strain errors correlate with temperature changes. For the specific stereo-DIC configuration used in this work, the temperature-induced strain errors were estimated to be approximately 30–50 με/°C. To minimize the adverse effect of camera temperature variations on stereo-DIC measurements, two simple but effective solutions are suggested.
Effect of camera temperature variations on stereo-digital image correlation measurements
Pan, Bing; Shi, Wentao; Lubineau, Gilles
2015-01-01
In laboratory and especially non-laboratory stereo-digital image correlation (stereo-DIC) applications, the extrinsic and intrinsic parameters of the cameras used in the system may change slightly due to the camera warm-up effect and possible variations in ambient temperature. Because these camera parameters are generally calibrated once prior to measurements and considered to be unaltered during the whole measurement period, the changes in these parameters unavoidably induce displacement/strain errors. In this study, the effect of temperature variations on stereo-DIC measurements is investigated experimentally. To quantify the errors associated with camera or ambient temperature changes, surface displacements and strains of a stationary optical quartz glass plate with near-zero thermal expansion were continuously measured using a regular stereo-DIC system. The results confirm that (1) temperature variations in the cameras and ambient environment have a considerable influence on the displacements and strains measured by stereo-DIC due to the slightly altered extrinsic and intrinsic camera parameters; and (2) the corresponding displacement and strain errors correlate with temperature changes. For the specific stereo-DIC configuration used in this work, the temperature-induced strain errors were estimated to be approximately 30–50 με/°C. To minimize the adverse effect of camera temperature variations on stereo-DIC measurements, two simple but effective solutions are suggested.
Modeling temperature variations in a pilot plant thermophilic anaerobic digester.
Valle-Guadarrama, Salvador; Espinosa-Solares, Teodoro; López-Cruz, Irineo L; Domaschko, Max
2011-05-01
A model that predicts temperature changes in a pilot plant thermophilic anaerobic digester was developed based on fundamental thermodynamic laws. The methodology utilized two simulation strategies. In the first, model equations were solved through a searching routine based on a minimal square optimization criterion, from which the overall heat transfer coefficient values, for both biodigester and heat exchanger, were determined. In the second, the simulation was performed with variable values of these overall coefficients. The prediction with both strategies allowed reproducing experimental data within 5% of the temperature span permitted in the equipment by the system control, which validated the model. The temperature variation was affected by the heterogeneity of the feeding and extraction processes, by the heterogeneity of the digestate recirculation through the heating system and by the lack of a perfect mixing inside the biodigester tank. The use of variable overall heat transfer coefficients improved the temperature change prediction and reduced the effect of a non-ideal performance of the pilot plant modeled.
Discrete Variational Approach for Modeling Laser-Plasma Interactions
Reyes, J. Paxon; Shadwick, B. A.
2014-10-01
The traditional approach for fluid models of laser-plasma interactions begins by approximating fields and derivatives on a grid in space and time, leading to difference equations that are manipulated to create a time-advance algorithm. In contrast, by introducing the spatial discretization at the level of the action, the resulting Euler-Lagrange equations have particular differencing approximations that will exactly satisfy discrete versions of the relevant conservation laws. For example, applying a spatial discretization in the Lagrangian density leads to continuous-time, discrete-space equations and exact energy conservation regardless of the spatial grid resolution. We compare the results of two discrete variational methods using the variational principles from Chen and Sudan and Brizard. Since the fluid system conserves energy and momentum, the relative errors in these conserved quantities are well-motivated physically as figures of merit for a particular method. This work was supported by the U. S. Department of Energy under Contract No. DE-SC0008382 and by the National Science Foundation under Contract No. PHY-1104683.
Tomarelli, Franco
1996-01-01
In recent years many researchers in material science have focused their attention on the study of composite materials, equilibrium of crystals and crack distribution in continua subject to loads. At the same time several new issues in computer vision and image processing have been studied in depth. The understanding of many of these problems has made significant progress thanks to new methods developed in calculus of variations, geometric measure theory and partial differential equations. In particular, new technical tools have been introduced and successfully applied. For example, in order to describe the geometrical complexity of unknown patterns, a new class of problems in calculus of variations has been introduced together with a suitable functional setting: the free-discontinuity problems and the special BV and BH functions. The conference held at Villa Olmo on Lake Como in September 1994 spawned successful discussion of these topics among mathematicians, experts in computer science and material scientis...
Two-dimensional strain gradient damage modeling: a variational approach
Placidi, Luca; Misra, Anil; Barchiesi, Emilio
2018-06-01
In this paper, we formulate a linear elastic second gradient isotropic two-dimensional continuum model accounting for irreversible damage. The failure is defined as the condition in which the damage parameter reaches 1, at least in one point of the domain. The quasi-static approximation is done, i.e., the kinetic energy is assumed to be negligible. In order to deal with dissipation, a damage dissipation term is considered in the deformation energy functional. The key goal of this paper is to apply a non-standard variational procedure to exploit the damage irreversibility argument. As a result, we derive not only the equilibrium equations but, notably, also the Karush-Kuhn-Tucker conditions. Finally, numerical simulations for exemplary problems are discussed as some constitutive parameters are varying, with the inclusion of a mesh-independence evidence. Element-free Galerkin method and moving least square shape functions have been employed.
Modeling Geomagnetic Variations using a Machine Learning Framework
Cheung, C. M. M.; Handmer, C.; Kosar, B.; Gerules, G.; Poduval, B.; Mackintosh, G.; Munoz-Jaramillo, A.; Bobra, M.; Hernandez, T.; McGranaghan, R. M.
2017-12-01
We present a framework for data-driven modeling of Heliophysics time series data. The Solar Terrestrial Interaction Neural net Generator (STING) is an open source python module built on top of state-of-the-art statistical learning frameworks (traditional machine learning methods as well as deep learning). To showcase the capability of STING, we deploy it for the problem of predicting the temporal variation of geomagnetic fields. The data used includes solar wind measurements from the OMNI database and geomagnetic field data taken by magnetometers at US Geological Survey observatories. We examine the predictive capability of different machine learning techniques (recurrent neural networks, support vector machines) for a range of forecasting times (minutes to 12 hours). STING is designed to be extensible to other types of data. We show how STING can be used on large sets of data from different sensors/observatories and adapted to tackle other problems in Heliophysics.
Seasonal and spatial variation in broadleaf forest model parameters
Groenendijk, M.; van der Molen, M. K.; Dolman, A. J.
2009-04-01
Process based, coupled ecosystem carbon, energy and water cycle models are used with the ultimate goal to project the effect of future climate change on the terrestrial carbon cycle. A typical dilemma in such exercises is how much detail the model must be given to describe the observations reasonably realistic while also be general. We use a simple vegetation model (5PM) with five model parameters to study the variability of the parameters. These parameters are derived from the observed carbon and water fluxes from the FLUXNET database. For 15 broadleaf forests the model parameters were derived for different time resolutions. It appears that in general for all forests, the correlation coefficient between observed and simulated carbon and water fluxes improves with a higher parameter time resolution. The quality of the simulations is thus always better when a higher time resolution is used. These results show that annual parameters are not capable of properly describing weather effects on ecosystem fluxes, and that two day time resolution yields the best results. A first indication of the climate constraints can be found by the seasonal variation of the covariance between Jm, which describes the maximum electron transport for photosynthesis, and climate variables. A general seasonality we found is that during winter the covariance with all climate variables is zero. Jm increases rapidly after initial spring warming, resulting in a large covariance with air temperature and global radiation. During summer Jm is less variable, but co-varies negatively with air temperature and vapour pressure deficit and positively with soil water content. A temperature response appears during spring and autumn for broadleaf forests. This shows that an annual model parameter cannot be representative for the entire year. And relations with mean annual temperature are not possible. During summer the photosynthesis parameters are constrained by water availability, soil water content and
Modeling seasonal surface temperature variations in secondary tropical dry forests
Cao, Sen; Sanchez-Azofeifa, Arturo
2017-10-01
Secondary tropical dry forests (TDFs) provide important ecosystem services such as carbon sequestration, biodiversity conservation, and nutrient cycle regulation. However, their biogeophysical processes at the canopy-atmosphere interface remain unknown, limiting our understanding of how this endangered ecosystem influences, and responds to the ongoing global warming. To facilitate future development of conservation policies, this study characterized the seasonal land surface temperature (LST) behavior of three successional stages (early, intermediate, and late) of a TDF, at the Santa Rosa National Park (SRNP), Costa Rica. A total of 38 Landsat-8 Thermal Infrared Sensor (TIRS) data and the Surface Reflectance (SR) product were utilized to model LST time series from July 2013 to July 2016 using a radiative transfer equation (RTE) algorithm. We further related the LST time series to seven vegetation indices which reflect different properties of TDFs, and soil moisture data obtained from a Wireless Sensor Network (WSN). Results showed that the LST in the dry season was 15-20 K higher than in the wet season at SRNP. We found that the early successional stages were about 6-8 K warmer than the intermediate successional stages and were 9-10 K warmer than the late successional stages in the middle of the dry season; meanwhile, a minimum LST difference (0-1 K) was observed at the end of the wet season. Leaf phenology and canopy architecture explained most LST variations in both dry and wet seasons. However, our analysis revealed that it is precipitation that ultimately determines the LST variations through both biogeochemical (leaf phenology) and biogeophysical processes (evapotranspiration) of the plants. Results of this study could help physiological modeling studies in secondary TDFs.
Photometric Modeling of Simulated Surace-Resolved Bennu Images
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
Modeling Wettability Variation during Long-Term Water Flooding
Directory of Open Access Journals (Sweden)
Renyi Cao
2015-01-01
Full Text Available Surface property of rock affects oil recovery during water flooding. Oil-wet polar substances adsorbed on the surface of the rock will gradually be desorbed during water flooding, and original reservoir wettability will change towards water-wet, and the change will reduce the residual oil saturation and improve the oil displacement efficiency. However there is a lack of an accurate description of wettability alternation model during long-term water flooding and it will lead to difficulties in history match and unreliable forecasts using reservoir simulators. This paper summarizes the mechanism of wettability variation and characterizes the adsorption of polar substance during long-term water flooding from injecting water or aquifer and relates the residual oil saturation and relative permeability to the polar substance adsorbed on clay and pore volumes of flooding water. A mathematical model is presented to simulate the long-term water flooding and the model is validated with experimental results. The simulation results of long-term water flooding are also discussed.
Digital Image Stabilization Method Based on Variational Mode Decomposition and Relative Entropy
Directory of Open Access Journals (Sweden)
Duo Hao
2017-11-01
Full Text Available Cameras mounted on vehicles frequently suffer from image shake due to the vehicles’ motions. To remove jitter motions and preserve intentional motions, a hybrid digital image stabilization method is proposed that uses variational mode decomposition (VMD and relative entropy (RE. In this paper, the global motion vector (GMV is initially decomposed into several narrow-banded modes by VMD. REs, which exhibit the difference of probability distribution between two modes, are then calculated to identify the intentional and jitter motion modes. Finally, the summation of the jitter motion modes constitutes jitter motions, whereas the subtraction of the resulting sum from the GMV represents the intentional motions. The proposed stabilization method is compared with several known methods, namely, medium filter (MF, Kalman filter (KF, wavelet decomposition (MD method, empirical mode decomposition (EMD-based method, and enhanced EMD-based method, to evaluate stabilization performance. Experimental results show that the proposed method outperforms the other stabilization methods.
Yu, Haiqing; Chen, Shuhang; Chen, Yunmei; Liu, Huafeng
2017-05-01
Dynamic positron emission tomography (PET) is capable of providing both spatial and temporal information of radio tracers in vivo. In this paper, we present a novel joint estimation framework to reconstruct temporal sequences of dynamic PET images and the coefficients characterizing the system impulse response function, from which the associated parametric images of the system macro parameters for tracer kinetics can be estimated. The proposed algorithm, which combines statistical data measurement and tracer kinetic models, integrates a dictionary sparse coding (DSC) into a total variational minimization based algorithm for simultaneous reconstruction of the activity distribution and parametric map from measured emission sinograms. DSC, based on the compartmental theory, provides biologically meaningful regularization, and total variation regularization is incorporated to provide edge-preserving guidance. We rely on techniques from minimization algorithms (the alternating direction method of multipliers) to first generate the estimated activity distributions with sub-optimal kinetic parameter estimates, and then recover the parametric maps given these activity estimates. These coupled iterative steps are repeated as necessary until convergence. Experiments with synthetic, Monte Carlo generated data, and real patient data have been conducted, and the results are very promising.
Energy Technology Data Exchange (ETDEWEB)
Li, L; Tan, S [Huazhong University of Science and Technology, Wuhan, Hubei (China); Lu, W [University of Maryland School of Medicine, Baltimore, MD (United States)
2015-06-15
Purpose: To propose a new variational method which couples image restoration with tumor segmentation for PET images using multiple regularizations. Methods: Partial volume effect (PVE) is a major degrading factor impacting tumor segmentation accuracy in PET imaging. The existing segmentation methods usually need to take prior calibrations to compensate PVE and they are highly system-dependent. Taking into account that image restoration and segmentation can promote each other and they are tightly coupled, we proposed a variational method to solve the two problems together. Our method integrated total variation (TV) semi-blind deconvolution and Mumford-Shah (MS) segmentation. The TV norm was used on edges to protect the edge information, and the L{sub 2} norm was used to avoid staircase effect in the no-edge area. The blur kernel was constrained to the Gaussian model parameterized by its variance and we assumed that the variances in the X-Y and Z directions are different. The energy functional was iteratively optimized by an alternate minimization algorithm. Segmentation performance was tested on eleven patients with non-Hodgkin’s lymphoma, and evaluated by Dice similarity index (DSI) and classification error (CE). For comparison, seven other widely used methods were also tested and evaluated. Results: The combination of TV and L{sub 2} regularizations effectively improved the segmentation accuracy. The average DSI increased by around 0.1 than using either the TV or the L{sub 2} norm. The proposed method was obviously superior to other tested methods. It has an average DSI and CE of 0.80 and 0.41, while the FCM method — the second best one — has only an average DSI and CE of 0.66 and 0.64. Conclusion: Coupling image restoration and segmentation can handle PVE and thus improves tumor segmentation accuracy in PET. Alternate use of TV and L2 regularizations can further improve the performance of the algorithm. This work was supported in part by National Natural
Schlaffke, Lara; Rehmann, Robert; Froeling, Martijn; Kley, Rudolf; Tegenthoff, Martin; Vorgerd, Matthias; Schmidt-Wilcke, Tobias
2017-10-01
To investigate to what extent inter- and intramuscular variations of diffusion parameters of human calf muscles can be explained by age, gender, muscle location, and body mass index (BMI) in a specific age group (20-35 years). Whole calf muscles of 18 healthy volunteers were evaluated. Magnetic resonance imaging (MRI) was performed using a 3T scanner and a 16-channel Torso XL coil. Diffusion-weighted images were acquired to perform fiber tractography and diffusion tensor imaging (DTI) analysis for each muscle of both legs. Fiber tractography was used to separate seven lower leg muscles. Associations between DTI parameters and confounds were evaluated. All muscles were additionally separated in seven identical segments along the z-axis to evaluate intramuscular differences in diffusion parameters. Fractional anisotropy (FA) and mean diffusivity (MD) were obtained for each muscle with low standard deviations (SDs) (SD FA : 0.01-0.02; SD MD : 0.07-0.14(10 -3 )). We found significant differences in FA values of the tibialis anterior muscle (AT) and extensor digitorum longus (EDL) muscles between men and women for whole muscle FA (two-sample t-tests; AT: P = 0.0014; EDL: P = 0.0004). We showed significant intramuscular differences in diffusion parameters between adjacent segments in most calf muscles (P < 0.001). Whereas muscle insertions showed higher (SD 0.03-0.06) than muscle bellies (SD 0.01-0.03), no relationships between FA or MD with age or BMI were found. Inter- and intramuscular variations in diffusion parameters of the calf were shown, which are not related to age or BMI in this age group. Differences between muscle belly and insertion should be considered when interpreting datasets not including whole muscles. 3 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1137-1148. © 2017 International Society for Magnetic Resonance in Medicine.
International Nuclear Information System (INIS)
Sidky, Emil Y; Pan Xiaochuan
2008-01-01
An iterative algorithm, based on recent work in compressive sensing, is developed for volume image reconstruction from a circular cone-beam scan. The algorithm minimizes the total variation (TV) of the image subject to the constraint that the estimated projection data is within a specified tolerance of the available data and that the values of the volume image are non-negative. The constraints are enforced by the use of projection onto convex sets (POCS) and the TV objective is minimized by steepest descent with an adaptive step-size. The algorithm is referred to as adaptive-steepest-descent-POCS (ASD-POCS). It appears to be robust against cone-beam artifacts, and may be particularly useful when the angular range is limited or when the angular sampling rate is low. The ASD-POCS algorithm is tested with the Defrise disk and jaw computerized phantoms. Some comparisons are performed with the POCS and expectation-maximization (EM) algorithms. Although the algorithm is presented in the context of circular cone-beam image reconstruction, it can also be applied to scanning geometries involving other x-ray source trajectories
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....
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.)
Nonparametric Mixture Models for Supervised Image Parcellation.
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.
International Nuclear Information System (INIS)
Parent, Laure; Seco, Joao; Evans, Phil M.; Fielding, Andrew; Dance, David R.
2006-01-01
This study focused on predicting the electronic portal imaging device (EPID) image of intensity modulated radiation treatment (IMRT) fields in the absence of attenuation material in the beam with Monte Carlo methods. As IMRT treatments consist of a series of segments of various sizes that are not always delivered on the central axis, large spectral variations may be observed between the segments. The effect of these spectral variations on the EPID response was studied with fields of various sizes and off-axis positions. A detailed description of the EPID was implemented in a Monte Carlo model. The EPID model was validated by comparing the EPID output factors for field sizes between 1x1 and 26x26 cm 2 at the isocenter. The Monte Carlo simulations agreed with the measurements to within 1.5%. The Monte Carlo model succeeded in predicting the EPID response at the center of the fields of various sizes and offsets to within 1% of the measurements. Large variations (up to 29%) of the EPID response were observed between the various offsets. The EPID response increased with field size and with field offset for most cases. The Monte Carlo model was then used to predict the image of a simple test IMRT field delivered on the beam axis and with an offset. A variation of EPID response up to 28% was found between the on- and off-axis delivery. Finally, two clinical IMRT fields were simulated and compared to the measurements. For all IMRT fields, simulations and measurements agreed within 3%--0.2 cm for 98% of the pixels. The spectral variations were quantified by extracting from the spectra at the center of the fields the total photon yield (Y total ), the photon yield below 1 MeV (Y low ), and the percentage of photons below 1 MeV (P low ). For the studied cases, a correlation was shown between the EPID response variation and Y total , Y low , and P low
Modelling basin-wide variations in Amazon forest photosynthesis
Mercado, Lina; Lloyd, Jon; Domingues, Tomas; Fyllas, Nikolaos; Patino, Sandra; Dolman, Han; Sitch, Stephen
2010-05-01
Given the importance of Amazon rainforest in the global carbon and hydrological cycles, there is a need to use parameterized and validated ecosystem gas exchange and vegetation models for this region in order to adequately simulate present and future carbon and water balances. Recent research has found major differences in above-ground net primary productivity (ANPP), above ground biomass and tree dynamics across Amazonia. West Amazonia is more dynamic, with younger trees, higher stem growth rates and lower biomass than central and eastern Amazon (Baker et al. 2004; Malhi et al. 2004; Phillips et al. 2004). A factor of three variation in above-ground net primary productivity has been estimated across Amazonia by Malhi et al. (2004). Different hypotheses have been proposed to explain the observed spatial variability in ANPP (Malhi et al. 2004). First, due to the proximity to the Andes, sites from western Amazonia tend to have richer soils than central and eastern Amazon and therefore soil fertility could possibly be highly related to the high wood productivity found in western sites. Second, if GPP does not vary across the Amazon basin then different patterns of carbon allocation to respiration could also explain the observed ANPP gradient. However since plant growth depends on the interaction between photosynthesis, transport of assimilates, plant respiration, water relations and mineral nutrition, variations in plant gross photosynthesis (GPP) could also explain the observed variations in ANPP. In this study we investigate whether Amazon GPP can explain variations of observed ANPP. We use a sun and shade canopy gas exchange model that has been calibrated and evaluated at five rainforest sites (Mercado et al. 2009) to simulate gross primary productivity of 50 sites across the Amazon basin during the period 1980-2001. Such simulation differs from the ones performed with global vegetation models (Cox et al. 1998; Sitch et al. 2003) where i) single plant functional
On well-posedness of variational models of charged drops.
Muratov, Cyrill B; Novaga, Matteo
2016-03-01
Electrified liquids are well known to be prone to a variety of interfacial instabilities that result in the onset of apparent interfacial singularities and liquid fragmentation. In the case of electrically conducting liquids, one of the basic models describing the equilibrium interfacial configurations and the onset of instability assumes the liquid to be equipotential and interprets those configurations as local minimizers of the energy consisting of the sum of the surface energy and the electrostatic energy. Here we show that, surprisingly, this classical geometric variational model is mathematically ill-posed irrespective of the degree to which the liquid is electrified. Specifically, we demonstrate that an isolated spherical droplet is never a local minimizer, no matter how small is the total charge on the droplet, as the energy can always be lowered by a smooth, arbitrarily small distortion of the droplet's surface. This is in sharp contrast to the experimental observations that a critical amount of charge is needed in order to destabilize a spherical droplet. We discuss several possible regularization mechanisms for the considered free boundary problem and argue that well-posedness can be restored by the inclusion of the entropic effects resulting in finite screening of free charges.
Modelling land degradation in IMAGE 2
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
Parametric uncertainty in optical image modeling
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.
Rosenkrantz, Andrew B; Liang, Yu; Duszak, Richard; Recht, Michael P
2017-08-01
Patients' willingness to travel farther distances for certain imaging services may reflect their perceptions of the degree of differentiation of such services. We compare patients' travel times for a range of imaging examinations performed across a large academic health system. We searched the NYU Langone Medical Center Enterprise Data Warehouse to identify 442,990 adult outpatient imaging examinations performed over a recent 3.5-year period. Geocoding software was used to estimate typical driving times from patients' residences to imaging facilities. Variation in travel times was assessed among examination types. The mean expected travel time was 29.2 ± 20.6 minutes, but this varied significantly (p travel times were shortest for ultrasound (26.8 ± 18.9) and longest for positron emission tomography-computed tomography (31.9 ± 21.5). For magnetic resonance imaging, travel times were shortest for musculoskeletal extremity (26.4 ± 19.2) and spine (28.6 ± 21.0) examinations and longest for prostate (35.9 ± 25.6) and breast (32.4 ± 22.3) examinations. For computed tomography, travel times were shortest for a range of screening examinations [colonography (25.5 ± 20.8), coronary artery calcium scoring (26.1 ± 19.2), and lung cancer screening (26.4 ± 14.9)] and longest for angiography (32.0 ± 22.6). For ultrasound, travel times were shortest for aortic aneurysm screening (22.3 ± 18.4) and longest for breast (30.1 ± 19.2) examinations. Overall, men (29.9 ± 21.6) had longer (p travel times than women (27.8 ± 20.3); this difference persisted for each modality individually (p ≤ 0.006). Patients' willingness to travel longer times for certain imaging examination types (particularly breast and prostate imaging) supports the role of specialized services in combating potential commoditization of imaging services. Disparities in travel times by gender warrant further investigation. Copyright
Accelerated gradient methods for total-variation-based CT image reconstruction
Energy Technology Data Exchange (ETDEWEB)
Joergensen, Jakob H.; Hansen, Per Christian [Technical Univ. of Denmark, Lyngby (Denmark). Dept. of Informatics and Mathematical Modeling; Jensen, Tobias L.; Jensen, Soeren H. [Aalborg Univ. (Denmark). Dept. of Electronic Systems; Sidky, Emil Y.; Pan, Xiaochuan [Chicago Univ., Chicago, IL (United States). Dept. of Radiology
2011-07-01
Total-variation (TV)-based CT image reconstruction has shown experimentally to be capable of producing accurate reconstructions from sparse-view data. In particular TV-based reconstruction is well suited for images with piecewise nearly constant regions. Computationally, however, TV-based reconstruction is demanding, especially for 3D imaging, and the reconstruction from clinical data sets is far from being close to real-time. This is undesirable from a clinical perspective, and thus there is an incentive to accelerate the solution of the underlying optimization problem. The TV reconstruction can in principle be found by any optimization method, but in practice the large scale of the systems arising in CT image reconstruction preclude the use of memory-intensive methods such as Newton's method. The simple gradient method has much lower memory requirements, but exhibits prohibitively slow convergence. In the present work we address the question of how to reduce the number of gradient method iterations needed to achieve a high-accuracy TV reconstruction. We consider the use of two accelerated gradient-based methods, GPBB and UPN, to solve the 3D-TV minimization problem in CT image reconstruction. The former incorporates several heuristics from the optimization literature such as Barzilai-Borwein (BB) step size selection and nonmonotone line search. The latter uses a cleverly chosen sequence of auxiliary points to achieve a better convergence rate. The methods are memory efficient and equipped with a stopping criterion to ensure that the TV reconstruction has indeed been found. An implementation of the methods (in C with interface to Matlab) is available for download from http://www2.imm.dtu.dk/~pch/TVReg/. We compare the proposed methods with the standard gradient method, applied to a 3D test problem with synthetic few-view data. We find experimentally that for realistic parameters the proposed methods significantly outperform the standard gradient method. (orig.)
Compensation of PVT Variations in ToF Imagers with In-Pixel TDC.
Vornicu, Ion; Carmona-Galán, Ricardo; Rodríguez-Vázquez, Ángel
2017-05-09
The design of a direct time-of-flight complementary metal-oxide-semiconductor (CMOS) image sensor (dToF-CIS) based on a single-photon avalanche-diode (SPAD) array with an in-pixel time-to-digital converter (TDC) must contemplate system-level aspects that affect its overall performance. This paper provides a detailed analysis of the impact of process parameters, voltage supply, and temperature (PVT) variations on the time bin of the TDC array. Moreover, the design and characterization of a global compensation loop is presented. It is based on a phase locked loop (PLL) that is integrated on-chip. The main building block of the PLL is a voltage-controlled ring-oscillator (VCRO) that is identical to the ones employed for the in-pixel TDCs. The reference voltage that drives the master VCRO is distributed to the voltage control inputs of the slave VCROs such that their multiphase outputs become invariant to PVT changes. These outputs act as time interpolators for the TDCs. Therefore the compensation scheme prevents the time bin of the TDCs from drifting over time due to the aforementioned factors. Moreover, the same scheme is used to program different time resolutions of the direct time-of-flight (ToF) imager aimed at 3D ranging or depth map imaging. Experimental results that validate the analysis are provided as well. The compensation loop proves to be remarkably effective. The spreading of the TDCs time bin is lowered from: (i) 20% down to 2.4% while the temperature ranges from 0 °C to 100 °C; (ii) 27% down to 0.27%, when the voltage supply changes within ±10% of the nominal value; (iii) 5.2 ps to 2 ps standard deviation over 30 sample chips, due to process parameters' variation.
International Nuclear Information System (INIS)
Aizawa, Isao; Muramatsu, Yoshihisa; Nomura, Keiichi; Shimizu, Fuminori
2010-01-01
The aim of this study was to analyze the reason for variation of image quality in the upper abdomen CT with the use of CT-automatic exposure control (AEC). The CT investigated was 3D modulation in the 16 multi detector row CT (MDCT) and lung cancer screening CT (LSCT) phantom was used to simulate the patient. When there was a phase difference, an image noise increase of around 15% at the maximum was accepted. It is concluded that the major reason for variation in image quality is respiratory motion and the importance of respiration control must be recognized. (author)
Hacker, Joshua; Vandenberghe, Francois; Jung, Byoung-Jo; Snyder, Chris
2017-04-01
Effective assimilation of cloud-affected radiance observations from space-borne imagers, with the aim of improving cloud analysis and forecasting, has proven to be difficult. Large observation biases, nonlinear observation operators, and non-Gaussian innovation statistics present many challenges. Ensemble-variational data assimilation (EnVar) systems offer the benefits of flow-dependent background error statistics from an ensemble, and the ability of variational minimization to handle nonlinearity. The specific benefits of ensemble statistics, relative to static background errors more commonly used in variational systems, have not been quantified for the problem of assimilating cloudy radiances. A simple experiment framework is constructed with a regional NWP model and operational variational data assimilation system, to provide the basis understanding the importance of ensemble statistics in cloudy radiance assimilation. Restricting the observations to those corresponding to clouds in the background forecast leads to innovations that are more Gaussian. The number of large innovations is reduced compared to the more general case of all observations, but not eliminated. The Huber norm is investigated to handle the fat tails of the distributions, and allow more observations to be assimilated without the need for strict background checks that eliminate them. Comparing assimilation using only ensemble background error statistics with assimilation using only static background error statistics elucidates the importance of the ensemble statistics. Although the cost functions in both experiments converge to similar values after sufficient outer-loop iterations, the resulting cloud water, ice, and snow content are greater in the ensemble-based analysis. The subsequent forecasts from the ensemble-based analysis also retain more condensed water species, indicating that the local environment is more supportive of clouds. In this presentation we provide details that explain the
Gong, J.; Zeng, X.; Wu, D. L.; Li, X.
2017-12-01
Diurnal variation of tropical ice cloud has been well observed and examined in terms of the area of coverage, occurring frequency, and total mass, but rarely on ice microphysical parameters (habit, size, orientation, etc.) because of lack of direct measurements of ice microphysics on a high temporal and spatial resolutions. This accounts for a great portion of the uncertainty in evaluating ice cloud's role on global radiation and hydrological budgets. The design of Global Precipitation Measurement (GPM) mission's procession orbit gives us an unprecedented opportunity to study the diurnal variation of ice microphysics on the global scale for the first time. Dominated by cloud ice scattering, high-frequency microwave polarimetric difference (PD, namely the brightness temperature difference between vertically- and horizontally-polarized paired channel measurements) from the GPM Microwave Imager (GMI) has been proven by our previous study to be very valuable to infer cloud ice microphysical properties. Using one year of PD measurements at 166 GHz, we found that cloud PD exhibits a strong diurnal cycle in the tropics (25S-25N). The peak PD amplitude varies as much as 35% over land, compared to only 6% over ocean. The diurnal cycle of the peak PD value is strongly anti-correlated with local ice cloud occurring frequency and the total ice mass with a leading period of 3 hours for the maximum correlation. The observed PD diurnal cycle can be explained by the change of ice crystal axial ratio. Using a radiative transfer model, we can simulate the observed 166 GHz PD-brightness temperature curve as well as its diurnal variation using different axial ratio values, which can be caused by the diurnal variation of ice microphysical properties including particle size, percentage of horizontally-aligned non-spherical particles, and ice habit. The leading of the change of PD ahead of ice cloud mass and occurring frequency implies the important role microphysics play in the
Gopi, Varun P; Palanisamy, P; Wahid, Khan A; Babyn, Paul; Cooper, David
2013-01-01
Micro-computed tomography (micro-CT) plays an important role in pre-clinical imaging. The radiation from micro-CT can result in excess radiation exposure to the specimen under test, hence the reduction of radiation from micro-CT is essential. The proposed research focused on analyzing and testing an alternating direction augmented Lagrangian (ADAL) algorithm to recover images from random projections using total variation (TV) regularization. The use of TV regularization in compressed sensing problems makes the recovered image quality sharper by preserving the edges or boundaries more accurately. In this work TV regularization problem is addressed by ADAL which is a variant of the classic augmented Lagrangian method for structured optimization. The per-iteration computational complexity of the algorithm is two fast Fourier transforms, two matrix vector multiplications and a linear time shrinkage operation. Comparison of experimental results indicate that the proposed algorithm is stable, efficient and competitive with the existing algorithms for solving TV regularization problems. Copyright © 2013 Elsevier Ltd. All rights reserved.
Models of Solar Irradiance Variations: Current Status Natalie A ...
Indian Academy of Sciences (India)
Abstract. Regular monitoring of solar irradiance has been carried out since 1978 to show that solar total and spectral irradiance varies at different time scales. Whereas variations on time scales of minutes to hours are due to solar oscillations and granulation, variations on longer time scales are driven by the evolution of the ...
Possible variations on the calcrete-gypcrete uranium model
International Nuclear Information System (INIS)
Carlisle, D.
1980-01-01
Genetic models and favorability criteria for calcrete and gypcrete uranium deposits based upon Yeelirrie and other occurrences in Western Australia and upon Langer Henirich and others in Namibia-South West Africa are summarized. Viable analogues of these world-class deposits have not yet been found in USA even though several of the favorable conditions occur in the southwest. A principal deterrent to economic concentration has been tectonic instability. But even in the most favorable areas it is not clear that climates have ever been sufficiently similar to that of the valley-calcrete region of Western Australia. Extensive, thick valley (nonpedogenic) calcretes such as those which host the carnotite in Australia and in Namibia have not been documented here. Nevertheless, submarginal occurrances of carnotite have been found in southwestern United States in small bodies of nonpedogenic and mixed pedogenic-nonpedogenic calcrete. Much of the study is based upon occurrences of carnotite-bearing calcrete and calcrete-gypcrete in the Republic of South Africa. Several of these are described briefly. Some reference is also made to new occurrences and to new data on previously described occurrences on the Namib Desert. Possible variations on the Western Australian and Namibia-South West Africa models which are considered are capillary rise of U in solution, addition of new uraniferous sediment over a calcrete, lateral access of U into a pedogenic calcrete, reworking of U from a weekly mineralized pedogenic calcrete or gypcrete into a new or reconstituted calcrete, or into an unrelated environment for fixation of U
Possible variations on the calcrete-gypcrete uranium model
Energy Technology Data Exchange (ETDEWEB)
Carlisle, D.
1980-01-01
Genetic models and favorability criteria for calcrete and gypcrete uranium deposits based upon Yeelirrie and other occurrences in Western Australia and upon Langer Henirich and others in Namibia-South West Africa are summarized. Viable analogues of these world-class deposits have not yet been found in USA even though several of the favorable conditions occur in the southwest. A principal deterrent to economic concentration has been tectonic instability. But even in the most favorable areas it is not clear that climates have ever been sufficiently similar to that of the valley-calcrete region of Western Australia. Extensive, thick valley (nonpedogenic) calcretes such as those which host the carnotite in Australia and in Namibia have not been documented here. Nevertheless, submarginal occurrances of carnotite have been found in southwestern United States in small bodies of nonpedogenic and mixed pedogenic-nonpedogenic calcrete. Much of the study is based upon occurrences of carnotite-bearing calcrete and calcrete-gypcrete in the Republic of South Africa. Several of these are described briefly. Some reference is also made to new occurrences and to new data on previously described occurrences on the Namib Desert. Possible variations on the Western Australian and Namibia-South West Africa models which are considered are capillary rise of U in solution, addition of new uraniferous sediment over a calcrete, lateral access of U into a pedogenic calcrete, reworking of U from a weekly mineralized pedogenic calcrete or gypcrete into a new or reconstituted calcrete, or into an unrelated environment for fixation of U.
Image analysis and modeling in medical image computing. Recent developments and advances.
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
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
Variational model for one-dimensional quantum magnets
Kudasov, Yu. B.; Kozabaranov, R. V.
2018-04-01
A new variational technique for investigation of the ground state and correlation functions in 1D quantum magnets is proposed. A spin Hamiltonian is reduced to a fermionic representation by the Jordan-Wigner transformation. The ground state is described by a new non-local trial wave function, and the total energy is calculated in an analytic form as a function of two variational parameters. This approach is demonstrated with an example of the XXZ-chain of spin-1/2 under a staggered magnetic field. Generalizations and applications of the variational technique for low-dimensional magnetic systems are discussed.
International Nuclear Information System (INIS)
Hintermüller, Michael; Rautenberg, Carlos N; Hahn, Jooyoung
2014-01-01
Variable splitting schemes for the function space version of the image reconstruction problem with total variation regularization (TV-problem) in its primal and pre-dual formulations are considered. For the primal splitting formulation, while existence of a solution cannot be guaranteed, it is shown that quasi-minimizers of the penalized problem are asymptotically related to the solution of the original TV-problem. On the other hand, for the pre-dual formulation, a family of parametrized problems is introduced and a parameter dependent contraction of an associated fixed point iteration is established. Moreover, the theory is validated by numerical tests. Additionally, the augmented Lagrangian approach is studied, details on an implementation on a staggered grid are provided and numerical tests are shown. (paper)
Statistical intensity variation analysis for rapid volumetric imaging of capillary network flux.
Lee, Jonghwan; Jiang, James Y; Wu, Weicheng; Lesage, Frederic; Boas, David A
2014-04-01
We present a novel optical coherence tomography (OCT)-based technique for rapid volumetric imaging of red blood cell (RBC) flux in capillary networks. Previously we reported that OCT can capture individual RBC passage within a capillary, where the OCT intensity signal at a voxel fluctuates when an RBC passes the voxel. Based on this finding, we defined a metric of statistical intensity variation (SIV) and validated that the mean SIV is proportional to the RBC flux [RBC/s] through simulations and measurements. From rapidly scanned volume data, we used Hessian matrix analysis to vectorize a segment path of each capillary and estimate its flux from the mean of the SIVs gathered along the path. Repeating this process led to a 3D flux map of the capillary network. The present technique enabled us to trace the RBC flux changes over hundreds of capillaries with a temporal resolution of ~1 s during functional activation.
Image-guided radiotherapy of bladder cancer: bladder volume variation and its relation to margins
DEFF Research Database (Denmark)
Muren, Ludvig; Redpath, Anthony Thomas; Lord, Hannah
2007-01-01
: The correlation between the relative bladder volume (RBV, defined as repeat scan volume/planning scan volume) and the margins required to account for internal motion was first studied using a series of 20 bladder cancer patients with weekly repeat CT scanning during treatment. Both conformal RT (CRT) and IGRT......BACKGROUND AND PURPOSE: To control and account for bladder motion is a major challenge in radiotherapy (RT) of bladder cancer. This study investigates the relation between bladder volume variation and margins in conformal and image-guided RT (IGRT) for this disease. MATERIALS AND METHODS...... these patients were given fluid intake restrictions on alternating weeks during treatment. RESULTS: IGRT gave the strongest correlation between the RBV and margin size (R(2)=0.75; p10mm were required in only 1% of the situations when the RBV1, whereas isotropic margins >10...
Semi-Automatic Classification Of Histopathological Images: Dealing With Inter-Slide Variations
Directory of Open Access Journals (Sweden)
Michael Gadermayr
2016-06-01
In case of 50 available labelled sample patches of a certain whole slide image, the overall classification rate increased from 92 % to 98 % through including the interactive labelling step. Even with only 20 labelled patches, accuracy already increased to 97 %. Without a pre-trained model, if training is performed on target domain data only, 88 % (20 labelled samples and 95 % (50 labelled samples accuracy, respectively, were obtained. If enough target domain data was available (about 20 images, the amount of source domain data was of minor relevance. The difference in outcome between a source domain training data set containing 100 patches from one whole slide image and a set containing 700 patches from seven images was lower than 1 %. Contrarily, without target domain data, the difference in accuracy was 10 % (82 % compared to 92 % between these two settings. Execution runtime between two interaction steps is significantly below one second (0.23 s, which is an important usability criterion. It proved to be beneficial to select specific target domain data in an active learning sense based on the currently available trained model. While experimental evaluation provided strong empirical evidence for increased classification performance with the proposed method, the additional manual effort can be kept at a low level. The labelling of e.g. 20 images per slide is surely less time consuming than the validation of a complete whole slide image processed with a fully automatic, but less reliable, segmentation approach. Finally, it should be highlighted that the proposed interaction protocol could easily be adapted to other histopathological classification or segmentation tasks, also for implementation in a clinical system.
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
International Nuclear Information System (INIS)
Zhu, Ting Ting; Ai, Tao; Zhang, Wei; Li, Tao; Li, Xiao Ming
2015-01-01
To investigate the changes in water content in the lumbar intervertebral discs by quantitative T2 MR imaging in the morning after bed rest and evening after a diurnal load. Twenty healthy volunteers were separately examined in the morning after bed rest and in the evening after finishing daily work. T2-mapping images were obtained and analyzed. An equally-sized rectangular region of interest (ROI) was manually placed in both, the anterior and the posterior annulus fibrosus (AF), in the outermost 20% of the disc. Three ROIs were placed in the space defined as the nucleus pulposus (NP). Repeated-measures analysis of variance and paired 2-tailed t tests were used for statistical analysis, with p < 0.05 as significantly different. T2 values significantly decreased from morning to evening, in the NP (anterior NP = -13.9 ms; central NP = -17.0 ms; posterior NP = -13.3 ms; all p < 0.001). Meanwhile T2 values significantly increased in the anterior AF (+2.9 ms; p = 0.025) and the posterior AF (+5.9 ms; p < 0.001). T2 values in the posterior AF showed the largest degree of variation among the 5 ROIs, but there was no statistical significance (p = 0.414). Discs with initially low T2 values in the center NP showed a smaller degree of variation in the anterior NP and in the central NP, than in discs with initially high T2 values in the center NP (10.0% vs. 16.1%, p = 0.037; 6.4% vs. 16.1%, p = 0.006, respectively). Segmental quantitative T2 MRI provides valuable insights into physiological aspects of normal discs.
Model of Dipole Field Variations in the LEP Bending Magnets
Bravin, Enrico; Drees, A; Mugnai, G
1998-01-01
The determination of the Z mass at LEP requires a knowledge of the relative beam energy in the order of 10 ppm, therefore it is essential to understand the dipole field variations to the same level of accuracy. In LEP the bending magnet field shows a relative increase of the order of 100 ppm over 10 hours, which was found to be caused by leakage currents from railways flowing along the vacuum cham ber and temperature variations. A LEP dipole test bench was set up for systematic investigations. Field variations were monitored with NMR probes while the cooling water temperature of both coil and vacuum chamber was kept under control. The results lead to a parametrisation of the magnetic field variation as a function of the vacuum chamber current and temperature.
Dong, Yang; He, Honghui; He, Chao; Ma, Hui
2016-10-01
Polarized light is sensitive to the microstructures of biological tissues and can be used to detect physiological changes. Meanwhile, spectral features of the scattered light can also provide abundant microstructural information of tissues. In this paper, we take the backscattering polarization Mueller matrix images of bovine skeletal muscle tissues during the 24-hour experimental time, and analyze their multispectral behavior using quantitative Mueller matrix parameters. In the processes of rigor mortis and proteolysis of muscle samples, multispectral frequency distribution histograms (FDHs) of the Mueller matrix elements can reveal rich qualitative structural information. In addition, we analyze the temporal variations of the sample using the multispectral Mueller matrix transformation (MMT) parameters. The experimental results indicate that the different stages of rigor mortis and proteolysis for bovine skeletal muscle samples can be judged by these MMT parameters. The results presented in this work show that combining with the multispectral technique, the FDHs and MMT parameters can characterize the microstructural variation features of skeletal muscle tissues. The techniques have the potential to be used as tools for quantitative assessment of meat qualities in food industry.
Normal variation and long-term reproducibility of image-selected in vivo brain MR spectroscopy
International Nuclear Information System (INIS)
Smith, M.A.; Porter, D.; Lowry, M.; Ayton, V.; Twelves, C.J.; Richards, M.A.; Garlick, P.; Maisey, M.N.
1988-01-01
MR spectroscopy of P-31 in the brain was performed with a 1.5-T MR imaging and spectroscopy system using ISIS with a 5-cm cube. A standardized spectral processing routine was adopted, and the ratios of peak areas were measured. Localized brain spectra were obtained from 17 healthy subjects, of whom ten had undergone repeated investigations after a delay of at least 1 month. The variation among healthy subjects, expressed as the mean +- standard deviation, and the long-term reproducibility, expressed as the coefficient of variation, were as follows: for peak areas phosphocreatine (PCr) Pi 2.46 +- 0.72, 21.3%, for PCr/PME, 1.97 +- 0.62, 16.8%, for PCr/PDE, 0.51 +- 0.07, 8.1%; for PCr/Υ-adenosine triphosphate (ATP), 1.13 + 0.15, 6.3%; for PCr/α-ATP, 1.09 +- 0.21, 10.3%, for PCr/β-ATP, 1.66 +- .027, 10.4%; and for pH, 7.00 +- 0.05, 0.8%
Variational methods and effective actions in string models
International Nuclear Information System (INIS)
Dereli, T.; Tucker, R.W.
1987-01-01
Effective actions motivated by zero-order and first-order actions are examined. Particular attention is devoted to a variational procedure that is consistent with the structure equations involving the Lorentz connection. Attention is drawn to subtleties that can arise in varying higher-order actions and an efficient procedure developed to handle these cases using the calculus of forms. The effect of constrained variations on the field equations is discussed. (author)
Testing the Processing Hypothesis of word order variation using a probabilistic language model
Bloem, J.
2016-01-01
This work investigates the application of a measure of surprisal to modeling a grammatical variation phenomenon between near-synonymous constructions. We investigate a particular variation phenomenon, word order variation in Dutch two-verb clusters, where it has been established that word order
Omics approaches to individual variation: modeling networks and the virtual patient.
Lehrach, Hans
2016-09-01
Every human is unique. We differ in our genomes, environment, behavior, disease history, and past and current medical treatment-a complex catalog of differences that often leads to variations in the way each of us responds to a particular therapy. We argue here that true personalization of drug therapies will rely on "virtual patient" models based on a detailed characterization of the individual patient by molecular, imaging, and sensor techniques. The models will be based, wherever possible, on the molecular mechanisms of disease processes and drug action but can also expand to hybrid models including statistics/machine learning/artificial intelligence-based elements trained on available data to address therapeutic areas or therapies for which insufficient information on mechanisms is available. Depending on the disease, its mechanisms, and the therapy, virtual patient models can be implemented at a fairly high level of abstraction, with molecular models representing cells, cell types, or organs relevant to the clinical question, interacting not only with each other but also the environment. In the future, "virtual patient/in-silico self" models may not only become a central element of our health care system, reducing otherwise unavoidable mistakes and unnecessary costs, but also act as "guardian angels" accompanying us through life to protect us against dangers and to help us to deal intelligently with our own health and wellness.
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
Modelling the Probability Density Function of IPTV Traffic Packet Delay Variation
Directory of Open Access Journals (Sweden)
Michal Halas
2012-01-01
Full Text Available This article deals with modelling the Probability density function of IPTV traffic packet delay variation. The use of this modelling is in an efficient de-jitter buffer estimation. When an IP packet travels across a network, it experiences delay and its variation. This variation is caused by routing, queueing systems and other influences like the processing delay of the network nodes. When we try to separate these at least three types of delay variation, we need a way to measure these types separately. This work is aimed to the delay variation caused by queueing systems which has the main implications to the form of the Probability density function.
2015-01-01
Assistant for Calculus (winter 2011) xii CHAPTER 1 Introduction We present several methods, outlined in Chapters 3-5, for image processing and data...local calculus formulation [103] to generalize the continuous formulation to a (non-local) discrete setting, while other non-local versions for...graph-based model based on the Ginzburg-Landau functional in their work [9]. To define the functional on a graph, the spatial gradient is replaced by a
Jiang, Jie; Zhang, Shumei; Cao, Shixiang
2015-01-01
Multitemporal remote sensing images generally suffer from background variations, which significantly disrupt traditional region feature and descriptor abstracts, especially between pre and postdisasters, making registration by local features unreliable. Because shapes hold relatively stable information, a rotation and scale invariant shape context based on multiscale edge features is proposed. A multiscale morphological operator is adapted to detect edges of shapes, and an equivalent difference of Gaussian scale space is built to detect local scale invariant feature points along the detected edges. Then, a rotation invariant shape context with improved distance discrimination serves as a feature descriptor. For a distance shape context, a self-adaptive threshold (SAT) distance division coordinate system is proposed, which improves the discriminative property of the feature descriptor in mid-long pixel distances from the central point while maintaining it in shorter ones. To achieve rotation invariance, the magnitude of Fourier transform in one-dimension is applied to calculate angle shape context. Finally, the residual error is evaluated after obtaining thin-plate spline transformation between reference and sensed images. Experimental results demonstrate the robustness, efficiency, and accuracy of this automatic algorithm.
International Nuclear Information System (INIS)
Muzamil, Akhmad; Firmansyah, Achmad Haries
2017-01-01
The research was done the optimization image of Magnetic Resonance Imaging (MRI) T2 Fast Spin Echo (FSE) with variation Echo Train Length (ETL) on the Rupture Tendon Achilles case. This study aims to find the variations Echo Train Length (ETL) from the results of ankle’s MRI image and find out how the value of Echo Train Length (ETL) works on the MRI ankle to produce optimal image. In this research, the used ETL variations were 12 and 20 with the interval 2 on weighting T2 FSE sagittal. The study obtained the influence of Echo Train Length (ETL) on the quality of ankle MRI image sagittal using T2 FSE weighting and analyzed in 25 images of five patients. The data analysis has done quantitatively with the Region of Interest (ROI) directly on computer MRI image planes which conducted statistical tests Signal to Noise Ratio (SNR) and Contras to Noise Ratio (CNR). The Signal to Noise Ratio (SNR) was the highest finding on fat tissue, while the Contras to Noise Ratio (CNR) on the Tendon-Fat tissue with ETL 12 found in two patients. The statistics test showed the significant SNR value of the 0.007 (p<0.05) of Tendon tissue, 0.364 (p>0.05) of the Fat, 0.912 (p>0.05) of the Fibula, and 0.436 (p>0.05) of the Heel Bone. For the contrast to noise ratio (CNR) of the Tendon-FAT tissue was about 0.041 (p>0.05). The results of the study showed that ETL variation with T2 FSE sagittal weighting had difference at Tendon tissue and Tendon-Fat tissue for MRI imaging quality. SNR and CNR were an important aspect on imaging optimization process to give the diagnose information. (paper)
Stoll, Markus; Stoiber, Eva Maria; Grimm, Sarah; Debus, Jürgen; Bendl, Rolf; Giske, Kristina
2016-01-01
Intensity modulated radiation therapy (IMRT) of head and neck tumors allows a precise conformation of the high-dose region to clinical target volumes (CTVs) while respecting dose limits to organs a risk (OARs). Accurate patient setup reduces translational and rotational deviations between therapy planning and therapy delivery days. However, uncertainties in the shape of the CTV and OARs due to e.g. small pose variations in the highly deformable anatomy of the head and neck region can still compromise the dose conformation. Routinely applied safety margins around the CTV cause higher dose deposition in adjacent healthy tissue and should be kept as small as possible. In this work we evaluate and compare three approaches for margin generation 1) a clinically used approach with a constant isotropic 3 mm margin, 2) a previously proposed approach adopting a spatial model of the patient and 3) a newly developed approach adopting a biomechanical model of the patient. All approaches are retrospectively evaluated using a large patient cohort of over 500 fraction control CT images with heterogeneous pose changes. Automatic methods for finding landmark positions in the control CT images are combined with a patient specific biomechanical finite element model to evaluate the CTV deformation. The applied methods for deformation modeling show that the pose changes cause deformations in the target region with a mean motion magnitude of 1.80 mm. We found that the CTV size can be reduced by both variable margin approaches by 15.6% and 13.3% respectively, while maintaining the CTV coverage. With approach 3 an increase of target coverage was obtained. Variable margins increase target coverage, reduce risk to OARs and improve healthy tissue sparing at the same time.
Optimal transport for applied mathematicians calculus of variations, PDEs, and modeling
Santambrogio, Filippo
2015-01-01
This monograph presents a rigorous mathematical introduction to optimal transport as a variational problem, its use in modeling various phenomena, and its connections with partial differential equations. Its main goal is to provide the reader with the techniques necessary to understand the current research in optimal transport and the tools which are most useful for its applications. Full proofs are used to illustrate mathematical concepts and each chapter includes a section that discusses applications of optimal transport to various areas, such as economics, finance, potential games, image processing and fluid dynamics. Several topics are covered that have never been previously in books on this subject, such as the Knothe transport, the properties of functionals on measures, the Dacorogna-Moser flow, the formulation through minimal flows with prescribed divergence formulation, the case of the supremal cost, and the most classical numerical methods. Graduate students and researchers in both pure and appl...
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.)
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...
Reconstructing building mass models from UAV images
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.
JUPITER’S PHASE VARIATIONS FROM CASSINI : A TESTBED FOR FUTURE DIRECT-IMAGING MISSIONS
International Nuclear Information System (INIS)
Mayorga, L. C.; Jackiewicz, J.; Rages, K.; West, R. A.; Knowles, B.; Lewis, N.; Marley, M. S.
2016-01-01
We present empirical phase curves of Jupiter from ∼0° to 140° as measured in multiple optical bandpasses by Cassini /Imaging Science Subsystem (ISS) during the Millennium flyby of Jupiter in late 2000 to early 2001. Phase curves are of interest for studying the energy balance of Jupiter and understanding the scattering behavior of the planet as an exoplanet analog. We find that Jupiter is significantly darker at partial phases than an idealized Lambertian planet by roughly 25% and is not well fit by Jupiter-like exoplanet atmospheric models across all wavelengths. We provide analytic fits to Jupiter’s phase function in several Cassini /ISS imaging filter bandpasses. In addition, these observations show that Jupiter’s color is more variable with phase angle than predicted by models. Therefore, the color of even a near Jupiter-twin planet observed at a partial phase cannot be assumed to be comparable to that of Jupiter at full phase. We discuss how the Wide-Field Infrared Survey Telescope and other future direct-imaging missions can enhance the study of cool giants.
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...
Variational cellular model of the molecular and crystal electronic structure
International Nuclear Information System (INIS)
Ferreira, L.G.; Leite, J.R.
1977-12-01
A variational version of the cellular method is developed to calculate the electronic structure of molecules and crystals. Due to the simplicity of the secular equation, the method is easy to be implemented. Preliminary calculations on the hydrogen molecular ion suggest that it is also accurate and of fast convergence [pt
Towards Modelling Variation in Music as Foundation for Similarity
Volk, A.; de Haas, W.B.; van Kranenburg, P.; Cambouropoulos, E.; Tsougras, C.; Mavromatis, P.; Pastiadis, K.
2012-01-01
This paper investigates the concept of variation in music from the perspective of music similarity. Music similarity is a central concept in Music Information Retrieval (MIR), however there exists no comprehensive approach to music similarity yet. As a consequence, MIR faces the challenge on how to
Siegal, B. S.; Short, N. M.
1977-01-01
The significance of operator variation and the angle of illumination in acquired imagery is analyzed for lineament analysis. Five operators analyzed a LANDSAT image and four photographs of a plastic relief map illuminated at a low angle from varying directions of the Prescott, Arizona region. Significant differences were found in both number and length of the lineaments recognized by the different investigators for the images. The actual coincidence of lineaments recognized by the investigators for the same image is exceptionally low. Even the directional data on lineament orientation is significantly different from operator to operator and from image to image. Cluster analysis of the orientation data displays a clustering by operators rather than by images. It is recommended that extreme caution be taken before attempting to compare different investigators' results in lineament analysis.
Diurnal microstructural variations in healthy adult brain revealed by diffusion tensor imaging.
Directory of Open Access Journals (Sweden)
Chunxiang Jiang
Full Text Available Biorhythm is a fundamental property of human physiology. Changes in the extracellular space induced by cell swelling in response to the neural activity enable the in vivo characterization of cerebral microstructure by measuring the water diffusivity using diffusion tensor imaging (DTI. To study the diurnal microstructural alterations of human brain, fifteen right-handed healthy adult subjects were recruited for DTI studies in two repeated sessions (8∶30 AM and 8∶30 PM within a 24-hour interval. Fractional anisotropy (FA, apparent diffusion coefficient (ADC, axial (λ// and radial diffusivity (λ⊥ were compared pixel by pixel between the sessions for each subject. Significant increased morning measurements in FA, ADC, λ// and λ⊥ were seen in a wide range of brain areas involving frontal, parietal, temporal and occipital lobes. Prominent evening dominant λ⊥ (18.58% was detected in the right inferior temporal and ventral fusiform gyri. AM-PM variation of λ⊥ was substantially left side hemisphere dominant (p<0.05, while no hemispheric preference was observed for the same analysis for ADC (p = 0.77, λ// (p = 0.08 or FA (p = 0.25. The percentage change of ADC, λ//, λ⊥, and FA were 1.59%, 2.15%, 1.20% and 2.84%, respectively, for brain areas without diurnal diffusivity contrast. Microstructural variations may function as the substrates of the phasic neural activities in correspondence to the environment adaptation in a light-dark cycle. This research provided a baseline for researches in neuroscience, sleep medicine, psychological and psychiatric disorders, and necessitates that diurnal effect should be taken into account in following up studies using diffusion tensor quantities.
Hosni, Ali; Rosewall, Tara; Craig, Timothy; Kong, Vickie; Bayley, Andrew; Berlin, Alejandro; Bristow, Robert; Catton, Charles; Warde, Padraig; Chung, Peter
2017-03-09
This study aimed to investigate the tolerability and impact of milk of magnesia (MoM) on interfraction rectal filling during prostate cancer radiotherapy. Two groups were retrospectively identified, each consisting of 40 patients with prostate cancer treated with radiotherapy to prostate+/-seminal vesicles, with daily image-guidance in 78Gy/39fractions/8 weeks. The first-group followed anti-flatulence diet with MoM started 3-days prior to planning-CT and continued during radiotherapy, while the second-group followed the same anti-flatulence diet only. The rectum between upper and lower limit of the clinical target volume (CTV) was delineated on planning-CT and on weekly cone-beam-CT (CBCT). Rectal filling was assessed by measurement of anterio-posterior diameter of the rectum at the superior and mid levels of CTV, rectal volume (RV), and average cross-sectional rectal area (CSA; RV/length). Overall 720 images (80 planning-CT and 640 CBCT images) from 80 patients were analyzed. Using linear mixed models, and after adjusting for baseline values at the time of planning-CT to test the differences in rectal dimensions between both groups over the 8-week treatment period, there were no significant differences in RV (p = 0.4), CSA (p = 0.5), anterio-posterior diameter of rectum at superior (p = 0.4) or mid level of CTV (p = 0.4). In the non-MoM group; 22.5% of patients had diarrhea compared to 60% in the MoM group, while 40% discontinued use of MoM by end of radiotherapy. The addition of MoM to antiflatulence diet did not reduce the interfraction variation in rectal filling but caused diarrhea in a substantial proportion of patients who then discontinued its use.
Delay Variation Model with RTP Flows Behavior in Accordance with M/D/1 Kendall's Notation
Directory of Open Access Journals (Sweden)
Miroslav Voznak
2010-01-01
Full Text Available This paper focuses on the design of a mathematical model of end-to-end delay of a VoIP connection, in particular on a delay variation. It describes all partial delay components and mechanisms, its generation, facilities and its mathematical formulations. A new approach to the delay variation model is presented; its validation has been done by an experiment.
Directory of Open Access Journals (Sweden)
Ramin Jaberi
2017-12-01
Full Text Available Purpose : Intra-fractional organs at risk (OARs deformations can lead to dose variation during image-guided adaptive brachytherapy (IGABT. The aim of this study was to modify the final accepted brachytherapy treatment plan to dosimetrically compensate for these intra-fractional organs-applicators position variations and, at the same time, fulfilling the dosimetric criteria. Material and methods : Thirty patients with locally advanced cervical cancer, after external beam radiotherapy (EBRT of 45-50 Gy over five to six weeks with concomitant weekly chemotherapy, and qualified for intracavitary high-dose-rate (HDR brachytherapy with tandem-ovoid applicators were selected for this study. Second computed tomography scan was done for each patient after finishing brachytherapy treatment with applicators in situ. Artificial neural networks (ANNs based models were used to predict intra-fractional OARs dose-volume histogram parameters variations and propose a new final plan. Results : A model was developed to estimate the intra-fractional organs dose variations during gynaecological intracavitary brachytherapy. Also, ANNs were used to modify the final brachytherapy treatment plan to compensate dosimetrically for changes in ‘organs-applicators’, while maintaining target dose at the original level. Conclusions : There are semi-automatic and fast responding models that can be used in the routine clinical workflow to reduce individually IGABT uncertainties. These models can be more validated by more patients’ plans to be able to serve as a clinical tool.
Jaberi, Ramin; Siavashpour, Zahra; Aghamiri, Mahmoud Reza; Kirisits, Christian; Ghaderi, Reza
2017-12-01
Intra-fractional organs at risk (OARs) deformations can lead to dose variation during image-guided adaptive brachytherapy (IGABT). The aim of this study was to modify the final accepted brachytherapy treatment plan to dosimetrically compensate for these intra-fractional organs-applicators position variations and, at the same time, fulfilling the dosimetric criteria. Thirty patients with locally advanced cervical cancer, after external beam radiotherapy (EBRT) of 45-50 Gy over five to six weeks with concomitant weekly chemotherapy, and qualified for intracavitary high-dose-rate (HDR) brachytherapy with tandem-ovoid applicators were selected for this study. Second computed tomography scan was done for each patient after finishing brachytherapy treatment with applicators in situ. Artificial neural networks (ANNs) based models were used to predict intra-fractional OARs dose-volume histogram parameters variations and propose a new final plan. A model was developed to estimate the intra-fractional organs dose variations during gynaecological intracavitary brachytherapy. Also, ANNs were used to modify the final brachytherapy treatment plan to compensate dosimetrically for changes in 'organs-applicators', while maintaining target dose at the original level. There are semi-automatic and fast responding models that can be used in the routine clinical workflow to reduce individually IGABT uncertainties. These models can be more validated by more patients' plans to be able to serve as a clinical tool.
Modeling of skin cancer dermatoscopy images
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.
A Variational Model for Two-Phase Immiscible Electroosmotic Flow at Solid Surfaces
Shao, Sihong; Qian, Tiezheng
2012-01-01
We develop a continuum hydrodynamic model for two-phase immiscible flows that involve electroosmotic effect in an electrolyte and moving contact line at solid surfaces. The model is derived through a variational approach based on the Onsager
DEFF Research Database (Denmark)
Rosthøj, Susanne; Keiding, Niels
2004-01-01
When studying a regression model measures of explained variation are used to assess the degree to which the covariates determine the outcome of interest. Measures of predictive accuracy are used to assess the accuracy of the predictions based on the covariates and the regression model. We give a ...... a detailed and general introduction to the two measures and the estimation procedures. The framework we set up allows for a study of the effect of misspecification on the quantities estimated. We also introduce a generalization to survival analysis....
Statistical image processing and multidimensional modeling
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
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.
Davila, Yves; Crouzeix, Laurent; Douchin, Bernard; Collombet, Francis; Grunevald, Yves-Henri
2017-08-01
Reinforcement angle orientation has a significant effect on the mechanical properties of composite materials. This work presents a methodology to introduce variable reinforcement angles into finite element (FE) models of composite structures. The study of reinforcement orientation variations uses meta-models to identify and control a continuous variation across the composite ply. First, the reinforcement angle is measured through image analysis techniques of the composite plies during the lay-up phase. Image analysis results show that variations in the mean ply orientations are between -0.5 and 0.5° with standard deviations ranging between 0.34 and 0.41°. An automatic post-treatment of the images determines the global and local angle variations yielding good agreements visually and numerically between the analysed images and the identified parameters. A composite plate analysed at the end of the cooling phase is presented as a case of study. Here, the variation in residual strains induced by the variability in the reinforcement orientation are up to 28% of the strain field of the homogeneous FE model. The proposed methodology has shown its capabilities to introduce material and geometrical variability into FE analysis of layered composite structures.
Davila, Yves; Crouzeix, Laurent; Douchin, Bernard; Collombet, Francis; Grunevald, Yves-Henri
2018-06-01
Reinforcement angle orientation has a significant effect on the mechanical properties of composite materials. This work presents a methodology to introduce variable reinforcement angles into finite element (FE) models of composite structures. The study of reinforcement orientation variations uses meta-models to identify and control a continuous variation across the composite ply. First, the reinforcement angle is measured through image analysis techniques of the composite plies during the lay-up phase. Image analysis results show that variations in the mean ply orientations are between -0.5 and 0.5° with standard deviations ranging between 0.34 and 0.41°. An automatic post-treatment of the images determines the global and local angle variations yielding good agreements visually and numerically between the analysed images and the identified parameters. A composite plate analysed at the end of the cooling phase is presented as a case of study. Here, the variation in residual strains induced by the variability in the reinforcement orientation are up to 28% of the strain field of the homogeneous FE model. The proposed methodology has shown its capabilities to introduce material and geometrical variability into FE analysis of layered composite structures.
Empirical model of subdaily variations in the Earth rotation from GPS and its stability
Panafidina, N.; Kurdubov, S.; Rothacher, M.
2012-12-01
The model recommended by the IERS for these variations at diurnal and semidiurnal periods has been computed from an ocean tide model and comprises 71 terms in polar motion and Universal Time. In the present study we compute an empirical model of variations in the Earth rotation on tidal frequencies from homogeneously re-processed GPS-observations over 1994-2007 available as free daily normal equations. We discuss the reliability of the obtained amplitudes of the ERP variations and compare results from GPS and VLBI data to identify technique-specific problems and instabilities of the empirical tidal models.
Introductory Biology Students’ Conceptual Models and Explanations of the Origin of Variation
Shaw, Neil; Momsen, Jennifer; Reinagel, Adam; Le, Paul; Taqieddin, Ranya; Long, Tammy
2014-01-01
Mutation is the key molecular mechanism generating phenotypic variation, which is the basis for evolution. In an introductory biology course, we used a model-based pedagogy that enabled students to integrate their understanding of genetics and evolution within multiple case studies. We used student-generated conceptual models to assess understanding of the origin of variation. By midterm, only a small percentage of students articulated complete and accurate representations of the origin of variation in their models. Targeted feedback was offered through activities requiring students to critically evaluate peers’ models. At semester's end, a substantial proportion of students significantly improved their representation of how variation arises (though one-third still did not include mutation in their models). Students’ written explanations of the origin of variation were mostly consistent with their models, although less effective than models in conveying mechanistic reasoning. This study contributes evidence that articulating the genetic origin of variation is particularly challenging for learners and may require multiple cycles of instruction, assessment, and feedback. To support meaningful learning of the origin of variation, we advocate instruction that explicitly integrates multiple scales of biological organization, assessment that promotes and reveals mechanistic and causal reasoning, and practice with explanatory models with formative feedback. PMID:25185235
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.
A variational multiscale constitutive model for nanocrystalline materials
Gurses, Ercan; El Sayed, Tamer S.
2011-01-01
grain interior phase and a grain boundary effected zone (GBAZ). A rate-independent isotropic porous plasticity model is employed to describe the GBAZ, whereas a crystal-plasticity model which accounts for the transition from partial dislocation to full
Brain MRI Tumor Detection using Active Contour Model and Local Image Fitting Energy
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.
Natural variation of model mutant phenotypes in Ciona intestinalis.
Directory of Open Access Journals (Sweden)
Paolo Sordino
Full Text Available BACKGROUND: The study of ascidians (Chordata, Tunicata has made a considerable contribution to our understanding of the origin and evolution of basal chordates. To provide further information to support forward genetics in Ciona intestinalis, we used a combination of natural variation and neutral population genetics as an approach for the systematic identification of new mutations. In addition to the significance of developmental variation for phenotype-driven studies, this approach can encompass important implications in evolutionary and population biology. METHODOLOGY/PRINCIPAL FINDINGS: Here, we report a preliminary survey for naturally occurring mutations in three geographically interconnected populations of C. intestinalis. The influence of historical, geographical and environmental factors on the distribution of abnormal phenotypes was assessed by means of 12 microsatellites. We identified 37 possible mutant loci with stereotyped defects in embryonic development that segregate in a way typical of recessive alleles. Local populations were found to differ in genetic organization and frequency distribution of phenotypic classes. CONCLUSIONS/SIGNIFICANCE: Natural genetic polymorphism of C. intestinalis constitutes a valuable source of phenotypes for studying embryonic development in ascidians. Correlating genetic structure and the occurrence of abnormal phenotypes is a crucial focus for understanding the selective forces that shape natural finite populations, and may provide insights of great importance into the evolutionary mechanisms that generate animal diversity.
Natural Variation of Model Mutant Phenotypes in Ciona intestinalis
Brown, Euan R.; Leccia, Nicola I.; Squarzoni, Paola; Tarallo, Raffaella; Alfano, Christian; Caputi, Luigi; D'Ambrosio, Palmira; Daniele, Paola; D'Aniello, Enrico; D'Aniello, Salvatore; Maiella, Sylvie; Miraglia, Valentina; Russo, Monia Teresa; Sorrenti, Gerarda; Branno, Margherita; Cariello, Lucio; Cirino, Paola; Locascio, Annamaria; Spagnuolo, Antonietta; Zanetti, Laura; Ristoratore, Filomena
2008-01-01
Background The study of ascidians (Chordata, Tunicata) has made a considerable contribution to our understanding of the origin and evolution of basal chordates. To provide further information to support forward genetics in Ciona intestinalis, we used a combination of natural variation and neutral population genetics as an approach for the systematic identification of new mutations. In addition to the significance of developmental variation for phenotype-driven studies, this approach can encompass important implications in evolutionary and population biology. Methodology/Principal Findings Here, we report a preliminary survey for naturally occurring mutations in three geographically interconnected populations of C. intestinalis. The influence of historical, geographical and environmental factors on the distribution of abnormal phenotypes was assessed by means of 12 microsatellites. We identified 37 possible mutant loci with stereotyped defects in embryonic development that segregate in a way typical of recessive alleles. Local populations were found to differ in genetic organization and frequency distribution of phenotypic classes. Conclusions/Significance Natural genetic polymorphism of C. intestinalis constitutes a valuable source of phenotypes for studying embryonic development in ascidians. Correlating genetic structure and the occurrence of abnormal phenotypes is a crucial focus for understanding the selective forces that shape natural finite populations, and may provide insights of great importance into the evolutionary mechanisms that generate animal diversity. PMID:18523552
Onishi, Okihiro; Ikoma, Kazuya; Oda, Ryo; Yamazaki, Tetsuro; Fujiwara, Hiroyoshi; Yamada, Shunji; Tanaka, Masaki; Kubo, Toshikazu
2018-04-23
Although treatment protocols are available, patients experience both acute neuropathic pain and chronic neuropathic pain, hyperalgesia, and allodynia after peripheral nerve injury. The purpose of this study was to identify the brain regions activated after peripheral nerve injury using functional magnetic resonance imaging (fMRI) sequentially and assess the relevance of the imaging results using histological findings. To model peripheral nerve injury in male Sprague-Dawley rats, the right sciatic nerve was crushed using an aneurysm clip, under general anesthesia. We used a 7.04T MRI system. T 2 * weighted image, coronal slice, repetition time, 7 ms; echo time, 3.3 ms; field of view, 30 mm × 30 mm; pixel matrix, 64 × 64 by zero-filling; slice thickness, 2 mm; numbers of slices, 9; numbers of average, 2; and flip angle, 8°. fMR images were acquired during electrical stimulation to the rat's foot sole; after 90 min, c-Fos immunohistochemical staining of the brain was performed in rats with induced peripheral nerve injury for 3, 6, and 9 weeks. Data were pre-processed by realignment in the Statistical Parametric Mapping 8 software. A General Linear Model first level analysis was used to obtain T-values. One week after the injury, significant changes were detected in the cingulate cortex, insular cortex, amygdala, and basal ganglia; at 6 weeks, the brain regions with significant changes in signal density were contracted; at 9 weeks, the amygdala and hippocampus showed activation. Histological findings of the rat brain supported the fMRI findings. We detected sequential activation in the rat brain using fMRI after sciatic nerve injury. Many brain regions were activated during the acute stage of peripheral nerve injury. Conversely, during the chronic stage, activation of the amygdala and hippocampus may be related to chronic-stage hyperalgesia, allodynia, and chronic neuropathic pain. Copyright © 2018 Elsevier B.V. All rights reserved.
Suhartono, Lee, Muhammad Hisyam; Prastyo, Dedy Dwi
2015-12-01
The aim of this research is to develop a calendar variation model for forecasting retail sales data with the Eid ul-Fitr effect. The proposed model is based on two methods, namely two levels ARIMAX and regression methods. Two levels ARIMAX and regression models are built by using ARIMAX for the first level and regression for the second level. Monthly men's jeans and women's trousers sales in a retail company for the period January 2002 to September 2009 are used as case study. In general, two levels of calendar variation model yields two models, namely the first model to reconstruct the sales pattern that already occurred, and the second model to forecast the effect of increasing sales due to Eid ul-Fitr that affected sales at the same and the previous months. The results show that the proposed two level calendar variation model based on ARIMAX and regression methods yields better forecast compared to the seasonal ARIMA model and Neural Networks.
International Nuclear Information System (INIS)
Mendes, L.M.M.; Pereira, W.B.R.; Vieira, J.G.; Lamounier, C.S.; Gonçalves, D.A.; Carvalho, G.N.P.; Santana, P.C.; Oliveira, P.M.C.; Reis, L.P.
2017-01-01
Computed tomography had great advances in the equipment used in the diagnostic practice, directly influencing the levels of radiation for the patient. It is essential to optimize techniques that must be employed to comply with the ALARA (As Low As Reasonably Achievable) principle of radioprotection. The relationship of ASIR (Adaptive Statistical Iterative Reconstruction) with image noise was studied. Central images of a homogeneous water simulator were obtained in a 20 mm scan using a 64-channel Lightspeed VCT tomograph of General Electric in helical acquisitions with a rotation time of 0.5 seconds, Pitch 0.984: 1, and thickness of cut 0.625 mm. All these constant parameters varying the voltage in two distinct values: 120 and 140 kV with use of the automatic current by the CAE (Automatic Exposure Control), ranging from 50 to 675 mA (120 kV) and from 50 to 610 mA (140kV), minimum and maximum values, respectively allowed for each voltage. Image noise was determined through ImageJ free software. The analysis of the obtained data compared the percentage variation of the noise in the image based on the ASIR value of 10%, concluding that there is a variation of approximately 50% when compared to the values of ASIR (100%) in both tensions. Dose evaluation is required in future studies to better utilize the relationship between dose and image quality
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
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...
Kinetic modeling in PET imaging of hypoxia
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
Bruschetta, M.; Saccon, A.; Picci, G.
2014-01-01
The theory of variational integration provides a systematic procedure to discretize the equations of motion of a mechanical system, preserving key properties of the continuous time flow. The discrete-time model obtained by variational integration theory inherits structural conditions which in
Long-Term Evaluation of Ocean Tidal Variation Models of Polar Motion and UT1
Karbon, Maria; Balidakis, Kyriakos; Belda, Santiago; Nilsson, Tobias; Hagedoorn, Jan; Schuh, Harald
2018-04-01
Recent improvements in the development of VLBI (very long baseline interferometry) and other space geodetic techniques such as the global navigation satellite systems (GNSS) require very precise a-priori information of short-period (daily and sub-daily) Earth rotation variations. One significant contribution to Earth rotation is caused by the diurnal and semi-diurnal ocean tides. Within this work, we developed a new model for the short-period ocean tidal variations in Earth rotation, where the ocean tidal angular momentum model and the Earth rotation variation have been setup jointly. Besides the model of the short-period variation of the Earth's rotation parameters (ERP), based on the empirical ocean tide model EOT11a, we developed also ERP models, that are based on the hydrodynamic ocean tide models FES2012 and HAMTIDE. Furthermore, we have assessed the effect of uncertainties in the elastic Earth model on the resulting ERP models. Our proposed alternative ERP model to the IERS 2010 conventional model considers the elastic model PREM and 260 partial tides. The choice of the ocean tide model and the determination of the tidal velocities have been identified as the main uncertainties. However, in the VLBI analysis all models perform on the same level of accuracy. From these findings, we conclude that the models presented here, which are based on a re-examined theoretical description and long-term satellite altimetry observation only, are an alternative for the IERS conventional model but do not improve the geodetic results.
Variations within simple models for structure-soil interaction
DEFF Research Database (Denmark)
Peplow, Andrew; Andersen, Lars Vabbersgaard; Bucinskas, Paulius
, obstacles such as concrete blocks lead to wave scattering that may be beneficial or unfavourable for the response of a building close to, for example, a railway. To account for this dynamic cross coupling via the soil, a model must be accurate enough to provide the correct overall behaviour of the scattered...... wave field. However, simplicity is also important when a model should be used for design purposes, especially in the early stages of design and feasibility studies. The paper addresses two models in 2D and 3D based on different methodologies. Results are discussed regarding their capability to quantify...
DEFF Research Database (Denmark)
Rose, Sean; Andersen, Martin S.; Sidky, Emil Y.
2015-01-01
Purpose: The authors develop and investigate iterative image reconstruction algorithms based on data-discrepancy minimization with a total-variation (TV) constraint. The various algorithms are derived with different data-discrepancy measures reflecting the maximum likelihood (ML) principle......: An incremental algorithm framework is developed for this purpose. The instances of the incremental algorithms are derived for solving optimization problems including a data fidelity objective function combined with a constraint on the image TV. For the data fidelity term the authors, compare application....... Simulations demonstrate the iterative algorithms and the resulting image statistical properties for low-dose CT data acquired with sparse projection view angle sampling. Of particular interest is to quantify improvement of image statistical properties by use of the ML data fidelity term. Methods...
Statistical model for OCT image denoising
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
Single image interpolation via adaptive nonlocal sparsity-based modeling.
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.
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.
Energy Technology Data Exchange (ETDEWEB)
Sobolik, S.R.; Ho, C.K.; Dunn, E. [Sandia National Labs., Albuquerque, NM (United States); Robey, T.H. [Spectra Research Inst., Albuquerque, NM (United States); Cruz, W.T. [Univ. del Turabo, Gurabo (Puerto Rico)
1996-07-01
The Yucca Mountain Site Characterization Project is studying Yucca Mountain in southwestern Nevada as a potential site for a high-level nuclear waste repository. Site characterization includes surface- based and underground testing. Analyses have been performed to support the design of an Exploratory Studies Facility (ESF) and the design of the tests performed as part of the characterization process, in order to ascertain that they have minimal impact on the natural ability of the site to isolate waste. The information in this report pertains to sensitivity studies evaluating previous hydrological performance assessment analyses to variation in the material properties, conceptual models, and ventilation models, and the implications of this sensitivity on previous recommendations supporting ESF design. This document contains information that has been used in preparing recommendations for Appendix I of the Exploratory Studies Facility Design Requirements document.
International Nuclear Information System (INIS)
Sobolik, S.R.; Ho, C.K.; Dunn, E.; Robey, T.H.; Cruz, W.T.
1996-07-01
The Yucca Mountain Site Characterization Project is studying Yucca Mountain in southwestern Nevada as a potential site for a high-level nuclear waste repository. Site characterization includes surface- based and underground testing. Analyses have been performed to support the design of an Exploratory Studies Facility (ESF) and the design of the tests performed as part of the characterization process, in order to ascertain that they have minimal impact on the natural ability of the site to isolate waste. The information in this report pertains to sensitivity studies evaluating previous hydrological performance assessment analyses to variation in the material properties, conceptual models, and ventilation models, and the implications of this sensitivity on previous recommendations supporting ESF design. This document contains information that has been used in preparing recommendations for Appendix I of the Exploratory Studies Facility Design Requirements document
Siddiq, A.; El Sayed, Tamer S.
2013-01-01
We present a variational multiscale constitutive model that accounts for intergranular failure in nanocrystalline fcc metals due to void growth and coalescence in the grain boundary region. Following previous work by the authors, a nanocrystalline
Abellán-Nebot, J. V.; Liu, J.; Romero, F.
2009-11-01
The State Space modelling approach has been recently proposed as an engineering-driven technique for part quality prediction in Multistage Machining Processes (MMP). Current State Space models incorporate fixture and datum variations in the multi-stage variation propagation, without explicitly considering common operation variations such as machine-tool thermal distortions, cutting-tool wear, cutting-tool deflections, etc. This paper shows the limitations of the current State Space model through an experimental case study where the effect of the spindle thermal expansion, cutting-tool flank wear and locator errors are introduced. The paper also discusses the extension of the current State Space model to include operation variations and its potential benefits.
International Nuclear Information System (INIS)
Dehghani, Hamid; Brooksby, Ben; Vishwanath, Karthik; Pogue, Brian W; Paulsen, Keith D
2003-01-01
Near-infrared (NIR) tomography is a technique used to measure light propagation through tissue and generate images of internal optical property distributions from boundary measurements. Most popular applications have concentrated on female breast imaging, neonatal and adult head imaging, as well as muscle and small animal studies. In most instances a highly scattering medium with a homogeneous refractive index is assumed throughout the imaging domain. Using these assumptions, it is possible to simplify the model to the diffusion approximation. However, biological tissue contains regions of varying optical absorption and scatter, as well as varying refractive index. In this work, we introduce an internal boundary constraint in the finite element method approach to modelling light propagation through tissue that accounts for regions of different refractive indices. We have compared the results to data from a Monte Carlo simulation and show that for a simple two-layered slab model of varying refractive index, the phase of the measured reflectance data is significantly altered by the variation in internal refractive index, whereas the amplitude data are affected only slightly
Solar Luminosity on the Main Sequence, Standard Model and Variations
Ayukov, S. V.; Baturin, V. A.; Gorshkov, A. B.; Oreshina, A. V.
2017-05-01
Our Sun became Main Sequence star 4.6 Gyr ago according Standard Solar Model. At that time solar luminosity was 30% lower than current value. This conclusion is based on assumption that Sun is fueled by thermonuclear reactions. If Earth's albedo and emissivity in infrared are unchanged during Earth history, 2.3 Gyr ago oceans had to be frozen. This contradicts to geological data: there was liquid water 3.6-3.8 Gyr ago on Earth. This problem is known as Faint Young Sun Paradox. We analyze luminosity change in standard solar evolution theory. Increase of mean molecular weight in the central part of the Sun due to conversion of hydrogen to helium leads to gradual increase of luminosity with time on the Main Sequence. We also consider several exotic models: fully mixed Sun; drastic change of pp reaction rate; Sun consisting of hydrogen and helium only. Solar neutrino observations however exclude most non-standard solar models.
Parametric modelling of temporal variations in radon concentrations in homes
International Nuclear Information System (INIS)
Revzan, K.L.; Turk, B.H.; Harrison, J.; Nero, A.V.; Sextro, R.G.
1988-01-01
The 222 Rn concentrations in the living area, the basement, and the undelying soil of a New Jersey home have been measured at half-hour intervals over the course of a year, as have indoor and outdoor temperatures, wind speed and direction, and indoor-outdoor and basement-subslab pressures; in addition, periods of furnace opration have been logged. We generalize and extend an existing radon entry model in order to demonstrate the dependence of the radon concentration on the environmental variales and the extent of furnace use. The model contains parameters which are dependent on geological and structural factors which have not been measured or otherwise determined; statistical methods are used to find the best values of the parameters. The non-linear regression of the model predictions (over time) on the measured living area radon concentrations yields an R/aup 2/ of 0.88. 9 refs., 2 figs
Sparse Decomposition and Modeling of Anatomical Shape Variation
DEFF Research Database (Denmark)
Sjöstrand, Karl; Rostrup, Egill; Ryberg, Charlotte
2007-01-01
counterparts if constructed carefully. In most medical applications, models are required to have both good statistical performance and a relevant clinical interpretation to be of value. Morphometry of the corpus callosum is one illustrative example. This paper presents a method for relating spatial features...... to clinical outcome data. A set of parsimonious variables is extracted using sparse principal component analysis, producing simple yet characteristic features. The relation of these variables with clinical data is then established using a regression model. The result may be visualized as patterns...... two alternative techniques, one where features are derived using a model-based wavelet approach, and one where the original variables are regressed directly on the outcome....
Sensitivity of euphotic zone properties to CDOM variations in marine ecosystem models
Urtizberea, Agurtzane; Dupont, Nicolas; Rosland, Rune; Aksnes, Dag L.
2013-01-01
In marine ecosystem models, the underwater light intensity is commonly characterized by the shading of phytoplankton in addition to a background light attenuation coefficient. Colour dissolved organic matter (CDOM) is an important component of the background light attenuation, and we investigate how variation in CDOM attenuation affects euphotic zone properties in a general marine ecosystem model. Our results suggest that euphotic zone properties are highly sensitive to CDOM variations occurr...
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)
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.
The nicolet lettuce model : a theme with variations
Seginer, I.; Linker, F.; Buwalda, F.; Straten, van G.
2004-01-01
The NICOLET model has been developed to predict the growth and nitrate content of greenhouse lettuce. Four single-organ versions have been developed: [1] abundant supply of nitrogen (1998), [2] mild N-stress (1999), [3] severe N-stress (2003), and [4] ontogenetic changes of organic-N and water
Cunha-Lignon, M.; Kampel, M.; Menghini, R.P.; Schaeffer-Novelli, Y.; Cintrón, G.; Dahdouh-Guebas, F.
2011-01-01
The current paper examines the growth and spatio-temporal variation of mangrove forests in response to depositional processes and different salinity conditions. Data from mangrove vegetation structure collected at permanent plots and satellite images were used. In the northern sector important environmental changes occurred due to an artificial channel producing modifications in salinity. The southern sector is considered the best conserved mangrove area along the coast of São Paulo State, Br...
Roof planes detection via a second-order variational model
Benciolini, Battista; Ruggiero, Valeria; Vitti, Alfonso; Zanetti, Massimo
2018-04-01
The paper describes a unified automatic procedure for the detection of roof planes in gridded height data. The procedure exploits the Blake-Zisserman (BZ) model for segmentation in both 2D and 1D, and aims to detect, to model and to label roof planes. The BZ model relies on the minimization of a functional that depends on first- and second-order derivatives, free discontinuities and free gradient discontinuities. During the minimization, the relative strength of each competitor is controlled by a set of weight parameters. By finding the minimum of the approximated BZ functional, one obtains: (1) an approximation of the data that is smoothed solely within regions of homogeneous gradient, and (2) an explicit detection of the discontinuities and gradient discontinuities of the approximation. Firstly, input data is segmented using the 2D BZ. The maps of data and gradient discontinuities are used to isolate building candidates and planar patches (i.e. regions with homogeneous gradient) that correspond to roof planes. Connected regions that can not be considered as buildings are filtered according to both patch dimension and distribution of the directions of the normals to the boundary. The 1D BZ model is applied to the curvilinear coordinates of boundary points of building candidates in order to reduce the effect of data granularity when the normals are evaluated. In particular, corners are preserved and can be detected by means of gradient discontinuity. Lastly, a total least squares model is applied to estimate the parameters of the plane that best fits the points of each planar patch (orthogonal regression with planar model). Refinement of planar patches is performed by assigning those points that are close to the boundaries to the planar patch for which a given proximity measure assumes the smallest value. The proximity measure is defined to account for the variance of a fitting plane and a weighted distance of a point from the plane. The effectiveness of the
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)
Moho Depth Variations in the Northeastern North China Craton Revealed by Receiver Function Imaging
Zhang, P.; Chen, L.; Yao, H.; Fang, L.
2016-12-01
The North China Craton (NCC), one of the oldest cratons in the world, has attracted wide attention in Earth Science for decades because of the unusual Mesozoic destruction of its cratonic lithosphere. Understanding the deep processes and mechanism of this craton destruction demands detailed knowledge about the deep structure of the region. In this study, we used two-year teleseismic receiver function data from the North China Seismic Array consisting of 200 broadband stations deployed in the northeastern NCC to image the Moho undulation of the region. A 2-D wave equation-based poststack depth migration method was employed to construct the structural images along 19 profiles, and a pseudo 3D crustal velocity model of the region based on previous ambient noise tomography and receiver function study was adopted in the migration. We considered both the Ps and PpPs phases, but in some cases we also conducted PpSs+PsPs migration using different back azimuth ranges of the data, and calculated the travel times of all the considered phases to constrain the Moho depths. By combining the structure images along the 19 profiles, we got a high-resolution Moho depth map beneath the northeastern NCC. Our results broadly consist with the results of previous active source studies [http://www.craton.cn/data], and show a good correlation of the Moho depths with geological and tectonic features. Generally, the Moho depths are distinctly different on the opposite sides of the North-South Gravity Lineament. The Moho in the west are deeper than 40 km and shows a rapid uplift from 40 km to 30 km beneath the Taihang Mountain Range in the middle. To the east in the Bohai Bay Basin, the Moho further shallows to 30-26 km depth and undulates by 3 km, coinciding well with the depressions and uplifts inside the basin. The Moho depth beneath the Yin-Yan Mountains in the north gradually decreases from 42 km in the west to 25 km in the east, varying much smoother than that to the south.
Robert E. Keane
2012-01-01
Simulation modeling can be a powerful tool for generating information about historical range of variation (HRV) in landscape conditions. In this chapter, I will discuss several aspects of the use of simulation modeling to generate landscape HRV data, including (1) the advantages and disadvantages of using simulation, (2) a brief review of possible landscape models. and...
Continuous monitoring of arthritis in animal models using optical imaging modalities
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.
Real-time intravital imaging of pH variation associated with osteoclast activity.
Maeda, Hiroki; Kowada, Toshiyuki; Kikuta, Junichi; Furuya, Masayuki; Shirazaki, Mai; Mizukami, Shin; Ishii, Masaru; Kikuchi, Kazuya
2016-08-01
Intravital imaging by two-photon excitation microscopy (TPEM) has been widely used to visualize cell functions. However, small molecular probes (SMPs), commonly used for cell imaging, cannot be simply applied to intravital imaging because of the challenge of delivering them into target tissues, as well as their undesirable physicochemical properties for TPEM imaging. Here, we designed and developed a functional SMP with an active-targeting moiety, higher photostability, and a fluorescence switch and then imaged target cell activity by injecting the SMP into living mice. The combination of the rationally designed SMP with a fluorescent protein as a reporter of cell localization enabled quantitation of osteoclast activity and time-lapse imaging of its in vivo function associated with changes in cell deformation and membrane fluctuations. Real-time imaging revealed heterogenic behaviors of osteoclasts in vivo and provided insights into the mechanism of bone resorption.
Core surface flow modelling from high-resolution secular variation
DEFF Research Database (Denmark)
Holme, R.; Olsen, Nils
2006-01-01
-flux hypothesis, but the spectrum of the SV implies that a conclusive test of frozen-flux is not possible. We parametrize the effects of diffusion as an expected misfit in the flow prediction due to departure from the frozen-flux hypothesis; at low spherical harmonic degrees, this contribution dominates...... the expected departure of the SV predictions from flow to the observed SV, while at high degrees the SV model uncertainty is dominant. We construct fine-scale core surface flows to model the SV. Flow non-uniqueness is a serious problem because the flows are sufficiently small scale to allow flow around non......-series of magnetic data and better parametrization of the external magnetic field....
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
On Geometric Variational Models for Inpainting Surface Holes (PREPRINT)
2006-01-01
email: haro@ima.umn.edu Phone: (612) 626-1501 Fax: (612) 626-7370 Affiliations: 1 Dept. de Tecnologia , University of Pompeu-Fabra, Passeig de...regions where the 3D model is incomplete. The main cause of holes are occlusions, but these can also be due to low reflectance, constraints in the...major areas where range scanners are used. With the increasing popularity of range scanners as 3D shape acquisition devices, with applications in
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.
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)
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...
Giannessi, Franco; Maugeri, Antonino; Equilibrium Problems and Variational Models
2000-01-01
The volume, devoted to variational analysis and its applications, collects selected and refereed contributions, which provide an outline of the field. The meeting of the title "Equilibrium Problems and Variational Models", which was held in Erice (Sicily) in the period June 23 - July 2 2000, was the occasion of the presentation of some of these papers; other results are a consequence of a fruitful and constructive atmosphere created during the meeting. New results, which enlarge the field of application of variational analysis, are presented in the book; they deal with the vectorial analysis, time dependent variational analysis, exact penalization, high order deriva tives, geometric aspects, distance functions and log-quadratic proximal methodology. The new theoretical results allow one to improve in a remarkable way the study of significant problems arising from the applied sciences, as continuum model of transportation, unilateral problems, multicriteria spatial price models, network equilibrium...
Woods, Thomas N; Snow, Martin; Harder, Jerald; Chapman, Gary; Cookson, Angela
A different approach to studying solar spectral irradiance (SSI) variations, without the need for long-term (multi-year) instrument degradation corrections, is examining the total energy of the irradiance variation during 6-month periods. This duration is selected because a solar active region typically appears suddenly and then takes 5 to 7 months to decay and disperse back into the quiet-Sun network. The solar outburst energy, which is defined as the irradiance integrated over the 6-month period and thus includes the energy from all phases of active region evolution, could be considered the primary cause for the irradiance variations. Because solar cycle variation is the consequence of multiple active region outbursts, understanding the energy spectral variation may provide a reasonable estimate of the variations for the 11-year solar activity cycle. The moderate-term (6-month) variations from the Solar Radiation and Climate Experiment (SORCE) instruments can be decomposed into positive (in-phase with solar cycle) and negative (out-of-phase) contributions by modeling the variations using the San Fernando Observatory (SFO) facular excess and sunspot deficit proxies, respectively. These excess and deficit variations are fit over 6-month intervals every 2 months over the mission, and these fitted variations are then integrated over time for the 6-month energy. The dominant component indicates which wavelengths are in-phase and which are out-of-phase with solar activity. The results from this study indicate out-of-phase variations for the 1400 - 1600 nm range, with all other wavelengths having in-phase variations.
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
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.
Solar activity variations of ionosonde measurements and modeling results
Czech Academy of Sciences Publication Activity Database
Altadill, D.; Arrazola, D.; Blanch, E.; Burešová, Dalia
2008-01-01
Roč. 42, č. 4 (2008), s. 610-616 ISSN 0273-1177 R&D Projects: GA AV ČR 1QS300120506 Grant - others:MCYT(ES) REN2003-08376-C02-02; CSIC(XE) 2004CZ0002; AGAUR(XE) 2006BE00112; AF Research Laboratory(XE) FA8718-L-0072 Institutional research plan: CEZ:AV0Z30420517 Keywords : mid-latitude ionosphere * bottomside modeling * ionospheric variability Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 0.860, year: 2008 http://www.sciencedirect.com/science/journal/02731177
Optical Imaging and Radiometric Modeling and Simulation
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
Introductory biology students' conceptual models and explanations of the origin of variation.
Speth, Elena Bray; Shaw, Neil; Momsen, Jennifer; Reinagel, Adam; Le, Paul; Taqieddin, Ranya; Long, Tammy
2014-01-01
Mutation is the key molecular mechanism generating phenotypic variation, which is the basis for evolution. In an introductory biology course, we used a model-based pedagogy that enabled students to integrate their understanding of genetics and evolution within multiple case studies. We used student-generated conceptual models to assess understanding of the origin of variation. By midterm, only a small percentage of students articulated complete and accurate representations of the origin of variation in their models. Targeted feedback was offered through activities requiring students to critically evaluate peers' models. At semester's end, a substantial proportion of students significantly improved their representation of how variation arises (though one-third still did not include mutation in their models). Students' written explanations of the origin of variation were mostly consistent with their models, although less effective than models in conveying mechanistic reasoning. This study contributes evidence that articulating the genetic origin of variation is particularly challenging for learners and may require multiple cycles of instruction, assessment, and feedback. To support meaningful learning of the origin of variation, we advocate instruction that explicitly integrates multiple scales of biological organization, assessment that promotes and reveals mechanistic and causal reasoning, and practice with explanatory models with formative feedback. © 2014 E. Bray Speth et al. CBE—Life Sciences Education © 2014 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).
Directory of Open Access Journals (Sweden)
Bin Yan
2015-01-01
Full Text Available Sparse-view imaging is a promising scanning method which can reduce the radiation dose in X-ray computed tomography (CT. Reconstruction algorithm for sparse-view imaging system is of significant importance. The adoption of the spatial iterative algorithm for CT image reconstruction has a low operation efficiency and high computation requirement. A novel Fourier-based iterative reconstruction technique that utilizes nonuniform fast Fourier transform is presented in this study along with the advanced total variation (TV regularization for sparse-view CT. Combined with the alternating direction method, the proposed approach shows excellent efficiency and rapid convergence property. Numerical simulations and real data experiments are performed on a parallel beam CT. Experimental results validate that the proposed method has higher computational efficiency and better reconstruction quality than the conventional algorithms, such as simultaneous algebraic reconstruction technique using TV method and the alternating direction total variation minimization approach, with the same time duration. The proposed method appears to have extensive applications in X-ray CT imaging.
Arous, Edward J; Simons, Jessica P; Flahive, Julie M; Beck, Adam W; Stone, David H; Hoel, Andrew W; Messina, Louis M; Schanzer, Andres
2015-10-01
Carotid endarterectomy (CEA) for asymptomatic carotid artery stenosis is among the most common procedures performed in the United States. However, consensus is lacking regarding optimal preoperative imaging, carotid duplex ultrasound criteria, and ultimately, the threshold for surgery. We sought to characterize national variation in preoperative imaging, carotid duplex ultrasound criteria, and threshold for surgery for asymptomatic CEA. The Society for Vascular Surgery Vascular Quality Initiative (VQI) database was used to identify all CEA procedures performed for asymptomatic carotid artery stenosis between 2003 and 2014. VQI currently captures 100% of CEA procedures performed at >300 centers by >2000 physicians nationwide. Three analyses were performed to quantify the variation in (1) preoperative imaging, (2) carotid duplex ultrasound criteria, and (3) threshold for surgery. Of 35,695 CEA procedures in 33,488 patients, the study cohort was limited to 19,610 CEA procedures (55%) performed for asymptomatic disease. The preoperative imaging modality used before CEA varied widely, with 57% of patients receiving a single preoperative imaging study (duplex ultrasound imaging, 46%; computed tomography angiography, 7.5%; magnetic resonance angiography, 2.0%; cerebral angiography, 1.3%) and 43% of patients receiving multiple preoperative imaging studies. Of the 16,452 asymptomatic patients (89%) who underwent preoperative duplex ultrasound imaging, there was significant variability between centers in the degree of stenosis (50%-69%, 70%-79%, 80%-99%) designated for a given peak systolic velocity, end diastolic velocity, and internal carotid artery-to-common carotid artery ratio. Although 68% of CEA procedures in asymptomatic patients were performed for an 80% to 99% stenosis, 26% were performed for a 70% to 79% stenosis, and 4.1% were performed for a 50% to 69% stenosis. At the surgeon level, the range in the percentage of CEA procedures performed for a duplex ultrasound
Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem
Lellmann, Jan; Lenzen, Frank; Schnö rr, Christoph
2012-01-01
We consider a variational convex relaxation of a class of optimal partitioning and multiclass labeling problems, which has recently proven quite successful and can be seen as a continuous analogue of Linear Programming (LP) relaxation methods
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)
A statistical model for radar images of agricultural scenes
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.
Energy Technology Data Exchange (ETDEWEB)
Cai, Zhen-Yi; Wang, Jun-Xian; Sun, Yu-Han; Wu, Mao-Chun; Huang, Xing-Xing; Chen, Xiao-Yang [CAS Key Laboratory for Researches in Galaxies and Cosmology, University of Science and Technology of China, Chinese Academy of Sciences, Hefei, Anhui 230026 (China); Gu, Wei-Min, E-mail: zcai@ustc.edu.cn, E-mail: jxw@ustc.edu.cn [Department of Astronomy and Institute of Theoretical Physics and Astrophysics, Xiamen University, Xiamen, Fujian 361005 (China)
2016-07-20
The UV–optical variability of active galactic nuclei and quasars is useful for understanding the physics of the accretion disk and is gradually being attributed to stochastic fluctuations over the accretion disk. Quasars generally appear bluer when they brighten in the UV–optical bands; the nature of this phenomenon remains controversial. Recently, Sun et al. discovered that the color variation of quasars is timescale-dependent, in the way that faster variations are even bluer than longer term ones. While this discovery can directly rule out models that simply attribute the color variation to contamination from the host galaxies, or to changes in the global accretion rates, it favors the stochastic disk fluctuation model as fluctuations in the inner-most hotter disk could dominate the short-term variations. In this work, we show that a revised inhomogeneous disk model, where the characteristic timescales of thermal fluctuations in the disk are radius-dependent (i.e., τ ∼ r ; based on that originally proposed by Dexter and Agol), can reproduce well a timescale-dependent color variation pattern, similar to the observed one and unaffected by the uneven sampling and photometric error. This demonstrates that one may statistically use variation emission at different timescales to spatially resolve the accretion disk in quasars, thus opening a new window with which to probe and test the accretion disk physics in the era of time domain astronomy. Caveats of the current model, which ought to be addressed in future simulations, are discussed.
Calabia, A.; Matsuo, T.; Jin, S.
2017-12-01
The upper atmospheric expansion refers to an increase in the temperature and density of Earth's thermosphere due to increased geomagnetic and space weather activities, producing anomalous atmospheric drag on LEO spacecraft. Increased drag decelerates satellites, moving their orbit closer to Earth, decreasing the lifespan of satellites, and making satellite orbit determination difficult. In this study, thermospheric neutral density variations due to geomagnetic forcing are investigated from 10 years (2003-2013) of GRACE's accelerometer-based estimates. In order to isolate the variations produced by geomagnetic forcing, 99.8% of the total variability has been modeled and removed through the parameterization of annual, LST, and solar-flux variations included in the primary Empirical Orthogonal Functions. The residual disturbances of neutral density variations have been investigated further in order to unravel their relationship to several geomagnetic indices and space weather activity indicators. Stronger fluctuations have been found in the southern polar cap, following the dipole-tilt angle variations. While the parameterization of the residual disturbances in terms of Dst index results in the best fit to training data, the use of merging electric field as a predictor leads to the best forecasting performance. An important finding is that modeling of neutral density variations in response geomagnetic forcing can be improved by accounting for the latitude-dependent delay. Our data-driven modeling results are further compared to modeling with TIEGCM.
Modeling pH variation in reverse osmosis.
Nir, Oded; Bishop, Noga Fridman; Lahav, Ori; Freger, Viatcheslav
2015-12-15
The transport of hydronium and hydroxide ions through reverse osmosis membranes constitutes a unique case of ionic species characterized by uncommonly high permeabilities. Combined with electromigration, this leads to complex behavior of permeate pH, e.g., negative rejection, as often observed for monovalent ions in nanofiltration of salt mixtures. In this work we employed a rigorous phenomenological approach combined with chemical equilibrium to describe the trans-membrane transport of hydronium and hydroxide ions along with salt transport and calculate the resulting permeate pH. Starting from the Nernst-Planck equation, a full non-linear transport equation was derived, for which an approximate solution was proposed based on the analytical solution previously developed for trace ions in a dominant salt. Using the developed approximate equation, transport coefficients were deduced from experimental results obtained using a spiral wound reverse osmosis module operated under varying permeate flux (2-11 μm/s), NaCl feed concentrations (0.04-0.18 M) and feed pH values (5.5-9.0). The approximate equation agreed well with the experimental results, corroborating the finding that diffusion and electromigration, rather than a priori neglected convection, were the major contributors to the transport of hydronium and hydroxide. The approach presented here has the potential to improve the predictive capacity of reverse osmosis transport models for acid-base species, thereby improving process design/control. Copyright © 2015 Elsevier Ltd. All rights reserved.
Variations in Modeled Dengue Transmission over Puerto Rico Using a Climate Driven Dynamic Model
Morin, Cory; Monaghan, Andrew; Crosson, William; Quattrochi, Dale; Luvall, Jeffrey
2014-01-01
Dengue fever is a mosquito-borne viral disease reemerging throughout much of the tropical Americas. Dengue virus transmission is explicitly influenced by climate and the environment through its primary vector, Aedes aegypti. Temperature regulates Ae. aegypti development, survival, and replication rates as well as the incubation period of the virus within the mosquito. Precipitation provides water for many of the preferred breeding habitats of the mosquito, including buckets, old tires, and other places water can collect. Because of variations in topography, ocean influences and atmospheric processes, temperature and rainfall patterns vary across Puerto Rico and so do dengue virus transmission rates. Using NASA's TRMM (Tropical Rainfall Measuring Mission) satellite for precipitation input, ground-based observations for temperature input, and laboratory confirmed dengue cases reported by the Centers for Disease Control and Prevention for parameter calibration, we modeled dengue transmission at the county level across Puerto Rico from 2010-2013 using a dynamic dengue transmission model that includes interacting vector ecology and epidemiological components. Employing a Monte Carlo approach, we performed ensembles of several thousands of model simulations for each county in order to resolve the model uncertainty arising from using different combinations of parameter values that are not well known. The top 1% of model simulations that best reproduced the reported dengue case data were then analyzed to determine the most important parameters for dengue virus transmission in each county, as well as the relative influence of climate variability on transmission. These results can be used by public health workers to implement dengue control methods that are targeted for specific locations and climate conditions.
DEFF Research Database (Denmark)
Finlay, Chris; Olsen, Nils; Gillet, Nicolas
We present a new ensemble of time-dependent magnetic field models constructed from satellite and observatory data spanning 1997-2013 that are compatible with prior information concerning the temporal spectrum of core field variations. These models allow sharper field changes compared to tradition...... physical hypotheses can be tested by asking questions of the entire ensemble of core field models, rather than by interpreting any single model.......We present a new ensemble of time-dependent magnetic field models constructed from satellite and observatory data spanning 1997-2013 that are compatible with prior information concerning the temporal spectrum of core field variations. These models allow sharper field changes compared to traditional...... regularization methods based on minimizing the square of second or third time derivative. We invert satellite and observatory data directly by adopting the external field and crustal field modelling framework of the CHAOS model, but apply the stochastic process method of Gillet et al. (2013) to the core field...
International Nuclear Information System (INIS)
Cunningham, G. S.; Lehovich, A.
2000-01-01
The Bayes Inference Engine (BIE) has been used to perform a 4D reconstruction of a first-pass radiotracer bolus distribution inside a CardioWest Total Artificial Heart, imaged with the University of Arizona's FastSPECT system. The BIE estimates parameter values that define the 3D model of the radiotracer distribution at each of 41 times spanning about two seconds. The 3D models have two components: a closed surface, composed of hi-quadratic Bezier triangular surface patches, that defines the interface between the part of the blood pool that contains radiotracer and the part that contains no radiotracer, and smooth voxel-to-voxel variations in intensity within the closed surface. Ideally, the surface estimates the ventricular wall location where the bolus is infused throughout the part of the blood pool contained by the right ventricle. The voxel-to-voxel variations are needed to model an inhomogeneously-mixed bolus. Maximum a posterior (MAP) estimates of the Bezier control points and voxel values are obtained for each time frame. We show new reconstructions using the Bezier surface models, and discuss estimates of ventricular volume as a function of time, ejection fraction, and wall motion. The computation time for our reconstruction process, which directly estimates complex 3D model parameters from the raw data, is performed in a time that is competitive with more traditional voxel-based methods (ML-EM, e.g.)
The continuing challenge of understanding and modeling hemodynamic variation in fMRI
Handwerker, Daniel A.; Gonzalez-Castillo, Javier; D’Esposito, Mark; Bandettini, Peter A.
2012-01-01
Interpretation of fMRI data depends on our ability to understand or model the shape of the hemodynamic response (HR) to a neural event. Although the HR has been studied almost since the beginning of fMRI, we are still far from having robust methods to account for the full range of known HR variation in typical fMRI analyses. This paper reviews how the authors and others contributed to our understanding of HR variation. We present an overview of studies that describe HR variation across voxels...
Zeder, M; Van den Wyngaert, S; Köster, O; Felder, K M; Pernthaler, J
2010-01-01
Quantification and sizing of filamentous cyanobacteria in environmental samples or cultures are time-consuming and are often performed by using manual or semiautomated microscopic analysis. Automation of conventional image analysis is difficult because filaments may exhibit great variations in length and patchy autofluorescence. Moreover, individual filaments frequently cross each other in microscopic preparations, as deduced by modeling. This paper describes a novel approach based on object-...
International Nuclear Information System (INIS)
Boning, Duane S.; Chung, James E.
1998-01-01
Advanced process technology will require more detailed understanding and tighter control of variation in devices and interconnects. The purpose of statistical metrology is to provide methods to measure and characterize variation, to model systematic and random components of that variation, and to understand the impact of variation on both yield and performance of advanced circuits. Of particular concern are spatial or pattern-dependencies within individual chips; such systematic variation within the chip can have a much larger impact on performance than wafer-level random variation. Statistical metrology methods will play an important role in the creation of design rules for advanced technologies. For example, a key issue in multilayer interconnect is the uniformity of interlevel dielectric (ILD) thickness within the chip. For the case of ILD thickness, we describe phases of statistical metrology development and application to understanding and modeling thickness variation arising from chemical-mechanical polishing (CMP). These phases include screening experiments including design of test structures and test masks to gather electrical or optical data, techniques for statistical decomposition and analysis of the data, and approaches to calibrating empirical and physical variation models. These models can be integrated with circuit CAD tools to evaluate different process integration or design rule strategies. One focus for the generation of interconnect design rules are guidelines for the use of 'dummy fill' or 'metal fill' to improve the uniformity of underlying metal density and thus improve the uniformity of oxide thickness within the die. Trade-offs that can be evaluated via statistical metrology include the improvements to uniformity possible versus the effect of increased capacitance due to additional metal
Modelling the quiet-time geomagnetic daily variations using observatory data
Hamilton, Brian; Macmillan, Susan
2008-01-01
We present on-going work towards building a global model of the quiet-time geomagnetic daily variation using bservatory data. We select hourly mean data during June 2006 (solar minimum). We fit Fourier series in time, with a fundamental period of 24 hours, to the data at each observatory. We then use global spherical harmonic expansions to separate the daily variation signal, as characterised by the Fourier coefficients in time, into external and induced internal contributions. The mode...
Inter-temporal variation in the travel time and travel cost parameters of transport models
Börjesson, Maria
2012-01-01
The parameters for travel time and travel cost are central in travel demand forecasting models. Since valuation of infrastructure investments requires prediction of travel demand for future evaluation years, inter-temporal variation of the travel time and travel cost parameters is a key issue in forecasting. Using two identical stated choice experiments conducted among Swedish drivers with an interval of 13 years, 1994 and 2007, this paper estimates the inter-temporal variation in travel time...
The Kadanoff lower-bound variational renormalization group applied to an SU(2) lattice spin model
International Nuclear Information System (INIS)
Thorleifsson, G.; Damgaard, P.H.
1990-07-01
We apply the variational lower-bound Renormalization Group transformation of Kadanoff to an SU(2) lattice spin model in 2 and 3 dimensions. Even in the one-hypercube framework of this renormalization group transformation the present model is characterised by having an infinite basis of fundamental operators. We investigate whether the lower-bound variational renormalization group transformation yields results stable under truncations of this operator basis. Our results show that for this particular spin model this is not the case. (orig.)
Lesparre, Nolwenn; Cabrera, Justo; Courbet, Christelle
2015-04-01
We explore the capacity of electrical resistivity tomography and muon density imaging to detect spatio-temporal variations of the medium surrounding a regional fault crossing the underground platform of Tournemire (Aveyron, France). The studied Cernon fault is sub-vertical and intersects perpendicularly the tunnel of Tournemire and extends to surface. The fault separates clay and limestones layers of the Dogger from limestones layers of the Lias. The Cernon fault presents a thickness of a ten of meters and drives water from an aquifer circulating at the top of the Dogger clay layer to the tunnel. An experiment combining electrical resistivity imaging and muon density imaging was setup taking advantage of the tunnel presence. A specific array of electrodes were set up, adapted for the characterization of the fault. Electrodes were placed along the tunnel as well as at the surface above the tunnel on both sides of the fault in order to acquire data in transmission across the massif to better cover the sounded medium. Electrical resistivity is particularly sensitive to water presence in the medium and thus carry information on the main water flow paths and on the pore space saturation. At the same time a muon sensor was placed in the tunnel under the fault region to detect muons coming from the sky after their crossing of the rock medium. Since the muon flux is attenuated as function of the quantity of matter crossed, muons flux measurements supply information on the medium average density along muons paths. The sensor presents 961 angles of view so measurements performed from one station allows a comparison of the muon flux temporal variations along the fault as well as in the medium surrounding the fault. As the water saturation of the porous medium fluctuates through time the medium density might indeed present sensible variations as shown by gravimetric studies. During the experiment important rainfalls occurred leading variations of the medium properties
Pelech, E. A.; McGrath, J.; Pederson, T.; Bernacchi, C.
2017-12-01
Increases in the global average temperature will consequently induce a higher occurrence of severe environmental conditions such as drought on arable land. To mitigate these threats, crops for fuel and food must be bred for higher water-use efficiencies (WUE). Defining genomic variation through high-throughput phenotypic analysis in field conditions has the potential to relieve the major bottleneck in linking desirable genetic traits to the associated phenotypic response. This can subsequently enable breeders to create new agricultural germplasm that supports the need for higher water-use efficient crops. From satellites to field-based aerial and ground sensors, the reflectance properties of vegetation measured by hyperspectral imaging is becoming a rapid high-throughput phenotyping technique. A variety of physiological traits can be inferred by regression analysis with leaf reflectance which is controlled by the properties and abundance of water, carbon, nitrogen and pigments. Although, given that the current established vegetation indices are designed to accentuate these properties from spectral reflectance, it becomes a challenge to infer relative measurements of WUE at a crop canopy scale without ground-truth data collection. This study aims to correlate established biomass and canopy-water-content indices with ground-truth data. Five bioenergy sorghum genotypes (Sorghum bicolor L. Moench) that have differences in WUE and wild-type Tobacco (Nicotiana tabacum var. Samsun) under irrigated and rainfed field conditions were examined. A linear regression analysis was conducted to determine if variation in canopy water content and biomass, driven by natural genotypic and artificial treatment influences, can be inferred using established vegetation indices. The results from this study will elucidate the ability of ground field-based hyperspectral imaging to assess variation in water content, biomass and water-use efficiency. This can lead to improved opportunities to
Sparse representation based image interpolation with nonlocal autoregressive modeling.
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.
Hamad, Ana Paula Andrade; Carrete, Henrique; Bianchin, Marino Muxfeldt; Ferrari-Marinho, Taissa; Lin, Katia; Yacubian, Elza Márcia Targas; Vilanova, Luiz Celso Pereira; Garzon, Eliana; Caboclo, Luís Otávio; Sakamoto, Américo Ceiki
2013-01-01
Morphological variations of hippocampal formation (MVHF) are observed in patients with epilepsy but also in asymptomatic individuals. The precise role of these findings in epilepsy is not yet fully understood. This study analyzes the hippocampal formation (HF) morphology of asymptomatic individuals (n = 30) and of patients with mesial temporal lobe epilepsy associated with hippocampal sclerosis (MTLE-HS) (n = 68), patients with malformations of cortical development (MCD) (n = 34), or patients with pure morphological variations of hippocampal formation (pure MVHF) (n = 12). Main clinical and electrophysiological data of patients with MVHF were also analyzed. Morphological variations of hippocampal formation are more frequently observed in patients with MCD than in patients with MTLE-HS or in asymptomatic individuals. Patients with pure morphological variations of hippocampal formation showed higher incidence of extratemporal seizure onset. Refractoriness seems to be more associated with other abnormalities, like HS or MCD, than with the HF variation itself. Thus, although morphological HF abnormalities might play a role in epileptogenicity, they seem to contribute less to refractoriness. Copyright © 2012 Elsevier Inc. All rights reserved.
A variation method in the optimization problem of the minority game model
International Nuclear Information System (INIS)
Blazhyijevs'kij, L.; Yanyishevs'kij, V.
2009-01-01
This article contains the results of applying a variation method in the investigation of the optimization problem in the minority game model. That suggested approach is shown to give relevant results about phase transition in the model. Other methods pertinent to the problem have also been assessed.
Does litter size variation affect models of terrestrial carnivore extinction risk and management?
Directory of Open Access Journals (Sweden)
Eleanor S Devenish-Nelson
Full Text Available Individual variation in both survival and reproduction has the potential to influence extinction risk. Especially for rare or threatened species, reliable population models should adequately incorporate demographic uncertainty. Here, we focus on an important form of demographic stochasticity: variation in litter sizes. We use terrestrial carnivores as an example taxon, as they are frequently threatened or of economic importance. Since data on intraspecific litter size variation are often sparse, it is unclear what probability distribution should be used to describe the pattern of litter size variation for multiparous carnivores.We used litter size data on 32 terrestrial carnivore species to test the fit of 12 probability distributions. The influence of these distributions on quasi-extinction probabilities and the probability of successful disease control was then examined for three canid species - the island fox Urocyon littoralis, the red fox Vulpes vulpes, and the African wild dog Lycaon pictus. Best fitting probability distributions differed among the carnivores examined. However, the discretised normal distribution provided the best fit for the majority of species, because variation among litter-sizes was often small. Importantly, however, the outcomes of demographic models were generally robust to the distribution used.These results provide reassurance for those using demographic modelling for the management of less studied carnivores in which litter size variation is estimated using data from species with similar reproductive attributes.
Jánský, Jaroslav; Lucas, Greg M.; Kalb, Christina; Bayona, Victor; Peterson, Michael J.; Deierling, Wiebke; Flyer, Natasha; Pasko, Victor P.
2017-12-01
This work analyzes different current source and conductivity parameterizations and their influence on the diurnal variation of the global electric circuit (GEC). The diurnal variations of the current source parameterizations obtained using electric field and conductivity measurements from plane overflights combined with global Tropical Rainfall Measuring Mission satellite data give generally good agreement with measured diurnal variation of the electric field at Vostok, Antarctica, where reference experimental measurements are performed. An approach employing 85 GHz passive microwave observations to infer currents within the GEC is compared and shows the best agreement in amplitude and phase with experimental measurements. To study the conductivity influence, GEC models solving the continuity equation in 3-D are used to calculate atmospheric resistance using yearly averaged conductivity obtained from the global circulation model Community Earth System Model (CESM). Then, using current source parameterization combining mean currents and global counts of electrified clouds, if the exponential conductivity is substituted by the conductivity from CESM, the peak to peak diurnal variation of the ionospheric potential of the GEC decreases from 24% to 20%. The main reason for the change is the presence of clouds while effects of 222Rn ionization, aerosols, and topography are less pronounced. The simulated peak to peak diurnal variation of the electric field at Vostok is increased from 15% to 18% from the diurnal variation of the global current in the GEC if conductivity from CESM is used.
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
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.
Razafindrakoto, H. N. T.
2014-03-25
One way to improve the accuracy and reliability of kinematic earthquake source imaging is to investigate the origin of uncertainty and to minimize their effects. The difficulties in kinematic source inversion arise from the nonlinearity of the problem, nonunique choices in the parameterization, and observational errors. We analyze particularly the uncertainty related to the choice of the source time function (STF) and the variability in Earth structure. We consider a synthetic data set generated from a spontaneous dynamic rupture calculation. Using Bayesian inference, we map the solution space of peak slip rate, rupture time, and rise time to characterize the kinematic rupture in terms of posterior density functions. Our test to investigate the effect of the choice of STF reveals that all three tested STFs (isosceles triangle, regularized Yoffe with acceleration time of 0.1 and 0.3 s) retrieve the patch of high slip and slip rate around the hypocenter. However, the use of an isosceles triangle as STF artificially accelerates the rupture to propagate faster than the target solution. It additionally generates an artificial linear correlation between rupture onset time and rise time. These appear to compensate for the dynamic source effects that are not included in the symmetric triangular STF. The exact rise time for the tested STFs is difficult to resolve due to the small amount of radiated seismic moment in the tail of STF. To highlight the effect of Earth structure variability, we perform inversions including the uncertainty in the wavespeed only, and variability in both wavespeed and layer depth. We find that little difference is noticeable between the resulting rupture model uncertainties from these two parameterizations. Both significantly broaden the posterior densities and cause faster rupture propagation particularly near the hypocenter due to the major velocity change at the depth where the fault is located.
Razafindrakoto, H. N. T.; Mai, Paul Martin
2014-01-01
One way to improve the accuracy and reliability of kinematic earthquake source imaging is to investigate the origin of uncertainty and to minimize their effects. The difficulties in kinematic source inversion arise from the nonlinearity of the problem, nonunique choices in the parameterization, and observational errors. We analyze particularly the uncertainty related to the choice of the source time function (STF) and the variability in Earth structure. We consider a synthetic data set generated from a spontaneous dynamic rupture calculation. Using Bayesian inference, we map the solution space of peak slip rate, rupture time, and rise time to characterize the kinematic rupture in terms of posterior density functions. Our test to investigate the effect of the choice of STF reveals that all three tested STFs (isosceles triangle, regularized Yoffe with acceleration time of 0.1 and 0.3 s) retrieve the patch of high slip and slip rate around the hypocenter. However, the use of an isosceles triangle as STF artificially accelerates the rupture to propagate faster than the target solution. It additionally generates an artificial linear correlation between rupture onset time and rise time. These appear to compensate for the dynamic source effects that are not included in the symmetric triangular STF. The exact rise time for the tested STFs is difficult to resolve due to the small amount of radiated seismic moment in the tail of STF. To highlight the effect of Earth structure variability, we perform inversions including the uncertainty in the wavespeed only, and variability in both wavespeed and layer depth. We find that little difference is noticeable between the resulting rupture model uncertainties from these two parameterizations. Both significantly broaden the posterior densities and cause faster rupture propagation particularly near the hypocenter due to the major velocity change at the depth where the fault is located.
Directory of Open Access Journals (Sweden)
Shuangcheng Deng
2016-04-01
Full Text Available Surface reconstruction for freehand 3D ultrasound is used to provide 3D visualization of a VOI (volume of interest during image-guided tumor ablation surgery. This is a challenge because the recorded 2D B-scans are not only sparse but also non-parallel. To solve this issue, we established a framework to reconstruct the surface of freehand 3D ultrasound imaging in 2011. The key technique for surface reconstruction in that framework is based on variational interpolation presented by Greg Turk for shape transformation and is named Variational Surface Reconstruction (VSR. The main goal of this paper is to evaluate the quality of surface reconstructions, especially when the input data are extremely sparse point clouds from freehand 3D ultrasound imaging, using four methods: Ball Pivoting, Power Crust, Poisson, and VSR. Four experiments are conducted, and quantitative metrics, such as the Hausdorff distance, are introduced for quantitative assessment. The experiment results show that the performance of the proposed VSR method is the best of the four methods at reconstructing surface from sparse data. The VSR method can produce a close approximation to the original surface from as few as two contours, whereas the other three methods fail to do so. The experiment results also illustrate that the reproducibility of the VSR method is the best of the four methods.
Energy Technology Data Exchange (ETDEWEB)
Van Leersum, M.D. [Dept. of Radiology, Thomas Jefferson Univ. Hospital, Philadelphia, PA (United States); Schweitzer, M.E. [Dept. of Radiology, Thomas Jefferson Univ. Hospital, Philadelphia, PA (United States); Gannon, F. [Dept. of Pathology, Thomas Jefferson Univ. Hospital, Philadelphia, PA (United States); Vinitski, S. [Dept. of Radiology, Thomas Jefferson Univ. Hospital, Philadelphia, PA (United States); Finkel, G. [Dept. of Pathology, Thomas Jefferson Univ. Hospital, Philadelphia, PA (United States); Mitchell, D.G. [Dept. of Radiology, Thomas Jefferson Univ. Hospital, Philadelphia, PA (United States)
1995-08-01
This study was undertaken to assess the accuracy, precision, and reliability of magnetic resonance (MR) measurements of articular cartilage. Fifteen cadaveric patellas were imaged in the axial plane at 1.5 T. Gradient echo and fat-suppressed FSE, T2-weighted, proton density, and T1-weighted sequences were performed. We measured each 5-mm section separately at three standardized positions, giving a total of 900 measurements. These findings were correlated with independently performed measurements of the corresponding anatomic sections. A hundred random measurements were also evaluated for reproducibility and interobserver variation. Although all sequences were highly accurate, the T1-weighted images were the most accurate, with a mean difference of 0.25 mm and a correlation coefficient of 0.85. All sequences were also highly reproducible with little inter-observer variation. In an attempt to improve the accuracy of the MR measurements further, we retrospectively evaluated all measurements with discrepancies greater than 1 mm from the specimen. All these differences were attributable to focal defects causing exaggeration of the thickness on MR imaging. (orig.)
International Nuclear Information System (INIS)
Van Leersum, M.D.; Schweitzer, M.E.; Gannon, F.; Vinitski, S.; Finkel, G.; Mitchell, D.G.
1995-01-01
This study was undertaken to assess the accuracy, precision, and reliability of magnetic resonance (MR) measurements of articular cartilage. Fifteen cadaveric patellas were imaged in the axial plane at 1.5 T. Gradient echo and fat-suppressed FSE, T2-weighted, proton density, and T1-weighted sequences were performed. We measured each 5-mm section separately at three standardized positions, giving a total of 900 measurements. These findings were correlated with independently performed measurements of the corresponding anatomic sections. A hundred random measurements were also evaluated for reproducibility and interobserver variation. Although all sequences were highly accurate, the T1-weighted images were the most accurate, with a mean difference of 0.25 mm and a correlation coefficient of 0.85. All sequences were also highly reproducible with little inter-observer variation. In an attempt to improve the accuracy of the MR measurements further, we retrospectively evaluated all measurements with discrepancies greater than 1 mm from the specimen. All these differences were attributable to focal defects causing exaggeration of the thickness on MR imaging. (orig.)
Hybrid model for forecasting time series with trend, seasonal and salendar variation patterns
Suhartono; Rahayu, S. P.; Prastyo, D. D.; Wijayanti, D. G. P.; Juliyanto
2017-09-01
Most of the monthly time series data in economics and business in Indonesia and other Moslem countries not only contain trend and seasonal, but also affected by two types of calendar variation effects, i.e. the effect of the number of working days or trading and holiday effects. The purpose of this research is to develop a hybrid model or a combination of several forecasting models to predict time series that contain trend, seasonal and calendar variation patterns. This hybrid model is a combination of classical models (namely time series regression and ARIMA model) and/or modern methods (artificial intelligence method, i.e. Artificial Neural Networks). A simulation study was used to show that the proposed procedure for building the hybrid model could work well for forecasting time series with trend, seasonal and calendar variation patterns. Furthermore, the proposed hybrid model is applied for forecasting real data, i.e. monthly data about inflow and outflow of currency at Bank Indonesia. The results show that the hybrid model tend to provide more accurate forecasts than individual forecasting models. Moreover, this result is also in line with the third results of the M3 competition, i.e. the hybrid model on average provides a more accurate forecast than the individual model.
Directory of Open Access Journals (Sweden)
Rawid Banchuin
2013-01-01
Full Text Available The novel probabilistic models of the random variations in nanoscale MOSFET's high frequency performance defined in terms of gate capacitance and transition frequency have been proposed. As the transition frequency variation has also been considered, the proposed models are considered as complete unlike the previous one which take only the gate capacitance variation into account. The proposed models have been found to be both analytic and physical level oriented as they are the precise mathematical expressions in terms of physical parameters. Since the up-to-date model of variation in MOSFET's characteristic induced by physical level fluctuation has been used, part of the proposed models for gate capacitance is more accurate and physical level oriented than its predecessor. The proposed models have been verified based on the 65 nm CMOS technology by using the Monte-Carlo SPICE simulations of benchmark circuits and Kolmogorov-Smirnov tests as highly accurate since they fit the Monte-Carlo-based analysis results with 99% confidence. Hence, these novel models have been found to be versatile for the statistical/variability aware analysis/design of nanoscale MOSFET-based analog/mixed signal circuits and systems.
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)
Fisheye image rectification using spherical and digital distortion models
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.
Improved Denoising via Poisson Mixture Modeling of Image Sensor Noise.
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.
pyBSM: A Python package for modeling imaging systems
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.
Flux and color variations of the doubly imaged quasar UM673
DEFF Research Database (Denmark)
Ricci, D.; Elyiv, A.; Finet, F.
2013-01-01
Aims. With the aim of characterizing the flux and color variations of the multiple components of the gravitationally lensed quasar UM673 as a function of time, we have performed multiepoch and multiband photometric observations with the Danish telescope at the La Silla Observatory. Methods...
Schlaffke, Lara; Rehmann, Robert; Froeling, Martijn; Kley, Rudolf; Tegenthoff, Martin; Vorgerd, Matthias; Schmidt-Wilcke, Tobias
2017-01-01
Purpose: To investigate to what extent inter- and intramuscular variations of diffusion parameters of human calf muscles can be explained by age, gender, muscle location, and body mass index (BMI) in a specific age group (20-35 years). Materials and Methods: Whole calf muscles of 18 healthy
Monitoring scale-specific and temporal variation in electromagnetic conductivity images
In the semi-arid and arid landscapes of southwest USA, irrigation sustains agricultural activity; however, there are increasing demands on water resources. As such spatial temporal variation of soil moisture needs to be monitored. One way to do this is to use electromagnetic (EM) induction instrumen...
Correlation of breast image alignment using biomechanical modelling
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.
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.
Camps; Prevot
1996-08-09
The statistical characteristics of the local magnetic field of Earth during paleosecular variation, excursions, and reversals are described on the basis of a database that gathers the cleaned mean direction and average remanent intensity of 2741 lava flows that have erupted over the last 20 million years. A model consisting of a normally distributed axial dipole component plus an independent isotropic set of vectors with a Maxwellian distribution that simulates secular variation fits the range of geomagnetic fluctuations, in terms of both direction and intensity. This result suggests that the magnitude of secular variation vectors is independent of the magnitude of Earth's axial dipole moment and that the amplitude of secular variation is unchanged during reversals.
Directory of Open Access Journals (Sweden)
Rawid Banchuin
2014-01-01
Full Text Available In this research, the analysis of statistical variations in subthreshold MOSFET's high frequency characteristics defined in terms of gate capacitance and transition frequency, have been shown and the resulting comprehensive analytical models of such variations in terms of their variances have been proposed. Major imperfection in the physical level properties including random dopant fluctuation and effects of variations in MOSFET's manufacturing process, have been taken into account in the proposed analysis and modeling. The up to dated comprehensive analytical model of statistical variation in MOSFET's parameter has been used as the basis of analysis and modeling. The resulting models have been found to be both analytic and comprehensive as they are the precise mathematical expressions in terms of physical level variables of MOSFET. Furthermore, they have been verified at the nanometer level by using 65~nm level BSIM4 based benchmarks and have been found to be very accurate with smaller than 5 % average percentages of errors. Hence, the performed analysis gives the resulting models which have been found to be the potential mathematical tool for the statistical and variability aware analysis and design of subthreshold MOSFET based VHF circuits, systems and applications.
Variational Data Assimilative Modeling of the Gulf of Maine Circulation in Spring and Summer 2010
Li, Yizhen; He, Ruoying; Chen, Ke; McGillicuddy, Dennis J.
2015-01-01
A data assimilative ocean circulation model is used to hindcast the Gulf of Maine (GOM) circulation in spring and summer 2010. Using the recently developed incremental strong constraint 4D Variational data assimilation algorithm, the model assimilates satellite sea surface temperature and in situ temperature and salinity profiles measured by expendable bathythermograph, Argo floats, and shipboard CTD casts. Validation against independent observations shows that the model skill is significantl...
Market Microstructure Model: study of variations of exchange rate for Asia and Latin America
Lima, Antonieta; Salazar Soares , Vasco
2008-01-01
The paper studies the commercial relations between Europe and its principal commercial partners, such as Asia and Latin America, for the period of 1999 to 2007. The methodology appeals to the correlation analysis of the variables of the model and the autocorrelation of the exchange rate variation variable, to the Augmented DickeyFuller (1979) and Philips Perron tests (1988), and finally, to the market microstructure model suggested by Medeiros(2005). Medeiros(2005) model, when applied to the ...
DEFF Research Database (Denmark)
Löwe, Roland; Del Giudice, Dario; Mikkelsen, Peter Steen
of input uncertainties observed in the models. The explicit inclusion of such variations in the modelling process will lead to a better fulfilment of the assumptions made in formal statistical frameworks, thus reducing the need to resolve to informal methods. The two approaches presented here...
APPLICATION OF LEARNING CYCLE MODEL (5E LEARNING WITH CHART VARIATION TOWARDSTUDENTS’ CREATIVITY
Directory of Open Access Journals (Sweden)
Suciati -
2015-04-01
Full Text Available This study aims to determine the differences in the application of the model LC (5E with a technique variation (interrelationship diagram / ID and affinity diagrams / AD of two classes of different school (XIPA-8 class of SMAN 3 Surakarta and class XIPA-6 of SMAN 3 Boyolali, toward the increase of students’ creativity. This research is a qualitative descriptive study. The results of this study, we can conclude that the application of the model LC (5E with a technique variation at two schools can improve students' creativity despite different levels of improvement.
Variational solution of the Gross-Neveu model; 2, finite-N and renormalization
Arvanitis, C; Iacomi, M; Kneur, J L; Neveu, A
1995-01-01
We show how to perform systematically improvable variational calculations in the O(2N) Gross-Neveu model for generic N, in such a way that all infinities usually plaguing such calculations are accounted for in a way compatible with the renormalization group. The final point is a general framework for the calculation of non-perturbative quantities like condensates, masses, etc..., in an asymptotically free field theory. For the Gross-Neveu model, the numerical results obtained from a "two-loop" variational calculation are in very good agreement with exact quantities down to low values of N.
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...
Fuzzy object models for newborn brain MR image segmentation
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.
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.
Infrared and visible image fusion based on total variation and augmented Lagrangian.
Guo, Hanqi; Ma, Yong; Mei, Xiaoguang; Ma, Jiayi
2017-11-01
This paper proposes a new algorithm for infrared and visible image fusion based on gradient transfer that achieves fusion by preserving the intensity of the infrared image and then transferring gradients in the corresponding visible one to the result. The gradient transfer suffers from the problems of low dynamic range and detail loss because it ignores the intensity from the visible image. The new algorithm solves these problems by providing additive intensity from the visible image to balance the intensity between the infrared image and the visible one. It formulates the fusion task as an l 1 -l 1 -TV minimization problem and then employs variable splitting and augmented Lagrangian to convert the unconstrained problem to a constrained one that can be solved in the framework of alternating the multiplier direction method. Experiments demonstrate that the new algorithm achieves better fusion results with a high computation efficiency in both qualitative and quantitative tests than gradient transfer and most state-of-the-art methods.
International Nuclear Information System (INIS)
Price, S.J.; Fryer, T.D.; Cleij, M.C.; Dean, A.F.; Joseph, J.; Salvador, R.; Wang, D.D.; Hutchinson, P.J.; Clark, J.C.; Burnet, N.G.; Pickard, J.D.; Aigbirhio, F.I.
2009-01-01
Aim: To compare regional variations in uptake of 3'-deoxy-3'- [ 18 F]-fluorothymidine (FLT) images using positron-emission tomography (PET) with measures of cellular proliferation from biopsy specimens obtained by image-guided brain biopsies. Materials and methods: Fourteen patients with a supratentorial glioma that required an image-guided brain biopsy were imaged preoperatively with dynamic PET after the administration of FLT. Maps of FLT irreversible uptake rate (K i ) and standardized uptake value (SUV) were calculated. These maps were co-registered to a gadolinium-enhanced T1-weighted spoiled gradient echo (SPGR) sequence that was used for biopsy guidance, and the mean and maximum K i and SUV determined for each biopsy site. These values were correlated with the MIB-1 labelling index (a tissue marker of proliferation) from these biopsy sites. Results: A total of 57 biopsy sites were studied. Although all measures correlated with MIB-1 labelling index, K i max provided the best correlation (Pearson coefficient, r = 0.68; p i mean (±SD) was significantly higher than in normal tissue (3.3 ± 1.7 x 10 -3 ml plasma /min/ml tissue versus 1.2 ± 0.7 x 10 -3 ml plasma /min/ml tissue ; p = 0.001). High-grade gliomas showed heterogeneous uptake with a mean K i of 7.7 ± 4 x 10 -3 ml plasma /min/ml tissue . A threshold K i mean of 1.8 x 10 -3 differentiates between normal tissue and tumour (sensitivity 84%, specificity 88%); however, the latter threshold underestimated the extent of tumour in half the cases. SUV closely agreed with K i measurements. Conclusion: FLT PET is a useful marker of cellular proliferation that correlates with regional variation in cellular proliferation; however, it is unable to identify the margin of gliomas
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)
Modelling of chromatic contrast for retrieval of wallpaper images
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...
Reconstructing building mass models from UAV images
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
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)
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
International Nuclear Information System (INIS)
He Bin; Du Yong; Segars, W. Paul; Wahl, Richard L.; Sgouros, George; Jacene, Heather; Frey, Eric C.
2009-01-01
Estimating organ residence times is an essential part of patient-specific dosimetry for radioimmunotherapy (RIT). Quantitative imaging methods for RIT are often evaluated using a single physical or simulated phantom but are intended to be applied clinically where there is variability in patient anatomy, biodistribution, and biokinetics. To provide a more relevant evaluation, the authors have thus developed a population of phantoms with realistic variations in these factors and applied it to the evaluation of quantitative imaging methods both to find the best method and to demonstrate the effects of these variations. Using whole body scans and SPECT/CT images, organ shapes and time-activity curves of 111In ibritumomab tiuxetan were measured in dosimetrically important organs in seven patients undergoing a high dose therapy regimen. Based on these measurements, we created a 3D NURBS-based cardiac-torso (NCAT)-based phantom population. SPECT and planar data at realistic count levels were then simulated using previously validated Monte Carlo simulation tools. The projections from the population were used to evaluate the accuracy and variation in accuracy of residence time estimation methods that used a time series of SPECT and planar scans. Quantitative SPECT (QSPECT) reconstruction methods were used that compensated for attenuation, scatter, and the collimator-detector response. Planar images were processed with a conventional (CPlanar) method that used geometric mean attenuation and triple-energy window scatter compensation and a quantitative planar (QPlanar) processing method that used model-based compensation for image degrading effects. Residence times were estimated from activity estimates made at each of five time points. The authors also evaluated hybrid methods that used CPlanar or QPlanar time-activity curves rescaled to the activity estimated from a single QSPECT image. The methods were evaluated in terms of mean relative error and standard deviation of the
International Nuclear Information System (INIS)
Tyler, Philippa; Datir, Abhijit; Saifuddin, Asif
2010-01-01
Magnetic resonance imaging (MRI) is now the modality of choice for the investigation of internal derangement of the knee. Technological advances, including the wider availability of stronger magnets and new sequences, allows improved visualisation of smaller structures. Normal variants must be recognised as such, so that both over-investigation and mis-diagnosis are avoided. This article reviews both the well-recognised and the less common ligamentous and musculotendinous anatomical variants within the knee and illustrates their imaging characteristics on MRI. (orig.)
Energy Technology Data Exchange (ETDEWEB)
Tyler, Philippa [The Royal National Orthopaedic Hospital NHS Trust, Department of Radiology, Stanmore, Middlesex (United Kingdom); Imperial College Healthcare NHS Trust, Department of Radiology, St Mary' s Hospital, London (United Kingdom); Datir, Abhijit [Jackson Memorial Hospital, Department of Radiology, Miami, FL (United States); Saifuddin, Asif [The Royal National Orthopaedic Hospital NHS Trust, Department of Radiology, Stanmore, Middlesex (United Kingdom); University College London, The Institute of Orthopaedics and Musculoskeletal Sciences, London (United Kingdom)
2010-12-15
Magnetic resonance imaging (MRI) is now the modality of choice for the investigation of internal derangement of the knee. Technological advances, including the wider availability of stronger magnets and new sequences, allows improved visualisation of smaller structures. Normal variants must be recognised as such, so that both over-investigation and mis-diagnosis are avoided. This article reviews both the well-recognised and the less common ligamentous and musculotendinous anatomical variants within the knee and illustrates their imaging characteristics on MRI. (orig.)
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
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.
Temporal variations of natural soil salinity in an arid environment using satellite images
Gutierrez, M.; Johnson, E.
2010-11-01
In many remote arid areas the scarce amount of conventional soil salinity data precludes detailed analyses of salinity variations for the purpose of predicting its impact on agricultural production. A tool that is an appropriate surrogate for on-ground testing in determining temporal variations of soil salinity is Landsat satellite data. In this study six Landsat scenes over El Cuervo, a closed basin adjacent to the middle Rio Conchos basin in northern Mexico, were used to show temporal variation of natural salts from 1986 to 2005. Natural salts were inferred from ground reference data and spectral responses. Transformations used were Tasseled Cap, Principal Components and several (band) ratios. Classification of each scene was performed from the development of Regions Of Interest derived from geochemical data collected by SGM, spectral responses derived from ENVI software, and a small amount of field data collected by the authors. The resultant land cover classes showed a relationship between climatic drought and areal coverage of natural salts. When little precipitation occurred three months prior to the capture of the Landsat scene, approximately 15%-20% of the area was classified as salt. This is compared to practically no classified salt in the wetter years of 1992 and 2005 Landsat scenes.
Modeling per capita state health expenditure variation: state-level characteristics matter.
Cuckler, Gigi; Sisko, Andrea
2013-01-01
In this paper, we describe the methods underlying the econometric model developed by the Office of the Actuary in the Centers for Medicare & Medicaid Services, to explain differences in per capita total personal health care spending by state, as described in Cuckler, et al. (2011). Additionally, we discuss many alternative model specifications to provide additional insights for valid interpretation of the model. We study per capita personal health care spending as measured by the State Health Expenditures, by State of Residence for 1991-2009, produced by the Centers for Medicare & Medicaid Services' Office of the Actuary. State-level demographic, health status, economic, and health economy characteristics were gathered from a variety of U.S. government sources, such as the Census Bureau, Bureau of Economic Analysis, the Centers for Disease Control, the American Hospital Association, and HealthLeaders-InterStudy. State-specific factors, such as income, health care capacity, and the share of elderly residents, are important factors in explaining the level of per capita personal health care spending variation among states over time. However, the slow-moving nature of health spending per capita and close relationships among state-level factors create inefficiencies in modeling this variation, likely resulting in incorrectly estimated standard errors. In addition, we find that both pooled and fixed effects models primarily capture cross-sectional variation rather than period-specific variation.
Modeling fish community dynamics in Florida Everglades: Role of temperature variation
Al-Rabai'ah, H. A.; Koh, H. L.; DeAngelis, Donald L.; Lee, Hooi-Ling
2002-01-01
Temperature variation is an important factor in Everglade wetlands ecology. A temperature fluctuation from 17°C to 32°C recorded in the Everglades may have significant impact on fish dynamics. The short life cycles of some of Everglade fishes has rendered this temperature variation to have even more impacts on the ecosystem. Fish population dynamic models, which do not explicitly consider seasonal oscillations in temperature, may fail to describe the details of such a population. Hence, a model for fish in freshwater marshes of the Florida Everglades that explicitly incorporates seasonal temperature variations is developed. The model's main objective is to assess the temporal pattern of fish population and densities through time subject to temperature variations. Fish population is divided into 2 functional groups (FGs) consisting of small fishes; each group is subdivided into 5-day age classes during their life cycles. Many governing sub-modules are set directly or indirectly to be temperature dependent. Growth, fecundity, prey availability, consumption rates and mortality are examples. Several mortality sub-modules are introduced in the model, of which starvation mortality is set to be proportional to the ratio of prey needed to prey available at that particular time step. As part of the calibration process, the model is run for 50 years to ensure that fish densities do not go to extinction, while the simulation period is about 8 years.
International Nuclear Information System (INIS)
Gutierrez-Alcaraz, G.; Tovar-Hernandez, Jose H.; Moreno-Goytia, Edgar L.
2009-01-01
Electricity spot markets generally operate on an hourly basis; under this condition GENCOs can closely observe their competitors' market behavior. For this purposes, a detailed dynamic model is one of the tools used by GENCOs to understand the behavioral variations of competitors over time. The required abilities to rapidly adjust one's own decision-making create a need for new learning procedures and models. Conjectural variations (CV) have been proposed as a learning approach. In this paper a model based on forward expectations (FE) is proposed as a learning approach, and through illustrative examples it is shown that the market equilibria found by the CV model are also obtained by the FE model. (author)
Bas-Relief Modeling from Normal Images with Intuitive Styles.
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.
International Nuclear Information System (INIS)
Nguyen, U; Kumaraswamy, N; Markey, M
2014-01-01
Purpose: To investigate variation in measurements of breast skin thickness obtained using different imaging modalities, including mammography, computed tomography (CT), ultrasound, and magnetic resonance imaging (MRI). Methods: Breast skin thicknesses as measured by mammography, CT, ultrasound, and MRI were compared. Mammographic measurements of skin thickness were obtained from published studies that utilized standard positioning (upright) and compression. CT measurements of skin thickness were obtained from a published study of a prototype breast CT scanner in which the women were in the prone position and the breast was uncompressed. Dermatological ultrasound exams of the breast skin were conducted at our institution, with the subjects in the upright position and the breast uncompressed. Breast skin thickness was calculated from breast MRI exams at our institution, with the patient in the prone position and the breast uncompressed. Results: T tests for independent samples demonstrated significant differences in the mean breast skin thickness as measured by different imaging modalities. Repeated measures ANOVA revealed significant differences in breast skin thickness across different quadrants of the breast for some modalities. Conclusion: The measurement of breast skin thickness is significantly different across different imaging modalities. Differences in the amount of compression and differences in patient positioning are possible reasons why measurements of breast skin thickness vary by modality
Temporal variation and scaling of parameters for a monthly hydrologic model
Deng, Chao; Liu, Pan; Wang, Dingbao; Wang, Weiguang
2018-03-01
The temporal variation of model parameters is affected by the catchment conditions and has a significant impact on hydrological simulation. This study aims to evaluate the seasonality and downscaling of model parameter across time scales based on monthly and mean annual water balance models with a common model framework. Two parameters of the monthly model, i.e., k and m, are assumed to be time-variant at different months. Based on the hydrological data set from 121 MOPEX catchments in the United States, we firstly analyzed the correlation between parameters (k and m) and catchment properties (NDVI and frequency of rainfall events, α). The results show that parameter k is positively correlated with NDVI or α, while the correlation is opposite for parameter m, indicating that precipitation and vegetation affect monthly water balance by controlling temporal variation of parameters k and m. The multiple linear regression is then used to fit the relationship between ε and the means and coefficient of variations of parameters k and m. Based on the empirical equation and the correlations between the time-variant parameters and NDVI, the mean annual parameter ε is downscaled to monthly k and m. The results show that it has lower NSEs than these from model with time-variant k and m being calibrated through SCE-UA, while for several study catchments, it has higher NSEs than that of the model with constant parameters. The proposed method is feasible and provides a useful tool for temporal scaling of model parameter.
Dynamics of epidemic spreading model with drug-resistant variation on scale-free networks
Wan, Chen; Li, Tao; Zhang, Wu; Dong, Jing
2018-03-01
Considering the influence of the virus' drug-resistant variation, a novel SIVRS (susceptible-infected-variant-recovered-susceptible) epidemic spreading model with variation characteristic on scale-free networks is proposed in this paper. By using the mean-field theory, the spreading dynamics of the model is analyzed in detail. Then, the basic reproductive number R0 and equilibriums are derived. Studies show that the existence of disease-free equilibrium is determined by the basic reproductive number R0. The relationships between the basic reproductive number R0, the variation characteristic and the topology of the underlying networks are studied in detail. Furthermore, our studies prove the global stability of the disease-free equilibrium, the permanence of epidemic and the global attractivity of endemic equilibrium. Numerical simulations are performed to confirm the analytical results.
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...
International Nuclear Information System (INIS)
Griffiths, Paul D.; Batty, Ruth; Connolly, Dan J.A.; Reeves, Michael J.
2009-01-01
The midline structures of the supra-tentorial brain are important landmarks for judging if the brain has formed correctly. In this article, we consider the normal appearances of the corpus callosum, septum pellucidum and fornix as shown on MR imaging in normal and near-normal states. (orig.)
Flux and color variations of the quadruply imaged quasar HE 0435-1223
DEFF Research Database (Denmark)
Ricci, D.; Poels, J.; Elyiv, A.
2011-01-01
Aims: We present VRi photometric observations of the quadruply imaged quasarHE0435-1223, carried out with the Danish 1.54 m telescope at the La Silla Observatory. Our aim was to monitor and study the magnitudes and colors of each lensed component as a function of time. Methods. We monitored...
Variation of the count-dependent Metz filter with imaging system modulation transfer function
International Nuclear Information System (INIS)
King, M.A.; Schwinger, R.B.; Penney, B.C.
1986-01-01
A systematic investigation was conducted of how a number of parameters which alter the system modulation transfer function (MTF) influence the count-dependent Metz filter. Since restoration filters are most effective at those frequencies where the object power spectrum dominates that of the noise, it was observed that parameters which significantly degrade the MTF at low spatial frequencies strongly influence the formation of the Metz filter. Thus the radionuclide imaged and the depth of the source in a scattering medium had the most influence. This is because they alter the relative amount of scattered radiation being imaged. For low-energy photon emitters, the collimator employed and the distance from the collimator were found to have less of an influence but still to be significant. These cause alterations in the MTF which are more gradual, and hence are most pronounced at mid to high spatial frequencies. As long as adequate spatial sampling is employed, the Metz filter was determined to be independent of the exact size of the sampling bin width, to a first approximation. For planar and single photon emission computed tomographic (SPECT) imaging, it is shown that two-dimensional filtering with the Metz filter optimized for the imaging conditions is able to deconvolve scatter and other causes of spatial resolution loss while diminishing noise, all in a balanced manner
Gender and Age Variations in the Self-Image of Jamaican Adolescents.
Smith, Delores E.; Muenchen, Robert A.
1995-01-01
Investigated the relationships among gender, age, and self-image of adolescents attending three secondary schools in Jamaica. Results revealed statistically significant effects for both gender and age. Gender significantly influenced morals, while age differences affected six other dimensions. Some results contradicted past research. (RJM)
A generalized logarithmic image processing model based on the gigavision sensor model.
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.
Directory of Open Access Journals (Sweden)
Nikakhlagh
2014-12-01
Full Text Available Background Sphenoid sinus is surrounded by many vital vascular and nervous structures. In more than 20% of patients with chronic sinusitis, involvement of sphenoid sinus has been observed. Besides, sphenoid sinus is an appropriate route to access anterior and middle cranial fossa in surgery. Therefore, it is important to have an adequate knowledge about the contents of sphenoid sinus and its proximity for nasal endoscopy, sinus surgeries and neurosurgeries. Objectives The aim of this study was to study sphenoid sinus proximity with carotid artery and the optic nerve using computerized tomographic imaging. Materials and Methods In this prospective study, computerized tomographic images of sphenoid sinus of patients referred to Imam Khomeini and Apadana hospitals were studied. The images were studied regarding any bulging, as well as not having a bone covering in sphenoid sinus regarding internal carotid artery and optic nerve. Furthermore, unilateralness or bilateralness of their relationships was studied. Results Among 468 coronal and axial CT scan images of sphenoid sinus, 365 (78% showed post-sellar pneumatization and 103 (22% pre-sellar pneumatization. Regarding existence of internal septa, 346 (74% cases showed multiple septation, and the remaining images were reported to have a single septum. According to the reports of CT scan images, the existence of bulging as a result of internal carotid artery and uncovered artery were 4.22% and 5.8% in the right sinus, 4.9% and 5.4% in the left sinus, and 4.34% and 4.6% in both sinuses, respectively. According to the reports of CT scan images, existence of bulging as a result of optic nerve and uncovered nerve were 5.7% and 4.3% in the right sinus, 6% and 5.4% in the left sinus, and 12% and 3.2% in both sinuses, respectively. Conclusions Due to variability of sphenoid sinus pneumatization and the separator blade of the two sinus cavities, careful attention is required during sinus surgery to avoid
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)
A generalized model for optimal transport of images including dissipation and density modulation
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.
Directory of Open Access Journals (Sweden)
Jamil Amanollahi
2012-06-01
Full Text Available Recently, period frequency and effect domain of the dust storms that enter Iran from Iraq have increased. In this study, in addition to detecting the creation zones of the dust storms, the effect of vegetation cover variation on their creation was investigated using remote sensing. Moderate resolution image Spectroradiometer (MODIS and Landsat Thematic Mapper (TM5 have been utilized to identify the primarily creation zones of the dust storms and to assess the vegetation cover variation, respectively. Vegetation cover variation was studied using Normalized Differences Vegetation Index (NDVI obtained from band 3 and band 4 of the Landsate satellite. The results showed that the surrounding area of the Euphrates in Syria, the desert in the vicinity of this river in Iraq, including the deserts of Alanbar Province, and the north deserts of Saudi Arabia are the primarily creation zones of the dust storms entering west and south west of Iran. The results of NDVI showed that excluding the deserts in the border of Syria and Iraq, the area with very weak vegetation cover have increased between 2.44% and 20.65% from 1991 to 2009. In the meanwhile, the retention pound surface areas in the south deserts of Syria as well as the deserts in its border with Iraq have decreased 6320 and 4397 hectares, respectively. As it can be concluded from the findings, one of the main environmental parameters initiating these dust storms is the decrease in the vegetation cover in their primarily creation zones.
DEFF Research Database (Denmark)
Andersen, Torben G.; Bollerslev, Tim; Huang, Xin
Building on realized variance and bi-power variation measures constructed from high-frequency financial prices, we propose a simple reduced form framework for effectively incorporating intraday data into the modeling of daily return volatility. We decompose the total daily return variability...
Variation in Measurements of Transtibial Stump Model Volume A Comparison of Five Methods
Bolt, A.; de Boer-Wilzing, V. G.; Geertzen, J. H. B.; Emmelot, C. H.; Baars, E. C. T.; Dijkstra, P. U.
Objective: To determine the right moment for fitting the first prosthesis, it is necessary to know when the volume of the stump has stabilized. The aim of this study is to analyze variation in measurements of transtibial stump model volumes using the water immersion method, the Design TT system, the
The variational 2D Boussinesq model for wave propagation over a shoal
Adytia, D.; van Groesen, Embrecht W.C.
2011-01-01
The Variational Boussinesq Model (VBM) for waves (Klopman et al. 2010) is based on the Hamiltonian structure of gravity surface waves. In its approximation, the fluid potential in the kinetic energy is approximated by the sum of its value at the free surface and a linear combination of vertical
Optimized Variational 1D Boussinesq Modelling for broad-band waves over flat bottom
Lakhturov, I.; Adytia, D.; van Groesen, Embrecht W.C.
The Variational Boussinesq Model (VBM) for waves above a layer of ideal fluid conserves mass, momentum, energy, and has decreased dimensionality compared to the full problem. It is derived from the Hamiltonian formulation via an approximation of the kinetic energy, and can provide approximate
Use of a variational principle for the study of supersymmetric models
International Nuclear Information System (INIS)
Krasnikov, N.V.
1985-01-01
A variational principle is used for study of the possibility of spontaneous symmetry breaking. It is shown that if supersymmetry in the generalized Wess-Zumino model is not broken at the classical level, taking account of quantum corrections also does not lead to symmetry breaking
Using of the variational principle for investigation of the supersymmetry models
International Nuclear Information System (INIS)
Krasnikov, N.V.
1985-01-01
The variational principle is used for investigation of possible spontaneous breaking of supersymmetry. It is shown that if supersymmetry in the generalized Wess-Zumino model is not broken on the classical level, it is neither broken as well with account for quantum corrections
Improved variational estimates for the mass gap in the 2-dimensional XY-model
International Nuclear Information System (INIS)
Patkos, A.; Hari Dass, N.D.
1982-07-01
The variational estimate obtained recently for the mass gap of the 2-dimensional XY-model is improved by extending the treatment to higher powers of the transfer operator. The relativistic dispersion relation for single particle states of low momentum is also verified. (Auth.)
A Model for Quantifying Sources of Variation in Test-day Milk Yield ...
African Journals Online (AJOL)
A cow's test-day milk yield is influenced by several systematic environmental effects, which have to be removed when estimating the genetic potential of an animal. The present study quantified the variation due to test date and month of test in test-day lactation yield records using full and reduced models. The data consisted ...
Laurinaviciene, Aida; Plancoulaine, Benoit; Baltrusaityte, Indra; Meskauskas, Raimundas; Besusparis, Justinas; Lesciute-Krilaviciene, Daiva; Raudeliunas, Darius; Iqbal, Yasir; Herlin, Paulette; Laurinavicius, Arvydas
2014-01-01
Digital immunohistochemistry (IHC) is one of the most promising applications brought by new generation image analysis (IA). While conventional IHC staining quality is monitored by semi-quantitative visual evaluation of tissue controls, IA may require more sensitive measurement. We designed an automated system to digitally monitor IHC multi-tissue controls, based on SQL-level integration of laboratory information system with image and statistical analysis tools. Consecutive sections of TMA containing 10 cores of breast cancer tissue were used as tissue controls in routine Ki67 IHC testing. Ventana slide label barcode ID was sent to the LIS to register the serial section sequence. The slides were stained and scanned (Aperio ScanScope XT), IA was performed by the Aperio/Leica Colocalization and Genie Classifier/Nuclear algorithms. SQL-based integration ensured automated statistical analysis of the IA data by the SAS Enterprise Guide project. Factor analysis and plot visualizations were performed to explore slide-to-slide variation of the Ki67 IHC staining results in the control tissue. Slide-to-slide intra-core IHC staining analysis revealed rather significant variation of the variables reflecting the sample size, while Brown and Blue Intensity were relatively stable. To further investigate this variation, the IA results from the 10 cores were aggregated to minimize tissue-related variance. Factor analysis revealed association between the variables reflecting the sample size detected by IA and Blue Intensity. Since the main feature to be extracted from the tissue controls was staining intensity, we further explored the variation of the intensity variables in the individual cores. MeanBrownBlue Intensity ((Brown+Blue)/2) and DiffBrownBlue Intensity (Brown-Blue) were introduced to better contrast the absolute intensity and the colour balance variation in each core; relevant factor scores were extracted. Finally, tissue-related factors of IHC staining variance were
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.
Tornado hazard model with the variation effects of tornado intensity along the path length
International Nuclear Information System (INIS)
Hirakuchi, Hiromaru; Nohara, Daisuke; Sugimoto, Soichiro; Eguchi, Yuzuru; Hattori, Yasuo
2015-01-01
Most of Japanese tornados have been reported near the coast line, where all of Japanese nuclear power plants are located. It is necessary for Japanese electric power companies to assess tornado risks on the plants according to a new regulation in 2013. The new regulatory guide exemplifies a tornado hazard model, which cannot consider the variation of tornado intensity along the path length and consequently produces conservative risk estimates. The guide also recommends the long narrow strip area along the coast line with the width of 5-10 km as a region of interest, although the model tends to estimate inadequate wind speeds due to the limit of application. The purpose of this study is to propose a new tornado hazard model which can be apply to the long narrow strip area. The new model can also consider the variation of tornado intensity along the path length and across the path width. (author)
Constraining spatial variations of the fine-structure constant in symmetron models
Directory of Open Access Journals (Sweden)
A.M.M. Pinho
2017-06-01
Full Text Available We introduce a methodology to test models with spatial variations of the fine-structure constant α, based on the calculation of the angular power spectrum of these measurements. This methodology enables comparisons of observations and theoretical models through their predictions on the statistics of the α variation. Here we apply it to the case of symmetron models. We find no indications of deviations from the standard behavior, with current data providing an upper limit to the strength of the symmetron coupling to gravity (logβ2<−0.9 when this is the only free parameter, and not able to constrain the model when also the symmetry breaking scale factor aSSB is free to vary.
SMOS images restoration from L1A data: A sparsity-based variational approach
Preciozzi, J.; Musé, Pablo; Almansa, A.; Durand, Sylvain; Khazaal, Ali; Rougé, B.
2014-01-01
International audience; Data degradation by radio frequency interferences (RFI) is one of the major challenges that SMOS and other interferometers radiometers missions have to face. Although a great number of the illegal emitters were turned off since the mission was launched, not all of the sources were completely removed. Moreover, the data obtained previously is already corrupted by these RFI. Thus, the recovery of brightness temperature from corrupted data by image restoration techniques ...
Gender and age variations in the self-image of Jamaican adolescents.
Smith, D E; Muenchen, R A
1995-01-01
The purpose of the study was to investigate the relationships among gender, age, and self-image of adolescents attending three secondary schools in Jamaica. The relatively few studies that have been done regarding self-perceptions of these youth are not only dated but have utilized a unidimensional conceptualization of the self. The Offer Self-Image Questionnaire which employs a multidimensional construct of the self was administered to a sample of 174 Jamaican adolescents ranging in age from 14 to 18 years (M = 15.90 years, SD = 1.21). Results revealed statistically significant effects for both gender and age. Gender was found to be significant on one self-image dimension: Morals, while age differences were evident on six dimensions: Social Relationships, Morals, Sexual Attitudes, Mastery of the External World, Vocational and Educational Goals, and Emotional Health. The results in some instances were contrary to those of past research. Discussion focused on cultural socialization and other factors affecting youth in Jamaican society.
A center-median filtering method for detection of temporal variation in coronal images
Directory of Open Access Journals (Sweden)
Plowman Joseph
2016-01-01
Full Text Available Events in the solar corona are often widely separated in their timescales, which can allow them to be identified when they would otherwise be confused with emission from other sources in the corona. Methods for cleanly separating such events based on their timescales are thus desirable for research in the field. This paper develops a technique for identifying time-varying signals in solar coronal image sequences which is based on a per-pixel running median filter and an understanding of photon-counting statistics. Example applications to “EIT waves” (named after EIT, the EUV Imaging Telescope on the Solar and Heliospheric Observatory and small-scale dynamics are shown, both using 193 Å data from the Atmospheric Imaging Assembly (AIA on the Solar Dynamics Observatory. The technique is found to discriminate EIT waves more cleanly than the running and base difference techniques most commonly used. It is also demonstrated that there is more signal in the data than is commonly appreciated, finding that the waves can be traced to the edge of the AIA field of view when the data are rebinned to increase the signal-to-noise ratio.
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
Variational approach for the N-state spin and gauge Potts model
International Nuclear Information System (INIS)
Masperi, L.; Omero, C.
1981-05-01
A hamiltonian variational treatment is applied both to the spin Potts model and to its gauge version for any number of states N and spatial dimensions d>=2. Regarding the former we reproduce correct critical coupling and latent heat for not too low N and d. For the latter, our approach turns the gauge theory into an equivalent d-dimensional classical spin model, which evaluated for d+1=4 gives results in agreement with 1/N expansions. (author)
Simple model of variation of the signature of a space-time metric
International Nuclear Information System (INIS)
Konstantinov, M.Yu.
2004-01-01
The problem on the changes in the space-time signature metrics is discussed. The simple model, wherein the space-time metrics signature is determined by the nonlinear scalar field, is proposed. It is shown that both classical and quantum description of changes in the metrics signature is possible within the frames of the considered model; the most characteristic peculiarities and variations of the classical and quantum descriptions are also briefly noted [ru
Sumiyana, Sumiyana; Baridwan, Zaki
2015-01-01
This study investigates association between accounting fundamentals and variations of stock prices using recursive simultaneous equation model. The accounting fundamentalsconsist of earnings yield, book value, profitability, growth opportunities and discount rate. The prior single relationships model has been investigated by Chen and Zhang (2007),Sumiyana (2011) and Sumiyana et al. (2010). They assume that all accounting fundamentals associate direct-linearly to the stock returns. This study ...
Sumiyana, Sumiyana; Baridwan, Zaki
2013-01-01
This study investigates association between accounting fundamentals and variations of stock prices using recursive simultaneous equation model. The accounting fundamentalsconsist of earnings yield, book value, profitability, growth opportunities and discount rate. The prior single relationships model has been investigated by Chen and Zhang (2007),Sumiyana (2011) and Sumiyana et al. (2010). They assume that all accounting fundamentals associate direct-linearly to the stock returns. This study ...
Li, Jianqi; Wang, Yi; Jiang, Yu; Xie, Haibin; Li, Gengying
2009-09-01
An open permanent magnet system with vertical B(0) field and without self-shielding can be quite susceptible to perturbations from external magnetic sources. B(0) variation in such a system located close to a subway station was measured to be greater than 0.7 microT by both MRI and a fluxgate magnetometer. This B(0) variation caused image artifacts. A navigator echo approach that monitored and compensated the view-to-view variation in magnetic resonance signal phase was developed to correct for image artifacts. Human brain imaging experiments using a multislice gradient-echo sequence demonstrated that the ghosting and blurring artifacts associated with B(0) variations were effectively removed using the navigator method.
Image-Based Geometric Modeling and Mesh Generation
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,...
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
International Nuclear Information System (INIS)
Bildhauer, Michael; Fuchs, Martin
2012-01-01
We discuss several variants of the TV-regularization model used in image recovery. The proposed alternatives are either of nearly linear growth or even of linear growth, but with some weak ellipticity properties. The main feature of the paper is the investigation of the analytic properties of the corresponding solutions.
Gallbladder shape extraction from ultrasound images using active contour models.
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.
Decision-case mix model for analyzing variation in cesarean rates.
Eldenburg, L; Waller, W S
2001-01-01
This article contributes a decision-case mix model for analyzing variation in c-section rates. Like recent contributions to the literature, the model systematically takes into account the effect of case mix. Going beyond past research, the model highlights differences in physician decision making in response to obstetric factors. Distinguishing the effects of physician decision making and case mix is important in understanding why c-section rates vary and in developing programs to effect change in physician behavior. The model was applied to a sample of deliveries at a hospital where physicians exhibited considerable variation in their c-section rates. Comparing groups with a low versus high rate, the authors' general conclusion is that the difference in physician decision tendencies (to perform a c-section), in response to specific obstetric factors, is at least as important as case mix in explaining variation in c-section rates. The exact effects of decision making versus case mix depend on how the model application defines the obstetric condition of interest and on the weighting of deliveries by their estimated "risk of Cesarean." The general conclusion is supported by an additional analysis that uses the model's elements to predict individual physicians' annual c-section rates.
Filtering adult image content with topic models
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 ...
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....
Assessing and quantifying inter-rater variation for dichotomous ratings using a Rasch model
DEFF Research Database (Denmark)
Petersen, Jørgen Holm; Larsen, Klaus; Kreiner, Svend
2010-01-01
quantifying the rater variation as a suitable measure of the variation of the rater odds ratios. An important example that will serve to motivate and illustrate the proposed model, is the study of Umbilical artery Doppler velocimetry used by obstetricians to assess the status of a foetus. The purpose...... of the assessment is to improve the foetus' chance of survival by choosing the optimal time of elective delivery. In the study, data related to 139 perinatal deaths were sent to 32 experts who were asked whether the use of Doppler velocimetry might have prevented each death....
Investigation of Spatial Variation of Sea States Offshore of Humboldt Bay CA Using a Hindcast Model.
Energy Technology Data Exchange (ETDEWEB)
Dallman, Ann Renee; Neary, Vincent Sinclair
2014-10-01
Spatial variability of sea states is an important consideration when performing wave resource assessments and wave resource characterization studies for wave energy converter (WEC) test sites and commercial WEC deployments. This report examines the spatial variation of sea states offshore of Humboldt Bay, CA, using the wave model SWAN . The effect of depth and shoaling on bulk wave parameters is well resolved using the model SWAN with a 200 m grid. At this site, the degree of spatial variation of these bulk wave parameters, with shoaling generally perpendicular to the depth contours, is found to depend on the season. The variation in wave height , for example, was higher in the summer due to the wind and wave sheltering from the protruding land on the coastline north of the model domain. Ho wever, the spatial variation within an area of a potential Tier 1 WEC test site at 45 m depth and 1 square nautical mile is almost negligible; at most about 0.1 m in both winter and summer. The six wave characterization parameters recommended by the IEC 6 2600 - 101 TS were compared at several points along a line perpendicular to shore from the WEC test site . As expected, these parameters varied based on depth , but showed very similar seasonal trends.
Rahpeyma, Sahar; Halldorsson, Benedikt; Hrafnkelsson, Birgir; Jonsson, Sigurjon
2018-01-01
Knowledge of the characteristics of earthquake ground motion is fundamental for earthquake hazard assessments. Over small distances, relative to the source–site distance, where uniform site conditions are expected, the ground motion variability is also expected to be insignificant. However, despite being located on what has been characterized as a uniform lava‐rock site condition, considerable peak ground acceleration (PGA) variations were observed on stations of a small‐aperture array (covering approximately 1 km2) of accelerographs in Southwest Iceland during the Ölfus earthquake of magnitude 6.3 on May 29, 2008 and its sequence of aftershocks. We propose a novel Bayesian hierarchical model for the PGA variations accounting separately for earthquake event effects, station effects, and event‐station effects. An efficient posterior inference scheme based on Markov chain Monte Carlo (MCMC) simulations is proposed for the new model. The variance of the station effect is certainly different from zero according to the posterior density, indicating that individual station effects are different from one another. The Bayesian hierarchical model thus captures the observed PGA variations and quantifies to what extent the source and recording sites contribute to the overall variation in ground motions over relatively small distances on the lava‐rock site condition.
Rahpeyma, Sahar
2018-04-17
Knowledge of the characteristics of earthquake ground motion is fundamental for earthquake hazard assessments. Over small distances, relative to the source–site distance, where uniform site conditions are expected, the ground motion variability is also expected to be insignificant. However, despite being located on what has been characterized as a uniform lava‐rock site condition, considerable peak ground acceleration (PGA) variations were observed on stations of a small‐aperture array (covering approximately 1 km2) of accelerographs in Southwest Iceland during the Ölfus earthquake of magnitude 6.3 on May 29, 2008 and its sequence of aftershocks. We propose a novel Bayesian hierarchical model for the PGA variations accounting separately for earthquake event effects, station effects, and event‐station effects. An efficient posterior inference scheme based on Markov chain Monte Carlo (MCMC) simulations is proposed for the new model. The variance of the station effect is certainly different from zero according to the posterior density, indicating that individual station effects are different from one another. The Bayesian hierarchical model thus captures the observed PGA variations and quantifies to what extent the source and recording sites contribute to the overall variation in ground motions over relatively small distances on the lava‐rock site condition.
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....
Optimality Bounds for a Variational Relaxation of the Image Partitioning Problem
Lellmann, Jan
2012-11-09
We consider a variational convex relaxation of a class of optimal partitioning and multiclass labeling problems, which has recently proven quite successful and can be seen as a continuous analogue of Linear Programming (LP) relaxation methods for finite-dimensional problems. While for the latter several optimality bounds are known, to our knowledge no such bounds exist in the infinite-dimensional setting. We provide such a bound by analyzing a probabilistic rounding method, showing that it is possible to obtain an integral solution of the original partitioning problem from a solution of the relaxed problem with an a priori upper bound on the objective. The approach has a natural interpretation as an approximate, multiclass variant of the celebrated coarea formula. © 2012 Springer Science+Business Media New York.
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.
Accelerated gradient methods for total-variation-based CT image reconstruction
DEFF Research Database (Denmark)
Jørgensen, Jakob Heide; Jensen, Tobias Lindstrøm; Hansen, Per Christian
2011-01-01
incorporates several heuristics from the optimization literature such as Barzilai-Borwein (BB) step size selection and nonmonotone line search. The latter uses a cleverly chosen sequence of auxiliary points to achieve a better convergence rate. The methods are memory efficient and equipped with a stopping...... reconstruction can in principle be found by any optimization method, but in practice the large scale of the systems arising in CT image reconstruction preclude the use of memory-demanding methods such as Newton’s method. The simple gradient method has much lower memory requirements, but exhibits slow convergence...
Superresolving Black Hole Images with Full-Closure Sparse Modeling
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.
Groenendijk, M.; Dolman, A. J.; Ammann, C.; Arneth, A.; Cescatti, A.; Dragoni, D.; Gash, J. H. C.; Gianelle, D.; Gioli, B.; Kiely, G.; Knohl, A.; Law, B. E.; Lund, M.; Marcolla, B.; van der Molen, M. K.; Montagnani, L.; Moors, E.; Richardson, A. D.; Roupsard, O.; Verbeeck, H.; Wohlfahrt, G.
2011-12-01
Global vegetation models require the photosynthetic parameters, maximum carboxylation capacity (Vcm), and quantum yield (α) to parameterize their plant functional types (PFTs). The purpose of this work is to determine how much the scaling of the parameters from leaf to ecosystem level through a seasonally varying leaf area index (LAI) explains the parameter variation within and between PFTs. Using Fluxnet data, we simulate a seasonally variable LAIF for a large range of sites, comparable to the LAIM derived from MODIS. There are discrepancies when LAIF reach zero levels and LAIM still provides a small positive value. We find that temperature is the most common constraint for LAIF in 55% of the simulations, while global radiation and vapor pressure deficit are the key constraints for 18% and 27% of the simulations, respectively, while large differences in this forcing still exist when looking at specific PFTs. Despite these differences, the annual photosynthesis simulations are comparable when using LAIF or LAIM (r2 = 0.89). We investigated further the seasonal variation of ecosystem-scale parameters derived with LAIF. Vcm has the largest seasonal variation. This holds for all vegetation types and climates. The parameter α is less variable. By including ecosystem-scale parameter seasonality we can explain a considerable part of the ecosystem-scale parameter variation between PFTs. The remaining unexplained leaf-scale PFT variation still needs further work, including elucidating the precise role of leaf and soil level nitrogen.
BOREAS TE-17 Production Efficiency Model Images
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,...
NEPR Bathymetry Model - NOAA TIFF Image
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:...
Infrared image background modeling based on improved Susan filtering
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.
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.
Variational data assimilation system with nesting model for high resolution ocean circulation
Energy Technology Data Exchange (ETDEWEB)
Ishikawa, Yoichi; Igarashi, Hiromichi; Hiyoshi, Yoshimasa; Sasaki, Yuji; Wakamatsu, Tsuyoshi; Awaji, Toshiyuki [Center for Earth Information Science and Technology, Japan Agency for Marine-Earth Science and Technology, 3173-25 Showa-machi, Kanazawa-Ku, Yokohama 236-0001 (Japan); In, Teiji [Japan Marine Science Foundation, 4-24, Minato-cho, Mutsu, Aomori, 035-0064 (Japan); Nakada, Satoshi [Graduate School of Maritime Science, Kobe University, 5-1-1, Fukae-minamimachi, Higashinada-Ku, Kobe, 658-0022 (Japan); Nishina, Kei, E-mail: ishikaway@jamstec.go.jp [Graduate School of Science, Kyoto University, Kitashirakawaoiwake-cho, Sakyo-Ku, Kyoto, 606-8502 (Japan)
2015-10-15
To obtain the high-resolution analysis fields for ocean circulation, a new incremental approach is developed using a four-dimensional variational data assimilation system with nesting models. The results show that there are substantial biases when using a classical method combined with data assimilation and downscaling, caused by different dynamics resulting from the different resolutions of the models used within the nesting models. However, a remarkable reduction in biases of the low-resolution model relative to the high-resolution model was observed using our new approach in narrow strait regions, such as the Tsushima and Tsugaru straits, where the difference in the dynamics represented by the high- and low-resolution models is substantial. In addition, error reductions are demonstrated in the downstream region of these narrow channels associated with the propagation of information through the model dynamics. (paper)
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.
International Nuclear Information System (INIS)
Bertagna, Luca; Veneziani, Alessandro
2014-01-01
Scientific computing has progressively become an important tool for research in cardiovascular diseases. The role of quantitative analyses based on numerical simulations has moved from ‘proofs of concept’ to patient-specific investigations, thanks to a strong integration between imaging and computational tools. However, beyond individual geometries, numerical models require the knowledge of parameters that are barely retrieved from measurements, especially in vivo. For this reason, recently cardiovascular mathematics considered data assimilation procedures for extracting the knowledge of patient-specific parameters from measures and images. In this paper, we consider specifically the quantification of vascular compliance, i.e. the parameter quantifying the tendency of arterial walls to deform under blood stress. Following up a previous paper, where a variational data assimilation procedure was proposed, based on solving an inverse fluid–structure interaction problem, here we consider model reduction techniques based on a proper orthogonal decomposition approach to accomplish the solution of the inverse problem in a computationally efficient way. (paper)
Energy Technology Data Exchange (ETDEWEB)
Jenkins-Smith, H.C. [New Mexico Univ., Albuquerque, NM (United States)
1994-12-01
This report analyzes data from surveys on the effects that images associated with nuclear power and waste (i.e., nuclear images) have on people`s preference to vacation in Nevada. The analysis was stimulated by a model of imagery and stigma which assumes that information about a potentially hazardous facility generates signals that elicit negative images about the place in which it is located. Individuals give these images negative values (valences) that lessen their desire to vacation, relocate, or retire in that place. The model has been used to argue that the proposed Yucca Mountain high-level nuclear waste repository could elicit images of nuclear waste that would stigmatize Nevada and thus impose substantial economic losses there. This report proposes a revised model that assumes that the acquisition and valuation of images depend on individuals` ideological and cultural predispositions and that the ways in which new images will affect their preferences and behavior partly depend on these predispositions. The report tests these hypotheses: (1) individuals with distinct cultural and ideological predispositions have different propensities for acquiring nuclear images, (2) these people attach different valences to these images, (3) the variations in these valences are important, and (4) the valences of the different categories of images within an individual`s image sets for a place correlate very well. The analysis largely confirms these hypotheses, indicating that the stigma model should be revised to (1) consider the relevant ideological and cultural predispositions of the people who will potentially acquire and attach value to the image, (2) specify the kinds of images that previously attracted people to the host state, and (3) consider interactions between the old and potential new images of the place. 37 refs., 18 figs., 17 tabs.
International Nuclear Information System (INIS)
Jenkins-Smith, H.C.
1994-12-01
This report analyzes data from surveys on the effects that images associated with nuclear power and waste (i.e., nuclear images) have on people's preference to vacation in Nevada. The analysis was stimulated by a model of imagery and stigma which assumes that information about a potentially hazardous facility generates signals that elicit negative images about the place in which it is located. Individuals give these images negative values (valences) that lessen their desire to vacation, relocate, or retire in that place. The model has been used to argue that the proposed Yucca Mountain high-level nuclear waste repository could elicit images of nuclear waste that would stigmatize Nevada and thus impose substantial economic losses there. This report proposes a revised model that assumes that the acquisition and valuation of images depend on individuals' ideological and cultural predispositions and that the ways in which new images will affect their preferences and behavior partly depend on these predispositions. The report tests these hypotheses: (1) individuals with distinct cultural and ideological predispositions have different propensities for acquiring nuclear images, (2) these people attach different valences to these images, (3) the variations in these valences are important, and (4) the valences of the different categories of images within an individual's image sets for a place correlate very well. The analysis largely confirms these hypotheses, indicating that the stigma model should be revised to (1) consider the relevant ideological and cultural predispositions of the people who will potentially acquire and attach value to the image, (2) specify the kinds of images that previously attracted people to the host state, and (3) consider interactions between the old and potential new images of the place. 37 refs., 18 figs., 17 tabs
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.
Institute of Scientific and Technical Information of China (English)
Sarp Adali
2012-01-01
Equations governing the vibrations and buckling of multilayered orthotropic graphene sheets can be expressed as a system of n partial differential equations where n refers to the number of sheets.This description is based on the continuum model of the graphene sheets which can also take the small scale effects into account by employing a nonlocal theory.In the present article a variational principle is derived for the nonlocal elastic theory of rectangular graphene sheets embedded in an elastic medium and undergoing transverse vibrations.Moreover the graphene sheets are subject to biaxial compression.Rayleigh quotients are obtained for the frequencies of freely vibrating graphene sheets and for the buckling load. The influence of small scale effects on the frequencies and the buckling load can be observed qualiatively from the expressions of the Rayleigh quotients.Elastic medium is modeled as a combination of Winkler and Pasternak foundations acting on the top and bottom layers of the mutilayered nano-structure.Natural boundary conditions of the problem are derived using the variational principle formulated in the study.It is observed that free boundaries lead to coupled boundary conditions due to nonlocal theory used in the continuum formulation while the local (classical) elasticity theory leads to uncoupled boundary conditions.The mathematical methods used in the study involve calculus of variations and the semi-inverse method for deriving the variational integrals.
Determination of bare soil and its seasonal variation using image analysis
International Nuclear Information System (INIS)
Pulido Fernandez, M.; Lavado Contador, J. F.; Schnabel, S.; Gomez Gutierrez, A.
2009-01-01
Bare soil is of outstanding interest as an indicator of land degradation because it is strongly related with water erosion, particularly in low-vegetated areas as those typical of the Mediterranean rangelands. In areas with high livestock densities, erosion can ultimately get to a partial or total soil loss, particularly at the beginning of the rainy season, when the surface cover is reduce after the dry summer period. Therefore, it is necessary to develop accurate methods allowing the quantification of soil exposed areas and their temporal dynamics. The main goal of this work is the determination of bare soil surface using aerial orthophotomaps and the analysis of the changes resulting from the analysis and classification of images corresponding to two contrasting seasons (summer and spring). (Author) 6 refs.
Improved total variation-based CT image reconstruction applied to clinical data
Energy Technology Data Exchange (ETDEWEB)
Ritschl, Ludwig; Bergner, Frank; Kachelriess, Marc [Institute of Medical Physics (IMP), University of Erlangen-Nuernberg, Henkestr. 91, 91052 Erlangen (Germany); Fleischmann, Christof, E-mail: ludwig.ritschl@imp.uni-erlangen.de [Ziehm Imaging GmbH, Donaustrasse 31, 90451 Nuernberg (Germany)
2011-03-21
In computed tomography there are different situations where reconstruction has to be performed with limited raw data. In the past few years it has been shown that algorithms which are based on compressed sensing theory are able to handle incomplete datasets quite well. As a cost function these algorithms use the l{sub 1}-norm of the image after it has been transformed by a sparsifying transformation. This yields to an inequality-constrained convex optimization problem. Due to the large size of the optimization problem some heuristic optimization algorithms have been proposed in the past few years. The most popular way is optimizing the raw data and sparsity cost functions separately in an alternating manner. In this paper we will follow this strategy and present a new method to adapt these optimization steps. Compared to existing methods which perform similarly, the proposed method needs no a priori knowledge about the raw data consistency. It is ensured that the algorithm converges to the lowest possible value of the raw data cost function, while holding the sparsity constraint at a low value. This is achieved by transferring the step-size determination of both optimization procedures into the raw data domain, where they are adapted to each other. To evaluate the algorithm, we process measured clinical datasets. To cover a wide field of possible applications, we focus on the problems of angular undersampling, data lost due to metal implants, limited view angle tomography and interior tomography. In all cases the presented method reaches convergence within less than 25 iteration steps, while using a constant set of algorithm control parameters. The image artifacts caused by incomplete raw data are mostly removed without introducing new effects like staircasing. All scenarios are compared to an existing implementation of the ASD-POCS algorithm, which realizes the step-size adaption in a different way. Additional prior information as proposed by the PICCS algorithm
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
Fast Algorithms for Fitting Active Appearance Models to Unconstrained Images
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‿
Projection model for flame chemiluminescence tomography based on lens imaging
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.
Minimizing EIT image artefacts from mesh variability in finite element models.
Adler, Andy; Lionheart, William R B
2011-07-01
Electrical impedance tomography (EIT) solves an inverse problem to estimate the conductivity distribution within a body from electrical simulation and measurements at the body surface, where the inverse problem is based on a solution of Laplace's equation in the body. Most commonly, a finite element model (FEM) is used, largely because of its ability to describe irregular body shapes. In this paper, we show that simulated variations in the positions of internal nodes within a FEM can result in serious image artefacts in the reconstructed images. Such variations occur when designing FEM meshes to conform to conductivity targets, but the effects may also be seen in other applications of absolute and difference EIT. We explore the hypothesis that these artefacts result from changes in the projection of the anisotropic conductivity tensor onto the FEM system matrix, which introduces anisotropic components into the simulated voltages, which cannot be reconstructed onto an isotropic image, and appear as artefacts. The magnitude of the anisotropic effect is analysed for a small regular FEM, and shown to be proportional to the relative node movement as a fraction of element size. In order to address this problem, we show that it is possible to incorporate a FEM node movement component into the formulation of the inverse problem. These results suggest that it is important to consider artefacts due to FEM mesh geometry in EIT image reconstruction.
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.
Generative Topic Modeling in Image Data Mining and Bioinformatics Studies
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…
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
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, ...
On use of image quality metrics for perceptual blur modeling: image/video compression case
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.
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.
International Nuclear Information System (INIS)
Yee, Don; Parliament, Matthew; Rathee, Satyapal; Ghosh, Sunita; Ko, Lawrence; Murray, Brad
2010-01-01
Purpose: To quantify daily bladder size and position variations during bladder cancer radiotherapy. Methods and Materials: Ten bladder cancer patients underwent daily cone beam CT (CBCT) imaging of the bladder during radiotherapy. Bladder and planning target volumes (bladder/PTV) from CBCT and planning CT scans were compared with respect to bladder center-of-mass shifts in the x (lateral), y (anterior-posterior), and z (superior-inferior) coordinates, bladder/PTV size, bladder/PTV margin positions, overlapping areas, and mutually exclusive regions. Results: A total of 262 CBCT images were obtained from 10 bladder cancer patients. Bladder center of mass shifted most in the y coordinate (mean, -0.32 cm). The anterior bladder wall shifted the most (mean, -0.58 cm). Mean ratios of CBCT-derived bladder and PTV volumes to planning CT-derived counterparts were 0.83 and 0.88. The mean CBCT-derived bladder volume (± standard deviation [SD]) outside the planning CT counterpart was 29.24 cm 3 (SD, 29.71 cm 3 ). The mean planning CT-derived bladder volume outside the CBCT counterpart was 47.74 cm 3 (SD, 21.64 cm 3 ). The mean CBCT PTV outside the planning CT-derived PTV was 47.35 cm 3 (SD, 36.51 cm 3 ). The mean planning CT-derived PTV outside the CBCT-derived PTV was 93.16 cm 3 (SD, 50.21). The mean CBCT-derived bladder volume outside the planning PTV was 2.41 cm 3 (SD, 3.97 cm 3 ). CBCT bladder/ PTV volumes significantly differed from planning CT counterparts (p = 0.047). Conclusions: Significant variations in bladder and PTV volume and position occurred in patients in this trial.
Model-based diagnosis of large diesel engines based on angular speed variations of the crankshaft
Desbazeille, M.; Randall, R. B.; Guillet, F.; El Badaoui, M.; Hoisnard, C.
2010-07-01
This work aims at monitoring large diesel engines by analyzing the crankshaft angular speed variations. It focuses on a powerful 20-cylinder diesel engine with crankshaft natural frequencies within the operating speed range. First, the angular speed variations are modeled at the crankshaft free end. This includes modeling both the crankshaft dynamical behavior and the excitation torques. As the engine is very large, the first crankshaft torsional modes are in the low frequency range. A model with the assumption of a flexible crankshaft is required. The excitation torques depend on the in-cylinder pressure curve. The latter is modeled with a phenomenological model. Mechanical and combustion parameters of the model are optimized with the help of actual data. Then, an automated diagnosis based on an artificially intelligent system is proposed. Neural networks are used for pattern recognition of the angular speed waveforms in normal and faulty conditions. Reference patterns required in the training phase are computed with the model, calibrated using a small number of actual measurements. Promising results are obtained. An experimental fuel leakage fault is successfully diagnosed, including detection and localization of the faulty cylinder, as well as the approximation of the fault severity.
Variational Wavefunction for the Periodic Anderson Model with Onsite Correlation Factors
Kubo, Katsunori; Onishi, Hiroaki
2017-01-01
We propose a variational wavefunction containing parameters to tune the probabilities of all the possible onsite configurations for the periodic Anderson model. We call it the full onsite-correlation wavefunction (FOWF). This is a simple extension of the Gutzwiller wavefunction (GWF), in which one parameter is included to tune the double occupancy of the f electrons at the same site. We compare the energy of the GWF and the FOWF evaluated by the variational Monte Carlo method and that obtained with the density-matrix renormalization group method. We find that the energy is considerably improved in the FOWF. On the other hand, the physical quantities do not change significantly between these two wavefunctions as long as they describe the same phase, such as the paramagnetic phase. From these results, we not only demonstrate the improvement by the FOWF, but we also gain insights on the applicability and limitation of the GWF to the periodic Anderson model.
Reducing the variation in animal models by standardizing the gut microbiota
DEFF Research Database (Denmark)
Ellekilde, Merete; Hufeldt, Majbritt Ravn; Hansen, Camilla Hartmann Friis
2011-01-01
, a large proportion of laboratory animals are used to study such diseases, but inter-individual variation in these animal models leads to the need for larger group sizes to reach statistical significance and adequate power. By standardizing the microbial and immunological status of laboratory animals we...... mice changed the glucose tolerance without affecting weight or mucosal immunity. Further investigations concerning the mechanisms of how GM influences disease development is necessary, but based on these results it seems reasonable to assume that by manipulating the GM we may produce animal models...... may therefore be able to produce animals with a more standardized response and less variation. This would lead to more precise results and a reduced number of animals needed for statistical significance. Denaturing gradient gel electrophoresis (DGGE) - a culture independent approach separating PCR...
Variational wavefunction for the periodic anderson model with onsite correlation factors
International Nuclear Information System (INIS)
Kubo, Katsunori; Onishi, Hiroaki
2017-01-01
We propose a variational wavefunction containing parameters to tune the probabilities of all the possible onsite configurations for the periodic Anderson model. We call it the full onsite-correlation wavefunction (FOWF). This is a simple extension of the Gutzwiller wavefunction (GWF), in which one parameter is included to tune the double occupancy of the f electrons at the same site. We compare the energy of the GWF and the FOWF evaluated by the variational Monte Carlo method and that obtained with the density-matrix renormalization group method. We find that the energy is considerably improved in the FOWF. On the other hand, the physical quantities do not change significantly between these two wavefunctions as long as they describe the same phase, such as the paramagnetic phase. From these results, we not only demonstrate the improvement by the FOWF, but we also gain insights on the applicability and limitation of the GWF to the periodic Anderson model. (author)
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
Forward modeling of gravity data using geostatistically generated subsurface density variations
Phelps, Geoffrey
2016-01-01
Using geostatistical models of density variations in the subsurface, constrained by geologic data, forward models of gravity anomalies can be generated by discretizing the subsurface and calculating the cumulative effect of each cell (pixel). The results of such stochastically generated forward gravity anomalies can be compared with the observed gravity anomalies to find density models that match the observed data. These models have an advantage over forward gravity anomalies generated using polygonal bodies of homogeneous density because generating numerous realizations explores a larger region of the solution space. The stochastic modeling can be thought of as dividing the forward model into two components: that due to the shape of each geologic unit and that due to the heterogeneous distribution of density within each geologic unit. The modeling demonstrates that the internally heterogeneous distribution of density within each geologic unit can contribute significantly to the resulting calculated forward gravity anomaly. Furthermore, the stochastic models match observed statistical properties of geologic units, the solution space is more broadly explored by producing a suite of successful models, and the likelihood of a particular conceptual geologic model can be compared. The Vaca Fault near Travis Air Force Base, California, can be successfully modeled as a normal or strike-slip fault, with the normal fault model being slightly more probable. It can also be modeled as a reverse fault, although this structural geologic configuration is highly unlikely given the realizations we explored.
Gao, Ying; Chen, Yong; Ma, Dan; Jiang, Yun; Herrmann, Kelsey A.; Vincent, Jason A.; Dell, Katherine M.; Drumm, Mitchell L.; Brady-Kalnay, Susann M.; Griswold, Mark A.; Flask, Chris A.; Lu, Lan
2015-01-01
High field, preclinical magnetic resonance imaging (MRI) scanners are now commonly used to quantitatively assess disease status and efficacy of novel therapies in a wide variety of rodent models. Unfortunately, conventional MRI methods are highly susceptible to respiratory and cardiac motion artifacts resulting in potentially inaccurate and misleading data. We have developed an initial preclinical, 7.0 T MRI implementation of the highly novel Magnetic Resonance Fingerprinting (MRF) methodology that has been previously described for clinical imaging applications. The MRF technology combines a priori variation in the MRI acquisition parameters with dictionary-based matching of acquired signal evolution profiles to simultaneously generate quantitative maps of T1 and T2 relaxation times and proton density. This preclinical MRF acquisition was constructed from a Fast Imaging with Steady-state Free Precession (FISP) MRI pulse sequence to acquire 600 MRF images with both evolving T1 and T2 weighting in approximately 30 minutes. This initial high field preclinical MRF investigation demonstrated reproducible and differentiated estimates of in vitro phantoms with different relaxation times. In vivo preclinical MRF results in mouse kidneys and brain tumor models demonstrated an inherent resistance to respiratory motion artifacts as well as sensitivity to known pathology. These results suggest that MRF methodology may offer the opportunity for quantification of numerous MRI parameters for a wide variety of preclinical imaging applications. PMID:25639694
D'Ambra, Pasqua; Tartaglione, Gaetano
2015-04-01
Image segmentation addresses the problem to partition a given image into its constituent objects and then to identify the boundaries of the objects. This problem can be formulated in terms of a variational model aimed to find optimal approximations of a bounded function by piecewise-smooth functions, minimizing a given functional. The corresponding Euler-Lagrange equations are a set of two coupled elliptic partial differential equations with varying coefficients. Numerical solution of the above system often relies on alternating minimization techniques involving descent methods coupled with explicit or semi-implicit finite-difference discretization schemes, which are slowly convergent and poorly scalable with respect to image size. In this work we focus on generalized relaxation methods also coupled with multigrid linear solvers, when a finite-difference discretization is applied to the Euler-Lagrange equations of Ambrosio-Tortorelli model. We show that non-linear Gauss-Seidel, accelerated by inner linear iterations, is an effective method for large-scale image analysis as those arising from high-throughput screening platforms for stem cells targeted differentiation, where one of the main goal is segmentation of thousand of images to analyze cell colonies morphology.
Solution of Ambrosio-Tortorelli model for image segmentation by generalized relaxation method
D'Ambra, Pasqua; Tartaglione, Gaetano
2015-03-01
Image segmentation addresses the problem to partition a given image into its constituent objects and then to identify the boundaries of the objects. This problem can be formulated in terms of a variational model aimed to find optimal approximations of a bounded function by piecewise-smooth functions, minimizing a given functional. The corresponding Euler-Lagrange equations are a set of two coupled elliptic partial differential equations with varying coefficients. Numerical solution of the above system often relies on alternating minimization techniques involving descent methods coupled with explicit or semi-implicit finite-difference discretization schemes, which are slowly convergent and poorly scalable with respect to image size. In this work we focus on generalized relaxation methods also coupled with multigrid linear solvers, when a finite-difference discretization is applied to the Euler-Lagrange equations of Ambrosio-Tortorelli model. We show that non-linear Gauss-Seidel, accelerated by inner linear iterations, is an effective method for large-scale image analysis as those arising from high-throughput screening platforms for stem cells targeted differentiation, where one of the main goal is segmentation of thousand of images to analyze cell colonies morphology.
Assessing the performance of variational methods for mixed logistic regression models
Czech Academy of Sciences Publication Activity Database
Rijmen, F.; Vomlel, Jiří
2008-01-01
Roč. 78, č. 8 (2008), s. 765-779 ISSN 0094-9655 R&D Projects: GA MŠk 1M0572 Grant - others:GA MŠk(CZ) 2C06019 Institutional research plan: CEZ:AV0Z10750506 Keywords : Mixed models * Logistic regression * Variational methods * Lower bound approximation Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 0.353, year: 2008
Modeling the National Ignition Facility neutron imaging system.
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.
International Nuclear Information System (INIS)
Irwan, Roy; Edens, Mireille A.; Sijens, Paul E.
2008-01-01
A recently published Dixon-based MRI method for quantifying liver fat content using dual-echo breath-hold gradient echo imaging was validated by phantom experiments and compared with results of biopsy in two patients (Radiology 2005;237:1048-1055). We applied this method in ten healthy volunteers and compared the outcomes with the results of MR spectroscopy (MRS), the gold standard in quantifying liver fat content. Novel was the use of spectroscopic imaging yielding the variations in fat content across the liver rather than a single value obtained by single voxel MRS. Compared with the results of MRS, liver fat content according to MRI was too high in nine subjects (range 3.3-10.7% vs. 0.9-7.7%) and correct in one (21.1 vs. 21.3%). Furthermore, in one of the ten subjects the MRI fat content according to the Dixon-based MRI method was incorrect due to a (100-x) versus x percent lipid content mix-up. The second problem was fixed by a minor adjustment of the MRI algorithm. Despite systematic overestimation of liver fat contents by MRI, Spearman's correlation between the adjusted MRI liver fat contents with MRS was high (r = 0.927, P < 0.001). Even after correction of the algorithm, the problem remaining with the Dixon-based MRI method for the assessment of liver fat content,is that, at the lower end range, liver fat content is systematically overestimated by 4%. (orig.)
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)
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
Exploring gravitational lensing model variations in the Frontier Fields galaxy clusters
Harris James, Nicholas John; Raney, Catie; Brennan, Sean; Keeton, Charles
2018-01-01
Multiple groups have been working on modeling the mass distributions of the six lensing galaxy clusters in the Hubble Space Telescope Frontier Fields data set. The magnification maps produced from these mass models will be important for the future study of the lensed background galaxies, but there exists significant variation in the different groups’ models and magnification maps. We explore the use of two-dimensional histograms as a tool for visualizing these magnification map variations. Using a number of simple, one- or two-halo singular isothermal sphere models, we explore the features that are produced in 2D histogram model comparisons when parameters such as halo mass, ellipticity, and location are allowed to vary. Our analysis demonstrates the potential of 2D histograms as a means of observing the full range of differences between the Frontier Fields groups’ models.This work has been supported by funding from National Science Foundation grants PHY-1560077 and AST-1211385, and from the Space Telescope Science Institute.
Dickinson, Alex; White, N. J.; Caulfield, C. P.
2017-12-01
Bright reflections are observed within the upper 1,000 m of the water column along a seismic reflection profile that traverses the northern margin of the Gulf of Mexico. Independent hydrographic calibration demonstrates that these reflections are primarily caused by temperature changes associated with different water masses that are entrained into the Gulf along the Loop Current. The internal wave field is analyzed by automatically tracking 1,171 reflections, each of which is greater than 2 km in length. Power spectra of the horizontal gradient of isopycnal displacement, ϕξx, are calculated from these tracked reflections. At low horizontal wave numbers (kxcpm), ϕξx∝kx-0.2±0.6, in agreement with hydrographic observations of the internal wave field. The turbulent spectral subrange is rarely observed. Diapycnal diffusivity, K, is estimated from the observed internal wave spectral subrange of each tracked reflection using a fine-scale parametrization of turbulent mixing. Calculated values of K vary between 10-8 and 10-4 m2 s-1 with a mean value of K˜4×10-6 m2 s-1. The spatial distribution of turbulent mixing shows that K˜10-7 m2 s-1 away from the shelf edge in the upper 300 m where stratification is strong. Mixing is enhanced by up to 4 orders of magnitude adjacent to the shoaling bathymetry of the continental slope. This overall pattern matches that determined by analyzing nearby suites of CTD casts. However, the range of values recovered by spectral analysis of the seismic image is greater as a consequence of significantly better horizontal resolution.
Suarez, Wilson; Cerna, Marcos; Ordoñez, Julio; Frey, Holger; Giráldez, Claudia; Huggel, Christian
2013-04-01
The Urubamba and Vilcabamba mountain ranges are two geological structures belonging to the Andes in the southern part of Peru, which is located in the tropical region. These mountain ranges are especially located within the transition area between the Amazon region (altitudes close to 1'000 m a.s.l.) and the Andes. These mountains, with a maximum height of 6'280 m a.s.l. (Salkantay Snow Peak in the Vilcabamba range), are characterized by glaciers mainly higher than 5000 m a.s.l. Here we present a study on the evolution of the ice cover based on "Landsat 5" images from 1991 and 2011 is presented in this paper. These data are freely available from the USGS in a georeferenced format and cover a time span of more than 25 years. The glacier mapping is based on the Normalized Difference Snow Index (NDSI). In 1991 the Vilcabamba mountain range had 221 km2 of glacier cover, being reduced to 116.4 km2 in 2011, which represents a loss of 48%. In the Urubamba mountain range, the total glacier area was 64.9 km2 in 1991 and 29.4 km2 in 2011, representing a loss of 54.7%. It means that the glacier area was halved during the past two decades although precipitation patterns show an increase in recent years (the wet season lasts from September to April with precipitation peaks in February and March). Glacier changes in these two tropical mountain ranges also impact from an economic point of view due to small local farming common in this region (use of water from the melting glacier). Furthermore, potential glacier related hazards can pose a threat to people and infrastructure in the valleys below these glaciers, where the access routes to Machu Picchu Inca City, Peru's main tourist destination, are located too.
Graham, Michael M; Badawi, Ramsey D; Wahl, Richard L
2011-02-01
In 2005, 8 Imaging Response Assessment Teams (IRATs) were funded by the National Cancer Institute (NCI) as supplemental grants to existing NCI Cancer Centers. After discussion among the IRATs regarding the need for increased standardization of clinical and research PET/CT methodology, it became apparent that data acquisition and processing approaches differ considerably among centers. To determine the variability in detail, a survey of IRAT sites and IRAT affiliates was performed. A 34-question instrument evaluating patient preparation, scanner type, performance approach, display, and analysis was developed. Fifteen institutions, including the 8 original IRATs and 7 institutions that had developed affiliate IRATs, were surveyed. The major areas of variation were (18)F-FDG dose (259-740 MBq [7-20 mCi]) uptake time (45-90 min), sedation (never to frequently), handling of diabetic patients, imaging time (2-7 min/bed position), performance of diagnostic CT scans as a part of PET/CT, type of acquisition (2-dimensional vs. 3-dimensional), CT technique, duration of fasting (4 or 6 h), and (varying widely) acquisition, processing, display, and PACS software--with 4 sites stating that poor-quality images appear on PACS. There is considerable variability in the way PET/CT scans are performed at academic institutions that are part of the IRAT network. This variability likely makes it difficult to quantitatively compare studies performed at different centers. These data suggest that additional standardization in methodology will be required so that PET/CT studies, especially those performed quantitatively, are more comparable across sites.
Penenko, Alexey; Penenko, Vladimir; Tsvetova, Elena; Antokhin, Pavel
2016-04-01
The work is devoted to data assimilation algorithm for atmospheric chemistry transport and transformation models. In the work a control function is introduced into the model source term (emission rate) to provide flexibility to adjust to data. This function is evaluated as the constrained minimum of the target functional combining a control function norm with a norm of the misfit between measured data and its model-simulated analog. Transport and transformation processes model is acting as a constraint. The constrained minimization problem is solved with Euler-Lagrange variational principle [1] which allows reducing it to a system of direct, adjoint and control function estimate relations. This provides a physically-plausible structure of the resulting analysis without model error covariance matrices that are sought within conventional approaches to data assimilation. High dimensionality of the atmospheric chemistry models and a real-time mode of operation demand for computational efficiency of the data assimilation algorithms. Computational issues with complicated models can be solved by using a splitting technique. Within this approach a complex model is split to a set of relatively independent simpler models equipped with a coupling procedure. In a fine-grained approach data assimilation is carried out quasi-independently on the separate splitting stages with shared measurement data [2]. In integrated schemes data assimilation is carried out with respect to the split model as a whole. We compare the two approaches both theoretically and numerically. Data assimilation on the transport stage is carried out with a direct algorithm without iterations. Different algorithms to assimilate data on nonlinear transformation stage are compared. In the work we compare data assimilation results for both artificial and real measurement data. With these data we study the impact of transformation processes and data assimilation to the performance of the modeling system [3]. The
Research into the effects of seawater velocity variation on migration imaging in deep-water geology
Directory of Open Access Journals (Sweden)
Hui Sun
2016-07-01
Full Text Available This paper aims at the problem that in deep water the migration quality is poor, and starts with the influence that velocity model accuracy has on migration, studying influence that variable seawater velocity makes on migration effect. At first, variable seawater velocity influenced by temperature, pressure and salinity is defined to replace the true seawater velocity. Then variable seawater velocity’s influence on interface migration location, layer sickness and migration energy focusing degree are analyzed in theory. And finally a deep water layered medium model containing variable seawater velocity, a syncline wedge shape model and a complex seafloor velocity model are constructed. By changing the seawater velocity of each model and comparing migration results of constant seawater-velocity model and variable seawater-velocity model, we can draw the conclusion: Under the condition of deep water, variable seawater-velocity’s impact on the quality of seismic migration is significant, which not only can change the location of geologic body migration result, but also can influence the resolution of geologic interface in the migration section and maybe can cause migration illusion. Investigación de los efectos de la variación en la velocidad del agua marina sobre las imágenes de migración en la geología de aguas profundas Resumen Este artículo se enfoca en el problema de la baja calidad de la migración en aguas profundas. Se analiza la influencia que tiene el modelo de precisión de velocidad en la migración y se estudia el impacto que la variación de velocidad del agua marina tiene en el efecto de movimiento. En primera instancia, se define la variación de la velocidad del agua marina afectada por la temperatura, la presión y la salinidad para reemplazar la velocidad del agua marina actual. Luego se analiza la teoría de la influencia de la velocidad del agua marina sobre la interfaz de la ubicación de migración, el grosor de
Eibern, Hendrik; Schmidt, Hauke
1999-08-01
The inverse problem of data assimilation of tropospheric trace gas observations into an Eulerian chemistry transport model has been solved by the four-dimensional variational technique including chemical reactions, transport, and diffusion. The University of Cologne European Air Pollution Dispersion Chemistry Transport Model 2 with the Regional Acid Deposition Model 2 gas phase mechanism is taken as the basis for developing a full four-dimensional variational data assimilation package, on the basis of the adjoint model version, which includes the adjoint operators of horizontal and vertical advection, implicit vertical diffusion, and the adjoint gas phase mechanism. To assess the potential and limitations of the technique without degrading the impact of nonperfect meteorological analyses and statistically not established error covariance estimates, artificial meteorological data and observations are used. The results are presented on the basis of a suite of experiments, where reduced records of artificial "observations" are provided to the assimilation procedure, while other "data" is retained for performance control of the analysis. The paper demonstrates that the four-dimensional variational technique is applicable for a comprehensive chemistry transport model in terms of computational and storage requirements on advanced parallel platforms. It is further shown that observed species can generally be analyzed, even if the "measurements" have unbiased random errors. More challenging experiments are presented, aiming to tax the skill of the method (1) by restricting available observations mostly to surface ozone observations for a limited assimilation interval of 6 hours and (2) by starting with poorly chosen first guess values. In this first such application to a three-dimensional chemistry transport model, success was also achieved in analyzing not only observed but also chemically closely related unobserved constituents.
Image-based Modeling of PSF Deformation with Application to Limited Angle PET Data
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
Vp-Vs relationship and amplitude variation with offset modelling of glauconitic greensand
DEFF Research Database (Denmark)
Hossain, Zakir; Mukerji, Tapan; Fabricius, Ida Lykke
2012-01-01
The relationship between Vp and Vs may be used to predict Vs where only Vp is known. Vp/Vs is also used to identify pore fluids from seismic data and amplitude variation with offset analysis. Theoretical, physical, as well as statistical empirical Vp-Vs relationships have been proposed...... modelling works well for greensand shear-wave velocity prediction. We model the seismic response of glauconitic greensand by using laboratory data from the Nini field. Our studies here reveal that brine-saturated glauconitic greensand can have a similar seismic response to that from oil-saturated quartzitic...
Wilkinson, Sarah; Ogée, Jérôme; Domec, Jean-Christophe; Rayment, Mark; Wingate, Lisa
2015-03-01
Process-based models that link seasonally varying environmental signals to morphological features within tree rings are essential tools to predict tree growth response and commercially important wood quality traits under future climate scenarios. This study evaluated model portrayal of radial growth and wood anatomy observations within a mature maritime pine (Pinus pinaster (L.) Aït.) stand exposed to seasonal droughts. Intra-annual variations in tracheid anatomy and wood density were identified through image analysis and X-ray densitometry on stem cores covering the growth period 1999-2010. A cambial growth model was integrated with modelled plant water status and sugar availability from the soil-plant-atmosphere transfer model MuSICA to generate estimates of cell number, cell volume, cell mass and wood density on a weekly time step. The model successfully predicted inter-annual variations in cell number, ring width and maximum wood density. The model was also able to predict the occurrence of special anatomical features such as intra-annual density fluctuations (IADFs) in growth rings. Since cell wall thickness remained surprisingly constant within and between growth rings, variations in wood density were primarily the result of variations in lumen diameter, both in the model and anatomical data. In the model, changes in plant water status were identified as the main driver of the IADFs through a direct effect on cell volume. The anatomy data also revealed that a trade-off existed between hydraulic safety and hydraulic efficiency. Although a simplified description of cambial physiology is presented, this integrated modelling approach shows potential value for identifying universal patterns of tree-ring growth and anatomical features over a broad climatic gradient. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
Wang, Daosheng; Zhang, Jicai; He, Xianqiang; Chu, Dongdong; Lv, Xianqing; Wang, Ya Ping; Yang, Yang; Fan, Daidu; Gao, Shu
2018-01-01
Model parameters in the suspended cohesive sediment transport models are critical for the accurate simulation of suspended sediment concentrations (SSCs). Difficulties in estimating the model parameters still prevent numerical modeling of the sediment transport from achieving a high level of predictability. Based on a three-dimensional cohesive sediment transport model and its adjoint model, the satellite remote sensing data of SSCs during both spring tide and neap tide, retrieved from Geostationary Ocean Color Imager (GOCI), are assimilated to synchronously estimate four spatially and temporally varying parameters in the Hangzhou Bay in China, including settling velocity, resuspension rate, inflow open boundary conditions and initial conditions. After data assimilation, the model performance is significantly improved. Through several sensitivity experiments, the spatial and temporal variation tendencies of the estimated model parameters are verified to be robust and not affected by model settings. The pattern for the variations of the estimated parameters is analyzed and summarized. The temporal variations and spatial distributions of the estimated settling velocity are negatively correlated with current speed, which can be explained using the combination of flocculation process and Stokes' law. The temporal variations and spatial distributions of the estimated resuspension rate are also negatively correlated with current speed, which are related to the grain size of the seabed sediments under different current velocities. Besides, the estimated inflow open boundary conditions reach the local maximum values near the low water slack conditions and the estimated initial conditions are negatively correlated with water depth, which is consistent with the general understanding. The relationships between the estimated parameters and the hydrodynamic fields can be suggestive for improving the parameterization in cohesive sediment transport models.
Gallbladder Boundary Segmentation from Ultrasound Images Using Active Contour Model
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%.
Modeling digital breast tomosynthesis imaging systems for optimization studies
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
Model-Based Referenceless Quality Metric of 3D Synthesized Images Using Local Image Description.
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.
Software to model AXAF image quality
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
Directory of Open Access Journals (Sweden)
Haiyun Shi
2017-09-01
Full Text Available River islands are sandbars formed by scouring and silting. Their evolution is affected by several factors, among which are runoff and sediment discharge. The spatial-temporal evolution of seven river islands in the Nanjing Section of the Yangtze River of China was examined using TM (Thematic Mapper and ETM (Enhanced Thematic Mapper+ images from 1985 to 2015 at five year intervals. The following approaches were applied in this study: the threshold value method, binarization model, image registration, image cropping, convolution and cluster analysis. Annual runoff and sediment discharge data as measured at the Datong hydrological station upstream of Nanjing section were also used to determine the roles and impacts of various factors. The results indicated that: (1 TM/ETM+ images met the criteria of information extraction of river islands; (2 generally, the total area of these islands in this section and their changing rate decreased over time; (3 sediment and river discharge were the most significant factors in island evolution. They directly affect river islands through silting or erosion. Additionally, anthropocentric influences could play increasingly important roles.
A variational model of disjoining pressure: Liquid film on a nonplanar surface
Energy Technology Data Exchange (ETDEWEB)
Silin, D.; Virnovsky, G.
2009-06-01
Variational methods have been successfully used in modelling thin liquid films in numerous theoretical studies of wettability. In this paper, the variational model of the disjoining pressure is extended to the general case of a two-dimensional solid surface. The Helmgoltz free energy functional depends both on the disjoining pressure isotherm and the shape of the solid surface. The augmented Young-Laplace equation (AYLE) is a nonlinear second-order partial differential equation. A number of solutions describing wetting films on spherical grains have been obtained. In the case of cylindrical films, the phase portrait technique describes the entire variety of mathematically feasible solutions. It turns out that a periodic solution, which would describe wave-like wetting films, does not satisfy the Jacobi's condition of the classical calculus of variations. Therefore, such a solution is nonphysical. The roughness of the solid surface significantly affects liquid film stability. AYLE solutions suggest that film rupture is more likely at a location where the pore-wall surface is most exposed into the pore space and the curvature is positive.
International Nuclear Information System (INIS)
Rosenfelder, R.; Schreiber, A.W.
2002-01-01
We generalize the worldline variational approach to field theory by introducing a trial action which allows for anisotropic terms to be induced by external 4-momenta of Green's functions. By solving the ensuing variational equations numerically we demonstrate that within the (quenched) scalar Wick-Cutkosky model considerable improvement can be achieved over results obtained previously with isotropic actions. In particular, the critical coupling associated with the instability of the model is lowered, in accordance with expectations from Baym's proof of the instability in the unquenched theory. The physical picture associated with a different quantum mechanical motion of the dressed particle along and perpendicular to its classical momentum is discussed. Indeed, we find that for large couplings the dressed particle is strongly distorted in the direction of its four-momentum. In addition, we obtain an exact relation between the renormalized coupling of the theory and the propagator. Along the way we introduce new and efficient methods to evaluate the averages needed in the variational approach and apply them to the calculation of the 2-point function. (orig.)
Origins of Tropospheric Ozone Interannual Variation (IAV) over Reunion: A Model Investigation
Liu, Junhua; Rodriguez, Jose M.; Thompson, Anne M.; Logan, Jennifer A.; Douglass, Anne R.; Olsen, Mark A.; Steenrod, Stephen D.; Posny, Francoise
2016-01-01
Observations from long-term ozonesonde measurements show robust variations and trends in the evolution of ozone in the middle and upper troposphere over Reunion Island (21.1 degrees South Latitude, 55.5 degrees East Longitude) in June-August. Here we examine possible causes of the observed ozone variation at Reunion Island using hindcast simulations by the stratosphere-troposphere Global Modeling Initiative chemical transport model for 1992-2014, driven by assimilated Modern-Era Retrospective Analysis for Research and Applications (MERRA) meteorological fields. Reunion Island is at the edge of the subtropical jet, a region of strong stratospheric-tropospheric exchange. Our analysis implies that the large interannual variation (IAV) of upper tropospheric ozone over Reunion is driven by the large IAV of the stratospheric influence. The IAV of the large-scale, quasi-horizontal wind patterns also contributes to the IAV of ozone in the upper troposphere. Comparison to a simulation with constant emissions indicates that increasing emissions do not lead to the maximum trend in the middle and upper troposphere over Reunion during austral winter implied by the sonde data. The effects of increasing emission over southern Africa are limited tothe lower troposphere near the surface in August-September.
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
Computational model of lightness perception in high dynamic range imaging
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.
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.
Siddiq, A.
2013-09-01
We present a variational multiscale constitutive model that accounts for intergranular failure in nanocrystalline fcc metals due to void growth and coalescence in the grain boundary region. Following previous work by the authors, a nanocrystalline material is modeled as a two-phase material consisting of a grain interior phase and a grain boundary affected zone (GBAZ). A crystal plasticity model that accounts for the transition from partial dislocation to full dislocation mediated plasticity is used for the grain interior. Isotropic porous plasticity model with further extension to account for failure due to the void coalescence was used for the GBAZ. The extended model contains all the deformation phases, i.e. elastic deformation, plastic deformation including deviatoric and volumetric plasticity (void growth) followed by damage initiation and evolution due to void coalescence. Parametric studies have been performed to assess the model\\'s dependence on the different input parameters. The model is then validated against uniaxial loading experiments for different materials. Lastly we show the model\\'s ability to predict the damage and fracture of a dog-bone shaped specimen as observed experimentally. © 2013 Elsevier B.V.
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
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
International Nuclear Information System (INIS)
Dolly, S; Mutic, S; Anastasio, M; Li, H; Yu, L
2016-01-01
Purpose: Traditionally, image quality in radiation therapy is assessed subjectively or by utilizing physically-based metrics. Some model observers exist for task-based medical image quality assessment, but almost exclusively for diagnostic imaging tasks. As opposed to disease diagnosis, the task for image observers in radiation therapy is to utilize the available images to design and deliver a radiation dose which maximizes patient disease control while minimizing normal tissue damage. The purpose of this study was to design and implement a new computer simulation model observer to enable task-based image quality assessment in radiation therapy. Methods: A modular computer simulation framework was developed to resemble the radiotherapy observer by simulating an end-to-end radiation therapy treatment. Given images and the ground-truth organ boundaries from a numerical phantom as inputs, the framework simulates an external beam radiation therapy treatment and quantifies patient treatment outcomes using the previously defined therapeutic operating characteristic (TOC) curve. As a preliminary demonstration, TOC curves were calculated for various CT acquisition and reconstruction parameters, with the goal of assessing and optimizing simulation CT image quality for radiation therapy. Sources of randomness and bias within the system were analyzed. Results: The relationship between CT imaging dose and patient treatment outcome was objectively quantified in terms of a singular value, the area under the TOC (AUTOC) curve. The AUTOC decreases more rapidly for low-dose imaging protocols. AUTOC variation introduced by the dose optimization algorithm was approximately 0.02%, at the 95% confidence interval. Conclusion: A model observer has been developed and implemented to assess image quality based on radiation therapy treatment efficacy. It enables objective determination of appropriate imaging parameter values (e.g. imaging dose). Framework flexibility allows for incorporation
Coarse graining from variationally enhanced sampling applied to the Ginzburg–Landau model
Invernizzi, Michele; Valsson, Omar; Parrinello, Michele
2017-01-01
A powerful way to deal with a complex system is to build a coarse-grained model capable of catching its main physical features, while being computationally affordable. Inevitably, such coarse-grained models introduce a set of phenomenological parameters, which are often not easily deducible from the underlying atomistic system. We present a unique approach to the calculation of these parameters, based on the recently introduced variationally enhanced sampling method. It allows us to obtain the parameters from atomistic simulations, providing thus a direct connection between the microscopic and the mesoscopic scale. The coarse-grained model we consider is that of Ginzburg–Landau, valid around a second-order critical point. In particular, we use it to describe a Lennard–Jones fluid in the region close to the liquid–vapor critical point. The procedure is general and can be adapted to other coarse-grained models. PMID:28292890
Coarse graining from variationally enhanced sampling applied to the Ginzburg-Landau model
Invernizzi, Michele; Valsson, Omar; Parrinello, Michele
2017-03-01
A powerful way to deal with a complex system is to build a coarse-grained model capable of catching its main physical features, while being computationally affordable. Inevitably, such coarse-grained models introduce a set of phenomenological parameters, which are often not easily deducible from the underlying atomistic system. We present a unique approach to the calculation of these parameters, based on the recently introduced variationally enhanced sampling method. It allows us to obtain the parameters from atomistic simulations, providing thus a direct connection between the microscopic and the mesoscopic scale. The coarse-grained model we consider is that of Ginzburg-Landau, valid around a second-order critical point. In particular, we use it to describe a Lennard-Jones fluid in the region close to the liquid-vapor critical point. The procedure is general and can be adapted to other coarse-grained models.
Benton, E. R.
1986-01-01
A spherical harmonic representation of the geomagnetic field and its secular variation for epoch 1980, designated GSFC(9/84), is derived and evaluated. At three epochs (1977.5, 1980.0, 1982.5) this model incorporates conservation of magnetic flux through five selected patches of area on the core/mantle boundary bounded by the zero contours of vertical magnetic field. These fifteen nonlinear constraints are included like data in an iterative least squares parameter estimation procedure that starts with the recently derived unconstrained field model GSFC (12/83). Convergence is approached within three iterations. The constrained model is evaluated by comparing its predictive capability outside the time span of its data, in terms of residuals at magnetic observatories, with that for the unconstrained model.
Dynamics of the sub-Ohmic spin-boson model: A time-dependent variational study
International Nuclear Information System (INIS)
Wu Ning; Duan Liwei; Zhao Yang; Li Xin
2013-01-01
The Dirac-Frenkel time-dependent variation is employed to probe the dynamics of the zero temperature sub-Ohmic spin-boson model with strong friction utilizing the Davydov D 1 ansatz. It is shown that initial conditions of the phonon bath have considerable influence on the dynamics. Counterintuitively, even in the very strong coupling regime, quantum coherence features still manage to survive under the polarized bath initial condition, while such features are absent under the factorized bath initial condition. In addition, a coherent-incoherent transition is found at a critical coupling strength α≈ 0.1 for s= 0.25 under the factorized bath initial condition. We quantify how faithfully our ansatz follows the Schrödinger equation, finding that the time-dependent variational approach is robust for strong dissipation and deep sub-Ohmic baths (s≪ 1).
Predictive Distribution of the Dirichlet Mixture Model by the Local Variational Inference Method
DEFF Research Database (Denmark)
Ma, Zhanyu; Leijon, Arne; Tan, Zheng-Hua
2014-01-01
the predictive likelihood of the new upcoming data, especially when the amount of training data is small. The Bayesian estimation of a Dirichlet mixture model (DMM) is, in general, not analytically tractable. In our previous work, we have proposed a global variational inference-based method for approximately...... calculating the posterior distributions of the parameters in the DMM analytically. In this paper, we extend our previous study for the DMM and propose an algorithm to calculate the predictive distribution of the DMM with the local variational inference (LVI) method. The true predictive distribution of the DMM...... is analytically intractable. By considering the concave property of the multivariate inverse beta function, we introduce an upper-bound to the true predictive distribution. As the global minimum of this upper-bound exists, the problem is reduced to seek an approximation to the true predictive distribution...
Symmetry-projected variational approach to the one-dimensional Hubbard model
International Nuclear Information System (INIS)
Schmid, K.W.; Dahm, T.; Margueron, J.; Muether, H.
2005-01-01
We apply a variational method devised for the nuclear many-body problem to the one-dimensional Hubbard model with nearest neighbor hopping and periodic boundary conditions. The test wave function consist for each state out of a single Hartree-Fock determinant mixing all the sites (or momenta) as well as the spin projections of the electrons. Total spin and linear momentum are restored by projection methods before the variation. It is demonstrated that this approach reproduces the results of exact diagonalizations for half-filled N=12 and N=14 lattices not only for the energies and occupation numbers of the ground but also of the lowest excited states rather well. Furthermore, a system of ten electrons in an N=12 lattice is investigated and, finally, an N=30 lattice is studied. In addition to energies and occupation numbers we present the spectral functions computed with the help of the symmetry-projected wave functions as well
Botelho, Fabio
2014-01-01
This book introduces the basic concepts of real and functional analysis. It presents the fundamentals of the calculus of variations, convex analysis, duality, and optimization that are necessary to develop applications to physics and engineering problems. The book includes introductory and advanced concepts in measure and integration, as well as an introduction to Sobolev spaces. The problems presented are nonlinear, with non-convex variational formulation. Notably, the primal global minima may not be attained in some situations, in which cases the solution of the dual problem corresponds to an appropriate weak cluster point of minimizing sequences for the primal one. Indeed, the dual approach more readily facilitates numerical computations for some of the selected models. While intended primarily for applied mathematicians, the text will also be of interest to engineers, physicists, and other researchers in related fields.
Modeling human faces with multi-image photogrammetry
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