Robust functional statistics applied to Probability Density Function shape screening of sEMG data.

PubMed

Boudaoud, S; Rix, H; Al Harrach, M; Marin, F

2014-01-01

Recent studies pointed out possible shape modifications of the Probability Density Function (PDF) of surface electromyographical (sEMG) data according to several contexts like fatigue and muscle force increase. Following this idea, criteria have been proposed to monitor these shape modifications mainly using High Order Statistics (HOS) parameters like skewness and kurtosis. In experimental conditions, these parameters are confronted with small sample size in the estimation process. This small sample size induces errors in the estimated HOS parameters restraining real-time and precise sEMG PDF shape monitoring. Recently, a functional formalism, the Core Shape Model (CSM), has been used to analyse shape modifications of PDF curves. In this work, taking inspiration from CSM method, robust functional statistics are proposed to emulate both skewness and kurtosis behaviors. These functional statistics combine both kernel density estimation and PDF shape distances to evaluate shape modifications even in presence of small sample size. Then, the proposed statistics are tested, using Monte Carlo simulations, on both normal and Log-normal PDFs that mimic observed sEMG PDF shape behavior during muscle contraction. According to the obtained results, the functional statistics seem to be more robust than HOS parameters to small sample size effect and more accurate in sEMG PDF shape screening applications.

Statistical shape (ASM) and appearance (AAM) models for the segmentation of the cerebellum in fetal ultrasound

NASA Astrophysics Data System (ADS)

Reyes López, Misael; Arámbula Cosío, Fernando

2017-11-01

The cerebellum is an important structure to determine the gestational age of the fetus, moreover most of the abnormalities it presents are related to growth disorders. In this work, we present the results of the segmentation of the fetal cerebellum applying statistical shape and appearance models. Both models were tested on ultrasound images of the fetal brain taken from 23 pregnant women, between 18 and 24 gestational weeks. The accuracy results obtained on 11 ultrasound images show a mean Hausdorff distance of 6.08 mm between the manual segmentation and the segmentation using active shape model, and a mean Hausdorff distance of 7.54 mm between the manual segmentation and the segmentation using active appearance model. The reported results demonstrate that the active shape model is more robust in the segmentation of the fetal cerebellum in ultrasound images.

Application of statistical shape analysis for the estimation of bone and forensic age using the shapes of the 2nd, 3rd, and 4th cervical vertebrae in a young Japanese population.

PubMed

Rhee, Chang-Hoon; Shin, Sang Min; Choi, Yong-Seok; Yamaguchi, Tetsutaro; Maki, Koutaro; Kim, Yong-Il; Kim, Seong-Sik; Park, Soo-Byung; Son, Woo-Sung

2015-12-01

From computed tomographic images, the dentocentral synchondrosis can be identified in the second cervical vertebra. This can demarcate the border between the odontoid process and the body of the 2nd cervical vertebra and serve as a good model for the prediction of bone and forensic age. Nevertheless, until now, there has been no application of the 2nd cervical vertebra based on the dentocentral synchondrosis. In this study, statistical shape analysis was used to build bone and forensic age estimation regression models. Following the principles of statistical shape analysis and principal components analysis, we used cone-beam computed tomography (CBCT) to evaluate a Japanese population (35 males and 45 females, from 5 to 19 years old). The narrowest prediction intervals among the multivariate regression models were 19.63 for bone age and 2.99 for forensic age. There was no significant difference between form space and shape space in the bone and forensic age estimation models. However, for gender comparison, the bone and forensic age estimation models for males had the higher explanatory power. This study derived an improved objective and quantitative method for bone and forensic age estimation based on only the 2nd, 3rd and 4th cervical vertebral shapes. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Prostate segmentation in MRI using a convolutional neural network architecture and training strategy based on statistical shape models.

PubMed

Karimi, Davood; Samei, Golnoosh; Kesch, Claudia; Nir, Guy; Salcudean, Septimiu E

2018-05-15

Most of the existing convolutional neural network (CNN)-based medical image segmentation methods are based on methods that have originally been developed for segmentation of natural images. Therefore, they largely ignore the differences between the two domains, such as the smaller degree of variability in the shape and appearance of the target volume and the smaller amounts of training data in medical applications. We propose a CNN-based method for prostate segmentation in MRI that employs statistical shape models to address these issues. Our CNN predicts the location of the prostate center and the parameters of the shape model, which determine the position of prostate surface keypoints. To train such a large model for segmentation of 3D images using small data (1) we adopt a stage-wise training strategy by first training the network to predict the prostate center and subsequently adding modules for predicting the parameters of the shape model and prostate rotation, (2) we propose a data augmentation method whereby the training images and their prostate surface keypoints are deformed according to the displacements computed based on the shape model, and (3) we employ various regularization techniques. Our proposed method achieves a Dice score of 0.88, which is obtained by using both elastic-net and spectral dropout for regularization. Compared with a standard CNN-based method, our method shows significantly better segmentation performance on the prostate base and apex. Our experiments also show that data augmentation using the shape model significantly improves the segmentation results. Prior knowledge about the shape of the target organ can improve the performance of CNN-based segmentation methods, especially where image features are not sufficient for a precise segmentation. Statistical shape models can also be employed to synthesize additional training data that can ease the training of large CNNs.

Methods of Information Geometry to model complex shapes

NASA Astrophysics Data System (ADS)

De Sanctis, A.; Gattone, S. A.

2016-09-01

In this paper, a new statistical method to model patterns emerging in complex systems is proposed. A framework for shape analysis of 2- dimensional landmark data is introduced, in which each landmark is represented by a bivariate Gaussian distribution. From Information Geometry we know that Fisher-Rao metric endows the statistical manifold of parameters of a family of probability distributions with a Riemannian metric. Thus this approach allows to reconstruct the intermediate steps in the evolution between observed shapes by computing the geodesic, with respect to the Fisher-Rao metric, between the corresponding distributions. Furthermore, the geodesic path can be used for shape predictions. As application, we study the evolution of the rat skull shape. A future application in Ophthalmology is introduced.

Six new mechanics corresponding to further shape theories

NASA Astrophysics Data System (ADS)

Anderson, Edward

2016-02-01

In this paper, suite of relational notions of shape are presented at the level of configuration space geometry, with corresponding new theories of shape mechanics and shape statistics. These further generalize two quite well known examples: (i) Kendall’s (metric) shape space with his shape statistics and Barbour’s mechanics thereupon. (ii) Leibnizian relational space alias metric scale-and-shape space to which corresponds Barbour-Bertotti mechanics. This paper’s new theories include, using the invariant and group namings, (iii) Angle alias conformal shape mechanics. (iv) Area ratio alias e shape mechanics. (v) Area alias e scale-and-shape mechanics. (iii)-(v) rest respectively on angle space, area-ratio space, and area space configuration spaces. Probability and statistics applications are also pointed to in outline. (vi) Various supersymmetric counterparts of (i)-(v) are considered. Since supergravity differs considerably from GR-based conceptions of background independence, some of the new supersymmetric shape mechanics are compared with both. These reveal compatibility between supersymmetry and GR-based conceptions of background independence, at least within these simpler model arenas.

Bayesian Statistics and Uncertainty Quantification for Safety Boundary Analysis in Complex Systems

NASA Technical Reports Server (NTRS)

He, Yuning; Davies, Misty Dawn

2014-01-01

The analysis of a safety-critical system often requires detailed knowledge of safe regions and their highdimensional non-linear boundaries. We present a statistical approach to iteratively detect and characterize the boundaries, which are provided as parameterized shape candidates. Using methods from uncertainty quantification and active learning, we incrementally construct a statistical model from only few simulation runs and obtain statistically sound estimates of the shape parameters for safety boundaries.

Liver segmentation from CT images using a sparse priori statistical shape model (SP-SSM).

PubMed

Wang, Xuehu; Zheng, Yongchang; Gan, Lan; Wang, Xuan; Sang, Xinting; Kong, Xiangfeng; Zhao, Jie

2017-01-01

This study proposes a new liver segmentation method based on a sparse a priori statistical shape model (SP-SSM). First, mark points are selected in the liver a priori model and the original image. Then, the a priori shape and its mark points are used to obtain a dictionary for the liver boundary information. Second, the sparse coefficient is calculated based on the correspondence between mark points in the original image and those in the a priori model, and then the sparse statistical model is established by combining the sparse coefficients and the dictionary. Finally, the intensity energy and boundary energy models are built based on the intensity information and the specific boundary information of the original image. Then, the sparse matching constraint model is established based on the sparse coding theory. These models jointly drive the iterative deformation of the sparse statistical model to approximate and accurately extract the liver boundaries. This method can solve the problems of deformation model initialization and a priori method accuracy using the sparse dictionary. The SP-SSM can achieve a mean overlap error of 4.8% and a mean volume difference of 1.8%, whereas the average symmetric surface distance and the root mean square symmetric surface distance can reach 0.8 mm and 1.4 mm, respectively.

Landmark-free statistical analysis of the shape of plant leaves.

PubMed

Laga, Hamid; Kurtek, Sebastian; Srivastava, Anuj; Miklavcic, Stanley J

2014-12-21

The shapes of plant leaves are important features to biologists, as they can help in distinguishing plant species, measuring their health, analyzing their growth patterns, and understanding relations between various species. Most of the methods that have been developed in the past focus on comparing the shape of individual leaves using either descriptors or finite sets of landmarks. However, descriptor-based representations are not invertible and thus it is often hard to map descriptor variability into shape variability. On the other hand, landmark-based techniques require automatic detection and registration of the landmarks, which is very challenging in the case of plant leaves that exhibit high variability within and across species. In this paper, we propose a statistical model based on the Squared Root Velocity Function (SRVF) representation and the Riemannian elastic metric of Srivastava et al. (2011) to model the observed continuous variability in the shape of plant leaves. We treat plant species as random variables on a non-linear shape manifold and thus statistical summaries, such as means and covariances, can be computed. One can then study the principal modes of variations and characterize the observed shapes using probability density models, such as Gaussians or Mixture of Gaussians. We demonstrate the usage of such statistical model for (1) efficient classification of individual leaves, (2) the exploration of the space of plant leaf shapes, which is important in the study of population-specific variations, and (3) comparing entire plant species, which is fundamental to the study of evolutionary relationships in plants. Our approach does not require descriptors or landmarks but automatically solves for the optimal registration that aligns a pair of shapes. We evaluate the performance of the proposed framework on publicly available benchmarks such as the Flavia, the Swedish, and the ImageCLEF2011 plant leaf datasets. Copyright © 2014 Elsevier Ltd. All rights reserved.

Average is Over

NASA Astrophysics Data System (ADS)

Eliazar, Iddo

2018-02-01

The popular perception of statistical distributions is depicted by the iconic bell curve which comprises of a massive bulk of 'middle-class' values, and two thin tails - one of small left-wing values, and one of large right-wing values. The shape of the bell curve is unimodal, and its peak represents both the mode and the mean. Thomas Friedman, the famous New York Times columnist, recently asserted that we have entered a human era in which "Average is Over" . In this paper we present mathematical models for the phenomenon that Friedman highlighted. While the models are derived via different modeling approaches, they share a common foundation. Inherent tipping points cause the models to phase-shift from a 'normal' bell-shape statistical behavior to an 'anomalous' statistical behavior: the unimodal shape changes to an unbounded monotone shape, the mode vanishes, and the mean diverges. Hence: (i) there is an explosion of small values; (ii) large values become super-large; (iii) 'middle-class' values are wiped out, leaving an infinite rift between the small and the super large values; and (iv) "Average is Over" indeed.

Training models of anatomic shape variability

PubMed Central

Merck, Derek; Tracton, Gregg; Saboo, Rohit; Levy, Joshua; Chaney, Edward; Pizer, Stephen; Joshi, Sarang

2008-01-01

Learning probability distributions of the shape of anatomic structures requires fitting shape representations to human expert segmentations from training sets of medical images. The quality of statistical segmentation and registration methods is directly related to the quality of this initial shape fitting, yet the subject is largely overlooked or described in an ad hoc way. This article presents a set of general principles to guide such training. Our novel method is to jointly estimate both the best geometric model for any given image and the shape distribution for the entire population of training images by iteratively relaxing purely geometric constraints in favor of the converging shape probabilities as the fitted objects converge to their target segmentations. The geometric constraints are carefully crafted both to obtain legal, nonself-interpenetrating shapes and to impose the model-to-model correspondences required for useful statistical analysis. The paper closes with example applications of the method to synthetic and real patient CT image sets, including same patient male pelvis and head and neck images, and cross patient kidney and brain images. Finally, we outline how this shape training serves as the basis for our approach to IGRT∕ART. PMID:18777919

Mapping morphological shape as a high-dimensional functional curve

PubMed Central

Fu, Guifang; Huang, Mian; Bo, Wenhao; Hao, Han; Wu, Rongling

2018-01-01

Abstract Detecting how genes regulate biological shape has become a multidisciplinary research interest because of its wide application in many disciplines. Despite its fundamental importance, the challenges of accurately extracting information from an image, statistically modeling the high-dimensional shape and meticulously locating shape quantitative trait loci (QTL) affect the progress of this research. In this article, we propose a novel integrated framework that incorporates shape analysis, statistical curve modeling and genetic mapping to detect significant QTLs regulating variation of biological shape traits. After quantifying morphological shape via a radius centroid contour approach, each shape, as a phenotype, was characterized as a high-dimensional curve, varying as angle θ runs clockwise with the first point starting from angle zero. We then modeled the dynamic trajectories of three mean curves and variation patterns as functions of θ. Our framework led to the detection of a few significant QTLs regulating the variation of leaf shape collected from a natural population of poplar, Populus szechuanica var tibetica. This population, distributed at altitudes 2000–4500 m above sea level, is an evolutionarily important plant species. This is the first work in the quantitative genetic shape mapping area that emphasizes a sense of ‘function’ instead of decomposing the shape into a few discrete principal components, as the majority of shape studies do. PMID:28062411

Sparse intervertebral fence composition for 3D cervical vertebra segmentation

NASA Astrophysics Data System (ADS)

Liu, Xinxin; Yang, Jian; Song, Shuang; Cong, Weijian; Jiao, Peifeng; Song, Hong; Ai, Danni; Jiang, Yurong; Wang, Yongtian

2018-06-01

Statistical shape models are capable of extracting shape prior information, and are usually utilized to assist the task of segmentation of medical images. However, such models require large training datasets in the case of multi-object structures, and it also is difficult to achieve satisfactory results for complex shapes. This study proposed a novel statistical model for cervical vertebra segmentation, called sparse intervertebral fence composition (SiFC), which can reconstruct the boundary between adjacent vertebrae by modeling intervertebral fences. The complex shape of the cervical spine is replaced by a simple intervertebral fence, which considerably reduces the difficulty of cervical segmentation. The final segmentation results are obtained by using a 3D active contour deformation model without shape constraint, which substantially enhances the recognition capability of the proposed method for objects with complex shapes. The proposed segmentation framework is tested on a dataset with CT images from 20 patients. A quantitative comparison against corresponding reference vertebral segmentation yields an overall mean absolute surface distance of 0.70 mm and a dice similarity index of 95.47% for cervical vertebral segmentation. The experimental results show that the SiFC method achieves competitive cervical vertebral segmentation performances, and completely eliminates inter-process overlap.

Multi-region statistical shape model for cochlear implantation

NASA Astrophysics Data System (ADS)

Romera, Jordi; Kjer, H. Martin; Piella, Gemma; Ceresa, Mario; González Ballester, Miguel A.

2016-03-01

Statistical shape models are commonly used to analyze the variability between similar anatomical structures and their use is established as a tool for analysis and segmentation of medical images. However, using a global model to capture the variability of complex structures is not enough to achieve the best results. The complexity of a proper global model increases even more when the amount of data available is limited to a small number of datasets. Typically, the anatomical variability between structures is associated to the variability of their physiological regions. In this paper, a complete pipeline is proposed for building a multi-region statistical shape model to study the entire variability from locally identified physiological regions of the inner ear. The proposed model, which is based on an extension of the Point Distribution Model (PDM), is built for a training set of 17 high-resolution images (24.5 μm voxels) of the inner ear. The model is evaluated according to its generalization ability and specificity. The results are compared with the ones of a global model built directly using the standard PDM approach. The evaluation results suggest that better accuracy can be achieved using a regional modeling of the inner ear.

Whole vertebral bone segmentation method with a statistical intensity-shape model based approach

NASA Astrophysics Data System (ADS)

Hanaoka, Shouhei; Fritscher, Karl; Schuler, Benedikt; Masutani, Yoshitaka; Hayashi, Naoto; Ohtomo, Kuni; Schubert, Rainer

2011-03-01

An automatic segmentation algorithm for the vertebrae in human body CT images is presented. Especially we focused on constructing and utilizing 4 different statistical intensity-shape combined models for the cervical, upper / lower thoracic and lumbar vertebrae, respectively. For this purpose, two previously reported methods were combined: a deformable model-based initial segmentation method and a statistical shape-intensity model-based precise segmentation method. The former is used as a pre-processing to detect the position and orientation of each vertebra, which determines the initial condition for the latter precise segmentation method. The precise segmentation method needs prior knowledge on both the intensities and the shapes of the objects. After PCA analysis of such shape-intensity expressions obtained from training image sets, vertebrae were parametrically modeled as a linear combination of the principal component vectors. The segmentation of each target vertebra was performed as fitting of this parametric model to the target image by maximum a posteriori estimation, combined with the geodesic active contour method. In the experimental result by using 10 cases, the initial segmentation was successful in 6 cases and only partially failed in 4 cases (2 in the cervical area and 2 in the lumbo-sacral). In the precise segmentation, the mean error distances were 2.078, 1.416, 0.777, 0.939 mm for cervical, upper and lower thoracic, lumbar spines, respectively. In conclusion, our automatic segmentation algorithm for the vertebrae in human body CT images showed a fair performance for cervical, thoracic and lumbar vertebrae.

Spatial scan statistics for detection of multiple clusters with arbitrary shapes.

PubMed

Lin, Pei-Sheng; Kung, Yi-Hung; Clayton, Murray

2016-12-01

In applying scan statistics for public health research, it would be valuable to develop a detection method for multiple clusters that accommodates spatial correlation and covariate effects in an integrated model. In this article, we connect the concepts of the likelihood ratio (LR) scan statistic and the quasi-likelihood (QL) scan statistic to provide a series of detection procedures sufficiently flexible to apply to clusters of arbitrary shape. First, we use an independent scan model for detection of clusters and then a variogram tool to examine the existence of spatial correlation and regional variation based on residuals of the independent scan model. When the estimate of regional variation is significantly different from zero, a mixed QL estimating equation is developed to estimate coefficients of geographic clusters and covariates. We use the Benjamini-Hochberg procedure (1995) to find a threshold for p-values to address the multiple testing problem. A quasi-deviance criterion is used to regroup the estimated clusters to find geographic clusters with arbitrary shapes. We conduct simulations to compare the performance of the proposed method with other scan statistics. For illustration, the method is applied to enterovirus data from Taiwan. © 2016, The International Biometric Society.

Quantitative analysis of fetal facial morphology using 3D ultrasound and statistical shape modeling: a feasibility study.

PubMed

Dall'Asta, Andrea; Schievano, Silvia; Bruse, Jan L; Paramasivam, Gowrishankar; Kaihura, Christine Tita; Dunaway, David; Lees, Christoph C

2017-07-01

The antenatal detection of facial dysmorphism using 3-dimensional ultrasound may raise the suspicion of an underlying genetic condition but infrequently leads to a definitive antenatal diagnosis. Despite advances in array and noninvasive prenatal testing, not all genetic conditions can be ascertained from such testing. The aim of this study was to investigate the feasibility of quantitative assessment of fetal face features using prenatal 3-dimensional ultrasound volumes and statistical shape modeling. STUDY DESIGN: Thirteen normal and 7 abnormal stored 3-dimensional ultrasound fetal face volumes were analyzed, at a median gestation of 29 +4  weeks (25 +0 to 36 +1 ). The 20 3-dimensional surface meshes generated were aligned and served as input for a statistical shape model, which computed the mean 3-dimensional face shape and 3-dimensional shape variations using principal component analysis. Ten shape modes explained more than 90% of the total shape variability in the population. While the first mode accounted for overall size differences, the second highlighted shape feature changes from an overall proportionate toward a more asymmetric face shape with a wide prominent forehead and an undersized, posteriorly positioned chin. Analysis of the Mahalanobis distance in principal component analysis shape space suggested differences between normal and abnormal fetuses (median and interquartile range distance values, 7.31 ± 5.54 for the normal group vs 13.27 ± 9.82 for the abnormal group) (P = .056). This feasibility study demonstrates that objective characterization and quantification of fetal facial morphology is possible from 3-dimensional ultrasound. This technique has the potential to assist in utero diagnosis, particularly of rare conditions in which facial dysmorphology is a feature. Copyright © 2017 Elsevier Inc. All rights reserved.

Generalized Models for Rock Joint Surface Shapes

PubMed Central

Du, Shigui; Hu, Yunjin; Hu, Xiaofei

2014-01-01

Generalized models of joint surface shapes are the foundation for mechanism studies on the mechanical effects of rock joint surface shapes. Based on extensive field investigations of rock joint surface shapes, generalized models for three level shapes named macroscopic outline, surface undulating shape, and microcosmic roughness were established through statistical analyses of 20,078 rock joint surface profiles. The relative amplitude of profile curves was used as a borderline for the division of different level shapes. The study results show that the macroscopic outline has three basic features such as planar, arc-shaped, and stepped; the surface undulating shape has three basic features such as planar, undulating, and stepped; and the microcosmic roughness has two basic features such as smooth and rough. PMID:25152901

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

Rueegsegger, Michael B.; Bach Cuadra, Meritxell; Pica, Alessia

Purpose: Ocular anatomy and radiation-associated toxicities provide unique challenges for external beam radiation therapy. For treatment planning, precise modeling of organs at risk and tumor volume are crucial. Development of a precise eye model and automatic adaptation of this model to patients' anatomy remain problematic because of organ shape variability. This work introduces the application of a 3-dimensional (3D) statistical shape model as a novel method for precise eye modeling for external beam radiation therapy of intraocular tumors. Methods and Materials: Manual and automatic segmentations were compared for 17 patients, based on head computed tomography (CT) volume scans. A 3Dmore » statistical shape model of the cornea, lens, and sclera as well as of the optic disc position was developed. Furthermore, an active shape model was built to enable automatic fitting of the eye model to CT slice stacks. Cross-validation was performed based on leave-one-out tests for all training shapes by measuring dice coefficients and mean segmentation errors between automatic segmentation and manual segmentation by an expert. Results: Cross-validation revealed a dice similarity of 95% {+-} 2% for the sclera and cornea and 91% {+-} 2% for the lens. Overall, mean segmentation error was found to be 0.3 {+-} 0.1 mm. Average segmentation time was 14 {+-} 2 s on a standard personal computer. Conclusions: Our results show that the solution presented outperforms state-of-the-art methods in terms of accuracy, reliability, and robustness. Moreover, the eye model shape as well as its variability is learned from a training set rather than by making shape assumptions (eg, as with the spherical or elliptical model). Therefore, the model appears to be capable of modeling nonspherically and nonelliptically shaped eyes.« less

A Computational Model of Multidimensional Shape

PubMed Central

Liu, Xiuwen; Shi, Yonggang; Dinov, Ivo

2010-01-01

We develop a computational model of shape that extends existing Riemannian models of curves to multidimensional objects of general topological type. We construct shape spaces equipped with geodesic metrics that measure how costly it is to interpolate two shapes through elastic deformations. The model employs a representation of shape based on the discrete exterior derivative of parametrizations over a finite simplicial complex. We develop algorithms to calculate geodesics and geodesic distances, as well as tools to quantify local shape similarities and contrasts, thus obtaining a formulation that accounts for regional differences and integrates them into a global measure of dissimilarity. The Riemannian shape spaces provide a common framework to treat numerous problems such as the statistical modeling of shapes, the comparison of shapes associated with different individuals or groups, and modeling and simulation of shape dynamics. We give multiple examples of geodesic interpolations and illustrations of the use of the models in brain mapping, particularly, the analysis of anatomical variation based on neuroimaging data. PMID:21057668

A Statistical Skull Geometry Model for Children 0-3 Years Old

PubMed Central

Li, Zhigang; Park, Byoung-Keon; Liu, Weiguo; Zhang, Jinhuan; Reed, Matthew P.; Rupp, Jonathan D.; Hoff, Carrie N.; Hu, Jingwen

2015-01-01

Head injury is the leading cause of fatality and long-term disability for children. Pediatric heads change rapidly in both size and shape during growth, especially for children under 3 years old (YO). To accurately assess the head injury risks for children, it is necessary to understand the geometry of the pediatric head and how morphologic features influence injury causation within the 0–3 YO population. In this study, head CT scans from fifty-six 0–3 YO children were used to develop a statistical model of pediatric skull geometry. Geometric features important for injury prediction, including skull size and shape, skull thickness and suture width, along with their variations among the sample population, were quantified through a series of image and statistical analyses. The size and shape of the pediatric skull change significantly with age and head circumference. The skull thickness and suture width vary with age, head circumference and location, which will have important effects on skull stiffness and injury prediction. The statistical geometry model developed in this study can provide a geometrical basis for future development of child anthropomorphic test devices and pediatric head finite element models. PMID:25992998

A statistical skull geometry model for children 0-3 years old.

PubMed

Li, Zhigang; Park, Byoung-Keon; Liu, Weiguo; Zhang, Jinhuan; Reed, Matthew P; Rupp, Jonathan D; Hoff, Carrie N; Hu, Jingwen

2015-01-01

Head injury is the leading cause of fatality and long-term disability for children. Pediatric heads change rapidly in both size and shape during growth, especially for children under 3 years old (YO). To accurately assess the head injury risks for children, it is necessary to understand the geometry of the pediatric head and how morphologic features influence injury causation within the 0-3 YO population. In this study, head CT scans from fifty-six 0-3 YO children were used to develop a statistical model of pediatric skull geometry. Geometric features important for injury prediction, including skull size and shape, skull thickness and suture width, along with their variations among the sample population, were quantified through a series of image and statistical analyses. The size and shape of the pediatric skull change significantly with age and head circumference. The skull thickness and suture width vary with age, head circumference and location, which will have important effects on skull stiffness and injury prediction. The statistical geometry model developed in this study can provide a geometrical basis for future development of child anthropomorphic test devices and pediatric head finite element models.

A statistical shape modelling framework to extract 3D shape biomarkers from medical imaging data: assessing arch morphology of repaired coarctation of the aorta.

PubMed

Bruse, Jan L; McLeod, Kristin; Biglino, Giovanni; Ntsinjana, Hopewell N; Capelli, Claudio; Hsia, Tain-Yen; Sermesant, Maxime; Pennec, Xavier; Taylor, Andrew M; Schievano, Silvia

2016-05-31

Medical image analysis in clinical practice is commonly carried out on 2D image data, without fully exploiting the detailed 3D anatomical information that is provided by modern non-invasive medical imaging techniques. In this paper, a statistical shape analysis method is presented, which enables the extraction of 3D anatomical shape features from cardiovascular magnetic resonance (CMR) image data, with no need for manual landmarking. The method was applied to repaired aortic coarctation arches that present complex shapes, with the aim of capturing shape features as biomarkers of potential functional relevance. The method is presented from the user-perspective and is evaluated by comparing results with traditional morphometric measurements. Steps required to set up the statistical shape modelling analyses, from pre-processing of the CMR images to parameter setting and strategies to account for size differences and outliers, are described in detail. The anatomical mean shape of 20 aortic arches post-aortic coarctation repair (CoA) was computed based on surface models reconstructed from CMR data. By analysing transformations that deform the mean shape towards each of the individual patient's anatomy, shape patterns related to differences in body surface area (BSA) and ejection fraction (EF) were extracted. The resulting shape vectors, describing shape features in 3D, were compared with traditionally measured 2D and 3D morphometric parameters. The computed 3D mean shape was close to population mean values of geometric shape descriptors and visually integrated characteristic shape features associated with our population of CoA shapes. After removing size effects due to differences in body surface area (BSA) between patients, distinct 3D shape features of the aortic arch correlated significantly with EF (r = 0.521, p = .022) and were well in agreement with trends as shown by traditional shape descriptors. The suggested method has the potential to discover previously unknown 3D shape biomarkers from medical imaging data. Thus, it could contribute to improving diagnosis and risk stratification in complex cardiac disease.

Probabilistic registration of an unbiased statistical shape model to ultrasound images of the spine

NASA Astrophysics Data System (ADS)

Rasoulian, Abtin; Rohling, Robert N.; Abolmaesumi, Purang

2012-02-01

The placement of an epidural needle is among the most difficult regional anesthetic techniques. Ultrasound has been proposed to improve success of placement. However, it has not become the standard-of-care because of limitations in the depictions and interpretation of the key anatomical features. We propose to augment the ultrasound images with a registered statistical shape model of the spine to aid interpretation. The model is created with a novel deformable group-wise registration method which utilizes a probabilistic approach to register groups of point sets. The method is compared to a volume-based model building technique and it demonstrates better generalization and compactness. We instantiate and register the shape model to a spine surface probability map extracted from the ultrasound images. Validation is performed on human subjects. The achieved registration accuracy (2-4 mm) is sufficient to guide the choice of puncture site and trajectory of an epidural needle.

Statistical appearance models based on probabilistic correspondences.

PubMed

Krüger, Julia; Ehrhardt, Jan; Handels, Heinz

2017-04-01

Model-based image analysis is indispensable in medical image processing. One key aspect of building statistical shape and appearance models is the determination of one-to-one correspondences in the training data set. At the same time, the identification of these correspondences is the most challenging part of such methods. In our earlier work, we developed an alternative method using correspondence probabilities instead of exact one-to-one correspondences for a statistical shape model (Hufnagel et al., 2008). In this work, a new approach for statistical appearance models without one-to-one correspondences is proposed. A sparse image representation is used to build a model that combines point position and appearance information at the same time. Probabilistic correspondences between the derived multi-dimensional feature vectors are used to omit the need for extensive preprocessing of finding landmarks and correspondences as well as to reduce the dependence of the generated model on the landmark positions. Model generation and model fitting can now be expressed by optimizing a single global criterion derived from a maximum a-posteriori (MAP) approach with respect to model parameters that directly affect both shape and appearance of the considered objects inside the images. The proposed approach describes statistical appearance modeling in a concise and flexible mathematical framework. Besides eliminating the demand for costly correspondence determination, the method allows for additional constraints as topological regularity in the modeling process. In the evaluation the model was applied for segmentation and landmark identification in hand X-ray images. The results demonstrate the feasibility of the model to detect hand contours as well as the positions of the joints between finger bones for unseen test images. Further, we evaluated the model on brain data of stroke patients to show the ability of the proposed model to handle partially corrupted data and to demonstrate a possible employment of the correspondence probabilities to indicate these corrupted/pathological areas. Copyright © 2017 Elsevier B.V. All rights reserved.

Automatic liver segmentation in computed tomography using general-purpose shape modeling methods.

PubMed

Spinczyk, Dominik; Krasoń, Agata

2018-05-29

Liver segmentation in computed tomography is required in many clinical applications. The segmentation methods used can be classified according to a number of criteria. One important criterion for method selection is the shape representation of the segmented organ. The aim of the work is automatic liver segmentation using general purpose shape modeling methods. As part of the research, methods based on shape information at various levels of advancement were used. The single atlas based segmentation method was used as the simplest shape-based method. This method is derived from a single atlas using the deformable free-form deformation of the control point curves. Subsequently, the classic and modified Active Shape Model (ASM) was used, using medium body shape models. As the most advanced and main method generalized statistical shape models, Gaussian Process Morphable Models was used, which are based on multi-dimensional Gaussian distributions of the shape deformation field. Mutual information and sum os square distance were used as similarity measures. The poorest results were obtained for the single atlas method. For the ASM method in 10 analyzed cases for seven test images, the Dice coefficient was above 55[Formula: see text], of which for three of them the coefficient was over 70[Formula: see text], which placed the method in second place. The best results were obtained for the method of generalized statistical distribution of the deformation field. The DICE coefficient for this method was 88.5[Formula: see text] CONCLUSIONS: This value of 88.5 [Formula: see text] Dice coefficient can be explained by the use of general-purpose shape modeling methods with a large variance of the shape of the modeled object-the liver and limitations on the size of our training data set, which was limited to 10 cases. The obtained results in presented fully automatic method are comparable with dedicated methods for liver segmentation. In addition, the deforamtion features of the model can be modeled mathematically by using various kernel functions, which allows to segment the liver on a comparable level using a smaller learning set.

Functional constraints on tooth morphology in carnivorous mammals

PubMed Central

2012-01-01

Background The range of potential morphologies resulting from evolution is limited by complex interacting processes, ranging from development to function. Quantifying these interactions is important for understanding adaptation and convergent evolution. Using three-dimensional reconstructions of carnivoran and dasyuromorph tooth rows, we compared statistical models of the relationship between tooth row shape and the opposing tooth row, a static feature, as well as measures of mandibular motion during chewing (occlusion), which are kinetic features. This is a new approach to quantifying functional integration because we use measures of movement and displacement, such as the amount the mandible translates laterally during occlusion, as opposed to conventional morphological measures, such as mandible length and geometric landmarks. By sampling two distantly related groups of ecologically similar mammals, we study carnivorous mammals in general rather than a specific group of mammals. Results Statistical model comparisons demonstrate that the best performing models always include some measure of mandibular motion, indicating that functional and statistical models of tooth shape as purely a function of the opposing tooth row are too simple and that increased model complexity provides a better understanding of tooth form. The predictors of the best performing models always included the opposing tooth row shape and a relative linear measure of mandibular motion. Conclusions Our results provide quantitative support of long-standing hypotheses of tooth row shape as being influenced by mandibular motion in addition to the opposing tooth row. Additionally, this study illustrates the utility and necessity of including kinetic features in analyses of morphological integration. PMID:22899809

The role of shape complexity in the detection of closed contours.

PubMed

Wilder, John; Feldman, Jacob; Singh, Manish

2016-09-01

The detection of contours in noise has been extensively studied, but the detection of closed contours, such as the boundaries of whole objects, has received relatively little attention. Closed contours pose substantial challenges not present in the simple (open) case, because they form the outlines of whole shapes and thus take on a range of potentially important configural properties. In this paper we consider the detection of closed contours in noise as a probabilistic decision problem. Previous work on open contours suggests that contour complexity, quantified as the negative log probability (Description Length, DL) of the contour under a suitably chosen statistical model, impairs contour detectability; more complex (statistically surprising) contours are harder to detect. In this study we extended this result to closed contours, developing a suitable probabilistic model of whole shapes that gives rise to several distinct though interrelated measures of shape complexity. We asked subjects to detect either natural shapes (Exp. 1) or experimentally manipulated shapes (Exp. 2) embedded in noise fields. We found systematic effects of global shape complexity on detection performance, demonstrating how aspects of global shape and form influence the basic process of object detection. Copyright © 2015 Elsevier Ltd. All rights reserved.

Segmentation of prostate boundaries from ultrasound images using statistical shape model.

PubMed

Shen, Dinggang; Zhan, Yiqiang; Davatzikos, Christos

2003-04-01

This paper presents a statistical shape model for the automatic prostate segmentation in transrectal ultrasound images. A Gabor filter bank is first used to characterize the prostate boundaries in ultrasound images in both multiple scales and multiple orientations. The Gabor features are further reconstructed to be invariant to the rotation of the ultrasound probe and incorporated in the prostate model as image attributes for guiding the deformable segmentation. A hierarchical deformation strategy is then employed, in which the model adaptively focuses on the similarity of different Gabor features at different deformation stages using a multiresolution technique, i.e., coarse features first and fine features later. A number of successful experiments validate the algorithm.

Graphene growth process modeling: a physical-statistical approach

NASA Astrophysics Data System (ADS)

Wu, Jian; Huang, Qiang

2014-09-01

As a zero-band semiconductor, graphene is an attractive material for a wide variety of applications such as optoelectronics. Among various techniques developed for graphene synthesis, chemical vapor deposition on copper foils shows high potential for producing few-layer and large-area graphene. Since fabrication of high-quality graphene sheets requires the understanding of growth mechanisms, and methods of characterization and control of grain size of graphene flakes, analytical modeling of graphene growth process is therefore essential for controlled fabrication. The graphene growth process starts with randomly nucleated islands that gradually develop into complex shapes, grow in size, and eventually connect together to cover the copper foil. To model this complex process, we develop a physical-statistical approach under the assumption of self-similarity during graphene growth. The growth kinetics is uncovered by separating island shapes from area growth rate. We propose to characterize the area growth velocity using a confined exponential model, which not only has clear physical explanation, but also fits the real data well. For the shape modeling, we develop a parametric shape model which can be well explained by the angular-dependent growth rate. This work can provide useful information for the control and optimization of graphene growth process on Cu foil.

Statistical shape analysis of clavicular cortical bone with applications to the development of mean and boundary shape models.

PubMed

Lu, Yuan-Chiao; Untaroiu, Costin D

2013-09-01

During car collisions, the shoulder belt exposes the occupant's clavicle to large loading conditions which often leads to a bone fracture. To better understand the geometric variability of clavicular cortical bone which may influence its injury tolerance, twenty human clavicles were evaluated using statistical shape analysis. The interior and exterior clavicular cortical bone surfaces were reconstructed from CT-scan images. Registration between one selected template and the remaining 19 clavicle models was conducted to remove translation and rotation differences. The correspondences of landmarks between the models were then established using coordinates and surface normals. Three registration methods were compared: the LM-ICP method; the global method; and the SHREC method. The LM-ICP registration method showed better performance than the global and SHREC registration methods, in terms of compactness, generalization, and specificity. The first four principal components obtained by using the LM-ICP registration method account for 61% and 67% of the overall anatomical variation for the exterior and interior cortical bone shapes, respectively. The length was found to be the most significant variation mode of the human clavicle. The mean and two boundary shape models were created using the four most significant principal components to investigate the size and shape variation of clavicular cortical bone. In the future, boundary shape models could be used to develop probabilistic finite element models which may help to better understand the variability in biomechanical responses and injuries to the clavicle. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Statistical estimation of femur micro-architecture using optimal shape and density predictors.

PubMed

Lekadir, Karim; Hazrati-Marangalou, Javad; Hoogendoorn, Corné; Taylor, Zeike; van Rietbergen, Bert; Frangi, Alejandro F

2015-02-26

The personalization of trabecular micro-architecture has been recently shown to be important in patient-specific biomechanical models of the femur. However, high-resolution in vivo imaging of bone micro-architecture using existing modalities is still infeasible in practice due to the associated acquisition times, costs, and X-ray radiation exposure. In this study, we describe a statistical approach for the prediction of the femur micro-architecture based on the more easily extracted subject-specific bone shape and mineral density information. To this end, a training sample of ex vivo micro-CT images is used to learn the existing statistical relationships within the low and high resolution image data. More specifically, optimal bone shape and mineral density features are selected based on their predictive power and used within a partial least square regression model to estimate the unknown trabecular micro-architecture within the anatomical models of new subjects. The experimental results demonstrate the accuracy of the proposed approach, with average errors of 0.07 for both the degree of anisotropy and tensor norms. Copyright © 2015 Elsevier Ltd. All rights reserved.

Image segmentation using local shape and gray-level appearance models

NASA Astrophysics Data System (ADS)

Seghers, Dieter; Loeckx, Dirk; Maes, Frederik; Suetens, Paul

2006-03-01

A new generic model-based segmentation scheme is presented, which can be trained from examples akin to the Active Shape Model (ASM) approach in order to acquire knowledge about the shape to be segmented and about the gray-level appearance of the object in the image. Because in the ASM approach the intensity and shape models are typically applied alternately during optimizing as first an optimal target location is selected for each landmark separately based on local gray-level appearance information only to which the shape model is fitted subsequently, the ASM may be misled in case of wrongly selected landmark locations. Instead, the proposed approach optimizes for shape and intensity characteristics simultaneously. Local gray-level appearance information at the landmark points extracted from feature images is used to automatically detect a number of plausible candidate locations for each landmark. The shape information is described by multiple landmark-specific statistical models that capture local dependencies between adjacent landmarks on the shape. The shape and intensity models are combined in a single cost function that is optimized non-iteratively using dynamic programming which allows to find the optimal landmark positions using combined shape and intensity information, without the need for initialization.

Using statistical deformable models to reconstruct vocal tract shape from magnetic resonance images.

PubMed

Vasconcelos, M J M; Rua Ventura, S M; Freitas, D R S; Tavares, J M R S

2010-10-01

The mechanisms involved in speech production are complex and have thus been subject to growing attention by the scientific community. It has been demonstrated that magnetic resonance imaging (MRI) is a powerful means in the understanding of the morphology of the vocal tract. Over the last few years, statistical deformable models have been successfully used to identify and characterize bones and organs in medical images and point distribution models (PDMs) have gained particular relevance. In this work, the suitability of these models has been studied to characterize and further reconstruct the shape of the vocal tract in the articulation of Portuguese European (EP) speech sounds, one of the most spoken languages worldwide, with the aid of MR images. Therefore, a PDM has been built from a set of MR images acquired during the artificially sustained articulation of 25 EP speech sounds. Following this, the capacity of this statistical model to characterize the shape deformation of the vocal tract during the production of sounds was analysed. Next, the model was used to reconstruct five EP oral vowels and the EP fricative consonants. As far as a study on speech production is concerned, this study is considered to be the first approach to characterize and reconstruct the vocal tract shape from MR images by using PDMs. In addition, the findings achieved permit one to conclude that this modelling technique compels an enhanced understanding of the dynamic speech events involved in sustained articulations based on MRI, which are of particular interest for speech rehabilitation and simulation.

Self-organized network of fractal-shaped components coupled through statistical interaction.

PubMed

Ugajin, R

2001-09-01

A dissipative dynamics is introduced to generate self-organized networks of interacting objects, which we call coupled-fractal networks. The growth model is constructed based on a growth hypothesis in which the growth rate of each object is a product of the probability of receiving source materials from faraway and the probability of receiving adhesives from other grown objects, where each object grows to be a random fractal if isolated, but connects with others if glued. The network is governed by the statistical interaction between fractal-shaped components, which can only be identified in a statistical manner over ensembles. This interaction is investigated using the degree of correlation between fractal-shaped components, enabling us to determine whether it is attractive or repulsive.

General Multivariate Linear Modeling of Surface Shapes Using SurfStat

PubMed Central

Chung, Moo K.; Worsley, Keith J.; Nacewicz, Brendon, M.; Dalton, Kim M.; Davidson, Richard J.

2010-01-01

Although there are many imaging studies on traditional ROI-based amygdala volumetry, there are very few studies on modeling amygdala shape variations. This paper present a unified computational and statistical framework for modeling amygdala shape variations in a clinical population. The weighted spherical harmonic representation is used as to parameterize, to smooth out, and to normalize amygdala surfaces. The representation is subsequently used as an input for multivariate linear models accounting for nuisance covariates such as age and brain size difference using SurfStat package that completely avoids the complexity of specifying design matrices. The methodology has been applied for quantifying abnormal local amygdala shape variations in 22 high functioning autistic subjects. PMID:20620211

A Statistical Analysis of YORP Coefficients

NASA Astrophysics Data System (ADS)

McMahon, Jay W.; Scheeres, D.

2013-10-01

The YORP (Yarkovsky-O'Keefe-Radzievskii-Paddack) effect is theorized to be a major factor in the evolution of small asteroids (<10 km) in the near-Earth and main belt populations. YORP torques, which originate from absorbed sunlight and subsequent thermal radiation, causes secular changes in an asteroid's spin rate and spin vector orientation (e.g. Rubincam, Journal of Geophysical Research, 1995). This in turn controls the magnitude and direction of the Yarkovsky effect, which causes a drift in an asteroid's heliocentric semi-major axis (Vokrouhlicky and Farinella, Nature, 2000). YORP is also thought to be responsible for the creation of multiple asteroid systems and asteroid pairs through the process of rotational fission (Pravec et al, Nature, 2010). Despite the fact that the YORP effect has been measured on several asteroids (e.g. Taylor et al, Science, 2007 and Kaasalainen et al, Nature, 2007), it has proven very difficult to predict the effect accurately from a shape model due to the sensitivity of the YORP coefficients to shape changes (Statler, Icarus, 2009). This has been especially troublesome for Itokawa, for which a very detailed shape model is available (Scheeres et al, Icarus 2007; Breiter et al, Astronomy & Astrophysics, 2009). In this study, we compute the YORP coefficients for a number asteroids with detailed shape models available on the PDS-SBN. We then statistically perturb the asteroid shapes at the same resolution, creating a family of YORP coefficients for each shape. Next, we analyze the change in YORP coefficients between a shape model of accuracy obtainable from radar with one including small-scale topography on the surface as was observed on Itokawa. The combination of these families of coefficients will effectively give error bars on our knowledge of the YORP coefficients given a shape model of some accuracy. Finally, we discuss the statistical effect of boulder and craters, and the modification of these results due to recent studies on thermal beaming (Rozitis and Green, Mon. Not. R. Astron. Soc., 2012) and "tangential" YORP (Golubov and Krugly, The Astrophysical Journal Letters, 2012).

A subdivision-based parametric deformable model for surface extraction and statistical shape modeling of the knee cartilages

NASA Astrophysics Data System (ADS)

Fripp, Jurgen; Crozier, Stuart; Warfield, Simon K.; Ourselin, Sébastien

2006-03-01

Subdivision surfaces and parameterization are desirable for many algorithms that are commonly used in Medical Image Analysis. However, extracting an accurate surface and parameterization can be difficult for many anatomical objects of interest, due to noisy segmentations and the inherent variability of the object. The thin cartilages of the knee are an example of this, especially after damage is incurred from injuries or conditions like osteoarthritis. As a result, the cartilages can have different topologies or exist in multiple pieces. In this paper we present a topology preserving (genus 0) subdivision-based parametric deformable model that is used to extract the surfaces of the patella and tibial cartilages in the knee. These surfaces have minimal thickness in areas without cartilage. The algorithm inherently incorporates several desirable properties, including: shape based interpolation, sub-division remeshing and parameterization. To illustrate the usefulness of this approach, the surfaces and parameterizations of the patella cartilage are used to generate a 3D statistical shape model.

Adapting Active Shape Models for 3D segmentation of tubular structures in medical images.

PubMed

de Bruijne, Marleen; van Ginneken, Bram; Viergever, Max A; Niessen, Wiro J

2003-07-01

Active Shape Models (ASM) have proven to be an effective approach for image segmentation. In some applications, however, the linear model of gray level appearance around a contour that is used in ASM is not sufficient for accurate boundary localization. Furthermore, the statistical shape model may be too restricted if the training set is limited. This paper describes modifications to both the shape and the appearance model of the original ASM formulation. Shape model flexibility is increased, for tubular objects, by modeling the axis deformation independent of the cross-sectional deformation, and by adding supplementary cylindrical deformation modes. Furthermore, a novel appearance modeling scheme that effectively deals with a highly varying background is developed. In contrast with the conventional ASM approach, the new appearance model is trained on both boundary and non-boundary points, and the probability that a given point belongs to the boundary is estimated non-parametrically. The methods are evaluated on the complex task of segmenting thrombus in abdominal aortic aneurysms (AAA). Shape approximation errors were successfully reduced using the two shape model extensions. Segmentation using the new appearance model significantly outperformed the original ASM scheme; average volume errors are 5.1% and 45% respectively.

Inter-speaker speech variability assessment using statistical deformable models from 3.0 tesla magnetic resonance images.

PubMed

Vasconcelos, Maria J M; Ventura, Sandra M R; Freitas, Diamantino R S; Tavares, João Manuel R S

2012-03-01

The morphological and dynamic characterisation of the vocal tract during speech production has been gaining greater attention due to the motivation of the latest improvements in magnetic resonance (MR) imaging; namely, with the use of higher magnetic fields, such as 3.0 Tesla. In this work, the automatic study of the vocal tract from 3.0 Tesla MR images was assessed through the application of statistical deformable models. Therefore, the primary goal focused on the analysis of the shape of the vocal tract during the articulation of European Portuguese sounds, followed by the evaluation of the results concerning the automatic segmentation, i.e. identification of the vocal tract in new MR images. In what concerns speech production, this is the first attempt to automatically characterise and reconstruct the vocal tract shape of 3.0 Tesla MR images by using deformable models; particularly, by using active and appearance shape models. The achieved results clearly evidence the adequacy and advantage of the automatic analysis of the 3.0 Tesla MR images of these deformable models in order to extract the vocal tract shape and assess the involved articulatory movements. These achievements are mostly required, for example, for a better knowledge of speech production, mainly of patients suffering from articulatory disorders, and to build enhanced speech synthesizer models.

The potential of statistical shape modelling for geometric morphometric analysis of human teeth in archaeological research

PubMed Central

Fernee, Christianne; Browne, Martin; Zakrzewski, Sonia

2017-01-01

This paper introduces statistical shape modelling (SSM) for use in osteoarchaeology research. SSM is a full field, multi-material analytical technique, and is presented as a supplementary geometric morphometric (GM) tool. Lower mandibular canines from two archaeological populations and one modern population were sampled, digitised using micro-CT, aligned, registered to a baseline and statistically modelled using principal component analysis (PCA). Sample material properties were incorporated as a binary enamel/dentin parameter. Results were assessed qualitatively and quantitatively using anatomical landmarks. Finally, the technique’s application was demonstrated for inter-sample comparison through analysis of the principal component (PC) weights. It was found that SSM could provide high detail qualitative and quantitative insight with respect to archaeological inter- and intra-sample variability. This technique has value for archaeological, biomechanical and forensic applications including identification, finite element analysis (FEA) and reconstruction from partial datasets. PMID:29216199

Uncertainty-enabled design of electromagnetic reflectors with integrated shape control

NASA Astrophysics Data System (ADS)

Haque, Samiul; Kindrat, Laszlo P.; Zhang, Li; Mikheev, Vikenty; Kim, Daewa; Liu, Sijing; Chung, Jooyeon; Kuian, Mykhailo; Massad, Jordan E.; Smith, Ralph C.

2018-03-01

We implemented a computationally efficient model for a corner-supported, thin, rectangular, orthotropic polyvinylidene fluoride (PVDF) laminate membrane, actuated by a two-dimensional array of segmented electrodes. The laminate can be used as shape-controlled electromagnetic reflector and the model estimates the reflector's shape given an array of control voltages. In this paper, we describe a model to determine the shape of the laminate for a given distribution of control voltages. Then, we investigate the surface shape error and its sensitivity to the model parameters. Subsequently, we analyze the simulated deflection of the actuated bimorph using a Zernike polynomial decomposition. Finally, we provide a probabilistic description of reflector performance using statistical methods to quantify uncertainty. We make design recommendations for nominal parameter values and their tolerances based on optimization under uncertainty using multiple methods.

Statistical modeling of space shuttle environmental data

NASA Technical Reports Server (NTRS)

Tubbs, J. D.; Brewer, D. W.

1983-01-01

Statistical models which use a class of bivariate gamma distribution are examined. Topics discussed include: (1) the ratio of positively correlated gamma varieties; (2) a method to determine if unequal shape parameters are necessary in bivariate gamma distribution; (3) differential equations for modal location of a family of bivariate gamma distribution; and (4) analysis of some wind gust data using the analytical results developed for modeling application.

Modeling the shape and composition of the human body using dual energy X-ray absorptiometry images

PubMed Central

Shepherd, John A.; Fan, Bo; Schwartz, Ann V.; Cawthon, Peggy; Cummings, Steven R.; Kritchevsky, Stephen; Nevitt, Michael; Santanasto, Adam; Cootes, Timothy F.

2017-01-01

There is growing evidence that body shape and regional body composition are strong indicators of metabolic health. The purpose of this study was to develop statistical models that accurately describe holistic body shape, thickness, and leanness. We hypothesized that there are unique body shape features that are predictive of mortality beyond standard clinical measures. We developed algorithms to process whole-body dual-energy X-ray absorptiometry (DXA) scans into body thickness and leanness images. We performed statistical appearance modeling (SAM) and principal component analysis (PCA) to efficiently encode the variance of body shape, leanness, and thickness across sample of 400 older Americans from the Health ABC study. The sample included 200 cases and 200 controls based on 6-year mortality status, matched on sex, race and BMI. The final model contained 52 points outlining the torso, upper arms, thighs, and bony landmarks. Correlation analyses were performed on the PCA parameters to identify body shape features that vary across groups and with metabolic risk. Stepwise logistic regression was performed to identify sex and race, and predict mortality risk as a function of body shape parameters. These parameters are novel body composition features that uniquely identify body phenotypes of different groups and predict mortality risk. Three parameters from a SAM of body leanness and thickness accurately identified sex (training AUC = 0.99) and six accurately identified race (training AUC = 0.91) in the sample dataset. Three parameters from a SAM of only body thickness predicted mortality (training AUC = 0.66, validation AUC = 0.62). Further study is warranted to identify specific shape/composition features that predict other health outcomes. PMID:28423041

Using active shape modeling based on MRI to study morphologic and pitch-related functional changes affecting vocal structures and the airway.

PubMed

Miller, Nicola A; Gregory, Jennifer S; Aspden, Richard M; Stollery, Peter J; Gilbert, Fiona J

2014-09-01

The shape of the vocal tract and associated structures (eg, tongue and velum) is complicated and varies according to development and function. This variability challenges interpretation of voice experiments. Quantifying differences between shapes and understanding how vocal structures move in relation to each other is difficult using traditional linear and angle measurements. With statistical shape models, shape can be characterized in terms of independent modes of variation. Here, we build an active shape model (ASM) to assess morphologic and pitch-related functional changes affecting vocal structures and the airway. Using a cross-sectional study design, we obtained six midsagittal magnetic resonance images from 10 healthy adults (five men and five women) at rest, while breathing out, and while listening to, and humming low and high notes. Eighty landmark points were chosen to define the shape of interest and an ASM was built using these (60) images. Principal component analysis was used to identify independent modes of variation, and statistical analysis was performed using one-way repeated-measures analysis of variance. Twenty modes of variation were identified with modes 1 and 2 accounting for half the total variance. Modes 1 and 9 were significantly associated with humming low and high notes (P < 0.001) and showed coordinated changes affecting the cervical spine, vocal structures, and airway. Mode 2 highlighted wide structural variations between subjects. This study highlights the potential of active shape modeling to advance understanding of factors underlying morphologic and pitch-related functional variations affecting vocal structures and the airway in health and disease. Copyright © 2014 The Voice Foundation. Published by Elsevier Inc. All rights reserved.

Static shape control for flexible structures

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Scheid, R. E., Jr.

1986-01-01

An integrated methodology is described for defining static shape control laws for large flexible structures. The techniques include modeling, identifying and estimating the control laws of distributed systems characterized in terms of infinite dimensional state and parameter spaces. The models are expressed as interconnected elliptic partial differential equations governing a range of static loads, with the capability of analyzing electromagnetic fields around antenna systems. A second-order analysis is carried out for statistical errors, and model parameters are determined by maximizing an appropriate defined likelihood functional which adjusts the model to observational data. The parameter estimates are derived from the conditional mean of the observational data, resulting in a least squares superposition of shape functions obtained from the structural model.

Statistical Shape Modeling for Cavopulmonary Assist Device Development: Variability of Vascular Graft Geometry and Implications for Hemodynamics.

PubMed

Bruse, Jan L; Giusti, Giuliano; Baker, Catriona; Cervi, Elena; Hsia, Tain-Yen; Taylor, Andrew M; Schievano, Silvia

2017-06-01

Patients born with a single functional ventricle typically undergo three-staged surgical palliation in the first years of life, with the last stage realizing a cross-like total cavopulmonary connection (TCPC) of superior and inferior vena cavas (SVC and IVC) with both left and right pulmonary arteries, allowing all deoxygenated blood to flow passively back to the lungs (Fontan circulation). Even though within the past decades more patients survive into adulthood, the connection comes at the prize of deficiencies such as chronic systemic venous hypertension and low cardiac output, which ultimately may lead to Fontan failure. Many studies have suggested that the TCPC's inherent insufficiencies might be addressed by adding a cavopulmonary assist device (CPAD) to provide the necessary pressure boost. While many device concepts are being explored, few take into account the complex cardiac anatomy typically associated with TCPCs. In this study, we focus on the extra cardiac conduit vascular graft connecting IVC and pulmonary arteries as one possible landing zone for a CPAD and describe its geometric variability in a cohort of 18 patients that had their TCPC realized with a 20mm vascular graft. We report traditional morphometric parameters and apply statistical shape modeling to determine the main contributors of graft shape variability. Such information may prove useful when designing CPADs that are adapted to the challenging anatomical boundaries in Fontan patients. We further compute the anatomical mean 3D graft shape (template graft) as a representative of key shape features of our cohort and prove this template graft to be a significantly better approximation of population and individual patient's hemodynamics than a commonly used simplified tube geometry. We therefore conclude that statistical shape modeling results can provide better models of geometric and hemodynamic boundary conditions associated with complex cardiac anatomy, which in turn may impact on improved cardiac device development.

Detecting global and local hippocampal shape changes in Alzheimer's disease using statistical shape models.

PubMed

Shen, Kai-kai; Fripp, Jurgen; Mériaudeau, Fabrice; Chételat, Gaël; Salvado, Olivier; Bourgeat, Pierrick

2012-02-01

The hippocampus is affected at an early stage in the development of Alzheimer's disease (AD). With the use of structural magnetic resonance (MR) imaging, we can investigate the effect of AD on the morphology of the hippocampus. The hippocampal shape variations among a population can be usually described using statistical shape models (SSMs). Conventional SSMs model the modes of variations among the population via principal component analysis (PCA). Although these modes are representative of variations within the training data, they are not necessarily discriminative on labeled data or relevant to the differences between the subpopulations. We use the shape descriptors from SSM as features to classify AD from normal control (NC) cases. In this study, a Hotelling's T2 test is performed to select a subset of landmarks which are used in PCA. The resulting variation modes are used as predictors of AD from NC. The discrimination ability of these predictors is evaluated in terms of their classification performances with bagged support vector machines (SVMs). Restricting the model to landmarks with better separation between AD and NC increases the discrimination power of SSM. The predictors extracted on the subregions also showed stronger correlation with the memory-related measurements such as Logical Memory, Auditory Verbal Learning Test (AVLT) and the memory subscores of Alzheimer Disease Assessment Scale (ADAS). Crown Copyright © 2011. Published by Elsevier Inc. All rights reserved.

Intrinsic Bayesian Active Contours for Extraction of Object Boundaries in Images

PubMed Central

Srivastava, Anuj

2010-01-01

We present a framework for incorporating prior information about high-probability shapes in the process of contour extraction and object recognition in images. Here one studies shapes as elements of an infinite-dimensional, non-linear quotient space, and statistics of shapes are defined and computed intrinsically using differential geometry of this shape space. Prior models on shapes are constructed using probability distributions on tangent bundles of shape spaces. Similar to the past work on active contours, where curves are driven by vector fields based on image gradients and roughness penalties, we incorporate the prior shape knowledge in the form of vector fields on curves. Through experimental results, we demonstrate the use of prior shape models in the estimation of object boundaries, and their success in handling partial obscuration and missing data. Furthermore, we describe the use of this framework in shape-based object recognition or classification. PMID:21076692

Detection of Single Standing Dead Trees from Aerial Color Infrared Imagery by Segmentation with Shape and Intensity Priors

NASA Astrophysics Data System (ADS)

Polewski, P.; Yao, W.; Heurich, M.; Krzystek, P.; Stilla, U.

2015-03-01

Standing dead trees, known as snags, are an essential factor in maintaining biodiversity in forest ecosystems. Combined with their role as carbon sinks, this makes for a compelling reason to study their spatial distribution. This paper presents an integrated method to detect and delineate individual dead tree crowns from color infrared aerial imagery. Our approach consists of two steps which incorporate statistical information about prior distributions of both the image intensities and the shapes of the target objects. In the first step, we perform a Gaussian Mixture Model clustering in the pixel color space with priors on the cluster means, obtaining up to 3 components corresponding to dead trees, living trees, and shadows. We then refine the dead tree regions using a level set segmentation method enriched with a generative model of the dead trees' shape distribution as well as a discriminative model of their pixel intensity distribution. The iterative application of the statistical shape template yields the set of delineated dead crowns. The prior information enforces the consistency of the template's shape variation with the shape manifold defined by manually labeled training examples, which makes it possible to separate crowns located in close proximity and prevents the formation of large crown clusters. Also, the statistical information built into the segmentation gives rise to an implicit detection scheme, because the shape template evolves towards an empty contour if not enough evidence for the object is present in the image. We test our method on 3 sample plots from the Bavarian Forest National Park with reference data obtained by manually marking individual dead tree polygons in the images. Our results are scenario-dependent and range from a correctness/completeness of 0.71/0.81 up to 0.77/1, with an average center-of-gravity displacement of 3-5 pixels between the detected and reference polygons.

Interactive lesion segmentation with shape priors from offline and online learning.

PubMed

Shepherd, Tony; Prince, Simon J D; Alexander, Daniel C

2012-09-01

In medical image segmentation, tumors and other lesions demand the highest levels of accuracy but still call for the highest levels of manual delineation. One factor holding back automatic segmentation is the exemption of pathological regions from shape modelling techniques that rely on high-level shape information not offered by lesions. This paper introduces two new statistical shape models (SSMs) that combine radial shape parameterization with machine learning techniques from the field of nonlinear time series analysis. We then develop two dynamic contour models (DCMs) using the new SSMs as shape priors for tumor and lesion segmentation. From training data, the SSMs learn the lower level shape information of boundary fluctuations, which we prove to be nevertheless highly discriminant. One of the new DCMs also uses online learning to refine the shape prior for the lesion of interest based on user interactions. Classification experiments reveal superior sensitivity and specificity of the new shape priors over those previously used to constrain DCMs. User trials with the new interactive algorithms show that the shape priors are directly responsible for improvements in accuracy and reductions in user demand.

The shaped pulses control and operation on the SG-III prototype facility

NASA Astrophysics Data System (ADS)

Ping, Li; Wei, Wang; Sai, Jin; Wanqing, Huang; Wenyi, Wang; Jingqin, Su; Runchang, Zhao

2018-04-01

The laser driven inertial confined fusion experiments require careful temporal shape control of the laser pulse. Two approaches are introduced to improve the accuracy and efficiency of the close loop feedback system for long term operation in TIL; the first one is a statistical model to analyze the variation of the parameters obtained from previous shots, the other is a matrix algorithm proposed to relate the electrical signal and the impulse amplitudes. With the model and algorithm applied in the pulse shaping in TIL, a variety of shaped pulses were produced with a 10% precision in half an hour for almost three years under different circumstance.

The Shape of a Ponytail and the Statistical Physics of Hair Fiber Bundles

NASA Astrophysics Data System (ADS)

Goldstein, Raymond E.; Warren, Patrick B.; Ball, Robin C.

2012-02-01

From Leonardo to the Brothers Grimm our fascination with hair has endured in art and science. Yet, a quantitative understanding of the shapes of a hair bundles has been lacking. Here we combine experiment and theory to propose an answer to the most basic question: What is the shape of a ponytail? A model for the shape of hair bundles is developed from the perspective of statistical physics, treating individual fibers as elastic filaments with random intrinsic curvatures. The combined effects of bending elasticity, gravity, and bundle compressibility are recast as a differential equation for the envelope of a bundle, in which the compressibility enters through an ``equation of state.'' From this, we identify the balance of forces in various regions of the ponytail, extract the equation of state from analysis of ponytail shapes, and relate the observed pressure to the measured random curvatures of individual hairs.

A Minimal Path Searching Approach for Active Shape Model (ASM)-based Segmentation of the Lung.

PubMed

Guo, Shengwen; Fei, Baowei

2009-03-27

We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 ± 0.33 pixels, while the error is 1.99 ± 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs.

A minimal path searching approach for active shape model (ASM)-based segmentation of the lung

NASA Astrophysics Data System (ADS)

Guo, Shengwen; Fei, Baowei

2009-02-01

We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 +/- 0.33 pixels, while the error is 1.99 +/- 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs.

A Minimal Path Searching Approach for Active Shape Model (ASM)-based Segmentation of the Lung

PubMed Central

Guo, Shengwen; Fei, Baowei

2013-01-01

We are developing a minimal path searching method for active shape model (ASM)-based segmentation for detection of lung boundaries on digital radiographs. With the conventional ASM method, the position and shape parameters of the model points are iteratively refined and the target points are updated by the least Mahalanobis distance criterion. We propose an improved searching strategy that extends the searching points in a fan-shape region instead of along the normal direction. A minimal path (MP) deformable model is applied to drive the searching procedure. A statistical shape prior model is incorporated into the segmentation. In order to keep the smoothness of the shape, a smooth constraint is employed to the deformable model. To quantitatively assess the ASM-MP segmentation, we compare the automatic segmentation with manual segmentation for 72 lung digitized radiographs. The distance error between the ASM-MP and manual segmentation is 1.75 ± 0.33 pixels, while the error is 1.99 ± 0.45 pixels for the ASM. Our results demonstrate that our ASM-MP method can accurately segment the lung on digital radiographs. PMID:24386531

Online Statistical Modeling (Regression Analysis) for Independent Responses

NASA Astrophysics Data System (ADS)

Made Tirta, I.; Anggraeni, Dian; Pandutama, Martinus

2017-06-01

Regression analysis (statistical analmodelling) are among statistical methods which are frequently needed in analyzing quantitative data, especially to model relationship between response and explanatory variables. Nowadays, statistical models have been developed into various directions to model various type and complex relationship of data. Rich varieties of advanced and recent statistical modelling are mostly available on open source software (one of them is R). However, these advanced statistical modelling, are not very friendly to novice R users, since they are based on programming script or command line interface. Our research aims to developed web interface (based on R and shiny), so that most recent and advanced statistical modelling are readily available, accessible and applicable on web. We have previously made interface in the form of e-tutorial for several modern and advanced statistical modelling on R especially for independent responses (including linear models/LM, generalized linier models/GLM, generalized additive model/GAM and generalized additive model for location scale and shape/GAMLSS). In this research we unified them in the form of data analysis, including model using Computer Intensive Statistics (Bootstrap and Markov Chain Monte Carlo/ MCMC). All are readily accessible on our online Virtual Statistics Laboratory. The web (interface) make the statistical modeling becomes easier to apply and easier to compare them in order to find the most appropriate model for the data.

Shape prior modeling using sparse representation and online dictionary learning.

PubMed

Zhang, Shaoting; Zhan, Yiqiang; Zhou, Yan; Uzunbas, Mustafa; Metaxas, Dimitris N

2012-01-01

The recently proposed sparse shape composition (SSC) opens a new avenue for shape prior modeling. Instead of assuming any parametric model of shape statistics, SSC incorporates shape priors on-the-fly by approximating a shape instance (usually derived from appearance cues) by a sparse combination of shapes in a training repository. Theoretically, one can increase the modeling capability of SSC by including as many training shapes in the repository. However, this strategy confronts two limitations in practice. First, since SSC involves an iterative sparse optimization at run-time, the more shape instances contained in the repository, the less run-time efficiency SSC has. Therefore, a compact and informative shape dictionary is preferred to a large shape repository. Second, in medical imaging applications, training shapes seldom come in one batch. It is very time consuming and sometimes infeasible to reconstruct the shape dictionary every time new training shapes appear. In this paper, we propose an online learning method to address these two limitations. Our method starts from constructing an initial shape dictionary using the K-SVD algorithm. When new training shapes come, instead of re-constructing the dictionary from the ground up, we update the existing one using a block-coordinates descent approach. Using the dynamically updated dictionary, sparse shape composition can be gracefully scaled up to model shape priors from a large number of training shapes without sacrificing run-time efficiency. Our method is validated on lung localization in X-Ray and cardiac segmentation in MRI time series. Compared to the original SSC, it shows comparable performance while being significantly more efficient.

Global statistics of microphysical properties of cloud-top ice crystals

NASA Astrophysics Data System (ADS)

van Diedenhoven, B.; Fridlind, A. M.; Cairns, B.; Ackerman, A. S.; Riedi, J.

2017-12-01

Ice crystals in clouds are highly complex. Their sizes, macroscale shape (i.e., habit), mesoscale shape (i.e., aspect ratio of components) and microscale shape (i.e., surface roughness) determine optical properties and affect physical properties such as fall speeds, growth rates and aggregation efficiency. Our current understanding on the formation and evolution of ice crystals under various conditions can be considered poor. Commonly, ice crystal size and shape are related to ambient temperature and humidity, but global observational statistics on the variation of ice crystal size and particularly shape have not been available. Here we show results of a project aiming to infer ice crystal size, shape and scattering properties from a combination of MODIS measurements and POLDER-PARASOL multi-angle polarimetry. The shape retrieval procedure infers the mean aspect ratios of components of ice crystals and the mean microscale surface roughness levels, which are quantifiable parameters that mostly affect the scattering properties, in contrast to "habit". We present global statistics on the variation of ice effective radius, component aspect ratio, microscale surface roughness and scattering asymmetry parameter as a function of cloud top temperature, latitude, location, cloud type, season, etc. Generally, with increasing height, sizes decrease, roughness increases, asymmetry parameters decrease and aspect ratios increase towards unity. Some systematic differences are observed for clouds warmer and colder than the homogeneous freezing level. Uncertainties in the retrievals will be discussed. These statistics can be used as observational targets for modeling efforts and to better constrain other satellite remote sensing applications and their uncertainties.

Global Statistics of Microphysical Properties of Cloud-Top Ice Crystals

NASA Technical Reports Server (NTRS)

Van Diedenhoven, Bastiaan; Fridlind, Ann; Cairns, Brian; Ackerman, Andrew; Riedl, Jerome

2017-01-01

Ice crystals in clouds are highly complex. Their sizes, macroscale shape (i.e., habit), mesoscale shape (i.e., aspect ratio of components) and microscale shape (i.e., surface roughness) determine optical properties and affect physical properties such as fall speeds, growth rates and aggregation efficiency. Our current understanding on the formation and evolution of ice crystals under various conditions can be considered poor. Commonly, ice crystal size and shape are related to ambient temperature and humidity, but global observational statistics on the variation of ice crystal size and particularly shape have not been available. Here we show results of a project aiming to infer ice crystal size, shape and scattering properties from a combination of MODIS measurements and POLDER-PARASOL multi-angle polarimetry. The shape retrieval procedure infers the mean aspect ratios of components of ice crystals and the mean microscale surface roughness levels, which are quantifiable parameters that mostly affect the scattering properties, in contrast to a habit. We present global statistics on the variation of ice effective radius, component aspect ratio, microscale surface roughness and scattering asymmetry parameter as a function of cloud top temperature, latitude, location, cloud type, season, etc. Generally, with increasing height, sizes decrease, roughness increases, asymmetry parameters decrease and aspect ratios increase towards unity. Some systematic differences are observed for clouds warmer and colder than the homogeneous freezing level. Uncertainties in the retrievals will be discussed. These statistics can be used as observational targets for modeling efforts and to better constrain other satellite remote sensing applications and their uncertainties.

Weighted regularized statistical shape space projection for breast 3D model reconstruction.

PubMed

Ruiz, Guillermo; Ramon, Eduard; García, Jaime; Sukno, Federico M; Ballester, Miguel A González

2018-07-01

The use of 3D imaging has increased as a practical and useful tool for plastic and aesthetic surgery planning. Specifically, the possibility of representing the patient breast anatomy in a 3D shape and simulate aesthetic or plastic procedures is a great tool for communication between surgeon and patient during surgery planning. For the purpose of obtaining the specific 3D model of the breast of a patient, model-based reconstruction methods can be used. In particular, 3D morphable models (3DMM) are a robust and widely used method to perform 3D reconstruction. However, if additional prior information (i.e., known landmarks) is combined with the 3DMM statistical model, shape constraints can be imposed to improve the 3DMM fitting accuracy. In this paper, we present a framework to fit a 3DMM of the breast to two possible inputs: 2D photos and 3D point clouds (scans). Our method consists in a Weighted Regularized (WR) projection into the shape space. The contribution of each point in the 3DMM shape is weighted allowing to assign more relevance to those points that we want to impose as constraints. Our method is applied at multiple stages of the 3D reconstruction process. Firstly, it can be used to obtain a 3DMM initialization from a sparse set of 3D points. Additionally, we embed our method in the 3DMM fitting process in which more reliable or already known 3D points or regions of points, can be weighted in order to preserve their shape information. The proposed method has been tested in two different input settings: scans and 2D pictures assessing both reconstruction frameworks with very positive results. Copyright © 2018 Elsevier B.V. All rights reserved.

Detecting the subtle shape differences in hemodynamic responses at the group level

PubMed Central

Chen, Gang; Saad, Ziad S.; Adleman, Nancy E.; Leibenluft, Ellen; Cox, Robert W.

2015-01-01

The nature of the hemodynamic response (HDR) is still not fully understood due to the multifaceted processes involved. Aside from the overall amplitude, the response may vary across cognitive states, tasks, brain regions, and subjects with respect to characteristics such as rise and fall speed, peak duration, undershoot shape, and overall duration. Here we demonstrate that the fixed-shape (FSM) or adjusted-shape (ASM) methods may fail to detect some shape subtleties (e.g., speed of rise or recovery, or undershoot). In contrast, the estimated-shape method (ESM) through multiple basis functions can provide the opportunity to identify some subtle shape differences and achieve higher statistical power at both individual and group levels. Previously, some dimension reduction approaches focused on the peak magnitude, or made inferences based on the area under the curve (AUC) or interaction, which can lead to potential misidentifications. By adopting a generic framework of multivariate modeling (MVM), we showcase a hybrid approach that is validated by simulations and real data. With the whole HDR shape integrity maintained as input at the group level, the approach allows the investigator to substantiate these more nuanced effects through the unique HDR shape features. Unlike the few analyses that were limited to main effect, two- or three-way interactions, we extend the modeling approach to an inclusive platform that is more adaptable than the conventional GLM. With multiple effect estimates from ESM for each condition, linear mixed-effects (LME) modeling should be used at the group level when there is only one group of subjects without any other explanatory variables. Under other situations, an approximate approach through dimension reduction within the MVM framework can be adopted to achieve a practical equipoise among representation, false positive control, statistical power, and modeling flexibility. The associated program 3dMVM is publicly available as part of the AFNI suite. PMID:26578853

Joint Clustering and Component Analysis of Correspondenceless Point Sets: Application to Cardiac Statistical Modeling.

PubMed

Gooya, Ali; Lekadir, Karim; Alba, Xenia; Swift, Andrew J; Wild, Jim M; Frangi, Alejandro F

2015-01-01

Construction of Statistical Shape Models (SSMs) from arbitrary point sets is a challenging problem due to significant shape variation and lack of explicit point correspondence across the training data set. In medical imaging, point sets can generally represent different shape classes that span healthy and pathological exemplars. In such cases, the constructed SSM may not generalize well, largely because the probability density function (pdf) of the point sets deviates from the underlying assumption of Gaussian statistics. To this end, we propose a generative model for unsupervised learning of the pdf of point sets as a mixture of distinctive classes. A Variational Bayesian (VB) method is proposed for making joint inferences on the labels of point sets, and the principal modes of variations in each cluster. The method provides a flexible framework to handle point sets with no explicit point-to-point correspondences. We also show that by maximizing the marginalized likelihood of the model, the optimal number of clusters of point sets can be determined. We illustrate this work in the context of understanding the anatomical phenotype of the left and right ventricles in heart. To this end, we use a database containing hearts of healthy subjects, patients with Pulmonary Hypertension (PH), and patients with Hypertrophic Cardiomyopathy (HCM). We demonstrate that our method can outperform traditional PCA in both generalization and specificity measures.

Estimation of Mouse Organ Locations Through Registration of a Statistical Mouse Atlas With Micro-CT Images

PubMed Central

Stout, David B.; Chatziioannou, Arion F.

2012-01-01

Micro-CT is widely used in preclinical studies of small animals. Due to the low soft-tissue contrast in typical studies, segmentation of soft tissue organs from noncontrast enhanced micro-CT images is a challenging problem. Here, we propose an atlas-based approach for estimating the major organs in mouse micro-CT images. A statistical atlas of major trunk organs was constructed based on 45 training subjects. The statistical shape model technique was used to include inter-subject anatomical variations. The shape correlations between different organs were described using a conditional Gaussian model. For registration, first the high-contrast organs in micro-CT images were registered by fitting the statistical shape model, while the low-contrast organs were subsequently estimated from the high-contrast organs using the conditional Gaussian model. The registration accuracy was validated based on 23 noncontrast-enhanced and 45 contrast-enhanced micro-CT images. Three different accuracy metrics (Dice coefficient, organ volume recovery coefficient, and surface distance) were used for evaluation. The Dice coefficients vary from 0.45 ± 0.18 for the spleen to 0.90 ± 0.02 for the lungs, the volume recovery coefficients vary from for the liver to 1.30 ± 0.75 for the spleen, the surface distances vary from 0.18 ± 0.01 mm for the lungs to 0.72 ± 0.42 mm for the spleen. The registration accuracy of the statistical atlas was compared with two publicly available single-subject mouse atlases, i.e., the MOBY phantom and the DIGIMOUSE atlas, and the results proved that the statistical atlas is more accurate than the single atlases. To evaluate the influence of the training subject size, different numbers of training subjects were used for atlas construction and registration. The results showed an improvement of the registration accuracy when more training subjects were used for the atlas construction. The statistical atlas-based registration was also compared with the thin-plate spline based deformable registration, commonly used in mouse atlas registration. The results revealed that the statistical atlas has the advantage of improving the estimation of low-contrast organs. PMID:21859613

Reconstructing liver shape and position from MR image slices using an active shape model

NASA Astrophysics Data System (ADS)

Fenchel, Matthias; Thesen, Stefan; Schilling, Andreas

2008-03-01

We present an algorithm for fully automatic reconstruction of 3D position, orientation and shape of the human liver from a sparsely covering set of n 2D MR slice images. Reconstructing the shape of an organ from slice images can be used for scan planning, for surgical planning or other purposes where 3D anatomical knowledge has to be inferred from sparse slices. The algorithm is based on adapting an active shape model of the liver surface to a given set of slice images. The active shape model is created from a training set of liver segmentations from a group of volunteers. The training set is set up with semi-manual segmentations of T1-weighted volumetric MR images. Searching for the optimal shape model that best fits to the image data is done by maximizing a similarity measure based on local appearance at the surface. Two different algorithms for the active shape model search are proposed and compared: both algorithms seek to maximize the a-posteriori probability of the grey level appearance around the surface while constraining the surface to the space of valid shapes. The first algorithm works by using grey value profile statistics in normal direction. The second algorithm uses average and variance images to calculate the local surface appearance on the fly. Both algorithms are validated by fitting the active shape model to abdominal 2D slice images and comparing the shapes, which have been reconstructed, to the manual segmentations and to the results of active shape model searches from 3D image data. The results turn out to be promising and competitive to active shape model segmentations from 3D data.

Segmentation of knee cartilage by using a hierarchical active shape model based on multi-resolution transforms in magnetic resonance images

NASA Astrophysics Data System (ADS)

León, Madeleine; Escalante-Ramirez, Boris

2013-11-01

Knee osteoarthritis (OA) is characterized by the morphological degeneration of cartilage. Efficient segmentation of cartilage is important for cartilage damage diagnosis and to support therapeutic responses. We present a method for knee cartilage segmentation in magnetic resonance images (MRI). Our method incorporates the Hermite Transform to obtain a hierarchical decomposition of contours which describe knee cartilage shapes. Then, we compute a statistical model of the contour of interest from a set of training images. Thereby, our Hierarchical Active Shape Model (HASM) captures a large range of shape variability even from a small group of training samples, improving segmentation accuracy. The method was trained with a training set of 16- MRI of knee and tested with leave-one-out method.

Heavy residues from very mass asymmetric heavy ion reactions

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

Hanold, Karl Alan

1994-08-01

The isotopic production cross sections and momenta of all residues with nuclear charge (Z) greater than 39 from the reaction of 26, 40, and 50 MeV/nucleon 129Xe + Be, C, and Al were measured. The isotopic cross sections, the momentum distribution for each isotope, and the cross section as a function of nuclear charge and momentum are presented here. The new cross sections are consistent with previous measurements of the cross sections from similar reaction systems. The shape of the cross section distribution, when considered as a function of Z and velocity, was found to be qualitatively consistent with thatmore » expected from an incomplete fusion reaction mechanism. An incomplete fusion model coupled to a statistical decay model is able to reproduce many features of these reactions: the shapes of the elemental cross section distributions, the emission velocity distributions for the intermediate mass fragments, and the Z versus velocity distributions. This model gives a less satisfactory prediction of the momentum distribution for each isotope. A very different model based on the Boltzman-Nordheim-Vlasov equation and which was also coupled to a statistical decay model reproduces many features of these reactions: the shapes of the elemental cross section distributions, the intermediate mass fragment emission velocity distributions, and the Z versus momentum distributions. Both model calculations over-estimate the average mass for each element by two mass units and underestimate the isotopic and isobaric widths of the experimental distributions. It is shown that the predicted average mass for each element can be brought into agreement with the data by small, but systematic, variation of the particle emission barriers used in the statistical model. The predicted isotopic and isobaric widths of the cross section distributions can not be brought into agreement with the experimental data using reasonable parameters for the statistical model.« less

Why Income Comparison is Rational

NASA Technical Reports Server (NTRS)

Wolpert, David H.

2010-01-01

A major factor affecting a person s happiness is the gap between their income and their neighbors , independent of their own income. This effect is strongest when the neighbor has moderately higher income. In addition a person s lifetime happiness often follows a "U" shape. Previous models have explained subsets of these phenomena, typically assuming the person has limited ability to assess their own (hedonic) utility. Here I present a model that explains all the phenomena, without such assumptions. In this model greater income of your neighbor is statistical data that, if carefully analyzed, would recommend that you explore for a new income-generating strategy. This explains unhappiness that your neighbor has greater income, as an emotional "prod" that induces you to explore, in accord with careful statistical analysis. It explains the "U" shape of happiness similarly. Another benefit of this model is that it makes many falsifiable predictions.

Anatomical shape analysis of the mandible in Caucasian and Chinese for the production of preformed mandible reconstruction plates.

PubMed

Metzger, Marc C; Vogel, Mathias; Hohlweg-Majert, Bettina; Mast, Hansjörg; Fan, Xianqun; Rüdell, Alexandra; Schlager, Stefan

2011-09-01

The purpose of this study was to evaluate and analyze statistical shapes of the outer mandible contour of Caucasian and Chinese people, offering data for the production of preformed mandible reconstruction plates. A CT-database of 925 Caucasians (male: n=463, female: n=462) and 960 Chinese (male: n=469, female: n=491) including scans of unaffected mandibles were used and imported into the 3D modeling software Voxim (IVS-Solutions, Chemnitz, Germany). Anatomical landmarks (n=22 points for both sides) were set using the 3D view along the outer contour of the mandible at the area where reconstruction plates are commonly located. We used morphometric methods for statistical shape analysis. We found statistical relevant differences between populations including a distinct discrimination given by the landmarks at the mandible. After generating a metric model this shape information which separated the populations appeared to be of no clinical relevance. The metric size information given by ramus length however provided a profound base for the production of standard reconstruction plates. Clustering by ramus length into three sizes and calculating means of these size-clusters seem to be a good solution for constructing preformed reconstruction plates that will fit a vast majority. Copyright © 2010 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

Simulation of parametric model towards the fixed covariate of right censored lung cancer data

NASA Astrophysics Data System (ADS)

Afiqah Muhamad Jamil, Siti; Asrul Affendi Abdullah, M.; Kek, Sie Long; Ridwan Olaniran, Oyebayo; Enera Amran, Syahila

2017-09-01

In this study, simulation procedure was applied to measure the fixed covariate of right censored data by using parametric survival model. The scale and shape parameter were modified to differentiate the analysis of parametric regression survival model. Statistically, the biases, mean biases and the coverage probability were used in this analysis. Consequently, different sample sizes were employed to distinguish the impact of parametric regression model towards right censored data with 50, 100, 150 and 200 number of sample. R-statistical software was utilised to develop the coding simulation with right censored data. Besides, the final model of right censored simulation was compared with the right censored lung cancer data in Malaysia. It was found that different values of shape and scale parameter with different sample size, help to improve the simulation strategy for right censored data and Weibull regression survival model is suitable fit towards the simulation of survival of lung cancer patients data in Malaysia.

YORP effect on real objects. I. Statistical properties

NASA Astrophysics Data System (ADS)

Micheli, M.; Paolicchi, P.

2008-10-01

Context: The intensity of the YORP (Yarkovsky, O'Keefe, Radzievskii, and Paddack) effect and its ability to affect the rotational properties of asteroids depend mainly on the size of the body and on its shape. At present, we have a database of about 30 well-defined shapes of real minor bodies (most of them asteroids, but also planetary satellites and cometary nuclei). Aims: In this paper we perform a statistical analysis of how the YORP effect depends on the shape. Methods: We used the Rubincam approximation (i.e. neglecting the effects of a finite thermal conductivity). Results: We show that, among real bodies, the distribution of the YORP types, according to the classification of Vokrouhlický and Čapek, is significantly different from the one obtained in the same paper from theoretical modeling of shapes. A new “type” also comes out. Moreover, we show that the types are strongly correlated with the intensity of the YORP effect (when normalized to eliminate the dependence on the size, and thus only related to the shape).

Variations in Hip Shape Are Associated with Radiographic Knee Osteoarthritis: Cross-sectional and Longitudinal Analyses of the Johnston County Osteoarthritis Project.

PubMed

Nelson, Amanda E; Golightly, Yvonne M; Renner, Jordan B; Schwartz, Todd A; Liu, Felix; Lynch, John A; Gregory, Jenny S; Aspden, Richard M; Lane, Nancy E; Jordan, Joanne M

2016-02-01

Hip shape by statistical shape modeling (SSM) is associated with hip radiographic osteoarthritis (rOA). We examined associations between hip shape and knee rOA given the biomechanical interrelationships between these joints. Bilateral baseline hip shape assessments [for those with at least 1 hip with a Kellgren-Lawrence arthritis grading scale (KL) 0 or 1] from the Johnston County Osteoarthritis Project were available. Proximal femur shape was defined on baseline pelvis radiographs and evaluated by SSM, producing mean shape and continuous variables representing independent modes of variation (14 modes = 95% of shape variance). Outcomes included prevalent [baseline KL ≥ 2 or total knee replacement (TKR)], incident (baseline KL 0/1 with followup ≥ 2), and progressive knee rOA (KL increase of ≥ 1 or TKR). Limb-based logistic regression models for ipsilateral and contralateral comparisons were adjusted for age, sex, race, body mass index (BMI), and hip rOA, accounting for intraperson correlations. We evaluated 681 hips and 682 knees from 342 individuals (61% women, 83% white, mean age 62 yrs, BMI 29 kg/m(2)). Ninety-nine knees (15%) had prevalent rOA (4 knees with TKR). Lower modes 2 and 3 scores were associated with ipsilateral prevalent knee rOA, and only lower mode 3 scores were associated with contralateral prevalent knee rOA. No statistically significant associations were seen for incident or progressive knee rOA. Variations in hip shape were associated with prevalent, but not incident or progressive, knee rOA in this cohort, and may reflect biomechanical differences between limbs, genetic influences, or common factors related to both hip shape and knee rOA.

A stochastic model for early placental development†

PubMed Central

Cotter, Simon L.; Klika, Václav; Kimpton, Laura; Collins, Sally; Heazell, Alexander E. P.

2014-01-01

In the human, placental structure is closely related to placental function and consequent pregnancy outcome. Studies have noted abnormal placental shape in small-for-gestational-age infants which extends to increased lifetime risk of cardiovascular disease. The origins and determinants of placental shape are incompletely understood and are difficult to study in vivo. In this paper, we model the early development of the human placenta, based on the hypothesis that this is driven by a chemoattractant effect emanating from proximal spiral arteries in the decidua. We derive and explore a two-dimensional stochastic model, and investigate the effects of loss of spiral arteries in regions near to the cord insertion on the shape of the placenta. This model demonstrates that disruption of spiral arteries can exert profound effects on placental shape, particularly if this is close to the cord insertion. Thus, placental shape reflects the underlying maternal vascular bed. Abnormal placental shape may reflect an abnormal uterine environment, predisposing to pregnancy complications. Through statistical analysis of model placentas, we are able to characterize the probability that a given placenta grew in a disrupted environment, and even able to distinguish between different disruptions. PMID:24850904

Quantification of localized vertebral deformities using a sparse wavelet-based shape model.

PubMed

Zewail, R; Elsafi, A; Durdle, N

2008-01-01

Medical experts often examine hundreds of spine x-ray images to determine existence of various pathologies. Common pathologies of interest are anterior osteophites, disc space narrowing, and wedging. By careful inspection of the outline shapes of the vertebral bodies, experts are able to identify and assess vertebral abnormalities with respect to the pathology under investigation. In this paper, we present a novel method for quantification of vertebral deformation using a sparse shape model. Using wavelets and Independent component analysis (ICA), we construct a sparse shape model that benefits from the approximation power of wavelets and the capability of ICA to capture higher order statistics in wavelet space. The new model is able to capture localized pathology-related shape deformations, hence it allows for quantification of vertebral shape variations. We investigate the capability of the model to predict localized pathology related deformations. Next, using support-vector machines, we demonstrate the diagnostic capabilities of the method through the discrimination of anterior osteophites in lumbar vertebrae. Experiments were conducted using a set of 150 contours from digital x-ray images of lumbar spine. Each vertebra is labeled as normal or abnormal. Results reported in this work focus on anterior osteophites as the pathology of interest.

Fully automatic segmentation of the femur from 3D-CT images using primitive shape recognition and statistical shape models.

PubMed

Ben Younes, Lassad; Nakajima, Yoshikazu; Saito, Toki

2014-03-01

Femur segmentation is well established and widely used in computer-assisted orthopedic surgery. However, most of the robust segmentation methods such as statistical shape models (SSM) require human intervention to provide an initial position for the SSM. In this paper, we propose to overcome this problem and provide a fully automatic femur segmentation method for CT images based on primitive shape recognition and SSM. Femur segmentation in CT scans was performed using primitive shape recognition based on a robust algorithm such as the Hough transform and RANdom SAmple Consensus. The proposed method is divided into 3 steps: (1) detection of the femoral head as sphere and the femoral shaft as cylinder in the SSM and the CT images, (2) rigid registration between primitives of SSM and CT image to initialize the SSM into the CT image, and (3) fitting of the SSM to the CT image edge using an affine transformation followed by a nonlinear fitting. The automated method provided good results even with a high number of outliers. The difference of segmentation error between the proposed automatic initialization method and a manual initialization method is less than 1 mm. The proposed method detects primitive shape position to initialize the SSM into the target image. Based on primitive shapes, this method overcomes the problem of inter-patient variability. Moreover, the results demonstrate that our method of primitive shape recognition can be used for 3D SSM initialization to achieve fully automatic segmentation of the femur.

Quantitative gene-gene and gene-environment mapping for leaf shape variation using tree-based models.

PubMed

Fu, Guifang; Dai, Xiaotian; Symanzik, Jürgen; Bushman, Shaun

2017-01-01

Leaf shape traits have long been a focus of many disciplines, but the complex genetic and environmental interactive mechanisms regulating leaf shape variation have not yet been investigated in detail. The question of the respective roles of genes and environment and how they interact to modulate leaf shape is a thorny evolutionary problem, and sophisticated methodology is needed to address it. In this study, we investigated a framework-level approach that inputs shape image photographs and genetic and environmental data, and then outputs the relative importance ranks of all variables after integrating shape feature extraction, dimension reduction, and tree-based statistical models. The power of the proposed framework was confirmed by simulation and a Populus szechuanica var. tibetica data set. This new methodology resulted in the detection of novel shape characteristics, and also confirmed some previous findings. The quantitative modeling of a combination of polygenetic, plastic, epistatic, and gene-environment interactive effects, as investigated in this study, will improve the discernment of quantitative leaf shape characteristics, and the methods are ready to be applied to other leaf morphology data sets. Unlike the majority of approaches in the quantitative leaf shape literature, this framework-level approach is data-driven, without assuming any pre-known shape attributes, landmarks, or model structures. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

The beta distribution: A statistical model for world cloud cover

NASA Technical Reports Server (NTRS)

Falls, L. W.

1973-01-01

Much work has been performed in developing empirical global cloud cover models. This investigation was made to determine an underlying theoretical statistical distribution to represent worldwide cloud cover. The beta distribution with probability density function is given to represent the variability of this random variable. It is shown that the beta distribution possesses the versatile statistical characteristics necessary to assume the wide variety of shapes exhibited by cloud cover. A total of 160 representative empirical cloud cover distributions were investigated and the conclusion was reached that this study provides sufficient statical evidence to accept the beta probability distribution as the underlying model for world cloud cover.

Improved biovolume estimation of Microcystis aeruginosa colonies: A statistical approach.

PubMed

Alcántara, I; Piccini, C; Segura, A M; Deus, S; González, C; Martínez de la Escalera, G; Kruk, C

2018-05-27

The Microcystis aeruginosa complex (MAC) clusters many of the most common freshwater and brackish bloom-forming cyanobacteria. In monitoring protocols, biovolume estimation is a common approach to determine MAC colonies biomass and useful for prediction purposes. Biovolume (μm 3 mL -1 ) is calculated multiplying organism abundance (orgL -1 ) by colonial volume (μm 3 org -1 ). Colonial volume is estimated based on geometric shapes and requires accurate measurements of dimensions using optical microscopy. A trade-off between easy-to-measure but low-accuracy simple shapes (e.g. sphere) and time costly but high-accuracy complex shapes (e.g. ellipsoid) volume estimation is posed. Overestimations effects in ecological studies and management decisions associated to harmful blooms are significant due to the large sizes of MAC colonies. In this work, we aimed to increase the precision of MAC biovolume estimations by developing a statistical model based on two easy-to-measure dimensions. We analyzed field data from a wide environmental gradient (800 km) spanning freshwater to estuarine and seawater. We measured length, width and depth from ca. 5700 colonies under an inverted microscope and estimated colonial volume using three different recommended geometrical shapes (sphere, prolate spheroid and ellipsoid). Because of the non-spherical shape of MAC the ellipsoid resulted in the most accurate approximation, whereas the sphere overestimated colonial volume (3-80) especially for large colonies (MLD higher than 300 μm). Ellipsoid requires measuring three dimensions and is time-consuming. Therefore, we constructed different statistical models to predict organisms depth based on length and width. Splitting the data into training (2/3) and test (1/3) sets, all models resulted in low training (1.41-1.44%) and testing average error (1.3-2.0%). The models were also evaluated using three other independent datasets. The multiple linear model was finally selected to calculate MAC volume as an ellipsoid based on length and width. This work contributes to achieve a better estimation of MAC volume applicable to monitoring programs as well as to ecological research. Copyright © 2017. Published by Elsevier B.V.

Active shape models unleashed

NASA Astrophysics Data System (ADS)

Kirschner, Matthias; Wesarg, Stefan

2011-03-01

Active Shape Models (ASMs) are a popular family of segmentation algorithms which combine local appearance models for boundary detection with a statistical shape model (SSM). They are especially popular in medical imaging due to their ability for fast and accurate segmentation of anatomical structures even in large and noisy 3D images. A well-known limitation of ASMs is that the shape constraints are over-restrictive, because the segmentations are bounded by the Principal Component Analysis (PCA) subspace learned from the training data. To overcome this limitation, we propose a new energy minimization approach which combines an external image energy with an internal shape model energy. Our shape energy uses the Distance From Feature Space (DFFS) concept to allow deviations from the PCA subspace in a theoretically sound and computationally fast way. In contrast to previous approaches, our model does not rely on post-processing with constrained free-form deformation or additional complex local energy models. In addition to the energy minimization approach, we propose a new method for liver detection, a new method for initializing an SSM and an improved k-Nearest Neighbour (kNN)-classifier for boundary detection. Our ASM is evaluated with leave-one-out tests on a data set with 34 tomographic CT scans of the liver and is compared to an ASM with standard shape constraints. The quantitative results of our experiments show that we achieve higher segmentation accuracy with our energy minimization approach than with standard shape constraints.nym

Superordinate Shape Classification Using Natural Shape Statistics

ERIC Educational Resources Information Center

Wilder, John; Feldman, Jacob; Singh, Manish

2011-01-01

This paper investigates the classification of shapes into broad natural categories such as "animal" or "leaf". We asked whether such coarse classifications can be achieved by a simple statistical classification of the shape skeleton. We surveyed databases of natural shapes, extracting shape skeletons and tabulating their…

Linking Mechanics and Statistics in Epidermal Tissues

NASA Astrophysics Data System (ADS)

Kim, Sangwoo; Hilgenfeldt, Sascha

2015-03-01

Disordered cellular structures, such as foams, polycrystals, or living tissues, can be characterized by quantitative measurements of domain size and topology. In recent work, we showed that correlations between size and topology in 2D systems are sensitive to the shape (eccentricity) of the individual domains: From a local model of neighbor relations, we derived an analytical justification for the famous empirical Lewis law, confirming the theory with experimental data from cucumber epidermal tissue. Here, we go beyond this purely geometrical model and identify mechanical properties of the tissue as the root cause for the domain eccentricity and thus the statistics of tissue structure. The simple model approach is based on the minimization of an interfacial energy functional. Simulations with Surface Evolver show that the domain statistics depend on a single mechanical parameter, while parameter fluctuations from cell to cell play an important role in simultaneously explaining the shape distribution of cells. The simulations are in excellent agreement with experiments and analytical theory, and establish a general link between the mechanical properties of a tissue and its structure. The model is relevant to diagnostic applications in a variety of animal and plant tissues.

Virtual reconstruction of glenoid bone defects using a statistical shape model.

PubMed

Plessers, Katrien; Vanden Berghe, Peter; Van Dijck, Christophe; Wirix-Speetjens, Roel; Debeer, Philippe; Jonkers, Ilse; Vander Sloten, Jos

2018-01-01

Description of the native shape of a glenoid helps surgeons to preoperatively plan the position of a shoulder implant. A statistical shape model (SSM) can be used to virtually reconstruct a glenoid bone defect and to predict the inclination, version, and center position of the native glenoid. An SSM-based reconstruction method has already been developed for acetabular bone reconstruction. The goal of this study was to evaluate the SSM-based method for the reconstruction of glenoid bone defects and the prediction of native anatomic parameters. First, an SSM was created on the basis of 66 healthy scapulae. Then, artificial bone defects were created in all scapulae and reconstructed using the SSM-based reconstruction method. For each bone defect, the reconstructed surface was compared with the original surface. Furthermore, the inclination, version, and glenoid center point of the reconstructed surface were compared with the original parameters of each scapula. For small glenoid bone defects, the healthy surface of the glenoid was reconstructed with a root mean square error of 1.2 ± 0.4 mm. Inclination, version, and glenoid center point were predicted with an accuracy of 2.4° ± 2.1°, 2.9° ± 2.2°, and 1.8 ± 0.8 mm, respectively. The SSM-based reconstruction method is able to accurately reconstruct the native glenoid surface and to predict the native anatomic parameters. Based on this outcome, statistical shape modeling can be considered a successful technique for use in the preoperative planning of shoulder arthroplasty. Copyright © 2017 Journal of Shoulder and Elbow Surgery Board of Trustees. Published by Elsevier Inc. All rights reserved.

On the statistical distribution in a deformed solid

NASA Astrophysics Data System (ADS)

Gorobei, N. N.; Luk'yanenko, A. S.

2017-09-01

A modification of the Gibbs distribution in a thermally insulated mechanically deformed solid, where its linear dimensions (shape parameters) are excluded from statistical averaging and included among the macroscopic parameters of state alongside with the temperature, is proposed. Formally, this modification is reduced to corresponding additional conditions when calculating the statistical sum. The shape parameters and the temperature themselves are found from the conditions of mechanical and thermal equilibria of a body, and their change is determined using the first law of thermodynamics. Known thermodynamic phenomena are analyzed for the simple model of a solid, i.e., an ensemble of anharmonic oscillators, within the proposed formalism with an accuracy of up to the first order by the anharmonicity constant. The distribution modification is considered for the classic and quantum temperature regions apart.

Sparse approximation of currents for statistics on curves and surfaces.

PubMed

Durrleman, Stanley; Pennec, Xavier; Trouvé, Alain; Ayache, Nicholas

2008-01-01

Computing, processing, visualizing statistics on shapes like curves or surfaces is a real challenge with many applications ranging from medical image analysis to computational geometry. Modelling such geometrical primitives with currents avoids feature-based approach as well as point-correspondence method. This framework has been proved to be powerful to register brain surfaces or to measure geometrical invariants. However, if the state-of-the-art methods perform efficiently pairwise registrations, new numerical schemes are required to process groupwise statistics due to an increasing complexity when the size of the database is growing. Statistics such as mean and principal modes of a set of shapes often have a heavy and highly redundant representation. We propose therefore to find an adapted basis on which mean and principal modes have a sparse decomposition. Besides the computational improvement, this sparse representation offers a way to visualize and interpret statistics on currents. Experiments show the relevance of the approach on 34 sets of 70 sulcal lines and on 50 sets of 10 meshes of deep brain structures.

The crossing statistic: dealing with unknown errors in the dispersion of Type Ia supernovae

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

Shafieloo, Arman; Clifton, Timothy; Ferreira, Pedro, E-mail: arman@ewha.ac.kr, E-mail: tclifton@astro.ox.ac.uk, E-mail: p.ferreira1@physics.ox.ac.uk

2011-08-01

We propose a new statistic that has been designed to be used in situations where the intrinsic dispersion of a data set is not well known: The Crossing Statistic. This statistic is in general less sensitive than χ{sup 2} to the intrinsic dispersion of the data, and hence allows us to make progress in distinguishing between different models using goodness of fit to the data even when the errors involved are poorly understood. The proposed statistic makes use of the shape and trends of a model's predictions in a quantifiable manner. It is applicable to a variety of circumstances, althoughmore » we consider it to be especially well suited to the task of distinguishing between different cosmological models using type Ia supernovae. We show that this statistic can easily distinguish between different models in cases where the χ{sup 2} statistic fails. We also show that the last mode of the Crossing Statistic is identical to χ{sup 2}, so that it can be considered as a generalization of χ{sup 2}.« less

3D automatic anatomy recognition based on iterative graph-cut-ASM

NASA Astrophysics Data System (ADS)

Chen, Xinjian; Udupa, Jayaram K.; Bagci, Ulas; Alavi, Abass; Torigian, Drew A.

2010-02-01

We call the computerized assistive process of recognizing, delineating, and quantifying organs and tissue regions in medical imaging, occurring automatically during clinical image interpretation, automatic anatomy recognition (AAR). The AAR system we are developing includes five main parts: model building, object recognition, object delineation, pathology detection, and organ system quantification. In this paper, we focus on the delineation part. For the modeling part, we employ the active shape model (ASM) strategy. For recognition and delineation, we integrate several hybrid strategies of combining purely image based methods with ASM. In this paper, an iterative Graph-Cut ASM (IGCASM) method is proposed for object delineation. An algorithm called GC-ASM was presented at this symposium last year for object delineation in 2D images which attempted to combine synergistically ASM and GC. Here, we extend this method to 3D medical image delineation. The IGCASM method effectively combines the rich statistical shape information embodied in ASM with the globally optimal delineation capability of the GC method. We propose a new GC cost function, which effectively integrates the specific image information with the ASM shape model information. The proposed methods are tested on a clinical abdominal CT data set. The preliminary results show that: (a) it is feasible to explicitly bring prior 3D statistical shape information into the GC framework; (b) the 3D IGCASM delineation method improves on ASM and GC and can provide practical operational time on clinical images.

Statistical shape modelling of hip and lumbar spine morphology and their relationship in the MRC National Survey of Health and Development.

PubMed

Pavlova, Anastasia V; Saunders, Fiona R; Muthuri, Stella G; Gregory, Jennifer S; Barr, Rebecca J; Martin, Kathryn R; Hardy, Rebecca J; Cooper, Rachel; Adams, Judith E; Kuh, Diana; Aspden, Richard M

2017-08-01

The anatomical shape of bones and joints is important for their proper function but quantifying this, and detecting pathological variations, is difficult to do. Numerical descriptions would also enable correlations between joint shapes to be explored. Statistical shape modelling (SSM) is a method of image analysis employing pattern recognition statistics to describe and quantify such shapes from images; it uses principal components analysis to generate modes of variation describing each image in terms of a set of numerical scores after removing global size variation. We used SSM to quantify the shapes of the hip and the lumbar spine in dual-energy x-ray absorptiometry (DXA) images from 1511 individuals in the MRC National Survey of Health and Development at ages 60-64 years. We compared shapes of both joints in men and women and hypothesised that hip and spine shape would be strongly correlated. We also investigated associations with height, weight, body mass index (BMI) and local (hip or lumber spine) bone mineral density. In the hip, all except one of the first 10 modes differed between men and women. Men had a wider femoral neck, smaller neck-shaft angle, increased presence of osteophytes and a loss of the femoral head/neck curvature compared with women. Women presented with a flattening of the femoral head and greater acetabular coverage of the femoral head. Greater weight was associated with a shorter, wider femoral neck and larger greater and lesser trochanters. Taller height was accompanied by a flattening of the curve between superior head and neck and a larger lesser trochanter. Four of the first eight modes describing lumbar spine shape differed between men and women. Women tended to have a more lordotic spine than men with relatively smaller but caudally increasing anterior-posterior (a-p) vertebral diameters. Men were more likely to have a straighter spine with larger vertebral a-p diameters relative to vertebral height than women, increasing cranially. A weak correlation was found between body weight and a-p vertebral diameter. No correlations were found between shape modes and height in men, whereas in women there was a weak positive correlation between height and evenness of spinal curvature. Linear relationships between hip and spine shapes were weak and inconsistent in both sexes, thereby offering little support for our hypothesis. In conclusion, men and women entering their seventh decade have small but statistically significant differences in the shapes of their hips and their spines. Associations with height, weight, BMI and BMD are small and correspond to subtle variations whose anatomical significance is not yet clear. Correlations between hip and spine shapes are small. © 2017 The Authors. Journal of Anatomy published by John Wiley & Sons Ltd on behalf of Anatomical Society.

An Analytical Thermal Model for Autonomous Soaring Research

NASA Technical Reports Server (NTRS)

Allen, Michael

2006-01-01

A viewgraph presentation describing an analytical thermal model used to enable research on autonomous soaring for a small UAV aircraft is given. The topics include: 1) Purpose; 2) Approach; 3) SURFRAD Data; 4) Convective Layer Thickness; 5) Surface Heat Budget; 6) Surface Virtual Potential Temperature Flux; 7) Convective Scaling Velocity; 8) Other Calculations; 9) Yearly trends; 10) Scale Factors; 11) Scale Factor Test Matrix; 12) Statistical Model; 13) Updraft Strength Calculation; 14) Updraft Diameter; 15) Updraft Shape; 16) Smoothed Updraft Shape; 17) Updraft Spacing; 18) Environment Sink; 19) Updraft Lifespan; 20) Autonomous Soaring Research; 21) Planned Flight Test; and 22) Mixing Ratio.

Empirical Investigations of the Opportunity Limits of Automatic Residential Electric Load Shaping

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

Cruickshank, Robert F.; Henze, Gregor P.; Balaji, Rajagopalan

Residential electric load shaping is often modeled as infrequent, utility-initiated, short-duration deferral of peak demand through direct load control. In contrast, modeled herein is the potential for frequent, transactive, intraday, consumer-configurable load shaping for storage-capable thermostatically controlled electric loads (TCLs), including refrigerators, freezers, and hot water heaters. Unique to this study are 28 months of 15-minute-interval observations of usage in 101 homes in the Pacific Northwest United States that specify exact start, duration, and usage patterns of approximately 25 submetered loads per home. The magnitudes of the load shift from voluntarily-participating TCL appliances are aggregated to form hourly upper andmore » lower load-shaping limits for the coordination of electrical generation, transmission, distribution, storage, and demand. Empirical data are statistically analyzed to define metrics that help quantify load-shaping opportunities.« less

Empirical Investigations of the Opportunity Limits of Automatic Residential Electric Load Shaping: Preprint

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

Cruickshank, Robert F.; Henze, Gregor P.; Balaji, Rajagopalan

Residential electric load shaping is often modeled as infrequent, utility-initiated, short-duration deferral of peak demand through direct load control. In contrast, modeled herein is the potential for frequent, transactive, intraday, consumer-configurable load shaping for storage-capable thermostatically controlled electric loads (TCLs), including refrigerators, freezers, and hot water heaters. Unique to this study are 28 months of 15-minute-interval observations of usage in 101 homes in the Pacific Northwest United States that specify exact start, duration, and usage patterns of approximately 25 submetered loads per home. The magnitudes of the load shift from voluntarily-participating TCL appliances are aggregated to form hourly upper andmore » lower load-shaping limits for the coordination of electrical generation, transmission, distribution, storage, and demand. Empirical data are statistically analyzed to define metrics that help quantify load-shaping opportunities.« less

Clusters in irregular areas and lattices.

PubMed

Wieczorek, William F; Delmerico, Alan M; Rogerson, Peter A; Wong, David W S

2012-01-01

Geographic areas of different sizes and shapes of polygons that represent counts or rate data are often encountered in social, economic, health, and other information. Often political or census boundaries are used to define these areas because the information is available only for those geographies. Therefore, these types of boundaries are frequently used to define neighborhoods in spatial analyses using geographic information systems and related approaches such as multilevel models. When point data can be geocoded, it is possible to examine the impact of polygon shape on spatial statistical properties, such as clustering. We utilized point data (alcohol outlets) to examine the issue of polygon shape and size on visualization and statistical properties. The point data were allocated to regular lattices (hexagons and squares) and census areas for zip-code tabulation areas and tracts. The number of units in the lattices was set to be similar to the number of tract and zip-code areas. A spatial clustering statistic and visualization were used to assess the impact of polygon shape for zip- and tract-sized units. Results showed substantial similarities and notable differences across shape and size. The specific circumstances of a spatial analysis that aggregates points to polygons will determine the size and shape of the areal units to be used. The irregular polygons of census units may reflect underlying characteristics that could be missed by large regular lattices. Future research to examine the potential for using a combination of irregular polygons and regular lattices would be useful.

3D shape recovery from image focus using gray level co-occurrence matrix

NASA Astrophysics Data System (ADS)

Mahmood, Fahad; Munir, Umair; Mehmood, Fahad; Iqbal, Javaid

2018-04-01

Recovering a precise and accurate 3-D shape of the target object utilizing robust 3-D shape recovery algorithm is an ultimate objective of computer vision community. Focus measure algorithm plays an important role in this architecture which convert the color values of each pixel of the acquired 2-D image dataset into corresponding focus values. After convolving the focus measure filter with the input 2-D image dataset, a 3-D shape recovery approach is applied which will recover the depth map. In this document, we are concerned with proposing Gray Level Co-occurrence Matrix along with its statistical features for computing the focus information of the image dataset. The Gray Level Co-occurrence Matrix quantifies the texture present in the image using statistical features and then applies joint probability distributive function of the gray level pairs of the input image. Finally, we quantify the focus value of the input image using Gaussian Mixture Model. Due to its little computational complexity, sharp focus measure curve, robust to random noise sources and accuracy, it is considered as superior alternative to most of recently proposed 3-D shape recovery approaches. This algorithm is deeply investigated on real image sequences and synthetic image dataset. The efficiency of the proposed scheme is also compared with the state of art 3-D shape recovery approaches. Finally, by means of two global statistical measures, root mean square error and correlation, we claim that this approach -in spite of simplicity generates accurate results.

Vibration mode shape recognition using image processing

NASA Astrophysics Data System (ADS)

Wang, Weizhuo; Mottershead, John E.; Mares, Cristinel

2009-10-01

Currently the most widely used method for comparing mode shapes from finite elements and experimental measurements is the modal assurance criterion (MAC), which can be interpreted as the cosine of the angle between the numerical and measured eigenvectors. However, the eigenvectors only contain the displacement of discrete coordinates, so that the MAC index carries no explicit information on shape features. New techniques, based upon the well-developed philosophies of image processing (IP) and pattern recognition (PR) are considered in this paper. The Zernike moment descriptor (ZMD), Fourier descriptor (FD), and wavelet descriptor (WD) are the most popular shape descriptors due to their outstanding properties in IP and PR. These include (1) for the ZMD-rotational invariance, expression and computing efficiency, ease of reconstruction and robustness to noise; (2) for the FD—separation of the global shape and shape-details by low and high frequency components, respectively, invariance under geometric transformation; (3) for the WD—multi-scale representation and local feature detection. Once a shape descriptor has been adopted, the comparison of mode shapes is transformed to a comparison of multidimensional shape feature vectors. Deterministic and statistical methods are presented. The deterministic problem of measuring the degree of similarity between two mode shapes (possibly one from a vibration test and the other from a finite element model) may be carried out using Pearson's correlation. Similar shape feature vectors may be arranged in clusters separated by Euclidian distances in the feature space. In the statistical analysis we are typically concerned with the classification of a test mode shape according to clusters of shape feature vectors obtained from a randomised finite element model. The dimension of the statistical problem may often be reduced by principal component analysis. Then, in addition to the Euclidian distance, the Mahalanobis distance, defining the separation of the test point from the cluster in terms of its standard deviation, becomes an important measure. Bayesian decision theory may be applied to formally minimise the risk of misclassification of the test shape feature vector. In this paper the ZMD is applied to the problem of mode shape recognition for a circular plate. Results show that the ZMD has considerable advantages over the traditional MAC index when identifying the cyclically symmetric mode shapes that occur in axisymmetric structures at identical frequencies. Mode shape recognition of rectangular plates is carried out by the FD. Also, the WD is applied to the problem of recognising the mode shapes in the thin and thick regions of a plate with different thicknesses. It shows the benefit of using the WD to identify mode-shapes having both local and global components. The comparison and classification of mode shapes using IP and PR provides a 'toolkit' to complement the conventional MAC approach. The selection of a particular shape descriptor and classification method will depend upon the problem in hand and the experience of the analyst.

Zigzagging causility model of EPR correlations and on the interpretation of quantum mechanics

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

de Beauregard, O.C.

1988-09-01

Being formalized inside the S-matrix scheme, the zigzagging causility model of EPR correlations has full Lorentz and CPT invariance. EPR correlations, proper or reversed, and Wheeler's smoky dragon metaphor are respectively pictured in a spacetime or in the momentum-energy space, as V-shaped, anti LAMBDA-shaped, or C-shaped ABC zigzags, with a summation at B over virtual states absolute value B>=*. The reversibility = * implies that causality is CPT-invariant, or arrowless, at the microlevel. Arrowed causality is a macroscopic emergence, corollary to wave retardation and probability increase. Factlike irreversibility states repression, not suppression, of blind statistical retrodiction- that is, of finalmore » cause.« less

An application of principal component analysis to the clavicle and clavicle fixation devices.

PubMed

Daruwalla, Zubin J; Courtis, Patrick; Fitzpatrick, Clare; Fitzpatrick, David; Mullett, Hannan

2010-03-26

Principal component analysis (PCA) enables the building of statistical shape models of bones and joints. This has been used in conjunction with computer assisted surgery in the past. However, PCA of the clavicle has not been performed. Using PCA, we present a novel method that examines the major modes of size and three-dimensional shape variation in male and female clavicles and suggests a method of grouping the clavicle into size and shape categories. Twenty-one high-resolution computerized tomography scans of the clavicle were reconstructed and analyzed using a specifically developed statistical software package. After performing statistical shape analysis, PCA was applied to study the factors that account for anatomical variation. The first principal component representing size accounted for 70.5 percent of anatomical variation. The addition of a further three principal components accounted for almost 87 percent. Using statistical shape analysis, clavicles in males have a greater lateral depth and are longer, wider and thicker than in females. However, the sternal angle in females is larger than in males. PCA confirmed these differences between genders but also noted that men exhibit greater variance and classified clavicles into five morphological groups. This unique approach is the first that standardizes a clavicular orientation. It provides information that is useful to both, the biomedical engineer and clinician. Other applications include implant design with regard to modifying current or designing future clavicle fixation devices. Our findings support the need for further development of clavicle fixation devices and the questioning of whether gender-specific devices are necessary.

Quantitative Outline-based Shape Analysis and Classification of Planetary Craterforms using Supervised Learning Models

NASA Astrophysics Data System (ADS)

Slezak, Thomas Joseph; Radebaugh, Jani; Christiansen, Eric

2017-10-01

The shapes of craterform morphology on planetary surfaces provides rich information about their origins and evolution. While morphologic information provides rich visual clues to geologic processes and properties, the ability to quantitatively communicate this information is less easily accomplished. This study examines the morphology of craterforms using the quantitative outline-based shape methods of geometric morphometrics, commonly used in biology and paleontology. We examine and compare landforms on planetary surfaces using shape, a property of morphology that is invariant to translation, rotation, and size. We quantify the shapes of paterae on Io, martian calderas, terrestrial basaltic shield calderas, terrestrial ash-flow calderas, and lunar impact craters using elliptic Fourier analysis (EFA) and the Zahn and Roskies (Z-R) shape function, or tangent angle approach to produce multivariate shape descriptors. These shape descriptors are subjected to multivariate statistical analysis including canonical variate analysis (CVA), a multiple-comparison variant of discriminant analysis, to investigate the link between craterform shape and classification. Paterae on Io are most similar in shape to terrestrial ash-flow calderas and the shapes of terrestrial basaltic shield volcanoes are most similar to martian calderas. The shapes of lunar impact craters, including simple, transitional, and complex morphology, are classified with a 100% rate of success in all models. Multiple CVA models effectively predict and classify different craterforms using shape-based identification and demonstrate significant potential for use in the analysis of planetary surfaces.

A segmentation editing framework based on shape change statistics

NASA Astrophysics Data System (ADS)

Mostapha, Mahmoud; Vicory, Jared; Styner, Martin; Pizer, Stephen

2017-02-01

Segmentation is a key task in medical image analysis because its accuracy significantly affects successive steps. Automatic segmentation methods often produce inadequate segmentations, which require the user to manually edit the produced segmentation slice by slice. Because editing is time-consuming, an editing tool that enables the user to produce accurate segmentations by only drawing a sparse set of contours would be needed. This paper describes such a framework as applied to a single object. Constrained by the additional information enabled by the manually segmented contours, the proposed framework utilizes object shape statistics to transform the failed automatic segmentation to a more accurate version. Instead of modeling the object shape, the proposed framework utilizes shape change statistics that were generated to capture the object deformation from the failed automatic segmentation to its corresponding correct segmentation. An optimization procedure was used to minimize an energy function that consists of two terms, an external contour match term and an internal shape change regularity term. The high accuracy of the proposed segmentation editing approach was confirmed by testing it on a simulated data set based on 10 in-vivo infant magnetic resonance brain data sets using four similarity metrics. Segmentation results indicated that our method can provide efficient and adequately accurate segmentations (Dice segmentation accuracy increase of 10%), with very sparse contours (only 10%), which is promising in greatly decreasing the work expected from the user.

Flow field and oscillatory shear stress in a tuning-fork-shaped model of the average human carotid bifurcation.

PubMed

Ding, Z; Wang, K; Li, J; Cong, X

2001-12-01

The oscillatory shear index (OSI) was developed based on the hypothesis that intimal hyperplasia was correlated with oscillatory shear stresses. However, the validity of the OSI was in question since the correlation between intimal thickness and the OSI at the side walls of the sinus in the Y-shaped model of the average human carotid bifurcation (Y-AHCB) was weak. The objectives of this paper are to examine whether the reason for the weak correlation lies in the deviation in geometry of Y-AHCB from real human carotid bifurcation, and whether this correlation is clearly improved in the tuning-fork-shaped model of the average human carotid bifurcation (TF-AHCB). The geometry of the TF-AHCB model was based on observation and statistical analysis of specimens from 74 cadavers. The flow fields in both models were studied and compared by using flow visualization methods under steady flow conditions and by using laser Doppler anemometer (LDA) under pulsatile flow conditions. The TF-shaped geometry leads to a more complex flow field than the Y-shaped geometry. This added complexity includes strengthened helical movements in the sinus, new flow separation zone, and directional changes in the secondary flow patterns. The results show that the OSI-values at the side walls of the sinus in the TF-shaped model were more than two times as large as those in the Y-shaped model. This study confirmed the stronger correlation between the OSI and intimal thickness in the tuning-fork geometry of human carotid bifurcation, and the TF-AHCB model is a significant improvement over the traditional Y-shaped model.

The use of higher-order statistics in rapid object categorization in natural scenes.

PubMed

Banno, Hayaki; Saiki, Jun

2015-02-04

We can rapidly and efficiently recognize many types of objects embedded in complex scenes. What information supports this object recognition is a fundamental question for understanding our visual processing. We investigated the eccentricity-dependent role of shape and statistical information for ultrarapid object categorization, using the higher-order statistics proposed by Portilla and Simoncelli (2000). Synthesized textures computed by their algorithms have the same higher-order statistics as the originals, while the global shapes were destroyed. We used the synthesized textures to manipulate the availability of shape information separately from the statistics. We hypothesized that shape makes a greater contribution to central vision than to peripheral vision and that statistics show the opposite pattern. Results did not show contributions clearly biased by eccentricity. Statistical information demonstrated a robust contribution not only in peripheral but also in central vision. For shape, the results supported the contribution in both central and peripheral vision. Further experiments revealed some interesting properties of the statistics. They are available for a limited time, attributable to the presence or absence of animals without shape, and predict how easily humans detect animals in original images. Our data suggest that when facing the time constraint of categorical processing, higher-order statistics underlie our significant performance for rapid categorization, irrespective of eccentricity. © 2015 ARVO.

Quantitative assessment of human body shape using Fourier analysis

NASA Astrophysics Data System (ADS)

Friess, Martin; Rohlf, F. J.; Hsiao, Hongwei

2004-04-01

Fall protection harnesses are commonly used to reduce the number and severity of injuries. Increasing the efficiency of harness design requires the size and shape variation of the user population to be assessed as detailed and as accurately as possible. In light of the unsatisfactory performance of traditional anthropometry with respect to such assessments, we propose the use of 3D laser surface scans of whole bodies and the statistical analysis of elliptic Fourier coefficients. Ninety-eight male and female adults were scanned. Key features of each torso were extracted as a 3D curve along front, back and the thighs. A 3D extension of Elliptic Fourier analysis4 was used to quantify their shape through multivariate statistics. Shape change as a function of size (allometry) was predicted by regressing the coefficients onto stature, weight and hip circumference. Upper and lower limits of torso shape variation were determined and can be used to redefine the design of the harness that will fit most individual body shapes. Observed allometric changes are used for adjustments to the harness shape in each size. Finally, the estimated outline data were used as templates for a free-form deformation of the complete torso surface using NURBS models (non-uniform rational B-splines).

Statistical analysis of modeling error in structural dynamic systems

NASA Technical Reports Server (NTRS)

Hasselman, T. K.; Chrostowski, J. D.

1990-01-01

The paper presents a generic statistical model of the (total) modeling error for conventional space structures in their launch configuration. Modeling error is defined as the difference between analytical prediction and experimental measurement. It is represented by the differences between predicted and measured real eigenvalues and eigenvectors. Comparisons are made between pre-test and post-test models. Total modeling error is then subdivided into measurement error, experimental error and 'pure' modeling error, and comparisons made between measurement error and total modeling error. The generic statistical model presented in this paper is based on the first four global (primary structure) modes of four different structures belonging to the generic category of Conventional Space Structures (specifically excluding large truss-type space structures). As such, it may be used to evaluate the uncertainty of predicted mode shapes and frequencies, sinusoidal response, or the transient response of other structures belonging to the same generic category.

A Model Based Deconvolution Approach for Creating Surface Composition Maps of Irregularly Shaped Bodies from Limited Orbiting Nuclear Spectrometer Measurements

NASA Astrophysics Data System (ADS)

Dallmann, N. A.; Carlsten, B. E.; Stonehill, L. C.

2017-12-01

Orbiting nuclear spectrometers have contributed significantly to our understanding of the composition of solar system bodies. Gamma rays and neutrons are produced within the surfaces of bodies by impacting galactic cosmic rays (GCR) and by intrinsic radionuclide decay. Measuring the flux and energy spectrum of these products at one point in an orbit elucidates the elemental content of the area in view. Deconvolution of measurements from many spatially registered orbit points can produce detailed maps of elemental abundances. In applying these well-established techniques to small and irregularly shaped bodies like Phobos, one encounters unique challenges beyond those of a large spheroid. Polar mapping orbits are not possible for Phobos and quasistatic orbits will realize only modest inclinations unavoidably limiting surface coverage and creating North-South ambiguities in deconvolution. The irregular shape causes self-shadowing both of the body to the spectrometer but also of the body to the incoming GCR. The view angle to the surface normal as well as the distance between the surface and the spectrometer is highly irregular. These characteristics can be synthesized into a complicated and continuously changing measurement system point spread function. We have begun to explore different model-based, statistically rigorous, iterative deconvolution methods to produce elemental abundance maps for a proposed future investigation of Phobos. By incorporating the satellite orbit, the existing high accuracy shape-models of Phobos, and the spectrometer response function, a detailed and accurate system model can be constructed. Many aspects of this model formation are particularly well suited to modern graphics processing techniques and parallel processing. We will present the current status and preliminary visualizations of the Phobos measurement system model. We will also discuss different deconvolution strategies and their relative merit in statistical rigor, stability, achievable resolution, and exploitation of the irregular shape to partially resolve ambiguities. The general applicability of these new approaches to existing data sets from Mars, Mercury, and Lunar investigations will be noted.

Semi-automated measurement of anatomical structures using statistical and morphological priors

NASA Astrophysics Data System (ADS)

Ashton, Edward A.; Du, Tong

2004-05-01

Rapid, accurate and reproducible delineation and measurement of arbitrary anatomical structures in medical images is a widely held goal, with important applications in both clinical diagnostics and, perhaps more significantly, pharmaceutical trial evaluation. This process requires the ability first to localize a structure within the body, and then to find a best approximation of the structure"s boundaries within a given scan. Structures that are tortuous and small in cross section, such as the hippocampus in the brain or the abdominal aorta, present a particular challenge. Their apparent shape and position can change significantly from slice to slice, and accurate prior shape models for such structures are often difficult to form. In this work, we have developed a system that makes use of both a user-defined shape model and a statistical maximum likelihood classifier to identify and measure structures of this sort in MRI and CT images. Experiments show that this system can reduce analysis time by 75% or more with respect to manual tracing with no loss of precision or accuracy.

Comparative evaluation of root canal preparations of maxillary first molars with self-adjusting file, reciproc single file, and revo-s rotary file: A micro-computed tomography study.

PubMed

Ahmetoglu, Fuat; Keles, Ali; Simsek, Neslihan; Ocak, M Sinan; Yologlu, Saim

2015-01-01

This study was aimed to use micro-computed tomography (μ-CT) to evaluate the canal shaping properties of three nickel-titanium instruments, Self-Adjusting File (SAF), Reciproc, and Revo-S rotary file, in maxillary first molars. Thirty maxillary molars were scanned preoperatively by using micro-computed tomography (μ-CT) scans at 13,68 μm resolution. The teeth were randomly assigned to three groups (n = 10). The root canals were shaped with SAF, Reciproc, and Revo-S, respectively. The shaped root canals were rescanned. Changes in canal volumes and surface areas were compared with preoperative values. The data were analyzed using Kruskal-Wallis and Conover's post hoc tests, with p < .05 denoting a statistically significant difference. Preoperatively canal volumes and surface area were statistically similar among the three groups (p > .05). There were statistically significant differences in all measures comparing preoperative and postoperative canal models (p = 0.0001). These differences occurred after instrumentation among the three experimental groups showed no statistically significant difference for volume (p > .05). Surface area showed the similar activity in buccal canals in each of the three techniques whereas no statistically significant difference was detected among surface area, the SAF, and the Revo-S in the palatal (P) canal. Each of three shaping system showed the similar volume activity in all canals, but SAF and Revo-S provided more effectively root planning in comparison with Reciproc in P canal. © Wiley Periodicals, Inc.

Statistical 3D shape analysis of gender differences in lateral ventricles

NASA Astrophysics Data System (ADS)

He, Qing; Karpman, Dmitriy; Duan, Ye

2010-03-01

This paper aims at analyzing gender differences in the 3D shapes of lateral ventricles, which will provide reference for the analysis of brain abnormalities related to neurological disorders. Previous studies mostly focused on volume analysis, and the main challenge in shape analysis is the required step of establishing shape correspondence among individual shapes. We developed a simple and efficient method based on anatomical landmarks. 14 females and 10 males with matching ages participated in this study. 3D ventricle models were segmented from MR images by a semiautomatic method. Six anatomically meaningful landmarks were identified by detecting the maximum curvature point in a small neighborhood of a manually clicked point on the 3D model. Thin-plate spline was used to transform a randomly selected template shape to each of the rest shape instances, and the point correspondence was established according to Euclidean distance and surface normal. All shapes were spatially aligned by Generalized Procrustes Analysis. Hotelling T2 twosample metric was used to compare the ventricle shapes between males and females, and False Discovery Rate estimation was used to correct for the multiple comparison. The results revealed significant differences in the anterior horn of the right ventricle.

A rigidity transition and glassy dynamics in a model for confluent 3D tissues

NASA Astrophysics Data System (ADS)

Merkel, Matthias; Manning, M. Lisa

The origin of rigidity in disordered materials is an outstanding open problem in statistical physics. Recently, a new type of rigidity transition was discovered in a family of models for 2D biological tissues, but the mechanisms responsible for rigidity remain unclear. This is not just a statistical physics problem, but also relevant for embryonic development, cancer growth, and wound healing. To gain insight into this rigidity transition and make new predictions about biological bulk tissues, we have developed a fully 3D self-propelled Voronoi (SPV) model. The model takes into account shape, elasticity, and self-propelled motion of the individual cells. We find that in the absence of self-propulsion, this model exhibits a rigidity transition that is controlled by a dimensionless model parameter describing the preferred cell shape, with an accompanying structural order parameter. In the presence of self-propulsion, the rigidity transition appears as a glass-like transition featuring caging and aging effects. Given the similarities between this transition and jamming in particulate solids, it is natural to ask if the two transitions are related. By comparing statistics of Voronoi geometries, we show the transitions are surprisingly close but demonstrably distinct. Furthermore, an index theorem used to identify topologically protected mechanical modes in jammed systems can be extended to these vertex-type models. In our model, residual stresses govern the transition and enter the index theorem in a different way compared to jammed particles, suggesting the origin of rigidity may be different between the two.

The analysis of morphometric data on rocky mountain wolves and artic wolves using statistical method

NASA Astrophysics Data System (ADS)

Ammar Shafi, Muhammad; Saifullah Rusiman, Mohd; Hamzah, Nor Shamsidah Amir; Nor, Maria Elena; Ahmad, Noor’ani; Azia Hazida Mohamad Azmi, Nur; Latip, Muhammad Faez Ab; Hilmi Azman, Ahmad

2018-04-01

Morphometrics is a quantitative analysis depending on the shape and size of several specimens. Morphometric quantitative analyses are commonly used to analyse fossil record, shape and size of specimens and others. The aim of the study is to find the differences between rocky mountain wolves and arctic wolves based on gender. The sample utilised secondary data which included seven variables as independent variables and two dependent variables. Statistical modelling was used in the analysis such was the analysis of variance (ANOVA) and multivariate analysis of variance (MANOVA). The results showed there exist differentiating results between arctic wolves and rocky mountain wolves based on independent factors and gender.

Introduction of non-linear elasticity models for characterization of shape and deformation statistics: application to contractility assessment of isolated adult cardiocytes.

PubMed

Bazan, Carlos; Hawkins, Trevor; Torres-Barba, David; Blomgren, Peter; Paolini, Paul

2011-08-22

We are exploring the viability of a novel approach to cardiocyte contractility assessment based on biomechanical properties of the cardiac cells, energy conservation principles, and information content measures. We define our measure of cell contraction as being the distance between the shapes of the contracting cell, assessed by the minimum total energy of the domain deformation (warping) of one cell shape into another. To guarantee a meaningful vis-à-vis correspondence between the two shapes, we employ both a data fidelity term and a regularization term. The data fidelity term is based on nonlinear features of the shapes while the regularization term enforces the compatibility between the shape deformations and that of a hyper-elastic material. We tested the proposed approach by assessing the contractile responses in isolated adult rat cardiocytes and contrasted these measurements against two different methods for contractility assessment in the literature. Our results show good qualitative and quantitative agreements with these methods as far as frequency, pacing, and overall behavior of the contractions are concerned. We hypothesize that the proposed methodology, once appropriately developed and customized, can provide a framework for computational cardiac cell biomechanics that can be used to integrate both theory and experiment. For example, besides giving a good assessment of contractile response of the cardiocyte, since the excitation process of the cell is a closed system, this methodology can be employed in an attempt to infer statistically significant model parameters for the constitutive equations of the cardiocytes.

Bone shape difference between control and osteochondral defect groups of the ankle joint.

PubMed

Tümer, N; Blankevoort, L; van de Giessen, M; Terra, M P; de Jong, P A; Weinans, H; Tuijthof, G J M; Zadpoor, A A

2016-12-01

The etiology of osteochondral defects (OCDs), for which the ankle (talocrural) joint is one of the common sites, is not yet fully understood. In this study, we hypothesized that bone shape plays a role in development of OCDs. Therefore, we quantitatively compared the morphology of the talus and the distal tibia between an OCD group and a control group. The shape variations of the talus and distal tibia were described separately by constructing two statistical shape models (SSMs) based on the segmentation of the bones from ankle computed tomography (CT) scans obtained from control (i.e., 35 CT scans) and OCD (i.e., 37 CT scans) groups. The first five modes of shape variation for the SSM corresponding to each bone were statistically compared between control and OCD groups using an analysis of variance (ANOVA) corrected with the Bonferroni for multiple comparisons. The first five modes of variation in the SSMs respectively represented 49% and 40% of the total variance of talus and tibia. Less than 5% of the variance per mode was described by the higher modes. Mode 5 of the talus (P = 0.004) primarily describing changes in the vertical neck angle and Mode 1 of the tibia (P < 0.0001) representing variations at the medial malleolus, showed statistically significant difference between the control and OCD groups. Shape differences exist between control and OCD groups. This indicates that a geometry modulated biomechanical behavior of the talocrural joint may be a risk factor for OCD. Copyright © 2016. Published by Elsevier Ltd.

Zygomatic bone shape in intentional cranial deformations: a model for the study of the interactions between skull growth and facial morphology.

PubMed

Ketoff, S; Girinon, F; Schlager, S; Friess, M; Schouman, T; Rouch, P; Khonsari, R H

2017-04-01

Intentional cranial deformations (ICD) were obtained by exerting external mechanical constraints on the skull vault during the first years of life to permanently modify head shape. The repercussions of ICD on the face are not well described in the midfacial region. Here we assessed the shape of the zygomatic bone in different types of ICDs. We considered 14 non-deformed skulls, 19 skulls with antero-posterior deformation, nine skulls with circumferential deformation and seven skulls with Toulouse deformation. The shape of the zygomatic bone was assessed using a statistical shape model after mesh registration. Euclidian distances between mean models and Mahalanobis distances after canonical variate analysis were computed. Classification accuracy was computed using a cross-validation approach. Different ICDs cause specific zygomatic shape modifications corresponding to different degrees of retrusion but the shape of the zygomatic bone alone is not a sufficient parameter for classifying populations into ICD groups defined by deformation types. We illustrate the fact that external mechanical constraints on the skull vault influence midfacial growth. ICDs are a model for the study of the influence of epigenetic factors on craniofacial growth and can help to understand the facial effects of congenital skull malformations such as single or multi-suture synostoses, or of external orthopedic devices such as helmets used to correct deformational plagiocephaly. © 2016 Anatomical Society.

Modeling envelope statistics of blood and myocardium for segmentation of echocardiographic images.

PubMed

Nillesen, Maartje M; Lopata, Richard G P; Gerrits, Inge H; Kapusta, Livia; Thijssen, Johan M; de Korte, Chris L

2008-04-01

The objective of this study was to investigate the use of speckle statistics as a preprocessing step for segmentation of the myocardium in echocardiographic images. Three-dimensional (3D) and biplane image sequences of the left ventricle of two healthy children and one dog (beagle) were acquired. Pixel-based speckle statistics of manually segmented blood and myocardial regions were investigated by fitting various probability density functions (pdf). The statistics of heart muscle and blood could both be optimally modeled by a K-pdf or Gamma-pdf (Kolmogorov-Smirnov goodness-of-fit test). Scale and shape parameters of both distributions could differentiate between blood and myocardium. Local estimation of these parameters was used to obtain parametric images, where window size was related to speckle size (5 x 2 speckles). Moment-based and maximum-likelihood estimators were used. Scale parameters were still able to differentiate blood from myocardium; however, smoothing of edges of anatomical structures occurred. Estimation of the shape parameter required a larger window size, leading to unacceptable blurring. Using these parameters as an input for segmentation resulted in unreliable segmentation. Adaptive mean squares filtering was then introduced using the moment-based scale parameter (sigma(2)/mu) of the Gamma-pdf to automatically steer the two-dimensional (2D) local filtering process. This method adequately preserved sharpness of the edges. In conclusion, a trade-off between preservation of sharpness of edges and goodness-of-fit when estimating local shape and scale parameters is evident for parametric images. For this reason, adaptive filtering outperforms parametric imaging for the segmentation of echocardiographic images.

A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit

NASA Technical Reports Server (NTRS)

Kim, K. Han; Young, Karen S.; Bernal, Yaritza; Boppana, Abhishektha; Vu, Linh Q.; Benson, Elizabeth A.; Jarvis, Sarah; Rajulu, Sudhakar L.

2016-01-01

Shoulder injury is one of the most severe risks that have the potential to impair crewmembers' performance and health in long duration space flight. Overall, 64% of crewmembers experience shoulder pain after extra-vehicular training in a space suit, and 14% of symptomatic crewmembers require surgical repair (Williams & Johnson, 2003). Suboptimal suit fit, in particular at the shoulder region, has been identified as one of the predominant risk factors. However, traditional suit fit assessments and laser scans represent only a single person's data, and thus may not be generalized across wide variations of body shapes and poses. The aim of this work is to develop a software tool based on a statistical analysis of a large dataset of crewmember body shapes. This tool can accurately predict the skin deformation and shape variations for any body size and shoulder pose for a target population, from which the geometry can be exported and evaluated against suit models in commercial CAD software. A preliminary software tool was developed by statistically analyzing 150 body shapes matched with body dimension ranges specified in the Human-Systems Integration Requirements of NASA ("baseline model"). Further, the baseline model was incorporated with shoulder joint articulation ("articulation model"), using additional subjects scanned in a variety of shoulder poses across a pre-specified range of motion. Scan data was cleaned and aligned using body landmarks. The skin deformation patterns were dimensionally reduced and the co-variation with shoulder angles was analyzed. A software tool is currently in development and will be presented in the final proceeding. This tool would allow suit engineers to parametrically generate body shapes in strategically targeted anthropometry dimensions and shoulder poses. This would also enable virtual fit assessments, with which the contact volume and clearance between the suit and body surface can be predictively quantified at reduced time and cost.

Application of Elliptic Fourier Analysis to Describe the Lamina Cribrosa Shape with Age and Intraocular Pressure

PubMed Central

Sanfilippo, P.G.; Grimm, J.L.; Flanagan, J.G.; Lathrop, K.L.; Sigal, I.A.

2014-01-01

The lamina cribrosa (LC) plays an important biomechanical role in the optic nerve head (ONH). We developed a statistical shape model of the LC and tested if the shape varies with age or IOP. The ONHs of 18 donor eyes (47 to 91 years, mean 76 years) fixed at either 5 or 50 mm Hg of IOP were sectioned, stained, and imaged under a microscope. A 3D model of each ONH was reconstructed and the outline of the vertical sagittal section closest to the geometric centre of the LC extracted. The outline shape was described using elliptic Fourier analysis, and principal components analysis (PCA) employed to identify the primary modes of LC shape variation. Linear mixed effect models were used to determine if the shape measurements were associated with age or IOP. The analysis revealed several modes of shape variation: thickness and depth directly (PC1), or inversely (PC2) related, and superior-inferior asymmetry (PC3). Only PC3 was associated with IOP, with higher IOP correlating with greater curvature of the LC superiorly compared to inferiorly. Our analysis enabled a concise and complete characterization of LC shape, revealing variations without defining them a priori. No association between LC shape and age was found for the relatively old population studied. Superior-inferior asymmetry of LC shape was associated with IOP, with more asymmetry at higher IOP. Increased IOP was not associated with LC thickness or depth. PMID:25193035

Application of Elliptic Fourier analysis to describe the lamina cribrosa shape with age and intraocular pressure.

PubMed

Sanfilippo, P G; Grimm, J L; Flanagan, J G; Lathrop, K L; Sigal, I A

2014-11-01

The lamina cribrosa (LC) plays an important biomechanical role in the optic nerve head (ONH). We developed a statistical shape model of the LC and tested if the shape varies with age or IOP. The ONHs of 18 donor eyes (47-91 years, mean 76 years) fixed at either 5 or 50 mmHg of IOP were sectioned, stained, and imaged under a microscope. A 3D model of each ONH was reconstructed and the outline of the vertical sagittal section closest to the geometric center of the LC extracted. The outline shape was described using Elliptic Fourier analysis, and principal components analysis (PCA) employed to identify the primary modes of LC shape variation. Linear mixed effect models were used to determine if the shape measurements were associated with age or IOP. The analysis revealed several modes of shape variation: thickness and depth directly (PC 1), or inversely (PC 2) related, and superior-inferior asymmetry (PC 3). Only PC 3 was associated with IOP, with higher IOP correlating with greater curvature of the LC superiorly compared to inferiorly. Our analysis enabled a concise and complete characterization of LC shape, revealing variations without defining them a priori. No association between LC shape and age was found for the relatively old population studied. Superior-inferior asymmetry of LC shape was associated with IOP, with more asymmetry at higher IOP. Increased IOP was not associated with LC thickness or depth. Copyright © 2014 Elsevier Ltd. All rights reserved.

Principal Component Analysis in Construction of 3D Human Knee Joint Models Using a Statistical Shape Model Method

PubMed Central

Tsai, Tsung-Yuan; Li, Jing-Sheng; Wang, Shaobai; Li, Pingyue; Kwon, Young-Min; Li, Guoan

2013-01-01

The statistical shape model (SSM) method that uses 2D images of the knee joint to predict the 3D joint surface model has been reported in literature. In this study, we constructed a SSM database using 152 human CT knee joint models, including the femur, tibia and patella and analyzed the characteristics of each principal component of the SSM. The surface models of two in vivo knees were predicted using the SSM and their 2D bi-plane fluoroscopic images. The predicted models were compared to their CT joint models. The differences between the predicted 3D knee joint surfaces and the CT image-based surfaces were 0.30 ± 0.81 mm, 0.34 ± 0.79 mm and 0.36 ± 0.59 mm for the femur, tibia and patella, respectively (average ± standard deviation). The computational time for each bone of the knee joint was within 30 seconds using a personal computer. The analysis of this study indicated that the SSM method could be a useful tool to construct 3D surface models of the knee with sub-millimeter accuracy in real time. Thus it may have a broad application in computer assisted knee surgeries that require 3D surface models of the knee. PMID:24156375

Smooth extrapolation of unknown anatomy via statistical shape models

NASA Astrophysics Data System (ADS)

Grupp, R. B.; Chiang, H.; Otake, Y.; Murphy, R. J.; Gordon, C. R.; Armand, M.; Taylor, R. H.

2015-03-01

Several methods to perform extrapolation of unknown anatomy were evaluated. The primary application is to enhance surgical procedures that may use partial medical images or medical images of incomplete anatomy. Le Fort-based, face-jaw-teeth transplant is one such procedure. From CT data of 36 skulls and 21 mandibles separate Statistical Shape Models of the anatomical surfaces were created. Using the Statistical Shape Models, incomplete surfaces were projected to obtain complete surface estimates. The surface estimates exhibit non-zero error in regions where the true surface is known; it is desirable to keep the true surface and seamlessly merge the estimated unknown surface. Existing extrapolation techniques produce non-smooth transitions from the true surface to the estimated surface, resulting in additional error and a less aesthetically pleasing result. The three extrapolation techniques evaluated were: copying and pasting of the surface estimate (non-smooth baseline), a feathering between the patient surface and surface estimate, and an estimate generated via a Thin Plate Spline trained from displacements between the surface estimate and corresponding vertices of the known patient surface. Feathering and Thin Plate Spline approaches both yielded smooth transitions. However, feathering corrupted known vertex values. Leave-one-out analyses were conducted, with 5% to 50% of known anatomy removed from the left-out patient and estimated via the proposed approaches. The Thin Plate Spline approach yielded smaller errors than the other two approaches, with an average vertex error improvement of 1.46 mm and 1.38 mm for the skull and mandible respectively, over the baseline approach.

Statistical shape modeling based renal volume measurement using tracked ultrasound

NASA Astrophysics Data System (ADS)

Pai Raikar, Vipul; Kwartowitz, David M.

2017-03-01

Autosomal dominant polycystic kidney disease (ADPKD) is the fourth most common cause of kidney transplant worldwide accounting for 7-10% of all cases. Although ADPKD usually progresses over many decades, accurate risk prediction is an important task.1 Identifying patients with progressive disease is vital to providing new treatments being developed and enable them to enter clinical trials for new therapy. Among other factors, total kidney volume (TKV) is a major biomarker predicting the progression of ADPKD. Consortium for Radiologic Imaging Studies in Polycystic Kidney Disease (CRISP)2 have shown that TKV is an early, and accurate measure of cystic burden and likely growth rate. It is strongly associated with loss of renal function.3 While ultrasound (US) has proven as an excellent tool for diagnosing the disease; monitoring short-term changes using ultrasound has been shown to not be accurate. This is attributed to high operator variability and reproducibility as compared to tomographic modalities such as CT and MR (Gold standard). Ultrasound has emerged as one of the standout modality for intra-procedural imaging and with methods for spatial localization has afforded us the ability to track 2D ultrasound in physical space which it is being used. In addition to this, the vast amount of recorded tomographic data can be used to generate statistical shape models that allow us to extract clinical value from archived image sets. In this work, we aim at improving the prognostic value of US in managing ADPKD by assessing the accuracy of using statistical shape model augmented US data, to predict TKV, with the end goal of monitoring short-term changes.

Statistical-mechanics theory of active mode locking with noise.

PubMed

Gordon, Ariel; Fischer, Baruch

2004-05-01

Actively mode-locked lasers with noise are studied employing statistical mechanics. A mapping of the system to the spherical model (related to the Ising model) of ferromagnets in one dimension that has an exact solution is established. It gives basic features, such as analytical expressions for the correlation function between modes, and the widths and shapes of the pulses [different from the Kuizenga-Siegman expression; IEEE J. Quantum Electron. QE-6, 803 (1970)] and reveals the susceptibility to noise of mode ordering compared with passive mode locking.

The Stent Patency and Migration Rate of Different Shaped Plastic Stents in Bile Flow Phantom Model and In Vivo Animal Bile Duct Dilation Model.

PubMed

Kwon, Chang-Il; Kim, Gwangil; Jeong, Seok; Lee, Don Haeng; Kim, Kyoung Ah; Ko, Kwang Hyun; Cho, Joo Young; Hong, Sung Pyo

2017-05-01

In research and development of biliary plastic stents (PS), continuous efforts have been made to overcome short patency time and high rate of migration. The aim of this study was to evaluate the patency and migration rate of different PS shapes for a given period of time. Using an in vitro bile phantom model, we compared the patency among different shapes of PS (three straight PS, four double-pigtail PS, and a new screw-shaped PS). We performed an analysis of the degree of luminal narrowing by light microscopic examination. Using an in vivo swine model, we compared the patency and migration rate among the three different types of PS. Eight weeks after the bile exposure in the bile flow phantom model, 80 PS were retrieved and analyzed. The straight PS showed less biofilm formation and luminal narrowing than other types of PS (p < 0.05). Forty-nine PS were inserted into the dilated bile ducts of 10 swine models, and 39 PS were successfully retrieved 8 weeks later. The stent migration occurred less frequently in the double-pigtail PS and the screw-shaped PS than it did in the straight PS (11.1, 10, and 27.3%, respectively). However, there was no statistical difference in stent patency among the different shapes. Stent patency may not be significantly different depending on the shape of PS for 8 weeks. The screw-shaped PS showed similar patency and migration rate to the double-pigtail PS. These results may help guiding future PS development and clinical decisions.

Development and Validation of a Statistical Shape Modeling-Based Finite Element Model of the Cervical Spine Under Low-Level Multiple Direction Loading Conditions

PubMed Central

Bredbenner, Todd L.; Eliason, Travis D.; Francis, W. Loren; McFarland, John M.; Merkle, Andrew C.; Nicolella, Daniel P.

2014-01-01

Cervical spinal injuries are a significant concern in all trauma injuries. Recent military conflicts have demonstrated the substantial risk of spinal injury for the modern warfighter. Finite element models used to investigate injury mechanisms often fail to examine the effects of variation in geometry or material properties on mechanical behavior. The goals of this study were to model geometric variation for a set of cervical spines, to extend this model to a parametric finite element model, and, as a first step, to validate the parametric model against experimental data for low-loading conditions. Individual finite element models were created using cervical spine (C3–T1) computed tomography data for five male cadavers. Statistical shape modeling (SSM) was used to generate a parametric finite element model incorporating variability of spine geometry, and soft-tissue material property variation was also included. The probabilistic loading response of the parametric model was determined under flexion-extension, axial rotation, and lateral bending and validated by comparison to experimental data. Based on qualitative and quantitative comparison of the experimental loading response and model simulations, we suggest that the model performs adequately under relatively low-level loading conditions in multiple loading directions. In conclusion, SSM methods coupled with finite element analyses within a probabilistic framework, along with the ability to statistically validate the overall model performance, provide innovative and important steps toward describing the differences in vertebral morphology, spinal curvature, and variation in material properties. We suggest that these methods, with additional investigation and validation under injurious loading conditions, will lead to understanding and mitigating the risks of injury in the spine and other musculoskeletal structures. PMID:25506051

Prediction of In Vivo Knee Joint Kinematics Using a Combined Dual Fluoroscopy Imaging and Statistical Shape Modeling Technique

PubMed Central

Li, Jing-Sheng; Tsai, Tsung-Yuan; Wang, Shaobai; Li, Pingyue; Kwon, Young-Min; Freiberg, Andrew; Rubash, Harry E.; Li, Guoan

2014-01-01

Using computed tomography (CT) or magnetic resonance (MR) images to construct 3D knee models has been widely used in biomedical engineering research. Statistical shape modeling (SSM) method is an alternative way to provide a fast, cost-efficient, and subject-specific knee modeling technique. This study was aimed to evaluate the feasibility of using a combined dual-fluoroscopic imaging system (DFIS) and SSM method to investigate in vivo knee kinematics. Three subjects were studied during a treadmill walking. The data were compared with the kinematics obtained using a CT-based modeling technique. Geometric root-mean-square (RMS) errors between the knee models constructed using the SSM and CT-based modeling techniques were 1.16 mm and 1.40 mm for the femur and tibia, respectively. For the kinematics of the knee during the treadmill gait, the SSM model can predict the knee kinematics with RMS errors within 3.3 deg for rotation and within 2.4 mm for translation throughout the stance phase of the gait cycle compared with those obtained using the CT-based knee models. The data indicated that the combined DFIS and SSM technique could be used for quick evaluation of knee joint kinematics. PMID:25320846

Multi-object segmentation using coupled nonparametric shape and relative pose priors

NASA Astrophysics Data System (ADS)

Uzunbas, Mustafa Gökhan; Soldea, Octavian; Çetin, Müjdat; Ünal, Gözde; Erçil, Aytül; Unay, Devrim; Ekin, Ahmet; Firat, Zeynep

2009-02-01

We present a new method for multi-object segmentation in a maximum a posteriori estimation framework. Our method is motivated by the observation that neighboring or coupling objects in images generate configurations and co-dependencies which could potentially aid in segmentation if properly exploited. Our approach employs coupled shape and inter-shape pose priors that are computed using training images in a nonparametric multi-variate kernel density estimation framework. The coupled shape prior is obtained by estimating the joint shape distribution of multiple objects and the inter-shape pose priors are modeled via standard moments. Based on such statistical models, we formulate an optimization problem for segmentation, which we solve by an algorithm based on active contours. Our technique provides significant improvements in the segmentation of weakly contrasted objects in a number of applications. In particular for medical image analysis, we use our method to extract brain Basal Ganglia structures, which are members of a complex multi-object system posing a challenging segmentation problem. We also apply our technique to the problem of handwritten character segmentation. Finally, we use our method to segment cars in urban scenes.

Thermophysical modeling of main-belt asteroids from WISE thermal data

NASA Astrophysics Data System (ADS)

Hanuš, J.; Delbo', M.; Ďurech, J.; Alí-Lagoa, V.

2018-07-01

By means of a varied-shape thermophysical model of Hanuš et al. (2015) that takes into account asteroid shape and pole uncertainties, we analyze the thermal infrared data acquired by the NASA's Wide-field Infrared Survey Explorer of about 300 asteroids with derived convex shape models. We utilize publicly available convex shape models and rotation states as input for the thermophysical modeling. For more than one hundred asteroids, the thermophysical modeling gives us an acceptable fit to the thermal infrared data allowing us to report their thermophysical properties such as size, thermal inertia, surface roughness or visible geometric albedo. This work more than doubles the number of asteroids with determined thermophysical properties, especially the thermal inertia. In the remaining cases, the shape model and pole orientation uncertainties, specific rotation or thermophysical properties, poor thermal infrared data or their coverage prevent the determination of reliable thermophysical properties. Finally, we present the main results of the statistical study of derived thermophysical parameters within the whole population of main-belt asteroids and within few asteroid families. Our sizes based on TPM are, in average, consistent with the radiometric sizes reported by Mainzer et al. (2016). The thermal inertia increases with decreasing size, but a large range of thermal inertia values is observed within the similar size ranges between D ∼ 10-100 km. We derived unexpectedly low thermal inertias ( < 20 J m-2 s- 1 / 2 K-1) for several asteroids with sizes 10 < D < 50 km, indicating a very fine and mature regolith on these small bodies. The thermal inertia values seem to be consistent within several collisional families, however, the statistical sample is in all cases rather small. The fast rotators with rotation period P ≲ 4 h tend to have slightly larger thermal inertia values, so probably do not have a fine regolith on the surface. This could be explained, for example, by the loss of the fine regolith due to the centrifugal force, or by the ineffectiveness of the regolith production(e.g., by the thermal cracking mechanism of Delbo' et al. 2014).

Comparison of hypertabastic survival model with other unimodal hazard rate functions using a goodness-of-fit test.

PubMed

Tahir, M Ramzan; Tran, Quang X; Nikulin, Mikhail S

2017-05-30

We studied the problem of testing a hypothesized distribution in survival regression models when the data is right censored and survival times are influenced by covariates. A modified chi-squared type test, known as Nikulin-Rao-Robson statistic, is applied for the comparison of accelerated failure time models. This statistic is used to test the goodness-of-fit for hypertabastic survival model and four other unimodal hazard rate functions. The results of simulation study showed that the hypertabastic distribution can be used as an alternative to log-logistic and log-normal distribution. In statistical modeling, because of its flexible shape of hazard functions, this distribution can also be used as a competitor of Birnbaum-Saunders and inverse Gaussian distributions. The results for the real data application are shown. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

Prostate segmentation in MR images using discriminant boundary features.

PubMed

Yang, Meijuan; Li, Xuelong; Turkbey, Baris; Choyke, Peter L; Yan, Pingkun

2013-02-01

Segmentation of the prostate in magnetic resonance image has become more in need for its assistance to diagnosis and surgical planning of prostate carcinoma. Due to the natural variability of anatomical structures, statistical shape model has been widely applied in medical image segmentation. Robust and distinctive local features are critical for statistical shape model to achieve accurate segmentation results. The scale invariant feature transformation (SIFT) has been employed to capture the information of the local patch surrounding the boundary. However, when SIFT feature being used for segmentation, the scale and variance are not specified with the location of the point of interest. To deal with it, the discriminant analysis in machine learning is introduced to measure the distinctiveness of the learned SIFT features for each landmark directly and to make the scale and variance adaptive to the locations. As the gray values and gradients vary significantly over the boundary of the prostate, separate appearance descriptors are built for each landmark and then optimized. After that, a two stage coarse-to-fine segmentation approach is carried out by incorporating the local shape variations. Finally, the experiments on prostate segmentation from MR image are conducted to verify the efficiency of the proposed algorithms.

The color of sea level: Importance of spatial variations in spectral shape for assessing the significance of trends

NASA Astrophysics Data System (ADS)

Hughes, Chris W.; Williams, Simon D. P.

2010-10-01

We investigate spatial variations in the shape of the spectrum of sea level variability based on a homogeneously sampled 12 year gridded altimeter data set. We present a method of plotting spectral information as color, focusing on periods between 2 and 24 weeks, which shows that significant spatial variations in the spectral shape exist and contain useful dynamical information. Using the Bayesian Information Criterion, we determine that, typically, a fifth-order autoregressive model is needed to capture the structure in the spectrum. Using this model, we show that statistical errors in fitted local trends range between less than 1 and more than 5 times of what would be calculated assuming "white" noise and that the time needed to detect a 1 mm/yr trend ranges between about 5 years and many decades. For global mean sea level, the statistical error reduces to 0.1 mm/yr over 12 years, with only 2 years needed to detect a 1 mm/yr trend. We find significant regional differences in trend from the global mean. The patterns of these regional differences are indicative of a sea level trend dominated by dynamical ocean processes over this period.

Bonded-cell model for particle fracture.

PubMed

Nguyen, Duc-Hanh; Azéma, Emilien; Sornay, Philippe; Radjai, Farhang

2015-02-01

Particle degradation and fracture play an important role in natural granular flows and in many applications of granular materials. We analyze the fracture properties of two-dimensional disklike particles modeled as aggregates of rigid cells bonded along their sides by a cohesive Mohr-Coulomb law and simulated by the contact dynamics method. We show that the compressive strength scales with tensile strength between cells but depends also on the friction coefficient and a parameter describing cell shape distribution. The statistical scatter of compressive strength is well described by the Weibull distribution function with a shape parameter varying from 6 to 10 depending on cell shape distribution. We show that this distribution may be understood in terms of percolating critical intercellular contacts. We propose a random-walk model of critical contacts that leads to particle size dependence of the compressive strength in good agreement with our simulation data.

TH-CD-202-07: A Methodology for Generating Numerical Phantoms for Radiation Therapy Using Geometric Attribute Distribution Models

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

Dolly, S; Chen, H; Mutic, S

Purpose: A persistent challenge for the quality assessment of radiation therapy treatments (e.g. contouring accuracy) is the absence of the known, ground truth for patient data. Moreover, assessment results are often patient-dependent. Computer simulation studies utilizing numerical phantoms can be performed for quality assessment with a known ground truth. However, previously reported numerical phantoms do not include the statistical properties of inter-patient variations, as their models are based on only one patient. In addition, these models do not incorporate tumor data. In this study, a methodology was developed for generating numerical phantoms which encapsulate the statistical variations of patients withinmore » radiation therapy, including tumors. Methods: Based on previous work in contouring assessment, geometric attribute distribution (GAD) models were employed to model both the deterministic and stochastic properties of individual organs via principle component analysis. Using pre-existing radiation therapy contour data, the GAD models are trained to model the shape and centroid distributions of each organ. Then, organs with different shapes and positions can be generated by assigning statistically sound weights to the GAD model parameters. Organ contour data from 20 retrospective prostate patient cases were manually extracted and utilized to train the GAD models. As a demonstration, computer-simulated CT images of generated numerical phantoms were calculated and assessed subjectively and objectively for realism. Results: A cohort of numerical phantoms of the male human pelvis was generated. CT images were deemed realistic both subjectively and objectively in terms of image noise power spectrum. Conclusion: A methodology has been developed to generate realistic numerical anthropomorphic phantoms using pre-existing radiation therapy data. The GAD models guarantee that generated organs span the statistical distribution of observed radiation therapy patients, according to the training dataset. The methodology enables radiation therapy treatment assessment with multi-modality imaging and a known ground truth, and without patient-dependent bias.« less

Cube search, revisited.

PubMed

Zhang, Xuetao; Huang, Jie; Yigit-Elliott, Serap; Rosenholtz, Ruth

2015-03-16

Observers can quickly search among shaded cubes for one lit from a unique direction. However, replace the cubes with similar 2-D patterns that do not appear to have a 3-D shape, and search difficulty increases. These results have challenged models of visual search and attention. We demonstrate that cube search displays differ from those with "equivalent" 2-D search items in terms of the informativeness of fairly low-level image statistics. This informativeness predicts peripheral discriminability of target-present from target-absent patches, which in turn predicts visual search performance, across a wide range of conditions. Comparing model performance on a number of classic search tasks, cube search does not appear unexpectedly easy. Easy cube search, per se, does not provide evidence for preattentive computation of 3-D scene properties. However, search asymmetries derived from rotating and/or flipping the cube search displays cannot be explained by the information in our current set of image statistics. This may merely suggest a need to modify the model's set of 2-D image statistics. Alternatively, it may be difficult cube search that provides evidence for preattentive computation of 3-D scene properties. By attributing 2-D luminance variations to a shaded 3-D shape, 3-D scene understanding may slow search for 2-D features of the target. © 2015 ARVO.

Cube search, revisited

PubMed Central

Zhang, Xuetao; Huang, Jie; Yigit-Elliott, Serap; Rosenholtz, Ruth

2015-01-01

Observers can quickly search among shaded cubes for one lit from a unique direction. However, replace the cubes with similar 2-D patterns that do not appear to have a 3-D shape, and search difficulty increases. These results have challenged models of visual search and attention. We demonstrate that cube search displays differ from those with “equivalent” 2-D search items in terms of the informativeness of fairly low-level image statistics. This informativeness predicts peripheral discriminability of target-present from target-absent patches, which in turn predicts visual search performance, across a wide range of conditions. Comparing model performance on a number of classic search tasks, cube search does not appear unexpectedly easy. Easy cube search, per se, does not provide evidence for preattentive computation of 3-D scene properties. However, search asymmetries derived from rotating and/or flipping the cube search displays cannot be explained by the information in our current set of image statistics. This may merely suggest a need to modify the model's set of 2-D image statistics. Alternatively, it may be difficult cube search that provides evidence for preattentive computation of 3-D scene properties. By attributing 2-D luminance variations to a shaded 3-D shape, 3-D scene understanding may slow search for 2-D features of the target. PMID:25780063

Deformable segmentation via sparse representation and dictionary learning.

PubMed

Zhang, Shaoting; Zhan, Yiqiang; Metaxas, Dimitris N

2012-10-01

"Shape" and "appearance", the two pillars of a deformable model, complement each other in object segmentation. In many medical imaging applications, while the low-level appearance information is weak or mis-leading, shape priors play a more important role to guide a correct segmentation, thanks to the strong shape characteristics of biological structures. Recently a novel shape prior modeling method has been proposed based on sparse learning theory. Instead of learning a generative shape model, shape priors are incorporated on-the-fly through the sparse shape composition (SSC). SSC is robust to non-Gaussian errors and still preserves individual shape characteristics even when such characteristics is not statistically significant. Although it seems straightforward to incorporate SSC into a deformable segmentation framework as shape priors, the large-scale sparse optimization of SSC has low runtime efficiency, which cannot satisfy clinical requirements. In this paper, we design two strategies to decrease the computational complexity of SSC, making a robust, accurate and efficient deformable segmentation system. (1) When the shape repository contains a large number of instances, which is often the case in 2D problems, K-SVD is used to learn a more compact but still informative shape dictionary. (2) If the derived shape instance has a large number of vertices, which often appears in 3D problems, an affinity propagation method is used to partition the surface into small sub-regions, on which the sparse shape composition is performed locally. Both strategies dramatically decrease the scale of the sparse optimization problem and hence speed up the algorithm. Our method is applied on a diverse set of biomedical image analysis problems. Compared to the original SSC, these two newly-proposed modules not only significant reduce the computational complexity, but also improve the overall accuracy. Copyright © 2012 Elsevier B.V. All rights reserved.

Extracting Spurious Latent Classes in Growth Mixture Modeling with Nonnormal Errors

ERIC Educational Resources Information Center

Guerra-Peña, Kiero; Steinley, Douglas

2016-01-01

Growth mixture modeling is generally used for two purposes: (1) to identify mixtures of normal subgroups and (2) to approximate oddly shaped distributions by a mixture of normal components. Often in applied research this methodology is applied to both of these situations indistinctly: using the same fit statistics and likelihood ratio tests. This…

Statistics of Dark Matter Halos from Gravitational Lensing.

PubMed

Jain; Van Waerbeke L

2000-02-10

We present a new approach to measure the mass function of dark matter halos and to discriminate models with differing values of Omega through weak gravitational lensing. We measure the distribution of peaks from simulated lensing surveys and show that the lensing signal due to dark matter halos can be detected for a wide range of peak heights. Even when the signal-to-noise ratio is well below the limit for detection of individual halos, projected halo statistics can be constrained for halo masses spanning galactic to cluster halos. The use of peak statistics relies on an analytical model of the noise due to the intrinsic ellipticities of source galaxies. The noise model has been shown to accurately describe simulated data for a variety of input ellipticity distributions. We show that the measured peak distribution has distinct signatures of gravitational lensing, and its non-Gaussian shape can be used to distinguish models with different values of Omega. The use of peak statistics is complementary to the measurement of field statistics, such as the ellipticity correlation function, and is possibly not susceptible to the same systematic errors.

A flexibly shaped space-time scan statistic for disease outbreak detection and monitoring.

PubMed

Takahashi, Kunihiko; Kulldorff, Martin; Tango, Toshiro; Yih, Katherine

2008-04-11

Early detection of disease outbreaks enables public health officials to implement disease control and prevention measures at the earliest possible time. A time periodic geographical disease surveillance system based on a cylindrical space-time scan statistic has been used extensively for disease surveillance along with the SaTScan software. In the purely spatial setting, many different methods have been proposed to detect spatial disease clusters. In particular, some spatial scan statistics are aimed at detecting irregularly shaped clusters which may not be detected by the circular spatial scan statistic. Based on the flexible purely spatial scan statistic, we propose a flexibly shaped space-time scan statistic for early detection of disease outbreaks. The performance of the proposed space-time scan statistic is compared with that of the cylindrical scan statistic using benchmark data. In order to compare their performances, we have developed a space-time power distribution by extending the purely spatial bivariate power distribution. Daily syndromic surveillance data in Massachusetts, USA, are used to illustrate the proposed test statistic. The flexible space-time scan statistic is well suited for detecting and monitoring disease outbreaks in irregularly shaped areas.

Evaluation of the Gini Coefficient in Spatial Scan Statistics for Detecting Irregularly Shaped Clusters

PubMed Central

Kim, Jiyu; Jung, Inkyung

2017-01-01

Spatial scan statistics with circular or elliptic scanning windows are commonly used for cluster detection in various applications, such as the identification of geographical disease clusters from epidemiological data. It has been pointed out that the method may have difficulty in correctly identifying non-compact, arbitrarily shaped clusters. In this paper, we evaluated the Gini coefficient for detecting irregularly shaped clusters through a simulation study. The Gini coefficient, the use of which in spatial scan statistics was recently proposed, is a criterion measure for optimizing the maximum reported cluster size. Our simulation study results showed that using the Gini coefficient works better than the original spatial scan statistic for identifying irregularly shaped clusters, by reporting an optimized and refined collection of clusters rather than a single larger cluster. We have provided a real data example that seems to support the simulation results. We think that using the Gini coefficient in spatial scan statistics can be helpful for the detection of irregularly shaped clusters. PMID:28129368

Forensic age estimation by morphometric analysis of the manubrium from 3D MR images.

PubMed

Martínez Vera, Naira P; Höller, Johannes; Widek, Thomas; Neumayer, Bernhard; Ehammer, Thomas; Urschler, Martin

2017-08-01

Forensic age estimation research based on skeletal structures focuses on patterns of growth and development using different bones. In this work, our aim was to study growth-related evolution of the manubrium in living adolescents and young adults using magnetic resonance imaging (MRI), which is an image acquisition modality that does not involve ionizing radiation. In a first step, individual manubrium and subject features were correlated with age, which confirmed a statistically significant change of manubrium volume (M vol :p<0.01, R 2 ¯=0.50) and surface area (M sur :p<0.01, R 2 ¯=0.53) for the studied age range. Additionally, shapes of the manubria were for the first time investigated using principal component analysis. The decomposition of the data in principal components allowed to analyse the contribution of each component to total shape variation. With 13 principal components, ∼96% of shape variation could be described (M shp :p<0.01, R 2 ¯=0.60). Multiple linear regression analysis modelled the relationship between the statistically best correlated variables and age. Models including manubrium shape, volume or surface area divided by the height of the subject (Y∼M shp M sur /S h :p<0.01, R 2 ¯=0.71; Y∼M shp M vol /S h :p<0.01, R 2 ¯=0.72) presented a standard error of estimate of two years. In order to estimate the accuracy of these two manubrium-based age estimation models, cross validation experiments predicting age on held-out test sets were performed. Median absolute difference of predicted and known chronological age was 1.18 years for the best performing model (Y∼M shp M sur /S h :p<0.01, R p 2 =0.67). In conclusion, despite limitations in determining legal majority age, manubrium morphometry analysis presented statistically significant results for skeletal age estimation, which indicates that this bone structure may be considered as a new candidate in multi-factorial MRI-based age estimation. Copyright © 2017 Elsevier B.V. All rights reserved.

Lower limb estimation from sparse landmarks using an articulated shape model.

PubMed

Zhang, Ju; Fernandez, Justin; Hislop-Jambrich, Jacqui; Besier, Thor F

2016-12-08

Rapid generation of lower limb musculoskeletal models is essential for clinically applicable patient-specific gait modeling. Estimation of muscle and joint contact forces requires accurate representation of bone geometry and pose, as well as their muscle attachment sites, which define muscle moment arms. Motion-capture is a routine part of gait assessment but contains relatively sparse geometric information. Standard methods for creating customized models from motion-capture data scale a reference model without considering natural shape variations. We present an articulated statistical shape model of the left lower limb with embedded anatomical landmarks and muscle attachment regions. This model is used in an automatic workflow, implemented in an easy-to-use software application, that robustly and accurately estimates realistic lower limb bone geometry, pose, and muscle attachment regions from seven commonly used motion-capture landmarks. Estimated bone models were validated on noise-free marker positions to have a lower (p=0.001) surface-to-surface root-mean-squared error of 4.28mm, compared to 5.22mm using standard isotropic scaling. Errors at a variety of anatomical landmarks were also lower (8.6mm versus 10.8mm, p=0.001). We improve upon standard lower limb model scaling methods with shape model-constrained realistic bone geometries, regional muscle attachment sites, and higher accuracy. Copyright © 2016 Elsevier Ltd. All rights reserved.

Global-to-local, shape-based, real and virtual landmarks for shape modeling by recursive boundary subdivision

NASA Astrophysics Data System (ADS)

Rueda, Sylvia; Udupa, Jayaram K.

2011-03-01

Landmark based statistical object modeling techniques, such as Active Shape Model (ASM), have proven useful in medical image analysis. Identification of the same homologous set of points in a training set of object shapes is the most crucial step in ASM, which has encountered challenges such as (C1) defining and characterizing landmarks; (C2) ensuring homology; (C3) generalizing to n > 2 dimensions; (C4) achieving practical computations. In this paper, we propose a novel global-to-local strategy that attempts to address C3 and C4 directly and works in Rn. The 2D version starts from two initial corresponding points determined in all training shapes via a method α, and subsequently by subdividing the shapes into connected boundary segments by a line determined by these points. A shape analysis method β is applied on each segment to determine a landmark on the segment. This point introduces more pairs of points, the lines defined by which are used to further subdivide the boundary segments. This recursive boundary subdivision (RBS) process continues simultaneously on all training shapes, maintaining synchrony of the level of recursion, and thereby keeping correspondence among generated points automatically by the correspondence of the homologous shape segments in all training shapes. The process terminates when no subdividing lines are left to be considered that indicate (as per method β) that a point can be selected on the associated segment. Examples of α and β are presented based on (a) distance; (b) Principal Component Analysis (PCA); and (c) the novel concept of virtual landmarks.

QSAR study of curcumine derivatives as HIV-1 integrase inhibitors.

PubMed

Gupta, Pawan; Sharma, Anju; Garg, Prabha; Roy, Nilanjan

2013-03-01

A QSAR study was performed on curcumine derivatives as HIV-1 integrase inhibitors using multiple linear regression. The statistically significant model was developed with squared correlation coefficients (r(2)) 0.891 and cross validated r(2) (r(2) cv) 0.825. The developed model revealed that electronic, shape, size, geometry, substitution's information and hydrophilicity were important atomic properties for determining the inhibitory activity of these molecules. The model was also tested successfully for external validation (r(2) pred = 0.849) as well as Tropsha's test for model predictability. Furthermore, the domain analysis was carried out to evaluate the prediction reliability of external set molecules. The model was statistically robust and had good predictive power which can be successfully utilized for screening of new molecules.

Uncovering Topological Structures in Unstructured Data

DTIC Science & Technology

2015-04-20

paper [4] presents an approach for constructing statistical shape models (SSMs) for aortic surfaces with the eventual goal of mapping the mean aorta ...characterize the variation pattern are found after optimizing the group-wise correspondence across the aorta training set. We use the direct

Why the Long Face? The Mechanics of Mandibular Symphysis Proportions in Crocodiles

PubMed Central

Walmsley, Christopher W.; Smits, Peter D.; Quayle, Michelle R.; McCurry, Matthew R.; Richards, Heather S.; Oldfield, Christopher C.; Wroe, Stephen; Clausen, Phillip D.; McHenry, Colin R.

2013-01-01

Background Crocodilians exhibit a spectrum of rostral shape from long snouted (longirostrine), through to short snouted (brevirostrine) morphologies. The proportional length of the mandibular symphysis correlates consistently with rostral shape, forming as much as 50% of the mandible’s length in longirostrine forms, but 10% in brevirostrine crocodilians. Here we analyse the structural consequences of an elongate mandibular symphysis in relation to feeding behaviours. Methods/Principal Findings Simple beam and high resolution Finite Element (FE) models of seven species of crocodile were analysed under loads simulating biting, shaking and twisting. Using beam theory, we statistically compared multiple hypotheses of which morphological variables should control the biomechanical response. Brevi- and mesorostrine morphologies were found to consistently outperform longirostrine types when subject to equivalent biting, shaking and twisting loads. The best predictors of performance for biting and twisting loads in FE models were overall length and symphyseal length respectively; for shaking loads symphyseal length and a multivariate measurement of shape (PC1– which is strongly but not exclusively correlated with symphyseal length) were equally good predictors. Linear measurements were better predictors than multivariate measurements of shape in biting and twisting loads. For both biting and shaking loads but not for twisting, simple beam models agree with best performance predictors in FE models. Conclusions/Significance Combining beam and FE modelling allows a priori hypotheses about the importance of morphological traits on biomechanics to be statistically tested. Short mandibular symphyses perform well under loads used for feeding upon large prey, but elongate symphyses incur high strains under equivalent loads, underlining the structural constraints to prey size in the longirostrine morphotype. The biomechanics of the crocodilian mandible are largely consistent with beam theory and can be predicted from simple morphological measurements, suggesting that crocodilians are a useful model for investigating the palaeobiomechanics of other aquatic tetrapods. PMID:23342027

The Effect of Photon Statistics and Pulse Shaping on the Performance of the Wiener Filter Crystal Identification Algorithm Applied to LabPET Phoswich Detectors

NASA Astrophysics Data System (ADS)

Yousefzadeh, Hoorvash Camilia; Lecomte, Roger; Fontaine, Réjean

2012-06-01

A fast Wiener filter-based crystal identification (WFCI) algorithm was recently developed to discriminate crystals with close scintillation decay times in phoswich detectors. Despite the promising performance of WFCI, the influence of various physical factors and electrical noise sources of the data acquisition chain (DAQ) on the crystal identification process was not fully investigated. This paper examines the effect of different noise sources, such as photon statistics, avalanche photodiode (APD) excess multiplication noise, and front-end electronic noise, as well as the influence of different shaping filters on the performance of the WFCI algorithm. To this end, a PET-like signal simulator based on a model of the LabPET DAQ, a small animal APD-based digital PET scanner, was developed. Simulated signals were generated under various noise conditions with CR-RC shapers of order 1, 3, and 5 having different time constants (τ). Applying the WFCI algorithm to these simulated signals showed that the non-stationary Poisson photon statistics is the main contributor to the identification error of WFCI algorithm. A shaping filter of order 1 with τ = 50 ns yielded the best WFCI performance (error 1%), while a longer shaping time of τ = 100 ns slightly degraded the WFCI performance (error 3%). Filters of higher orders with fast shaping time constants (10-33 ns) also produced good WFCI results (error 1.4% to 1.6%). This study shows the advantage of the pulse simulator in evaluating various DAQ conditions and confirms the influence of the detection chain on the WFCI performance.

Thermodynamic limit of random partitions and dispersionless Toda hierarchy

NASA Astrophysics Data System (ADS)

Takasaki, Kanehisa; Nakatsu, Toshio

2012-01-01

We study the thermodynamic limit of random partition models for the instanton sum of 4D and 5D supersymmetric U(1) gauge theories deformed by some physical observables. The physical observables correspond to external potentials in the statistical model. The partition function is reformulated in terms of the density function of Maya diagrams. The thermodynamic limit is governed by a limit shape of Young diagrams associated with dominant terms in the partition function. The limit shape is characterized by a variational problem, which is further converted to a scalar-valued Riemann-Hilbert problem. This Riemann-Hilbert problem is solved with the aid of a complex curve, which may be thought of as the Seiberg-Witten curve of the deformed U(1) gauge theory. This solution of the Riemann-Hilbert problem is identified with a special solution of the dispersionless Toda hierarchy that satisfies a pair of generalized string equations. The generalized string equations for the 5D gauge theory are shown to be related to hidden symmetries of the statistical model. The prepotential and the Seiberg-Witten differential are also considered.

Stage-structured transmission of phocine distemper virus in the Dutch 2002 outbreak

PubMed Central

Klepac, Petra; Pomeroy, Laura W.; Bjørnstad, Ottar N.; Kuiken, Thijs; Osterhaus, Albert D.M.E.; Rijks, Jolianne M.

2009-01-01

Heterogeneities in transmission among hosts can be very important in shaping infectious disease dynamics. In mammals with strong social organization, such heterogeneities are often structured by functional stage: juveniles, subadults and adults. We investigate the importance of such stage-related heterogeneities in shaping the 2002 phocine distemper virus (PDV) outbreak in the Dutch Wadden Sea, when more than 40 per cent of the harbour seals were killed. We do this by comparing the statistical fit of a hierarchy of models with varying transmission complexity: homogeneous versus heterogeneous mixing and density- versus frequency-dependent transmission. We use the stranding data as a proxy for incidence and use Poisson likelihoods to estimate the ‘who acquires infection from whom’ (WAIFW) matrix. Statistically, the model with strong heterogeneous mixing and density-dependent transmission was found to best describe the transmission dynamics. However, patterns of incidence support a model of frequency-dependent transmission among adults and juveniles. Based on the maximum-likelihood WAIFW matrix estimates, we use the next-generation formalism to calculate an R0 between 2 and 2.5 for the Dutch 2002 PDV epidemic. PMID:19364743

The Center for Computational Biology: resources, achievements, and challenges

PubMed Central

Dinov, Ivo D; Thompson, Paul M; Woods, Roger P; Van Horn, John D; Shattuck, David W; Parker, D Stott

2011-01-01

The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains. PMID:22081221

The Center for Computational Biology: resources, achievements, and challenges.

PubMed

Toga, Arthur W; Dinov, Ivo D; Thompson, Paul M; Woods, Roger P; Van Horn, John D; Shattuck, David W; Parker, D Stott

2012-01-01

The Center for Computational Biology (CCB) is a multidisciplinary program where biomedical scientists, engineers, and clinicians work jointly to combine modern mathematical and computational techniques, to perform phenotypic and genotypic studies of biological structure, function, and physiology in health and disease. CCB has developed a computational framework built around the Manifold Atlas, an integrated biomedical computing environment that enables statistical inference on biological manifolds. These manifolds model biological structures, features, shapes, and flows, and support sophisticated morphometric and statistical analyses. The Manifold Atlas includes tools, workflows, and services for multimodal population-based modeling and analysis of biological manifolds. The broad spectrum of biomedical topics explored by CCB investigators include the study of normal and pathological brain development, maturation and aging, discovery of associations between neuroimaging and genetic biomarkers, and the modeling, analysis, and visualization of biological shape, form, and size. CCB supports a wide range of short-term and long-term collaborations with outside investigators, which drive the center's computational developments and focus the validation and dissemination of CCB resources to new areas and scientific domains.

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

Harris, Michael D.; Dater, Manasi; Whitaker, Ross

In this study, statistical shape modeling (SSM) was used to quantify three-dimensional (3D) variation and morphologic differences between femurs with and without cam femoroacetabular impingement (FAI). 3D surfaces were generated from CT scans of femurs from 41 controls and 30 cam FAI patients. SSM correspondence particles were optimally positioned on each surface using a gradient descent energy function. Mean shapes for control and patient groups were defined from the resulting particle configurations. Morphological differences between group mean shapes and between the control mean and individual patients were calculated. Principal component analysis was used to describe anatomical variation present in bothmore » groups. The first 6 modes (or principal components) captured statistically significant shape variations, which comprised 84% of cumulative variation among the femurs. Shape variation was greatest in femoral offset, greater trochanter height, and the head-neck junction. The mean cam femur shape protruded above the control mean by a maximum of 3.3 mm with sustained protrusions of 2.5-3.0 mm along the anterolateral head-neck junction and distally along the anterior neck, corresponding well with reported cam lesion locations and soft-tissue damage. This study provides initial evidence that SSM can describe variations in femoral morphology in both controls and cam FAI patients and may be useful for developing new measurements of pathological anatomy. SSM may also be applied to characterize cam FAI severity and provide templates to guide patient-specific surgical resection of bone.« less

Effect of Gravity Level on the Particle Shape and Size During Zeolite Crystal Growth

NASA Technical Reports Server (NTRS)

Song, Hong-Wei; Ilebusi, Olusegun J.; Sacco, Albert, Jr.

2003-01-01

A microscopic diffusion model is developed to represent solute transport in the boundary layer of a growing zeolite crystal. This model is used to describe the effect of gravity on particle shape and solute distribution. Particle dynamics and crystal growth kinetics serve as the boundary conditions of flow and convection-diffusion equations. A statistical rate theory is used to obtain the rate of solute transport across the growing interface, which is expressed in terms of concentration and velocity of solute species. Microgravity can significantly decrease the solute velocity across the growing interface compared to its earth-based counterpart. The extent of this reduction highly depends on solute diffusion constant in solution. Under gravity, the flow towards the crystal enhances solute transport rate across the growing interface while the flow away from crystals reduces this rate, suggesting a non-uniform growth rate and thus an elliptic final shape. However, microgravity can significantly reduce the influence of flow and obtain a final product with perfect spherical shape. The model predictions compare favorably with the data of space experiment of zeolites grown in space.

A Parametric Model of Shoulder Articulation for Virtual Assessment of Space Suit Fit

NASA Technical Reports Server (NTRS)

Kim, K. Han; Young, Karen S.; Bernal, Yaritza; Boppana, Abhishektha; Vu, Linh Q.; Benson, Elizabeth A.; Jarvis, Sarah; Rajulu, Sudhakar L.

2016-01-01

Suboptimal suit fit is a known risk factor for crewmember shoulder injury. Suit fit assessment is however prohibitively time consuming and cannot be generalized across wide variations of body shapes and poses. In this work, we have developed a new design tool based on the statistical analysis of body shape scans. This tool is aimed at predicting the skin deformation and shape variations for any body size and shoulder pose for a target population. This new process, when incorporated with CAD software, will enable virtual suit fit assessments, predictively quantifying the contact volume, and clearance between the suit and body surface at reduced time and cost.

Face shape differs in phylogenetically related populations.

PubMed

Hopman, Saskia M J; Merks, Johannes H M; Suttie, Michael; Hennekam, Raoul C M; Hammond, Peter

2014-11-01

3D analysis of facial morphology has delineated facial phenotypes in many medical conditions and detected fine grained differences between typical and atypical patients to inform genotype-phenotype studies. Next-generation sequencing techniques have enabled extremely detailed genotype-phenotype correlative analysis. Such comparisons typically employ control groups matched for age, sex and ethnicity and the distinction between ethnic categories in genotype-phenotype studies has been widely debated. The phylogenetic tree based on genetic polymorphism studies divides the world population into nine subpopulations. Here we show statistically significant face shape differences between two European Caucasian populations of close phylogenetic and geographic proximity from the UK and The Netherlands. The average face shape differences between the Dutch and UK cohorts were visualised in dynamic morphs and signature heat maps, and quantified for their statistical significance using both conventional anthropometry and state of the art dense surface modelling techniques. Our results demonstrate significant differences between Dutch and UK face shape. Other studies have shown that genetic variants influence normal facial variation. Thus, face shape difference between populations could reflect underlying genetic difference. This should be taken into account in genotype-phenotype studies and we recommend that in those studies reference groups be established in the same population as the individuals who form the subject of the study.

Principal component analysis in construction of 3D human knee joint models using a statistical shape model method.

PubMed

Tsai, Tsung-Yuan; Li, Jing-Sheng; Wang, Shaobai; Li, Pingyue; Kwon, Young-Min; Li, Guoan

2015-01-01

The statistical shape model (SSM) method that uses 2D images of the knee joint to predict the three-dimensional (3D) joint surface model has been reported in the literature. In this study, we constructed a SSM database using 152 human computed tomography (CT) knee joint models, including the femur, tibia and patella and analysed the characteristics of each principal component of the SSM. The surface models of two in vivo knees were predicted using the SSM and their 2D bi-plane fluoroscopic images. The predicted models were compared to their CT joint models. The differences between the predicted 3D knee joint surfaces and the CT image-based surfaces were 0.30 ± 0.81 mm, 0.34 ± 0.79 mm and 0.36 ± 0.59 mm for the femur, tibia and patella, respectively (average ± standard deviation). The computational time for each bone of the knee joint was within 30 s using a personal computer. The analysis of this study indicated that the SSM method could be a useful tool to construct 3D surface models of the knee with sub-millimeter accuracy in real time. Thus, it may have a broad application in computer-assisted knee surgeries that require 3D surface models of the knee.

Statistics of acoustic emissions and stress drops during granular shearing using a stick-slip fiber bundle mode

NASA Astrophysics Data System (ADS)

Cohen, D.; Michlmayr, G.; Or, D.

2012-04-01

Shearing of dense granular materials appears in many engineering and Earth sciences applications. Under a constant strain rate, the shearing stress at steady state oscillates with slow rises followed by rapid drops that are linked to the build up and failure of force chains. Experiments indicate that these drops display exponential statistics. Measurements of acoustic emissions during shearing indicates that the energy liberated by failure of these force chains has power-law statistics. Representing force chains as fibers, we use a stick-slip fiber bundle model to obtain analytical solutions of the statistical distribution of stress drops and failure energy. In the model, fibers stretch, fail, and regain strength during deformation. Fibers have Weibull-distributed threshold strengths with either quenched and annealed disorder. The shape of the distribution for drops and energy obtained from the model are similar to those measured during shearing experiments. This simple model may be useful to identify failure events linked to force chain failures. Future generalizations of the model that include different types of fiber failure may also allow identification of different types of granular failures that have distinct statistical acoustic emission signatures.

Body Fineness Ratio as a Predictor of Maximum Prolonged-Swimming Speed in Coral Reef Fishes

PubMed Central

Walker, Jeffrey A.; Alfaro, Michael E.; Noble, Mae M.; Fulton, Christopher J.

2013-01-01

The ability to sustain high swimming speeds is believed to be an important factor affecting resource acquisition in fishes. While we have gained insights into how fin morphology and motion influences swimming performance in coral reef fishes, the role of other traits, such as body shape, remains poorly understood. We explore the ability of two mechanistic models of the causal relationship between body fineness ratio and endurance swimming-performance to predict maximum prolonged-swimming speed (Umax) among 84 fish species from the Great Barrier Reef, Australia. A drag model, based on semi-empirical data on the drag of rigid, submerged bodies of revolution, was applied to species that employ pectoral-fin propulsion with a rigid body at U max. An alternative model, based on the results of computer simulations of optimal shape in self-propelled undulating bodies, was applied to the species that swim by body-caudal-fin propulsion at Umax. For pectoral-fin swimmers, Umax increased with fineness, and the rate of increase decreased with fineness, as predicted by the drag model. While the mechanistic and statistical models of the relationship between fineness and Umax were very similar, the mechanistic (and statistical) model explained only a small fraction of the variance in Umax. For body-caudal-fin swimmers, we found a non-linear relationship between fineness and Umax, which was largely negative over most of the range of fineness. This pattern fails to support either predictions from the computational models or standard functional interpretations of body shape variation in fishes. Our results suggest that the widespread hypothesis that a more optimal fineness increases endurance-swimming performance via reduced drag should be limited to fishes that swim with rigid bodies. PMID:24204575

Statistical shape analysis using 3D Poisson equation--A quantitatively validated approach.

PubMed

Gao, Yi; Bouix, Sylvain

2016-05-01

Statistical shape analysis has been an important area of research with applications in biology, anatomy, neuroscience, agriculture, paleontology, etc. Unfortunately, the proposed methods are rarely quantitatively evaluated, and as shown in recent studies, when they are evaluated, significant discrepancies exist in their outputs. In this work, we concentrate on the problem of finding the consistent location of deformation between two population of shapes. We propose a new shape analysis algorithm along with a framework to perform a quantitative evaluation of its performance. Specifically, the algorithm constructs a Signed Poisson Map (SPoM) by solving two Poisson equations on the volumetric shapes of arbitrary topology, and statistical analysis is then carried out on the SPoMs. The method is quantitatively evaluated on synthetic shapes and applied on real shape data sets in brain structures. Copyright © 2016 Elsevier B.V. All rights reserved.

Towards random matrix model of breaking the time-reversal invariance of elastic waves in chaotic cavities by feedback

NASA Astrophysics Data System (ADS)

Antoniuk, Oleg; Sprik, Rudolf

2010-03-01

We developed a random matrix model to describe the statistics of resonances in an acoustic cavity with broken time-reversal invariance. Time-reversal invariance braking is achieved by connecting an amplified feedback loop between two transducers on the surface of the cavity. The model is based on approach [1] that describes time- reversal properties of the cavity without a feedback loop. Statistics of eigenvalues (nearest neighbor resonance spacing distributions and spectral rigidity) has been calculated and compared to the statistics obtained from our experimental data. Experiments have been performed on aluminum block of chaotic shape confining ultrasound waves. [1] Carsten Draeger and Mathias Fink, One-channel time- reversal in chaotic cavities: Theoretical limits, Journal of Acoustical Society of America, vol. 105, Nr. 2, pp. 611-617 (1999)

LES/PDF studies of joint statistics of mixture fraction and progress variable in piloted methane jet flames with inhomogeneous inlet flows

NASA Astrophysics Data System (ADS)

Zhang, Pei; Barlow, Robert; Masri, Assaad; Wang, Haifeng

2016-11-01

The mixture fraction and progress variable are often used as independent variables for describing turbulent premixed and non-premixed flames. There is a growing interest in using these two variables for describing partially premixed flames. The joint statistical distribution of the mixture fraction and progress variable is of great interest in developing models for partially premixed flames. In this work, we conduct predictive studies of the joint statistics of mixture fraction and progress variable in a series of piloted methane jet flames with inhomogeneous inlet flows. The employed models combine large eddy simulations with the Monte Carlo probability density function (PDF) method. The joint PDFs and marginal PDFs are examined in detail by comparing the model predictions and the measurements. Different presumed shapes of the joint PDFs are also evaluated.

cgDNAweb: a web interface to the cgDNA sequence-dependent coarse-grain model of double-stranded DNA.

PubMed

De Bruin, Lennart; Maddocks, John H

2018-06-14

The sequence-dependent statistical mechanical properties of fragments of double-stranded DNA is believed to be pertinent to its biological function at length scales from a few base pairs (or bp) to a few hundreds of bp, e.g. indirect read-out protein binding sites, nucleosome positioning sequences, phased A-tracts, etc. In turn, the equilibrium statistical mechanics behaviour of DNA depends upon its ground state configuration, or minimum free energy shape, as well as on its fluctuations as governed by its stiffness (in an appropriate sense). We here present cgDNAweb, which provides browser-based interactive visualization of the sequence-dependent ground states of double-stranded DNA molecules, as predicted by the underlying cgDNA coarse-grain rigid-base model of fragments with arbitrary sequence. The cgDNAweb interface is specifically designed to facilitate comparison between ground state shapes of different sequences. The server is freely available at cgDNAweb.epfl.ch with no login requirement.

Intrinsic alignment in redMaPPer clusters – II. Radial alignment of satellites towards cluster centres

DOE PAGES

Huang, Hung-Jin; Mandelbaum, Rachel; Freeman, Peter E.; ...

2017-11-23

We study the orientations of satellite galaxies in redMaPPer clusters constructed from the Sloan Digital Sky Survey at 0.1 < z < 0.35 to determine whether there is any preferential tendency for satellites to point radially towards cluster centres. Here, we analyse the satellite alignment (SA) signal based on three shape measurement methods (re-Gaussianization, de Vaucouleurs, and isophotal shapes), which trace galaxy light profiles at different radii. The measured SA signal depends on these shape measurement methods. We detect the strongest SA signal in isophotal shapes, followed by de Vaucouleurs shapes. While no net SA signal is detected using re-Gaussianizationmore » shapes across the entire sample, the observed SA signal reaches a statistically significant level when limiting to a subsample of higher luminosity satellites. We further investigate the impact of noise, systematics, and real physical isophotal twisting effects in the comparison between the SA signal detected via different shape measurement methods. Unlike previous studies, which only consider the dependence of SA on a few parameters, here we explore a total of 17 galaxy and cluster properties, using a statistical model averaging technique to naturally account for parameter correlations and identify significant SA predictors. We find that the measured SA signal is strongest for satellites with the following characteristics: higher luminosity, smaller distance to the cluster centre, rounder in shape, higher bulge fraction, and distributed preferentially along the major axis directions of their centrals. Finally, we provide physical explanations for the identified dependences and discuss the connection to theories of SA.« less

Intrinsic alignment in redMaPPer clusters – II. Radial alignment of satellites towards cluster centres

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

Huang, Hung-Jin; Mandelbaum, Rachel; Freeman, Peter E.

We study the orientations of satellite galaxies in redMaPPer clusters constructed from the Sloan Digital Sky Survey at 0.1 < z < 0.35 to determine whether there is any preferential tendency for satellites to point radially towards cluster centres. Here, we analyse the satellite alignment (SA) signal based on three shape measurement methods (re-Gaussianization, de Vaucouleurs, and isophotal shapes), which trace galaxy light profiles at different radii. The measured SA signal depends on these shape measurement methods. We detect the strongest SA signal in isophotal shapes, followed by de Vaucouleurs shapes. While no net SA signal is detected using re-Gaussianizationmore » shapes across the entire sample, the observed SA signal reaches a statistically significant level when limiting to a subsample of higher luminosity satellites. We further investigate the impact of noise, systematics, and real physical isophotal twisting effects in the comparison between the SA signal detected via different shape measurement methods. Unlike previous studies, which only consider the dependence of SA on a few parameters, here we explore a total of 17 galaxy and cluster properties, using a statistical model averaging technique to naturally account for parameter correlations and identify significant SA predictors. We find that the measured SA signal is strongest for satellites with the following characteristics: higher luminosity, smaller distance to the cluster centre, rounder in shape, higher bulge fraction, and distributed preferentially along the major axis directions of their centrals. Finally, we provide physical explanations for the identified dependences and discuss the connection to theories of SA.« less

Shape analysis of corpus callosum in autism subtype using planar conformal mapping

NASA Astrophysics Data System (ADS)

He, Qing; Duan, Ye; Yin, Xiaotian; Gu, Xianfeng; Karsch, Kevin; Miles, Judith

2009-02-01

A number of studies have documented that autism has a neurobiological basis, but the anatomical extent of these neurobiological abnormalities is largely unknown. In this study, we aimed at analyzing highly localized shape abnormalities of the corpus callosum in a homogeneous group of autism children. Thirty patients with essential autism and twenty-four controls participated in this study. 2D contours of the corpus callosum were extracted from MR images by a semiautomatic segmentation method, and the 3D model was constructed by stacking the contours. The resulting 3D model had two openings at the ends, thus a new conformal parameterization for high genus surfaces was applied in our shape analysis work, which mapped each surface onto a planar domain. Surface matching among different individual meshes was achieved by re-triangulating each mesh according to a template surface. Statistical shape analysis was used to compare the 3D shapes point by point between patients with autism and their controls. The results revealed significant abnormalities in the anterior most and anterior body in essential autism group.

Aging ballistic Lévy walks

NASA Astrophysics Data System (ADS)

Magdziarz, Marcin; Zorawik, Tomasz

2017-02-01

Aging can be observed for numerous physical systems. In such systems statistical properties [like probability distribution, mean square displacement (MSD), first-passage time] depend on a time span ta between the initialization and the beginning of observations. In this paper we study aging properties of ballistic Lévy walks and two closely related jump models: wait-first and jump-first. We calculate explicitly their probability distributions and MSDs. It turns out that despite similarities these models react very differently to the delay ta. Aging weakly affects the shape of probability density function and MSD of standard Lévy walks. For the jump models the shape of the probability density function is changed drastically. Moreover for the wait-first jump model we observe a different behavior of MSD when ta≪t and ta≫t .

Representation and visualization of variability in a 3D anatomical atlas using the kidney as an example

NASA Astrophysics Data System (ADS)

Hacker, Silke; Handels, Heinz

2006-03-01

Computer-based 3D atlases allow an interactive exploration of the human body. However, in most cases such 3D atlases are derived from one single individual, and therefore do not regard the variability of anatomical structures concerning their shape and size. Since the geometric variability across humans plays an important role in many medical applications, our goal is to develop a framework of an anatomical atlas for representation and visualization of the variability of selected anatomical structures. The basis of the project presented is the VOXEL-MAN atlas of inner organs that was created from the Visible Human data set. For modeling anatomical shapes and their variability we utilize "m-reps" which allow a compact representation of anatomical objects on the basis of their skeletons. As an example we used a statistical model of the kidney that is based on 48 different variants. With the integration of a shape description into the VOXEL-MAN atlas it is now possible to query and visualize different shape variations of an organ, e.g. by specifying a person's age or gender. In addition to the representation of individual shape variants, the average shape of a population can be displayed. Besides a surface representation, a volume-based representation of the kidney's shape variants is also possible. It results from the deformation of the reference kidney of the volume-based model using the m-rep shape description. In this way a realistic visualization of the shape variants becomes possible, as well as the visualization of the organ's internal structures.

Three dimensional measurement of minimum joint space width in the knee from stereo radiographs using statistical shape models.

PubMed

van IJsseldijk, E A; Valstar, E R; Stoel, B C; Nelissen, R G H H; Baka, N; Van't Klooster, R; Kaptein, B L

2016-08-01

An important measure for the diagnosis and monitoring of knee osteoarthritis is the minimum joint space width (mJSW). This requires accurate alignment of the x-ray beam with the tibial plateau, which may not be accomplished in practice. We investigate the feasibility of a new mJSW measurement method from stereo radiographs using 3D statistical shape models (SSM) and evaluate its sensitivity to changes in the mJSW and its robustness to variations in patient positioning and bone geometry. A validation study was performed using five cadaver specimens. The actual mJSW was varied and images were acquired with variation in the cadaver positioning. For comparison purposes, the mJSW was also assessed from plain radiographs. To study the influence of SSM model accuracy, the 3D mJSW measurement was repeated with models from the actual bones, obtained from CT scans. The SSM-based measurement method was more robust (consistent output for a wide range of input data/consistent output under varying measurement circumstances) than the conventional 2D method, showing that the 3D reconstruction indeed reduces the influence of patient positioning. However, the SSM-based method showed comparable sensitivity to changes in the mJSW with respect to the conventional method. The CT-based measurement was more accurate than the SSM-based measurement (smallest detectable differences 0.55 mm versus 0. 82 mm, respectively). The proposed measurement method is not a substitute for the conventional 2D measurement due to limitations in the SSM model accuracy. However, further improvement of the model accuracy and optimisation technique can be obtained. Combined with the promising options for applications using quantitative information on bone morphology, SSM based 3D reconstructions of natural knees are attractive for further development.Cite this article: E. A. van IJsseldijk, E. R. Valstar, B. C. Stoel, R. G. H. H. Nelissen, N. Baka, R. van't Klooster, B. L. Kaptein. Three dimensional measurement of minimum joint space width in the knee from stereo radiographs using statistical shape models. Bone Joint Res 2016;320-327. DOI: 10.1302/2046-3758.58.2000626. © 2016 van IJsseldijk et al.

Deep Generative Models of Galaxy Images for the Calibration of the Next Generation of Weak Lensing Surveys

NASA Astrophysics Data System (ADS)

Lanusse, Francois; Ravanbakhsh, Siamak; Mandelbaum, Rachel; Schneider, Jeff; Poczos, Barnabas

2017-01-01

Weak gravitational lensing has long been identified as one of the most powerful probes to investigate the nature of dark energy. As such, weak lensing is at the heart of the next generation of cosmological surveys such as LSST, Euclid or WFIRST.One particularly crititcal source of systematic errors in these surveys comes from the shape measurement algorithms tasked with estimating galaxy shapes. GREAT3, the last community challenge to assess the quality of state-of-the-art shape measurement algorithms has in particular demonstrated that all current methods are biased to various degrees and, more importantly, that these biases depend on the details of the galaxy morphologies. These biases can be measured and calibrated by generating mock observations where a known lensing signal has been introduced and comparing the resulting measurements to the ground-truth. Producing these mock observations however requires input galaxy images of higher resolution and S/N than the simulated survey, which typically implies acquiring extremely expensive space-based observations.The goal of this work is to train a deep generative model on already available Hubble Space Telescope data which can then be used to sample new galaxy images conditioned on parameters such as magnitude, size or redshift and exhibiting complex morphologies. Such model can allow us to inexpensively produce large set of realistic realistic images for calibration purposes.We implement a conditional generative model based on state-of-the-art deep learning methods and fit it to deep galaxy images from the COSMOS survey. The quality of the model is assessed by computing an extensive set of galaxy morphology statistics on the generated images. Beyond simple second moment statistics such as size and ellipticity, we apply more complex statistics specifically designed to be sensitive to disturbed galaxy morphologies. We find excellent agreement between the morphologies of real and model generated galaxies.Our results suggest that such deep generative models represent a reliable alternative to the acquisition of expensive high quality observations for generating the calibration data needed by the next generation of weak lensing surveys.

Modeling, estimation and identification methods for static shape determination of flexible structures. [for large space structure design

NASA Technical Reports Server (NTRS)

Rodriguez, G.; Scheid, R. E., Jr.

1986-01-01

This paper outlines methods for modeling, identification and estimation for static determination of flexible structures. The shape estimation schemes are based on structural models specified by (possibly interconnected) elliptic partial differential equations. The identification techniques provide approximate knowledge of parameters in elliptic systems. The techniques are based on the method of maximum-likelihood that finds parameter values such that the likelihood functional associated with the system model is maximized. The estimation methods are obtained by means of a function-space approach that seeks to obtain the conditional mean of the state given the data and a white noise characterization of model errors. The solutions are obtained in a batch-processing mode in which all the data is processed simultaneously. After methods for computing the optimal estimates are developed, an analysis of the second-order statistics of the estimates and of the related estimation error is conducted. In addition to outlining the above theoretical results, the paper presents typical flexible structure simulations illustrating performance of the shape determination methods.

Statistics of voids in hierarchical universes

NASA Technical Reports Server (NTRS)

Fry, J. N.

1986-01-01

As one alternative to the N-point galaxy correlation function statistics, the distribution of holes or the probability that a volume of given size and shape be empty of galaxies can be considered. The probability of voids resulting from a variety of hierarchical patterns of clustering is considered, and these are compared with the results of numerical simulations and with observations. A scaling relation required by the hierarchical pattern of higher order correlation functions is seen to be obeyed in the simulations, and the numerical results show a clear difference between neutrino models and cold-particle models; voids are more likely in neutrino universes. Observational data do not yet distinguish but are close to being able to distinguish between models.

A radiosity-based model to compute the radiation transfer of soil surface

NASA Astrophysics Data System (ADS)

Zhao, Feng; Li, Yuguang

2011-11-01

A good understanding of interactions of electromagnetic radiation with soil surface is important for a further improvement of remote sensing methods. In this paper, a radiosity-based analytical model for soil Directional Reflectance Factor's (DRF) distributions was developed and evaluated. The model was specifically dedicated to the study of radiation transfer for the soil surface under tillage practices. The soil was abstracted as two dimensional U-shaped or V-shaped geometric structures with periodic macroscopic variations. The roughness of the simulated surfaces was expressed as a ratio of the height to the width for the U and V-shaped structures. The assumption was made that the shadowing of soil surface, simulated by U or V-shaped grooves, has a greater influence on the soil reflectance distribution than the scattering properties of basic soil particles of silt and clay. Another assumption was that the soil is a perfectly diffuse reflector at a microscopic level, which is a prerequisite for the application of the radiosity method. This radiosity-based analytical model was evaluated by a forward Monte Carlo ray-tracing model under the same structural scenes and identical spectral parameters. The statistics of these two models' BRF fitting results for several soil structures under the same conditions showed the good agreements. By using the model, the physical mechanism of the soil bidirectional reflectance pattern was revealed.

Long-term changes in the statistical distribution of Dobson total ozone in selected Northern Hemisphere geographical regions

NASA Technical Reports Server (NTRS)

Krzyscin, Janusz W.

1994-01-01

The daily averages of total column amount of ozone taken in the period 1964-1988 at a network of 24 Dobson stations have been analyzed. Year-round data as well as summer data (May - Aug.) and winter data (Dec. - March) have been examined in the following regions: latitude bands (30 deg N - 39 deg N, 40 deg N - 52 deg N, 30 deg N - 60 deg N), North America, Europe, and Japan. To find year-to-year changes in the shape of the annual statistical distribution of total ozone (ASDTO) for these regions, we analyze trends in the following statistic characteristics of ASDTO: mean, standard deviation, median, and 10 and 90 percentiles. Time series of the statistical characteristics for the selected regions have been combined by averaging the individual stations values of these characteristics. The trends have been calculated by the multiple regression model adjusted for: the 11-year solar cycle, the Southern Oscillations effects, and for serial correlations. We have found that: a) in all regions (excluding Japan, North America), the shape of ASDTO has been drifting towards low ozone values. The drift seems to be not accompanied with a transformation in the shape of ASDTO. The drift speed (the rate of decrease in the annual means of total ozone) is of order 1-3 percent per decade (in the period 1970-1988). b) In Japan, the interannual changes in the shape of ASDTO have not been revealed. c) In North America, the drift of the year-round ASDTO (the year-round ASDTO comprises all the daily means of total ozone in a given year) has been accompanied with a transformation in the shape. The shape of the year round ASDTO becomes narrower. d) In all regions, except Japan and the band 30 deg - 39 deg N, the winter ASDTO (the winter ASDTO comprises the data taken in the period December in a given year through March next year) moves faster towards low ozone values than the summer ASDTO (the summer ASDTO comprises the data taken in the period May through August in a given year).

Statistics of a neuron model driven by asymmetric colored noise.

PubMed

Müller-Hansen, Finn; Droste, Felix; Lindner, Benjamin

2015-02-01

Irregular firing of neurons can be modeled as a stochastic process. Here we study the perfect integrate-and-fire neuron driven by dichotomous noise, a Markovian process that jumps between two states (i.e., possesses a non-Gaussian statistics) and exhibits nonvanishing temporal correlations (i.e., represents a colored noise). Specifically, we consider asymmetric dichotomous noise with two different transition rates. Using a first-passage-time formulation, we derive exact expressions for the probability density and the serial correlation coefficient of the interspike interval (time interval between two subsequent neural action potentials) and the power spectrum of the spike train. Furthermore, we extend the model by including additional Gaussian white noise, and we give approximations for the interspike interval (ISI) statistics in this case. Numerical simulations are used to validate the exact analytical results for pure dichotomous noise, and to test the approximations of the ISI statistics when Gaussian white noise is included. The results may help to understand how correlations and asymmetry of noise and signals in nerve cells shape neuronal firing statistics.

Symbolic feature detection for image understanding

NASA Astrophysics Data System (ADS)

Aslan, Sinem; Akgül, Ceyhun Burak; Sankur, Bülent

2014-03-01

In this study we propose a model-driven codebook generation method used to assign probability scores to pixels in order to represent underlying local shapes they reside in. In the first version of the symbol library we limited ourselves to photometric and similarity transformations applied on eight prototypical shapes of flat plateau , ramp, valley, ridge, circular and elliptic respectively pit and hill and used randomized decision forest as the statistical classifier to compute shape class ambiguity of each pixel. We achieved90% accuracy in identification of known objects from alternate views, however, we could not outperform texture, global and local shape methods, but only color-based method in recognition of unknown objects. We present a progress plan to be accomplished as a future work to improve the proposed approach further.

Statistical atlas based extrapolation of CT data

NASA Astrophysics Data System (ADS)

Chintalapani, Gouthami; Murphy, Ryan; Armiger, Robert S.; Lepisto, Jyri; Otake, Yoshito; Sugano, Nobuhiko; Taylor, Russell H.; Armand, Mehran

2010-02-01

We present a framework to estimate the missing anatomical details from a partial CT scan with the help of statistical shape models. The motivating application is periacetabular osteotomy (PAO), a technique for treating developmental hip dysplasia, an abnormal condition of the hip socket that, if untreated, may lead to osteoarthritis. The common goals of PAO are to reduce pain, joint subluxation and improve contact pressure distribution by increasing the coverage of the femoral head by the hip socket. While current diagnosis and planning is based on radiological measurements, because of significant structural variations in dysplastic hips, a computer-assisted geometrical and biomechanical planning based on CT data is desirable to help the surgeon achieve optimal joint realignments. Most of the patients undergoing PAO are young females, hence it is usually desirable to minimize the radiation dose by scanning only the joint portion of the hip anatomy. These partial scans, however, do not provide enough information for biomechanical analysis due to missing iliac region. A statistical shape model of full pelvis anatomy is constructed from a database of CT scans. The partial volume is first aligned with the statistical atlas using an iterative affine registration, followed by a deformable registration step and the missing information is inferred from the atlas. The atlas inferences are further enhanced by the use of X-ray images of the patient, which are very common in an osteotomy procedure. The proposed method is validated with a leave-one-out analysis method. Osteotomy cuts are simulated and the effect of atlas predicted models on the actual procedure is evaluated.

The Cardiac Atlas Project--an imaging database for computational modeling and statistical atlases of the heart.

PubMed

Fonseca, Carissa G; Backhaus, Michael; Bluemke, David A; Britten, Randall D; Chung, Jae Do; Cowan, Brett R; Dinov, Ivo D; Finn, J Paul; Hunter, Peter J; Kadish, Alan H; Lee, Daniel C; Lima, Joao A C; Medrano-Gracia, Pau; Shivkumar, Kalyanam; Suinesiaputra, Avan; Tao, Wenchao; Young, Alistair A

2011-08-15

Integrative mathematical and statistical models of cardiac anatomy and physiology can play a vital role in understanding cardiac disease phenotype and planning therapeutic strategies. However, the accuracy and predictive power of such models is dependent upon the breadth and depth of noninvasive imaging datasets. The Cardiac Atlas Project (CAP) has established a large-scale database of cardiac imaging examinations and associated clinical data in order to develop a shareable, web-accessible, structural and functional atlas of the normal and pathological heart for clinical, research and educational purposes. A goal of CAP is to facilitate collaborative statistical analysis of regional heart shape and wall motion and characterize cardiac function among and within population groups. Three main open-source software components were developed: (i) a database with web-interface; (ii) a modeling client for 3D + time visualization and parametric description of shape and motion; and (iii) open data formats for semantic characterization of models and annotations. The database was implemented using a three-tier architecture utilizing MySQL, JBoss and Dcm4chee, in compliance with the DICOM standard to provide compatibility with existing clinical networks and devices. Parts of Dcm4chee were extended to access image specific attributes as search parameters. To date, approximately 3000 de-identified cardiac imaging examinations are available in the database. All software components developed by the CAP are open source and are freely available under the Mozilla Public License Version 1.1 (http://www.mozilla.org/MPL/MPL-1.1.txt). http://www.cardiacatlas.org a.young@auckland.ac.nz Supplementary data are available at Bioinformatics online.

A computer program for thermal radiation from gaseous rocket exhuast plumes (GASRAD)

NASA Technical Reports Server (NTRS)

Reardon, J. E.; Lee, Y. C.

1979-01-01

A computer code is presented for predicting incident thermal radiation from defined plume gas properties in either axisymmetric or cylindrical coordinate systems. The radiation model is a statistical band model for exponential line strength distribution with Lorentz/Doppler line shapes for 5 gaseous species (H2O, CO2, CO, HCl and HF) and an appoximate (non-scattering) treatment of carbon particles. The Curtis-Godson approximation is used for inhomogeneous gases, but a subroutine is available for using Young's intuitive derivative method for H2O with Lorentz line shape and exponentially-tailed-inverse line strength distribution. The geometry model provides integration over a hemisphere with up to 6 individually oriented identical axisymmetric plumes, a single 3-D plume, Shading surfaces may be used in any of 7 shapes, and a conical limit may be defined for the plume to set individual line-of-signt limits. Intermediate coordinate systems may specified to simplify input of plumes and shading surfaces.

3D-Printed Visceral Aneurysm Models Based on CT Data for Simulations of Endovascular Embolization: Evaluation of Size and Shape Accuracy.

PubMed

Shibata, Eisuke; Takao, Hidemasa; Amemiya, Shiori; Ohtomo, Kuni

2017-08-01

The objective of this study is to verify the accuracy of 3D-printed hollow models of visceral aneurysms created from CT angiography (CTA) data, by evaluating the sizes and shapes of aneurysms and related arteries. From March 2006 to August 2015, 19 true visceral aneurysms were embolized via interventional radiologic treatment provided by the radiology department at our institution; aneurysms with bleeding (n = 3) or without thin-slice (< 1 mm) preembolization CT data (n = 1) were excluded. A total of 15 consecutive true visceral aneurysms from 11 patients (eight women and three men; mean age, 61 years; range, 53-72 years) whose aneurysms were embolized via endovascular procedures were included in this study. Three-dimensional-printed hollow models of aneurysms and related arteries were fabricated from CTA data. The accuracies of the sizes and shapes of the 3D-printed hollow models were evaluated using the nonparametric Wilcoxon signed rank test and the Dice coefficient index. Aneurysm sizes ranged from 138 to 18,691 mm 3 (diameter, 6.1-35.7 mm), and no statistically significant difference was noted between patient data and 3D-printed models (p = 0.56). Shape analysis of whole aneurysms and related arteries indicated a high level of accuracy (Dice coefficient index value, 84.2-95.8%; mean [± SD], 91.1 ± 4.1%). The sizes and shapes of 3D-printed hollow visceral aneurysm models created from CTA data were accurate. These models can be used for simulations of endovascular treatment and precise anatomic information.

A new test statistic for climate models that includes field and spatial dependencies using Gaussian Markov random fields

DOE PAGES

Nosedal-Sanchez, Alvaro; Jackson, Charles S.; Huerta, Gabriel

2016-07-20

A new test statistic for climate model evaluation has been developed that potentially mitigates some of the limitations that exist for observing and representing field and space dependencies of climate phenomena. Traditionally such dependencies have been ignored when climate models have been evaluated against observational data, which makes it difficult to assess whether any given model is simulating observed climate for the right reasons. The new statistic uses Gaussian Markov random fields for estimating field and space dependencies within a first-order grid point neighborhood structure. We illustrate the ability of Gaussian Markov random fields to represent empirical estimates of fieldmore » and space covariances using "witch hat" graphs. We further use the new statistic to evaluate the tropical response of a climate model (CAM3.1) to changes in two parameters important to its representation of cloud and precipitation physics. Overall, the inclusion of dependency information did not alter significantly the recognition of those regions of parameter space that best approximated observations. However, there were some qualitative differences in the shape of the response surface that suggest how such a measure could affect estimates of model uncertainty.« less

A new test statistic for climate models that includes field and spatial dependencies using Gaussian Markov random fields

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

Nosedal-Sanchez, Alvaro; Jackson, Charles S.; Huerta, Gabriel

A new test statistic for climate model evaluation has been developed that potentially mitigates some of the limitations that exist for observing and representing field and space dependencies of climate phenomena. Traditionally such dependencies have been ignored when climate models have been evaluated against observational data, which makes it difficult to assess whether any given model is simulating observed climate for the right reasons. The new statistic uses Gaussian Markov random fields for estimating field and space dependencies within a first-order grid point neighborhood structure. We illustrate the ability of Gaussian Markov random fields to represent empirical estimates of fieldmore » and space covariances using "witch hat" graphs. We further use the new statistic to evaluate the tropical response of a climate model (CAM3.1) to changes in two parameters important to its representation of cloud and precipitation physics. Overall, the inclusion of dependency information did not alter significantly the recognition of those regions of parameter space that best approximated observations. However, there were some qualitative differences in the shape of the response surface that suggest how such a measure could affect estimates of model uncertainty.« less

A study on the dependence of nuclear viscosity on temperature

NASA Astrophysics Data System (ADS)

Vardaci, E.; Di Nitto, A.; Nadtochy, P. N.; La Rana, G.; Cinausero, M.; Prete, G.; Gelli, N.; Ashaduzzaman, M.; Davide, F.; Pulcini, A.; Quero, D.; Kozulin, E. M.; Knyazheva, G. N.; Itkis, I. M.

2018-05-01

Nuclear viscosity is an irreplaceable ingredient of nuclear fission collective dynamical models. It drives the exchange of energy between the collective variables and the thermal bath of single particle degrees of freedom. Its dependence on the shape and temperature is a matter of controversy. By using systems of intermediate fissility we have demonstrated in a recent study that the viscosity parameters is larger for compact shapes, and decreases for larger deformations of the fissioning system, at variance with the conclusions of the statistical model modified to include empirically viscosity and time scales. In this contribution we propose an experimental scenario to highlight the possible dependence of the viscosity from the temperature.

Critical dimensions of trans-sacral corridors assessed by 3D CT models: Relevance for implant positioning in fractures of the sacrum.

PubMed

Wagner, Daniel; Kamer, Lukas; Sawaguchi, Takeshi; Geoff Richards, R; Noser, Hansrudi; Uesugi, Masafumi; Ossendorf, Christian; Rommens, Pol M

2017-11-01

Trans-sacral implants can be used alternatively to sacro-iliac screws in the treatment of osteoporosis-associated fragility fractures of the pelvis and the sacrum. We investigated trans-sacral corridor dimensions, the number of individuals amenable to trans-sacral fixation, as well as the osseous boundaries and shape of the S1 corridor. 3D models were reconstructed from pelvic CT scans from 92 Europeans and 64 Japanese. A corridor of <12 mm was considered critical for trans-sacral implant positioning, and <8 mm as impossible. A statistical model of trans-sacral corridor S1 was computed. The limiting cranio-caudal diameter was 11.6 mm (±5.4) for S1 and 14 mm (±2.4) for S2. Trans-sacral implant positioning was critical in 52% of cases for S1, and in 21% for S2. The S1 corridor was impossible in 26%, with no impossible corridor in S2. Antero-superiorly, the S1 corridor was limited not only by the sacrum but in 40% by the iliac fossa. The statistical model demonstrated a consistent oval shape of the trans-section of corridor S1. Considering the variable in size and shape of trans-sacral corridors in S1, a thorough anatomical knowledge and preoperative planning are mandatory using trans-sacral implants. In critical cases, S2 is a veritable alternative. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 35:2577-2584, 2017. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

Reproducibility of structural strength and stiffness for graphite-epoxy aircraft spoilers

NASA Technical Reports Server (NTRS)

Howell, W. E.; Reese, C. D.

1978-01-01

Structural strength reproducibility of graphite epoxy composite spoilers for the Boeing 737 aircraft was evaluated by statically loading fifteen spoilers to failure at conditions simulating aerodynamic loads. Spoiler strength and stiffness data were statistically modeled using a two parameter Weibull distribution function. Shape parameter values calculated for the composite spoiler strength and stiffness were within the range of corresponding shape parameter values calculated for material property data of composite laminates. This agreement showed that reproducibility of full scale component structural properties was within the reproducibility range of data from material property tests.

Differentiating gold nanorod samples using particle size and shape distributions from transmission electron microscope images

NASA Astrophysics Data System (ADS)

Grulke, Eric A.; Wu, Xiaochun; Ji, Yinglu; Buhr, Egbert; Yamamoto, Kazuhiro; Song, Nam Woong; Stefaniak, Aleksandr B.; Schwegler-Berry, Diane; Burchett, Woodrow W.; Lambert, Joshua; Stromberg, Arnold J.

2018-04-01

Size and shape distributions of gold nanorod samples are critical to their physico-chemical properties, especially their longitudinal surface plasmon resonance. This interlaboratory comparison study developed methods for measuring and evaluating size and shape distributions for gold nanorod samples using transmission electron microscopy (TEM) images. The objective was to determine whether two different samples, which had different performance attributes in their application, were different with respect to their size and/or shape descriptor distributions. Touching particles in the captured images were identified using a ruggedness shape descriptor. Nanorods could be distinguished from nanocubes using an elongational shape descriptor. A non-parametric statistical test showed that cumulative distributions of an elongational shape descriptor, that is, the aspect ratio, were statistically different between the two samples for all laboratories. While the scale parameters of size and shape distributions were similar for both samples, the width parameters of size and shape distributions were statistically different. This protocol fulfills an important need for a standardized approach to measure gold nanorod size and shape distributions for applications in which quantitative measurements and comparisons are important. Furthermore, the validated protocol workflow can be automated, thus providing consistent and rapid measurements of nanorod size and shape distributions for researchers, regulatory agencies, and industry.

Statistical mechanics of binary mixture adsorption in metal-organic frameworks in the osmotic ensemble.

PubMed

Dunne, Lawrence J; Manos, George

2018-03-13

Although crucial for designing separation processes little is known experimentally about multi-component adsorption isotherms in comparison with pure single components. Very few binary mixture adsorption isotherms are to be found in the literature and information about isotherms over a wide range of gas-phase composition and mechanical pressures and temperature is lacking. Here, we present a quasi-one-dimensional statistical mechanical model of binary mixture adsorption in metal-organic frameworks (MOFs) treated exactly by a transfer matrix method in the osmotic ensemble. The experimental parameter space may be very complex and investigations into multi-component mixture adsorption may be guided by theoretical insights. The approach successfully models breathing structural transitions induced by adsorption giving a good account of the shape of adsorption isotherms of CO 2 and CH 4 adsorption in MIL-53(Al). Binary mixture isotherms and co-adsorption-phase diagrams are also calculated and found to give a good description of the experimental trends in these properties and because of the wide model parameter range which reproduces this behaviour suggests that this is generic to MOFs. Finally, a study is made of the influence of mechanical pressure on the shape of CO 2 and CH 4 adsorption isotherms in MIL-53(Al). Quite modest mechanical pressures can induce significant changes to isotherm shapes in MOFs with implications for binary mixture separation processes.This article is part of the theme issue 'Modern theoretical chemistry'. © 2018 The Author(s).

Statistical mechanics of binary mixture adsorption in metal-organic frameworks in the osmotic ensemble

NASA Astrophysics Data System (ADS)

Dunne, Lawrence J.; Manos, George

2018-03-01

Although crucial for designing separation processes little is known experimentally about multi-component adsorption isotherms in comparison with pure single components. Very few binary mixture adsorption isotherms are to be found in the literature and information about isotherms over a wide range of gas-phase composition and mechanical pressures and temperature is lacking. Here, we present a quasi-one-dimensional statistical mechanical model of binary mixture adsorption in metal-organic frameworks (MOFs) treated exactly by a transfer matrix method in the osmotic ensemble. The experimental parameter space may be very complex and investigations into multi-component mixture adsorption may be guided by theoretical insights. The approach successfully models breathing structural transitions induced by adsorption giving a good account of the shape of adsorption isotherms of CO2 and CH4 adsorption in MIL-53(Al). Binary mixture isotherms and co-adsorption-phase diagrams are also calculated and found to give a good description of the experimental trends in these properties and because of the wide model parameter range which reproduces this behaviour suggests that this is generic to MOFs. Finally, a study is made of the influence of mechanical pressure on the shape of CO2 and CH4 adsorption isotherms in MIL-53(Al). Quite modest mechanical pressures can induce significant changes to isotherm shapes in MOFs with implications for binary mixture separation processes. This article is part of the theme issue `Modern theoretical chemistry'.

A novel modeling approach to the mixing process in twin-screw extruders

NASA Astrophysics Data System (ADS)

Kennedy, Amedu Osaighe; Penlington, Roger; Busawon, Krishna; Morgan, Andy

2014-05-01

In this paper, a theoretical model for the mixing process in a self-wiping co-rotating twin screw extruder by combination of statistical techniques and mechanistic modelling has been proposed. The approach was to examine the mixing process in the local zones via residence time distribution and the flow dynamics, from which predictive models of the mean residence time and mean time delay were determined. Increase in feed rate at constant screw speed was found to narrow the shape of the residence time distribution curve, reduction in the mean residence time and time delay and increase in the degree of fill. Increase in screw speed at constant feed rate was found to narrow the shape of the residence time distribution curve, decrease in the degree of fill in the extruder and thus an increase in the time delay. Experimental investigation was also done to validate the modeling approach.

Marginal Shape Deep Learning: Applications to Pediatric Lung Field Segmentation.

PubMed

Mansoor, Awais; Cerrolaza, Juan J; Perez, Geovanny; Biggs, Elijah; Nino, Gustavo; Linguraru, Marius George

2017-02-11

Representation learning through deep learning (DL) architecture has shown tremendous potential for identification, localization, and texture classification in various medical imaging modalities. However, DL applications to segmentation of objects especially to deformable objects are rather limited and mostly restricted to pixel classification. In this work, we propose marginal shape deep learning (MaShDL), a framework that extends the application of DL to deformable shape segmentation by using deep classifiers to estimate the shape parameters. MaShDL combines the strength of statistical shape models with the automated feature learning architecture of DL. Unlike the iterative shape parameters estimation approach of classical shape models that often leads to a local minima, the proposed framework is robust to local minima optimization and illumination changes. Furthermore, since the direct application of DL framework to a multi-parameter estimation problem results in a very high complexity, our framework provides an excellent run-time performance solution by independently learning shape parameter classifiers in marginal eigenspaces in the decreasing order of variation. We evaluated MaShDL for segmenting the lung field from 314 normal and abnormal pediatric chest radiographs and obtained a mean Dice similarity coefficient of 0.927 using only the four highest modes of variation (compared to 0.888 with classical ASM 1 (p-value=0.01) using same configuration). To the best of our knowledge this is the first demonstration of using DL framework for parametrized shape learning for the delineation of deformable objects.

Marginal shape deep learning: applications to pediatric lung field segmentation

NASA Astrophysics Data System (ADS)

Mansoor, Awais; Cerrolaza, Juan J.; Perez, Geovany; Biggs, Elijah; Nino, Gustavo; Linguraru, Marius George

2017-02-01

Representation learning through deep learning (DL) architecture has shown tremendous potential for identification, local- ization, and texture classification in various medical imaging modalities. However, DL applications to segmentation of objects especially to deformable objects are rather limited and mostly restricted to pixel classification. In this work, we propose marginal shape deep learning (MaShDL), a framework that extends the application of DL to deformable shape segmentation by using deep classifiers to estimate the shape parameters. MaShDL combines the strength of statistical shape models with the automated feature learning architecture of DL. Unlike the iterative shape parameters estimation approach of classical shape models that often leads to a local minima, the proposed framework is robust to local minima optimization and illumination changes. Furthermore, since the direct application of DL framework to a multi-parameter estimation problem results in a very high complexity, our framework provides an excellent run-time performance solution by independently learning shape parameter classifiers in marginal eigenspaces in the decreasing order of variation. We evaluated MaShDL for segmenting the lung field from 314 normal and abnormal pediatric chest radiographs and obtained a mean Dice similarity coefficient of 0:927 using only the four highest modes of variation (compared to 0:888 with classical ASM1 (p-value=0:01) using same configuration). To the best of our knowledge this is the first demonstration of using DL framework for parametrized shape learning for the delineation of deformable objects.

Marginal Shape Deep Learning: Applications to Pediatric Lung Field Segmentation

PubMed Central

Mansoor, Awais; Cerrolaza, Juan J.; Perez, Geovanny; Biggs, Elijah; Nino, Gustavo; Linguraru, Marius George

2017-01-01

Representation learning through deep learning (DL) architecture has shown tremendous potential for identification, localization, and texture classification in various medical imaging modalities. However, DL applications to segmentation of objects especially to deformable objects are rather limited and mostly restricted to pixel classification. In this work, we propose marginal shape deep learning (MaShDL), a framework that extends the application of DL to deformable shape segmentation by using deep classifiers to estimate the shape parameters. MaShDL combines the strength of statistical shape models with the automated feature learning architecture of DL. Unlike the iterative shape parameters estimation approach of classical shape models that often leads to a local minima, the proposed framework is robust to local minima optimization and illumination changes. Furthermore, since the direct application of DL framework to a multi-parameter estimation problem results in a very high complexity, our framework provides an excellent run-time performance solution by independently learning shape parameter classifiers in marginal eigenspaces in the decreasing order of variation. We evaluated MaShDL for segmenting the lung field from 314 normal and abnormal pediatric chest radiographs and obtained a mean Dice similarity coefficient of 0.927 using only the four highest modes of variation (compared to 0.888 with classical ASM1 (p-value=0.01) using same configuration). To the best of our knowledge this is the first demonstration of using DL framework for parametrized shape learning for the delineation of deformable objects. PMID:28592911

Impact of Temperature and Non-Gaussian Statistics on Electron Transfer in Donor-Bridge-Acceptor Molecules.

PubMed

Waskasi, Morteza M; Newton, Marshall D; Matyushov, Dmitry V

2017-03-30

A combination of experimental data and theoretical analysis provides evidence of a bell-shaped kinetics of electron transfer in the Arrhenius coordinates ln k vs 1/T. This kinetic law is a temperature analogue of the familiar Marcus bell-shaped dependence based on ln k vs the reaction free energy. These results were obtained for reactions of intramolecular charge shift between the donor and acceptor separated by a rigid spacer studied experimentally by Miller and co-workers. The non-Arrhenius kinetic law is a direct consequence of the solvent reorganization energy and reaction driving force changing approximately as hyperbolic functions with temperature. The reorganization energy decreases and the driving force increases when temperature is increased. The point of equality between them marks the maximum of the activationless reaction rate. Reaching the consistency between the kinetic and thermodynamic experimental data requires the non-Gaussian statistics of the donor-acceptor energy gap described by the Q-model of electron transfer. The theoretical formalism combines the vibrational envelope of quantum vibronic transitions with the Q-model describing the classical component of the Franck-Condon factor and a microscopic solvation model of the solvent reorganization energy and the reaction free energy.

Gradient-based reliability maps for ACM-based segmentation of hippocampus.

PubMed

Zarpalas, Dimitrios; Gkontra, Polyxeni; Daras, Petros; Maglaveras, Nicos

2014-04-01

Automatic segmentation of deep brain structures, such as the hippocampus (HC), in MR images has attracted considerable scientific attention due to the widespread use of MRI and to the principal role of some structures in various mental disorders. In this literature, there exists a substantial amount of work relying on deformable models incorporating prior knowledge about structures' anatomy and shape information. However, shape priors capture global shape characteristics and thus fail to model boundaries of varying properties; HC boundaries present rich, poor, and missing gradient regions. On top of that, shape prior knowledge is blended with image information in the evolution process, through global weighting of the two terms, again neglecting the spatially varying boundary properties, causing segmentation faults. An innovative method is hereby presented that aims to achieve highly accurate HC segmentation in MR images, based on the modeling of boundary properties at each anatomical location and the inclusion of appropriate image information for each of those, within an active contour model framework. Hence, blending of image information and prior knowledge is based on a local weighting map, which mixes gradient information, regional and whole brain statistical information with a multi-atlas-based spatial distribution map of the structure's labels. Experimental results on three different datasets demonstrate the efficacy and accuracy of the proposed method.

Variation in reaction norms: Statistical considerations and biological interpretation.

PubMed

Morrissey, Michael B; Liefting, Maartje

2016-09-01

Analysis of reaction norms, the functions by which the phenotype produced by a given genotype depends on the environment, is critical to studying many aspects of phenotypic evolution. Different techniques are available for quantifying different aspects of reaction norm variation. We examine what biological inferences can be drawn from some of the more readily applicable analyses for studying reaction norms. We adopt a strongly biologically motivated view, but draw on statistical theory to highlight strengths and drawbacks of different techniques. In particular, consideration of some formal statistical theory leads to revision of some recently, and forcefully, advocated opinions on reaction norm analysis. We clarify what simple analysis of the slope between mean phenotype in two environments can tell us about reaction norms, explore the conditions under which polynomial regression can provide robust inferences about reaction norm shape, and explore how different existing approaches may be used to draw inferences about variation in reaction norm shape. We show how mixed model-based approaches can provide more robust inferences than more commonly used multistep statistical approaches, and derive new metrics of the relative importance of variation in reaction norm intercepts, slopes, and curvatures. © 2016 The Author(s). Evolution © 2016 The Society for the Study of Evolution.

The use of generalised additive models (GAM) in dentistry.

PubMed

Helfenstein, U; Steiner, M; Menghini, G

1997-12-01

Ordinary multiple regression and logistic multiple regression are widely applied statistical methods which allow a researcher to 'explain' or 'predict' a response variable from a set of explanatory variables or predictors. In these models it is usually assumed that quantitative predictors such as age enter linearly into the model. During recent years these methods have been further developed to allow more flexibility in the way explanatory variables 'act' on a response variable. The methods are called 'generalised additive models' (GAM). The rigid linear terms characterising the association between response and predictors are replaced in an optimal way by flexible curved functions of the predictors (the 'profiles'). Plotting the 'profiles' allows the researcher to visualise easily the shape by which predictors 'act' over the whole range of values. The method facilitates detection of particular shapes such as 'bumps', 'U-shapes', 'J-shapes, 'threshold values' etc. Information about the shape of the association is not revealed by traditional methods. The shapes of the profiles may be checked by performing a Monte Carlo simulation ('bootstrapping'). After the presentation of the GAM a relevant case study is presented in order to demonstrate application and use of the method. The dependence of caries in primary teeth on a set of explanatory variables is investigated. Since GAMs may not be easily accessible to dentists, this article presents them in an introductory condensed form. It was thought that a nonmathematical summary and a worked example might encourage readers to consider the methods described. GAMs may be of great value to dentists in allowing visualisation of the shape by which predictors 'act' and obtaining a better understanding of the complex relationships between predictors and response.

Fragment size distribution statistics in dynamic fragmentation of laser shock-loaded tin

NASA Astrophysics Data System (ADS)

He, Weihua; Xin, Jianting; Zhao, Yongqiang; Chu, Genbai; Xi, Tao; Shui, Min; Lu, Feng; Gu, Yuqiu

2017-06-01

This work investigates the geometric statistics method to characterize the size distribution of tin fragments produced in the laser shock-loaded dynamic fragmentation process. In the shock experiments, the ejection of the tin sample with etched V-shape groove in the free surface are collected by the soft recovery technique. Subsequently, the produced fragments are automatically detected with the fine post-shot analysis techniques including the X-ray micro-tomography and the improved watershed method. To characterize the size distributions of the fragments, a theoretical random geometric statistics model based on Poisson mixtures is derived for dynamic heterogeneous fragmentation problem, which reveals linear combinational exponential distribution. The experimental data related to fragment size distributions of the laser shock-loaded tin sample are examined with the proposed theoretical model, and its fitting performance is compared with that of other state-of-the-art fragment size distribution models. The comparison results prove that our proposed model can provide far more reasonable fitting result for the laser shock-loaded tin.

Test of the statistical model in {sup 96}Mo with the BaF{sub 2}{gamma} calorimeter DANCE array

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

Sheets, S. A.; Mitchell, G. E.; Agvaanluvsan, U.

2009-02-15

The {gamma}-ray cascades following the {sup 95}Mo(n,{gamma}){sup 96}Mo reaction were studied with the {gamma} calorimeter DANCE (Detector for Advanced Neutron Capture Experiments) consisting of 160 BaF{sub 2} scintillation detectors at the Los Alamos Neutron Science Center. The {gamma}-ray energy spectra for different multiplicities were measured for s- and p-wave resonances below 2 keV. The shapes of these spectra were found to be in very good agreement with simulations using the DICEBOX statistical model code. The relevant model parameters used for the level density and photon strength functions were identical with those that provided the best fit of the data frommore » a recent measurement of the thermal {sup 95}Mo(n,{gamma}){sup 96}Mo reaction with the two-step-cascade method. The reported results strongly suggest that the extreme statistical model works very well in the mass region near A=100.« less

Random walk to a nonergodic equilibrium concept

NASA Astrophysics Data System (ADS)

Bel, G.; Barkai, E.

2006-01-01

Random walk models, such as the trap model, continuous time random walks, and comb models, exhibit weak ergodicity breaking, when the average waiting time is infinite. The open question is, what statistical mechanical theory replaces the canonical Boltzmann-Gibbs theory for such systems? In this paper a nonergodic equilibrium concept is investigated, for a continuous time random walk model in a potential field. In particular we show that in the nonergodic phase the distribution of the occupation time of the particle in a finite region of space approaches U- or W-shaped distributions related to the arcsine law. We show that when conditions of detailed balance are applied, these distributions depend on the partition function of the problem, thus establishing a relation between the nonergodic dynamics and canonical statistical mechanics. In the ergodic phase the distribution function of the occupation times approaches a δ function centered on the value predicted based on standard Boltzmann-Gibbs statistics. The relation of our work to single-molecule experiments is briefly discussed.

SEGMENTING CT PROSTATE IMAGES USING POPULATION AND PATIENT-SPECIFIC STATISTICS FOR RADIOTHERAPY.

PubMed

Feng, Qianjin; Foskey, Mark; Tang, Songyuan; Chen, Wufan; Shen, Dinggang

2009-08-07

This paper presents a new deformable model using both population and patient-specific statistics to segment the prostate from CT images. There are two novelties in the proposed method. First, a modified scale invariant feature transform (SIFT) local descriptor, which is more distinctive than general intensity and gradient features, is used to characterize the image features. Second, an online training approach is used to build the shape statistics for accurately capturing intra-patient variation, which is more important than inter-patient variation for prostate segmentation in clinical radiotherapy. Experimental results show that the proposed method is robust and accurate, suitable for clinical application.

SEGMENTING CT PROSTATE IMAGES USING POPULATION AND PATIENT-SPECIFIC STATISTICS FOR RADIOTHERAPY

PubMed Central

Feng, Qianjin; Foskey, Mark; Tang, Songyuan; Chen, Wufan; Shen, Dinggang

2010-01-01

This paper presents a new deformable model using both population and patient-specific statistics to segment the prostate from CT images. There are two novelties in the proposed method. First, a modified scale invariant feature transform (SIFT) local descriptor, which is more distinctive than general intensity and gradient features, is used to characterize the image features. Second, an online training approach is used to build the shape statistics for accurately capturing intra-patient variation, which is more important than inter-patient variation for prostate segmentation in clinical radiotherapy. Experimental results show that the proposed method is robust and accurate, suitable for clinical application. PMID:21197416

Global Sensitivity Analysis of Environmental Systems via Multiple Indices based on Statistical Moments of Model Outputs

NASA Astrophysics Data System (ADS)

Guadagnini, A.; Riva, M.; Dell'Oca, A.

2017-12-01

We propose to ground sensitivity of uncertain parameters of environmental models on a set of indices based on the main (statistical) moments, i.e., mean, variance, skewness and kurtosis, of the probability density function (pdf) of a target model output. This enables us to perform Global Sensitivity Analysis (GSA) of a model in terms of multiple statistical moments and yields a quantification of the impact of model parameters on features driving the shape of the pdf of model output. Our GSA approach includes the possibility of being coupled with the construction of a reduced complexity model that allows approximating the full model response at a reduced computational cost. We demonstrate our approach through a variety of test cases. These include a commonly used analytical benchmark, a simplified model representing pumping in a coastal aquifer, a laboratory-scale tracer experiment, and the migration of fracturing fluid through a naturally fractured reservoir (source) to reach an overlying formation (target). Our strategy allows discriminating the relative importance of model parameters to the four statistical moments considered. We also provide an appraisal of the error associated with the evaluation of our sensitivity metrics by replacing the original system model through the selected surrogate model. Our results suggest that one might need to construct a surrogate model with increasing level of accuracy depending on the statistical moment considered in the GSA. The methodological framework we propose can assist the development of analysis techniques targeted to model calibration, design of experiment, uncertainty quantification and risk assessment.

Probabilistic description of ice-supersaturated layers in low resolution profiles of relative humidity

NASA Astrophysics Data System (ADS)

Dickson, N. C.; Gierens, K. M.; Rogers, H. L.; Jones, R. L.

2010-02-01

The global observation, assimilation and prediction in numerical models of ice super-saturated (ISS) regions (ISSR) are crucial if the climate impact of aircraft condensations trails (contrails) is to be fully understood, and if, for example, contrail formation is to be avoided through aircraft operational measures. A robust assessment of the global distribution of ISSR will further this debate, and ISS event occurrence, frequency and spatial scales have recently attracted significant attention. The mean horizontal path length through ISSR as observed by MOZAIC aircraft is 150 km (±250 km). The average vertical thickness of ISS layers is 600-800 m (±575 m) but layers ranging from 25 m to 3000 m have been observed, with up to one third of ISS layers thought to be less than 100 m deep. Given their small scales compared to typical atmospheric model grid sizes, statistical representations of the spatial scales of ISSR are required, in both horizontal and vertical dimensions, if global occurrence of ISSR is to be adequately represented in climate models. This paper uses radiosonde launches made by the UK Meteorological Office, from the British Isles, Gibraltar, St. Helena and the Falkland Islands between January 2002 and December 2006, to investigate the probabilistic occurrence of ISSR. Specifically each radiosonde profile is divided into 50- and 100-hPa pressure layers, to emulate the coarse vertical resolution of some atmospheric models. Then the high resolution observations contained within each thick pressure layer are used to calculate an average relative humidity and an ISS fraction for each individual thick pressure layer. These relative humidity pressure layer descriptions are then linked through a probability function to produce an s-shaped curve describing the ISS fraction in any average relative humidity pressure layer. An empirical investigation has shown that this one curve is statistically valid for mid-latitude locations, irrespective of season and altitude, however, pressure layer depth is an important variable. Using this empirical understanding of the s-shaped relationship a mathematical model was developed to represent the ISS fraction within any arbitrary thick pressure layer. Here the statistical distributions of actual high resolution RHi observations in any thick pressure layer, along with an error function, are used to mathematically describe the s-shape. Two models were developed to represent both 50- and 100-hPa pressure layers with each reconstructing their respective s-shapes within 8-10% of the empirical curves. These new models can be used, to represent the small scale structures of ISS events, in modelled data where only low vertical resolution is available. This will be useful in understanding, and improving the global distribution, both observed and forecasted, of ice super-saturation.

Probabilistic liver atlas construction.

PubMed

Dura, Esther; Domingo, Juan; Ayala, Guillermo; Marti-Bonmati, Luis; Goceri, E

2017-01-13

Anatomical atlases are 3D volumes or shapes representing an organ or structure of the human body. They contain either the prototypical shape of the object of interest together with other shapes representing its statistical variations (statistical atlas) or a probability map of belonging to the object (probabilistic atlas). Probabilistic atlases are mostly built with simple estimations only involving the data at each spatial location. A new method for probabilistic atlas construction that uses a generalized linear model is proposed. This method aims to improve the estimation of the probability to be covered by the liver. Furthermore, all methods to build an atlas involve previous coregistration of the sample of shapes available. The influence of the geometrical transformation adopted for registration in the quality of the final atlas has not been sufficiently investigated. The ability of an atlas to adapt to a new case is one of the most important quality criteria that should be taken into account. The presented experiments show that some methods for atlas construction are severely affected by the previous coregistration step. We show the good performance of the new approach. Furthermore, results suggest that extremely flexible registration methods are not always beneficial, since they can reduce the variability of the atlas and hence its ability to give sensible values of probability when used as an aid in segmentation of new cases.

Numerical details and SAS programs for parameter recovery of the SB distribution

Treesearch

Bernard R. Parresol; Teresa Fidalgo Fonseca; Carlos Pacheco Marques

2010-01-01

The four-parameter SB distribution has seen widespread use in growth-and-yield modeling because it covers a broad spectrum of shapes, fitting both positively and negatively skewed data and bimodal configurations. Two recent parameter recovery schemes, an approach whereby characteristics of a statistical distribution are equated with attributes of...

A Performance Comparison on the Probability Plot Correlation Coefficient Test using Several Plotting Positions for GEV Distribution.

NASA Astrophysics Data System (ADS)

Ahn, Hyunjun; Jung, Younghun; Om, Ju-Seong; Heo, Jun-Haeng

2014-05-01

It is very important to select the probability distribution in Statistical hydrology. Goodness of fit test is a statistical method that selects an appropriate probability model for a given data. The probability plot correlation coefficient (PPCC) test as one of the goodness of fit tests was originally developed for normal distribution. Since then, this test has been widely applied to other probability models. The PPCC test is known as one of the best goodness of fit test because it shows higher rejection powers among them. In this study, we focus on the PPCC tests for the GEV distribution which is widely used in the world. For the GEV model, several plotting position formulas are suggested. However, the PPCC statistics are derived only for the plotting position formulas (Goel and De, In-na and Nguyen, and Kim et al.) in which the skewness coefficient (or shape parameter) are included. And then the regression equations are derived as a function of the shape parameter and sample size for a given significance level. In addition, the rejection powers of these formulas are compared using Monte-Carlo simulation. Keywords: Goodness-of-fit test, Probability plot correlation coefficient test, Plotting position, Monte-Carlo Simulation ACKNOWLEDGEMENTS This research was supported by a grant 'Establishing Active Disaster Management System of Flood Control Structures by using 3D BIM Technique' [NEMA-12-NH-57] from the Natural Hazard Mitigation Research Group, National Emergency Management Agency of Korea.

Statistical damage constitutive model for rocks subjected to cyclic stress and cyclic temperature

NASA Astrophysics Data System (ADS)

Zhou, Shu-Wei; Xia, Cai-Chu; Zhao, Hai-Bin; Mei, Song-Hua; Zhou, Yu

2017-10-01

A constitutive model of rocks subjected to cyclic stress-temperature was proposed. Based on statistical damage theory, the damage constitutive model with Weibull distribution was extended. Influence of model parameters on the stress-strain curve for rock reloading after stress-temperature cycling was then discussed. The proposed model was initially validated by rock tests for cyclic stress-temperature and only cyclic stress. Finally, the total damage evolution induced by stress-temperature cycling and reloading after cycling was explored and discussed. The proposed constitutive model is reasonable and applicable, describing well the stress-strain relationship during stress-temperature cycles and providing a good fit to the test results. Elastic modulus in the reference state and the damage induced by cycling affect the shape of reloading stress-strain curve. Total damage induced by cycling and reloading after cycling exhibits three stages: initial slow increase, mid-term accelerated increase, and final slow increase.

Measurement of Satellite Impact Test Fragments for Modeling Orbital Debris

NASA Technical Reports Server (NTRS)

Hill, Nicole M.

2009-01-01

There are over 13,000 pieces of catalogued objects 10cm and larger in orbit around Earth [ODQN, January 2009, p12]. More than 6000 of these objects are fragments from explosions and collisions. As the earth-orbiting object count increases, debris-generating collisions in the future become a statistical inevitability. To aid in understanding this collision risk, the NASA Orbital Debris Program Office has developed computer models that calculate quantity and orbits of debris both currently in orbit and in future epochs. In order to create a reasonable computer model of the orbital debris environment, it is important to understand the mechanics of creation of debris as a result of a collision. The measurement of the physical characteristics of debris resulting from ground-based, hypervelocity impact testing aids in understanding the sizes and shapes of debris produced from potential impacts in orbit. To advance the accuracy of fragment shape/size determination, the NASA Orbital Debris Program Office recently implemented a computerized measurement system. The goal of this system is to improve knowledge and understanding of the relation between commonly used dimensions and overall shape. The technique developed involves scanning a single fragment with a hand-held laser device, measuring its size properties using a sophisticated software tool, and creating a three-dimensional computer model to demonstrate how the object might appear in orbit. This information is used to aid optical techniques in shape determination. This more automated and repeatable method provides higher accuracy in the size and shape determination of debris.

Electromagnetic sinc Schell-model beams and their statistical properties.

PubMed

Mei, Zhangrong; Mao, Yonghua

2014-09-22

A class of electromagnetic sources with sinc Schell-model correlations is introduced. The conditions on source parameters guaranteeing that the source generates a physical beam are derived. The evolution behaviors of statistical properties for the electromagnetic stochastic beams generated by this new source on propagating in free space and in atmosphere turbulence are investigated with the help of the weighted superposition method and by numerical simulations. It is demonstrated that the intensity distributions of such beams exhibit unique features on propagating in free space and produce a double-layer flat-top profile of being shape-invariant in the far field. This feature makes this new beam particularly suitable for some special laser processing applications. The influences of the atmosphere turbulence with a non-Kolmogorov power spectrum on statistical properties of the new beams are analyzed in detail.

Exploiting Molecular Weight Distribution Shape to Tune Domain Spacing in Block Copolymer Thin Films.

PubMed

Gentekos, Dillon T; Jia, Junteng; Tirado, Erika S; Barteau, Katherine P; Smilgies, Detlef-M; DiStasio, Robert A; Fors, Brett P

2018-04-04

We report a method for tuning the domain spacing ( D sp ) of self-assembled block copolymer thin films of poly(styrene- block-methyl methacrylate) (PS- b-PMMA) over a large range of lamellar periods. By modifying the molecular weight distribution (MWD) shape (including both the breadth and skew) of the PS block via temporal control of polymer chain initiation in anionic polymerization, we observe increases of up to 41% in D sp for polymers with the same overall molecular weight ( M n ≈ 125 kg mol -1 ) without significantly changing the overall morphology or chemical composition of the final material. In conjunction with our experimental efforts, we have utilized concepts from population statistics and least-squares analysis to develop a model for predicting D sp based on the first three moments of the MWDs. This statistical model reproduces experimental D sp values with high fidelity (with mean absolute errors of 1.2 nm or 1.8%) and provides novel physical insight into the individual and collective roles played by the MWD moments in determining this property of interest. This work demonstrates that both MWD breadth and skew have a profound influence over D sp , thereby providing an experimental and conceptual platform for exploiting MWD shape as a simple and modular handle for fine-tuning D sp in block copolymer thin films.

Empirical phylogenies and species abundance distributions are consistent with preequilibrium dynamics of neutral community models with gene flow.

PubMed

Bonnet-Lebrun, Anne-Sophie; Manica, Andrea; Eriksson, Anders; Rodrigues, Ana S L

2017-05-01

Community characteristics reflect past ecological and evolutionary dynamics. Here, we investigate whether it is possible to obtain realistically shaped modeled communities-that is with phylogenetic trees and species abundance distributions shaped similarly to typical empirical bird and mammal communities-from neutral community models. To test the effect of gene flow, we contrasted two spatially explicit individual-based neutral models: one with protracted speciation, delayed by gene flow, and one with point mutation speciation, unaffected by gene flow. The former produced more realistic communities (shape of phylogenetic tree and species-abundance distribution), consistent with gene flow being a key process in macro-evolutionary dynamics. Earlier models struggled to capture the empirically observed branching tempo in phylogenetic trees, as measured by the gamma statistic. We show that the low gamma values typical of empirical trees can be obtained in models with protracted speciation, in preequilibrium communities developing from an initially abundant and widespread species. This was even more so in communities sampled incompletely, particularly if the unknown species are the youngest. Overall, our results demonstrate that the characteristics of empirical communities that we have studied can, to a large extent, be explained through a purely neutral model under preequilibrium conditions. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.

Long-term changes (1980-2003) in total ozone time series over Northern Hemisphere midlatitudes

NASA Astrophysics Data System (ADS)

Białek, Małgorzata

2006-03-01

Long-term changes in total ozone time series for Arosa, Belsk, Boulder and Sapporo stations are examined. For each station we analyze time series of the following statistical characteristics of the distribution of daily ozone data: seasonal mean, standard deviation, maximum and minimum of total daily ozone values for all seasons. The iterative statistical model is proposed to estimate trends and long-term changes in the statistical distribution of the daily total ozone data. The trends are calculated for the period 1980-2003. We observe lessening of negative trends in the seasonal means as compared to those calculated by WMO for 1980-2000. We discuss a possibility of a change of the distribution shape of ozone daily data using the Kolmogorov-Smirnov test and comparing trend values in the seasonal mean, standard deviation, maximum and minimum time series for the selected stations and seasons. The distribution shift toward lower values without a change in the distribution shape is suggested with the following exceptions: the spreading of the distribution toward lower values for Belsk during winter and no decisive result for Sapporo and Boulder in summer.

Extended q -Gaussian and q -exponential distributions from gamma random variables

NASA Astrophysics Data System (ADS)

Budini, Adrián A.

2015-05-01

The family of q -Gaussian and q -exponential probability densities fit the statistical behavior of diverse complex self-similar nonequilibrium systems. These distributions, independently of the underlying dynamics, can rigorously be obtained by maximizing Tsallis "nonextensive" entropy under appropriate constraints, as well as from superstatistical models. In this paper we provide an alternative and complementary scheme for deriving these objects. We show that q -Gaussian and q -exponential random variables can always be expressed as a function of two statistically independent gamma random variables with the same scale parameter. Their shape index determines the complexity q parameter. This result also allows us to define an extended family of asymmetric q -Gaussian and modified q -exponential densities, which reduce to the standard ones when the shape parameters are the same. Furthermore, we demonstrate that a simple change of variables always allows relating any of these distributions with a beta stochastic variable. The extended distributions are applied in the statistical description of different complex dynamics such as log-return signals in financial markets and motion of point defects in a fluid flow.

Statistics of backscatter radar return from vegetation

NASA Technical Reports Server (NTRS)

Karam, M. A.; Chen, K. S.; Fung, A. K.

1992-01-01

The statistical characteristics of radar return from vegetation targets are investigated through a simulation study based upon the first-order scattered field. For simulation purposes, the vegetation targets are modeled as a layer of randomly oriented and spaced finite cylinders, needles, or discs, or a combination of them. The finite cylinder is used to represent a branch or a trunk, the needle for a stem or a coniferous leaf, and the disc for a decidous leaf. For a plane wave illuminating a vegetation canopy, simulation results show that the signal returned from a layer of disc- or needle-shaped leaves follows the Gamma distribution, and that the signal returned from a layer of branches resembles the log normal distribution. The Gamma distribution also represents the signal returned from a layer of a mixture of branches and leaves regardless of the leaf shapes. Results also indicate that the polarization state does not have a significant impact on signal distribution.

A generalized K statistic for estimating phylogenetic signal from shape and other high-dimensional multivariate data.

PubMed

Adams, Dean C

2014-09-01

Phylogenetic signal is the tendency for closely related species to display similar trait values due to their common ancestry. Several methods have been developed for quantifying phylogenetic signal in univariate traits and for sets of traits treated simultaneously, and the statistical properties of these approaches have been extensively studied. However, methods for assessing phylogenetic signal in high-dimensional multivariate traits like shape are less well developed, and their statistical performance is not well characterized. In this article, I describe a generalization of the K statistic of Blomberg et al. that is useful for quantifying and evaluating phylogenetic signal in highly dimensional multivariate data. The method (K(mult)) is found from the equivalency between statistical methods based on covariance matrices and those based on distance matrices. Using computer simulations based on Brownian motion, I demonstrate that the expected value of K(mult) remains at 1.0 as trait variation among species is increased or decreased, and as the number of trait dimensions is increased. By contrast, estimates of phylogenetic signal found with a squared-change parsimony procedure for multivariate data change with increasing trait variation among species and with increasing numbers of trait dimensions, confounding biological interpretations. I also evaluate the statistical performance of hypothesis testing procedures based on K(mult) and find that the method displays appropriate Type I error and high statistical power for detecting phylogenetic signal in high-dimensional data. Statistical properties of K(mult) were consistent for simulations using bifurcating and random phylogenies, for simulations using different numbers of species, for simulations that varied the number of trait dimensions, and for different underlying models of trait covariance structure. Overall these findings demonstrate that K(mult) provides a useful means of evaluating phylogenetic signal in high-dimensional multivariate traits. Finally, I illustrate the utility of the new approach by evaluating the strength of phylogenetic signal for head shape in a lineage of Plethodon salamanders. © The Author(s) 2014. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Segmentation of the Aortic Valve Apparatus in 3D Echocardiographic Images: Deformable Modeling of a Branching Medial Structure

PubMed Central

Pouch, Alison M.; Tian, Sijie; Takabe, Manabu; Wang, Hongzhi; Yuan, Jiefu; Cheung, Albert T.; Jackson, Benjamin M.; Gorman, Joseph H.; Gorman, Robert C.; Yushkevich, Paul A.

2015-01-01

3D echocardiographic (3DE) imaging is a useful tool for assessing the complex geometry of the aortic valve apparatus. Segmentation of this structure in 3DE images is a challenging task that benefits from shape-guided deformable modeling methods, which enable inter-subject statistical shape comparison. Prior work demonstrates the efficacy of using continuous medial representation (cm-rep) as a shape descriptor for valve leaflets. However, its application to the entire aortic valve apparatus is limited since the structure has a branching medial geometry that cannot be explicitly parameterized in the original cm-rep framework. In this work, we show that the aortic valve apparatus can be accurately segmented using a new branching medial modeling paradigm. The segmentation method achieves a mean boundary displacement of 0.6 ± 0.1 mm (approximately one voxel) relative to manual segmentation on 11 3DE images of normal open aortic valves. This study demonstrates a promising approach for quantitative 3DE analysis of aortic valve morphology. PMID:26247062

Characterizing the size and shape of sea ice floes

PubMed Central

Gherardi, Marco; Lagomarsino, Marco Cosentino

2015-01-01

Monitoring drift ice in the Arctic and Antarctic regions directly and by remote sensing is important for the study of climate, but a unified modeling framework is lacking. Hence, interpretation of the data, as well as the decision of what to measure, represent a challenge for different fields of science. To address this point, we analyzed, using statistical physics tools, satellite images of sea ice from four different locations in both the northern and southern hemispheres, and measured the size and the elongation of ice floes (floating pieces of ice). We find that (i) floe size follows a distribution that can be characterized with good approximation by a single length scale , which we discuss in the framework of stochastic fragmentation models, and (ii) the deviation of their shape from circularity is reproduced with remarkable precision by a geometric model of coalescence by freezing, based on random Voronoi tessellations, with a single free parameter expressing the shape disorder. Although the physical interpretations remain open, this advocates the parameters and as two independent indicators of the environment in the polar regions, which are easily accessible by remote sensing. PMID:26014797

Shapes of rotating superfluid helium nanodroplets

DOE PAGES

Bernando, Charles; Tanyag, Rico Mayro P.; Jones, Curtis; ...

2017-02-16

Rotating superfluid He droplets of approximately 1 μm in diameter were obtained in a free nozzle beam expansion of liquid He in vacuum and were studied by single-shot coherent diffractive imaging using an x-ray free electron laser. The formation of strongly deformed droplets is evidenced by large anisotropies and intensity anomalies (streaks) in the obtained diffraction images. The analysis of the images shows that in addition to previously described axially symmetric oblate shapes, some droplets exhibit prolate shapes. Forward modeling of the diffraction images indicates that the shapes of rotating superfluid droplets are very similar to their classical counterparts, givingmore » direct access to the droplet angular momenta and angular velocities. Here, the analyses of the radial intensity distribution and appearance statistics of the anisotropic images confirm the existence of oblate metastable superfluid droplets with large angular momenta beyond the classical bifurcation threshold.« less

Shapes of rotating superfluid helium nanodroplets

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

Bernando, Charles; Tanyag, Rico Mayro P.; Jones, Curtis

Rotating superfluid He droplets of approximately 1 μm in diameter were obtained in a free nozzle beam expansion of liquid He in vacuum and were studied by single-shot coherent diffractive imaging using an x-ray free electron laser. The formation of strongly deformed droplets is evidenced by large anisotropies and intensity anomalies (streaks) in the obtained diffraction images. The analysis of the images shows that in addition to previously described axially symmetric oblate shapes, some droplets exhibit prolate shapes. Forward modeling of the diffraction images indicates that the shapes of rotating superfluid droplets are very similar to their classical counterparts, givingmore » direct access to the droplet angular momenta and angular velocities. Here, the analyses of the radial intensity distribution and appearance statistics of the anisotropic images confirm the existence of oblate metastable superfluid droplets with large angular momenta beyond the classical bifurcation threshold.« less

Statistical properties of superimposed stationary spike trains.

PubMed

Deger, Moritz; Helias, Moritz; Boucsein, Clemens; Rotter, Stefan

2012-06-01

The Poisson process is an often employed model for the activity of neuronal populations. It is known, though, that superpositions of realistic, non- Poisson spike trains are not in general Poisson processes, not even for large numbers of superimposed processes. Here we construct superimposed spike trains from intracellular in vivo recordings from rat neocortex neurons and compare their statistics to specific point process models. The constructed superimposed spike trains reveal strong deviations from the Poisson model. We find that superpositions of model spike trains that take the effective refractoriness of the neurons into account yield a much better description. A minimal model of this kind is the Poisson process with dead-time (PPD). For this process, and for superpositions thereof, we obtain analytical expressions for some second-order statistical quantities-like the count variability, inter-spike interval (ISI) variability and ISI correlations-and demonstrate the match with the in vivo data. We conclude that effective refractoriness is the key property that shapes the statistical properties of the superposition spike trains. We present new, efficient algorithms to generate superpositions of PPDs and of gamma processes that can be used to provide more realistic background input in simulations of networks of spiking neurons. Using these generators, we show in simulations that neurons which receive superimposed spike trains as input are highly sensitive for the statistical effects induced by neuronal refractoriness.

An integrated model-driven method for in-treatment upper airway motion tracking using cine MRI in head and neck radiation therapy

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

Li, Hua, E-mail: huli@radonc.wustl.edu; Chen, Hsin

Purpose: For the first time, MRI-guided radiation therapy systems can acquire cine images to dynamically monitor in-treatment internal organ motion. However, the complex head and neck (H&N) structures and low-contrast/resolution of on-board cine MRI images make automatic motion tracking a very challenging task. In this study, the authors proposed an integrated model-driven method to automatically track the in-treatment motion of the H&N upper airway, a complex and highly deformable region wherein internal motion often occurs in an either voluntary or involuntary manner, from cine MRI images for the analysis of H&N motion patterns. Methods: Considering the complex H&N structures andmore » ensuring automatic and robust upper airway motion tracking, the authors firstly built a set of linked statistical shapes (including face, face-jaw, and face-jaw-palate) using principal component analysis from clinically approved contours delineated on a set of training data. The linked statistical shapes integrate explicit landmarks and implicit shape representation. Then, a hierarchical model-fitting algorithm was developed to align the linked shapes on the first image frame of a to-be-tracked cine sequence and to localize the upper airway region. Finally, a multifeature level set contour propagation scheme was performed to identify the upper airway shape change, frame-by-frame, on the entire image sequence. The multifeature fitting energy, including the information of intensity variations, edge saliency, curve geometry, and temporal shape continuity, was minimized to capture the details of moving airway boundaries. Sagittal cine MR image sequences acquired from three H&N cancer patients were utilized to demonstrate the performance of the proposed motion tracking method. Results: The tracking accuracy was validated by comparing the results to the average of two manual delineations in 50 randomly selected cine image frames from each patient. The resulting average dice similarity coefficient (93.28%  ±  1.46%) and margin error (0.49  ±  0.12 mm) showed good agreement between the automatic and manual results. The comparison with three other deformable model-based segmentation methods illustrated the superior shape tracking performance of the proposed method. Large interpatient variations of swallowing frequency, swallowing duration, and upper airway cross-sectional area were observed from the testing cine image sequences. Conclusions: The proposed motion tracking method can provide accurate upper airway motion tracking results, and enable automatic and quantitative identification and analysis of in-treatment H&N upper airway motion. By integrating explicit and implicit linked-shape representations within a hierarchical model-fitting process, the proposed tracking method can process complex H&N structures and low-contrast/resolution cine MRI images. Future research will focus on the improvement of method reliability, patient motion pattern analysis for providing more information on patient-specific prediction of structure displacements, and motion effects on dosimetry for better H&N motion management in radiation therapy.« less

An integrated model-driven method for in-treatment upper airway motion tracking using cine MRI in head and neck radiation therapy.

PubMed

Li, Hua; Chen, Hsin-Chen; Dolly, Steven; Li, Harold; Fischer-Valuck, Benjamin; Victoria, James; Dempsey, James; Ruan, Su; Anastasio, Mark; Mazur, Thomas; Gach, Michael; Kashani, Rojano; Green, Olga; Rodriguez, Vivian; Gay, Hiram; Thorstad, Wade; Mutic, Sasa

2016-08-01

For the first time, MRI-guided radiation therapy systems can acquire cine images to dynamically monitor in-treatment internal organ motion. However, the complex head and neck (H&N) structures and low-contrast/resolution of on-board cine MRI images make automatic motion tracking a very challenging task. In this study, the authors proposed an integrated model-driven method to automatically track the in-treatment motion of the H&N upper airway, a complex and highly deformable region wherein internal motion often occurs in an either voluntary or involuntary manner, from cine MRI images for the analysis of H&N motion patterns. Considering the complex H&N structures and ensuring automatic and robust upper airway motion tracking, the authors firstly built a set of linked statistical shapes (including face, face-jaw, and face-jaw-palate) using principal component analysis from clinically approved contours delineated on a set of training data. The linked statistical shapes integrate explicit landmarks and implicit shape representation. Then, a hierarchical model-fitting algorithm was developed to align the linked shapes on the first image frame of a to-be-tracked cine sequence and to localize the upper airway region. Finally, a multifeature level set contour propagation scheme was performed to identify the upper airway shape change, frame-by-frame, on the entire image sequence. The multifeature fitting energy, including the information of intensity variations, edge saliency, curve geometry, and temporal shape continuity, was minimized to capture the details of moving airway boundaries. Sagittal cine MR image sequences acquired from three H&N cancer patients were utilized to demonstrate the performance of the proposed motion tracking method. The tracking accuracy was validated by comparing the results to the average of two manual delineations in 50 randomly selected cine image frames from each patient. The resulting average dice similarity coefficient (93.28%  ±  1.46%) and margin error (0.49  ±  0.12 mm) showed good agreement between the automatic and manual results. The comparison with three other deformable model-based segmentation methods illustrated the superior shape tracking performance of the proposed method. Large interpatient variations of swallowing frequency, swallowing duration, and upper airway cross-sectional area were observed from the testing cine image sequences. The proposed motion tracking method can provide accurate upper airway motion tracking results, and enable automatic and quantitative identification and analysis of in-treatment H&N upper airway motion. By integrating explicit and implicit linked-shape representations within a hierarchical model-fitting process, the proposed tracking method can process complex H&N structures and low-contrast/resolution cine MRI images. Future research will focus on the improvement of method reliability, patient motion pattern analysis for providing more information on patient-specific prediction of structure displacements, and motion effects on dosimetry for better H&N motion management in radiation therapy.

Comparison of organs' shapes with geometric and Zernike 3D moments.

PubMed

Broggio, D; Moignier, A; Ben Brahim, K; Gardumi, A; Grandgirard, N; Pierrat, N; Chea, M; Derreumaux, S; Desbrée, A; Boisserie, G; Aubert, B; Mazeron, J-J; Franck, D

2013-09-01

The morphological similarity of organs is studied with feature vectors based on geometric and Zernike 3D moments. It is particularly investigated if outliers and average models can be identified. For this purpose, the relative proximity to the mean feature vector is defined, principal coordinate and clustering analyses are also performed. To study the consistency and usefulness of this approach, 17 livers and 76 hearts voxel models from several sources are considered. In the liver case, models with similar morphological feature are identified. For the limited amount of studied cases, the liver of the ICRP male voxel model is identified as a better surrogate than the female one. For hearts, the clustering analysis shows that three heart shapes represent about 80% of the morphological variations. The relative proximity and clustering analysis rather consistently identify outliers and average models. For the two cases, identification of outliers and surrogate of average models is rather robust. However, deeper classification of morphological feature is subject to caution and can only be performed after cross analysis of at least two kinds of feature vectors. Finally, the Zernike moments contain all the information needed to re-construct the studied objects and thus appear as a promising tool to derive statistical organ shapes. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Tooth-size discrepancy: A comparison between manual and digital methods

PubMed Central

Correia, Gabriele Dória Cabral; Habib, Fernando Antonio Lima; Vogel, Carlos Jorge

2014-01-01

Introduction Technological advances in Dentistry have emerged primarily in the area of diagnostic tools. One example is the 3D scanner, which can transform plaster models into three-dimensional digital models. Objective This study aimed to assess the reliability of tooth size-arch length discrepancy analysis measurements performed on three-dimensional digital models, and compare these measurements with those obtained from plaster models. Material and Methods To this end, plaster models of lower dental arches and their corresponding three-dimensional digital models acquired with a 3Shape R700T scanner were used. All of them had lower permanent dentition. Four different tooth size-arch length discrepancy calculations were performed on each model, two of which by manual methods using calipers and brass wire, and two by digital methods using linear measurements and parabolas. Results Data were statistically assessed using Friedman test and no statistically significant differences were found between the two methods (P > 0.05), except for values found by the linear digital method which revealed a slight, non-significant statistical difference. Conclusions Based on the results, it is reasonable to assert that any of these resources used by orthodontists to clinically assess tooth size-arch length discrepancy can be considered reliable. PMID:25279529

Robust group-wise rigid registration of point sets using t-mixture model

NASA Astrophysics Data System (ADS)

Ravikumar, Nishant; Gooya, Ali; Frangi, Alejandro F.; Taylor, Zeike A.

2016-03-01

A probabilistic framework for robust, group-wise rigid alignment of point-sets using a mixture of Students t-distribution especially when the point sets are of varying lengths, are corrupted by an unknown degree of outliers or in the presence of missing data. Medical images (in particular magnetic resonance (MR) images), their segmentations and consequently point-sets generated from these are highly susceptible to corruption by outliers. This poses a problem for robust correspondence estimation and accurate alignment of shapes, necessary for training statistical shape models (SSMs). To address these issues, this study proposes to use a t-mixture model (TMM), to approximate the underlying joint probability density of a group of similar shapes and align them to a common reference frame. The heavy-tailed nature of t-distributions provides a more robust registration framework in comparison to state of the art algorithms. Significant reduction in alignment errors is achieved in the presence of outliers, using the proposed TMM-based group-wise rigid registration method, in comparison to its Gaussian mixture model (GMM) counterparts. The proposed TMM-framework is compared with a group-wise variant of the well-known Coherent Point Drift (CPD) algorithm and two other group-wise methods using GMMs, using both synthetic and real data sets. Rigid alignment errors for groups of shapes are quantified using the Hausdorff distance (HD) and quadratic surface distance (QSD) metrics.

Lymph node segmentation on CT images by a shape model guided deformable surface methodh

NASA Astrophysics Data System (ADS)

Maleike, Daniel; Fabel, Michael; Tetzlaff, Ralf; von Tengg-Kobligk, Hendrik; Heimann, Tobias; Meinzer, Hans-Peter; Wolf, Ivo

2008-03-01

With many tumor entities, quantitative assessment of lymph node growth over time is important to make therapy choices or to evaluate new therapies. The clinical standard is to document diameters on transversal slices, which is not the best measure for a volume. We present a new algorithm to segment (metastatic) lymph nodes and evaluate the algorithm with 29 lymph nodes in clinical CT images. The algorithm is based on a deformable surface search, which uses statistical shape models to restrict free deformation. To model lymph nodes, we construct an ellipsoid shape model, which strives for a surface with strong gradients and user-defined gray values. The algorithm is integrated into an application, which also allows interactive correction of the segmentation results. The evaluation shows that the algorithm gives good results in the majority of cases and is comparable to time-consuming manual segmentation. The median volume error was 10.1% of the reference volume before and 6.1% after manual correction. Integrated into an application, it is possible to perform lymph node volumetry for a whole patient within the 10 to 15 minutes time limit imposed by clinical routine.

Separation of the atmospheric variability into non-Gaussian multidimensional sources by projection pursuit techniques

NASA Astrophysics Data System (ADS)

Pires, Carlos A. L.; Ribeiro, Andreia F. S.

2017-02-01

We develop an expansion of space-distributed time series into statistically independent uncorrelated subspaces (statistical sources) of low-dimension and exhibiting enhanced non-Gaussian probability distributions with geometrically simple chosen shapes (projection pursuit rationale). The method relies upon a generalization of the principal component analysis that is optimal for Gaussian mixed signals and of the independent component analysis (ICA), optimized to split non-Gaussian scalar sources. The proposed method, supported by information theory concepts and methods, is the independent subspace analysis (ISA) that looks for multi-dimensional, intrinsically synergetic subspaces such as dyads (2D) and triads (3D), not separable by ICA. Basically, we optimize rotated variables maximizing certain nonlinear correlations (contrast functions) coming from the non-Gaussianity of the joint distribution. As a by-product, it provides nonlinear variable changes `unfolding' the subspaces into nearly Gaussian scalars of easier post-processing. Moreover, the new variables still work as nonlinear data exploratory indices of the non-Gaussian variability of the analysed climatic and geophysical fields. The method (ISA, followed by nonlinear unfolding) is tested into three datasets. The first one comes from the Lorenz'63 three-dimensional chaotic model, showing a clear separation into a non-Gaussian dyad plus an independent scalar. The second one is a mixture of propagating waves of random correlated phases in which the emergence of triadic wave resonances imprints a statistical signature in terms of a non-Gaussian non-separable triad. Finally the method is applied to the monthly variability of a high-dimensional quasi-geostrophic (QG) atmospheric model, applied to the Northern Hemispheric winter. We find that quite enhanced non-Gaussian dyads of parabolic shape, perform much better than the unrotated variables in which concerns the separation of the four model's centroid regimes (positive and negative phases of the Arctic Oscillation and of the North Atlantic Oscillation). Triads are also likely in the QG model but of weaker expression than dyads due to the imposed shape and dimension. The study emphasizes the existence of nonlinear dyadic and triadic nonlinear teleconnections.

Statistical shape modeling of human cochlea: alignment and principal component analysis

NASA Astrophysics Data System (ADS)

Poznyakovskiy, Anton A.; Zahnert, Thomas; Fischer, Björn; Lasurashvili, Nikoloz; Kalaidzidis, Yannis; Mürbe, Dirk

2013-02-01

The modeling of the cochlear labyrinth in living subjects is hampered by insufficient resolution of available clinical imaging methods. These methods usually provide resolutions higher than 125 μm. This is too crude to record the position of basilar membrane and, as a result, keep apart even the scala tympani from other scalae. This problem could be avoided by the means of atlas-based segmentation. The specimens can endure higher radiation loads and, conversely, provide better-resolved images. The resulting surface can be used as the seed for atlas-based segmentation. To serve this purpose, we have developed a statistical shape model (SSM) of human scala tympani based on segmentations obtained from 10 μCT image stacks. After segmentation, we aligned the resulting surfaces using Procrustes alignment. This algorithm was slightly modified to accommodate single models with nodes which do not necessarily correspond to salient features and vary in number between models. We have established correspondence by mutual proximity between nodes. Rather than using the standard Euclidean norm, we have applied an alternative logarithmic norm to improve outlier treatment. The minimization was done using BFGS method. We have also split the surface nodes along an octree to reduce computation cost. Subsequently, we have performed the principal component analysis of the training set with Jacobi eigenvalue algorithm. We expect the resulting method to help acquiring not only better understanding in interindividual variations of cochlear anatomy, but also a step towards individual models for pre-operative diagnostics prior to cochlear implant insertions.

Statistical Analyses of Brain Surfaces Using Gaussian Random Fields on 2-D Manifolds

PubMed Central

Staib, Lawrence H.; Xu, Dongrong; Zhu, Hongtu; Peterson, Bradley S.

2008-01-01

Interest in the morphometric analysis of the brain and its subregions has recently intensified because growth or degeneration of the brain in health or illness affects not only the volume but also the shape of cortical and subcortical brain regions, and new image processing techniques permit detection of small and highly localized perturbations in shape or localized volume, with remarkable precision. An appropriate statistical representation of the shape of a brain region is essential, however, for detecting, localizing, and interpreting variability in its surface contour and for identifying differences in volume of the underlying tissue that produce that variability across individuals and groups of individuals. Our statistical representation of the shape of a brain region is defined by a reference region for that region and by a Gaussian random field (GRF) that is defined across the entire surface of the region. We first select a reference region from a set of segmented brain images of healthy individuals. The GRF is then estimated as the signed Euclidean distances between points on the surface of the reference region and the corresponding points on the corresponding region in images of brains that have been coregistered to the reference. Correspondences between points on these surfaces are defined through deformations of each region of a brain into the coordinate space of the reference region using the principles of fluid dynamics. The warped, coregistered region of each subject is then unwarped into its native space, simultaneously bringing into that space the map of corresponding points that was established when the surfaces of the subject and reference regions were tightly coregistered. The proposed statistical description of the shape of surface contours makes no assumptions, other than smoothness, about the shape of the region or its GRF. The description also allows for the detection and localization of statistically significant differences in the shapes of the surfaces across groups of subjects at both a fine and coarse scale. We demonstrate the effectiveness of these statistical methods by applying them to study differences in shape of the amygdala and hippocampus in a large sample of normal subjects and in subjects with attention deficit/hyperactivity disorder (ADHD). PMID:17243583

Interactive surface correction for 3D shape based segmentation

NASA Astrophysics Data System (ADS)

Schwarz, Tobias; Heimann, Tobias; Tetzlaff, Ralf; Rau, Anne-Mareike; Wolf, Ivo; Meinzer, Hans-Peter

2008-03-01

Statistical shape models have become a fast and robust method for segmentation of anatomical structures in medical image volumes. In clinical practice, however, pathological cases and image artifacts can lead to local deviations of the detected contour from the true object boundary. These deviations have to be corrected manually. We present an intuitively applicable solution for surface interaction based on Gaussian deformation kernels. The method is evaluated by two radiological experts on segmentations of the liver in contrast-enhanced CT images and of the left heart ventricle (LV) in MRI data. For both applications, five datasets are segmented automatically using deformable shape models, and the resulting surfaces are corrected manually. The interactive correction step improves the average surface distance against ground truth from 2.43mm to 2.17mm for the liver, and from 2.71mm to 1.34mm for the LV. We expect this method to raise the acceptance of automatic segmentation methods in clinical application.

A κ-generalized statistical mechanics approach to income analysis

NASA Astrophysics Data System (ADS)

Clementi, F.; Gallegati, M.; Kaniadakis, G.

2009-02-01

This paper proposes a statistical mechanics approach to the analysis of income distribution and inequality. A new distribution function, having its roots in the framework of κ-generalized statistics, is derived that is particularly suitable for describing the whole spectrum of incomes, from the low-middle income region up to the high income Pareto power-law regime. Analytical expressions for the shape, moments and some other basic statistical properties are given. Furthermore, several well-known econometric tools for measuring inequality, which all exist in a closed form, are considered. A method for parameter estimation is also discussed. The model is shown to fit remarkably well the data on personal income for the United States, and the analysis of inequality performed in terms of its parameters is revealed as very powerful.

Multi-pulse multi-delay (MPMD) multiple access modulation for UWB

DOEpatents

Dowla, Farid U.; Nekoogar, Faranak

2007-03-20

A new modulation scheme in UWB communications is introduced. This modulation technique utilizes multiple orthogonal transmitted-reference pulses for UWB channelization. The proposed UWB receiver samples the second order statistical function at both zero and non-zero lags and matches the samples to stored second order statistical functions, thus sampling and matching the shape of second order statistical functions rather than just the shape of the received pulses.

Impact of Temperature and Non-Gaussian Statistics on Electron Transfer in Donor–Bridge–Acceptor Molecules

DOE PAGES

Waskasi, Morteza M.; Newton, Marshall D.; Matyushov, Dmitry V.

2017-03-16

A combination of experimental data and theoretical analysis provides evidence of a bell-shaped kinetics of electron transfer in the Arrhenius coordinates ln k vs 1/T . This kinetic law is a temperature analog of the familiar Marcus bell-shaped dependence based on ln k vs the reaction free energy. These results were obtained for reactions of intramolecular charge shift between the donor and acceptor separated by a rigid spacer studied experimentally by Miller and co-workers. The non-Arrhenius kinetic law is a direct consequence of the solvent reorganization energy and reaction driving force changing approximately as hyperbolic functions with temperature. The reorganizationmore » energy decreases and the driving force increases when temperature is increased. The point of equality between them marks the maximum of the activationless reaction rate. Reaching the consistency between the kinetic and thermodynamic experimental data requires the non-Gaussian statistics of the donor-acceptor energy gap described by the Q-model of electron transfer. Furthermore, the theoretical formalism combines the vibrational envelope of quantum vibronic transitions with the Q-model describing the classical component of the Franck-Condon factor and a microscopic solvation model of the solvent reorganization energy and the reaction free energy.« less

The ratio of profile peak separations as a probe of pulsar radio-beam structure

NASA Astrophysics Data System (ADS)

Dyks, J.; Pierbattista, M.

2015-12-01

The known population of pulsars contains objects with four- and five-component profiles, for which the peak-to-peak separations between the inner and outer components can be measured. These Q- and M-type profiles can be interpreted as a result of sightline cut through a nested-cone beam, or through a set of azimuthal fan beams. We show that the ratio RW of the components' separations provides a useful measure of the beam shape, which is mostly independent of parameters that determine the beam scale and complicate interpretation of simpler profiles. In particular, the method does not depend on the emission altitude and the dipole tilt distribution. The different structures of the radio beam imply manifestly different statistical distributions of RW, with the conal model being several orders of magnitude less consistent with data than the fan-beam model. To bring the conal model into consistency with data, strong effects of observational selection need to be called for, with 80 per cent of Q and M profiles assumed to be undetected because of intrinsic blending effects. It is concluded that the statistical properties of Q and M profiles are more consistent with the fan-shaped beams, than with the traditional nested-cone geometry.

Applications of wavelets in morphometric analysis of medical images

NASA Astrophysics Data System (ADS)

Davatzikos, Christos; Tao, Xiaodong; Shen, Dinggang

2003-11-01

Morphometric analysis of medical images is playing an increasingly important role in understanding brain structure and function, as well as in understanding the way in which these change during development, aging and pathology. This paper presents three wavelet-based methods with related applications in morphometric analysis of magnetic resonance (MR) brain images. The first method handles cases where very limited datasets are available for the training of statistical shape models in the deformable segmentation. The method is capable of capturing a larger range of shape variability than the standard active shape models (ASMs) can, by using the elegant spatial-frequency decomposition of the shape contours provided by wavelet transforms. The second method addresses the difficulty of finding correspondences in anatomical images, which is a key step in shape analysis and deformable registration. The detection of anatomical correspondences is completed by using wavelet-based attribute vectors as morphological signatures of voxels. The third method uses wavelets to characterize the morphological measurements obtained from all voxels in a brain image, and the entire set of wavelet coefficients is further used to build a brain classifier. Since the classification scheme operates in a very-high-dimensional space, it can determine subtle population differences with complex spatial patterns. Experimental results are provided to demonstrate the performance of the proposed methods.

A variational approach to liver segmentation using statistics from multiple sources

NASA Astrophysics Data System (ADS)

Zheng, Shenhai; Fang, Bin; Li, Laquan; Gao, Mingqi; Wang, Yi

2018-01-01

Medical image segmentation plays an important role in digital medical research, and therapy planning and delivery. However, the presence of noise and low contrast renders automatic liver segmentation an extremely challenging task. In this study, we focus on a variational approach to liver segmentation in computed tomography scan volumes in a semiautomatic and slice-by-slice manner. In this method, one slice is selected and its connected component liver region is determined manually to initialize the subsequent automatic segmentation process. From this guiding slice, we execute the proposed method downward to the last one and upward to the first one, respectively. A segmentation energy function is proposed by combining the statistical shape prior, global Gaussian intensity analysis, and enforced local statistical feature under the level set framework. During segmentation, the shape of the liver shape is estimated by minimization of this function. The improved Chan-Vese model is used to refine the shape to capture the long and narrow regions of the liver. The proposed method was verified on two independent public databases, the 3D-IRCADb and the SLIVER07. Among all the tested methods, our method yielded the best volumetric overlap error (VOE) of 6.5 +/- 2.8 % , the best root mean square symmetric surface distance (RMSD) of 2.1 +/- 0.8 mm, the best maximum symmetric surface distance (MSD) of 18.9 +/- 8.3 mm in 3D-IRCADb dataset, and the best average symmetric surface distance (ASD) of 0.8 +/- 0.5 mm, the best RMSD of 1.5 +/- 1.1 mm in SLIVER07 dataset, respectively. The results of the quantitative comparison show that the proposed liver segmentation method achieves competitive segmentation performance with state-of-the-art techniques.

Characterization of Type Ia Supernova Light Curves Using Principal Component Analysis of Sparse Functional Data

NASA Astrophysics Data System (ADS)

He, Shiyuan; Wang, Lifan; Huang, Jianhua Z.

2018-04-01

With growing data from ongoing and future supernova surveys, it is possible to empirically quantify the shapes of SNIa light curves in more detail, and to quantitatively relate the shape parameters with the intrinsic properties of SNIa. Building such relationships is critical in controlling systematic errors associated with supernova cosmology. Based on a collection of well-observed SNIa samples accumulated in the past years, we construct an empirical SNIa light curve model using a statistical method called the functional principal component analysis (FPCA) for sparse and irregularly sampled functional data. Using this method, the entire light curve of an SNIa is represented by a linear combination of principal component functions, and the SNIa is represented by a few numbers called “principal component scores.” These scores are used to establish relations between light curve shapes and physical quantities such as intrinsic color, interstellar dust reddening, spectral line strength, and spectral classes. These relations allow for descriptions of some critical physical quantities based purely on light curve shape parameters. Our study shows that some important spectral feature information is being encoded in the broad band light curves; for instance, we find that the light curve shapes are correlated with the velocity and velocity gradient of the Si II λ6355 line. This is important for supernova surveys (e.g., LSST and WFIRST). Moreover, the FPCA light curve model is used to construct the entire light curve shape, which in turn is used in a functional linear form to adjust intrinsic luminosity when fitting distance models.

EAS fluctuation approach to primary mass composition investigation

NASA Technical Reports Server (NTRS)

Stamenov, J. N.; Janminchev, V. D.

1985-01-01

The analysis of muon and electron fluctuation distribution shapes by statistical method of invers problem solution gives the possibility to obtain the relative contribution values of the five main primary nuclei groups. The method is model-independent for a big class of interaction models and can give good results for observation levels not too far from the development maximum and for the selection of showers with fixed sizes and zenith angles not bigger than 30 deg.

3D statistical shape models incorporating 3D random forest regression voting for robust CT liver segmentation

NASA Astrophysics Data System (ADS)

Norajitra, Tobias; Meinzer, Hans-Peter; Maier-Hein, Klaus H.

2015-03-01

During image segmentation, 3D Statistical Shape Models (SSM) usually conduct a limited search for target landmarks within one-dimensional search profiles perpendicular to the model surface. In addition, landmark appearance is modeled only locally based on linear profiles and weak learners, altogether leading to segmentation errors from landmark ambiguities and limited search coverage. We present a new method for 3D SSM segmentation based on 3D Random Forest Regression Voting. For each surface landmark, a Random Regression Forest is trained that learns a 3D spatial displacement function between the according reference landmark and a set of surrounding sample points, based on an infinite set of non-local randomized 3D Haar-like features. Landmark search is then conducted omni-directionally within 3D search spaces, where voxelwise forest predictions on landmark position contribute to a common voting map which reflects the overall position estimate. Segmentation experiments were conducted on a set of 45 CT volumes of the human liver, of which 40 images were randomly chosen for training and 5 for testing. Without parameter optimization, using a simple candidate selection and a single resolution approach, excellent results were achieved, while faster convergence and better concavity segmentation were observed, altogether underlining the potential of our approach in terms of increased robustness from distinct landmark detection and from better search coverage.

Thermal Intertias of Main-Belt Asteroids from Wise Thermal Infrared Data

NASA Astrophysics Data System (ADS)

Hanus, Josef; Delbo', Marco; Durech, Josef; Alí-Lagoa, Victor

2014-11-01

By means of a modified thermophysical model (TPM) that takes into account asteroid shape and pole uncertainties, we analyze the thermal infrared data acquired by the NASA's Wide-field Infrared Survey Explorer (WISE) of about 300 asteroids with derived convex shape models. We adopt convex shape models from the DAMIT database (Durech et al., 2010, A&A 513, A46) and present new determinations based on optical disk-integrated photometry and the lightcurve inversion method (Kaasalainen & Torppa, 2001, Icarus 153, 37). This work more than double the number of asteroids with determined thermophysical properties. We also discuss cases in which shape uncertainties prevent the determination of reliable thermophysical properties. This is per-se a novel result, as the effect of shape has been often neglected in thermophysical modeling of asteroids.We also present the main results of the statistical study of derived thermophysical parameters within the whole population of MBAs and within few asteroid families. The thermal inertia increases with decreasing size, but a large range of thermal inertia values is observed within the similar size ranges between 10-100 km. Surprisingly, we derive low (<20J m^{-2} s^{-1/2} K^{-1}) thermal inertia values for several asteroids with sizes D>10 km, indicating a very fine and mature regolith on these small bodies. The work of JH and MD was carried under the contract 11-BS56-008 (SHOCKS) of the French Agence National de la Recherche (ANR), and JD has been supported by the grant GACR P209/10/0537 of the Czech Science Foundation.

Shape regularized active contour based on dynamic programming for anatomical structure segmentation

NASA Astrophysics Data System (ADS)

Yu, Tianli; Luo, Jiebo; Singhal, Amit; Ahuja, Narendra

2005-04-01

We present a method to incorporate nonlinear shape prior constraints into segmenting different anatomical structures in medical images. Kernel space density estimation (KSDE) is used to derive the nonlinear shape statistics and enable building a single model for a class of objects with nonlinearly varying shapes. The object contour is coerced by image-based energy into the correct shape sub-distribution (e.g., left or right lung), without the need for model selection. In contrast to an earlier algorithm that uses a local gradient-descent search (susceptible to local minima), we propose an algorithm that iterates between dynamic programming (DP) and shape regularization. DP is capable of finding an optimal contour in the search space that maximizes a cost function related to the difference between the interior and exterior of the object. To enforce the nonlinear shape prior, we propose two shape regularization methods, global and local regularization. Global regularization is applied after each DP search to move the entire shape vector in the shape space in a gradient descent fashion to the position of probable shapes learned from training. The regularized shape is used as the starting shape for the next iteration. Local regularization is accomplished through modifying the search space of the DP. The modified search space only allows a certain amount of deformation of the local shape from the starting shape. Both regularization methods ensure the consistency between the resulted shape with the training shapes, while still preserving DP"s ability to search over a large range and avoid local minima. Our algorithm was applied to two different segmentation tasks for radiographic images: lung field and clavicle segmentation. Both applications have shown that our method is effective and versatile in segmenting various anatomical structures under prior shape constraints; and it is robust to noise and local minima caused by clutter (e.g., blood vessels) and other similar structures (e.g., ribs). We believe that the proposed algorithm represents a major step in the paradigm shift to object segmentation under nonlinear shape constraints.

Yarkovsky effect and V-shapes: New method to compute family ages

NASA Astrophysics Data System (ADS)

Spoto, F.; Milani, A.; Cellino, A.; Knezevic, Z.; Novakovic, B.; Paolicchi, P.

2014-07-01

The computation of family ages is a high-priority goal. As a matter of principle, it can be achieved by using V-shape plots for the families old enough to have the Yarkovsky effect dominating the spread of the proper a and large enough for a statistically significant analysis of the shape. By performing an asteroid family classification with a very enlarged dataset, the results are not just ''more families'', but there are interesting qualitative changes. These are due to the large-number statistics, but also to the larger fraction of smaller objects contained in recently numbered asteroids. We are convinced that our method is effective in adding many smaller asteroids to the core families. As a result, we have a large number of families with very well defined V-shapes, thus with a good possibility of age estimation. We have developed our method to compute ages, which we believe is better than those used previously because it is more objective. Since there are no models for error in absolute magnitude H and for albedo, we have also developed a model of the error in the inverse of the diameter and then we have performed a weighted least-squares fit. We report at least 5/6 examples of dynamical families for which the computation of the V-shape is possible. These examples show the presence of different internal structure of the families, e.g., in the dynamical family of (4) Vesta, we have found two collisional families. The main problem in estimating the ages is the calibration. The difficulty in the Yarkovsky calibration, due to the need to extrapolate from near-Earth asteroids (NEAs) with measured da/dt to main-belt asteroids, is in most cases the main limitation to the accuracy of the age estimation. We obtain an age estimation by scaling the results for the NEA for which there is the best Yarkovsky effect determination, namely (101955) Bennu.

ECG Identification System Using Neural Network with Global and Local Features

ERIC Educational Resources Information Center

Tseng, Kuo-Kun; Lee, Dachao; Chen, Charles

2016-01-01

This paper proposes a human identification system via extracted electrocardiogram (ECG) signals. Two hierarchical classification structures based on global shape feature and local statistical feature is used to extract ECG signals. Global shape feature represents the outline information of ECG signals and local statistical feature extracts the…

Statistical shape model-based reconstruction of a scaled, patient-specific surface model of the pelvis from a single standard AP x-ray radiograph

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

Zheng Guoyan

2010-04-15

Purpose: The aim of this article is to investigate the feasibility of using a statistical shape model (SSM)-based reconstruction technique to derive a scaled, patient-specific surface model of the pelvis from a single standard anteroposterior (AP) x-ray radiograph and the feasibility of estimating the scale of the reconstructed surface model by performing a surface-based 3D/3D matching. Methods: Data sets of 14 pelvises (one plastic bone, 12 cadavers, and one patient) were used to validate the single-image based reconstruction technique. This reconstruction technique is based on a hybrid 2D/3D deformable registration process combining a landmark-to-ray registration with a SSM-based 2D/3D reconstruction.more » The landmark-to-ray registration was used to find an initial scale and an initial rigid transformation between the x-ray image and the SSM. The estimated scale and rigid transformation were used to initialize the SSM-based 2D/3D reconstruction. The optimal reconstruction was then achieved in three stages by iteratively matching the projections of the apparent contours extracted from a 3D model derived from the SSM to the image contours extracted from the x-ray radiograph: Iterative affine registration, statistical instantiation, and iterative regularized shape deformation. The image contours are first detected by using a semiautomatic segmentation tool based on the Livewire algorithm and then approximated by a set of sparse dominant points that are adaptively sampled from the detected contours. The unknown scales of the reconstructed models were estimated by performing a surface-based 3D/3D matching between the reconstructed models and the associated ground truth models that were derived from a CT-based reconstruction method. Such a matching also allowed for computing the errors between the reconstructed models and the associated ground truth models. Results: The technique could reconstruct the surface models of all 14 pelvises directly from the landmark-based initialization. Depending on the surface-based matching techniques, the reconstruction errors were slightly different. When a surface-based iterative affine registration was used, an average reconstruction error of 1.6 mm was observed. This error was increased to 1.9 mm, when a surface-based iterative scaled rigid registration was used. Conclusions: It is feasible to reconstruct a scaled, patient-specific surface model of the pelvis from single standard AP x-ray radiograph using the present approach. The unknown scale of the reconstructed model can be estimated by performing a surface-based 3D/3D matching.« less

Universality of fragment shapes.

PubMed

Domokos, Gábor; Kun, Ferenc; Sipos, András Árpád; Szabó, Tímea

2015-03-16

The shape of fragments generated by the breakup of solids is central to a wide variety of problems ranging from the geomorphic evolution of boulders to the accumulation of space debris orbiting Earth. Although the statistics of the mass of fragments has been found to show a universal scaling behavior, the comprehensive characterization of fragment shapes still remained a fundamental challenge. We performed a thorough experimental study of the problem fragmenting various types of materials by slowly proceeding weathering and by rapid breakup due to explosion and hammering. We demonstrate that the shape of fragments obeys an astonishing universality having the same generic evolution with the fragment size irrespective of materials details and loading conditions. There exists a cutoff size below which fragments have an isotropic shape, however, as the size increases an exponential convergence is obtained to a unique elongated form. We show that a discrete stochastic model of fragmentation reproduces both the size and shape of fragments tuning only a single parameter which strengthens the general validity of the scaling laws. The dependence of the probability of the crack plan orientation on the linear extension of fragments proved to be essential for the shape selection mechanism.

Universality of fragment shapes

PubMed Central

Domokos, Gábor; Kun, Ferenc; Sipos, András Árpád; Szabó, Tímea

2015-01-01

The shape of fragments generated by the breakup of solids is central to a wide variety of problems ranging from the geomorphic evolution of boulders to the accumulation of space debris orbiting Earth. Although the statistics of the mass of fragments has been found to show a universal scaling behavior, the comprehensive characterization of fragment shapes still remained a fundamental challenge. We performed a thorough experimental study of the problem fragmenting various types of materials by slowly proceeding weathering and by rapid breakup due to explosion and hammering. We demonstrate that the shape of fragments obeys an astonishing universality having the same generic evolution with the fragment size irrespective of materials details and loading conditions. There exists a cutoff size below which fragments have an isotropic shape, however, as the size increases an exponential convergence is obtained to a unique elongated form. We show that a discrete stochastic model of fragmentation reproduces both the size and shape of fragments tuning only a single parameter which strengthens the general validity of the scaling laws. The dependence of the probability of the crack plan orientation on the linear extension of fragments proved to be essential for the shape selection mechanism. PMID:25772300

Statistical Modeling of Extreme Values and Evidence of Presence of Dragon King (DK) in Solar Wind

NASA Astrophysics Data System (ADS)

Gomes, T.; Ramos, F.; Rempel, E. L.; Silva, S.; C-L Chian, A.

2017-12-01

The solar wind constitutes a nonlinear dynamical system, presenting intermittent turbulence, multifractality and chaotic dynamics. One characteristic shared by many such complex systems is the presence of extreme events, that play an important role in several Geophysical phenomena and their statistical characterization is a problem of great practical relevance. This work investigates the presence of extreme events in time series of the modulus of the interplanetary magnetic field measured by Cluster spacecraft on February 2, 2002. One of the main results is that the solar wind near the Earth's bow shock can be modeled by the Generalized Pareto (GP) and Generalized Extreme Values (GEV) distributions. Both models present a statistically significant positive shape parameter which implyies a heavy tail in the probability distribution functions and an unbounded growth in return values as return periods become too long. There is evidence that current sheets are the main responsible for positive values of the shape parameter. It is also shown that magnetic reconnection at the interface between two interplanetary magnetic flux ropes in the solar wind can be considered as Dragon Kings (DK), a class of extreme events whose formation mechanisms are fundamentally different from others. As long as magnetic reconnection can be classified as a Dragon King, there is the possibility of its identification and even its prediction. Dragon kings had previously been identified in time series of financial crashes, nuclear power generation accidents, stock market and so on. It is believed that they are associated with the occurrence of extreme events in dynamical systems at phase transition, bifurcation, crises or tipping points.

Automatic identification of bullet signatures based on consecutive matching striae (CMS) criteria.

PubMed

Chu, Wei; Thompson, Robert M; Song, John; Vorburger, Theodore V

2013-09-10

The consecutive matching striae (CMS) numeric criteria for firearm and toolmark identifications have been widely accepted by forensic examiners, although there have been questions concerning its observer subjectivity and limited statistical support. In this paper, based on signal processing and extraction, a model for the automatic and objective counting of CMS is proposed. The position and shape information of the striae on the bullet land is represented by a feature profile, which is used for determining the CMS number automatically. Rapid counting of CMS number provides a basis for ballistics correlations with large databases and further statistical and probability analysis. Experimental results in this report using bullets fired from ten consecutively manufactured barrels support this developed model. Published by Elsevier Ireland Ltd.

Modelling nitrate pollution pressure using a multivariate statistical approach: the case of Kinshasa groundwater body, Democratic Republic of Congo

NASA Astrophysics Data System (ADS)

Mfumu Kihumba, Antoine; Ndembo Longo, Jean; Vanclooster, Marnik

2016-03-01

A multivariate statistical modelling approach was applied to explain the anthropogenic pressure of nitrate pollution on the Kinshasa groundwater body (Democratic Republic of Congo). Multiple regression and regression tree models were compared and used to identify major environmental factors that control the groundwater nitrate concentration in this region. The analyses were made in terms of physical attributes related to the topography, land use, geology and hydrogeology in the capture zone of different groundwater sampling stations. For the nitrate data, groundwater datasets from two different surveys were used. The statistical models identified the topography, the residential area, the service land (cemetery), and the surface-water land-use classes as major factors explaining nitrate occurrence in the groundwater. Also, groundwater nitrate pollution depends not on one single factor but on the combined influence of factors representing nitrogen loading sources and aquifer susceptibility characteristics. The groundwater nitrate pressure was better predicted with the regression tree model than with the multiple regression model. Furthermore, the results elucidated the sensitivity of the model performance towards the method of delineation of the capture zones. For pollution modelling at the monitoring points, therefore, it is better to identify capture-zone shapes based on a conceptual hydrogeological model rather than to adopt arbitrary circular capture zones.

Probabilistic description of ice-supersaturated layers in low resolution profiles of relative humidity N. C. Dickson, K. Gierens, H. L. Rogers, R. L. Jones

NASA Astrophysics Data System (ADS)

Dickson, N.

2009-12-01

The global observation, assimilation and prediction in numerical models of ice super-saturated (ISS) regions (ISSR) are crucial if the climate impact of aircraft condensations trails (contrails) is to be fully understood, and if, for example, contrail formation is to be avoided through aircraft operational measures. A robust assessment of the global distribution of ISSR will further this debate, and ISS event occurrence, frequency and spatial scales have recently attracted significant attention. The mean horizontal size of ISSR is 150 km (±250km) although 12-14% of ISS events occur on horizontal scales of less than 5km. The average vertical thickness of ISS layers is 600-800m (±575m) but layers ranging from 25m to 3000m have been observed, with up to one third of ISS layers thought to be less than 100m deep. Given their small scales compared to typical atmospheric model grid sizes, statistical representations of the spatial scales of ISSR are required, in both horizontal and vertical dimensions, if global occurrence of ISSR is to be adequately represented in climate models. This paper uses radiosonde launches made by the UK Meteorological Office, from the British Isles, Gibraltar, St. Helena and the Falkland Islands between January 2002 and December 2006, to investigate the probabilistic occurrence of ISSR. Specifically each radiosonde profile is divided into 50 and 100 hPa pressure layers, to emulate the coarse vertical resolution of some atmospheric models. Then the high resolution observations contained within each thick pressure layer are used to calculate an average relative humidity and an ISS fraction for each individual thick pressure layer. These relative humidity pressure layer descriptions are then linked through a probability function to produce an s-shaped curve describing the ISS fraction in any average relative humidity pressure layer. An empirical investigation has shown that this one curve is statistically valid for mid-latitude locations, irrespective of season and altitude, however, pressure layer depth is an important variable. Using this empirical understanding of the s-shaped relationship a mathematical model was developed to represent the ISS fraction within any arbitrary thick pressure layer. Here the statistical distributions of actual high resolution RHi observations in any thick pressure layer, along with an error function, are used to mathematically describe the s-shape. Two models were developed to represent both 50 and 100 hPa pressure layers with each reconstructing their respective s-shapes within 8-10% of the empirical curves. These new models can be used, to represent the small scale structures of ISS events, in modelled data where only low vertical resolution is available. This will be useful in understanding, and improving the global distribution, both observed and forecasted, of ice super-saturation.

Reweighting anthropometric data using a nearest neighbour approach.

PubMed

Kumar, Kannan Anil; Parkinson, Matthew B

2018-07-01

When designing products and environments, detailed data on body size and shape are seldom available for the specific user population. One way to mitigate this issue is to reweight available data such that they provide an accurate estimate of the target population of interest. This is done by assigning a statistical weight to each individual in the reference data, increasing or decreasing their influence on statistical models of the whole. This paper presents a new approach to reweighting these data. Instead of stratified sampling, the proposed method uses a clustering algorithm to identify relationships between the detailed and reference populations using their height, mass, and body mass index (BMI). The newly weighted data are shown to provide more accurate estimates than traditional approaches. The improved accuracy that accompanies this method provides designers with an alternative to data synthesis techniques as they seek appropriate data to guide their design practice.Practitioner Summary: Design practice is best guided by data on body size and shape that accurately represents the target user population. This research presents an alternative to data synthesis (e.g. regression or proportionality constants) for adapting data from one population for use in modelling another.

A flexible spatial scan statistic with a restricted likelihood ratio for detecting disease clusters.

PubMed

Tango, Toshiro; Takahashi, Kunihiko

2012-12-30

Spatial scan statistics are widely used tools for detection of disease clusters. Especially, the circular spatial scan statistic proposed by Kulldorff (1997) has been utilized in a wide variety of epidemiological studies and disease surveillance. However, as it cannot detect noncircular, irregularly shaped clusters, many authors have proposed different spatial scan statistics, including the elliptic version of Kulldorff's scan statistic. The flexible spatial scan statistic proposed by Tango and Takahashi (2005) has also been used for detecting irregularly shaped clusters. However, this method sets a feasible limitation of a maximum of 30 nearest neighbors for searching candidate clusters because of heavy computational load. In this paper, we show a flexible spatial scan statistic implemented with a restricted likelihood ratio proposed by Tango (2008) to (1) eliminate the limitation of 30 nearest neighbors and (2) to have surprisingly much less computational time than the original flexible spatial scan statistic. As a side effect, it is shown to be able to detect clusters with any shape reasonably well as the relative risk of the cluster becomes large via Monte Carlo simulation. We illustrate the proposed spatial scan statistic with data on mortality from cerebrovascular disease in the Tokyo Metropolitan area, Japan. Copyright © 2012 John Wiley & Sons, Ltd.

Ein statistisches Modell zum Einfluß der thermischen Bewegung auf NMR-Festkörperspektren

NASA Astrophysics Data System (ADS)

Ploss, W.; Freude, D.; Pfeifer, H.; Schmiedel, H.

Es wird ein statistisches Modell zum Einfluß der thermischen Bewegung auf die NMR-Linienform vorgestellt, das die Verschmälerung von Festkörper-Spektren bei wachsender Temperatur beschreibt. Das Modell geht von der Annahme aus, daß nach einer Ortsveränderung eines Kerns infolge thermischer Bewegung jede beliebige Kernresonanzfrequenz mit der durch das Festkörperspektrum vorgegebenen Wahrscheinlichkeit angenommen werden kann. Am Beispiel der Festkörper-Gaußlinie wird der Unterschied zu dem bekannten Modell von ANDERSON und WEISS verdeutlicht.Translated AbstractA Statistical Model for the Influence of Thermal Motion on N. M. R. Spectra in SolidsA theory is proposed which allows to describe the narrowing of n. m. r.-line width in the presence of thermal motions of the spins. The model is based on the assumption, that the local resonance frequency of a given spin immediately after the jump is distributed according to the n. m. r.-line shape of the rigid lattice. The difference to the well-known ANDERSON-WEISS-model of spectral narrowing is demonstrated for a gaussian line shape.

A note on statistical analysis of shape through triangulation of landmarks

PubMed Central

Rao, C. Radhakrishna

2000-01-01

In an earlier paper, the author jointly with S. Suryawanshi proposed statistical analysis of shape through triangulation of landmarks on objects. It was observed that the angles of the triangles are invariant to scaling, location, and rotation of objects. No distinction was made between an object and its reflection. The present paper provides the methodology of shape discrimination when reflection is also taken into account and makes suggestions for modifications to be made when some of the landmarks are collinear. PMID:10737780

Erlang circular model motivated by inverse stereographic projection

NASA Astrophysics Data System (ADS)

Pramesti, G.

2018-05-01

The Erlang distribution is a special case of the Gamma distribution with the shape parameter is an integer. This paper proposed a new circular model used inverse stereographic projection. The inverse stereographic projection which is a mapping that projects a random variable from a real line onto a circle can be used in circular statistics to construct a distribution on the circle from real domain. From the circular model, then can be derived the characteristics of the Erlang circular model such as the mean resultant length, mean direction, circular variance and trigonometric moments of the distribution.

Interactive classification and content-based retrieval of tissue images

NASA Astrophysics Data System (ADS)

Aksoy, Selim; Marchisio, Giovanni B.; Tusk, Carsten; Koperski, Krzysztof

2002-11-01

We describe a system for interactive classification and retrieval of microscopic tissue images. Our system models tissues in pixel, region and image levels. Pixel level features are generated using unsupervised clustering of color and texture values. Region level features include shape information and statistics of pixel level feature values. Image level features include statistics and spatial relationships of regions. To reduce the gap between low-level features and high-level expert knowledge, we define the concept of prototype regions. The system learns the prototype regions in an image collection using model-based clustering and density estimation. Different tissue types are modeled using spatial relationships of these regions. Spatial relationships are represented by fuzzy membership functions. The system automatically selects significant relationships from training data and builds models which can also be updated using user relevance feedback. A Bayesian framework is used to classify tissues based on these models. Preliminary experiments show that the spatial relationship models we developed provide a flexible and powerful framework for classification and retrieval of tissue images.

Terahertz-dependent identification of simulated hole shapes in oil-gas reservoirs

NASA Astrophysics Data System (ADS)

Bao, Ri-Ma; Zhan, Hong-Lei; Miao, Xin-Yang; Zhao, Kun; Feng, Cheng-Jing; Dong, Chen; Li, Yi-Zhang; Xiao, Li-Zhi

2016-10-01

Detecting holes in oil-gas reservoirs is vital to the evaluation of reservoir potential. The main objective of this study is to demonstrate the feasibility of identifying general micro-hole shapes, including triangular, circular, and square shapes, in oil-gas reservoirs by adopting terahertz time-domain spectroscopy (THz-TDS). We evaluate the THz absorption responses of punched silicon (Si) wafers having micro-holes with sizes of 20 μm-500 μm. Principal component analysis (PCA) is used to establish a model between THz absorbance and hole shapes. The positions of samples in three-dimensional spaces for three principal components are used to determine the differences among diverse hole shapes and the homogeneity of similar shapes. In addition, a new Si wafer with the unknown hole shapes, including triangular, circular, and square, can be qualitatively identified by combining THz-TDS and PCA. Therefore, the combination of THz-TDS with mathematical statistical methods can serve as an effective approach to the rapid identification of micro-hole shapes in oil-gas reservoirs. Project supported by the National Natural Science Foundation of China (Grant No. 61405259), the National Basic Research Program of China (Grant No. 2014CB744302), and the Specially Founded Program on National Key Scientific Instruments and Equipment Development, China (Grant No. 2012YQ140005).

Uniting statistical and individual-based approaches for animal movement modelling.

PubMed

Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

2014-01-01

The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems.

Uniting Statistical and Individual-Based Approaches for Animal Movement Modelling

PubMed Central

Latombe, Guillaume; Parrott, Lael; Basille, Mathieu; Fortin, Daniel

2014-01-01

The dynamic nature of their internal states and the environment directly shape animals' spatial behaviours and give rise to emergent properties at broader scales in natural systems. However, integrating these dynamic features into habitat selection studies remains challenging, due to practically impossible field work to access internal states and the inability of current statistical models to produce dynamic outputs. To address these issues, we developed a robust method, which combines statistical and individual-based modelling. Using a statistical technique for forward modelling of the IBM has the advantage of being faster for parameterization than a pure inverse modelling technique and allows for robust selection of parameters. Using GPS locations from caribou monitored in Québec, caribou movements were modelled based on generative mechanisms accounting for dynamic variables at a low level of emergence. These variables were accessed by replicating real individuals' movements in parallel sub-models, and movement parameters were then empirically parameterized using Step Selection Functions. The final IBM model was validated using both k-fold cross-validation and emergent patterns validation and was tested for two different scenarios, with varying hardwood encroachment. Our results highlighted a functional response in habitat selection, which suggests that our method was able to capture the complexity of the natural system, and adequately provided projections on future possible states of the system in response to different management plans. This is especially relevant for testing the long-term impact of scenarios corresponding to environmental configurations that have yet to be observed in real systems. PMID:24979047

Derivation of the Statistical Distribution of the Mass Peak Centroids of Mass Spectrometers Employing Analog-to-Digital Converters and Electron Multipliers

DOE PAGES

Ipsen, Andreas

2017-02-03

Here, the mass peak centroid is a quantity that is at the core of mass spectrometry (MS). However, despite its central status in the field, models of its statistical distribution are often chosen quite arbitrarily and without attempts at establishing a proper theoretical justification for their use. Recent work has demonstrated that for mass spectrometers employing analog-to-digital converters (ADCs) and electron multipliers, the statistical distribution of the mass peak intensity can be described via a relatively simple model derived essentially from first principles. Building on this result, the following article derives the corresponding statistical distribution for the mass peak centroidsmore » of such instruments. It is found that for increasing signal strength, the centroid distribution converges to a Gaussian distribution whose mean and variance are determined by physically meaningful parameters and which in turn determine bias and variability of the m/z measurements of the instrument. Through the introduction of the concept of “pulse-peak correlation”, the model also elucidates the complicated relationship between the shape of the voltage pulses produced by the preamplifier and the mean and variance of the centroid distribution. The predictions of the model are validated with empirical data and with Monte Carlo simulations.« less

Derivation of the Statistical Distribution of the Mass Peak Centroids of Mass Spectrometers Employing Analog-to-Digital Converters and Electron Multipliers

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

Ipsen, Andreas

Here, the mass peak centroid is a quantity that is at the core of mass spectrometry (MS). However, despite its central status in the field, models of its statistical distribution are often chosen quite arbitrarily and without attempts at establishing a proper theoretical justification for their use. Recent work has demonstrated that for mass spectrometers employing analog-to-digital converters (ADCs) and electron multipliers, the statistical distribution of the mass peak intensity can be described via a relatively simple model derived essentially from first principles. Building on this result, the following article derives the corresponding statistical distribution for the mass peak centroidsmore » of such instruments. It is found that for increasing signal strength, the centroid distribution converges to a Gaussian distribution whose mean and variance are determined by physically meaningful parameters and which in turn determine bias and variability of the m/z measurements of the instrument. Through the introduction of the concept of “pulse-peak correlation”, the model also elucidates the complicated relationship between the shape of the voltage pulses produced by the preamplifier and the mean and variance of the centroid distribution. The predictions of the model are validated with empirical data and with Monte Carlo simulations.« less

Occupation times and ergodicity breaking in biased continuous time random walks

NASA Astrophysics Data System (ADS)

Bel, Golan; Barkai, Eli

2005-12-01

Continuous time random walk (CTRW) models are widely used to model diffusion in condensed matter. There are two classes of such models, distinguished by the convergence or divergence of the mean waiting time. Systems with finite average sojourn time are ergodic and thus Boltzmann-Gibbs statistics can be applied. We investigate the statistical properties of CTRW models with infinite average sojourn time; in particular, the occupation time probability density function is obtained. It is shown that in the non-ergodic phase the distribution of the occupation time of the particle on a given lattice point exhibits bimodal U or trimodal W shape, related to the arcsine law. The key points are as follows. (a) In a CTRW with finite or infinite mean waiting time, the distribution of the number of visits on a lattice point is determined by the probability that a member of an ensemble of particles in equilibrium occupies the lattice point. (b) The asymmetry parameter of the probability distribution function of occupation times is related to the Boltzmann probability and to the partition function. (c) The ensemble average is given by Boltzmann-Gibbs statistics for either finite or infinite mean sojourn time, when detailed balance conditions hold. (d) A non-ergodic generalization of the Boltzmann-Gibbs statistical mechanics for systems with infinite mean sojourn time is found.

Design Oriented Structural Modeling for Airplane Conceptual Design Optimization

NASA Technical Reports Server (NTRS)

Livne, Eli

1999-01-01

The main goal for research conducted with the support of this grant was to develop design oriented structural optimization methods for the conceptual design of airplanes. Traditionally in conceptual design airframe weight is estimated based on statistical equations developed over years of fitting airplane weight data in data bases of similar existing air- planes. Utilization of such regression equations for the design of new airplanes can be justified only if the new air-planes use structural technology similar to the technology on the airplanes in those weight data bases. If any new structural technology is to be pursued or any new unconventional configurations designed the statistical weight equations cannot be used. In such cases any structural weight estimation must be based on rigorous "physics based" structural analysis and optimization of the airframes under consideration. Work under this grant progressed to explore airframe design-oriented structural optimization techniques along two lines of research: methods based on "fast" design oriented finite element technology and methods based on equivalent plate / equivalent shell models of airframes, in which the vehicle is modelled as an assembly of plate and shell components, each simulating a lifting surface or nacelle / fuselage pieces. Since response to changes in geometry are essential in conceptual design of airplanes, as well as the capability to optimize the shape itself, research supported by this grant sought to develop efficient techniques for parametrization of airplane shape and sensitivity analysis with respect to shape design variables. Towards the end of the grant period a prototype automated structural analysis code designed to work with the NASA Aircraft Synthesis conceptual design code ACS= was delivered to NASA Ames.

Intrinsic alignments of galaxies in the MassiveBlack-II simulation: Analysis of two-point statistics

DOE PAGES

Tenneti, Ananth; Singh, Sukhdeep; Mandelbaum, Rachel; ...

2015-03-11

The intrinsic alignment of galaxies with the large-scale density field in an important astrophysical contaminant in upcoming weak lensing surveys. We present detailed measurements of the galaxy intrinsic alignments and associated ellipticity-direction (ED) and projected shape (w g₊) correlation functions for galaxies in the cosmological hydrodynamic MassiveBlack-II (MB-II) simulation. We carefully assess the effects on galaxy shapes, misalignment of the stellar component with the dark matter shape and two-point statistics of iterative weighted (by mass and luminosity) definitions of the (reduced and unreduced) inertia tensor. We find that iterative procedures must be adopted for a reliable measurement of the reducedmore » tensor but that luminosity versus mass weighting has only negligible effects. Both ED and w g₊ correlations increase in amplitude with subhalo mass (in the range of 10¹⁰ – 6.0 X 10¹⁴h⁻¹ M ⊙), with a weak redshift dependence (from z = 1 to z = 0.06) at fixed mass. At z ~ 0.3, we predict a w g₊ that is in reasonable agreement with SDSS LRG measurements and that decreases in amplitude by a factor of ~ 5–18 for galaxies in the LSST survey. We also compared the intrinsic alignment of centrals and satellites, with clear detection of satellite radial alignments within the host halos. Finally, we show that w g₊ (using subhalos as tracers of density and w δ (using dark matter density) predictions from the simulations agree with that of non-linear alignment models (NLA) at scales where the 2-halo term dominates in the correlations (and tabulate associated NLA fitting parameters). The 1-halo term induces a scale dependent bias at small scales which is not modeled in the NLA model.« less

Intrinsic alignments of galaxies in the MassiveBlack-II simulation: analysis of two-point statistics

NASA Astrophysics Data System (ADS)

Tenneti, Ananth; Singh, Sukhdeep; Mandelbaum, Rachel; di Matteo, Tiziana; Feng, Yu; Khandai, Nishikanta

2015-04-01

The intrinsic alignment of galaxies with the large-scale density field is an important astrophysical contaminant in upcoming weak lensing surveys. We present detailed measurements of the galaxy intrinsic alignments and associated ellipticity-direction (ED) and projected shape (wg+) correlation functions for galaxies in the cosmological hydrodynamic MassiveBlack-II simulation. We carefully assess the effects on galaxy shapes, misalignment of the stellar component with the dark matter shape and two-point statistics of iterative weighted (by mass and luminosity) definitions of the (reduced and unreduced) inertia tensor. We find that iterative procedures must be adopted for a reliable measurement of the reduced tensor but that luminosity versus mass weighting has only negligible effects. Both ED and wg+ correlations increase in amplitude with subhalo mass (in the range of 1010-6.0 × 1014 h-1 M⊙), with a weak redshift dependence (from z = 1 to 0.06) at fixed mass. At z ˜ 0.3, we predict a wg+ that is in reasonable agreement with Sloan Digital Sky Survey luminous red galaxy measurements and that decreases in amplitude by a factor of ˜5-18 for galaxies in the Large Synoptic Survey Telescope survey. We also compared the intrinsic alignments of centrals and satellites, with clear detection of satellite radial alignments within their host haloes. Finally, we show that wg+ (using subhaloes as tracers of density) and wδ+ (using dark matter density) predictions from the simulations agree with that of non-linear alignment (NLA) models at scales where the two-halo term dominates in the correlations (and tabulate associated NLA fitting parameters). The one-halo term induces a scale-dependent bias at small scales which is not modelled in the NLA model.

A statistical human rib cage geometry model accounting for variations by age, sex, stature and body mass index.

PubMed

Shi, Xiangnan; Cao, Libo; Reed, Matthew P; Rupp, Jonathan D; Hoff, Carrie N; Hu, Jingwen

2014-07-18

In this study, we developed a statistical rib cage geometry model accounting for variations by age, sex, stature and body mass index (BMI). Thorax CT scans were obtained from 89 subjects approximately evenly distributed among 8 age groups and both sexes. Threshold-based CT image segmentation was performed to extract the rib geometries, and a total of 464 landmarks on the left side of each subject׳s ribcage were collected to describe the size and shape of the rib cage as well as the cross-sectional geometry of each rib. Principal component analysis and multivariate regression analysis were conducted to predict rib cage geometry as a function of age, sex, stature, and BMI, all of which showed strong effects on rib cage geometry. Except for BMI, all parameters also showed significant effects on rib cross-sectional area using a linear mixed model. This statistical rib cage geometry model can serve as a geometric basis for developing a parametric human thorax finite element model for quantifying effects from different human attributes on thoracic injury risks. Copyright © 2014 Elsevier Ltd. All rights reserved.

Gap Shape Classification using Landscape Indices and Multivariate Statistics

PubMed Central

Wu, Chih-Da; Cheng, Chi-Chuan; Chang, Che-Chang; Lin, Chinsu; Chang, Kun-Cheng; Chuang, Yung-Chung

2016-01-01

This study proposed a novel methodology to classify the shape of gaps using landscape indices and multivariate statistics. Patch-level indices were used to collect the qualified shape and spatial configuration characteristics for canopy gaps in the Lienhuachih Experimental Forest in Taiwan in 1998 and 2002. Non-hierarchical cluster analysis was used to assess the optimal number of gap clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy gap classification. The gaps for the two periods were optimally classified into three categories. In general, gap type 1 had a more complex shape, gap type 2 was more elongated and gap type 3 had the largest gaps that were more regular in shape. The results were evaluated using Wilks’ lambda as satisfactory (p < 0.001). The agreement rate of confusion matrices exceeded 96%. Differences in gap characteristics between the classified gap types that were determined using a one-way ANOVA showed a statistical significance in all patch indices (p = 0.00), except for the Euclidean nearest neighbor distance (ENN) in 2002. Taken together, these results demonstrated the feasibility and applicability of the proposed methodology to classify the shape of a gap. PMID:27901127

Gap Shape Classification using Landscape Indices and Multivariate Statistics.

PubMed

Wu, Chih-Da; Cheng, Chi-Chuan; Chang, Che-Chang; Lin, Chinsu; Chang, Kun-Cheng; Chuang, Yung-Chung

2016-11-30

This study proposed a novel methodology to classify the shape of gaps using landscape indices and multivariate statistics. Patch-level indices were used to collect the qualified shape and spatial configuration characteristics for canopy gaps in the Lienhuachih Experimental Forest in Taiwan in 1998 and 2002. Non-hierarchical cluster analysis was used to assess the optimal number of gap clusters and canonical discriminant analysis was used to generate the discriminant functions for canopy gap classification. The gaps for the two periods were optimally classified into three categories. In general, gap type 1 had a more complex shape, gap type 2 was more elongated and gap type 3 had the largest gaps that were more regular in shape. The results were evaluated using Wilks' lambda as satisfactory (p < 0.001). The agreement rate of confusion matrices exceeded 96%. Differences in gap characteristics between the classified gap types that were determined using a one-way ANOVA showed a statistical significance in all patch indices (p = 0.00), except for the Euclidean nearest neighbor distance (ENN) in 2002. Taken together, these results demonstrated the feasibility and applicability of the proposed methodology to classify the shape of a gap.

Shape Analysis of the Peripapillary RPE Layer in Papilledema and Ischemic Optic Neuropathy

PubMed Central

Kupersmith, Mark J.; Rohlf, F. James

2011-01-01

Purpose. Geometric morphometrics (GM) was used to analyze the shape of the peripapillary retinal pigment epithelium–Bruch's membrane (RPE/BM) layer imaged on the SD-OCT 5-line raster in normal subjects and in patients with papilledema and ischemic optic neuropathy. Methods. Three groups of subjects were compared: 30 normals, 20 with anterior ischemic optic neuropathy (AION), and 25 with papilledema and intracranial hypertension. Twenty equidistant semilandmarks were digitized on OCT images of the RPE/BM layer spanning 2500 μm on each side of the neural canal opening (NCO). The data were analyzed using standard GM techniques, including a generalized least-squares Procrustes superimposition, principal component analysis, thin-plate spline (to visualize deformations), and permutation statistical analysis to evaluate differences in shape variables. Results. The RPE/BM layer in normals and AION have a characteristic V shape pointing away from the vitreous; the RPE/BM layer in papilledema has an inverted U shape, skewed nasally inward toward the vitreous. The differences were statistically significant. There was no significant difference in shapes between normals and AION. Pre- and posttreatment OCTs, in select cases of papilledema, showed that the inverted U-shaped RPE/BM moved posteriorly into a normal V shape as the papilledema resolved with weight loss or shunting. Conclusions. The shape difference in papilledema, absent in AION, cannot be explained by disc edema alone. The difference is a consequence of both the translaminar pressure gradient and the material properties of the peripapillary sclera. GM offers a novel way of statistically assessing shape differences of the peripapillary optic nerve head. PMID:21896851

3D active shape models of human brain structures: application to patient-specific mesh generation

NASA Astrophysics Data System (ADS)

Ravikumar, Nishant; Castro-Mateos, Isaac; Pozo, Jose M.; Frangi, Alejandro F.; Taylor, Zeike A.

2015-03-01

The use of biomechanics-based numerical simulations has attracted growing interest in recent years for computer-aided diagnosis and treatment planning. With this in mind, a method for automatic mesh generation of brain structures of interest, using statistical models of shape (SSM) and appearance (SAM), for personalised computational modelling is presented. SSMs are constructed as point distribution models (PDMs) while SAMs are trained using intensity profiles sampled from a training set of T1-weighted magnetic resonance images. The brain structures of interest are, the cortical surface (cerebrum, cerebellum & brainstem), lateral ventricles and falx-cerebri membrane. Two methods for establishing correspondences across the training set of shapes are investigated and compared (based on SSM quality): the Coherent Point Drift (CPD) point-set registration method and B-spline mesh-to-mesh registration method. The MNI-305 (Montreal Neurological Institute) average brain atlas is used to generate the template mesh, which is deformed and registered to each training case, to establish correspondence over the training set of shapes. 18 healthy patients' T1-weightedMRimages form the training set used to generate the SSM and SAM. Both model-training and model-fitting are performed over multiple brain structures simultaneously. Compactness and generalisation errors of the BSpline-SSM and CPD-SSM are evaluated and used to quantitatively compare the SSMs. Leave-one-out cross validation is used to evaluate SSM quality in terms of these measures. The mesh-based SSM is found to generalise better and is more compact, relative to the CPD-based SSM. Quality of the best-fit model instance from the trained SSMs, to test cases are evaluated using the Hausdorff distance (HD) and mean absolute surface distance (MASD) metrics.

Seeing number using texture: How summary statistics account for reductions in perceived numerosity in the visual periphery.

PubMed

Balas, Benjamin

2016-11-01

Peripheral visual perception is characterized by reduced information about appearance due to constraints on how image structure is represented. Visual crowding is a consequence of excessive integration in the visual periphery. Basic phenomenology of visual crowding and other tasks have been successfully accounted for by a summary-statistic model of pooling, suggesting that texture-like processing is useful for how information is reduced in peripheral vision. I attempt to extend the scope of this model by examining a property of peripheral vision: reduced perceived numerosity in the periphery. I demonstrate that a summary-statistic model of peripheral appearance accounts for reduced numerosity in peripherally viewed arrays of randomly placed dots, but does not account for observed effects of dot clustering within such arrays. The model thus offers a limited account of how numerosity is perceived in the visual periphery. I also demonstrate that the model predicts that numerosity estimation is sensitive to element shape, which represents a novel prediction regarding the phenomenology of peripheral numerosity perception. Finally, I discuss ways to extend the model to a broader range of behavior and the potential for using the model to make further predictions about how number is perceived in untested scenarios in peripheral vision.

Counting-loss correction for X-ray spectroscopy using unit impulse pulse shaping.

PubMed

Hong, Xu; Zhou, Jianbin; Ni, Shijun; Ma, Yingjie; Yao, Jianfeng; Zhou, Wei; Liu, Yi; Wang, Min

2018-03-01

High-precision measurement of X-ray spectra is affected by the statistical fluctuation of the X-ray beam under low-counting-rate conditions. It is also limited by counting loss resulting from the dead-time of the system and pile-up pulse effects, especially in a high-counting-rate environment. In this paper a detection system based on a FAST-SDD detector and a new kind of unit impulse pulse-shaping method is presented, for counting-loss correction in X-ray spectroscopy. The unit impulse pulse-shaping method is evolved by inverse deviation of the pulse from a reset-type preamplifier and a C-R shaper. It is applied to obtain the true incoming rate of the system based on a general fast-slow channel processing model. The pulses in the fast channel are shaped to unit impulse pulse shape which possesses small width and no undershoot. The counting rate in the fast channel is corrected by evaluating the dead-time of the fast channel before it is used to correct the counting loss in the slow channel.

Preforming of polydioxanone sheets for orbital wall fractures - A technical note.

PubMed

Kruber, Daniel; Hierl, Thomas; Doerfler, Hans-Martin; Huempfner-Hierl, Heike; Krause, Matthias

2018-07-01

Polydioxanone (PDS) sheets are commonly used in the treatment of orbital wall fractures. A potential drawback of PDS is that it may be difficult to adapt to the anatomy of the orbital walls. Therefore a study was conceived to test the feasibility of preforming PDS sheets. PDS sheet material was water-heated and preformed using a template based on a statistical anatomical model. Then the deformed sheet was cooled, stored and compared to the original model to investigate post-deformation changes. PDS sheet material could easily be deformed using a mould. No significant post-cooling shape changes were noticed. PDS sheet material can be preformed into complex geometric shapes. This could be a benefit in the treatment of orbital wall fractures. Copyright © 2018 European Association for Cranio-Maxillo-Facial Surgery. Published by Elsevier Ltd. All rights reserved.

Impact of Early and Late Visual Deprivation on the Structure of the Corpus Callosum: A Study Combining Thickness Profile with Surface Tensor-Based Morphometry.

PubMed

Shi, Jie; Collignon, Olivier; Xu, Liang; Wang, Gang; Kang, Yue; Leporé, Franco; Lao, Yi; Joshi, Anand A; Leporé, Natasha; Wang, Yalin

2015-07-01

Blindness represents a unique model to study how visual experience may shape the development of brain organization. Exploring how the structure of the corpus callosum (CC) reorganizes ensuing visual deprivation is of particular interest due to its important functional implication in vision (e.g., via the splenium of the CC). Moreover, comparing early versus late visually deprived individuals has the potential to unravel the existence of a sensitive period for reshaping the CC structure. Here, we develop a novel framework to capture a complete set of shape differences in the CC between congenitally blind (CB), late blind (LB) and sighted control (SC) groups. The CCs were manually segmented from T1-weighted brain MRI and modeled by 3D tetrahedral meshes. We statistically compared the combination of local area and thickness at each point between subject groups. Differences in area are found using surface tensor-based morphometry; thickness is estimated by tracing the streamlines in the volumetric harmonic field. Group differences were assessed on this combined measure using Hotelling's T(2) test. Interestingly, we observed that the total callosal volume did not differ between the groups. However, our fine-grained analysis reveals significant differences mostly localized around the splenium areas between both blind groups and the sighted group (general effects of blindness) and, importantly, specific dissimilarities between the LB and CB groups, illustrating the existence of a sensitive period for reorganization. The new multivariate statistics also gave better effect sizes for detecting morphometric differences, relative to other statistics. They may boost statistical power for CC morphometric analyses.

IMPACT OF EARLY AND LATE VISUAL DEPRIVATION ON THE STRUCTURE OF THE CORPUS CALLOSUM: A STUDY COMBINING THICKNESS PROFILE WITH SURFACE TENSOR-BASED MORPHOMETRY

PubMed Central

Shi, Jie; Collignon, Olivier; Xu, Liang; Wang, Gang; Kang, Yue; Leporé, Franco; Lao, Yi; Joshi, Anand A.

2015-01-01

Blindness represents a unique model to study how visual experience may shape the development of brain organization. Exploring how the structure of the corpus callosum (CC) reorganizes ensuing visual deprivation is of particular interest due to its important functional implication in vision (e.g. via the splenium of the CC). Moreover, comparing early versus late visually deprived individuals has the potential to unravel the existence of a sensitive period for reshaping the CC structure. Here, we develop a novel framework to capture a complete set of shape differences in the CC between congenitally blind (CB), late blind (LB) and sighted control (SC) groups. The CCs were manually segmented from T1-weighted brain MRI and modeled by 3D tetrahedral meshes. We statistically compared the combination of local area and thickness at each point between subject groups. Differences in area are found using surface tensor-based morphometry; thickness is estimated by tracing the streamlines in the volumetric harmonic field. Group differences were assessed on this combined measure using Hotelling’s T2 test. Interestingly, we observed that the total callosal volume did not differ between the groups. However, our fine-grained analysis reveals significant differences mostly localized around the splenium areas between both blind groups and the sighted group (general effects of blindness) and, importantly, specific dissimilarities between the LB and CB groups, illustrating the existence of a sensitive period for reorganization. The new multivariate statistics also gave better effect sizes for detecting morphometric differences, relative to other statistics. They may boost statistical power for CC morphometric analyses. PMID:25649876

A Parametric Study of Fine-scale Turbulence Mixing Noise

NASA Technical Reports Server (NTRS)

Khavaran, Abbas; Bridges, James; Freund, Jonathan B.

2002-01-01

The present paper is a study of aerodynamic noise spectra from model functions that describe the source. The study is motivated by the need to improve the spectral shape of the MGBK jet noise prediction methodology at high frequency. The predicted spectral shape usually appears less broadband than measurements and faster decaying at high frequency. Theoretical representation of the source is based on Lilley's equation. Numerical simulations of high-speed subsonic jets as well as some recent turbulence measurements reveal a number of interesting statistical properties of turbulence correlation functions that may have a bearing on radiated noise. These studies indicate that an exponential spatial function may be a more appropriate representation of a two-point correlation compared to its Gaussian counterpart. The effect of source non-compactness on spectral shape is discussed. It is shown that source non-compactness could well be the differentiating factor between the Gaussian and exponential model functions. In particular, the fall-off of the noise spectra at high frequency is studied and it is shown that a non-compact source with an exponential model function results in a broader spectrum and better agreement with data. An alternate source model that represents the source as a covariance of the convective derivative of fine-scale turbulence kinetic energy is also examined.

On joint subtree distributions under two evolutionary models.

PubMed

Wu, Taoyang; Choi, Kwok Pui

2016-04-01

In population and evolutionary biology, hypotheses about micro-evolutionary and macro-evolutionary processes are commonly tested by comparing the shape indices of empirical evolutionary trees with those predicted by neutral models. A key ingredient in this approach is the ability to compute and quantify distributions of various tree shape indices under random models of interest. As a step to meet this challenge, in this paper we investigate the joint distribution of cherries and pitchforks (that is, subtrees with two and three leaves) under two widely used null models: the Yule-Harding-Kingman (YHK) model and the proportional to distinguishable arrangements (PDA) model. Based on two novel recursive formulae, we propose a dynamic approach to numerically compute the exact joint distribution (and hence the marginal distributions) for trees of any size. We also obtained insights into the statistical properties of trees generated under these two models, including a constant correlation between the cherry and the pitchfork distributions under the YHK model, and the log-concavity and unimodality of the cherry distributions under both models. In addition, we show that there exists a unique change point for the cherry distributions between these two models. Copyright © 2015 Elsevier Inc. All rights reserved.

Nonlinear Hebbian Learning as a Unifying Principle in Receptive Field Formation.

PubMed

Brito, Carlos S N; Gerstner, Wulfram

2016-09-01

The development of sensory receptive fields has been modeled in the past by a variety of models including normative models such as sparse coding or independent component analysis and bottom-up models such as spike-timing dependent plasticity or the Bienenstock-Cooper-Munro model of synaptic plasticity. Here we show that the above variety of approaches can all be unified into a single common principle, namely nonlinear Hebbian learning. When nonlinear Hebbian learning is applied to natural images, receptive field shapes were strongly constrained by the input statistics and preprocessing, but exhibited only modest variation across different choices of nonlinearities in neuron models or synaptic plasticity rules. Neither overcompleteness nor sparse network activity are necessary for the development of localized receptive fields. The analysis of alternative sensory modalities such as auditory models or V2 development lead to the same conclusions. In all examples, receptive fields can be predicted a priori by reformulating an abstract model as nonlinear Hebbian learning. Thus nonlinear Hebbian learning and natural statistics can account for many aspects of receptive field formation across models and sensory modalities.

Nonlinear Hebbian Learning as a Unifying Principle in Receptive Field Formation

PubMed Central

Gerstner, Wulfram

2016-01-01

The development of sensory receptive fields has been modeled in the past by a variety of models including normative models such as sparse coding or independent component analysis and bottom-up models such as spike-timing dependent plasticity or the Bienenstock-Cooper-Munro model of synaptic plasticity. Here we show that the above variety of approaches can all be unified into a single common principle, namely nonlinear Hebbian learning. When nonlinear Hebbian learning is applied to natural images, receptive field shapes were strongly constrained by the input statistics and preprocessing, but exhibited only modest variation across different choices of nonlinearities in neuron models or synaptic plasticity rules. Neither overcompleteness nor sparse network activity are necessary for the development of localized receptive fields. The analysis of alternative sensory modalities such as auditory models or V2 development lead to the same conclusions. In all examples, receptive fields can be predicted a priori by reformulating an abstract model as nonlinear Hebbian learning. Thus nonlinear Hebbian learning and natural statistics can account for many aspects of receptive field formation across models and sensory modalities. PMID:27690349

Body mass index and waist circumference in early adulthood are associated with thoracolumbar spine shape at age 60-64: The Medical Research Council National Survey of Health and Development.

PubMed

Pavlova, Anastasia V; Muthuri, Stella G; Cooper, Rachel; Saunders, Fiona R; Gregory, Jennifer S; Barr, Rebecca J; Martin, Kathryn R; Adams, Judith E; Kuh, Diana; Hardy, Rebecca J; Aspden, Richard M

2018-01-01

This study investigated associations between measures of adiposity from age 36 and spine shape at 60-64 years. Thoracolumbar spine shape was characterised using statistical shape modelling on lateral dual-energy x-ray absorptiometry images of the spine from 1529 participants of the MRC National Survey of Health and Development, acquired at age 60-64. Associations of spine shape modes with: 1) contemporaneous measures of total and central adiposity (body mass index (BMI), waist circumference (WC)) and body composition (android:gynoid fat mass ratio and lean and fat mass indices, calculated as whole body (excluding the head) lean or fat mass (kg) divided by height2 (m)2); 2) changes in total and central adiposity between age 36 and 60-64 and 3) age at onset of overweight, were tested using linear regression models. Four modes described 79% of the total variance in spine shape. In men, greater lean mass index was associated with a larger lordosis whereas greater fat mass index was associated with straighter spines. Greater current BMI was associated with a more uneven curvature in men and with larger anterior-posterior (a-p) vertebral diameters in both sexes. Greater WC and fat mass index were also associated with a-p diameter in both sexes. There was no clear evidence that gains in BMI and WC during earlier stages of adulthood were associated with spine shape but younger onset of overweight was associated with a more uneven spine and greater a-p diameter. In conclusion, sagittal spine shapes had different associations with total and central adiposity; earlier onset of overweight and prior measures of WC were particularly important.

Statistically-Estimated Tree Composition for the Northeastern United States at Euro-American Settlement.

PubMed

Paciorek, Christopher J; Goring, Simon J; Thurman, Andrew L; Cogbill, Charles V; Williams, John W; Mladenoff, David J; Peters, Jody A; Zhu, Jun; McLachlan, Jason S

2016-01-01

We present a gridded 8 km-resolution data product of the estimated composition of tree taxa at the time of Euro-American settlement of the northeastern United States and the statistical methodology used to produce the product from trees recorded by land surveyors. Composition is defined as the proportion of stems larger than approximately 20 cm diameter at breast height for 22 tree taxa, generally at the genus level. The data come from settlement-era public survey records that are transcribed and then aggregated spatially, giving count data. The domain is divided into two regions, eastern (Maine to Ohio) and midwestern (Indiana to Minnesota). Public Land Survey point data in the midwestern region (ca. 0.8-km resolution) are aggregated to a regular 8 km grid, while data in the eastern region, from Town Proprietor Surveys, are aggregated at the township level in irregularly-shaped local administrative units. The product is based on a Bayesian statistical model fit to the count data that estimates composition on the 8 km grid across the entire domain. The statistical model is designed to handle data from both the regular grid and the irregularly-shaped townships and allows us to estimate composition at locations with no data and to smooth over noise caused by limited counts in locations with data. Critically, the model also allows us to quantify uncertainty in our composition estimates, making the product suitable for applications employing data assimilation. We expect this data product to be useful for understanding the state of vegetation in the northeastern United States prior to large-scale Euro-American settlement. In addition to specific regional questions, the data product can also serve as a baseline against which to investigate how forests and ecosystems change after intensive settlement. The data product is being made available at the NIS data portal as version 1.0.

Online Dectection and Modeling of Safety Boundaries for Aerospace Application Using Bayesian Statistics

NASA Technical Reports Server (NTRS)

He, Yuning

2015-01-01

The behavior of complex aerospace systems is governed by numerous parameters. For safety analysis it is important to understand how the system behaves with respect to these parameter values. In particular, understanding the boundaries between safe and unsafe regions is of major importance. In this paper, we describe a hierarchical Bayesian statistical modeling approach for the online detection and characterization of such boundaries. Our method for classification with active learning uses a particle filter-based model and a boundary-aware metric for best performance. From a library of candidate shapes incorporated with domain expert knowledge, the location and parameters of the boundaries are estimated using advanced Bayesian modeling techniques. The results of our boundary analysis are then provided in a form understandable by the domain expert. We illustrate our approach using a simulation model of a NASA neuro-adaptive flight control system, as well as a system for the detection of separation violations in the terminal airspace.

Planck 2015 results. XVII. Constraints on primordial non-Gaussianity

NASA Astrophysics Data System (ADS)

Planck Collaboration; Ade, P. A. R.; Aghanim, N.; Arnaud, M.; Arroja, F.; Ashdown, M.; Aumont, J.; Baccigalupi, C.; Ballardini, M.; Banday, A. J.; Barreiro, R. B.; Bartolo, N.; Basak, S.; Battaner, E.; Benabed, K.; Benoît, A.; Benoit-Lévy, A.; Bernard, J.-P.; Bersanelli, M.; Bielewicz, P.; Bock, J. J.; Bonaldi, A.; Bonavera, L.; Bond, J. R.; Borrill, J.; Bouchet, F. R.; Boulanger, F.; Bucher, M.; Burigana, C.; Butler, R. C.; Calabrese, E.; Cardoso, J.-F.; Catalano, A.; Challinor, A.; Chamballu, A.; Chiang, H. C.; Christensen, P. R.; Church, S.; Clements, D. L.; Colombi, S.; Colombo, L. P. L.; Combet, C.; Couchot, F.; Coulais, A.; Crill, B. P.; Curto, A.; Cuttaia, F.; Danese, L.; Davies, R. D.; Davis, R. J.; de Bernardis, P.; de Rosa, A.; de Zotti, G.; Delabrouille, J.; Désert, F.-X.; Diego, J. M.; Dole, H.; Donzelli, S.; Doré, O.; Douspis, M.; Ducout, A.; Dupac, X.; Efstathiou, G.; Elsner, F.; Enßlin, T. A.; Eriksen, H. K.; Fergusson, J.; Finelli, F.; Forni, O.; Frailis, M.; Fraisse, A. A.; Franceschi, E.; Frejsel, A.; Galeotta, S.; Galli, S.; Ganga, K.; Gauthier, C.; Ghosh, T.; Giard, M.; Giraud-Héraud, Y.; Gjerløw, E.; González-Nuevo, J.; Górski, K. M.; Gratton, S.; Gregorio, A.; Gruppuso, A.; Gudmundsson, J. E.; Hamann, J.; Hansen, F. K.; Hanson, D.; Harrison, D. L.; Heavens, A.; Helou, G.; Henrot-Versillé, S.; Hernández-Monteagudo, C.; Herranz, D.; Hildebrandt, S. R.; Hivon, E.; Hobson, M.; Holmes, W. A.; Hornstrup, A.; Hovest, W.; Huang, Z.; Huffenberger, K. M.; Hurier, G.; Jaffe, A. H.; Jaffe, T. R.; Jones, W. C.; Juvela, M.; Keihänen, E.; Keskitalo, R.; Kim, J.; Kisner, T. S.; Knoche, J.; Kunz, M.; Kurki-Suonio, H.; Lacasa, F.; Lagache, G.; Lähteenmäki, A.; Lamarre, J.-M.; Lasenby, A.; Lattanzi, M.; Lawrence, C. R.; Leonardi, R.; Lesgourgues, J.; Levrier, F.; Lewis, A.; Liguori, M.; Lilje, P. B.; Linden-Vørnle, M.; López-Caniego, M.; Lubin, P. M.; Macías-Pérez, J. F.; Maggio, G.; Maino, D.; Mandolesi, N.; Mangilli, A.; Marinucci, D.; Maris, M.; Martin, P. G.; Martínez-González, E.; Masi, S.; Matarrese, S.; McGehee, P.; Meinhold, P. R.; Melchiorri, A.; Mendes, L.; Mennella, A.; Migliaccio, M.; Mitra, S.; Miville-Deschênes, M.-A.; Moneti, A.; Montier, L.; Morgante, G.; Mortlock, D.; Moss, A.; Münchmeyer, M.; Munshi, D.; Murphy, J. A.; Naselsky, P.; Nati, F.; Natoli, P.; Netterfield, C. B.; Nørgaard-Nielsen, H. U.; Noviello, F.; Novikov, D.; Novikov, I.; Oxborrow, C. A.; Paci, F.; Pagano, L.; Pajot, F.; Paoletti, D.; Pasian, F.; Patanchon, G.; Peiris, H. V.; Perdereau, O.; Perotto, L.; Perrotta, F.; Pettorino, V.; Piacentini, F.; Piat, M.; Pierpaoli, E.; Pietrobon, D.; Plaszczynski, S.; Pointecouteau, E.; Polenta, G.; Popa, L.; Pratt, G. W.; Prézeau, G.; Prunet, S.; Puget, J.-L.; Rachen, J. P.; Racine, B.; Rebolo, R.; Reinecke, M.; Remazeilles, M.; Renault, C.; Renzi, A.; Ristorcelli, I.; Rocha, G.; Rosset, C.; Rossetti, M.; Roudier, G.; Rubiño-Martín, J. A.; Rusholme, B.; Sandri, M.; Santos, D.; Savelainen, M.; Savini, G.; Scott, D.; Seiffert, M. D.; Shellard, E. P. S.; Shiraishi, M.; Smith, K.; Spencer, L. D.; Stolyarov, V.; Stompor, R.; Sudiwala, R.; Sunyaev, R.; Sutter, P.; Sutton, D.; Suur-Uski, A.-S.; Sygnet, J.-F.; Tauber, J. A.; Terenzi, L.; Toffolatti, L.; Tomasi, M.; Tristram, M.; Troja, A.; Tucci, M.; Tuovinen, J.; Valenziano, L.; Valiviita, J.; Van Tent, B.; Vielva, P.; Villa, F.; Wade, L. A.; Wandelt, B. D.; Wehus, I. K.; Yvon, D.; Zacchei, A.; Zonca, A.

2016-09-01

The Planck full mission cosmic microwave background (CMB) temperature and E-mode polarization maps are analysed to obtain constraints on primordial non-Gaussianity (NG). Using three classes of optimal bispectrum estimators - separable template-fitting (KSW), binned, and modal - we obtain consistent values for the primordial local, equilateral, and orthogonal bispectrum amplitudes, quoting as our final result from temperature alone ƒlocalNL = 2.5 ± 5.7, ƒequilNL= -16 ± 70, , and ƒorthoNL = -34 ± 32 (68% CL, statistical). Combining temperature and polarization data we obtain ƒlocalNL = 0.8 ± 5.0, ƒequilNL= -4 ± 43, and ƒorthoNL = -26 ± 21 (68% CL, statistical). The results are based on comprehensive cross-validation of these estimators on Gaussian and non-Gaussian simulations, are stable across component separation techniques, pass an extensive suite of tests, and are consistent with estimators based on measuring the Minkowski functionals of the CMB. The effect of time-domain de-glitching systematics on the bispectrum is negligible. In spite of these test outcomes we conservatively label the results including polarization data as preliminary, owing to a known mismatch of the noise model in simulations and the data. Beyond estimates of individual shape amplitudes, we present model-independent, three-dimensional reconstructions of the Planck CMB bispectrum and derive constraints on early universe scenarios that generate primordial NG, including general single-field models of inflation, axion inflation, initial state modifications, models producing parity-violating tensor bispectra, and directionally dependent vector models. We present a wide survey of scale-dependent feature and resonance models, accounting for the "look elsewhere" effect in estimating the statistical significance of features. We also look for isocurvature NG, and find no signal, but we obtain constraints that improve significantly with the inclusion of polarization. The primordial trispectrum amplitude in the local model is constrained to be 𝓰localNL = (-0.9 ± 7.7 ) X 104(68% CL statistical), and we perform an analysis of trispectrum shapes beyond the local case. The global picture that emerges is one of consistency with the premises of the ΛCDM cosmology, namely that the structure we observe today was sourced by adiabatic, passive, Gaussian, and primordial seed perturbations.

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

Ade, P. A. R.; Aghanim, N.; Arnaud, M.

We report that the Planck full mission cosmic microwave background (CMB) temperature and E-mode polarization maps are analysed to obtain constraints on primordial non-Gaussianity (NG). Using three classes of optimal bispectrum estimators – separable template-fitting (KSW), binned, and modal – we obtain consistent values for the primordial local, equilateral, and orthogonal bispectrum amplitudes, quoting as our final result from temperature alone ƒ local NL = 2.5 ± 5.7, ƒ equil NL= -16 ± 70, , and ƒ ortho NL = -34 ± 32 (68% CL, statistical). Combining temperature and polarization data we obtain ƒ local NL = 0.8 ± 5.0,more » ƒ equil NL= -4 ± 43, and ƒ ortho NL = -26 ± 21 (68% CL, statistical). The results are based on comprehensive cross-validation of these estimators on Gaussian and non-Gaussian simulations, are stable across component separation techniques, pass an extensive suite of tests, and are consistent with estimators based on measuring the Minkowski functionals of the CMB. The effect of time-domain de-glitching systematics on the bispectrum is negligible. In spite of these test outcomes we conservatively label the results including polarization data as preliminary, owing to a known mismatch of the noise model in simulations and the data. Beyond estimates of individual shape amplitudes, we present model-independent, three-dimensional reconstructions of the Planck CMB bispectrum and derive constraints on early universe scenarios that generate primordial NG, including general single-field models of inflation, axion inflation, initial state modifications, models producing parity-violating tensor bispectra, and directionally dependent vector models. We present a wide survey of scale-dependent feature and resonance models, accounting for the “look elsewhere” effect in estimating the statistical significance of features. We also look for isocurvature NG, and find no signal, but we obtain constraints that improve significantly with the inclusion of polarization. The primordial trispectrum amplitude in the local model is constrained to be g local NL = (-0.9 ± 7.7 ) X 10 4(68% CL statistical), and we perform an analysis of trispectrum shapes beyond the local case. The global picture that emerges is one of consistency with the premises of the ΛCDM cosmology, namely that the structure we observe today was sourced by adiabatic, passive, Gaussian, and primordial seed perturbations.« less

Planck 2015 results: XVII. Constraints on primordial non-Gaussianity

DOE PAGES

Ade, P. A. R.; Aghanim, N.; Arnaud, M.; ...

2016-09-20

We report that the Planck full mission cosmic microwave background (CMB) temperature and E-mode polarization maps are analysed to obtain constraints on primordial non-Gaussianity (NG). Using three classes of optimal bispectrum estimators – separable template-fitting (KSW), binned, and modal – we obtain consistent values for the primordial local, equilateral, and orthogonal bispectrum amplitudes, quoting as our final result from temperature alone ƒ local NL = 2.5 ± 5.7, ƒ equil NL= -16 ± 70, , and ƒ ortho NL = -34 ± 32 (68% CL, statistical). Combining temperature and polarization data we obtain ƒ local NL = 0.8 ± 5.0,more » ƒ equil NL= -4 ± 43, and ƒ ortho NL = -26 ± 21 (68% CL, statistical). The results are based on comprehensive cross-validation of these estimators on Gaussian and non-Gaussian simulations, are stable across component separation techniques, pass an extensive suite of tests, and are consistent with estimators based on measuring the Minkowski functionals of the CMB. The effect of time-domain de-glitching systematics on the bispectrum is negligible. In spite of these test outcomes we conservatively label the results including polarization data as preliminary, owing to a known mismatch of the noise model in simulations and the data. Beyond estimates of individual shape amplitudes, we present model-independent, three-dimensional reconstructions of the Planck CMB bispectrum and derive constraints on early universe scenarios that generate primordial NG, including general single-field models of inflation, axion inflation, initial state modifications, models producing parity-violating tensor bispectra, and directionally dependent vector models. We present a wide survey of scale-dependent feature and resonance models, accounting for the “look elsewhere” effect in estimating the statistical significance of features. We also look for isocurvature NG, and find no signal, but we obtain constraints that improve significantly with the inclusion of polarization. The primordial trispectrum amplitude in the local model is constrained to be g local NL = (-0.9 ± 7.7 ) X 10 4(68% CL statistical), and we perform an analysis of trispectrum shapes beyond the local case. The global picture that emerges is one of consistency with the premises of the ΛCDM cosmology, namely that the structure we observe today was sourced by adiabatic, passive, Gaussian, and primordial seed perturbations.« less

Probing the dark sector through mono-Z boson leptonic decays

NASA Astrophysics Data System (ADS)

Yang, Daneng; Li, Qiang

2018-02-01

Collider search for dark matter production has been performed over the years based on high p T standard model signatures balanced by large missing transverse energy. The mono-Z boson production with leptonic decay has a clean signature with the advantage that the decaying electrons and muons can be precisely measured. This signature not only enables reconstruction of the Z boson rest frame, but also makes possible recovery of the underlying production dynamics through the decaying lepton angular distribution. In this work, we exploit full information carried by the leptonic Z boson decays to set limits on coupling strength parameters of the dark sector. We study simplified dark sector models with scalar, vector, and tensor mediators and observe among them different signatures in the distribution of angular coefficients. Specifically, we show that angular coefficients can be used to distinguish different scenarios of the spin-0 and spin-1 models, including the ones with parity-odd and charge conjugation parity-odd operators. To maximize the statistical power, we perform a matrix element method study with a dynamic construction of event likelihood function. We parametrize the test statistic such that sensitivity from the matrix element is quantified through a term measuring the shape difference. Our results show that the shape differences provide significant improvements in the limits, especially for the scalar mediator models. We also present an example application of a matrix-element-kinematic-discriminator, an easier approach that is applicable for experimental data.

Computer aided weld defect delineation using statistical parametric active contours in radiographic inspection.

PubMed

Goumeidane, Aicha Baya; Nacereddine, Nafaa; Khamadja, Mohammed

2015-01-01

A perfect knowledge of a defect shape is determinant for the analysis step in automatic radiographic inspection. Image segmentation is carried out on radiographic images and extract defects indications. This paper deals with weld defect delineation in radiographic images. The proposed method is based on a new statistics-based explicit active contour. An association of local and global modeling of the image pixels intensities is used to push the model to the desired boundaries. Furthermore, other strategies are proposed to accelerate its evolution and make the convergence speed depending only on the defect size as selecting a band around the active contour curve. The experimental results are very promising, since experiments on synthetic and radiographic images show the ability of the proposed model to extract a piece-wise homogenous object from very inhomogeneous background, even in a bad quality image.

Optimal Multiple Surface Segmentation With Shape and Context Priors

PubMed Central

Bai, Junjie; Garvin, Mona K.; Sonka, Milan; Buatti, John M.; Wu, Xiaodong

2014-01-01

Segmentation of multiple surfaces in medical images is a challenging problem, further complicated by the frequent presence of weak boundary evidence, large object deformations, and mutual influence between adjacent objects. This paper reports a novel approach to multi-object segmentation that incorporates both shape and context prior knowledge in a 3-D graph-theoretic framework to help overcome the stated challenges. We employ an arc-based graph representation to incorporate a wide spectrum of prior information through pair-wise energy terms. In particular, a shape-prior term is used to penalize local shape changes and a context-prior term is used to penalize local surface-distance changes from a model of the expected shape and surface distances, respectively. The globally optimal solution for multiple surfaces is obtained by computing a maximum flow in a low-order polynomial time. The proposed method was validated on intraretinal layer segmentation of optical coherence tomography images and demonstrated statistically significant improvement of segmentation accuracy compared to our earlier graph-search method that was not utilizing shape and context priors. The mean unsigned surface positioning errors obtained by the conventional graph-search approach (6.30 ± 1.58 μm) was improved to 5.14 ± 0.99 μm when employing our new method with shape and context priors. PMID:23193309

Assessment of Coronal Spinal Alignment for Adult Spine Deformity Cases After Intraoperative T Square Shaped Use.

PubMed

Kurra, Swamy; Metkar, Umesh; Yirenkyi, Henaku; Tallarico, Richard A; Lavelle, William F

Retrospectively reviewed surgeries between 2011 and 2015 of patients who underwent posterior spinal deformity instrumentation with constructs involving fusions to pelvis and encompassing at least five levels. Measure the radiographic outcomes of coronal malalignment (CM) after use of an intraoperative T square shaped instrument in posterior spinal deformity surgeries with at least five levels of fusion and extension to pelvis. Neuromuscular children found to benefit from intraoperative T square technique to help achieve proper coronal spinal balance with extensive fusions. This intraoperative technique used in our posterior spine deformity instrumentation surgeries with the aforementioned parameters. There were 50 patients: n = 16 with intraoperative T square and n = 34 no-T square shaped device. Subgroups divided based on greater than 20 mm displacement and greater than 40 mm displacement of the C7 plumb line to the central sacral vertical line on either side in preoperative radiographs. We analyzed the demographics and the pre- and postoperative radiographic parameters of standing films: standing CM (displacement of C7 plumb line to central sacral vertical line), and major coronal Cobb angles in total sample and subgroups and compared T square shaped device with no-T square shaped device use by analysis of variance. A p value ≤.05 is statistically significant. In the total sample, though postoperative CM mean was not statistically different, we observed greater CM corrections in patients where a T square shaped device was used (70%) versus no-T square shaped device used (18%). In >20 mm and >40 mm subgroups, the postoperative mean CM values were statistically lower for the patients where a T square shaped device was used, p = .016 and p = .003, respectively. Cobb corrections were statistically higher for T square shaped device use in both >20 mm and >40 mm subgroups, 68%, respectively. The intraoperative T square shaped device technique had a positive effect on the amount of spine coronal malalignment correction after its use and for lumbar and thoracic coronal Cobb angles. Level III. Copyright © 2017 Scoliosis Research Society. Published by Elsevier Inc. All rights reserved.

Influence of eye biometrics and corneal micro-structure on noncontact tonometry.

PubMed

Jesus, Danilo A; Majewska, Małgorzata; Krzyżanowska-Berkowska, Patrycja; Iskander, D Robert

2017-01-01

Tonometry is widely used as the main screening tool supporting glaucoma diagnosis. Still, its accuracy could be improved if full knowledge about the variation of the corneal biomechanical properties was available. In this study, Optical Coherence Tomography (OCT) speckle statistics are used to infer the organisation of the corneal micro-structure and hence, to analyse its influence on intraocular pressure (IOP) measurements. Fifty-six subjects were recruited for this prospective study. Macro and micro-structural corneal parameters as well as subject age were considered. Macro-structural analysis included the parameters that are associated with the ocular anatomy, such as central corneal thickness (CCT), corneal radius, axial length, anterior chamber depth and white-to-white corneal diameter. Micro-structural parameters which included OCT speckle statistics were related to the internal organisation of the corneal tissue and its physiological changes during lifetime. The corneal speckle obtained from OCT was modelled with the Generalised Gamma (GG) distribution that is characterised with a scale parameter and two shape parameters. In macro-structure analysis, only CCT showed a statistically significant correlation with IOP (R2 = 0.25, p<0.001). The scale parameter and the ratio of the shape parameters of GG distribution showed statistically significant correlation with IOP (R2 = 0.19, p<0.001 and R2 = 0.17, p<0.001, respectively). For the studied group, a weak, although significant correlation was found between age and IOP (R2 = 0.053, p = 0.04). Forward stepwise regression showed that CCT and the scale parameter of the Generalised Gamma distribution can be combined in a regression model (R2 = 0.39, p<0.001) to study the role of the corneal structure on IOP. We show, for the first time, that corneal micro-structure influences the IOP measurements obtained from noncontact tonometry. OCT speckle statistics can be employed to learn about the corneal micro-structure and hence, to further calibrate the IOP measurements.

Influence of eye biometrics and corneal micro-structure on noncontact tonometry

PubMed Central

Majewska, Małgorzata; Krzyżanowska-Berkowska, Patrycja; Iskander, D. Robert

2017-01-01

Purpose Tonometry is widely used as the main screening tool supporting glaucoma diagnosis. Still, its accuracy could be improved if full knowledge about the variation of the corneal biomechanical properties was available. In this study, Optical Coherence Tomography (OCT) speckle statistics are used to infer the organisation of the corneal micro-structure and hence, to analyse its influence on intraocular pressure (IOP) measurements. Methods Fifty-six subjects were recruited for this prospective study. Macro and micro-structural corneal parameters as well as subject age were considered. Macro-structural analysis included the parameters that are associated with the ocular anatomy, such as central corneal thickness (CCT), corneal radius, axial length, anterior chamber depth and white-to-white corneal diameter. Micro-structural parameters which included OCT speckle statistics were related to the internal organisation of the corneal tissue and its physiological changes during lifetime. The corneal speckle obtained from OCT was modelled with the Generalised Gamma (GG) distribution that is characterised with a scale parameter and two shape parameters. Results In macro-structure analysis, only CCT showed a statistically significant correlation with IOP (R2 = 0.25, p<0.001). The scale parameter and the ratio of the shape parameters of GG distribution showed statistically significant correlation with IOP (R2 = 0.19, p<0.001 and R2 = 0.17, p<0.001, respectively). For the studied group, a weak, although significant correlation was found between age and IOP (R2 = 0.053, p = 0.04). Forward stepwise regression showed that CCT and the scale parameter of the Generalised Gamma distribution can be combined in a regression model (R2 = 0.39, p<0.001) to study the role of the corneal structure on IOP. Conclusions We show, for the first time, that corneal micro-structure influences the IOP measurements obtained from noncontact tonometry. OCT speckle statistics can be employed to learn about the corneal micro-structure and hence, to further calibrate the IOP measurements. PMID:28472178

Meta-analysis of prediction model performance across multiple studies: Which scale helps ensure between-study normality for the C-statistic and calibration measures?

PubMed

Snell, Kym Ie; Ensor, Joie; Debray, Thomas Pa; Moons, Karel Gm; Riley, Richard D

2017-01-01

If individual participant data are available from multiple studies or clusters, then a prediction model can be externally validated multiple times. This allows the model's discrimination and calibration performance to be examined across different settings. Random-effects meta-analysis can then be used to quantify overall (average) performance and heterogeneity in performance. This typically assumes a normal distribution of 'true' performance across studies. We conducted a simulation study to examine this normality assumption for various performance measures relating to a logistic regression prediction model. We simulated data across multiple studies with varying degrees of variability in baseline risk or predictor effects and then evaluated the shape of the between-study distribution in the C-statistic, calibration slope, calibration-in-the-large, and E/O statistic, and possible transformations thereof. We found that a normal between-study distribution was usually reasonable for the calibration slope and calibration-in-the-large; however, the distributions of the C-statistic and E/O were often skewed across studies, particularly in settings with large variability in the predictor effects. Normality was vastly improved when using the logit transformation for the C-statistic and the log transformation for E/O, and therefore we recommend these scales to be used for meta-analysis. An illustrated example is given using a random-effects meta-analysis of the performance of QRISK2 across 25 general practices.

Signal Statistics and Maximum Likelihood Sequence Estimation in Intensity Modulated Fiber Optic Links Containing a Single Optical Pre-amplifier.

PubMed

Alić, Nikola; Papen, George; Saperstein, Robert; Milstein, Laurence; Fainman, Yeshaiahu

2005-06-13

Exact signal statistics for fiber-optic links containing a single optical pre-amplifier are calculated and applied to sequence estimation for electronic dispersion compensation. The performance is evaluated and compared with results based on the approximate chi-square statistics. We show that detection in existing systems based on exact statistics can be improved relative to using a chi-square distribution for realistic filter shapes. In contrast, for high-spectral efficiency systems the difference between the two approaches diminishes, and performance tends to be less dependent on the exact shape of the filter used.

Circularly-symmetric complex normal ratio distribution for scalar transmissibility functions. Part III: Application to statistical modal analysis

NASA Astrophysics Data System (ADS)

Yan, Wang-Ji; Ren, Wei-Xin

2018-01-01

This study applies the theoretical findings of circularly-symmetric complex normal ratio distribution Yan and Ren (2016) [1,2] to transmissibility-based modal analysis from a statistical viewpoint. A probabilistic model of transmissibility function in the vicinity of the resonant frequency is formulated in modal domain, while some insightful comments are offered. It theoretically reveals that the statistics of transmissibility function around the resonant frequency is solely dependent on 'noise-to-signal' ratio and mode shapes. As a sequel to the development of the probabilistic model of transmissibility function in modal domain, this study poses the process of modal identification in the context of Bayesian framework by borrowing a novel paradigm. Implementation issues unique to the proposed approach are resolved by Lagrange multiplier approach. Also, this study explores the possibility of applying Bayesian analysis in distinguishing harmonic components and structural ones. The approaches are verified through simulated data and experimentally testing data. The uncertainty behavior due to variation of different factors is also discussed in detail.

Influence of velocity effects on the shape of N2 (and air) broadened H2O lines revisited with classical molecular dynamics simulations

NASA Astrophysics Data System (ADS)

Ngo, N. H.; Tran, H.; Gamache, R. R.; Bermejo, D.; Domenech, J.-L.

2012-08-01

The modeling of the shape of H2O lines perturbed by N2 (and air) using the Keilson-Storer (KS) kernel for collision-induced velocity changes is revisited with classical molecular dynamics simulations (CMDS). The latter have been performed for a large number of molecules starting from intermolecular-potential surfaces. Contrary to the assumption made in a previous study [H. Tran, D. Bermejo, J.-L. Domenech, P. Joubert, R. R. Gamache, and J.-M. Hartmann, J. Quant. Spectrosc. Radiat. Transf. 108, 126 (2007)], 10.1016/j.jqsrt.2007.03.009, the results of these CMDS show that the velocity-orientation and -modulus changes statistically occur at the same time scale. This validates the use of a single memory parameter in the Keilson-Storer kernel to describe both the velocity-orientation and -modulus changes. The CMDS results also show that velocity- and rotational state-changing collisions are statistically partially correlated. A partially correlated speed-dependent Keilson-Storer model has thus been used to describe the line-shape. For this, the velocity changes KS kernel parameters have been directly determined from CMDS, while the speed-dependent broadening and shifting coefficients have been calculated with a semi-classical approach. Comparisons between calculated spectra and measurements of several lines of H2O broadened by N2 (and air) in the ν3 and 2ν1 + ν2 + ν3 bands for a wide range of pressure show very satisfactory agreement. The evolution of non-Voigt effects from Doppler to collisional regimes is also presented and discussed.

Stalactite growth as a free-boundary problem: a geometric law and its platonic ideal.

PubMed

Short, Martin B; Baygents, James C; Beck, J Warren; Stone, David A; Toomey, Rickard S; Goldstein, Raymond E

2005-01-14

The chemical mechanisms underlying the growth of cave formations such as stalactites are well known, yet no theory has yet been proposed which successfully accounts for the dynamic evolution of their shapes. Here we consider the interplay of thin-film fluid dynamics, calcium carbonate chemistry, and CO2 transport in the cave to show that stalactites evolve according to a novel local geometric growth law which exhibits extreme amplification at the tip as a consequence of the locally-varying fluid layer thickness. Studies of this model show that a broad class of initial conditions is attracted to an ideal shape which is strikingly close to a statistical average of natural stalactites.

Automated planning of ablation targets in atrial fibrillation treatment

NASA Astrophysics Data System (ADS)

Keustermans, Johannes; De Buck, Stijn; Heidbüchel, Hein; Suetens, Paul

2011-03-01

Catheter based radio-frequency ablation is used as an invasive treatment of atrial fibrillation. This procedure is often guided by the use of 3D anatomical models obtained from CT, MRI or rotational angiography. During the intervention the operator accurately guides the catheter to prespecified target ablation lines. The planning stage, however, can be time consuming and operator dependent which is suboptimal both from a cost and health perspective. Therefore, we present a novel statistical model-based algorithm for locating ablation targets from 3D rotational angiography images. Based on a training data set of 20 patients, consisting of 3D rotational angiography images with 30 manually indicated ablation points, a statistical local appearance and shape model is built. The local appearance model is based on local image descriptors to capture the intensity patterns around each ablation point. The local shape model is constructed by embedding the ablation points in an undirected graph and imposing that each ablation point only interacts with its neighbors. Identifying the ablation points on a new 3D rotational angiography image is performed by proposing a set of possible candidate locations for each ablation point, as such, converting the problem into a labeling problem. The algorithm is validated using a leave-one-out-approach on the training data set, by computing the distance between the ablation lines obtained by the algorithm and the manually identified ablation points. The distance error is equal to 3.8+/-2.9 mm. As ablation lesion size is around 5-7 mm, automated planning of ablation targets by the presented approach is sufficiently accurate.

Lagrangian statistics of turbulent dispersion from 81923 direct numerical simulation of isotropic turbulence

NASA Astrophysics Data System (ADS)

Buaria, Dhawal; Yeung, P. K.; Sawford, B. L.

2016-11-01

An efficient massively parallel algorithm has allowed us to obtain the trajectories of 300 million fluid particles in an 81923 simulation of isotropic turbulence at Taylor-scale Reynolds number 1300. Conditional single-particle statistics are used to investigate the effect of extreme events in dissipation and enstrophy on turbulent dispersion. The statistics of pairs and tetrads, both forward and backward in time, are obtained via post-processing of single-particle trajectories. For tetrads, since memory of shape is known to be short, we focus, for convenience, on samples which are initially regular, with all sides of comparable length. The statistics of tetrad size show similar behavior as the two-particle relative dispersion, i.e., stronger backward dispersion at intermediate times with larger backward Richardson constant. In contrast, the statistics of tetrad shape show more robust inertial range scaling, in both forward and backward frames. However, the distortion of shape is stronger for backward dispersion. Our results suggest that the Reynolds number reached in this work is sufficient to settle some long-standing questions concerning Lagrangian scale similarity. Supported by NSF Grants CBET-1235906 and ACI-1036170.

A Comparison of Apical Bacterial Extrusion in Manual, ProTaper Rotary, and One Shape Rotary Instrumentation Techniques.

PubMed

Mittal, Rakesh; Singla, Meenu G; Garg, Ashima; Dhawan, Anu

2015-12-01

Apical extrusion of irrigants and debris is an inherent limitation associated with cleaning and shaping of root canals and has been studied extensively because of its clinical relevance as a cause of flare-ups. Many factors affect the amount of extruded intracanal materials. The purpose of this study was to assess the bacterial extrusion by using manual, multiple-file continuous rotary system (ProTaper) and single-file continuous rotary system (One Shape). Forty-two human mandibular premolars were inoculated with Enterococcus faecalis by using a bacterial extrusion model. The teeth were divided into 3 experimental groups (n = 12) and 1 control group (n = 6). The root canals of experimental groups were instrumented according to the manufacturers' instructions by using manual technique, ProTaper rotary system, or One Shape rotary system. Sterilized saline was used as an irrigant, and bacterial extrusion was quantified as colony-forming units/milliliter. The results obtained were statistically analyzed by using one-way analysis of variance for intergroup comparison and post hoc Tukey test for pair-wise comparison. The level for accepting statistical significance was set at P < .05. All the instrumentation techniques resulted in bacterial extrusion, with manual step-back technique exhibiting significantly more bacterial extrusion than the engine-driven systems. Of the 2 engine-driven systems, ProTaper rotary extruded significantly more bacteria than One Shape rotary system (P < .05). The engine-driven nickel-titanium systems were associated with less apical extrusion. The instrument design may play a role in amount of extrusion. Copyright © 2015 American Association of Endodontists. Published by Elsevier Inc. All rights reserved.

Pore geometry as a control on rock strength

NASA Astrophysics Data System (ADS)

Bubeck, A.; Walker, R. J.; Healy, D.; Dobbs, M.; Holwell, D. A.

2017-01-01

The strength of rocks in the subsurface is critically important across the geosciences, with implications for fluid flow, mineralisation, seismicity, and the deep biosphere. Most studies of porous rock strength consider the scalar quantity of porosity, in which strength shows a broadly inverse relationship with total porosity, but pore shape is not explicitly defined. Here we use a combination of uniaxial compressive strength measurements of isotropic and anisotropic porous lava samples, and numerical modelling to consider the influence of pore shape on rock strength. Micro computed tomography (CT) shows that pores range from sub-spherical to elongate and flat ellipsoids. Samples that contain flat pores are weaker if compression is applied parallel to the short axis (i.e. across the minimum curvature), compared to compression applied parallel to the long axis (i.e. across the maximum curvature). Numerical models for elliptical pores show that compression applied across the minimum curvature results in relatively broad amplification of stress, compared to compression applied across the maximum curvature. Certain pore shapes may be relatively stable and remain open in the upper crust under a given remote stress field, while others are inherently weak. Quantifying the shape, orientations, and statistical distributions of pores is therefore a critical step in strength testing of rocks.

Effects of parallelogram-shaped pavement markings on vehicle speed and safety of pedestrian crosswalks on urban roads in China.

PubMed

Guo, Yanyong; Liu, Pan; Liang, Qiyu; Wang, Wei

2016-10-01

The primary objective of this study was to evaluate the effects of parallelogram-shaped pavement markings on vehicle speed and crashes in the vicinity of urban pedestrian crosswalks. The research team measured speed data at twelve sites, and crash data at eleven sites. Observational cross-sectional studies were conducted to identify if the effects of parallelogram-shaped pavement markings on vehicle speeds and speed violations were statistically significant. The results showed that parallelogram-shaped pavement markings significantly reduced vehicle speeds and speed violations in the vicinity of pedestrian crosswalks. More specifically, the speed reduction effects varied from 1.89km/h to 4.41km/h with an average of 3.79km/h. The reduction in the 85th percentile speed varied from 0.81km/h to 5.34km/h with an average of 4.19km/h. Odds ratios (OR) showed that the parallelogram-shaped pavement markings had effects of a 7.1% reduction in the mean speed and a 6.9% reduction in the 85th percentile speed at the pedestrian crosswalks. The reduction of proportion of drivers exceeding the speed limit varied from 8.64% to 14.15% with an average of 11.03%. The results of the crash data analysis suggested that the use of parallelogram-shaped pavement markings reduced both the frequency and severity of crashes at pedestrian crosswalks. The parallelogram-shaped pavement markings had a significant effect on reducing the vehicle-pedestrian crashes. Two crash prediction models were developed for vehicle-pedestrian crashes and rear-end crashes. According to the crash models, the presence of parallelogram-shaped pavement markings reduced vehicle-pedestrian crashes at pedestrian crosswalks by 24.87% with a 95% confidence interval of [10.06-30.78%]. However, the model results also showed that the presence of parallelogram-shaped pavement markings increased rear-end crashes at pedestrian crosswalks by 5.4% with a 95% confidence interval of [0-11.2%]. Copyright © 2015 Elsevier Ltd. All rights reserved.

Analysis of Immune Complex Structure by Statistical Mechanics and Light Scattering Techniques.

NASA Astrophysics Data System (ADS)

Busch, Nathan Adams

1995-01-01

The size and structure of immune complexes determine their behavior in the immune system. The chemical physics of the complex formation is not well understood; this is due in part to inadequate characterization of the proteins involved, and in part by lack of sufficiently well developed theoretical techniques. Understanding the complex formation will permit rational design of strategies for inhibiting tissue deposition of the complexes. A statistical mechanical model of the proteins based upon the theory of associating fluids was developed. The multipole electrostatic potential for each protein used in this study was characterized for net protein charge, dipole moment magnitude, and dipole moment direction. The binding sites, between the model antigen and antibodies, were characterized for their net surface area, energy, and position relative to the dipole moment of the protein. The equilibrium binding graphs generated with the protein statistical mechanical model compares favorably with experimental data obtained from radioimmunoassay results. The isothermal compressibility predicted by the model agrees with results obtained from dynamic light scattering. The statistical mechanics model was used to investigate association between the model antigen and selected pairs of antibodies. It was found that, in accordance to expectations from thermodynamic arguments, the highest total binding energy yielded complex distributions which were skewed to higher complex size. From examination of the simulated formation of ring structures from linear chain complexes, and from the joint shape probability surfaces, it was found that ring configurations were formed by the "folding" of linear chains until the ends are within binding distance. By comparing the single antigen/two antibody system which differ only in their respective binding site locations, it was found that binding site location influences complex size and shape distributions only when ring formation occurs. The internal potential energy of a ring complex is considerably less than that of the non-associating system; therefore the ring complexes are quite stable and show no evidence of breaking, and collapsing into smaller complexes. The ring formation will occur only in systems where the total free energy of each complex may be minimized. Thus, ring formation will occur even though entropically unfavorable conformations result if the total free energy can be minimized by doing so.

Surface switching statistics of rotating fluid: Disk-rim gap effects

NASA Astrophysics Data System (ADS)

Tasaka, Yuji; Iima, Makoto

2017-04-01

We examined the influence of internal noise on the irregular switching of the shape of the free surface of fluids in an open cylindrical vessel driven by a bottom disk rotating at constant speed [Suzuki, Iima, and Hayase, Phys. Fluids 18, 101701 (2006), 10.1063/1.2359740]. A slight increase in the disk-rim gap (less than 3% of the disk radius) was established experimentally to cause significant changes in this system, specifically, frequent appearance of the surface descending event connecting a nonaxisymmetric shape in strong mixing flow (turbulent flow) and an axisymmetric shape in laminar flow, as well as a shift in critical Reynolds number that define the characteristic states. The physical mechanism underlying the change is analyzed in terms of flow characteristics in the disk-rim gap, which acts as a noise source, and a mathematical model established from measurements of the surface height fluctuations with noise term.

Side Effects of Being Blue: Influence of Sad Mood on Visual Statistical Learning

PubMed Central

Bertels, Julie; Demoulin, Catherine; Franco, Ana; Destrebecqz, Arnaud

2013-01-01

It is well established that mood influences many cognitive processes, such as learning and executive functions. Although statistical learning is assumed to be part of our daily life, as mood does, the influence of mood on statistical learning has never been investigated before. In the present study, a sad vs. neutral mood was induced to the participants through the listening of stories while they were exposed to a stream of visual shapes made up of the repeated presentation of four triplets, namely sequences of three shapes presented in a fixed order. Given that the inter-stimulus interval was held constant within and between triplets, the only cues available for triplet segmentation were the transitional probabilities between shapes. Direct and indirect measures of learning taken either immediately or 20 minutes after the exposure/mood induction phase revealed that participants learned the statistical regularities between shapes. Interestingly, although participants from the sad and neutral groups performed similarly in these tasks, subjective measures (confidence judgments taken after each trial) revealed that participants who experienced the sad mood induction showed increased conscious access to their statistical knowledge. These effects were not modulated by the time delay between the exposure/mood induction and the test phases. These results are discussed within the scope of the robustness principle and the influence of negative affects on processing style. PMID:23555797

Diagnostic index: an open-source tool to classify TMJ OA condyles

NASA Astrophysics Data System (ADS)

Paniagua, Beatriz; Pascal, Laura; Prieto, Juan; Vimort, Jean Baptiste; Gomes, Liliane; Yatabe, Marilia; Ruellas, Antonio Carlos; Budin, Francois; Pieper, Steve; Styner, Martin; Benavides, Erika; Cevidanes, Lucia

2017-03-01

Osteoarthritis (OA) of temporomandibular joints (TMJ) occurs in about 40% of the patients who present TMJ disorders. Despite its prevalence, OA diagnosis and treatment remain controversial since there are no clear symptoms of the disease, especially in early stages. Quantitative tools based on 3D imaging of the TMJ condyle have the potential to help characterize TMJ OA changes. The goals of the tools proposed in this study are to ultimately develop robust imaging markers for diagnosis and assessment of treatment efficacy. This work proposes to identify differences among asymptomatic controls and different clinical phenotypes of TMJ OA by means of Statistical Shape Modeling (SSM), obtained via clinical expert consensus. From three different grouping schemes (with 3, 5 and 7 groups), our best results reveal that that the majority (74.5%) of the classifications occur in agreement with the groups assigned by consensus between our clinical experts. Our findings suggest the existence of different disease-based phenotypic morphologies in TMJ OA. Our preliminary findings with statistical shape modeling based biomarkers may provide a quantitative staging of the disease. The methodology used in this study is included in an open source image analysis toolbox, to ensure reproducibility and appropriate distribution and dissemination of the solution proposed.

Simulating the impact of dust cooling on the statistical properties of the intra-cluster medium

NASA Astrophysics Data System (ADS)

Pointecouteau, Etienne; da Silva, Antonio; Catalano, Andrea; Montier, Ludovic; Lanoux, Joseph; Roncarelli, Mauro; Giard, Martin

2009-08-01

From the first stages of star and galaxy formation, non-gravitational processes such as ram pressure stripping, SNs, galactic winds, AGNs, galaxy-galaxy mergers, etc. lead to the enrichment of the IGM in stars, metals as well as dust, via the ejection of galactic material into the IGM. We know now that these processes shape, side by side with gravitation, the formation and the evolution of structures. We present here hydrodynamic simulations of structure formation implementing the effect of the cooling by dust on large scale structure formation. We focus on the scale of galaxy clusters and study the statistical properties of clusters. Here, we present our results on the TX-M and the LX-M scaling relations which exhibit changes on both the slope and normalization when adding cooling by dust to the standard radiative cooling model. For example, the normalization of the TX-M relation changes only by a maximum of 2% at M=1014M⊙ whereas the normalization of the LX-TX changes by as much as 10% at TX=1keV for models that including dust cooling. Our study shows that the dust is an added non-gravitational process that contributes shaping the thermodynamical state of the hot ICM gas.

Substorm injection boundaries. [magnetospheric electric field model

NASA Technical Reports Server (NTRS)

Mcilwain, C. E.

1974-01-01

An improved magnetospheric electric field model is used to compute the initial locations of particles injected by several substorms. Trajectories are traced from the time of their encounter with the ATS-5 satellite backwards to the onset time given by ground-based magnetometers. A spiral shaped inner boundary of injection is found which is quite similar to that found by a statistical analysis. This injection boundary is shown to move in an energy dependent fashion which can explain the soft energy spectra observed at the inner edge of the electrons plasma sheet.

Poverty as a Predictor of 4-Year-Olds’ Executive Function: New Perspectives on Models of Differential Susceptibility

PubMed Central

Raver, C. Cybele; Blair, Clancy; Willoughby, Michael

2017-01-01

In a predominantly low-income, population-based longitudinal sample of 1,259 children followed from birth, results suggest that chronic exposure to poverty and the strains of financial hardship were each uniquely predictive of young children’s performance on measures of executive functioning. Results suggest that temperament-based vulnerability serves as a statistical moderator of the link between poverty-related risk and children’s executive functioning. Implications for models of ecology and biology in shaping the development of children’s self-regulation are discussed. PMID:22563675

A Probabilistic Model of Meter Perception: Simulating Enculturation.

PubMed

van der Weij, Bastiaan; Pearce, Marcus T; Honing, Henkjan

2017-01-01

Enculturation is known to shape the perception of meter in music but this is not explicitly accounted for by current cognitive models of meter perception. We hypothesize that the induction of meter is a result of predictive coding: interpreting onsets in a rhythm relative to a periodic meter facilitates prediction of future onsets. Such prediction, we hypothesize, is based on previous exposure to rhythms. As such, predictive coding provides a possible explanation for the way meter perception is shaped by the cultural environment. Based on this hypothesis, we present a probabilistic model of meter perception that uses statistical properties of the relation between rhythm and meter to infer meter from quantized rhythms. We show that our model can successfully predict annotated time signatures from quantized rhythmic patterns derived from folk melodies. Furthermore, we show that by inferring meter, our model improves prediction of the onsets of future events compared to a similar probabilistic model that does not infer meter. Finally, as a proof of concept, we demonstrate how our model can be used in a simulation of enculturation. From the results of this simulation, we derive a class of rhythms that are likely to be interpreted differently by enculturated listeners with different histories of exposure to rhythms.

S-shape relationship between customer satisfaction and willingness to pay premium prices for high quality cured pork products in Spain.

PubMed

Cotes-Torres, Alejandro; Muñoz-Gallego, Pablo A; Cotes-Torres, José Miguel

2012-03-01

This paper explores 2 different probabilistic models explaining willingness to pay premium prices for high-quality cured products from the swine industry. Seven cured pork products (sausage, fuet, ham, loin, shoulder, salami and pepperoni) were studied in 9 food-stores in Valladolid, Spain. Consumers of the products were interviewed (686 completed surveys). It was found by using mixed effect statistical models that the relationship between willingness to pay a premium price and customer satisfaction had nonlinear behavior, following an S-shape with inverted slope which was the first empirical evidence of this type of behavior in meat products in real market conditions. It was also established that the interaction between satisfaction and current expenditure on the product was significant and indispensable for explaining consumers' willingness to pay premium price for cured pork products. Copyright © 2011 Elsevier Ltd. All rights reserved.

Multi-stage learning for robust lung segmentation in challenging CT volumes.

PubMed

Sofka, Michal; Wetzl, Jens; Birkbeck, Neil; Zhang, Jingdan; Kohlberger, Timo; Kaftan, Jens; Declerck, Jérôme; Zhou, S Kevin

2011-01-01

Simple algorithms for segmenting healthy lung parenchyma in CT are unable to deal with high density tissue common in pulmonary diseases. To overcome this problem, we propose a multi-stage learning-based approach that combines anatomical information to predict an initialization of a statistical shape model of the lungs. The initialization first detects the carina of the trachea, and uses this to detect a set of automatically selected stable landmarks on regions near the lung (e.g., ribs, spine). These landmarks are used to align the shape model, which is then refined through boundary detection to obtain fine-grained segmentation. Robustness is obtained through hierarchical use of discriminative classifiers that are trained on a range of manually annotated data of diseased and healthy lungs. We demonstrate fast detection (35s per volume on average) and segmentation of 2 mm accuracy on challenging data.

Quantitative structure-activity relationships of selective antagonists of glucagon receptor using QuaSAR descriptors.

PubMed

Manoj Kumar, Palanivelu; Karthikeyan, Chandrabose; Hari Narayana Moorthy, Narayana Subbiah; Trivedi, Piyush

2006-11-01

In the present paper, quantitative structure activity relationship (QSAR) approach was applied to understand the affinity and selectivity of a novel series of triaryl imidazole derivatives towards glucagon receptor. Statistically significant and highly predictive QSARs were derived for glucagon receptor inhibition by triaryl imidazoles using QuaSAR descriptors of molecular operating environment (MOE) employing computer-assisted multiple regression procedure. The generated QSAR models revealed that factors related to hydrophobicity, molecular shape and geometry predominantly influences glucagon receptor binding affinity of the triaryl imidazoles indicating the relevance of shape specific steric interactions between the molecule and the receptor. Further, QSAR models formulated for selective inhibition of glucagon receptor over p38 mitogen activated protein (MAP) kinase of the compounds in the series highlights that the same structural features, which influence the glucagon receptor affinity, also contribute to their selective inhibition.

A Nonrigid Kernel-Based Framework for 2D-3D Pose Estimation and 2D Image Segmentation

PubMed Central

Sandhu, Romeil; Dambreville, Samuel; Yezzi, Anthony; Tannenbaum, Allen

2013-01-01

In this work, we present a nonrigid approach to jointly solving the tasks of 2D-3D pose estimation and 2D image segmentation. In general, most frameworks that couple both pose estimation and segmentation assume that one has exact knowledge of the 3D object. However, under nonideal conditions, this assumption may be violated if only a general class to which a given shape belongs is given (e.g., cars, boats, or planes). Thus, we propose to solve the 2D-3D pose estimation and 2D image segmentation via nonlinear manifold learning of 3D embedded shapes for a general class of objects or deformations for which one may not be able to associate a skeleton model. Thus, the novelty of our method is threefold: First, we present and derive a gradient flow for the task of nonrigid pose estimation and segmentation. Second, due to the possible nonlinear structures of one’s training set, we evolve the preimage obtained through kernel PCA for the task of shape analysis. Third, we show that the derivation for shape weights is general. This allows us to use various kernels, as well as other statistical learning methodologies, with only minimal changes needing to be made to the overall shape evolution scheme. In contrast with other techniques, we approach the nonrigid problem, which is an infinite-dimensional task, with a finite-dimensional optimization scheme. More importantly, we do not explicitly need to know the interaction between various shapes such as that needed for skeleton models as this is done implicitly through shape learning. We provide experimental results on several challenging pose estimation and segmentation scenarios. PMID:20733218

Impact of Atmospheric Chromatic Effects on Weak Lensing Measurements

NASA Astrophysics Data System (ADS)

Meyers, Joshua E.; Burchat, Patricia R.

2015-07-01

Current and future imaging surveys will measure cosmic shear with statistical precision that demands a deeper understanding of potential systematic biases in galaxy shape measurements than has been achieved to date. We use analytic and computational techniques to study the impact on shape measurements of two atmospheric chromatic effects for ground-based surveys such as the Dark Energy Survey and the Large Synoptic Survey Telescope (LSST): (1) atmospheric differential chromatic refraction and (2) wavelength dependence of seeing. We investigate the effects of using the point-spread function (PSF) measured with stars to determine the shapes of galaxies that have different spectral energy distributions than the stars. We find that both chromatic effects lead to significant biases in galaxy shape measurements for current and future surveys, if not corrected. Using simulated galaxy images, we find a form of chromatic “model bias” that arises when fitting a galaxy image with a model that has been convolved with a stellar, instead of galactic, PSF. We show that both forms of atmospheric chromatic biases can be predicted (and corrected) with minimal model bias by applying an ordered set of perturbative PSF-level corrections based on machine-learning techniques applied to six-band photometry. Catalog-level corrections do not address the model bias. We conclude that achieving the ultimate precision for weak lensing from current and future ground-based imaging surveys requires a detailed understanding of the wavelength dependence of the PSF from the atmosphere, and from other sources such as optics and sensors. The source code for this analysis is available at https://github.com/DarkEnergyScienceCollaboration/chroma.

Phenotypic plasticity in haptoral structures of Ligophorus cephali (Monogenea: Dactylogyridae) on the flathead mullet (Mugil cephalus): a geometric morphometric approach.

PubMed

Rodríguez-González, Abril; Míguez-Lozano, Raúl; Llopis-Belenguer, Cristina; Balbuena, Juan Antonio

2015-04-01

Evaluating phenotypic plasticity in attachment organs of parasites can provide information on the capacity to colonise new hosts and illuminate evolutionary processes driving host specificity. We analysed the variability in shape and size of the dorsal and ventral anchors of Ligophorus cephali from Mugil cephalus by means of geometric morphometrics and multivariate statistics. We also assessed the morphological integration between anchors and between the roots and points in order to gain insight into their functional morphology. Dorsal and ventral anchors showed a similar gradient of overall shape variation, but the amount of localised changes was much higher in the former. Statistical models describing variations in shape and size revealed clear differences between anchors. The dorsal anchor/bar complex seems more mobile than the ventral one in Ligophorus, and these differences may reflect different functional roles in attachment to the gills. The lower residual variation associated with the ventral anchor models suggests a tighter control of their shape and size, perhaps because these anchors seem to be responsible for firmer attachment and their size and shape would allow more effective responses to characteristics of the microenvironment within the individual host. Despite these putative functional differences, the high level of morphological integration indicates a concerted action between anchors. In addition, we found a slight, although significant, morphological integration between roots and points in both anchors, which suggests that a large fraction of the observed phenotypic variation does not compromise the functional role of anchors as levers. Given the low level of genetic variation in our sample, it is likely that much of the morphological variation reflects host-driven plastic responses. This supports the hypothesis of monogenean specificity through host-switching and rapid speciation. The present study demonstrates the potential of geometric morphometrics to provide new and previously unexplored insights into the functional morphology of attachment and evolutionary processes of host-parasite coevolution. Copyright © 2015 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

Identifying irregularly shaped crime hot-spots using a multiobjective evolutionary algorithm

NASA Astrophysics Data System (ADS)

Wu, Xiaolan; Grubesic, Tony H.

2010-12-01

Spatial cluster detection techniques are widely used in criminology, geography, epidemiology, and other fields. In particular, spatial scan statistics are popular and efficient techniques for detecting areas of elevated crime or disease events. The majority of spatial scan approaches attempt to delineate geographic zones by evaluating the significance of clusters using likelihood ratio statistics tested with the Poisson distribution. While this can be effective, many scan statistics give preference to circular clusters, diminishing their ability to identify elongated and/or irregular shaped clusters. Although adjusting the shape of the scan window can mitigate some of these problems, both the significance of irregular clusters and their spatial structure must be accounted for in a meaningful way. This paper utilizes a multiobjective evolutionary algorithm to find clusters with maximum significance while quantitatively tracking their geographic structure. Crime data for the city of Cincinnati are utilized to demonstrate the advantages of the new approach and highlight its benefits versus more traditional scan statistics.

Stochastic modeling of sunshine number data

NASA Astrophysics Data System (ADS)

Brabec, Marek; Paulescu, Marius; Badescu, Viorel

2013-11-01

In this paper, we will present a unified statistical modeling framework for estimation and forecasting sunshine number (SSN) data. Sunshine number has been proposed earlier to describe sunshine time series in qualitative terms (Theor Appl Climatol 72 (2002) 127-136) and since then, it was shown to be useful not only for theoretical purposes but also for practical considerations, e.g. those related to the development of photovoltaic energy production. Statistical modeling and prediction of SSN as a binary time series has been challenging problem, however. Our statistical model for SSN time series is based on an underlying stochastic process formulation of Markov chain type. We will show how its transition probabilities can be efficiently estimated within logistic regression framework. In fact, our logistic Markovian model can be relatively easily fitted via maximum likelihood approach. This is optimal in many respects and it also enables us to use formalized statistical inference theory to obtain not only the point estimates of transition probabilities and their functions of interest, but also related uncertainties, as well as to test of various hypotheses of practical interest, etc. It is straightforward to deal with non-homogeneous transition probabilities in this framework. Very importantly from both physical and practical points of view, logistic Markov model class allows us to test hypotheses about how SSN dependents on various external covariates (e.g. elevation angle, solar time, etc.) and about details of the dynamic model (order and functional shape of the Markov kernel, etc.). Therefore, using generalized additive model approach (GAM), we can fit and compare models of various complexity which insist on keeping physical interpretation of the statistical model and its parts. After introducing the Markovian model and general approach for identification of its parameters, we will illustrate its use and performance on high resolution SSN data from the Solar Radiation Monitoring Station of the West University of Timisoara.

Stochastic modeling of sunshine number data

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

Brabec, Marek, E-mail: mbrabec@cs.cas.cz; Paulescu, Marius; Badescu, Viorel

2013-11-13

In this paper, we will present a unified statistical modeling framework for estimation and forecasting sunshine number (SSN) data. Sunshine number has been proposed earlier to describe sunshine time series in qualitative terms (Theor Appl Climatol 72 (2002) 127-136) and since then, it was shown to be useful not only for theoretical purposes but also for practical considerations, e.g. those related to the development of photovoltaic energy production. Statistical modeling and prediction of SSN as a binary time series has been challenging problem, however. Our statistical model for SSN time series is based on an underlying stochastic process formulation ofmore » Markov chain type. We will show how its transition probabilities can be efficiently estimated within logistic regression framework. In fact, our logistic Markovian model can be relatively easily fitted via maximum likelihood approach. This is optimal in many respects and it also enables us to use formalized statistical inference theory to obtain not only the point estimates of transition probabilities and their functions of interest, but also related uncertainties, as well as to test of various hypotheses of practical interest, etc. It is straightforward to deal with non-homogeneous transition probabilities in this framework. Very importantly from both physical and practical points of view, logistic Markov model class allows us to test hypotheses about how SSN dependents on various external covariates (e.g. elevation angle, solar time, etc.) and about details of the dynamic model (order and functional shape of the Markov kernel, etc.). Therefore, using generalized additive model approach (GAM), we can fit and compare models of various complexity which insist on keeping physical interpretation of the statistical model and its parts. After introducing the Markovian model and general approach for identification of its parameters, we will illustrate its use and performance on high resolution SSN data from the Solar Radiation Monitoring Station of the West University of Timisoara.« less

DAMIT: a database of asteroid models

NASA Astrophysics Data System (ADS)

Durech, J.; Sidorin, V.; Kaasalainen, M.

2010-04-01

Context. Apart from a few targets that were directly imaged by spacecraft, remote sensing techniques are the main source of information about the basic physical properties of asteroids, such as the size, the spin state, or the spectral type. The most widely used observing technique - time-resolved photometry - provides us with data that can be used for deriving asteroid shapes and spin states. In the past decade, inversion of asteroid lightcurves has led to more than a hundred asteroid models. In the next decade, when data from all-sky surveys are available, the number of asteroid models will increase. Combining photometry with, e.g., adaptive optics data produces more detailed models. Aims: We created the Database of Asteroid Models from Inversion Techniques (DAMIT) with the aim of providing the astronomical community access to reliable and up-to-date physical models of asteroids - i.e., their shapes, rotation periods, and spin axis directions. Models from DAMIT can be used for further detailed studies of individual objects, as well as for statistical studies of the whole set. Methods: Most DAMIT models were derived from photometric data by the lightcurve inversion method. Some of them have been further refined or scaled using adaptive optics images, infrared observations, or occultation data. A substantial number of the models were derived also using sparse photometric data from astrometric databases. Results: At present, the database contains models of more than one hundred asteroids. For each asteroid, DAMIT provides the polyhedral shape model, the sidereal rotation period, the spin axis direction, and the photometric data used for the inversion. The database is updated when new models are available or when already published models are updated or refined. We have also released the C source code for the lightcurve inversion and for the direct problem (updates and extensions will follow).

Ontogenetic scaling of caudal fin shape in Squalus acanthias (Chondrichthyes, Elasmobranchii): a geometric morphometric analysis with implications for caudal fin functional morphology.

PubMed

Reiss, Katie L; Bonnan, Matthew F

2010-07-01

The shark heterocercal caudal fin and its contribution to locomotion are of interest to biologists and paleontologists. Current hydrodynamic data show that the stiff dorsal lobe leads the ventral lobe, both lobes of the tail are synchronized during propulsion, and tail shape reflects its overall locomotor function. Given the difficulties surrounding the analysis of shark caudal fins in vivo, little is known about changes in tail shape related to ontogeny and sex in sharks. A quantifiable analysis of caudal fin shape may provide an acceptable proxy for inferring gross functional morphology where direct testing is difficult or impossible. We examined ontogenetic and sex-related shape changes in the caudal fins of 115 Squalus acanthias museum specimens, to test the hypothesis that significant shape changes in the caudal fin shape occur with increasing size and between the sexes. Using linear and geometric morphometrics, we examined caudal shape changes within the context of current hydrodynamic models. We found no statistically significant linear or shape difference between sexes, and near-isometric scaling trends for caudal dimensions. These results suggest that lift and thrust increase linearly with size and caudal span. Thin-plate splines results showed a significant allometric shape change associated with size and caudal span: the dorsal lobe elongates and narrows, whereas the ventral lobe broadens and expands ventrally. Our data suggest a combination of caudal fin morphology with other body morphology aspects, would refine, and better elucidate the hydrodynamic factors (if any) that underlie the significant shape changes we report here for S. acanthias.

Planning of skull reconstruction based on a statistical shape model combined with geometric morphometrics.

PubMed

Fuessinger, Marc Anton; Schwarz, Steffen; Cornelius, Carl-Peter; Metzger, Marc Christian; Ellis, Edward; Probst, Florian; Semper-Hogg, Wiebke; Gass, Mathieu; Schlager, Stefan

2018-04-01

Virtual reconstruction of large cranial defects is still a challenging task. The current reconstruction procedures depend on the surgeon's experience and skills in planning the reconstruction based on mirroring and manual adaptation. The aim of this study is to propose and evaluate a computer-based approach employing a statistical shape model (SSM) of the cranial vault. An SSM was created based on 131 CT scans of pathologically unaffected adult crania. After segmentation, the resulting surface mesh of one patient was established as template and subsequently registered to the entire sample. Using the registered surface meshes, an SSM was generated capturing the shape variability of the cranial vault. The knowledge about this shape variation in healthy patients was used to estimate the missing parts. The accuracy of the reconstruction was evaluated by using 31 CT scans not included in the SSM. Both unilateral and bilateral bony defects were created on each skull. The reconstruction was performed using the current gold standard of mirroring the intact to the affected side, and the result was compared to the outcome of our proposed SSM-driven method. The accuracy of the reconstruction was determined by calculating the distances to the corresponding parts on the intact skull. While unilateral defects could be reconstructed with both methods, the reconstruction of bilateral defects was, for obvious reasons, only possible employing the SSM-based method. Comparing all groups, the analysis shows a significantly higher precision of the SSM group, with a mean error of 0.47 mm compared to the mirroring group which exhibited a mean error of 1.13 mm. Reconstructions of bilateral defects yielded only slightly higher estimation errors than those of unilateral defects. The presented computer-based approach using SSM is a precise and simple tool in the field of computer-assisted surgery. It helps to reconstruct large-size defects of the skull considering the natural asymmetry of the cranium and is not limited to unilateral defects.

Blood pressure indices and cardiovascular disease mortality in persons with or without diabetes mellitus.

PubMed

Gomadam, Pallavi; Shah, Amit; Qureshi, Waqas; Yeboah, Phyllis N; Freedman, Barry I; Bowden, Donald; Soliman, Elsayed Z; Yeboah, Joseph

2018-01-01

We examined the associations between blood pressure indices (SBP, DBP, mean arterial pressure and pulse pressure) and cardiovascular disease (CVD) mortality among persons with or without diabetes mellitus (NON-DM) in a multiethnic cohort. We included 17 650 participants from National Health and Nutrition Examination Survey III and 1439 participants from Diabetes Heart Study (total n = 19 089, 16.3% had diabetes mellitus, mean age 48.5 years, 44.4% white, 27.1% black, 28.5% other race, 54.4% women). Cox proportional hazard, cubic spline and area under the curve analyses were used to assess the associations. CVD death was ascertained via social security registry or the National Death Index. After a mean (SD) of 16.2 (6.1) years of follow-up, 17.9% of diabetes mellitus and 8.8% of those NON-DM died of CVD. Diabetes mellitus was associated with an increased risk of CVD death [hazard ratio (95% confidence interval): 1.50 (1.25-1.82)]. One SD increase in SBP was significantly associated with CVD mortality in NON-DM [1.28 (1.18-1.39)] but not diabetes mellitus [1.04 (0.88-1.23)] in the full Cox models. Adjusted cubic spline analysis showed significant nonlinear but different association between SBP and CVD mortality among diabetes mellitus (U-shaped) and NON-DM (J-shaped). The C-statistics of our full model in NON-DM and diabetes mellitus were (0.888 vs. 0.735, P < 0.001). SBP showed a trend toward improving C statistics in NON-DM but not diabetes mellitus. The association between SBP and CVD mortality risk is nonlinear but different in diabetes mellitus (U-shaped) and NON-DM (J-shaped), explaining why aggressive blood pressure lowering may have different outcomes in these two groups.

Statistical and dynamical modeling of heavy-ion fusion-fission reactions

NASA Astrophysics Data System (ADS)

Eslamizadeh, H.; Razazzadeh, H.

2018-02-01

A modified statistical model and a four dimensional dynamical model based on Langevin equations have been used to simulate the fission process of the excited compound nuclei 207At and 216Ra produced in the fusion 19F + 188Os and 19F + 197Au reactions. The evaporation residue cross section, the fission cross section, the pre-scission neutron, proton and alpha multiplicities and the anisotropy of fission fragments angular distribution have been calculated for the excited compound nuclei 207At and 216Ra. In the modified statistical model the effects of spin K about the symmetry axis and temperature have been considered in calculations of the fission widths and the potential energy surfaces. It was shown that the modified statistical model can reproduce the above mentioned experimental data by using appropriate values of the temperature coefficient of the effective potential equal to λ = 0.0180 ± 0.0055, 0.0080 ± 0.0030 MeV-2 and the scaling factor of the fission barrier height equal to rs = 1.0015 ± 0.0025, 1.0040 ± 0.0020 for the compound nuclei 207At and 216Ra, respectively. Three collective shape coordinates plus the projection of total spin of the compound nucleus on the symmetry axis, K, were considered in the four dimensional dynamical model. In the dynamical calculations, dissipation was generated through the chaos weighted wall and window friction formula. Comparison of the theoretical results with the experimental data showed that two models make it possible to reproduce satisfactorily the above mentioned experimental data for the excited compound nuclei 207At and 216Ra.

Experimental and numerical investigation into the behavior of shape memory alloys

NASA Astrophysics Data System (ADS)

Philander, Oscar; Oliver, Graeme John; Sun, Bohua

2012-11-01

Research and development of smart alignment systems is currently being undertaken at the Smart Devices and MEMS Laboratory at the Cape Peninsula University of Technology. The intended devices will harness the remarkable phenomena of shape memory alloys (SMAs), i.e. the shape memory effect and pseudo-elasticity, for actuation purposes. These unique characteristics of shape memory alloy behavior results from an austenitic ⇔ martensitic phase transformation during heating or cooling and/or a de-twinning of the martensitic variants due to an applied load. This paper investigates the microscopic and macroscopic behavior of SMA wires and uses the dynamic one-dimensional thermodynamic and statistical thermodynamic constitutive model proposed by Müller and Achenbach and further refined by Müller and Seelecke in the design of SMA line actuators. This model permits the simulation of the response of a tensile specimen to a thermodynamic input and calculates all phase transformations, phase proportions and deformations as functions of time if the temperature and applied load are prescribed as functions of time. The aim of this research is to develop an understanding of the numerical model and its implementation in the design of SMA line actuators. Specific results should show response time of a given length of SMA wire subjected to an applied load and temperature increase, and the load - displacement relationships for both quasi-plastic and pseudo-elastic behaviors. This paper also introduces some of the devices currently under investigation by the Smart Alignment Systems Research Group.

Random bursts determine dynamics of active filaments.

PubMed

Weber, Christoph A; Suzuki, Ryo; Schaller, Volker; Aranson, Igor S; Bausch, Andreas R; Frey, Erwin

2015-08-25

Constituents of living or synthetic active matter have access to a local energy supply that serves to keep the system out of thermal equilibrium. The statistical properties of such fluctuating active systems differ from those of their equilibrium counterparts. Using the actin filament gliding assay as a model, we studied how nonthermal distributions emerge in active matter. We found that the basic mechanism involves the interplay between local and random injection of energy, acting as an analog of a thermal heat bath, and nonequilibrium energy dissipation processes associated with sudden jump-like changes in the system's dynamic variables. We show here how such a mechanism leads to a nonthermal distribution of filament curvatures with a non-Gaussian shape. The experimental curvature statistics and filament relaxation dynamics are reproduced quantitatively by stochastic computer simulations and a simple kinetic model.

Random bursts determine dynamics of active filaments

PubMed Central

Weber, Christoph A.; Suzuki, Ryo; Schaller, Volker; Aranson, Igor S.; Bausch, Andreas R.; Frey, Erwin

2015-01-01

Constituents of living or synthetic active matter have access to a local energy supply that serves to keep the system out of thermal equilibrium. The statistical properties of such fluctuating active systems differ from those of their equilibrium counterparts. Using the actin filament gliding assay as a model, we studied how nonthermal distributions emerge in active matter. We found that the basic mechanism involves the interplay between local and random injection of energy, acting as an analog of a thermal heat bath, and nonequilibrium energy dissipation processes associated with sudden jump-like changes in the system’s dynamic variables. We show here how such a mechanism leads to a nonthermal distribution of filament curvatures with a non-Gaussian shape. The experimental curvature statistics and filament relaxation dynamics are reproduced quantitatively by stochastic computer simulations and a simple kinetic model. PMID:26261319

Statistical multi-path exposure method for assessing the whole-body SAR in a heterogeneous human body model in a realistic environment.

PubMed

Vermeeren, Günter; Joseph, Wout; Martens, Luc

2013-04-01

Assessing the whole-body absorption in a human in a realistic environment requires a statistical approach covering all possible exposure situations. This article describes the development of a statistical multi-path exposure method for heterogeneous realistic human body models. The method is applied for the 6-year-old Virtual Family boy (VFB) exposed to the GSM downlink at 950 MHz. It is shown that the whole-body SAR does not differ significantly over the different environments at an operating frequency of 950 MHz. Furthermore, the whole-body SAR in the VFB for multi-path exposure exceeds the whole-body SAR for worst-case single-incident plane wave exposure by 3.6%. Moreover, the ICNIRP reference levels are not conservative with the basic restrictions in 0.3% of the exposure samples for the VFB at the GSM downlink of 950 MHz. The homogeneous spheroid with the dielectric properties of the head suggested by the IEC underestimates the absorption compared to realistic human body models. Moreover, the variation in the whole-body SAR for realistic human body models is larger than for homogeneous spheroid models. This is mainly due to the heterogeneity of the tissues and the irregular shape of the realistic human body model compared to homogeneous spheroid human body models. Copyright © 2012 Wiley Periodicals, Inc.

Learning-based stochastic object models for use in optimizing imaging systems

NASA Astrophysics Data System (ADS)

Dolly, Steven R.; Anastasio, Mark A.; Yu, Lifeng; Li, Hua

2017-03-01

It is widely known that the optimization of imaging systems based on objective, or task-based, measures of image quality via computer-simulation requires use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in anatomy within a specified ensemble of patients remains a challenging task. Because they are established by use of image data corresponding a single patient, previously reported numerical anatomical models lack of the ability to accurately model inter- patient variations in anatomy. In certain applications, however, databases of high-quality volumetric images are available that can facilitate this task. In this work, a novel and tractable methodology for learning a SOM from a set of volumetric training images is developed. The proposed method is based upon geometric attribute distribution (GAD) models, which characterize the inter-structural centroid variations and the intra-structural shape variations of each individual anatomical structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations learned from training data. By use of the GAD models, random organ shapes and positions can be generated and integrated to form an anatomical phantom. The randomness in organ shape and position will reflect the variability of anatomy present in the training data. To demonstrate the methodology, a SOM corresponding to the pelvis of an adult male was computed and a corresponding ensemble of phantoms was created. Additionally, computer-simulated X-ray projection images corresponding to the phantoms were computed, from which tomographic images were reconstructed.

Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation

NASA Astrophysics Data System (ADS)

Urata, Kengo; Inoue, Masaki; Murayama, Dai; Adachi, Shuichi

2016-09-01

We propose a statistical modeling method of wind power output for very short-term prediction. The modeling method with a nonlinear model has cascade structure composed of two parts. One is a linear dynamic part that is driven by a Gaussian white noise and described by an autoregressive model. The other is a nonlinear static part that is driven by the output of the linear part. This nonlinear part is designed for output distribution matching: we shape the distribution of the model output to match with that of the wind power output. The constructed model is utilized for one-step ahead prediction of the wind power output. Furthermore, we study the relation between the prediction accuracy and the prediction horizon.

THE TEMPORAL AND SPECTRAL CHARACTERISTICS OF 'FAST RISE AND EXPONENTIAL DECAY' GAMMA-RAY BURST PULSES

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

Peng, Z. Y.; Ma, L.; Yin, Y.

2010-08-01

In this paper, we have analyzed the temporal and spectral behavior of 52 fast rise and exponential decay (FRED) pulses in 48 long-duration gamma-ray bursts (GRBs) observed by the CGRO/BATSE, using a pulse model with two shape parameters and the Band model with three shape parameters, respectively. It is found that these FRED pulses are distinguished both temporally and spectrally from those in the long-lag pulses. In contrast to the long-lag pulses, only one parameter pair indicates an evident correlation among the five parameters, which suggests that at least four parameters are needed to model burst temporal and spectral behavior.more » In addition, our studies reveal that these FRED pulses have the following correlated properties: (1) long-duration pulses have harder spectra and are less luminous than short-duration pulses and (2) the more asymmetric the pulses are, the steeper are the evolutionary curves of the peak energy (E{sub p}) in the {nu}f{sub {nu}} spectrum within the pulse decay phase. Our statistical results give some constraints on the current GRB models.« less

Multi-Scale Surface Descriptors

PubMed Central

Cipriano, Gregory; Phillips, George N.; Gleicher, Michael

2010-01-01

Local shape descriptors compactly characterize regions of a surface, and have been applied to tasks in visualization, shape matching, and analysis. Classically, curvature has be used as a shape descriptor; however, this differential property characterizes only an infinitesimal neighborhood. In this paper, we provide shape descriptors for surface meshes designed to be multi-scale, that is, capable of characterizing regions of varying size. These descriptors capture statistically the shape of a neighborhood around a central point by fitting a quadratic surface. They therefore mimic differential curvature, are efficient to compute, and encode anisotropy. We show how simple variants of mesh operations can be used to compute the descriptors without resorting to expensive parameterizations, and additionally provide a statistical approximation for reduced computational cost. We show how these descriptors apply to a number of uses in visualization, analysis, and matching of surfaces, particularly to tasks in protein surface analysis. PMID:19834190

Body shape analyses of large persons in South Korea.

PubMed

Park, Woojin; Park, Sungjoon

2013-01-01

Despite the prevalence of obesity and overweight, anthropometric characteristics of large individuals have not been extensively studied. This study investigated body shapes of large persons (Broca index ≥ 20, BMI ≥ 25 or WHR>1.0) using stature-normalised body dimensions data from the latest South Korean anthropometric survey. For each sex, a factor analysis was performed on the anthropometric data set to identify the key factors that explain the shape variability; and then, a cluster analysis was conducted on the factor scores data to determine a set of representative body types. The body types were labelled in terms of their distinct shape characteristics and their relative frequencies were computed for each of the four age groups considered: the 10s, 20s-30s, 40s-50s and 60s. The study findings may facilitate creating artefacts that anthropometrically accommodate large individuals, developing digital human models of large persons and designing future ergonomics studies on largeness. This study investigated body shapes of large persons using anthropometric data from South Korea. For each sex, multivariate statistical analyses were conducted to identify the key factors of the body shape variability and determine the representative body types. The study findings may facilitate designing artefacts that anthropometrically accommodate large persons.

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

Nose, Y.

The goal of the present program is to define the spatial constraints of the body for a totally implantable radioisotope-powered cardiac prosthesis. The design is such that the prosthesis is compatib1e with both the human and the experimental animal, the calf. Most recent efforts were directed to the definition of the size and shape of the human thorax for implanting the blood pump. This was done by formulating a mathematical shape model from dimensions obtained from plastic molds made in the chest cavity of human cadavers. The shape model was used in conjunction with dimensions obtained from 100 chest radiographsmore » of living humans to arrive at a statistical distribution of chest dimensions. The results are presented as scale drawings of the walls of the thorax as a iunction of the percent of the population having sizes smaller than the given curves. An effort is underway to define the natural heart boundaries in the chest to define soft tissue and vascular connections in the thorax. A parallel effort was to determine the anatomical and physiological tolerance of calves to implanted models of the thermal conventer. Five calves were implanted with models, four have been sacrificed at 8 to 12 months after implantation, and one remains under observation. All calves were in good physical condition with the retroperitoneal infrarenal space appearing to be most feasible for implantation. (auth)« less

Rigorous Results for the Distribution of Money on Connected Graphs

NASA Astrophysics Data System (ADS)

Lanchier, Nicolas; Reed, Stephanie

2018-05-01

This paper is concerned with general spatially explicit versions of three stochastic models for the dynamics of money that have been introduced and studied numerically by statistical physicists: the uniform reshuffling model, the immediate exchange model and the model with saving propensity. All three models consist of systems of economical agents that consecutively engage in pairwise monetary transactions. Computer simulations performed in the physics literature suggest that, when the number of agents and the average amount of money per agent are large, the limiting distribution of money as time goes to infinity approaches the exponential distribution for the first model, the gamma distribution with shape parameter two for the second model and a distribution similar but not exactly equal to a gamma distribution whose shape parameter depends on the saving propensity for the third model. The main objective of this paper is to give rigorous proofs of these conjectures and also extend these conjectures to generalizations of the first two models and a variant of the third model that include local rather than global interactions, i.e., instead of choosing the two interacting agents uniformly at random from the system, the agents are located on the vertex set of a general connected graph and can only interact with their neighbors.

A statistical investigation of the mass discrepancy-acceleration relation

NASA Astrophysics Data System (ADS)

Desmond, Harry

2017-02-01

We use the mass discrepancy-acceleration relation (the correlation between the ratio of total-to-visible mass and acceleration in galaxies; MDAR) to test the galaxy-halo connection. We analyse the MDAR using a set of 16 statistics that quantify its four most important features: shape, scatter, the presence of a `characteristic acceleration scale', and the correlation of its residuals with other galaxy properties. We construct an empirical framework for the galaxy-halo connection in LCDM to generate predictions for these statistics, starting with conventional correlations (halo abundance matching; AM) and introducing more where required. Comparing to the SPARC data, we find that: (1) the approximate shape of the MDAR is readily reproduced by AM, and there is no evidence that the acceleration at which dark matter becomes negligible has less spread in the data than in AM mocks; (2) even under conservative assumptions, AM significantly overpredicts the scatter in the relation and its normalization at low acceleration, and furthermore positions dark matter too close to galaxies' centres on average; (3) the MDAR affords 2σ evidence for an anticorrelation of galaxy size and Hubble type with halo mass or concentration at fixed stellar mass. Our analysis lays the groundwork for a bottom-up determination of the galaxy-halo connection from relations such as the MDAR, provides concrete statistical tests for specific galaxy formation models, and brings into sharper focus the relative evidence accorded by galaxy kinematics to LCDM and modified gravity alternatives.

A statistical investigation of the mass discrepancy–acceleration relation

DOE PAGES

Desmond, Harry

2016-10-08

We use the mass discrepancy–acceleration relation (the correlation between the ratio of total-to-visible mass and acceleration in galaxies; MDAR) to test the galaxy–halo connection. Here, we analyse the MDAR using a set of 16 statistics that quantify its four most important features: shape, scatter, the presence of a ‘characteristic acceleration scale’, and the correlation of its residuals with other galaxy properties. We construct an empirical framework for the galaxy–halo connection in LCDM to generate predictions for these statistics, starting with conventional correlations (halo abundance matching; AM) and introducing more where required. Comparing to the SPARC data, we find that: (1)more » the approximate shape of the MDAR is readily reproduced by AM, and there is no evidence that the acceleration at which dark matter becomes negligible has less spread in the data than in AM mocks; (2) even under conservative assumptions, AM significantly overpredicts the scatter in the relation and its normalization at low acceleration, and furthermore positions dark matter too close to galaxies’ centres on average; (3) the MDAR affords 2σ evidence for an anticorrelation of galaxy size and Hubble type with halo mass or concentration at fixed stellar mass. Lastly, our analysis lays the groundwork for a bottom-up determination of the galaxy–halo connection from relations such as the MDAR, provides concrete statistical tests for specific galaxy formation models, and brings into sharper focus the relative evidence accorded by galaxy kinematics to LCDM and modified gravity alternatives.« less

WE-G-BRD-04: BEST IN PHYSICS (JOINT IMAGING-THERAPY): An Integrated Model-Based Intrafractional Organ Motion Tracking Approach with Dynamic MRI in Head and Neck Radiotherapy

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

Chen, H; Dolly, S; Anastasio, M

Purpose: In-treatment dynamic cine images, provided by the first commercially available MRI-guided radiotherapy system, allow physicians to observe intrafractional motion of head and neck (H&N) internal structures. Nevertheless, high anatomical complexity and relatively poor cine image contrast/resolution have complicated automatic intrafractional motion evaluation. We proposed an integrated model-based approach to automatically delineate and analyze moving structures from on-board cine images. Methods: The H&N upper airway, a complex and highly deformable region wherein severe internal motion often occurs, was selected as the target-to-be-tracked. To reliably capture its motion, a hierarchical structure model containing three statistical shapes (face, face-jaw, and face-jaw-palate) wasmore » first built from a set of manually delineated shapes using principal component analysis. An integrated model-fitting algorithm was then employed to align the statistical shapes to the first to-be-detected cine frame, and multi-feature level-set contour propagation was performed to identify the airway shape change in the remaining frames. Ninety sagittal cine MR image sets, acquired from three H&N cancer patients, were utilized to demonstrate this approach. Results: The tracking accuracy was validated by comparing the results to the average of two manual delineations in 20 randomly selected images from each patient. The resulting dice similarity coefficient (93.28+/−1.46 %) and margin error (0.49+/−0.12 mm) showed good agreement with the manual results. Intrafractional displacements of anterior, posterior, inferior, and superior airway boundaries were observed, with values of 2.62+/−2.92, 1.78+/−1.43, 3.51+/−3.99, and 0.68+/−0.89 mm, respectively. The H&N airway motion was found to vary across directions, fractions, and patients, and highly correlated with patients’ respiratory frequency. Conclusion: We proposed the integrated computational approach, which for the first time allows to automatically identify the H&N upper airway and quantify in-treatment H&N internal motion in real-time. This approach can be applied to track other structures’ motion, and provide guidance on patient-specific prediction of intra-/inter-fractional structure displacements.« less

Problematizing Statistical Literacy: An Intersection of Critical and Statistical Literacies

ERIC Educational Resources Information Center

Weiland, Travis

2017-01-01

In this paper, I problematize traditional notions of statistical literacy by juxtaposing it with critical literacy. At the school level statistical literacy is vitally important for students who are preparing to become citizens in modern societies that are increasingly shaped and driven by data based arguments. The teaching of statistics, which is…

Real-Time Ultrasound Segmentation, Analysis and Visualisation of Deep Cervical Muscle Structure.

PubMed

Cunningham, Ryan J; Harding, Peter J; Loram, Ian D

2017-02-01

Despite widespread availability of ultrasound and a need for personalised muscle diagnosis (neck/back pain-injury, work related disorder, myopathies, neuropathies), robust, online segmentation of muscles within complex groups remains unsolved by existing methods. For example, Cervical Dystonia (CD) is a prevalent neurological condition causing painful spasticity in one or multiple muscles in the cervical muscle system. Clinicians currently have no method for targeting/monitoring treatment of deep muscles. Automated methods of muscle segmentation would enable clinicians to study, target, and monitor the deep cervical muscles via ultrasound. We have developed a method for segmenting five bilateral cervical muscles and the spine via ultrasound alone, in real-time. Magnetic Resonance Imaging (MRI) and ultrasound data were collected from 22 participants (age: 29.0±6.6, male: 12). To acquire ultrasound muscle segment labels, a novel multimodal registration method was developed, involving MRI image annotation, and shape registration to MRI-matched ultrasound images, via approximation of the tissue deformation. We then applied polynomial regression to transform our annotations and textures into a mean space, before using shape statistics to generate a texture-to-shape dictionary. For segmentation, test images were compared to dictionary textures giving an initial segmentation, and then we used a customized Active Shape Model to refine the fit. Using ultrasound alone, on unseen participants, our technique currently segments a single image in [Formula: see text] to over 86% accuracy (Jaccard index). We propose this approach is applicable generally to segment, extrapolate and visualise deep muscle structure, and analyse statistical features online.

Restoration of the Patient-Specific Anatomy of the Proximal and Distal Parts of the Humerus: Statistical Shape Modeling Versus Contralateral Registration Method.

PubMed

Vlachopoulos, Lazaros; Lüthi, Marcel; Carrillo, Fabio; Gerber, Christian; Székely, Gábor; Fürnstahl, Philipp

2018-04-18

In computer-assisted reconstructive surgeries, the contralateral anatomy is established as the best available reconstruction template. However, existing intra-individual bilateral differences or a pathological, contralateral humerus may limit the applicability of the method. The aim of the study was to evaluate whether a statistical shape model (SSM) has the potential to predict accurately the pretraumatic anatomy of the humerus from the posttraumatic condition. Three-dimensional (3D) triangular surface models were extracted from the computed tomographic data of 100 paired cadaveric humeri without a pathological condition. An SSM was constructed, encoding the characteristic shape variations among the individuals. To predict the patient-specific anatomy of the proximal (or distal) part of the humerus with the SSM, we generated segments of the humerus of predefined length excluding the part to predict. The proximal and distal humeral prediction (p-HP and d-HP) errors, defined as the deviation of the predicted (bone) model from the original (bone) model, were evaluated. For comparison with the state-of-the-art technique, i.e., the contralateral registration method, we used the same segments of the humerus to evaluate whether the SSM or the contralateral anatomy yields a more accurate reconstruction template. The p-HP error (mean and standard deviation, 3.8° ± 1.9°) using 85% of the distal end of the humerus to predict the proximal humeral anatomy was significantly smaller (p = 0.001) compared with the contralateral registration method. The difference between the d-HP error (mean, 5.5° ± 2.9°), using 85% of the proximal part of the humerus to predict the distal humeral anatomy, and the contralateral registration method was not significant (p = 0.61). The restoration of the humeral length was not significantly different between the SSM and the contralateral registration method. SSMs accurately predict the patient-specific anatomy of the proximal and distal aspects of the humerus. The prediction errors of the SSM depend on the size of the healthy part of the humerus. The prediction of the patient-specific anatomy of the humerus is of fundamental importance for computer-assisted reconstructive surgeries.

Automated Identification and Shape Analysis of Chorus Elements in the Van Allen Radiation Belts

NASA Astrophysics Data System (ADS)

Sen Gupta, Ananya; Kletzing, Craig; Howk, Robin; Kurth, William; Matheny, Morgan

2017-12-01

An important goal of the Van Allen Probes mission is to understand wave-particle interaction by chorus emissions in terrestrial Van Allen radiation belts. To test models, statistical characterization of chorus properties, such as amplitude variation and sweep rates, is an important scientific goal. The Electric and Magnetic Field Instrument Suite and Integrated Science (EMFISIS) instrumentation suite provides measurements of wave electric and magnetic fields as well as DC magnetic fields for the Van Allen Probes mission. However, manual inspection across terabytes of EMFISIS data is not feasible and as such introduces human confirmation bias. We present signal processing techniques for automated identification, shape analysis, and sweep rate characterization of high-amplitude whistler-mode chorus elements in the Van Allen radiation belts. Specifically, we develop signal processing techniques based on the radon transform that disambiguate chorus elements with a dominant sweep rate against hiss-like chorus. We present representative results validating our techniques and also provide statistical characterization of detected chorus elements across a case study of a 6 s epoch.

Statistical analysis of the ambiguities in the asteroid period determinations

NASA Astrophysics Data System (ADS)

Butkiewicz-Bąk, M.; Kwiatkowski, T.; Bartczak, P.; Dudziński, G.; Marciniak, A.

2017-09-01

Among asteroids there exist ambiguities in their rotation period determinations. They are due to incomplete coverage of the rotation, noise and/or aliases resulting from gaps between separate lightcurves. To help to remove such uncertainties, basic characteristic of the lightcurves resulting from constraints imposed by the asteroid shapes and geometries of observations should be identified. We simulated light variations of asteroids whose shapes were modelled as Gaussian random spheres, with random orientations of spin vectors and phase angles changed every 5° from 0° to 65°. This produced 1.4 million lightcurves. For each simulated lightcurve, Fourier analysis has been made and the harmonic of the highest amplitude was recorded. From the statistical point of view, all lightcurves observed at phase angles α < 30°, with peak-to-peak amplitudes A > 0.2 mag, are bimodal. Second most frequently dominating harmonic is the first one, with the 3rd harmonic following right after. For 1 per cent of lightcurves with amplitudes A < 0.1 mag and phase angles α < 40°, 4th harmonic dominates.

Binary Programming Models of Spatial Pattern Recognition: Applications in Remote Sensing Image Analysis

DTIC Science & Technology

1991-12-01

9 2.6.1 Multi-Shape Detection. .. .. .. .. .. .. ...... 9 Page 2.6.2 Line Segment Extraction and Re-Combination.. 9 2.6.3 Planimetric Feature... Extraction ............... 10 2.6.4 Line Segment Extraction From Statistical Texture Analysis .............................. 11 2.6.5 Edge Following as Graph...image after image, could benefit clue to the fact that major spatial characteristics of subregions could be extracted , and minor spatial changes could be

Neutral Evolution of Duplicated DNA: An Evolutionary Stick-Breaking Process Causes Scale-Invariant Behavior

NASA Astrophysics Data System (ADS)

Massip, Florian; Arndt, Peter F.

2013-04-01

Recently, an enrichment of identical matching sequences has been found in many eukaryotic genomes. Their length distribution exhibits a power law tail raising the question of what evolutionary mechanism or functional constraints would be able to shape this distribution. Here we introduce a simple and evolutionarily neutral model, which involves only point mutations and segmental duplications, and produces the same statistical features as observed for genomic data. Further, we extend a mathematical model for random stick breaking to analytically show that the exponent of the power law tail is -3 and universal as it does not depend on the microscopic details of the model.

Global MHD Simulations of the Earth's Bow Shock Shape and Motion Under Variable Solar Wind Conditions

NASA Astrophysics Data System (ADS)

Mejnertsen, L.; Eastwood, J. P.; Hietala, H.; Schwartz, S. J.; Chittenden, J. P.

2018-01-01

Empirical models of the Earth's bow shock are often used to place in situ measurements in context and to understand the global behavior of the foreshock/bow shock system. They are derived statistically from spacecraft bow shock crossings and typically treat the shock surface as a conic section parameterized according to a uniform solar wind ram pressure, although more complex models exist. Here a global magnetohydrodynamic simulation is used to analyze the variability of the Earth's bow shock under real solar wind conditions. The shape and location of the bow shock is found as a function of time, and this is used to calculate the shock velocity over the shock surface. The results are compared to existing empirical models. Good agreement is found in the variability of the subsolar shock location. However, empirical models fail to reproduce the two-dimensional shape of the shock in the simulation. This is because significant solar wind variability occurs on timescales less than the transit time of a single solar wind phase front over the curved shock surface. Empirical models must therefore be used with care when interpreting spacecraft data, especially when observations are made far from the Sun-Earth line. Further analysis reveals a bias to higher shock speeds when measured by virtual spacecraft. This is attributed to the fact that the spacecraft only observes the shock when it is in motion. This must be accounted for when studying bow shock motion and variability with spacecraft data.

A Global Fitting Approach For Doppler Broadening Thermometry

NASA Astrophysics Data System (ADS)

Amodio, Pasquale; Moretti, Luigi; De Vizia, Maria Domenica; Gianfrani, Livio

2014-06-01

Very recently, a spectroscopic determination of the Boltzmann constant, kB, has been performed at the Second University of Naples by means of a rather sophisticated implementation of Doppler Broadening Thermometry (DBT)1. Performed on a 18O-enriched water sample, at a wavelength of 1.39 µm, the experiment has provided a value for kB with a combined uncertainty of 24 parts over 106, which is the best result obtained so far, by using an optical method. In the spectral analysis procedure, the partially correlated speed-dependent hard-collision (pC-SDHC) model was adopted. The uncertainty budget has clearly revealed that the major contributions come from the statistical uncertainty (type A) and from the uncertainty associated to the line-shape model (type B)2. In the present work, we present the first results of a theoretical and numerical work aimed at reducing these uncertainty components. It is well known that molecular line shapes exhibit clear deviations from the time honoured Voigt profile. Even in the case of a well isolated spectral line, under the influence of binary collisions, in the Doppler regime, the shape can be quite complicated by the joint occurrence of velocity-change collisions and speed-dependent effects. The partially correlated speed-dependent Keilson-Storer profile (pC-SDKS) has been recently proposed as a very realistic model, capable of reproducing very accurately the absorption spectra for self-colliding water molecules, in the near infrared3. Unfortunately, the model is so complex that it cannot be implemented into a fitting routine for the analysis of experimental spectra. Therefore, we have developed a MATLAB code to simulate a variety of H218O spectra in thermodynamic conditions identical to the one of our DBT experiment, using the pC-SDKS model. The numerical calculations to determine such a profile have a very large computational cost, resulting from a very sophisticated iterative procedure. Hence, the numerically simulated spectra (with the addition of random noise) have been used to test the validity of simplified line shape models, such as the speed-dependent Galatry (SDG) profile and pC-SDHC model. In particular, we have used the global fitting procedure that is described in Amodio et al4. Such a procedure is very effective in reducing the uncertainty resulting from statistical correlation among free parameters. Therefore, the analysis of large amounts of simulated spectra has allowed us to study the influence of the choice of the model and quantify the achievable precision and accuracy levels, at the present value of the signal-to-noise ratio. freely redistributable under the GPL http://www.gnu.org.

Design considerations and analysis planning of a phase 2a proof of concept study in rheumatoid arthritis in the presence of possible non-monotonicity.

PubMed

Liu, Feng; Walters, Stephen J; Julious, Steven A

2017-10-02

It is important to quantify the dose response for a drug in phase 2a clinical trials so the optimal doses can then be selected for subsequent late phase trials. In a phase 2a clinical trial of new lead drug being developed for the treatment of rheumatoid arthritis (RA), a U-shaped dose response curve was observed. In the light of this result further research was undertaken to design an efficient phase 2a proof of concept (PoC) trial for a follow-on compound using the lessons learnt from the lead compound. The planned analysis for the Phase 2a trial for GSK123456 was a Bayesian Emax model which assumes the dose-response relationship follows a monotonic sigmoid "S" shaped curve. This model was found to be suboptimal to model the U-shaped dose response observed in the data from this trial and alternatives approaches were needed to be considered for the next compound for which a Normal dynamic linear model (NDLM) is proposed. This paper compares the statistical properties of the Bayesian Emax model and NDLM model and both models are evaluated using simulation in the context of adaptive Phase 2a PoC design under a variety of assumed dose response curves: linear, Emax model, U-shaped model, and flat response. It is shown that the NDLM method is flexible and can handle a wide variety of dose-responses, including monotonic and non-monotonic relationships. In comparison to the NDLM model the Emax model excelled with higher probability of selecting ED90 and smaller average sample size, when the true dose response followed Emax like curve. In addition, the type I error, probability of incorrectly concluding a drug may work when it does not, is inflated with the Bayesian NDLM model in all scenarios which would represent a development risk to pharmaceutical company. The bias, which is the difference between the estimated effect from the Emax and NDLM models and the simulated value, is comparable if the true dose response follows a placebo like curve, an Emax like curve, or log linear shape curve under fixed dose allocation, no adaptive allocation, half adaptive and adaptive scenarios. The bias though is significantly increased for the Emax model if the true dose response follows a U-shaped curve. In most cases the Bayesian Emax model works effectively and efficiently, with low bias and good probability of success in case of monotonic dose response. However, if there is a belief that the dose response could be non-monotonic then the NDLM is the superior model to assess the dose response.

Physical models of collective cell motility: from cell to tissue

NASA Astrophysics Data System (ADS)

Camley, B. A.; Rappel, W.-J.

2017-03-01

In this article, we review physics-based models of collective cell motility. We discuss a range of techniques at different scales, ranging from models that represent cells as simple self-propelled particles to phase field models that can represent a cell’s shape and dynamics in great detail. We also extensively review the ways in which cells within a tissue choose their direction, the statistics of cell motion, and some simple examples of how cell-cell signaling can interact with collective cell motility. This review also covers in more detail selected recent works on collective cell motion of small numbers of cells on micropatterns, in wound healing, and the chemotaxis of clusters of cells.

Root canal morphology of primary molars: a micro-computed tomography study.

PubMed

Fumes, A C; Sousa-Neto, M D; Leoni, G B; Versiani, M A; da Silva, L A B; da Silva, R A B; Consolaro, A

2014-10-01

This was to investigate the root canal morphology of primary molar teeth using micro-computed tomography. Primary maxillary (n = 20) and mandibular (n = 20) molars were scanned at a resolution of 16.7 μm and analysed regarding the number, location, volume, area, structured model index (SMI), area, roundness, diameters, and length of canals, as well as the thickness of dentine in the apical third. Data were statistically compared by using paired-sample t test, independent sample t test, and one-way analysis of variance with significance level set as 5%. Overall, no statistical differences were found between the canals with respect to length, SMI, dentine thickness, area, roundness, and diameter (p > 0.05). A double canal system was observed in the mesial and mesio-buccal roots of the mandibular and maxillary molars, respectively. The thickness in the internal aspect of the roots was lower than in the external aspect. Cross-sectional evaluation of the roots in the apical third showed flat-shaped canals in the mandibular molars and ribbon- and oval-shaped canals in the maxillary molars. External and internal anatomy of the primary first molars closely resemble the primary second molars. The reported data may help clinicians to obtain a thorough understanding of the morphological variations of root canals in primary molars to overcome problems related to shaping and cleaning procedures, allowing appropriate management strategies for root canal treatment.

Atlas-based analysis of cardiac shape and function: correction of regional shape bias due to imaging protocol for population studies.

PubMed

Medrano-Gracia, Pau; Cowan, Brett R; Bluemke, David A; Finn, J Paul; Kadish, Alan H; Lee, Daniel C; Lima, Joao A C; Suinesiaputra, Avan; Young, Alistair A

2013-09-13

Cardiovascular imaging studies generate a wealth of data which is typically used only for individual study endpoints. By pooling data from multiple sources, quantitative comparisons can be made of regional wall motion abnormalities between different cohorts, enabling reuse of valuable data. Atlas-based analysis provides precise quantification of shape and motion differences between disease groups and normal subjects. However, subtle shape differences may arise due to differences in imaging protocol between studies. A mathematical model describing regional wall motion and shape was used to establish a coordinate system registered to the cardiac anatomy. The atlas was applied to data contributed to the Cardiac Atlas Project from two independent studies which used different imaging protocols: steady state free precession (SSFP) and gradient recalled echo (GRE) cardiovascular magnetic resonance (CMR). Shape bias due to imaging protocol was corrected using an atlas-based transformation which was generated from a set of 46 volunteers who were imaged with both protocols. Shape bias between GRE and SSFP was regionally variable, and was effectively removed using the atlas-based transformation. Global mass and volume bias was also corrected by this method. Regional shape differences between cohorts were more statistically significant after removing regional artifacts due to imaging protocol bias. Bias arising from imaging protocol can be both global and regional in nature, and is effectively corrected using an atlas-based transformation, enabling direct comparison of regional wall motion abnormalities between cohorts acquired in separate studies.

Polymer Crowding in Confined Polymer-Nanoparticle Mixtures

NASA Astrophysics Data System (ADS)

Davis, Wyatt J.; Denton, Alan R.

Crowding can influence the conformations and thus functionality of macromolecules in quasi-two-dimensional environments, such as DNA or proteins confined to a cell membrane. We explore such crowding within a model of polymers as penetrable ellipses, whose shapes are governed by the statistics of a 2D random walk. The principal radii of the polymers fluctuate according to probability distributions of the eigenvalues of the gyration tensor. Within this coarse-grained model, we perform Monte Carlo simulations of mixtures of polymers and hard nanodisks, including trial changes in polymer conformation (shape and orientation). Penetration of polymers by nanodisks is incorporated with a free energy cost predicted by polymer field theory. Over ranges of size ratio and nanodisk density, we analyze the influence of crowding on polymer shape by computing eigenvalue distributions, mean radius of gyration, and mean asphericity of the polymer. We compare results with predictions of free-volume theory and with corresponding results in three dimensions. Our approach may help to interpret recent (and motivate future) experimental studies of biopolymers interacting with cell membranes, with relevance for drug delivery and gene therapy. This work was supported by the National Science Foundation under Grant No. DMR-1106331.

A Kp-based model of auroral boundaries

NASA Astrophysics Data System (ADS)

Carbary, James F.

2005-10-01

The auroral oval can serve as both a representation and a prediction of space weather on a global scale, so a competent model of the oval as a function of a geomagnetic index could conveniently appraise space weather itself. A simple model of the auroral boundaries is constructed by binning several months of images from the Polar Ultraviolet Imager by Kp index. The pixel intensities are first averaged into magnetic latitude-magnetic local time (MLT-MLAT) and local time bins, and intensity profiles are then derived for each Kp level at 1 hour intervals of MLT. After background correction, the boundary latitudes of each profile are determined at a threshold of 4 photons cm-2 s1. The peak locations and peak intensities are also found. The boundary and peak locations vary linearly with Kp index, and the coefficients of the linear fits are tabulated for each MLT. As a general rule of thumb, the UV intensity peak shifts 1° in magnetic latitude for each increment in Kp. The fits are surprisingly good for Kp < 6 but begin to deteriorate at high Kp because of auroral boundary irregularities and poor statistics. The statistical model allows calculation of the auroral boundaries at most MLTs as a function of Kp and can serve as an approximation to the shape and extent of the statistical oval.

Comparison of linear measurements and analyses taken from plaster models and three-dimensional images.

PubMed

Porto, Betina Grehs; Porto, Thiago Soares; Silva, Monica Barros; Grehs, Renésio Armindo; Pinto, Ary dos Santos; Bhandi, Shilpa H; Tonetto, Mateus Rodrigues; Bandéca, Matheus Coelho; dos Santos-Pinto, Lourdes Aparecida Martins

2014-11-01

Digital models are an alternative for carrying out analyses and devising treatment plans in orthodontics. The objective of this study was to evaluate the accuracy and the reproducibility of measurements of tooth sizes, interdental distances and analyses of occlusion using plaster models and their digital images. Thirty pairs of plaster models were chosen at random, and the digital images of each plaster model were obtained using a laser scanner (3Shape R-700, 3Shape A/S). With the plaster models, the measurements were taken using a caliper (Mitutoyo Digimatic(®), Mitutoyo (UK) Ltd) and the MicroScribe (MS) 3DX (Immersion, San Jose, Calif). For the digital images, the measurement tools used were those from the O3d software (Widialabs, Brazil). The data obtained were compared statistically using the Dahlberg formula, analysis of variance and the Tukey test (p < 0.05). The majority of the measurements, obtained using the caliper and O3d were identical, and both were significantly different from those obtained using the MS. Intra-examiner agreement was lowest when using the MS. The results demonstrated that the accuracy and reproducibility of the tooth measurements and analyses from the plaster models using the caliper and from the digital models using O3d software were identical.

A family of triaxial modified Hubble mass models: Effects of the additional radial functions

NASA Astrophysics Data System (ADS)

Das, Mousumi; Thakur, Parijat; Ann, H. B.

2005-03-01

The projected properties of triaxial generalization of the modified Hubble mass models are studied. These models are constructed by adding the additional radial functions, each multiplied by a low-order spherical harmonic, to the models of [Chakraborty, D.K., Thakur, P., 2000. MNRAS 318, 1273]. The projected surface density of mass models can be calculated analytically which allows us to derive the analytic expressions of axial ratio and position angle of major axis of constant density elliptical contours at asymptotic radii. The models are more general than those studied earlier in the sense that the inclusions of additional terms in density distribution, allow one to produce varieties of the radial profile of axial ratio and position angle, in particular, their small scale variations at inner radii. Strong correlations are found to exist between the observed axial ratio evaluated at 0.25Re and at 4Re which occupy well-separated regions in the parameter space for different choices of the intrinsic axial ratios. These correlations can be exploited to predict the intrinsic shape of the mass model, independent of the viewing angles. Using Bayesian statistics, the result of a test case launched for an estimation of the shape of a model galaxy is found to be satisfactory.

Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

PubMed Central

Guo, Yanrong; Gao, Yaozong; Shao, Yeqin; Price, True; Oto, Aytekin; Shen, Dinggang

2014-01-01

Purpose: Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integrate the appearance model into a deformable segmentation framework for prostate MR segmentation. Methods: To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on different patches of the prostate surface and trained to adaptively capture the appearance in different prostate zones, thus achieving better local tissue differentiation. For each local region, multiple classifiers are trained based on the randomly selected samples and finally assembled by a specific fusion method. In addition to this nonparametric appearance model, a prostate shape model is learned from the shape statistics using a novel approach, sparse shape composition, which can model nonGaussian distributions of shape variation and regularize the 3D mesh deformation by constraining it within the observed shape subspace. Results: The proposed method has been evaluated on two datasets consisting of T2-weighted MR prostate images. For the first (internal) dataset, the classification effectiveness of the authors' improved dictionary learning has been validated by comparing it with three other variants of traditional dictionary learning methods. The experimental results show that the authors' method yields a Dice Ratio of 89.1% compared to the manual segmentation, which is more accurate than the three state-of-the-art MR prostate segmentation methods under comparison. For the second dataset, the MICCAI 2012 challenge dataset, the authors' proposed method yields a Dice Ratio of 87.4%, which also achieves better segmentation accuracy than other methods under comparison. Conclusions: A new magnetic resonance image prostate segmentation method is proposed based on the combination of deformable model and dictionary learning methods, which achieves more accurate segmentation performance on prostate T2 MR images. PMID:24989402

Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning.

PubMed

Guo, Yanrong; Gao, Yaozong; Shao, Yeqin; Price, True; Oto, Aytekin; Shen, Dinggang

2014-07-01

Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integrate the appearance model into a deformable segmentation framework for prostate MR segmentation. To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on different patches of the prostate surface and trained to adaptively capture the appearance in different prostate zones, thus achieving better local tissue differentiation. For each local region, multiple classifiers are trained based on the randomly selected samples and finally assembled by a specific fusion method. In addition to this nonparametric appearance model, a prostate shape model is learned from the shape statistics using a novel approach, sparse shape composition, which can model nonGaussian distributions of shape variation and regularize the 3D mesh deformation by constraining it within the observed shape subspace. The proposed method has been evaluated on two datasets consisting of T2-weighted MR prostate images. For the first (internal) dataset, the classification effectiveness of the authors' improved dictionary learning has been validated by comparing it with three other variants of traditional dictionary learning methods. The experimental results show that the authors' method yields a Dice Ratio of 89.1% compared to the manual segmentation, which is more accurate than the three state-of-the-art MR prostate segmentation methods under comparison. For the second dataset, the MICCAI 2012 challenge dataset, the authors' proposed method yields a Dice Ratio of 87.4%, which also achieves better segmentation accuracy than other methods under comparison. A new magnetic resonance image prostate segmentation method is proposed based on the combination of deformable model and dictionary learning methods, which achieves more accurate segmentation performance on prostate T2 MR images.

Bayesian model selection techniques as decision support for shaping a statistical analysis plan of a clinical trial: An example from a vertigo phase III study with longitudinal count data as primary endpoint

PubMed Central

2012-01-01

Background A statistical analysis plan (SAP) is a critical link between how a clinical trial is conducted and the clinical study report. To secure objective study results, regulatory bodies expect that the SAP will meet requirements in pre-specifying inferential analyses and other important statistical techniques. To write a good SAP for model-based sensitivity and ancillary analyses involves non-trivial decisions on and justification of many aspects of the chosen setting. In particular, trials with longitudinal count data as primary endpoints pose challenges for model choice and model validation. In the random effects setting, frequentist strategies for model assessment and model diagnosis are complex and not easily implemented and have several limitations. Therefore, it is of interest to explore Bayesian alternatives which provide the needed decision support to finalize a SAP. Methods We focus on generalized linear mixed models (GLMMs) for the analysis of longitudinal count data. A series of distributions with over- and under-dispersion is considered. Additionally, the structure of the variance components is modified. We perform a simulation study to investigate the discriminatory power of Bayesian tools for model criticism in different scenarios derived from the model setting. We apply the findings to the data from an open clinical trial on vertigo attacks. These data are seen as pilot data for an ongoing phase III trial. To fit GLMMs we use a novel Bayesian computational approach based on integrated nested Laplace approximations (INLAs). The INLA methodology enables the direct computation of leave-one-out predictive distributions. These distributions are crucial for Bayesian model assessment. We evaluate competing GLMMs for longitudinal count data according to the deviance information criterion (DIC) or probability integral transform (PIT), and by using proper scoring rules (e.g. the logarithmic score). Results The instruments under study provide excellent tools for preparing decisions within the SAP in a transparent way when structuring the primary analysis, sensitivity or ancillary analyses, and specific analyses for secondary endpoints. The mean logarithmic score and DIC discriminate well between different model scenarios. It becomes obvious that the naive choice of a conventional random effects Poisson model is often inappropriate for real-life count data. The findings are used to specify an appropriate mixed model employed in the sensitivity analyses of an ongoing phase III trial. Conclusions The proposed Bayesian methods are not only appealing for inference but notably provide a sophisticated insight into different aspects of model performance, such as forecast verification or calibration checks, and can be applied within the model selection process. The mean of the logarithmic score is a robust tool for model ranking and is not sensitive to sample size. Therefore, these Bayesian model selection techniques offer helpful decision support for shaping sensitivity and ancillary analyses in a statistical analysis plan of a clinical trial with longitudinal count data as the primary endpoint. PMID:22962944

Bayesian model selection techniques as decision support for shaping a statistical analysis plan of a clinical trial: an example from a vertigo phase III study with longitudinal count data as primary endpoint.

PubMed

Adrion, Christine; Mansmann, Ulrich

2012-09-10

A statistical analysis plan (SAP) is a critical link between how a clinical trial is conducted and the clinical study report. To secure objective study results, regulatory bodies expect that the SAP will meet requirements in pre-specifying inferential analyses and other important statistical techniques. To write a good SAP for model-based sensitivity and ancillary analyses involves non-trivial decisions on and justification of many aspects of the chosen setting. In particular, trials with longitudinal count data as primary endpoints pose challenges for model choice and model validation. In the random effects setting, frequentist strategies for model assessment and model diagnosis are complex and not easily implemented and have several limitations. Therefore, it is of interest to explore Bayesian alternatives which provide the needed decision support to finalize a SAP. We focus on generalized linear mixed models (GLMMs) for the analysis of longitudinal count data. A series of distributions with over- and under-dispersion is considered. Additionally, the structure of the variance components is modified. We perform a simulation study to investigate the discriminatory power of Bayesian tools for model criticism in different scenarios derived from the model setting. We apply the findings to the data from an open clinical trial on vertigo attacks. These data are seen as pilot data for an ongoing phase III trial. To fit GLMMs we use a novel Bayesian computational approach based on integrated nested Laplace approximations (INLAs). The INLA methodology enables the direct computation of leave-one-out predictive distributions. These distributions are crucial for Bayesian model assessment. We evaluate competing GLMMs for longitudinal count data according to the deviance information criterion (DIC) or probability integral transform (PIT), and by using proper scoring rules (e.g. the logarithmic score). The instruments under study provide excellent tools for preparing decisions within the SAP in a transparent way when structuring the primary analysis, sensitivity or ancillary analyses, and specific analyses for secondary endpoints. The mean logarithmic score and DIC discriminate well between different model scenarios. It becomes obvious that the naive choice of a conventional random effects Poisson model is often inappropriate for real-life count data. The findings are used to specify an appropriate mixed model employed in the sensitivity analyses of an ongoing phase III trial. The proposed Bayesian methods are not only appealing for inference but notably provide a sophisticated insight into different aspects of model performance, such as forecast verification or calibration checks, and can be applied within the model selection process. The mean of the logarithmic score is a robust tool for model ranking and is not sensitive to sample size. Therefore, these Bayesian model selection techniques offer helpful decision support for shaping sensitivity and ancillary analyses in a statistical analysis plan of a clinical trial with longitudinal count data as the primary endpoint.

An improved ultra wideband channel model including the frequency-dependent attenuation for in-body communications.

PubMed

Khaleghi, A; Chávez-Santiago, R; Balasingham, I

2012-01-01

Ultra wideband (UWB) technology has big potential for applications in wireless body area networks (WBANs). The inherent characteristics of UWB signals make them suitable for the wireless interface of medical sensors. In particular, implanted medical wireless sensors for monitoring physiological parameters, automatic drug provision, etc. can benefit greatly from this ultra low power (ULP) interface. As with any other wireless technology, accurate knowledge of the channel is necessary for the proper design of communication systems. Only a few models that describe the radio propagation inside the human body have been published. Moreover, there is no comprehensive UWB in-body propagation model that includes the frequency-dependent attenuation. Hence, this paper extends a statistical model for UWB propagation channels inside the human chest in the 1-6 GHz frequency range by including the frequency-dependent attenuation. This is done by modeling the spectrum shape of distorted pulses at different depths inside the human chest. The distortion of the pulse was obtained through numerical simulations using a voxel representation of the human body. We propose a mathematical expression for the spectrum shape of the distorted pulses that act as a window function to reproduce the effects of frequency-dependent attenuation.

Automatic age and gender classification using supervised appearance model

NASA Astrophysics Data System (ADS)

Bukar, Ali Maina; Ugail, Hassan; Connah, David

2016-11-01

Age and gender classification are two important problems that recently gained popularity in the research community, due to their wide range of applications. Research has shown that both age and gender information are encoded in the face shape and texture, hence the active appearance model (AAM), a statistical model that captures shape and texture variations, has been one of the most widely used feature extraction techniques for the aforementioned problems. However, AAM suffers from some drawbacks, especially when used for classification. This is primarily because principal component analysis (PCA), which is at the core of the model, works in an unsupervised manner, i.e., PCA dimensionality reduction does not take into account how the predictor variables relate to the response (class labels). Rather, it explores only the underlying structure of the predictor variables, thus, it is no surprise if PCA discards valuable parts of the data that represent discriminatory features. Toward this end, we propose a supervised appearance model (sAM) that improves on AAM by replacing PCA with partial least-squares regression. This feature extraction technique is then used for the problems of age and gender classification. Our experiments show that sAM has better predictive power than the conventional AAM.

Atlas-Based Ventricular Shape Analysis for Understanding Congenital Heart Disease.

PubMed

Farrar, Genevieve; Suinesiaputra, Avan; Gilbert, Kathleen; Perry, James C; Hegde, Sanjeet; Marsden, Alison; Young, Alistair A; Omens, Jeffrey H; McCulloch, Andrew D

2016-12-01

Congenital heart disease is associated with abnormal ventricular shape that can affect wall mechanics and may be predictive of long-term adverse outcomes. Atlas-based parametric shape analysis was used to analyze ventricular geometries of eight adolescent or adult single-ventricle CHD patients with tricuspid atresia and Fontans. These patients were compared with an "atlas" of non-congenital asymptomatic volunteers, resulting in a set of z-scores which quantify deviations from the control population distribution on a patient-by-patient basis. We examined the potential of these scores to: (1) quantify abnormalities of ventricular geometry in single ventricle physiologies relative to the normal population; (2) comprehensively quantify wall motion in CHD patients; and (3) identify possible relationships between ventricular shape and wall motion that may reflect underlying functional defects or remodeling in CHD patients. CHD ventricular geometries at end-diastole and end-systole were individually compared with statistical shape properties of an asymptomatic population from the Cardiac Atlas Project. Shape analysis-derived model properties, and myocardial wall motions between end-diastole and end-systole, were compared with physician observations of clinical functional parameters. Relationships between altered shape and altered function were evaluated via correlations between atlas-based shape and wall motion scores. Atlas-based shape analysis identified a diverse set of specific quantifiable abnormalities in ventricular geometry or myocardial wall motion in all subjects. Moreover, this initial cohort displayed significant relationships between specific shape abnormalities such as increased ventricular sphericity and functional defects in myocardial deformation, such as decreased long-axis wall motion. These findings suggest that atlas-based ventricular shape analysis may be a useful new tool in the management of patients with CHD who are at risk of impaired ventricular wall mechanics and chamber remodeling.

Accounting for the relationship between per diem cost and LOS when estimating hospitalization costs.

PubMed

Ishak, K Jack; Stolar, Marilyn; Hu, Ming-yi; Alvarez, Piedad; Wang, Yamei; Getsios, Denis; Williams, Gregory C

2012-12-01

Hospitalization costs in clinical trials are typically derived by multiplying the length of stay (LOS) by an average per-diem (PD) cost from external sources. This assumes that PD costs are independent of LOS. Resource utilization in early days of the stay is usually more intense, however, and thus, the PD cost for a short hospitalization may be higher than for longer stays. The shape of this relationship is unlikely to be linear, as PD costs would be expected to gradually plateau. This paper describes how to model the relationship between PD cost and LOS using flexible statistical modelling techniques. An example based on a clinical study of clevidipine for the treatment of peri-operative hypertension during hospitalizations for cardiac surgery is used to illustrate how inferences about cost-savings associated with good blood pressure (BP) control during the stay can be affected by the approach used to derive hospitalization costs.Data on the cost and LOS of hospitalizations for coronary artery bypass grafting (CABG) from the Massachusetts Acute Hospital Case Mix Database (the MA Case Mix Database) were analyzed to link LOS to PD cost, factoring in complications that may have occurred during the hospitalization or post-discharge. The shape of the relationship between LOS and PD costs in the MA Case Mix was explored graphically in a regression framework. A series of statistical models including those based on simple logarithmic transformation of LOS to more flexible models using LOcally wEighted Scatterplot Smoothing (LOESS) techniques were considered. A final model was selected, using simplicity and parsimony as guiding principles in addition traditional fit statistics (like Akaike's Information Criterion, or AIC). This mapping was applied in ECLIPSE to predict an LOS-specific PD cost, and then a total cost of hospitalization. These were then compared for patients who had good vs. poor peri-operative blood-pressure control. The MA Case Mix dataset included data from over 10,000 patients. Visual inspection of PD vs. LOS revealed a non-linear relationship. A logarithmic model and a series of LOESS and piecewise-linear models with varying connection points were tested. The logarithmic model was ultimately favoured for its fit and simplicity. Using this mapping in the ECLIPSE trials, we found that good peri-operative BP control was associated with a cost savings of $5,366 when costs were derived using the mapping, compared with savings of $7,666 obtained using the traditional approach of calculating the cost. PD costs vary systematically with LOS, with short stays being associated with high PD costs that drop gradually and level off. The shape of the relationship may differ in other settings. It is important to assess this and model the observed pattern, as this may have an impact on conclusions based on derived hospitalization costs.

Accounting for the relationship between per diem cost and LOS when estimating hospitalization costs

PubMed Central

2012-01-01

Background Hospitalization costs in clinical trials are typically derived by multiplying the length of stay (LOS) by an average per-diem (PD) cost from external sources. This assumes that PD costs are independent of LOS. Resource utilization in early days of the stay is usually more intense, however, and thus, the PD cost for a short hospitalization may be higher than for longer stays. The shape of this relationship is unlikely to be linear, as PD costs would be expected to gradually plateau. This paper describes how to model the relationship between PD cost and LOS using flexible statistical modelling techniques. Methods An example based on a clinical study of clevidipine for the treatment of peri-operative hypertension during hospitalizations for cardiac surgery is used to illustrate how inferences about cost-savings associated with good blood pressure (BP) control during the stay can be affected by the approach used to derive hospitalization costs. Data on the cost and LOS of hospitalizations for coronary artery bypass grafting (CABG) from the Massachusetts Acute Hospital Case Mix Database (the MA Case Mix Database) were analyzed to link LOS to PD cost, factoring in complications that may have occurred during the hospitalization or post-discharge. The shape of the relationship between LOS and PD costs in the MA Case Mix was explored graphically in a regression framework. A series of statistical models including those based on simple logarithmic transformation of LOS to more flexible models using LOcally wEighted Scatterplot Smoothing (LOESS) techniques were considered. A final model was selected, using simplicity and parsimony as guiding principles in addition traditional fit statistics (like Akaike’s Information Criterion, or AIC). This mapping was applied in ECLIPSE to predict an LOS-specific PD cost, and then a total cost of hospitalization. These were then compared for patients who had good vs. poor peri-operative blood-pressure control. Results The MA Case Mix dataset included data from over 10,000 patients. Visual inspection of PD vs. LOS revealed a non-linear relationship. A logarithmic model and a series of LOESS and piecewise-linear models with varying connection points were tested. The logarithmic model was ultimately favoured for its fit and simplicity. Using this mapping in the ECLIPSE trials, we found that good peri-operative BP control was associated with a cost savings of $5,366 when costs were derived using the mapping, compared with savings of $7,666 obtained using the traditional approach of calculating the cost. Conclusions PD costs vary systematically with LOS, with short stays being associated with high PD costs that drop gradually and level off. The shape of the relationship may differ in other settings. It is important to assess this and model the observed pattern, as this may have an impact on conclusions based on derived hospitalization costs. PMID:23198908

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

Jin Fengtao; Yuan Jianmin

The experimental transmission spectrum of a hot bromine plasma [J. E. Bailey et al., J. Quant. Spectrosc. Radiat. Transf. 81, 31 (2003)] has been simulated by using a detailed level accounting model (DLA). With assumption of the local thermodynamic equilibrium, the major absorption lines of the experimental spectrum are well reproduced by the present DLA calculation, and the details of the absorption line shapes are used to determine the temperature of the plasma. In contrast to the results of two former statistical models, where the temperature was determined via a global fitting to the experimental data, the present DLA diagnosesmore » the plasma temperature by the line ratios of different charge states in the 2p{yields}3d transition groups resulting in a temperature of 37 eV. It is shown that a change of 1 eV in temperature could cause perceptible changes in the simulated spectrum. It is also shown that the 2p{sub 1/2}{yields}3d{sub 3/2} absorptions have been overestimated by the statistical models.« less

Moving line model and avalanche statistics of Bingham fluid flow in porous media.

PubMed

Chevalier, Thibaud; Talon, Laurent

2015-07-01

In this article, we propose a simple model to understand the critical behavior of path opening during flow of a yield stress fluid in porous media as numerically observed by Chevalier and Talon (2015). This model can be mapped to the problem of a contact line moving in an heterogeneous field. Close to the critical point, this line presents an avalanche dynamic where the front advances by a succession of waiting time and large burst events. These burst events are then related to the non-flowing (i.e. unyielded) areas. Remarkably, the statistics of these areas reproduce the same properties as in the direct numerical simulations. Furthermore, even if our exponents seem to be close to the mean field universal exponents, we report an unusual bump in the distribution which depends on the disorder. Finally, we identify a scaling invariance of the cluster spatial shape that is well fit, to first order, by a self-affine parabola.

[The reentrant binomial model of nuclear anomalies growth in rhabdomyosarcoma RA-23 cell populations under increasing doze of rare ionizing radiation].

PubMed

Alekseeva, N P; Alekseev, A O; Vakhtin, Iu B; Kravtsov, V Iu; Kuzovatov, S N; Skorikova, T I

2008-01-01

Distributions of nuclear morphology anomalies in transplantable rabdomiosarcoma RA-23 cell populations were investigated under effect of ionizing radiation from 0 to 45 Gy. Internuclear bridges, nuclear protrusions and dumbbell-shaped nuclei were accepted for morphological anomalies. Empirical distributions of the number of anomalies per 100 nuclei were used. The adequate model of reentrant binomial distribution has been found. The sum of binomial random variables with binomial number of summands has such distribution. Averages of these random variables were named, accordingly, internal and external average reentrant components. Their maximum likelihood estimations were received. Statistical properties of these estimations were investigated by means of statistical modeling. It has been received that at equally significant correlation between the radiation dose and the average of nuclear anomalies in cell populations after two-three cellular cycles from the moment of irradiation in vivo the irradiation doze significantly correlates with internal average reentrant component, and in remote descendants of cell transplants irradiated in vitro - with external one.

Visualization of time series statistical data by shape analysis (GDP ratio changes among Asia countries)

NASA Astrophysics Data System (ADS)

Shirota, Yukari; Hashimoto, Takako; Fitri Sari, Riri

2018-03-01

It has been very significant to visualize time series big data. In the paper we shall discuss a new analysis method called “statistical shape analysis” or “geometry driven statistics” on time series statistical data in economics. In the paper, we analyse the agriculture, value added and industry, value added (percentage of GDP) changes from 2000 to 2010 in Asia. We handle the data as a set of landmarks on a two-dimensional image to see the deformation using the principal components. The point of the analysis method is the principal components of the given formation which are eigenvectors of its bending energy matrix. The local deformation can be expressed as the set of non-Affine transformations. The transformations give us information about the local differences between in 2000 and in 2010. Because the non-Affine transformation can be decomposed into a set of partial warps, we present the partial warps visually. The statistical shape analysis is widely used in biology but, in economics, no application can be found. In the paper, we investigate its potential to analyse the economic data.

Model-based error diffusion for high fidelity lenticular screening.

PubMed

Lau, Daniel; Smith, Trebor

2006-04-17

Digital halftoning is the process of converting a continuous-tone image into an arrangement of black and white dots for binary display devices such as digital ink-jet and electrophotographic printers. As printers are achieving print resolutions exceeding 1,200 dots per inch, it is becoming increasingly important for halftoning algorithms to consider the variations and interactions in the size and shape of printed dots between neighboring pixels. In the case of lenticular screening where statistically independent images are spatially multiplexed together, ignoring these variations and interactions, such as dot overlap, will result in poor lenticular image quality. To this end, we describe our use of model-based error-diffusion for the lenticular screening problem where statistical independence between component images is achieved by restricting the diffusion of error to only those pixels of the same component image where, in order to avoid instabilities, the proposed approach involves a novel error-clipping procedure.

Particle filters, a quasi-Monte-Carlo-solution for segmentation of coronaries.

PubMed

Florin, Charles; Paragios, Nikos; Williams, Jim

2005-01-01

In this paper we propose a Particle Filter-based approach for the segmentation of coronary arteries. To this end, successive planes of the vessel are modeled as unknown states of a sequential process. Such states consist of the orientation, position, shape model and appearance (in statistical terms) of the vessel that are recovered in an incremental fashion, using a sequential Bayesian filter (Particle Filter). In order to account for bifurcations and branchings, we consider a Monte Carlo sampling rule that propagates in parallel multiple hypotheses. Promising results on the segmentation of coronary arteries demonstrate the potential of the proposed approach.

H2 emission from non-stationary magnetized bow shocks

NASA Astrophysics Data System (ADS)

Tram, L. N.; Lesaffre, P.; Cabrit, S.; Gusdorf, A.; Nhung, P. T.

2018-01-01

When a fast moving star or a protostellar jet hits an interstellar cloud, the surrounding gas gets heated and illuminated: a bow shock is born that delineates the wake of the impact. In such a process, the new molecules that are formed and excited in the gas phase become accessible to observations. In this paper, we revisit models of H2 emission in these bow shocks. We approximate the bow shock by a statistical distribution of planar shocks computed with a magnetized shock model. We improve on previous works by considering arbitrary bow shapes, a finite irradiation field and by including the age effect of non-stationary C-type shocks on the excitation diagram and line profiles of H2. We also examine the dependence of the line profiles on the shock velocity and on the viewing angle: we suggest that spectrally resolved observations may greatly help to probe the dynamics inside the bow shock. For reasonable bow shapes, our analysis shows that low-velocity shocks largely contribute to H2 excitation diagram. This can result in an observational bias towards low velocities when planar shocks are used to interpret H2 emission from an unresolved bow. We also report a large magnetization bias when the velocity of the planar model is set independently. Our 3D models reproduce excitation diagrams in BHR 71 and Orion bow shocks better than previous 1D models. Our 3D model is also able to reproduce the shape and width of the broad H2 1-0S(1) line profile in an Orion bow shock (Brand et al. 1989).

Machine learning to analyze images of shocked materials for precise and accurate measurements

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

Dresselhaus-Cooper, Leora; Howard, Marylesa; Hock, Margaret C.

A supervised machine learning algorithm, called locally adaptive discriminant analysis (LADA), has been developed to locate boundaries between identifiable image features that have varying intensities. LADA is an adaptation of image segmentation, which includes techniques that find the positions of image features (classes) using statistical intensity distributions for each class in the image. In order to place a pixel in the proper class, LADA considers the intensity at that pixel and the distribution of intensities in local (nearby) pixels. This paper presents the use of LADA to provide, with statistical uncertainties, the positions and shapes of features within ultrafast imagesmore » of shock waves. We demonstrate the ability to locate image features including crystals, density changes associated with shock waves, and material jetting caused by shock waves. This algorithm can analyze images that exhibit a wide range of physical phenomena because it does not rely on comparison to a model. LADA enables analysis of images from shock physics with statistical rigor independent of underlying models or simulations.« less

WE-AB-207B-03: A Computational Methodology for Determination of CTV-To-PTV Margins with Inter Fractional Shape Variations Based On a Statistical Point Distribution Model for Prostate Cancer Radiation Therapy

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

Shibayama, Y; Umezu, Y; Nakamura, Y

2016-06-15

Purpose: Our assumption was that interfractional shape variations of target volumes could not be negligible for determination of clinical target volume (CTV)-to-planning target volume (PTV) margins. The aim of this study was to investigate this assumption as a simulation study by developing a computational framework of CTV-to-PTV margins with taking the interfractional shape variations into account based on point distribution model (PDM) Methods: The systematic and random errors for interfractional shape variations and translations of target volumes were evaluated for four types of CTV regions (only a prostate, a prostate plus proximal 1-cm seminal vesicles, a prostate plus proximal 2-cmmore » seminal vesicles, and a prostate plus whole seminal vesicles). The CTV regions were delineated depending on prostate cancer risk groups on planning computed tomography (CT) and cone beam CT (CBCT) images of 73 fractions of 10 patients. The random and systematic errors for shape variations of CTV regions were derived from PDMs of CTV surfaces for all fractions of each patient. Systematic errors of shape variations of CTV regions were derived by comparing PDMs between planning CTV surfaces and average CTV surfaces. Finally, anisotropic CTV-to-PTV margins with shape variations in 6 directions (anterior, posterior, superior, inferior, right, and left) were computed by using a van Herk margin formula. Results: Differences between CTV-to-PTV margins with and without shape variations ranged from 0.7 to 1.7 mm in anterior direction, 1.0 to 2.8 mm in posterior direction, 0.8 to 2.8 mm in superior direction, 0.6 to 1.6 mm in inferior direction, 1.4 to 4.4 mm in right direction, and 1.3 to 5.2 mm in left direction. Conclusion: More than 1.0 mm additional margins were needed at least in 3 directions to guarantee CTV coverage due to shape variations. Therefore, shape variations should be taken into account for the determination of CTV-to-PTV margins.« less

Cliffs versus plains: Can ROSINA/COPS and OSIRIS data of comet 67P/Churyumov-Gerasimenko in autumn 2014 constrain inhomogeneous outgassing?

NASA Astrophysics Data System (ADS)

Marschall, R.; Mottola, S.; Su, C. C.; Liao, Y.; Rubin, M.; Wu, J. S.; Thomas, N.; Altwegg, K.; Sierks, H.; Ip, W.-H.; Keller, H. U.; Knollenberg, J.; Kührt, E.; Lai, I. L.; Skorov, Y.; Jorda, L.; Preusker, F.; Scholten, F.; Vincent, J.-B.; Osiris Team; Rosina Team

2017-09-01

Context. This paper describes the modelling of gas and dust data acquired in the period August to October 2014 from the European Space Agency's Rosetta spacecraft when it was in close proximity to the nucleus of comet 67P/Churyumov-Gerasimenko. Aims: With our 3D gas and dust comae models this work attempts to test the hypothesis that cliff activity on comet 67P/Churyumov-Gerasimenko can solely account for the local gas density data observed by the Rosetta Orbiter Spectrometer for Ion and Neutral Analysis (ROSINA) and the dust brightnesses seen by the Optical, Spectroscopic, and Infrared Remote Imaging System (OSIRIS) in the considered time span. Methods: The model uses a previously developed shape model of the nucleus. From this, the water sublimation rates and gas temperatures at the surface are computed. The gas expansion is modelled with a 3D Direct Simulation Monte Carlo algorithm. A dust drag algorithm is then used to compute dust volume number densities in the coma, which are then converted to brightnesses using Mie theory and a line-of-sight integration. Furthermore we have studied the impact of topographic re-radiation on the models. Results: We show that gas activity from only cliff areas produces a fit to the ROSINA/COPS data that is as statistically good as a purely insolation-driven model. In contrast, pure cliff activity does not reproduce the dust brightness observed by OSIRIS and can thus be ruled out. On the other hand, gas activity from the Hapi region in addition to cliff activity produces a statistically better fit to the ROSINA/COPS data than purely insolation-driven outgassing and also fits the OSIRIS observations rather well. We found that topographic re-radiation does not contribute significantly to the sublimation behaviour of H2O but plays an important role in how the gas flux interacts with the irregular shape of the nucleus. Conclusions: We demonstrate that fits to the observations are non-unique. We can conclude however that gas and dust activity from cliffs and the Hapi region are consistent with the ROSINA/COPS and OSIRIS data sets for the considered time span and are thus a plausible solution. Models with activity from low gravitational slopes alone provide a statistically inferior solution.

Damage localization by statistical evaluation of signal-processed mode shapes

NASA Astrophysics Data System (ADS)

Ulriksen, M. D.; Damkilde, L.

2015-07-01

Due to their inherent, ability to provide structural information on a local level, mode shapes and t.lieir derivatives are utilized extensively for structural damage identification. Typically, more or less advanced mathematical methods are implemented to identify damage-induced discontinuities in the spatial mode shape signals, hereby potentially facilitating damage detection and/or localization. However, by being based on distinguishing damage-induced discontinuities from other signal irregularities, an intrinsic deficiency in these methods is the high sensitivity towards measurement, noise. The present, article introduces a damage localization method which, compared to the conventional mode shape-based methods, has greatly enhanced robustness towards measurement, noise. The method is based on signal processing of spatial mode shapes by means of continuous wavelet, transformation (CWT) and subsequent, application of a generalized discrete Teager-Kaiser energy operator (GDTKEO) to identify damage-induced mode shape discontinuities. In order to evaluate whether the identified discontinuities are in fact, damage-induced, outlier analysis of principal components of the signal-processed mode shapes is conducted on the basis of T2-statistics. The proposed method is demonstrated in the context, of analytical work with a free-vibrating Euler-Bernoulli beam under noisy conditions.

Comprehensive Analyses of Ventricular Myocyte Models Identify Targets Exhibiting Favorable Rate Dependence

PubMed Central

Bugana, Marco; Severi, Stefano; Sobie, Eric A.

2014-01-01

Reverse rate dependence is a problematic property of antiarrhythmic drugs that prolong the cardiac action potential (AP). The prolongation caused by reverse rate dependent agents is greater at slow heart rates, resulting in both reduced arrhythmia suppression at fast rates and increased arrhythmia risk at slow rates. The opposite property, forward rate dependence, would theoretically overcome these parallel problems, yet forward rate dependent (FRD) antiarrhythmics remain elusive. Moreover, there is evidence that reverse rate dependence is an intrinsic property of perturbations to the AP. We have addressed the possibility of forward rate dependence by performing a comprehensive analysis of 13 ventricular myocyte models. By simulating populations of myocytes with varying properties and analyzing population results statistically, we simultaneously predicted the rate-dependent effects of changes in multiple model parameters. An average of 40 parameters were tested in each model, and effects on AP duration were assessed at slow (0.2 Hz) and fast (2 Hz) rates. The analysis identified a variety of FRD ionic current perturbations and generated specific predictions regarding their mechanisms. For instance, an increase in L-type calcium current is FRD when this is accompanied by indirect, rate-dependent changes in slow delayed rectifier potassium current. A comparison of predictions across models identified inward rectifier potassium current and the sodium-potassium pump as the two targets most likely to produce FRD AP prolongation. Finally, a statistical analysis of results from the 13 models demonstrated that models displaying minimal rate-dependent changes in AP shape have little capacity for FRD perturbations, whereas models with large shape changes have considerable FRD potential. This can explain differences between species and between ventricular cell types. Overall, this study provides new insights, both specific and general, into the determinants of AP duration rate dependence, and illustrates a strategy for the design of potentially beneficial antiarrhythmic drugs. PMID:24675446

Comprehensive analyses of ventricular myocyte models identify targets exhibiting favorable rate dependence.

PubMed

Cummins, Megan A; Dalal, Pavan J; Bugana, Marco; Severi, Stefano; Sobie, Eric A

2014-03-01

Reverse rate dependence is a problematic property of antiarrhythmic drugs that prolong the cardiac action potential (AP). The prolongation caused by reverse rate dependent agents is greater at slow heart rates, resulting in both reduced arrhythmia suppression at fast rates and increased arrhythmia risk at slow rates. The opposite property, forward rate dependence, would theoretically overcome these parallel problems, yet forward rate dependent (FRD) antiarrhythmics remain elusive. Moreover, there is evidence that reverse rate dependence is an intrinsic property of perturbations to the AP. We have addressed the possibility of forward rate dependence by performing a comprehensive analysis of 13 ventricular myocyte models. By simulating populations of myocytes with varying properties and analyzing population results statistically, we simultaneously predicted the rate-dependent effects of changes in multiple model parameters. An average of 40 parameters were tested in each model, and effects on AP duration were assessed at slow (0.2 Hz) and fast (2 Hz) rates. The analysis identified a variety of FRD ionic current perturbations and generated specific predictions regarding their mechanisms. For instance, an increase in L-type calcium current is FRD when this is accompanied by indirect, rate-dependent changes in slow delayed rectifier potassium current. A comparison of predictions across models identified inward rectifier potassium current and the sodium-potassium pump as the two targets most likely to produce FRD AP prolongation. Finally, a statistical analysis of results from the 13 models demonstrated that models displaying minimal rate-dependent changes in AP shape have little capacity for FRD perturbations, whereas models with large shape changes have considerable FRD potential. This can explain differences between species and between ventricular cell types. Overall, this study provides new insights, both specific and general, into the determinants of AP duration rate dependence, and illustrates a strategy for the design of potentially beneficial antiarrhythmic drugs.

Geometric, Statistical, and Topological Modeling of Intrinsic Data Manifolds: Application to 3D Shapes

DTIC Science & Technology

2009-01-01

representation to a simple curve in 3D by using the Whitney embedding theorem. In a very ludic way, we propose to combine phases one and two to...elimination principle which takes advantage of the designed parametrization. To further refine discrimination among objects, we introduce a post...packing numbers and design of principal curves. IEEE transactions on Pattern Analysis and Machine Intel- ligence, 22(3):281-297, 2000. [68] M. H. Yang, Face

Chemical indices and methods of multivariate statistics as a tool for odor classification.

PubMed

Mahlke, Ingo T; Thiesen, Peter H; Niemeyer, Bernd

2007-04-01

Industrial and agricultural off-gas streams are comprised of numerous volatile compounds, many of which have substantially different odorous properties. State-of-the-art waste-gas treatment includes the characterization of these molecules and is directed at, if possible, either the avoidance of such odorants during processing or the use of existing standardized air purification techniques like bioscrubbing or afterburning, which however, often show low efficiency under ecological and economical regards. Selective odor separation from the off-gas streams could ease many of these disadvantages but is not yet widely applicable. Thus, the aim of this paper is to identify possible model substances in selective odor separation research from 155 volatile molecules mainly originating from livestock facilities, fat refineries, and cocoa and coffee production by knowledge-based methods. All compounds are examined with regard to their structure and information-content using topological and information-theoretical indices. Resulting data are fitted in an observation matrix, and similarities between the substances are computed. Principal component analysis and k-means cluster analysis are conducted showing that clustering of indices data can depict odor information correlating well to molecular composition and molecular shape. Quantitative molecule describtion along with the application of such statistical means therefore provide a good classification tool of malodorant structure properties with no thermodynamic data needed. The approximate look-alike shape of odorous compounds within the clusters suggests a fair choice of possible model molecules.

A Sorting Statistic with Application in Neurological Magnetic Resonance Imaging of Autism.

PubMed

Levman, Jacob; Takahashi, Emi; Forgeron, Cynthia; MacDonald, Patrick; Stewart, Natalie; Lim, Ashley; Martel, Anne

2018-01-01

Effect size refers to the assessment of the extent of differences between two groups of samples on a single measurement. Assessing effect size in medical research is typically accomplished with Cohen's d statistic. Cohen's d statistic assumes that average values are good estimators of the position of a distribution of numbers and also assumes Gaussian (or bell-shaped) underlying data distributions. In this paper, we present an alternative evaluative statistic that can quantify differences between two data distributions in a manner that is similar to traditional effect size calculations; however, the proposed approach avoids making assumptions regarding the shape of the underlying data distribution. The proposed sorting statistic is compared with Cohen's d statistic and is demonstrated to be capable of identifying feature measurements of potential interest for which Cohen's d statistic implies the measurement would be of little use. This proposed sorting statistic has been evaluated on a large clinical autism dataset from Boston Children's Hospital , Harvard Medical School , demonstrating that it can potentially play a constructive role in future healthcare technologies.

A Sorting Statistic with Application in Neurological Magnetic Resonance Imaging of Autism

PubMed Central

Takahashi, Emi; Lim, Ashley; Martel, Anne

2018-01-01

Effect size refers to the assessment of the extent of differences between two groups of samples on a single measurement. Assessing effect size in medical research is typically accomplished with Cohen's d statistic. Cohen's d statistic assumes that average values are good estimators of the position of a distribution of numbers and also assumes Gaussian (or bell-shaped) underlying data distributions. In this paper, we present an alternative evaluative statistic that can quantify differences between two data distributions in a manner that is similar to traditional effect size calculations; however, the proposed approach avoids making assumptions regarding the shape of the underlying data distribution. The proposed sorting statistic is compared with Cohen's d statistic and is demonstrated to be capable of identifying feature measurements of potential interest for which Cohen's d statistic implies the measurement would be of little use. This proposed sorting statistic has been evaluated on a large clinical autism dataset from Boston Children's Hospital, Harvard Medical School, demonstrating that it can potentially play a constructive role in future healthcare technologies. PMID:29796236

3D Face Modeling Using the Multi-Deformable Method

PubMed Central

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

2012-01-01

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

The Two-Dimensional Gabor Function Adapted to Natural Image Statistics: A Model of Simple-Cell Receptive Fields and Sparse Structure in Images.

PubMed

Loxley, P N

2017-10-01

The two-dimensional Gabor function is adapted to natural image statistics, leading to a tractable probabilistic generative model that can be used to model simple cell receptive field profiles, or generate basis functions for sparse coding applications. Learning is found to be most pronounced in three Gabor function parameters representing the size and spatial frequency of the two-dimensional Gabor function and characterized by a nonuniform probability distribution with heavy tails. All three parameters are found to be strongly correlated, resulting in a basis of multiscale Gabor functions with similar aspect ratios and size-dependent spatial frequencies. A key finding is that the distribution of receptive-field sizes is scale invariant over a wide range of values, so there is no characteristic receptive field size selected by natural image statistics. The Gabor function aspect ratio is found to be approximately conserved by the learning rules and is therefore not well determined by natural image statistics. This allows for three distinct solutions: a basis of Gabor functions with sharp orientation resolution at the expense of spatial-frequency resolution, a basis of Gabor functions with sharp spatial-frequency resolution at the expense of orientation resolution, or a basis with unit aspect ratio. Arbitrary mixtures of all three cases are also possible. Two parameters controlling the shape of the marginal distributions in a probabilistic generative model fully account for all three solutions. The best-performing probabilistic generative model for sparse coding applications is found to be a gaussian copula with Pareto marginal probability density functions.

Laplace-Beltrami Eigenvalues and Topological Features of Eigenfunctions for Statistical Shape Analysis

PubMed Central

Reuter, Martin; Wolter, Franz-Erich; Shenton, Martha; Niethammer, Marc

2009-01-01

This paper proposes the use of the surface based Laplace-Beltrami and the volumetric Laplace eigenvalues and -functions as shape descriptors for the comparison and analysis of shapes. These spectral measures are isometry invariant and therefore allow for shape comparisons with minimal shape pre-processing. In particular, no registration, mapping, or remeshing is necessary. The discriminatory power of the 2D surface and 3D solid methods is demonstrated on a population of female caudate nuclei (a subcortical gray matter structure of the brain, involved in memory function, emotion processing, and learning) of normal control subjects and of subjects with schizotypal personality disorder. The behavior and properties of the Laplace-Beltrami eigenvalues and -functions are discussed extensively for both the Dirichlet and Neumann boundary condition showing advantages of the Neumann vs. the Dirichlet spectra in 3D. Furthermore, topological analyses employing the Morse-Smale complex (on the surfaces) and the Reeb graph (in the solids) are performed on selected eigenfunctions, yielding shape descriptors, that are capable of localizing geometric properties and detecting shape differences by indirectly registering topological features such as critical points, level sets and integral lines of the gradient field across subjects. The use of these topological features of the Laplace-Beltrami eigenfunctions in 2D and 3D for statistical shape analysis is novel. PMID:20161035

Language learning, language use and the evolution of linguistic variation

PubMed Central

Perfors, Amy; Fehér, Olga; Samara, Anna; Swoboda, Kate; Wonnacott, Elizabeth

2017-01-01

Linguistic universals arise from the interaction between the processes of language learning and language use. A test case for the relationship between these factors is linguistic variation, which tends to be conditioned on linguistic or sociolinguistic criteria. How can we explain the scarcity of unpredictable variation in natural language, and to what extent is this property of language a straightforward reflection of biases in statistical learning? We review three strands of experimental work exploring these questions, and introduce a Bayesian model of the learning and transmission of linguistic variation along with a closely matched artificial language learning experiment with adult participants. Our results show that while the biases of language learners can potentially play a role in shaping linguistic systems, the relationship between biases of learners and the structure of languages is not straightforward. Weak biases can have strong effects on language structure as they accumulate over repeated transmission. But the opposite can also be true: strong biases can have weak or no effects. Furthermore, the use of language during interaction can reshape linguistic systems. Combining data and insights from studies of learning, transmission and use is therefore essential if we are to understand how biases in statistical learning interact with language transmission and language use to shape the structural properties of language. This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences’. PMID:27872370

Language learning, language use and the evolution of linguistic variation.

PubMed

Smith, Kenny; Perfors, Amy; Fehér, Olga; Samara, Anna; Swoboda, Kate; Wonnacott, Elizabeth

2017-01-05

Linguistic universals arise from the interaction between the processes of language learning and language use. A test case for the relationship between these factors is linguistic variation, which tends to be conditioned on linguistic or sociolinguistic criteria. How can we explain the scarcity of unpredictable variation in natural language, and to what extent is this property of language a straightforward reflection of biases in statistical learning? We review three strands of experimental work exploring these questions, and introduce a Bayesian model of the learning and transmission of linguistic variation along with a closely matched artificial language learning experiment with adult participants. Our results show that while the biases of language learners can potentially play a role in shaping linguistic systems, the relationship between biases of learners and the structure of languages is not straightforward. Weak biases can have strong effects on language structure as they accumulate over repeated transmission. But the opposite can also be true: strong biases can have weak or no effects. Furthermore, the use of language during interaction can reshape linguistic systems. Combining data and insights from studies of learning, transmission and use is therefore essential if we are to understand how biases in statistical learning interact with language transmission and language use to shape the structural properties of language.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Authors.

Deformed Materials: Towards a Theory of Materials Morphology Dynamics

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

Sethna, James P

This grant supported work on the response of crystals to external stress. Our primary work described how disordered structural materials break in two (statistical models of fracture in disordered materials), studied models of deformation bursts (avalanches) that mediate deformation on the microscale, and developed continuum dislocation dynamics models for plastic deformation (as when scooping ice cream bends a spoon, Fig. 9). Glass is brittle -- it breaks with almost atomically smooth fracture surfaces. Many metals are ductile -- when they break, the fracture surface is locally sheared and stretched, and it is this damage that makes them hard to break.more » Bone and seashells are made of brittle material, but they are strong because they are disordered -- lots of little cracks form as they are sheared and near the fracture surface, diluting the external force. We have studied materials like bone and seashells using simulations, mathematical tools, and statistical mechanics models from physics. In particular, we studied the extreme values of fracture strengths (how likely will a beam in a bridge break far below its design strength), and found that the traditional engineering tools could be improved greatly. We also studied fascinating crackling-noise precursors -- systems which formed microcracks of a broad range of sizes before they broke. Ductile metals under stress undergo irreversible plastic deformation -- the planes of atoms must slide across one another (through the motion of dislocations) to change the overall shape in response to the external force. Microscopically, the dislocations in crystals move in bursts of a broad range of sizes (termed 'avalanches' in the statistical mechanics community, whose motion is deemed 'crackling noise'). In this grant period, we resolved a longstanding mystery about the average shape of avalanches of fixed duration (using tools related to an emergent scale invariance), we developed the fundamental theory describing the shapes of avalanches and how they are affected by the edges of the microscope viewing window, we found that slow creep of dislocations can trigger an oscillating response explaining recent experiments, we explained avalanches under external voltage, and we have studied how avalanches in experiments on the microscale relate to deformation of large samples. Inside the crystals forming the metal, the dislocations arrange into mysterious cellular structures, usually ignored in theories of plasticity. Writing a natural continuum theory for dislocation dynamics, we found that it spontaneously formed walls -- much like models of traffic jams and sonic booms. These walls formed rather realistic cellular structures, which we examined in great detail -- our walls formed fractal structures with fascinating scaling properties, related to those found in turbulent fluids. We found, however, that the numerical and mathematical tools available to solve our equations were not flexible enough to incorporate materials-specific information, and our models did not show the dislocation avalanches seen experimentally. In the last year of this grant, we wrote an invited review article, explaining how plastic flow in metals shares features with other stressed materials, and how tools of statistical physics used in these other systems might be crucial for understanding plasticity.« less

Statistical assessment of normal mitral annular geometry using automated three-dimensional echocardiographic analysis.

PubMed

Pouch, Alison M; Vergnat, Mathieu; McGarvey, Jeremy R; Ferrari, Giovanni; Jackson, Benjamin M; Sehgal, Chandra M; Yushkevich, Paul A; Gorman, Robert C; Gorman, Joseph H

2014-01-01

The basis of mitral annuloplasty ring design has progressed from qualitative surgical intuition to experimental and theoretical analysis of annular geometry with quantitative imaging techniques. In this work, we present an automated three-dimensional (3D) echocardiographic image analysis method that can be used to statistically assess variability in normal mitral annular geometry to support advancement in annuloplasty ring design. Three-dimensional patient-specific models of the mitral annulus were automatically generated from 3D echocardiographic images acquired from subjects with normal mitral valve structure and function. Geometric annular measurements including annular circumference, annular height, septolateral diameter, intercommissural width, and the annular height to intercommissural width ratio were automatically calculated. A mean 3D annular contour was computed, and principal component analysis was used to evaluate variability in normal annular shape. The following mean ± standard deviations were obtained from 3D echocardiographic image analysis: annular circumference, 107.0 ± 14.6 mm; annular height, 7.6 ± 2.8 mm; septolateral diameter, 28.5 ± 3.7 mm; intercommissural width, 33.0 ± 5.3 mm; and annular height to intercommissural width ratio, 22.7% ± 6.9%. Principal component analysis indicated that shape variability was primarily related to overall annular size, with more subtle variation in the skewness and height of the anterior annular peak, independent of annular diameter. Patient-specific 3D echocardiographic-based modeling of the human mitral valve enables statistical analysis of physiologically normal mitral annular geometry. The tool can potentially lead to the development of a new generation of annuloplasty rings that restore the diseased mitral valve annulus back to a truly normal geometry. Copyright © 2014 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

Interpolation of longitudinal shape and image data via optimal mass transport

NASA Astrophysics Data System (ADS)

Gao, Yi; Zhu, Liang-Jia; Bouix, Sylvain; Tannenbaum, Allen

2014-03-01

Longitudinal analysis of medical imaging data has become central to the study of many disorders. Unfortunately, various constraints (study design, patient availability, technological limitations) restrict the acquisition of data to only a few time points, limiting the study of continuous disease/treatment progression. Having the ability to produce a sensible time interpolation of the data can lead to improved analysis, such as intuitive visualizations of anatomical changes, or the creation of more samples to improve statistical analysis. In this work, we model interpolation of medical image data, in particular shape data, using the theory of optimal mass transport (OMT), which can construct a continuous transition from two time points while preserving "mass" (e.g., image intensity, shape volume) during the transition. The theory even allows a short extrapolation in time and may help predict short-term treatment impact or disease progression on anatomical structure. We apply the proposed method to the hippocampus-amygdala complex in schizophrenia, the heart in atrial fibrillation, and full head MR images in traumatic brain injury.

Loop Analysis of Causal Feedback in Epidemiology: An Illustration Relating To Urban Neighborhoods and Resident Depressive Experiences

PubMed Central

2008-01-01

The causal feedback implied by urban neighborhood conditions that shape human health experiences, that in turn shape neighborhood conditions through a complex causal web, raises a challenge for traditional epidemiological causal analyses. This article introduces the loop analysis method, and builds off of a core loop model linking neighborhood property vacancy rate, resident depressive symptoms, rate of neighborhood death, and rate of neighborhood exit in a feedback network. I justify and apply loop analysis to the specific example of depressive symptoms and abandoned urban residential property to show how inquiries into the behavior of causal systems can answer different kinds of hypotheses, and thereby compliment those of causal modeling using statistical models. Neighborhood physical conditions that are only indirectly influenced by depressive symptoms may nevertheless manifest in the mental health experiences of their residents; conversely, neighborhood physical conditions may be a significant mental health risk for the population of neighborhood residents. I find that participatory greenspace programs are likely to produce adaptive responses in depressive symptoms and different neighborhood conditions, which are different in character to non-participatory greenspace interventions. PMID:17706851

The notion of snow grain shape: Ambiguous definitions, retrievalfrom tomography and implications on remote sensing

NASA Astrophysics Data System (ADS)

Krol, Q. E.; Loewe, H.

2016-12-01

Grain shape is known to influence the effective physical properties of snow and therefore included in the international classification of seasonal snow. Accordingly, snowpack models account for phenomenological shape parameters (sphericity, dendricity) to capture shape variations. These parameters are however difficult to validate due to the lack of clear-cut definitions from the 3D microstucture and insufficient links to physical properties. While the definition of traditional shape was tailored to the requirements of observers, a more objective definition should be tailored to the requirements of physical properties, by analyzing geometrical (shape) corrections in existing theoretical formulations directly. To this end we revisited the autocorrelation function (ACF) and the chord length distribution (CLD) of snow. Both functions capture size distributions of the microstructure, can be calculated from X-ray tomography and are related to various physical properties. Both functions involve the optical equivalent diameter as dominant quantity, however the respective higher-order geometrical correction differ. We have analyzed these corrections, namely interfacial curvatures for the ACF and the second moment for the CLD, using an existing data set of 165 tomography samples. To unify the notion of shape, we derived various statistical relations between the length scales. Our analysis bears three key practical implications. First, we derived a significantly improved relation between the exponential correlation length and the optical diameter by taking curvatures into account. This adds to the understanding of linking "microwave grain size" and "optical grain size" of snow for remote sensing. Second, we retrieve the optical shape parameter (commonly referred to as B) from tomography images via the moment of the CLD. Third, shape variations seen by observers do not necessarily correspond to shape variations probed by physical properties.

Autogenic and Allogenic: Emergent Coastline Patterns Interact With Forcing Variations

NASA Astrophysics Data System (ADS)

Murray, A. B.; Alvarez Antolinez, J. A.; Mendez, F. J.; Moore, L. J.; Wood, J.; Farley, G.

2017-12-01

A range of coastline shapes can emerge from large-scale morphodynamic interactions. Coastline shape determines local wave influences. Local wave influences (fluxes of alongshore momentum), determine sediment fluxes, and gradients in these sediment fluxes, in turn, alter coastline shape. Modeling studies show that such feedbacks lead to an instability, and to subsequent finite-amplitude interactions, producing self-organized patterns and emergent structures including sandwaves, capes, and spits (e.g. Ashton and Murray, 2006; Ashton et al., 2015); spiral bays on rocky coastlines (e.g. Barkwith et al., 2014); and convex, spit-bounded coastlines (Ells et al., in prep.). Coastline shapes depend sensitively on wave climate, defined as the angular distribution of wave influences on alongshore sediment transport. Therefore, shifts in wave climate arising from shifts in storms (decadal scale fluctuations or longer-term trends) will tend to change coastline shape. Previous efforts have detected changing coastline shape, likely related to changing influence from hurricane-generated waves, as expressed in changes in the location and intensity of coastal erosion zones along the cuspate capes in North Carolina, USA (Moore et al., 2013). These efforts involved the assumption that coastline response to changing forcing occurs in a quasi-equilibrium manner. However, in some cases coastline responses can exhibit long-term memory and path dependence (Thomas et al., 2016). Recently, we have hindcast the wave climate affecting the North Carolina coast since 1870, using a series of statistical analyses to downscale from basin-scale surface pressure fields to regional deep-water wave climate, and then a numerical transformation to local offshore wave climate. We used this wave climate as input for the Coastline Evolution Model (CEM). The results show that the emergent coastline features respond to decadal-scale shifts in wave climate, but with time lags that complicate the relationship between forcing and coastline shape. Comparisons between model predictions and observed shoreline-change patterns support the suggestion that the relationship between emergent coastline behaviours (autogenic processes) and external influences (autogenic forcing) involves such memory effects (Antolinez et al., in revision).

An optimal set of landmarks for metopic craniosynostosis diagnosis from shape analysis of pediatric CT scans of the head

NASA Astrophysics Data System (ADS)

Mendoza, Carlos S.; Safdar, Nabile; Myers, Emmarie; Kittisarapong, Tanakorn; Rogers, Gary F.; Linguraru, Marius George

2013-02-01

Craniosynostosis (premature fusion of skull sutures) is a severe condition present in one of every 2000 newborns. Metopic craniosynostosis, accounting for 20-27% of cases, is diagnosed qualitatively in terms of skull shape abnormality, a subjective call of the surgeon. In this paper we introduce a new quantitative diagnostic feature for metopic craniosynostosis derived optimally from shape analysis of CT scans of the skull. We built a robust shape analysis pipeline that is capable of obtaining local shape differences in comparison to normal anatomy. Spatial normalization using 7-degree-of-freedom registration of the base of the skull is followed by a novel bone labeling strategy based on graph-cuts according to labeling priors. The statistical shape model built from 94 normal subjects allows matching a patient's anatomy to its most similar normal subject. Subsequently, the computation of local malformations from a normal subject allows characterization of the points of maximum malformation on each of the frontal bones adjacent to the metopic suture, and on the suture itself. Our results show that the malformations at these locations vary significantly (p<0.001) between abnormal/normal subjects and that an accurate diagnosis can be achieved using linear regression from these automatic measurements with an area under the curve for the receiver operating characteristic of 0.97.

A revision of chiggers of the minuta species-group (Acari: Trombiculidae: Neotrombicula Hirst, 1925) using multivariate morphometrics.

PubMed

Stekolnikov, Alexandr A; Klimov, Pavel B

2010-09-01

We revise chiggers belonging to the minuta-species group (genus Neotrombicula Hirst, 1925) from the Palaearctic using size-free multivariate morphometrics. This approach allowed us to resolve several diagnostic problems. We show that the widely distributed Neotrombicula scrupulosa Kudryashova, 1993 forms three spatially and ecologically isolated groups different from each other in size or shape (morphometric property) only: specimens from the Caucasus are distinct from those from Asia in shape, whereas the Asian specimens from plains and mountains are different from each other in size. We developed a multivariate classification model to separate three closely related species: N. scrupulosa, N. lubrica Kudryashova, 1993 and N. minuta Schluger, 1966. This model is based on five shape variables selected from an initial 17 variables by a best subset analysis using a custom size-correction subroutine. The variable selection procedure slightly improved the predictive power of the model, suggesting that it not only removed redundancy but also reduced 'noise' in the dataset. The overall classification accuracy of this model is 96.2, 96.2 and 95.5%, as estimated by internal validation, external validation and jackknife statistics, respectively. Our analyses resulted in one new synonymy: N. dimidiata Stekolnikov, 1995 is considered to be a synonym of N. lubrica. Both N. scrupulosa and N. lubrica are recorded from new localities. A key to species of the minuta-group incorporating results from our multivariate analyses is presented.

Patterns of subcutaneous fat deposition and the relationship between body mass index and waist-to-hip ratio: implications for models of physical attractiveness.

PubMed

Cornelissen, Piers L; Toveé, Martin J; Bateson, Melissa

2009-02-07

Body mass index (BMI) and waist-to-hip ratio (WHR) are two widely used anthropometric indices of body shape argued to convey different information about health and fertility. Both indices have also been shown to affect attractiveness ratings of female bodies. However, BMI and WHR are naturally positively correlated, complicating studies designed to identify their relative importance in predicting health and attractiveness outcomes. We show that the correlation between BMI and WHR depends on the assumed model of subcutaneous fat deposition. An additive model, whereby fat is added to the waist and hips at a constant rate, predicts a correlation between BMI and WHR because with increasing fat, the difference between the waist and hips becomes smaller relative to total width. This model is supported by longitudinal and cross-sectional data. We parameterized the function relating WHR to BMI for white UK females of reproductive age, and used this function to statistically decompose body shape into two independent components. We show that judgements of the attractiveness of female bodies are well explained by the component of curvaceousness related to BMI but not by residual curvaceousness. Our findings resolve a long-standing dispute in the attractiveness literature by confirming that although WHR appears to be an important predictor of attractiveness, this is largely explained by the direct effect of total body fat on WHR, thus reinforcing the conclusion that total body fat is the primary determinant of female body shape attractiveness.

Penalized likelihood and multi-objective spatial scans for the detection and inference of irregular clusters

PubMed Central

2010-01-01

Background Irregularly shaped spatial clusters are difficult to delineate. A cluster found by an algorithm often spreads through large portions of the map, impacting its geographical meaning. Penalized likelihood methods for Kulldorff's spatial scan statistics have been used to control the excessive freedom of the shape of clusters. Penalty functions based on cluster geometry and non-connectivity have been proposed recently. Another approach involves the use of a multi-objective algorithm to maximize two objectives: the spatial scan statistics and the geometric penalty function. Results & Discussion We present a novel scan statistic algorithm employing a function based on the graph topology to penalize the presence of under-populated disconnection nodes in candidate clusters, the disconnection nodes cohesion function. A disconnection node is defined as a region within a cluster, such that its removal disconnects the cluster. By applying this function, the most geographically meaningful clusters are sifted through the immense set of possible irregularly shaped candidate cluster solutions. To evaluate the statistical significance of solutions for multi-objective scans, a statistical approach based on the concept of attainment function is used. In this paper we compared different penalized likelihoods employing the geometric and non-connectivity regularity functions and the novel disconnection nodes cohesion function. We also build multi-objective scans using those three functions and compare them with the previous penalized likelihood scans. An application is presented using comprehensive state-wide data for Chagas' disease in puerperal women in Minas Gerais state, Brazil. Conclusions We show that, compared to the other single-objective algorithms, multi-objective scans present better performance, regarding power, sensitivity and positive predicted value. The multi-objective non-connectivity scan is faster and better suited for the detection of moderately irregularly shaped clusters. The multi-objective cohesion scan is most effective for the detection of highly irregularly shaped clusters. PMID:21034451

Sex-related shape dimorphism in the human radiocarpal and midcarpal joints.

PubMed

Kivell, Tracy L; Guimont, Isabelle; Wall, Christine E

2013-01-01

Previous research has revealed significant size differences between human male and female carpal bones but it is unknown if there are significant shape differences as well. This study investigated sex-related shape variation and allometric patterns in five carpal bones that make up the radiocarpal and midcarpal joints in modern humans. We found that many aspects of carpal shape (76% of all variables quantified) were similar between males and females, despite variation in size. However, 10 of the shape ratios were significantly different between males and females, with at least one significant shape difference observed in each carpal bone. Within-sex standard major axis regressions (SMA) of the numerator (i.e., the linear variables) on the denominator (i.e., the geometric mean) for each significantly different shape ratio indicated that most linear variables scaled with positive allometry in both males and females, and that for eight of the shape ratios, sex-related shape variation is associated with statistically similar sex-specific scaling relationships. Only the length of the scaphoid body and the height of the lunate triquetrum facet showed a significantly higher SMA slope in females compared with males. These findings indicate that the significant differences in the majority of the shape ratios are a function of subtle (i.e., not statistically significant) scaling differences between males and females. There are a number of potential developmental, functional, and evolutionary factors that may cause sex-related shape differences in the human carpus. The results highlight the potential for subtle differences in scaling to result in functionally significant differences in shape. Copyright © 2012 Wiley Periodicals, Inc.

Study of morphological variation of northern Neotropical Ariidae reveals conservatism despite macrohabitat transitions.

PubMed

Stange, Madlen; Aguirre-Fernández, Gabriel; Salzburger, Walter; Sánchez-Villagra, Marcelo R

2018-03-27

Morphological convergence triggered by trophic adaptations is a common pattern in adaptive radiations. The study of shape variation in an evolutionary context is usually restricted to well-studied fish models. We take advantage of the recently revised systematics of New World Ariidae and investigate skull shape evolution in six genera of northern Neotropical Ariidae. They constitute a lineage that diversified in the marine habitat but repeatedly adapted to freshwater habitats. 3D geometric morphometrics was applied for the first time in catfish skulls and phylogenetically informed statistical analyses were performed to test for the impact of habitat on skull diversification after habitat transition in this lineage. We found that skull shape is conserved throughout phylogeny. A morphospace analysis revealed that freshwater and marine species occupy extreme ends of the first principal component axis and that they exhibit similar Procrustes variances. Yet freshwater species occupy the smallest shape space compared to marine and brackish species (based on partial disparity), and marine and freshwater species have the largest Procrustes distance to each other. We observed a single case of shape convergence as derived from 'C-metrics', which cannot be explained by the occupation of the same habitat. Although Ariidae occupy such a broad spectrum of different habitats from sea to freshwater, the morphospace analysis and analyses of shape and co-variation with habitat in a phylogenetic context shows that conservatism dominates skull shape evolution among ariid genera.

Phenotypic characterization of glioblastoma identified through shape descriptors

NASA Astrophysics Data System (ADS)

Chaddad, Ahmad; Desrosiers, Christian; Toews, Matthew

2016-03-01

This paper proposes quantitatively describing the shape of glioblastoma (GBM) tissue phenotypes as a set of shape features derived from segmentations, for the purposes of discriminating between GBM phenotypes and monitoring tumor progression. GBM patients were identified from the Cancer Genome Atlas, and quantitative MR imaging data were obtained from the Cancer Imaging Archive. Three GBM tissue phenotypes are considered including necrosis, active tumor and edema/invasion. Volumetric tissue segmentations are obtained from registered T1˗weighted (T1˗WI) postcontrast and fluid-attenuated inversion recovery (FLAIR) MRI modalities. Shape features are computed from respective tissue phenotype segmentations, and a Kruskal-Wallis test was employed to select features capable of classification with a significance level of p < 0.05. Several classifier models are employed to distinguish phenotypes, where a leave-one-out cross-validation was performed. Eight features were found statistically significant for classifying GBM phenotypes with p <0.05, orientation is uninformative. Quantitative evaluations show the SVM results in the highest classification accuracy of 87.50%, sensitivity of 94.59% and specificity of 92.77%. In summary, the shape descriptors proposed in this work show high performance in predicting GBM tissue phenotypes. They are thus closely linked to morphological characteristics of GBM phenotypes and could potentially be used in a computer assisted labeling system.

Geometric morphometrics reveals shifts in flower shape symmetry and size following gene knockdown of CYCLOIDEA and ANTHOCYANIDIN SYNTHASE.

PubMed

Berger, Brent A; Ricigliano, Vincent A; Savriama, Yoland; Lim, Aedric; Thompson, Veronica; Howarth, Dianella G

2017-11-17

While floral symmetry has traditionally been assessed qualitatively, recent advances in geometric morphometrics have opened up new avenues to specifically quantify flower shape and size using robust multivariate statistical methods. In this study, we examine, for the first time, the ability of geometric morphometrics to detect morphological differences in floral dorsoventral asymmetry following virus-induced gene silencing (VIGS). Using Fedia graciliflora Fisch. & Meyer (Valerianaceae) as a model, corolla shape of untreated flowers was compared using canonical variate analysis to knockdown phenotypes of CYCLOIDEA2A (FgCYC2A), ANTHOCYANIDIN SYNTHASE (FgANS), and empty vector controls. Untreated flowers and all VIGS treatments were morphologically distinct from each other, suggesting that VIGS may cause subtle shifts in floral shape. Knockdowns of FgCYC2A were the most dramatic, affecting the position of dorsal petals in relation to lateral petals, thereby resulting in more actinomorphic-like flowers. Additionally, FgANS knockdowns developed larger flowers with wider corolla tube openings. These results provide a method to quantify the role that specific genes play in the developmental pathway affecting the dorsoventral axis of symmetry in zygomorphic flowers. Additionally, they suggest that ANS may have an unintended effect on floral size and shape.

Testing the shape of distributions of weather data

NASA Astrophysics Data System (ADS)

Baccon, Ana L. P.; Lunardi, José T.

2016-08-01

The characterization of the statistical distributions of observed weather data is of crucial importance both for the construction and for the validation of weather models, such as weather generators (WG's). An important class of WG's (e.g., the Richardson-type generators) reduce the time series of each variable to a time series of its residual elements, and the residuals are often assumed to be normally distributed. In this work we propose an approach to investigate if the shape assumed for the distribution of residuals is consistent or not with the observed data of a given site. Specifically, this procedure tests if the same distribution shape for the residuals noise is maintained along the time. The proposed approach is an adaptation to climate time series of a procedure first introduced to test the shapes of distributions of growth rates of business firms aggregated in large panels of short time series. We illustrate the procedure by applying it to the residuals time series of maximum temperature in a given location, and investigate the empirical consistency of two assumptions, namely i) the most common assumption that the distribution of the residuals is Gaussian and ii) that the residuals noise has a time invariant shape which coincides with the empirical distribution of all the residuals noise of the whole time series pooled together.

Atmospheric fate and transport of fine volcanic ash: Does particle shape matter?

NASA Astrophysics Data System (ADS)

White, C. M.; Allard, M. P.; Klewicki, J.; Proussevitch, A. A.; Mulukutla, G.; Genareau, K.; Sahagian, D. L.

2013-12-01

Volcanic ash presents hazards to infrastructure, agriculture, and human and animal health. In particular, given the economic importance of intercontinental aviation, understanding how long ash is suspended in the atmosphere, and how far it is transported has taken on greater importance. Airborne ash abrades the exteriors of aircraft, enters modern jet engines and melts while coating interior engine parts causing damage and potential failure. The time fine ash stays in the atmosphere depends on its terminal velocity. Existing models of ash terminal velocities are based on smooth, quasi-spherical particles characterized by Stokes velocity. Ash particles, however, violate the various assumptions upon which Stokes flow and associated models are based. Ash particles are non-spherical and can have complex surface and internal structure. This suggests that particle shape may be one reason that models fail to accurately predict removal rates of fine particles from volcanic ash clouds. The present research seeks to better parameterize predictive models for ash particle terminal velocities, diffusivity, and dispersion in the atmospheric boundary layer. The fundamental hypothesis being tested is that particle shape irreducibly impacts the fate and transport properties of fine volcanic ash. Pilot studies, incorporating modeling and experiments, are being conducted to test this hypothesis. Specifically, a statistical model has been developed that can account for actual volcanic ash size distributions, complex ash particle geometry, and geometry variability. Experimental results are used to systematically validate and improve the model. The experiments are being conducted at the Flow Physics Facility (FPF) at UNH. Terminal velocities and dispersion properties of fine ash are characterized using still air drop experiments in an unconstrained open space using a homogenized mix of source particles. Dispersion and sedimentation dynamics are quantified using particle image velocimetry (PIV). Scanning Electron Microscopy (SEM) of ash particles collected in localized deposition areas is used to correlate the PIV results to particle shape. In addition, controlled wind tunnel experiments are used to determine particle fate and transport in a turbulent boundary layer for a mixed particle population. Collectively, these studies will provide an improved understanding of the effects of particle shape on sedimentation and dispersion, and foundational data for the predictive modeling of the fate and transport of fine ash particles suspended in the atmosphere.

Distinct polymer physics principles govern chromatin dynamics in mouse and Drosophila topological domains.

PubMed

Ea, Vuthy; Sexton, Tom; Gostan, Thierry; Herviou, Laurie; Baudement, Marie-Odile; Zhang, Yunzhe; Berlivet, Soizik; Le Lay-Taha, Marie-Noëlle; Cathala, Guy; Lesne, Annick; Victor, Jean-Marc; Fan, Yuhong; Cavalli, Giacomo; Forné, Thierry

2015-08-15

In higher eukaryotes, the genome is partitioned into large "Topologically Associating Domains" (TADs) in which the chromatin displays favoured long-range contacts. While a crumpled/fractal globule organization has received experimental supports at higher-order levels, the organization principles that govern chromatin dynamics within these TADs remain unclear. Using simple polymer models, we previously showed that, in mouse liver cells, gene-rich domains tend to adopt a statistical helix shape when no significant locus-specific interaction takes place. Here, we use data from diverse 3C-derived methods to explore chromatin dynamics within mouse and Drosophila TADs. In mouse Embryonic Stem Cells (mESC), that possess large TADs (median size of 840 kb), we show that the statistical helix model, but not globule models, is relevant not only in gene-rich TADs, but also in gene-poor and gene-desert TADs. Interestingly, this statistical helix organization is considerably relaxed in mESC compared to liver cells, indicating that the impact of the constraints responsible for this organization is weaker in pluripotent cells. Finally, depletion of histone H1 in mESC alters local chromatin flexibility but not the statistical helix organization. In Drosophila, which possesses TADs of smaller sizes (median size of 70 kb), we show that, while chromatin compaction and flexibility are finely tuned according to the epigenetic landscape, chromatin dynamics within TADs is generally compatible with an unconstrained polymer configuration. Models issued from polymer physics can accurately describe the organization principles governing chromatin dynamics in both mouse and Drosophila TADs. However, constraints applied on this dynamics within mammalian TADs have a peculiar impact resulting in a statistical helix organization.

An exponential filter model predicts lightness illusions

PubMed Central

Zeman, Astrid; Brooks, Kevin R.; Ghebreab, Sennay

2015-01-01

Lightness, or perceived reflectance of a surface, is influenced by surrounding context. This is demonstrated by the Simultaneous Contrast Illusion (SCI), where a gray patch is perceived lighter against a black background and vice versa. Conversely, assimilation is where the lightness of the target patch moves toward that of the bounding areas and can be demonstrated in White's effect. Blakeslee and McCourt (1999) introduced an oriented difference-of-Gaussian (ODOG) model that is able to account for both contrast and assimilation in a number of lightness illusions and that has been subsequently improved using localized normalization techniques. We introduce a model inspired by image statistics that is based on a family of exponential filters, with kernels spanning across multiple sizes and shapes. We include an optional second stage of normalization based on contrast gain control. Our model was tested on a well-known set of lightness illusions that have previously been used to evaluate ODOG and its variants, and model lightness values were compared with typical human data. We investigate whether predictive success depends on filters of a particular size or shape and whether pooling information across filters can improve performance. The best single filter correctly predicted the direction of lightness effects for 21 out of 27 illusions. Combining two filters together increased the best performance to 23, with asymptotic performance at 24 for an arbitrarily large combination of filter outputs. While normalization improved prediction magnitudes, it only slightly improved overall scores in direction predictions. The prediction performance of 24 out of 27 illusions equals that of the best performing ODOG variant, with greater parsimony. Our model shows that V1-style orientation-selectivity is not necessary to account for lightness illusions and that a low-level model based on image statistics is able to account for a wide range of both contrast and assimilation effects. PMID:26157381

Did Groundwater Processes Shape the Saharan Landscape during the Previous Wet Periods? a Remote Sensing and Geostatistical Approach

NASA Astrophysics Data System (ADS)

Farag, A. Z. A.; Sultan, M.; Elkadiri, R.; Abdelhalim, A.

2014-12-01

An integrated approach using remote sensing, landscape analysis and statistical methods was conducted to assess the role of groundwater sapping in shaping the Saharan landscape. A GIS-based logistic regression model was constructed to automatically delineate the spatial distribution of the sapping features over areas occupied by the Nubian Sandstone Aquifer System (NSAS): (1) an inventory was compiled of known locations of sapping features identified either in the field or from satellite datasets (e.g. Orbview-3 and Google Earth Digital Globe imagery); (2) spatial analyses were conducted in a GIS environment and seven geomorphological and geological predisposing factors (i.e. slope, stream density, cross-sectional and profile curvature, minimum and maximum curvature, and lithology) were identified; (3) a binary logistic regression model was constructed, optimized and validated to describe the relationship between the sapping locations and the set of controlling factors and (4) the generated model (prediction accuracy: 90.1%) was used to produce a regional sapping map over the NSAS. Model outputs indicate: (1) groundwater discharge and structural control played an important role in excavating the Saharan natural depressions as evidenced by the wide distribution of sapping features (areal extent: 1180 km2) along the fault-controlled escarpments of the Libyan Plateau; (2) proximity of mapped sapping features to reported paleolake and tufa deposits suggesting a causal effect. Our preliminary observations (from satellite imagery) and statistical analyses together with previous studies in the North Western Sahara Aquifer System (North Africa), Sinai Peninsula, Negev Desert, and The Plateau of Najd (Saudi Arabia) indicate extensive occurrence of sapping features along the escarpments bordering the northern margins of the Saharan-Arabian Desert; these areas share similar hydrologic settings with the NSAS domains and they too witnessed wet climatic periods in the Mid-Late Quaternary.

Trends in stratospheric ozone profiles using functional mixed models

NASA Astrophysics Data System (ADS)

Park, A.; Guillas, S.; Petropavlovskikh, I.

2013-11-01

This paper is devoted to the modeling of altitude-dependent patterns of ozone variations over time. Umkehr ozone profiles (quarter of Umkehr layer) from 1978 to 2011 are investigated at two locations: Boulder (USA) and Arosa (Switzerland). The study consists of two statistical stages. First we approximate ozone profiles employing an appropriate basis. To capture primary modes of ozone variations without losing essential information, a functional principal component analysis is performed. It penalizes roughness of the function and smooths excessive variations in the shape of the ozone profiles. As a result, data-driven basis functions (empirical basis functions) are obtained. The coefficients (principal component scores) corresponding to the empirical basis functions represent dominant temporal evolution in the shape of ozone profiles. We use those time series coefficients in the second statistical step to reveal the important sources of the patterns and variations in the profiles. We estimate the effects of covariates - month, year (trend), quasi-biennial oscillation, the solar cycle, the Arctic oscillation, the El Niño/Southern Oscillation cycle and the Eliassen-Palm flux - on the principal component scores of ozone profiles using additive mixed effects models. The effects are represented as smooth functions and the smooth functions are estimated by penalized regression splines. We also impose a heteroscedastic error structure that reflects the observed seasonality in the errors. The more complex error structure enables us to provide more accurate estimates of influences and trends, together with enhanced uncertainty quantification. Also, we are able to capture fine variations in the time evolution of the profiles, such as the semi-annual oscillation. We conclude by showing the trends by altitude over Boulder and Arosa, as well as for total column ozone. There are great variations in the trends across altitudes, which highlights the benefits of modeling ozone profiles.

Subcritical crack growth in fibrous materials

NASA Astrophysics Data System (ADS)

Santucci, S.; Cortet, P.-P.; Deschanel, S.; Vanel, L.; Ciliberto, S.

2006-05-01

We present experiments on the slow growth of a single crack in a fax paper sheet submitted to a constant force F. We find that statistically averaged crack growth curves can be described by only two parameters: the mean rupture time τ and a characteristic growth length ζ. We propose a model based on a thermally activated rupture process that takes into account the microstructure of cellulose fibers. The model is able to reproduce the shape of the growth curve, the dependence of ζ on F as well as the effect of temperature on the rupture time τ. We find that the length scale at which rupture occurs in this model is consistently close to the diameter of cellulose microfibrils.

Forecasting experiments of a dynamical-statistical model of the sea surface temperature anomaly field based on the improved self-memorization principle

NASA Astrophysics Data System (ADS)

Hong, Mei; Chen, Xi; Zhang, Ren; Wang, Dong; Shen, Shuanghe; Singh, Vijay P.

2018-04-01

With the objective of tackling the problem of inaccurate long-term El Niño-Southern Oscillation (ENSO) forecasts, this paper develops a new dynamical-statistical forecast model of the sea surface temperature anomaly (SSTA) field. To avoid single initial prediction values, a self-memorization principle is introduced to improve the dynamical reconstruction model, thus making the model more appropriate for describing such chaotic systems as ENSO events. The improved dynamical-statistical model of the SSTA field is used to predict SSTA in the equatorial eastern Pacific and during El Niño and La Niña events. The long-term step-by-step forecast results and cross-validated retroactive hindcast results of time series T1 and T2 are found to be satisfactory, with a Pearson correlation coefficient of approximately 0.80 and a mean absolute percentage error (MAPE) of less than 15 %. The corresponding forecast SSTA field is accurate in that not only is the forecast shape similar to the actual field but also the contour lines are essentially the same. This model can also be used to forecast the ENSO index. The temporal correlation coefficient is 0.8062, and the MAPE value of 19.55 % is small. The difference between forecast results in spring and those in autumn is not high, indicating that the improved model can overcome the spring predictability barrier to some extent. Compared with six mature models published previously, the present model has an advantage in prediction precision and length, and is a novel exploration of the ENSO forecast method.

Abrasion-ablation model for neutron production in heavy ion reactions

NASA Technical Reports Server (NTRS)

Cucinotta, Francis A.; Wilson, John W.; Townsend, Lawrence W.

1995-01-01

In heavy ion reactions, neutron production at forward angles is observed to occur with a Gaussian shape that is centered near the beam energy and extends to energies well above that of the beam. This paper presents an abrasion-ablation model for making quantitative predictions of the neutron spectrum. To describe neutrons produced from the abrasion step of the reaction where the projectile and target overlap, the authors use the Glauber model and include effects of final-state interactions. They then use the prefragment mass distribution from abrasion with a statistical evaporation model to estimate the neutron spectrum resulting from ablation. Measurements of neutron production from Ne and Nb beams are compared with calculations, and good agreement is found.

Manifestation of two-channel nonlocal spin transport in the shapes of Hanle curves

NASA Astrophysics Data System (ADS)

Roundy, R. C.; Prestgard, M. C.; Tiwari, A.; Mishchenko, E. G.; Raikh, M. E.

2014-09-01

The dynamics of charge-density fluctuations in a system of two tunnel-coupled wires contains two diffusion modes with dispersion iω =Dq2 and iω =Dq2+2/τt, where D is the diffusion coefficient and τt is the tunneling time between the wires. The dispersion of corresponding spin-density modes depends on magnetic field as a result of the spin precession with Larmour frequency ωL. The presence of two modes affects the shape of the Hanle curve describing the spin-dependent resistance R between the ferromagnetic strips covering the nonmagnetic wires. We demonstrate that the relative shapes of the R (ωL) curves, one measured within the same wire and the other measured between the wires, depends on the ratio τt/τs, where τs is the spin-diffusion time. If the coupling between the wires is local, i.e., only at the point x =0, then the difference of the shapes of intrawire and interwire Hanle curves reflects the difference in statistics of diffusive trajectories, which "switch" or do not switch near x =0. When one of the coupled wires is bent into a loop with a radius a, the shape of the Hanle curve reflects the statistics of random walks on the loop. This statistics is governed by the dimensionless parameter a /√Dτs .

Laser ektacytometry and evaluation of statistical characteristics of inhomogeneous ensembles of red blood cells

NASA Astrophysics Data System (ADS)

Nikitin, S. Yu.; Priezzhev, A. V.; Lugovtsov, A. E.; Ustinov, V. D.; Razgulin, A. V.

2014-10-01

The paper is devoted to development of the laser ektacytometry technique for evaluation of the statistical characteristics of inhomogeneous ensembles of red blood cells (RBCs). We have analyzed theoretically laser beam scattering by the inhomogeneous ensembles of elliptical discs, modeling red blood cells in the ektacytometer. The analysis shows that the laser ektacytometry technique allows for quantitative evaluation of such population characteristics of RBCs as the cells mean shape, the cells deformability variance and asymmetry of the cells distribution in the deformability. Moreover, we show that the deformability distribution itself can be retrieved by solving a specific Fredholm integral equation of the first kind. At this stage we do not take into account the scatter in the RBC sizes.

A Statistical Analysis of the Economic Drivers of Battery Energy Storage in Commercial Buildings: Preprint

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

Long, Matthew; Simpkins, Travis; Cutler, Dylan

There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that peak demand charges are the most significant predictor of an economically viable battery, and that the shape ofmore » the load profile is the most significant predictor of the size of the battery.« less

A Statistical Analysis of the Economic Drivers of Battery Energy Storage in Commercial Buildings

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

Long, Matthew; Simpkins, Travis; Cutler, Dylan

There is significant interest in using battery energy storage systems (BESS) to reduce peak demand charges, and therefore the life cycle cost of electricity, in commercial buildings. This paper explores the drivers of economic viability of BESS in commercial buildings through statistical analysis. A sample population of buildings was generated, a techno-economic optimization model was used to size and dispatch the BESS, and the resulting optimal BESS sizes were analyzed for relevant predictor variables. Explanatory regression analyses were used to demonstrate that peak demand charges are the most significant predictor of an economically viable battery, and that the shape ofmore » the load profile is the most significant predictor of the size of the battery.« less

Progress Toward an Integration of Process-Structure-Property-Performance Models for "Three-Dimensional (3-D) Printing" of Titanium Alloys

NASA Astrophysics Data System (ADS)

Collins, P. C.; Haden, C. V.; Ghamarian, I.; Hayes, B. J.; Ales, T.; Penso, G.; Dixit, V.; Harlow, G.

2014-07-01

Electron beam direct manufacturing, synonymously known as electron beam additive manufacturing, along with other additive "3-D printing" manufacturing processes, are receiving widespread attention as a means of producing net-shape (or near-net-shape) components, owing to potential manufacturing benefits. Yet, materials scientists know that differences in manufacturing processes often significantly influence the microstructure of even widely accepted materials and, thus, impact the properties and performance of a material in service. It is important to accelerate the understanding of the processing-structure-property relationship of materials being produced via these novel approaches in a framework that considers the performance in a statistically rigorous way. This article describes the development of a process model, the assessment of key microstructural features to be incorporated into a microstructure simulation model, a novel approach to extract a constitutive equation to predict tensile properties in Ti-6Al-4V (Ti-64), and a probabilistic approach to measure the fidelity of the property model against real data. This integrated approach will provide designers a tool to vary process parameters and understand the influence on performance, enabling design and optimization for these highly visible manufacturing approaches.

Multiscale Modeling of Polycrystalline NiTi Shape Memory Alloy under Various Plastic Deformation Conditions by Coupling Microstructure Evolution and Macroscopic Mechanical Response

PubMed Central

Jiang, Shuyong; Zhou, Tao; Tu, Jian; Shi, Laixin; Chen, Qiang; Yang, Mingbo

2017-01-01

Numerical modeling of microstructure evolution in various regions during uniaxial compression and canning compression of NiTi shape memory alloy (SMA) are studied through combined macroscopic and microscopic finite element simulation in order to investigate plastic deformation of NiTi SMA at 400 °C. In this approach, the macroscale material behavior is modeled with a relatively coarse finite element mesh, and then the corresponding deformation history in some selected regions in this mesh is extracted by the sub-model technique of finite element code ABAQUS and subsequently used as boundary conditions for the microscale simulation by means of crystal plasticity finite element method (CPFEM). Simulation results show that NiTi SMA exhibits an inhomogeneous plastic deformation at the microscale. Moreover, regions that suffered canning compression sustain more homogeneous plastic deformation by comparison with the corresponding regions subjected to uniaxial compression. The mitigation of inhomogeneous plastic deformation contributes to reducing the statistically stored dislocation (SSD) density in polycrystalline aggregation and also to reducing the difference of stress level in various regions of deformed NiTi SMA sample, and therefore sustaining large plastic deformation in the canning compression process. PMID:29027925

Multiscale Modeling of Polycrystalline NiTi Shape Memory Alloy under Various Plastic Deformation Conditions by Coupling Microstructure Evolution and Macroscopic Mechanical Response.

PubMed

Hu, Li; Jiang, Shuyong; Zhou, Tao; Tu, Jian; Shi, Laixin; Chen, Qiang; Yang, Mingbo

2017-10-13

Numerical modeling of microstructure evolution in various regions during uniaxial compression and canning compression of NiTi shape memory alloy (SMA) are studied through combined macroscopic and microscopic finite element simulation in order to investigate plastic deformation of NiTi SMA at 400 °C. In this approach, the macroscale material behavior is modeled with a relatively coarse finite element mesh, and then the corresponding deformation history in some selected regions in this mesh is extracted by the sub-model technique of finite element code ABAQUS and subsequently used as boundary conditions for the microscale simulation by means of crystal plasticity finite element method (CPFEM). Simulation results show that NiTi SMA exhibits an inhomogeneous plastic deformation at the microscale. Moreover, regions that suffered canning compression sustain more homogeneous plastic deformation by comparison with the corresponding regions subjected to uniaxial compression. The mitigation of inhomogeneous plastic deformation contributes to reducing the statistically stored dislocation (SSD) density in polycrystalline aggregation and also to reducing the difference of stress level in various regions of deformed NiTi SMA sample, and therefore sustaining large plastic deformation in the canning compression process.

Learning-based stochastic object models for characterizing anatomical variations

NASA Astrophysics Data System (ADS)

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.

Shape and Albedo from Shading (SAfS) for Pixel-Level dem Generation from Monocular Images Constrained by Low-Resolution dem

NASA Astrophysics Data System (ADS)

Wu, Bo; Chung Liu, Wai; Grumpe, Arne; Wöhler, Christian

2016-06-01

Lunar topographic information, e.g., lunar DEM (Digital Elevation Model), is very important for lunar exploration missions and scientific research. Lunar DEMs are typically generated from photogrammetric image processing or laser altimetry, of which photogrammetric methods require multiple stereo images of an area. DEMs generated from these methods are usually achieved by various interpolation techniques, leading to interpolation artifacts in the resulting DEM. On the other hand, photometric shape reconstruction, e.g., SfS (Shape from Shading), extensively studied in the field of Computer Vision has been introduced to pixel-level resolution DEM refinement. SfS methods have the ability to reconstruct pixel-wise terrain details that explain a given image of the terrain. If the terrain and its corresponding pixel-wise albedo were to be estimated simultaneously, this is a SAfS (Shape and Albedo from Shading) problem and it will be under-determined without additional information. Previous works show strong statistical regularities in albedo of natural objects, and this is even more logically valid in the case of lunar surface due to its lower surface albedo complexity than the Earth. In this paper we suggest a method that refines a lower-resolution DEM to pixel-level resolution given a monocular image of the coverage with known light source, at the same time we also estimate the corresponding pixel-wise albedo map. We regulate the behaviour of albedo and shape such that the optimized terrain and albedo are the likely solutions that explain the corresponding image. The parameters in the approach are optimized through a kernel-based relaxation framework to gain computational advantages. In this research we experimentally employ the Lunar-Lambertian model for reflectance modelling; the framework of the algorithm is expected to be independent of a specific reflectance model. Experiments are carried out using the monocular images from Lunar Reconnaissance Orbiter (LRO) Narrow Angle Camera (NAC) (0.5 m spatial resolution), constrained by the SELENE and LRO Elevation Model (SLDEM 2015) of 60 m spatial resolution. The results indicate that local details are largely recovered by the algorithm while low frequency topographic consistency is affected by the low-resolution DEM.

Oriented active shape models.

PubMed

Liu, Jiamin; Udupa, Jayaram K

2009-04-01

Active shape models (ASM) are widely employed for recognizing anatomic structures and for delineating them in medical images. In this paper, a novel strategy called oriented active shape models (OASM) is presented in an attempt to overcome the following five limitations of ASM: 1) lower delineation accuracy, 2) the requirement of a large number of landmarks, 3) sensitivity to search range, 4) sensitivity to initialization, and 5) inability to fully exploit the specific information present in the given image to be segmented. OASM effectively combines the rich statistical shape information embodied in ASM with the boundary orientedness property and the globally optimal delineation capability of the live wire methodology of boundary segmentation. The latter characteristics allow live wire to effectively separate an object boundary from other nonobject boundaries with similar properties especially when they come very close in the image domain. The approach leads to a two-level dynamic programming method, wherein the first level corresponds to boundary recognition and the second level corresponds to boundary delineation, and to an effective automatic initialization method. The method outputs a globally optimal boundary that agrees with the shape model if the recognition step is successful in bringing the model close to the boundary in the image. Extensive evaluation experiments have been conducted by utilizing 40 image (magnetic resonance and computed tomography) data sets in each of five different application areas for segmenting breast, liver, bones of the foot, and cervical vertebrae of the spine. Comparisons are made between OASM and ASM based on precision, accuracy, and efficiency of segmentation. Accuracy is assessed using both region-based false positive and false negative measures and boundary-based distance measures. The results indicate the following: 1) The accuracy of segmentation via OASM is considerably better than that of ASM; 2) The number of landmarks can be reduced by a factor of 3 in OASM over that in ASM; 3) OASM becomes largely independent of search range and initialization becomes automatic. All three benefits of OASM ensue mainly from the severe constraints brought in by the boundary-orientedness property of live wire and the globally optimal solution found by the 2-level dynamic programming algorithm.

Statistical context shapes stimulus-specific adaptation in human auditory cortex

PubMed Central

Henry, Molly J.; Fromboluti, Elisa Kim; McAuley, J. Devin

2015-01-01

Stimulus-specific adaptation is the phenomenon whereby neural response magnitude decreases with repeated stimulation. Inconsistencies between recent nonhuman animal recordings and computational modeling suggest dynamic influences on stimulus-specific adaptation. The present human electroencephalography (EEG) study investigates the potential role of statistical context in dynamically modulating stimulus-specific adaptation by examining the auditory cortex-generated N1 and P2 components. As in previous studies of stimulus-specific adaptation, listeners were presented with oddball sequences in which the presentation of a repeated tone was infrequently interrupted by rare spectral changes taking on three different magnitudes. Critically, the statistical context varied with respect to the probability of small versus large spectral changes within oddball sequences (half of the time a small change was most probable; in the other half a large change was most probable). We observed larger N1 and P2 amplitudes (i.e., release from adaptation) for all spectral changes in the small-change compared with the large-change statistical context. The increase in response magnitude also held for responses to tones presented with high probability, indicating that statistical adaptation can overrule stimulus probability per se in its influence on neural responses. Computational modeling showed that the degree of coadaptation in auditory cortex changed depending on the statistical context, which in turn affected stimulus-specific adaptation. Thus the present data demonstrate that stimulus-specific adaptation in human auditory cortex critically depends on statistical context. Finally, the present results challenge the implicit assumption of stationarity of neural response magnitudes that governs the practice of isolating established deviant-detection responses such as the mismatch negativity. PMID:25652920

Diagnostic index of 3D osteoarthritic changes in TMJ condylar morphology

NASA Astrophysics Data System (ADS)

Gomes, Liliane R.; Gomes, Marcelo; Jung, Bryan; Paniagua, Beatriz; Ruellas, Antonio C.; Gonçalves, João. Roberto; Styner, Martin A.; Wolford, Larry; Cevidanes, Lucia

2015-03-01

The aim of this study was to investigate imaging statistical approaches for classifying 3D osteoarthritic morphological variations among 169 Temporomandibular Joint (TMJ) condyles. Cone beam Computed Tomography (CBCT) scans were acquired from 69 patients with long-term TMJ Osteoarthritis (OA) (39.1 ± 15.7 years), 15 patients at initial diagnosis of OA (44.9 ± 14.8 years) and 7 healthy controls (43 ± 12.4 years). 3D surface models of the condyles were constructed and Shape Correspondence was used to establish correspondent points on each model. The statistical framework included a multivariate analysis of covariance (MANCOVA) and Direction-Projection- Permutation (DiProPerm) for testing statistical significance of the differences between healthy control and the OA group determined by clinical and radiographic diagnoses. Unsupervised classification using hierarchical agglomerative clustering (HAC) was then conducted. Condylar morphology in OA and healthy subjects varied widely. Compared with healthy controls, OA average condyle was statistically significantly smaller in all dimensions except its anterior surface. Significant flattening of the lateral pole was noticed at initial diagnosis (p < 0.05). It was observed areas of 3.88 mm bone resorption at the superior surface and 3.10 mm bone apposition at the anterior aspect of the long-term OA average model. 1000 permutation statistics of DiProPerm supported a significant difference between the healthy control group and OA group (t = 6.7, empirical p-value = 0.001). Clinically meaningful unsupervised classification of TMJ condylar morphology determined a preliminary diagnostic index of 3D osteoarthritic changes, which may be the first step towards a more targeted diagnosis of this condition.

A web-based system for neural network based classification in temporomandibular joint osteoarthritis.

PubMed

de Dumast, Priscille; Mirabel, Clément; Cevidanes, Lucia; Ruellas, Antonio; Yatabe, Marilia; Ioshida, Marcos; Ribera, Nina Tubau; Michoud, Loic; Gomes, Liliane; Huang, Chao; Zhu, Hongtu; Muniz, Luciana; Shoukri, Brandon; Paniagua, Beatriz; Styner, Martin; Pieper, Steve; Budin, Francois; Vimort, Jean-Baptiste; Pascal, Laura; Prieto, Juan Carlos

2018-07-01

The purpose of this study is to describe the methodological innovations of a web-based system for storage, integration and computation of biomedical data, using a training imaging dataset to remotely compute a deep neural network classifier of temporomandibular joint osteoarthritis (TMJOA). This study imaging dataset consisted of three-dimensional (3D) surface meshes of mandibular condyles constructed from cone beam computed tomography (CBCT) scans. The training dataset consisted of 259 condyles, 105 from control subjects and 154 from patients with diagnosis of TMJ OA. For the image analysis classification, 34 right and left condyles from 17 patients (39.9 ± 11.7 years), who experienced signs and symptoms of the disease for less than 5 years, were included as the testing dataset. For the integrative statistical model of clinical, biological and imaging markers, the sample consisted of the same 17 test OA subjects and 17 age and sex matched control subjects (39.4 ± 15.4 years), who did not show any sign or symptom of OA. For these 34 subjects, a standardized clinical questionnaire, blood and saliva samples were also collected. The technological methodologies in this study include a deep neural network classifier of 3D condylar morphology (ShapeVariationAnalyzer, SVA), and a flexible web-based system for data storage, computation and integration (DSCI) of high dimensional imaging, clinical, and biological data. The DSCI system trained and tested the neural network, indicating 5 stages of structural degenerative changes in condylar morphology in the TMJ with 91% close agreement between the clinician consensus and the SVA classifier. The DSCI remotely ran with a novel application of a statistical analysis, the Multivariate Functional Shape Data Analysis, that computed high dimensional correlations between shape 3D coordinates, clinical pain levels and levels of biological markers, and then graphically displayed the computation results. The findings of this study demonstrate a comprehensive phenotypic characterization of TMJ health and disease at clinical, imaging and biological levels, using novel flexible and versatile open-source tools for a web-based system that provides advanced shape statistical analysis and a neural network based classification of temporomandibular joint osteoarthritis. Published by Elsevier Ltd.

Collective Phase in Resource Competition in a Highly Diverse Ecosystem.

PubMed

Tikhonov, Mikhail; Monasson, Remi

2017-01-27

Organisms shape their own environment, which in turn affects their survival. This feedback becomes especially important for communities containing a large number of species; however, few existing approaches allow studying this regime, except in simulations. Here, we use methods of statistical physics to analytically solve a classic ecological model of resource competition introduced by MacArthur in 1969. We show that the nonintuitive phenomenology of highly diverse ecosystems includes a phase where the environment constructed by the community becomes fully decoupled from the outside world.

Modelling average maximum daily temperature using r largest order statistics: An application to South African data

PubMed Central

2018-01-01

Natural hazards (events that may cause actual disasters) are established in the literature as major causes of various massive and destructive problems worldwide. The occurrences of earthquakes, floods and heat waves affect millions of people through several impacts. These include cases of hospitalisation, loss of lives and economic challenges. The focus of this study was on the risk reduction of the disasters that occur because of extremely high temperatures and heat waves. Modelling average maximum daily temperature (AMDT) guards against the disaster risk and may also help countries towards preparing for extreme heat. This study discusses the use of the r largest order statistics approach of extreme value theory towards modelling AMDT over the period of 11 years, that is, 2000–2010. A generalised extreme value distribution for r largest order statistics is fitted to the annual maxima. This is performed in an effort to study the behaviour of the r largest order statistics. The method of maximum likelihood is used in estimating the target parameters and the frequency of occurrences of the hottest days is assessed. The study presents a case study of South Africa in which the data for the non-winter season (September–April of each year) are used. The meteorological data used are the AMDT that are collected by the South African Weather Service and provided by Eskom. The estimation of the shape parameter reveals evidence of a Weibull class as an appropriate distribution for modelling AMDT in South Africa. The extreme quantiles for specified return periods are estimated using the quantile function and the best model is chosen through the use of the deviance statistic with the support of the graphical diagnostic tools. The Entropy Difference Test (EDT) is used as a specification test for diagnosing the fit of the models to the data.

Concurrent segmentation of the prostate on MRI and CT via linked statistical shape models for radiotherapy planning

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

Chowdhury, Najeeb; Toth, Robert; Chappelow, Jonathan

2012-04-15

Purpose: Prostate gland segmentation is a critical step in prostate radiotherapy planning, where dose plans are typically formulated on CT. Pretreatment MRI is now beginning to be acquired at several medical centers. Delineation of the prostate on MRI is acknowledged as being significantly simpler to perform, compared to delineation on CT. In this work, the authors present a novel framework for building a linked statistical shape model (LSSM), a statistical shape model (SSM) that links the shape variation of a structure of interest (SOI) across multiple imaging modalities. This framework is particularly relevant in scenarios where accurate boundary delineations ofmore » the SOI on one of the modalities may not be readily available, or difficult to obtain, for training a SSM. In this work the authors apply the LSSM in the context of multimodal prostate segmentation for radiotherapy planning, where the prostate is concurrently segmented on MRI and CT. Methods: The framework comprises a number of logically connected steps. The first step utilizes multimodal registration of MRI and CT to map 2D boundary delineations of the prostate from MRI onto corresponding CT images, for a set of training studies. Hence, the scheme obviates the need for expert delineations of the gland on CT for explicitly constructing a SSM for prostate segmentation on CT. The delineations of the prostate gland on MRI and CT allows for 3D reconstruction of the prostate shape which facilitates the building of the LSSM. In order to perform concurrent prostate MRI and CT segmentation using the LSSM, the authors employ a region-based level set approach where the authors deform the evolving prostate boundary to simultaneously fit to MRI and CT images in which voxels are classified to be either part of the prostate or outside the prostate. The classification is facilitated by using a combination of MRI-CT probabilistic spatial atlases and a random forest classifier, driven by gradient and Haar features. Results: The authors acquire a total of 20 MRI-CT patient studies and use the leave-one-out strategy to train and evaluate four different LSSMs. First, a fusion-based LSSM (fLSSM) is built using expert ground truth delineations of the prostate on MRI alone, where the ground truth for the gland on CT is obtained via coregistration of the corresponding MRI and CT slices. The authors compare the fLSSM against another LSSM (xLSSM), where expert delineations of the gland on both MRI and CT are employed in the model building; xLSSM representing the idealized LSSM. The authors also compare the fLSSM against an exclusive CT-based SSM (ctSSM), built from expert delineations of the gland on CT alone. In addition, two LSSMs trained using trainee delineations (tLSSM) on CT are compared with the fLSSM. The results indicate that the xLSSM, tLSSMs, and the fLSSM perform equivalently, all of them out-performing the ctSSM. Conclusions: The fLSSM provides an accurate alternative to SSMs that require careful expert delineations of the SOI that may be difficult or laborious to obtain. Additionally, the fLSSM has the added benefit of providing concurrent segmentations of the SOI on multiple imaging modalities.« less

Deformable segmentation of 3D MR prostate images via distributed discriminative dictionary and ensemble learning

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

Guo, Yanrong; Shao, Yeqin; Gao, Yaozong

Purpose: Automatic prostate segmentation from MR images is an important task in various clinical applications such as prostate cancer staging and MR-guided radiotherapy planning. However, the large appearance and shape variations of the prostate in MR images make the segmentation problem difficult to solve. Traditional Active Shape/Appearance Model (ASM/AAM) has limited accuracy on this problem, since its basic assumption, i.e., both shape and appearance of the targeted organ follow Gaussian distributions, is invalid in prostate MR images. To this end, the authors propose a sparse dictionary learning method to model the image appearance in a nonparametric fashion and further integratemore » the appearance model into a deformable segmentation framework for prostate MR segmentation. Methods: To drive the deformable model for prostate segmentation, the authors propose nonparametric appearance and shape models. The nonparametric appearance model is based on a novel dictionary learning method, namely distributed discriminative dictionary (DDD) learning, which is able to capture fine distinctions in image appearance. To increase the differential power of traditional dictionary-based classification methods, the authors' DDD learning approach takes three strategies. First, two dictionaries for prostate and nonprostate tissues are built, respectively, using the discriminative features obtained from minimum redundancy maximum relevance feature selection. Second, linear discriminant analysis is employed as a linear classifier to boost the optimal separation between prostate and nonprostate tissues, based on the representation residuals from sparse representation. Third, to enhance the robustness of the authors' classification method, multiple local dictionaries are learned for local regions along the prostate boundary (each with small appearance variations), instead of learning one global classifier for the entire prostate. These discriminative dictionaries are located on different patches of the prostate surface and trained to adaptively capture the appearance in different prostate zones, thus achieving better local tissue differentiation. For each local region, multiple classifiers are trained based on the randomly selected samples and finally assembled by a specific fusion method. In addition to this nonparametric appearance model, a prostate shape model is learned from the shape statistics using a novel approach, sparse shape composition, which can model nonGaussian distributions of shape variation and regularize the 3D mesh deformation by constraining it within the observed shape subspace. Results: The proposed method has been evaluated on two datasets consisting of T2-weighted MR prostate images. For the first (internal) dataset, the classification effectiveness of the authors' improved dictionary learning has been validated by comparing it with three other variants of traditional dictionary learning methods. The experimental results show that the authors' method yields a Dice Ratio of 89.1% compared to the manual segmentation, which is more accurate than the three state-of-the-art MR prostate segmentation methods under comparison. For the second dataset, the MICCAI 2012 challenge dataset, the authors' proposed method yields a Dice Ratio of 87.4%, which also achieves better segmentation accuracy than other methods under comparison. Conclusions: A new magnetic resonance image prostate segmentation method is proposed based on the combination of deformable model and dictionary learning methods, which achieves more accurate segmentation performance on prostate T2 MR images.« less

When things go pear shaped: contour variations of contacts

NASA Astrophysics Data System (ADS)

Utzny, Clemens

2013-04-01

Traditional control of critical dimensions (CD) on photolithographic masks considers the CD average and a measure for the CD variation such as the CD range or the standard deviation. Also systematic CD deviations from the mean such as CD signatures are subject to the control. These measures are valid for mask quality verification as long as patterns across a mask exhibit only size variations and no shape variation. The issue of shape variations becomes especially important in the context of contact holes on EUV masks. For EUV masks the CD error budget is much smaller than for standard optical masks. This means that small deviations from the contact shape can impact EUV waver prints in the sense that contact shape deformations induce asymmetric bridging phenomena. In this paper we present a detailed study of contact shape variations based on regular product data. Two data sets are analyzed: 1) contacts of varying target size and 2) a regularly spaced field of contacts. Here, the methods of statistical shape analysis are used to analyze CD SEM generated contour data. We demonstrate that contacts on photolithographic masks do not only show size variations but exhibit also pronounced nontrivial shape variations. In our data sets we find pronounced shape variations which can be interpreted as asymmetrical shape squeezing and contact rounding. Thus we demonstrate the limitations of classic CD measures for describing the feature variations on masks. Furthermore we show how the methods of statistical shape analysis can be used for quantifying the contour variations thus paving the way to a new understanding of mask linearity and its specification.

Reconstructing surface wave profiles from reflected acoustic pulses using multiple receivers.

PubMed

Walstead, Sean P; Deane, Grant B

2014-08-01

Surface wave shapes are determined by analyzing underwater reflected acoustic signals collected at multiple receivers. The transmitted signals are of nominal frequency 300 kHz and are reflected off surface gravity waves that are paddle-generated in a wave tank. An inverse processing algorithm reconstructs 50 surface wave shapes over a length span of 2.10 m. The inverse scheme uses a broadband forward scattering model based on Kirchhoff's diffraction formula to determine wave shapes. The surface reconstruction algorithm is self-starting in that source and receiver geometry and initial estimates of wave shape are determined from the same acoustic signals used in the inverse processing. A high speed camera provides ground-truth measurements of the surface wave field for comparison with the acoustically derived surface waves. Within Fresnel zone regions the statistical confidence of the inversely optimized surface profile exceeds that of the camera profile. Reconstructed surfaces are accurate to a resolution of about a quarter-wavelength of the acoustic pulse only within Fresnel zones associated with each source and receiver pair. Multiple isolated Fresnel zones from multiple receivers extend the spatial extent of accurate surface reconstruction while overlapping Fresnel zones increase confidence in the optimized profiles there.

Prostate contouring in MRI guided biopsy.

PubMed

Vikal, Siddharth; Haker, Steven; Tempany, Clare; Fichtinger, Gabor

2009-03-27

With MRI possibly becoming a modality of choice for detection and staging of prostate cancer, fast and accurate outlining of the prostate is required in the volume of clinical interest. We present a semi-automatic algorithm that uses a priori knowledge of prostate shape to arrive at the final prostate contour. The contour of one slice is then used as initial estimate in the neighboring slices. Thus we propagate the contour in 3D through steps of refinement in each slice. The algorithm makes only minimum assumptions about the prostate shape. A statistical shape model of prostate contour in polar transform space is employed to narrow search space. Further, shape guidance is implicitly imposed by allowing only plausible edge orientations using template matching. The algorithm does not require region-homogeneity, discriminative edge force, or any particular edge profile. Likewise, it makes no assumption on the imaging coils and pulse sequences used and it is robust to the patient's pose (supine, prone, etc.). The contour method was validated using expert segmentation on clinical MRI data. We recorded a mean absolute distance of 2.0 ± 0.6 mm and dice similarity coefficient of 0.93 ± 0.3 in midsection. The algorithm takes about 1 second per slice.

Prostate contouring in MRI guided biopsy

PubMed Central

Vikal, Siddharth; Haker, Steven; Tempany, Clare; Fichtinger, Gabor

2010-01-01

With MRI possibly becoming a modality of choice for detection and staging of prostate cancer, fast and accurate outlining of the prostate is required in the volume of clinical interest. We present a semi-automatic algorithm that uses a priori knowledge of prostate shape to arrive at the final prostate contour. The contour of one slice is then used as initial estimate in the neighboring slices. Thus we propagate the contour in 3D through steps of refinement in each slice. The algorithm makes only minimum assumptions about the prostate shape. A statistical shape model of prostate contour in polar transform space is employed to narrow search space. Further, shape guidance is implicitly imposed by allowing only plausible edge orientations using template matching. The algorithm does not require region-homogeneity, discriminative edge force, or any particular edge profile. Likewise, it makes no assumption on the imaging coils and pulse sequences used and it is robust to the patient's pose (supine, prone, etc.). The contour method was validated using expert segmentation on clinical MRI data. We recorded a mean absolute distance of 2.0 ± 0.6 mm and dice similarity coefficient of 0.93 ± 0.3 in midsection. The algorithm takes about 1 second per slice. PMID:21132083

Dynamic model of the force driving kinesin to move along microtubule-Simulation with a model system

NASA Astrophysics Data System (ADS)

Chou, Y. C.; Hsiao, Yi-Feng; To, Kiwing

2015-09-01

A dynamic model for the motility of kinesin, including stochastic-force generation and step formation is proposed. The force driving the motion of kinesin motor is generated by the impulse from the collision between the randomly moving long-chain stalk and the ratchet-shaped outer surface of microtubule. Most of the dynamical and statistical features of the motility of kinesin are reproduced in a simulation system, with (a) ratchet structures similar to the outer surface of microtubule, (b) a bead chain connected to two heads, similarly to the stalk of the real kinesin motor, and (c) the interaction between the heads of the simulated kinesin and microtubule. We also propose an experiment to discriminate between the conventional hand-over-hand model and the dynamic model.

Automated detection, 3D segmentation and analysis of high resolution spine MR images using statistical shape models

NASA Astrophysics Data System (ADS)

Neubert, A.; Fripp, J.; Engstrom, C.; Schwarz, R.; Lauer, L.; Salvado, O.; Crozier, S.

2012-12-01

Recent advances in high resolution magnetic resonance (MR) imaging of the spine provide a basis for the automated assessment of intervertebral disc (IVD) and vertebral body (VB) anatomy. High resolution three-dimensional (3D) morphological information contained in these images may be useful for early detection and monitoring of common spine disorders, such as disc degeneration. This work proposes an automated approach to extract the 3D segmentations of lumbar and thoracic IVDs and VBs from MR images using statistical shape analysis and registration of grey level intensity profiles. The algorithm was validated on a dataset of volumetric scans of the thoracolumbar spine of asymptomatic volunteers obtained on a 3T scanner using the relatively new 3D T2-weighted SPACE pulse sequence. Manual segmentations and expert radiological findings of early signs of disc degeneration were used in the validation. There was good agreement between manual and automated segmentation of the IVD and VB volumes with the mean Dice scores of 0.89 ± 0.04 and 0.91 ± 0.02 and mean absolute surface distances of 0.55 ± 0.18 mm and 0.67 ± 0.17 mm respectively. The method compares favourably to existing 3D MR segmentation techniques for VBs. This is the first time IVDs have been automatically segmented from 3D volumetric scans and shape parameters obtained were used in preliminary analyses to accurately classify (100% sensitivity, 98.3% specificity) disc abnormalities associated with early degenerative changes.

Dose coverage calculation using a statistical shape model—applied to cervical cancer radiotherapy

NASA Astrophysics Data System (ADS)

Tilly, David; van de Schoot, Agustinus J. A. J.; Grusell, Erik; Bel, Arjan; Ahnesjö, Anders

2017-05-01

A comprehensive methodology for treatment simulation and evaluation of dose coverage probabilities is presented where a population based statistical shape model (SSM) provide samples of fraction specific patient geometry deformations. The learning data consists of vector fields from deformable image registration of repeated imaging giving intra-patient deformations which are mapped to an average patient serving as a common frame of reference. The SSM is created by extracting the most dominating eigenmodes through principal component analysis of the deformations from all patients. The sampling of a deformation is thus reduced to sampling weights for enough of the most dominating eigenmodes that describe the deformations. For the cervical cancer patient datasets in this work, we found seven eigenmodes to be sufficient to capture 90% of the variance in the deformations of the, and only three eigenmodes for stability in the simulated dose coverage probabilities. The normality assumption of the eigenmode weights was tested and found relevant for the 20 most dominating eigenmodes except for the first. Individualization of the SSM is demonstrated to be improved using two deformation samples from a new patient. The probabilistic evaluation provided additional information about the trade-offs compared to the conventional single dataset treatment planning.

Quantifying Melt Ponds in the Beaufort MIZ using Linear Support Vector Machines from High Resolution Panchromatic Images

NASA Astrophysics Data System (ADS)

Ortiz, M.; Graber, H. C.; Wilkinson, J.; Nyman, L. M.; Lund, B.

2017-12-01

Much work has been done on determining changes in summer ice albedo and morphological properties of melt ponds such as depth, shape and distribution using in-situ measurements and satellite-based sensors. Although these studies have dedicated much pioneering work in this area, there still lacks sufficient spatial and temporal scales. We present a prototype algorithm using Linear Support Vector Machines (LSVMs) designed to quantify the evolution of melt pond fraction from a recently government-declassified high-resolution panchromatic optical dataset. The study area of interest lies within the Beaufort marginal ice zone (MIZ), where several in-situ instruments were deployed by the British Antarctic Survey in joint with the MIZ Program, from April-September, 2014. The LSVM uses four dimensional feature data from the intensity image itself, and from various textures calculated from a modified first-order histogram technique using probability density of occurrences. We explore both the temporal evolution of melt ponds and spatial statistics such as pond fraction, pond area, and number pond density, to name a few. We also introduce a linear regression model that can potentially be used to estimate average pond area by ingesting several melt pond statistics and shape parameters.

Automatic recognition of surface landmarks of anatomical structures of back and posture

NASA Astrophysics Data System (ADS)

Michoński, Jakub; Glinkowski, Wojciech; Witkowski, Marcin; Sitnik, Robert

2012-05-01

Faulty postures, scoliosis and sagittal plane deformities should be detected as early as possible to apply preventive and treatment measures against major clinical consequences. To support documentation of the severity of deformity and diminish x-ray exposures, several solutions utilizing analysis of back surface topography data were introduced. A novel approach to automatic recognition and localization of anatomical landmarks of the human back is presented that may provide more repeatable results and speed up the whole procedure. The algorithm was designed as a two-step process involving a statistical model built upon expert knowledge and analysis of three-dimensional back surface shape data. Voronoi diagram is used to connect mean geometric relations, which provide a first approximation of the positions, with surface curvature distribution, which further guides the recognition process and gives final locations of landmarks. Positions obtained using the developed algorithms are validated with respect to accuracy of manual landmark indication by experts. Preliminary validation proved that the landmarks were localized correctly, with accuracy depending mostly on the characteristics of a given structure. It was concluded that recognition should mainly take into account the shape of the back surface, putting as little emphasis on the statistical approximation as possible.

Optimizing the maximum reported cluster size in the spatial scan statistic for ordinal data.

PubMed

Kim, Sehwi; Jung, Inkyung

2017-01-01

The spatial scan statistic is an important tool for spatial cluster detection. There have been numerous studies on scanning window shapes. However, little research has been done on the maximum scanning window size or maximum reported cluster size. Recently, Han et al. proposed to use the Gini coefficient to optimize the maximum reported cluster size. However, the method has been developed and evaluated only for the Poisson model. We adopt the Gini coefficient to be applicable to the spatial scan statistic for ordinal data to determine the optimal maximum reported cluster size. Through a simulation study and application to a real data example, we evaluate the performance of the proposed approach. With some sophisticated modification, the Gini coefficient can be effectively employed for the ordinal model. The Gini coefficient most often picked the optimal maximum reported cluster sizes that were the same as or smaller than the true cluster sizes with very high accuracy. It seems that we can obtain a more refined collection of clusters by using the Gini coefficient. The Gini coefficient developed specifically for the ordinal model can be useful for optimizing the maximum reported cluster size for ordinal data and helpful for properly and informatively discovering cluster patterns.

Optimizing the maximum reported cluster size in the spatial scan statistic for ordinal data

PubMed Central

Kim, Sehwi

2017-01-01

The spatial scan statistic is an important tool for spatial cluster detection. There have been numerous studies on scanning window shapes. However, little research has been done on the maximum scanning window size or maximum reported cluster size. Recently, Han et al. proposed to use the Gini coefficient to optimize the maximum reported cluster size. However, the method has been developed and evaluated only for the Poisson model. We adopt the Gini coefficient to be applicable to the spatial scan statistic for ordinal data to determine the optimal maximum reported cluster size. Through a simulation study and application to a real data example, we evaluate the performance of the proposed approach. With some sophisticated modification, the Gini coefficient can be effectively employed for the ordinal model. The Gini coefficient most often picked the optimal maximum reported cluster sizes that were the same as or smaller than the true cluster sizes with very high accuracy. It seems that we can obtain a more refined collection of clusters by using the Gini coefficient. The Gini coefficient developed specifically for the ordinal model can be useful for optimizing the maximum reported cluster size for ordinal data and helpful for properly and informatively discovering cluster patterns. PMID:28753674

Right ventricle functional parameters estimation in arrhythmogenic right ventricular dysplasia using a robust shape based deformable model.

PubMed

Oghli, Mostafa Ghelich; Dehlaghi, Vahab; Zadeh, Ali Mohammad; Fallahi, Alireza; Pooyan, Mohammad

2014-07-01

Assessment of cardiac right-ventricle functions plays an essential role in diagnosis of arrhythmogenic right ventricular dysplasia (ARVD). Among clinical tests, cardiac magnetic resonance imaging (MRI) is now becoming the most valid imaging technique to diagnose ARVD. Fatty infiltration of the right ventricular free wall can be visible on cardiac MRI. Finding right-ventricle functional parameters from cardiac MRI images contains segmentation of right-ventricle in each slice of end diastole and end systole phases of cardiac cycle and calculation of end diastolic and end systolic volume and furthermore other functional parameters. The main problem of this task is the segmentation part. We used a robust method based on deformable model that uses shape information for segmentation of right-ventricle in short axis MRI images. After segmentation of right-ventricle from base to apex in end diastole and end systole phases of cardiac cycle, volume of right-ventricle in these phases calculated and then, ejection fraction calculated. We performed a quantitative evaluation of clinical cardiac parameters derived from the automatic segmentation by comparison against a manual delineation of the ventricles. The manually and automatically determined quantitative clinical parameters were statistically compared by means of linear regression. This fits a line to the data such that the root-mean-square error (RMSE) of the residuals is minimized. The results show low RMSE for Right Ventricle Ejection Fraction and Volume (≤ 0.06 for RV EF, and ≤ 10 mL for RV volume). Evaluation of segmentation results is also done by means of four statistical measures including sensitivity, specificity, similarity index and Jaccard index. The average value of similarity index is 86.87%. The Jaccard index mean value is 83.85% which shows a good accuracy of segmentation. The average of sensitivity is 93.9% and mean value of the specificity is 89.45%. These results show the reliability of proposed method in these cases that manual segmentation is inapplicable. Huge shape variety of right-ventricle led us to use a shape prior based method and this work can develop by four-dimensional processing for determining the first ventricular slices.

Shaping Ability of Single-file Systems with Different Movements: A Micro-computed Tomographic Study.

PubMed

Santa-Rosa, Joedy; de Sousa-Neto, Manoel Damião; Versiani, Marco Aurelio; Nevares, Giselle; Xavier, Felipe; Romeiro, Kaline; Cassimiro, Marcely; Leoni, Graziela Bianchi; de Menezes, Rebeca Ferraz; Albuquerque, Diana

2016-01-01

This study aimed to perform a rigorous sample standardization and also evaluate the preparation of mesiobuccal (MB) root canals of maxillary molars with severe curvatures using two single-file engine-driven systems (WaveOne with reciprocating motion and OneShape with rotary movement), using micro-computed tomography (micro-CT). Ten MB roots with single canals were included, uniformly distributed into two groups (n=5). The samples were prepared with a WaveOne or OneShape files. The shaping ability and amount of canal transportation were assessed by a comparison of the pre- and post-instrumentation micro-CT scans. The Kolmogorov-Smirnov and t-tests were used for statistical analysis. The level of significance was set at 0.05. Instrumentation of canals increased their surface area and volume. Canal transportation occurred in coronal, middle and apical thirds and no statistical difference was observed between the two systems (P>0.05). In apical third, significant differences were found between groups in canal roundness (in 3 mm level) and perimeter (in 3 and 4 mm levels) (P<0.05). The WaveOne and One Shape single-file systems were able to shape curved root canals, producing minor changes in the canal curvature.

Dark-ages reionization and galaxy formation simulation V: morphology and statistical signatures of reionization

NASA Astrophysics Data System (ADS)

Geil, Paul M.; Mutch, Simon J.; Poole, Gregory B.; Angel, Paul W.; Duffy, Alan R.; Mesinger, Andrei; Wyithe, J. Stuart B.

2016-10-01

We use the Dark-ages, Reionization And Galaxy formation Observables from Numerical Simulations (DRAGONS) framework to investigate the effect of galaxy formation physics on the morphology and statistics of ionized hydrogen (H II) regions during the Epoch of Reioinization (EoR). DRAGONS self-consistently couples a semi-analytic galaxy formation model with the inhomogeneous ionizing UV background, and can therefore be used to study the dependence of morphology and statistics of reionization on feedback phenomena of the ionizing source galaxy population. Changes in galaxy formation physics modify the sizes of H II regions and the amplitude and shape of 21-cm power spectra. Of the galaxy physics investigated, we find that supernova feedback plays the most important role in reionization, with H II regions up to ≈20 per cent smaller and a fractional difference in the amplitude of power spectra of up to ≈17 per cent at fixed ionized fraction in the absence of this feedback. We compare our galaxy formation-based reionization models with past calculations that assume constant stellar-to-halo mass ratios and find that with the correct choice of minimum halo mass, such models can mimic the predicted reionization morphology. Reionization morphology at fixed neutral fraction is therefore not uniquely determined by the details of galaxy formation, but is sensitive to the mass of the haloes hosting the bulk of the ionizing sources. Simple EoR parametrizations are therefore accurate predictors of reionization statistics. However, a complete understanding of reionization using future 21-cm observations will require interpretation with realistic galaxy formation models, in combination with other observations.

Suppression pattern of neutral pions at high transverse momentum in Au + Au collisions at sqrt[sNN]=200 GeV and constraints on medium transport coefficients.

PubMed

Adare, A; Afanasiev, S; Aidala, C; Ajitanand, N N; Akiba, Y; Al-Bataineh, H; Alexander, J; Al-Jamel, A; Aoki, K; Aphecetche, L; Armendariz, R; Aronson, S H; Asai, J; Atomssa, E T; Averbeck, R; Awes, T C; Azmoun, B; Babintsev, V; Baksay, G; Baksay, L; Baldisseri, A; Barish, K N; Barnes, P D; Bassalleck, B; Bathe, S; Batsouli, S; Baublis, V; Bauer, F; Bazilevsky, A; Belikov, S; Bennett, R; Berdnikov, Y; Bickley, A A; Bjorndal, M T; Boissevain, J G; Borel, H; Boyle, K; Brooks, M L; Brown, D S; Bucher, D; Buesching, H; Bumazhnov, V; Bunce, G; Burward-Hoy, J M; Butsyk, S; Campbell, S; Chai, J-S; Chang, B S; Charvet, J-L; Chernichenko, S; Chiba, J; Chi, C Y; Chiu, M; Choi, I J; Chujo, T; Chung, P; Churyn, A; Cianciolo, V; Cleven, C R; Cobigo, Y; Cole, B A; Comets, M P; Constantin, P; Csanád, M; Csörgo, T; Dahms, T; Das, K; David, G; Deaton, M B; Dehmelt, K; Delagrange, H; Denisov, A; d'Enterria, D; Deshpande, A; Desmond, E J; Dietzsch, O; Dion, A; Donadelli, M; Drachenberg, J L; Drapier, O; Drees, A; Dubey, A K; Durum, A; Dzhordzhadze, V; Efremenko, Y V; Egdemir, J; Ellinghaus, F; Emam, W S; Enokizono, A; En'yo, H; Espagnon, B; Esumi, S; Eyser, K O; Fields, D E; Finger, M; Finger, M; Fleuret, F; Fokin, S L; Forestier, B; Fraenkel, Z; Frantz, J E; Franz, A; Frawley, A D; Fujiwara, K; Fukao, Y; Fung, S-Y; Fusayasu, T; Gadrat, S; Garishvili, I; Gastineau, F; Germain, M; Glenn, A; Gong, H; Gonin, M; Gosset, J; Goto, Y; de Cassagnac, R Granier; Grau, N; Greene, S V; Perdekamp, M Grosse; Gunji, T; Gustafsson, H-A; Hachiya, T; Henni, A Hadj; Haegemann, C; Haggerty, J S; Hagiwara, M N; Hamagaki, H; Han, R; Harada, H; Hartouni, E P; Haruna, K; Harvey, M; Haslum, E; Hasuko, K; Hayano, R; Heffner, M; Hemmick, T K; Hester, T; Heuser, J M; He, X; Hiejima, H; Hill, J C; Hobbs, R; Hohlmann, M; Holmes, M; Holzmann, W; Homma, K; Hong, B; Horaguchi, T; Hornback, D; Hur, M G; Ichihara, T; Imai, K; Imrek, J; Inaba, M; Inoue, Y; Isenhower, D; Isenhower, L; Ishihara, M; Isobe, T; Issah, M; Isupov, A; Jacak, B V; Jia, J; Jin, J; Jinnouchi, O; Johnson, B M; Joo, K S; Jouan, D; Kajihara, F; Kametani, S; Kamihara, N; Kamin, J; Kaneta, M; Kang, J H; Kanou, H; Kawagishi, T; Kawall, D; Kazantsev, A V; Kelly, S; Khanzadeev, A; Kikuchi, J; Kim, D H; Kim, D J; Kim, E; Kim, Y-S; Kinney, E; Kiss, A; Kistenev, E; Kiyomichi, A; Klay, J; Klein-Boesing, C; Kochenda, L; Kochetkov, V; Komkov, B; Konno, M; Kotchetkov, D; Kozlov, A; Král, A; Kravitz, A; Kroon, P J; Kubart, J; Kunde, G J; Kurihara, N; Kurita, K; Kweon, M J; Kwon, Y; Kyle, G S; Lacey, R; Lai, Y-S; Lajoie, J G; Lebedev, A; Le Bornec, Y; Leckey, S; Lee, D M; Lee, M K; Lee, T; Leitch, M J; Leite, M A L; Lenzi, B; Lim, H; Liska, T; Litvinenko, A; Liu, M X; Li, X; Li, X H; Love, B; Lynch, D; Maguire, C F; Makdisi, Y I; Malakhov, A; Malik, M D; Manko, V I; Mao, Y; Masek, L; Masui, H; Matathias, F; McCain, M C; McCumber, M; McGaughey, P L; Miake, Y; Mikes, P; Miki, K; Miller, T E; Milov, A; Mioduszewski, S; Mishra, G C; Mishra, M; Mitchell, J T; Mitrovski, M; Morreale, A; Morrison, D P; Moss, J M; Moukhanova, T V; Mukhopadhyay, D; Murata, J; Nagamiya, S; Nagata, Y; Nagle, J L; Naglis, M; Nakagawa, I; Nakamiya, Y; Nakamura, T; Nakano, K; Newby, J; Nguyen, M; Norman, B E; Nyanin, A S; Nystrand, J; O'Brien, E; Oda, S X; Ogilvie, C A; Ohnishi, H; Ojha, I D; Okada, H; Okada, K; Oka, M; Omiwade, O O; Oskarsson, A; Otterlund, I; Ouchida, M; Ozawa, K; Pak, R; Pal, D; Palounek, A P T; Pantuev, V; Papavassiliou, V; Park, J; Park, W J; Pate, S F; Pei, H; Peng, J-C; Pereira, H; Peresedov, V; Peressounko, D Yu; Pinkenburg, C; Pisani, R P; Purschke, M L; Purwar, A K; Qu, H; Rak, J; Rakotozafindrabe, A; Ravinovich, I; Read, K F; Rembeczki, S; Reuter, M; Reygers, K; Riabov, V; Riabov, Y; Roche, G; Romana, A; Rosati, M; Rosendahl, S S E; Rosnet, P; Rukoyatkin, P; Rykov, V L; Ryu, S S; Sahlmueller, B; Saito, N; Sakaguchi, T; Sakai, S; Sakata, H; Samsonov, V; Sato, H D; Sato, S; Sawada, S; Seele, J; Seidl, R; Semenov, V; Seto, R; Sharma, D; Shea, T K; Shein, I; Shevel, A; Shibata, T-A; Shigaki, K; Shimomura, M; Shohjoh, T; Shoji, K; Sickles, A; Silva, C L; Silvermyr, D; Silvestre, C; Sim, K S; Singh, C P; Singh, V; Skutnik, S; Slunecka, M; Smith, W C; Soldatov, A; Soltz, R A; Sondheim, W E; Sorensen, S P; Sourikova, I V; Staley, F; Stankus, P W; Stenlund, E; Stepanov, M; Ster, A; Stoll, S P; Sugitate, T; Suire, C; Sullivan, J P; Sziklai, J; Tabaru, T; Takagi, S; Takagui, E M; Taketani, A; Tanaka, K H; Tanaka, Y; Tanida, K; Tannenbaum, M J; Taranenko, A; Tarján, P; Thomas, T L; Togawa, M; Toia, A; Tojo, J; Tomásek, L; Torii, H; Towell, R S; Tram, V-N; Tserruya, I; Tsuchimoto, Y; Tuli, S K; Tydesjö, H; Tyurin, N; Vale, C; Valle, H; van Hecke, H W; Velkovska, J; Vertesi, R; Vinogradov, A A; Virius, M; Vrba, V; Vznuzdaev, E; Wagner, M; Walker, D; Wang, X R; Watanabe, Y; Wessels, J; White, S N; Willis, N; Winter, D; Woody, C L; Wysocki, M; Xie, W; Yamaguchi, Y L; Yanovich, A; Yasin, Z; Ying, J; Yokkaichi, S; Young, G R; Younus, I; Yushmanov, I E; Zajc, W A; Zaudtke, O; Zhang, C; Zhou, S; Zimányi, J; Zolin, L

2008-12-05

For Au + Au collisions at 200 GeV, we measure neutral pion production with good statistics for transverse momentum, pT, up to 20 GeV/c. A fivefold suppression is found, which is essentially constant for 5 < pT < 20 GeV/c. Experimental uncertainties are small enough to constrain any model-dependent parametrization for the transport coefficient of the medium, e.g., q in the parton quenching model. The spectral shape is similar for all collision classes, and the suppression does not saturate in Au + Au collisions.

Automatic firearm class identification from cartridge cases

NASA Astrophysics Data System (ADS)

Kamalakannan, Sridharan; Mann, Christopher J.; Bingham, Philip R.; Karnowski, Thomas P.; Gleason, Shaun S.

2011-03-01

We present a machine vision system for automatic identification of the class of firearms by extracting and analyzing two significant properties from spent cartridge cases, namely the Firing Pin Impression (FPI) and the Firing Pin Aperture Outline (FPAO). Within the framework of the proposed machine vision system, a white light interferometer is employed to image the head of the spent cartridge cases. As a first step of the algorithmic procedure, the Primer Surface Area (PSA) is detected using a circular Hough transform. Once the PSA is detected, a customized statistical region-based parametric active contour model is initialized around the center of the PSA and evolved to segment the FPI. Subsequently, the scaled version of the segmented FPI is used to initialize a customized Mumford-Shah based level set model in order to segment the FPAO. Once the shapes of FPI and FPAO are extracted, a shape-based level set method is used in order to compare these extracted shapes to an annotated dataset of FPIs and FPAOs from varied firearm types. A total of 74 cartridge case images non-uniformly distributed over five different firearms are processed using the aforementioned scheme and the promising nature of the results (95% classification accuracy) demonstrate the efficacy of the proposed approach.

Statistical validation of brain tumor shape approximation via spherical harmonics for image-guided neurosurgery.

PubMed

Goldberg-Zimring, Daniel; Talos, Ion-Florin; Bhagwat, Jui G; Haker, Steven J; Black, Peter M; Zou, Kelly H

2005-04-01

Surgical planning now routinely uses both two-dimensional (2D) and three-dimensional (3D) models that integrate data from multiple imaging modalities, each highlighting one or more aspects of morphology or function. We performed a preliminary evaluation of the use of spherical harmonics (SH) in approximating the 3D shape and estimating the volume of brain tumors of varying characteristics. Magnetic resonance (MR) images from five patients with brain tumors were selected randomly from our MR-guided neurosurgical practice. Standardized mean square reconstruction errors (SMSRE) by tumor volume were measured. Validation metrics for comparing performances of the SH method against segmented contours (SC) were the dice similarity coefficient (DSC) and standardized Euclidean distance (SED) measure. Tumor volume range was 22,413-85,189 mm3, and range of number of vertices in triangulated models was 3674-6544. At SH approximations with degree of at least 30, SMSRE were within 1.66 x 10(-5) mm(-1). Summary measures yielded a DSC range of 0.89-0.99 (pooled median, 0.97 and significantly >0.7; P < .001) and an SED range of 0.0002-0.0028 (pooled median, 0.0005). 3D shapes of tumors may be approximated by using SH for neurosurgical applications.

Sensitivities of the hydrologic cycle to model physics, grid resolution, and ocean type in the aquaplanet Community Atmosphere Model

NASA Astrophysics Data System (ADS)

Benedict, James J.; Medeiros, Brian; Clement, Amy C.; Pendergrass, Angeline G.

2017-06-01

Precipitation distributions and extremes play a fundamental role in shaping Earth's climate and yet are poorly represented in many global climate models. Here, a suite of idealized Community Atmosphere Model (CAM) aquaplanet simulations is examined to assess the aquaplanet's ability to reproduce hydroclimate statistics of real-Earth configurations and to investigate sensitivities of precipitation distributions and extremes to model physics, horizontal grid resolution, and ocean type. Little difference in precipitation statistics is found between aquaplanets using time-constant sea-surface temperatures and those implementing a slab ocean model with a 50 m mixed-layer depth. In contrast, CAM version 5.3 (CAM5.3) produces more time mean, zonally averaged precipitation than CAM version 4 (CAM4), while CAM4 generates significantly larger precipitation variance and frequencies of extremely intense precipitation events. The largest model configuration-based precipitation sensitivities relate to choice of horizontal grid resolution in the selected range 1-2°. Refining grid resolution has significant physics-dependent effects on tropical precipitation: for CAM4, time mean zonal mean precipitation increases along the Equator and the intertropical convergence zone (ITCZ) narrows, while for CAM5.3 precipitation decreases along the Equator and the twin branches of the ITCZ shift poleward. Increased grid resolution also reduces light precipitation frequencies and enhances extreme precipitation for both CAM4 and CAM5.3 resulting in better alignment with observational estimates. A discussion of the potential implications these hydrologic cycle sensitivities have on the interpretation of precipitation statistics in future climate projections is also presented.