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In the largest sample studied to date, white matter microstructural trajectories and their relation to persistent symptoms were examined after pediatric mild traumatic brain injury (mTBI). This prospective, longitudinal cohort study recruited children aged 8-16.99 years with mTBI or mild orthopedic injury (OI) from five pediatric emergency departments. Children's pre-injury and 1-month post-injury symptom ratings were used to classify mTBI with or without persistent symptoms. Children completed diffusion-weighted imaging at post-acute (2-33 days post-injury) and chronic (3 or 6 months via random assignment) post-injury assessments. Mean diffusivity (MD) and fractional anisotropy (FA) were derived for 18 white matter tracts in 560 children (362 mTBI/198 OI), 407 with longitudinal data. Superior longitudinal fasciculus FA was higher in mTBI without persistent symptoms relative to OI, d (95% confidence interval) = 0.31 to 0.37 (0.02, 0.68), across time. In younger children, MD of the anterior thalamic radiations was higher in mTBI with persistent symptoms relative to both mTBI without persistent symptoms, 1.43 (0.59, 2.27), and OI, 1.94 (1.07, 2.81). MD of the arcuate fasciculus, -0.58 (-1.04, -0.11), and superior longitudinal fasciculus, -0.49 (-0.90, -0.09) was lower in mTBI without persistent symptoms relative to OI at 6 months post-injury. White matter microstructural changes suggesting neuroinflammation and axonal swelling occurred chronically and continued 6 months post injury in children with mTBI, especially in younger children with persistent symptoms, relative to OI. White matter microstructure appears more organized in children without persistent symptoms, consistent with their better clinical outcomes.

Introduction: Children with a history of bronchopulmonary dysplasia (BPD) may have lower physical activity levels, but evidence to date is based on self-report. This study compared physical activity levels between children born extremely preterm with and without history of BPD, and examined their associations with pulmonary magnetic resonance imaging (MRI) and pulmonary function test (PFT) indices. Methods: This multi-centre cross-sectional study included children aged 7-9 years born extremely preterm, with and without BPD. Children wore a pedometer for one week, then completed the Physical Activity Questionnaire (PAQ), pulmonary MRI, and PFT. Spearman correlations and multivariable linear regression modelling were performed. Results: Of 45 children, 28 had a history of moderate-severe BPD. There were no differences in any physical activity outcomes by BPD status. Higher average daily step count and higher average daily moderate-vigorous physical activity (MVPA) were each correlated with greater forced vital capacity (r=0.41 and 0.58), greater MRI lung proton density at full expiration (r=0.42 and 0.49), and lower lung clearance index (r=-0.50 and -0.41). After adjusting for MRI total proton density and BPD status, a 5% increase in forced expiratory volume at one second was associated with 738 (95%CI: 208, 1268) more steps per day and 0.1 (0.0, 0.2) more hours of MVPA, respectively. Conclusion: School-aged children born extremely preterm have similar physical activity levels to their peers, regardless of history of BPD. MRI and PFT measures suggestive of gas trapping and/or airflow obstruction are associated with lower physical activity levels.

OBJECTIVE Vagus nerve stimulation (VNS) is a common treatment for medically intractable epilepsy, but response rates are highly variable, with no preoperative means of identifying good candidates. This study aimed to predict VNS response using structural and functional connectomic profiling. METHODS Fifty-six children, comprising discovery (n = 38) and validation (n = 18) cohorts, were recruited from 3 separate institutions. Diffusion tensor imaging was used to identify group differences in white matter microstructure, which in turn informed beamforming of resting-state magnetoencephalography recordings. The results were used to generate a support vector machine learning classifier, which was independently validated. This algorithm was compared to a second classifier generated using 31 clinical covariates. RESULTS Treatment responders demonstrated greater fractional anisotropy in left thalamocortical, limbic, and association fibers, as well as greater connectivity in a functional network encompassing left thalamic, insular, and temporal nodes (p

Introduction Paediatric mild traumatic brain injury (mTBI) is a public health burden. Clinicians urgently need evidence-based guidance to manage mTBI, but gold standards for diagnosing and predicting the outcomes of mTBI are lacking. The objective of the Advancing Concussion Assessment in Pediatrics (A-CAP) study is to assess a broad pool of neurobiological and psychosocial markers to examine associations with postinjury outcomes in a large sample of children with either mTBI or orthopaedic injury (OI), with the goal of improving the diagnosis and prognostication of outcomes of paediatric mTBI. Methods and analysis A-CAP is a prospective, longitudinal cohort study of children aged 8.00–16.99 years with either mTBI or OI, recruited during acute emergency department (ED) visits at five sites from the Pediatric Emergency Research Canada network. Injury information is collected in the ED; follow-up assessments at 10 days and 3 and 6 months postinjury measure a variety of neurobiological and psychosocial markers, covariates/confounders and outcomes. Weekly postconcussive symptom ratings are obtained electronically. Recruitment began in September 2016 and will occur for approximately 24 months. Analyses will test the major hypotheses that neurobiological and psychosocial markers can: (1) differentiate mTBI from OI and (2) predict outcomes of mTBI. Models initially will focus within domains (eg, genes, imaging biomarkers, psychosocial markers), followed by multivariable modelling across domains. The planned sample size (700 mTBI, 300 OI) provides adequate statistical power and allows for internal cross-validation of some analyses. Ethics and dissemination The ethics boards at all participating institutions have approved the study and all participants and their parents will provide informed consent or assent. Dissemination will follow an integrated knowledge translation plan, with study findings presented at scientific conferences and in multiple manuscripts in peer-reviewed journals.

We propose a fast stereoradiographic reconstruction method for the spine. Semiautomatic detection of the vertebral bodies' corners is obtained using splines, multi-scale analysis and dynamic programming. These points, combined with calibration data, delimit a hexahedron in space where we can match the vertebral body. This hexahedron is then passed through a 3D statistical database built using local and global information generated from a bank of normal and scoliotic spines. Finally, models of the vertebrae are positioned with respect to these landmarks, completing the 3D reconstruction.

This paper proposes a multi-resolution analysis (MRA) approach to vertebral body segmentation in digital radiographs. A wavelet-based technique carries out the extraction of the most significant features in the radiographs. It generates a multi-resolution edge characterization, discarding noisy artifacts in the meantime. Specific features classification and geometric alignment is then performed, using statistical data to build the. models and curvature analysis to sort the edges. An active contour scheme generates the final contours to be used in clinical studies of the spine.

We wavelet transform a non-diffracting field into a linear combination of the non-diffracting electromagnetic wavelets, which are spatially localized in the lateral direction, translated in the propagation direction and scaled in the time and temporal frequency. The non-diffracting wavelet is the window Fourier transform of the Bessel beam with a dilated temporal window. The proposed transform will be useful for analyzing the non-diffracting pulses and polychromatic beams.© (1999) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

We use the cubic spline interpolation instead of the linear interpolation of the feature space trajectories for 3-D objectrecognition from its 2-D perspective views. The accuracy of the interpolated trajectories to the testing views is greatlyenhance by this change. The experiments are on the real—world JR images of military vehicles. Edge-based approach is usedto reduce the effect of the changes in infrared image intensity distribution due to temperature changes in some running partsof vehicles.Keywords: 3-D object recognition, feature space trajectory algorithm, cubic spline regularity, wavelet transform 1. INTRODUCTION The recognition of a three-dimensional (3-D) object from its single or multiple 2-D projection images is a practical problem.Theoretically, this is an ill-posed problem, since the solution is not unique. Given a set of 2-D projection images, there couldexist different 3-D objects that could provide the same 2-D projection images at the given view angles. In general, oneassume that when a 3-D object rotates out-plane consecutively, its 2-D image varies smoothly. Hence, one can transfer the ill-pose problem to the well-posed one, by applying the regularity constraint, such as that used in the generalized radial basisfunction regularization neural network proposed by Poggio' .

We show 3D object classification from their 2D infrared images. Our feature-based approach is robust to image brightness variations due to the temperature changes. An original feature space cubic spline interpolation is introduced to build feature space trajectories for the recognition.

We review the optical wavelets proposed by Onural and the electromagnetic wavelets proposed by Kaiser. We show that the wavelet transform of the electromagnetic wavelets can be computed with the direct inner product in the space time between the field and the scaled and shifted wavelets.In the case of monochromatic field, Kaiser's physical wavelets become monochromatic spherical wavelets.

we show that the Fourier-Mellin moments can provide an invariant and orthogonal description for binary and contour images. we use the cubic spline interpolation of the feature space trajectories to improve the linear interpolation for 3-D object recognition from 2-D perspective views.

For the first time, to our knowledge, optical diffraction is shown to be a wavelet transform with the electromagnetic wavelets. We show that the optical wavelets proposed by Onural [Opt. Lett. 18, 846 (1993)] are the Huygens wavelets under a Fresnel approximation, and the electromagnetic wavelets proposed by Kaiser [A Friendly Guide to Wavelets (Birkhauser, Boston, Mass., 1994)] reduce to Hyugens wavelets in the case of a monochromatic field.

The estimation of the spatial variability of ion deposition from acid precipitation is commonly faced with the problem of sparse data networks sampled over a short period of time. In such cases, geostatistical techniques are pertinent as long as they are properly applied. According to some practical examples, the use of ordinary kriging 1 given an experimental semi-variogram function based on scattered data values can be misleading in terms of predicted estimation variances; however, the choice of additional sampling stations based on such a semi-variogram remains valid. It is also preferable to work with regularly spaced data values that allow the identification of preferential directional variabilities even from a small number of data points. In order to predict the performance of kriging, the use of semi-variogram cross-validation techniques in the presence of small data sets can be misleading and is not recommended. Finally, the integration of additional information from denser precipitation networks through the cokriging technique is questionable when based on a very small number of concomitant deposition and precipitation data values.

Ordinary kriging presents an optimal tool to estimate the spatial distribution of ion concentration from acid precipitation and produce risk-qualified maps of the phenomenon over the studied area. However, being expressed as a linear combination of data values, the kriging estimator should not be calculated directly from ion concentration values unless their corresponding precipitation volumes are essentially constant over the area. In theory, spatial linear combinations of volume-weighted concentrations should be considered, meaning that concentration estimates should be obtained by dividing kriged depositions by their corresponding kriged precipitation totals. In practice, the choice of appropriate working variables for the estimation of ion concentration will depend on the nature of the studied phenomena and on the objective of the study. In this paper, the effect of this choice on estimation results is illustrated through a comparison of experimental results obtained from the direct kriging of concentration and from the estimation of concentration by quotient. It appears that even with fairly constant precipitation totals with respect to ion concentrations and given a small correlation between both variables, discrepancies between results from the two approaches can be significant, especially at a local scale: the spatial distribution of estimated values varies locally according to each procedure, and the level of uncertainty is systematically better predicted through an estimation by quotient, even though it is based on an approximate formula. In order to avoid misleading results, the direct kriging of ion concentration should be applied only for global estimation purposes after its practical equivalence with the estimation by quotient has been appraised.