Global Tracking Algorithm Research Articles

Optimization and validation of diffusion MRI-based fiber tracking with neural tracer data as a reference

Diffusion-weighted magnetic resonance imaging (dMRI) allows non-invasive investigation of whole-brain connectivity, which can reveal the brain’s global network architecture and also abnormalities involved in neurological and mental disorders. However, the reliability of connection inferences from dMRI-based fiber tracking is still debated, due to low sensitivity, dominance of false positives, and inaccurate and incomplete reconstruction of long-range connections. Furthermore, parameters of tracking algorithms are typically tuned in a heuristic way, which leaves room for manipulation of an intended result. Here we propose a general data-driven framework to optimize and validate parameters of dMRI-based fiber tracking algorithms using neural tracer data as a reference. Japan’s Brain/MINDS Project provides invaluable datasets containing both dMRI and neural tracer data from the same primates. A fundamental difference when comparing dMRI-based tractography and neural tracer data is that the former cannot specify the direction of connectivity; therefore, evaluating the fitting of dMRI-based tractography becomes challenging. The framework implements multi-objective optimization based on the non-dominated sorting genetic algorithm II. Its performance is examined in two experiments using data from ten subjects for optimization and six for testing generalization. The first uses a seed-based tracking algorithm, iFOD2, and objectives for sensitivity and specificity of region-level connectivity. The second uses a global tracking algorithm and a more refined set of objectives: distance-weighted coverage, true/false positive ratio, projection coincidence, and commissural passage. In both experiments, with optimized parameters compared to default parameters, fiber tracking performance was significantly improved in coverage and fiber length. Improvements were more prominent using global tracking with refined objectives, achieving an average fiber length from 10 to 17 mm, voxel-wise coverage of axonal tracts from 0.9 to 15%, and the correlation of target areas from 40 to 68%, while minimizing false positives and impossible cross-hemisphere connections. Optimized parameters showed good generalization capability for test brain samples in both experiments, demonstrating the flexible applicability of our framework to different tracking algorithms and objectives. These results indicate the importance of data-driven adjustment of fiber tracking algorithms and support the validity of dMRI-based tractography, if appropriate adjustments are employed.

Alterations of intracerebral connectivity in epilepsy patients with secondary bilateral synchrony

IntroductionThe aim of our study was to evaluate intracerebral network changes in epilepsy patients demonstrating secondary bilateral synchrony (SBS) in EEG by applying a new Diffusion Tensor Imaging (DTI) method using an energy-based global tracking algorithm. Materials and methods10 MRI negative epilepsy patients demonstrating SBS in 10–20 surface EEG were included. EEG findings were analyzed for irritative zones characterized by focal interictal epileptiform discharges (IEDs) triggering SBS. In addition, DTI including an energy-based global tracking algorithm was applied to analyze fiber tract alterations in irritative zones. To measure the deviation of a certain cortical connection in comparison to healthy controls, normalized differences of fiber tract streamline counts (SC) and their p-values were evaluated in comparison to corresponding fibers of the control group. ResultsIn 6 patients the irritative zone initiating SBS was located in the frontal lobe, in 3 patients in the temporal lobe and in 1 patient in the region surrounding the right central sulcus. All patients demonstrated significantly altered SC in brain lobes where the irritative zone triggering SBS was located (p ≤ 0.05). Seven out of 10 patients demonstrated SC alterations in tracts connecting brain lobes between the ipsilateral and the contralateral hemisphere (p ≤ 0.05). ConclusionOur data demonstrate that alterations in fiber tracts in irritative zones triggering SBS are not necessarily associated with intracerebral lesions visible in high resolution MRI. Our study gives evidence that diffusion tensor imaging is a promising non-invasive additive tool for intracerebral network analyses even in MRI-negative epilepsy patients.

FPGA Implementation for the Linking of Cell Tracks Using New Structure Algorithm

In microscopy images automatically tracking of living cells is an important and challenging problem. So this paper will concentrate on global tracking algorithm, which links cell outlines generated by a segmentation algorithm into tracks. This is attained eventually finding those tracks which provide for the biggest can be allowed to build with probabilistic persuaded scoring function, utilizing another structure calculation. This paper provided for the vitality about advanced image transforming and the noteworthiness for their usage ahead FPGAs should accomplish exceptional performance, this fills in addresses of the execution of image transforming calculations in average filter, morphological, convolution furthermore smoothing operation and then edge identification on FPGA utilizing VHDL language.

An Improved Damage Mechanics Method for Solving Three Dimensional Crack Problems of Concrete

In this paper, a damage mechanical model is improved to simulate the three-dimensional (3D) mixed mode cracking process of quasi-brittle material such as concrete. The cracking and crack propagating in an element is reflected in the model by controlling the degraded stiffness matrix and the dissipated energy. The local tracking algorithm (LTA) is employed to preselect the element that will belong to the crack path to be damaged. The local tracking algorithm is extended to 3D by analyzing and overcoming defects in the previous 3D LTAs. The present LTA has very low computational cost and this fact is proved by comparison with well-known global tracking algorithm. The numerical results from the novel damage model added 3D local tracking algorithm show good agreement with the results of the previous researches, demonstrating the superior performance of the approach in predicting crack propagation and fracture strength.

Bilateral cingulum fiber reductions in temporal lobe epilepsy with unilateral hippocampal sclerosis

PurposeTo evaluate whether white matter tracts within the Papez circuit are altered in patients with unilateral hippocampal sclerosis (HS). MethodsTwenty patients with histologically proven unilateral HS and 20 age-matched controls were studied with a 3T Epilepsy-dedicated MRI protocol including a MPRAGE sequence for hippocampus volumetry and a diffusion tensor imaging (DTI) sequence (61 diffusion-encoding directions, 2×2×2mm3 voxels) for diffusion tensor tractography (DTT). An energy-based global tracking algorithm was used to calculate streamline counts (SC) and fractional anisotropy (FA) of cingulate, fornix, and mammillo-thalamic tracts, respectively. ResultsSclerotic hippocampi were significantly smaller compared to the contralateral side and to age-matched controls. Cingulum SC but not FA were reduced on the hippocampal sclerosis (258+81.0) and contralateral side (271+85.6) compared to age-matched controls (447+138). ConclusionFocusing on white matter tracts of the Papez circuit we showed that in patients with intractable temporal lobe epilepsy unilateral hippocampal sclerosis is associated with a bilateral reduction of cingulum association fibers projecting from the cingulate gyrus to the parahippocampal gyrus.

Stochastic Fracture Response and Crack Growth Analysis of Laminated Composite Edge Crack Beams Using Extended Finite Element Method

This paper presents a stochastic fracture response and crack growth analysis of mixed-mode stress intensity factors (MSIFs) for edge cracked laminated composite beams subjected to uniaxial, uniform tensile, shear and combined stresses with random system properties. The randomness in material properties of the composite material, lamination angle, laminate thickness, the crack length and the crack angle are modeled as both input uncorrelated and correlated random variables. An extended finite element method (XFEM) through the so-called M-interaction approach combined with the second-order perturbation technique (SOPT) and Monte Carlo simulation (MCS) is used to obtain the statistics in terms of the mean and coefficient of variation (COV) of MSIFs for edge cracked laminated composite beams. The effect of crack propagation on the MSIFs in the presence of tensile, shear and combined stresses using a global tracking algorithm is also investigated. The results using the present approach are compared with the available published results. A good agreement is seen whenever alternative results are available.

Stochastic fracture analysis of laminated composite plate with arbitrary cracks using X-FEM

In this paper, second order statistics of mixed mode stress intensity factors (MSIFs) and crack propagation analysis of the symmetric angle ply laminated composite plate with through thickness arbitrary curve cracks subjected to tensile and shear stress is presented. The fracture behaviour is analysed using extended finite element method (X-FEM). The cracks like line, semi elliptical, semi circular and arbitrary curves are considered for the detailed numerical study. The material properties, lamination angle, loading, crack width and crack depth are modelled as independent, combine uncorrelated and correlated input random Gaussian variables. The interaction integral (M-integral) is adopted for calculating the MSIFs. The second order perturbation technique and Monte Carlo simulations are proposed to obtain the mean and coefficient of variance of MSIFs by random change in input system parameters. This work signifies the accurate and realistic evaluation of fracture response by handling the various levels of uncertainties. The effect of crack propagation on MSIFs using tensile and shear stresses using global tracking algorithm is also highlighted.

Tractography of Association Fibers Associated with Language Processing.

Several major association fiber tracts are known to be part of the language processing system. There is evidence that high angular diffusion-based MRI is able to separate these fascicles in a constant way. In this study, we wanted to proof this thesis using a novel whole brain "global tracking" approach and to test for possible lateralization. Global tracking was performed in six healthy right-handed volunteers for the arcuate fascicle (AF), the medial longitudinal fascicle (MdLF), the inferior fronto-occipital fascicle (IFOF), and the inferior longitudinal fascicle (ILF). These fiber tracts were characterized quantitatively using the number of streamlines (SL) and the mean fractional anisotropy (FA). We were able to characterize the AF, the MdLF, the IFOF, and the ILF consistently in six healthy volunteers using global tracking. A left-sided dominance (LI > 0.2) for the AF was found in all participants. The MdLF showed a left-sided dominance in four participants (one female, three male). Regarding the FA, no lateralization (LI > 0.2) could be shown in any of the fascicles. Using a novel global tracking algorithm we confirmed that the courses of the primary language processing associated fascicles can consistently be differentiated. Additionally we were able to show a streamline-based left-sided lateralization in the AF of all right-handed healthy subjects.

Local and Global Fiber Tractography in Patients with Epilepsy

Fiber tractography is increasingly used in the preoperative evaluation of endangered fiber bundles. From a clinical point of view, an accurate and methodologically transparent procedure is desired. Our aim was to evaluate the recently described global tracking algorithm compared with other established methods, such as deterministic and probabilistic tractography. Twenty patients, candidates for excision of epileptogenic lesions, were subjected to higher-angular resolution diffusion imaging-based fiber tractography. Seed points were created without manual bias, predominantly by FreeSurfer and voxel-based atlases. We focused on 2 important fiber bundles, namely the descending motor pathways and the optic radiation. Postoperatively, the accuracy of the predicted fiber route was controlled by structural MR imaging and by inflicted functional deficits. Among the 3 evaluated methods, global tracking was the only method capable of reconstructing the full extent of the descending motor pathways, including corticobulbar fibers from the area of face representation. Still, probabilistic tractography depicted the optic radiation better, especially the Meyer loop. The deterministic algorithm performed less adequately. The probabilistic method seems to be the best balance between computational time and effectiveness and seems to be the best choice in most cases, particularly for the optic radiation. If, however, a detailed depiction of the fiber anatomy is intended and tract crossings are implicated, then the computationally time-consuming global tracking should be preferred.

The structural–functional connectome and the default mode network of the human brain

An emerging field of human brain imaging deals with the characterization of the connectome, a comprehensive global description of structural and functional connectivity within the human brain. However, the question of how functional and structural connectivity are related has not been fully answered yet. Here, we used different methods to estimate the connectivity between each voxel of the cerebral cortex based on functional magnetic resonance imaging (fMRI) and diffusion tensor imaging (DTI) data in order to obtain observer-independent functional–structural connectomes of the human brain. Probabilistic fiber-tracking and a novel global fiber-tracking technique were used to measure structural connectivity whereas for functional connectivity, full and partial correlations between each voxel pair's fMRI-timecourses were calculated. For every voxel, two vectors consisting of functional and structural connectivity estimates to all other voxels in the cortex were correlated with each other. In this way, voxels structurally and functionally connected to similar regions within the rest of the brain could be identified. Areas forming parts of the ‘default mode network’ (DMN) showed the highest agreement of structure–function connectivity. Bilateral precuneal and inferior parietal regions were found using all applied techniques, whereas the global tracking algorithm additionally revealed bilateral medial prefrontal cortices and early visual areas. There were no significant differences between the results obtained from full and partial correlations. Our data suggests that the DMN is the functional brain network, which uses the most direct structural connections. Thus, the anatomical profile of the brain seems to shape its functional repertoire and the computation of the whole-brain functional–structural connectome appears to be a valuable method to characterize global brain connectivity within and between populations.

A marching cubes based failure surface propagation concept for three‐dimensional finite elements with non‐planar embedded strong discontinuities of higher‐order kinematics

SUMMARYThis paper presents an advanced failure surface propagation concept based on the marching cubes algorithm initially proposed in the field of computer graphics and applies it to the embedded finite element method. When modeling three‐dimensional (3D) solids at failure, the propagation of the failure surface representing a crack or shear band should not exhibit a strong sensitivity to the details of the finite element discretization. This results in the need for a propagation of the discrete failure zone through the individual finite elements, which is possible for finite elements with embedded strong discontinuities. Whereas for two‐dimensional calculations the failure zone propagation location is easily predicted by the maximal principal stress direction, more advanced strategies are needed to achieve a smooth failure surface in 3D simulations. An example for such method is the global tracking algorithm, which predicts the crack path by a scalar level set function computed on the basis of the solution of a simplified heat conduction like problem. Its prediction may though lead to various scenarios on how the failure surface may propagate through the individual finite elements. In particular, for a hexahedral eight‐node finite element, 256 such cases exist. To capture all those possibilities, the marching cubes algorithm is combined with the global tracking algorithm and the finite elements with embedded strong discontinuities in this work. In addition, because many of the possible cases result in non‐planar failure surfaces within a single finite element and because the local quantities used to describe the kinematics of the embedded strong discontinuities are physically meaningful in a strict sense only for planar failure surfaces, a remedy for such scenarios is proposed. Various 3D failure propagation simulations outline the performance of the proposed concept. Copyright © 2013 John Wiley & Sons, Ltd.

New three‐dimensional finite elements with embedded strong discontinuities to model solids at failure

AbstractThis work focuses on the development of new finite elements which can capture strong discontinuities in three‐dimensional failure problems. The displacement jumps in the solid are approximated by a linear interpolation obtained by enforcing a new class of enhanced separation modes to exactly be satisfied by the formulation. Efforts are also put towards the development of a proper crack propagation tracking algorithm needed for the complicated crack surfaces appearing in realistic 3D failure simulations, based on a combination of the global tracking algorithm and the marching cubes algorithm. (© 2012 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Combining object and feature dynamics in probabilistic tracking

Objects can exhibit different dynamics at different spatio-temporal scales, a property that is often exploited by visual tracking algorithms. A local dynamic model is typically used to extract image features that are then used as inputs to a system for tracking the object using a global dynamic model. Approximate local dynamics may be brittle—point trackers drift due to image noise and adaptive background models adapt to foreground objects that become stationary—and constraints from the global model can make them more robust. We propose a probabilistic framework for incorporating knowledge about global dynamics into the local feature extraction processes. A global tracking algorithm can be formulated as a generative model and used to predict feature values thereby influencing the observation process of the feature extractor, which in turn produces feature values that are used in high-level inference. We combine such models utilizing a multichain graphical model framework. We show the utility of our framework for improving feature tracking as well as shape and motion estimates in a batch factorization algorithm. We also propose an approximate filtering algorithm appropriate for online applications and demonstrate its application to tasks in background subtraction, structure from motion and articulated body tracking.