Coordinate System Representation Research Articles

Beyond the root: Geometric characterization for the diagnosis of syndromic heritable thoracic aortic diseases

Syndromic heritable thoracic aortic diseases (sHTAD), such as Marfan (MFS) or Loeys–Dietz (LDS) syndromes, involve high risk of life threatening aortic events. Diagnosis of syndromic features alone is difficult, and negative genetic tests do not necessarily exclude a genetic or hereditary condition. Periodic 3D imaging of the aorta is recommended in patients with aortic disease. Thus, an imaging-based approach aimed at identifying unique features of aortic geometry can be highly effective for diagnosing sHTAD and assessing risk. In this study, we present a method that can help identify the manifestations of sHTAD by focusing on the entire geometry of the thoracic aorta, rather than only using measurements of dilation of the aortic root. We analyze the geometric phenotype of 97 patients with genetically confirmed sHTAD (79 MF and 18 LDS) and of 45 healthy volunteers, using 3D aorta meshes obtained from phase contrast-enhanced magnetic resonance angiograms computed from 4D flow cardiac magnetic resonance. We build a geometric encoding of the aorta, based on a vessel coordinate system, and use several mathematical models to discriminate between controls and patients with sHTAD: a baseline scenario, based on aortic root dimensions only, a descriptor typically used in sHTAD patients; a low dimensional scenario, with a reduce encoding using principal component analysis; and a high-dimensional scenario, which included the full coefficient representation for geometry encoding, aiming to capture finer geometric details. The results indicate that considering the anatomy of the whole thoracic aorta can improve predictive ability. We achieve precision and sensitivity values over 0.8, with a specificity of over 70% in all the models used, while a single value classifiers (based only on aortic root diameter) demonstrated a trade-off between sensitivity and specificity. Using the mathematical properties of the vessel coordinate system representation, feature importance is mapped onto a set of anatomical traits that are used by the models to do the classification, thus providing interpretability of the results. This analysis indicates that in addition to the diameter of the aortic root, aortic elongation and a narrowing of the descending thoracic aorta may be markers of positive sHTAD.

A study on the impact of theater performing arts combined with drama arts on the stage in the context of big data

Abstract In this paper, based on the law of motion, combining the spherical coordinate system representation with the drama art of action feature recognition in the process of theatrical performance, the joint points of wrist, elbow and shoulder and the corresponding feature vectors as well as the school angular velocity are calculated. The affine invariant domain of feature matching is constructed, and the algorithms of dynamic frame difference merging and dynamic detection of human-computer interaction are applied to obtain similar feature components of the recognition of body movements and gesture commands in the process of theatrical performance. The harmony factor, emotion factor and contrast factor in the stage scene are used as evaluation parameters to derive the color evaluation function and keyframes of theatrical stage lighting combined with drama art. For the research purpose, the research on the stage influence of the theatrical performance of combining drama is designed, and the example analysis of the stage influence of the theatrical performance of combining drama is analyzed by using origin software. The results show that the level of the audience’s arousal dimension is significantly higher than its level in CSP, t(1, 29)=3.959, p<0.001, upper threshold (Engagement=0.38, Arousal=0.26), lower threshold (Engagement=0.35, Arousal=0.21), i.e., the specific performance episode for the audience to bring about significant emotional relaxation. Audience ratings of CAC were generally higher than their ratings of CSP, with differences ranging from 0.2 to 1.5. The mean times that subjects were in the “S(n)=1” state in the three modes were 219.86 (SD=60.62), 287.37 (SD=80.68), and 310.7 (SD=45.83), respectively. 45.83). This study greatly improves the impact of stage art and gives a whole new life to the combination of theater performance and drama stage art.

Lumen Segmentation in Optical Coherence Tomography Images using Convolutional Neural Network.

Lumen segmentation in Optical Coherence Tomography (OCT) images is a very important step to analyze points of interest that may help on atherosclerosis diagnostic and treatment. Past studies use many different methods to segment the lumen in IVOCT images, like level set, morphological reconstruction, Markov random fields, and Otsu binarization. Despite Convolutional Neural Networks (CNN) have shown promising results in the image processing area, we did not identify, in the literature, works applying CNN in IVOCT images. In this paper, we present the lumen segmentation using CNN. We evaluated three different CNN architectures. The CNNs were evaluated using three versions from the image dataset, differing from each other by image size (768x768 pixels and 192x192 pixels), and by coordinate system representation (Cartesian and polar). The best results, Accuracy, Dice index and Jaccard index of over 99%, 98% and 97%, respectively, were obtained with the smallest size images represented by polar coordinate system.

Drone as an autonomous aerial sensor system for motion planning

A system capable of both autonomous navigation and remote fire detection was developed from first principles. Using a complementary filter and attitude fundamentals, an Euler coordinate system representation of the aircraft’s orientation was measured using a widely available low-cost inertial measurement unit incorporating MEMS accelerometers, gyroscopes and magnetometers. Using line-of-sight guidance principles, navigation trajectories could be calculated in real-time providing autonomous navigation between user designated waypoints. A stabilisation control system using proportional-integral-derivative (PID) controllers was developed in order to achieve stabilised flight on the calculated navigation trajectories. Fire detection was facilitated with the use of three low-cost air composition sensors fed into an artificial neural network. A motion planner was developed to assist in flight planning by using topology information for the flight area to construct an optimal flight path based on distance and climb penalties.

A Map-Assisted WiFi AP Placement Algorithm Enabling Mobile Device’s Indoor Positioning

Location information and positioning technology are important to some Internet of Things (IoT) applications. The accuracy of indoor positioning using WiFi can be substantially enhanced by appropriate access point (AP) placement strategies, i.e., in a given indoor environment to deploy the WiFi APs at the locations where the mobile devices can work out their location more precisely. The plan of AP placement needs to be generated automatically by algorithms, especially for large-scale indoor environment. This paper presents an indoor map system that provides coordinate system and graphic representation. The detailed map information such as walls can be explicitly expressed and used to assist the AP placement algorithm. In this paper, AP placement is formulated into an optimization problem in which the sum of Euclidean distance of fingerprints among all the reference points (RPs) is maximized. The fingerprint at RP is predicted by an indoor radio propagation model which takes the attenuation of walls into consideration with the assistance of our indoor map. The optimization problem is solved by particle swarm optimization (PSO) and evaluated by k-nearest neighbors positioning algorithm in a real-world environment. The experimental results show that our map-assisted AP placement can provide higher positioning accuracy.

Dynamic simulation metamodeling using MARS: A case of radar simulation

Dynamic system simulations require relating the inputs to the multivariate output which can be a function of time–space coordinates. In this work, we propose a methodology for the metamodeling of dynamic simulation models via Multivariate Adaptive Regression Splines (MARS). To handle incomplete output processes, where the simulation model does not produce an output in some steps due to missing inputs, we have devised a two-stage metamodeling scheme. The methodology is demonstrated on a dynamic radar simulation model. The prediction performance of the resulting metamodel is tested with four different sampling techniques (i.e., designs) and 16 sample sizes. We also investigate the effect of alternative coordinate system representations on the metamodeling performance. The results suggest that MARS is an effective method for metamodeling dynamic simulations, particularly, when expert judgment is not readily available. Results also show that there are interactions between the coordinate systems and sampling techniques, and some design-representation-size combinations are very promising in the metamodeling of radar simulations.

Design of switching hyperplanes for multi‐inputs multi‐outputs discrete‐time linear systems

The design of sliding switching surfaces consist in finding a manifold where the controlled system dynamics are asymptotically stable. This problem has been studied for a long time, during which a wide range of designing approaches has been proposed, which can be classified into two research methodologies; the first one corresponding to eigenvalues designing approaches and the second one is based on optimal approaches. In addition, some research approaches only can be applied to specific type of systems, e.g. single-input single-output systems or continuous time systems. Finally, the performance or the level of the achieved accuracy among the different approaches varies significantly. The proposed approach facilitates the task of designing sliding surfaces applied to multi-input multi-output (MIMO) linear systems. The presented methodology introduces a switching surface for MIMO linear systems through a simple equation that allows both eigenvalues placement design or optimal methods without any coordinate system representation transformation. In addition, a design parameter is also included for the adjustment of the non-ideal dynamics. Moreover, this approach guarantees high accuracy of the system dynamics, either for arbitrary eigenvalues assignment or for optimal switching surface definitions. In addition, these benefits are attained using a single switching surface equation. An illustrative example is included to show the advantages of the proposed design methodology.

Network tomography for integer-valued traffic

A classic network tomography problem is estimation of properties of the distribution of route traffic volumes based on counts taken on the network links. We consider inference for a general class of models for integer-valued traffic. Model identifiability is examined. We investigate both maximum likelihood and Bayesian methods of estimation. In practice, these must be implemented using stochastic EM and MCMC approaches. This requires a methodology for sampling latent route flows conditional on the observed link counts. We show that existing algorithms for doing so can fail entirely, because inflexibility in the choice of sampling directions can leave the sampler trapped at a vertex of the convex polytope that describes the feasible set of route flows. We prove that so long as the network's link-path incidence matrix is totally unimodular, it is always possible to select a coordinate system representation of the polytope for which sampling parallel to the axes is adequate. This motivates a modified sampler in which the representation of the polytope adapts to provide good mixing behavior. This methodology is applied to three road traffic data sets. We conclude with a discussion of the ramifications of the unimodularity requirements for the routing matrix.

Design and Real-Time Control of a 4-DOF Biped Robot

This work is focused on the design, construction and model based control of a biped robot during the walking cycle on the sagittal plane. For the analysis, the single support phase is considered to be the dominating dynamics, by assuming an instantaneous double support phase which is only described by the impact phenomenon. The joint tracking problem is analyzed by means of a model based control strategy, which incorporates a reformulation of the Coriolis matrix that allows the cancellation of non antisymmetric terms in order to formally proof the asymptotic stability of the coordinate error system representation in a local sense. Some experiments are carried out for a pre-defined reference trajectory for the walking cycle of a 4-DOF biped robot.

Contrasting Interpretations of the Nonuniform Distribution of Preferred Directions Within Primary Motor Cortex

to the editor: A recent paper by Georgopoulos and colleagues ([Naselaris et al. 2006][1]) revisits the influential and controversial issue of population coding within primary motor cortex (M1). Although researchers uniformly recognize that neural activity in M1 often covaries with the direction of

Coordinate system representations of movement direction in the premotor cortex

Recently, we compared the encoding of movement direction in primary motor cortex (MI) under three coordinate systems, an extrinsic cartesian (CA), an intrinsic joint angle (JA), and an intermediate shoulder-centered (SC) and found that no single coordinate system was uniquely represented in MI. Here we extend this investigation to the premotor area which is regarded as a major source of input to the MI. Multiple single units were simultaneously recorded from the caudal portions of dorsal premotor (PMd) and ventral premotor (PMv) cortices as a behaving monkey moved its hand over the horizontal work space. We compared the mutual information between the neuronal firing rate of each unit and hand movement direction under each of the three coordinate systems. As in the MI study, the results showed that there was no evidence for a unique coordinate system representation. There was a bias towards the SC system in PMd, albeit weaker than the SC bias observed in MI. In PMv, there was a strong bias for both SC and JA coordinate systems as compared to a CA coordinate system. These results provided further evidence against a unique coordinate system for movement direction within the motor cortex. However, the directional information within both PMd and PMv was significantly less than that of MI suggesting that factors other than the detailed motion of the arm account for much of the variance of activity within the premotor cortex.

Evidence against a single coordinate system representation in the motor cortex

Understanding the coordinate systems in which the motor cortical cells encode movement parameters such as direction is a fundamental yet unresolved issue. Although many studies have assumed that motor cortex encodes direction in an extrinsic, Cartesian (CA) coordinate system, other studies have provided evidence for encoding in intermediate coordinate systems such as a shoulder-centered (SC) or in a purely intrinsic, joint-angle-based (JA) coordinate frame. By simultaneously recording from multiple single units in primary motor cortex, we examined movement direction encoding under each of these three coordinate systems. We directly compared the degree of directional tuning invariance over multiple sub-regions in the workspace. We also compared the mutual information between neuronal firing rate and movement direction in the three systems. We observed a broad range of directional invariance in all three coordinate systems with no strong dominance of any single coordinate system. The mutual information analyses corroborated this observation. However, we found a small but significant bias toward the SC coordinate frame, which was also supported by population vector decoding. Similar results were found when we compared hand/torque force direction encoding in all three coordinate systems. These results suggest that the motor cortex employs a coordinate system that is yet to be discovered or perhaps that the motor cortex should not be viewed as a substrate for any coordinate system representation.

Computational anatomy and neuropsychiatric disease: probabilistic assessment of variation and statistical inference of group difference, hemispheric asymmetry, and time-dependent change

Three components of computational anatomy (CA) are reviewed in this paper: (i) the computation of large-deformation maps, that is, for any given coordinate system representations of two anatomies, computing the diffeomorphic transformation from one to the other; (ii) the computation of empirical probability laws of anatomical variation between anatomies; and (iii) the construction of inferences regarding neuropsychiatric disease states. CA utilizes spatial-temporal vector field information obtained from large-deformation maps to assess anatomical variabilities and facilitate the detection and quantification of abnormalities of brain structure in subjects with neuropsychiatric disorders. Neuroanatomical structures are divided into two types: subcortical structures-gray matter (GM) volumes enclosed by a single surface-and cortical mantle structures-anatomically distinct portions of the cerebral cortical mantle layered between the white matter (WM) and cerebrospinal fluid (CSF). Because of fundamental differences in the geometry of these two types of structures, image-based large-deformation high-dimensional brain mapping (HDBM-LD) and large-deformation diffeomorphic metric matching (LDDMM) were developed for the study of subcortical structures and labeled cortical mantle distance mapping (LCMDM) was developed for the study of cortical mantle structures. Studies of neuropsychiatric disorders using CA usually require the testing of hypothesized group differences with relatively small numbers of subjects per group. Approaches that increase the power for testing such hypotheses include methods to quantify the shapes of individual structures, relationships between the shapes of related structures (e.g., asymmetry), and changes of shapes over time. Promising preliminary studies employing these approaches to studies of subjects with schizophrenia and very mild to mild Alzheimer's disease (AD) are presented.

A preliminary step towards a language for picture control in a real-time mode

With the proliferation of extremely complex analog systems for the control of television images it has become evident that some more efficient system has to be found for dealing with the mire of knobs, switches, levers, and patch cords which make up any video processing device. In planning an attack on this situation, we soon realized that a major aspect of the problem is a linquistic one. Television has only a few terms which deal with the almost infinite number of effects possible in any given system. The specification of wipes, fades, dissolves, keys, etc. tells one the process used, but does not go into great detail as to what it looks like on the screen. A circle wipe, for instance, may start in any part of the screen, have an edge in any of several degrees of softness, may be modulated by a wide range of frequencies, and may have a number of outlines around it in any combination of colors. Given these technical capabilities, the problem of how to catalog the possible effects and how to specify them was approached in terms of a description based on a Cartesian coordinate system representation of the multidimensional video space. The use of such a coordinate system has given us several advantages. The first is that there is a large body of existing work dealing with physical movements along orthogonal axes. Secondly, image color in television can be measured or specified in terms of phase shifts from 0 to 360 degrees in a planar reference axis system. Another consideration which makes this description natural is that it is standard for zero voltage on a CRT display to be center screen, thus defining our origin and relating it in a simple way to the physical control values. With this as our point of departure we embarked on our work with the clear realization that, because the dimensions and variability of the system were almost infinite, due to the unconstrained combination of analog patches and digital programming, some severe restraint would be necessary in order to make the results meaningful.

A preliminary step towards a language for picture control in a real-time mode

With the proliferation of extremely complex analog systems for the control of television images it has become evident that some more efficient system has to be found for dealing with the mire of knobs, switches, levers, and patch cords which make up any video processing device. In planning an attack on this situation, we soon realized that a major aspect of the problem is a linquistic one. Television has only a few terms which deal with the almost infinite number of effects possible in any given system. The specification of wipes, fades, dissolves, keys, etc. tells one the process used, but does not go into great detail as to what it looks like on the screen. A circle wipe, for instance, may start in any part of the screen, have an edge in any of several degrees of softness, may be modulated by a wide range of frequencies, and may have a number of outlines around it in any combination of colors. Given these technical capabilities, the problem of how to catalog the possible effects and how to specify them was approached in terms of a description based on a Cartesian coordinate system representation of the multidimensional video space. The use of such a coordinate system has given us several advantages. The first is that there is a large body of existing work dealing with physical movements along orthogonal axes. Secondly, image color in television can be measured or specified in terms of phase shifts from 0 to 360 degrees in a planar reference axis system. Another consideration which makes this description natural is that it is standard for zero voltage on a CRT display to be center screen, thus defining our origin and relating it in a simple way to the physical control values. With this as our point of departure we embarked on our work with the clear realization that, because the dimensions and variability of the system were almost infinite, due to the unconstrained combination of analog patches and digital programming, some severe restraint would be necessary in order to make the results meaningful.