Effect of gravity on subject-specific human lung deformation

A biomechanical model of human lung is developed and used to investigate the effect of gravity on lung deformation. The lung is assumed to behave as a poro-elastic medium with spatially dependent elastic property. Finite element analysis is performed on a three-dimensional (3D) lung geometry reconstructed from a four-dimensional Computed Tomography (4DCT) scan dataset of human patient. The spatially dependent Young’s modulus (YM) values are estimated using inverse analysis from a linear elastic deformation model. The predicted deformation of selected landmarks is monitored with and without gravity, and compared with data obtained from 4DCT registration. The results show that gravity indeed significantly affects the magnitude and distribution of lung deformation with the maximum displacement enhanced by 54% in the direction of gravity, for the conditions investigated. In summary, the accuracy of predicted deformation is improved through incorporation of gravity in the biomechanical model of lung.     

Mathematical modelling of tongue deformation during swallow in patients with head and neck cancer

ABSTRACT

Cancer localized to the tongue is often characterized by increased stiffness in the affected region. This stiffness affects swallow in a manner that is difficult to quantify in patients. A biomechanical model was developed to simulate the spatio-temporal deformation of the tongue during the pharyngeal phase of swallow in patients with cancer of the tongue base. The model involves finite element analysis (FEA) of a three-dimensional (3D) model of the tongue reconstructed from magnetic resonance images (MRI). The tongue tissue is assumed to be hyper-elastic. In order to examine the effects of tissue change (increased stiffness) due to the presence of cancer localized to the tongue base, various sections of the 3D geometry are modified to exhibit different elastic properties. Three cases are considered, representing the normal tongue, a tongue with early-stage cancer, and tongue with late-stage cancer. Early- and late-stage cancers are differentiated by the degree of stiffness within the base of tongue tissue. Analysis of the model suggests that healthy tongue has a maximum deformation of 9.38 mm, whereas tongues having mild cancer and severe cancer have a maximum deformation of 8.65 and 6.17 mm, respectively. Biomechanical modelling is a useful tool to explain and estimate swallowing abnormalities associated with tongue cancer and post-treatment characteristics.     

Approximation of Martensitic Microstructure with General Homogeneous Boundary Data

We consider the approximation of martensitic microstructure for a class of martensitic transformations. We model such microstructures by multi-well energy minimization problems with general homogeneous boundary data. Under our assumptions on such boundary data, the underlying microstructure can be nonunique. We first show that any energy-minimizing sequence converges strongly to a unique macroscopic deformation that is precisely the homogeneous deformation in the boundary condition. We then prove a series of estimates for the approximation of admissible deformations to the unique macroscopic deformation of the microstructure and for the closeness of the gradients of admissible deformations to the energy wells.     

Theoretical study and numerical simulation of textiles

We propose a new approach for developing continuum models fit to describe the mechanical behavior of textiles. We develop a physically motivated model, based on the properties of the yarns, which can predict and simulate the textile behavior. The approach relies on the selection of a suitable topological model for the patch of the textile, coupled with constitutive models for the yarn behavior. The textile structural configuration is related to the deformation through an energy functional, which depends on both the macroscopic deformation and the distribution of internal nodes. We determine the equilibrium positions of these latter, constrained to an assigned macroscopic deformation. As a result, we derive a macroscopic strain energy function, which reflects the possibly nonlinear character of the yarns as well as the anisotropy induced by the microscopic topological pattern. By means of both analytical estimates and numerical experiments, we show that our model is well suited for both academic test cases and real industrial textiles, with particular emphasis on the tricot textile.     

Two-Stage Image Segmentation Scheme Based on Inexact Alternating Direction Method

Image segmentation is a fundamental problem in both image processing and computer vision with numerous applications. In this paper, we propose a two-stage image segmentation scheme based on inexact alternating direction method. Specifically, we first solve the convex variant of the Mumford-Shah model to get the smooth solution, and the segmentation is then obtained by applying the K-means clustering method to the solution. Some numerical comparisons are arranged to show the effectiveness of our proposed schemes by segmenting many kinds of images such as artificial images, natural images, and brain MRI images.     

Stability analysis for a new model of multi-species convection-diffusion-reaction in poroelastic tissue

We perform the linear stability analysis of a new model for poromechanical processes with inertia (formulated in mixed form using the solid deformation, fluid pressure, and total pressure) interacting with diffusing and reacting solutes convected in the medium. We find parameter regions that lead to spatio-temporal instabilities of the coupled system. The mutual dependences between deformation and diffusive patterns are of substantial relevance in the study of morphoelastic changes in bio-materials. We provide a set of computational examples in 2D and 3D (related to brain mechanobiology) that can be used to form a better understanding on how, and up to which extent, the deformations of the porous structure dictate the generation and suppression of spatial patterning dynamics, also related to the onset of mechano-chemical waves.     

Navigation of moving objects by geophysical fields

The navigation problem of a moving object by geophysical fields is considered. Within the framework of the proposed mathematical model of the navigation process, the approximation problems of a geophysical field ensuring the best correction of the navigation parameters are studied, algorithms for matching the measurements of the fields with their standard images are described, estimates for the informativity of geodesic fields are presented, and the problem of searching for the best (in the sense of informativity) trajectory are discussed. __________ Translated from Sovremennaya Matematika i Ee Prilozheniya (Contemporary Mathematics and Its Applications), Vol. 26, Nonlinear Dynamics, 2005.     

A framelet algorithm for de-blurring images corrupted by multiplicative noise

This paper considers a variational model for restoring images from blurry and speckled observations. This model utilizes the favorable properties of framelet regularization (e.g., the sparsity and multiresolution properties of the framelet) that are well suited for speckle noise reduction. For solving the model, we first propose an approximation model that is motivated by the well-known variable-splitting and penalty techniques in optimization. We then develop an alternating minimization algorithm to solve the approximation model. We also show that the sequence generated by the algorithm converges to the solution of the proposed model. The numerical results on simulated data and real utrasound images demonstrate that our approach outperforms several state-of-the-art algorithms.     

Certain algebraic surfaces with Eisenbud‐Harris general fibration of genus 4

We classify the algebraic surfaces with Eisenbud‐Harris general fibration of genus 4 over a rational curve or an elliptic curve whose slope attains the lower bound. The classification of our surfaces is strongly related to the result of the classification for certain relative quadric hypersurfaces in 3‐dimensional projective space bundles over a rational curve and an elliptic curve. We further prove some results about the canonical maps, the quadric hulls of the canonical images and the deformation for these surfaces.     

Weak solutions for nonlinear antiplane problems leading to hemivariational inequalities

We analyze the antiplane shear deformation of an elastic cylinder in frictional contact with a rigid foundation, for static processes, under the small deformation hypothesis. Based on the Knaster–Kuratowski–Mazurkiewicz technique in the theory of the hemivariational inequalities, we prove that the model has at least one weak solution. Moreover, we present several examples of constitutive laws and friction laws for which our theoretical results are valid. Finally, we comment on the conditions which guarantee the uniqueness of the solution.     

Split Bregman method for minimization of improved active contour model combining local and global information dynamically

This paper presents an improved active contour model by combining the Chan–Vese model, the region-scalable fitting energy model, the globally convex segmentation method and the split Bregman method. A weight function that varies with the location of a given image is used to control the influence of the local and global information dynamically. We first present our model in a 2-phase level set formulation and then extend it to a multi-phase formulation. By taking the local and global information into consideration together, our model can segment more general images, especially images with intensity inhomogeneity. Our model has been applied to synthetic and real images with promising results. Numerical results show the advantages of our model compared with other models. The accuracy and efficiency are demonstrated by the numerical results. Besides, our model is robust in the presence of noise.     

A nonlinear viscoelastic fractional derivative model of infant hydrocephalus

Infant communicating hydrocephalus is a clinical condition where the cerebral ventricles become enlarged causing the developing brain parenchyma of the newborn to be displaced outwards into the soft, unfused skull. In this paper, a hyperelastic, fractional derivative viscoelastic model is derived to describe infant brain tissue under conditions consistent with the development of hydrocephalus. An incremental numerical technique is developed to determine the relationship between tissue deformation and applied pressure gradients. Using parameter values appropriate for infant parenchyma, it is shown that pressure gradients of the order of 1 mm Hg are sufficient to cause hydrocephalus. Predicting brain tissue deformations resulting from pressure gradients is of interest and relevance to the treatment and management of hydrocephalus, and to the best of our knowledge, this is the first time that results of this nature have been established.     

Fluid Structure Interaction of Blood Vessels in Circle of Willis

This work involves studying the role of the Brain Blood Barriers (BBB) on damping the stress applied on brain tissue through blood pressure that is the main cause of brain aneurysm. The numerical simulations are focused on the geometry of the Anterior Communicating Artery (ACoA) because there is a 30 % higher probability for a brain aneurysm in this location. A linear elastic model is used to model the structure part including BBB and brain tissue. Regarding the fluid properties, blood is assumed to behave as a Newtonian fluid. The stress and deformation of the brain tissue is analyzed. (© 2016 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

An Algorithm for Combined Code and Carrier Phase Based GPS Positioning

The Global Positioning System (GPS) is a satellite based navigation system. GPS satellites transmit signals that allow one to quite accurately estimate the location of GPS receivers. In GPS a typical technique for kinematic position estimation is relative positioning where two receivers are used, one receiver is stationary and its exact position is known, the other is roving and its position is to be estimated. We describe the physical situation and give the mathematical model based on the difference of the measurements at the stationary and roving receivers. The model we consider combines both the code and carrier phase measurements. We then present a recursive least squares approach for position estimation. We take full account of the structure of the problem to make our algorithm efficient, and use orthogonal transformations to ensure numerical reliability of the algorithm. Real data test results suggest our algorithm is effective. An additional benefit of this approach is that the drawbacks of double differencing are avoided. The paper could also serve as a straightforward introduction for numerical analysts to an interesting area of GPS.This revised version was published online in October 2005 with corrections to the Cover Date.     

Data-Driven Tight Frame Construction for Impulsive Noise Removal

The method of data-driven tight frame has been shown very useful in image restoration problems.We consider in this paper extending this important technique,by incorporating L₁ data fidelity into the original data-driven model,for removing impulsive noise which is a very common and basic type of noise in image data.The model contains three variables and can be solved through an efficient iterative alternating minimization algorithm in patch implementation,where the tight frame is dynamically updated.It constructs a tight frame system from the input corrupted image adaptively,and then removes impulsive noise by the derived system.We also show that the sequence generated by our algorithm converges globally to a stationary point of the optimization model.Numerical experiments and comparisons demonstrate that our approach performs well for various kinds of images.This benefits from its data-driven nature and the learned tight frames from input images capture richer image structures adaptively.     

A Geometric Framework for Stochastic Shape Analysis

We introduce a stochastic model of diffeomorphisms, whose action on a variety of data types descends to stochastic evolution of shapes, images and landmarks. The stochasticity is introduced in the vector field which transports the data in the large deformation diffeomorphic metric mapping framework for shape analysis and image registration. The stochasticity thereby models errors or uncertainties of the flow in following the prescribed deformation velocity. The approach is illustrated in the example of finite-dimensional landmark manifolds, whose stochastic evolution is studied both via the Fokker–Planck equation and by numerical simulations. We derive two approaches for inferring parameters of the stochastic model from landmark configurations observed at discrete time points. The first of the two approaches matches moments of the Fokker–Planck equation to sample moments of the data, while the second approach employs an expectation-maximization based algorithm using a Monte Carlo bridge sampling scheme to optimise the data likelihood. We derive and numerically test the ability of the two approaches to infer the spatial correlation length of the underlying noise.

     

Optimal ship navigation with safety distance and realistic turn constraints

We consider the optimal ship navigation problem wherein the goal is to find the shortest path between two given coordinates in the presence of obstacles subject to safety distance and turn-radius constraints. These obstacles can be debris, rock formations, small islands, ice blocks, other ships, or even an entire coastline. We present a graph-theoretic solution on an appropriately-weighted directed graph representation of the navigation area obtained via 8-adjacency integer lattice discretization and utilization of the A^∗ algorithm. We explicitly account for the following three conditions as part of the turn-radius constraints: (1) the ship’s left and right turn radii are different, (2) ship’s speed reduces while turning, and (3) the ship needs to navigate a certain minimum number of lattice edges along a straight line before making any turns. The last constraint ensures that the navigation area can be discretized at any desired resolution. Once the optimal (discrete) path is determined, we smoothen it to emulate the actual navigation of the ship. We illustrate our methodology on an ice navigation example involving a 100,000 DWT merchant ship and present a proof-of-concept by simulating the ship’s path in a full-mission ship handling simulator.     

Variational Phase Field Modeling of Laminate Deformation Microstructure in Finite Gradient Crystal Plasticity

The macroscopic mechanical behavior of many materials crucially depends on the formation and evolution of their microstructure. In this work, we consider the formation and evolution of laminate deformation microstructure in plasticity. Inspired by work on the variational modeling of phase transformation [5] and building on related work on multislip gradient crystal plasticity [9], we present a new finite strain model for the formation and evolution of laminate deformation microstructure in double slip gradient crystal plasticity. Basic ingredients of our model are a nonconvex hardening potential and two gradient terms accounting for geometrically necessary dislocations (GNDs) by use of the dislocation density tensor and regularizing the sharp interfaces between different kinematically coherent plastic slip states. The plastic evolution is described by means of a nonsmooth dissipation potential for which we propose a new regularization. We formulate a continuous gradient-extended rate-variational framework and discretize it in time to obtain an incremental-variational formulation. Discretization in space yields a finite element formulation which is used to demonstrate the capability of our model to predict the formation and evolution of laminate deformation microstructure in f.c.c. Copper with two active slip systems in the same slip plane. (© 2012 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim)     

Deformations of open stein manifolds

We consider the deformation of the complex structure on an open Stein manifold. We show that a tame, compactly supported deformation of a Stein manifold is trivial. The remainder of our results are for deformations of the standard complex structure on Cⁿ. A deformation of Cⁿ which tends to a constant deformation faster that r^-3 is trivial. Harmonic deformation tensors (w.r.t to the standard Euclidean metric) which are regular at infinity are constant.     

A variational formulation for physical noised image segmentation

Image segmentation is a hot topic in image science. In this paper we present a new variational segmentation model based on the theory of Mumford-Shah model. The aim of our model is to divide noised image, according to a certain criterion, into homogeneous and smooth regions that should correspond to structural units in the scene or objects of interest. The proposed region-based model uses total variation as a regularization term, and different fidelity term can be used for image segmentation in the cases of physical noise, such as Gaussian, Poisson and multiplicative speckle noise. Our model consists of five weighted terms, two of them are responsible for image denoising based on fidelity term and total variation term, the others assure that the three conditions of adherence to the data, smoothing, and discontinuity detection are met at once. We also develop a primal-dual hybrid gradient algorithm for our model. Numerical results on various synthetic and real images are provided to compare our method with others,these results show that our proposed model and algorithms are effective.