Semi-automated application for kidney motion correction and filtration analysis in MR renography

pre-printAltered renal function commonly affects patients with cirrhosis, a consequence of chronic liver disease. From lowdose contrast material-enhanced magnetic resonance (MR) renography, we can estimate the Glomerular Filtration Rate (GFR), an important parameter to assess renal function. Two-dimensional MR images are acquired every 2 seconds for approximately 5 minutes during free breathing, which results in a dynamic series of 140 images representing kidney filtration over time. This specific acquisition presents dynamic contrast changes but is also challenged by organ motion due to breathing. Rather than use conventional image registration techniques, we opted for an alternative method based on object detection. We developed a novel analysis framework available under a stand-alone toolkit to efficiently register dynamic kidney series, manually select regions of interest, visualize the concentration curves for these ROIs, and fit them into a model to obtain GFR values. This open-source cross-platform application is written in C++, using the Insight Segmentation and Registration Toolkit (ITK) library, and QT4 as a graphical user interface

A Comparison of Two Equivalent Source Methods for Noise Source Visualization

The various equivalent source methods for noise source visualization can generally be categorized according to two factors: the complexity of the model (order of the sources) and the flexibility of the model (sources at fixed or unfixed location). The models used in the present work comprised: (i) a large number of low-order sources at fixed locations (low model order, low flexibility), and (ii) a high model order series at an unfixed location (high model order, high flexibility). With reference to case (i), a new equivalent source procedure based on a monopole distribution at fixed locations, which is referred to as wideband holography was recently developed by Hald. By using this method the balance between the model accuracy and the sparsity of the underdetermined system can be optimized. For case (ii), a higher order series at unfixed locations was recently proposed by Liu and Bolton. The unfixed location model was found to offer better accuracy of noise source location estimation compared with the more usual fixed-location model. In the present work, these two methods were used to reconstruct the noise sources of a loudspeaker cabinet. The measurement were conducted using an eighteen channel irregular array. A comparison of the reconstruction result from these two method help to highlight the strengths and weakness of each procedure

Second order gradient ascent pulse engineering

We report some improvements to the gradient ascent pulse engineering (GRAPE) algorithm for optimal control of quantum systems. These include more accurate gradients, convergence acceleration using the BFGS quasi-Newton algorithm as well as faster control derivative calculation algorithms. In all test systems, the wall clock time and the convergence rates show a considerable improvement over the approximate gradient ascent.Comment: Submitted for publicatio

Large Scale Computational Problems in Numerical Optimization

Our work under this support broadly falls into five categories: automatic differentiation, sparsity, constraints, parallel computation, and applications. Automatic Differentiation (AD): We developed strong practical methods for computing sparse Jacobian and Hessian matrices which arise frequently in large scale optimization problems [10,35]. In addition, we developed a novel view of "structure" in applied problems along with AD techniques that allowed for the efficient application of sparse AD techniques to dense, but structured, problems. Our AD work included development of freely available MATLAB AD software. Sparsity: We developed new effective and practical techniques for exploiting sparsity when solving a variety of optimization problems. These problems include: bound constrained problems, robust regression problems, the null space problem, and sparse orthogonal factorization. Our sparsity work included development of freely available and published software [38,39]. Constraints: Effectively handling constraints in large scale optimization remains a challenge. We developed a number of new approaches to constrained problems with emphasis on trust region methodologies. Parallel Computation: Our work included the development of specifically parallel techniques for the linear algebra tasks underpinning optimization algorithms. Our work contributed to the nonlinear least-squares problem, nonlinear equations, triangular systems, orthogonalization, and linear programming. Applications: Our optimization work is broadly applicable across numerous application domains. Nevertheless we have specifically worked in several application areas including molecular conformation, molecular energy minimization, computational finance, and bone remodeling

Experimental and numerical evaluation of viscoelastic sandwich beams

Viscoelastic materials can dissipate a large amount of energy when subjected to cyclic shear deformations, but they have low bearing capacity. Therefore they are often employed as a damping layer in sandwich structures. These sandwich structures present a high damping ratio and simple application. In order to design sandwich structures, many aspects ranging from computer modeling to laboratory testing should be considered. In this study, a test set of experiments were performed and results are compared with a numerical GHM (Golla, Hughes and Mc Tavish method) based model, in order to establish a method to support viscoelastic sandwich beam design. In this way, starting from the dynamic properties of a viscoelastic material, a numerical model is used to evaluate the behavior of these structures. Comparisons with uncontrolled structures are also presented, showing the dissipative characteristics of this passive control.

Fitting a 3D Morphable Model to Edges: A Comparison Between Hard and Soft Correspondences

We propose a fully automatic method for fitting a 3D morphable model to single face images in arbitrary pose and lighting. Our approach relies on geometric features (edges and landmarks) and, inspired by the iterated closest point algorithm, is based on computing hard correspondences between model vertices and edge pixels. We demonstrate that this is superior to previous work that uses soft correspondences to form an edge-derived cost surface that is minimised by nonlinear optimisation.Comment: To appear in ACCV 2016 Workshop on Facial Informatic