Blind deconvolution of medical ultrasound images: parametric inverse filtering approach

©2007 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or distribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.DOI: 10.1109/TIP.2007.910179The problem of reconstruction of ultrasound images by means of blind deconvolution has long been recognized as one of the central problems in medical ultrasound imaging. In this paper, this problem is addressed via proposing a blind deconvolution method which is innovative in several ways. In particular, the method is based on parametric inverse filtering, whose parameters are optimized using two-stage processing. At the first stage, some partial information on the point spread function is recovered. Subsequently, this information is used to explicitly constrain the spectral shape of the inverse filter. From this perspective, the proposed methodology can be viewed as a ldquohybridizationrdquo of two standard strategies in blind deconvolution, which are based on either concurrent or successive estimation of the point spread function and the image of interest. Moreover, evidence is provided that the ldquohybridrdquo approach can outperform the standard ones in a number of important practical cases. Additionally, the present study introduces a different approach to parameterizing the inverse filter. Specifically, we propose to model the inverse transfer function as a member of a principal shift-invariant subspace. It is shown that such a parameterization results in considerably more stable reconstructions as compared to standard parameterization methods. Finally, it is shown how the inverse filters designed in this way can be used to deconvolve the images in a nonblind manner so as to further improve their quality. The usefulness and practicability of all the introduced innovations are proven in a series of both in silico and in vivo experiments. Finally, it is shown that the proposed deconvolution algorithms are capable of improving the resolution of ultrasound images by factors of 2.24 or 6.52 (as judged by the autocorrelation criterion) depending on the type of regularization method used

Geometry definition and grid generation for a complete fighter aircraft

Recent advances in computing power and numerical solution procedures have enabled computational fluid dynamicists to attempt increasingly difficult problems. In particular, efforts are focusing on computations of complex three-dimensional flow fields about realistic aerodynamic bodies. To perform such computations, a very accurate and detailed description of the surface geometry must be provided, and a three-dimensional grid must be generated in the space around the body. The geometry must be supplied in a format compatible with the grid generation requirements, and must be verified to be free of inconsistencies. This paper presents a procedure for performing the geometry definition of a fighter aircraft that makes use of a commercial computer-aided design/computer-aided manufacturing system. Furthermore, visual representations of the geometry are generated using a computer graphics system for verification of the body definition. Finally, the three-dimensional grids for fighter-like aircraft are generated by means of an efficient new parabolic grid generation method. This method exhibits good control of grid quality

4D commercial trajectory optimization for fuel saving and environmemtal impact reduction

The main purpose of the thesis is to optimize commercial aircraft 4D trajectories to improve flight efficiency and reduce fuel consumption and environmental impact caused by airliners. The Trajectory Optimization Problem (TOP) technique can be used to accomplish this goal. The formulation of the aircraft TOP involves the mathematical model of the system (i.e., dynamics model, performance model, and emissions model of the aircraft), Performance Index (PI), and boundary and path constraints of the system. Typically, the TOP is solved by a wide range of numerical approaches. They can be classified into three basic classes of numerical methods: indirect methods, direct methods, and dynamic programming. In this thesis, several instances of problems were considered to optimize commercial aircraft trajectories. Firstly, the problem of optimal trajectory generation from predefined 4D waypoint networks was considered. A single source shortest path algorithm (Dijkstra’s algorithm) was applied to generate the optimal aircraft trajectories that minimize aircraft fuel burn and total trip time between the initial and final waypoint in the networks. Dijkstra’s Algorithm (DA) successfully found the path (trajectory) with the lowest cost (i.e., fuel consumption, and total trip time) from the predefined 4D waypoint networks. Next, the problem of generating minimum length optimal trajectory along a set of predefined 4D waypoints was considered. A cubic spline parameterization was used to solve the TOP. The state vector, its time derivative, and control vector are parameterized using Cubic Spline Interpolation (CSI). Consequently, the objective function and constraints are expressed as functions of the value of state and control at the temporal nodes, this representation transforms the TOP into a Nonlinear Programming (NLP) problem, which is then solved numerically using a well-established NLP solver. The proposed method generated a smooth 4D optimal trajectory with very accurate results. Following, the problem considers generating optimal trajectories between two 4D waypoints. Dynamic Programming (DP) a well-established numerical method was considered to solve this problem. The traditional DP bears some shortcomings that prevent its use in many practical real-time implementations. This thesis proposes a Modified Dynamic Programming (MDP) approach which reduces the computational effort and overcomes the drawbacks of the traditional DP. The proposed MDP approach was successfully implemented to generate optimal trajectories that minimize aircraft fuel consumption and emissions in several case studies, the obtained optimal trajectories are then compared with the corresponding reference commercial flight trajectory for the same route in order to quantify the potential benefit of reduction of aircraft fuel consumption and emissions. The numerical examples demonstrate that the MDP can successfully generate fuel and emissions optimal trajectory with little computational effort, which implies it can also be applied to online trajectory generation. Finally, the problem of predicting the fuel flow rate from actual flight data or manual data was considered. The Radial Basis Function (RBF) neural network was applied to predict the fuel flow rate in the climb, cruise, and descent phases of flight. In the RBF neural network, the true airspeed and flight altitude were taken as the input parameters and the fuel flow rate as the output parameter. The RBF neural network produced a highly accurate fuel flow rate model with a high value of coefficients of determination, together with the low relative approximation errors. Later on, the resulted fuel flow rate model was used to solve a 4D TOP by optimizing aircraft green cost between two 4D waypoints.O principal objetivo desta tese é otimizar as trajetórias em 4D de aeronaves comerciais, de forma a melhorar a eficiência de voo e reduzir o consumo de combustível e o impacto ambiental causado pelos aviões. A técnica de otimização de trajetória pode ser utilizada para atingir este objetivo. A formulação do problema de otimização de trajetória de uma aeronave envolve o modelo matemático do sistema (isto é, modelo de dinâmica, modelo de desempenho, e modelo de emissões de aeronaves), a função objetiva e os limites e restrições do sistema. Normalmente, o problema de otimização de trajetória é solucionado por uma ampla variedade de abordagens numéricas, que podem ser classificadas em três classes básicas de métodos numéricos: métodos indiretos, métodos diretos e programação dinâmica. Nesta tese, foram consideradas várias instâncias de problemas para otimizar trajetórias de aeronaves comerciais. Em primeiro lugar, foi considerado um problema de geração de trajetória ótima em 4D a partir de redes de waypoints predefinidas. Para tal, foi aplicado um algoritmo de single source shortest path (neste caso, algoritmo de Dijkstra), de forma a gerar trajetórias ótimas que minimizem o consumo de combustível da aeronave e o seu tempo total de viagem. O algoritmo de Dijkstra encontrou com sucesso a trajetória com menor custo, isto é, a trajetória de menor consumo de combustível e menor tempo total de viagem, a partir da rede predefinida de waypoints. Em seguida, foi considerado o problema de gerar uma trajetória ótima em 4D de comprimento mínimo ao longo de um conjunto de waypoints predefinidos. Para tal, foi utilizada uma parametrização da spline cúbica. O vetor de estado, a sua derivada e o vetor de controlo são parametrizados utilizando a interpolação cúbica da spline. Consequentemente, a função objetivo e as restrições são expressas como funções do valor de estado e controlo nos nós temporais. Esta representação transforma o problema de otimização de trajetória em um problema de programação não-linear, que por sua vez, é resolvido numericamente por um solucionador já bem estabelecido de programação não-linear. O método proposto gerou uma trajetória ótima em 4D com resultados precisos. Posteriormente, considerou-se o problema de geração de trajetórias ótimas em 4D entre dois waypoints. Para solucionar este problema foi utilizado a programação dinâmica que é um método numérico já bem estabelecido. A programação dinâmica apresenta algumas deficiências que impedem o seu uso em muitas aplicações práticas de tempo-real. Por isso, esta tese propõe uma abordagem de programação dinâmica modificada que reduz o esforço computacional e supera as desvantagens do Programação Dinâmica tradicional. A abordagem programação dinâmica modificada proposta, foi implementada com sucesso em vários casos de estudo, em que foram geradas trajetórias ótimas que minimizam o consumo de combustível da aeronave e as suas emissões. Estas trajetórias são, posteriormente, comparadas com a trajetória de voo comercial de referência, para quantificar a potencial redução do consumo de combustível da aeronave e das suas emissões. Os exemplos numéricos demonstram que a programação dinâmica modificada pode gerar com sucesso e com pouco esforço computacional trajetórias ótimas para o combustível e as emissões, o que sugere que este método pode ser aplicado em situações online, isto é, geração de trajetórias online. Por fim, foi considerado o problema de previsão da taxa temporal de consumo de combustível (FF) a partir de dados de voo reais. A rede neural da função de base radial (RBF) foi aplicada para prever a essa mesma taxa temporal nas fases de voo: subida, cruzeiro e descida. Na aplicação da rede neural RBF, a velocidade real e a altitude de voo foram consideradas como parâmetros de entrada e a FF foi considerada como parâmetro de saída. A rede neural RBF foi capaz de produzir um modelo adequado para estimar corretamente essa taxa temporal, com um elevado valor de coeficientes de determinação, juntamente com baixos valores nos erros relativos de aproximação. Posteriormente, este modelo de FF foi utilizado para resolver o problema de otimização de trajetórias em 4D, em que o custo total entre dois waypoints foi otimizado

Image segmentation and reconstruction of 3D surfaces from carotid ultrasound images

Tese de doutoramento. Engenharia Electrotécnica e de Computadores. Faculdade de Engenharia. Universidade do Porto. 200