Dense Vision in Image-guided Surgery

Image-guided surgery needs an efficient and effective camera tracking system in order to perform augmented reality for overlaying preoperative models or label cancerous tissues on the 2D video images of the surgical scene. Tracking in endoscopic/laparoscopic scenes however is an extremely difficult task primarily due to tissue deformation, instrument invasion into the surgical scene and the presence of specular highlights. State of the art feature-based SLAM systems such as PTAM fail in tracking such scenes since the number of good features to track is very limited. When the scene is smoky and when there are instrument motions, it will cause feature-based tracking to fail immediately. The work of this thesis provides a systematic approach to this problem using dense vision. We initially attempted to register a 3D preoperative model with multiple 2D endoscopic/laparoscopic images using a dense method but this approach did not perform well. We subsequently proposed stereo reconstruction to directly obtain the 3D structure of the scene. By using the dense reconstructed model together with robust estimation, we demonstrate that dense stereo tracking can be incredibly robust even within extremely challenging endoscopic/laparoscopic scenes. Several validation experiments have been conducted in this thesis. The proposed stereo reconstruction algorithm has turned out to be the state of the art method for several publicly available ground truth datasets. Furthermore, the proposed robust dense stereo tracking algorithm has been proved highly accurate in synthetic environment (< 0.1 mm RMSE) and qualitatively extremely robust when being applied to real scenes in RALP prostatectomy surgery. This is an important step toward achieving accurate image-guided laparoscopic surgery.Open Acces

Multi-objective optimisation of aircraft flight trajectories in the ATM and avionics context

The continuous increase of air transport demand worldwide and the push for a more economically viable and environmentally sustainable aviation are driving significant evolutions of aircraft, airspace and airport systems design and operations. Although extensive research has been performed on the optimisation of aircraft trajectories and very efficient algorithms were widely adopted for the optimisation of vertical flight profiles, it is only in the last few years that higher levels of automation were proposed for integrated flight planning and re-routing functionalities of innovative Communication Navigation and Surveillance/Air Traffic Management (CNS/ATM) and Avionics (CNS+A) systems. In this context, the implementation of additional environmental targets and of multiple operational constraints introduces the need to efficiently deal with multiple objectives as part of the trajectory optimisation algorithm. This article provides a comprehensive review of Multi-Objective Trajectory Optimisation (MOTO) techniques for transport aircraft flight operations, with a special focus on the recent advances introduced in the CNS+A research context. In the first section, a brief introduction is given, together with an overview of the main international research initiatives where this topic has been studied, and the problem statement is provided. The second section introduces the mathematical formulation and the third section reviews the numerical solution techniques, including discretisation and optimisation methods for the specific problem formulated. The fourth section summarises the strategies to articulate the preferences and to select optimal trajectories when multiple conflicting objectives are introduced. The fifth section introduces a number of models defining the optimality criteria and constraints typically adopted in MOTO studies, including fuel consumption, air pollutant and noise emissions, operational costs, condensation trails, airspace and airport operations

A generic, collaborative framework for internal constraint solving

Esta tesis propone un esquema genérico y cooperativo para CLP(Interval(X)) donde X es cualquier dominio de computación con estructura de retículo. El esquema, que está basado en la teoría de retículos, es un enfoque general para la satisfacción y op-timización de restricciones de intervalo así como para la cooperación de resolutores de intervalo definidos sobre dominios de computación con estructura de retículos, independientemente de la cardinalidad de estos. Nuestra propuesta asegura un enfoque transparente sobre el cual las restricciones, los dominios de computación y los mecanismos de propagación y cooperación, definidos entre las variables restringidas, pueden ser fácilmente especificados a nivel del usuario. La parte principal de la tesis presenta una especificación formal de este esquema.Los principales resultados conseguidos en esta tesis son los siguientes:Una comparativa global de la eficiencia y algunos aspectos de la expresividad de ocho sistemas de restricciones. Esta comparativa, realizada sobre el dominio finito y el dominio Booleano, muestra diferencias principales entre los sistemas de restricciones existentes.Para formalizar el marco de satisfacción de restricciones para CLP(Interval(X))hemos descrito el proceso global de resolución de restricciones de intervalo sobre cualquier retículo, separando claramente los procesos de propagación y división (ramificación) de intervalos. Una de las ventajas de nuestra propuesta es que la monótona de las restricciones esta implícitamente definida en la teoría. Además, declaramos un conjunto de propiedades interesantes que, bajo ciertas condiciones, son satisfechas por cualquier instancia del esquema genérico. Mas aún, mostramos que muchos sistemas de restricciones actualmente existentes satisfacen estas condiciones y, además, proporcionamos indicaciones sobre como extender el sistema mediante la especificación de otras instancias interesantes y novedosas. Nuestro esquema para CLP(Interval(X)) permite la cooperación de resolutores de manera que la información puede ⁰uir entre diferentes dominios de computación.Además, es posible combinar distintas instancias del esquema: por ejemplo, instancias bien conocidas tales como CLP(Interval(<)), CLP(Interval(Integer)),CLP(Interval(Set)), CLP(Interval(Bool)), y otras novedosas que son el resultado de la generación de nuevos dominios de computación definidos por el usuario, o incluso que surgen de la combinación de dominios ya existentes como puede ser CLP(Interval(X1 £ : : : £ Xn)). Por lo tanto, X puede ser instanciado a cualquier conjunto de dominios de computación con estructura de retículo de forma que su correspondiente instancia CLP(Interval(X)) permite una amplia flexibilidad en la definición de dominios en X (probablemente definidos por el usuario) y en la interaccion entre estos dominios.Mediante la implementacion de un prototipo, demostramos que un unico sistema,que este basado en nuestro esquema para CLP(Interval(X)), puede proporcionarsoporte para la satisfaccion y la optimizacion de restricciones as como para la cooperacion de resolutores sobre un conjunto conteniendo multiples dominios decomputacion. Ademas, el sistema sigue un novedoso enfoque transparente sujeto a una doble perspectiva ya que el usuario puede definir no solo nuevas restricciones y su mecanismo de propagacion, sino tambien nuevos dominios sobre los cuales nuevas restricciones pueden ser resueltas as como el mecanismo de cooperacion entre todos los dominios de computación (ya sean definidos por el usuario o predefinidos por el sistema).En nuestra opinión, esta tesis apunta nuevas y potenciales direcciones de investigación dentro de la comunidad de las restricciones de intervalo.Para alcanzar los resultados expuestos, hemos seguido los siguientes pasos (1) la elección de un enfoque adecuado sobre el cual construir los fundamentos teóricos de nuestro esquema genérico; (2) la construcción de un marco teórico genérico (que llamaremos el marco básico) para la propagación de restricciones de intervalo sobre cualquier retículo; (3) la integración, en el marco básico, de una técnica novedosa que facilita la cooperación de resolutores y que surge de la definición, sobre múltiples dominios, de operadores de restricciones y (4) la extensión del marco resultante para la resolución y optimización completa de las restricciones de intervalo.Finalmente presentamos clp(L), un lenguaje de programación lógica de restricciones de intervalo que posibilita la resolución de restricciones sobre cualquier conjunto de retículos y que esta implementado a partir de las ideas formalizadas en el marco teórico. Describimos una primera implementación de este lenguaje y desarrollamos algunos ejemplos de como usarla. Este prototipo demuestra que nuestro esquema para CLP(Interval(X)) puede ser implementado en un sistema único que, como consecuencia, proporciona, bajo un enfoque transparente sobre dominios y restricciones, cooperación de resolutores así como satisfacción y optimización completa de restricciones sobre diferentes dominios de computación

Concurrent multiscale modelling for heterogeneous materials with CutFEM

Computational modelling of heterogeneous materials with complex microstructures is challenging due to their multiscale nature. While direct numerical simulations lead to accurate results, it is not tractable for large-scale models. Therefore, in this thesis, two novel concurrent multiscale frameworks have been developed for tractable simulation of 2D/3D highly heterogeneous materials, including composites and trabecular bone materials. The difficulty of discretising such materials with complex microstructure is circumvented by using the cut finite element method (CutFEM). Then, two efficient zooming techniques are proposed for coupling micro and acroscale models. In our multiscale frameworks, the CutFEM technique is utilised to discretise the corresponding micro/macro interface besides the microstructure. In the first framework, the smooth transition concurrent multiscale method, the two models are blended in a transition region and discretised over a single fixed computational mesh. While in the second framework, the two models have different meshes and are coupled over a sharp interface using Nitsche’s method. In both frameworks, the CutFEM technology has been used for discretisation purposes that permits representing the microstructure and micro/macro interfaces in a mesh-independent fashion. This feature of CutFEM allows to (re)locate the zooming region(s) (the region(s) we require microscopic analysis) over a fixed background mesh arbitrarily, thus improving the robustness of multiscale modelling and analysis. In chapter 3, the efficiency and robustness of the smoothed concurrent multiscale method is demonstrated for 2D and 3D linear elasticity problems. Then, in chapter 5, the performance of the second concurrent multiscale framework with a sharp interface is tested for 2D linear elasticity and plasticity materials. In chapter 4, the smoothed concurrent multiscale method developed in Chapter 3 is extended for brittle fracture problems, which are a prevalent example of multiscale phenomena. According to the literature, fracture initiation starts in microscopic length scales by an accumulation of micro cracks in a process zone that eventually leads to the creation of macro cracks. In this thesis, the phase field model has been adopted for the fracture problem, which considers the fracture in a diffusive way. Since phase field models suffer from demanding extremely refined meshes to represent cracks, an efficient numerical framework is essential to balance accuracy and computational costs. In chapter 4, we show that our smoothed concurrent multiscale framework is a suitable choice for such problems

Design and implementation of components for renewably-powered base-stations with heterogeneous access channel

Providing high-speed broadband services in remote areas can be a challenging task, especially because of the lack of network infrastructure. As typical broadband technologies are often expensive to deploy, they require large investment from the local authorities. Previous studies have shown that a viable alternative is to use wireless base stations with high-throughput point to point (PTP) backhaul links. With base stations comes the problem of powering their systems, it is tackled in this thesis by relying on renewable energy harvesting, such as solar panels or wind turbines. This thesis, in the context of the sustainable cellular network harvesting ambient energy (SCAVENGE) project, aims to contribute to a reliable and energy efficient solution to this problem, by adjusting the design of an existing multi-radio energy harvesting base station. In Western Europe, 49 channels of 8 MHz were used for analogue TV transmissions, ranging from 470 MHz (Channel 21) to 862 MHz (Channel 69); this spectrum, now partially unused due to the digital television (DTV) switch-over, has been opened to alternative uses by the regulatory authorities. Using this newly freed ultra high frequency (UHF) range, also known as TV white space (TVWS), can offer reliable low-cost broadband access to housings and businesses in low-density areas. While UHF transmitters allow long range links, the overcrowding of the TV spectrum limits the achievable throughput; to increase the capacity of such TVWS rural broadband base station the UHF radio has previously been combined with a lower-range higher throughput GHz radio like Wireless Fidelity (WiFi). From the regulatory constraints of TVWS applications arises the need for frequency agile transceivers that observe strict spectral mask requirements, this guided previous works towards discrete Fourier transform (DFT) modulated filter-bank multicarrier (FBMC) systems. These systems are numerically efficient, as they permit the up-and-down conversion of the 40 TV channels at the cost of a single channel transceiver and the modulating transform. Typical implementations rely on power-of two fast Fourier transforms (FFTs); however the smallest transform covering the full 40 channels of the TVWS spectrum is a 64 points wide, thus involving 24 unused channels. In order to attain a more numerically-efficient implemented design, we introduce the use of mixed-radix FFTs modulating transform. Testing various sizes and architectures, this approach provides up to 6.7% of energy saving compared to previous designs. Different from orthogonal frequency-division multiplexing (OFDM), FBMC systems are generally expected to be more robust to synchronisation errors, as oversampled FBMC systems can include a guard band, and even in a doubly-dispersive channel, inter-carrier interference (ICI) can be considered negligible. Even though sub-channels can be treated independently—i.e. without the use of cross-terms—they still require equalisation. We introduce a per-band equalisation, amongst different options, a robust and fast blind approach based on a concurrent constant modulus (CM)/decision directed (DD) fractionally-space equaliser (FSE) is selected. The selected approach is capable of equalising a frequency-selective channel. Furthermore the proposed architecture is advantageous in terms of power consumption and implementation cost. After focussing on the design of the radio for TVWS transmission, we address a multi-radio user assignment problem. Using various power consumption and harvesting models for the base station, we formulate two optimisation problems, the first focuses on the base station power consumption, while the second concentrates on load balancing. We employ a dynamic programming approach to optimise the user assignment. The use of such algorithms could allow a downsizing of the power supply systems (harvesters and batteries), thus reducing the cost of the base station. Furthermore the algorithms provide a better balance between the number of users assigned to each network, resulting in a higher quality of service (QoS) and energy efficiency.Providing high-speed broadband services in remote areas can be a challenging task, especially because of the lack of network infrastructure. As typical broadband technologies are often expensive to deploy, they require large investment from the local authorities. Previous studies have shown that a viable alternative is to use wireless base stations with high-throughput point to point (PTP) backhaul links. With base stations comes the problem of powering their systems, it is tackled in this thesis by relying on renewable energy harvesting, such as solar panels or wind turbines. This thesis, in the context of the sustainable cellular network harvesting ambient energy (SCAVENGE) project, aims to contribute to a reliable and energy efficient solution to this problem, by adjusting the design of an existing multi-radio energy harvesting base station. In Western Europe, 49 channels of 8 MHz were used for analogue TV transmissions, ranging from 470 MHz (Channel 21) to 862 MHz (Channel 69); this spectrum, now partially unused due to the digital television (DTV) switch-over, has been opened to alternative uses by the regulatory authorities. Using this newly freed ultra high frequency (UHF) range, also known as TV white space (TVWS), can offer reliable low-cost broadband access to housings and businesses in low-density areas. While UHF transmitters allow long range links, the overcrowding of the TV spectrum limits the achievable throughput; to increase the capacity of such TVWS rural broadband base station the UHF radio has previously been combined with a lower-range higher throughput GHz radio like Wireless Fidelity (WiFi). From the regulatory constraints of TVWS applications arises the need for frequency agile transceivers that observe strict spectral mask requirements, this guided previous works towards discrete Fourier transform (DFT) modulated filter-bank multicarrier (FBMC) systems. These systems are numerically efficient, as they permit the up-and-down conversion of the 40 TV channels at the cost of a single channel transceiver and the modulating transform. Typical implementations rely on power-of two fast Fourier transforms (FFTs); however the smallest transform covering the full 40 channels of the TVWS spectrum is a 64 points wide, thus involving 24 unused channels. In order to attain a more numerically-efficient implemented design, we introduce the use of mixed-radix FFTs modulating transform. Testing various sizes and architectures, this approach provides up to 6.7% of energy saving compared to previous designs. Different from orthogonal frequency-division multiplexing (OFDM), FBMC systems are generally expected to be more robust to synchronisation errors, as oversampled FBMC systems can include a guard band, and even in a doubly-dispersive channel, inter-carrier interference (ICI) can be considered negligible. Even though sub-channels can be treated independently—i.e. without the use of cross-terms—they still require equalisation. We introduce a per-band equalisation, amongst different options, a robust and fast blind approach based on a concurrent constant modulus (CM)/decision directed (DD) fractionally-space equaliser (FSE) is selected. The selected approach is capable of equalising a frequency-selective channel. Furthermore the proposed architecture is advantageous in terms of power consumption and implementation cost. After focussing on the design of the radio for TVWS transmission, we address a multi-radio user assignment problem. Using various power consumption and harvesting models for the base station, we formulate two optimisation problems, the first focuses on the base station power consumption, while the second concentrates on load balancing. We employ a dynamic programming approach to optimise the user assignment. The use of such algorithms could allow a downsizing of the power supply systems (harvesters and batteries), thus reducing the cost of the base station. Furthermore the algorithms provide a better balance between the number of users assigned to each network, resulting in a higher quality of service (QoS) and energy efficiency

A discrete graph Laplacian for signal processing

In this thesis we exploit diffusion processes on graphs to effect two fundamental problems of image processing: denoising and segmentation. We treat these two low-level vision problems on the pixel-wise level under a unified framework: a graph embedding. Using this framework opens us up to the possibilities of exploiting recently introduced algorithms from the semi-supervised machine learning literature. We contribute two novel edge-preserving smoothing algorithms to the literature. Furthermore we apply these edge-preserving smoothing algorithms to some computational photography tasks. Many recent computational photography tasks require the decomposition of an image into a smooth base layer containing large scale intensity variations and a residual layer capturing fine details. Edge-preserving smoothing is the main computational mechanism in producing these multi-scale image representations. We, in effect, introduce a new approach to edge-preserving multi-scale image decompositions. Where as prior approaches such as the Bilateral filter and weighted-least squares methods require multiple parameters to tune the response of the filters our method only requires one. This parameter can be interpreted as a scale parameter. We demonstrate the utility of our approach by applying the method to computational photography tasks that utilise multi-scale image decompositions. With minimal modification to these edge-preserving smoothing algorithms we show that we can extend them to produce interactive image segmentation. As a result the operations of segmentation and denoising are conducted under a unified framework. Moreover we discuss how our method is related to region based active contours. We benchmark our proposed interactive segmentation algorithms against those based upon energy-minimisation, specifically graph-cut methods. We demonstrate that we achieve competitive performance

4-D Tomographic Inference: Application to SPECT and MR-driven PET

Emission tomographic imaging is framed in the Bayesian and information theoretic framework. The first part of the thesis is inspired by the new possibilities offered by PET-MR systems, formulating models and algorithms for 4-D tomography and for the integration of information from multiple imaging modalities. The second part of the thesis extends the models described in the first part, focusing on the imaging hardware. Three key aspects for the design of new imaging systems are investigated: criteria and efficient algorithms for the optimisation and real-time adaptation of the parameters of the imaging hardware; learning the characteristics of the imaging hardware; exploiting the rich information provided by depthof- interaction (DOI) and energy resolving devices. The document concludes with the description of the NiftyRec software toolkit, developed to enable 4-D multi-modal tomographic inference