Advances in single frame image recovery

This thesis tackles a problem of recovering a high resolution image from a single compressed frame. A new image-prior that is devised based on Pearson type VII density is integrated with a Markov Random Field model which has desirable robustness properties. A fully automated hyper-parameter estimation procedure for this approach is developed, which makes it advantageous in comparison with alternatives. Although this recovery algorithm is very simple to implement, it achieves statistically significant improvements over previous results in under-determined problem settings, and it is able to recover images that contain texture. This advancement opens up the opportunities for several potential extensions, of which we pursue two: (i) Most of previous work does not consider any specific extra information to recover the signal. Thus, this thesis exploits the similarity between the signal of interest and a consecutive motionless frame to address this problem. Additional information of similarity that is available is incorporated into a probabilistic image-prior based on the Pearson type VII Markov Random Field model. Results on both synthetic and real data of Magnetic Resonance Imaging (MRI) images demonstrate the effectiveness of our method in both compressed setting and classical super-resolution experiments. (ii) This thesis also presents a multi-task approach for signal recovery by sharing higher-level hyperparameters which do not relate directly to the actual content of the signals of interest but only to their statistical characteristics. Our approach leads to a very simple model and algorithm that can be used to simultaneously recover multipl

Video foreground extraction for mobile camera platforms

Foreground object detection is a fundamental task in computer vision with many applications in areas such as object tracking, event identification, and behavior analysis. Most conventional foreground object detection methods work only in a stable illumination environments using fixed cameras. In real-world applications, however, it is often the case that the algorithm needs to operate under the following challenging conditions: drastic lighting changes, object shape complexity, moving cameras, low frame capture rates, and low resolution images. This thesis presents four novel approaches for foreground object detection on real-world datasets using cameras deployed on moving vehicles.The first problem addresses passenger detection and tracking tasks for public transport buses investigating the problem of changing illumination conditions and low frame capture rates. Our approach integrates a stable SIFT (Scale Invariant Feature Transform) background seat modelling method with a human shape model into a weighted Bayesian framework to detect passengers. To deal with the problem of tracking multiple targets, we employ the Reversible Jump Monte Carlo Markov Chain tracking algorithm. Using the SVM classifier, the appearance transformation models capture changes in the appearance of the foreground objects across two consecutives frames under low frame rate conditions. In the second problem, we present a system for pedestrian detection involving scenes captured by a mobile bus surveillance system. It integrates scene localization, foreground-background separation, and pedestrian detection modules into a unified detection framework. The scene localization module performs a two stage clustering of the video data.In the first stage, SIFT Homography is applied to cluster frames in terms of their structural similarity, and the second stage further clusters these aligned frames according to consistency in illumination. This produces clusters of images that are differential in viewpoint and lighting. A kernel density estimation (KDE) technique for colour and gradient is then used to construct background models for each image cluster, which is further used to detect candidate foreground pixels. Finally, using a hierarchical template matching approach, pedestrians can be detected.In addition to the second problem, we present three direct pedestrian detection methods that extend the HOG (Histogram of Oriented Gradient) techniques (Dalal and Triggs, 2005) and provide a comparative evaluation of these approaches. The three approaches include: a) a new histogram feature, that is formed by the weighted sum of both the gradient magnitude and the filter responses from a set of elongated Gaussian filters (Leung and Malik, 2001) corresponding to the quantised orientation, which we refer to as the Histogram of Oriented Gradient Banks (HOGB) approach; b) the codebook based HOG feature with branch-and-bound (efficient subwindow search) algorithm (Lampert et al., 2008) and; c) the codebook based HOGB approach.In the third problem, a unified framework that combines 3D and 2D background modelling is proposed to detect scene changes using a camera mounted on a moving vehicle. The 3D scene is first reconstructed from a set of videos taken at different times. The 3D background modelling identifies inconsistent scene structures as foreground objects. For the 2D approach, foreground objects are detected using the spatio-temporal MRF algorithm. Finally, the 3D and 2D results are combined using morphological operations.The significance of these research is that it provides basic frameworks for automatic large-scale mobile surveillance applications and facilitates many higher-level applications such as object tracking and behaviour analysis

Towards patient-specific modelling as a pre-operative planning strategy and follow up assessment for the treatment of advanced heart failure with rotary blood pumps

Background: Ventricular Assist Devices (VADs) insertion is an established treatment for patients with end-stage heart failure waiting for a heart transplant or in need for long-term circulatory support (destination therapy). Rotary blood pumps (RBP) are the most popular devices in view of their size and performance. Pre-operative planning strategy for the insertion of a left ventricular assist device (LVAD) requires a timely discussion at a Multi-Disciplinary Team Meeting (MDT). Clinical-decision making is based according to the needs of the patient and must be processed without delays. Nevertheless, thrombus formation remains a feared complication which affects outcome. VADs operate in a flow regime which is difficult to simulate: the transitional region at the boundary of laminar and turbulent flow (low Reynolds number). Different methods have been used but the best approach remains debatable. Computational Fluid Dynamics (CFD) is an attractive and invaluable tool for the study of the interactions between VADs and the cardiovascular system. The aim of this thesis is three-fold: a) to investigate the use of pressure-volume analysis in a clinical setting through the review of six heart failure patients previously discussed at a MDT meeting with a view to predict or guide further management; b) to review the theory behind modelling approaches to VADs and their interactions with the cardiovascular system for better understanding of their clinical use. Then, an overview of computational fluid dynamics (CFD) is considered as a prelude to its application to the analysis of VADs performance. Additionally, the development of a simplified model of centrifugal pump will be used in initial simulations as preliminary analysis; c) to examine an example of a proof-of-concept pilot patient-specific model of an axial flow pump (HeartMate II) as pre-operative planning strategy in a patient-specific model with a view to identify potential critical areas that may affect pump function and outcome in a clinical setting. Material and Methods: 3D reconstruction from CT-scan images of patients who underwent the insertion of rotary blood pumps, namely HeartWare HVAD and HeartMate II. Ansys Fluent has been used for CFD analysis based on the fundamental governing equations of motion. Blood has been modelled as incompressible, Newtonian fluid with density = 1060 and viscosity = 0.0035 kg/m-s. The laminar and SST models have been used for comparison purposes. The rotational motion of the impeller has been implemented using the moving reference frame (MRF) approach. The sliding mesh method has also been used to account for unsteady interaction between stationary and moving part. The no-slip condition has been applied to all walls, which were assumed to be rigid. Boundary conditions consisting of velocity inlet and pressure outlet of the pump based on different settings and constant rotational speed for the impeller. Pressure-velocity coupling has been based on the coupled scheme. Spatial discretisation consisted of the “least square cell based” gradient for velocity and “PRESTO” or second order for pressure. Second order upwind has been set for the momentum, turbulent kinetic energy and specific dissipation rate. First order implicit has been set for transient formulation. The pseudo transient algorithm (steady state), the high order relaxation term and the warped-face gradient correction have been used to add an unsteady term to the solution equations with the aim to improve stability and enhance convergence. Specific settings have been considered for comparison purposes. Results: Pressure-volume simulation analysis in six advanced heart failure patients showed that an integrated model of the cardiovascular system based on lumped-parameter representation, modified time-varying elastance and pressure-volume analysis of ventricular function seems a feasible and suitable approach yielding a sufficiently accurate quantitative analysis in real time, therefore applicable within the time-constraints of a clinical setting. Lumped-parameter models consist of simultaneous ordinary differential equations complemented by an algebraic balance equation and are suitable for examination of global distribution of pressure, flow and volume over a range of physiological conditions with inclusion of the interaction between modelled components. Higher level lumped-parameter modelling is needed to address the interaction between the circulation and other systems based on a compromise between complexity and ability to set the required parameters to personalise an integrated lumped-parameter model for a patient-specific approach. CARDIOSIM© fulfils these requirements and does address the systems interaction with its modular approach and assembly of models with varying degree of complexity although 0-D and 1-D coupling may be required for the evaluation of long-term VAD support. The challenge remains the ability to predict outcome over a longer period of time. The preliminary CFD simulations with the HeartWare HVAD centrifugal pump demonstrated that it is possible to obtain an accurate analysis in a timely manner to complement the clinical review process. The simulations with the pilot patient-specific model of the HeartMate II axial flow pump revealed that a complex 3D reconstruction is feasible in a timely manner and can be used to generate sufficiently accurate results to be used in the context of a MDT meeting for the purposes of clinical decision-making. Overall, these three studies demonstrate that the time frame of the simulations was within hours which may fit the time constraints of the clinical environment in the context of a MDT meeting. More specifically, it was shown that the laminar model may be used for an initial evaluation of the flow development within the pump. Nonetheless, the k- model offers higher accuracy if the timeline of the clinical setting allows for a longer simulation. Conclusion: This thesis aimed at the understanding of the use of computational modelling as a pre-operative planning strategy and follow up assessment for the treatment of advanced heart failure with rotary blood pumps. The novelty lays in the use of both pressure-volume simulation analysis and 3D flow dynamics studies in VADs with a view to treatment optimisation and outcome prediction within the time constraints of a clinical setting in the context of a MDT meeting. The clinical significance and the contribution to the field is a more targeted approach for different groups of patients and a more quantitative evaluation in the clinical decision process based on a pro-active co-operation between clinicians and scientists reducing the potential for “guess work”. The results of this thesis are a proof-of-concept as a prelude to a potential future implementation of patient-specific modelling within a clinical setting on a daily basis demonstrating a clear clinical significance and contribution to the field. The proposed approach does not consider modelling and simulation as a substitute for clinical experience but an additional tool to guide therapeutic intervention and complement the clinical decision process in which the clinician remains the ultimate decision-maker. Such an approach may well add a different dimension to the problem of heart failure with potential for high return in terms of patient’s outcome and long-term surveillance. The same principles would be applicable to other cardiovascular problems in line with the current concept of “Team Approach” such as the Heart Team, the Structural Heart Team or the Aortic Team. The present work has taken this concept closer to clinical delivery and has highlighted its potential but further work remains to be done in refining the technique.Background: Ventricular Assist Devices (VADs) insertion is an established treatment for patients with end-stage heart failure waiting for a heart transplant or in need for long-term circulatory support (destination therapy). Rotary blood pumps (RBP) are the most popular devices in view of their size and performance. Pre-operative planning strategy for the insertion of a left ventricular assist device (LVAD) requires a timely discussion at a Multi-Disciplinary Team Meeting (MDT). Clinical-decision making is based according to the needs of the patient and must be processed without delays. Nevertheless, thrombus formation remains a feared complication which affects outcome. VADs operate in a flow regime which is difficult to simulate: the transitional region at the boundary of laminar and turbulent flow (low Reynolds number). Different methods have been used but the best approach remains debatable. Computational Fluid Dynamics (CFD) is an attractive and invaluable tool for the study of the interactions between VADs and the cardiovascular system. The aim of this thesis is three-fold: a) to investigate the use of pressure-volume analysis in a clinical setting through the review of six heart failure patients previously discussed at a MDT meeting with a view to predict or guide further management; b) to review the theory behind modelling approaches to VADs and their interactions with the cardiovascular system for better understanding of their clinical use. Then, an overview of computational fluid dynamics (CFD) is considered as a prelude to its application to the analysis of VADs performance. Additionally, the development of a simplified model of centrifugal pump will be used in initial simulations as preliminary analysis; c) to examine an example of a proof-of-concept pilot patient-specific model of an axial flow pump (HeartMate II) as pre-operative planning strategy in a patient-specific model with a view to identify potential critical areas that may affect pump function and outcome in a clinical setting. Material and Methods: 3D reconstruction from CT-scan images of patients who underwent the insertion of rotary blood pumps, namely HeartWare HVAD and HeartMate II. Ansys Fluent has been used for CFD analysis based on the fundamental governing equations of motion. Blood has been modelled as incompressible, Newtonian fluid with density = 1060 and viscosity = 0.0035 kg/m-s. The laminar and SST models have been used for comparison purposes. The rotational motion of the impeller has been implemented using the moving reference frame (MRF) approach. The sliding mesh method has also been used to account for unsteady interaction between stationary and moving part. The no-slip condition has been applied to all walls, which were assumed to be rigid. Boundary conditions consisting of velocity inlet and pressure outlet of the pump based on different settings and constant rotational speed for the impeller. Pressure-velocity coupling has been based on the coupled scheme. Spatial discretisation consisted of the “least square cell based” gradient for velocity and “PRESTO” or second order for pressure. Second order upwind has been set for the momentum, turbulent kinetic energy and specific dissipation rate. First order implicit has been set for transient formulation. The pseudo transient algorithm (steady state), the high order relaxation term and the warped-face gradient correction have been used to add an unsteady term to the solution equations with the aim to improve stability and enhance convergence. Specific settings have been considered for comparison purposes. Results: Pressure-volume simulation analysis in six advanced heart failure patients showed that an integrated model of the cardiovascular system based on lumped-parameter representation, modified time-varying elastance and pressure-volume analysis of ventricular function seems a feasible and suitable approach yielding a sufficiently accurate quantitative analysis in real time, therefore applicable within the time-constraints of a clinical setting. Lumped-parameter models consist of simultaneous ordinary differential equations complemented by an algebraic balance equation and are suitable for examination of global distribution of pressure, flow and volume over a range of physiological conditions with inclusion of the interaction between modelled components. Higher level lumped-parameter modelling is needed to address the interaction between the circulation and other systems based on a compromise between complexity and ability to set the required parameters to personalise an integrated lumped-parameter model for a patient-specific approach. CARDIOSIM© fulfils these requirements and does address the systems interaction with its modular approach and assembly of models with varying degree of complexity although 0-D and 1-D coupling may be required for the evaluation of long-term VAD support. The challenge remains the ability to predict outcome over a longer period of time. The preliminary CFD simulations with the HeartWare HVAD centrifugal pump demonstrated that it is possible to obtain an accurate analysis in a timely manner to complement the clinical review process. The simulations with the pilot patient-specific model of the HeartMate II axial flow pump revealed that a complex 3D reconstruction is feasible in a timely manner and can be used to generate sufficiently accurate results to be used in the context of a MDT meeting for the purposes of clinical decision-making. Overall, these three studies demonstrate that the time frame of the simulations was within hours which may fit the time constraints of the clinical environment in the context of a MDT meeting. More specifically, it was shown that the laminar model may be used for an initial evaluation of the flow development within the pump. Nonetheless, the k- model offers higher accuracy if the timeline of the clinical setting allows for a longer simulation. Conclusion: This thesis aimed at the understanding of the use of computational modelling as a pre-operative planning strategy and follow up assessment for the treatment of advanced heart failure with rotary blood pumps. The novelty lays in the use of both pressure-volume simulation analysis and 3D flow dynamics studies in VADs with a view to treatment optimisation and outcome prediction within the time constraints of a clinical setting in the context of a MDT meeting. The clinical significance and the contribution to the field is a more targeted approach for different groups of patients and a more quantitative evaluation in the clinical decision process based on a pro-active co-operation between clinicians and scientists reducing the potential for “guess work”. The results of this thesis are a proof-of-concept as a prelude to a potential future implementation of patient-specific modelling within a clinical setting on a daily basis demonstrating a clear clinical significance and contribution to the field. The proposed approach does not consider modelling and simulation as a substitute for clinical experience but an additional tool to guide therapeutic intervention and complement the clinical decision process in which the clinician remains the ultimate decision-maker. Such an approach may well add a different dimension to the problem of heart failure with potential for high return in terms of patient’s outcome and long-term surveillance. The same principles would be applicable to other cardiovascular problems in line with the current concept of “Team Approach” such as the Heart Team, the Structural Heart Team or the Aortic Team. The present work has taken this concept closer to clinical delivery and has highlighted its potential but further work remains to be done in refining the technique

Biomechanics of transapical mitral valve implantation

2014 Summer.Includes bibliographical references.Heart disease is the number one killer in the United States. Within this sector, valve disease plays a very important role: Approximately 6% of the entire population has either prolapse or stenosis of the mitral valve and this percentage only increases when looking only at the elderly population. Transapical mitral valve implantation has promised to be a potential therapy for high-risk patients presenting with MR; however it is unclear what the best method of securing a valve within the mitral annulus may be to provide a safe and efficient valve replacement. The objective of this research is to study and understand the underlying biomechanics of fixation of transapical mitral valves within the native mitral annulus. Two different transapical mitral valve prosthesis designs were tested: One valve design has a portion of the leaflets atrialized such that it has a shorter stent height and the valve itself sits within the native annulus, the other design is not atrialized and protrudes further into the left ventricle. The valves were implanted in a left heart simulator to assess leaflet kinematics and hemodynamics using high speed imagery and particle image velocimetry techniques. An in vitro passive beating heart model was then used to assess the two different fixation methods (namely, anchored at the apex vs. anchored at the annulus) with respect to paravalvular regurgitation. Leaflet kinematics and hemodynamics revealed proper leaflet coaptation and acceptable pressure gradients and inflow fillings; however, both designs yielded elevated turbulence stresses within the ventricle. At 60 beats per minute, leaflet opening and closing times were both under 0.1 seconds, max Reynolds shear stresses were between 40 and 60 N/m2 and maximum velocities were approximately 1.4 m/s. Assessment of the different fixation methods during implantation revealed the superiority of the atrialized valve when anchored at the annulus (p<0.05), but showed no such comparison during tethered implantation. In addition to the results of statistical testing, observations show that the importance of the relationship between ventricular stent height and fixation method compared with native anatomy plays an important role in overall prosthesis function regardless of implantation method

HIGH-FREQUENCY MOTION RESIDUALS IN MULTIBEAM ECHOSOUNDER DATA: ANALYSIS AND ESTIMATION

Advances in multibeam sonar mapping and data visualization have increasingly brought to light the subtle integration errors remaining in bathymetric datasets. Traditional field calibration procedures, such as the patch test, just account for static orientation bias and sonar-to-position latency. This, however, ignores the generally subtler integration problems that generate time-varying depth errors. Such dynamic depth errors are the result of an unknown offset in one or more of orientation, space, sound speed or time between the sonar and ancillary sensors. Such errors are systematic, and thus should be predictable, based on their relationship between the input data and integrated output. A first attempt at addressing this problem utilized correlations between motion and temporally smoothed, ping-averaged residuals. The known limitations of that approach, however, included only being able to estimate the dominant integration error, imperfectly accounting for irregularly spaced sounding distribution and only working in shallow water. This thesis presents a new and improved means of considering the dynamics of the integration error signatures which can address multiple issues simultaneously, better account for along-track sounding distribution, and is not restricted to shallow water geometry. The motion-driven signatures of six common errors are simultaneously identified. This is achieved through individually considering each sounding’s input-error relationship along extended sections of a single swath corridor. Such an approach provides a means of underway system optimization using nothing more than the bathymetry of typical seafloors acquired during transit. Initial results of the new algorithm are presented using data generated from a simulator, with known inputs and integration errors, to test the efficacy of the method. Results indicate that successful estimation requires conditions of significant vessel motion over periods of a few tens of seconds as well as smooth, gently rolling bathymetry along the equivalent spatial extent covered by the moving survey platform

Artificial Intelligence in Materials Science: Applications of Machine Learning to Extraction of Physically Meaningful Information from Atomic Resolution Microscopy Imaging

Materials science is the cornerstone for technological development of the modern world that has been largely shaped by the advances in fabrication of semiconductor materials and devices. However, the Moore’s Law is expected to stop by 2025 due to reaching the limits of traditional transistor scaling. However, the classical approach has shown to be unable to keep up with the needs of materials manufacturing, requiring more than 20 years to move a material from discovery to market. To adapt materials fabrication to the needs of the 21st century, it is necessary to develop methods for much faster processing of experimental data and connecting the results to theory, with feedback flow in both directions. However, state-of-the-art analysis remains selective and manual, prone to human error and unable to handle large quantities of data generated by modern equipment. Recent advances in scanning transmission electron and scanning tunneling microscopies have allowed imaging and manipulation of materials on the atomic level, and these capabilities require development of automated, robust, reproducible methods.Artificial intelligence and machine learning have dealt with similar issues in applications to image and speech recognition, autonomous vehicles, and other projects that are beginning to change the world around us. However, materials science faces significant challenges preventing direct application of the such models without taking physical constraints and domain expertise into account.Atomic resolution imaging can generate data that can lead to better understanding of materials and their properties through using artificial intelligence methods. Machine learning, in particular combinations of deep learning and probabilistic modeling, can learn to recognize physical features in imaging, making this process automated and speeding up characterization. By incorporating the knowledge from theory and simulations with such frameworks, it is possible to create the foundation for the automated atomic scale manufacturing