Segundo a definição original de MCINERNEY & TERZOPOULOS (1995), modelos deformáveis são curvas ou superfícies formadas por pontos conectados que simulam corpos elásticos. Por superarem muitas limitações associadas ao procedimento manual e às técnicas tradicionais de processamento, os contornos deformáveis têm se popularizado. Ainda que o uso dos contornos deformáveis seja vasto e crescente, aspectos relevantes da teoria ainda têm demandado atenção. Muitas referências têm sido feitas às limitações da técnica impostas sobretudo pelo seu processo evolutivo. A convergência a mínimos locais e o agrupamento indesejado de pontos, por exemplo, limitam o emprego da técnica em cenários ruidosos e complexos como os encontrados em reservatórios de petróleo. Esse trabalho apresenta uma abordagem inédita às limitações dos contornos deformáveis. Pela definição de um segundo problema de minimização são definidas distâncias ótimas dos pontos do contorno deformável segundo critério de optimalidade que contempla as particularidades do contorno buscado. Os resultados demonstram que a técnica proposta é provedora de maior enquadramento entre o contorno buscado e o identificado, define solução definitiva aos problemas do agrupamento e espalhamento indesejados de pontos, aumenta a efetividade dos contornos deformáveis em regiões côncavas e, em acréscimo, define metodologia unicamente capaz de dotar os contornos deformáveis de sensibilidade quanto às particularidades de contorno. / According to the original definition of Terzopoulos, deformable models are curves or surfaces formed by connected points that simulate elastic bodies. By overcoming many limitations associated with the manual procedure and the traditional techniques of processing, deformable contours have become popular. Although the use of deformable contours is vast and growing aspects of the theory still demand attention. Many references have been made to the limitations of the technique imposed by the process evolution process. The convergence to minimum and unwanted bundling points, for example, limit the use of the technic on noisy and complex scenarios as those found in oil reservoirs. This work presents a novel approach to the limitations of deformable contours. By the definition of a second problem of minimization are defined optimal distances of the points of deformable contour according to a optimality criterion that incorporates features of the contour sought. The results show that the proposed technique peovides a larger framework between the contour sought and identified, defines a permanent solution to the problems of grouping and unwanted scattering of points, increases the effectiveness of deformable contours in concave regions and, in addition, defines methodology only able to provide the contours deformable sensitivity about the peculiarities of the contour.

Deformable mirror is a widely used wavefront corrector in adaptive optics system, especially in astronomical, image and laser optics. A new structure of DM-3D DM is proposed, which has removable actuators and can correct different aberrations with different actuator arrangements. A 3D DM consists of several reflection mirrors. Every mirror has a single actuator and is independent of each other. Two kinds of actuator arrangement algorithm are compared: random disturbance algorithm (RDA) and global arrangement algorithm (GAA). Correction effects of these two algorithms and comparison are analyzed through numerical simulation. The simulation results show that 3D DM with removable actuators can obviously improve the correction effects.

Robotic grasping and manipulation of three-dimensional deformable objects is a complex task that currently does not have robust and flexible solutions. Deformable objects include a wide variety of elastic and inelastic objects that change size and shape during manipulation. The development of adaptable methods for grasping and autonomously controlling the shape of three-dimensional deformable objects will benefit many commercial applications, including shaping parts for assembly in manufacturing, manipulating food for packaging and controlling tissues during robotic surgery. Controlling a deformable object to a desired shape requires first choosing contact points on the object's surface. Next, the robotic hand is positioned in the correct position and orientation to grasp and deform the object. After deformation, the object is assessed to evaluate the quality of the shape control procedure. In many cases, this process is completed without knowing the object's properties or behaviour before deformation. This work proposes and implements the framework for a robotic arm and hand system to control the shape of a previously unseen deformable object autonomously. Significant original contributions are made in developing an original algorithm to plan contact points on a three-dimensional object for grasping and shape control. This research uses a novel object representation to reduce the dimensionality of the deformable object manipulation problem. A path planning algorithm guides the robot arm to the optimal valid grasp pose to deform the object at the determined contact points. Additional contributions include developing a multi-view assessment strategy to determine the quality of the deformation towards the desired shape. The system completes the objectives using depth and colour images captured from a single point of view to locate and identify a previously unseen three-dimensional object within a robotic workspace. After estimating the unknown object's geometry, initial grasp contact points are planned to control the object to the desired shape. The grasp points are used to plan and execute a collision-free trajectory for the robot manipulator to place the robotic hand in the optimal position and orientation to grasp and deform the object. After the deformation is complete, the object is moved to a variety of assessment positions to determine the success of the shape control procedure. The system is validated experimentally on a variety of deformable three-dimensional objects.

fMRI imaging is considered key on the understanding of the brain and the mind, for this reason has been the subject of tremendous research connecting different disciplines. The intrinsic complexity of this 4-D type of data processing and analysis has been approached with every single computational perspective, lately increasing the trend to include artificial intelligence. One step critical on the fMRI pipeline is image registration. A model of Deep Networks based on Fully Convolutional Neural Networks, spatial transformation neural networks with a self-learning strategy was proposed for the implementation of a Fully deformable model image registration algorithm. Publicly available fMRI datasets with images from real-life subjects were used for training, testing and validating the model. The model performance was measured in comparison with ANTs deformable registration method with good results suggesting that Deep Learning can be used successfully for the development of the field using the basic strategy of studying the brain using the brain-self strategies.

Dexterous robotic manipulation of non-rigid objects is a challenging problem but necessary to explore as robots are increasingly interacting with more complex environments in which such objects are frequently present. In particular, common manipulation tasks such as molding clay to a target shape or picking fruits and vegetables for use in the kitchen, require a high-level understanding of the scene and objects. Commonly, the behavior of non-rigid objects is described by a model. Although, well-established modeling techniques are difficult to apply in robotic tasks since objects and their properties are unknown in such unstructured environments. This work proposes a sensing and modeling framework to measure the 3D shape deformation of non-rigid objects. Unlike traditional methods, this framework explores data-driven learning techniques focused on shape representation and deformation dynamics prediction using a graph-based approach. The proposal is validated experimentally, analyzing the performance of the representation model to capture the current state of the non-rigid object shape. In addition, the performance of the prediction model is analyzed in terms of its ability to produce future states of the non-rigid object shape due to the manipulation actions of the robotic system. The results suggest that the representation model is able to produce graphs that closely capture the deformation behavior of the non-rigid object. Whereas, the prediction model produces visually plausible graphs when short-term predictions are required.

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In medical images, intensity changes caused by certain pathology can change the topology of image level-sets and are thus commonly referred to as topological changes. Topological changes cause false deformation in existing deformable registration algorithms, which in turn leads to unreliable observations in the clinical study that relies on the deformation fields, such as deformation based morphometry (DBM). In this work, we develop a new deformable registration algorithm for images with topological changes. In our proposed algorithm, 3D images are embedded as 4D surfaces in a Riemannian space. The registration is therefore conducted as a surface evolution, which is modeled by a diffusion process. Our algorithm differs from existing methods in the sense that it takes an a-priori estimation of areas with topological change as an additional input and generates dense deformation vector fields which are free of false deformation. In particular, the output of our algorithm is composed of a diffeomorphic deformation field and an intensity displacement which corrects intensity difference caused by topological changes. By conducting multiple sets of experiments, we demonstrate that our proposed algorithm is capable of accurately registering images with considerable topological changes. More importantly, the resulting deformation field is not impacted by topological changes, i.e., there is no false deformation. / Ph. D.

This work investigates steady deformations, measured spectra of quasi-static ring deformations, natural frequencies, vibration modes, parametric instabilities, and nonlinear dynamics of high-speed planetary gears with an elastically deformable ring gear and equally-spaced planets. An analytical dynamic model is developed with rigid sun, carrier, and planets coupled to an elastic continuum ring. Coriolis and centripetal acceleration effects resulting from carrier and ring gear rotation are included. Steady deformations and measured spectra of the ring deflections are examined with a quasi-static model reduced from the dynamic one. The steady deformations calculated from the analytical model agree well with those from a finite element/contact mechanics (FE/CM) model. The spectra of ring deflections measured by sensors fixed to the rotating ring, space-fixed ground, and the rotating carrier are much different. Planet mesh phasing significantly affects the measured spectra. Simple rules are derived to explain the spectra for all three sensor locations for in-phase and out-of-phase systems. A floating central member eliminates spectral content near certain mesh frequency harmonics for out-of-phase systems. Natural frequencies and vibration modes are calculated from the analytical dynamic model, and they compare well with those from a FE/CM model. Planetary gears have structured modal properties due to cyclic symmetry, but these modal properties are different for spinning systems with gyroscopic effects and stationary systems without gyroscopic effects. Vibration modes for stationary systems are real-valued standing wave modes, while those for spinning systems are complex-valued traveling wave modes. Stationary planetary gears have exactly four types of modes: rotational, translational, planet, and purely ring modes. Each type has distinctive modal properties. Planet modes may not exist or have one or more subtypes depending on the number of planets. Rotational, translational, and planet modes persist with gyroscopic effects included, but purely ring modes evolve into rotational or one subtype of planet modes. Translational and certain subtypes of planet modes are degenerate with multiplicity two for stationary systems. These modes split into two different subtypes of translational or planet modes when gyroscopic effects are included. Parametric instabilities of planetary gears are examined with the analytical dynamic model subject to time-varying mesh stiffness excitations. With the method of multiple scales, closed-form expressions for the instability boundaries are derived and verified with numerical results from Floquet theory. An instability suppression rule is identified with the modal structure of spinning planetary gears with gyroscopic effects. Each mode is associated with a phase index such that the gear mesh deflections between different planets have unique phase relations. The suppression rule depends on only the modal phase index and planet mesh phasing parameters (gear tooth numbers and the number of planets). Numerical integration of the analytical model with time-varying mesh stiffnesses and tooth separation nonlinearity gives dynamic responses, and they compare well with those from a FE/CM model. Closed-form solutions for primary, subharmonic, superharmonic, and second harmonic resonances are derived with a perturbation analysis. These analytical results agree well with the results from numerical integration. The analytical solutions show suppression of certain resonances as a result of planet mesh phasing. The tooth separation conditions are analytically determined. The influence of the gyroscopic effects on dynamic response is examined numerically and analytically. / Doctor of Philosophy / Planetary gears in aerospace applications have thin ring gears for reducing weight. These lightweight ring gears deform elastically when transmitting power. At high speed, Coriolis and centripetal accelerations of planetary gears become significant. This work develops an analytical planetary gear model that takes account of an elastically deformable ring gear and speed-dependent gyroscopic (i.e., Coriolis) and centripetal effects. Steady deformations, measured spectra of quasi-static ring deformations, natural frequencies, vibration modes, parametric instabilities, and dynamic responses of planetary gears with equally-spaced planets are investigated with the analytical model. Steady deformations refer to quasi-static deflections that result from applied torques and centripetal acceleration effects. These steady deformations vary because of periodically changing mesh interactions. Such variation leads to cyclic stress that reduces system fatigue lives. This work evaluates planetary gear steady deformations with the analytical model and studies the effects of system parameters on the steady deformations. Ring deflections measured by sensors fixed to the rotating ring gear (e.g., a strain gauge), space-fixed ground (e.g., a displacement probe), and the rotating carrier have much different spectra. The planet mesh phasing, which is determined by gear tooth numbers and the number of planets, significantly influences these spectra. Simple rules are derived that govern the occurrence of spectral content in all the three measurements. Understanding these spectra is of practical significance to planetary gear engineers and researchers. Planetary gears have highly structured modal properties due to cyclic symmetry. Vibration modes are classified into rotational, translational, and planet modes in terms of the motion of central members (sun and carrier). The central members have only rotation for a rotational mode, only translation for a translational mode, and no motion for a planet mode. Translational modes have two subtypes, rotational modes have only one subtype, and planet modes may not exist or have one or more subtypes depending on the number of planets. For each subtype of modes, all planets have the same motion with a unique phase relation between different planets and the elastic ring gear has unique deformations. Understanding this modal structure is important for modal testing and resonant mode identification in dynamic responses. Sun-planet and ring-planet mesh interactions change periodically with mesh frequency. These mesh interactions are modeled as time-varying stiffnesses that parametrically excite the planetary gear system. Parametric instabilities, in general, occur when the mesh frequency or one of its harmonics is near twice a natural frequency or combinations of two natural frequencies. Closed-form expressions for parametric instability boundaries that bound the instability region are determined from the analytical model. Certain parametric instabilities are suppressed as a result of planet mesh phasing. Near resonances, vibration can become large enough that meshing teeth lose contact. The analytical model is extended to include the tooth separation nonlinearity. Closed-form approximations for dynamic responses near resonances are determined from the analytical model, and these analytical results compare well with those from numerical simulations of the analytical model. Tooth separation conditions are analytically determined. The influences of planet mesh phasing and Coriolis acceleration on dynamic responses near resonances are investigated numerically and analytically.

As of July 2012, 777 exoplanets have been discovered utilizing mainly indirect detection techniques. The direct imaging of exoplanets is the next goal for astronomers, because it will reveal the diversity of planets and planetary systems, and will give access to the exoplanet's chemical composition via spectroscopy. With this spectroscopic knowledge, astronomers will be able to know, if a planet is terrestrial and, possibly, even find evidence of life. With so much potential, this branch of astronomy has also captivated the general public attention. The direct imaging of exoplanets remains a challenging task, due to (i) the extremely high contrast between the parent star and the orbiting exoplanet and (ii) their small angular separation. For ground-based observatories, this task is made even more difficult, due to the presence of atmospheric turbulence. High Contrast Imaging (HCI) instruments have been designed to meet this challenge. HCI instruments are usually composed of a coronagraph coupled with the full on-axis corrective capability of an Extreme Adaptive Optics (ExAO) system. An efficient coronagraph separates the faint planet's light from the much brighter starlight, but the dynamic boiling speckles, created by the stellar image, make exoplanet detection impossible without the help of a wavefront correction device. The Subaru Coronagraphic Extreme Adaptive Optics (SCExAO) system is a high performance HCI instrument developed at Subaru Telescope. The wavefront control system of SCExAO consists of three wavefront sensors (WFS) coupled with a 1024-actuator Micro-Electro-Mechanical-System (MEMS) deformable mirror (DM). MEMS DMs offer a large actuator density, allowing high count DMs to be deployed in small size beams. Therefore, MEMS DMs are an attractive technology for Adaptive Optics (AO) systems and are particularly well suited for HCI instruments employing ExAO technologies. SCExAO uses coherent light modulation in the focal plane introduced by the DM, for both wavefront sensing and correction. In this scheme, the DM is used to introduce known aberrations (speckles in the focal plane), which interfere with existing speckles. By monitoring the interference between the pre-existing speckles and the speckles added deliberately by the DM, it is possible to reconstruct the complex amplitude (amplitude and phase) of the focal plane speckles. Thus, the DM is used for wavefront sensing, in a scheme akin to phase diversity. For SCExAO and other HCI systems using phase diversity, the wavefront compensation is a mix of closed-loop and open-loop control of the DM. The successful implementation of MEMS DMs open-loop control relies on a thorough modelling of the DM response to the control system commands. The work presented in this thesis, motivated by the need to provide accurate DM control for the wavefront control system of SCExAO, was centred around the development of MEMS DM models. This dissertation reports the characterization of MEMS DMs and the development of two efficient modelling approaches. The open-loop performance of both approaches has been investigated. The model providing the best result has been implemented within the SCExAO wavefront control software. Within SCExAO, the model was used to command the DM to create focal plane speckles. The work is now focused on using the model within a full speckle nulling process and on increasing the execution speed to make the model suitable for on-sky operation. / Graduate

The hippocampus is a complex brain structure that has been studied extensively and is subject to abnormal structural change in various neuropsychiatric disorders. The highest definition in vivo method of visualizing the anatomy of this structure is structural Magnetic Resonance Imaging (MRI). Gross structure can be assessed by the naked eye inspection of MRI scans but measurement is required to compare scans from individuals within normal ranges, and to assess change over time in individuals. The gold standard of such measurement is manual tracing of the boundaries of the hippocampus on scans. This is known as a Region Of Interest (ROI) approach. ROI is laborious and there are difficulties with test-retest and inter-rater reliability. These difficulties are primarily due to uncertainty in designation of the hippocampus boundary. An improved, less labour intensive and more reliable method is clearly desirable. This thesis describes a fully automated hybrid methodology that is able to first locate and then extract hippocampal volumes from 3D 1.5T MRI T1 brain scans automatically. The hybrid algorithm uses brain atlas mappings and fuzzy inference to locate hippocampal areas and create initial hippocampal boundaries. This initial location is used to seed a deformable manifold algorithm. Rule based deformations are then applied to refine the estimate of the hippocampus locations. Finally, the hippocampus boundaries are corrected through an inference process that assures adherence to an expected hippocampus volume. The ICC values of this methodology when compared to the manual segmentation of the same hippocampi result in a 0.73 for the left and 0.81 for the right hippocampi. These values both fall within the range of reliability testing according to the manual ‘gold standard’ technique. Thus, this thesis describes the development and validation of a genuinely automated approach to hippocampal volume extraction of potential utility in studies of a range of neuropsychiatric disorders and could eventually find clinical applications.