Development of an Atlas-Based Segmentation of Cranial Nerves Using Shape-Aware Discrete Deformable Models for Neurosurgical Planning and Simulation

Twelve pairs of cranial nerves arise from the brain or brainstem and control our sensory functions such as vision, hearing, smell and taste as well as several motor functions to the head and neck including facial expressions and eye movement. Often, these cranial nerves are difficult to detect in MRI data, and thus represent problems in neurosurgery planning and simulation, due to their thin anatomical structure, in the face of low imaging resolution as well as image artifacts. As a result, they may be at risk in neurosurgical procedures around the skull base, which might have dire consequences such as the loss of eyesight or hearing and facial paralysis. Consequently, it is of great importance to clearly delineate cranial nerves in medical images for avoidance in the planning of neurosurgical procedures and for targeting in the treatment of cranial nerve disorders. In this research, we propose to develop a digital atlas methodology that will be used to segment the cranial nerves from patient image data. The atlas will be created from high-resolution MRI data based on a discrete deformable contour model called 1-Simplex mesh. Each of the cranial nerves will be modeled using its centerline and radius information where the centerline is estimated in a semi-automatic approach by finding a shortest path between two user-defined end points. The cranial nerve atlas is then made more robust by integrating a Statistical Shape Model so that the atlas can identify and segment nerves from images characterized by artifacts or low resolution. To the best of our knowledge, no such digital atlas methodology exists for segmenting nerves cranial nerves from MRI data. Therefore, our proposed system has important benefits to the neurosurgical community

AN AUTOMATED DENTAL CARIES DETECTION AND SCORING SYSTEM FOR OPTIC IMAGES OF TOOTH OCCLUSAL SURFACE

Dental caries are one of the most prevalent chronic diseases. Worldwide 60 to 90 percent of school children and nearly 100 percent of adults experienced dental caries. The management of dental caries demands detection of carious lesions at early stages. The research of designing diagnostic tools in caries has been at peak for the last decade. This research aims to design an automated system to detect and score dental caries according to the International Caries Detection and Assessment System (ICDAS) guidelines using the optical images of the occlusal tooth surface. There have been numerous works that address the problem of caries detection by using new imaging technologies or advanced measurements. However, no such study has been done to detect and score caries with the use of optical images of the tooth surface. The aim of this dissertation is to develop image processing and machine learning algorithms to address the problem of detection and scoring the caries by the use of optical image of the tooth surface

Registration and statistical analysis of the tongue shape during speech production

This thesis analyzes the human tongue shape during speech production. First, a semi-supervised approach is derived for estimating the tongue shape from volumetric magnetic resonance imaging data of the human vocal tract. Results of this extraction are used to derive parametric tongue models. Next, a framework is presented for registering sparse motion capture data of the tongue by means of such a model. This method allows to generate full three-dimensional animations of the tongue. Finally, a multimodal and statistical text-to-speech system is developed that is able to synthesize audio and synchronized tongue motion from text.Diese Dissertation beschäftigt sich mit der Analyse der menschlichen Zungenform während der Sprachproduktion. Zunächst wird ein semi-überwachtes Verfahren vorgestellt, mit dessen Hilfe sich Zungenformen von volumetrischen Magnetresonanztomographie- Aufnahmen des menschlichen Vokaltrakts schätzen lassen. Die Ergebnisse dieses Extraktionsverfahrens werden genutzt, um ein parametrisches Zungenmodell zu konstruieren. Danach wird eine Methode hergeleitet, die ein solches Modell nutzt, um spärliche Bewegungsaufnahmen der Zunge zu registrieren. Dieser Ansatz erlaubt es, dreidimensionale Animationen der Zunge zu erstellen. Zuletzt wird ein multimodales und statistisches Text-to-Speech-System entwickelt, das in der Lage ist, Audio und die dazu synchrone Zungenbewegung zu synthetisieren.German Research Foundatio

Wire-driven mechanism and highly efficient propulsion in water.

自然生物的杰出表现往往令人们叹为观止。正因为如此，在机器人研究中对自然界动植物的模仿从未间断。本文受动物肌肉骨骼系统（尤其是蛇的脊柱以及章鱼手臂的肌肉分布）的启发，设计了一种新型的仿生拉线机构。该机构由柔性骨架以及成对拉线组成。柔性骨架提供支撑，拉线模拟肌肉将驱动器的运动和力传递给骨架，并控制骨架运动。从骨架结构分，拉线机构可分为蛇形拉线机构以及连续型拉线机构；从骨架分段来看，拉线机构可分为单段式拉线机构以及多段式拉线机构，其中每段由一或两对拉线控制。拉线机构的主要性能特征包括：大柔性，高度欠驱动，杠杆效应，以及远程传力。机构的柔性使得它可以产生很大的弯曲变形；欠驱动设计极大地减少了驱动器的数目，简化了系统结构；在杠杆效应下，骨架末端速度、加速度与拉线的速度、加速度相比得到数十倍放大；通过拉线将驱动器的运动和力远程传递给执行机构，使得拉线机构结构简单紧凑。基于以上特征，拉线机构不仅适合工作于狭窄空间，同时也适合于摆动推进，尤其是水下推进。论文系统地介绍了拉线机构的设计，运动学，工作空间，静力学以及动力学模型。在常曲率假设下分别建立了蛇形拉线机构以及连续型拉线机构的运动学模型，在此基础上建立了一个通用运动学模型，以及工作空间模型。与传统避障相反，本文提出了一种利用现有障碍或主动布置约束来拓展工作空间的新方法。通过牛顿-欧拉法以及拉格朗日方程建立了蛇形拉线机构的静力学模型以及动力学模型。在非线性欧拉-伯努利梁理论下结合汉密尔顿原理建立了连续型拉线机构的静力学模型以及动力学模型。论文中利用拉线机构设计了一系列新型水下推进器。与传统机器鱼推进器设计方法（单关节，多关节以及基于智能材料的连续型设计）相比，基于拉线机构的水下推进器的优点在于：所需驱动器少，能更好地模拟鱼的游动，易于控制，推进效率高，以及容易衍生新型推进器。设计制作了四条拉线驱动机器鱼，以此为平台验证了拉线推进器的性能以及优点。实验结果表明，基于蛇形拉线机构的推进器可以提供较大推力；基于连续型拉线机构设计的推进器受摩擦影响较小；基于单段式拉线机构的推进器可以模仿鱼类摆动式推进，具有很好的转弯性能；基于多段式拉线机构的推进器可以同时模仿摆动式推进和波动式推进，具有更好的稳定性以及游速。此外，基于拉线机构制造了一种新型矢量推进器。该推进器可以提供任意方向的推力，从而提高机器鱼的机动性能。实验中，在两个额定功率为1瓦的电机驱动下，机器鱼的最大游速为0.67 体长/秒；最小转弯半径为0.24倍体长；转弯速度为51.4 度/秒；最高推进效率为92.85%。最后，采用拉线推进器制作了一个室内空中移动机器人，取名为Flying Octopus。它由一个氦气球提供浮力悬停在空中，通过四个独立控制的拉线扑翼驱动可在三维空间自由运动。Attracted by the outstanding performance of natural creatures, researchers have been mimicking animals and plants to develop their robots. Inspired by animals’ musculoskeletal system, especially the skeletal structure of snakes and octopus arm muscle arrangement, in this thesis, a novel wire-driven mechanism (WDM) is designed. It is composed of a flexible backbone and a number of controlling wire groups. The flexible backbone provides support, while the wire groups transmit motion and force from the actuators, mimicking the muscles. According to its backbone structure, the WDM is categorized as serpentine WDM and continuum WDM. Depending on the backbone segmentation, WDM is divided into single segment WDM and multi-segment WDM. Each segment is controlled by one or two wire groups. Features of WDM include: flexible, highly under-actuated, leverage effect, and long range force and motion transmission. The flexibility enables the WDM making large deformation, while the under-actuation greatly reduces th number of actuators, simplifying the system. With the leverage effect, WDM distal end velocity and acceleration is greatly amplified from that of wire. Also, in the WDM, the actuators and the backbone are serperated. Actuator’s motion is transmitted by the wires. This makes the WDM very compact. With these features, the WDM is not only well suited to confined space, but also flapping propulsion, especially in water.In the thesis, the design, kinematics, workspace, static and dynamic models of the WDM are explored systematically. Under the constant curvature assumption, the kinematic model of serpentine WDM and continuum WDM are established. A generalized model is also developed. Workspace model is built from the forward kinematic model. Rather than avoiding obstacles, a novel idea of employing obstacles or actively deploying constraints to expand workspace is also discussed for WDM-based flexible manipulators. The static model and dynamic model of serpentine WDM is developed using the Newton-Euler method and the Lagrange Equation, while that of continuum WDM is built under the non-linear Euler-Bernoulli Beam theory and the extended Hamilton’s principle.In the thesis, a number of novel WDM based underwater propulsors are developed. Compared with existing fish-like propulsor designs, including single joint design, multi-joint design, and smart material based continuum design, the proposed WDM-based propulsors have advantages in several aspects, such as employing less actuators, better resembling the fish swimming body curve, ease of control, and more importantly, being highly efficient. Also, brand new propulsors can be easily developed using the WDM. To demonstrate the features as well as the advantages of WDM propulsors, four robot fish prototypes are developed. Experiments show that the serpentine WDM-based propulsor could provide large flapping force while the continuum WDM-based propulsor is less affected by joint friction. On the other hand, single segment WDM propulsor can make oscillatory swim while multi- segment WDM propulsor can make both oscillatory and undulatory swims. The undulatory swimming outperforms the oscillatory swimming in stability and speed, but is inferior in turning around. In addition, a novel robot fish with vector propulsion capability is also developed. It can provide thrust in arbitrary directions, hence, improving the maneuverability of the robot fish. In the experiments, with the power limit of two watts, the maximum forward speed of the WDM robot fishes can reach 0.67 BL (Body Length)/s. The minimum turning radius is 0.24 BL, and the turning speed is 51.4°/s. The maximum Froude efficiency of the WDM robot fishes is 92.85%. Finally, the WDM-based propulsor is used to build an indoor Lighter-than-Air- Vehicle (LTAV), named Flying Octopus. It is suspended in the air by a helium balloon and actuated by four independently controlled wire-driven flapping wings. With the wing propulsion, it can move in 3D space effectively.Detailed summary in vernacular field only.Detailed summary in vernacular field only.Detailed summary in vernacular field only.Li, Zheng.Thesis (Ph.D.)--Chinese University of Hong Kong, 2013.Includes bibliographical references (leaves 205-214).Abstracts also in Chinese.Abstracth --- p.i摘要 --- p.iiiAcknowledgement --- p.vList of Figures --- p.xiList of Tables --- p.xviiChapter Chapter 1 --- Introduction --- p.1Chapter 1.1 --- Background --- p.1Chapter 1.2 --- Related Research --- p.2Chapter 1.2.1 --- Flexible Manipulator --- p.2Chapter 1.2.2 --- Robot Fish --- p.10Chapter 1.3 --- Motivation of the Dissertation --- p.13Chapter 1.4 --- Organization of the Dissertation --- p.14Chapter Chapter 2 --- Biomimetic Wire-Driven Mechanism --- p.16Chapter 2.1 --- Inspiration from Nature --- p.16Chapter 2.1.1 --- Snake Skeleton --- p.18Chapter 2.1.2 --- Octopus Arm --- p.19Chapter 2.2 --- Wire-Driven Mechanism Design --- p.20Chapter 2.2.1 --- Flexible Backbone --- p.20Chapter 2.2.2 --- Backbone Segmentation --- p.26Chapter 2.2.3 --- Wire Configuration --- p.28Chapter 2.3 --- Wire-Driven Mechanism Categorization --- p.31Chapter 2.4 --- Summary --- p.32Chapter Chapter 3 --- Kinematics and Workspace of the Wire-Driven Mechanism --- p.33Chapter 3.1 --- Kinematic Model of Single Segment WDM --- p.33Chapter 3.1.1 --- Kinematic Model of the Serpentine WDM --- p.34Chapter 3.1.2 --- Kinematic Model of the Continuum WDM --- p.39Chapter 3.1.3 --- A Generalized Kinematic Model --- p.43Chapter 3.2 --- Kinematic Model of Multi-Segment WDM --- p.47Chapter 3.2.1 --- Forward Kinematics --- p.47Chapter 3.2.2 --- Inverse Kinematics --- p.51Chapter 3.3 --- Workspace --- p.52Chapter 3.3.1 --- Workspace of Single Segment WDM --- p.52Chapter 3.3.2 --- Workspace of Multi-Segment WDM --- p.53Chapter 3.4 --- Employing Obstacles to Expand WDM Workspace --- p.55Chapter 3.4.1 --- Constrained Kinematics Model of WDM --- p.55Chapter 3.4.2 --- WDM Workspace with Constraints --- p.61Chapter 3.5 --- Model Validation via Experiment --- p.64Chapter 3.5.1 --- Single Segment WDM Kinematic Model Validation --- p.64Chapter 3.5.2 --- Multi-Segment WDM Kinematic Model Validation --- p.66Chapter 3.5.3 --- Constrained Kinematic Model Validation --- p.70Chapter 3.6 --- Summary --- p.73Chapter Chapter 4 --- Statics and Dynamics of the Wire-Driven Mechanism --- p.75Chapter 4.1 --- Static Model of the Wire-Driven Mechanism --- p.75Chapter 4.1.1 --- Static Model of SPSP WDM --- p.75Chapter 4.1.2 --- Static Model of SPCP WDM --- p.81Chapter 4.2 --- Dynamic Model of the Wire-Driven Mechanism --- p.88Chapter 4.2.1 --- Dynamic Model of SPSP WDM --- p.88Chapter 4.2.2 --- Dynamic Model of SPCP WDM --- p.92Chapter 4.3 --- Summary --- p.94Chapter Chapter 5 --- Application I - Wire-Driven Robot Fish --- p.95Chapter 5.1 --- Fish Swimming Introduction --- p.95Chapter 5.1.1 --- Fish Swimming Categories --- p.95Chapter 5.1.2 --- Body Curve Function --- p.96Chapter 5.1.3 --- Fish Swimming Hydrodynamics --- p.101Chapter 5.1.4 --- Fish Swimming Data --- p.103Chapter 5.2 --- Oscillatory Wire-Driven Robot Fish --- p.104Chapter 5.2.1 --- Serpentine Oscillatory Wire-Driven Robot Fish Design --- p.105Chapter 5.2.2 --- Continuum Oscillatory Wire-Driven Robot Fish Design --- p.110Chapter 5.2.3 --- Oscillatory Robot Fish Propulsion Model --- p.114Chapter 5.2.4 --- Robot Fish Swimming Control --- p.116Chapter 5.2.5 --- Swimming Experiments --- p.118Chapter 5.3 --- Undulatory Wire-Driven Robot Fish --- p.125Chapter 5.3.1 --- Undulatory Wire-Driven Robot Fish Design --- p.125Chapter 5.3.2 --- Undulatory Wire-Driven Robot Fish Propulsion Model --- p.130Chapter 5.3.3 --- Swimming Experiments --- p.131Chapter 5.4 --- Vector Propelled Wire-Driven Robot Fish --- p.136Chapter 5.4.1 --- Vector Propelled Wire-Driven Robot Fish Design --- p.136Chapter 5.4.2 --- Tail Motion Analysis --- p.140Chapter 5.4.3 --- Swimming Experiments --- p.142Chapter 5.5 --- Wire-Driven Robot Fish Performance and Discussion --- p.144Chapter 5.5.1 --- Performance --- p.144Chapter 5.5.2 --- Discussion --- p.147Chapter 5.6 --- Summary --- p.149Chapter Chapter 6 --- Aplication II - Wire-Driven LTAV - Flying Octopus --- p.151Chapter 6.1 --- Introduction --- p.151Chapter 6.2 --- Flying Octopus Design --- p.152Chapter 6.2.1 --- Flying Octopus Body Design --- p.152Chapter 6.2.2 --- Wire-Driven Flapping Wing Design --- p.153Chapter 6.3 --- Flying Octopus Motion Control --- p.156Chapter 6.3.1 --- Propulsion Model --- p.156Chapter 6.3.2 --- Motion Control Strategy --- p.157Chapter 6.3.3 --- Motion Simulation --- p.159Chapter 6.4 --- Prototype and Indoor Experiments --- p.161Chapter 6.4.1 --- Flying Octopus Prototype --- p.161Chapter 6.4.2 --- Indoor Experiments --- p.163Chapter 6.4.3 --- Discussion --- p.165Chapter 6.5 --- Summary --- p.166Chapter Chapter 7 --- Conclusions and Future Work --- p.167Chapter Appendix A - --- Publication Record --- p.170Chapter Appendix B - --- Derivation --- p.172Chapter Appendix C --- Matlab Programs --- p.176References --- p.20

Non-invasive ultrasound monitoring of regional carotid wall structure and deformation in atherosclerosis

Thesis (Ph. D.)--Harvard--Massachusetts Institute of Technology Division of Health Sciences and Technology, 2001.Includes bibliographical references (p. 223-242).Atherosclerosis is characterized by local remodeling of arterial structure and distensibility. Developing lesions either progress gradually to compromise tissue perfusion or rupture suddenly to cause catastrophic myocardial infarction or stroke. Reliable measurement of changes in arterial structure and composition is required for assessment of disease progression. Non-invasive carotid ultrasound can image the heterogeneity of wall structure and distensibility caused by atherosclerosis. However, this capability has not been utilized for clinical monitoring because of speckle noise and other artifacts. Clinical measures focus instead on average wall thickness and diameter distension in the distal common carotid to reduce sensitivity to noise. The goal of our research was to develop an effective system for reliable regional structure and deformation measurements since these are more sensitive indicators of disease progression. We constructed a system for freehand ultrasound scanning based on custom software which simultaneously acquires real-time image sequences and 3D frame localization data from an electromagnetic spatial localizer. With finite element modeling, we evaluated candidate measures of regional wall deformation.(cont.) Finally, we developed a multi-step scheme for robust estimation of local wall structure and deformation. This new strategy is based on a directionally-sensitive segmentation functional and a motion-region-of-interest constrained optical flow algorithm. We validated this estimator with simulated images and clinical ultrasound data. The results show structure estimates that are accurate and precise, with inter- and intra-observer reproducibility surpassing existing methods. Estimates of wall velocity and deformation likewise show good overall accuracy and precision. We present results from a proof-of-principle evaluation conducted in a pilot study of normal subjects and clinical patients. For one example, we demonstrate the combination of 2D image processing with 3D frame localization for visualization of the carotid volume. With slice localization, estimates of carotid wall structure and deformation can be derived for all axial positions along the carotid artery. The elements developed here provide the tools necessary for reliable quantification of regional wall structure and composition changes which result from atherosclerosis.by Raymond C. Chan.Ph.D

Image segmentation with variational active contours

An important branch of computer vision is image segmentation. Image segmentation aims at extracting meaningful objects lying in images either by dividing images into contiguous semantic regions, or by extracting one or more specific objects in images such as medical structures. The image segmentation task is in general very difficult to achieve since natural images are diverse, complex and the way we perceive them vary according to individuals. For more than a decade, a promising mathematical framework, based on variational models and partial differential equations, have been investigated to solve the image segmentation problem. This new approach benefits from well-established mathematical theories that allow people to analyze, understand and extend segmentation methods. Moreover, this framework is defined in a continuous setting which makes the proposed models independent with respect to the grid of digital images. This thesis proposes four new image segmentation models based on variational models and the active contours method. The active contours or snakes model is more and more used in image segmentation because it relies on solid mathematical properties and its numerical implementation uses the efficient level set method to track evolving contours. The first model defined in this dissertation proposes to determine global minimizers of the active contour/snake model. Despite of great theoretic properties, the active contours model suffers from the existence of local minima which makes the initial guess critical to get satisfactory results. We propose to couple the geodesic/geometric active contours model with the total variation functional and the Mumford-Shah functional to determine global minimizers of the snake model. It is interesting to notice that the merging of two well-known and "opposite" models of geodesic/geometric active contours, based on the detection of edges, and active contours without edges provides a global minimum to the image segmentation algorithm. The second model introduces a method that combines at the same time deterministic and statistical concepts. We define a non-parametric and non-supervised image classification model based on information theory and the shape gradient method. We show that this new segmentation model generalizes, in a conceptual way, many existing models based on active contours, statistical and information theoretic concepts such as mutual information. The third model defined in this thesis is a variational model that extracts in images objects of interest which geometric shape is given by the principal components analysis. The main interest of the proposed model is to combine the three families of active contours, based on the detection of edges, the segmentation of homogeneous regions and the integration of geometric shape prior, in order to use simultaneously the advantages of each family. Finally, the last model presents a generalization of the active contours model in scale spaces in order to extract structures at different scales of observation. The mathematical framework which allows us to define an evolution equation for active contours in scale spaces comes from string theory. This theory introduces a mathematical setting to process a manifold such as an active contour embedded in higher dimensional Riemannian spaces such as scale spaces. We thus define the energy functional and the evolution equation of the multiscale active contours model which can evolve in the most well-known scale spaces such as the linear or the curvature scale space

Variational methods for texture segmentation

In the last decades, image production has grown significantly. From digital photographs to the medical scans, including satellite images and video films, more and more data need to be processed. Consequently the number of applications based on digital images has increased, either for medicine, research for country planning or for entertainment business such as animation or video games. All these areas, although very different one to another, need the same image processing techniques. Among all these techniques, segmentation is probably one of the most studied because of its important role. Segmentation is the process of extracting meaningful objects from an image. This task, although easily achieved by the human visual system, is actually complex and still a true challenge for the image processing community despite several decades of research. The thesis work presented in this manuscript proposes solutions to the image segmentation problem in a well established mathematical framework, i.e. variational models. The image is defined in a continuous space and the segmentation problem is expressed through a functional or energy optimization. Depending on the object to be segmented, this energy definition can be difficult; in particular for objects with ambiguous borders or objects with textures. For the latter, the difficulty lies already in the definition of the term texture. The human eye can easily recognize a texture, but it is quite difficult to find words to define it, even more in mathematical terms. There is a deliberate vagueness in the definition of texture which explains the difficulty to conceptualize a model able to describe it. Often these textures can neither be described by homogeneous regions nor by sharp contours. This is why we are first interested in the extraction of texture features, that is to say, finding one representation that can discriminate a textured region from another. The first contribution of this thesis is the construction of a texture descriptor from the representation of the image similar to a surface in a volume. This descriptor belongs to the framework of non-supervised segmentation, since it will not require any user interaction. The second contribution is a solution for the segmentation problem based on active contour models and information theory tools. Third contribution is a semi-supervised segmentation model, i.e. where constraints provided by the user will be integrated in the segmentation framework. This processus is actually derived from the graph of image patches. This graph gives the connectivity measure between the different points of the image. The segmentation will be expressed by a graph partition and a variational model. This manuscript proposes to tackle the segmentation problem for textured images