Multi-Material Mesh Representation of Anatomical Structures for Deep Brain Stimulation Planning

The Dual Contouring algorithm (DC) is a grid-based process used to generate surface meshes from volumetric data. However, DC is unable to guarantee 2-manifold and watertight meshes due to the fact that it produces only one vertex for each grid cube. We present a modified Dual Contouring algorithm that is capable of overcoming this limitation. The proposed method decomposes an ambiguous grid cube into a set of tetrahedral cells and uses novel polygon generation rules that produce 2-manifold and watertight surface meshes with good-quality triangles. These meshes, being watertight and 2-manifold, are geometrically correct, and therefore can be used to initialize tetrahedral meshes. The 2-manifold DC method has been extended into the multi-material domain. Due to its multi-material nature, multi-material surface meshes will contain non-manifold elements along material interfaces or shared boundaries. The proposed multi-material DC algorithm can (1) generate multi-material surface meshes where each material sub-mesh is a 2-manifold and watertight mesh, (2) preserve the non-manifold elements along the material interfaces, and (3) ensure that the material interface or shared boundary between materials is consistent. The proposed method is used to generate multi-material surface meshes of deep brain anatomical structures from a digital atlas of the basal ganglia and thalamus. Although deep brain anatomical structures can be labeled as functionally separate, they are in fact continuous tracts of soft tissue in close proximity to each other. The multi-material meshes generated by the proposed DC algorithm can accurately represent the closely-packed deep brain structures as a single mesh consisting of multiple material sub-meshes. Each sub-mesh represents a distinct functional structure of the brain. Printed and/or digital atlases are important tools for medical research and surgical intervention. While these atlases can provide guidance in identifying anatomical structures, they do not take into account the wide variations in the shape and size of anatomical structures that occur from patient to patient. Accurate, patient-specific representations are especially important for surgical interventions like deep brain stimulation, where even small inaccuracies can result in dangerous complications. The last part of this research effort extends the discrete deformable 2-simplex mesh into the multi-material domain where geometry-based internal forces and image-based external forces are used in the deformation process. This multi-material deformable framework is used to segment anatomical structures of the deep brain region from Magnetic Resonance (MR) data

Articulated Statistical Shape Modelling of the Shoulder Joint

The shoulder joint is the most mobile and unstable joint in the human body. This makes it vulnerable to soft tissue pathologies and dislocation. Insight into the kinematics of the joint may enable improved diagnosis and treatment of different shoulder pathologies. Shoulder joint kinematics can be influenced by the articular geometry of the joint. The aim of this project was to develop an analysis framework for shoulder joint kinematics via the use of articulated statistical shape models (ASSMs). Articulated statistical shape models extend conventional statistical shape models by combining the shape variability of anatomical objects collected from different subjects (statistical shape models), with the physical variation of pose between the same objects (articulation). The developed pipeline involved manual annotation of anatomical landmarks selected on 3D surface meshes of scapulae and humeri and establishing dense surface correspondence across these data through a registration process. The registration was performed using a Gaussian process morphable model fitting approach. In order to register two objects separately, while keeping their shape and kinematics relationship intact, one of the objects (scapula) was fixed leaving the other (humerus) to be mobile. All the pairs of registered humeri and scapulae were brought back to their native imaged position using the inverse of the associated registration transformation. The glenohumeral rotational center and local anatomic coordinate system of the humeri and scapulae were determined using the definitions suggested by the International Society of Biomechanics. Three motions (flexion, abduction, and internal rotation) were generated using Euler angle sequences. The ASSM of the model was built using principal component analysis and validated. The validation results show that the model adequately estimated the shape and pose encoded in the training data. Developing ASSM of the shoulder joint helps to define the statistical shape and pose parameters of the gleno humeral articulating surfaces. An ASSM of the shoulder joint has potential applications in the analysis and investigation of population-wide joint posture variation and kinematics. Such analyses may include determining and quantifying abnormal articulation of the joint based on the range of motion; understanding of detailed glenohumeral joint function and internal joint measurement; and diagnosis of shoulder pathologies. Future work will involve developing a protocol for encoding the shoulder ASSM with real, rather than handcrafted, pose variation

Analysis, Segmentation and Prediction of Knee Cartilage using Statistical Shape Models

Osteoarthritis (OA) of the knee is one of the leading causes of chronic disability (along with the hip). Due to rising healthcare costs associated with OA, it is important to fully understand the disease and how it progresses in the knee. One symptom of knee OA is the degeneration of cartilage in the articulating knee. The cartilage pad plays a major role in painting the biomechanical picture of the knee. This work attempts to quantify the cartilage thickness of healthy male and female knees using statistical shape models (SSMs) for a deep knee bend activity. Additionally, novel cartilage segmentation from magnetic resonance imaging (MRI) and estimation algorithms from computer tomography (CT) or x-rays are proposed to facilitate the efficient development and accurate analysis of future treatments related to the knee. Cartilage morphology results suggest distinct patterns of wear in varus, valgus, and neutral degenerative knees, and examination of contact regions during the deep knee bend activity further emphasizes these patterns. Segmentation results were achieved that were comparable if not of higher quality than existing state-of-the-art techniques for both femoral and tibial cartilage. Likewise, using the point correspondence properties of SSMs, estimation of articulating cartilage was effective in healthy and degenerative knees. In conclusion, this work provides novel, clinically relevant morphological data to compute segmentation and estimate new data in such a way to potentially contribute to improving results and efficiency in evaluation of the femorotibial cartilage layer

Design and control of amphibious robots with multiple degrees of freedom

This thesis presents the design and realization of two generations of robot elements that can be assembled together to construct amphibious mobile robots. These elements, designed to be individually waterproof and having their own battery, motor controller, and motor, have been used to actually construct a snake, a boxfish and a salamander robot. Central pattern generator (CPG) models inspired from those found in vertebrates have been used for online trajectory generation on these robots and implemented on their onboard locomotion controllers. CPGs proved to be an interesting way of controlling complex robots, providing a simple interface which hides the complexity of the robot to the end user. Online learning algorithms that can be used to dynamically adapt the locomotion parameters to the environment have been implemented. Finally, this work also shows how robotics can be a useful tool to verify biological hypotheses. For instance, the salamander robot has been used to test a model of CPG for salamander locomotion

Behavioural drivers of fertility in red junglefowl Gallus gallus and commercial chicken flocks

The fowl, Gallus gallus, has been used to study sexual behaviour and sexual selection for many years: its combination of reproductive biology that is fairly typical of birds and a polygynandrous mating system makes it an ideal model species for studying the effects of pre- and post- copulatory competition and of conflict between the sexes. There is a large body of research spanning many decades on these processes in domestic chickens and their wild ancestor, the red junglefowl. As well as being an ideal model system, the sexual behaviour and fertility of this species is of great significance to the poultry industry, where the reproductive efficiency of broiler breeders (birds whose commercial purpose is to produce hatching eggs) is a key concern. However, the behaviour of broiler breeders in a commercial setting, and how their behaviour links to fertility, is little understood. Females of this species are subject to intense sexual harassment, and some behavioural strategies exhibited by females in response to sexual harassment have been described. However, we lack a detailed and systematic understanding of the suite of female responses to sexual harassment, despite these having the potential to significantly affect reproductive success for males and females. In this thesis, I build on existing knowledge of sexual behaviour and its influence on fertility, with a focus on female responses to sexual coercion and on commercially relevant insights in broiler breeders. I use a mix of approaches, from a theoretical model, to an experiment on a captive population of junglefowl, to translational research in broiler breeders. The findings of this thesis add new detail to our understanding of female resistance against sexual coercion, both in this species and in general, and inform suggestions for husbandry optimisations that could be trialled in broiler breeders

2017 Annual Research Symposium Abstract Book

2017 annual volume of abstracts for science research projects conducted by students at Trinity College

Form and function of the craniomandibular complex in subterranean rodents

Rodents are the most speciose mammalian order and are represented in arboreal, semiaquatic, subterranean and terrestrial niches. To flourish in such environments, rodents must exhibit morphological traits that can reflect functions that are needed to survive. This thesis focuses on the functional morphology of digging subterranean rodents and in particular, African mole-rats (Bathyergidae). Species dependent, subterranean rodents dig using a number of different methods. This thesis concentrates on the morphological differences in the craniomandibular complex in scratch digging and chisel-tooth digging subterranean rodents. Scratch digging rodents use only their claws to remove softer soil whilst their chisel-tooth digging counterparts use their incisors in concert with their powerful masticatory muscles to remove harder soils.Chapter two looks at morphological traits associated with bite force and gape in African mole-rats (Bathyergidae). The study shows that chisel-tooth digging rodents have morphological traits that are associated with a larger bite force at wider gapes, which is probably achieved by having a temporalis with a greater mechanical advantage.Chapter three examines a selection of chisel-tooth digging, scratch digging and terrestrial rodents. It shows that the upper incisors of chisel-tooth digging rodents have a larger radius of curvature. Also, it shows that chisel-tooth digging rodent cranial shape converges in morphospace and covaries with the upper incisors, although these results were not significant when phylogeny was accounted for.Chapter four shows that, using finite element analysis, the cranium of a chisel-tooth digging mole-rat can create larger bite forces at wider gapes, compared to a scratch digging mole-rat. Using a novel method of combining geometric morphometrics with finite element analysis, this study also shows that the cranium of the chisel-tooth digging rodent deforms less, making it more efficient at performing chisel-tooth digging tasks.Overall, this thesis shows that the craniomandibular form of subterranean rodents can be strongly influenced by function. The digging method used by a subterranean rodent is therefore important to how they have evolved.[Thesis also includes article published in:Biological journal of the Linnean Societyhttp://onlinelibrary.wiley.com/doi/10.1111/bij.12691/fullDOI: 10.1111/bij.12691

A biomechanics-based articulation model for medical applications

Computer Graphics came into the medical world especially after the arrival of 3D medical imaging. Computer Graphics techniques are already integrated in the diagnosis procedure by means of the visual tridimensional analysis of computer tomography, magnetic resonance and even ultrasound data. The representations they provide, nevertheless, are static pictures of the patients' body, lacking in functional information. We believe that the next step in computer assisted diagnosis and surgery planning depends on the development of functional 3D models of human body. It is in this context that we propose a model of articulations based on biomechanics. Such model is able to simulate the joint functionality in order to allow for a number of medical applications. It was developed focusing on the following requirements: it must be at the same time simple enough to be implemented on computer, and realistic enough to allow for medical applications; it must be visual in order for applications to be able to explore the joint in a 3D simulation environment. Then, we propose to combine kinematical motion for the parts that can be considered as rigid, such as bones, and physical simulation of the soft tissues. We also deal with the interaction between the different elements of the joint, and for that we propose a specific contact management model. Our kinematical skeleton is based on anatomy. Special considerations have been taken to include anatomical features like axis displacements, range of motion control, and joints coupling. Once a 3D model of the skeleton is built, it can be simulated by data coming from motion capture or can be specified by a specialist, a clinician for instance. Our deformation model is an extension of the classical mass-spring systems. A spherical volume is considered around mass points, and mechanical properties of real materials can be used to parameterize the model. Viscoelasticity, anisotropy and non-linearity of the tissues are simulated. We particularly proposed a method to configure the mass-spring matrix such that the objects behave according to a predefined Young's modulus. A contact management model is also proposed to deal with the geometric interactions between the elements inside the joint. After having tested several approaches, we proposed a new method for collision detection which measures in constant time the signed distance to the closest point for each point of two meshes subject to collide. We also proposed a method for collision response which acts directly on the surfaces geometry, in a way that the physical behavior relies on the propagation of reaction forces produced inside the tissue. Finally, we proposed a 3D model of a joint combining the three elements: anatomical skeleton motion, biomechanical soft tissues deformation, and contact management. On the top of that we built a virtual hip joint and implemented a set of medical applications prototypes. Such applications allow for assessment of stress distribution on the articular surfaces, range of motion estimation based on ligament constraint, ligament elasticity estimation from clinically measured range of motion, and pre- and post-operative evaluation of stress distribution. Although our model provides physicians with a number of useful variables for diagnosis and surgery planning, it should be improved for effective clinical use. Validation has been done partially. However, a global clinical validation is necessary. Patient specific data are still difficult to obtain, especially individualized mechanical properties of tissues. The characterization of material properties in our soft tissues model can also be improved by including control over the shear modulus