Three Dimensional Nonlinear Statistical Modeling Framework for Morphological Analysis

This dissertation describes a novel three-dimensional (3D) morphometric analysis framework for building statistical shape models and identifying shape differences between populations. This research generalizes the use of anatomical atlases on more complex anatomy as in case of irregular, flat bones, and bones with deformity and irregular bone growth. The foundations for this framework are: 1) Anatomical atlases which allow the creation of homologues anatomical models across populations; 2) Statistical representation for output models in a compact form to capture both local and global shape variation across populations; 3) Shape Analysis using automated 3D landmarking and surface matching. The proposed framework has various applications in clinical, forensic and physical anthropology fields. Extensive research has been published in peer-reviewed image processing, forensic anthropology, physical anthropology, biomedical engineering, and clinical orthopedics conferences and journals. The forthcoming discussion of existing methods for morphometric analysis, including manual and semi-automatic methods, addresses the need for automation of morphometric analysis and statistical atlases. Explanations of these existing methods for the construction of statistical shape models, including benefits and limitations of each method, provide evidence of the necessity for such a novel algorithm. A novel approach was taken to achieve accurate point correspondence in case of irregular and deformed anatomy. This was achieved using a scale space approach to detect prominent scale invariant features. These features were then matched and registered using a novel multi-scale method, utilizing both coordinate data as well as shape descriptors, followed by an overall surface deformation using a new constrained free-form deformation. Applications of output statistical atlases are discussed, including forensic applications for the skull sexing, as well as physical anthropology applications, such as asymmetry in clavicles. Clinical applications in pelvis reconstruction and studying of lumbar kinematics and studying thickness of bone and soft tissue are also discussed

Novel Techniques for Tissue Imaging and Characterization Using Biomedical Ultrasound

The use of ultrasound technology in the biomedical field has been widely increased in recent decades. Ultrasound modalities are considered more safe and cost effective than others that use ionizing radiation. Moreover, the use of high-frequency ultrasound provides means of high-resolution and precise tissue assessment. Consequently, ultrasound elastic waves have been widely used to develop non-invasive techniques for tissue assessment. In this work, ultrasound waves have been used to develop non-invasive techniques for tissue imaging and characterization in three different applications.;Currently, there is a lack of imaging modalities to accurately predict minute structures and defects in the jawbone. In particular, the inability of 2D radiographic images to detect bony periodontal defects resulted from infection of the periodontium. They also may carry known risks of cancer generation or may be limited in accurate diagnosis scope. Ultrasonic guided waves are sensitive to changes in microstructural properties, while high-frequency ultrasound has been used to reconstruct high-resolution images for tissue. The use of these ultrasound techniques may provide means for early diagnosis of marrow ischemic disorders via detecting focal osteoporotic marrow defect, chronic nonsuppurative osteomyelitis, and cavitations in the mandible (jawbone). The first part of this work investigates the feasibility of using guided waves and high frequency ultrasound for non-invasive human jawbone assessment. The experimental design and the signal/image processing procedures for each technique are developed, and multiple in vitro studies are carried out using dentate and non-dentate mandibles. Results from both the ultrasonic guided waves analysis and the high frequency 3D echodentographic imaging suggest that these techniques show great potential in providing non-invasive methods to characterize the jawbone and detect periodontal diseases at earlier stages.;The second part of this work describes indirect technique for characterization via reconstructing high-resolution microscopic images. The availability of well-defined genetic strains and the ability to create transgenic and knockout mice makes mouse models extremely significant tools in different kinds of research. For example, noninvasive measurement of cardiovascular function in mouse hearts has become a valuable need when studying the development or treatment of various diseases. This work describes the development and testing of a single-element ultrasound imaging system that can reconstruct high-resolution brightness mode (B-mode) images for mouse hearts and blood vessels that can be used for quantitative measurements in vitro. Signal processing algorithms are applied on the received ultrasound signals including filtering, focusing, and envelope detection prior to image reconstruction. Additionally, image enhancement techniques and speckle reduction are adopted to improve the image resolution and quality. The system performance is evaluated using both phantom and in vitro studies using isolated mouse hearts and blood vessels from APOE-KO and its wild type control. This imaging system shall provide a basis for early and accurate detection of different kinds of diseases such as atherosclerosis in mouse model.;The last part of this work is initialized by the increasing need for a non-invasive method to assess vascular wall mechanics. Endothelial dysfunction is considered a key factor in the development of atherosclerosis. Flow-mediated vasodilatation (FMD) measurement in brachial and other conduit arteries has become a common method to assess the endothelial function in vivo. In spite of the direct relationship that could be between the arterial wall multi-component strains and the FMD response, direct measurement of wall strain tensor due to FMD has not yet been reported in the literature. In this work, a noninvasive direct ultrasound-based strain tensor measuring (STM) technique is presented to assess changes in the mechanical parameters of the vascular wall during post-occlusion reactive hyperemia and/or FMD, including local velocities and displacements, diameter change, local strain tensor and strain rates. The STM technique utilizes sequences of B-mode ultrasound images as its input with no extra hardware requirement. The accuracy of the STM algorithm is assessed using phantom, and in vivo studies using human subjects during pre- and post-occlusion. Good correlations are found between the post-occlusion responses of diameter change and local wall strains. Results indicate the validity and versatility of the STM algorithm, and describe how parameters other than the diameter change are sensitive to reactive hyperemia following occlusion. This work suggests that parameters such as local strains and strain rates within the arterial wall are promising metrics for the assessment of endothelial function, which can then be used for accurate assessment of atherosclerosis

A Method to Represent Heterogeneous Materials for Rapid Prototyping: The Matryoshka Approach

Purpose—The purpose of this paper is to present a new method for representing heterogeneous materials using nested STL shells, based, in particular, on the density distributions of human bones. Design/methodology/approach—Nested STL shells, called Matryoshka models, are described, based on their namesake Russian nesting dolls. In this approach, polygonal models, such as STL shells, are “stacked” inside one another to represent different material regions. The Matryoshka model addresses the challenge of representing different densities and different types of bone when reverse engineering from medical images. The Matryoshka model is generated via an iterative process of thresholding the Hounsfield Unit (HU) data using computed tomography (CT), thereby delineating regions of progressively increasing bone density. These nested shells can represent regions starting with the medullary (bone marrow) canal, up through and including the outer surface of the bone. Findings—The Matryoshka approach introduced can be used to generate accurate models of heterogeneous materials in an automated fashion, avoiding the challenge of hand-creating an assembly model for input to multi-material additive or subtractive manufacturing. Originality/Value—This paper presents a new method for describing heterogeneous materials: in this case, the density distribution in a human bone. The authors show how the Matryoshka model can be used to plan harvesting locations for creating custom rapid allograft bone implants from donor bone. An implementation of a proposed harvesting method is demonstrated, followed by a case study using subtractive rapid prototyping to harvest a bone implant from a human tibia surrogate

Black-box printer models and their applications

In the electrophotographic printing process, the deposition of toner within the area of a given printer addressable pixel is strongly influenced by the values of its neighboring pixels. The interaction between neighboring pixels, which is commonly referred to as dot-gain, is complicated. The printer models which are developed according to a pre-designed test page can either be embedded in the halftoning algorithm, or used to predict the printed halftone image at the input to an algorithm being used to assess print quality. In our research, we examine the potential influence of a larger neighborhood (45?45) of the digital halftone image on the measured value of a printed pixel at the center of that neighborhood by introducing a feasible strategy for the contribution. We developed a series of six models with different accuracy and computational complexity to account for local neighborhood effects and the influence of a 45?45 neighborhood of pixels on the central printer-addressable pixel tone development. All these models are referred to as Black Box Model (BBM) since they are based solely on measuring what is on the printed page, and do not incorporate any information about the marking process itself. We developed two different types of printer models Standard Definition (SD) BBM and High Definition (HD) BBM with capture device Epson Expression 10000XL (Epson America, Inc., Long Beach, CA, USA) flatbed scanner operated at 2400 dpi under different analysis resolutions. The experiment results show that the larger neighborhood models yield a significant improvement in the accuracy of the prediction of the pixel values of the printed halftone image. The sample function generation black box model (SFG-BBM) is an extension of SD-BBM that adds the printing variation to the mean prediction to improve the prediction by more accurately matching the characteristics of the actual printed image. We also followed a structure similar to that used to develop our series of BBMs to develop a two-stage toner usage predictor for electrophotographic printers. We first obtained on a pixel-by-pixel basis, the predicted absorptance of printed and scanned page with the digital input using BBM. We then form a weighted sum of these predicted pixel values to predict overall toner usage on the printed page. Our two-stage predictor significantly outperforms existing method that is based on a simple pixel counting strategy, in terms of both accuracy and robustness of the prediction

Data-Driven Shape Analysis and Processing

Data-driven methods play an increasingly important role in discovering geometric, structural, and semantic relationships between 3D shapes in collections, and applying this analysis to support intelligent modeling, editing, and visualization of geometric data. In contrast to traditional approaches, a key feature of data-driven approaches is that they aggregate information from a collection of shapes to improve the analysis and processing of individual shapes. In addition, they are able to learn models that reason about properties and relationships of shapes without relying on hard-coded rules or explicitly programmed instructions. We provide an overview of the main concepts and components of these techniques, and discuss their application to shape classification, segmentation, matching, reconstruction, modeling and exploration, as well as scene analysis and synthesis, through reviewing the literature and relating the existing works with both qualitative and numerical comparisons. We conclude our report with ideas that can inspire future research in data-driven shape analysis and processing.Comment: 10 pages, 19 figure

Ship Multimodel 3D Reconstruction and Corrosion Detection

3D reconstruction has been an area of increased interest due to the current higher demand in applications, such as virtual realities, 3D mapping, medical imaging, and many others. Although, there are still many problems associated with reconstructing a real-life object, such as capturing occluded zones, noise, and processing time. Furthermore, as deep learning technologies advance, there has been a growing interest in using such methods to replace human-driven tasks, namely corrosion inspection, as it decreases the risk of injury of the inspector, it is more efficient due to less time taken, and is cost-saving. This dissertation proposes a method for reconstructing a 3D model of ships using aerial RGB images and terrestrial RGB-D images, along with a system capable of detecting the corroded parts of the ship and highlighting them in the model. Using two different sensors in two different ground planes mitigates some of the occlusion problems and increases the final model’s accuracy. The current dissertation also aims to pick the methods that have the best trade-off between accuracy and computational speed. The final model can be advantageous for corrosion inspectors, as they will have the model of the ship, as well as the corroded zones which, with that information, can choose the steps to take next without the need to manually inspect the ship or even be in the same site as the ship. The final model is a fusion of three different 3D models. The model obtained from RGB images exploits Structure from Motion algorithm which recovers the 3D aspect of the ship from 2D images. As for the remaining models, RGB-D images were used in conjunction with the Open3D library to create 3D structures from both sides of the ship. The corrosion classifier model was trained in Google Colab and achieved an accuracy of 97.44 % on the test dataset. The images used to create the SfM 3D model were each divided into a total of 40 regions and fed into the classifier to simulate a less concise image detection algorithm instead of an image classification algorithm. The results were encoded into the 3D model, highlighting the corroded zones.A reconstrução 3D tem sido uma área com crescente interesse devido à maior demanda em aplicações como realidade virtual, mapeamento 3D, imagens médicas e muitos outros. Embora, existem ainda muitos problemas associados à reconstrução 3D de um objeto real. Exemplos desses são a captura de zonas oclusas, o ruído e o tempo de processamento necessário para efetuar a reconstrução. Adicionalmente, com o avanço das tecnologias de deep learning, tem havido um acrescido interesse em usar ditos métodos para substituir tarefas realizadas por humanos como, por exemplo, a inspeção de corrosão, pois diminui o risco de lesões ao inspetor, tem maior eficiência devido a um menor tempo gasto, e economiza os custos. Esta dissertação propõe um método de reconstrução de um modelo 3D de navios, utilizando imagens RGB aéreas e imagens RGB-D terrestres, juntamente com um sistema capaz de detetar as zonas com corrosão no navio e destacá-las no modelo. O uso de dois sensores diferentes em dois meios diferentes atenuará alguns dos problemas de oclusão e aumentará a precisão do modelo final. A presente dissertação também visa escolher os métodos que apresentam o melhor compromisso entre precisão e velocidade de processamento. O modelo final poderá ser vantajoso para os inspetores de corrosão, pois terão o modelo do navio, bem como as zonas com corrosão que, com essa informação, poderão escolher quais os passos a seguir, sem a necessidade de inspecionar manualmente o navio ou mesmo deslocar-se para o local do navio. O modelo final é uma fusão de três modelos 3D diferentes. O modelo obtido a partir de imagens RGB tirou partido do algoritmo Structure from Motion, que recupera o aspeto 3D do navio a partir de imagens 2D. Quanto aos modelos restantes, as imagens RGB-D foram utilizadas em conjunto com a biblioteca Open3D para criar estruturas 3D de ambos os lados do navio. O modelo de classificação de corrosão foi treinado em ambiente Google Colab e alcançou uma exatidão de 97.44% no dataset de teste. As imagens usadas para criar o modelo SfM 3D foram, cada uma, fracionadas num total de 40 regiões e dadas ao modelo de classificação com o intuito de simularum modelo de deteção de imagem menos conciso em vez de um modelo de classificação de imagem. Os resultados foram codificados no modelo 3D, destacando as zonas com corrosão

Multi-scale metrology for automated non-destructive testing systems

This thesis was previously held under moratorium from 5/05/2020 to 5/05/2022The use of lightweight composite structures in the aerospace industry is now commonplace. Unlike conventional materials, these parts can be moulded into complex aerodynamic shapes, which are diffcult to inspect rapidly using conventional Non-Destructive Testing (NDT) techniques. Industrial robots provide a means of automating the inspection process due to their high dexterity and improved path planning methods. This thesis concerns using industrial robots as a method for assessing the quality of components with complex geometries. The focus of the investigations in this thesis is on improving the overall system performance through the use of concepts from the field of metrology, specifically calibration and traceability. The use of computer vision is investigated as a way to increase automation levels by identifying a component's type and approximate position through comparison with CAD models. The challenges identified through this research include developing novel calibration techniques for optimising sensor integration, verifying system performance using laser trackers, and improving automation levels through optical sensing. The developed calibration techniques are evaluated experimentally using standard reference samples. A 70% increase in absolute accuracy was achieved in comparison to manual calibration techniques. Inspections were improved as verified by a 30% improvement in ultrasonic signal response. A new approach to automatically identify and estimate the pose of a component was developed specifically for automated NDT applications. The method uses 2D and 3D camera measurements along with CAD models to extract and match shape information. It was found that optical large volume measurements could provide suffciently high accuracy measurements to allow ultrasonic alignment methods to work, establishing a multi-scale metrology approach to increasing automation levels. A classification framework based on shape outlines extracted from images was shown to provide over 88% accuracy on a limited number of samples.The use of lightweight composite structures in the aerospace industry is now commonplace. Unlike conventional materials, these parts can be moulded into complex aerodynamic shapes, which are diffcult to inspect rapidly using conventional Non-Destructive Testing (NDT) techniques. Industrial robots provide a means of automating the inspection process due to their high dexterity and improved path planning methods. This thesis concerns using industrial robots as a method for assessing the quality of components with complex geometries. The focus of the investigations in this thesis is on improving the overall system performance through the use of concepts from the field of metrology, specifically calibration and traceability. The use of computer vision is investigated as a way to increase automation levels by identifying a component's type and approximate position through comparison with CAD models. The challenges identified through this research include developing novel calibration techniques for optimising sensor integration, verifying system performance using laser trackers, and improving automation levels through optical sensing. The developed calibration techniques are evaluated experimentally using standard reference samples. A 70% increase in absolute accuracy was achieved in comparison to manual calibration techniques. Inspections were improved as verified by a 30% improvement in ultrasonic signal response. A new approach to automatically identify and estimate the pose of a component was developed specifically for automated NDT applications. The method uses 2D and 3D camera measurements along with CAD models to extract and match shape information. It was found that optical large volume measurements could provide suffciently high accuracy measurements to allow ultrasonic alignment methods to work, establishing a multi-scale metrology approach to increasing automation levels. A classification framework based on shape outlines extracted from images was shown to provide over 88% accuracy on a limited number of samples

Intertwined chiral charge orders and topological stabilization of the light-induced state of a prototypical transition metal dichalcogenide

The fundamental idea that the constituents of interacting many body systems in complex quantum materials may self-organise into long range order under highly non-equilibrium conditions leads to the notion that entirely new and unexpected functionalities might be artificially created. However, demonstrating new emergent order in highly non-equilibrium transitions has proven surprisingly difficult. In spite of huge recent advances in experimental ultrafast time-resolved techniques, methods that average over successive transition outcomes have so far proved incapable of elucidating the emerging spatial structure. Here, using scanning tunneling microscopy, we report for the first time the charge order emerging after a single transition outcome in a prototypical two-dimensional dichalcogenide 1T-TaS$_2$ initiated by a single optical pulse. By mapping the vector field of charge displacements of the emergent state, we find surprisingly intricate, long-range, topologically non-trivial charge order in which chiral domain tiling is intertwined with unique unpaired dislocations which play a crucial role in enhancing the emergent states remarkable stability. The discovery of the principles that lead to metastability in charge-ordered systems open the way to designing novel emergent functionalities, particularly ultrafast all-electronic non-volatile cryo-memories.Comment: preprint version of the paper published in npj Quantum Material