Towards breast tomography with synchrotron radiation at Elettra: First images

The aim of the SYRMA-CT collaboration is to set-up the first clinical trial of phase-contrast breast CT with synchrotron radiation (SR). In order to combine high image quality and low delivered dose a number of innovative elements are merged: a CdTe single photon counting detector, state-of-the-art CT reconstruction and phase retrieval algorithms. To facilitate an accurate exam optimization, a Monte Carlo model was developed for dose calculation using GEANT4. In this study, high isotropic spatial resolution (120 μm)3 CT scans of objects with dimensions and attenuation similar to a human breast were acquired, delivering mean glandular doses in the range of those delivered in clinical breast CT (5-25 mGy). Due to the spatial coherence of the SR beam and the long distance between sample and detector, the images contain, not only absorption, but also phase information from the samples. The application of a phase-retrieval procedure increases the contrast-to-noise ratio of the tomographic images, while the contrast remains almost constant. After applying the simultaneous algebraic reconstruction technique to low-dose phase-retrieved data sets (about 5 mGy) with a reduced number of projections, the spatial resolution was found to be equal to filtered back projection utilizing a four fold higher dose, while the contrast-to-noise ratio was reduced by 30%. These first results indicate the feasibility of clinical breast CT with SR

Research of Optimum Depth of Overlapping in Cellular Automata

The speed of calculations homogeneous cellular automata is determined depending on depth of overlapping with use of a method of overlapped Windows. Optimum depth of overlapping also is investigated depending on parameters cellular automata

Bio-Inspired Computer Vision: Towards a Synergistic Approach of Artificial and Biological Vision

To appear in CVIUStudies in biological vision have always been a great source of inspiration for design of computer vision algorithms. In the past, several successful methods were designed with varying degrees of correspondence with biological vision studies, ranging from purely functional inspiration to methods that utilise models that were primarily developed for explaining biological observations. Even though it seems well recognised that computational models of biological vision can help in design of computer vision algorithms, it is a non-trivial exercise for a computer vision researcher to mine relevant information from biological vision literature as very few studies in biology are organised at a task level. In this paper we aim to bridge this gap by providing a computer vision task centric presentation of models primarily originating in biological vision studies. Not only do we revisit some of the main features of biological vision and discuss the foundations of existing computational studies modelling biological vision, but also we consider three classical computer vision tasks from a biological perspective: image sensing, segmentation and optical flow. Using this task-centric approach, we discuss well-known biological functional principles and compare them with approaches taken by computer vision. Based on this comparative analysis of computer and biological vision, we present some recent models in biological vision and highlight a few models that we think are promising for future investigations in computer vision. To this extent, this paper provides new insights and a starting point for investigators interested in the design of biology-based computer vision algorithms and pave a way for much needed interaction between the two communities leading to the development of synergistic models of artificial and biological vision

X-ray Phase-Contrast Tomography: Underlying Physics and Developments for Breast Imaging

X-ray phase-contrast tomography is a powerful tool to dramatically increase the visibility of features exhibiting a faint attenuation contrast within bulk samples, as is generally the case of light (low-Z) materials. For this reason, the application to clinical tasks aiming at imaging soft tissues, as e.g., breast imaging, has always been a driving force in the development of this field. In this context, the SYRMA-3D project, which constitutes the framework of the present work, aims to develop and implement the first breast computed tomography system relying on the propagation-based phase-contrast technique at the Elettra synchrotron facility (Trieste, Italy). This thesis finds itself in the \u2018last mile\u2019 towards the in-vivo implementation, and the obtained results add some of the missing pieces in the realization of the project. The first part of the work introduces a homogeneous mathematical framework describing propagation-based phase contrast from the sample-induced X-ray refraction, to detection, processing and tomographic reconstruction. The original results reported in the following chapters include the implementation of a pre-processing procedure dedicated for a novel photon-counting CdTe detector; a study, supported by a rigorous theoretical model, on signal and noise dependence on physical parameters such as propagation distance and detector pixel size; hardware and software developments for improving signal-to-noise ratio and reducing the scan time; and, finally, a clinically-oriented study based on comparisons with clinical mammographic and histological images. The last part of the thesis attempts to widen the experimental horizon: first, a quantitative image comparison of the synchrotron-based setup and a clinically available breast-CT scanner is presented and then a practical laboratory implementation is detailed, introducing a monochromatic propagation-based micro-tomography setup making use on a high-power rotating anode source

Real-time simulation and visualisation of cloth using edge-based adaptive meshes

Real-time rendering and the animation of realistic virtual environments and characters has progressed at a great pace, following advances in computer graphics hardware in the last decade. The role of cloth simulation is becoming ever more important in the quest to improve the realism of virtual environments. The real-time simulation of cloth and clothing is important for many applications such as virtual reality, crowd simulation, games and software for online clothes shopping. A large number of polygons are necessary to depict the highly exible nature of cloth with wrinkling and frequent changes in its curvature. In combination with the physical calculations which model the deformations, the effort required to simulate cloth in detail is very computationally expensive resulting in much diffculty for its realistic simulation at interactive frame rates. Real-time cloth simulations can lack quality and realism compared to their offline counterparts, since coarse meshes must often be employed for performance reasons. The focus of this thesis is to develop techniques to allow the real-time simulation of realistic cloth and clothing. Adaptive meshes have previously been developed to act as a bridge between low and high polygon meshes, aiming to adaptively exploit variations in the shape of the cloth. The mesh complexity is dynamically increased or refined to balance quality against computational cost during a simulation. A limitation of many approaches is they do not often consider the decimation or coarsening of previously refined areas, or otherwise are not fast enough for real-time applications. A novel edge-based adaptive mesh is developed for the fast incremental refinement and coarsening of a triangular mesh. A mass-spring network is integrated into the mesh permitting the real-time adaptive simulation of cloth, and techniques are developed for the simulation of clothing on an animated character

Exploração inteligente de objetos por manipulador robótico

The end goal of this dissertation is to develop an autonomous exploration robot that is capable of choosing the Next Best View which reveals the most amount of information about a given volume. The exploration solution is based on a robotic manipulator, a RGB-D sensor and ROS. The manipulator provides movement while the sensor evaluates the scene in its Field of View. Using an OcTree implementation to reconstruct the environment, the portions of the de ned exploration volume where no information has been gathered yet are segmented. This segmentation (or clustering) will help on the pose sampling operation in the sense that all generated poses are plausible. Ray casting is performed, either based on the sensor's resolution or the characteristics of the unknown scene, to assess the pose quality. The pose that is estimated to provide the evaluation of the highest amount of unknown space is the one chosen to be visited next, i.e., the Next Best View. The exploration reaches its end when all the unknown voxels have been evaluated or, those who were not, are not possible to be measured by any reachable pose. Two case studies are presented to test the performance and adaptability of this work. The developed system is able to explore a given scene which, initially, it has no information about. The solution provided is, not only, adaptable to changes in the environment during the exploration, but also, portable to other manipualtors rather than the one used in the development.O objetivo nal desta dissertação é desenvolver um robot de exploração autônomo capaz de escolher a Próxima Melhor Vista que revela a maior quantidade de informações sobre um determinado volume. A solução de exploração é baseada num manipulador robótico, num sensor RGB-D e em ROS. O manipulador proporciona movimento enquanto o sensor avalia a cena no seu campo de visão. Usando uma implementação Oc- Tree para reconstruir o ambiente, as partes do volume de exploração de nido onde nenhuma informação ainda foi recolhida são segmentadas. Esta segmenta ção (ou agrupamento) ajudará na operação de amostragem de poses no sentido em que todas as poses geradas são plausíveis. Ray casting é realizado, seja com base na resolução do sensor ou nas características da cena desconhecida, para avaliar a qualidade da pose. A pose que é estimado fornecer a avaliação da maior quantidade de espaço desconhecido é a escolhida para ser visitada em seguida, ou seja, a Próxima Melhor Vista. A exploração chega ao m quando todos os voxels desconhecidos tiverem sido avaliados ou, aqueles que não o foram, não sejam possíveis de serem medidos por qualquer pose alcançável. Dois casos de estudo são apresentados para testar o desempenho e adaptabilidade deste trabalho. O sistema desenvolvido é capaz de explorar uma determinada cena sobre a qual, inicialmente, não tem informação. A solução apresentada é, não só, adaptável às mudanças no ambiente durante a explora ção, mas também, portável para outros manipuladores que não o utilizado no desenvolvimento.Mestrado em Engenharia Mecânic

Textile Manufacturing Processes

Textile manufacturing is an important subject in textile programs and processing industries. The introduction of manmade and synthetic fibers, such as polyester, nylon, acrylic, cellulose, and Kevlar, among others, has greatly expanded the variety of textile products available today. In addition, new fiber development has brought about new machines for producing yarns, fabrics, and garments. Textile Manufacturing Processes is a collection of academic and research work in the field of textile manufacturing. Written by experts, chapters cover topics such as yarn manufacturing, fabric manufacturing, and garment and technical textiles. This book is useful for students, industry workers, and anyone interested in learning the fundamentals of textile manufacturing