28 research outputs found

    Balancing Fidelity and Performance in Iridal Light Transport Simulations Aimed at Interactive Applications

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    Specific light transport models based on first-principles approaches have been proposed for complex organic materials such as human skin and blood. The driving force behind these efforts has been the high-fidelity reproduction of material appearance attributes without one having to rely on the manipulation of ad hoc parameters. These models, however, are usually considered excessively time consuming for rendering applications requiring interactive rates. In this thesis, we address this open problem with respect to one of the most challenging of these organic materials, namely the human iris. More specifically, we present a framework that consists in the careful configuration of algorithms employed by a biophysically-based iridal light transport model on the CUDA (Compute Unified Device Architecture) parallel computing platform. We then investigate the sensitivity of iridal appearance attributes to key model running parameters, namely spectral resolution and number of sample rays, in order to obtain a practical balance between appearance fidelity and performance on this platform. The results of our investigation indicate that predictive light transport simulations can be effectively employed in the generation of iridal images that are not only believable, but also controlled by biophysically meaningful parameters. Although our investigation is centered at the human iris, we believe that it can be viewed as a proof of concept, and the proposed configuration strategies and parameter space explorations can be employed to obtain similar results for other organic materials

    Retinal vessel segmentation using textons

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    Segmenting vessels from retinal images, like segmentation in many other medical image domains, is a challenging task, as there is no unified way that can be adopted to extract the vessels accurately. However, it is the most critical stage in automatic assessment of various forms of diseases (e.g. Glaucoma, Age-related macular degeneration, diabetic retinopathy and cardiovascular diseases etc.). Our research aims to investigate retinal image segmentation approaches based on textons as they provide a compact description of texture that can be learnt from a training set. This thesis presents a brief review of those diseases and also includes their current situations, future trends and techniques used for their automatic diagnosis in routine clinical applications. The importance of retinal vessel segmentation is particularly emphasized in such applications. An extensive review of previous work on retinal vessel segmentation and salient texture analysis methods is presented. Five automatic retinal vessel segmentation methods are proposed in this thesis. The first method focuses on addressing the problem of removing pathological anomalies (Drusen, exudates) for retinal vessel segmentation, which have been identified by other researchers as a problem and a common source of error. The results show that the modified method shows some improvement compared to a previously published method. The second novel supervised segmentation method employs textons. We propose a new filter bank (MR11) that includes bar detectors for vascular feature extraction and other kernels to detect edges and photometric variations in the image. The k-means clustering algorithm is adopted for texton generation based on the vessel and non-vessel elements which are identified by ground truth. The third improved supervised method is developed based on the second one, in which textons are generated by k-means clustering and texton maps representing vessels are derived by back projecting pixel clusters onto hand labelled ground truth. A further step is implemented to ensure that the best combinations of textons are represented in the map and subsequently used to identify vessels in the test set. The experimental results on two benchmark datasets show that our proposed method performs well compared to other published work and the results of human experts. A further test of our system on an independent set of optical fundus images verified its consistent performance. The statistical analysis on experimental results also reveals that it is possible to train unified textons for retinal vessel segmentation. In the fourth method a novel scheme using Gabor filter bank for vessel feature extraction is proposed. The ii method is inspired by the human visual system. Machine learning is used to optimize the Gabor filter parameters. The experimental results demonstrate that our method significantly enhances the true positive rate while maintaining a level of specificity that is comparable with other approaches. Finally, we proposed a new unsupervised texton based retinal vessel segmentation method using derivative of SIFT and multi-scale Gabor filers. The lack of sufficient quantities of hand labelled ground truth and the high level of variability in ground truth labels amongst experts provides the motivation for this approach. The evaluation results reveal that our unsupervised segmentation method is comparable with the best other supervised methods and other best state of the art methods

    Multi-dimensional volume rendering for PC- based medical simulation

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    Ph.DDOCTOR OF PHILOSOPH

    3D statistical shape analysis of the face in Apert syndrome

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    Timely diagnosis of craniofacial syndromes as well as adequate timing and choice of surgical technique are essential for proper care management. Statistical shape models and machine learning approaches are playing an increasing role in Medicine and have proven its usefulness. Frameworks that automate processes have become more popular. The use of 2D photographs for automated syndromic identification has shown its potential with the Face2Gene application. Yet, using 3D shape information without texture has not been studied in such depth. Moreover, the use of these models to understand shape change during growth and its applicability for surgical outcome measurements have not been analysed at length. This thesis presents a framework using state-of-the-art machine learning and computer vision algorithms to explore possibilities for automated syndrome identification based on shape information only. The purpose of this was to enhance understanding of the natural development of the Apert syndromic face and its abnormality as compared to a normative group. An additional method was used to objectify changes as result of facial bipartition distraction, a common surgical correction technique, providing information on the successfulness and on inadequacies in terms of facial normalisation. Growth curves were constructed to further quantify facial abnormalities in Apert syndrome over time along with 3D shape models for intuitive visualisation of the shape variations. Post-operative models were built and compared with age-matched normative data to understand where normalisation is coming short. The findings in this thesis provide markers for future translational research and may accelerate the adoption of the next generation diagnostics and surgical planning tools to further supplement the clinical decision-making process and ultimately to improve patients’ quality of life

    PaRSys: Un nuevo modelo deformable interactivo basado en sistemas de partículas

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    En esta tesis se ha presentado un nuevo modelo deformable (ParSys) que, al igual que otros modelos deformables, permite, de forma simple, la incorporación de elasticidad a los modelos geométricos sintéticos 3D. Este modelo, basado en volúmenes ligados, se ha centrado principalmente en la velocidad por encima de la precisión, aunque no se ha dejado de lado el comportamiento realista basado en parámetros físicos reales. ParSys ha intentado unir las ventajas de cada uno de los modelos deformables existentes, presentando las siguientes características principales: Es un modelo rápido de calcular. Casi tan rápido como los modelos deformables heurísticos más simples basados en el punto muelle. Permite la realización de cambios topológicos de forma sencilla. Los parámetros que gobiernan la deformación pueden estar basados en parámetros físicos reales, en concreto en el módulo de Young, al igual que los modelos basados en mecánica continua. Posee un comportamiento volumétrico, lo que permite un mayor realismo visual ante las deformaciones producidas. Puede obtener el sistema de partículas encargado de la deformación sin necesidad de conocer la estructura interna de los objetos. Estas características invitan a pensar que ParSys es un modelo ideal para su uso en entornos virtuales interactivos y, en particular, en entornos tan complejos como la simulación quirúrgica.López Escobar, Ó. (2008). PaRSys: Un nuevo modelo deformable interactivo basado en sistemas de partículas [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/2007Palanci

    Ophthalmic Optics and Visual Function

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    Exploring quality of vision is one of the most important issues in modern ophthalmology, and research into ophthalmic optics and visual function is essential for making progress in this field. The present Special Issue aims to enlighten readers about the broad range of clinical research in the field of ophthalmic optics and visual function, mainly related to the anterior segment and myopia control. Submissions of original research articles were welcomed that highlight innovative findings with the potential to enhance the clinical capabilities of diagnosing and monitoring ophthalmic conditions and treatments especially of the anterior segment. Review articles of high interest were also considered for publication

    Distant Operational Care Centre: Design Project Report

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    The goal of this project is to outline the design of the Distant Operational Care Centre (DOCC), a modular medical facility to maintain human health and performance in space, that is adaptable to a range of remote human habitats. The purpose of this project is to outline a design, not to go into a complete technical specification of a medical facility for space. This project involves a process to produce a concise set of requirements, addressing the fundamental problems and issues regarding all aspects of a space medical facility for the future. The ideas presented here are at a high level, based on existing, researched, and hypothetical technologies. Given the long development times for space exploration, the outlined concepts from this project embodies a collection of identified problems, and corresponding proposed solutions and ideas, ready to contribute to future space exploration efforts. In order to provide a solid extrapolation and speculation in the context of the future of space medicine, the extent of this project's vision is roughly within the next two decades. The Distant Operational Care Centre (DOCC) is a modular medical facility for space. That is, its function is to maintain human health and performance in space environments, through prevention, diagnosis, and treatment. Furthermore, the DOCC must be adaptable to meet the environmental requirements of different remote human habitats, and support a high quality of human performance. To meet a diverse range of remote human habitats, the DOCC concentrates on a core medical capability that can then be adapted. Adaptation would make use of the DOCC's functional modularity, providing the ability to replace, add, and modify core functions of the DOCC by updating hardware, operations, and procedures. Some of the challenges to be addressed by this project include what constitutes the core medical capability in terms of hardware, operations, and procedures, and how DOCC can be adapted to different remote habitats

    Biomedical Engineering

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    Biomedical engineering is currently relatively wide scientific area which has been constantly bringing innovations with an objective to support and improve all areas of medicine such as therapy, diagnostics and rehabilitation. It holds a strong position also in natural and biological sciences. In the terms of application, biomedical engineering is present at almost all technical universities where some of them are targeted for the research and development in this area. The presented book brings chosen outputs and results of research and development tasks, often supported by important world or European framework programs or grant agencies. The knowledge and findings from the area of biomaterials, bioelectronics, bioinformatics, biomedical devices and tools or computer support in the processes of diagnostics and therapy are defined in a way that they bring both basic information to a reader and also specific outputs with a possible further use in research and development

    Aerospace Medicine and Biology: 1983 cumulative index

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    This publication is a cumulative index to the abstracts contained in the Supplements 242 through 253 of Aerospace Medicine and Biology: A Continuing Bibliography. It includes six indexes--subject, personal author, corporate source, contract number, report number, and accession number

    PRELIMINARY FINDINGS OF A POTENZIATED PIEZOSURGERGICAL DEVICE AT THE RABBIT SKULL

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    The number of available ultrasonic osteotomes has remarkably increased. In vitro and in vivo studies have revealed differences between conventional osteotomes, such as rotating or sawing devices, and ultrasound-supported osteotomes (Piezosurgery®) regarding the micromorphology and roughness values of osteotomized bone surfaces. Objective: the present study compares the micro-morphologies and roughness values of osteotomized bone surfaces after the application of rotating and sawing devices, Piezosurgery Medical® and Piezosurgery Medical New Generation Powerful Handpiece. Methods: Fresh, standard-sized bony samples were taken from a rabbit skull using the following osteotomes: rotating and sawing devices, Piezosurgery Medical® and a Piezosurgery Medical New Generation Powerful Handpiece. The required duration of time for each osteotomy was recorded. Micromorphologies and roughness values to characterize the bone surfaces following the different osteotomy methods were described. The prepared surfaces were examined via light microscopy, environmental surface electron microscopy (ESEM), transmission electron microscopy (TEM), confocal laser scanning microscopy (CLSM) and atomic force microscopy. The selective cutting of mineralized tissues while preserving adjacent soft tissue (dura mater and nervous tissue) was studied. Bone necrosis of the osteotomy sites and the vitality of the osteocytes near the sectional plane were investigated, as well as the proportion of apoptosis or cell degeneration. Results and Conclusions: The potential positive effects on bone healing and reossification associated with different devices were evaluated and the comparative analysis among the different devices used was performed, in order to determine the best osteotomes to be employed during cranio-facial surgery
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