994 resultados para stereo correspondence estimation


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We investigate the problem of obtaining a dense reconstruction in real-time, from a live video stream. In recent years, multi-view stereo (MVS) has received considerable attention and a number of methods have been proposed. However, most methods operate under the assumption of a relatively sparse set of still images as input and unlimited computation time. Video based MVS has received less attention despite the fact that video sequences offer significant benefits in terms of usability of MVS systems. In this paper we propose a novel video based MVS algorithm that is suitable for real-time, interactive 3d modeling with a hand-held camera. The key idea is a per-pixel, probabilistic depth estimation scheme that updates posterior depth distributions with every new frame. The current implementation is capable of updating 15 million distributions/s. We evaluate the proposed method against the state-of-the-art real-time MVS method and show improvement in terms of accuracy. © 2011 Elsevier B.V. All rights reserved.

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Cardiotocography provides significant information on foetal oxygenation linked to characteristics of foetal heart rate signals. Among most important we can mention foetal heart rate variability, whose spectral analysis is recognised like useful in improving diagnosis of pathologic conditions. However, despite its importance, a standardisation of definition and estimation of foetal heart rate variability is still searched. Some guidelines state that variability refers to fluctuations in the baseline free from accelerations and decelerations. This is an important limit in clinical routine since variability in correspondence of these FHR alterations has always been regarded as particularly significant in terms of prognostic value. In this work we compute foetal heart rate variability as difference between foetal heart rate and floatingline and we propose a method for extraction of floatingline which takes into account accelerations and decelerations. © 2011 Springer-Verlag Berlin Heidelberg.

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X-ray computed tomography (CT) is a non-invasive medical imaging technique that generates cross-sectional images by acquiring attenuation-based projection measurements at multiple angles. Since its first introduction in the 1970s, substantial technical improvements have led to the expanding use of CT in clinical examinations. CT has become an indispensable imaging modality for the diagnosis of a wide array of diseases in both pediatric and adult populations [1, 2]. Currently, approximately 272 million CT examinations are performed annually worldwide, with nearly 85 million of these in the United States alone [3]. Although this trend has decelerated in recent years, CT usage is still expected to increase mainly due to advanced technologies such as multi-energy [4], photon counting [5], and cone-beam CT [6].

Despite the significant clinical benefits, concerns have been raised regarding the population-based radiation dose associated with CT examinations [7]. From 1980 to 2006, the effective dose from medical diagnostic procedures rose six-fold, with CT contributing to almost half of the total dose from medical exposure [8]. For each patient, the risk associated with a single CT examination is likely to be minimal. However, the relatively large population-based radiation level has led to enormous efforts among the community to manage and optimize the CT dose.

As promoted by the international campaigns Image Gently and Image Wisely, exposure to CT radiation should be appropriate and safe [9, 10]. It is thus a responsibility to optimize the amount of radiation dose for CT examinations. The key for dose optimization is to determine the minimum amount of radiation dose that achieves the targeted image quality [11]. Based on such principle, dose optimization would significantly benefit from effective metrics to characterize radiation dose and image quality for a CT exam. Moreover, if accurate predictions of the radiation dose and image quality were possible before the initiation of the exam, it would be feasible to personalize it by adjusting the scanning parameters to achieve a desired level of image quality. The purpose of this thesis is to design and validate models to quantify patient-specific radiation dose prospectively and task-based image quality. The dual aim of the study is to implement the theoretical models into clinical practice by developing an organ-based dose monitoring system and an image-based noise addition software for protocol optimization.

More specifically, Chapter 3 aims to develop an organ dose-prediction method for CT examinations of the body under constant tube current condition. The study effectively modeled the anatomical diversity and complexity using a large number of patient models with representative age, size, and gender distribution. The dependence of organ dose coefficients on patient size and scanner models was further evaluated. Distinct from prior work, these studies use the largest number of patient models to date with representative age, weight percentile, and body mass index (BMI) range.

With effective quantification of organ dose under constant tube current condition, Chapter 4 aims to extend the organ dose prediction system to tube current modulated (TCM) CT examinations. The prediction, applied to chest and abdominopelvic exams, was achieved by combining a convolution-based estimation technique that quantifies the radiation field, a TCM scheme that emulates modulation profiles from major CT vendors, and a library of computational phantoms with representative sizes, ages, and genders. The prospective quantification model is validated by comparing the predicted organ dose with the dose estimated based on Monte Carlo simulations with TCM function explicitly modeled.

Chapter 5 aims to implement the organ dose-estimation framework in clinical practice to develop an organ dose-monitoring program based on a commercial software (Dose Watch, GE Healthcare, Waukesha, WI). In the first phase of the study we focused on body CT examinations, and so the patient’s major body landmark information was extracted from the patient scout image in order to match clinical patients against a computational phantom in the library. The organ dose coefficients were estimated based on CT protocol and patient size as reported in Chapter 3. The exam CTDIvol, DLP, and TCM profiles were extracted and used to quantify the radiation field using the convolution technique proposed in Chapter 4.

With effective methods to predict and monitor organ dose, Chapters 6 aims to develop and validate improved measurement techniques for image quality assessment. Chapter 6 outlines the method that was developed to assess and predict quantum noise in clinical body CT images. Compared with previous phantom-based studies, this study accurately assessed the quantum noise in clinical images and further validated the correspondence between phantom-based measurements and the expected clinical image quality as a function of patient size and scanner attributes.

Chapter 7 aims to develop a practical strategy to generate hybrid CT images and assess the impact of dose reduction on diagnostic confidence for the diagnosis of acute pancreatitis. The general strategy is (1) to simulate synthetic CT images at multiple reduced-dose levels from clinical datasets using an image-based noise addition technique; (2) to develop quantitative and observer-based methods to validate the realism of simulated low-dose images; (3) to perform multi-reader observer studies on the low-dose image series to assess the impact of dose reduction on the diagnostic confidence for multiple diagnostic tasks; and (4) to determine the dose operating point for clinical CT examinations based on the minimum diagnostic performance to achieve protocol optimization.

Chapter 8 concludes the thesis with a summary of accomplished work and a discussion about future research.

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The aim of this report is to provide biomass estimates (AFDW, g.m-2 ) of the four main components of the benthic food web in the southern part of the Bay of St-Brieuc: suspension-feeders, deposit-feeders, herbivores and carnivores. Patterns in the environmental data (i.e., sedimentary characters) are first analysed, and then related to the spatial distribution of communities ; both approaches use classical ordination techniques (PCA, correspondence analysis). A second typology, based on a review of published litterature concerning coastal macrozoobenthos feeding, ascribes each taxonomic unit to a trophic group. Finally, quantitative results are thus given per biota ; suspension-feeders appear to dominate (in terms of biomass) most of fine-sand habitats of the studied area.

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In this thesis, we propose several advances in the numerical and computational algorithms that are used to determine tomographic estimates of physical parameters in the solar corona. We focus on methods for both global dynamic estimation of the coronal electron density and estimation of local transient phenomena, such as coronal mass ejections, from empirical observations acquired by instruments onboard the STEREO spacecraft. We present a first look at tomographic reconstructions of the solar corona from multiple points-of-view, which motivates the developments in this thesis. In particular, we propose a method for linear equality constrained state estimation that leads toward more physical global dynamic solar tomography estimates. We also present a formulation of the local static estimation problem, i.e., the tomographic estimation of local events and structures like coronal mass ejections, that couples the tomographic imaging problem to a phase field based level set method. This formulation will render feasible the 3D tomography of coronal mass ejections from limited observations. Finally, we develop a scalable algorithm for ray tracing dense meshes, which allows efficient computation of many of the tomographic projection matrices needed for the applications in this thesis.

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Purpose: The main purpose of the study is to promote consideration of the issues and approaches available for costing sustainable buildings with a view to minimising cost overruns, occasioned by conservative whole-life cost estimates. The paper primarily looks at the impact of adopting continuity in whole-life cost models for zero carbon houses. Design/methodology/approach: The study embraces a mathematically based risk procedure based on the binomial theorem for analysing the cost implication of the Lighthouse zero-carbon house project. A practical application of the continuous whole-life cost model is developed and results are compared with existing whole-life cost techniques using finite element methods and Monte Carlo analysis. Findings: With standard whole-life costing, discounted present-value analysis tends to underestimate the cost of a project. Adopting continuity in whole-life cost models presents a clearer picture and profile of the economic realities and decision-choices confronting clients and policy-makers. It also expands the informative scope on the costs of zero-carbon housing projects. Research limitations/implications: A primary limitation in this work is its focus on just one property type as the unit of analysis. This research is also limited in its consideration of initial and running cost categories only. The capital cost figures for the Lighthouse are indicative rather than definitive. Practical implications: The continuous whole-life cost technique is a novel and innovative approach in financial appraisal [...] Benefits of an improved costing framework will be far-reaching in establishing effective policies aimed at client acceptance and optimally performing supply chain networks. Originality/value: The continuous whole-life costing pioneers an experimental departure from the stereo-typical discounting mechanism in standard whole-life costing procedures.

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