1,720,969 research outputs found
Novel algorithms in X-ray computed tomography imaging from under-sampled data
Full text linkThis thesis presents novel algorithms in X-ray computed tomography imaging using limited or sparse data:
I. A non-uniform rational basis splines (NURBS) curve is used to represent the boundary of a target. Markov chain Monte Carlo (MCMC) strategy is applied for estimating the unknown curve from the projection data and an attenuation value of the target. In this case, the target is assumed to be homogeneous (it contains only one material).
Instead of a single output, the solution of MCMC as a Bayesian framework is a posterior distribution. In addition, the results of the method are conveniently in CAD-compatible format.
II. Adaptive methods for choosing regularization parameter are proposed. The first approach is called the controlled wavelet domain sparsity (CWDS). This is based on enforcing sparsity in the two-dimensional wavelet transform domain, and the second so-called the controlled shearlet domain sparsity (CSDS) in the three-dimensional shearlet transform domain. The proposed methods offer a strategy to automatically choosing regularization parameter where the end-users could avoid manually tuning the parameters. A known {\it a priori} sparsity level calculated from some available objects/samples is required.
Both algorithms above have been successfully implemented for real measured X-ray data and the results using under-sampled data outperform the baseline method. The proposed methods incur heavy computation costs, however implementing parallelization strategy could save the computation time.Tiivistelmä
Tässä väitöskirjassa esitetään uusia algoritmeja röntgenkuvaukseen perustuvaan tietokonetomografiaan käyttäen harvan ja rajoitetun kulman mittausdataa. Erityisesti työssä esitetään seuraavat lähestymistavat:
I. Ensimmäinen lähestymistapa perustuu NURBS (engl., non-uniform rational basis splines) –mallin käyttöön. NURBS on matemaattinen malli, jota käytetään kuvattavan kohteen reunojen esittämiseen. Soveltamalla tätä yhdessä Markovin ketju Monte Carlo –strategian (MCMC) kanssa voidaan estimoida reunan käyrä, sekä kohteen vaimenemista kuvaava arvo. Tässä lähestymistavassa kohde oletetaan homogeeniseksi eli sen oletetaan sisältävän vain yhtä ainetta. Käyttäen MCMC-mentelmää saadaan estimoitaville parametreille tilastollinen a posteriori -jakauma.
II. Toinen lähestymistapa perustuu adaptiiviseen regularisointiparametrin valitsemiseen. Tätä varten kehitettiin kaksi strategiaa. Ensimmäinen näistä perustuu harvuuden vahvistamiseen ja kontrolloimiseen kaksiulotteisessa aallokemuunoksessa. Toinen taas perustuu harvuuden kontrolloimiseen nk. komiulotteisessa shearlet-sivuttaissiirtymämuunnoksessa. Molemmat menetelmät mahdollistavat regularisointiparametrin automaattisen valitsemisen ilman että loppukäyttäjän tarvitsee itse siihen puuttua. Ennakkotieto kuvattavan objektin harvuuden tasosta kuitenkin vaaditaan.
Tässä väitöskirjassa molempia lähestymistapoja testattiin käytännössä käyttäen oikeaa mitattua röntgendataa. Molemmissa lähestymistavoissa uudet algoritmit toimivat paremmin kuin perinteiset vertailumenetelmät. Uudet algoritmit ovat kuitenkin laskennallisesti erittäin raskaita. Tulevaisuudessa suurteholaskennan keinoilla niihin käytettyä laskenta-aikaa voitaneen kuitenkin pienentää.ei saavutettav
Reconstruction of X-ray Tomography for Incomplete Projection Data Using Machine Learning
No full text
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
CT Data of a Pen-Spring: Application to Under-Sampled Dynamic X-ray Tomography
No full textThis is the documentation of Computed Tomography (CT) data of a pen-spring. It can be freely used for scientific purposes with appropriate references to the data and to this document in http://arxiv.org/. The provided data set includes the X-ray sinograms finalSino of a single 2D slice from a different height of the spring. The finalSino was obtained from a measured 10-projection or 100-projection sinogram using fan-beam geometry
by down-sampling and taking logarithms. The data set includes also those original measured sinograms and corresponding measurement matrices.</p
Tomographic X-ray data of 3D emoji
No full text<p>This is the documentation of the tomographic X-ray data of emoji<br>
phantom made available at http://www.fips.fi/dataset.php. The data can be freely used for scienti c purposes with appropriate references to the data and to this document in http://arxiv.org/. The data set consists of (1) the X-ray sinogram of a single 2D slice of 33 emoji faces (contains 15 different emoji faces) made by small squared ceramic stones and (2) the corresponding static and dynamic measurement matrices modeling the linear operation of the X-ray transform. Each of these sinograms was obtained from a measured 60-projection fan-beam sinogram by down-sampling and taking logarithms. The original (measured) sinogram is also provided in its original form and resolution. The original (measured) sinogram is also provided in its original form and resolution.</p>This work was supported by the Academy of Finland through
the Finnish Centre of Excellence in Inverse Problems Research
2012–2017 (Academy of Finland CoE-project 284715)
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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