TITLE

Estimating view parameters from random projections for Tomography using spherical MDS

AUTHOR(S)
Yi Fang; Murugappan, Sundar; Ramani, Karthik
PUB. DATE
January 2010
SOURCE
BMC Medical Imaging;2010, Vol. 10, p12
SOURCE TYPE
Academic Journal
DOC. TYPE
Article
ABSTRACT
Background: During the past decade, the computed tomography has been successfully applied to various fields especially in medicine. The estimation of view angles for projections is necessary in some special applications of tomography, for example, the structuring of viruses using electron microscopy and the compensation of the patient's motion over long scanning period. Methods: This work introduces a novel approach, based on the spherical multidimensional scaling (sMDS), which transforms the problem of the angle estimation to a sphere constrained embedding problem. The proposed approach views each projection as a high dimensional vector with dimensionality equal to the number of sampling points on the projection. By using SMDS, then each projection vector is embedded onto a 1D sphere which parameterizes the projection with respect to view angles in a globally consistent manner. The parameterized projections are used for the final reconstruction of the image through the inverse radon transform. The entire reconstruction process is noniterative and computationally efficient. Results: The effectiveness of the sMDS is verified with various experiments, including the evaluation of the reconstruction quality from different number of projections and resistance to different noise levels. The experimental results demonstrate the efficiency of the proposed method. Conclusion: Our study provides an effective technique for the solution of 2D tomography with unknown acquisition view angles. The proposed method will be extended to three dimensional reconstructions in our future work. All materials, including source code and demos, are available on https://engineering.purdue.edu/PRECISE/SMDS.
ACCESSION #
52843483

 

Related Articles

  • STRATEGIES OF SELECTING THE BASIS VECTOR SET IN THE RELATIVE MDS. Bernatavičienė, Jolita; Dzemyda, Gintautas; Kurasova, Olga; Marcinkevičius, Virginijus // Technological & Economic Development of Economy;2006, Vol. 12 Issue 4, p283 

    In this paper, a method of large multidimensional data visualization that associates the multidimensional scaling (MDS) with clustering is modified and investigated. In the original algorithm, the visualization process is divided into three steps: the basis vector set is constructed using the...

  • U.S.-developed nonmetric scaling gets practical use abroad: Brown.  // Marketing News;5/4/1979, Vol. 12 Issue 22, p8 

    Reports on the emerging popularity of the use of U.S. non-metric multidimensional scaling abroad as of 1979, according to research consultant Michael Brown. Difference between the location of the diffusion of innovation in the U.S. and Europe; Contribution of U.S. academics to the publication...

  • A Test of Holland's Environment Formulations. Rounds Jr., James B.; Shubsachs, Alexander P.W.; Dawis, René V.; Lofquist, Lloyd H. // Journal of Applied Psychology;Oct78, Vol. 63 Issue 5, p609 

    One hundred and eighty-one occupations, for which reinforcer rating data were available, were classified into the six Holland environment models. Mean reinforcer scale scores were found to differ significantly among the six environments on 17 reinforcer scales, on 12 of which there were...

  • ABSTRACT: PARTIAL ORDER SCALOGRAM ANALYSIS; A TECHNIQUE FOR SCALING QUALITATIVE DATA ON TWO DIMENSIONS. Merschrod, Kris // Quality & Quantity;Oct80, Vol. 14 Issue 5, p698 

    The article presents information on Partial Order Scalogram Analysis (POSA). POSA is one of several multidimensional scaling procedures designed for use with qualitative data. Unfortunately most studies which employ POSA present the results of the analysis in the absence of a discussion...

  • Psychometric properties of the Brief Symptoms Inventory-18 (BSI-18) in a Spanish sample of outpatients with psychiatric disorders. Andreu, Yolanda; Galdón, María José; Dura, Estrella; Ferrando, Maite; Murgui, Sergio; García, Amparo; Ibáñez, Elena // Psicothema;nov2008, Vol. 20 Issue 4, p844 

    This study analyzes the psychometric and structural properties of the BSI-18 in a sample of Spanish outpatients with psychiatric disorders (N= 200), with three basic objectives: (a) to study the structural validity of the instrument; (b) to analyse reliability (internal consistency and...

  • A Comparison of the Multidimensional Scaling of Triadic and Dyadic Distances. Gower, John C.; De Rooij, Mark // Journal of Classification;2004, Vol. 21 Issue 1, p115 

    We examine the use of triadic distances as a basis for multidimensional scaling (MDS). The MDS of triadic distances (MDS3) and a conventional MDS of dyadic distances (MDS2) both give Euclidean representations. Our analysis suggests that MDS2 and MDS3 can be expected to give very similar results,...

  • A NOTE ON ITEM INFORMATION IN ANY DIRECTION FOR THE MULTIDIMENSIONAL THREE-PARAMETER LOGISTIC MODEL. Bryant, Damon U. // Psychometrika;Mar2005, Vol. 70 Issue 1, p213 

    The purpose of this note is twofold: (a) to present the formula for the item information function (IIF) in any direction for the Multidimensional 3-Parameter Logistic (M3-PL) model and (b) to give the equation for the location of maximum item information (θmax) in the direction of the item...

  • Comparing Multiple Social Networks Using Mutiple Dimensional Scaling. Stevens, John // Methodological Innovations Online;2010, Vol. 5 Issue 1, p86 

    The article describes multi-dimensional scaling, an approach used to compare multiple social networks. Descriptive network statistics, triad census and network similarities are the methods and factors cited to compare only one feature of the given networks. Multi-dimensional scaling, a graphical...

  • "Just another pretty face": A multidimensional scaling approach to face attractiveness and variability. Timothy Potter; Olivier Corneille; Kirsten I. Ruys; Gillian Rhodes // Psychonomic Bulletin & Review;Apr2007, Vol. 14 Issue 2, p368 

    Findings on both attractiveness and memory for faces suggest that people should perceive more similarity among attractive than among unattractive faces. A multidimensional scaling approach was used to test this hypothesis in two studies. In Study 1, we derived a psychological face space from...

Share

Read the Article

Courtesy of NEW JERSEY STATE LIBRARY

Sorry, but this item is not currently available from your library.

Try another library?
Sign out of this library

Other Topics