Literature DB >> 23559505

Visual analysis of cardiac 4D MRI blood flow using line predicates.

Silvia Born1, Matthias Pfeifle, Michael Markl, Matthias Gutberlet, Gerik Scheuermann.   

Abstract

Four-dimensional MRI is an in vivo flow imaging modality that is expected to significantly enhance the understanding of cardiovascular diseases. Among other fields, 4D MRI provides valuable data for the research of cardiac blood flow and with that the development, diagnosis, and treatment of various cardiac pathologies. However, to gain insights from larger research studies or to apply 4D MRI in the clinical routine later on, analysis techniques become necessary that allow to robustly identify important flow characteristics without demanding too much time and expert knowledge. Heart muscle contractions and the particular complexity of the flow in the heart imply further challenges when analyzing cardiac blood flow. Working toward the goal of simplifying the analysis of 4D MRI heart data, we present a visual analysis method using line predicates. With line predicates precalculated integral lines are sorted into bundles with similar flow properties, such as velocity, vorticity, or flow paths. The user can combine the line predicates flexibly and by that carve out interesting flow features helping to gain overview. We applied our analysis technique to 4D MRI data of healthy and pathological hearts and present several flow aspects that could not be shown with current methods. Three 4D MRI experts gave feedback and confirmed the additional benefit of our method for their understanding of cardiac blood flow.

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Year:  2013        PMID: 23559505     DOI: 10.1109/TVCG.2012.318

Source DB:  PubMed          Journal:  IEEE Trans Vis Comput Graph        ISSN: 1077-2626            Impact factor:   4.579


  4 in total

1.  [Cardiac magnetic resonance imaging: from imaging to diagnosis].

Authors:  M Gutberlet
Journal:  Radiologe       Date:  2013-11       Impact factor: 0.635

2.  Motion-aware stroke volume quantification in 4D PC-MRI data of the human aorta.

Authors:  Benjamin Köhler; Uta Preim; Matthias Grothoff; Matthias Gutberlet; Katharina Fischbach; Bernhard Preim
Journal:  Int J Comput Assist Radiol Surg       Date:  2015-07-17       Impact factor: 2.924

Review 3.  Lagrangian postprocessing of computational hemodynamics.

Authors:  Shawn C Shadden; Amirhossein Arzani
Journal:  Ann Biomed Eng       Date:  2014-07-25       Impact factor: 3.934

4.  Quantitative Analysis of Vortical Blood Flow in the Thoracic Aorta Using 4D Phase Contrast MRI.

Authors:  Jochen von Spiczak; Gerard Crelier; Daniel Giese; Sebastian Kozerke; David Maintz; Alexander Christian Bunck
Journal:  PLoS One       Date:  2015-09-29       Impact factor: 3.240

  4 in total

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