Literature DB >> 22034334

Interactive virtual probing of 4D MRI blood-flow.

Roy van Pelt1, Javier Oliván Bescós, Marcel Breeuwer, Rachel E Clough, M Eduard Gröller, Bart ter Haar Romenij, Anna Vilanova.   

Abstract

Better understanding of hemodynamics conceivably leads to improved diagnosis and prognosis of cardiovascular diseases. Therefore, an elaborate analysis of the blood-flow in heart and thoracic arteries is essential. Contemporary MRI techniques enable acquisition of quantitative time-resolved flow information, resulting in 4D velocity fields that capture the blood-flow behavior. Visual exploration of these fields provides comprehensive insight into the unsteady blood-flow behavior, and precedes a quantitative analysis of additional blood-flow parameters. The complete inspection requires accurate segmentation of anatomical structures, encompassing a time-consuming and hard-to-automate process, especially for malformed morphologies. We present a way to avoid the laborious segmentation process in case of qualitative inspection, by introducing an interactive virtual probe. This probe is positioned semi-automatically within the blood-flow field, and serves as a navigational object for visual exploration. The difficult task of determining position and orientation along the view-direction is automated by a fitting approach, aligning the probe with the orientations of the velocity field. The aligned probe provides an interactive seeding basis for various flow visualization approaches. We demonstrate illustration-inspired particles, integral lines and integral surfaces, conveying distinct characteristics of the unsteady blood-flow. Lastly, we present the results of an evaluation with domain experts, valuing the practical use of our probe and flow visualization techniques.
© 2011 IEEE

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Year:  2011        PMID: 22034334     DOI: 10.1109/TVCG.2011.215

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


  3 in total

1.  Automatic measurement plane placement for 4D Flow MRI of the great vessels using deep learning.

Authors:  Philip A Corrado; Daniel P Seiter; Oliver Wieben
Journal:  Int J Comput Assist Radiol Surg       Date:  2021-08-17       Impact factor: 2.924

2.  Uncertainty Footprint: Visualization of Nonuniform Behavior of Iterative Algorithms Applied to 4D Cell Tracking.

Authors:  Y Wan; C Hansen
Journal:  Comput Graph Forum       Date:  2017-07-04       Impact factor: 2.078

3.  Atlas-based analysis of 4D flow CMR: automated vessel segmentation and flow quantification.

Authors:  Mariana Bustamante; Sven Petersson; Jonatan Eriksson; Urban Alehagen; Petter Dyverfeldt; Carl-Johan Carlhäll; Tino Ebbers
Journal:  J Cardiovasc Magn Reson       Date:  2015-10-05       Impact factor: 5.364

  3 in total

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