Probabilistic 4D blood flow mapping

Ola Friman*, Anja Hennemuth, Andreas Harloff, Jelena Bock, Michael Markl, Heinz Otto Peitgen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Blood flow and tissue velocity can be measured using phase-contrast MRI. In this work, the statistical properties of 4D phase-contrast images are derived, and a novel probabilistic blood flow mapping method based on sequential Monte Carlo sampling is presented. The resulting flow maps visualize and quantify the uncertainty in conventional flow visualization techniques such as streamlines and particle traces.

Original languageEnglish (US)
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings
Pages416-423
Number of pages8
EditionPART 3
DOIs
StatePublished - Nov 22 2010
Event13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010 - Beijing, China
Duration: Sep 20 2010Sep 24 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 3
Volume6363 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010
CountryChina
CityBeijing
Period9/20/109/24/10

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

Fingerprint Dive into the research topics of 'Probabilistic 4D blood flow mapping'. Together they form a unique fingerprint.

Cite this