Deriving anatomical context from 4D ultrasound

M. Müller, L. E.S. Helljesen, R. Prevost, I. Viola, K. Nylund, O. H. Gilja, N. Navab, W. Wein

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

Real-time three-dimensional (also known as 4D) ultrasound imaging using matrix array probes has the potential to create large-volume information of entire organs such as the liver without external tracking hardware. This information can in turn be placed into the context of a CT or MRI scan of the same patient. However for such an approach many image processing challenges need to be overcome and sources of error addressed, including reconstruction drift, anatomical deformations, varying appearance of anatomy, and imaging artifacts. In this work, we present a fully automatic system including robust image-based ultrasound tracking, a novel learning-based global initialization of the anatomical context, and joint mono- and multi-modal registration. In an evaluation on 4D US sequences and MRI scans of eight volunteers we achieve automatic reconstruction and registration without any user interaction, assess the registration errors based on physician-defined landmarks, and demonstrate real-time tracking of free-breathing sequences.

Original languageEnglish (US)
Title of host publicationEurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2014
EditorsIvan Viola, Katja Buhler, Timo Ropinski
PublisherEurographics Association
Pages173-180
Number of pages8
ISBN (Electronic)9783905674620
DOIs
StatePublished - 2014
Event2014 Eurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2014 - Vienna, Austria
Duration: Sep 4 2014Sep 5 2014

Publication series

NameEurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2014

Conference

Conference2014 Eurographics Workshop on Visual Computing for Biology and Medicine, VCBM 2014
Country/TerritoryAustria
CityVienna
Period09/4/1409/5/14

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Biomedical Engineering

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