3D catheter tip tracking in 2D X-ray image sequences using a hidden Markov model and 3D rotational angiography

Pierre Ambrosini, Ihor Smal, Daniel Ruijters, Wiro J. Niessen, Adriaan Moelker, Theo van Walsum

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

4 Citations (Scopus)

Abstract

Integration of pre-or peri-operative images may improve image guidance in minimally invasive interventions. In abdominal catheterization procedures such as transcatheter arterial chemoembolization, 3D pre-/peri-operative images contain relevant information, such as complete 3D vasculature, that is not directly available from 2D imaging. Accurate knowledge of the catheter tip position in 3D is currently not available, and after registration of 3D information to 2D images (angiographies), the registration is invalidated by breathing motion and thus requires continuous updates. We propose a hidden Markov model based method to track the 3D catheter position, using 2D fluoroscopic image sequences and a 3D vessel tree obtained from 3D Rotational Angiography. Such a tracking facilitates display of the catheter in the 3D anatomy, and it enables to use the 3D vessels as a roadmap in 2D imaging. The tracking is initialized with the first 2D image of the sequence. For the subsequent images, based on a state transition probability distribution and the registration observations, the catheter tip position is tracked in the 3D vessel tree using registrations to the 2D fluoroscopic images. The method is evaluated on simulated data and two clinical sequences. In the simulations, we obtain a median tip position accuracies up to 2.9 mm. On clinical sequence, the distance between the catheter and the projected vessels after registration is below 1.9 mm.

Original languageEnglish
Title of host publicationAugmented Environments for Computer-Assisted Interventions
Subtitle of host publication10th International Workshop, AE-CAI 2015 Held in Conjunction with MICCAI 2015, Proceedings
EditorsCristian A. Linte, Ziv Yaniv, Pascal Fallavollita
Place of PublicationCham
PublisherSpringer
Chapter5
Pages38-49
Number of pages12
ISBN (Electronic)978-3-319-24601-7
ISBN (Print)978-3-319-24600-0
DOIs
Publication statusPublished - 2015
Externally publishedYes
Event10th International Workshop on Augmented Environments for Computer-Assisted Interventions, AE-CAI 2015 and Held in Conjunction with, MICCAI 2015 - Munich, Germany
Duration: 9 Oct 20159 Oct 2015

Publication series

NameLecture Notes in Computer Science (LNCS)
Volume9365
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349
NameImage Processing, Computer Vision, Pattern Recognition, and Graphics (LNIP)
Volume9365

Workshop

Workshop10th International Workshop on Augmented Environments for Computer-Assisted Interventions, AE-CAI 2015 and Held in Conjunction with, MICCAI 2015
Country/TerritoryGermany
CityMunich
Period9/10/159/10/15

Funding

This research is funded by Philips Healthcare, Best, The Netherlands.

Keywords

  • 3DRA
  • Abdominal
  • Breathing
  • Catheter
  • Fluoroscopy
  • Guidance
  • Hidden markov model
  • Liver
  • Registration
  • Rigid
  • TACE
  • Tip
  • Tracking
  • X-ray

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