Repository logo
  • Log In
    Log in via Symplectic to deposit your publication(s).
Repository logo
  • Communities & Collections
  • Research Outputs
  • Statistics
  • Log In
    Log in via Symplectic to deposit your publication(s).
  1. Home
  2. Faculty of Engineering
  3. Computing
  4. Computing PhD theses
  5. Fast catheter segmentation and tracking based on x-ray fluoroscopic and echocardiographic modalities for catheter-based cardiac minimally invasive interventions
 
  • Details
Fast catheter segmentation and tracking based on x-ray fluoroscopic and echocardiographic modalities for catheter-based cardiac minimally invasive interventions
File(s)
Wu-X-2015-PhD-Thesis.pdf (10.05 MB)
Thesis
Author(s)
Wu, Xianliang
Type
Thesis or dissertation
Abstract
X-ray fluoroscopy and echocardiography imaging (ultrasound, US) are two imaging modalities that are widely used in cardiac catheterization. For these modalities, a fast, accurate and stable algorithm for the detection and tracking of catheters is required to allow clinicians to observe the catheter location in real-time. Currently X-ray fluoroscopy is routinely used as the standard modality in catheter ablation interventions. However, it lacks the ability to visualize soft tissue and uses harmful radiation. US does not have these limitations but often contains acoustic artifacts and has a small field of view. These make the detection and tracking of the catheter in US very challenging.



The first contribution in this thesis is a framework which combines Kalman filter and discrete optimization for multiple catheter segmentation and tracking in X-ray images. Kalman filter is used to identify the whole catheter from a single point detected on the catheter in the first frame of a sequence of x-ray images. An energy-based formulation is developed that can be used to track the catheters in the following frames. We also propose a discrete optimization for minimizing the energy function in each frame of the X-ray image sequence. Our approach is robust to tangential motion of the catheter and combines the tubular and salient feature measurements into a single robust and efficient framework.

The second contribution is an algorithm for catheter extraction in 3D ultrasound images based on (a) the registration between the X-ray and ultrasound images and (b) the segmentation of the catheter in X-ray images. The search space for the catheter extraction in the ultrasound images is constrained to lie on or close to a curved surface in the ultrasound volume. The curved surface corresponds to the back-projection of the extracted catheter from the X-ray image to the ultrasound volume. Blob-like features are detected in the US images and organized in a graphical model. The extracted catheter is modelled as the optimal path in this graphical model.

Both contributions allow the use of ultrasound imaging for the improved visualization of soft tissue. However, X-ray imaging is still required for each ultrasound frame and the amount of X-ray exposure has not been reduced. The final contribution in this thesis is a system that can track the catheter in ultrasound volumes automatically without the need for X-ray imaging during the tracking. Instead X-ray imaging is only required for the system initialization and for recovery from tracking failures. This allows a significant reduction in the amount of X-ray exposure for patient and clinicians.
Version
Open Access
Date Issued
2015-01
Date Awarded
2015-06
URI
http://hdl.handle.net/10044/1/46168
DOI
https://doi.org/10.25560/46168
Advisor
Rueckert, Daniel
Sponsor
China Scholarship Council
Publisher Department
Computing
Publisher Institution
Imperial College London
Qualification Level
Doctoral
Qualification Name
Doctor of Philosophy (PhD)
About
Spiral Depositing with Spiral Publishing with Spiral Symplectic
Contact us
Open access team Report an issue
Other Services
Scholarly Communications Library Services
logo

Imperial College London

South Kensington Campus

London SW7 2AZ, UK

tel: +44 (0)20 7589 5111

Accessibility Modern slavery statement Cookie Policy

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Cookie settings
  • Privacy policy
  • End User Agreement
  • Send Feedback