During interventional radiology procedures, guide-wires are usually inserted into the patients vascular tree for diagnosis or healing purpose. These procedures are monitored with an Xray interventional system providing images of the interventional devices navigating through the patient's body. The automatic detection of such tools by image processing means has gained maturity over the past years and enables applications ranging from image enhancement to multimodal image fusion. Sophisticated detection methods are emerging, which rely on a variety of device enhancement techniques. In this article we reviewed and classified these techniques into three families. We chose a state of the art approach in each of them and built a rigorous framework to compare their detection capability and their computational complexity. Through simulations and the intensive use of ROC curves we demonstrated that the Hessian based methods are the most robust to strong curvature of the devices and that the family of rotated filters technique is the most suited for detecting low CNR and low curvature devices. The steerable filter approach demonstrated less interesting detection capabilities and appears to be the most expensive one to compute. Finally we demonstrated the interest of automatic guide-wire detection on a clinical topic: the compensation of respiratory motion in multimodal image fusion.

Date Published: 27 March 2009
PDF: 9 pages
Proc. SPIE 7259, Medical Imaging 2009: Image Processing, 72591M (27 March 2009); doi: 10.1117/12.812241

Published in SPIE Proceedings Vol. 7259:
Medical Imaging 2009: Image Processing
Josien P. W. Pluim; Benoit M. Dawant, Editor(s)