Nowadays, hepatic artery catheterizations are performed under live 2D X-ray fluoroscopy guidance, where the visualization of blood vessels requires the injection of contrast agent. The projection of a 3D static roadmap of the complex branches of the liver artery system onto 2D fluoroscopy images can aid catheter navigation and minimize the use of contrast agent. However, the presence of a significant hepatic motion due to patient’s respiration necessitates a real-time motion correction in order to align the projected vessels. The objective of our work is to introduce dynamic roadmaps into clinical workflow for hepatic artery catheterizations and allow for continuous visualization of the vessels in 2D fluoroscopy images without additional contrast injection. To this end, we propose a method for real-time estimation of the apparent displacement of the hepatic arteries in 2D flouroscopy images. Our approach approximates respiratory motion of hepatic arteries from the catheter motion in 2D fluoroscopy images. The proposed method consists of two main steps. First, a filtering is applied to 2D fluoroscopy images in order to enhance the catheter and reduce the noise level. Then, a part of the catheter is tracked in the filtered images using template matching. A dynamic template update strategy makes our method robust to deformations. The accuracy and robustness of the algorithm are demonstrated by experimental studies on 22 simulated and 4 clinical sequences containing 330 and 571 image frames, respectively.
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Nowadays, hepatic artery catheterizations are performed under live 2D X-ray fluoroscopy guidance, where the visualization of blood vessels requires the injection of contrast agent. The projection of a 3D static roadmap of the complex branches of the liver artery system onto 2D fluoroscopy images can aid catheter navigation and minimize the use of contrast agent. However, the presence of a significant hepatic motion due to patient’s respiration necessitates a real-time motion correction in order...
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