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An Algorithm for Tracking Microcatheters in Fluoroscopy
Authors:Akihiro Takemura  Kenneth R Hoffmann  Masayuki Suzuki  Zhou Wang  Hussain S Rangwala  Hajime Harauchi  Stephen Rudin  Tokuo Umeda
Institution:(1) School of Health Sciences, Faculty of Medicine, Kanazawa University, 5-11-80 Kodatsuno, Kanazawa 920-0942, Japan;(2) Toshiba Stroke Research Center, University at Buffalo (SUNY), 3435 Main St., Buffalo, NY 14214, USA;(3) Roswell Park Cancer Institute, Elm & Carlton St., Buffalo, NY 14263, USA;(4) Department of Radiological Technology, Kawasaki College of Allied Health Professions, 316 Matsushima, Kurashiki, Okayama 701-0194, Japan;(5) School of Allied Health Sciences, Kitasato University, 1-15-1 Kitasato, Sagamihara Kanagawa, 228-8555, Japan
Abstract:Currently, a large number of endovascular interventions are performed for treatment of intracranial aneurysms. For these treatments, correct positioning of microcatheter tips, microguide wire tips, or coils is essential. Techniques to detect such devices may facilitate endovascular interventions. In this paper, we describe an algorithm for tracking of microcatheter tips during fluoroscopically guided neuroendovascular interventions. A sequence of fluoroscopic images (1,024 × 1,024 × 12 bits) was acquired using a C-arm angiography system as a microcatheter was passed through a carotid phantom which was on top of a head phantom. The carotid phantom was a silicone cylinder containing a simulated vessel with the shape and curvatures of the internal carotid artery. The head phantom consisted of a human skull and tissue-equivalent material. To detect the microcatheter in a given fluoroscopic frame, a background image consisting of an average of the four previous frames is subtracted from the current frame, the resulting image is filtered using a matched filter, and the position of maximum intensity in the filtered image is taken as the catheter tip position in the current frame. The distance between the tracked position and the correct position (error distance) was measured in each of the fluoroscopic images. The mean and standard deviation of the error distance values were 0.277 mm (1.59 pixels) and 0.26 mm (1.5 pixels), respectively. The error distance was less than 3 pixels in the 93.0% frames. Although the algorithm intermittently failed to correctly detect the catheter, the algorithm recovered the catheter in subsequent frames.
Keywords:Catheter motion tracking  vascular intervention  fluorography  cerebral artery  image subtraction  microcatheter  navigation system
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