title: Robust and fast contrast inflow detection for 2D X-ray fluoroscopy.
abstract: 2D X-ray fluoroscopy is widely used in computer assisted and image guided interventions because of the real time visual guidance it can provide to the physicians. During cardiac interventions, acquisitions of angiography are often used to assist the physician in visualizing the blood vessel structures, guide wires, or catheters, localizing bifurcations, estimating severity of a lesion, or observing the blood flow. Computational algorithms often need to process differently to frames with or without contrast medium. In order to automate this process and streamline the clinical workflow, a fully automatic contrast inflow detection algorithm is proposed. The robustness of the algorithm is validated by more than 1300 real fluoroscopic scenes. The algorithm is computationally efficient; a sequence with 100 frames can be processed within a second.
authors: Siemens Corporation, Corporate Research, 755 College Road East, Princeton, NJ, USA.
authors: Terrence
authors: T
authors: Chen
authors: Gareth
authors: G
authors: Funka-Lea
authors: Dorin
authors: D
authors: Comaniciu
mesh_terms: D000465:Algorithms; D000792:Angiography / Q000379:methods; D001185:Artificial Intelligence; D001808:Blood Vessels / Q000473:pathology; D002404:Catheterization; D003198:Computer Simulation; D003199:Computer Systems; D003287:Contrast Media / Q000494:pharmacology; D005471:Fluoroscopy / Q000295:instrumentation* / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008962:Models, Theoretical; D015203:Reproducibility of Results; D012984:Software; D014965:X-Rays
chemical_list: D003287:Contrast Media