Robust and fast contrast inflow detection for 2D X-ray fluoroscopy

Authors:
Terrence Chen;Gareth Funka-Lea;Dorin Comaniciu
Affiliations:
Siemens Corporation, Corporate Research, Princeton, NJ;Siemens Corporation, Corporate Research, Princeton, NJ;Siemens Corporation, Corporate Research, Princeton, NJ
Venue:
MICCAI'11 Proceedings of the 14th international conference on Medical image computing and computer-assisted intervention - Volume Part I
Year:
2011

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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.