Abstract
We investigated a method, motion compensated integration (MCI), for enhancing stent Contrast-to-Noise Ratio (CNR) such that stent deployment may be more easily assessed. MCI registers fluoroscopic frames on the basis of stent motion and performs pixel-wise integration to reduce noise. Registration is based on marker balls, high contrast interventional devices which guide the clinician in stent placement. It is assumed that stent motion is identical to that of the marker balls. Detecting marker balls and identifying their centroids with a high degree of accuracy is a non-trivial task. To address the required registration accuracy, in this work we examine MCI’s visualization benefit as a function of registration error. We employ adaptive forced choice experiments to quantify human discrimination fidelity. Perception results are contrasted with CNR measurements. For each level of registration inaccuracy investigated, MCI conferred a benefit (p<0.05) on stent deployment assessment suggesting the technique is tolerant of modest registration error. We also consider the blurring effect of cardiac motion during the x-ray pulse and select frames for integration as a function of cardiac phase imaged.
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© 2005 Springer-Verlag Berlin Heidelberg
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Ross, J.C., Langan, D., Manjeshwar, R., Kaufhold, J., Manak, J., Wilson, D. (2005). Registration and Integration for Fluoroscopy Device Enhancement. In: Duncan, J.S., Gerig, G. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2005. MICCAI 2005. Lecture Notes in Computer Science, vol 3749. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11566465_105
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DOI: https://doi.org/10.1007/11566465_105
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-29327-9
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