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Proceedings Paper

Motion artifact reduction with predictive gating
Author(s): Jiang Hsieh
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Paper Abstract

It is well known that patient motion causes artifacts that can mimic disease and lead to mis-diagnosis. Various physiological gating methods have been investigated in the past to combat this problem by acquiring CT scans during the quiescent motion periods. Previously, we proposed a predictive gating algorithm for computing the quiescent time intervals to automatically starting the scanner. The algorithm uses adaptive moving correlation to exploit the fact that the shape of the inspiratory or expiratory segment of the waveform is similar from breath to breath. The CT data acquisition is triggered when the correlation coefficient exceeds a predefined threshold. Although this method performs satisfactorily in most patients, it fails to trigger CT scans in some patients when excessive variation in the motion waveform exists. To overcome this difficulty, we propose an improved algorithm that will determine the correlation threshold based on the waveform history acquired during the patient preparation. We further exclude the portions of the breathing curve that deviate significantly from the average breathing curve based on the low correlation coefficients. We then calculate the weighted correlation coefficients with the most recent samples carrying higher weights. The start of a CT scan is then determined based on the weighted average. Various experiments have demonstrated the advantages and effectiveness of our approach.

Paper Details

Date Published: 11 November 1996
PDF: 9 pages
Proc. SPIE 2824, Adaptive Computing: Mathematical and Physical Methods for Complex Environments, (11 November 1996); doi: 10.1117/12.258135
Show Author Affiliations
Jiang Hsieh, General Electric Medical Systems (United States)


Published in SPIE Proceedings Vol. 2824:
Adaptive Computing: Mathematical and Physical Methods for Complex Environments
H. John Caulfield; Su-Shing Chen, Editor(s)

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