An automated method for comparing motion artifacts in cine four-dimensional computed tomography images.
Repository Usage Stats
The aim of this study is to develop an automated method to objectively compare motion artifacts in two four-dimensional computed tomography (4D CT) image sets, and identify the one that would appear to human observers with fewer or smaller artifacts. Our proposed method is based on the difference of the normalized correlation coefficients between edge slices at couch transitions, which we hypothesize may be a suitable metric to identify motion artifacts. We evaluated our method using ten pairs of 4D CT image sets that showed subtle differences in artifacts between images in a pair, which were identifiable by human observers. One set of 4D CT images was sorted using breathing traces in which our clinically implemented 4D CT sorting software miscalculated the respiratory phase, which expectedly led to artifacts in the images. The other set of images consisted of the same images; however, these were sorted using the same breathing traces but with corrected phases. Next we calculated the normalized correlation coefficients between edge slices at all couch transitions for all respiratory phases in both image sets to evaluate for motion artifacts. For nine image set pairs, our method identified the 4D CT sets sorted using the breathing traces with the corrected respiratory phase to result in images with fewer or smaller artifacts, whereas for one image pair, no difference was noted. Two observers independently assessed the accuracy of our method. Both observers identified 9 image sets that were sorted using the breathing traces with corrected respiratory phase as having fewer or smaller artifacts. In summary, using the 4D CT data of ten pairs of 4D CT image sets, we have demonstrated proof of principle that our method is able to replicate the results of two human observers in identifying the image set with fewer or smaller artifacts.
Radiographic Image Interpretation, Computer-Assisted
Four-Dimensional Computed Tomography
Published Version (Please cite this version)10.1120/jacmp.v13i6.3838
Publication InfoCui, Guoqiang; Jew, Brian; Hong, Julian C; Johnston, Eric W; Loo, Billy W; & Maxim, Peter G (2012). An automated method for comparing motion artifacts in cine four-dimensional computed tomography images. Journal of applied clinical medical physics, 13(6). pp. 3838. 10.1120/jacmp.v13i6.3838. Retrieved from https://hdl.handle.net/10161/19086.
This is constructed from limited available data and may be imprecise. To cite this article, please review & use the official citation provided by the journal.
More InfoShow full item record
Assistant Professor of Radiation Oncology
I am a current resident physician in radiation oncology and will be completing residency in June 2019. I will be starting as faculty in the Department of Radiation Oncology and in the Bakar Computational Sciences Health Institute at the University of California, San Francisco in September 2019.
Alphabetical list of authors with Scholars@Duke profiles.