Automated identification and reduction of artifacts in cine four-dimensional computed tomography (4DCT) images using respiratory motion model

Automated identification and reduction of artifacts in cine four-dimensional computed tomography... Int J CARS (2017) 12:1521–1532 DOI 10.1007/s11548-017-1538-0 ORIGINAL ARTICLE Automated identification and reduction of artifacts in cine four-dimensional computed tomography (4DCT) images using respiratory motion model 1,2 2,3 2,3 2,4,5 Min Li · Sarah Joy Castillo · Richard Castillo · Edward Castillo · 2,4 1 6 Thomas Guerrero · Liang Xiao · Xiaolin Zheng Received: 14 November 2016 / Accepted: 1 February 2017 / Published online: 14 February 2017 © CARS 2017 Abstract facts were located according to deviations between image Purpose Four-dimensional computed tomography (4DCT) points and their motion trajectories and further corrected images are often marred by artifacts that substantially based on position prediction. degrade image quality and confound image interpretation. Results The mean spatial error (standard deviation) was Human observation remains the standard method of 4DCT 1.00 (0.85) mm after registration as opposed to 6.96 (4.61) artifact evaluation, which is time-consuming and subjective. mm before registration. In addition, we took human observa- We develop a method to automatically identify and reduce tion conducted by medical experts as the gold standard. The artifacts in cine 4DCT images. average sensitivity, specificity, and accuracy of the proposed Methods We proposed an algorithm that consisted of two method in artifact http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png International Journal of Computer Assisted Radiology and Surgery Springer Journals

Automated identification and reduction of artifacts in cine four-dimensional computed tomography (4DCT) images using respiratory motion model

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Publisher
Springer International Publishing
Copyright
Copyright © 2017 by CARS
Subject
Medicine & Public Health; Imaging / Radiology; Surgery; Health Informatics; Computer Imaging, Vision, Pattern Recognition and Graphics; Computer Science, general
ISSN
1861-6410
eISSN
1861-6429
D.O.I.
10.1007/s11548-017-1538-0
Publisher site
See Article on Publisher Site

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