Paper Info
Title
Respiratory signal generation for retrospective gating of cone-beam CT images
Abstract
We are currently investigating the acquisition of 4D cone-beam CT data using retrospective gating of the X-ray projection images. This approach requires a respiratory signal that is synchronized with image acquisition. To obtain such a signal we propose to use a spherical fiducial attached to the patient's skin surface such that it is visible in the images. A region of interest containing the fiducial is manually identified in an initial image and is then automatically detected in all other images. Subsequently, we perform an approximate spatial (3D) reconstruction of the marker location from its 2D locations. Finally, we compute a respiratory signal by projecting the 3D points onto the major axis estimated via principle component analysis. As this respiratory signal was obtained from the fiducial location in each of the images it is implicitly synchronized with image acquisition. We evaluate the robustness of our fiducial detection using an anthropomorphic respiratory phantom. To evaluate the quality of the estimated respiratory signal we use a motion platform that follows the respiratory motion obtained by tracking the skin surface of a volunteer. We show that our method generates a respiratory signal that is in phase with the ground truth signal, but suffers from inaccuracies in amplitude close to the anterior-posterior imaging setup where the primary direction of motion is perpendicular to the image plane. Thus, our method should only be used for phase based retrospective gating.
Year
DOI
Venue
2008
10.1117/12.768849
PROCEEDINGS OF THE SOCIETY OF PHOTO-OPTICAL INSTRUMENTATION ENGINEERS (SPIE)
Keywords
Field
DocType
image-guided therapy,respiratory motion,respiratory signal,cone-beam CT,trajectory reconstruction
Computer vision,Imaging phantom,Image plane,Robustness (computer science),Ground truth,Artificial intelligence,Region of interest,Image-Guided Therapy,Amplitude,Trajectory,Mathematics
Conference
Volume
ISSN
Citations 
6918
0277-786X
3
PageRank 
References 
Authors
0.50
7
2
Name
Order
Citations
PageRank
Stefan Wiesner1529.06
Ziv Yaniv211419.93