KEYWORDS: Image registration, Data acquisition, Image quality, Image restoration, 3D acquisition, Radon, Matrices, Data modeling, Computed tomography, Medical image reconstruction, 3D image reconstruction
In many interventional settings it would be beneficial to perform a final CBCT acquisition for outcome control after the intervention is done. However, due to high patient dose this is often omitted. Volume-of-interest acquisitions offer considerable dose reduction, but image reconstruction typically suffers from cupping artifacts and offsets in radiodensity due to the truncated projection data. In a previous work we presented a method which allows to incorporate available prior volume data into the reconstruction of volume-of-interest acquisitions in CBCT. The method works by making use of the fluoroscopic positioning images typically acquired before CBCT acquisitions in a 3D Radon space-based registration method registering the prior volume to the volumeof-interest scenario. Here, we demonstrate the application of this method on real clinical data or the first time.
Optical flow-based methods are commonly used to detect and correct patient motion in modalities such as cone-beam computed tomography. With such methods, the rotational motion deriving from the acquisition trajectory itself is obscuring the patient motion and therefore considered a perturbation. In this work, the question commonly posed in motion estimation is reversed. Instead of considering the rotational motion as obscuring the patient motion, it can be used to derive shape information about the patient. This is done by computing the optical flow from projection images in order to find point correspondences in different frames of the acquisition. Finally, projective geometry is used to localize a given pair of corresponding 2D image points in 3D object space.
The advantage of this method is that it allows for the localization of structures which are not contained within the scan field of view of truncated acquisitions but within an extended projection field of view. Therefore, it is shown that for certain high contrast structures, e.g. the skull, this localization method can be used to estimate the maximum extent of a patient from truncated projection data, which is an important information for extrapolation methods, or to localize highly absorbing structures outside of the scan field of view which contribute to the severity of the typically observed truncation artifacts.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.