Abstract：
PURPOSE:Computed tomography (CT) and, in particular, cone beam CT (CBCT) have been increasingly used as a diagnostic tool in recent years. Patient motion during acquisition is common in CBCT due to long scan times. This results in degraded image quality and may potentially increase the number of retakes. Our aim was to develop a marker-free iterative motion correction algorithm that works on the projection images and is suitable for local tomography. METHODS:We present an iterative motion correction algorithm that allows the patient's motion to be detected and taken into account during reconstruction. The core of our method is a fast GPU-accelerated three-dimensional reconstruction algorithm. Assuming rigid motion, motion correction is performed by minimizing a pixel-wise cost function between all captured x-ray images and parameterized projections of the reconstructed volume. RESULTS:Our method is marker-free and requires only projection images. Furthermore, it can deal with local tomography data. We demonstrate the effectiveness of our approach on both simulated and real motion-beset patient images. The results show that our new motion correction algorithm leads to accurate reconstructions with sharper edges, better contrasts and more detail. CONCLUSIONS:The presented method allows for correction of patient motion with observable improvements in image quality compared to uncorrected reconstructions. Potentially, this may reduce the number of retakes caused by corrupted reconstructions due to patient movements.
journal_name
Med Physjournal_title
Medical physicsauthors
Niebler S,Schömer E,Tjaden H,Schwanecke U,Schulze Rdoi
10.1002/mp.13731subject
Has Abstractpub_date
2019-10-01 00:00:00pages
4470-4480issue
10eissn
0094-2405issn
2473-4209journal_volume
46pub_type
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