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Correction of image artifacts from treatment couch in cone-beam CT from kV on-board imaging
Imad Ali1, Salahuddin Ahmad, Nesreen Alsbou
1Department of Radiation Oncology, University of Oklahoma Health Sciences Center, Oklahoma City, OK 73104, USA. iali@ouhsc.edu
Purpose:
To investigate image artifacts caused by a standard treatment couch on cone-beam CT (CBCT) images from a kV on-board imager and to develop an algorithm based on spatial domain filtering to remove image artifacts in CBCT induced by the treatment couch.
Methods:
Image artifacts in CBCT induced by the treatment couch were quantified by scanning a phantom used to quantify CT image performance. This was performed by scanning the phantom setup on a regular treatment couch and in air with the kV on-board imager. An algorithm was developed to filter image artifacts from the treatment couch by processing of cone-beam radiographic projections using two scans: one scan of the phantom and treatment couch and a second scan of the treatment couch only. This algorithm is based on a pixel-by-pixel removal of beam attenuation due to the treatment couch from each projection of the phantom and couch scan. The net couch-filtered projections were then used to reconstruct CBCT.
Results:
We found that the treatment couch causes considerable image artifacts: CT number uniformity is degraded and varies as much as 15%, and noise in CBCT scans with phantom plus couch (3.5%) is higher than for the phantom in air (1.5%). The spatial domain filtering technique reduces noise by more than 1.5%, improves uniformity by a factor of 2, and removes ringing and streaking artifacts related to the standard treatment couch in CBCT reconstructed from couch-filtered projections. This filtering technique was tested successfully to filter other hardware objects such as a patient immobilization body-fix frame.
Conclusions:
The standard treatment couch causes image artifact in CBCT from kV on-board imaging systems. The spatial domain filtering technique developed in this work improves image quality of CBCT by preprocessing the projections prior to CBCT reconstruction. This technique might be useful to filter other hardware objects from CBCT which may contribute to the degradation of image quality.
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