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High-quality 3D correction of ring and radiant artifacts in flat panel detector-based cone beam volume CT imaging
- Source :
- Physics in Medicine and Biology. 56:6495-6519
- Publication Year :
- 2011
- Publisher :
- IOP Publishing, 2011.
-
Abstract
- The use of an x-ray flat panel detector is increasingly becoming popular in 3D cone beam volume CT machines. Due to the deficient semiconductor array manufacturing process, the cone beam projection data are often corrupted by different types of abnormalities, which cause severe ring and radiant artifacts in a cone beam reconstruction image, and as a result, the diagnostic image quality is degraded. In this paper, a novel technique is presented for the correction of error in the 2D cone beam projections due to abnormalities often observed in 2D x-ray flat panel detectors. Template images are derived from the responses of the detector pixels using their statistical properties and then an effective non-causal derivative-based detection algorithm in 2D space is presented for the detection of defective and mis-calibrated detector elements separately. An image inpainting-based 3D correction scheme is proposed for the estimation of responses of defective detector elements, and the responses of the mis-calibrated detector elements are corrected using the normalization technique. For real-time implementation, a simplification of the proposed off-line method is also suggested. Finally, the proposed algorithms are tested using different real cone beam volume CT images and the experimental results demonstrate that the proposed methods can effectively remove ring and radiant artifacts from cone beam volume CT images compared to other reported techniques in the literature.
- Subjects :
- Image quality
Inpainting
Normalization (image processing)
Flat panel detector
Imaging, Three-Dimensional
Optics
Image Processing, Computer-Assisted
Animals
X-Ray Intensifying Screens
Radiology, Nuclear Medicine and imaging
Computer vision
Mathematics
Radiological and Ultrasound Technology
Pixel
Phantoms, Imaging
business.industry
Detector
Cone-Beam Computed Tomography
Models, Theoretical
Semiconductors
Calibration
Artificial intelligence
Ct imaging
Artifacts
business
Algorithms
Cone beam reconstruction
Subjects
Details
- ISSN :
- 13616560 and 00319155
- Volume :
- 56
- Database :
- OpenAIRE
- Journal :
- Physics in Medicine and Biology
- Accession number :
- edsair.doi.dedup.....ac707804ce22bb8663ca3f5f5ce23b93
- Full Text :
- https://doi.org/10.1088/0031-9155/56/19/020