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X-Ray Scatter Correction on Soft Tissue Images for Portable Cone Beam CT
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Metadata
Document Title
X-Ray Scatter Correction on Soft Tissue Images for Portable Cone Beam CT
Author
Aootaphao S., Thongvigitmanee S.S., Rajruangrabin J., Thanasupsombat C., Srivongsa T., Thajchayapong P.
Name from Authors Collection
Affiliations
X-Ray CT and Medical Imaging Laboratory, National Electronics and Computer Technology Center, National Science and Technology Development Agency, 112 Thailand Science Park, Phahonyothin Road, Khlong Nueng, Khlong Luang, Pathum Thani 12120, Thailand; National Science and Technology Development Agency, 111 Thailand Science Park, Phahonyothin Road, Khlong Nueng, Khlong Luang, Pathum Thani 12120, Thailand
Type
Article
Source Title
BioMed Research International
ISSN
23146133
Year
2016
Volume
2016
Open Access
All Open Access, Gold, Green
Publisher
Hindawi Limited
DOI
10.1155/2016/3262795
Format
Abstract
Soft tissue images from portable cone beam computed tomography (CBCT) scanners can be used for diagnosis and detection of tumor, cancer, intracerebral hemorrhage, and so forth. Due to large field of view, X-ray scattering which is the main cause of artifacts degrades image quality, such as cupping artifacts, CT number inaccuracy, and low contrast, especially on soft tissue images. In this work, we propose the X-ray scatter correction method for improving soft tissue images. The X-ray scatter correction scheme to estimate X-ray scatter signals is based on the deconvolution technique using the maximum likelihood estimation maximization (MLEM) method. The scatter kernels are obtained by simulating the PMMA sheet on the Monte Carlo simulation (MCS) software. In the experiment, we used the QRM phantom to quantitatively compare with fan-beam CT (FBCT) data in terms of CT number values, contrast to noise ratio, cupping artifacts, and low contrast detectability. Moreover, the PH3 angiography phantom was also used to mimic human soft tissues in the brain. The reconstructed images with our proposed scatter correction show significant improvement on image quality. Thus the proposed scatter correction technique has high potential to detect soft tissues in the brain. Copyright © 2016 Sorapong Aootaphao et al.
Industrial Classification
Knowledge Taxonomy Level 1
Knowledge Taxonomy Level 2
Knowledge Taxonomy Level 3
Funding Sponsor
Faculty of Medicine, Prince of Songkla University
License
N/A
Rights
N/A
Publication Source
Scopus