Limits...
A Novel Iterative CT Reconstruction Approach Based on FBP Algorithm.

Shi H, Luo S, Yang Z, Wu G - PLoS ONE (2015)

Bottom Line: In this paper, an iterative FBP approach is proposed to reduce the aliasing degradation.This procedure can be performed iteratively to improve the reconstruction performance gradually until certain stopping criterion is satisfied.The calculation burden is several times that of FBP, which is much less than that of general IR algorithms and acceptable in the most situations.

View Article: PubMed Central - PubMed

Affiliation: School of Biomedical Engineering, Capital Medical University of China, Beijing, China, 100069.

ABSTRACT
The Filtered Back-Projection (FBP) algorithm and its modified versions are the most important techniques for CT (Computerized tomography) reconstruction, however, it may produce aliasing degradation in the reconstructed images due to projection discretization. The general iterative reconstruction (IR) algorithms suffer from their heavy calculation burden and other drawbacks. In this paper, an iterative FBP approach is proposed to reduce the aliasing degradation. In the approach, the image reconstructed by FBP algorithm is treated as the intermediate image and projected along the original projection directions to produce the reprojection data. The difference between the original and reprojection data is filtered by a special digital filter, and then is reconstructed by FBP to produce a correction term. The correction term is added to the intermediate image to update it. This procedure can be performed iteratively to improve the reconstruction performance gradually until certain stopping criterion is satisfied. Some simulations and tests on real data show the proposed approach is better than FBP algorithm or some IR algorithms in term of some general image criteria. The calculation burden is several times that of FBP, which is much less than that of general IR algorithms and acceptable in the most situations. Therefore, the proposed algorithm has the potential applications in practical CT systems.

No MeSH data available.


Related in: MedlinePlus

The images of mouse liver reconstructed using different schemes.(a) The image using the classic FBP, (b) using the iterative FBP, (c) and (d) are the portions of (a) and (b), respectively.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4587734&req=5

pone.0138498.g008: The images of mouse liver reconstructed using different schemes.(a) The image using the classic FBP, (b) using the iterative FBP, (c) and (d) are the portions of (a) and (b), respectively.

Mentions: Example 4. In this example, the proposed algorithm is used in the practical application. The sample is a mouse liver, and the experiment is performed in the X-ray Imaging and Biomedical Application Beamline station (BL13W1) at the SSRF(Shanghai Synchrotron Radiation Facility, China). All animal experiments and procedures carried out on the animals are approved by the animal welfare committee of Capital Medical University and the approval ID is SCXK-(Army) 2013-X-99. The setup can ensure x-ray beam to be near parallel. The energy is about 21 keV. A CCD camera (the size of pixel is 13μm × 13μm) is used as the detector, comprising 2,588 × 458 pixels. During scanning, the sample is rotated on a turntable around its cylindrical axis by 180° at step of 0.4411°. The rotation speed is about 0.25°/s and the exposure time was 11 millisecond. Before and after scan, the background images (the sample is absent) and dark field images (the x-ray beam is closed) are recorded for preprocessing. The background images are used for normalization, the dark field images are used to reduce the noise of various kinds(mainly camera noise). Finally, the logarithm transform is employed to enhance the image contrast,pi=lg(pib-pid)-lg(pio-pid)where , and denote i-th column of background image, dark field image and projection image. The images are reconstructed by the classic FBP and the proposed iterative FBP, which are shown in Fig 8.


A Novel Iterative CT Reconstruction Approach Based on FBP Algorithm.

Shi H, Luo S, Yang Z, Wu G - PLoS ONE (2015)

The images of mouse liver reconstructed using different schemes.(a) The image using the classic FBP, (b) using the iterative FBP, (c) and (d) are the portions of (a) and (b), respectively.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4587734&req=5

pone.0138498.g008: The images of mouse liver reconstructed using different schemes.(a) The image using the classic FBP, (b) using the iterative FBP, (c) and (d) are the portions of (a) and (b), respectively.
Mentions: Example 4. In this example, the proposed algorithm is used in the practical application. The sample is a mouse liver, and the experiment is performed in the X-ray Imaging and Biomedical Application Beamline station (BL13W1) at the SSRF(Shanghai Synchrotron Radiation Facility, China). All animal experiments and procedures carried out on the animals are approved by the animal welfare committee of Capital Medical University and the approval ID is SCXK-(Army) 2013-X-99. The setup can ensure x-ray beam to be near parallel. The energy is about 21 keV. A CCD camera (the size of pixel is 13μm × 13μm) is used as the detector, comprising 2,588 × 458 pixels. During scanning, the sample is rotated on a turntable around its cylindrical axis by 180° at step of 0.4411°. The rotation speed is about 0.25°/s and the exposure time was 11 millisecond. Before and after scan, the background images (the sample is absent) and dark field images (the x-ray beam is closed) are recorded for preprocessing. The background images are used for normalization, the dark field images are used to reduce the noise of various kinds(mainly camera noise). Finally, the logarithm transform is employed to enhance the image contrast,pi=lg(pib-pid)-lg(pio-pid)where , and denote i-th column of background image, dark field image and projection image. The images are reconstructed by the classic FBP and the proposed iterative FBP, which are shown in Fig 8.

Bottom Line: In this paper, an iterative FBP approach is proposed to reduce the aliasing degradation.This procedure can be performed iteratively to improve the reconstruction performance gradually until certain stopping criterion is satisfied.The calculation burden is several times that of FBP, which is much less than that of general IR algorithms and acceptable in the most situations.

View Article: PubMed Central - PubMed

Affiliation: School of Biomedical Engineering, Capital Medical University of China, Beijing, China, 100069.

ABSTRACT
The Filtered Back-Projection (FBP) algorithm and its modified versions are the most important techniques for CT (Computerized tomography) reconstruction, however, it may produce aliasing degradation in the reconstructed images due to projection discretization. The general iterative reconstruction (IR) algorithms suffer from their heavy calculation burden and other drawbacks. In this paper, an iterative FBP approach is proposed to reduce the aliasing degradation. In the approach, the image reconstructed by FBP algorithm is treated as the intermediate image and projected along the original projection directions to produce the reprojection data. The difference between the original and reprojection data is filtered by a special digital filter, and then is reconstructed by FBP to produce a correction term. The correction term is added to the intermediate image to update it. This procedure can be performed iteratively to improve the reconstruction performance gradually until certain stopping criterion is satisfied. Some simulations and tests on real data show the proposed approach is better than FBP algorithm or some IR algorithms in term of some general image criteria. The calculation burden is several times that of FBP, which is much less than that of general IR algorithms and acceptable in the most situations. Therefore, the proposed algorithm has the potential applications in practical CT systems.

No MeSH data available.


Related in: MedlinePlus