Projected Image Restoration Method Based on Genetic Algorithm for Cone-Beam CT

Kui Dong Huang; Liang Zhang; Kun Bu; Hua Zhang

doi:10.4028/www.scientific.net/AMM.401-403.1406

Paper Titles

Machining Parameters Optimization for WEDM Based on Grey Relational Analysis
p.1385

Magnetic Generator with Automatic Gain Regulation in a Wireless Tracking System for a Capsule Endoscope
p.1393

Novel Iterative Truncated Total Least Squares Algorithm for Image Restoration
p.1397

Prediction Research of Highway Traveling Passenger Volume Based on Wavelet Neural Network
p.1401

Projected Image Restoration Method Based on Genetic Algorithm for Cone-Beam CT
p.1406

Real-Time Human Skeleton Extraction Based on Video Sequences
p.1410

Research and Design of Digital Signal Processing Virtual Experiment Platform
p.1415

Research of FMCW for Perfect Binary Sequences Pairs
p.1419

Vibration Signal of Recoil Mechanism De-Noising Processing Based on Wavelet Analysis
p.1424

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 401-403Projected Image Restoration Method Based on...

Projected Image Restoration Method Based on Genetic Algorithm for Cone-Beam CT

Abstract:

For the problem of image quality degradation in cone-beam CT (CBCT) based on flat panel detector (FPD), a genetic algorithm based on pre-segmentation (PS-GA) is proposed for CBCT projected image restoration. According to the characteristic of that most of the area of the projected image is empty and without the tested object, a robust segmentation algorithm is used in this method to segment the smallest rectangle that contains the tested object, and the calculating range is limited to the smallest rectangle by the specially designed genetic algorithm, which significantly reduced the amount of calculated data. The experimental results show that the method raised the edge sharpness, contrast-to-noise ratio (CNR) and average gradient (AG) of the projected images and slice images, and there is no visible artifacts introduced.

You might also be interested in these eBooks

Frontiers of Manufacturing Science and Measuring Technology III

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 401-403)

Pages:

1406-1409

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.401-403.1406

Citation:

Cite this paper

Online since:

September 2013

Authors:

Kui Dong Huang, Liang Zhang, Kun Bu, Hua Zhang

Keywords:

Cone Beam Computed Tomography (CBCT), Genetic Algorithm (GA), Image Restoration, Pre-Segmentation

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] D.H. Zhang, R. Ning, K. Bu and H.P. Mao: Chinese Journal of Scientific Instrument Vol. 26 (2005), pp.157-163.

Google Scholar

[2] A.K. Hunter and W.D. McDavid: Dentomaxillofacial Radiology Vol. 41 (2012), pp.217-223.

Google Scholar

[3] J.J. Li, H.N. Lu and B.L. Li: Optical Technique Vol. 33 (2007), pp.113-115.

Google Scholar

[4] C.T. Chen, B.G. Huang, W.R. Gao and C.K. Tao: Optical Technique Vol. 30 (2004), pp.36-39.

Google Scholar

[5] G.K. Moon and A.K. Katsaggelos: IEEE Transactions on Image Processing Vol. 4 (1995), pp.594-602.

Google Scholar

[6] Y. Wang and Z.F. Hu: Journal of Chongqing University of Posts and Telecommunications (Natural Science) Vol. 19 (2007), pp.745-747.

Google Scholar

[7] H. Zhang, Y.K. Shi, K.D. Huang and Q.C. Yu: Applied Mechanics and Materials Vol. 229-231 (2012), pp.1858-1861.

Google Scholar

[8] S. Hashemi, S. Kiani, N. Noroozi and M. E. Moghaddam: Pattern Recognition Letters Vol. 31 (2010), pp.1816-1824.

DOI: 10.1016/j.patrec.2009.12.006

Google Scholar

[9] A. Khan and H. Yin: Lecture Notes in Computer Science Vol. 6936 (2011), pp.144-151.

Google Scholar

[10] M.J. Li, D.H. Zhang, K.D. Huang, S.L. Zhang and F.L. Zha: Journal of Northwestern Polytechnical University Vol. 29 (2011), pp.68-73.

Google Scholar

[11] K.D. Huang, D.H. Zhang, M.J. Li and H. Zhang: Applied Mechanics and Materials Vol. 229-231 (2012), pp.1819-1822.

Google Scholar