Powiadomienia systemowe
- Sesja wygasła!
Tytuł artykułu
Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
Computed tomography (CT) is a widely used imaging technique in medical diagnosis. Among the latest advances in CT imaging techniques, the use of cone-beam X-ray projections, instead of the usual planar fan beam, promises faster yet safer 3D imaging in comparison to the previous CT imaging methodologies. This technique is called Cone Beam CT (CBCT). However, these advantages come at the expense of a more challenging 3D reconstruction problem that is still an active research area to improve the speed and quality of image reconstruction. In this paper, we propose a rapid parallel Multiplicative Algebraic Reconstruction Technique (rpMART) via a vectorization process for CBCT which gives more accurate and faster reconstruction even with a lower number of projections via parallel computing. We have compared rpMART with the parallel version of Algebraic Reconstruction Technique (pART) and the conventional non-parallel versions of npART, npMART and Feldkamp, Davis, and Kress (npFDK) techniques. The results indicate that the reconstructed volume images from rpMART provide a higher image quality index of 0.99 than the indices of pART and npFDK of 0.80 and 0.39, respectively. Also the proposed implementation of rpMART and pART via parallel computing significantly reduce the reconstruction time from more than 6 h with npART and npMART to 580 and 560 s with the full 360° projections data, respectively. We consider that rpMART could be a better image reconstruction technique for CBCT in clinical applications instead of the widely used FDK method.
Wydawca
Czasopismo
Rocznik
Tom
Strony
619--629
Opis fizyczny
Bibliogr. 30 poz., rys., tab., wykr.
Twórcy
autor
- Department of Biomedical Engineering, College of Electronics and Information, Kyung Hee University, Yongin, Republic of Korea
autor
- Department of Biomedical Engineering, College of Electronics and Information, Kyung Hee University, Yongin, Republic of Korea
autor
- Department of Biomedical Engineering, College of Electronics and Information, Kyung Hee University, Yongin, Republic of Korea
autor
- Electrical and Computer Engineering Department, King Abdulaziz University, Jeddah, Saudi Arabia
autor
- Department of Biomedical Engineering, College of Electronics and Information, Kyung Hee University, Yongin, Republic of Korea
autor
- Department of Biomedical Engineering, College of Electronics and Information, Kyung Hee University, 1732, Deogyeong-daero, Giheung-gu, Yongin-si, Gyeonggi-do 17104, Republic of Korea
Bibliografia
- [1] Scarfe WC, Farman AG, Sukovic P. Clinical applications of cone-beam computed tomography in dental practice. J Can Dent Assoc 2006;72(1):75–80.
- [2] Xiao S, Bresler Y, Munson DC. Fast Feldkamp algorithm for cone-beam computer tomography. Proceedings of the IEEE International Conference on Image Processing; 2003. p. 819–22.
- [3] Feldkamp L, Davis L, Kress J. Practical cone-beam algorithm. J Opt Soc Am A 1984;1(6):612.
- [4] Mueller K, Yagel R, Wheller J. Fast implementations of algebraic methods for three-dimensional reconstruction from cone-beam data. IEEE Trans Med Imag 1999;18 (6):538–48.
- [5] Avilés JE. Multiplicative algebraic reconstruction techniques for 3D cone beam CT of the breast.Engineering Physics Thesis Yucatan, Mexico: Faculty of Engineering, Autonoma University; 2004.
- [6] Cengiz K, Kamasak M. Comparison of algebraic reconstruction algorithms for tomosynthesis.MSc. Thesis Turkey: Computer Engineering Department, Faculty of Engineering, Istanbul Technical University; 2014.
- [7] Fu J, Hu X, Velroyen A, Bech M, Jiang M, Pfeiffer F. 3D algebraic iterative reconstruction for cone-beam X-ray differential phase-contrast computed tomography. PLOS ONE 2015;10(3). http://dx.doi.org/10.1371/journal.pone.0117502.
- [8] Qiu W, Tong J, Mitchell C, Marchant T, Spencer P, Moore C, et al. New iterative cone beam CT reconstruction software: parameter optimisation and convergence study. Comput Methods Programs Biomed 2010;100(2):166–74.
- [9] Fan Z, Xie Y. A block-wise approximate parallel implementation for ART algorithm on CUDA-enabled GPU. Bio-Med Mater Eng 2015;26(s1):S1027–35.
- [10] Zeng G. Medical image reconstruction. Beijing: Higher Education Press; 2010.
- [11] Siddon R. Fast calculation of the exact radiological path for a three-dimensional CT array. Med Phys 1985;12(2):252.
- [12] Jacobs F, Sundermann E, Sutter BD, Lemahieu I. A fast algorithm to calculate the exact radiological path through a pixel or voxel space. J Comput Inf Technol 1998;6:89–94.
- [13] Nguyen V, Lee S. Parallelizing a matched pair of ray-tracing projector and backprojector for iterative cone-beam CT reconstruction. IEEE Trans Nucl Sci 2015;62(1):171–81.
- [14] Buzug T. Computed tomography. Berlin: Springer; 2008.
- [15] Scherl H. Evaluation of state-of-the-art hardware architectures for fast cone-beam CT reconstruction. Wiesbaden: Vieweg+Teubner Verlag; 2011.
- [16] Mori S, Endo M, Komatsu S, Kandatsu S, Yashiro T, Baba M. A combination-weighted Feldkamp-based reconstruction algorithm for cone-beam CT. Phys Med Biol 2006;51(16):3953–65.
- [17] Simon R, David S, Laurent D. Comparison of analytic and algebraic methods for motion-compensated cone-beam CT reconstruction of the thorax. IEEE Trans Med Imag 2009;28 (10):1513–25.
- [18] Xu F, Mueller K. Real-time 3D computed tomographic reconstruction using commodity graphics hardware. Phys Med Biol 2007;52(12):3405–19.
- [19] Rezvani N, Aruliah D, Jackson K, Moseley D, Siewerdsen J. OSCaR: an open-source cone-beam CT reconstruction tool for imaging research. Med Phys 2007;34:2341.
- [20] Chlewicki W, Badea C, Pallikarakis N. Cone based 3D reconstruction: a FDK – SART comparison for limited number of projections. Proceedings of the 9th Mediterranean Conference on Medical and Biological Engineering and Computing; 2001. p. 495–7.
- [21] Mueller K, Yagel R. Rapid 3-D cone-beam reconstruction with the simultaneous algebraic reconstruction technique (SART) using 2-D texture mapping hardware. IEEE Trans Med Imag 2000;19(12):1227–37.
- [22] Mian-Yi C, Yong R, Peng F, Peng H, Lu-Zhen D, Biao W, Zhi- Chao L, Jian W. Computed tomography image reconstruction from few-views data by multi-directional total variation. J Med Imag Health Inform 2015;5(2):309–16.
- [23] Gordon D. Parallel ART for image reconstruction in CT using processor arrays. Int J Parallel Emerg Distrib Syst 2006;21 (5):365–80.
- [24] Saha S, Tahtali M, Lambert A, Pickering M. CT reconstruction from simultaneous projections: a step towards capturing CT in One Go. Comput Methods Biomech Biomed Eng: Imag Vis 2015;1–13.
- [25] Gordon R, Bender R, Herman G. Algebraic reconstruction techniques (ART) for three-dimensional electron microscopy and X-ray photography. J Theor Biol 1970;29 (3):471–81.
- [26] Atkinson CH, Soria J. Algebraic reconstruction techniques for tomographic particle image velocimetry. Proceedings of the 16th Australasian Fluid Mechanics Conference; 2007. p. 191–8.
- [27] Zeng K, Bai E, Wang G. A fast CT reconstruction scheme for a general multi-core PC. Int J Biomed Imag 2007;1–9. Article ID 29610.
- [28] MATLAB version 8.5.0.197613 (R2015a). Natick, MA: The MathWorks Inc.; 2015.
- [29] Loizou C, Pattichis C. Despeckle filtering algorithms and software for ultrasound imaging. San Rafael, CA: Morgan & Claypool Publishers; 2008.
- [30] Wang Z, Bovik A, Sheikh H, Simoncelli E. Image quality assessment: from error visibility to structural similarity. IEEE Trans Image Process 2004;13(4):600–12.
Uwagi
PL
Opracowanie w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-edbf78b2-f882-4deb-ad51-268fc07ac4c1