Software architecture for multi-bed FDK-based reconstruction in X-ray CT scanners

Computer Methods and Programs in Biomedicine

Volumn 107, Issue 2, 2012, Pages 218-232

  Abella, M ^a   Vaquero, J J ^b   Sisniega, A ^b   Pascau, J ^a,b   Udias A ^a   Garcia V ^a,c   Vidal, I ^a   Desco, M ^a,b,c  

^a HOSPITAL GENERAL UNIVERSITARIO GREGORIO MARAÑÓN   (Spain)

^b UNIVERSIDAD CARLOS III DE MADRID   (Spain)

^c CENTRO DE INVESTIGACIÓN BIOMÉDICA EN RED DE SALUD MENTAL CIBERSAM   (Spain)

Author keywords

Cone beam; CT; CT artifacts; FDK; Reconstruction; X ray computed tomography

Indexed keywords

CONE BEAM; CT; CT ARTIFACTS; FDK; X-RAY COMPUTED TOMOGRAPHY;

ALGORITHMS; ANIMALS; APPROXIMATION THEORY; CALIBRATION; GEOMETRY; IMAGE RECONSTRUCTION; SCANNING; SOFTWARE ARCHITECTURE; X RAYS;

COMPUTERIZED TOMOGRAPHY;

ALGORITHM; ARTICLE; ARTIFACT REDUCTION; CALIBRATION; COMPUTED TOMOGRAPHY SCANNER; CONTROLLED STUDY; DATA ANALYSIS SOFTWARE; IMAGE RECONSTRUCTION; SYSTEM ANALYSIS;

ALGORITHMS; ANIMALS; MICE; RADIOGRAPHIC IMAGE ENHANCEMENT; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SOFTWARE; TOMOGRAPHY, X-RAY COMPUTED; WHOLE BODY IMAGING;

EID: 84861982065     PISSN: 01692607     EISSN: 18727565     Source Type: Journal    
DOI: 10.1016/j.cmpb.2011.06.008     Document Type: Article

References (53)

1. Goertzen A.L., Nagarkar V., Street R.A., Paulus M.J., Boone J.M., Cherry S.R. A comparison of X-ray detectors for mouse CT imaging. Phys. Med. Biol. 2004, 5251-5265.
2. Kim H.K., Lee S.C., Cho M.H., Lee S.Y., Cho G. Use of a flat-panel detector for microtomography: a feasibility study for small-animal imaging. IEEE Trans. Nucl. Sci. 2005, 193-198.
3. Ritman E.L. Small-animal CT: its difference from, and impact on, clinical CT. Nucl. Instum. Methods Phys. Res. A 2007, 968-970.
4. Badea C.T., Drangova M., Holdsworth D.W., Johnson G.A. In vivo small-animal imaging using micro-CT and digital subtraction angiography. Phys. Med. Biol. 2008, R319-R350.
5. Vaquero J.J., Redondo S., Lage E., Abella M., Sisniega A., Tapias G., Montenegro M.L.S., Desco M. Assessment of a new high-performance small-animal X-ray tomograph. IEEE Trans. Nucl. Sci. 2008, 898-905.
6. Feldkamp L.A., Davis L.C., Kress J.W. Practical cone-beam algorithm. J. Opt. Soc. Am. 1984, 612-619.
7. Zeng G.S.L., Gullberg G.T. A cone-beam tomography algorithm for orthogonal circle-and-line orbit. Phys. Med. Biol. 1992, 563-577.
8. Liang H., Zhang C., Yan M. A Feldkamp-type approximate algorithm for helical multislice ct using extended scanning helix. Comput. Med. Imaging Graph. 2009, 197-204.
9. Scherl H., Keck B., Kowarschik M., Homegger J. Fast GPU-based ct reconstruction using the common unified device architecture (CUDA). IEEE Nucl. Sci. Symp. Conf. Record 2007, 4464-4466.
10. Okitsu Y., Ino F., Hagihara K. Accelerating cone beam reconstruction using the cuda-enabled GPU. Proceedings of the 15th International Conference on High Performance Computing 2008, 108-119.
11. Yan G.R., Tian J., Zhu S.P., Dai Y.K., Qin C.H. Fast cone-beam CT image reconstruction using GPU hardware. J. X-Ray Sci. Technol. 2008, 225-234.
12. Zhao X., Hu J.-J., Zhang P. GPU-based 3D cone-beam CT image reconstruction for large data volume. Int. J. Biomed. Imaging 2009, 149079.
13. Noël P.B., Walczaka A.M., Xua J., Corsoa J.J., Hoffmanna K.R., Schafera S. GPU-based cone beam computed tomography. Comput. Methods Programs Biomed. 2010, 271-277.
14. Yusuke O., Ino F., Hagihara K. High-performance cone beam reconstruction using cuda compatible GPUS. Parallel Comput. 2010, 129-141.
15. Schiwietz T., Bose S., Maltz J., Westermann R. A fast and high-quality cone beam reconstruction pipeline using the GPU. Proc. SPIE Med. Imaging 2007, 65105H.
16. Grass M., Kohler T., Proksa R. Angular weighted hybrid cone-beam ct reconstruction for circular trajectories. Phys. Med. Biol. 2001, 1595-1610.
17. Tang X.Y., Hsieh J., Hagiwara A., Nilsen R.A., Thibault J.B., Drapkin E. A three-dimensional weighted cone beam filtered backprojection (CB-FBP) algorithm for image reconstruction in volumetric ct under a circular source trajectory. Phys. Med. Biol. 2005, 3889-3905.
18. Rodet T., Noo F., Defrise M. The cone-beam algorithm of Feldkamp, Davis, and Kress preserves oblique line integrals. Med. Phys. 2004, 1972-1975.
19. Bresler Y., Brokish J. A hierarchical algorithm for fast backprojection in helical cone-beam tomography. IEEE Int. Symp. Biol. Imaging 2004, 1420-1423.
20. Noo F., Clackdoyle R., Mennessier C., White T.A., Roney T.J. An analytic method based on identification of ellipse parameters for scanner calibration in conebeam tomography. Phys. Med. Biol. 2000, 3489-3508.
21. Joseph P.M., Spital R.D. A method for correcting bone induced artifacts in computed tomography scanners. J. Comput. Assist. Tomogr. 1978, 100-108.
22. Kyriakou Y., Prell D., Kalender W.A. Ring artifact correction for high-resolution micro CT. Phys. Med. Biol. 2009, N385-N391.
23. Kak A.C., Slaney, Malcolm Principles of Computerized Tomographic Imaging 1988, IEEE Press.
24. Peters T. Algorithms for fast back- and re-projection in computed tomography. IEEE Trans. Nucl. Sci. 1981, 3641-3647.
25. Vidal-Migallon I., Abella M., Sisniega A., Vaquero J.J., Desco M. Simulation of mechanical misalignments in a cone-beam micro-CT system. IEEE Nucl. Sci. Symp. Conf. Record 2009, 4273-4275.
26. Gullberg G.T., Tsui B.M.W., Crawford C.R., Ballard J.G., Hagius J.T. Estimation of geometrical parameters and collimator evaluation for cone beam tomography. Med. Phys. 1990, 264-272.
27. Rougee A., Picard C., Ponchut C., Trousset Y. Geometrical calibration of X-ray-imaging chains for 3-dimensional reconstruction. Comput. Med. Imaging Graph. 1993, 295-300.
28. Sun Y., Hou Y., Zhao F.Y., Hu J.H. A calibration method for misaligned scanner geometry in cone-beam computed tomography. NDT&E Int. 2006, 499-513.
29. Cho Y., Moseley D.J., Siewerdsen J.H., Jaffray D.A. Accurate technique for complete geometric calibration of cone-beam computed tomography systems. Med. Phys. 2005, 968-983.
30. Johnston S.M., Johnson G.A., Badeaa C.T. Geometric calibration for a dual tube{plus 45 degree rule}detector micro-CT system. Med. Phys. 2008, 1820-1829.
31. von Smekal L., Kachelriess M., Stepina E., Kalender W. Geometric misalignment and calibration in cone-beam tomography. Med. Phys. 2004, 3242-3266.
32. Panetta D., Belcari N., Del Guerra A., Moehrs S. An optimization-based method for geometrical calibration in cone-beam CT without dedicated phantoms. Phys. Med. Biol. 2008, 3841-3861.
33. Brooks R.A., Chiro G.D. Beam hardening in X-ray reconstruction tomography. Phys. Med. Biol. 1976, 390-398.
34. Kachelriess M., Sourbelle K., Kalender W.A. Empirical cupping correction: a first-order raw data precorrection for cone-beam computed tomography. Med. Phys. 2006, 1269-1274.
35. Li B., Zhang Q., Li J. A novel beam hardening correction method for computed tomography. IEEE/ICME Int. Conf. Complex Med. Eng. 2007, 891-895.
36. Grimmer R., Maass C., Kachelriess M. A new method for cupping and scatter precorrection for flat detector CT. IEEE Nucl. Sci. Symp. 2009, 3517-3522.
37. Hsieh J., Molthen R.C., Dawson C.A., Johnson R.H. An iterative approach to the beam hardening correction in cone beam CT. Med. Phys. 2000, 23-29.
38. Nalcioglu O., Lou R.Y. Post-reconstruction method for beam hardening in computerised tomography. Phys. Med. Biol. 1979, 330-340.
39. Vidal F.P., Letang J.M., Peix G., Cloetens P. Investigation of artifact sources in synchrotron microtomography via virtual X-ray imaging. Nucl. Instum. Methods Phys. Res. 2005, 333-348.
40. Seibert J.A., Boone J.M., Lindfors K.K. Flat-field correction technique for digital detectors. Phys. Med. Imaging 1998, 348-354.
41. Arivazhagan S., Deivalakshmi S., Kannan K., Gajbhiye B.N., Muralidhar C., Lukose S.N., Subramanian M.P. Multi-resolution system for artifact removal and edge enhancement in computerized tomography images. Pattern Recogn. Lett. 2007, 1769-1780.
42. Axelsson M., Svensson S., Borgefors G. Reduction of ring artifacts in high resolution X-ray microtomography images. Pattern Recognition 2006, Springer, Berlin/Heidelberg, pp. 61-70.
43. Boin M., Haibel A. Compensation of ring artefacts in synchrotron tomographic images. Opt. Express 2006, 12071-12075.
44. Chen G.H., Leng S. A new data consistency condition for fan-beam projection data. Med. Phys. 2005, 961-967.
45. Ketcham R.A. New algorithms for ring artifact removal. Proc. SPIE 2006, 63180O.
46. Raven C. Numerical removal of ring artifacts in microtomography. Rev. Sci. Instrum. 1998, 2978-2980.
47. Rivers M. Tutorial Introduction to X-Ray Computed Microtomography Data Processing 1998.
48. Sijbers J., Postnov A. Reduction of ring artifacts in high resolution micro-CT reconstructions. Phys. Med. Biol. 2004, 247-253.
49. Abu Anas E.M., Lee S.L., Kamrul Hasan M.K. Removal of ring artifacts in ct imaging through detection and correction of stripes in the sinogram. Phys. Med. Biol. 2010, 6911-6930.
50. Sadi F., Lee S.Y., Hasan M.K. Removal of ring artifacts in computed tomographic imaging using iterative center weighted median filter. Comput. Biol. Med. 2010, 109-118.
51. Yousuf M.A., Asaduzzaman M. An efficient ring artifact reduction method based on projection data for micro-CT images. J. Sci. Res. 2010, 37-45.
52. De Man B., Basu S. Distance-driven projection and backprojection in three dimensions. Phys. Med. Biol. 2004, 2463-2475.
53. Meyer E., Maaß C., Baer M., Raupach R., Schmidt B., Kachelrieß M. A new method for scatter correction in cone-beam CT and its application to metal artifact reduction. IEEE NSS/MIC Conference Record 2010.