A new statistical reconstruction method for the computed tomography using an X-ray tube with flying focal spot

• Autorzy: Cierniak Robert , Pluta Piotr , Waligóra Marek , Szymański Zdzisław , Grzanek Konrad , Pałka Filip , Piuri Vincenzo

Identyfikatory

DOI

10.2478/jaiscr-2021-0016

• Języki publikacji: EN

Abstrakty

EN

This paper presents a new image reconstruction method for spiral cone- beam tomography scanners in which an X-ray tube with a flying focal spot is used. The method is based on principles related to the statistical model-based iterative reconstruction (MBIR) methodology. The proposed approach is a continuous-to-continuous data model approach, and the forward model is formulated as a shift-invariant system. This allows for avoiding a nutating reconstruction-based approach, e.g. the advanced single slice rebinning methodology (ASSR) that is usually applied in computed tomography (CT) scanners with X-ray tubes with a flying focal spot. In turn, the proposed approach allows for significantly accelerating the reconstruction processing and, generally, for greatly simplifying the entire reconstruction procedure. Additionally, it improves the quality of the reconstructed images in comparison to the traditional algorithms, as confirmed by extensive simulations. It is worth noting that the main purpose of introducing statistical reconstruction methods to medical CT scanners is the reduction of the impact of measurement noise on the quality of tomography images and, consequently, the dose reduction of X-ray radiation absorbed by a patient. A series of computer simulations followed by doctor’s assessments have been performed, which indicate how great a reduction of the absorbed dose can be achieved using the reconstruction approach presented here.

Słowa kluczowe

EN

computed tomography; iterative statistical reconstruction method; flying focal spot

• Wydawca: University of Social Sciences
• Czasopismo: Journal of Artificial Intelligence and Soft Computing Research
• Rocznik: 2021
• Tom: Vol. 11, No. 4
• Strony: 271--286
• Opis fizyczny: Bibliogr. 22 poz., rys.

Twórcy

autor

Cierniak Robert

• Department of Intelligent Computer Systems, Czestochowa University of Technology, Armii Krajowej 36, 42-200 Częstochowa, Poland

autor

Pluta Piotr

• Department of Intelligent Computer Systems, Czestochowa University of Technology, Armii Krajowej 36, 42-200 Częstochowa, Poland

autor

Waligóra Marek

• Clinical Diagnostic Imaging Department, University of Opole, Opole, Poland

autor

Szymański Zdzisław

• Management Department, University of Social Sciences, Lodz, Poland
• Clark University, Worcester, MA 01610, USA

autor

Grzanek Konrad

• Institute of Information Technology, University of Social Sciences, Lodz, Poland

autor

Pałka Filip

• Faculty of Computer Science and Telecommunications, Cracow University of Technology Warszawska 24, 31-155 Krakow, Poland

autor

Piuri Vincenzo

• University of Milan, Department of Computer Science, Milan, Italy

Bibliografia

• [1] P. Schardt, J. Deuringer, J. Fruedenberger, E. Hell, W. Knuüpfer, D. Mattern, M. Schild, New x-ray tube performance in computed tomography by introducing the rotating envelope tube technology, Medical Physics, vol. 31, 2004, pp. 2699–2706.
• [2] T. Flohr, T. G., Stierstofer, K. Ulzhaimer, S. Ulzheimer, H. Bruder, A. N. Promak, C. H. Mc-Collough, Image reconstruction and image quality evaluation for a 64-slice CT scanner with zflying focal spot, Medical Physics, vol. 32, 2005, pp. 2536–2547.
• [3] M. Kachelrieß, M. Knaup, C. Penssel, W. A. Kalender, Flying focal spot (FFS) in cone-beam CT, IEEE Transactions on Nuclear Science, vol. 53, 2006, pp. 1238–1247.
• [4] Th. Flohr, K. Stierstofer, H. Bruder, J. Simon, A. Polacin, S. Schaller, Image reconstruction and image quality evaluation for a 16-slice CT scanner, Medical Physics, vol. 30, 2003, pp. 832–845.
• [5] M. Kachelrieß, S. Schaller, W. A. Kalender, Advanced single-slice rebinning in cone-beam spiral CT, Medical Physics, vol. 27, 2000, pp.754–773.
• [6] M. Kachelrieß;, Th. Fuchs, S. Schaller, W. A. Kalender, Advanced single-slice rebinning for tilted spiral cone-beam CT, Medical Physics, vol. 28, 2001, pp.1033–1041.
• [7] R. Cierniak, P. Pluta, A. Kaźmierczak, A practical statistical approach to the reconstruction problem using a single slice rebinning method, Journal of Artificial Intelligence and Soft Computing Research, vol. 10, 2021, pp. 137–149.
• [8] J. D. Mathews et al., Cancer risk in 680 peope expose to computed tomography scans in childhood or adolescent: data inkage study of 11 million Australians, British Medical Journal, f2360, 2013, pp. 346-360.
• [9] K. Sauer, C. Bouman, A local update strategy for iterative reconstruction from projections, IEEE Transactions on Signal Processing, vol. 41, 1993, pp. 534–548.
• [10] C. Bouman, K. Sauer, A unified approach to statistical tomography using coordinate descent optimization. IEEE Transations on Image Processing, vol. 5, 1996, pp. 480–492.
• [11] J. -B. Thibault, C. A. Bouman, K. D. Sauer, J. Hsieh, A recursive filter noise reduction in statistical iterative tomographic imaging, Proc. of SPIE-IS&T Symposium on Electronic Imaging Science and Technology–Computational Imaging, vol. 6065, 2006, pp. 15–19.
• [12] J. -B Thibault, K. D. Sauer, C. A. Bouman, J. Hsieh, A three-dimensional statistical approach to improved image quality for multislice helical CT, Med. Phys., vol. 34, 2007, pp. 4526–4544.
• [13] Y. Zhou, J.-B. Thibault, C.A. Bouman, J. Hsieh, J., K.D. Sauer, Fast model-based x-ray CT reconstruction using spatially non-homogeneous ICD optimization, IEEE Tranactions on Image Processing, vol. 20, 2011, pp. 161–175.
• [14] R. Cierniak, A new approach to image reconstruction from projections problem using a recurrent neural network, International Journal of Applied Mathematics and Computer Science, vol. 183, 2008, pp. 147–157.
• [15] R. Cierniak, New neural network algorithm for image reconstruction from fan-beam projections, Neurocomputing, vol. 72, 2009, pp. 3238–3244.
• [16] R. Cierniak, A three-dimensional neural network based approach to the image reconstruction from projections problem, Lecture Notes in Artificial Intelligence, vol. 6113, 2010, pp.505–514.
• [17] R. Cierniak, Analytical statistical reconstruction algorithm with the direct use of projections performed in spiral cone-beam scanners, In Proc. of the 5th International Meeting on Image Formation in X-Ray Computed Tomography, Salt Lake City, 2018, pp. 293–296.
• [18] R. Cierniak, A. Lorent, Comparison of algebraic and analytical approaches to the formulation of the statistical model-based reconstruction problem for x-ray computed tomography, Computerized Medical Imaging and Graphics, vol. 52, 2016, pp. 19-27.
• [19] R. Cierniak, P. Pluta, Fast statistical reconstruction algorithm for a CT scanner with flying focal spot, in Proc. of the 6th International Meeting on Image Formation in X-Ray Computed Tomography, Regensburg, 2020, pp.586-589.
• [20] R. Cierniak, P. Pluta, Statistical iterative reconstruction algorithm based on a continuous-to-continuous model formulated for spiral cone-beam CT, In Proc. of the International Conference on Computational Science (ICCS 2020), Amsterdam, 2020, LNCS 12139, pp. 613-620.
• [21] J. El Zini, Y. Rizk, M. Awad, An optimized parallel implementation of non-iteratively trained recurrent neural networks, Journal of Artificial Intelligence and Soft Computing Research, vol. 11, 2020, pp. 33–50.
• [22] X. Wang, R.D. MacDougall, C.A. Bouman, S.K. Warfield, Model-based iterative reconstruction for dual source and flying focal spot computed tomography, arXiv:2001.09471v2, 14.II.2020.

Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).