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20th International Conference on Artificial Intelligence and Soft Computing (ICAISC)

作者： Cierniak, Robert Pluta, Piotr Czestochowa Tech Univ Dept Intelligent Comp Syst Armii Krajowej 36 PL-42200 Czestochowa Poland

ISBN: (纸本)9783030878979;9783030878962

This work is related to the originally formulated 3D statistical model-based iterative reconstruction algorithm adopted to computed tomography with flying focal spot. This new reconstruction method is based on a continuous-to-continuous data model, where the forward model is formulated as a shift invariant system. The proposed approach resembles the well-known Feldkamp (FDK) algorithm, which cannot be used with a flying focal spot scanner as the paths of the X-rays used are not equi-angularly distributed. In this situation, a so-called "nutating" reconstruction algorithm is usually used, which is based on a rebinning methodology, thus transforming the reconstruction problem to that of a parallel beam system. Our approach has some significant advantages compared with the FBP methods. Moreover, although our method belongs to the category of iterative reconstruction approaches, thanks to the fact that our proposed model is derived as a shift invariant system, it is possible to use an FFT algorithm to accelerate the calculations that have to be performed. Because of this, we can obtain diagnostic images in a time comparable to that of FBP methods. Computer simulations have shown that the reconstruction method presented here outperforms referential FBP methods with regard to the image quality obtained and can be competitive in terms of time of calculation.

关键词： Image reconstruction from projections X-ray computed tomography statistical reconstruction algorithm Flying focal spot

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Iterative statistical reconstruction algorithm Based on C-C Data Model with the Direct Use of Projections Performed in Spiral Cone-Beam CT Scanners 1

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7th International Conference on Information Technology in Biomedicine (ITIB)

作者： Cierniak, Robert Pluta, Piotr Czestochowa Tech Univ Inst Computat Intelligence Armii Krajowej 36 PL-42200 Czestochowa Poland

ISBN: (数字)9783030237622

ISBN: (纸本)9783030237622;9783030237615

This paper is concerned with the originally formulated 3D statistical model-based iterative reconstruction algorithm for spiral cone-beam x-ray tomography. The conception proposed here is based on a continuous-continuous data model, and a reconstruction problem is formulated as a shift invariant system. This algorithm significantly improves the quality of the subsequently reconstructed images, so allowing a decrease in the x-ray dose absorbed by a patient. The analytical roots of the algorithm proposed here permit a decrease in the complexity of the reconstruction problem in comparison with other model-based iterative approaches. In this paper, we proved that this statistical approach, originally formulated for parallel beam geometry, can be adapted for helical cone-beam geometry of scanner, with the direct use of projections. Computer simulations have shown that the reconstruction algorithm presented here outperforms conventional analytical methods with regard to the image quality obtained.

关键词： Image reconstruction from projections X-ray computed tomography statistical reconstruction algorithm

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Parallel Realizations of the Iterative statistical reconstruction algorithm for 3D Computed Tomography 16th

Parallel Realizations of the Iterative Statistical Reconstru...

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16th International Conference on Artificial Intelligence and Soft Computing (ICAISC)

作者： Cierniak, Robert Bilski, Jaroslaw Smolag, Jacek Pluta, Piotr Shah, Nimit Czestochowa Tech Univ Inst Computat Intelligence Armii Krajowej 36 PL-42200 Czestochowa Poland Maharaja Sayajirao Univ Baroda Dept Elect Engn Vadodara India

ISBN: (纸本)9783319590639;9783319590622

The presented paper describes a parallel realization of an approach to the reconstruction problem for 3D spiral x-ray tomography. The reconstruction problem is formulated taking into consideration the statistical properties of signals obtained by x-ray CT and the analytical methodology of image processing. The concept shown here significantly accelerates calculations performed during iterative reconstruction process in the formulated algorithm. Computer simulations have been performed which prove that the reconstruction algorithm described here, does indeed significantly outperform conventional analytical methods in the quality of the images obtained.

关键词： Image reconstruction from projections X-ray computed tomography statistical reconstruction algorithm Parallel computation

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Comparison of algebraic and analytical approaches to the formulation of the statistical model-based reconstruction problem for X-ray computed tomography

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COMPUTERIZED MEDICAL IMAGING AND GRAPHICS 2016年 52卷 19-27页

作者： Cierniak, Robert Lorent, Anna Czestochowa Tech Univ Inst Computat Intelligence Armii Krajowej 36 PL-42200 Czestochowa Poland

The main aim of this paper is to investigate properties of our originally formulated statistical model-based iterative approach applied to the image reconstruction from projections problem which are related to its conditioning, and, in this manner, to prove a superiority of this approach over ones recently used by other authors. The reconstruction algorithm based on this conception uses a maximum likelihood estimation with an objective adjusted to the probability distribution of measured signals obtained from an X-ray computed tomography system with parallel beam geometry. The analysis and experimental results presented here show that our analytical approach outperforms the referential algebraic methodology which is explored widely in the literature and exploited in various commercial implementations. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Image reconstruction from projections X-ray computed tomography statistical reconstruction algorithm

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Regularization Methods for the Analytical statistical reconstruction Problem in Medical Computed Tomography 15th

Regularization Methods for the Analytical Statistical Recons...

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15th International Conference on Artificial Intelligence and Soft Computing (ICAISC)

作者： Cierniak, Robert Lorent, Anna Pluta, Piotr Shah, Nimit Czestochowa Tech Univ Inst Computat Intelligence Armii Krajowej 36 PL-42200 Czestochowa Poland Maharaja Sayajirao Univ Baroda Dept Elect Engn Vadodara India

ISBN: (纸本)9783319393841

The main purpose of this paper is to present the properties of our novel statistical model-based iterative approach to the image reconstruction from projections problem regarding its condition number. The reconstruction algorithm based on this concept uses a maximum likelihood estimation with an objective adjusted to the probability distribution of measured signals obtained using x-ray computed tomography. We compare this with some selected methods of regularizing the problem. The concept presented here is fundamental for 3D statistical tailored reconstruction methods designed for x-ray computed tomography.

关键词： Image reconstruction from projections X-ray computed tomography statistical reconstruction algorithm Overfitting Regularization

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AN ANALYTICAL ITERATIVE statistical algorithm FOR IMAGE reconstruction FROM PROJECTIONS

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INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE 2014年第1期24卷 7-17页

作者： Cierniak, Robert Czestochowa Tech Univ Inst Computat Intelligence PL-42200 Czestochowa Poland

The main purpose of the paper is to present a statistical model-based iterative approach to the problem of image reconstruction from projections. This originally formulated reconstruction algorithm is based on a maximum likelihood method with an objective adjusted to the probability distribution of measured signals obtained from an x-ray computed tomograph with parallel beam geometry. Various forms of objectives are tested. Experimental results show that an objective that is exactly tailored statistically yields the best results, and that the proposed reconstruction algorithm reconstructs an image with better quality than a conventional algorithm with convolution and back-projection.

关键词： computed tomography image reconstruction from projections statistical reconstruction algorithm

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Analytical statistical Approach for Fan-Beam Scanners 5th

Analytical Statistical Approach for Fan-Beam Scanners

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5th International Conference on Information Technologies in Biomedicine (ITIB)

作者： Cierniak, Robert Czestochowa Tech Univ Armii Krajowej 36 Czestochowa Poland

ISBN: (纸本)9783319397962;9783319397955

The main topic of this paper is strictly concerned with the 3D reconstruction algorithm for spiral cone-beam x-ray tomography. The approach proposed here is based on a fully analytical formulation of the reconstruction problem. This method can be classed as a statistical reconstruction method, which significantly improves the quality of the subsequently reconstructed images, so allowing a decrease in the x-ray dose absorbed by a patient during examination. In this paper, we proved that this statistical approach, originally formulated for parallel beam geometry, can be adapted for fan-beam geometry of scanner, with the direct use of projections, and consequently for helical cone-beam scanners. Computer simulations have shown that the reconstruction algorithm presented here outperforms conventional analytical methods with regard to the image quality obtained.

关键词： Image reconstruction from projections X-ray computed tomography statistical reconstruction algorithm

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