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Xia Y, Zhang L, Xing Y, Chen Z, Gao H. Generalized-equiangular geometry CT: Concept and shift-invariant FBP algorithms. Med Phys 2023; 50:5150-5165. [PMID: 37379056 DOI: 10.1002/mp.16560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/12/2022] [Revised: 04/05/2023] [Accepted: 05/19/2023] [Indexed: 06/29/2023] Open
Abstract
BACKGROUND With advanced x-ray source and detector technologies being continuously developed, non-traditional CT geometries have been widely explored. Generalized-Equiangular Geometry CT (GEGCT) architecture, in which an x-ray source might be positioned radially far away from the focus of arced detector array that is equiangularly spaced, is of importance in many novel CT systems and designs. PURPOSE GEGCT, unfortunately, has no theoretically exact and shift-invariant analytical image reconstruction algorithm in general. In this study, to obtain fast and accurate reconstruction from GEGCT and to promote its system design and optimization, an in-depth investigation on a group of approximate Filtered Back-Projection (FBP) algorithms with a variety of weighting strategies has been conducted. METHODS The architecture of GEGCT is first presented and characterized by using a normalized-radial-offset distance (NROD). Next, shift-invariant weighted FBP-type algorithms are derived in a unified framework, with pre-filtering, filtering, and post-filtering weights, for both fixed and dynamic NROD configurations. Three viable weighting strategies are then presented including a classic one developed by Besson in the literature and two new ones generated from a curvature fitting and from an empirical formula, where all of the three weights can be expressed as certain functions of NROD. After that, an analysis of reconstruction accuracy is conducted with a wide range of NROD. Finally, the weighted FBP algorithm for GEGCT is extended to a three-dimensional form in the case of cone-beam scan with a cylindrical detector array. RESULTS Theoretical analysis and numerical study show that weights in the shift-invariant FBP algorithms can guarantee highly accurate reconstruction for GEGCT. A simulation of Shepp-Logan phantom and a GEGCT scan of lung mimicked by using a clinical lung CT dataset both demonstrate that FBP reconstructions with Besson and polynomial weights can achieve excellent image quality, with Peak Signal to Noise Ratio and Structural Similarity being at the same level as that from the standard equiangular fan-beam CT scan. Reconstruction of a cylinder object with multiple contrasts from simulated GEGCT scan with dynamic NROD is also highly consistent with fixed ones when using the Besson and polynomial weights, with root mean square error less than 7 hounsfield units, demonstrating the robustness and flexibility of the presented FBP algorithms. In terms of resolution, the direct FBP methods for GEGCT could achieve 1.35 lp/mm of spatial resolution at 10% modulation transfer functions point, higher than that of the rebinning method which can only reach 1.14 lp/mm. Moreover, 3D reconstructions of a disc phantom reveal that a greater value of NROD for GEGCT will bring less cone beam artifacts as expected. CONCLUSIONS We propose the concept of GEGCT and investigate the feasibility of using shift-invariant weighted FBP-type algorithms for reconstruction from GEGCT data without rebinning. A comprehensive analysis and phantom studies have been conducted to validate the effectiveness of proposed weighting strategies in a wide range of NROD for GEGCT with fixed and dynamic NROD.
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Affiliation(s)
- Yingxian Xia
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging, Tsinghua University, Ministry of Education, Beijing, China
| | - Li Zhang
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging, Tsinghua University, Ministry of Education, Beijing, China
| | - Yuxiang Xing
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging, Tsinghua University, Ministry of Education, Beijing, China
| | - Zhiqiang Chen
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging, Tsinghua University, Ministry of Education, Beijing, China
| | - Hewei Gao
- Department of Engineering Physics, Tsinghua University, Beijing, China
- Key Laboratory of Particle & Radiation Imaging, Tsinghua University, Ministry of Education, Beijing, China
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Bhat SS, Fernandes TT, Poojar P, Silva Ferreira M, Rao PC, Hanumantharaju MC, Ogbole G, Nunes RG, Geethanath S. Low‐Field MRI of Stroke: Challenges and Opportunities. J Magn Reson Imaging 2020; 54:372-390. [DOI: 10.1002/jmri.27324] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2020] [Revised: 07/24/2020] [Accepted: 07/27/2020] [Indexed: 12/12/2022] Open
Affiliation(s)
- Seema S. Bhat
- Medical Imaging Research Centre Dayananda Sagar College of Engineering Bangalore India
| | - Tiago T. Fernandes
- Institute for Systems and Robotics and Department of Bioengineering, Instituto Superior Técnico Universidade de Lisboa Lisbon Portugal
| | - Pavan Poojar
- Medical Imaging Research Centre Dayananda Sagar College of Engineering Bangalore India
- Columbia University Magnetic Resonance Research Center New York New York USA
| | - Marta Silva Ferreira
- Institute for Systems and Robotics and Department of Bioengineering, Instituto Superior Técnico Universidade de Lisboa Lisbon Portugal
| | - Padma Chennagiri Rao
- Medical Imaging Research Centre Dayananda Sagar College of Engineering Bangalore India
| | | | - Godwin Ogbole
- Department of Radiology, College of Medicine University of Ibadan Ibadan Nigeria
| | - Rita G. Nunes
- Institute for Systems and Robotics and Department of Bioengineering, Instituto Superior Técnico Universidade de Lisboa Lisbon Portugal
| | - Sairam Geethanath
- Medical Imaging Research Centre Dayananda Sagar College of Engineering Bangalore India
- Columbia University Magnetic Resonance Research Center New York New York USA
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FitzGerald P, Bennett J, Carr J, Edic PM, Entrikin D, Gao H, Iatrou M, Jin Y, Liu B, Wang G, Wang J, Yin Z, Yu H, Zeng K, De Man B. Cardiac CT: A system architecture study. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2016; 24:43-65. [PMID: 26890906 PMCID: PMC7017544 DOI: 10.3233/xst-160537] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/10/2023]
Abstract
BACKGROUND We are interested in exploring dedicated, high-performance cardiac CT systems optimized to provide the best tradeoff between system cost, image quality, and radiation dose. OBJECTIVE We sought to identify and evaluate a broad range of CT architectures that could provide an optimal, dedicated cardiac CT solution. METHODS We identified and evaluated thirty candidate architectures using consistent design choices. We defined specific evaluation metrics related to cost and performance. We then scored the candidates versus the defined metrics. Lastly, we applied a weighting system to combine scores for all metrics into a single overall score for each architecture. CT experts with backgrounds in cardiovascular radiology, x-ray physics, CT hardware and CT algorithms performed the scoring and weighting. RESULTS We found nearly a twofold difference between the most and the least promising candidate architectures. Architectures employed by contemporary commercial diagnostic CT systems were among the highest-scoring candidates. We identified six architectures that show sufficient promise to merit further in-depth analysis and comparison. CONCLUSION Our results suggest that contemporary diagnostic CT system architectures outperform most other candidates that we evaluated, but the results for a few alternatives were relatively close. We selected six representative high-scoring candidates for more detailed design and further comparative evaluation.
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Affiliation(s)
- Paul FitzGerald
- CT Systems and Applications Laboratory, GE Global Research Center, 1 Research Circle, Niskayuna, NY, USA
- Corresponding author: Paul FitzGerald, 1 Research Circle, Niskayuna, NY 12309, USA. Tel.: +1 518 387 7752; Fax: +1 518 387 5975;
| | - James Bennett
- Biomedical Imaging Division, VT-WFU School of Biomedical Engineering and Sciences, Virginia Tech., Blacksburg, VA, USA
| | - Jeffrey Carr
- Department of Radiology, Division of Radiologic Sciences, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Peter M. Edic
- CT Systems and Applications Laboratory, GE Global Research Center, 1 Research Circle, Niskayuna, NY, USA
| | - Daniel Entrikin
- Department of Radiology, Division of Radiologic Sciences, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Hewei Gao
- CT Systems and Applications Laboratory, GE Global Research Center, 1 Research Circle, Niskayuna, NY, USA
| | - Maria Iatrou
- CT Systems and Applications Laboratory, GE Global Research Center, 1 Research Circle, Niskayuna, NY, USA
| | - Yannan Jin
- CT Systems and Applications Laboratory, GE Global Research Center, 1 Research Circle, Niskayuna, NY, USA
| | - Baodong Liu
- Department of Radiology, Division of Radiologic Sciences, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Biomedical Imaging Division, VT-WFU School of Biomedical Engineering and Sciences, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Ge Wang
- Biomedical Imaging Division, VT-WFU School of Biomedical Engineering and Sciences, Virginia Tech., Blacksburg, VA, USA
- Biomedical Imaging Division, VT-WFU School of Biomedical Engineering and Sciences, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA
| | - Jiao Wang
- CT Systems and Applications Laboratory, GE Global Research Center, 1 Research Circle, Niskayuna, NY, USA
| | - Zhye Yin
- CT Systems and Applications Laboratory, GE Global Research Center, 1 Research Circle, Niskayuna, NY, USA
| | - Hengyong Yu
- Department of Radiology, Division of Radiologic Sciences, Wake Forest University Health Sciences, Winston-Salem, NC, USA
- Biomedical Imaging Division, VT-WFU School of Biomedical Engineering and Sciences, Wake Forest University Health Sciences, Winston-Salem, NC, USA
| | - Kai Zeng
- CT Systems and Applications Laboratory, GE Global Research Center, 1 Research Circle, Niskayuna, NY, USA
| | - Bruno De Man
- CT Systems and Applications Laboratory, GE Global Research Center, 1 Research Circle, Niskayuna, NY, USA
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