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Wang W, Xia XG, He C, Ren Z, Lu J. A new weighting scheme for arc based circle cone-beam CT reconstruction. JOURNAL OF X-RAY SCIENCE AND TECHNOLOGY 2022; 30:145-163. [PMID: 34897109 DOI: 10.3233/xst-211000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
In this paper, we present an arc based fan-beam computed tomography (CT) reconstruction algorithm by applying Katsevich's helical CT image reconstruction formula to 2D fan-beam CT scanning data. Specifically, we propose a new weighting function to deal with the redundant data. Our weighting function ϖ(x_,λ) is an average of two characteristic functions, where each characteristic function indicates whether the projection data of the scanning angle contributes to the intensity of the pixel x_. In fact, for every pixel x_, our method uses the projection data of two scanning angle intervals to reconstruct its intensity, where one interval contains the starting angle and another contains the end angle. Each interval corresponds to a characteristic function. By extending the fan-beam algorithm to the circle cone-beam geometry, we also obtain a new circle cone-beam CT reconstruction algorithm. To verify the effectiveness of our method, the simulated experiments are performed for 2D fan-beam geometry with straight line detectors and 3D circle cone-beam geometry with flat-plan detectors, where the simulated sinograms are generated by the open-source software "ASTRA toolbox." We compare our method with the other existing algorithms. Our experimental results show that our new method yields the lowest root-mean-square-error (RMSE) and the highest structural-similarity (SSIM) for both reconstructed 2D and 3D fan-beam CT images.
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Affiliation(s)
- Wei Wang
- School of Biomedical Engineering, Shenzhen University, Shenzhen, Guangdong, China
| | - Xiang-Gen Xia
- Department of Electrical and Computer Engineering, University of Delaware, Newark, DE, USA
| | - Chuanjiang He
- College of Mathematics and Statistics, Chongqing University, Chongqing, China
| | - Zemin Ren
- College of Mathematics and Physics, Chongqing University of Science and Technology, Chongqing, China
| | - Jian Lu
- Shenzhen Key Laboratory of Advanced Machine Learning and Applications, Shenzhen University, Shenzhen, Guangdong, China
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Hua CH, Vern-Gross TZ, Hess CB, Olch AJ, Alaei P, Sathiaseelan V, Deng J, Ulin K, Laurie F, Gopalakrishnan M, Esiashvili N, Wolden SL, Krasin MJ, Merchant TE, Donaldson SS, FitzGerald TJ, Constine LS, Hodgson DC, Haas-Kogan DA, Mahajan A, Laack N, Marcus KJ, Taylor PA, Ahern VA, Followill DS, Buchsbaum JC, Breneman JC, Kalapurakal JA. Practice patterns and recommendations for pediatric image-guided radiotherapy: A Children's Oncology Group report. Pediatr Blood Cancer 2020; 67:e28629. [PMID: 32776500 PMCID: PMC7774502 DOI: 10.1002/pbc.28629] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/05/2020] [Revised: 06/16/2020] [Accepted: 07/19/2020] [Indexed: 12/18/2022]
Abstract
This report by the Radiation Oncology Discipline of Children's Oncology Group (COG) describes the practice patterns of pediatric image-guided radiotherapy (IGRT) based on a member survey and provides practice recommendations accordingly. The survey comprised of 11 vignettes asking clinicians about their recommended treatment modalities, IGRT preferences, and frequency of in-room verification. Technical questions asked physicists about imaging protocols, dose reduction, setup correction, and adaptive therapy. In this report, the COG Radiation Oncology Discipline provides an IGRT modality/frequency decision tree and the expert guidelines for the practice of ionizing image guidance in pediatric radiotherapy patients.
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Affiliation(s)
- Chia-ho Hua
- Department of Radiation Oncology, St. Jude Children’s Research Hospital, Memphis, Tennessee
| | | | - Clayton B. Hess
- Department of Radiation Oncology, Massachusetts General Hospital, Boston, Massachusetts
- Department of Radiation Oncology, Emory University, Atlanta, Georgia
| | - Arthur J. Olch
- Department of Radiation Oncology, University of Southern California and Children’s Hospital of Los Angeles, Los Angeles, California
| | - Parham Alaei
- Department of Radiation Oncology, University of Minnesota, Minneapolis, Minnesota
| | | | - Jun Deng
- Department of Therapeutic Radiology, Yale University, New Haven, Connecticut
| | - Kenneth Ulin
- Department of Radiation Oncology, University of Massachusetts, Worcester, Massachusetts
| | - Fran Laurie
- Department of Radiation Oncology, University of Massachusetts, Worcester, Massachusetts
| | | | - Natia Esiashvili
- Department of Radiation Oncology, Emory University, Atlanta, Georgia
| | - Suzanne L. Wolden
- Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Matthew J. Krasin
- Department of Radiation Oncology, St. Jude Children’s Research Hospital, Memphis, Tennessee
| | - Thomas E Merchant
- Department of Radiation Oncology, St. Jude Children’s Research Hospital, Memphis, Tennessee
| | - Sarah S. Donaldson
- Department of Radiation Oncology, Stanford University, Stanford, California
| | - Thomas J. FitzGerald
- Department of Radiation Oncology, University of Massachusetts, Worcester, Massachusetts
| | - Louis S. Constine
- Department of Radiation Oncology, University of Rochester, Rochester, New York
| | - David C. Hodgson
- Department of Radiation Oncology, University of Toronto, Toronto, Ontario, Canada
| | - Daphne A. Haas-Kogan
- Department of Radiation Oncology, Dana Farber Cancer Institute/Boston Children’s Hospital, Boston, Massachusetts
| | - Anita Mahajan
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota
| | - Nadia Laack
- Department of Radiation Oncology, Mayo Clinic, Rochester, Minnesota
| | - Karen J. Marcus
- Department of Radiation Oncology, Dana Farber Cancer Institute/Boston Children’s Hospital, Boston, Massachusetts
| | - Paige A Taylor
- Department of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Verity A Ahern
- Department of Radiation Oncology, Children’s Hospital at Westmead, Sydney, Australia
| | - David S. Followill
- Department of Radiation Physics, Division of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Jeffrey C. Buchsbaum
- Division of Cancer Treatment and Diagnosis, National Cancer Institute, Bethesda, Maryland
| | - John C. Breneman
- Department of Radiation Oncology, University of Cincinnati, Cincinnati, Ohio
| | - John A. Kalapurakal
- Department of Radiation Oncology, Northwestern University, Chicago, Illinois
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Matenine D, Kachelriess M, Després P, de Guise JA, Schmittbuhl M. Potential of iterative reconstruction for maxillofacial cone beam CT imaging: technical note. Neuroradiology 2020; 62:1511-1514. [PMID: 32556404 DOI: 10.1007/s00234-020-02467-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 05/27/2020] [Indexed: 11/26/2022]
Abstract
Iterative reconstruction has been proven to be an effective tool for low-dose computed tomography imaging. However, this technology is currently not available in commercial diagnostic maxillofacial cone beam CT. For this technical note, an iterative reconstruction technique was applied to cone beam CT raw data of two maxillofacial clinical cases to explore its potential for dose reduction and metal artifact reduction. Low-dose imaging was emulated by using only fractions of the clinical projection dataset. The reconstruction algorithms tested were filtered backprojection (FBP) as a reference method, and a total variation minimization (TV) regularized ordered subsets convex (OSC-TV) method as the iterative technique. Upon qualitative examination, the OSC-TV technique was found to conserve most diagnostic information using half the projections. Test images have also shown that at 1/4 of the projections, OSC-TV was more robust than FBP with respect to streaking and metal artifacts.
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Affiliation(s)
- Dmitri Matenine
- Laboratoire de recherche en imagerie et orthopédie, Centre de recherche du Centre hospitalier de l'Université de Montréal, 900 St-Denis, Montréal, QC, H2X 0A9, Canada.
- Département de génie des systèmes, École de technologie supérieure, Montréal, QC, H3C 1K3, Canada.
| | - Marc Kachelriess
- German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120, Heidelberg, Germany
- Ruprecht-Karls-University Heidelberg, Im Neuenheimer Feld 672, 69120, Heidelberg, Germany
| | - Philippe Després
- Département de physique, de génie physique et d'optique and Centre de recherche sur le cancer, Université Laval, Québec, QC, G1V 0A6, Canada
- Département de radio-oncologie, Centre de recherche du CHU de Québec, Québec, QC, G1R 2J6, Canada
| | - Jacques A de Guise
- Laboratoire de recherche en imagerie et orthopédie, Centre de recherche du Centre hospitalier de l'Université de Montréal, 900 St-Denis, Montréal, QC, H2X 0A9, Canada
- Département de génie des systèmes, École de technologie supérieure, Montréal, QC, H3C 1K3, Canada
| | - Matthieu Schmittbuhl
- Laboratoire de recherche en imagerie et orthopédie, Centre de recherche du Centre hospitalier de l'Université de Montréal, 900 St-Denis, Montréal, QC, H2X 0A9, Canada
- Faculté de médecine dentaire, Université de Montréal, Montréal, QC, H3T 1J4, Canada
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