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Guido G, Polici M, Nacci I, Bozzi F, De Santis D, Ubaldi N, Polidori T, Zerunian M, Bracci B, Laghi A, Caruso D. Iterative Reconstruction: State-of-the-Art and Future Perspectives. J Comput Assist Tomogr 2023; 47:244-254. [PMID: 36728734 DOI: 10.1097/rct.0000000000001401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023]
Abstract
ABSTRACT Image reconstruction processing in computed tomography (CT) has evolved tremendously since its creation, succeeding at optimizing radiation dose while maintaining adequate image quality. Computed tomography vendors have developed and implemented various technical advances, such as automatic noise reduction filters, automatic exposure control, and refined imaging reconstruction algorithms.Focusing on imaging reconstruction, filtered back-projection has represented the standard reconstruction algorithm for over 3 decades, obtaining adequate image quality at standard radiation dose exposures. To overcome filtered back-projection reconstruction flaws in low-dose CT data sets, advanced iterative reconstruction algorithms consisting of either backward projection or both backward and forward projections have been developed, with the goal to enable low-dose CT acquisitions with high image quality. Iterative reconstruction techniques play a key role in routine workflow implementation (eg, screening protocols, vascular and pediatric applications), in quantitative CT imaging applications, and in dose exposure limitation in oncologic patients.Therefore, this review aims to provide an overview of the technical principles and the main clinical application of iterative reconstruction algorithms, focusing on the strengths and weaknesses, in addition to integrating future perspectives in the new era of artificial intelligence.
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Affiliation(s)
- Gisella Guido
- From the Department of Surgical Medical Sciences and Translational Medicine, Sapienza University of Rome - Radiology Unit, Sant'Andrea University Hospital, Rome, Italy
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Mohammadinejad P, Mileto A, Yu L, Leng S, Guimaraes LS, Missert AD, Jensen CT, Gong H, McCollough CH, Fletcher JG. CT Noise-Reduction Methods for Lower-Dose Scanning: Strengths and Weaknesses of Iterative Reconstruction Algorithms and New Techniques. Radiographics 2021; 41:1493-1508. [PMID: 34469209 DOI: 10.1148/rg.2021200196] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Iterative reconstruction (IR) algorithms are the most widely used CT noise-reduction method to improve image quality and have greatly facilitated radiation dose reduction within the radiology community. Various IR methods have different strengths and limitations. Because IR algorithms are typically nonlinear, they can modify spatial resolution and image noise texture in different regions of the CT image; hence traditional image-quality metrics are not appropriate to assess the ability of IR to preserve diagnostic accuracy, especially for low-contrast diagnostic tasks. In this review, the authors highlight emerging IR algorithms and CT noise-reduction techniques and summarize how these techniques can be evaluated to help determine the appropriate radiation dose levels for different diagnostic tasks in CT. In addition to advanced IR techniques, we describe novel CT noise-reduction methods based on convolutional neural networks (CNNs). CNN-based noise-reduction techniques may offer the ability to reduce image noise while maintaining high levels of image detail but may have unique drawbacks. Other novel CT noise-reduction methods are being developed to leverage spatial and/or spectral redundancy in multiphase or multienergy CT. Radiologists and medical physicists should be familiar with these different alternatives to adapt available CT technology for different diagnostic tasks. The scope of this article is (a) to review the clinical applications of IR algorithms as well as their strengths, weaknesses, and methods of assessment and (b) to explore new CT image reconstruction and noise-reduction techniques that promise to facilitate radiation dose reduction. ©RSNA, 2021.
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Affiliation(s)
- Payam Mohammadinejad
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.M., L.Y., S.L., A.D.M., H.G., C.H.M., J.G.F.); Department of Radiology, Harborview Medical Center, Seattle, Wash (A.M.); Department of Medical Imaging, Toronto General Hospital, Toronto, ON, Canada (L.S.G.); and Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.T.J.)
| | - Achille Mileto
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.M., L.Y., S.L., A.D.M., H.G., C.H.M., J.G.F.); Department of Radiology, Harborview Medical Center, Seattle, Wash (A.M.); Department of Medical Imaging, Toronto General Hospital, Toronto, ON, Canada (L.S.G.); and Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.T.J.)
| | - Lifeng Yu
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.M., L.Y., S.L., A.D.M., H.G., C.H.M., J.G.F.); Department of Radiology, Harborview Medical Center, Seattle, Wash (A.M.); Department of Medical Imaging, Toronto General Hospital, Toronto, ON, Canada (L.S.G.); and Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.T.J.)
| | - Shuai Leng
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.M., L.Y., S.L., A.D.M., H.G., C.H.M., J.G.F.); Department of Radiology, Harborview Medical Center, Seattle, Wash (A.M.); Department of Medical Imaging, Toronto General Hospital, Toronto, ON, Canada (L.S.G.); and Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.T.J.)
| | - Luis S Guimaraes
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.M., L.Y., S.L., A.D.M., H.G., C.H.M., J.G.F.); Department of Radiology, Harborview Medical Center, Seattle, Wash (A.M.); Department of Medical Imaging, Toronto General Hospital, Toronto, ON, Canada (L.S.G.); and Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.T.J.)
| | - Andrew D Missert
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.M., L.Y., S.L., A.D.M., H.G., C.H.M., J.G.F.); Department of Radiology, Harborview Medical Center, Seattle, Wash (A.M.); Department of Medical Imaging, Toronto General Hospital, Toronto, ON, Canada (L.S.G.); and Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.T.J.)
| | - Corey T Jensen
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.M., L.Y., S.L., A.D.M., H.G., C.H.M., J.G.F.); Department of Radiology, Harborview Medical Center, Seattle, Wash (A.M.); Department of Medical Imaging, Toronto General Hospital, Toronto, ON, Canada (L.S.G.); and Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.T.J.)
| | - Hao Gong
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.M., L.Y., S.L., A.D.M., H.G., C.H.M., J.G.F.); Department of Radiology, Harborview Medical Center, Seattle, Wash (A.M.); Department of Medical Imaging, Toronto General Hospital, Toronto, ON, Canada (L.S.G.); and Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.T.J.)
| | - Cynthia H McCollough
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.M., L.Y., S.L., A.D.M., H.G., C.H.M., J.G.F.); Department of Radiology, Harborview Medical Center, Seattle, Wash (A.M.); Department of Medical Imaging, Toronto General Hospital, Toronto, ON, Canada (L.S.G.); and Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.T.J.)
| | - Joel G Fletcher
- From the Department of Radiology, Mayo Clinic, 200 First St SW, Rochester, MN 55905 (P.M., L.Y., S.L., A.D.M., H.G., C.H.M., J.G.F.); Department of Radiology, Harborview Medical Center, Seattle, Wash (A.M.); Department of Medical Imaging, Toronto General Hospital, Toronto, ON, Canada (L.S.G.); and Department of Abdominal Imaging, University of Texas MD Anderson Cancer Center, Houston, Tex (C.T.J.)
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