State-of-the-Art Deep Learning CT Reconstruction Algorithms in Abdominal Imaging.

Autor: Mileto A; From the Department of Radiology, University of Washington School of Medicine, Seattle, Wash (A.M.); Department of Radiology, Mayo Clinic, Rochester, Minn (L.Y.); Department of Radiology, New York University Grossman School of Medicine, NYU Langone Health, New York, NY (J.W.R.); Departments of Radiation Oncology (S.K.) and Abdominal Imaging (M.A.S., J.J.I.R., V.K.W., K.M.E., C.T.J.), The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; Department of Radiology, Texas Children's Hospital, Houston, Tex (A.M.R.C.); and Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea (J.M.L.)., Yu L; From the Department of Radiology, University of Washington School of Medicine, Seattle, Wash (A.M.); Department of Radiology, Mayo Clinic, Rochester, Minn (L.Y.); Department of Radiology, New York University Grossman School of Medicine, NYU Langone Health, New York, NY (J.W.R.); Departments of Radiation Oncology (S.K.) and Abdominal Imaging (M.A.S., J.J.I.R., V.K.W., K.M.E., C.T.J.), The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; Department of Radiology, Texas Children's Hospital, Houston, Tex (A.M.R.C.); and Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea (J.M.L.)., Revels JW; From the Department of Radiology, University of Washington School of Medicine, Seattle, Wash (A.M.); Department of Radiology, Mayo Clinic, Rochester, Minn (L.Y.); Department of Radiology, New York University Grossman School of Medicine, NYU Langone Health, New York, NY (J.W.R.); Departments of Radiation Oncology (S.K.) and Abdominal Imaging (M.A.S., J.J.I.R., V.K.W., K.M.E., C.T.J.), The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; Department of Radiology, Texas Children's Hospital, Houston, Tex (A.M.R.C.); and Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea (J.M.L.)., Kamel S; From the Department of Radiology, University of Washington School of Medicine, Seattle, Wash (A.M.); Department of Radiology, Mayo Clinic, Rochester, Minn (L.Y.); Department of Radiology, New York University Grossman School of Medicine, NYU Langone Health, New York, NY (J.W.R.); Departments of Radiation Oncology (S.K.) and Abdominal Imaging (M.A.S., J.J.I.R., V.K.W., K.M.E., C.T.J.), The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; Department of Radiology, Texas Children's Hospital, Houston, Tex (A.M.R.C.); and Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea (J.M.L.)., Shehata MA; From the Department of Radiology, University of Washington School of Medicine, Seattle, Wash (A.M.); Department of Radiology, Mayo Clinic, Rochester, Minn (L.Y.); Department of Radiology, New York University Grossman School of Medicine, NYU Langone Health, New York, NY (J.W.R.); Departments of Radiation Oncology (S.K.) and Abdominal Imaging (M.A.S., J.J.I.R., V.K.W., K.M.E., C.T.J.), The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; Department of Radiology, Texas Children's Hospital, Houston, Tex (A.M.R.C.); and Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea (J.M.L.)., Ibarra-Rovira JJ; From the Department of Radiology, University of Washington School of Medicine, Seattle, Wash (A.M.); Department of Radiology, Mayo Clinic, Rochester, Minn (L.Y.); Department of Radiology, New York University Grossman School of Medicine, NYU Langone Health, New York, NY (J.W.R.); Departments of Radiation Oncology (S.K.) and Abdominal Imaging (M.A.S., J.J.I.R., V.K.W., K.M.E., C.T.J.), The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; Department of Radiology, Texas Children's Hospital, Houston, Tex (A.M.R.C.); and Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea (J.M.L.)., Wong VK; From the Department of Radiology, University of Washington School of Medicine, Seattle, Wash (A.M.); Department of Radiology, Mayo Clinic, Rochester, Minn (L.Y.); Department of Radiology, New York University Grossman School of Medicine, NYU Langone Health, New York, NY (J.W.R.); Departments of Radiation Oncology (S.K.) and Abdominal Imaging (M.A.S., J.J.I.R., V.K.W., K.M.E., C.T.J.), The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; Department of Radiology, Texas Children's Hospital, Houston, Tex (A.M.R.C.); and Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea (J.M.L.)., Roman-Colon AM; From the Department of Radiology, University of Washington School of Medicine, Seattle, Wash (A.M.); Department of Radiology, Mayo Clinic, Rochester, Minn (L.Y.); Department of Radiology, New York University Grossman School of Medicine, NYU Langone Health, New York, NY (J.W.R.); Departments of Radiation Oncology (S.K.) and Abdominal Imaging (M.A.S., J.J.I.R., V.K.W., K.M.E., C.T.J.), The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; Department of Radiology, Texas Children's Hospital, Houston, Tex (A.M.R.C.); and Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea (J.M.L.)., Lee JM; From the Department of Radiology, University of Washington School of Medicine, Seattle, Wash (A.M.); Department of Radiology, Mayo Clinic, Rochester, Minn (L.Y.); Department of Radiology, New York University Grossman School of Medicine, NYU Langone Health, New York, NY (J.W.R.); Departments of Radiation Oncology (S.K.) and Abdominal Imaging (M.A.S., J.J.I.R., V.K.W., K.M.E., C.T.J.), The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; Department of Radiology, Texas Children's Hospital, Houston, Tex (A.M.R.C.); and Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea (J.M.L.)., Elsayes KM; From the Department of Radiology, University of Washington School of Medicine, Seattle, Wash (A.M.); Department of Radiology, Mayo Clinic, Rochester, Minn (L.Y.); Department of Radiology, New York University Grossman School of Medicine, NYU Langone Health, New York, NY (J.W.R.); Departments of Radiation Oncology (S.K.) and Abdominal Imaging (M.A.S., J.J.I.R., V.K.W., K.M.E., C.T.J.), The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; Department of Radiology, Texas Children's Hospital, Houston, Tex (A.M.R.C.); and Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea (J.M.L.)., Jensen CT; From the Department of Radiology, University of Washington School of Medicine, Seattle, Wash (A.M.); Department of Radiology, Mayo Clinic, Rochester, Minn (L.Y.); Department of Radiology, New York University Grossman School of Medicine, NYU Langone Health, New York, NY (J.W.R.); Departments of Radiation Oncology (S.K.) and Abdominal Imaging (M.A.S., J.J.I.R., V.K.W., K.M.E., C.T.J.), The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Unit 1473, Houston, TX 77030-4009; Department of Radiology, Texas Children's Hospital, Houston, Tex (A.M.R.C.); and Department of Radiology, Seoul National University College of Medicine, Seoul, South Korea (J.M.L.).
Jazyk: angličtina
Zdroj: Radiographics : a review publication of the Radiological Society of North America, Inc [Radiographics] 2024 Dec; Vol. 44 (12), pp. e240095.
DOI: 10.1148/rg.240095
Abstrakt: The implementation of deep neural networks has spurred the creation of deep learning reconstruction (DLR) CT algorithms. DLR CT techniques encompass a spectrum of deep learning-based methodologies that operate during the different steps of the image creation, prior to or after the traditional image formation process (eg, filtered backprojection [FBP] or iterative reconstruction [IR]), or alternatively by fully replacing FBP or IR techniques. DLR algorithms effectively facilitate the reduction of image noise associated with low photon counts from reduced radiation dose protocols. DLR methods have emerged as an effective solution to ameliorate limitations observed with prior CT image reconstruction algorithms, including FBP and IR algorithms, which are not able to preserve image texture and diagnostic performance at low radiation dose levels. An additional advantage of DLR algorithms is their high reconstruction speed, hence targeting the ideal triad of features for a CT image reconstruction (ie, the ability to consistently provide diagnostic-quality images and achieve radiation dose imaging levels as low as reasonably possible, with high reconstruction speed). An accumulated body of evidence supports the clinical use of DLR algorithms in abdominal imaging across multiple CT imaging tasks. The authors explore the technical aspects of DLR CT algorithms and examine various approaches to image synthesis in DLR creation. The clinical applications of DLR algorithms are highlighted across various abdominal CT imaging domains, with emphasis on the supporting evidence for diverse clinical tasks. An overview of the current limitations of and outlook for DLR algorithms for CT is provided. © RSNA, 2024.
Databáze: MEDLINE
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