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Updated: Jun 6, 2025

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在腹部成像中最先进的深度学习CT重建算法

Achille Mileto1, Lifeng Yu1, Jonathan W Revels1

  • 1From 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.).

Radiographics : a review publication of the Radiological Society of North America, Inc
|November 29, 2024
PubMed
概括

深度学习重建 (DLR) CT算法提高图像质量和降低噪音,特别是在低辐射剂量下. 这些先进的方法提供更快的重建速度,同时保持腹部成像诊断性能.

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