Convolutional Neural Network Based Metal Artifact Reduction in X-Ray Computed Tomography
نویسندگان
چکیده
منابع مشابه
Evaluation of Metal Artifact Reduction software in Computed Tomography
Introduction: The image quality of computed tomography (CT) can be seriously lowered by metal implants of patients. These implants are known to exert a significant impact on diagnostic accuracy due to artifacts. The current study aimed to assess the usefulness of Metal Artifact Reduction (MAR) software in the reduction of metal artifacts, in comparison to iterative rec...
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Esther Meyer1,2, Rainer Raupach2, Michael Lell3, Bernhard Schmidt2, and Marc Kachelrieß1,4 1Institute of Medical Physics, Friedrich–Alexander University of Erlangen–Nürnberg (FAU), Erlangen, Germany 2Siemens Healthcare, Forchheim, Germany 3Institute of Diagnostic Radiology, Friedrich–Alexander University of Erlangen–Nürnberg (FAU), Erlangen, Germany 4Medical Physics in Radiology, German Cance...
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PURPOSE The problem of metal artifact reduction (MAR) is almost as old as the clinical use of computed tomography itself. When metal implants are present in the field of measurement, severe artifacts degrade the image quality and the diagnostic value of CT images. Up to now, no generally accepted solution to this issue has been found. In this work, a method based on a new MAR concept is present...
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We propose a method, which treats metal artifact reduction in CT by sinogram restoration as a problem of scattered data interpolation. Corrupted sinogram entries are discarded and replaced with artificially generated values. The presented interpolation algorithm is based on the 2D non-equispaced fast Fourier transform (NFFT). Results are compared to two common polynomial interpolation schemes.
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Introduction: Cone beam computed tomography (CBCT) was introduced and became more common based on its low cost, fast image procedure rate and low radiation dose compared to CT. This imaging modality improved diagnostic and treatment-planning procedures by providing three-dimensional information with greatly reduced level of radiation dose compared to 2D dental imaging modalitie...
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ژورنال
عنوان ژورنال: IEEE Transactions on Medical Imaging
سال: 2018
ISSN: 0278-0062,1558-254X
DOI: 10.1109/tmi.2018.2823083