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10.1016/j.ejmp.2020.11.038

http://scihub22266oqcxt.onion/10.1016/j.ejmp.2020.11.038
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33440281!ä!33440281

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suck abstract from ncbi


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pmid33440281      Phys+Med 2021 ; 81 (ä): 52-59
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  • Utility of fast non-local means (FNLM) filter for detection of pulmonary nodules in chest CT for pediatric patient #MMPMID33440281
  • Shim J; Yoon M; Lee MJ; Lee Y
  • Phys Med 2021[Jan]; 81 (ä): 52-59 PMID33440281show ga
  • PURPOSE: This study was aimed to evaluate the utility based on imaging quality of the fast non-local means (FNLM) filter in diagnosing lung nodules in pediatric chest computed tomography (CT). METHODS: We retrospectively reviewed the chest CT reconstructed with both filtered back projection (FBP) and iterative reconstruction (IR) in pediatric patients with metastatic lung nodules. After applying FNLM filter with six h values (0.0001, 0.001, 0.01, 0.1, 1, and 10) to the FBP images, eight sets of images including FBP, IR, and FNLM were analyzed. The image quality of the lung nodules was evaluated objectively for coefficient of variation (COV), contrast to noise ratio (CNR), and point spread function (PSF), and subjectively for noise, sharpness, artifacts, and diagnostic acceptability. RESULTS: The COV was lowest in IR images and decreased according to increasing h values and highest with FBP images (P < 0.001). The CNR was highest with IR images, increased according to increasing h values and lowest with FBP images (P < 0.001). The PSF was lower only in FNLM filter with h value of 0.0001 or 0.001 than in IR images (P < 0.001). In subjective analysis, only images of FNLM filter with h value of 0.0001 or 0.001 rarely showed unacceptable quality and had comparable results with IR images. There were less artifacts in FNLM images with h value of 0.0001 compared with IR images (p < 0.001). CONCLUSION: FNLM filter with h values of 0.0001 allows comparable image quality with less artifacts compared with IR in diagnosing metastatic lung nodules in pediatric chest CT.
  • |Algorithms[MESH]
  • |Artifacts[MESH]
  • |Child[MESH]
  • |Humans[MESH]
  • |Multiple Pulmonary Nodules/*diagnostic imaging[MESH]
  • |Phantoms, Imaging[MESH]
  • |Radiographic Image Interpretation, Computer-Assisted/*methods[MESH]
  • |Radiography, Thoracic/*methods[MESH]
  • |Retrospective Studies[MESH]
  • |Thorax/*diagnostic imaging[MESH]


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