Search alternatives:
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
bins decrease » point decrease (Expand Search), sizes decrease (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), mean decrease (Expand Search)
significant decrease » significant increase (Expand Search), significantly increased (Expand Search)
bins decrease » point decrease (Expand Search), sizes decrease (Expand Search)
nn decrease » _ decrease (Expand Search), a decrease (Expand Search), mean decrease (Expand Search)
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2481
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2483
Evaluation results.
Published 2024“…Evaluation metrics including signal-to-noise ratio (SNR), linearity of attenuation profiles, root mean square error (RMSE), and area under the curve (AUC) were employed to assess the energy and material-density images with and without metal inserts. Results show decreased metal artefacts and a better signal-to-noise ratio (up to 25%) with increased energy bins as compared to reference data. …”
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2484
Dataset with steel insert.
Published 2024“…Evaluation metrics including signal-to-noise ratio (SNR), linearity of attenuation profiles, root mean square error (RMSE), and area under the curve (AUC) were employed to assess the energy and material-density images with and without metal inserts. Results show decreased metal artefacts and a better signal-to-noise ratio (up to 25%) with increased energy bins as compared to reference data. …”
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2485
Reference dataset.
Published 2024“…Evaluation metrics including signal-to-noise ratio (SNR), linearity of attenuation profiles, root mean square error (RMSE), and area under the curve (AUC) were employed to assess the energy and material-density images with and without metal inserts. Results show decreased metal artefacts and a better signal-to-noise ratio (up to 25%) with increased energy bins as compared to reference data. …”
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2486
Dataset with aluminium insert.
Published 2024“…Evaluation metrics including signal-to-noise ratio (SNR), linearity of attenuation profiles, root mean square error (RMSE), and area under the curve (AUC) were employed to assess the energy and material-density images with and without metal inserts. Results show decreased metal artefacts and a better signal-to-noise ratio (up to 25%) with increased energy bins as compared to reference data. …”
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2487
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2488
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2489
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2490
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2491
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2492
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2493
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2494
Assessing Bivalves as Biomonitors of Per- and Polyfluoroalkyl Substances in Coastal Environments
Published 2025Subjects: -
2495
Temperature-dependent parameter values under stable temperatures conditions.
Published 2025Subjects: -
2496
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2497
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2498
Project the global leukemia burden in patients younger and older than 20 years.
Published 2025Subjects: -
2499
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2500