Showing 541 - 560 results of 29,602 for search '(( 50 ((we decrease) OR (((nn decrease) OR (a decrease)))) ) OR ( a web decrease ))', query time: 0.89s Refine Results
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    Evaluation index results for the JS-10 phantom. by Masakazu Tsujimoto (22339504)

    Published 2025
    “…In conclusion, accurate SUV measurement with ¹²³I-MIBG requires an acquisition time of ≥50 s/view, an SI product of approximately 120, and a Gaussian filter of 10 − 12 mm. …”
  9. 549

    NEMA IEC body phantom. by Masakazu Tsujimoto (22339504)

    Published 2025
    “…In conclusion, accurate SUV measurement with ¹²³I-MIBG requires an acquisition time of ≥50 s/view, an SI product of approximately 120, and a Gaussian filter of 10 − 12 mm. …”
  10. 550

    Relationship between contrast, noise, and CNR. by Masakazu Tsujimoto (22339504)

    Published 2025
    “…In conclusion, accurate SUV measurement with ¹²³I-MIBG requires an acquisition time of ≥50 s/view, an SI product of approximately 120, and a Gaussian filter of 10 − 12 mm. …”
  11. 551

    JS-10 phantom. by Masakazu Tsujimoto (22339504)

    Published 2025
    “…In conclusion, accurate SUV measurement with ¹²³I-MIBG requires an acquisition time of ≥50 s/view, an SI product of approximately 120, and a Gaussian filter of 10 − 12 mm. …”
  12. 552

    The raw data used for the analyses in this study. by Masakazu Tsujimoto (22339504)

    Published 2025
    “…In conclusion, accurate SUV measurement with ¹²³I-MIBG requires an acquisition time of ≥50 s/view, an SI product of approximately 120, and a Gaussian filter of 10 − 12 mm. …”
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    A Case Study and Methodology for OpenSWATH Parameter Optimization Using the ProCan90 Data Set and 45 810 Computational Analysis Runs by Sean Peters (1490623)

    Published 2019
    “…For the compute poor parameter set, we find a 55% improvement in the run time from the default parameter set, at the expense of a 3.4% decrease in the number of quality protein identifications, and an intensity CV decrease from 14.0% to 13.7%.…”
  20. 560

    A Case Study and Methodology for OpenSWATH Parameter Optimization Using the ProCan90 Data Set and 45 810 Computational Analysis Runs by Sean Peters (1490623)

    Published 2019
    “…For the compute poor parameter set, we find a 55% improvement in the run time from the default parameter set, at the expense of a 3.4% decrease in the number of quality protein identifications, and an intensity CV decrease from 14.0% to 13.7%.…”