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Monte Carlo reference data sets for imaging research: Executive summary of the report of AAPM Research Committee Task Group 195

Overview of attention for article published in Medical Physics, September 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (81st percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

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11 tweeters

Citations

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31 Dimensions

Readers on

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57 Mendeley
Title
Monte Carlo reference data sets for imaging research: Executive summary of the report of AAPM Research Committee Task Group 195
Published in
Medical Physics, September 2015
DOI 10.1118/1.4928676
Pubmed ID
Authors

Ioannis Sechopoulos, Elsayed S. M. Ali, Andreu Badal, Aldo Badano, John M. Boone, Iacovos S. Kyprianou, Ernesto Mainegra-Hing, Kyle L. McMillan, Michael F. McNitt-Gray, D. W. O. Rogers, Ehsan Samei, Adam C. Turner

Abstract

The use of Monte Carlo simulations in diagnostic medical imaging research is widespread due to its flexibility and ability to estimate quantities that are challenging to measure empirically. However, any new Monte Carlo simulation code needs to be validated before it can be used reliably. The type and degree of validation required depends on the goals of the research project, but, typically, such validation involves either comparison of simulation results to physical measurements or to previously published results obtained with established Monte Carlo codes. The former is complicated due to nuances of experimental conditions and uncertainty, while the latter is challenging due to typical graphical presentation and lack of simulation details in previous publications. In addition, entering the field of Monte Carlo simulations in general involves a steep learning curve. It is not a simple task to learn how to program and interpret a Monte Carlo simulation, even when using one of the publicly available code packages. This Task Group report provides a common reference for benchmarking Monte Carlo simulations across a range of Monte Carlo codes and simulation scenarios. In the report, all simulation conditions are provided for six different Monte Carlo simulation cases that involve common x-ray based imaging research areas. The results obtained for the six cases using four publicly available Monte Carlo software packages are included in tabular form. In addition to a full description of all simulation conditions and results, a discussion and comparison of results among the Monte Carlo packages and the lessons learned during the compilation of these results are included. This abridged version of the report includes only an introductory description of the six cases and a brief example of the results of one of the cases. This work provides an investigator the necessary information to benchmark his/her Monte Carlo simulation software against the reference cases included here before performing his/her own novel research. In addition, an investigator entering the field of Monte Carlo simulations can use these descriptions and results as a self-teaching tool to ensure that he/she is able to perform a specific simulation correctly. Finally, educators can assign these cases as learning projects as part of course objectives or training programs.

Twitter Demographics

The data shown below were collected from the profiles of 11 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 2 4%
France 1 2%
Germany 1 2%
Malaysia 1 2%
Spain 1 2%
United States 1 2%
Unknown 50 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 33%
Researcher 13 23%
Other 6 11%
Student > Master 6 11%
Professor > Associate Professor 4 7%
Other 9 16%
Readers by discipline Count As %
Physics and Astronomy 21 37%
Engineering 16 28%
Medicine and Dentistry 8 14%
Unspecified 6 11%
Computer Science 2 4%
Other 4 7%

Attention Score in Context

This research output has an Altmetric Attention Score of 8. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 September 2015.
All research outputs
#1,837,650
of 12,362,744 outputs
Outputs from Medical Physics
#249
of 5,413 outputs
Outputs of similar age
#44,553
of 247,187 outputs
Outputs of similar age from Medical Physics
#6
of 181 outputs
Altmetric has tracked 12,362,744 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,413 research outputs from this source. They receive a mean Attention Score of 3.0. This one has done particularly well, scoring higher than 95% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 247,187 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 81% of its contemporaries.
We're also able to compare this research output to 181 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.