trinicheng / imrmc

iMRMC: Software to do multi-reader multi-case analysis of reader studies

README for iMRMC and iRoeMetz

Here is a high-level overview of the iMRMC software: LINK

Visit the release Page to download the software or access the repository HERE.

The documentation for both packages can be found here.

Here is a summary of updates to iMRMC and a summary of updates to iRoeMetz.

Please check out a statement of the licenses related to our software here.

iMRMC

Desc: The primary objective of the iMRMC application is to assist investigators with analyzing and sizing multi-reader multi-case (MRMC) reader studies that compare the difference in the area under Receiver Operating Characteristic curves (AUCs) from two modalities. The core elements of this application include the ability to perform MRMC variance analysis and the ability to size an MRMC trial.

• The core iMRMC application is a stand-alone, precompiled, license-free Java applications and the source code. It can be used in GUI mode or on the command line.
• There is also an R package that utilizes the core Java application. Examples for using the programs can be found in the R help files.

Here are some ways to cite our work:

• Gallas, Brandon D., Andriy Bandos, Frank Samuelson, and Robert F. Wagner. “A Framework for Random-Effects ROC Analysis: Biases with the Bootstrap and Other Variance Estimators.” Commun Stat A-Theory 38, no. 15 (2009): 2586–2603. https://doi.org/10.1080/03610920802610084.
• Gallas, Brandon D. “One-Shot Estimate of MRMC Variance: AUC.” Acad Radiol 13, no. 3 (2006): 353–62. https://doi.org/10.1016/j.acra.2005.11.030.

To cite the java code, please use this (with the appropriate version number):

• Gallas, Brandon D., "IMRMC-java vX.XX: Application for Analyzing and Sizing MRMC Reader Studies." Silver Spring, MD, 2017. https://github.com/DIDSR/iMRMC/releases.

To cite the R package, please use this (version number depends on whether you downloaded the code from GitHub or CRAN):

• Gallas, Brandon D., "IMRMC-R vX.XX: Application for Analyzing and Sizing MRMC Reader Studies." Silver Spring, MD, 2017. https://cran.r-project.org/web/packages/iMRMC/index.html.

iRoeMetz

Desc: The iRoeMetz application can be used to simulate the reader scores for MRMC experiments via Monte Carlo methods given variance components of the ROC scores. The application also estimates the variance components of AUC and can calculate the variance components directly with numerical integration. The simulated experiments can be saved and used in MRMC variance analysis programs, such as iMRMC. The iRoeMetz application is a stand-alone, precompiled, license-free Java applications and the source code.

R package iMRMC

Desc: The R package iMRMC executes the iMRMC program which writes the results to the local files system, it reads the analysis results from the local file system, packs the analysis results into a list object, deletes the data and analysis results from the local file system, and returns the list object.

Here is one way to cite our work:

• Gallas, Brandon D., and Stephen L. Hillis. “Generalized Roe and Metz ROC Model: Analytic Link between Simulated Decision Scores and Empirical AUC Variances and Covariances.” J Med Img 1, no. 3 (2014): 031006. https://doi.org/doi:10.1117/1.JMI.1.3.031006.