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RJafroc (version 0.1.1)

Analysis of Data Acquired Using the Receiver Operating Characteristic Paradigm and Its Extensions

Description

A common task in medical imaging is assessing whether a new imaging system or device is an improvement over an existing one. Observer performance methodology, such as receiver operating characteristic analysis, is widely used for this purpose. Receiver operating characteristic studies are often required for regulatory approval of new devices. The purpose of this work is to software for the analysis of data acquired using the receiver operating characteristic paradigm and its location specific extensions. It is an enhanced implementation of existing Windows software (http://www.devchakraborty.com). In this paradigm the radiologist rates each image for confidence in presence of disease. The images are typically split equally between actually non-diseased and diseased. A common figure of merit is the area under the receiver operating characteristic curve, which has the physical interpretation as the probability that a diseased image is rated higher than a non-diseased one. In receiver operating characteristic studies a number of radiologists (readers) rate images in two or more treatments, and the object of the analysis is to determine the significance of the inter-treatment difference between reader-averaged figures of merit. In the free-response paradigm the reader marks the locations of suspicious regions and rates each region for confidence in presence of disease, and credit for detection is only given if a true lesion is correctly localized. In the region of interest paradigm each image is divided into a number of regions and the reader rates each region. Each paradigm requires definition of a valid figure of merit that rewards correct decisions and penalizes incorrect ones and specialized significance testing procedures are applied. The package reads data in all currently used data formats including Excel. Significance testing uses two models in widespread use, a jackknife pseudo-value based model and an analysis of variance model with correlated errors. Included are tools for (1) calculating a variety of free-response figures of merit; (2) sample size estimation for planning a future study based on pilot data; (3) viewing empirical operating characteristics in receiver operating characteristic and free-response paradigms; (4) producing formatted report files; and (5) saving a data file in appropriate format for analysis with alternate software. In addition to open-source access to the functions, the package includes a graphical interface for users already familiar with the Windows software, who simply wish to run the program.

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Version

Install

install.packages('RJafroc')

Monthly Downloads

282

Version

0.1.1

License

GPL-3

Maintainer

Xuetong Zhai

Last Published

August 14th, 2015

Functions in RJafroc (0.1.1)

EmpiricalOpCharac

Plot empirical operating characteristic
FROC2HrROC

Convert FROC dataset
RJafroc-package

JAFROC analysis for MRMC data
PowerGivenJK

Calculate statistical power given numbers of readers J and cases K for ROC studies
PowerTable

Calculate power table, different combinations, of J and K for desired power for ROC studies.
DBMHAnalysis

DBM analysis with Hillis improvements
roiData

An ROI dataset produced by a data simulator
ReadDataFile

Reads the data file and creates a dataset object
SampleSizeGivenJ

Calculate number of cases for specified number of readers J to achieve the desired power for ROC studies.
rocData

An ROC dataset originally provided by Dr. Kevin Berbaum, U of Iowa, ca. 2002.
ORHAnalysis

Obuchowski-Rockette analysis with Hillis improvements
SaveDataFile

Save ROC data file in a different format
frocData

An example FROC dataset provided by Dr. Federica Zanca.
RJafrocGui

Graphical user interface to RJafroc functions
FigureOfMerit

Calculate figure of merit
OutputReport

Generate a formatted report of the analysis