SimulateFrocDataset: Simulates an MRMC uncorrelated FROC dataset using the RSM

In dpc10ster/rjafroc-master: Artificial Intelligence Systems and Observer Performance

Simulates an MRMC uncorrelated FROC dataset using the RSM

Description

Simulates an uncorrelated MRMC FROC dataset for specified numbers of readers and treatments

Usage

SimulateFrocDataset(
  mu,
  lambda,
  nu,
  zeta1,
  I,
  J,
  K1,
  K2,
  perCase,
  seed = NULL,
  deltaMu = 0
)

Arguments

mu	mu parameter of the RSM
lambda	RSM lambda parameter
nu	RSM nu parameter
zeta1	Lowest reporting threshold
I	Number of treatments, default is 1
J	Number of readers
K1	Number of non-diseased cases
K2	Number of diseased cases
perCase	A K2 length array containing the numbers of lesions per diseased case
seed	Initial seed for random number generator, default NULL, for random seed.
deltaMu	Inter-modality increment in mu, default zero

Details

See book chapters on the Radiological Search Model (RSM) for details. In this code correlations between ratings on the same case are assumed to be zero.

Value

An FROC dataset.

References

Chakraborty DP (2017) Observer Performance Methods for Diagnostic Imaging - Foundations, Modeling, and Applications with R-Based Examples, CRC Press, Boca Raton, FL. https://www.routledge.com/Observer-Performance-Methods-for-Diagnostic-Imaging-Foundations-Modeling/Chakraborty/p/book/9781482214840

Examples

set.seed(1) 
K1 <- 5;K2 <- 7;
maxLL <- 2;perCase <- floor(runif(K2, 1, maxLL + 1))
mu <- 1;lambda <- 1;nu <- 0.99 ;zeta1 <- -1
I <- 2; J <- 5

frocDataRaw <- SimulateFrocDataset(
  mu = mu, lambda = lambda, nu = nu, zeta1 = zeta1,
  I = I, J = J, K1 = K1, K2 = K2, perCase = perCase )
  
## plot the data
ret <- PlotEmpiricalOperatingCharacteristics(frocDataRaw, opChType = "FROC")
## print(ret$Plot)

dpc10ster/rjafroc-master documentation built on Jan. 31, 2024, 1:07 p.m.