View source: R/UtilRSM2Intrinsic.R
UtilRSM2Intrinsic | R Documentation |
Convert physical RSM parameters λ_i' and ν_i' to the intrinsic RSM parameters λ_i and ν_i. The physical parameters are more meaningful but they depend on μ. The intrinsic parameters are independent of μ. See book for details.
UtilRSM2Intrinsic(mu, lambda, nu)
mu |
The mean of the Gaussian distribution for the ratings of latent LLs, i.e. continuous ratings of lesions that were found by the search mechanism ~ N(μ,1). The corresponding distribution for the ratings of latent NLs is N(0,1) |
lambda |
The Poisson λ_i parameter, which describes the distribution of random numbers of latent NLs (suspicious regions that do not correspond to actual lesions) per case; the mean of these random numbers asymptotically approaches lambda |
nu |
The ν_i parameter; it is the success probability of the binomial distribution describing the random number of latent LLs (suspicious regions that correspond to actual lesions) per diseased case |
RSM is the Radiological Search Model described in the book. A latent mark
becomes an actual mark if the corresponding rating exceeds the lowest reporting
threshold zeta1. See also UtilIntrinsic2RSM
.
A list containing λ_i and ν_i, the RSM search parameters
Chakraborty DP (2006) A search model and figure of merit for observer data acquired according to the free-response paradigm, Phys Med Biol 51, 3449-3462.
Chakraborty DP (2006) ROC Curves predicted by a model of visual search, Phys Med Biol 51, 3463–3482.
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
mu <- 2;lambda <- 10;nu <- 0.9 lambda_i <- UtilRSM2Intrinsic(mu, lambda, nu)$lambda_i nu_i <- UtilRSM2Intrinsic(mu, lambda, nu)$nu_i ## note that the physical values are only constrained to be positive, e.g., nu_i is not constrained ## to be between 0 and one.
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