# Convert an FROC dataset to an ROC dataset Convert an FROC dataset to a highest rating inferred ROC dataset ```r DfFroc2Roc(dataset) ``` ## Arguments - `dataset`: The FROC dataset to be converted, `RJafroc-package`. ## Returns An ROC dataset with finite ratings in NL[,,1:K1,1] and LL[,,1:K2,1]. ## Details The first member of the ROC dataset is `NL`, whose 3rd dimension has length `(K1 + K2)`, the total number of cases. Ratings of cases `(K1 + 1)` through `(K1 + K2)` are `-Inf`. This is because in an ROC dataset FPs are only possible on non-diseasedcases. The second member of the list is `LL`. Its 3rd dimension has length K2, the number of diseased cases. This is because TPs are only possible on diseased cases . For each case the inferred ROC rating is the highest of all FROC ratings on that case. If a case has no marks, a finite ROC rating, guaranteed to be smaller than the rating on anymarked case , is assigned to it. The dataset structure is shown below: * `NL`Ratings array [1:I, 1:J, 1:(K1+K2), 1], of false positives, FPs * `LL`Ratings array [1:I, 1:J, 1:K2, 1], of true positives, TPs * `perCase`array [1:K2], number of lesions per diseased case * `IDs`array [1:K2, 1], labels of lesions on diseased cases * `weights`array [1:K2, 1], weights (or clinical importances) of lesions * `dataType`"ROC", the data type * `modalityID`[1:I] inherited modality labels * `readerID`[1:J] inherited reader labels ## Examples ```r rocDataSet <- DfFroc2Roc(dataset05) rocSpDataSet <- DfFroc2Roc(datasetFROCSpC) ## in the following example, because of the smaller number of cases, ## it is easy to see the process at work: set.seed(1);K1 <- 3;K2 <- 5 mu <- 1;nu <- 0.5;lambda <- 2;zeta1 <- 0 lambda_i <- UtilRSM2Intrinsic(mu,lambda,nu)$lambda_i nu_i <- UtilRSM2Intrinsic(mu,lambda,nu)$nu_i Lmax <- 2;Lk2 <- floor(runif(K2, 1, Lmax + 1)) frocDataRaw <- SimulateFrocDataset(mu, lambda_i, nu_i, zeta1, I = 1, J = 1, K1, K2, perCase = Lk2) hrData <- DfFroc2Roc(frocDataRaw) ## print("frocDataRaw$ratings$NL[1,1,,] = ") ## print("hrData$ratings$NL[1,1,1:K1,] = ") ## print("frocDataRaw$ratings$LL[1,1,,] = ") ## print("hrData$ratings$LL[1,1,,] = ") ## following is the output ## [1] "frocDataRaw$ratings$NL[1,1,,] = " ## [,1] [,2] [,3] [,4] ## [1,] 2.4046534 0.7635935 -Inf -Inf ## [2,] -Inf -Inf -Inf -Inf ## [3,] 0.2522234 -Inf -Inf -Inf ## [4,] 0.4356833 -Inf -Inf -Inf ## [5,] -Inf -Inf -Inf -Inf ## [6,] -Inf -Inf -Inf -Inf ## [7,] -Inf -Inf -Inf -Inf ## [8,] 0.8041895 0.3773956 0.1333364 -Inf ## > ## print("hrData$ratings$NL[1,1,1:K1,] = ") ## [1] "hrData$ratings$NL[1,1,1:K1,] = " ## [1] 2.4046534 -Inf 0.2522234 ## > ## print("frocDataRaw$ratings$LL[1,1,,] = ") ## [1] "frocDataRaw$ratings$LL[1,1,,] = " ## [,1] [,2] ## [1,] -Inf -Inf ## [2,] 1.5036080 -Inf ## [3,] 0.8442045 -Inf ## [4,] 1.0467262 -Inf ## [5,] -Inf -Inf ## > ## print("hrData$ratings$LL[1,1,,] = ") ## [1] "hrData$ratings$LL[1,1,,] = " ## [1] 0.4356833 1.5036080 0.8442045 1.0467262 0.8041895 ## Note that rating of the first and the last diseased case came from NL marks ```

DfFroc2Roc function