datasetCadSimuFroc {RJafroc} | R Documentation |
Simulated FROC CAD vs. RAD dataset
Description
Simulated FROC CAD vs. RAD dataset suitable for checking code. It was generated from datasetCadLroc using SimulateFrocFromLrocData.R. The LROC paradigm always yields a single mark per case. Therefore the equivalent FROC will also have only one mark per case. The NL arrays of the two datasets are identical. The LL array is created by copying the LL (correct localiztion) array of the LROC dataset to the LL array of the FROC dataset, from diseased case index k2 = 1 to k2 = K2. Additionally, the LL_IL array of the LROC dataset is copied to the NL array of the FROC dataset, starting at case index k1 = K1+1 to k1 = K1+K2. Any zero ratings are replace by -Infs. The equivalent FROC dataset has the same HrAuc as the original LROC dataset. See example. The main use of this dataset & function is to test the CAD significance testing functions using CAD FROC datasets, which I currently don't have.
Usage
datasetCadSimuFroc
Format
A list with 3 elements: $ratings
, $lesions
and $descriptions
; $ratings
contain 3 elements, $NL
, $LL
and $LL_IL
as sub-lists; $lesions
contain 3 elements, $perCase
, $IDs
and $weights
as sub-lists; $descriptions
contain 7 elements, $fileName
, $type
, $name
,
$truthTableStr
, $design
, $modalityID
and $readerID
as sub-lists;
rating$NL
, num [1, 1:10, 1:200, 1], ratings of non-lesion localizations, NLsrating$LL
, num [1, 1:10, 1:80, 1], ratings of lesion localizations, LLsrating$LL_IL
NA, this placeholder is used only for LROC datalesions$perCase
, int [1:80], number of lesions per diseased caselesions$IDs
, num [1:80, 1] , numeric labels of lesions on diseased caseslesions$weights
, num [1:80, 1], weights (or clinical importances) of lesionsdescriptions$fileName
, chr, "datasetCadSimuFroc", base name of dataset in 'data' folderdescriptions$type
, chr "LROC", the data typedescriptions$name
, chr "NICO-CAD-LROC", the name of the datasetdescriptions$truthTableStr
, num [1:2, 1:4, 1:200, 1:2], truth table structuredescriptions$design
, chr "FCTRL", study design, factorial datasetdescriptions$modalityID
, chr "1", treatment label(s)descriptions$readerID
, chr [1:10] "1" "2" "3" "4" ..., reader labels