datasetCadLroc {RJafroc} | R Documentation |
Nico Karssemeijer LROC dataset (CAD vs. radiologists)
Description
This is the actual LROC data corresponding to dataset09
, which was the inferred
ROC data. Note that the LL
field is split into two, LL
, representing true
positives where the lesions were correctly localized, and LL_IL
, representing true
positives where the lesions were incorrectly localized. The first reader is CAD
and the remaining readers are radiologists.
Usage
datasetCadLroc
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 localizations on normal casesrating$LL
, num [1, 1:10, 1:80, 1], ratings of correct localizations on abnormal casesrating$LL_IL
num [1, 1:10, 1:80, 1], ratings of incorrect localizations on abnormal caseslesions$perCase
, int [1:80], number of lesions per diseased caselesions$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, "datasetCadLroc", 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
References
Hupse R et al. Standalone computer-aided detection compared to radiologists' performance for the detection of mammographic masses. Eur Radiol. 2013;23(1):93-100.
Examples
str(datasetCadLroc)