Nico Karssemeijer ROC dataset (CAD vs. radiologists)

This is referred to in the book as the "NICO" dataset. It consists of 200 mammograms, 80 of which contain one malignant mass, interpreted by a CAD system and nine radiologists using the LROC paradigm. The first reader is CAD. The highest rating was used to convert this to an ROC dataset. The original LROC data is datasetCadLroc. Analyzing this data requires methods described in the book, implemented in the function StCadVsRad.

dataset09

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 Array[1, 1:10, 1:200, 1] ratings of non-lesion localizations NLs

  • rating$LL num Array[1, 1:10, 1:80, 1] ratings of lesion localizations LLs

  • rating$LL_IL NA This placeholder is used only for LROC data

  • lesions$perCase int Array[1:80], number of lesions per diseased case

  • lesions$IDs num Array[1:80, 1], numeric labels of lesions on diseased cases

  • lesions$weights num Array[1:80, 1], weights (or clinical importance) of lesions

  • descriptions$fileName chr "dataset09", base name of dataset in `data` folder

  • descriptions$type chr "ROC" the data type

  • descriptions$name chr "NICO-CAD-ROC", the name of the dataset

  • descriptions$truthTableStr num Array[1, 1:10, 1:200, 1:2] truth table structure

  • descriptions$design chr "FCTRL", study design factorial dataset

  • descriptions$modalityID chr "1" modality label

  • descriptions$readerID chr Array[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

res <- str(dataset09)
#> List of 3
#>  $ ratings     :List of 3
#>   ..$ NL   : num [1, 1:10, 1:200, 1] 28 0 14 0 16 0 31 0 0 0 ...
#>   ..$ LL   : num [1, 1:10, 1:80, 1] 29 12 13 10 41 67 61 51 67 0 ...
#>   ..$ LL_IL: logi NA
#>  $ lesions     :List of 3
#>   ..$ perCase: num [1:80] 1 1 1 1 1 1 1 1 1 1 ...
#>   ..$ IDs    : num [1:80, 1] 1 1 1 1 1 1 1 1 1 1 ...
#>   ..$ weights: num [1:80, 1] 1 1 1 1 1 1 1 1 1 1 ...
#>  $ descriptions:List of 7
#>   ..$ fileName     : chr "dataset09"
#>   ..$ type         : chr "ROC"
#>   ..$ name         : chr "NICO-CAD-ROC"
#>   ..$ truthTableStr: num [1, 1:10, 1:200, 1:2] 1 1 1 1 1 1 1 1 1 1 ...
#>   ..$ design       : chr "FCTRL"
#>   ..$ modalityID   : chr "1"
#>   ..$ readerID     : chr [1:10] "1" "2" "3" "4" ...
## PlotEmpOpChr(dataset = dataset09, rdrs = 1:10, opChType = "ROC")$Plot