This is referred to in the book as the "FED" dataset. It consists of 200 mammograms, 100 of which contained one to 3 simulated microcalcifications, interpreted in five treatments (basically different image processing algorithms) by four radiologists using the FROC paradigm and a 5-point rating scale. The maximum number of NLs per case, over the entire dataset was 7 and the dataset contained at least one diseased mammogram with 3 lesions. The Excel file containing this dataset is /inst/extdata/datasets/FZ_ALL.xlsx. The normal cases are labeled 100:199 while the normal cases are labeled 0:99.

dataset04

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 [1:5, 1:4, 1:200, 1:7], ratings of non-lesion localizations, NLs

  • rating$LL, num [1:5, 1:4, 1:100, 1:3], ratings of lesion localizations, LLs

  • rating$LL_ILNA, this placeholder is used only for LROC data

  • lesions$perCase, int [1:100], number of lesions per diseased case

  • lesions$IDs, num [1:100, 1:3], numeric labels of lesions on diseased cases

  • lesions$weights, num [1:100, 1:3], weights (or clinical importances) of lesions

  • descriptions$fileName, chr, "dataset04", base name of dataset in `data` folder

  • descriptions$type, chr "FROC", the data type

  • descriptions$name, chr "FEDERICA", the name of the dataset

  • descriptions$truthTableStr, num [1:5, 1:4, 1:200, 1:4], truth table structure

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

  • descriptions$modalityID, chr [1:5] "1" "2" "3" "4" "5", modality labels

  • descriptions$readerID, chr [1:4] "1" "3" "4" "5", reader labels

References

Zanca F et al. Evaluation of clinical image processing algorithms used in digital mammography. Medical Physics. 2009;36(3):765-775.

Examples

res <- str(dataset04)
#> List of 3
#>  $ ratings     :List of 3
#>   ..$ NL   : num [1:5, 1:4, 1:200, 1:7] -Inf -Inf 1 -Inf -Inf ...
#>   ..$ LL   : num [1:5, 1:4, 1:100, 1:3] 4 5 4 5 4 3 5 4 4 3 ...
#>   ..$ LL_IL: logi NA
#>  $ lesions     :List of 3
#>   ..$ perCase: int [1:100] 1 1 1 1 1 1 1 1 1 1 ...
#>   ..$ IDs    : num [1:100, 1:3] 1 1 1 1 1 1 1 1 1 1 ...
#>   ..$ weights: num [1:100, 1:3] 1 1 1 1 1 1 1 1 1 1 ...
#>  $ descriptions:List of 7
#>   ..$ fileName     : chr "dataset04"
#>   ..$ type         : chr "FROC"
#>   ..$ name         : chr "FEDERICA"
#>   ..$ truthTableStr: num [1:5, 1:4, 1:200, 1:4] 1 1 1 1 1 1 1 1 1 1 ...
#>   ..$ design       : chr "FCTRL"
#>   ..$ modalityID   : Named chr [1:5] "1" "2" "3" "4" ...
#>   .. ..- attr(*, "names")= chr [1:5] "1" "2" "3" "4" ...
#>   ..$ readerID     : Named chr [1:4] "1" "3" "4" "5"
#>   .. ..- attr(*, "names")= chr [1:4] "1" "3" "4" "5"
## PlotEmpiricalOperatingCharacteristics(dataset = dataset04, opChType = "wAFROC")$Plot