Mark Ruschin ROC dataset

This is referred to in the book as the "RUS" dataset. It consists of 90 cases, 40 of which are diseased, the images were acquired at three dose levels, which can be regarded as treatments. "0" = conventional film radiographs, "1" = digitized images viewed on monitors, Eight radiologists interpreted the cases using the FROC paradigm. These have been reduced to ROC data by using the highest ratings (the original FROC data is lost).

dataset10

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[1:3, 1:8, 1:90, 1] ratings of non-lesion localizations NLs

  • rating$LL num Array[1:3, 1:8, 1:40, 1] , ratings of lesion localizations LLs

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

  • lesions$perCase int Array[1:40], number of lesions per diseased case

  • lesions$IDs num Array[1:40, 1], numeric labels of lesions on diseased cases

  • lesions$weights num Array[1:40, 1], weights (or clinical importance) of lesions

  • descriptions$fileName chr "dataset10", base name of dataset in `data` folder

  • descriptions$type chr "ROC" the data type

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

  • descriptions$truthTableStr num Array[1:3, 1:8, 1:90, 1:2] truth table structure

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

  • descriptions$modalityID chr Array[1:3] "1" "2" "3", modality label(s)

  • descriptions$readerID chr Array[1:8] "1" "2" "3" "4" ..., reader labels

References

Ruschin M, et al. Dose dependence of mass and microcalcification detection in digital mammography: free response human observer studies. Med Phys. 2007;34:400 - 407.

Examples

res <- str(dataset10)
#> List of 3
#>  $ ratings     :List of 3
#>   ..$ NL   : num [1:3, 1:8, 1:90, 1] 1 0 0 0 0 0 1 0 0 0 ...
#>   ..$ LL   : num [1:3, 1:8, 1:40, 1] 2 1 1 2 0 0 0 0 0 3 ...
#>   ..$ LL_IL: logi NA
#>  $ lesions     :List of 3
#>   ..$ perCase: int [1:40] 1 1 1 1 1 1 1 1 1 1 ...
#>   ..$ IDs    : num [1:40, 1] 1 1 1 1 1 1 1 1 1 1 ...
#>   ..$ weights: num [1:40, 1] 1 1 1 1 1 1 1 1 1 1 ...
#>  $ descriptions:List of 7
#>   ..$ fileName     : chr "dataset10"
#>   ..$ type         : chr "ROC"
#>   ..$ name         : chr "RUSCHIN"
#>   ..$ truthTableStr: num [1:3, 1:8, 1:90, 1:2] 1 1 1 1 1 1 1 1 1 1 ...
#>   ..$ design       : chr "FCTRL"
#>   ..$ modalityID   : Named chr [1:3] "1" "2" "3"
#>   .. ..- attr(*, "names")= chr [1:3] "1" "2" "3"
#>   ..$ readerID     : Named chr [1:8] "1" "2" "3" "4" ...
#>   .. ..- attr(*, "names")= chr [1:8] "1" "2" "3" "4" ...
## PlotEmpOpChr(dataset = dataset10, opChType = "ROC")$Plot