dataset07: Lucy Warren FROC dataset

In dpc10ster/rjafroc-master: Artificial Intelligence Systems and Observer Performance

Lucy Warren FROC dataset

Description

This is referred to in the book as the "OPT" dataset (for OptiMam). It consists of 162 cases, 81 of which are diseased, interpreted in five treatments (see reference, basically different ways of acquiring the images) by seven radiologists using the FROC paradigm.

Usage

dataset07

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, 1:7, 1:162, 1:4], ratings of non-lesion localizations, NLs

• rating$LL, num [1:5, 1:7, 1:81, 1:3], ratings of lesion localizations, LLs

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

• lesions$perCase, int [1:81], number of lesions per diseased case

• lesions$IDs, num [1:81, 1:3], numeric labels of lesions on diseased cases

• lesions$weights, num [1:81, 1:3], weights (or clinical importances) of lesions

• descriptions$fileName, chr, "dataset07", base name of dataset in 'data' folder

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

• descriptions$name, chr "LUCY-WARREN", the name of the dataset

• descriptions$truthTableStr, num [1:5, 1:7, 1:162, 1:4], truth table structure

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

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

• descriptions$readerID, chr [1:7] "1" "2" "3" "4" ..., reader labels

References

Warren LM, Mackenzie A, Cooke J, et al. Effect of image quality on calcification detection in digital mammography. Medical Physics. 2012;39(6):3202-3213.

Examples

res <- str(dataset07)
## PlotEmpiricalOperatingCharacteristics(dataset = dataset07, opChType = "wAFROC")$Plot

dpc10ster/rjafroc-master documentation built on Jan. 31, 2024, 1:07 p.m.