data_2modaities_2readers_3confidence: data: 2 readers, 2 modalities and 3 confideneces

In BayesianFROC: FROC Analysis by Bayesian Approaches

Description

Example data-set which has small samples.

Details

the number of modalities, denoted by M.

M = 2 modalities

the number of Confidences, denoted by C.

C = 3 Confidence levels

the number of readers, denoted by Q.

Q = 2 readers

Contents

NL = 142 (Number of Lesions)

NI = 57 (Number of Images)#'

Contents:

Multiple readers and multiple modalities case, i.e., MRMC case

ModalityID	ReaderID	Confidence levels	No. of false alarms	No. of hits.
m	q	c	f	h
--------------	-------------	------------------------	-------------------	----------------
1	1	3	20	111
1	1	2	29	55
1	1	1	21	22
1	2	3	6	100
1	2	2	15	44
1	2	1	22	11
2	1	3	6	66
2	1	2	24	55
2	1	1	23	1
2	2	3	5	66
2	2	2	30	55
2	2	1	40	44

Author(s)

Issei Tsunoda [e-mail]

References

Example data of Jafroc software

See Also

Not dataList.Chakra.Web But dataList.Chakra.Web.orderd Not dd

Examples

#========================================================================================
#                        Show data by table
#========================================================================================



                        viewdata(data_of_36_readers_and_a_single_modality)


plot_FPF_and_TPF_from_a_dataset(data_of_36_readers_and_a_single_modality)

####1#### ####2#### ####3#### ####4#### ####5#### ####6#### ####7#### ####8#### ####9####
#========================================================================================
#                       make this data from functions in this package
#========================================================================================



v  <- v_truth_creator_for_many_readers_MRMC_data(M=1,Q=36)
m  <- mu_truth_creator_for_many_readers_MRMC_data(M=1,Q=36)
d  <- create_dataList_MRMC(mu.truth = m,v.truth = v)


# The last object named d is the desired dataset.

BayesianFROC documentation built on Jan. 23, 2022, 9:06 a.m.