Chapter 11 Datasets
11.1 Datasets embedded in RJafroc
They are identified in the code by datasetdd (where dd is an integer in the range 01 to 14). As an example, dataset01 can be viewed here.
11.1.1 Dataset01
dataset01 “TONY” FROC dataset (DP Chakraborty and Svahn 2011)
## List of 3
## $ NL : num [1:2, 1:5, 1:185, 1:3] 3 -Inf 3 -Inf 4 ...
## $ LL : num [1:2, 1:5, 1:89, 1:2] 4 4 3 -Inf 3.5 ...
## $ LL_IL: logi NA11.1.2 Dataset02
dataset02 “VAN-DYKE” (Van Dyke) ROC dataset (Van Dyke et al. 1993)
## List of 3
## $ NL : num [1:2, 1:5, 1:114, 1] 1 3 2 3 2 2 1 2 3 2 ...
## $ LL : num [1:2, 1:5, 1:45, 1] 5 5 5 5 5 5 5 5 5 5 ...
## $ LL_IL: logi NA11.1.3 Dataset03
dataset03 “FRANKEN” (Franken) ROC dataset (Franken et al. 1992)
## List of 3
## $ NL : num [1:2, 1:4, 1:100, 1] 3 3 4 3 3 3 4 1 1 3 ...
## $ LL : num [1:2, 1:4, 1:67, 1] 5 5 4 4 5 4 4 5 2 2 ...
## $ LL_IL: logi NA11.1.4 Dataset04
dataset04 “FEDERICA” (Federica Zanca) FROC dataset (Zanca et al. 2009)
## 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 NA11.1.5 Dataset05
dataset05 “THOMPSON” (John Thompson) FROC dataset (J. D. Thompson et al. 2014)
## List of 3
## $ NL : num [1:2, 1:9, 1:92, 1:7] 4 5 -Inf -Inf 8 ...
## $ LL : num [1:2, 1:9, 1:47, 1:3] 5 9 -Inf 10 8 ...
## $ LL_IL: logi NA11.1.6 Dataset06
dataset06“MAGNUS” (Magnus Bath) FROC dataset (Vikgren et al. 2008)
## List of 3
## $ NL : num [1:2, 1:4, 1:89, 1:17] 1 -Inf -Inf -Inf 1 ...
## $ LL : num [1:2, 1:4, 1:42, 1:15] -Inf -Inf -Inf -Inf -Inf ...
## $ LL_IL: logi NA11.1.7 Dataset07
dataset07 “LUCY-WARREN” (Lucy Warren) FROC dataset (Warren et al. 2014)
## List of 3
## $ NL : num [1:5, 1:7, 1:162, 1:4] 1 2 1 2 -Inf ...
## $ LL : num [1:5, 1:7, 1:81, 1:3] 2 -Inf 2 -Inf 1 ...
## $ LL_IL: logi NA11.1.8 Dataset08
dataset08 “PENEDO” (Monica Penedo) FROC dataset (Penedo et al. 2005)
## List of 3
## $ NL : num [1:5, 1:5, 1:112, 1] 3 2 3 2 3 0 0 4 0 2 ...
## $ LL : num [1:5, 1:5, 1:64, 1] 3 2 4 3 3 3 3 4 4 3 ...
## $ LL_IL: logi NA11.1.9 Dataset09
dataset09 “NICO-CAD-ROC” (Nico Karssemeijer) ROC dataset (Hupse et al. 2013)
## 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 NA11.1.10 Dataset10
dataset10 “RUSCHIN” (Mark Ruschin) ROC dataset (Ruschin et al. 2007)
## 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 NA11.1.11 Dataset11
dataset11 “DOBBINS-1” (James Dobbins) FROC dataset (Dobbins III et al. 2016)
## List of 3
## $ NL : num [1:4, 1:5, 1:158, 1:4] -Inf -Inf -Inf -Inf -Inf ...
## $ LL : num [1:4, 1:5, 1:115, 1:20] -Inf -Inf -Inf -Inf -Inf ...
## $ LL_IL: logi NA11.1.12 Dataset12
dataset12 “DOBBINS-2” (James Dobbins) ROC dataset (Dobbins III et al. 2016)
## List of 3
## $ NL : num [1:4, 1:5, 1:152, 1] -Inf -Inf -Inf -Inf -Inf ...
## $ LL : num [1:4, 1:5, 1:88, 1] 3 4 4 -Inf -Inf ...
## $ LL_IL: logi NA11.1.13 Dataset13
dataset13 “DOBBINS-3” (James Dobbins) FROC dataset (Dobbins III et al. 2016)
## List of 3
## $ NL : num [1:4, 1:5, 1:158, 1:4] -Inf 3 -Inf 4 5 ...
## $ LL : num [1:4, 1:5, 1:106, 1:15] -Inf -Inf -Inf -Inf -Inf ...
## $ LL_IL: logi NA11.1.14 Dataset14
dataset14 “FEDERICA-REAL-ROC” (Federica Zanca) real ROC dataset (Zanca et al. 2012)
## List of 3
## $ NL : num [1:2, 1:4, 1:200, 1] 2 2 2 2 1 3 2 2 3 1 ...
## $ LL : num [1:2, 1:4, 1:100, 1] 6 5 6 4 5 5 5 5 5 4 ...
## $ LL_IL: logi NA11.2 Other datasets
11.2.1 DatasetCadLroc
datasetCadLroc “NICO-CAD-LROC” (Nico Karssemeijer) standalone CAD LROC dataset
## 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] 0 0 0 0 0 0 0 0 67 0 ...
## $ LL_IL: num [1, 1:10, 1:80, 1] 29 12 13 10 41 67 61 51 0 0 ...REFERENCES
Chakraborty, DP, and Tony Svahn. 2011. “Estimating the Parameters of a Model of Visual Search from ROC Data: An Alternate Method for Fitting Proper ROC Curves.” In Medical Imaging 2011: Image Perception, Observer Performance, and Technology Assessment, 7966:189–97. SPIE.
Dobbins III, James T, H Page McAdams, John M Sabol, Dev P Chakraborty, Ella A Kazerooni, Gautham P Reddy, Jenny Vikgren, and Magnus Båth. 2016. “Multi-Institutional Evaluation of Digital Tomosynthesis, Dual-Energy Radiography, and Conventional Chest Radiography for the Detection and Management of Pulmonary Nodules.” Journal Article. Radiology 282 (1): 236–50.
Franken, Jr., Edmund A., Kevin S. Berbaum, Susan M. Marley, Wilbur L. Smith, Yutaka Sato, Simon C. S. Kao, and Steven G. Milam. 1992. “Evaluation of a Digital Workstation for Interpreting Neonatal Examinations: A Receiver Operating Characteristic Study.” Journal Article. Investigative Radiology 27 (9): 732–37. http://journals.lww.com/investigativeradiology/Fulltext/1992/09000/Evaluation_of_a_Digital_Workstation_for.16.aspx.
Hupse, Rianne, Maurice Samulski, Marc Lobbes, Ard Heeten, MechliW Imhof-Tas, David Beijerinck, Ruud Pijnappel, Carla Boetes, and Nico Karssemeijer. 2013. “Standalone Computer-Aided Detection Compared to Radiologists’ Performance for the Detection of Mammographic Masses.” Journal Article. European Radiology 23 (1): 93–100. https://doi.org/10.1007/s00330-012-2562-7.
Penedo, Monica, Miguel Souto, Pablo G. Tahoces, Jose M. Carreira, Justo Villalon, Gerardo Porto, Carmen Seoane, et al. 2005. “Free-Response Receiver Operating Characteristic Evaluation of Lossy JPEG2000 and Object-Based Set Partitioning in Hierarchical Trees Compression of Digitized Mammograms.” Journal Article. Radiology 237 (2): 450–57.
Ruschin, Mark., Pontus. Timberg, Magnus. Bath, Bengt. Hemdal, Tony. Svahn, Rob. Saunders, Ehsan. Samei, et al. 2007. “Dose Dependence of Mass and Microcalcification Detection in Digital Mammography: Free Response Human Observer Studies.” Journal Article. Medical Physics 34: 400–407.
Thompson, John D, Peter Hogg, David J Manning, Katy Szczepura, and Dev P Chakraborty. 2014. “A Free-Response Evaluation Determining Value in the Computed Tomography Attenuation Correction Image for Revealing Pulmonary Incidental Findings: A Phantom Study.” Journal Article. Academic Radiology 21 (4): 538–45.
Van Dyke, C. W., R. D. White, N. A. Obuchowski, M. A. Geisinger, R. J. Lorig, and M. A. Meziane. 1993. “Cine MRI in the Diagnosis of Thoracic Aortic Dissection.” Journal Article. 79th RSNA Meetings.
Vikgren, Jenny, Sara Zachrisson, Angelica Svalkvist, Ase A. Johnsson, Marianne Boijsen, Agneta Flinck, Susanne Kheddache, and Magnus Bath. 2008. “Comparison of Chest Tomosynthesis and Chest Radiography for Detection of Pulmonary Nodules: Human Observer Study of Clinical Cases.” Journal Article. Radiology 249 (3): 1034–41. https://doi.org/10.1148/radiol.2492080304.
Warren, Lucy M, Rosalind M Given-Wilson, Matthew G Wallis, Julie Cooke, Mark D Halling-Brown, Alistair Mackenzie, Dev P Chakraborty, Hilde Bosmans, David R Dance, and Kenneth C Young. 2014. “The Effect of Image Processing on the Detection of Cancers in Digital Mammography.” Journal Article. American Journal of Roentgenology 203 (2): 387–93.
Zanca, Federica, Stephen L Hillis, Filip Claus, Chantal Van Ongeval, Valerie Celis, Veerle Provoost, Hong-Jun Yoon, and Hilde Bosmans. 2012. “Correlation of Free-Response and Receiver-Operating-Characteristic Area-Under-the-Curve Estimates: Results from Independently Conducted FROC/ROC Studies in Mammography.” Medical Physics 39 (10): 5917–29.
Zanca, Federica, Jurgen Jacobs, Chantal Van Ongeval, Filip Claus, Valerie Celis, Catherine Geniets, Veerle Provost, Herman Pauwels, Guy Marchal, and Hilde Bosmans. 2009. “Evaluation of Clinical Image Processing Algorithms Used in Digital Mammography.” Medical Physics 36 (3): 765–75.