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Evaluation of computerâ aided detection and diagnosis systemsa)

dc.contributor.authorPetrick, Nicholas
dc.contributor.authorSahiner, Berkman
dc.contributor.authorArmato, Samuel G.
dc.contributor.authorBert, Alberto
dc.contributor.authorCorreale, Loredana
dc.contributor.authorDelsanto, Silvia
dc.contributor.authorFreedman, Matthew T.
dc.contributor.authorFryd, David
dc.contributor.authorGur, David
dc.contributor.authorHadjiiski, Lubomir
dc.contributor.authorHuo, Zhimin
dc.contributor.authorJiang, Yulei
dc.contributor.authorMorra, Lia
dc.contributor.authorPaquerault, Sophie
dc.contributor.authorRaykar, Vikas
dc.contributor.authorSamuelson, Frank
dc.contributor.authorSummers, Ronald M.
dc.contributor.authorTourassi, Georgia
dc.contributor.authorYoshida, Hiroyuki
dc.contributor.authorZheng, Bin
dc.contributor.authorZhou, Chuan
dc.contributor.authorChan, Heang‐ping
dc.date.accessioned2017-01-06T20:50:57Z
dc.date.available2017-01-06T20:50:57Z
dc.date.issued2013-08
dc.identifier.citationPetrick, Nicholas; Sahiner, Berkman; Armato, Samuel G.; Bert, Alberto; Correale, Loredana; Delsanto, Silvia; Freedman, Matthew T.; Fryd, David; Gur, David; Hadjiiski, Lubomir; Huo, Zhimin; Jiang, Yulei; Morra, Lia; Paquerault, Sophie; Raykar, Vikas; Samuelson, Frank; Summers, Ronald M.; Tourassi, Georgia; Yoshida, Hiroyuki; Zheng, Bin; Zhou, Chuan; Chan, Heang‐ping (2013). "Evaluation of computerâ aided detection and diagnosis systemsa)." Medical Physics 40(8): n/a-n/a.
dc.identifier.issn0094-2405
dc.identifier.issn2473-4209
dc.identifier.urihttps://hdl.handle.net/2027.42/135108
dc.publisherWiley Periodicals, Inc.
dc.publisherAmerican Association of Physicists in Medicine
dc.subject.otherPathology
dc.subject.otherComputerâ aided diagnosis
dc.subject.otherBiomedical imaging
dc.subject.otherDiseases
dc.subject.otherbiomedical imaging
dc.subject.otherdecision support systems
dc.subject.otherdiseases
dc.subject.othermedical diagnostic computing
dc.subject.othercomputerâ aided detection and diagnosis (CAD)
dc.subject.othercomputerâ aided detection (CADe)
dc.subject.othercomputerâ aided diagnosis (CADx)
dc.subject.otherperformance assessment
dc.subject.otherstandalone performance
dc.subject.otherreader performance
dc.subject.otherclinical performance
dc.subject.otherDigital computing or data processing equipment or methods, specially adapted for specific applications
dc.subject.otherComputer aided diagnosis
dc.subject.otherMedical imaging
dc.subject.otherData sets
dc.subject.otherCancer
dc.subject.otherImage detection systems
dc.subject.otherTesting procedures
dc.subject.otherComputed tomography
dc.subject.otherMammography
dc.subject.otherStatistical analysis
dc.titleEvaluation of computerâ aided detection and diagnosis systemsa)
dc.typeArticleen_US
dc.rights.robotsIndexNoFollow
dc.subject.hlbsecondlevelMedicine (General)
dc.subject.hlbtoplevelHealth Sciences
dc.description.peerreviewedPeer Reviewed
dc.contributor.affiliationumDepartment of Radiology, The University of Michigan, 1500 East Medical Center Drive, MIB C479, Ann Arbor, Michigan 48109â 5842
dc.contributor.affiliationumDepartment of Radiology, The University of Michigan, 1500 East Medical Center Drive, MIB C476, Ann Arbor, Michigan 48109â 5842
dc.contributor.affiliationotherSchool of Electrical and Computer Engineering University of Oklahoma 101 David L Boren Blvd, Suite 1001 Norman, OK 73019
dc.contributor.affiliationotherThe University of Pittsburgh, Department of Radiology, Radiology Imaging Research, 3362 Fifth Avenue, Pittsburgh, PA 15213
dc.contributor.affiliationotherRiverain Medical, 3020 South Tech Boulevard, Miamisburg, Ohio 45342
dc.contributor.affiliationotherLombardi Comprehensive Cancer Center, Georgetown University, 3900 Reservoir Road, Northwest, Washington, DC 20057
dc.contributor.affiliationotherim3D S.p.A. Via Lessolo, 3 â 10153 Torino â Italy
dc.contributor.affiliationotherDepartment of Radiology, The University of Chicago, 5841 South Maryland Avenue, MC 2026, Chicago, Illinois 60637
dc.contributor.affiliationotherCenter for Devices and Radiological Health, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993
dc.contributor.affiliationotherDepartment of Radiology, Massachusetts General Hospital and Harvard Medical School, 25 New Chardon Street, Suite 400C, Boston, Massachusetts 02114
dc.contributor.affiliationotherOak Ridge National Laboratory, Computational Sciences & Engineering Division, Oak Ridge National Laboratory Oak Ridge, TN 37831
dc.contributor.affiliationotherNational Institutes of Health Clinical Center, Building 10, Room 1C224D, MSC 1182, Bethesda, Maryland 20892
dc.contributor.affiliationotherCenter for Devices and Radiological Health, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, Silver Spring, Maryland 20993
dc.contributor.affiliationotherIBM Research â India G2 Block, 8th Floor Outer Ring Road, Nagawara Bangalore â 560 045, India
dc.contributor.affiliationother12300 Village Square Ter., Rockville, Maryland 20852
dc.contributor.affiliationotherim3D S.p.A. Via Lessolo, 3 â 10153 Torino â Italy
dc.contributor.affiliationotherDepartment of Radiology, The University of Chicago, 5841 South Maryland Avenue, MC 2026, Chicago, llinois 60637
dc.contributor.affiliationotherCarestream Health Inc., 1049 Ridge Road West, Rochester, New York 14615
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/135108/1/mp6310.pdf
dc.identifier.doi10.1118/1.4816310
dc.identifier.sourceMedical Physics
dc.identifier.citedreferenceD. P. Chakraborty, â Validation and statistical power comparison of methods for analyzing freeâ response observer performance studies,â Acad. Radiol. 15, 1554 â 1566 ( 2008 ). 10.1016/j.acra.2008.07.018
dc.identifier.citedreferenceJ. A. Swets, Signal Detection Theory and ROC Analysis in Psychology and Diagnostics: Collected Papers ( Lawrence Erlbaum Associates, NJ, 1996 ).
dc.identifier.citedreferenceL. E. Dodd and M. S. Pepe, â Partial AUC estimation and regression,â Biometrics 59, 614 â 623 ( 2003 ). 10.1111/1541â 0420.00071
dc.identifier.citedreferenceN. Obuchowski, â Receiver operating characteristic curves and their use in radiology,â Radiology 229, 3 â 8 ( 2003 ). 10.1148/radiol.2291010898
dc.identifier.citedreferenceB. Efron and R. Tibshirani, â Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy,â Stat. Sci. 1, 54 â 75 ( 1986 ). 10.1214/ss/1177013815
dc.identifier.citedreferenceK. H. Zou, A. J. O’Malley, and L. Mauri, â Receiverâ operating characteristic analysis for evaluating diagnostic tests and predictive models,â Circulation 115, 654 â 657 ( 2007 ). 10.1161/CIRCULATIONAHA.105.594929
dc.identifier.citedreferenceICRU, â Receiver operating characteristic analysis in medical imaging,â Report No. 79 (International Commission of Radiation Units and Measurements, Bethesda, MD, 2008 ).
dc.identifier.citedreferenceX. He and E. Frey, â ROC, LROC, FROC, AFROC: An alphabet soup,â J. Am. Coll. Radiol. 6, 652 â 655 ( 2009 ). 10.1016/j.jacr.2009.06.001
dc.identifier.citedreferenceSee: http://www.bio.ri.ccf.org/html/rocanalysis.html for Cleveland Clinic ROC Software.
dc.identifier.citedreferenceSee: http://metzâ roc.uchicago.edu/ for University of Chicago LABMRMC and CORROC Software.
dc.identifier.citedreferenceSee: http://perception.radiology.uiowa.edu/ for University of Iowa MRMC Software.
dc.identifier.citedreferenceN. A. Obuchowski, â Fundamentals of clinical research for radiologists â ROC analysis,â Am. J. Roentgenol. 184, 364 â 372 ( 2005 ). 10.2214/ajr.184.2.01840364
dc.identifier.citedreferenceS. J. Starr, C. E. Metz, L. B. Lusted, and D. J. Goodenough, â Visual detection and localization of radiographic images,â Radiology 116, 533 â 538 ( 1975 ).
dc.identifier.citedreferenceP. C. Bunch, J. F. Hamilton, G. K. Sanderson, and A. H. Simmons, â A free response approach to the measurement and characterization of radiographic observer performance,â Proc. SPIE 0127, 124 â 135 ( 1977 ). 10.1117/12.955926
dc.identifier.citedreferenceR. G. Swensson, â Unified measurement of observer performance in detection and localizing target objects on images,â Med. Phys. 23, 1709 â 1724 ( 1996 ). 10.1118/1.597758
dc.identifier.citedreferenceD. C. Edwards, M. A. Kupinski, C. E. Metz, and R. M. Nishikawa, â Maximum likelihood fitting of FROC curves under an initialâ detectionâ andâ candidateâ analysis model,â Med. Phys. 29, 2861 â 2870 ( 2002 ). 10.1118/1.1524631
dc.identifier.citedreferenceD. P. Chakraborty, â A search model and figure of merit for observer data acquired according to the freeâ response paradigm,â Phys. Med. Biol. 51, 3449 â 3462 ( 2006 ). 10.1088/0031â 9155/51/14/012
dc.identifier.citedreferenceH. J. Yoon, B. Zheng, B. Sahiner, and D. P. Chakraborty, â Evaluating computerâ aided detection algorithms,â Med. Phys. 34, 2024 â 2038 ( 2007 ). 10.1118/1.2736289
dc.identifier.citedreferenceSee: http://www.devchakraborty.com/ for JAFROC software.
dc.identifier.citedreferenceD. P. Chakraborty and K. S. Berbaum, â Observer studies involving detection and localization: Modeling, analysis, and validation,â Med. Phys. 31, 2313 â 2330 ( 2004 ). 10.1118/1.1769352
dc.identifier.citedreferenceD. P. Chakraborty, â Analysis of location specific observer performance data: Validated extensions of the jackknife freeâ response (JAFROC) method,â Acad. Radiol. 13, 1187 â 1193 ( 2006 ). 10.1016/j.acra.2006.06.016
dc.identifier.citedreferenceA. I. Bandos, H. E. Rockette, T. Song, and D. Gur, â Area under the freeâ response ROC curve (FROC) and a related summary index,â Biometrics 65, 247 â 256 ( 2009 ). 10.1111/j.1541â 0420.2008.01049.x
dc.identifier.citedreferenceH. Bornefalk and A. B. Hermansson, â On the comparison of FROC curves in mammography CAD systems,â Med. Phys. 32, 412 â 417 ( 2005 ). 10.1118/1.1844433
dc.identifier.citedreferenceF. W. Samuelson and N. Petrick, â Comparing image detection algorithms using resampling,â in 3rd IEEE International Symposium on Biomedical Imaging: Macro to Nano ( 2006 ), Vols. 1â 3, pp. 1312 â 1315.
dc.identifier.citedreferenceL. M. Popescu, â Nonparametric signal detectability evaluation using an exponential transformation of the FROC curve,â Med. Phys. 38, 5690 â 5702 ( 2011 ). 10.1118/1.3633938
dc.identifier.citedreferenceL. D. Brown, T. T. Cai, and A. DasGupta, â Interval estimation for a binomial proportion,â Stat. Sci. 16, 101 â 117 ( 2001 ).
dc.identifier.citedreferenceL. D. Brown, T. T. Cai, A. DasGupta, A. Agresti, B. A. Coull, G. Casella, C. Corcoran, C. Mehta, M. Ghosh, and T. J. Santner, â Interval estimation for a binomial proportion â Comment â Rejoinder,â Stat. Sci. 16, 101 â 133 ( 2001 ).
dc.identifier.citedreferenceL. D. Brown, T. T. Cai, and A. DasGupta, â Interval estimation in exponential families,â Stat. Sin. 13, 19 â 49 ( 2003 ).
dc.identifier.citedreferenceA. Agresti and B. A. Coull, â Approximate is better than â exactâ for interval estimation of binomial proportions,â Am. Stat. 52, 119 â 126 ( 1998 ). 10.2307/2685469
dc.identifier.citedreferenceP. C. Bunch, J. F. Hamilton, G. K. Sanderson, and A. H. Simmons, â A free response approach to the measurement and characterization of radiographic observer performance,â J. Appl. Photogr. Eng. 4, 166 â 171 ( 1978 ).
dc.identifier.citedreferenceD. P. Chakraborty, â Maximum likelihood analysis of freeâ response receiver operating characteristic (FROC) data,â Med. Phys. 16, 561 â 568 ( 1989 ). 10.1118/1.596358
dc.identifier.citedreferenceD. P. Chakraborty and L. H. L. Winter, â Freeâ response methodology: Alternate analysis and a new observerâ performance experiment,â Radiology 174, 873 â 881 ( 1990 ).
dc.identifier.citedreferenceJ. J. Nappi and K. Nagata, â Sources of false positives in computerâ assisted CT colonography,â Abdom. Imaging 36, 153 â 164 ( 2011 ). 10.1007/s00261â 010â 9625â 5
dc.identifier.citedreferenceV. S. Koshkin, J. L. Hinshaw, K. Wroblewski, and A. H. Dachman, â CADâ associated reader error in CT colonography,â Acad. Radiol. 19, 801 â 810 ( 2012 ). 10.1016/j.acra.2012.03.008
dc.identifier.citedreferenceD. J. Hand and R. J. Till, â A simple generalisation of the area under the ROC curve for multiple class classification problems,â Mach. Learn. 45, 171 â 186 ( 2001 ). 10.1023/A:1010920819831
dc.identifier.citedreferenceC. Ferri, J. Hernandezâ Orallo, and M. A. Salido, â Volume under the ROC surface for multiâ class problems,â in Machine Learning: ECML, edited by N. Lavrac, D. Gamberger, H. Blockeel, and L. Todorovski ( Cavtatâ Dubrovnik, Croatia, Springer, 2003 ), Vol. 2837, pp. 108 â 120.
dc.identifier.citedreferenceB. K. Scurfield, â Multipleâ event forcedâ choice tasks in the theory of signal detectability,â J. Math. Psychol. 40, 253 â 269 ( 1996 ). 10.1006/jmps.1996.0024
dc.identifier.citedreferenceD. Mossman, â Threeâ way ROCs,â Med. Decis. Making 19, 78 â 89 ( 1999 ). 10.1177/0272989X9901900110
dc.identifier.citedreferenceD. C. Edwards, C. E. Metz, and M. A. Kupinski, â Ideal observers and optimal ROC hypersurfaces in Nâ class classification,â IEEE Trans. Med. Imaging 23, 891 â 895 ( 2004 ). 10.1109/TMI.2004.828358
dc.identifier.citedreferenceX. He, C. E. Metz, B. M. W. Tsui, J. M. Links, and E. C. Frey, â Threeâ class ROC analysis â A decision theoreric approach under the ideal observer framework,â IEEE Trans. Med. Imaging 25, 571 â 581 ( 2006 ). 10.1109/TMI.2006.871416
dc.identifier.citedreferenceB. Sahiner, H.â P. Chan, and L. Hadjiiski, â Performance analysis of 3â class classifiers: Properties of the 3D ROC surface and the normalized volume under the surface for the ideal observer,â IEEE Trans. Med. Imaging 27, 215 â 227 ( 2008 ). 10.1109/TMI.2007.905822
dc.identifier.citedreferenceX. He and E. C. Frey, â The meaning and use of the volume under a threeâ class ROC surface (VUS),â IEEE Trans. Med. Imaging 27, 577 â 588 ( 2008 ). 10.1109/TMI.2007.908687
dc.identifier.citedreferenceC. Beam, P. Layde, and D. Sullivan, â Variability in the interpretation of screening mammograms by US Radiologists,â Arch. Intern Med. 156, 209 â 213 ( 1996 ). 10.1001/archinte.1996.00440020119016
dc.identifier.citedreferenceN. Petrick, M. Haider, R. M. Summers, S. C. Yeshwant, L. Brown, E. M. Iuliano, A. Louie, J. R. Choi, and P. J. Pickhardt, â CT colonography with computerâ aided detection as a second reader: Observer performance study,â Radiology 246, 148 â 156 ( 2008 ). 10.1148/radiol.2453062161
dc.identifier.citedreferenceS. A. Taylor, S. C. Charman, P. Lefere, E. G. McFarland, E. K. Paulson, J. Yee, R. Aslam, J. M. Barlow, A. Gupta, D. H. Kim, C. M. Miller, S. Halligan, S. A. Taylor, S. C. Charman, P. Lefere, E. G. McFarland, E. K. Paulson, J. Yee, R. Aslam, J. M. Barlow, A. Gupta, D. H. Kim, C. M. Miller, and S. Halligan, â CT colonography: Investigation of the optimum reader paradigm by using computerâ aided detection software,â Radiology 246, 463 â 471 ( 2008 ). 10.1148/radiol.2461070190
dc.identifier.citedreferenceH. P. Chan, K. Doi, C. J. Vyborny, R. A. Schmidt, C. E. Metz, K. L. Lam, T. Ogura, Y. Wu, and H. MacMahon, â Improvement in radiologistsâ detection of clustered microcalcifications on mammograms. The potential of computerâ aided diagnosis,â Invest. Radiol. 25, 1102 â 1110 ( 1990 ). 10.1097/00004424â 199010000â 00006
dc.identifier.citedreferenceS. H. Taplin, C. M. Rutter, and C. D. Lehman, â Testing the effect of computerâ assisted detection on interpretive performance in screening mammography.[see comment],â AJR, Am. J. Roentgenol. 187, 1475 â 1482 ( 2006 ). 10.2214/AJR.05.0940
dc.identifier.citedreferenceE. A. Krupinski, â Perceptual enhancement of pulmonary nodule recognition in chest radiographs,â Proc. SPIE 2166, 59 â 65 ( 1994 ). 10.1117/12.171750
dc.identifier.citedreferenceN. A. Obuchowski, â Reducing the number of reader interpretations in MRMC studies,â Acad. Radiol. 16, 209 â 217 ( 2009 ). 10.1016/j.acra.2008.05.014
dc.identifier.citedreferenceB. D. Gallas and D. G. Brown, â Reader studies for validation of CAD systems,â Neural Netw. 21, 387 â 397 ( 2008 ) 10.1016/j.neunet.2007.12.013 B. D. Gallas and D. G. Brown, [erratum in Neural Netw. 21(4), 698 2008)]10.1016/j.neunet.2008.04.001.
dc.identifier.citedreferenceN. A. Obuchowski, S. V. Beiden, K. S. Berbaum, S. L. Hillis, H. Ishwaran, H. H. Song, and R. F. Wagner, â Multireader, multicase receiver operating characteristic analysis: An empirical comparison of five methods,â Acad. Radiol. 11, 980 â 995 ( 2004 ). 10.1016/j.arca.2004.04.014
dc.identifier.citedreferenceD. D. Dorfman, K. S. Berbaum, and C. E. Metz, â Receiver operating characteristic rating analysis. Generalization to the population of readers and patients with the jackknife method,â Invest. Radiol. 27, 723 â 731 ( 1992 ). 10.1097/00004424â 199209000â 00015
dc.identifier.citedreferenceN. A. Obuchowski and H. E. Rockette, â Hypothesis testing of diagnostic accuracy for multiple readers and multiple tests an anova approach with dependent observations,â Commun. Stat. Simul. Comput. 24, 285 â 308 ( 1995 ). 10.1080/03610919508813243
dc.identifier.citedreferenceN. A. Obuchowski, â Multireader, multimodality receiver operating characteristic curve studies: Hypothesis testing and sample size estimation using an analysis of variance approach with dependent observations,â Acad. Radiol. 2 ( 1 ), S22 â S29 ( 1995 ), discussion S57â S64. 10.1016/S1076â 6332(05)80441â 6
dc.identifier.citedreferenceB. D. Gallas, â Oneâ shot estimate of MRMC variance: AUC,â Acad. Radiol. 13, 353 â 362 ( 2006 ). 10.1016/j.acra.2005.11.030
dc.identifier.citedreferenceB. D. Gallas, G. A. Pennello, and K. J. Myers, â Multireader multicase variance analysis for binary data,â J. Opt. Soc. Am. A 24, B70 â B80 ( 2007 ). 10.1364/JOSAA.24.000B70
dc.identifier.citedreferenceT. W. Freer and M. J. Ulissey, â Screening mammography with computerâ aided detection: Prospective study of 12,860 patients in a community breast center,â Radiology 220, 781 â 786 ( 2001 ). 10.1148/radiol.2203001282
dc.identifier.citedreferenceJ. C. Dean and C. C. Ilvento, â Improved cancer detection using computerâ aided detection with diagnostic and screening mammography: Prospective study of 104 cancers,â AJR, Am. J. Roentgenol. 187, 20 â 28 ( 2006 ). 10.2214/AJR.05.0111
dc.identifier.citedreferenceM. A. Helvie, L. Hadjiiski, E. Makariou, H. P. Chan, N. Petrick, B. Sahiner, S. C. B. Lo, M. Freedman, D. Adler, J. Bailey, C. Blane, D. Hoff, K. Hunt, L. Joynt, K. Klein, C. Paramagul, S. K. Patterson, and M. A. Roubidoux, â Sensitivity of noncommercial computerâ aided detection system for mammographic breast cancer detection: Pilot clinical trial,â Radiology 231, 208 â 214 ( 2004 ). 10.1148/radiol.2311030429
dc.identifier.citedreferenceR. L. Birdwell, P. Bandodkar, and D. M. Ikeda, â Computerâ aided detection with screening mammography in a university hospital setting,â Radiology 236, 451 â 457 ( 2005 ). 10.1148/radiol.2362040864
dc.identifier.citedreferenceM. J. Morton, D. H. Whaley, K. R. Brandt, and K. K. Amrami, â Screening mammograms: Interpretation with computerâ aided detection â Prospective evaluation,â Radiology 239, 375 â 383 ( 2006 ). 10.1148/radiol.2392042121
dc.identifier.citedreferenceD. Regge, P. Monica, G. Galatola, C. Laudi, A. Zambon, L. Correale, R. Asnaghi, B. Barbaro, C. Borghi, D. Campanella, M. Cassinis, R. Ferrari, A. Ferraris, R. Golfieri, C. Hassan, F. Iafrate, G. Iussich, A. Laghi, R. Massara, E. Neri, L. Sali, S. Venturini, and G. Gandini, â Efficacy of computerâ aided detection as a second reader for 6â 9â mm lesions at CT colonography: Multicenter prospective trial,â Radiology 266, 168 â 176 ( 2013 ). 10.1148/radiol.12120376
dc.identifier.citedreferenceD. Gur, J. H. Sumkin, H. E. Rockette, M. Ganott, C. Hakim, L. Hardesty, W. R. Poller, R. Shah, and L. Wallace, â Changes in breast cancer detection and mammography recall rates after the introduction of a computerâ aided detection system,â J. Natl. Cancer Inst. 96, 185 â 190 ( 2004 ). 10.1093/jnci/djh067
dc.identifier.citedreferenceM. Gromet, â Comparison of computerâ aided detection to double reading of screening mammograms: Review of 231,221 mammograms,â Am. J. Roentgenol. 190, 854 â 859 ( 2008 ). 10.2214/AJR.07.2812
dc.identifier.citedreferenceJ. J. Fenton, L. Abraham, S. H. Taplin, B. M. Geller, P. A. Carney, C. D’Orsi, J. G. Elmore, W. E. Barlow, and C. Breast Cancer Surveillance, â Effectiveness of computerâ aided detection in community mammography practice,â J. Natl. Cancer Inst. 103, 1152 â 1161 ( 2011 ). 10.1093/jnci/djr206
dc.identifier.citedreferenceD. Georgianâ Smith, R. H. Moore, E. Halpern, E. D. Yeh, E. A. Rafferty, H. A. D’Alessandro, M. Staffa, D. A. Hall, K. A. McCarthy, and D. B. Kopans, â Blinded comparison of computerâ aided detection with human second reading in screening mammography,â Am. J. Roentgenol. 189, 1135 â 1141 ( 2007 ). 10.2214/AJR.07.2393
dc.identifier.citedreferenceF. J. Gilbert, S. M. Astley, M. G. Gillan, O. F. Agbaje, M. G. Wallis, J. James, C. R. Boggis, S. W. Duffy, C. I. Group, F. J. Gilbert, S. M. Astley, M. G. C. Gillan, O. F. Agbaje, M. G. Wallis, J. James, C. R. M. Boggis, and S. W. Duffy, â Single reading with computerâ aided detection for screening mammography [see comment],â N. Engl. J. Med. 359, 1675 â 1684 ( 2008 ). 10.1056/NEJMoa0803545
dc.identifier.citedreferenceJ. J. Fenton, G. Xing, J. G. Elmore, H. Bang, S. L. Chen, K. K. Lindfors, and L.â M. Baldwin, â Shortâ term outcomes of screening mammography using computerâ aided detection. A populationâ based study of medicare enrollees,â Ann. Intern Med. 158, 580 â 587 ( 2013 ). 10.7326/0003â 4819â 158â 8â 201304160â 00002
dc.identifier.citedreferenceR. M. Nishikawa, and L. L. Pesce, â Computerâ aided detection evaluation methods are not created equal,â Radiology 251, 634 â 636 ( 2009 ). 10.1148/radiol.2513081130
dc.identifier.citedreferenceN. A. Obuchowski, M. L. Lieber, and K. A. Powell, â Data analysis for detection and localization of multiple abnormalities with application to mammography,â Acad. Radiol. 7, 516 â 525 ( 2000 ). 10.1016/S1076â 6332(00)80324â 4
dc.identifier.citedreferenceC. M. Rutter, â Bootstrap estimation of diagnostic accuracy with patientâ clustered data,â Acad. Radiol. 7, 413 â 419 ( 2000 ). 10.1016/S1076â 6332(00)80381â 5
dc.identifier.citedreferenceN. A. Obuchowski, â Sample size calculations in studies of test accuracy,â Stat. Methods Med. Res. 7, 371 â 392 ( 1998 ). 10.1191/096228098678080061
dc.identifier.citedreferenceS. L. Hillis and K. S. Berbaum, â Power estimation for the Dorfmanâ Berbaumâ Metz method,â Acad. Radiol. 11, 1260 â 1273 ( 2004 ). 10.1016/j.acra.2004.08.009
dc.identifier.citedreferenceS. L. Hillis, N. A. Obuchowski, and K. S. Berbaum, â Power estimation for multireader ROC methods: An updated and unified approach,â Acad. Radiol. 18, 129 â 142 ( 2011 ). 10.1016/j.acra.2010.09.007
dc.identifier.citedreferenceSee: http://js.cx/~xin/mrmc.html for iMRMC.
dc.identifier.citedreferenceN. A. Obuchowski and S. L. Hillis, â Sample size tables for computerâ aided detection studies,â Am. J. Roentgenol. 197, W821 â W828 ( 2011 ). 10.2214/AJR.11.6764
dc.identifier.citedreferenceD. P. Chakraborty, â New developments in observer performance methodology in medical imaging,â Semin. Nucl. Med. 41, 401 â 418 ( 2011 ). 10.1053/j.semnuclmed.2011.07.001
dc.identifier.citedreferenceL. B. Lusted, â Logical analysis in roentgen diagnosis â Memorial fund lecture,â Radiology 74, 178 â 193 ( 1960 ).
dc.identifier.citedreferenceW. J. Tuddenham, â Visual search, image organization, and reader error in roentgen diagnosis â Studies of the psychophysiology of roentgen image perception â Memorial fund lecture,â Radiology 78, 694 â 704 ( 1962 ).
dc.identifier.citedreferenceH. L. Kundel and G. Revesz, â Lesion conspicuity, structured noise, and film reader error,â Am. J. Roentgenol. 126, 1233 â 1238 ( 1976 ). 10.2214/ajr.126.6.1233
dc.identifier.citedreferenceJ. M. Neuhaus and J. D. Kalbfleisch, â Betweenâ and withinâ cluster covariate effects in the analysis of clustered data,â Biometrics 54, 638 â 645 ( 1998 ). 10.2307/3109770
dc.identifier.citedreferenceK. S. Berbaum, E. A. Franken, D. D. Dorfman, S. A. Rooholamini, M. H. Kathol, T. J. Barloon, F. M. Behlke, Y. Sato, C. H. Lu, G. Y. Elkhoury, F. W. Flickinger, and W. J. Montgomery, â Satisfaction of Search in diagnosticâ radiology,â Invest. Radiol. 25, 133 â 140 ( 1990 ). 10.1097/00004424â 199002000â 00006
dc.identifier.citedreferenceD. L. Renfrew, E. A. Franken, K. S. Berbaum, F. H. Weigelt, and M. M. Abuyousef, â Error in radiology â Classification and lessons in 182 cases presented at a problem case conference,â Radiology 183, 145 â 150 ( 1992 ).
dc.identifier.citedreferenceK. Doi, â Computerâ aided diagnosis in medical imaging: Historical review, current status and future potential,â Comput. Med. Imaging Graph. 31, 198 â 211 ( 2007 ). 10.1016/j.compmedimag.2007.02.002
dc.identifier.citedreferenceD. Bielen and G. Kiss, â Computerâ aided detection for CT colonography: Update 2007,â Abdom. Imaging 32, 571 â 581 ( 2007 ). 10.1007/s00261â 007â 9293â 2
dc.identifier.citedreferenceM. L. Giger, H. P. Chan, and J. Boone, â Anniversary paper: History and status of CAD and quantitative image analysis: The role of Medical Physics and AAPM,â Med. Phys. 35, 5799 â 5820 ( 2008 ). 10.1118/1.3013555
dc.identifier.citedreferenceH. P. Chan, L. Hadjiiski, C. Zhou, and B. Sahiner, â Computerâ aided diagnosis of lung cancer and pulmonary embolism in computed tomography â A review,â Acad. Radiol. 15, 535 â 555 ( 2008 ). 10.1016/j.acra.2008.01.014
dc.identifier.citedreferenceB. van Ginneken, L. Hogeweg, and M. Prokop, â Computerâ aided diagnosis in chest radiography: Beyond nodules,â Eur. J. Radiol. 72, 226 â 230 ( 2009 ). 10.1016/j.ejrad.2009.05.061
dc.identifier.citedreferenceM. Elter and A. Horsch, â CADx of mammographic masses and clustered microcalcifications: A review,â Med. Phys. 36, 2052 â 2068 ( 2009 ). 10.1118/1.3121511
dc.identifier.citedreferenceH. D. Cheng, J. Shan, W. Ju, Y. H. Guo, and L. Zhang, â Automated breast cancer detection and classification using ultrasound images: A survey,â Pattern Recognit. 43, 299 â 317 ( 2010 ). 10.1016/j.patcog.2009.05.012
dc.identifier.citedreferenceA. Oliver, J. Freixenet, J. Marti, E. Perez, J. Pont, E. R. E. Denton, and R. Zwiggelaar, â A review of automatic mass detection and segmentation in mammographic images,â Med. Image Anal. 14, 87 â 110 ( 2010 ). 10.1016/j.media.2009.12.005
dc.identifier.citedreferenceZ. Huo, R. M. Summers, S. Paquerault, J. Lo, J. Hoffmeister, S. G. Armato III, M. T. Freedman, J. Lin, S.â C. B. Lo, N. Petrick, B. Sahiner, D. Fryd, H. Yoshida, and H.â P. Chan, â Quality assurance and training procedures for computerâ aided detection and diagnosis systems in clinical use,â Med. Phys. 40, 077001 (13pp.) ( 2013 ). 10.1118/1.4807642
dc.identifier.citedreferenceB. Efron, â Estimating the error rate of a prediction rule â Improvement on crossâ validation,â J. Am. Stat. Assoc. 78, 316 â 331 ( 1983 ). 10.1080/01621459.1983.10477973
dc.identifier.citedreferenceT. Hastie, R. Tibshirani, and J. Friedman, The Elements of Statistical Learning ( Springerâ Verlag, New York, 2001 ).
dc.identifier.citedreferenceC. M. Bishop, Neural Networks for Pattern Recognition ( Clarendon Press, Oxford, 1995 ).
dc.identifier.citedreferenceL. E. Dodd, R. F. Wagner, S. G. Armato, M. F. McNittâ Gray, S. Beiden, H. P. Chan, D. Gur, G. McLennan, C. E. Metz, N. Petrick, B. Sahiner, J. Sayre, and R. Lung Image Database Consortium, â Assessment methodologies and statistical issues for computerâ aided diagnosis of lung nodules in computed tomography: Contemporary research topics relevant to the lung image database consortium,â Acad. Radiol. 11, 462 â 475 ( 2004 ). 10.1016/S1076â 6332(03)00814â 6
dc.identifier.citedreferenceM. T. Madsen, K. S. Berbaum, A. N. Ellingson, B. H. Thompson, B. F. Mullan, and R. T. Caldwell, â A new software tool for removing, storing, and adding abnormalities to medical images for perception research studies,â Acad. Radiol. 13, 305 â 312 ( 2006 ). 10.1016/j.acra.2005.11.041
dc.identifier.citedreferenceX. Li, E. Samei, D. M. Delong, R. P. Jones, A. M. Gaca, C. L. Hollingsworth, C. M. Maxfield, C. W. T. Carrico, and D. P. Frush, â Threeâ dimensional simulation of lung nodules for paediatric multidetector array CT,â Br. J. Radiol. 82, 401 â 411 ( 2009 ). 10.1259/bjr/51749983
dc.identifier.citedreferenceH. L. Kundel, â Disease prevalence and radiological decisionâ making,â Invest. Radiol. 17, 107 â 109 ( 1982 ). 10.1097/00004424â 198201000â 00020
dc.identifier.citedreferenceR. F. Wagner, C. A. Beam, and S. V. Beiden, â Reader variability in mammography and its implications for expected utility over the population of readers and cases,â Med. Decis. Making 24, 561 â 572 ( 2004 ). 10.1177/0272989X04271043
dc.identifier.citedreferenceD. Gur, A. I. Bandos, C. R. Fuhrman, A. H. Klym, J. L. King, and H. E. Rockette, â The prevalence effect in a laboratory environment: Changing the confidence ratings,â Acad. Radiol. 14, 49 â 53 ( 2007 ). 10.1016/j.acra.2006.10.003
dc.identifier.citedreferenceM. S. Pepe, The Statistical Evaluation of Medical Tests for Classification and Prediction ( Oxford University Press, New York, 2003 ).
dc.identifier.citedreferenceC. B. Begg and R. A. Greenes, â Assessment of diagnostic tests when disease verification is subject to selection bias,â Biometrics 39, 207 â 215 ( 1983 ). 10.2307/2530820
dc.identifier.citedreferenceR. F. Wagner, C. E. Metz, and G. Campbell, â Assessment of medical imaging systems and computer aids: A tutorial review,â Acad. Radiol. 14, 723 â 748 ( 2007 ). 10.1016/j.acra.2007.03.001
dc.identifier.citedreferenceJ. N. K. Rao and A. J. Scott, â A simple method for the analysis of clustered binary data,â Biometrics 48, 577 â 585 ( 1992 ). 10.2307/2532311
dc.identifier.citedreferenceB. Zheng, M. A. Ganott, C. A. Britton, C. M. Hakim, L. A. Hardesty, T. S. Chang, H. E. Rockette, and D. Gur, â Softâ copy mammographic readings with different computerâ assisted detection cuing environments: Preliminary findings,â Radiology 221, 633 â 640 ( 2001 ). 10.1148/radiol.2213010308
dc.identifier.citedreferenceM. Heath, K. Bowyer, D. Kopans, R. Moore, and P. Kegelmeyer, â The digital database for screening mammography,â in Digital Mammography; IWDM 2000, edited by M. J. Yaffe ( Medical Physics, Toronto, Canada, 2001 ), pp. 457 â 460.
dc.identifier.citedreferenceJ. Shiraishi, S. Katsuragawa, J. Ikezoe, T. Matsumoto, T. Kobayashi, K. Komatsu, M. Matsui, H. Fujita, Y. Kodera, and K. Doi, â Development of a digital image database for chest radiographs with and without a lung nodule: Receiver operating characteristic analysis of radiologistsâ detection of pulmonary nodules,â Am. J. Roentgenol. 174, 71 â 74 ( 2000 ). 10.2214/ajr.174.1.1740071
dc.identifier.citedreferenceS. G. Armato, G. McLennan, L. Bidaut, M. F. McNittâ Gray, C. R. Meyer, A. P. Reeves, B. S. Zhao, D. R. Aberle, C. I. Henschke, E. A. Hoffman, E. A. Kazerooni, H. MacMahon, E. J. R. van Beek, D. Yankelevitz, A. M. Biancardi, P. H. Bland, M. S. Brown, R. M. Engelmann, G. E. Laderach, D. Max, R. C. Pais, D. P. Y. Qing, R. Y. Roberts, A. R. Smith, A. Starkey, P. Batra, P. Caligiuri, A. Farooqi, G. W. Gladish, C. M. Jude, R. F. Munden, I. Petkovska, L. E. Quint, L. H. Schwartz, B. Sundaram, L. E. Dodd, C. Fenimore, D. Gur, N. Petrick, J. Freymann, J. Kirby, B. Hughes, A. V. Casteele, S. Gupte, M. Sallam, M. D. Heath, M. H. Kuhn, E. Dharaiya, R. Burns, D. S. Fryd, M. Salganicoff, V. Anand, U. Shreter, S. Vastagh, B. Y. Croft, and L. P. Clarke, â The lung image database consortium (LIDC) and image database resource initiative (IDRI): A completed reference database of lung nodules on CT scans,â Med. Phys. 38, 915 â 931 ( 2011 ). 10.1118/1.3528204
dc.identifier.citedreferenceS. S. Raab, D. M. Grzybicki, J. E. Janosky, R. J. Zarbo, F. A. Meier, C. Jensen, and S. J. Geyer, â Clinical impact and frequency of anatomic pathology errors in cancer diagnoses,â Cancer 104, 2205 â 2213 ( 2005 ). 10.1002/cncr.21431
dc.identifier.citedreferenceD. P. Miller, K. F. O’Shaughnessy, S. A. Wood, and R. A. Castellino, â Gold standards and expert panels: A pulmonary nodule case study with challenges and solutions,â Proc. SPIE 5372, 173 â 184 ( 2004 ). 10.1117/12.544716
dc.identifier.citedreferenceM. Das, G. Muhlenbruch, A. H. Mahnken, T. G. Flohr, L. Gundel, S. Stanzel, T. Kraus, R. W. Gunther, and J. E. Wildberger, â Small pulmonary nodules: Effect of two computerâ aided detection systems on radiologist performance,â Radiology 241, 564 â 571 ( 2006 ). 10.1148/radiol.2412051139
dc.identifier.citedreferenceS. Buhmann, P. Herzog, J. Liang, M. Wolf, M. Salganicoff, C. Kirchhoff, M. Reiser, and C. H. Becker, â Clinical evaluation of a computerâ aided diagnosis (CAD) prototype for the detection of pulmonary embolism,â Acad. Radiol. 14, 651 â 658 ( 2007 ). 10.1016/j.acra.2007.02.007
dc.identifier.citedreferenceA. M. Biancardi, A. C. Jirapatnakul, and A. P. Reeves, â A comparison of ground truth estimation methods,â Int. J. Comput. Assist. Radiol. Surg. 5, 295 â 305 ( 2010 ). 10.1007/s11548â 009â 0401â 3
dc.identifier.citedreferenceK. R. Choudhury, D. S. Paik, C. A. Yi, S. Napel, J. Roos, and G. D. Rubin, â Assessing operating characteristics of CAD algorithms in the absence of a gold standard,â Med. Phys. 37, 1788 â 1795 ( 2010 ). 10.1118/1.3352687
dc.identifier.citedreferenceS. G. Armato, R. Y. Roberts, M. Kocherginsky, D. R. Aberle, E. A. Kazerooni, H. MacMahon, E. J. R. van Beek, D. Yankelevitz, G. McLennan, M. F. McNittâ Gray, C. R. Meyer, A. P. Reeves, P. Caligiuri, L. E. Quint, B. Sundaram, B. Y. Croft, and L. P. Clarke, â Assessment of radiologist performance in the detection of lung nodules: Dependence on the definition of â Truth â ,â Acad. Radiol. 16, 28 â 38 ( 2009 ). 10.1016/j.acra.2008.05.022
dc.identifier.citedreferenceA. M. R. Schilham, B. van Ginneken, and M. Loog, â A computerâ aided diagnosis system for detection of lung nodules in chest radiographs with an evaluation on a public database,â Med. Image Anal. 10, 247 â 258 ( 2006 ). 10.1016/j.media.2005.09.003
dc.identifier.citedreferenceR. M. Summers, L. R. Handwerker, P. J. Pickhardt, R. L. Van Uitert, K. K. Deshpande, S. Yeshwant, J. Yao, and M. Franaszek, â Performance of a previously validated CT colonography computerâ aided detection system in a new patient population,â Am. J. Roentgenol. 191, 168 â 174 ( 2008 ). 10.2214/AJR.07.3354
dc.identifier.citedreferenceU. Bick, M. L. Giger, R. A. Schmidt, R. M. Nishikawa, D. E. Wolverton, and K. Doi, â Computerâ aided breast cancer detection in screening mammography,â in Digital Mammography, edited by A. G. Gale, S. M. Astley, D. R. Dance, and A. Y. Cairns ( Elsevier, Amsterdam, 1996 ).
dc.identifier.citedreferenceK. G. Kim, J. M. Goo, J. H. Kim, H. J. Lee, B. G. Min, K. T. Bae, and J.â G. Im, â Computerâ aided diagnosis of localized groundâ glass opacity in the lung at CT: Initial experience,â Radiology 237, 657 â 661 ( 2005 ). 10.1148/radiol.2372041461
dc.identifier.citedreferenceN. Petrick, B. Sahiner, H. P. Chan, M. A. Helvie, S. Paquerault, and L. M. Hadjiiski, â Breast cancer detection: Evaluation of a massâ detection algorithm for computerâ aided diagnosis â Experience in 263 patients,â Radiology 224, 217 â 224 ( 2002 ). 10.1148/radiol.2241011062
dc.identifier.citedreferenceH. D. Li, M. Kallergi, L. P. Clarke, V. K. Jain, and R. A. Clark, â Markov random field for tumor detection in digital mammography,â IEEE Trans. Med. Imaging 14, 565 â 576 ( 1995 ). 10.1109/42.414622
dc.identifier.citedreferenceX. W. Xu, K. Doi, T. Kobayashi, H. MacMahon, and M. L. Giger, â Development of an improved CAD scheme for automated detection of lung nodules in digital chest images,â Med. Phys. 24, 1395 â 1403 ( 1997 ). 10.1118/1.598028
dc.identifier.citedreferenceB. Keserci and H. Yoshida, â Computerized detection of pulmonary nodules in chest radiographs based on morphological features and wavelet snake model,â Med. Image Anal. 6, 431 â 447 ( 2002 ). 10.1016/S1361â 8415(02)00064â 6
dc.identifier.citedreferenceH. Yoshida, Y. Masutani, P. MacEneaney, D. T. Rubin, and A. H. Dachman, â Computerized detection of colonic polyps at CT colonography on the basis of volumetric features: Pilot study,â Radiology 222, 327 â 336 ( 2002 ). 10.1148/radiol.2222010506
dc.identifier.citedreferenceH.â P. Chan, S. C. B. Lo, B. Sahiner, K. L. Lam, and M. A. Helvie, â Computerâ aided detection of mammographic microcalcifications: Pattern recognition with an artificial neural network,â Med. Phys. 22, 1555 â 1567 ( 1995 ). 10.1118/1.597428
dc.identifier.citedreferenceA. A. Enquobahrie, A. P. Reeves, D. F. Yankelevitz, and C. I. Henschke, â Automated detection of small pulmonary nodules in whole lung CT scans,â Acad. Radiol. 14, 579 â 593 ( 2007 ). 10.1016/j.acra.2007.01.029
dc.identifier.citedreferenceD. S. Paik, C. F. Beaulieu, G. D. Rubin, B. Acar, R. B. Jeffrey Jr., J. Yee, J. Dey, and S. Napel, â Surface normal overlap: A computerâ aided detection algorithm with application to colonic polyps and lung nodules in helical CT,â IEEE Trans. Med. Imaging 23, 661 â 675 ( 2004 ). 10.1109/TMI.2004.826362
dc.identifier.citedreferenceC. S. White, T. Flukinger, J. Jeudy, and J. J. Chen, â Use of a computerâ aided detection system to detect missed lung cancer at chest radiography,â Radiology 252, 273 â 281 ( 2009 ). 10.1148/radiol.2522081319
dc.identifier.citedreferenceJ. Dehmeshki, S. Halligan, S. A. Taylor, M. E. Roddie, J. McQuillan, L. Honeyfield, and H. Amin, â Computer assisted detection software for CT colonography: Effect of sphericity filter on performance characteristics for patients with and without fecal tagging,â Eur. Radiol. 17, 662 â 668 ( 2007 ). 10.1007/s00330â 006â 0430â z
dc.identifier.citedreferenceQ. Li, F. Li and K. Doi, â Computerized detection of lung nodules in thinâ section CT images by use of selective enhancement filters and an automated ruleâ based classifier,â Acad. Radiol. 15, 165 â 175 ( 2008 ). 10.1016/j.acra.2007.09.018
dc.identifier.citedreferenceS. G. Armato, â Image annotation for conveying automated lung nodule detection results to radiologists,â Acad. Radiol. 10, 1000 â 1007 ( 2003 ). 10.1016/S1076â 6332(03)00116â 8
dc.identifier.citedreferenceS. A. Taylor, J. Brittenden, J. Lenton, H. Lambie, A. Goldstone, P. N. Wylie, D. Tolan, D. Burling, L. Honeyfield, P. Bassett, and S. Halligan, â Influence of computerâ aided detection falseâ positives on reader performance and diagnostic confidence for CT colonography,â Am. J. Roentgenol. 192, 1682 â 1689 ( 2009 ). 10.2214/AJR.08.1625
dc.identifier.citedreferenceM. Kallergi, G. M. Carney, and J. Garviria, â Evaluating the performance of detection algorithms in digital mammography,â Med. Phys. 26, 267 â 275 ( 1999 ). 10.1118/1.598514
dc.identifier.citedreferenceM. H. Zweig and G. Campbell, â Receiverâ operating characteristic (ROC) plots â A fundamental evaluation tool in clinical medicine,â Clin. Chem. 39, 561 â 577 ( 1993 ).
dc.identifier.citedreferenceD. D. Dorfman and E. Alf Jr., â Maximum likelihood estimation of parameters of signal detection theory and determination of confidence intervalsâ rating method data,â J. Math. Psychol. 6, 487 â 496 ( 1969 ). 10.1016/0022â 2496(69)90019â 4
dc.identifier.citedreferenceD. D. Dorfman, K. S. Berbaum, C. E. Metz, R. V. Lenth, J. A. Hanley, and H. AbuDagga, â Proper receiver operating characteristic analysis: The bigamma model,â Acad. Radiol. 4, 138 â 149 ( 1997 ). 10.1016/S1076â 6332(97)80013â X
dc.identifier.citedreferenceC. E. Metz and X. Pan, â Proper binormal ROC curves: Theory and maximumâ likelihood estimation,â J. Math. Psychol. 43, 1 â 33 ( 1999 ). 10.1006/jmps.1998.1218
dc.identifier.citedreferenceD. D. Dorfman and K. S. Berbaum, â A contaminated binormal model for ROC data â Part II. A formal model,â Acad. Radiol. 7, 427 â 437 ( 2000 ). 10.1016/S1076â 6332(00)80383â 9
dc.identifier.citedreferenceY. L. Jiang, C. E. Metz, and R. M. Nishikawa, â A receiver operating characteristic partial area index for highly sensitive diagnostic tests,â Radiology 201, 745 â 750 ( 1996 ).
dc.identifier.citedreferenceE. R. Delong, D. M. Delong, and D. I. Clarkepearson, â Comparing the areas under 2 or more correlated receiver operating characteristic curves â A nonparametric approach,â Biometrics 44, 837 â 845 ( 1988 ). 10.2307/2531595
dc.identifier.citedreferenceJ. P. Egan, Signal Detection Theory and ROC Analysis ( Academic, New York, 1975 ).
dc.identifier.citedreferenceC. E. Metz, â Basic principles of ROC analysis,â Semin. Nucl. Med. 8, 283 â 298 ( 1978 ). 10.1016/S0001â 2998(78)80014â 2
dc.identifier.citedreferenceJ. Hanley and B. McNeil, â The meaning and use of the area under a receiver operating characteristic (ROC) curve,â Radiology 143, 29 â 36 ( 1982 ).
dc.identifier.citedreferenceC. E. Metz, â Some practical issues of experimental design and data analysis in radiological ROC studies,â Invest. Radiol. 24, 234 â 245 ( 1989 ). 10.1097/00004424â 198903000â 00012
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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