Distributed human intelligence for colonic polyp classification in computer-aided detection for CT colonography

Radiology

Volumn 262, Issue 3, 2012, Pages 824-833

  Nguyen, Tan B ^a   Wang, Shijun ^a   Anugu, Vishal ^a   Rose, Natalie ^a   McKenna, Matthew ^a   Petrick, Nicholas ^b   Burns, Joseph E ^a,c   Summers, Ronald M ^a  

^a NATIONAL INSTITUTES OF HEALTH   (United States)

^b CENTER FOR DEVICES AND RADIOLOGICAL HEALTH   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ADULT; AGED; ARTICLE; CLASSIFICATION ALGORITHM; CLINICAL ARTICLE; COLON POLYP; COMPUTED TOMOGRAPHIC COLONOGRAPHY; COMPUTER ASSISTED DIAGNOSIS; CONTROLLED STUDY; DISEASE CLASSIFICATION; DISTRIBUTED HUMAN INTELLIGENCE; FALSE POSITIVE RESULT; FEMALE; HUMAN; INTERMETHOD COMPARISON; MALE; PRIORITY JOURNAL; REPRODUCIBILITY; SENSITIVITY AND SPECIFICITY;

AGED; ALGORITHMS; AREA UNDER CURVE; COLONIC POLYPS; COLONOGRAPHY, COMPUTED TOMOGRAPHIC; FEMALE; HUMANS; IMAGING, THREE-DIMENSIONAL; INTERNET; MALE; MIDDLE AGED; RADIOGRAPHIC IMAGE INTERPRETATION, COMPUTER-ASSISTED; REPRODUCIBILITY OF RESULTS; RETROSPECTIVE STUDIES; ROC CURVE; SOFTWARE; STATISTICS, NONPARAMETRIC;

EID: 84863338059     PISSN: 00338419     EISSN: 15271315     Source Type: Journal    
DOI: 10.1148/radiol.11110938     Document Type: Article

References (31)

1. Jemal A, Siegel R, Xu J, Ward E. Cancer statistics, 2010. CA Cancer J Clin 2010;60(5):277-300.
2. Smith RA, Cokkinides V, Brooks D, Saslow D, Brawley OW. Cancer screening in the United States, 2010: a review of current American Cancer Society guidelines and issues in cancer screening. CA Cancer J Clin 2010;60(2):99-119.
3. Dachman AH, Obuchowski NA, Hoffmeister JW, et al. Effect of computer-aided detection for CT colonography in a multireader, multicase trial. Radiology 2010;256(3):827-835.
4. Taylor SA, Charman SC, Lefere P, et al. CT colonography: investigation of the optimum reader paradigm by using computer-aided detection software. Radiology 2008;246(2):463-471.
5. Hock D, Ouhadi R, Materne R, et al. Virtual dissection CT colonography: evaluation of learning curves and reading times with and without computer-aided detection. Radiology 2008;248(3):860-868.
6. Petrick N, Haider M, Summers RM, et al. CT colonography with computer-aided detection as a second reader: observer performance study. Radiology 2008;246(1): 148-156. (Pubitemid 350305038)
7. Summers RM. Improving the accuracy of CTC interpretation: computer-aided detection. Gastrointest Endosc Clin N Am 2010;20(2):245-257.
8. Summers RM. How perceptual factors affect the use and accuracy of CAD for interpretation of CT images. In: Samei E, Krupinski E, eds. The handbook of medical image perception and techniques. Cambridge, England: Cambridge University Press, 2009; 311-319.
9. Pickhardt PJ, Choi JR, Hwang I, et al. Computed tomographic virtual colonoscopy to screen for colorectal neoplasia in asymptomatic adults. N Engl J Med 2003;349(23): 2191-2200. (Pubitemid 37485135)
10. Pickhardt PJ, Choi JH. Electronic cleansing and stool tagging in CT colonography: advantages and pitfalls with primary three-dimensional evaluation. AJR Am J Roentgenol 2003;181(3):799-805. (Pubitemid 37021858)
11. Summers RM, Yao J, Pickhardt PJ, et al. Computed tomographic virtual colonoscopy computer-aided polyp detection in a screening population. Gastroenterology 2005;129(6):1832-1844. (Pubitemid 41772962)
12. Summers RM, Beaulieu CF, Pusanik LM, et al. Automated polyp detector for CT colonography: feasibility study. Radiology 2000;216(1):284-290. (Pubitemid 30434757)
13. Summers RM, Johnson CD, Pusanik LM, Malley JD, Youssef AM, Reed JE. Automated polyp detection at CT colonography: feasibility assessment in a human population. Radiology 2001;219(1):51-59. (Pubitemid 32234051)
14. Summers RM, Jerebko AK, Franaszek M, Malley JD, Johnson CD. Colonic polyps: complementary role of computer-aided detection in CT colonography. Radiology 2002;225(2):391-399. (Pubitemid 35239238)
15. Jerebko AK, Malley JD, Franaszek M, Summers RM. Computer-aided polyp detection in CT colonography using an ensemble of support vector machines. In: Lemke HU, Vannier MW, Inamura K, Farman AG, Doi K, Reiber JHC, eds. CARS 2003. Computer Assisted Radiology and Surgery. Proceedings of the 17th International Congress and Exhibition. London, England: Elsevier, 2003;1019-1024.
16. Malley JD, Jerebko AK, Miller MT, Summers RM. Variance reduction for error estimation when classifying colon polyps from CT colonography. In: Clough AV, Amini AA, eds. SPIE medical imaging. San Diego, Calif: SPIE, 2003; 570-578.
17. Yao J, Summers RM. 3D colonic polyp segmentation using dynamic deformable surfaces. In: Amini AA, Manduca A, eds. SPIE medical imaging. San Diego, Calif: SPIE, 2004; 280-289.
18. Iordanescu G, Pickhardt PJ, Choi JR, Summers RM. Automated seed placement for colon segmentation in computed tomography colonography. Acad Radiol 2005;12(2):182-190. (Pubitemid 40269218)
19. Summers RM, Franaszek M, Miller MT, Pickhardt PJ, Choi JR, Schindler WR. Computer-aided detection of polyps on oral contrast-enhanced CT colonography. AJR Am J Roentgenol 2005;184(1):105-108. (Pubitemid 40040912)
20. Bunch PC, Hamilton JF, Sanderson GK, Simmons AH. A free-response approach to the measurement and characterization of radiographic-observer performance. J Appl Photogr Eng 1978;4(4):166-171. (Pubitemid 9408892)
21. Chakraborty DP. Validation and statistical power comparison of methods for analyzing free-response observer performance studies. Acad Radiol 2008;15(12):1554-1566.
22. Li Q, Doi K. Reduction of bias and variance for evaluation of computer-aided diagnostic schemes. Med Phys 2006;33(4):868-875.
23. Metz CE, Herman BA, Shen JH. Maximum likelihood estimation of receiver operating characteristic (ROC) curves from continuously-distributed data. Stat Med 1998;17(9): 1033-1053. (Pubitemid 28203832)
24. Shalizi C. The bootstrap. Am Sci 2010; 98:186-190.
25. Howe J. The rise of crowdsourcing. Wired 2006; 14(6). http://www.wired.com/wired/archive/14.06/crowds.html. Accessed November 23, 2010.
26. Paolacci G, Chandler J, Ipeirotis PG. Running experiments on Amazon Mechanical Turk. Judgm Decis Mak 2010;5(5):411-419.
27. Brabham DC. Crowdsourcing as a model for problem solving: an introduction and cases. Convergence 2008;14(1):75-90.
28. Oprea TI, Bologa CG, Boyer S, et al. A crowdsourcing evaluation of the NIH chemical probes. Nat Chem Biol 2009;5(7):441-447.
29. Johnston SC, Hauser SL. Crowdsourcing scientific innovation. Ann Neurol 2009; 65(6):A7-A8.
30. Raykar VC, Yu S, Zhao LH, et al. Learning from crowds. J Mach Learn Res 2010; 11:1297-1322.
31. Wang S, Anugu V, Nguyen TB, et al. Fusion of machine intelligence and human intelligence for colonic polyp detection in CT colonography. In: Biomedical imaging: from nano to macro, 2011 IEEE International Symposium on. Chicago, Ill: IEEE, 2011; 160-164.