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Items: 1 to 20 of 117

1.

Computer-aided nodule detection and volumetry to reduce variability between radiologists in the interpretation of lung nodules at low-dose screening computed tomography.

Jeon KN, Goo JM, Lee CH, Lee Y, Choo JY, Lee NK, Shim MS, Lee IS, Kim KG, Gierada DS, Bae KT.

Invest Radiol. 2012 Aug;47(8):457-61. doi: 10.1097/RLI.0b013e318250a5aa. Erratum in: Invest Radiol. 2012 Nov;47(11):675.

2.

Lung cancer: interobserver agreement on interpretation of pulmonary findings at low-dose CT screening.

Gierada DS, Pilgram TK, Ford M, Fagerstrom RM, Church TR, Nath H, Garg K, Strollo DC.

Radiology. 2008 Jan;246(1):265-72.

PMID:
18024436
3.

Evaluation of reader variability in the interpretation of follow-up CT scans at lung cancer screening.

Singh S, Pinsky P, Fineberg NS, Gierada DS, Garg K, Sun Y, Nath PH.

Radiology. 2011 Apr;259(1):263-70. doi: 10.1148/radiol.10101254.

4.

Performance of computer-aided detection of pulmonary nodules in low-dose CT: comparison with double reading by nodule volume.

Zhao Y, de Bock GH, Vliegenthart R, van Klaveren RJ, Wang Y, Bogoni L, de Jong PA, Mali WP, van Ooijen PM, Oudkerk M.

Eur Radiol. 2012 Oct;22(10):2076-84. doi: 10.1007/s00330-012-2437-y.

5.

Solid, part-solid, or non-solid?: classification of pulmonary nodules in low-dose chest computed tomography by a computer-aided diagnosis system.

Jacobs C, van Rikxoort EM, Scholten ET, de Jong PA, Prokop M, Schaefer-Prokop C, van Ginneken B.

Invest Radiol. 2015 Mar;50(3):168-73. doi: 10.1097/RLI.0000000000000121.

PMID:
25478740
6.

Computer-aided detection of malignant lung nodules on chest radiographs: effect on observers' performance.

Lee KH, Goo JM, Park CM, Lee HJ, Jin KN.

Korean J Radiol. 2012 Sep-Oct;13(5):564-71. doi: 10.3348/kjr.2012.13.5.564.

7.

Automated lung nodule detection at low-dose CT: preliminary experience.

Goo JM, Lee JW, Lee HJ, Kim S, Kim JH, Im JG.

Korean J Radiol. 2003 Oct-Dec;4(4):211-6.

8.

Linear and volume measurements of pulmonary nodules at different CT dose levels - intrascan and interscan analysis.

Hein PA, Romano VC, Rogalla P, Klessen C, Lembcke A, Dicken V, Bornemann L, Bauknecht HC.

Rofo. 2009 Jan;181(1):24-31. doi: 10.1055/s-2008-1027874.

PMID:
19085687
9.

Pulmonary nodules on multi-detector row CT scans: performance comparison of radiologists and computer-aided detection.

Rubin GD, Lyo JK, Paik DS, Sherbondy AJ, Chow LC, Leung AN, Mindelzun R, Schraedley-Desmond PK, Zinck SE, Naidich DP, Napel S.

Radiology. 2005 Jan;234(1):274-83.

PMID:
15537839
10.

Reader variability in identifying pulmonary nodules on chest radiographs from the national lung screening trial.

Singh SP, Gierada DS, Pinsky P, Sanders C, Fineberg N, Sun Y, Lynch D, Nath H.

J Thorac Imaging. 2012 Jul;27(4):249-54. doi: 10.1097/RTI.0b013e318256951e.

11.
12.

A computer-aided diagnosis for evaluating lung nodules on chest CT: the current status and perspective.

Goo JM.

Korean J Radiol. 2011 Mar-Apr;12(2):145-55. doi: 10.3348/kjr.2011.12.2.145. Review.

13.

Impact of a computer-aided detection (CAD) system integrated into a picture archiving and communication system (PACS) on reader sensitivity and efficiency for the detection of lung nodules in thoracic CT exams.

Bogoni L, Ko JP, Alpert J, Anand V, Fantauzzi J, Florin CH, Koo CW, Mason D, Rom W, Shiau M, Salganicoff M, Naidich DP.

J Digit Imaging. 2012 Dec;25(6):771-81. doi: 10.1007/s10278-012-9496-0.

14.

Computer-aided detection of solid lung nodules on follow-up MDCT screening: evaluation of detection, tracking, and reading time.

Beigelman-Aubry C, Raffy P, Yang W, Castellino RA, Grenier PA.

AJR Am J Roentgenol. 2007 Oct;189(4):948-55.

PMID:
17885070
15.

Is the computer-aided detection scheme for lung nodule also useful in detecting lung cancer?

Goo JM, Kim HY, Lee JW, Lee HJ, Lee CH, Lee KW, Kim TJ, Lim KY, Park SH, Bae KT.

J Comput Assist Tomogr. 2008 Jul-Aug;32(4):570-5. doi: 10.1097/RCT.0b013e318146261c.

PMID:
18664845
16.

[Computer-aided detection of small pulmonary nodules in multidetector spiral computed tomography (MSCT) in children].

Honnef D, Behrendt FF, Bakai A, Hohl C, Mahnken AH, Mertens R, Stanzel S, Günther RW, Das M.

Rofo. 2008 Jun;180(6):540-6. doi: 10.1055/s-2008-1027285. German.

PMID:
18504665
17.

Computer-aided detection in screening CT for pulmonary nodules.

Yuan R, Vos PM, Cooperberg PL.

AJR Am J Roentgenol. 2006 May;186(5):1280-7.

PMID:
16632719
18.

Lung cancer probability in patients with CT-detected pulmonary nodules: a prespecified analysis of data from the NELSON trial of low-dose CT screening.

Horeweg N, van Rosmalen J, Heuvelmans MA, van der Aalst CM, Vliegenthart R, Scholten ET, ten Haaf K, Nackaerts K, Lammers JW, Weenink C, Groen HJ, van Ooijen P, de Jong PA, de Bock GH, Mali W, de Koning HJ, Oudkerk M.

Lancet Oncol. 2014 Nov;15(12):1332-41. doi: 10.1016/S1470-2045(14)70389-4.

PMID:
25282285
19.

Benefit of computer-aided detection analysis for the detection of subsolid and solid lung nodules on thin- and thick-section CT.

Godoy MC, Kim TJ, White CS, Bogoni L, de Groot P, Florin C, Obuchowski N, Babb JS, Salganicoff M, Naidich DP, Anand V, Park S, Vlahos I, Ko JP.

AJR Am J Roentgenol. 2013 Jan;200(1):74-83. doi: 10.2214/AJR.11.7532.

PMID:
23255744
20.

[Computer-aided detection of lung nodules on thin collimation MDCT: impact on radiologists' performance].

Brochu B, Beigelman-Aubry C, Goldmard JL, Raffy P, Grenier PA, Lucidarme O.

J Radiol. 2007 Apr;88(4):573-8. French.

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