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Journal Abstract Search
1334 related items for PubMed ID: 19000867
1. Evaluation of computer-aided diagnosis (CAD) software for the detection of lung nodules on multidetector row computed tomography (MDCT): JAFROC study for the improvement in radiologists' diagnostic accuracy. Hirose T, Nitta N, Shiraishi J, Nagatani Y, Takahashi M, Murata K. Acad Radiol; 2008 Dec; 15(12):1505-12. PubMed ID: 19000867 [Abstract] [Full Text] [Related]
6. Computer-aided detection of solid lung nodules in lossy compressed multidetector computed tomography chest exams. Raffy P, Gaudeau Y, Miller DP, Moureaux JM, Castellino RA. Acad Radiol; 2006 Oct; 13(10):1194-203. PubMed ID: 16979068 [Abstract] [Full Text] [Related]
7. Efficacy of computer-aided detection system and thin-slab maximum intensity projection technique in the detection of pulmonary nodules in patients with resected metastases. Park EA, Goo JM, Lee JW, Kang CH, Lee HJ, Lee CH, Park CM, Lee HY, Im JG. Invest Radiol; 2009 Feb; 44(2):105-13. PubMed ID: 19034026 [Abstract] [Full Text] [Related]
9. Potential contribution of multiplanar reconstruction (MPR) to computer-aided detection of lung nodules on MDCT. Matsumoto S, Ohno Y, Yamagata H, Nogami M, Kono A, Sugimura K. Eur J Radiol; 2012 Feb; 81(2):366-70. PubMed ID: 21227621 [Abstract] [Full Text] [Related]
10. Usefulness of computer-aided diagnosis schemes for vertebral fractures and lung nodules on chest radiographs. Kasai S, Li F, Shiraishi J, Doi K. AJR Am J Roentgenol; 2008 Jul; 191(1):260-5. PubMed ID: 18562756 [Abstract] [Full Text] [Related]
14. Comparison of dual-energy subtraction and electronic bone suppression combined with computer-aided detection on chest radiographs: effect on human observers' performance in nodule detection. Szucs-Farkas Z, Schick A, Cullmann JL, Ebner L, Megyeri B, Vock P, Christe A. AJR Am J Roentgenol; 2013 May; 200(5):1006-13. PubMed ID: 23617482 [Abstract] [Full Text] [Related]
15. Lung cancer screening with CT: evaluation of radiologists and different computer assisted detection software (CAD) as first and second readers for lung nodule detection at different dose levels. Christe A, Leidolt L, Huber A, Steiger P, Szucs-Farkas Z, Roos JE, Heverhagen JT, Ebner L. Eur J Radiol; 2013 Dec; 82(12):e873-8. PubMed ID: 24074648 [Abstract] [Full Text] [Related]
16. Lung nodule CAD software as a second reader: a multicenter study. White CS, Pugatch R, Koonce T, Rust SW, Dharaiya E. Acad Radiol; 2008 Mar; 15(3):326-33. PubMed ID: 18280930 [Abstract] [Full Text] [Related]
17. A new computationally efficient CAD system for pulmonary nodule detection in CT imagery. Messay T, Hardie RC, Rogers SK. Med Image Anal; 2010 Jun; 14(3):390-406. PubMed ID: 20346728 [Abstract] [Full Text] [Related]
18. Computer-aided diagnosis for the detection and classification of lung cancers on chest radiographs ROC analysis of radiologists' performance. Shiraishi J, Abe H, Li F, Engelmann R, MacMahon H, Doi K. Acad Radiol; 2006 Aug; 13(8):995-1003. PubMed ID: 16843852 [Abstract] [Full Text] [Related]
19. Radiologists' performance for differentiating benign from malignant lung nodules on high-resolution CT using computer-estimated likelihood of malignancy. Li F, Aoyama M, Shiraishi J, Abe H, Li Q, Suzuki K, Engelmann R, Sone S, Macmahon H, Doi K. AJR Am J Roentgenol; 2004 Nov; 183(5):1209-15. PubMed ID: 15505279 [Abstract] [Full Text] [Related]