121 related articles for article (PubMed ID: 1428736)
21. Comparison of radiologist and CAD performance in the detection of CT-confirmed subtle pulmonary nodules on digital chest radiographs.
Bley TA; Baumann T; Saueressig U; Pache G; Treier M; Schaefer O; Neitzel U; Langer M; Kotter E
Invest Radiol; 2008 Jun; 43(6):343-8. PubMed ID: 18496038
[TBL] [Abstract][Full Text] [Related]
22. 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
[TBL] [Abstract][Full Text] [Related]
23. Computer-aided diagnoses: automatic detection of lung nodules.
Carreira MJ; Cabello D; Penedo MG; Mosquera A
Med Phys; 1998 Oct; 25(10):1998-2006. PubMed ID: 9800709
[TBL] [Abstract][Full Text] [Related]
24. Computer-aided diagnostic scheme for lung nodule detection in digital chest radiographs by use of a multiple-template matching technique.
Li Q; Katsuragawa S; Doi K
Med Phys; 2001 Oct; 28(10):2070-6. PubMed ID: 11695768
[TBL] [Abstract][Full Text] [Related]
25. Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique.
Teramoto A; Fujita H; Yamamuro O; Tamaki T
Med Phys; 2016 Jun; 43(6):2821-2827. PubMed ID: 27277030
[TBL] [Abstract][Full Text] [Related]
26. Small lung nodules detection based on local variance analysis and probabilistic neural network.
Woźniak M; Połap D; Capizzi G; Sciuto GL; Kośmider L; Frankiewicz K
Comput Methods Programs Biomed; 2018 Jul; 161():173-180. PubMed ID: 29852959
[TBL] [Abstract][Full Text] [Related]
27. Integrating PET and CT information to improve diagnostic accuracy for lung nodules: A semiautomatic computer-aided method.
Nie Y; Li Q; Li F; Pu Y; Appelbaum D; Doi K
J Nucl Med; 2006 Jul; 47(7):1075-80. PubMed ID: 16818939
[TBL] [Abstract][Full Text] [Related]
28. Development and evaluation of a computer-aided diagnostic scheme for lung nodule detection in chest radiographs by means of two-stage nodule enhancement with support vector classification.
Chen S; Suzuki K; MacMahon H
Med Phys; 2011 Apr; 38(4):1844-58. PubMed ID: 21626918
[TBL] [Abstract][Full Text] [Related]
29. Pulmonary nodules: computer-aided detection in digital chest images.
Giger ML; Doi K; MacMahon H; Metz CE; Yin FF
Radiographics; 1990 Jan; 10(1):41-51. PubMed ID: 2296696
[TBL] [Abstract][Full Text] [Related]
30. Value of a Computer-aided Detection System Based on Chest Tomosynthesis Imaging for the Detection of Pulmonary Nodules.
Yamada Y; Shiomi E; Hashimoto M; Abe T; Matsusako M; Saida Y; Ogawa K
Radiology; 2018 Apr; 287(1):333-339. PubMed ID: 29206596
[TBL] [Abstract][Full Text] [Related]
31. Lung nodule classification using deep feature fusion in chest radiography.
Wang C; Elazab A; Wu J; Hu Q
Comput Med Imaging Graph; 2017 Apr; 57():10-18. PubMed ID: 27986379
[TBL] [Abstract][Full Text] [Related]
32. Detection of lung nodules in digital chest radiographs using artificial neural networks: a pilot study.
Wu YC; Doi K; Giger ML
J Digit Imaging; 1995 May; 8(2):88-94. PubMed ID: 7612706
[TBL] [Abstract][Full Text] [Related]
33. Single-view 2D CNNs with fully automatic non-nodule categorization for false positive reduction in pulmonary nodule detection.
Eun H; Kim D; Jung C; Kim C
Comput Methods Programs Biomed; 2018 Oct; 165():215-224. PubMed ID: 30337076
[TBL] [Abstract][Full Text] [Related]
34. Commercially available computer-aided detection system for pulmonary nodules on thin-section images using 64 detectors-row CT: preliminary study of 48 cases.
Yanagawa M; Honda O; Yoshida S; Ono Y; Inoue A; Daimon T; Sumikawa H; Mihara N; Johkoh T; Tomiyama N; Nakamura H
Acad Radiol; 2009 Aug; 16(8):924-33. PubMed ID: 19394873
[TBL] [Abstract][Full Text] [Related]
35. Evaluation of a real-time interactive pulmonary nodule analysis system on chest digital radiographic images: a prospective study.
van Beek EJ; Mullan B; Thompson B
Acad Radiol; 2008 May; 15(5):571-5. PubMed ID: 18423313
[TBL] [Abstract][Full Text] [Related]
36. Computerized scheme for determination of the likelihood measure of malignancy for pulmonary nodules on low-dose CT images.
Aoyama M; Li Q; Katsuragawa S; Li F; Sone S; Doi K
Med Phys; 2003 Mar; 30(3):387-94. PubMed ID: 12674239
[TBL] [Abstract][Full Text] [Related]
37. Improved detection of lung nodules on chest radiographs using a commercial computer-aided diagnosis system.
Kakeda S; Moriya J; Sato H; Aoki T; Watanabe H; Nakata H; Oda N; Katsuragawa S; Yamamoto K; Doi K
AJR Am J Roentgenol; 2004 Feb; 182(2):505-10. PubMed ID: 14736690
[TBL] [Abstract][Full Text] [Related]
38. Computer-aided detection of pulmonary nodules using dynamic self-adaptive template matching and a FLDA classifier.
Gong J; Liu JY; Wang LJ; Zheng B; Nie SD
Phys Med; 2016 Dec; 32(12):1502-1509. PubMed ID: 27856118
[TBL] [Abstract][Full Text] [Related]
39. Computer-aided nodule detection system: results in an unselected series of consecutive chest radiographs.
Li F; Engelmann R; Armato SG; MacMahon H
Acad Radiol; 2015 Apr; 22(4):475-80. PubMed ID: 25592026
[TBL] [Abstract][Full Text] [Related]
40. Segmentation of lung nodules in computed tomography images using dynamic programming and multidirection fusion techniques.
Wang Q; Song E; Jin R; Han P; Wang X; Zhou Y; Zeng J
Acad Radiol; 2009 Jun; 16(6):678-88. PubMed ID: 19345122
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
