236 related articles for article (PubMed ID: 15132504)
41. Computer-aided detection of lung nodules by SVM based on 3D matrix patterns.
Wang Q; Kang W; Wu C; Wang B
Clin Imaging; 2013; 37(1):62-9. PubMed ID: 23206609
[TBL] [Abstract][Full Text] [Related]
42. Identifying pulmonary nodules or masses on chest radiography using deep learning: external validation and strategies to improve clinical practice.
Liang CH; Liu YC; Wu MT; Garcia-Castro F; Alberich-Bayarri A; Wu FZ
Clin Radiol; 2020 Jan; 75(1):38-45. PubMed ID: 31521323
[TBL] [Abstract][Full Text] [Related]
43. A comparison of computer-aided detection (CAD) effectiveness in pulmonary nodule identification using different methods of bone suppression in chest radiographs.
Novak RD; Novak NJ; Gilkeson R; Mansoori B; Aandal GE
J Digit Imaging; 2013 Aug; 26(4):651-6. PubMed ID: 23341178
[TBL] [Abstract][Full Text] [Related]
44. 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]
45. Pulmonary nodule detection on chest radiographs using balanced convolutional neural network and classic candidate detection.
Chen S; Han Y; Lin J; Zhao X; Kong P
Artif Intell Med; 2020 Jul; 107():101881. PubMed ID: 32828440
[TBL] [Abstract][Full Text] [Related]
46. Computer-aided diagnosis: a neural-network-based approach to lung nodule detection.
Penedo MG; Carreira MJ; Mosquera A; Cabello D
IEEE Trans Med Imaging; 1998 Dec; 17(6):872-80. PubMed ID: 10048844
[TBL] [Abstract][Full Text] [Related]
47. Is there an advantage to using computer aided detection for the early detection of pulmonary nodules within chest X-Ray imaging?
Haber M; Drake A; Nightingale J
Radiography (Lond); 2020 Aug; 26(3):e170-e178. PubMed ID: 32052750
[TBL] [Abstract][Full Text] [Related]
48. A fully automated method for lung nodule detection from postero-anterior chest radiographs.
Campadelli P; Casiraghi E; Artioli D
IEEE Trans Med Imaging; 2006 Dec; 25(12):1588-603. PubMed ID: 17167994
[TBL] [Abstract][Full Text] [Related]
49. 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]
50. Optimal matrix size of chest radiographs for computer-aided detection on lung nodule or mass with deep learning.
Kim YG; Lee SM; Lee KH; Jang R; Seo JB; Kim N
Eur Radiol; 2020 Sep; 30(9):4943-4951. PubMed ID: 32350657
[TBL] [Abstract][Full Text] [Related]
51. [Detection of lung mini-nodules using multi-feature tracking].
Tan L; Li B; Tian L; Wang L; Chen P
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2011 Jun; 28(3):437-41. PubMed ID: 21774197
[TBL] [Abstract][Full Text] [Related]
52. Computer-aided diagnosis and artificial intelligence in clinical imaging.
Shiraishi J; Li Q; Appelbaum D; Doi K
Semin Nucl Med; 2011 Nov; 41(6):449-62. PubMed ID: 21978447
[TBL] [Abstract][Full Text] [Related]
53. 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]
54. Gray-scale inversion radiographic display for the detection of pulmonary nodules on chest radiographs.
Lungren MP; Samei E; Barnhart H; McAdams HP; Leder RA; Christensen JD; Wylie JD; Tan JW; Li X; Hurwitz LM
Clin Imaging; 2012; 36(5):515-21. PubMed ID: 22920355
[TBL] [Abstract][Full Text] [Related]
55. Image feature analysis of false-positive diagnoses produced by automated detection of lung nodules.
Matsumoto T; Yoshimura H; Doi K; Giger ML; Kano A; MacMahon H; Abe K; Montner SM
Invest Radiol; 1992 Aug; 27(8):587-97. PubMed ID: 1428736
[TBL] [Abstract][Full Text] [Related]
56. Clinical evaluation of pulmonary nodules with dual-exposure dual-energy subtraction chest radiography.
Uemura M; Miyagawa M; Yasuhara Y; Murakami T; Ikura H; Sakamoto K; Tagashira H; Arakawa K; Mochizuki T
Radiat Med; 2005 Sep; 23(6):391-7. PubMed ID: 16389980
[TBL] [Abstract][Full Text] [Related]
57. Automatic detection of lesions in lung regions that are segmented using spatial relations.
Hassen DB; Taleb H
Clin Imaging; 2013; 37(3):498-503. PubMed ID: 23601768
[TBL] [Abstract][Full Text] [Related]
58. [Development of temporal subtraction method for chest radiographs by using pixel matching technique].
Sugimoto A; Katsuragawa S; Uchiyama Y; Shiraishi J
Nihon Hoshasen Gijutsu Gakkai Zasshi; 2013 Aug; 69(8):855-63. PubMed ID: 23965786
[TBL] [Abstract][Full Text] [Related]
59. Computerized detection of pulmonary nodules by single-exposure dual-energy computed radiography of the chest (part 1).
Kido S; Nakamura H; Ito W; Shimura K; Kato H
Eur J Radiol; 2002 Dec; 44(3):198-204. PubMed ID: 12468068
[TBL] [Abstract][Full Text] [Related]
60. Convolutional neural network-based PSO for lung nodule false positive reduction on CT images.
da Silva GLF; Valente TLA; Silva AC; de Paiva AC; Gattass M
Comput Methods Programs Biomed; 2018 Aug; 162():109-118. PubMed ID: 29903476
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]