168 related articles for article (PubMed ID: 18051137)
21. 3D shape analysis for early diagnosis of malignant lung nodules.
El-Bazl A; Nitzken M; Khalifa F; Elnakib A; Gimel'farb G; Falk R; El-Ghar MA
Inf Process Med Imaging; 2011; 22():772-83. PubMed ID: 21761703
[TBL] [Abstract][Full Text] [Related]
22. In vivo repeatability of automated volume calculations of small pulmonary nodules with CT.
Rampinelli C; De Fiori E; Raimondi S; Veronesi G; Bellomi M
AJR Am J Roentgenol; 2009 Jun; 192(6):1657-61. PubMed ID: 19457831
[TBL] [Abstract][Full Text] [Related]
23. Surface normal overlap: a computer-aided detection algorithm with application to colonic polyps and lung nodules in helical CT.
Paik DS; Beaulieu CF; Rubin GD; Acar B; Jeffrey RB; Yee J; Dey J; Napel S
IEEE Trans Med Imaging; 2004 Jun; 23(6):661-75. PubMed ID: 15191141
[TBL] [Abstract][Full Text] [Related]
24. Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose CT by use of massive training artificial neural network.
Suzuki K; Li F; Sone S; Doi K
IEEE Trans Med Imaging; 2005 Sep; 24(9):1138-50. PubMed ID: 16156352
[TBL] [Abstract][Full Text] [Related]
25. 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
[TBL] [Abstract][Full Text] [Related]
26. 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
[TBL] [Abstract][Full Text] [Related]
27. Vessel tree reconstruction in thoracic CT scans with application to nodule detection.
Agam G; Armato SG; Wu C
IEEE Trans Med Imaging; 2005 Apr; 24(4):486-99. PubMed ID: 15822807
[TBL] [Abstract][Full Text] [Related]
28. Automatic detection and segmentation of ground glass opacity nodules.
Zhou J; Chang S; Metaxas DN; Zhao B; Schwartz LH; Ginsberg MS
Med Image Comput Comput Assist Interv; 2006; 9(Pt 1):784-91. PubMed ID: 17354962
[TBL] [Abstract][Full Text] [Related]
29. A computer-aided diagnosis system for detection of lung nodules in chest radiographs with an evaluation on a public database.
Schilham AM; van Ginneken B; Loog M
Med Image Anal; 2006 Apr; 10(2):247-58. PubMed ID: 16293441
[TBL] [Abstract][Full Text] [Related]
30. How can a massive training artificial neural network (MTANN) be trained with a small number of cases in the distinction between nodules and vessels in thoracic CT?
Suzuki K; Doi K
Acad Radiol; 2005 Oct; 12(10):1333-41. PubMed ID: 16179210
[TBL] [Abstract][Full Text] [Related]
31. Feature subset selection for improving the performance of false positive reduction in lung nodule CAD.
Böröczky L; Zhao L; Lee KP
IEEE Trans Inf Technol Biomed; 2006 Jul; 10(3):504-11. PubMed ID: 16871718
[TBL] [Abstract][Full Text] [Related]
32. Supervised probabilistic segmentation of pulmonary nodules in CT scans.
van Ginneken B
Med Image Comput Comput Assist Interv; 2006; 9(Pt 2):912-9. PubMed ID: 17354860
[TBL] [Abstract][Full Text] [Related]
33. Pulmonary nodule volumetric measurement variability as a function of CT slice thickness and nodule morphology.
Petrou M; Quint LE; Nan B; Baker LH
AJR Am J Roentgenol; 2007 Feb; 188(2):306-12. PubMed ID: 17242235
[TBL] [Abstract][Full Text] [Related]
34. A novel approach to nodule feature optimization on thin section thoracic CT.
Samala R; Moreno W; You Y; Qian W
Acad Radiol; 2009 Apr; 16(4):418-27. PubMed ID: 19268853
[TBL] [Abstract][Full Text] [Related]
35. A supervised 'lesion-enhancement' filter by use of a massive-training artificial neural network (MTANN) in computer-aided diagnosis (CAD).
Suzuki K
Phys Med Biol; 2009 Sep; 54(18):S31-45. PubMed ID: 19687563
[TBL] [Abstract][Full Text] [Related]
36. Pulmonary nodules: Preliminary experience with semiautomated volumetric evaluation by CT stratum.
Sone S; Tsushima K; Yoshida K; Hamanaka K; Hanaoka T; Kondo R
Acad Radiol; 2010 Jul; 17(7):900-11. PubMed ID: 20447841
[TBL] [Abstract][Full Text] [Related]
37. Pulmonary Nodule Classification with Deep Convolutional Neural Networks on Computed Tomography Images.
Li W; Cao P; Zhao D; Wang J
Comput Math Methods Med; 2016; 2016():6215085. PubMed ID: 28070212
[TBL] [Abstract][Full Text] [Related]
38. Automated lung nodule classification following automated nodule detection on CT: a serial approach.
Armato SG; Altman MB; Wilkie J; Sone S; Li F; Doi K; Roy AS
Med Phys; 2003 Jun; 30(6):1188-97. PubMed ID: 12852543
[TBL] [Abstract][Full Text] [Related]
39. Optimization of a tomosynthesis system for the detection of lung nodules.
Pineda AR; Yoon S; Paik DS; Fahrig R
Med Phys; 2006 May; 33(5):1372-9. PubMed ID: 16752573
[TBL] [Abstract][Full Text] [Related]
40. Registration of lung nodules using a semi-rigid model: method and preliminary results.
Sun S; Rubin GD; Paik D; Steiner RM; Zhuge F; Napel S
Med Phys; 2007 Feb; 34(2):613-26. PubMed ID: 17388179
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]