289 related articles for article (PubMed ID: 15822807)
1. 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]
2. Quantitative nodule detection in low dose chest CT scans: new template modeling and evaluation for CAD system design.
Farag AA; El-Baz A; Gimelfarb G; El-Ghar MA; Eldiasty T
Med Image Comput Comput Assist Interv; 2005; 8(Pt 1):720-8. PubMed ID: 16685910
[TBL] [Abstract][Full Text] [Related]
3. Automated detection of lung nodules in CT images using shape-based genetic algorithm.
Dehmeshki J; Ye X; Lin X; Valdivieso M; Amin H
Comput Med Imaging Graph; 2007 Sep; 31(6):408-17. PubMed ID: 17524617
[TBL] [Abstract][Full Text] [Related]
4. A large-scale evaluation of automatic pulmonary nodule detection in chest CT using local image features and k-nearest-neighbour classification.
Murphy K; van Ginneken B; Schilham AM; de Hoop BJ; Gietema HA; Prokop M
Med Image Anal; 2009 Oct; 13(5):757-70. PubMed ID: 19646913
[TBL] [Abstract][Full Text] [Related]
5. 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
[TBL] [Abstract][Full Text] [Related]
6. A novel lung nodules detection scheme based on vessel segmentation on CT images.
Jia T; Zhang H; Meng H
Biomed Mater Eng; 2014; 24(6):3179-86. PubMed ID: 25227026
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. 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]
9. Three-dimensional volumetric assessment with thoracic CT: a reliable approach for noncalcified lung nodules?
Mazzei MA; Scialpi M; Mazzei FG; Giacobone G; Volterrani L
Radiology; 2010 Feb; 254(2):634; author reply 635. PubMed ID: 20093537
[No Abstract] [Full Text] [Related]
10. The GGO lesions detected by computer-aided detection system on chest MDCT images.
Lee JW; Jeong JW; Lee S; Yoo DS; Kim S
Conf Proc IEEE Eng Med Biol Soc; 2006; 2006():1983-5. PubMed ID: 17945689
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Pulmonary nodule registration in serial CT scans based on rib anatomy and nodule template matching.
Shi J; Sahiner B; Chan HP; Hadjiiski L; Zhou C; Cascade PN; Bogot N; Kazerooni EA; Wu YT; Wei J
Med Phys; 2007 Apr; 34(4):1336-47. PubMed ID: 17500464
[TBL] [Abstract][Full Text] [Related]
13. Shape-based computer-aided detection of lung nodules in thoracic CT images.
Ye X; Lin X; Dehmeshki J; Slabaugh G; Beddoe G
IEEE Trans Biomed Eng; 2009 Jul; 56(7):1810-20. PubMed ID: 19527950
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. 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]
16. Morphological segmentation and partial volume analysis for volumetry of solid pulmonary lesions in thoracic CT scans.
Kuhnigk JM; Dicken V; Bornemann L; Bakai A; Wormanns D; Krass S; Peitgen HO
IEEE Trans Med Imaging; 2006 Apr; 25(4):417-34. PubMed ID: 16608058
[TBL] [Abstract][Full Text] [Related]
17. Robust pulmonary nodule segmentation in CT: improving performance for juxtapleural cases.
Okada K; Ramesh V; Krishnan A; Singh M; Akdemir U
Med Image Comput Comput Assist Interv; 2005; 8(Pt 2):781-9. PubMed ID: 16686031
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Segmentation of pulmonary nodules in thoracic CT scans: a region growing approach.
Dehmeshki J; Amin H; Valdivieso M; Ye X
IEEE Trans Med Imaging; 2008 Apr; 27(4):467-80. PubMed ID: 18390344
[TBL] [Abstract][Full Text] [Related]
20. Computer aided characterization of the solitary pulmonary nodule using volumetric and contrast enhancement features.
Shah SK; McNitt-Gray MF; Rogers SR; Goldin JG; Suh RD; Sayre JW; Petkovska I; Kim HJ; Aberle DR
Acad Radiol; 2005 Oct; 12(10):1310-9. PubMed ID: 16179208
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
