438 related articles for article (PubMed ID: 21739111)
1. Automatic segmentation of pulmonary blood vessels and nodules based on local intensity structure analysis and surface propagation in 3D chest CT images.
Chen B; Kitasaka T; Honma H; Takabatake H; Mori M; Natori H; Mori K
Int J Comput Assist Radiol Surg; 2012 May; 7(3):465-82. PubMed ID: 21739111
[TBL] [Abstract][Full Text] [Related]
2. Automatic detection of lung nodules in CT datasets based on stable 3D mass-spring models.
Cascio D; Magro R; Fauci F; Iacomi M; Raso G
Comput Biol Med; 2012 Nov; 42(11):1098-109. PubMed ID: 23020972
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Refinement of lung nodule candidates based on local geometric shape analysis and Laplacian of Gaussian kernels.
Saien S; Hamid Pilevar A; Abrishami Moghaddam H
Comput Biol Med; 2014 Nov; 54():188-98. PubMed ID: 25303113
[TBL] [Abstract][Full Text] [Related]
5. Fast lung nodule detection in chest CT images using cylindrical nodule-enhancement filter.
Teramoto A; Fujita H
Int J Comput Assist Radiol Surg; 2013 Mar; 8(2):193-205. PubMed ID: 22684487
[TBL] [Abstract][Full Text] [Related]
6. Computer-aided diagnosis of pulmonary nodules on CT scans: segmentation and classification using 3D active contours.
Way TW; Hadjiiski LM; Sahiner B; Chan HP; Cascade PN; Kazerooni EA; Bogot N; Zhou C
Med Phys; 2006 Jul; 33(7):2323-37. PubMed ID: 16898434
[TBL] [Abstract][Full Text] [Related]
7. Automatic lung nodule detection using multi-scale dot nodule-enhancement filter and weighted support vector machines in chest computed tomography.
Gu Y; Lu X; Zhang B; Zhao Y; Yu D; Gao L; Cui G; Wu L; Zhou T
PLoS One; 2019; 14(1):e0210551. PubMed ID: 30629724
[TBL] [Abstract][Full Text] [Related]
8. A Segmentation Framework of Pulmonary Nodules in Lung CT Images.
Mukhopadhyay S
J Digit Imaging; 2016 Feb; 29(1):86-103. PubMed ID: 26055544
[TBL] [Abstract][Full Text] [Related]
9. The effect of pulmonary vessel suppression on computerized detection of nodules in chest CT scans.
Gu X; Xie W; Fang Q; Zhao J; Li Q
Med Phys; 2020 Oct; 47(10):4917-4927. PubMed ID: 32681587
[TBL] [Abstract][Full Text] [Related]
10. Effect of segmentation algorithms on the performance of computerized detection of lung nodules in CT.
Guo W; Li Q
Med Phys; 2014 Sep; 41(9):091906. PubMed ID: 25186393
[TBL] [Abstract][Full Text] [Related]
11. JOURNAL CLUB: Computer-Aided Detection of Lung Nodules on CT With a Computerized Pulmonary Vessel Suppressed Function.
Lo SB; Freedman MT; Gillis LB; White CS; Mun SK
AJR Am J Roentgenol; 2018 Mar; 210(3):480-488. PubMed ID: 29336601
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. An adaptive morphology based segmentation technique for lung nodule detection in thoracic CT image.
Halder A; Chatterjee S; Dey D; Kole S; Munshi S
Comput Methods Programs Biomed; 2020 Dec; 197():105720. PubMed ID: 32877818
[TBL] [Abstract][Full Text] [Related]
14. Multistage segmentation model and SVM-ensemble for precise lung nodule detection.
Naqi SM; Sharif M; Yasmin M
Int J Comput Assist Radiol Surg; 2018 Jul; 13(7):1083-1095. PubMed ID: 29492880
[TBL] [Abstract][Full Text] [Related]
15. Computerized detection of lung nodules in thin-section CT images by use of selective enhancement filters and an automated rule-based classifier.
Li Q; Li F; Doi K
Acad Radiol; 2008 Feb; 15(2):165-75. PubMed ID: 18206615
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Computer-aided detection of pulmonary nodules: a comparative study using the public LIDC/IDRI database.
Jacobs C; van Rikxoort EM; Murphy K; Prokop M; Schaefer-Prokop CM; van Ginneken B
Eur Radiol; 2016 Jul; 26(7):2139-47. PubMed ID: 26443601
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. Computer-aided diagnostic scheme for the detection of lung nodules on chest radiographs: localized search method based on anatomical classification.
Shiraishi J; Li Q; Suzuki K; Engelmann R; Doi K
Med Phys; 2006 Jul; 33(7):2642-53. PubMed ID: 16898468
[TBL] [Abstract][Full Text] [Related]
20. An integrated segmentation and shape-based classification scheme for distinguishing adenocarcinomas from granulomas on lung CT.
Alilou M; Beig N; Orooji M; Rajiah P; Velcheti V; Rakshit S; Reddy N; Yang M; Jacono F; Gilkeson RC; Linden P; Madabhushi A
Med Phys; 2017 Jul; 44(7):3556-3569. PubMed ID: 28295386
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
