BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

155 related articles for article (PubMed ID: 25173811)

  • 1. Soft computing approach to 3D lung nodule segmentation in CT.
    Badura P; Pietka E
    Comput Biol Med; 2014 Oct; 53():230-43. PubMed ID: 25173811
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. Segmentation of pulmonary nodules in computed tomography using a regression neural network approach and its application to the Lung Image Database Consortium and Image Database Resource Initiative dataset.
    Messay T; Hardie RC; Tuinstra TR
    Med Image Anal; 2015 May; 22(1):48-62. PubMed ID: 25791434
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Data analysis of the Lung Imaging Database Consortium and Image Database Resource Initiative.
    Wang W; Luo J; Yang X; Lin H
    Acad Radiol; 2015 Apr; 22(4):488-95. PubMed ID: 25601306
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Cloud-Based NoSQL Open Database of Pulmonary Nodules for Computer-Aided Lung Cancer Diagnosis and Reproducible Research.
    Ferreira Junior JR; Oliveira MC; de Azevedo-Marques PM
    J Digit Imaging; 2016 Dec; 29(6):716-729. PubMed ID: 27440183
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 3D skeletonization feature based computer-aided detection system for pulmonary nodules in CT datasets.
    Zhang W; Wang X; Li X; Chen J
    Comput Biol Med; 2018 Jan; 92():64-72. PubMed ID: 29154123
    [TBL] [Abstract][Full Text] [Related]  

  • 7. The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans.
    Armato SG; McLennan G; Bidaut L; McNitt-Gray MF; Meyer CR; Reeves AP; Zhao B; Aberle DR; Henschke CI; Hoffman EA; Kazerooni EA; MacMahon H; Van Beeke EJ; Yankelevitz D; Biancardi AM; Bland PH; Brown MS; Engelmann RM; Laderach GE; Max D; Pais RC; Qing DP; Roberts RY; Smith AR; Starkey A; Batrah P; Caligiuri P; Farooqi A; Gladish GW; Jude CM; Munden RF; Petkovska I; Quint LE; Schwartz LH; Sundaram B; Dodd LE; Fenimore C; Gur D; Petrick N; Freymann J; Kirby J; Hughes B; Casteele AV; Gupte S; Sallamm M; Heath MD; Kuhn MH; Dharaiya E; Burns R; Fryd DS; Salganicoff M; Anand V; Shreter U; Vastagh S; Croft BY
    Med Phys; 2011 Feb; 38(2):915-31. PubMed ID: 21452728
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. 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]  

  • 10. Measuring Interobserver Disagreement in Rating Diagnostic Characteristics of Pulmonary Nodule Using the Lung Imaging Database Consortium and Image Database Resource Initiative.
    Lin H; Huang C; Wang W; Luo J; Yang X; Liu Y
    Acad Radiol; 2017 Apr; 24(4):401-410. PubMed ID: 28169141
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 3-D Active Contour Segmentation Based on Sparse Linear Combination of Training Shapes (SCoTS).
    Farhangi MM; Frigui H; Seow A; Amini AA
    IEEE Trans Med Imaging; 2017 Nov; 36(11):2239-2249. PubMed ID: 28650806
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Segmentation of pulmonary nodules in three-dimensional CT images by use of a spiral-scanning technique.
    Wang J; Engelmann R; Li Q
    Med Phys; 2007 Dec; 34(12):4678-89. PubMed ID: 18196795
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Development of a personalized training system using the Lung Image Database Consortium and Image Database resource Initiative Database.
    Lin H; Wang W; Luo J; Yang X
    Acad Radiol; 2014 Dec; 21(12):1614-22. PubMed ID: 25442354
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Potential lung nodules identification for characterization by variable multistep threshold and shape indices from CT images.
    Iqbal S; Iqbal K; Arif F; Shaukat A; Khanum A
    Comput Math Methods Med; 2014; 2014():241647. PubMed ID: 25506388
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Automated segmentation refinement of small lung nodules in CT scans by local shape analysis.
    Diciotti S; Lombardo S; Falchini M; Picozzi G; Mascalchi M
    IEEE Trans Biomed Eng; 2011 Dec; 58(12):3418-28. PubMed ID: 21914567
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Ground-glass nodule segmentation in chest CT images using asymmetric multi-phase deformable model and pulmonary vessel removal.
    Jung J; Hong H; Goo JM
    Comput Biol Med; 2018 Jan; 92():128-138. PubMed ID: 29175099
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Multi-view secondary input collaborative deep learning for lung nodule 3D segmentation.
    Dong X; Xu S; Liu Y; Wang A; Saripan MI; Li L; Zhang X; Lu L
    Cancer Imaging; 2020 Aug; 20(1):53. PubMed ID: 32738913
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 8.