BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

405 related articles for article (PubMed ID: 25591989)

  • 1. Robust semi-automatic segmentation of pulmonary subsolid nodules in chest computed tomography scans.
    Lassen BC; Jacobs C; Kuhnigk JM; van Ginneken B; van Rikxoort EM
    Phys Med Biol; 2015 Feb; 60(3):1307-23. PubMed ID: 25591989
    [TBL] [Abstract][Full Text] [Related]  

  • 2. 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]  

  • 3. 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]  

  • 4. [Three-dimensional Mass Measurement of Subsolid Pulmonary Nodules on Chest CT: Intra and Inter-observer Variability].
    Liu H; Wang Y; Feng L; Yu T
    Zhongguo Fei Ai Za Zhi; 2015 May; 18(5):289-94. PubMed ID: 25975299
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Solid, part-solid, or non-solid?: classification of pulmonary nodules in low-dose chest computed tomography by a computer-aided diagnosis system.
    Jacobs C; van Rikxoort EM; Scholten ET; de Jong PA; Prokop M; Schaefer-Prokop C; van Ginneken B
    Invest Radiol; 2015 Mar; 50(3):168-73. PubMed ID: 25478740
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Inter-Reader Variability of Volumetric Subsolid Pulmonary Nodule Radiomic Features.
    Azour L; Moore WH; O'Donnell T; Truong MT; Babb J; Niu B; Wimmer A; Kiumehr S; Ko JP
    Acad Radiol; 2022 Feb; 29 Suppl 2():S98-S107. PubMed ID: 33610452
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. 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]  

  • 9. A weighted rule based method for predicting malignancy of pulmonary nodules by nodule characteristics.
    Kaya A; Can AB
    J Biomed Inform; 2015 Aug; 56():69-79. PubMed ID: 26008877
    [TBL] [Abstract][Full Text] [Related]  

  • 10. 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]  

  • 11. Automatic segmentation of the solid core and enclosed vessels in subsolid pulmonary nodules.
    Charbonnier JP; Chung K; Scholten ET; van Rikxoort EM; Jacobs C; Sverzellati N; Silva M; Pastorino U; van Ginneken B; Ciompi F
    Sci Rep; 2018 Jan; 8(1):646. PubMed ID: 29330380
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Automatic detection of subsolid pulmonary nodules in thoracic computed tomography images.
    Jacobs C; van Rikxoort EM; Twellmann T; Scholten ET; de Jong PA; Kuhnigk JM; Oudkerk M; de Koning HJ; Prokop M; Schaefer-Prokop C; van Ginneken B
    Med Image Anal; 2014 Feb; 18(2):374-84. PubMed ID: 24434166
    [TBL] [Abstract][Full Text] [Related]  

  • 13. An analysis of early studies released by the Lung Imaging Database Consortium (LIDC).
    Ross JC; Miller JV; Turner WD; Kelliher TP
    Acad Radiol; 2007 Nov; 14(11):1382-8. PubMed ID: 17964461
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. Effect of CAD on radiologists' detection of lung nodules on thoracic CT scans: analysis of an observer performance study by nodule size.
    Sahiner B; Chan HP; Hadjiiski LM; Cascade PN; Kazerooni EA; Chughtai AR; Poopat C; Song T; Frank L; Stojanovska J; Attili A
    Acad Radiol; 2009 Dec; 16(12):1518-30. PubMed ID: 19896069
    [TBL] [Abstract][Full Text] [Related]  

  • 16. 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]  

  • 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. Influence of lung nodule margin on volume- and diameter-based reader variability in CT lung cancer screening.
    Han D; Heuvelmans MA; Vliegenthart R; Rook M; Dorrius MD; de Jonge GJ; Walter JE; van Ooijen PMA; de Koning HJ; Oudkerk M
    Br J Radiol; 2018 Oct; 91(1090):20170405. PubMed ID: 28972803
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Detection and quantification of the solid component in pulmonary subsolid nodules by semiautomatic segmentation.
    Scholten ET; Jacobs C; van Ginneken B; van Riel S; Vliegenthart R; Oudkerk M; de Koning HJ; Horeweg N; Prokop M; Gietema HA; Mali WP; de Jong PA
    Eur Radiol; 2015 Feb; 25(2):488-96. PubMed ID: 25287262
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 21.