BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

293 related articles for article (PubMed ID: 12461246)

  • 21. Computerized detection of pulmonary nodules in computed tomography images.
    Giger ML; Bae KT; MacMahon H
    Invest Radiol; 1994 Apr; 29(4):459-65. PubMed ID: 8034453
    [TBL] [Abstract][Full Text] [Related]  

  • 22. 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]  

  • 23. Neural network-based computer-aided diagnosis in distinguishing malignant from benign solitary pulmonary nodules by computed tomography.
    Chen H; Wang XH; Ma DQ; Ma BR
    Chin Med J (Engl); 2007 Jul; 120(14):1211-5. PubMed ID: 17697569
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Integrating PET and CT information to improve diagnostic accuracy for lung nodules: A semiautomatic computer-aided method.
    Nie Y; Li Q; Li F; Pu Y; Appelbaum D; Doi K
    J Nucl Med; 2006 Jul; 47(7):1075-80. PubMed ID: 16818939
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Pulmonary nodules on multi-detector row CT scans: performance comparison of radiologists and computer-aided detection.
    Rubin GD; Lyo JK; Paik DS; Sherbondy AJ; Chow LC; Leung AN; Mindelzun R; Schraedley-Desmond PK; Zinck SE; Naidich DP; Napel S
    Radiology; 2005 Jan; 234(1):274-83. PubMed ID: 15537839
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Performance of a computer-aided program for automated matching of metastatic pulmonary nodules detected on follow-up chest CT.
    Lee KW; Kim M; Gierada DS; Bae KT
    AJR Am J Roentgenol; 2007 Nov; 189(5):1077-81. PubMed ID: 17954643
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Single-view 2D CNNs with fully automatic non-nodule categorization for false positive reduction in pulmonary nodule detection.
    Eun H; Kim D; Jung C; Kim C
    Comput Methods Programs Biomed; 2018 Oct; 165():215-224. PubMed ID: 30337076
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Automated lung segmentation for thoracic CT impact on computer-aided diagnosis.
    Armato SG; Sensakovic WF
    Acad Radiol; 2004 Sep; 11(9):1011-21. PubMed ID: 15350582
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Computer-aided diagnosis for the detection and classification of lung cancers on chest radiographs ROC analysis of radiologists' performance.
    Shiraishi J; Abe H; Li F; Engelmann R; MacMahon H; Doi K
    Acad Radiol; 2006 Aug; 13(8):995-1003. PubMed ID: 16843852
    [TBL] [Abstract][Full Text] [Related]  

  • 30. [Development of computer-aided diagnostic system for detection of lung nodules in three-dimensional computed tomography images].
    Yamamoto M; Ishida T; Kawashita I; Kagemoto M; Fujikawa K; Mitogawa Y; Ubagai T; Ishine M; Ito K; Akiyama M
    Nihon Hoshasen Gijutsu Gakkai Zasshi; 2006 Apr; 62(4):555-64. PubMed ID: 16639398
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Computer-aided detection (CAD) in lung cancer screening at chest MDCT: ROC analysis of CAD versus radiologist performance.
    Fraioli F; Bertoletti L; Napoli A; Pediconi F; Calabrese FA; Masciangelo R; Catalano C; Passariello R
    J Thorac Imaging; 2007 Aug; 22(3):241-6. PubMed ID: 17721333
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Computer-aided detection of peripheral lung cancers missed at CT: ROC analyses without and with localization.
    Li F; Arimura H; Suzuki K; Shiraishi J; Li Q; Abe H; Engelmann R; Sone S; MacMahon H; Doi K
    Radiology; 2005 Nov; 237(2):684-90. PubMed ID: 16244277
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Fast and adaptive detection of pulmonary nodules in thoracic CT images using a hierarchical vector quantization scheme.
    Han H; Li L; Han F; Song B; Moore W; Liang Z
    IEEE J Biomed Health Inform; 2015 Mar; 19(2):648-59. PubMed ID: 25486657
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Automated detection of lung nodules in CT scans: false-positive reduction with the radial-gradient index.
    Roy AS; Armato SG; Wilson A; Drukker K
    Med Phys; 2006 Apr; 33(4):1133-40. PubMed ID: 16696491
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Pulmonary nodule detection in CT images based on shape constraint CV model.
    Wang B; Tian X; Wang Q; Yang Y; Xie H; Zhang S; Gu L
    Med Phys; 2015 Mar; 42(3):1241-54. PubMed ID: 25735280
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Automated matching of pulmonary nodules: evaluation in serial screening chest CT.
    Tao C; Gierada DS; Zhu F; Pilgram TK; Wang JH; Bae KT
    AJR Am J Roentgenol; 2009 Mar; 192(3):624-8. PubMed ID: 19234256
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Ability of low-dose helical CT to distinguish between benign and malignant noncalcified lung nodules.
    Markowitz SB; Miller A; Miller J; Manowitz A; Kieding S; Sider L; Morabia A
    Chest; 2007 Apr; 131(4):1028-34. PubMed ID: 17426206
    [TBL] [Abstract][Full Text] [Related]  

  • 38. An automated CT based lung nodule detection scheme using geometric analysis of signed distance field.
    Pu J; Zheng B; Leader JK; Wang XH; Gur D
    Med Phys; 2008 Aug; 35(8):3453-61. PubMed ID: 18777905
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Improved detection of lung nodules on chest radiographs using a commercial computer-aided diagnosis system.
    Kakeda S; Moriya J; Sato H; Aoki T; Watanabe H; Nakata H; Oda N; Katsuragawa S; Yamamoto K; Doi K
    AJR Am J Roentgenol; 2004 Feb; 182(2):505-10. PubMed ID: 14736690
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Fast scanning tomosynthesis for the detection of pulmonary nodules: diagnostic performance compared with chest radiography, using multidetector-row computed tomography as the reference.
    Yamada Y; Jinzaki M; Hasegawa I; Shiomi E; Sugiura H; Abe T; Sato Y; Kuribayashi S; Ogawa K
    Invest Radiol; 2011 Aug; 46(8):471-7. PubMed ID: 21487302
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 15.