These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

523 related articles for article (PubMed ID: 29852959)

  • 1. Small lung nodules detection based on local variance analysis and probabilistic neural network.
    Woźniak M; Połap D; Capizzi G; Sciuto GL; Kośmider L; Frankiewicz K
    Comput Methods Programs Biomed; 2018 Jul; 161():173-180. PubMed ID: 29852959
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose computed tomography.
    Suzuki K; Armato SG; Li F; Sone S; Doi K
    Med Phys; 2003 Jul; 30(7):1602-17. PubMed ID: 12906178
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Pulmonary Nodule Classification with Deep Convolutional Neural Networks on Computed Tomography Images.
    Li W; Cao P; Zhao D; Wang J
    Comput Math Methods Med; 2016; 2016():6215085. PubMed ID: 28070212
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. 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]  

  • 6. 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]  

  • 7. Improved lung nodule diagnosis accuracy using lung CT images with uncertain class.
    Wang Z; Xin J; Sun P; Lin Z; Yao Y; Gao X
    Comput Methods Programs Biomed; 2018 Aug; 162():197-209. PubMed ID: 29903487
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 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]  

  • 9. 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]  

  • 10. Automatic classification of pulmonary peri-fissural nodules in computed tomography using an ensemble of 2D views and a convolutional neural network out-of-the-box.
    Ciompi F; de Hoop B; van Riel SJ; Chung K; Scholten ET; Oudkerk M; de Jong PA; Prokop M; van Ginneken B
    Med Image Anal; 2015 Dec; 26(1):195-202. PubMed ID: 26458112
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. 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]  

  • 13. Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose CT by use of massive training artificial neural network.
    Suzuki K; Li F; Sone S; Doi K
    IEEE Trans Med Imaging; 2005 Sep; 24(9):1138-50. PubMed ID: 16156352
    [TBL] [Abstract][Full Text] [Related]  

  • 14. 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]  

  • 15. A new method based on MTANNs for cutting down false-positives: an evaluation on different versions of commercial pulmonary nodule detection CAD software.
    Shi Z; Si C; Feng Y; He L; Suzuki K
    Biomed Mater Eng; 2014; 24(6):2839-46. PubMed ID: 25226989
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Supervised probabilistic segmentation of pulmonary nodules in CT scans.
    van Ginneken B
    Med Image Comput Comput Assist Interv; 2006; 9(Pt 2):912-9. PubMed ID: 17354860
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Image-processing technique for suppressing ribs in chest radiographs by means of massive training artificial neural network (MTANN).
    Suzuki K; Abe H; MacMahon H; Doi K
    IEEE Trans Med Imaging; 2006 Apr; 25(4):406-16. PubMed ID: 16608057
    [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. Evaluation of automated lung nodule detection on low-dose computed tomography scans from a lung cancer screening program(1).
    Armato SG; Roy AS; Macmahon H; Li F; Doi K; Sone S; Altman MB
    Acad Radiol; 2005 Mar; 12(3):337-46. PubMed ID: 15766694
    [TBL] [Abstract][Full Text] [Related]  

  • 20. False-positive reduction in computer-aided diagnostic scheme for detecting nodules in chest radiographs by means of massive training artificial neural network.
    Suzuki K; Shiraishi J; Abe H; MacMahon H; Doi K
    Acad Radiol; 2005 Feb; 12(2):191-201. PubMed ID: 15721596
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 27.