BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

298 related articles for article (PubMed ID: 32828440)

  • 1. Pulmonary nodule detection on chest radiographs using balanced convolutional neural network and classic candidate detection.
    Chen S; Han Y; Lin J; Zhao X; Kong P
    Artif Intell Med; 2020 Jul; 107():101881. PubMed ID: 32828440
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Development and evaluation of a computer-aided diagnostic scheme for lung nodule detection in chest radiographs by means of two-stage nodule enhancement with support vector classification.
    Chen S; Suzuki K; MacMahon H
    Med Phys; 2011 Apr; 38(4):1844-58. PubMed ID: 21626918
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Computerized detection of lung nodules by means of "virtual dual-energy" radiography.
    Chen S; Suzuki K
    IEEE Trans Biomed Eng; 2013 Feb; 60(2):369-78. PubMed ID: 23193306
    [TBL] [Abstract][Full Text] [Related]  

  • 4. 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]  

  • 5. A CAD system for pulmonary nodule prediction based on deep three-dimensional convolutional neural networks and ensemble learning.
    Huang W; Xue Y; Wu Y
    PLoS One; 2019; 14(7):e0219369. PubMed ID: 31299053
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Automatic lung nodule detection using a 3D deep convolutional neural network combined with a multi-scale prediction strategy in chest CTs.
    Gu Y; Lu X; Yang L; Zhang B; Yu D; Zhao Y; Gao L; Wu L; Zhou T
    Comput Biol Med; 2018 Dec; 103():220-231. PubMed ID: 30390571
    [TBL] [Abstract][Full Text] [Related]  

  • 7. 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]  

  • 8. Two-stage lung nodule detection framework using enhanced UNet and convolutional LSTM networks in CT images.
    Akila Agnes S; Anitha J; Arun Solomon A
    Comput Biol Med; 2022 Oct; 149():106059. PubMed ID: 36087510
    [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. One-stage pulmonary nodule detection using 3-D DCNN with feature fusion and attention mechanism in CT image.
    Huang YS; Chou PR; Chen HM; Chang YC; Chang RF
    Comput Methods Programs Biomed; 2022 Jun; 220():106786. PubMed ID: 35398579
    [TBL] [Abstract][Full Text] [Related]  

  • 11. 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]  

  • 12. A parameterized logarithmic image processing method with Laplacian of Gaussian filtering for lung nodule enhancement in chest radiographs.
    Chen S; Yao L; Chen B
    Med Biol Eng Comput; 2016 Nov; 54(11):1793-1806. PubMed ID: 27016368
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Expert knowledge-infused deep learning for automatic lung nodule detection.
    Tan J; Huo Y; Liang Z; Li L
    J Xray Sci Technol; 2019; 27(1):17-35. PubMed ID: 30452432
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Computer-aided nodule detection system: results in an unselected series of consecutive chest radiographs.
    Li F; Engelmann R; Armato SG; MacMahon H
    Acad Radiol; 2015 Apr; 22(4):475-80. PubMed ID: 25592026
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Fast and fully-automated detection and segmentation of pulmonary nodules in thoracic CT scans using deep convolutional neural networks.
    Huang X; Sun W; Tseng TB; Li C; Qian W
    Comput Med Imaging Graph; 2019 Jun; 74():25-36. PubMed ID: 30954678
    [TBL] [Abstract][Full Text] [Related]  

  • 16. An efficient multi-path 3D convolutional neural network for false-positive reduction of pulmonary nodule detection.
    Yuan H; Fan Z; Wu Y; Cheng J
    Int J Comput Assist Radiol Surg; 2021 Dec; 16(12):2269-2277. PubMed ID: 34449037
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Attention-embedded complementary-stream CNN for false positive reduction in pulmonary nodule detection.
    Sun L; Wang Z; Pu H; Yuan G; Guo L; Pu T; Peng Z
    Comput Biol Med; 2021 Jun; 133():104357. PubMed ID: 33836449
    [TBL] [Abstract][Full Text] [Related]  

  • 19. The detection of lung cancer using massive artificial neural network based on soft tissue technique.
    Rajagopalan K; Babu S
    BMC Med Inform Decis Mak; 2020 Oct; 20(1):282. PubMed ID: 33129343
    [TBL] [Abstract][Full Text] [Related]  

  • 20. 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]  

    [Next]    [New Search]
    of 15.