BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

313 related articles for article (PubMed ID: 31865281)

  • 1. Shape and margin-aware lung nodule classification in low-dose CT images via soft activation mapping.
    Lei Y; Tian Y; Shan H; Zhang J; Wang G; Kalra MK
    Med Image Anal; 2020 Feb; 60():101628. PubMed ID: 31865281
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Automatic Pulmonary Nodule Detection in CT Scans Using Convolutional Neural Networks Based on Maximum Intensity Projection.
    Zheng S; Guo J; Cui X; Veldhuis RNJ; Oudkerk M; van Ooijen PMA
    IEEE Trans Med Imaging; 2020 Mar; 39(3):797-805. PubMed ID: 31425026
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Improving Accuracy of Lung Nodule Classification Using Deep Learning with Focal Loss.
    Tran GS; Nghiem TP; Nguyen VT; Luong CM; Burie JC
    J Healthc Eng; 2019; 2019():5156416. PubMed ID: 30863524
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Lung Nodule Detection in CT Images Using a Raw Patch-Based Convolutional Neural Network.
    Wang Q; Shen F; Shen L; Huang J; Sheng W
    J Digit Imaging; 2019 Dec; 32(6):971-979. PubMed ID: 31062113
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Deep CNN models for pulmonary nodule classification: Model modification, model integration, and transfer learning.
    Zhao X; Qi S; Zhang B; Ma H; Qian W; Yao Y; Sun J
    J Xray Sci Technol; 2019; 27(4):615-629. PubMed ID: 31227682
    [TBL] [Abstract][Full Text] [Related]  

  • 6. 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]  

  • 7. An improved 3-D attention CNN with hybrid loss and feature fusion for pulmonary nodule classification.
    Huang YS; Wang TC; Huang SZ; Zhang J; Chen HM; Chang YC; Chang RF
    Comput Methods Programs Biomed; 2023 Feb; 229():107278. PubMed ID: 36463674
    [TBL] [Abstract][Full Text] [Related]  

  • 8. 3D multi-view squeeze-and-excitation convolutional neural network for lung nodule classification.
    Yang Y; Li X; Fu J; Han Z; Gao B
    Med Phys; 2023 Mar; 50(3):1905-1916. PubMed ID: 36639958
    [TBL] [Abstract][Full Text] [Related]  

  • 9. 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]  

  • 10. 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]  

  • 11. Multi-scale Convolutional Neural Networks for Lung Nodule Classification.
    Shen W; Zhou M; Yang F; Yang C; Tian J
    Inf Process Med Imaging; 2015; 24():588-99. PubMed ID: 26221705
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A semantic fidelity interpretable-assisted decision model for lung nodule classification.
    Zhan X; Long H; Gou F; Wu J
    Int J Comput Assist Radiol Surg; 2024 Apr; 19(4):625-633. PubMed ID: 38141069
    [TBL] [Abstract][Full Text] [Related]  

  • 13. 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]  

  • 14. Hyperparameter optimization and development of an advanced CNN-based technique for lung nodule assessment.
    Shivwanshi RR; Nirala N
    Phys Med Biol; 2023 Aug; 68(17):. PubMed ID: 37567211
    [No Abstract]   [Full Text] [Related]  

  • 15. 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]  

  • 16. Automated Pulmonary Nodule Classification in Computed Tomography Images Using a Deep Convolutional Neural Network Trained by Generative Adversarial Networks.
    Onishi Y; Teramoto A; Tsujimoto M; Tsukamoto T; Saito K; Toyama H; Imaizumi K; Fujita H
    Biomed Res Int; 2019; 2019():6051939. PubMed ID: 30719445
    [TBL] [Abstract][Full Text] [Related]  

  • 17. 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]  

  • 18. Classification of benign and malignant lung nodules from CT images based on hybrid features.
    Zhang G; Yang Z; Gong L; Jiang S; Wang L
    Phys Med Biol; 2019 Jun; 64(12):125011. PubMed ID: 31141794
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Automatic Scoring of Multiple Semantic Attributes With Multi-Task Feature Leverage: A Study on Pulmonary Nodules in CT Images.
    Sihong Chen ; Jing Qin ; Xing Ji ; Baiying Lei ; Tianfu Wang ; Dong Ni ; Jie-Zhi Cheng
    IEEE Trans Med Imaging; 2017 Mar; 36(3):802-814. PubMed ID: 28113928
    [TBL] [Abstract][Full Text] [Related]  

  • 20. A manifold learning regularization approach to enhance 3D CT image-based lung nodule classification.
    Ren Y; Tsai MY; Chen L; Wang J; Li S; Liu Y; Jia X; Shen C
    Int J Comput Assist Radiol Surg; 2020 Feb; 15(2):287-295. PubMed ID: 31768885
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 16.