751 related articles for article (PubMed ID: 31768885)
1. 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]
2. Classification of lung nodules in CT scans using three-dimensional deep convolutional neural networks with a checkpoint ensemble method.
Jung H; Kim B; Lee I; Lee J; Kang J
BMC Med Imaging; 2018 Dec; 18(1):48. PubMed ID: 30509191
[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. Pulmonary nodule detection in CT scans with equivariant CNNs.
Winkels M; Cohen TS
Med Image Anal; 2019 Jul; 55():15-26. PubMed ID: 31003034
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. 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]
7. Knowledge-based Collaborative Deep Learning for Benign-Malignant Lung Nodule Classification on Chest CT.
Xie Y; Xia Y; Zhang J; Song Y; Feng D; Fulham M; Cai W
IEEE Trans Med Imaging; 2019 Apr; 38(4):991-1004. PubMed ID: 30334786
[TBL] [Abstract][Full Text] [Related]
8. Semi-supervised adversarial model for benign-malignant lung nodule classification on chest CT.
Xie Y; Zhang J; Xia Y
Med Image Anal; 2019 Oct; 57():237-248. PubMed ID: 31352126
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. 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]
11. 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]
12. 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]
13. Incorporating automatically learned pulmonary nodule attributes into a convolutional neural network to improve accuracy of benign-malignant nodule classification.
Dai Y; Yan S; Zheng B; Song C
Phys Med Biol; 2018 Dec; 63(24):245004. PubMed ID: 30524071
[TBL] [Abstract][Full Text] [Related]
14. An Improved Convolution Neural Network and Modified Regularized K-Means-Based Automatic Lung Nodule Detection and Classification.
M DL; M DP
J Digit Imaging; 2023 Aug; 36(4):1431-1446. PubMed ID: 37106212
[TBL] [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. S-Net: an S-shaped network for nodule detection in 3D CT images.
Zhang J; Zou W; Hu N; Zhang B; Wang J
Phys Med Biol; 2024 Apr; 69(7):. PubMed ID: 38382097
[No Abstract] [Full Text] [Related]
17. 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]
18. Pulmonary nodules: a quantitative method of diagnosis by evaluating nodule perimeter difference to approximate oval using three-dimensional CT images.
Kamiya H; Murayama S; Kakinohana Y; Miyara T
Clin Imaging; 2011; 35(2):123-6. PubMed ID: 21377050
[TBL] [Abstract][Full Text] [Related]
19. Self-Supervised Transfer Learning Based on Domain Adaptation for Benign-Malignant Lung Nodule Classification on Thoracic CT.
Huang H; Wu R; Li Y; Peng C
IEEE J Biomed Health Inform; 2022 Aug; 26(8):3860-3871. PubMed ID: 35503850
[TBL] [Abstract][Full Text] [Related]
20. Computer-Aided Diagnosis (CAD) of Pulmonary Nodule of Thoracic CT Image Using Transfer Learning.
Zhang S; Sun F; Wang N; Zhang C; Yu Q; Zhang M; Babyn P; Zhong H
J Digit Imaging; 2019 Dec; 32(6):995-1007. PubMed ID: 31044393
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
