516 related articles for article (PubMed ID: 30334786)
1. 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]
2. 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]
3. 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]
4. Automated Lung Nodule Detection and Classification Using Deep Learning Combined with Multiple Strategies.
Nasrullah N; Sang J; Alam MS; Mateen M; Cai B; Hu H
Sensors (Basel); 2019 Aug; 19(17):. PubMed ID: 31466261
[TBL] [Abstract][Full Text] [Related]
5. Multi-view secondary input collaborative deep learning for lung nodule 3D segmentation.
Dong X; Xu S; Liu Y; Wang A; Saripan MI; Li L; Zhang X; Lu L
Cancer Imaging; 2020 Aug; 20(1):53. PubMed ID: 32738913
[TBL] [Abstract][Full Text] [Related]
6. 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]
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. Robust explanation supervision for false positive reduction in pulmonary nodule detection.
Zhao Q; Chang CW; Yang X; Zhao L
Med Phys; 2024 Mar; 51(3):1687-1701. PubMed ID: 38224306
[TBL] [Abstract][Full Text] [Related]
9. 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]
10. 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]
11. 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]
12. 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]
13. Nodule-CLIP: Lung nodule classification based on multi-modal contrastive learning.
Sun L; Zhang M; Lu Y; Zhu W; Yi Y; Yan F
Comput Biol Med; 2024 Jun; 175():108505. PubMed ID: 38688129
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge.
Setio AAA; Traverso A; de Bel T; Berens MSN; Bogaard CVD; Cerello P; Chen H; Dou Q; Fantacci ME; Geurts B; Gugten RV; Heng PA; Jansen B; de Kaste MMJ; Kotov V; Lin JY; Manders JTMC; Sóñora-Mengana A; García-Naranjo JC; Papavasileiou E; Prokop M; Saletta M; Schaefer-Prokop CM; Scholten ET; Scholten L; Snoeren MM; Torres EL; Vandemeulebroucke J; Walasek N; Zuidhof GCA; Ginneken BV; Jacobs C
Med Image Anal; 2017 Dec; 42():1-13. PubMed ID: 28732268
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Detection of pulmonary ground-glass opacity based on deep learning computer artificial intelligence.
Ye W; Gu W; Guo X; Yi P; Meng Y; Han F; Yu L; Chen Y; Zhang G; Wang X
Biomed Eng Online; 2019 Jan; 18(1):6. PubMed ID: 30670024
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. 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]
20. 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]
[Next] [New Search]
