311 related articles for article (PubMed ID: 35092608)
1. Automatic pulmonary ground-glass opacity nodules detection and classification based on 3D neural network.
Ma H; Guo H; Zhao M; Qi S; Li H; Tian Y; Li Z; Zhang G; Yao Y; Qian W
Med Phys; 2022 Apr; 49(4):2555-2569. PubMed ID: 35092608
[TBL] [Abstract][Full Text] [Related]
2. Pulmonary nodules detection assistant platform: An effective computer aided system for early pulmonary nodules detection in physical examination.
Han Y; Qi H; Wang L; Chen C; Miao J; Xu H; Wang Z; Guo Z; Xu Q; Lin Q; Liu H; Lu J; Liang F; Feng W; Li H; Liu Y
Comput Methods Programs Biomed; 2022 Apr; 217():106680. PubMed ID: 35176595
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. 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]
5. Detection of pulmonary nodules based on a multiscale feature 3D U-Net convolutional neural network of transfer learning.
Tang S; Yang M; Bai J
PLoS One; 2020; 15(8):e0235672. PubMed ID: 32845877
[TBL] [Abstract][Full Text] [Related]
6. Computerized detection of lung nodules in thin-section CT images by use of selective enhancement filters and an automated rule-based classifier.
Li Q; Li F; Doi K
Acad Radiol; 2008 Feb; 15(2):165-75. PubMed ID: 18206615
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Automatic detection and segmentation of ground glass opacity nodules.
Zhou J; Chang S; Metaxas DN; Zhao B; Schwartz LH; Ginsberg MS
Med Image Comput Comput Assist Interv; 2006; 9(Pt 1):784-91. PubMed ID: 17354962
[TBL] [Abstract][Full Text] [Related]
9. Pulmonary Nodule Detection Based on Multiscale Feature Fusion.
Zhao Y; Wang Z; Liu X; Chen Q; Li C; Zhao H; Wang Z
Comput Math Methods Med; 2022; 2022():8903037. PubMed ID: 36590762
[TBL] [Abstract][Full Text] [Related]
10. A cascade and heterogeneous neural network for CT pulmonary nodule detection and its evaluation on both phantom and patient data.
Xiao Y; Wang X; Li Q; Fan R; Chen R; Shao Y; Chen Y; Gao Y; Liu A; Chen L; Liu S
Comput Med Imaging Graph; 2021 Jun; 90():101889. PubMed ID: 33848755
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Automated pulmonary nodule detection in CT images using 3D deep squeeze-and-excitation networks.
Gong L; Jiang S; Yang Z; Zhang G; Wang L
Int J Comput Assist Radiol Surg; 2019 Nov; 14(11):1969-1979. PubMed ID: 31028657
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. Clinical, pathological and thin-section CT features of persistent multiple ground-glass opacity nodules: comparison with solitary ground-glass opacity nodule.
Kim TJ; Goo JM; Lee KW; Park CM; Lee HJ
Lung Cancer; 2009 May; 64(2):171-8. PubMed ID: 18799230
[TBL] [Abstract][Full Text] [Related]
15. 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]
16. An automatic method for ground glass opacity nodule detection and segmentation from CT studies.
Zhou J; Chang S; Metaxas DN; Zhao B; Ginsberg MS; Schwartz LH
Conf Proc IEEE Eng Med Biol Soc; 2006; 2006():3062-5. PubMed ID: 17946543
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Hierarchical approach for pulmonary-nodule identification from CT images using YOLO model and a 3D neural network classifier.
Ahmadyar Y; Kamali-Asl A; Arabi H; Samimi R; Zaidi H
Radiol Phys Technol; 2024 Mar; 17(1):124-134. PubMed ID: 37980315
[TBL] [Abstract][Full Text] [Related]
19. MSANet: Multiscale Aggregation Network Integrating Spatial and Channel Information for Lung Nodule Detection.
Guo Z; Zhao L; Yuan J; Yu H
IEEE J Biomed Health Inform; 2022 Jun; 26(6):2547-2558. PubMed ID: 34847048
[TBL] [Abstract][Full Text] [Related]
20. LGDNet: local feature coupling global representations network for pulmonary nodules detection.
Chi J; Zhao J; Wang S; Yu X; Wu C
Med Biol Eng Comput; 2024 Jul; 62(7):1991-2004. PubMed ID: 38429443
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
