133 related articles for article (PubMed ID: 33075637)
1. Re-Identification and growth detection of pulmonary nodules without image registration using 3D siamese neural networks.
Rafael-Palou X; Aubanell A; Bonavita I; Ceresa M; Piella G; Ribas V; González Ballester MA
Med Image Anal; 2021 Jan; 67():101823. PubMed ID: 33075637
[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. 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. 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]
5. 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]
6. Pulmonary nodule registration in serial CT scans based on rib anatomy and nodule template matching.
Shi J; Sahiner B; Chan HP; Hadjiiski L; Zhou C; Cascade PN; Bogot N; Kazerooni EA; Wu YT; Wei J
Med Phys; 2007 Apr; 34(4):1336-47. PubMed ID: 17500464
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. 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]
9. 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]
10. Deep convolutional neural networks for multiplanar lung nodule detection: Improvement in small nodule identification.
Zheng S; Cornelissen LJ; Cui X; Jing X; Veldhuis RNJ; Oudkerk M; van Ooijen PMA
Med Phys; 2021 Feb; 48(2):733-744. PubMed ID: 33300162
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. 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]
13. Registration of lung nodules using a semi-rigid model: method and preliminary results.
Sun S; Rubin GD; Paik D; Steiner RM; Zhuge F; Napel S
Med Phys; 2007 Feb; 34(2):613-26. PubMed ID: 17388179
[TBL] [Abstract][Full Text] [Related]
14. Minimum perceivable size difference: how well can radiologists visually detect a change in lung nodule size from CT images?
Solomon J; Ebner L; Christe A; Peters A; Munz J; Löbelenz L; Klaus J; Richards T; Samei E; Roos JE
Eur Radiol; 2021 Apr; 31(4):1947-1955. PubMed ID: 32997175
[TBL] [Abstract][Full Text] [Related]
15. Attribute-guided image generation of three-dimensional computed tomography images of lung nodules using a generative adversarial network.
Nishio M; Muramatsu C; Noguchi S; Nakai H; Fujimoto K; Sakamoto R; Fujita H
Comput Biol Med; 2020 Nov; 126():104032. PubMed ID: 33045649
[TBL] [Abstract][Full Text] [Related]
16. Data analysis of the Lung Imaging Database Consortium and Image Database Resource Initiative.
Wang W; Luo J; Yang X; Lin H
Acad Radiol; 2015 Apr; 22(4):488-95. PubMed ID: 25601306
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. 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]
19. 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]
20. Integration of convolutional neural networks for pulmonary nodule malignancy assessment in a lung cancer classification pipeline.
Bonavita I; Rafael-Palou X; Ceresa M; Piella G; Ribas V; González Ballester MA
Comput Methods Programs Biomed; 2020 Mar; 185():105172. PubMed ID: 31710985
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]