358 related articles for article (PubMed ID: 31003034)
21. 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]
22. Pulmonary nodule detection using hybrid two-stage 3D CNNs.
Tan M; Wu F; Yang B; Ma J; Kong D; Chen Z; Long D
Med Phys; 2020 Aug; 47(8):3376-3388. PubMed ID: 32239521
[TBL] [Abstract][Full Text] [Related]
23. 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]
24. Automatic classification of pulmonary peri-fissural nodules in computed tomography using an ensemble of 2D views and a convolutional neural network out-of-the-box.
Ciompi F; de Hoop B; van Riel SJ; Chung K; Scholten ET; Oudkerk M; de Jong PA; Prokop M; van Ginneken B
Med Image Anal; 2015 Dec; 26(1):195-202. PubMed ID: 26458112
[TBL] [Abstract][Full Text] [Related]
25. 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]
26. 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]
27. Toward an Expert Level of Lung Cancer Detection and Classification Using a Deep Convolutional Neural Network.
Zhang C; Sun X; Dang K; Li K; Guo XW; Chang J; Yu ZQ; Huang FY; Wu YS; Liang Z; Liu ZY; Zhang XG; Gao XL; Huang SH; Qin J; Feng WN; Zhou T; Zhang YB; Fang WJ; Zhao MF; Yang XN; Zhou Q; Wu YL; Zhong WZ
Oncologist; 2019 Sep; 24(9):1159-1165. PubMed ID: 30996009
[TBL] [Abstract][Full Text] [Related]
28. MD-NDNet: a multi-dimensional convolutional neural network for false-positive reduction in pulmonary nodule detection.
Wu Z; Ge R; Shi G; Zhang L; Chen Y; Luo L; Cao Y; Yu H
Phys Med Biol; 2020 Dec; 65(23):235053. PubMed ID: 32698172
[TBL] [Abstract][Full Text] [Related]
29. Pulmonary nodule detection on chest radiographs using balanced convolutional neural network and classic candidate detection.
Chen S; Han Y; Lin J; Zhao X; Kong P
Artif Intell Med; 2020 Jul; 107():101881. PubMed ID: 32828440
[TBL] [Abstract][Full Text] [Related]
30. A Two-Stage Convolutional Neural Networks for Lung Nodule Detection.
Cao H; Liu H; Song E; Ma G; Xu X; Jin R; Liu T; Hung CC
IEEE J Biomed Health Inform; 2020 Jul; 24(7):2006-2015. PubMed ID: 31905154
[TBL] [Abstract][Full Text] [Related]
31. Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks.
Setio AA; Ciompi F; Litjens G; Gerke P; Jacobs C; van Riel SJ; Wille MM; Naqibullah M; Sanchez CI; van Ginneken B
IEEE Trans Med Imaging; 2016 May; 35(5):1160-1169. PubMed ID: 26955024
[TBL] [Abstract][Full Text] [Related]
32. A Novel Deep Learning Model Based on Multi-Scale and Multi-View for Detection of Pulmonary Nodules.
Chen Y; Hou X; Yang Y; Ge Q; Zhou Y; Nie S
J Digit Imaging; 2023 Apr; 36(2):688-699. PubMed ID: 36544067
[TBL] [Abstract][Full Text] [Related]
33. 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]
34. 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]
35. Attention-embedded complementary-stream CNN for false positive reduction in pulmonary nodule detection.
Sun L; Wang Z; Pu H; Yuan G; Guo L; Pu T; Peng Z
Comput Biol Med; 2021 Jun; 133():104357. PubMed ID: 33836449
[TBL] [Abstract][Full Text] [Related]
36. 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]
37. A deep 3D residual CNN for false-positive reduction in pulmonary nodule detection.
Jin H; Li Z; Tong R; Lin L
Med Phys; 2018 May; 45(5):2097-2107. PubMed ID: 29500816
[TBL] [Abstract][Full Text] [Related]
38. 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]
39. Recurrent attention network for false positive reduction in the detection of pulmonary nodules in thoracic CT scans.
Farhangi MM; Petrick N; Sahiner B; Frigui H; Amini AA; Pezeshk A
Med Phys; 2020 Jun; 47(5):2150-2160. PubMed ID: 32030769
[TBL] [Abstract][Full Text] [Related]
40. 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]
[Previous] [Next] [New Search]