421 related articles for article (PubMed ID: 29154123)
21. 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]
22. 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]
23. Computer-aided detection of lung nodules using outer surface features.
Demir Ö; Yılmaz Çamurcu A
Biomed Mater Eng; 2015; 26 Suppl 1():S1213-22. PubMed ID: 26405880
[TBL] [Abstract][Full Text] [Related]
24. Computer-aided detection of lung nodules: false positive reduction using a 3D gradient field method and 3D ellipsoid fitting.
Ge Z; Sahiner B; Chan HP; Hadjiiski LM; Cascade PN; Bogot N; Kazerooni EA; Wei J; Zhou C
Med Phys; 2005 Aug; 32(8):2443-54. PubMed ID: 16193773
[TBL] [Abstract][Full Text] [Related]
25. 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]
26. JOURNAL CLUB: Computer-Aided Detection of Lung Nodules on CT With a Computerized Pulmonary Vessel Suppressed Function.
Lo SB; Freedman MT; Gillis LB; White CS; Mun SK
AJR Am J Roentgenol; 2018 Mar; 210(3):480-488. PubMed ID: 29336601
[TBL] [Abstract][Full Text] [Related]
27. Segmentation of pulmonary nodules in CT images based on 3D-UNET combined with three-dimensional conditional random field optimization.
Wu W; Gao L; Duan H; Huang G; Ye X; Nie S
Med Phys; 2020 Sep; 47(9):4054-4063. PubMed ID: 32428969
[TBL] [Abstract][Full Text] [Related]
28. 3D gray density coding feature for benign-malignant pulmonary nodule classification on chest CT.
Zheng B; Yang D; Zhu Y; Liu Y; Hu J; Bai C
Med Phys; 2021 Dec; 48(12):7826-7836. PubMed ID: 34655238
[TBL] [Abstract][Full Text] [Related]
29. Content-Based Image Retrieval System for Pulmonary Nodules: Assisting Radiologists in Self-Learning and Diagnosis of Lung Cancer.
Dhara AK; Mukhopadhyay S; Dutta A; Garg M; Khandelwal N
J Digit Imaging; 2017 Feb; 30(1):63-77. PubMed ID: 27678255
[TBL] [Abstract][Full Text] [Related]
30. Texture feature analysis for computer-aided diagnosis on pulmonary nodules.
Han F; Wang H; Zhang G; Han H; Song B; Li L; Moore W; Lu H; Zhao H; Liang Z
J Digit Imaging; 2015 Feb; 28(1):99-115. PubMed ID: 25117512
[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. Fully automatic detection of lung nodules in CT images using a hybrid feature set.
Shaukat F; Raja G; Gooya A; Frangi AF
Med Phys; 2017 Jul; 44(7):3615-3629. PubMed ID: 28409834
[TBL] [Abstract][Full Text] [Related]
33. Development of a modified 3D region proposal network for lung nodule detection in computed tomography scans: a secondary analysis of lung nodule datasets.
Lin CY; Guo SM; Lien JJ; Tsai TY; Liu YS; Lai CH; Hsu IL; Chang CC; Tseng YL
Cancer Imaging; 2024 Mar; 24(1):40. PubMed ID: 38509635
[TBL] [Abstract][Full Text] [Related]
34. 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]
35. Detection of pulmonary nodules in CT images based on fuzzy integrated active contour model and hybrid parametric mixture model.
Li B; Chen K; Tian L; Yeboah Y; Ou S
Comput Math Methods Med; 2013; 2013():515386. PubMed ID: 23690876
[TBL] [Abstract][Full Text] [Related]
36. Soft computing approach to 3D lung nodule segmentation in CT.
Badura P; Pietka E
Comput Biol Med; 2014 Oct; 53():230-43. PubMed ID: 25173811
[TBL] [Abstract][Full Text] [Related]
37. False positive reduction in pulmonary nodule classification using 3D texture and edge feature in CT images.
Wang B; Si S; Zhao H; Zhu H; Dou S
Technol Health Care; 2021; 29(6):1071-1088. PubMed ID: 30664518
[TBL] [Abstract][Full Text] [Related]
38. 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]
39. 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]
40. Automatic detection of multisize pulmonary nodules in CT images: Large-scale validation of the false-positive reduction step.
Gupta A; Saar T; Martens O; Moullec YL
Med Phys; 2018 Mar; 45(3):1135-1149. PubMed ID: 29359462
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]