177 related articles for article (PubMed ID: 36929569)
1. MS-Net: Learning to assess the malignant status of a lung nodule by a radiologist and her peers.
Dai D; Dong C; Li Z; Xu S
J Appl Clin Med Phys; 2023 Jul; 24(7):e13964. PubMed ID: 36929569
[TBL] [Abstract][Full Text] [Related]
2. Automatic Scoring of Multiple Semantic Attributes With Multi-Task Feature Leverage: A Study on Pulmonary Nodules in CT Images.
Sihong Chen ; Jing Qin ; Xing Ji ; Baiying Lei ; Tianfu Wang ; Dong Ni ; Jie-Zhi Cheng
IEEE Trans Med Imaging; 2017 Mar; 36(3):802-814. PubMed ID: 28113928
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. 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]
5. 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]
6. Measuring Interobserver Disagreement in Rating Diagnostic Characteristics of Pulmonary Nodule Using the Lung Imaging Database Consortium and Image Database Resource Initiative.
Lin H; Huang C; Wang W; Luo J; Yang X; Liu Y
Acad Radiol; 2017 Apr; 24(4):401-410. PubMed ID: 28169141
[TBL] [Abstract][Full Text] [Related]
7. A new computationally efficient CAD system for pulmonary nodule detection in CT imagery.
Messay T; Hardie RC; Rogers SK
Med Image Anal; 2010 Jun; 14(3):390-406. PubMed ID: 20346728
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. Neural network-based computer-aided diagnosis in distinguishing malignant from benign solitary pulmonary nodules by computed tomography.
Chen H; Wang XH; Ma DQ; Ma BR
Chin Med J (Engl); 2007 Jul; 120(14):1211-5. PubMed ID: 17697569
[TBL] [Abstract][Full Text] [Related]
10. Res-trans networks for lung nodule classification.
Liu D; Liu F; Tie Y; Qi L; Wang F
Int J Comput Assist Radiol Surg; 2022 Jun; 17(6):1059-1068. PubMed ID: 35290646
[TBL] [Abstract][Full Text] [Related]
11. Learning From Ambiguous Labels for Lung Nodule Malignancy Prediction.
Liao Z; Xie Y; Hu S; Xia Y
IEEE Trans Med Imaging; 2022 Jul; 41(7):1874-1884. PubMed ID: 35130152
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. 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]
14. 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]
15. Semantic characteristic grading of pulmonary nodules based on deep neural networks.
Liu C; Zhao R; Pang M
BMC Med Imaging; 2023 Oct; 23(1):156. PubMed ID: 37833636
[TBL] [Abstract][Full Text] [Related]
16. Assessment of radiologist performance in the detection of lung nodules: dependence on the definition of "truth".
Armato SG; Roberts RY; Kocherginsky M; Aberle DR; Kazerooni EA; Macmahon H; van Beek EJ; Yankelevitz D; McLennan G; McNitt-Gray MF; Meyer CR; Reeves AP; Caligiuri P; Quint LE; Sundaram B; Croft BY; Clarke LP
Acad Radiol; 2009 Jan; 16(1):28-38. PubMed ID: 19064209
[TBL] [Abstract][Full Text] [Related]
17. A Segmentation Framework of Pulmonary Nodules in Lung CT Images.
Mukhopadhyay S
J Digit Imaging; 2016 Feb; 29(1):86-103. PubMed ID: 26055544
[TBL] [Abstract][Full Text] [Related]
18. 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]
19. 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]
20. An adaptive morphology based segmentation technique for lung nodule detection in thoracic CT image.
Halder A; Chatterjee S; Dey D; Kole S; Munshi S
Comput Methods Programs Biomed; 2020 Dec; 197():105720. PubMed ID: 32877818
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]