631 related articles for article (PubMed ID: 31202567)
1. Artificial intelligence and radiomics in pulmonary nodule management: current status and future applications.
Ather S; Kadir T; Gleeson F
Clin Radiol; 2020 Jan; 75(1):13-19. PubMed ID: 31202567
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. Identifying pulmonary nodules or masses on chest radiography using deep learning: external validation and strategies to improve clinical practice.
Liang CH; Liu YC; Wu MT; Garcia-Castro F; Alberich-Bayarri A; Wu FZ
Clin Radiol; 2020 Jan; 75(1):38-45. PubMed ID: 31521323
[TBL] [Abstract][Full Text] [Related]
4. Deep Convolutional Neural Network-based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs.
Sim Y; Chung MJ; Kotter E; Yune S; Kim M; Do S; Han K; Kim H; Yang S; Lee DJ; Choi BW
Radiology; 2020 Jan; 294(1):199-209. PubMed ID: 31714194
[TBL] [Abstract][Full Text] [Related]
5. An Artificial Intelligence-Based Chest X-ray Model on Human Nodule Detection Accuracy From a Multicenter Study.
Homayounieh F; Digumarthy S; Ebrahimian S; Rueckel J; Hoppe BF; Sabel BO; Conjeti S; Ridder K; Sistermanns M; Wang L; Preuhs A; Ghesu F; Mansoor A; Moghbel M; Botwin A; Singh R; Cartmell S; Patti J; Huemmer C; Fieselmann A; Joerger C; Mirshahzadeh N; Muse V; Kalra M
JAMA Netw Open; 2021 Dec; 4(12):e2141096. PubMed ID: 34964851
[TBL] [Abstract][Full Text] [Related]
6. Evolving the pulmonary nodules diagnosis from classical approaches to deep learning-aided decision support: three decades' development course and future prospect.
Liu B; Chi W; Li X; Li P; Liang W; Liu H; Wang W; He J
J Cancer Res Clin Oncol; 2020 Jan; 146(1):153-185. PubMed ID: 31786740
[TBL] [Abstract][Full Text] [Related]
7. Artificial intelligence aided diagnosis of pulmonary nodules segmentation and feature extraction.
Tang TW; Lin WY; Liang JD; Li KM
Clin Radiol; 2023 Jun; 78(6):437-443. PubMed ID: 37028999
[TBL] [Abstract][Full Text] [Related]
8. 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]
9. [Performance of Deep-learning-based Artificial Intelligence on Detection of Pulmonary Nodules in Chest CT].
Li X; Guo F; Zhou Z; Zhang F; Wang Q; Peng Z; Su D; Fan Y; Wang Y
Zhongguo Fei Ai Za Zhi; 2019 Jun; 22(6):336-340. PubMed ID: 31196366
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. Overview of Computer Aided Detection and Computer Aided Diagnosis Systems for Lung Nodule Detection in Computed Tomography.
Ziyad SR; Radha V; Vayyapuri T
Curr Med Imaging Rev; 2020; 16(1):16-26. PubMed ID: 31989890
[TBL] [Abstract][Full Text] [Related]
12. A Simple Method to Train the AI Diagnosis Model of Pulmonary Nodules.
He Z; Lv W; Hu J
Comput Math Methods Med; 2020; 2020():2812874. PubMed ID: 32802147
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. 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]
15. Improving Accuracy of Lung Nodule Classification Using Deep Learning with Focal Loss.
Tran GS; Nghiem TP; Nguyen VT; Luong CM; Burie JC
J Healthc Eng; 2019; 2019():5156416. PubMed ID: 30863524
[TBL] [Abstract][Full Text] [Related]
16. 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]
17. Deep Learning for the Classification of Small (≤2 cm) Pulmonary Nodules on CT Imaging: A Preliminary Study.
Chae KJ; Jin GY; Ko SB; Wang Y; Zhang H; Choi EJ; Choi H
Acad Radiol; 2020 Apr; 27(4):e55-e63. PubMed ID: 31780395
[TBL] [Abstract][Full Text] [Related]
18. The Added Value of Computer-aided Detection of Small Pulmonary Nodules and Missed Lung Cancers.
Cai J; Xu D; Liu S; Cham MD
J Thorac Imaging; 2018 Nov; 33(6):390-395. PubMed ID: 30239461
[TBL] [Abstract][Full Text] [Related]
19. [Research progress on computed tomography image detection and classification of pulmonary nodule based on deep learning].
Wang J; Lin L; Zhao S; Wu X; Wu S
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2019 Aug; 36(4):670-676. PubMed ID: 31441270
[TBL] [Abstract][Full Text] [Related]
20. 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]
[Next] [New Search]