These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
174 related articles for article (PubMed ID: 31229761)
1. Fusing learned representations from Riesz Filters and Deep CNN for lung tissue classification. Joyseeree R; Otálora S; Müller H; Depeursinge A Med Image Anal; 2019 Aug; 56():172-183. PubMed ID: 31229761 [TBL] [Abstract][Full Text] [Related]
2. Multiscale lung texture signature learning using the Riesz transform. Depeursinge A; Foncubierta-Rodriguez A; Van de Ville D; Müller H Med Image Comput Comput Assist Interv; 2012; 15(Pt 3):517-24. PubMed ID: 23286170 [TBL] [Abstract][Full Text] [Related]
3. Deep CNN models for pulmonary nodule classification: Model modification, model integration, and transfer learning. Zhao X; Qi S; Zhang B; Ma H; Qian W; Yao Y; Sun J J Xray Sci Technol; 2019; 27(4):615-629. PubMed ID: 31227682 [TBL] [Abstract][Full Text] [Related]
4. Rotation-covariant tissue analysis for interstitial lung diseases using learned steerable filters: Performance evaluation and relevance for diagnostic aid. Joyseeree R; Müller H; Depeursinge A Comput Med Imaging Graph; 2018 Mar; 64():1-11. PubMed ID: 29397275 [TBL] [Abstract][Full Text] [Related]
5. 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]
6. Segmentation of lung parenchyma in CT images using CNN trained with the clustering algorithm generated dataset. Xu M; Qi S; Yue Y; Teng Y; Xu L; Yao Y; Qian W Biomed Eng Online; 2019 Jan; 18(1):2. PubMed ID: 30602393 [TBL] [Abstract][Full Text] [Related]
7. 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]
8. 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]
9. Lung texture classification using locally-oriented Riesz components. Depeursinge A; Foncubierta-Rodriguez A; Van de Ville D; Müller H Med Image Comput Comput Assist Interv; 2011; 14(Pt 3):231-8. PubMed ID: 22003704 [TBL] [Abstract][Full Text] [Related]
10. 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]
11. Deep learning to distinguish pancreatic cancer tissue from non-cancerous pancreatic tissue: a retrospective study with cross-racial external validation. Liu KL; Wu T; Chen PT; Tsai YM; Roth H; Wu MS; Liao WC; Wang W Lancet Digit Health; 2020 Jun; 2(6):e303-e313. PubMed ID: 33328124 [TBL] [Abstract][Full Text] [Related]
12. Classification of Interstitial Lung Abnormality Patterns with an Ensemble of Deep Convolutional Neural Networks. Bermejo-Peláez D; Ash SY; Washko GR; San José Estépar R; Ledesma-Carbayo MJ Sci Rep; 2020 Jan; 10(1):338. PubMed ID: 31941918 [TBL] [Abstract][Full Text] [Related]
13. Classification of CT brain images based on deep learning networks. Gao XW; Hui R; Tian Z Comput Methods Programs Biomed; 2017 Jan; 138():49-56. PubMed ID: 27886714 [TBL] [Abstract][Full Text] [Related]
14. Lung Pattern Classification for Interstitial Lung Diseases Using a Deep Convolutional Neural Network. Anthimopoulos M; Christodoulidis S; Ebner L; Christe A; Mougiakakou S IEEE Trans Med Imaging; 2016 May; 35(5):1207-1216. PubMed ID: 26955021 [TBL] [Abstract][Full Text] [Related]
15. Local rotation invariance in 3D CNNs. Andrearczyk V; Fageot J; Oreiller V; Montet X; Depeursinge A Med Image Anal; 2020 Oct; 65():101756. PubMed ID: 32623274 [TBL] [Abstract][Full Text] [Related]
16. A deep convolutional neural network architecture for interstitial lung disease pattern classification. Huang S; Lee F; Miao R; Si Q; Lu C; Chen Q Med Biol Eng Comput; 2020 Apr; 58(4):725-737. PubMed ID: 31965407 [TBL] [Abstract][Full Text] [Related]
17. Deep Learning-based Image Conversion of CT Reconstruction Kernels Improves Radiomics Reproducibility for Pulmonary Nodules or Masses. Choe J; Lee SM; Do KH; Lee G; Lee JG; Lee SM; Seo JB Radiology; 2019 Aug; 292(2):365-373. PubMed ID: 31210613 [TBL] [Abstract][Full Text] [Related]
18. The effects of physics-based data augmentation on the generalizability of deep neural networks: Demonstration on nodule false-positive reduction. Omigbodun AO; Noo F; McNitt-Gray M; Hsu W; Hsieh SS Med Phys; 2019 Oct; 46(10):4563-4574. PubMed ID: 31396974 [TBL] [Abstract][Full Text] [Related]
19. Deep learning for screening of interstitial lung disease patterns in high-resolution CT images. Agarwala S; Kale M; Kumar D; Swaroop R; Kumar A; Kumar Dhara A; Basu Thakur S; Sadhu A; Nandi D Clin Radiol; 2020 Jun; 75(6):481.e1-481.e8. PubMed ID: 32075744 [TBL] [Abstract][Full Text] [Related]
20. Automatic recognition of 3D GGO CT imaging signs through the fusion of hybrid resampling and layer-wise fine-tuning CNNs. Han G; Liu X; Zheng G; Wang M; Huang S Med Biol Eng Comput; 2018 Dec; 56(12):2201-2212. PubMed ID: 29873026 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]