488 related articles for article (PubMed ID: 34003394)
1. Automatic classification of solitary pulmonary nodules in PET/CT imaging employing transfer learning techniques.
Apostolopoulos ID; Pintelas EG; Livieris IE; Apostolopoulos DJ; Papathanasiou ND; Pintelas PE; Panayiotakis GS
Med Biol Eng Comput; 2021 Jun; 59(6):1299-1310. PubMed ID: 34003394
[TBL] [Abstract][Full Text] [Related]
2. 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]
3. 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]
4. Lung Nodule Detection in CT Images Using a Raw Patch-Based Convolutional Neural Network.
Wang Q; Shen F; Shen L; Huang J; Sheng W
J Digit Imaging; 2019 Dec; 32(6):971-979. PubMed ID: 31062113
[TBL] [Abstract][Full Text] [Related]
5. Computer-Aided Diagnosis (CAD) of Pulmonary Nodule of Thoracic CT Image Using Transfer Learning.
Zhang S; Sun F; Wang N; Zhang C; Yu Q; Zhang M; Babyn P; Zhong H
J Digit Imaging; 2019 Dec; 32(6):995-1007. PubMed ID: 31044393
[TBL] [Abstract][Full Text] [Related]
6. 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]
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. 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]
10. 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]
11. Pulmonary nodule detection in CT scans with equivariant CNNs.
Winkels M; Cohen TS
Med Image Anal; 2019 Jul; 55():15-26. PubMed ID: 31003034
[TBL] [Abstract][Full Text] [Related]
12. Lung Nodule Classification Using Biomarkers, Volumetric Radiomics, and 3D CNNs.
Mehta K; Jain A; Mangalagiri J; Menon S; Nguyen P; Chapman DR
J Digit Imaging; 2021 Jun; 34(3):647-666. PubMed ID: 33532893
[TBL] [Abstract][Full Text] [Related]
13. CAD system for lung nodule detection using deep learning with CNN.
Manickavasagam R; Selvan S; Selvan M
Med Biol Eng Comput; 2022 Jan; 60(1):221-228. PubMed ID: 34811644
[TBL] [Abstract][Full Text] [Related]
14. 3-D Convolutional Neural Networks for Automatic Detection of Pulmonary Nodules in Chest CT.
Pezeshk A; Hamidian S; Petrick N; Sahiner B
IEEE J Biomed Health Inform; 2019 Sep; 23(5):2080-2090. PubMed ID: 30418929
[TBL] [Abstract][Full Text] [Related]
15. The Performance of Deep Learning Algorithms on Automatic Pulmonary Nodule Detection and Classification Tested on Different Datasets That Are Not Derived from LIDC-IDRI: A Systematic Review.
Li D; Mikela Vilmun B; Frederik Carlsen J; Albrecht-Beste E; Ammitzbøl Lauridsen C; Bachmann Nielsen M; Lindskov Hansen K
Diagnostics (Basel); 2019 Nov; 9(4):. PubMed ID: 31795409
[TBL] [Abstract][Full Text] [Related]
16. Segmentation of pulmonary nodules in computed tomography using a regression neural network approach and its application to the Lung Image Database Consortium and Image Database Resource Initiative dataset.
Messay T; Hardie RC; Tuinstra TR
Med Image Anal; 2015 May; 22(1):48-62. PubMed ID: 25791434
[TBL] [Abstract][Full Text] [Related]
17. Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge.
Setio AAA; Traverso A; de Bel T; Berens MSN; Bogaard CVD; Cerello P; Chen H; Dou Q; Fantacci ME; Geurts B; Gugten RV; Heng PA; Jansen B; de Kaste MMJ; Kotov V; Lin JY; Manders JTMC; Sóñora-Mengana A; García-Naranjo JC; Papavasileiou E; Prokop M; Saletta M; Schaefer-Prokop CM; Scholten ET; Scholten L; Snoeren MM; Torres EL; Vandemeulebroucke J; Walasek N; Zuidhof GCA; Ginneken BV; Jacobs C
Med Image Anal; 2017 Dec; 42():1-13. PubMed ID: 28732268
[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. 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]
20. Robust explanation supervision for false positive reduction in pulmonary nodule detection.
Zhao Q; Chang CW; Yang X; Zhao L
Med Phys; 2024 Mar; 51(3):1687-1701. PubMed ID: 38224306
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
