586 related articles for article (PubMed ID: 26955024)
1. 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]
2. 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]
3. 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]
4. Automatic detection of subsolid pulmonary nodules in thoracic computed tomography images.
Jacobs C; van Rikxoort EM; Twellmann T; Scholten ET; de Jong PA; Kuhnigk JM; Oudkerk M; de Koning HJ; Prokop M; Schaefer-Prokop C; van Ginneken B
Med Image Anal; 2014 Feb; 18(2):374-84. PubMed ID: 24434166
[TBL] [Abstract][Full Text] [Related]
5. 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]
6. 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]
7. 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]
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. Multilevel Contextual 3-D CNNs for False Positive Reduction in Pulmonary Nodule Detection.
Dou Q; Chen H; Yu L; Qin J; Heng PA
IEEE Trans Biomed Eng; 2017 Jul; 64(7):1558-1567. PubMed ID: 28113302
[TBL] [Abstract][Full Text] [Related]
10. Multi-scale Convolutional Neural Networks for Lung Nodule Classification.
Shen W; Zhou M; Yang F; Yang C; Tian J
Inf Process Med Imaging; 2015; 24():588-99. PubMed ID: 26221705
[TBL] [Abstract][Full Text] [Related]
11. 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]
12. Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose computed tomography.
Suzuki K; Armato SG; Li F; Sone S; Doi K
Med Phys; 2003 Jul; 30(7):1602-17. PubMed ID: 12906178
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. 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]
15. 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]
16. Efficacy of computer-aided detection system and thin-slab maximum intensity projection technique in the detection of pulmonary nodules in patients with resected metastases.
Park EA; Goo JM; Lee JW; Kang CH; Lee HJ; Lee CH; Park CM; Lee HY; Im JG
Invest Radiol; 2009 Feb; 44(2):105-13. PubMed ID: 19034026
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. 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]
19. 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]
20. Pulmonary nodule detection in CT images with quantized convergence index filter.
Matsumoto S; Kundel HL; Gee JC; Gefter WB; Hatabu H
Med Image Anal; 2006 Jun; 10(3):343-52. PubMed ID: 16542867
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]