148 related articles for article (PubMed ID: 10776884)
1. Computer-aided diagnosis of small pulmonary nodules.
Reeves AP; Kostis WJ
Semin Ultrasound CT MR; 2000 Apr; 21(2):116-28. PubMed ID: 10776884
[TBL] [Abstract][Full Text] [Related]
2. Quantitative nodule detection in low dose chest CT scans: new template modeling and evaluation for CAD system design.
Farag AA; El-Baz A; Gimelfarb G; El-Ghar MA; Eldiasty T
Med Image Comput Comput Assist Interv; 2005; 8(Pt 1):720-8. PubMed ID: 16685910
[TBL] [Abstract][Full Text] [Related]
3. Computer-aided differentiation of malignant from benign solitary pulmonary nodules imaged by high-resolution CT.
Iwano S; Nakamura T; Kamioka Y; Ikeda M; Ishigaki T
Comput Med Imaging Graph; 2008 Jul; 32(5):416-22. PubMed ID: 18501556
[TBL] [Abstract][Full Text] [Related]
4. Cloud-Based NoSQL Open Database of Pulmonary Nodules for Computer-Aided Lung Cancer Diagnosis and Reproducible Research.
Ferreira Junior JR; Oliveira MC; de Azevedo-Marques PM
J Digit Imaging; 2016 Dec; 29(6):716-729. PubMed ID: 27440183
[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. Improvement in detection of pulmonary nodules: digital image processing and computer-aided diagnosis.
MacMahon H
Radiographics; 2000; 20(4):1169-77. PubMed ID: 10903706
[No Abstract] [Full Text] [Related]
7. Solid, part-solid, or non-solid?: classification of pulmonary nodules in low-dose chest computed tomography by a computer-aided diagnosis system.
Jacobs C; van Rikxoort EM; Scholten ET; de Jong PA; Prokop M; Schaefer-Prokop C; van Ginneken B
Invest Radiol; 2015 Mar; 50(3):168-73. PubMed ID: 25478740
[TBL] [Abstract][Full Text] [Related]
8. Computer-aided diagnostic scheme for distinction between benign and malignant nodules in thoracic low-dose CT by use of massive training artificial neural network.
Suzuki K; Li F; Sone S; Doi K
IEEE Trans Med Imaging; 2005 Sep; 24(9):1138-50. PubMed ID: 16156352
[TBL] [Abstract][Full Text] [Related]
9. Accuracy of the CT numbers of simulated lung nodules imaged with multi-detector CT scanners.
Goodsitt MM; Chan HP; Way TW; Larson SC; Christodoulou EG; Kim J
Med Phys; 2006 Aug; 33(8):3006-17. PubMed ID: 16964879
[TBL] [Abstract][Full Text] [Related]
10. 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]
11. 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]
12. 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]
13. 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]
14. Evaluation of computer-aided diagnosis (CAD) software for the detection of lung nodules on multidetector row computed tomography (MDCT): JAFROC study for the improvement in radiologists' diagnostic accuracy.
Hirose T; Nitta N; Shiraishi J; Nagatani Y; Takahashi M; Murata K
Acad Radiol; 2008 Dec; 15(12):1505-12. PubMed ID: 19000867
[TBL] [Abstract][Full Text] [Related]
15. In vivo repeatability of automated volume calculations of small pulmonary nodules with CT.
Rampinelli C; De Fiori E; Raimondi S; Veronesi G; Bellomi M
AJR Am J Roentgenol; 2009 Jun; 192(6):1657-61. PubMed ID: 19457831
[TBL] [Abstract][Full Text] [Related]
16. [CAD for identifying malignant lung nodules in early diagnosis: a survey].
Li B; Tian L; Ou S
Sheng Wu Yi Xue Gong Cheng Xue Za Zhi; 2009 Oct; 26(5):1141-5, 1157. PubMed ID: 19947507
[TBL] [Abstract][Full Text] [Related]
17. A weighted rule based method for predicting malignancy of pulmonary nodules by nodule characteristics.
Kaya A; Can AB
J Biomed Inform; 2015 Aug; 56():69-79. PubMed ID: 26008877
[TBL] [Abstract][Full Text] [Related]
18. A new method for spherical object detection and its application to computer aided detection of pulmonary nodules in CT images.
Zhang X; Stockel J; Wolf M; Cathier P; McLennan G; Hoffman EA; Sonka M
Med Image Comput Comput Assist Interv; 2007; 10(Pt 1):842-9. PubMed ID: 18051137
[TBL] [Abstract][Full Text] [Related]
19. JOURNAL CLUB: Computer-Aided Detection of Lung Nodules on CT With a Computerized Pulmonary Vessel Suppressed Function.
Lo SB; Freedman MT; Gillis LB; White CS; Mun SK
AJR Am J Roentgenol; 2018 Mar; 210(3):480-488. PubMed ID: 29336601
[TBL] [Abstract][Full Text] [Related]
20. Lung Nodule Image Classification Based on Local Difference Pattern and Combined Classifier.
Mao K; Deng Z
Comput Math Methods Med; 2016; 2016():1091279. PubMed ID: 28053650
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
