81 related articles for article (PubMed ID: 16898465)
1. Automated classification of hyperlucency, fibrosis, ground glass, solid, and focal lesions in high-resolution CT of the lung.
Sluimer IC; Prokop M; Hartmann I; van Ginneken B
Med Phys; 2006 Jul; 33(7):2610-20. PubMed ID: 16898465
[TBL] [Abstract][Full Text] [Related]
2. Texture classification-based segmentation of lung affected by interstitial pneumonia in high-resolution CT.
Korfiatis P; Kalogeropoulou C; Karahaliou A; Kazantzi A; Skiadopoulos S; Costaridou L
Med Phys; 2008 Dec; 35(12):5290-302. PubMed ID: 19175088
[TBL] [Abstract][Full Text] [Related]
3. 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]
4. Radiologists' performance for differentiating benign from malignant lung nodules on high-resolution CT using computer-estimated likelihood of malignancy.
Li F; Aoyama M; Shiraishi J; Abe H; Li Q; Suzuki K; Engelmann R; Sone S; Macmahon H; Doi K
AJR Am J Roentgenol; 2004 Nov; 183(5):1209-15. PubMed ID: 15505279
[TBL] [Abstract][Full Text] [Related]
5. High resolution multidetector CT-aided tissue analysis and quantification of lung fibrosis.
Zavaletta VA; Bartholmai BJ; Robb RA
Acad Radiol; 2007 Jul; 14(7):772-87. PubMed ID: 17574128
[TBL] [Abstract][Full Text] [Related]
6. Quantitative computerized analysis of diffuse lung disease in high-resolution computed tomography.
Uchiyama Y; Katsuragawa S; Abe H; Shiraishi J; Li F; Li Q; Zhang CT; Suzuki K; Doi K
Med Phys; 2003 Sep; 30(9):2440-54. PubMed ID: 14528966
[TBL] [Abstract][Full Text] [Related]
7. Pleural nodule identification in low-dose and thin-slice lung computed tomography.
Retico A; Fantacci ME; Gori I; Kasae P; Golosio B; Piccioli A; Cerello P; De Nunzio G; Tangaro S
Comput Biol Med; 2009 Dec; 39(12):1137-44. PubMed ID: 19883906
[TBL] [Abstract][Full Text] [Related]
8. Computer-aided diagnosis of localized ground-glass opacity in the lung at CT: initial experience.
Kim KG; Goo JM; Kim JH; Lee HJ; Min BG; Bae KT; Im JG
Radiology; 2005 Nov; 237(2):657-61. PubMed ID: 16192320
[TBL] [Abstract][Full Text] [Related]
9. Computer recognition of regional lung disease patterns.
Uppaluri R; Hoffman EA; Sonka M; Hartley PG; Hunninghake GW; McLennan G
Am J Respir Crit Care Med; 1999 Aug; 160(2):648-54. PubMed ID: 10430742
[TBL] [Abstract][Full Text] [Related]
10. Feasibility of automated quantification of regional disease patterns depicted on high-resolution computed tomography in patients with various diffuse lung diseases.
Park SO; Seo JB; Kim N; Park SH; Lee YK; Park BW; Sung YS; Lee Y; Lee J; Kang SH
Korean J Radiol; 2009; 10(5):455-63. PubMed ID: 19721830
[TBL] [Abstract][Full Text] [Related]
11. Automated interpretation of PET/CT images in patients with lung cancer.
Gutte H; Jakobsson D; Olofsson F; Ohlsson M; Valind S; Loft A; Edenbrandt L; Kjaer A
Nucl Med Commun; 2007 Feb; 28(2):79-84. PubMed ID: 17198346
[TBL] [Abstract][Full Text] [Related]
12. Computerized detection of diffuse lung disease in MDCT: the usefulness of statistical texture features.
Wang J; Li F; Doi K; Li Q
Phys Med Biol; 2009 Nov; 54(22):6881-99. PubMed ID: 19864701
[TBL] [Abstract][Full Text] [Related]
13. Multiple kernel learning for classification of diffuse lung disease using HRCT lung images.
Vo KT; Sowmya A
Annu Int Conf IEEE Eng Med Biol Soc; 2010; 2010():3085-8. PubMed ID: 21095740
[TBL] [Abstract][Full Text] [Related]
14. Computer-aided diagnosis of pulmonary nodules on CT scans: segmentation and classification using 3D active contours.
Way TW; Hadjiiski LM; Sahiner B; Chan HP; Cascade PN; Kazerooni EA; Bogot N; Zhou C
Med Phys; 2006 Jul; 33(7):2323-37. PubMed ID: 16898434
[TBL] [Abstract][Full Text] [Related]
15. A novel computer-aided lung nodule detection system for CT images.
Tan M; Deklerck R; Jansen B; Bister M; Cornelis J
Med Phys; 2011 Oct; 38(10):5630-45. PubMed ID: 21992380
[TBL] [Abstract][Full Text] [Related]
16. Automated detection of lung nodules in multidetector CT: influence of different reconstruction protocols on performance of a software prototype.
Gurung J; Maataoui A; Khan M; Wetter A; Harth M; Jacobi V; Vogl TJ
Rofo; 2006 Jan; 178(1):71-7. PubMed ID: 16392060
[TBL] [Abstract][Full Text] [Related]
17. Robustness-Driven Feature Selection in Classification of Fibrotic Interstitial Lung Disease Patterns in Computed Tomography Using 3D Texture Features.
Chong DY; Kim HJ; Lo P; Young S; McNitt-Gray MF; Abtin F; Goldin JG; Brown MS
IEEE Trans Med Imaging; 2016 Jan; 35(1):144-57. PubMed ID: 26208309
[TBL] [Abstract][Full Text] [Related]
18. Computer-aided detection of interstitial abnormalities in chest radiographs using a reference standard based on computed tomography.
Arzhaeva Y; Prokop M; Tax DM; De Jong PA; Schaefer-Prokop CM; van Ginneken B
Med Phys; 2007 Dec; 34(12):4798-809. PubMed ID: 18196808
[TBL] [Abstract][Full Text] [Related]
19. A support vector machine classifier reduces interscanner variation in the HRCT classification of regional disease pattern in diffuse lung disease: comparison to a Bayesian classifier.
Chang Y; Lim J; Kim N; Seo JB; Lynch DA
Med Phys; 2013 May; 40(5):051912. PubMed ID: 23635282
[TBL] [Abstract][Full Text] [Related]
20. Neural network-based computer-aided diagnosis in distinguishing malignant from benign solitary pulmonary nodules by computed tomography.
Chen H; Wang XH; Ma DQ; Ma BR
Chin Med J (Engl); 2007 Jul; 120(14):1211-5. PubMed ID: 17697569
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
