172 related articles for article (PubMed ID: 32930652)
1. Improved Interobserver Agreement on Lung-RADS Classification of Solid Nodules Using Semiautomated CT Volumetry.
Gierada DS; Rydzak CE; Zei M; Rhea L
Radiology; 2020 Dec; 297(3):675-684. PubMed ID: 32930652
[TBL] [Abstract][Full Text] [Related]
2. Improved interobserver agreement on nodule type and Lung-RADS classification of subsolid nodules using computer-aided solid component measurement.
Shu J; Wen D; Xu Z; Meng X; Zhang Z; Lin S; Zheng M
Eur J Radiol; 2022 Jul; 152():110339. PubMed ID: 35537358
[TBL] [Abstract][Full Text] [Related]
3. Cancer Risk in Nodules Detected at Follow-Up Lung Cancer Screening CT.
Hammer MM; Byrne SC
AJR Am J Roentgenol; 2022 Apr; 218(4):634-641. PubMed ID: 34755524
[No Abstract] [Full Text] [Related]
4. Interobserver variability in Lung CT Screening Reporting and Data System categorisation in subsolid nodule-enriched lung cancer screening CTs.
Yoon SH; Kim YJ; Doh K; Kim J; Lee KH; Lee KW; Kim J
Eur Radiol; 2021 Sep; 31(9):7184-7191. PubMed ID: 33733688
[TBL] [Abstract][Full Text] [Related]
5. Malignant Nodules Detected on Lung Cancer Screening CT: Yield of Short-Term Follow-Up CT in Showing Nodule Growth.
Byrne SC; Hammer MM
AJR Am J Roentgenol; 2022 Nov; 219(5):735-741. PubMed ID: 35674352
[No Abstract] [Full Text] [Related]
6. Efficacy of Ultrashort Echo Time Pulmonary MRI for Lung Nodule Detection and Lung-RADS Classification.
Ohno Y; Takenaka D; Yoshikawa T; Yui M; Koyama H; Yamamoto K; Hamabuchi N; Shigemura C; Watanabe A; Ueda T; Ikeda H; Hattori H; Murayama K; Toyama H
Radiology; 2022 Mar; 302(3):697-706. PubMed ID: 34846203
[TBL] [Abstract][Full Text] [Related]
7. Computer-aided volumetry of pulmonary nodules exhibiting ground-glass opacity at MDCT.
Oda S; Awai K; Murao K; Ozawa A; Yanaga Y; Kawanaka K; Yamashita Y
AJR Am J Roentgenol; 2010 Feb; 194(2):398-406. PubMed ID: 20093602
[TBL] [Abstract][Full Text] [Related]
8. Malignancy risk estimation of screen-detected nodules at baseline CT: comparison of the PanCan model, Lung-RADS and NCCN guidelines.
van Riel SJ; Ciompi F; Jacobs C; Winkler Wille MM; Scholten ET; Naqibullah M; Lam S; Prokop M; Schaefer-Prokop C; van Ginneken B
Eur Radiol; 2017 Oct; 27(10):4019-4029. PubMed ID: 28293773
[TBL] [Abstract][Full Text] [Related]
9. Variability of semiautomated lung nodule volumetry on ultralow-dose CT: comparison with nodule volumetry on standard-dose CT.
Hein PA; Romano VC; Rogalla P; Klessen C; Lembcke A; Bornemann L; Dicken V; Hamm B; Bauknecht HC
J Digit Imaging; 2010 Feb; 23(1):8-17. PubMed ID: 18773240
[TBL] [Abstract][Full Text] [Related]
10. Application of computer-aided diagnosis for Lung-RADS categorization in CT screening for lung cancer: effect on inter-reader agreement.
Park S; Park H; Lee SM; Ahn Y; Kim W; Jung K; Seo JB
Eur Radiol; 2022 Feb; 32(2):1054-1064. PubMed ID: 34331112
[TBL] [Abstract][Full Text] [Related]
11. Lung-RADS Version 1.0 versus Lung-RADS Version 1.1: Comparison of Categories Using Nodules from the National Lung Screening Trial.
Kastner J; Hossain R; Jeudy J; Dako F; Mehta V; Dalal S; Dharaiya E; White C
Radiology; 2021 Jul; 300(1):199-206. PubMed ID: 33944631
[TBL] [Abstract][Full Text] [Related]
12. Influence of lung nodule margin on volume- and diameter-based reader variability in CT lung cancer screening.
Han D; Heuvelmans MA; Vliegenthart R; Rook M; Dorrius MD; de Jonge GJ; Walter JE; van Ooijen PMA; de Koning HJ; Oudkerk M
Br J Radiol; 2018 Oct; 91(1090):20170405. PubMed ID: 28972803
[TBL] [Abstract][Full Text] [Related]
13. Volumetric measurements of pulmonary nodules at multi-row detector CT: in vivo reproducibility.
Wormanns D; Kohl G; Klotz E; Marheine A; Beyer F; Heindel W; Diederich S
Eur Radiol; 2004 Jan; 14(1):86-92. PubMed ID: 14615902
[TBL] [Abstract][Full Text] [Related]
14. Ultra-low-dose CT reconstructed with ASiR-V using SmartmA for pulmonary nodule detection and Lung-RADS classifications compared with low-dose CT.
Ye K; Chen M; Li J; Zhu Q; Lu Y; Yuan H
Clin Radiol; 2021 Feb; 76(2):156.e1-156.e8. PubMed ID: 33293025
[TBL] [Abstract][Full Text] [Related]
15. Strategies for Reducing False-Positive Screening Results for Intermediate-Size Nodules Evaluated Using Lung-RADS: A Secondary Analysis of National Lung Screening Trial Data.
Hammer MM; Hunsaker AR
AJR Am J Roentgenol; 2022 Sep; 219(3):397-405. PubMed ID: 35319912
[No Abstract] [Full Text] [Related]
16. Assisted versus Manual Interpretation of Low-Dose CT Scans for Lung Cancer Screening: Impact on Lung-RADS Agreement.
Jacobs C; Schreuder A; van Riel SJ; Scholten ET; Wittenberg R; Wille MMW; de Hoop B; Sprengers R; Mets OM; Geurts B; Prokop M; Schaefer-Prokop C; van Ginneken B
Radiol Imaging Cancer; 2021 Sep; 3(5):e200160. PubMed ID: 34559005
[TBL] [Abstract][Full Text] [Related]
17. Comparison of three software systems for semi-automatic volumetry of pulmonary nodules on baseline and follow-up CT examinations.
Zhao YR; van Ooijen PM; Dorrius MD; Heuvelmans M; de Bock GH; Vliegenthart R; Oudkerk M
Acta Radiol; 2014 Jul; 55(6):691-8. PubMed ID: 24132766
[TBL] [Abstract][Full Text] [Related]
18. Pulmonary nodules detected at lung cancer screening: interobserver variability of semiautomated volume measurements.
Gietema HA; Wang Y; Xu D; van Klaveren RJ; de Koning H; Scholten E; Verschakelen J; Kohl G; Oudkerk M; Prokop M
Radiology; 2006 Oct; 241(1):251-7. PubMed ID: 16908677
[TBL] [Abstract][Full Text] [Related]
19. Vessel suppressed chest Computed Tomography for semi-automated volumetric measurements of solid pulmonary nodules.
Milanese G; Eberhard M; Martini K; Vittoria De Martini I; Frauenfelder T
Eur J Radiol; 2018 Apr; 101():97-102. PubMed ID: 29571809
[TBL] [Abstract][Full Text] [Related]
20. Observer variability for Lung-RADS categorisation of lung cancer screening CTs: impact on patient management.
van Riel SJ; Jacobs C; Scholten ET; Wittenberg R; Winkler Wille MM; de Hoop B; Sprengers R; Mets OM; Geurts B; Prokop M; Schaefer-Prokop C; van Ginneken B
Eur Radiol; 2019 Feb; 29(2):924-931. PubMed ID: 30066248
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
