443 related articles for article (PubMed ID: 30255253)
1. A simple prediction model using size measures for discrimination of invasive adenocarcinomas among incidental pulmonary subsolid nodules considered for resection.
Kim H; Goo JM; Park CM
Eur Radiol; 2019 Apr; 29(4):1674-1683. PubMed ID: 30255253
[TBL] [Abstract][Full Text] [Related]
2. Validation of prediction models for risk stratification of incidentally detected pulmonary subsolid nodules: a retrospective cohort study in a Korean tertiary medical centre.
Kim H; Park CM; Jeon S; Lee JH; Ahn SY; Yoo RE; Lim HJ; Park J; Lim WH; Hwang EJ; Lee SM; Goo JM
BMJ Open; 2018 May; 8(5):e019996. PubMed ID: 29794091
[TBL] [Abstract][Full Text] [Related]
3. Preoperative CT-based radiomics combined with intraoperative frozen section is predictive of invasive adenocarcinoma in pulmonary nodules: a multicenter study.
Wu G; Woodruff HC; Sanduleanu S; Refaee T; Jochems A; Leijenaar R; Gietema H; Shen J; Wang R; Xiong J; Bian J; Wu J; Lambin P
Eur Radiol; 2020 May; 30(5):2680-2691. PubMed ID: 32006165
[TBL] [Abstract][Full Text] [Related]
4. Whole-Lesion Computed Tomography-Based Entropy Parameters for the Differentiation of Minimally Invasive and Invasive Adenocarcinomas Appearing as Pulmonary Subsolid Nodules.
Chen X; Feng B; Chen Y; Hao Y; Duan X; Cui E; Liu Z; Zhang C; Long W
J Comput Assist Tomogr; 2019; 43(5):817-824. PubMed ID: 31343995
[TBL] [Abstract][Full Text] [Related]
5. Deep learning-based differentiation of invasive adenocarcinomas from preinvasive or minimally invasive lesions among pulmonary subsolid nodules.
Park S; Park G; Lee SM; Kim W; Park H; Jung K; Seo JB
Eur Radiol; 2021 Aug; 31(8):6239-6247. PubMed ID: 33555355
[TBL] [Abstract][Full Text] [Related]
6. The predictive value of CT-based radiomics in differentiating indolent from invasive lung adenocarcinoma in patients with pulmonary nodules.
She Y; Zhang L; Zhu H; Dai C; Xie D; Xie H; Zhang W; Zhao L; Zou L; Fei K; Sun X; Chen C
Eur Radiol; 2018 Dec; 28(12):5121-5128. PubMed ID: 29869172
[TBL] [Abstract][Full Text] [Related]
7. CT-based deep learning model to differentiate invasive pulmonary adenocarcinomas appearing as subsolid nodules among surgical candidates: comparison of the diagnostic performance with a size-based logistic model and radiologists.
Kim H; Lee D; Cho WS; Lee JC; Goo JM; Kim HC; Park CM
Eur Radiol; 2020 Jun; 30(6):3295-3305. PubMed ID: 32055949
[TBL] [Abstract][Full Text] [Related]
8. A comparative study to evaluate CT-based semantic and radiomic features in preoperative diagnosis of invasive pulmonary adenocarcinomas manifesting as subsolid nodules.
Wu YJ; Liu YC; Liao CY; Tang EK; Wu FZ
Sci Rep; 2021 Jan; 11(1):66. PubMed ID: 33462251
[TBL] [Abstract][Full Text] [Related]
9. Thin-slice computed tomography enables to classify pulmonary subsolid nodules into pre-invasive lesion/minimally invasive adenocarcinoma and invasive adenocarcinoma: a retrospective study.
Li M; Zhu L; Lv Y; Shen L; Han Y; Ye B
Sci Rep; 2023 Apr; 13(1):6999. PubMed ID: 37117233
[TBL] [Abstract][Full Text] [Related]
10. Computerized texture analysis of persistent part-solid ground-glass nodules: differentiation of preinvasive lesions from invasive pulmonary adenocarcinomas.
Chae HD; Park CM; Park SJ; Lee SM; Kim KG; Goo JM
Radiology; 2014 Oct; 273(1):285-93. PubMed ID: 25102296
[TBL] [Abstract][Full Text] [Related]
11. Effect of CT window settings on size measurements of the solid component in subsolid nodules: evaluation of prediction efficacy of the degree of pathological malignancy in lung adenocarcinoma.
Li Q; Gu YF; Fan L; Li QC; Xiao Y; Liu SY
Br J Radiol; 2018 Jul; 91(1088):20180251. PubMed ID: 29791206
[TBL] [Abstract][Full Text] [Related]
12. Persistent Pure Ground-Glass Nodules Larger Than 5 mm: Differentiation of Invasive Pulmonary Adenocarcinomas From Preinvasive Lesions or Minimally Invasive Adenocarcinomas Using Texture Analysis.
Hwang IP; Park CM; Park SJ; Lee SM; McAdams HP; Jeon YK; Goo JM
Invest Radiol; 2015 Nov; 50(11):798-804. PubMed ID: 26146871
[TBL] [Abstract][Full Text] [Related]
13. Invasive Pulmonary Adenocarcinomas Versus Preinvasive Lesions Appearing as Pure Ground-Glass Nodules: Differentiation Using Enhanced Dual-Source Dual-Energy CT.
Yang Y; Li K; Sun D; Yu J; Cai Z; Cao Y; Wu J
AJR Am J Roentgenol; 2019 Sep; 213(3):W114-W122. PubMed ID: 31082273
[No Abstract] [Full Text] [Related]
14. Effect of CT Reconstruction Algorithm on the Diagnostic Performance of Radiomics Models: A Task-Based Approach for Pulmonary Subsolid Nodules.
Kim H; Park CM; Gwak J; Hwang EJ; Lee SY; Jung J; Hong H; Goo JM
AJR Am J Roentgenol; 2019 Mar; 212(3):505-512. PubMed ID: 30476456
[TBL] [Abstract][Full Text] [Related]
15. The morphological changes of bronchovascular bundles within subsolid nodules on HRCT correlate with the new IASLC classification of adenocarcinoma.
Liu L; Wu N; Tang W; Xu F; Zhou LN; Ma PQ; Li L; Liang X
Clin Radiol; 2018 Jun; 73(6):542-548. PubMed ID: 29329734
[TBL] [Abstract][Full Text] [Related]
16. Radiomics for lung adenocarcinoma manifesting as pure ground-glass nodules: invasive prediction.
Sun Y; Li C; Jin L; Gao P; Zhao W; Ma W; Tan M; Wu W; Duan S; Shan Y; Li M
Eur Radiol; 2020 Jul; 30(7):3650-3659. PubMed ID: 32162003
[TBL] [Abstract][Full Text] [Related]
17. Lung Adenocarcinoma Invasiveness Risk in Pure Ground-Glass Opacity Lung Nodules Smaller than 2 cm.
Lee GD; Park CH; Park HS; Byun MK; Lee IJ; Kim TH; Lee S
Thorac Cardiovasc Surg; 2019 Jun; 67(4):321-328. PubMed ID: 29359309
[TBL] [Abstract][Full Text] [Related]
18. Improving the prediction of lung adenocarcinoma invasive component on CT: Value of a vessel removal algorithm during software segmentation of subsolid nodules.
Garzelli L; Goo JM; Ahn SY; Chae KJ; Park CM; Jung J; Hong H
Eur J Radiol; 2018 Mar; 100():58-65. PubMed ID: 29496080
[TBL] [Abstract][Full Text] [Related]
19. Invasive pulmonary adenocarcinomas versus preinvasive lesions appearing as ground-glass nodules: differentiation by using CT features.
Lee SM; Park CM; Goo JM; Lee HJ; Wi JY; Kang CH
Radiology; 2013 Jul; 268(1):265-73. PubMed ID: 23468575
[TBL] [Abstract][Full Text] [Related]
20. Pulmonary subsolid nodules: value of semi-automatic measurement in diagnostic accuracy, diagnostic reproducibility and nodule classification agreement.
Kim H; Park CM; Hwang EJ; Ahn SY; Goo JM
Eur Radiol; 2018 May; 28(5):2124-2133. PubMed ID: 29196857
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
