138 related articles for article (PubMed ID: 34125856)
1. Evaluation of Computer-Aided Nodule Assessment and Risk Yield (CANARY) in Korean patients for prediction of invasiveness of ground-glass opacity nodule.
Lee J; Bartholmai B; Peikert T; Chun J; Kim H; Kim JS; Park SY
PLoS One; 2021; 16(6):e0253204. PubMed ID: 34125856
[TBL] [Abstract][Full Text] [Related]
2. Computer-Aided Diagnosis of Ground-Glass Opacity Nodules Using Open-Source Software for Quantifying Tumor Heterogeneity.
Li M; Narayan V; Gill RR; Jagannathan JP; Barile MF; Gao F; Bueno R; Jayender J
AJR Am J Roentgenol; 2017 Dec; 209(6):1216-1227. PubMed ID: 29045176
[TBL] [Abstract][Full Text] [Related]
3. A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images.
Gong J; Liu J; Hao W; Nie S; Zheng B; Wang S; Peng W
Eur Radiol; 2020 Apr; 30(4):1847-1855. PubMed ID: 31811427
[TBL] [Abstract][Full Text] [Related]
4. Changes in quantitative CT image features of ground-glass nodules in differentiating invasive pulmonary adenocarcinoma from benign and in situ lesions: histopathological comparisons.
Zhang YP; Heuvelmans MA; Zhang H; Oudkerk M; Zhang GX; Xie XQ
Clin Radiol; 2018 May; 73(5):504.e9-504.e16. PubMed ID: 29329732
[TBL] [Abstract][Full Text] [Related]
5. Computed Tomography-Based Score Indicative of Lung Cancer Aggression (SILA) Predicts the Degree of Histologic Tissue Invasion and Patient Survival in Lung Adenocarcinoma Spectrum.
Varghese C; Rajagopalan S; Karwoski RA; Bartholmai BJ; Maldonado F; Boland JM; Peikert T
J Thorac Oncol; 2019 Aug; 14(8):1419-1429. PubMed ID: 31063863
[TBL] [Abstract][Full Text] [Related]
6. Assessing the inter-observer variability of Computer-Aided Nodule Assessment and Risk Yield (CANARY) to characterize lung adenocarcinomas.
Nakajima EC; Frankland MP; Johnson TF; Antic SL; Chen H; Chen SC; Karwoski RA; Walker R; Landman BA; Clay RD; Bartholmai BJ; Rajagopalan S; Peikert T; Massion PP; Maldonado F
PLoS One; 2018; 13(6):e0198118. PubMed ID: 29856852
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. Utility of Maximum CT Value in Predicting the Invasiveness of Pure Ground-Glass Nodules.
Ichinose J; Kawaguchi Y; Nakao M; Matsuura Y; Okumura S; Ninomiya H; Oikado K; Nishio M; Mun M
Clin Lung Cancer; 2020 May; 21(3):281-287. PubMed ID: 32089477
[TBL] [Abstract][Full Text] [Related]
9. Software-based risk stratification of pulmonary adenocarcinomas manifesting as pure ground glass nodules on computed tomography.
Nemec U; Heidinger BH; Anderson KR; Westmore MS; VanderLaan PA; Bankier AA
Eur Radiol; 2018 Jan; 28(1):235-242. PubMed ID: 28710575
[TBL] [Abstract][Full Text] [Related]
10. Computer-aided diagnosis of ground glass pulmonary nodule by fusing deep learning and radiomics features.
Hu X; Gong J; Zhou W; Li H; Wang S; Wei M; Peng W; Gu Y
Phys Med Biol; 2021 Mar; 66(6):065015. PubMed ID: 33596552
[TBL] [Abstract][Full Text] [Related]
11. Computer-aided diagnosis of ground-glass opacity pulmonary nodules using radiomic features analysis.
Gong J; Liu J; Hao W; Nie S; Wang S; Peng W
Phys Med Biol; 2019 Jul; 64(13):135015. PubMed ID: 31167172
[TBL] [Abstract][Full Text] [Related]
12. Lung Adenocarcinoma Manifesting as Ground-Glass Opacity Nodules 3 cm or Smaller: Evaluation With Combined High-Resolution CT and PET/CT Modality.
Niu R; Shao X; Shao X; Wang J; Jiang Z; Wang Y
AJR Am J Roentgenol; 2019 Nov; 213(5):W236-W245. PubMed ID: 31361533
[No Abstract] [Full Text] [Related]
13. Predicting benign, preinvasive, and invasive lung nodules on computed tomography scans using machine learning.
Ashraf SF; Yin K; Meng CX; Wang Q; Wang Q; Pu J; Dhupar R
J Thorac Cardiovasc Surg; 2022 Apr; 163(4):1496-1505.e10. PubMed ID: 33726909
[TBL] [Abstract][Full Text] [Related]
14. [Diagnostic value of contrast-enhanced CT scans in identifying lung adenocarcinomas manifesting as ground glass nodules].
Sun YL; Gao F; Gao P; Jin L; Li C; Hua YQ; Li M
Zhonghua Zhong Liu Za Zhi; 2018 Jul; 40(7):534-538. PubMed ID: 30060363
[No Abstract] [Full Text] [Related]
15. Determining the invasiveness of ground-glass nodules using a 3D multi-task network.
Yu Y; Wang N; Huang N; Liu X; Zheng Y; Fu Y; Li X; Wu H; Xu J; Cheng J
Eur Radiol; 2021 Sep; 31(9):7162-7171. PubMed ID: 33665717
[TBL] [Abstract][Full Text] [Related]
16. Noninvasive characterization of the histopathologic features of pulmonary nodules of the lung adenocarcinoma spectrum using computer-aided nodule assessment and risk yield (CANARY)--a pilot study.
Maldonado F; Boland JM; Raghunath S; Aubry MC; Bartholmai BJ; Deandrade M; Hartman TE; Karwoski RA; Rajagopalan S; Sykes AM; Yang P; Yi ES; Robb RA; Peikert T
J Thorac Oncol; 2013 Apr; 8(4):452-60. PubMed ID: 23486265
[TBL] [Abstract][Full Text] [Related]
17. CT and histopathologic characteristics of lung adenocarcinoma with pure ground-glass nodules 10 mm or less in diameter.
Wu F; Tian SP; Jin X; Jing R; Yang YQ; Jin M; Zhao SH
Eur Radiol; 2017 Oct; 27(10):4037-4043. PubMed ID: 28386719
[TBL] [Abstract][Full Text] [Related]
18. CT quantitative parameters to predict the invasiveness of lung pure ground-glass nodules (pGGNs).
Han L; Zhang P; Wang Y; Gao Z; Wang H; Li X; Ye Z
Clin Radiol; 2018 May; 73(5):504.e1-504.e7. PubMed ID: 29397913
[TBL] [Abstract][Full Text] [Related]
19. 3D deep learning based classification of pulmonary ground glass opacity nodules with automatic segmentation.
Wang D; Zhang T; Li M; Bueno R; Jayender J
Comput Med Imaging Graph; 2021 Mar; 88():101814. PubMed ID: 33486368
[TBL] [Abstract][Full Text] [Related]
20. [CT diagnosis of different pathological types of ground-glass nodules].
Gao F; Ge XJ; Li M; Chen Y; Lyu F; Hua Y; Ren Q; Qi L
Zhonghua Zhong Liu Za Zhi; 2014 Mar; 36(3):188-92. PubMed ID: 24785278
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]