BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

160 related articles for article (PubMed ID: 37493322)

  • 21. Thin-section computed tomography-histopathologic comparisons of pulmonary focal interstitial fibrosis, atypical adenomatous hyperplasia, adenocarcinoma in situ, and minimally invasive adenocarcinoma with pure ground-glass opacity.
    Si MJ; Tao XF; Du GY; Cai LL; Han HX; Liang XZ; Zhao JM
    Eur J Radiol; 2016 Oct; 85(10):1708-1715. PubMed ID: 27666606
    [TBL] [Abstract][Full Text] [Related]  

  • 22. 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]  

  • 23. 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]  

  • 24. A radiomics study to predict invasive pulmonary adenocarcinoma appearing as pure ground-glass nodules.
    Cai J; Liu H; Yuan H; Wu Y; Xu Q; Lv Y; Li J; Fu J; Ye J
    Clin Radiol; 2021 Feb; 76(2):143-151. PubMed ID: 33187676
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Factors distinguishing invasive from pre-invasive adenocarcinoma presenting as pure ground glass pulmonary nodules.
    Yang HH; Lv YL; Fan XH; Ai ZY; Xu XC; Ye B; Hu DZ
    Radiat Oncol; 2020 Jul; 15(1):186. PubMed ID: 32736567
    [TBL] [Abstract][Full Text] [Related]  

  • 26. CT features and quantitative analysis of subsolid nodule lung adenocarcinoma for pathological classification prediction.
    Li X; Zhang W; Yu Y; Zhang G; Zhou L; Wu Z; Liu B
    BMC Cancer; 2020 Jan; 20(1):60. PubMed ID: 31992239
    [TBL] [Abstract][Full Text] [Related]  

  • 27. 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]  

  • 28. 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]  

  • 29. Measuring pure ground-glass nodules on computed tomography: assessing agreement between a commercially available deep learning algorithm and radiologists' readings.
    Zuo Z; Wang P; Zeng W; Qi W; Zhang W
    Acta Radiol; 2023 Apr; 64(4):1422-1430. PubMed ID: 36317301
    [TBL] [Abstract][Full Text] [Related]  

  • 30. 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]  

  • 31. [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]  

  • 32. 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]  

  • 33. 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]  

  • 34. Pathological components and CT imaging analysis of the area adjacent pleura within the pure ground-glass nodules with pleural deformation in invasive lung adenocarcinoma.
    Jiang Y; Xiong Z; Zhao W; Tian D; Zhang Q; Li Z
    BMC Cancer; 2022 Sep; 22(1):958. PubMed ID: 36068487
    [TBL] [Abstract][Full Text] [Related]  

  • 35. 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]  

  • 36. Morphological factors differentiating between early lung adenocarcinomas appearing as pure ground-glass nodules measuring ≤10 mm on thin-section computed tomography.
    Xiang W; Xing Y; Jiang S; Chen G; Mao H; Labh K; Jia X; Sun X
    Cancer Imaging; 2014 Nov; 14(1):33. PubMed ID: 25608623
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Pulmonary ground-glass nodules diagnosis: mean change rate of peak CT number as a discriminative factor of pathology during a follow-up.
    Peng M; Li Z; Hu H; Liu S; Xu B; Zhu W; Han Y; Xiong L; Lin Q
    Br J Radiol; 2016; 89(1058):20150556. PubMed ID: 26562098
    [TBL] [Abstract][Full Text] [Related]  

  • 38. 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]  

  • 39. Predictors of Invasive Adenocarcinomas among Pure Ground-Glass Nodules Less Than 2 cm in Diameter.
    Hsu WC; Huang PC; Pan KT; Chuang WY; Wu CY; Wong HF; Yang CT; Wan YL
    Cancers (Basel); 2021 Aug; 13(16):. PubMed ID: 34439100
    [TBL] [Abstract][Full Text] [Related]  

  • 40. High-resolution CT image analysis based on 3D convolutional neural network can enhance the classification performance of radiologists in classifying pulmonary non-solid nodules.
    Zhang T; Wang Y; Sun Y; Yuan M; Zhong Y; Li H; Yu T; Wang J
    Eur J Radiol; 2021 Aug; 141():109810. PubMed ID: 34102564
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 8.