A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images
Published 2019 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images
Authors
Keywords
-
Journal
EUROPEAN RADIOLOGY
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2019-12-07
DOI
10.1007/s00330-019-06533-w
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- CT features differentiating pre- and minimally invasive from invasive adenocarcinoma appearing as mixed ground-glass nodules: mass is a potential imaging biomarker
- (2018) X.-W. Wang et al. CLINICAL RADIOLOGY
- CT quantitative parameters to predict the invasiveness of lung pure ground-glass nodules (pGGNs)
- (2018) L. Han et al. CLINICAL RADIOLOGY
- Changes in quantitative CT image features of ground-glass nodules in differentiating invasive pulmonary adenocarcinoma from benign and in situ lesions: histopathological comparisons
- (2018) Y.P. Zhang et al. CLINICAL RADIOLOGY
- Radiomics signature: a biomarker for the preoperative discrimination of lung invasive adenocarcinoma manifesting as a ground-glass nodule
- (2018) Li Fan et al. EUROPEAN RADIOLOGY
- Liver Fibrosis: Deep Convolutional Neural Network for Staging by Using Gadoxetic Acid–enhanced Hepatobiliary Phase MR Images
- (2018) Koichiro Yasaka et al. RADIOLOGY
- Lung Adenocarcinoma Invasiveness Risk in Pure Ground-Glass Opacity Lung Nodules Smaller than 2 cm
- (2018) Geun Lee et al. THORACIC AND CARDIOVASCULAR SURGEON
- Solid component proportion is an important predictor of tumor invasiveness in clinical stage T1N0M0 (cT1N0M0) lung adenocarcinoma
- (2018) Meng Li et al. CANCER IMAGING
- 3D convolutional neural network for differentiating pre-invasive lesions from invasive adenocarcinomas appearing as ground-glass nodules with diameters ≤3 cm using HRCT
- (2018) Shengping Wang et al. QUANTITATIVE IMAGING IN MEDICINE AND SURGERY
- CT characterization of different pathologic types of subcentimeter pulmonary ground-glass nodular lesions
- (2018) Feng Gao et al. BRITISH JOURNAL OF RADIOLOGY
- 3D Deep Learning from CT Scans Predicts Tumor Invasiveness of Subcentimeter Pulmonary Adenocarcinomas
- (2018) Wei Zhao et al. CANCER RESEARCH
- Fusion of quantitative imaging features and serum biomarkers to improve performance of computer‐aided diagnosis scheme for lung cancer: A preliminary study
- (2018) Jing Gong et al. MEDICAL PHYSICS
- Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017
- (2017) Heber MacMahon et al. RADIOLOGY
- Analysis of pulmonary pure ground-glass nodule in enhanced dual energy CT imaging for predicting invasive adenocarcinoma: comparing with conventional thin-section CT imaging
- (2017) Ying Zhang et al. Journal of Thoracic Disease
- Software performance in segmenting ground-glass and solid components of subsolid nodules in pulmonary adenocarcinomas
- (2016) Julien G. Cohen et al. EUROPEAN RADIOLOGY
- Quantitative CT analysis of pulmonary ground-glass opacity nodules for distinguishing invasive adenocarcinoma from non-invasive or minimally invasive adenocarcinoma: the added value of using iodine mapping
- (2015) Ji Ye Son et al. EUROPEAN RADIOLOGY
- Multi-slice computed tomography characteristics of solitary pulmonary ground-glass nodules: Differences between malignant and benign
- (2015) Haiyang Hu et al. Thoracic Cancer
- Pure Ground-Glass Opacity Neoplastic Lung Nodules: Histopathology, Imaging, and Management
- (2014) Ho Yun Lee et al. AMERICAN JOURNAL OF ROENTGENOLOGY
- Computerized Texture Analysis of Persistent Part-Solid Ground-Glass Nodules: Differentiation of Preinvasive Lesions from Invasive Pulmonary Adenocarcinomas
- (2014) Hee-Dong Chae et al. RADIOLOGY
- International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society International Multidisciplinary Classification of Lung Adenocarcinoma
- (2011) William D. Travis et al. Journal of Thoracic Oncology
- About the relationship between ROC curves and Cohen's kappa
- (2007) Arie Ben-David ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now