Deep Learning-Based Stage-Wise Risk Stratification for Early Lung Adenocarcinoma in CT Images: A Multi-Center Study

Computer-aided diagnosis of ground glass pulmonary nodule by fusing deep learning and radiomics features

(2021) Xianfang Hu et al.   PHYSICS IN MEDICINE AND BIOLOGY

Cancer statistics, 2020

(2020) Rebecca L. Siegel et al.   CA-A CANCER JOURNAL FOR CLINICIANS

Feature‐shared adaptive‐boost deep learning for invasiveness classification of pulmonary subsolid nodules in CT images

(2020) Jun Wang et al.   MEDICAL PHYSICS

Comparison and Fusion of Deep Learning and Radiomics Features of Ground-Glass Nodules to Predict the Invasiveness Risk of Stage-I Lung Adenocarcinomas in CT Scan

(2020) Xianwu Xia et al.   Frontiers in Oncology

Non-invasive evaluation for benign and malignant subcentimeter pulmonary ground-glass nodules (≤1 cm) based on CT texture analysis

(2020) Xianghua Hu et al.   BRITISH JOURNAL OF RADIOLOGY

Predicting the invasiveness of lung adenocarcinomas appearing as ground-glass nodule on CT scan using multi-task learning and deep radiomics

(2020) Xiang Wang et al.   Translational Lung Cancer Research

3D deep learning based classification of pulmonary ground glass opacity nodules with automatic segmentation

(2020) Duo Wang et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

Development and validation of a radiomics nomogram for identifying invasiveness of pulmonary adenocarcinomas appearing as subcentimeter ground-glass opacity nodules

(2019) Wei Zhao et al.   EUROPEAN JOURNAL OF RADIOLOGY

Lung Adenocarcinomas Manifesting as Radiological Part-Solid Nodules Define a Special Clinical Subtype

(2019) Ting Ye et al.   Journal of Thoracic Oncology

Brief Report: Insights for management of ground-glass opacities from the National Lung Screening Trial

(2019) Hilary A. Robbins et al.   Journal of Thoracic Oncology

End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography

(2019) Diego Ardila et al.   NATURE MEDICINE

Lung adenocarcinoma diagnosis in one stage

(2019) Pengyi Hao et al.   NEUROCOMPUTING

Automated segmentation of macular edema in OCT using deep neural networks

(2019) Junjie Hu et al.   MEDICAL IMAGE ANALYSIS

A deep residual learning network for predicting lung adenocarcinoma manifesting as ground-glass nodule on CT images

(2019) Jing Gong et al.   EUROPEAN 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

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

(2018) Liang-Chieh Chen et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Predicting malignancy of pulmonary ground-glass nodules and their invasiveness by random forest

(2018) Xueyan Mei et al.   Journal of Thoracic Disease

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

Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning

(2018) Nicolas Coudray et al.   NATURE MEDICINE

3D Deep Learning from CT Scans Predicts Tumor Invasiveness of Subcentimeter Pulmonary Adenocarcinomas

(2018) Wei Zhao et al.   CANCER RESEARCH

Perinodular and Intranodular Radiomic Features on Lung CT Images Distinguish Adenocarcinomas from Granulomas

(2018) Niha Beig et al.   RADIOLOGY

Distinct Clinicopathologic Characteristics and Prognosis Based on the Presence of Ground Glass Opacity Component in Clinical Stage IA Lung Adenocarcinoma

(2018) Aritoshi Hattori et al.   Journal of Thoracic Oncology

Quantitative CT analysis of pulmonary pure ground-glass nodule predicts histological invasiveness

(2017) Qiong Li et al.   EUROPEAN JOURNAL OF RADIOLOGY

Software-based risk stratification of pulmonary adenocarcinomas manifesting as pure ground glass nodules on computed tomography

(2017) Ursula Nemec et al.   EUROPEAN RADIOLOGY

Central focused convolutional neural networks: Developing a data-driven model for lung nodule segmentation

(2017) Shuo Wang et al.   MEDICAL IMAGE ANALYSIS

Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017

(2017) Heber MacMahon et al.   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

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