Related references
Note: Only part of the references are listed.Deep Convolutional Neural Network-based Software Improves Radiologist Detection of Malignant Lung Nodules on Chest Radiographs
Yongsik Sim et al.
RADIOLOGY (2020)
Observer variability for Lung-RADS categorisation of lung cancer screening CTs: impact on patient management
Sarah J. van Riel et al.
EUROPEAN RADIOLOGY (2019)
End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography
Diego Ardila et al.
NATURE MEDICINE (2019)
Effectiveness of Lung-RADS in Reducing False-Positive Results in a Diverse, Underserved, Urban Lung Cancer Screening Cohort
Mark Kaminetzky et al.
JOURNAL OF THE AMERICAN COLLEGE OF RADIOLOGY (2019)
Perinodular and Intranodular Radiomic Features on Lung CT Images Distinguish Adenocarcinomas from Granulomas
Niha Beig et al.
RADIOLOGY (2019)
Screening for Lung Cancer: Lexicon for Communicating With Health Care Providers
Brett W. Carter et al.
AMERICAN JOURNAL OF ROENTGENOLOGY (2018)
Comparison Between Radiological Semantic Features and Lung-RADS in Predicting Malignancy of Screen-Detected Lung Nodules in the National Lung Screening Trial
Qian Li et al.
CLINICAL LUNG CANCER (2018)
Radiomics and radiogenomics in lung cancer: A review for the clinician
Rajat Thawani et al.
LUNG CANCER (2018)
Radiomic features analysis in computed tomography images of lung nodule classification
Chia-Hung Chen et al.
PLOS ONE (2018)
Quantitative vessel tortuosity: A potential CT imaging biomarker for distinguishing lung granulomas from adenocarcinomas
Mehdi Alilou et al.
SCIENTIFIC REPORTS (2018)
Combination of computer extracted shape and texture features enables discrimination of granulomas from adenocarcinoma on chest computed tomography
Mahdi Orooji et al.
JOURNAL OF MEDICAL IMAGING (2018)
Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: The LUNA16 challenge
Arnaud Arindra Adiyoso Setio et al.
MEDICAL IMAGE ANALYSIS (2017)
An integrated segmentation and shape-based classification scheme for distinguishing adenocarcinomas from granulomas on lung CT
Mehdi Alilou et al.
MEDICAL PHYSICS (2017)
Lung-RADS: Pushing the Limits
Maria D. Martin et al.
RADIOGRAPHICS (2017)
2D and 3D CT Radiomics Features Prognostic Performance Comparison in Non-Small Cell Lung Cancer
Chen Shen et al.
TRANSLATIONAL ONCOLOGY (2017)
Towards automatic pulmonary nodule management in lung cancer screening with deep learning
Francesco Ciompi et al.
SCIENTIFIC REPORTS (2017)
Human Attention in Visual Question Answering: Do Humans and Deep Networks Look at the Same Regions?
Abhishek Das et al.
COMPUTER VISION AND IMAGE UNDERSTANDING (2017)
Characterization of tumor and adjacent peritumoral stroma in patients with breast cancer using high-resolution diffusion-weighted imaging: Correlation with pathologic biomarkers
Hee Jung Shin et al.
EUROPEAN JOURNAL OF RADIOLOGY (2016)
Pulmonary Nodule Detection in CT Images: False Positive Reduction Using Multi-View Convolutional Networks
Arnaud Arindra Adiyoso Setio et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2016)
Prognostic Effect of Tumor Lymphocytic Infiltration in Resectable Non-Small-Cell Lung Cancer
Elisabeth Brambilla et al.
JOURNAL OF CLINICAL ONCOLOGY (2016)
Predicting Malignant Nodules from Screening CT Scans
Samuel Hawkins et al.
JOURNAL OF THORACIC ONCOLOGY (2016)
Automated detection of pulmonary nodules in PET/CT images: Ensemble false-positive reduction using a convolutional neural network technique
Atsushi Teramoto et al.
MEDICAL PHYSICS (2016)
Radiomics: Images Are More than Pictures, They Are Data
Robert J. Gillies et al.
RADIOLOGY (2016)
Reproducibility of radiomics for deciphering tumor phenotype with imaging
Binsheng Zhao et al.
SCIENTIFIC REPORTS (2016)
Co-occurrence of Local Anisotropic Gradient Orientations (CoLlAGe): A new radiomics descriptor
Prateek Prasanna et al.
SCIENTIFIC REPORTS (2016)
Test-Retest Data for Radiomics Feature Stability Analysis: Generalizable or Study-Specific?
Janna E. van Timmeren et al.
TOMOGRAPHY (2016)
Modes of cancer cell invasion and the role of the microenvironment
Andrew G. Clark et al.
CURRENT OPINION IN CELL BIOLOGY (2015)
CT-based radiomic signature predicts distant metastasis in lung adenocarcinoma
Thibaud P. Coroller et al.
RADIOTHERAPY AND ONCOLOGY (2015)
Machine Learning methods for Quantitative Radiomic Biomarkers
Chintan Parmar et al.
SCIENTIFIC REPORTS (2015)
Accuracy of FDG-PET to Diagnose Lung Cancer in Areas With Infectious Lung Disease A Meta-analysis
Stephen A. Deppen et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2014)
Stability of FDG-PET Radiomics features: An integrated analysis of test-retest and inter-observer variability
Ralph T. H. Leijenaar et al.
ACTA ONCOLOGICA (2013)
Texture analysis of advanced non-small cell lung cancer (NSCLC) on contrast-enhanced computed tomography: prediction of the response to the first-line chemotherapy
Marco Ravanelli et al.
EUROPEAN RADIOLOGY (2013)
PET/CT imaging in different types of lung cancer: An overview
Valentina Ambrosini et al.
EUROPEAN JOURNAL OF RADIOLOGY (2012)
Tumour heterogeneity in non-small cell lung carcinoma assessed by CT texture analysis: a potential marker of survival
Balaji Ganeshan et al.
EUROPEAN RADIOLOGY (2012)
3D Slicer as an image computing platform for the Quantitative Imaging Network
Andriy Fedorov et al.
MAGNETIC RESONANCE IMAGING (2012)
Can lung cancer screening by computed tomography be effective in areas with endemic histoplasmosis?
Sandra L. Starnes et al.
JOURNAL OF THORACIC AND CARDIOVASCULAR SURGERY (2011)
Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening
Denise R. Aberle et al.
NEW ENGLAND JOURNAL OF MEDICINE (2011)
Evaluation of Reader Variability in the Interpretation of Follow-up CT Scans at Lung Cancer Screening
Satinder Singh et al.
RADIOLOGY (2011)
CAD (computed-aided detection) and CADx (computer aided diagnosis) systems in identifying and characterising lung nodules on chest CT: overview of research, developments and new prospects
F. Fraioli et al.
RADIOLOGIA MEDICA (2010)
Ohio River Valley Fever Presenting as Isolated Granulomatous Hepatitis: A Case Report
Rizwan Kibria et al.
SOUTHERN MEDICAL JOURNAL (2009)
The Reference Image Database to Evaluate Response to therapy in lung cancer (RIDER) project: A resource for the development of change-analysis software
S. G. Armato et al.
CLINICAL PHARMACOLOGY & THERAPEUTICS (2008)
Lung cancer in never smokers: A review
Janakiraman Subramanian et al.
JOURNAL OF CLINICAL ONCOLOGY (2007)
Computer-aided diagnosis of the solitary pulmonary nodule
SK Shah et al.
ACADEMIC RADIOLOGY (2005)
Share Paper
