Samuel G. Armato

发表

The Lung Image Database Consortium (LIDC): pulmonary nodule measurements, the variation, and the difference between different size metrics

Geoffrey McLennan, Eric A. Hoffman, Michael F. McNitt-Gray, 2007, SPIE Medical Imaging.

CT Assessment of Response to Therapy: Tumor Volume Change Measurement, Truth Data & Error | NIST

Geoffrey McLennan, Marios A. Gavrielides, Nicholas Petrick, 2009 .

Analysis of a three-dimensional lung nodule detection method for thoracic CT scans

Heber MacMahon, Maryellen Lissak Giger, Samuel G. Armato, 2000, Medical Imaging: Image Processing.

Automated detection of pulmonary nodules in helical computed tomography images of the thorax

Kunio Doi, Heber MacMahon, Maryellen Lissak Giger, 1998, Medical Imaging.

A computer-aided diagnosis system to identify regions of pathologic change in temporal subtraction images of the chest

Samuel G. Armato, Katherine Lee, Charles Ho, 2015, Medical Imaging.

Variability in radiomics features among iDose4 reconstruction levels

Samuel G. Armato, Joseph J. Foy, Mena Shenouda, 2019, Medical Imaging.

PROSTATEx: Prostate MR Classification Challenge (Conference Presentation)

Nicholas Petrick, Karen Drukker, Samuel G. Armato, 2017, Medical Imaging.

Extrapolation techniques for textural characterization of tissue in medical images

Samuel G. Armato, Adam Starkey, William F. Sensakovic, 2007, SPIE Medical Imaging.

A study on the effect of CT imaging acquisition parameters on lung nodule image interpretation

Jacob D. Furst, Samuel G. Armato, David S. Channin, 2009, Medical Imaging.

Computerized lung nodule detection: comparison of performance for low-dose and standard-dose helical CT scans

Kunio Doi, Heber MacMahon, Maryellen Lissak Giger, 2001, SPIE Medical Imaging.

Automated segmentation of mucosal change in rhinosinusitis patients

Samuel G. Armato, Adam Starkey, William F. Sensakovic, 2010, Medical Imaging.

Radiomics-based texture analysis of idiopathic pulmonary fibrosis for genetic and survival predictions

Samuel G. Armato, Joseph J. Foy, Jorie D. Budzikowski, 2020, Medical Imaging.

The Lung Image Database Consortium (LIDC): a quality assurance model for the collection of expert-defined truth in lung-nodule-based image analysis studies

Eric A. Hoffman, Michael F. McNitt-Gray, Denise R. Aberle, 2007, SPIE Medical Imaging.

Development of a multiple-template matching technique for removal of false positives in a computer-aided diagnostic scheme

Kunio Doi, Qiang Li, Heber MacMahon, 2001, SPIE Medical Imaging.

Letter to the Editor: Use of Publicly Available Image Resources.

Maryellen L. Giger, Karen Drukker, Georgia D. Tourassi, 2017, Academic radiology.

Effect of a small number of training cases on the performance of massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose CT

Kunio Doi, Kenji Suzuki, Feng Li, 2003, SPIE Medical Imaging.

Pre-trained deep convolutional neural networks for the segmentation of malignant pleural mesothelioma tumor on CT scans

Samuel G. Armato, Christopher M. Straus, Eyjolfur Gudmundsson, 2019, Medical Imaging.

Automated lung segmentation in magnetic resonance images

Samuel G. Armato, Adam Starkey, William F. Sensakovic, 2005, SPIE Medical Imaging.

The Lung Image Database Consortium (LIDC) data collection process for nodule detection and annotation

Michael F. McNitt-Gray, Denise R. Aberle, Heber MacMahon, 2007, SPIE Medical Imaging.

Semantics and image content integration for pulmonary nodule interpretation in thoracic computed tomography

Jacob D. Furst, Samuel G. Armato, Daniela Stan Raicu, 2007, SPIE Medical Imaging.

Computerized lung nodule detection: effect of image annotation schemes for conveying results to radiologists

Samuel G. Armato, 2003, SPIE Medical Imaging.

Big Data Integration Case Study for Radiology Data Sources

Samuel G. Armato, Alexander Rasin, Priya Deshpande, 2018, 2018 IEEE Life Sciences Conference (LSC).

Regulated morphology approach to fuzzy shape analysis with application to blood vessel extraction in thoracic CT scans

Samuel G. Armato, Gady Agam, Changhua Wu, 2004, SPIE Medical Imaging.

Magnetic Resonance Imaging of the Lung: Automated Segmentation Methods

Samuel G. Armato, William F. Sensakovic, S. Armato, 2008 .

Investigating the dose dependence of median pixel value in CT lung images of patients undergoing stereotactic body radiation therapy

Samuel G. Armato, Hania A. Al-Hallaq, Alexandra R. Cunliffe, 2012, Medical Imaging.

Three-dimensional approach to lung nodule detection in helical CT

Kunio Doi, Heber MacMahon, Maryellen Lissak Giger, 1999, Medical Imaging.

A shape-dependent variability metric for evaluating panel segmentations with a case study on LIDC

Jacob D. Furst, Samuel G. Armato, Daniela Raicu, 2010, Medical Imaging.

Automatic detection of pulmonary nodules in low-dose screening thoracic CT examinations

Kenneth R. Hoffmann, Samuel G. Armato, Dag Wormanns, 1999, Medical Imaging.

Modelling semantics from image data: opportunities from LIDC

Jacob D. Furst, Samuel G. Armato, Daniela Stan Raicu, 2010 .

Radiomics-based assessment of idiopathic pulmonary fibrosis is associated with genetic mutations and patient survival

Samuel G. Armato, Jorie D. Budzikowski, Jonathan H. Chung, 2021, Journal of medical imaging.

Improved detection of focal pneumonia by chest radiography with bone suppression imaging

Heber MacMahon, Samuel G. Armato, Feng Li, 2012, European Radiology.

Computerized Detection of Lung Nodules

Maryellen L. Giger, Kunio Doi, Heber MacMahon, 2002 .

Automated lung segmentation in digital posteroanterior and lateral chest radiographs: Applications in diagnostic radiology and nuclear medicine

Samuel G. Armato, 1997 .

Revised Modified Response Evaluation Criteria in Solid Tumors for Assessment of Response in Malignant Pleural Mesothelioma (Version 1.1)

Samuel G. Armato, Anna K. Nowak, S. Armato, 2018, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.

Computer-Aided Diagnosis in Medical Imaging

Nico Karssemeijer, Maryellen L. Giger, Samuel G. Armato, 2001, IEEE Trans. Medical Imaging.

Incorporation of pre‐therapy 18F‐FDG uptake data with CT texture features into a radiomics model for radiation pneumonitis diagnosis

Thomas Guerrero, Samuel G. Armato, Richard Castillo, 2017, Medical physics.

Autosegmentation for thoracic radiation treatment planning: A grand challenge at AAPM 2017

Paul Aljabar, Harini Veeraraghavan, Andre Dekker, 2018, Medical physics.

SPIE hosts grand challenges to advance CAD in medical imaging

Samuel G. Armato, 2018 .

A Comparison of Different Size Metrics for Pulmonary Nodule Measurements 1

Geoffrey McLennan, Michael F. McNitt-Gray, Denise R. Aberle, 2007 .

North American Multicenter Volumetric CT Study for Clinical Staging of Malignant Pleural Mesothelioma: Feasibility and Logistics of Setting Up a Quantitative Imaging Study

Samuel G. Armato, David P. Naidich, Alan Mitchell, 2016, Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer.