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Samuel G. Armato III
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2020 – today
- 2023
- [c36]Samuel G. Armato III:
Computational Medicine in Radiology: Medical Images as Big Data. JVA 2023: 66-70 - [c35]Linnea Kremer, Boris Fosso, Lucy Groothuis, Arlene Chapman, Samuel G. Armato III:
Radiomics-based classification of autosomal dominant polycystic kidney disease (ADPKD) Mayo imaging classification (MIC) and the effect of gray-level discretization. Medical Imaging: Computer-Aided Diagnosis 2023 - [c34]Mena Shenouda, Aditi Kaveti, Isabella Flerlage, Jayashree Kalpathy-Cramer, Maryellen L. Giger, Samuel G. Armato III:
Assessing robustness of a deep-learning model for COVID-19 classification on chest radiographs. Medical Imaging: Computer-Aided Diagnosis 2023 - [i1]Mena Shenouda, Eyjólfur Gudmundsson, Feng Li, Christopher M. Straus, Hedy L. Kindler, Arkadiusz Z. Dudek, Thomas Stinchcombe, Xiaofei Wang, Adam Starkey, Samuel G. Armato III:
Convolutional Neural Networks for Segmentation of Malignant Pleural Mesothelioma: Analysis of Probability Map Thresholds (CALGB 30901, Alliance). CoRR abs/2312.00223 (2023) - 2022
- [c33]Linnea Kremer, Natalie Perri, Eliza Sorber, Arlene Chapman, Samuel G. Armato III:
Normalization of MRI signal intensity in polycystic kidney disease and the effect on radiomic features. Medical Imaging: Computer-Aided Diagnosis 2022 - 2021
- [j12]Feng Li
, Samuel G. Armato, Roger Engelmann, Thomas Rhines, Jennie Crosby, Li Lan, Maryellen L. Giger, Heber MacMahon:
Anatomic Point-Based Lung Region with Zone Identification for Radiologist Annotation and Machine Learning for Chest Radiographs. J. Digit. Imaging 34(4): 922-931 (2021) - 2020
- [j11]Priya Deshpande, Alexander Rasin, Jun Son, Sungmin Kim, Eli T. Brown, Jacob Furst, Daniela Stan Raicu, Steven M. Montner, Samuel G. Armato:
Ontology-Based Radiology Teaching File Summarization, Coverage, and Integration. J. Digit. Imaging 33(3): 797-813 (2020) - [c32]Jorie D. Budzikowski, Ahmed A. Rashid, Joseph J. Foy, Jonathan H. Chung, Imre Noth, Samuel G. Armato III:
Radiomics-based texture analysis of idiopathic pulmonary fibrosis for genetic and survival predictions. Medical Imaging: Computer-Aided Diagnosis 2020 - [c31]Joseph J. Foy, Inna H. Gertsenshteyn
Dependence of radiomics features on CT image acquisition and reconstruction parameters using a cadaveric liver. Medical Imaging: Computer-Aided Diagnosis 2020
2010 – 2019
- 2019
- [c30]Joseph J. Foy, Mena Shenouda, Sahar Ramahi, Samuel G. Armato, Daniel T. Ginat:
Variability in radiomics features among iDose reconstruction levels. Medical Imaging: Computer-Aided Diagnosis 2019: 109501M - [c29]Eyjolfur Gudmundsson
Pre-trained deep convolutional neural networks for the segmentation of malignant pleural mesothelioma tumor on CT scans. Medical Imaging: Computer-Aided Diagnosis 2019: 109503J - 2018
- [j10]Priya Deshpande, Alexander Rasin, Eli T. Brown, Jacob Furst, Steven M. Montner, Samuel G. Armato III, Daniela Stan Raicu:
Augmenting Medical Decision Making With Text-Based Search of Teaching File Repositories and Medical Ontologies: Text-Based Search of Radiology Teaching Files. Int. J. Knowl. Discov. Bioinform. 8(2): 18-43 (2018) - [c28]Joseph J. Foy, Prerana Mitta, Lauren R. Nowosatka, Kayla R. Mendel, Hui Li, Maryellen L. Giger, Hania A. Al-Hallaq
Variations in algorithm implementation among quantitative texture analysis software packages. Medical Imaging: Computer-Aided Diagnosis 2018: 105751K - 2017
- [c27]Priya Deshpande, Alexander Rasin, Eli T. Brown, Jacob Furst, Daniela Raicu, Steven M. Montner, Samuel G. Armato III:
An Integrated Database and Smart Search Tool for Medical Knowledge Extraction from Radiology Teaching Files. MIH@KDD 2017: 10-18 - [e2]Samuel G. Armato III, Nicholas A. Petrick:
Medical Imaging 2017: Computer-Aided Diagnosis, Orlando, Florida, United States, 11-16 February 2017. SPIE Proceedings 10134, SPIE 2017, ISBN 9781510607132 [contents] - 2016
- [c26]Melanie Harrison, Jared Looper, Samuel G. Armato III:
Adaptive thresholding of chest temporal subtraction images in computer-aided diagnosis of pathologic change. Medical Imaging: Computer-Aided Diagnosis 2016: 978536 - [c25]Jared Looper, Melanie Harrison, Samuel G. Armato III:
A computer-aided diagnosis system to detect pathologies in temporal subtraction images of chest radiographs. Medical Imaging: Computer-Aided Diagnosis 2016: 978539 - [e1]Georgia D. Tourassi, Samuel G. Armato III:
Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February - 3 March 2016. SPIE Proceedings 9785, SPIE 2016, ISBN 9781510600201 [contents] - 2015
- [j9]Ronald Niehaus, Daniela Stan Raicu, Jacob Furst, Samuel G. Armato III:
Toward Understanding the Size Dependence of Shape Features for Predicting Spiculation in Lung Nodules for Computer-Aided Diagnosis. J. Digit. Imaging 28(6): 704-717 (2015) - [j8]Alexandra R. Cunliffe, Bradley White, Julia Justusson, Christopher Straus, Renuka Malik, Hania A. Al-Hallaq
Comparison of Two Deformable Registration Algorithms in the Presence of Radiologic Change Between Serial Lung CT Scans. J. Digit. Imaging 28(6): 755-760 (2015) - [c24]Charles Ho, Katherine Lee, Samuel G. Armato:
A computer-aided diagnosis system to identify regions of pathologic change in temporal subtraction images of the chest. Medical Imaging: Computer-Aided Diagnosis 2015: 94141L - 2013
- [c23]Alexandra R. Cunliffe, Hania A. Al-Hallaq
Comparison of demons deformable registration-based methods for texture analysis of serial thoracic CT scans. Medical Imaging: Computer-Aided Diagnosis 2013: 86700D - 2012
- [j7]Dmitry Zinovev, Yujie Duo, Daniela Stan Raicu, Jacob Furst, Samuel G. Armato III:
Consensus Versus Disagreement in Imaging Research: a Case Study Using the LIDC Database. J. Digit. Imaging 25(3): 423-436 (2012) - [c22]Brianna Knoll, Alexandra R. Cunliffe, Hania A. Al-Hallaq
Investigating the dose dependence of median pixel value in CT lung images of patients undergoing stereotactic body radiation therapy. Medical Imaging: Computer-Aided Diagnosis 2012: 83152W - 2011
- [c21]Olga Zinoveva, Dmitry Zinovev, Stephen A. Siena, Daniela Stan Raicu, Jacob Furst, Samuel G. Armato III:
A Texture-Based Probabilistic Approach for Lung Nodule Segmentation. ICIAR (2) 2011: 21-30 - [c20]Kenji Suzuki
Temporal subtraction of 'virtual dual-energy' chest radiographs for improved conspicuity of growing cancers and other pathologic changes. Medical Imaging: Computer-Aided Diagnosis 2011: 79630F - 2010
- [j6]Bram van Ginneken
Comparing and combining algorithms for computer-aided detection of pulmonary nodules in computed tomography scans: The ANODE09 study. Medical Image Anal. 14(6): 707-722 (2010) - [c19]William F. Sensakovic
Automated segmentation of mucosal change in rhinosinusitis patients. Medical Imaging: Computer-Aided Diagnosis 2010: 76243N - [c18]Stephen A. Siena, Olga Zinoveva, Daniela Raicu, Jacob Furst, Samuel G. Armato:
A shape-dependent variability metric for evaluating panel segmentations with a case study on LIDC. Medical Imaging: Computer-Aided Diagnosis 2010: 762416
2000 – 2009
- 2009
- [j5]Dmitry Zinovev, Daniela Stan Raicu, Jacob Furst, Samuel G. Armato III:
Predicting Radiological Panel Opinions Using a Panel of Machine Learning Classifiers. Algorithms 2(4): 1473-1502 (2009) - [j4]Dmitry Zinovev, Ekarin Varutbangkul, Daniela Stan Raicu, Jacob D. Furst, Samuel G. Armato III:
Semi-supervised learning approaches for predicting semantic characteristics of lung nodules. Intell. Decis. Technol. 3(4): 207-217 (2009) - 2007
- [c17]Michael F. McNitt-Gray, Samuel G. Armato, Charles R. Meyer, Anthony P. Reeves, Geoffrey McLennan, Richard C. Pais, J. Freymann, Matthew S. Brown, Roger M. Engelmann, Peyton H. Bland, G. E. Laderach, C. Piker, J. Guo, D. P. Qing, David F. Yankelevitz, Denise R. Aberle
The Lung Image Database Consortium (LIDC) data collection process for nodule detection and annotation. Medical Imaging: Computer-Aided Diagnosis 2007: 65140K - [c16]Anthony P. Reeves, Alberto M. Biancardi
The Lung Image Database Consortium (LIDC): pulmonary nodule measurements, the variation, and the difference between different size metrics. Medical Imaging: Computer-Aided Diagnosis 2007: 65140J - [c15]William F. Sensakovic
Extrapolation techniques for textural characterization of tissue in medical images. Medical Imaging: Computer-Aided Diagnosis 2007: 65143G - [c14]Samuel G. Armato, Rachael Y. Roberts, Geoffrey McLennan, Michael F. McNitt-Gray, David F. Yankelevitz, Ella A. Kazerooni, Edwin J. R. van Beek, Heber MacMahon, Denise R. Aberle
The Lung Image Database Consortium (LIDC): a quality assurance model for the collection of expert-defined truth in lung-nodule-based image analysis studies. Medical Imaging: Computer-Aided Diagnosis 2007: 651429 - [c13]Daniela Stan Raicu, Ekarin Varutbangkul, Janie G. Cisneros, Jacob Furst, David S. Channin, Samuel G. Armato:
Semantics and image content integration for pulmonary nodule interpretation in thoracic computed tomography. Medical Imaging: Image Processing 2007: 65120S - 2005
- [j3]Gady Agam, Samuel G. Armato III, Changhua Wu:
Vessel tree reconstruction in thoracic CT scans with application to nodule detection. IEEE Trans. Medical Imaging 24(4): 486-499 (2005) - [c12]William F. Sensakovic
Automated lung segmentation in magnetic resonance images. Medical Imaging: Image Processing 2005 - 2004
- [c11]Changhua Wu, Gady Agam, Arunabha Shasanka Roy, Samuel G. Armato:
Regulated morphology approach to fuzzy shape analysis with application to blood vessel extraction in thoracic CT scans. Medical Imaging: Image Processing 2004 - 2003
- [c10]Samuel G. Armato III, Heber MacMahon:
Automated lung segmentation and computer-aided diagnosis for thoracic CT scans. CARS 2003: 977-982 - [c9]Samuel G. Armato:
Computerized lung nodule detection: effect of image annotation schemes for conveying results to radiologists. Medical Imaging: Image Processing 2003 - [c8]Kenji Suzuki
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. Medical Imaging: Image Processing 2003 - 2001
- [j2]Maryellen L. Giger
Computer-Aided Diagnosis in Medical Imaging. IEEE Trans. Medical Imaging 20(12): 1205-1208 (2001) - [c7]Maryellen L. Giger, Samuel G. Armato III:
Current status and future direction of computer-aided diagnosis in chest CT. CARS 2001: 621-630 - [c6]Samuel G. Armato, Maryellen Lissak Giger
Computerized lung nodule detection: comparison of performance for low-dose and standard-dose helical CT scans. Medical Imaging: Image Processing 2001 - [c5]Qiang Li, Shigehiko Katsuragawa, Roger M. Engelmann, Samuel G. Armato, Heber MacMahon, Kunio Doi:
Development of a multiple-template matching technique for removal of false positives in a computer-aided diagnostic scheme. Medical Imaging: Image Processing 2001 - 2000
- [c4]Samuel G. Armato, Maryellen Lissak Giger, Heber MacMahon:
Analysis of a three-dimensional lung nodule detection method for thoracic CT scans. Medical Imaging: Image Processing 2000
1990 – 1999
- 1999
- [j1]Samuel G. Armato III, Maryellen L. Giger, Heber MacMahon:
Computerized analysis of abnormal asymmetry in digital chest radiographs: Evaluation of potential utility. J. Digit. Imaging 12(1): 34-42 (1999) - [c3]Samuel G. Armato, Maryellen Lissak Giger, James T. Blackburn, Kunio Doi, Heber MacMahon:
Three-dimensional approach to lung nodule detection in helical CT. Medical Imaging: Image Processing 1999 - [c2]Martin Fiebich, Christian Wietholt, Bernhard C. Renger, Samuel G. Armato, Kenneth R. Hoffmann, Dag Wormanns, Stefan Diederich:
Automatic detection of pulmonary nodules in low-dose screening thoracic CT examinations. Medical Imaging: Image Processing 1999 - 1998
- [c1]Samuel G. Armato, Maryellen Lissak Giger
Automated detection of pulmonary nodules in helical computed tomography images of the thorax. Medical Imaging: Image Processing 1998
Coauthor Index
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