Samuel G. Armato to Radiographic Image Interpretation, Computer-Assisted
This is a "connection" page, showing publications Samuel G. Armato has written about Radiographic Image Interpretation, Computer-Assisted.
Connection Strength
3.359
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Toward Understanding the Size Dependence of Shape Features for Predicting Spiculation in Lung Nodules for Computer-Aided Diagnosis. J Digit Imaging. 2015 Dec; 28(6):704-17.
Score: 0.428
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Temporal subtraction chest radiography. Eur J Radiol. 2009 Nov; 72(2):238-43.
Score: 0.274
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Assessment of radiologist performance in the detection of lung nodules: dependence on the definition of "truth". Acad Radiol. 2009 Jan; 16(1):28-38.
Score: 0.265
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Discrete-space versus continuous-space lesion boundary and area definitions. Med Phys. 2008 Sep; 35(9):4070-8.
Score: 0.259
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The Lung Image Database Consortium (LIDC): an evaluation of radiologist variability in the identification of lung nodules on CT scans. Acad Radiol. 2007 Nov; 14(11):1409-21.
Score: 0.244
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Two-dimensional extrapolation methods for texture analysis on CT scans. Med Phys. 2007 Sep; 34(9):3465-72.
Score: 0.241
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Temporal subtraction in chest radiography: automated assessment of registration accuracy. Med Phys. 2006 May; 33(5):1239-49.
Score: 0.220
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Measurement of mesothelioma on thoracic CT scans: a comparison of manual and computer-assisted techniques. Med Phys. 2004 May; 31(5):1105-15.
Score: 0.192
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Automated lung nodule classification following automated nodule detection on CT: a serial approach. Med Phys. 2003 Jun; 30(6):1188-97.
Score: 0.180
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Automated detection of lung nodules in CT scans: effect of image reconstruction algorithm. Med Phys. 2003 Mar; 30(3):461-72.
Score: 0.177
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Automated lung segmentation in digital lateral chest radiographs. Med Phys. 1998 Aug; 25(8):1507-20.
Score: 0.129
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Computer-aided nodule detection system: results in an unselected series of consecutive chest radiographs. Acad Radiol. 2015 Apr; 22(4):475-80.
Score: 0.101
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CT-based pulmonary artery measurements for the assessment of pulmonary hypertension. Acad Radiol. 2014 Apr; 21(4):523-30.
Score: 0.095
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Lung texture in serial thoracic CT scans: registration-based methods to compare anatomically matched regions. Med Phys. 2013 Jun; 40(6):061906.
Score: 0.090
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The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): a completed reference database of lung nodules on CT scans. Med Phys. 2011 Feb; 38(2):915-31.
Score: 0.077
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Temporal subtraction in chest radiography: mutual information as a measure of image quality. Med Phys. 2009 Dec; 36(12):5675-82.
Score: 0.071
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Mixture of expert 3D massive-training ANNs for reduction of multiple types of false positives in CAD for detection of polyps in CT colonography. Med Phys. 2008 Feb; 35(2):694-703.
Score: 0.062
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Vessel tree reconstruction in thoracic CT scans with application to nodule detection. IEEE Trans Med Imaging. 2005 Apr; 24(4):486-99.
Score: 0.051
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Automated matching of temporally sequential CT sections. Med Phys. 2004 Dec; 31(12):3417-24.
Score: 0.050
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A Competition, Benchmark, Code, and Data for Using Artificial Intelligence to Detect Lesions in Digital Breast Tomosynthesis. JAMA Netw Open. 2023 02 01; 6(2):e230524.
Score: 0.044
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Computerized analysis of abnormal asymmetry in digital chest radiographs: evaluation of potential utility. J Digit Imaging. 1999 Feb; 12(1):34-42.
Score: 0.033
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Quality assurance and quantitative imaging biomarkers in low-dose CT lung cancer screening. Br J Radiol. 2018 Oct; 91(1090):20170401.
Score: 0.031
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Role of the Quantitative Imaging Biomarker Alliance in optimizing CT for the evaluation of lung cancer screen-detected nodules. J Am Coll Radiol. 2015 Apr; 12(4):390-5.
Score: 0.026
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Improved detection of focal pneumonia by chest radiography with bone suppression imaging. Eur Radiol. 2012 Dec; 22(12):2729-35.
Score: 0.021