Samuel G. Armato to Algorithms
This is a "connection" page, showing publications Samuel G. Armato has written about Algorithms.
Connection Strength
2.331
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Comparison of Two Deformable Registration Algorithms in the Presence of Radiologic Change Between Serial Lung CT Scans. J Digit Imaging. 2015 Dec; 28(6):755-60.
Score: 0.304
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The Reference Image Database to Evaluate Response to therapy in lung cancer (RIDER) project: a resource for the development of change-analysis software. Clin Pharmacol Ther. 2008 Oct; 84(4):448-56.
Score: 0.185
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Anniversary paper: image processing and manipulation through the pages of Medical Physics. Med Phys. 2008 Oct; 35(10):4488-500.
Score: 0.185
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Discrete-space versus continuous-space lesion boundary and area definitions. Med Phys. 2008 Sep; 35(9):4070-8.
Score: 0.184
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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: 0.174
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Temporal subtraction in chest radiography: automated assessment of registration accuracy. Med Phys. 2006 May; 33(5):1239-49.
Score: 0.157
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Evaluation of semiautomated measurements of mesothelioma tumor thickness on CT scans. Acad Radiol. 2005 Oct; 12(10):1301-9.
Score: 0.151
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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: 0.136
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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: 0.128
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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: 0.126
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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: 0.073
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CT-based pulmonary artery measurements for the assessment of pulmonary hypertension. Acad Radiol. 2014 Apr; 21(4):523-30.
Score: 0.068
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Lung texture in serial thoracic CT scans: assessment of change introduced by image registration. Med Phys. 2012 Aug; 39(8):4679-90.
Score: 0.060
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Characterization of mesothelioma and tissues present in contrast-enhanced thoracic CT scans. Med Phys. 2011 Feb; 38(2):942-7.
Score: 0.054
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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: 0.044
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Automated detection of lung nodules in CT scans: false-positive reduction with the radial-gradient index. Med Phys. 2006 Apr; 33(4):1133-40.
Score: 0.039
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Automated matching of temporally sequential CT sections. Med Phys. 2004 Dec; 31(12):3417-24.
Score: 0.036
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Automated lung segmentation for thoracic CT impact on computer-aided diagnosis. Acad Radiol. 2004 Sep; 11(9):1011-21.
Score: 0.035
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Massive training artificial neural network (MTANN) for reduction of false positives in computerized detection of lung nodules in low-dose computed tomography. Med Phys. 2003 Jul; 30(7):1602-17.
Score: 0.032
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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: 0.031
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Computerized detection of pulmonary nodules on CT scans. Radiographics. 1999 Sep-Oct; 19(5):1303-11.
Score: 0.025
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Autosegmentation for thoracic radiation treatment planning: A grand challenge at AAPM 2017. Med Phys. 2018 Oct; 45(10):4568-4581.
Score: 0.023
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Automated lung segmentation in digitized posteroanterior chest radiographs. Acad Radiol. 1998 Apr; 5(4):245-55.
Score: 0.022
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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: 0.016
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Three-dimensional stereoscopic volume rendering of malignant pleural mesothelioma. Int Surg. 2012 Jan-Mar; 97(1):65-70.
Score: 0.015
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Automated lung segmentation of diseased and artifact-corrupted magnetic resonance sections. Med Phys. 2006 Sep; 33(9):3085-93.
Score: 0.010
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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: 0.009
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Assessment methodologies and statistical issues for computer-aided diagnosis of lung nodules in computed tomography: contemporary research topics relevant to the lung image database consortium. Acad Radiol. 2004 Apr; 11(4):462-75.
Score: 0.008