 Connection
David Lynch to Image Processing, Computer-Assisted
This is a "connection" page, showing publications David Lynch has written about Image Processing, Computer-Assisted.
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Connection Strength |
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1.282 |
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Chang Y, Lim J, Kim N, Seo JB, Lynch DA. A support vector machine classifier reduces interscanner variation in the HRCT classification of regional disease pattern in diffuse lung disease: comparison to a Bayesian classifier. Med Phys. 2013 May; 40(5):051912.
Score: 0.295
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Lynch DA. Quantitative CT of fibrotic interstitial lung disease. Chest. 2007 Mar; 131(3):643-644.
Score: 0.193
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Lippitt WL, Maier LA, Fingerlin TE, Lynch DA, Yadav R, Rieck J, Hill AC, Liao SY, Mroz MM, Barkes BQ, Ju Chae K, Jeon Hwang H, Carlson NE. The textures of sarcoidosis: quantifying lung disease through variograms. Phys Med Biol. 2025 Jan 13; 70(2).
Score: 0.166
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Lynch DR, Mozley PD, Sokol S, Maas NM, Balcer LJ, Siderowf AD. Lack of effect of polymorphisms in dopamine metabolism related genes on imaging of TRODAT-1 in striatum of asymptomatic volunteers and patients with Parkinson's disease. Mov Disord. 2003 Jul; 18(7):804-12.
Score: 0.149
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Uthoff J, Stephens MJ, Newell JD, Hoffman EA, Larson J, Koehn N, De Stefano FA, Lusk CM, Wenzlaff AS, Watza D, Neslund-Dudas C, Carr LL, Lynch DA, Schwartz AG, Sieren JC. Machine learning approach for distinguishing malignant and benign lung nodules utilizing standardized perinodular parenchymal features from CT. Med Phys. 2019 Jul; 46(7):3207-3216.
Score: 0.113
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Salisbury ML, Lynch DA, van Beek EJ, Kazerooni EA, Guo J, Xia M, Murray S, Anstrom KJ, Yow E, Martinez FJ, Hoffman EA, Flaherty KR. Idiopathic Pulmonary Fibrosis: The Association between the Adaptive Multiple Features Method and Fibrosis Outcomes. Am J Respir Crit Care Med. 2017 04 01; 195(7):921-929.
Score: 0.097
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Ash SY, Harmouche R, Ross JC, Diaz AA, Hunninghake GM, Putman RK, Onieva J, Martinez FJ, Choi AM, Lynch DA, Hatabu H, Rosas IO, Estepar RSJ, Washko GR. The Objective Identification and Quantification of Interstitial Lung Abnormalities in Smokers. Acad Radiol. 2017 08; 24(8):941-946.
Score: 0.095
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Gallardo-Estrella L, Lynch DA, Prokop M, Stinson D, Zach J, Judy PF, van Ginneken B, van Rikxoort EM. Normalizing computed tomography data reconstructed with different filter kernels: effect on emphysema quantification. Eur Radiol. 2016 Feb; 26(2):478-86.
Score: 0.085
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Lynch DA, Travis WD, M?ller NL, Galvin JR, Hansell DM, Grenier PA, King TE. Idiopathic interstitial pneumonias: CT features. Radiology. 2005 Jul; 236(1):10-21.
Score: 0.043
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Halper-Stromberg E, Cho MH, Wilson C, Nevrekar D, Crapo JD, Washko G, Est?par RS, Lynch DA, Silverman EK, Leach S, Castaldi PJ. Visual Assessment of Chest Computed Tomographic Images Is Independently Useful for Genetic Association Analysis in Studies of Chronic Obstructive Pulmonary Disease. Ann Am Thorac Soc. 2017 Jan; 14(1):33-40.
Score: 0.024
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Cho MH, Castaldi PJ, Hersh CP, Hobbs BD, Barr RG, Tal-Singer R, Bakke P, Gulsvik A, San Jos? Est?par R, Van Beek EJ, Coxson HO, Lynch DA, Washko GR, Laird NM, Crapo JD, Beaty TH, Silverman EK. A Genome-Wide Association Study of Emphysema and Airway Quantitative Imaging Phenotypes. Am J Respir Crit Care Med. 2015 Sep 01; 192(5):559-69.
Score: 0.022
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Connection Strength
The connection strength for concepts is the sum of the scores for each matching publication.
Publication scores are based on many factors, including how long ago they were written and whether the person is a first or senior author.
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