Samantha K N Dilger
Overview
Explore the profile of Samantha K N Dilger including associated specialties, affiliations and a list of published articles.
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7
Citations
141
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0
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Recent Articles
1.
Dilger S, Nelson N, Venkatesh S, Ehman E, Fidler J, Fletcher J, et al.
Invest Radiol
. 2019 Jul;
54(9):572-579.
PMID: 31261292
Objective: The purpose of this work is to determine whether low doses of gadoxetate disodium (Eovist; Bayer Healthcare LLC, Whippany, NJ), a gadolinium-based contrast agent used for magnetic resonance liver...
2.
Dilger S, Leng S, Chen B, Carter R, Favazza C, Fletcher J, et al.
Phys Med Biol
. 2019 Apr;
64(10):105012.
PMID: 30995626
Determination of the effect of protocol modifications on diagnostic performance in CT with human observers is extremely time-consuming, limiting the applicability of such methods in routine clinical practice. In this...
3.
Dilger S, Yu L, Chen B, Favazza C, Carter R, Fletcher J, et al.
Phys Med Biol
. 2019 Apr;
64(10):105011.
PMID: 30995611
The purpose of this study was to determine the correlation between human observer performance for localization of small low contrast lesions within uniform water background versus an anatomical liver background,...
4.
Uthoff J, Koehn N, Larson J, Dilger S, Hammond E, Schwartz A, et al.
Eur Radiol
. 2019 Apr;
29(10):5367-5377.
PMID: 30937590
Objectives: Post-imaging mathematical prediction models (MPMs) provide guidance for the management of solid pulmonary nodules by providing a lung cancer risk score from demographic and radiologists-indicated imaging characteristics. We hypothesized...
5.
Kalpathy-Cramer J, Mamomov A, Zhao B, Lu L, Cherezov D, Napel S, et al.
Tomography
. 2017 Feb;
2(4):430-437.
PMID: 28149958
Radiomics is to provide quantitative descriptors of normal and abnormal tissues during classification and prediction tasks in radiology and oncology. Quantitative Imaging Network members are developing radiomic "feature" sets to...
6.
Dilger S, Uthoff J, Judisch A, Hammond E, Mott S, Smith B, et al.
J Med Imaging (Bellingham)
. 2016 Feb;
2(4):041004.
PMID: 26870744
Current computer-aided diagnosis (CAD) models for determining pulmonary nodule malignancy characterize nodule shape, density, and border in computed tomography (CT) data. Analyzing the lung parenchyma surrounding the nodule has been...
7.
Hammond E, Newell Jr J, Dilger S, Stoyles N, Morgan J, Sieren J, et al.
Toxicol Pathol
. 2016 Feb;
44(3):373-81.
PMID: 26839326
Medical imaging is a rapidly advancing field enabling the repeated, noninvasive assessment of physiological structure and function. These beneficial characteristics can supplement studies in swine by mirroring the clinical functions...