Daniel D. Samber

776 total citations
15 papers, 617 citations indexed

About

Daniel D. Samber is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, Daniel D. Samber has authored 15 papers receiving a total of 617 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Radiology, Nuclear Medicine and Imaging, 11 papers in Pulmonary and Respiratory Medicine and 5 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in Daniel D. Samber's work include Cerebrovascular and Carotid Artery Diseases (10 papers), Cardiac Imaging and Diagnostics (9 papers) and Advanced MRI Techniques and Applications (5 papers). Daniel D. Samber is often cited by papers focused on Cerebrovascular and Carotid Artery Diseases (10 papers), Cardiac Imaging and Diagnostics (9 papers) and Advanced MRI Techniques and Applications (5 papers). Daniel D. Samber collaborates with scholars based in United States, Netherlands and Australia. Daniel D. Samber's co-authors include Zahi A. Fayad, Venkatesh Mani, Vitalii V. Itskovich, Karen Briley‐Sæbø, Juan Gilberto S. Aguinaldo, Valentı́n Fuster, Gabor Mizsei, John T. Fallon, Torjus Skajaa and Willem J. M. Mulder and has published in prestigious journals such as Biomaterials, Radiology and Magnetic Resonance in Medicine.

In The Last Decade

Daniel D. Samber

14 papers receiving 611 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Daniel D. Samber United States 10 339 266 155 120 104 15 617
Smbat Amirbekian United States 7 199 0.6× 236 0.9× 98 0.6× 82 0.7× 77 0.7× 12 561
Jean‐Marc Vrigneaud France 16 355 1.0× 141 0.5× 49 0.3× 114 0.9× 53 0.5× 42 670
Michael C. John United States 11 141 0.4× 224 0.8× 249 1.6× 106 0.9× 87 0.8× 17 782
Luhua Shen United States 6 162 0.5× 76 0.3× 103 0.7× 45 0.4× 49 0.5× 13 529
Ashvin N. Pande United States 7 122 0.4× 92 0.3× 96 0.6× 142 1.2× 35 0.3× 8 463
Olivier Raguin France 16 227 0.7× 169 0.6× 31 0.2× 104 0.9× 42 0.4× 31 610
Lefteris Livieratos United Kingdom 16 810 2.4× 151 0.6× 59 0.4× 255 2.1× 38 0.4× 44 1.0k
Juan Carlos Huertas United States 6 111 0.3× 128 0.5× 61 0.4× 256 2.1× 59 0.6× 6 504
Theresa Reiter Germany 11 224 0.7× 104 0.4× 166 1.1× 87 0.7× 29 0.3× 36 514
Erxiong Lu China 12 248 0.7× 59 0.2× 117 0.8× 412 3.4× 36 0.3× 20 887

Countries citing papers authored by Daniel D. Samber

Since Specialization
Citations

This map shows the geographic impact of Daniel D. Samber's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel D. Samber with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel D. Samber more than expected).

Fields of papers citing papers by Daniel D. Samber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel D. Samber. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel D. Samber. The network helps show where Daniel D. Samber may publish in the future.

Co-authorship network of co-authors of Daniel D. Samber

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel D. Samber. A scholar is included among the top collaborators of Daniel D. Samber based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel D. Samber. Daniel D. Samber is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

15 of 15 papers shown
1.
Samber, Daniel D., et al.. (2019). Segmentation of carotid arterial walls using neural networks. World Journal of Radiology. 12(1). 1–9. 8 indexed citations
2.
Mani, Venkatesh, Mark Woodward, Daniel D. Samber, et al.. (2014). Predictors of change in carotid atherosclerotic plaque inflammation and burden as measured by 18-FDG-PET and MRI, respectively, in the dal-PLAQUE study. International journal of cardiac imaging. 30(3). 571–582. 26 indexed citations
3.
Lipinski, Michael J., Juan C. Frías, Vardan Amirbekian, et al.. (2009). Macrophage-Specific Lipid-Based Nanoparticles Improve Cardiac Magnetic Resonance Detection and Characterization of Human Atherosclerosis. JACC. Cardiovascular imaging. 2(5). 637–647. 70 indexed citations
4.
Jarzyna, Peter A., Torjus Skajaa, Anita Gianella, et al.. (2009). Iron oxide core oil-in-water emulsions as a multifunctional nanoparticle platform for tumor targeting and imaging. Biomaterials. 30(36). 6947–6954. 86 indexed citations
5.
Aidi, Hamza El, Venkatesh Mani, Hiroaki Taniguchi, et al.. (2009). Cross-sectional, prospective study of MRI reproducibility in the assessment of plaque burden of the carotid arteries and aorta. Nature Reviews Cardiology. 6(3). 219–228. 37 indexed citations
6.
Amirbekian, Vardan, Michael J. Lipinski, Juan C. Frías, et al.. (2009). MR imaging of human atherosclerosis using immunomicelles molecularly targeted to macrophages. Journal of Cardiovascular Magnetic Resonance. 11(S1). 3 indexed citations
7.
Altschuler, Eric Lewin, et al.. (2007). “Stroop Concordant” coloring of letters for remediation of dyslexia. Medical Hypotheses. 69(2). 381–382.
8.
Anderson, Russell W., Venkatesh Mani, Daniel D. Samber, et al.. (2006). Automated classification of atherosclerotic plaque from magnetic resonance images using predictive models. Biosystems. 90(2). 456–466. 9 indexed citations
9.
Mani, Venkatesh, et al.. (2006). Carotid Black Blood MRI Burden of Atherosclerotic Disease Assessment Correlates with Ultrasound Intima-Media Thickness. Journal of Cardiovascular Magnetic Resonance. 8(3). 529–534. 35 indexed citations
10.
Mani, Venkatesh, Karen Briley‐Sæbø, Vitalii V. Itskovich, Daniel D. Samber, & Zahi A. Fayad. (2005). Gradient echo acquisition for superparamagnetic particles with positive contrast (GRASP): Sequence characterization in membrane and glass superparamagnetic iron oxide phantoms at 1.5T and 3T. Magnetic Resonance in Medicine. 55(1). 126–135. 153 indexed citations
11.
Mani, Venkatesh, Vitalii V. Itskovich, Gabor Mizsei, et al.. (2005). Comparison of gated and nongated fast multislice black‐blood carotid imaging using rapid extended coverage and inflow/outflow saturation techniques. Journal of Magnetic Resonance Imaging. 22(5). 628–633. 34 indexed citations
12.
Itskovich, Vitalii V., Venkatesh Mani, Gabor Mizsei, et al.. (2004). Parallel and nonparallel simultaneous multislice black‐blood double inversion recovery techniques for vessel wall imaging. Journal of Magnetic Resonance Imaging. 19(4). 459–467. 36 indexed citations
13.
Itskovich, Vitalii V., Daniel D. Samber, Venkatesh Mani, et al.. (2004). Quantification of human atherosclerotic plaques using spatially enhanced cluster analysis of multicontrast‐weighted magnetic resonance images. Magnetic Resonance in Medicine. 52(3). 515–523. 63 indexed citations
14.
Mani, Venkatesh, Vitalii V. Itskovich, Michael Szimtenings, et al.. (2004). Rapid Extended Coverage Simultaneous Multisection Black-Blood Vessel Wall MR Imaging. Radiology. 232(1). 281–288. 52 indexed citations
15.
Itskovich, Vitalii V., et al.. (2003). Magnetic resonance microscopy quantifies the disease progression in Marfan syndrome mice. Journal of Magnetic Resonance Imaging. 17(4). 435–439. 5 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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