Daniel B. Rowe

1.8k total citations
57 papers, 1.2k citations indexed

About

Daniel B. Rowe is a scholar working on Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience and Artificial Intelligence. According to data from OpenAlex, Daniel B. Rowe has authored 57 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Radiology, Nuclear Medicine and Imaging, 32 papers in Cognitive Neuroscience and 8 papers in Artificial Intelligence. Recurrent topics in Daniel B. Rowe's work include Advanced MRI Techniques and Applications (34 papers), Functional Brain Connectivity Studies (30 papers) and Advanced Neuroimaging Techniques and Applications (23 papers). Daniel B. Rowe is often cited by papers focused on Advanced MRI Techniques and Applications (34 papers), Functional Brain Connectivity Studies (30 papers) and Advanced Neuroimaging Techniques and Applications (23 papers). Daniel B. Rowe collaborates with scholars based in United States, Spain and Saudi Arabia. Daniel B. Rowe's co-authors include Brent R. Logan, James S. Hyde, Kevin M. Bennett, Hanbing Lu, Kathleen M. Schmainda, Andrew S. Nencka, Andrew D. Hahn, Joseph G. Ibrahim, Yousef Mazaheri and Bradley S. Peterson and has published in prestigious journals such as Journal of the American Statistical Association, NeuroImage and Magnetic Resonance in Medicine.

In The Last Decade

Daniel B. Rowe

52 papers receiving 1.2k 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 B. Rowe United States 16 835 449 88 74 73 57 1.2k
Lipeng Ning United States 18 618 0.7× 231 0.5× 21 0.2× 52 0.7× 13 0.2× 60 865
Yves D’Asseler Belgium 20 963 1.2× 402 0.9× 6 0.1× 32 0.4× 120 1.6× 125 1.7k
Jörg Polzehl Germany 17 326 0.4× 161 0.4× 260 3.0× 14 0.2× 30 0.4× 57 921
Cheng Guan Koay United States 22 1.4k 1.6× 174 0.4× 9 0.1× 174 2.4× 18 0.2× 37 1.6k
Maria Filomena Santarelli Italy 24 973 1.2× 222 0.5× 5 0.1× 151 2.0× 59 0.8× 148 2.3k
Peter Stanchev United States 15 367 0.4× 88 0.2× 9 0.1× 66 0.9× 53 0.7× 75 987
James Ledoux France 11 557 0.7× 117 0.3× 76 0.9× 77 1.0× 5 0.1× 51 980
Christopher J. Moore United States 13 331 0.4× 80 0.2× 11 0.1× 17 0.2× 88 1.2× 59 871
Claude Comtat France 31 2.5k 3.0× 185 0.4× 29 0.3× 35 0.5× 6 0.1× 131 3.1k
Yaniv Gur United States 13 911 1.1× 201 0.4× 4 0.0× 33 0.4× 13 0.2× 31 1.2k

Countries citing papers authored by Daniel B. Rowe

Since Specialization
Citations

This map shows the geographic impact of Daniel B. Rowe'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 B. Rowe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel B. Rowe more than expected).

Fields of papers citing papers by Daniel B. Rowe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel B. Rowe. 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 B. Rowe. The network helps show where Daniel B. Rowe may publish in the future.

Co-authorship network of co-authors of Daniel B. Rowe

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel B. Rowe. A scholar is included among the top collaborators of Daniel B. Rowe 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 B. Rowe. Daniel B. Rowe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wang, Zhengxin, et al.. (2024). A fully Bayesian approach for comprehensive mapping of magnitude and phase brain activation in complex-valued fMRI data. Magnetic Resonance Imaging. 109. 271–285. 1 indexed citations
2.
Maitra, Ranjan, et al.. (2018). Complex-valued time series modeling for improved activation detection in fMRI studies. The Annals of Applied Statistics. 12(3). 1451–1478. 19 indexed citations
3.
Rowe, Daniel B., et al.. (2016). Complex-valued time-series correlation increases sensitivity in FMRI analysis. Magnetic Resonance Imaging. 34(6). 765–770. 10 indexed citations
4.
Karaman, Muge, et al.. (2015). Incorporating relaxivities to more accurately reconstruct MR images. Magnetic Resonance Imaging. 33(4). 374–384. 5 indexed citations
5.
Karaman, Muge, et al.. (2014). Quantification of the Statistical Effects of Spatiotemporal Processing of Nontask fMRI Data. Brain Connectivity. 4(9). 649–661. 6 indexed citations
6.
Karaman, Muge, et al.. (2013). A statistical fMRI model for differential T2* contrast incorporating T1 and T2* of gray matter. Magnetic Resonance Imaging. 32(1). 9–27. 5 indexed citations
7.
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9.
Li, Rupeng, Ji‐Geng Yan, Hani S. Matloub, et al.. (2011). Long-term vascular access ports as a means of sedative administration in a rodent fMRI survival model. Journal of Neuroscience Methods. 200(2). 106–112. 5 indexed citations
10.
Hernández-García, Luis, Hesamoddin Jahanian, & Daniel B. Rowe. (2010). Quantitative analysis of arterial spin labeling FMRI data using a general linear model. Magnetic Resonance Imaging. 28(7). 919–927. 19 indexed citations
11.
Sanger, James R., et al.. (2009). Ectopic scalp replantation: A case report. Journal of Plastic Reconstructive & Aesthetic Surgery. 63(1). e23–e27. 12 indexed citations
12.
Rowe, Daniel B. & E. Mark Haacke. (2009). MAgnitude and PHase Thresholding (MAPHT) of noisy complex-valued magnetic resonance images. Magnetic Resonance Imaging. 27(9). 1271–1280. 3 indexed citations
13.
Hahn, Andrew D., Andrew S. Nencka, & Daniel B. Rowe. (2008). Improving robustness and reliability of phase-sensitive fMRI analysis using temporal off-resonance alignment of single-echo timeseries (TOAST). NeuroImage. 44(3). 742–752. 29 indexed citations
14.
Nencka, Andrew S. & Daniel B. Rowe. (2007). Reducing the unwanted draining vein BOLD contribution in fMRI with statistical post-processing methods. NeuroImage. 37(1). 177–188. 33 indexed citations
15.
Xu, Yin, Gaohong Wu, Daniel B. Rowe, et al.. (2007). COmplex-Model-Based Estimation of thermal noise for fMRI data in the presence of artifacts. Magnetic Resonance Imaging. 25(7). 1079–1088. 6 indexed citations
16.
Rowe, Daniel B.. (2005). Modeling both the magnitude and phase of complex-valued fMRI data. NeuroImage. 25(4). 1310–1324. 86 indexed citations
17.
Logan, Brent R. & Daniel B. Rowe. (2004). An evaluation of thresholding techniques in fMRI analysis. NeuroImage. 22(1). 95–108. 100 indexed citations
18.
Rowe, Daniel B. & Brent R. Logan. (2004). A complex way to compute fMRI activation. NeuroImage. 23(3). 1078–1092. 82 indexed citations
19.
Rowe, Daniel B. & Brent R. Logan. (2004). Complex fMRI analysis with unrestricted phase is equivalent to a magnitude-only model. NeuroImage. 24(2). 603–606. 32 indexed citations
20.
Rowe, Daniel B.. (2001). Bayesian source separation for reference function determination in fMRI. Magnetic Resonance in Medicine. 46(2). 374–378. 16 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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