Alan J. Stone

532 total citations
29 papers, 344 citations indexed

About

Alan J. Stone is a scholar working on Radiology, Nuclear Medicine and Imaging, Cardiology and Cardiovascular Medicine and Surgery. According to data from OpenAlex, Alan J. Stone has authored 29 papers receiving a total of 344 indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Radiology, Nuclear Medicine and Imaging, 7 papers in Cardiology and Cardiovascular Medicine and 6 papers in Surgery. Recurrent topics in Alan J. Stone's work include Advanced MRI Techniques and Applications (15 papers), Advanced Neuroimaging Techniques and Applications (8 papers) and MRI in cancer diagnosis (5 papers). Alan J. Stone is often cited by papers focused on Advanced MRI Techniques and Applications (15 papers), Advanced Neuroimaging Techniques and Applications (8 papers) and MRI in cancer diagnosis (5 papers). Alan J. Stone collaborates with scholars based in United Kingdom, Ireland and United States. Alan J. Stone's co-authors include Nicholas P. Blockley, Kevin Murphy, Richard G. Wise, Ashley D. Harris, Caitríona Lally, Valerie E. M. Griffeth, Christian Kerskens, Robert D. Johnston, Daniel P. Bulte and Syed Salman Shahid and has published in prestigious journals such as NeuroImage, Scientific Reports and Arteriosclerosis Thrombosis and Vascular Biology.

In The Last Decade

Alan J. Stone

24 papers receiving 335 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Alan J. Stone United Kingdom 10 255 76 69 46 29 29 344
Sophie Schmid Netherlands 12 309 1.2× 41 0.5× 56 0.8× 61 1.3× 24 0.8× 21 442
Felipe B. Tancredi Canada 7 268 1.1× 67 0.9× 141 2.0× 56 1.2× 44 1.5× 10 334
Lindsey M. Dethrage United States 10 241 0.9× 26 0.3× 48 0.7× 66 1.4× 22 0.8× 12 349
Ksenija Grgac United States 8 408 1.6× 70 0.9× 45 0.7× 26 0.6× 25 0.9× 8 477
Jonathan Goodwin Japan 12 269 1.1× 37 0.5× 92 1.3× 67 1.5× 17 0.6× 22 374
Elisabeth Springer Austria 9 315 1.2× 58 0.8× 47 0.7× 16 0.3× 9 0.3× 15 440
Jason M. Zhao United States 5 256 1.0× 32 0.4× 41 0.6× 34 0.7× 13 0.4× 10 328
R. Marc Lebel United States 13 340 1.3× 40 0.5× 47 0.7× 42 0.9× 6 0.2× 20 417
Hyunyeol Lee United States 12 240 0.9× 55 0.7× 30 0.4× 33 0.7× 5 0.2× 36 331
Sascha Köhler Germany 11 230 0.9× 34 0.4× 14 0.2× 38 0.8× 49 1.7× 16 360

Countries citing papers authored by Alan J. Stone

Since Specialization
Citations

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

Fields of papers citing papers by Alan J. Stone

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alan J. Stone. 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 Alan J. Stone. The network helps show where Alan J. Stone may publish in the future.

Co-authorship network of co-authors of Alan J. Stone

This figure shows the co-authorship network connecting the top 25 collaborators of Alan J. Stone. A scholar is included among the top collaborators of Alan J. Stone 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 Alan J. Stone. Alan J. Stone 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.
Stone, Alan J., Salvatore Campisi, Christian Kerskens, et al.. (2025). A preliminary ex vivo diffusion tensor imaging study of distinct aortic morphologies. Journal of Anatomy. 246(5). 745–756.
2.
Stone, Alan J., et al.. (2025). Quantitative susceptibility mapping of the human carotid artery: Assessing sensitivity to elastin and collagen ex vivo. Magnetic Resonance in Medicine. 94(2). 771–784.
3.
Yalın, Nefize, Ivor Simpson, Riccardo De Marco, et al.. (2024). Altered oxidative neurometabolic response to methylene blue in bipolar disorder revealed by quantitative neuroimaging. Journal of Affective Disorders. 362. 790–798. 2 indexed citations
4.
Johnston, Robert D., et al.. (2023). Microstructural and mechanical insight into atherosclerotic plaques: an ex vivo DTI study to better assess plaque vulnerability. Biomechanics and Modeling in Mechanobiology. 22(5). 1515–1530. 7 indexed citations
5.
Stone, Alan J., Christian Kerskens, Scott T. Robinson, et al.. (2022). Towards a Whole Sample Imaging Approach Using Diffusion Tensor Imaging to Examine the Foreign Body Response to Explanted Medical Devices. Polymers. 14(22). 4819–4819.
6.
Shahid, Syed Salman, et al.. (2021). Exploring arterial tissue microstructural organization using non-Gaussian diffusion magnetic resonance schemes. Scientific Reports. 11(1). 22247–22247. 5 indexed citations
7.
Stone, Alan J., et al.. (2021). Quantitative susceptibility mapping of carotid arterial tissue ex vivo: Assessing sensitivity to vessel microstructural composition. Magnetic Resonance in Medicine. 86(5). 2512–2527. 5 indexed citations
8.
9.
Stone, Alan J., George Harston, Davide Carone, et al.. (2019). Prospects for investigating brain oxygenation in acute stroke: Experience with a non‐contrast quantitative BOLD based approach. Human Brain Mapping. 40(10). 2853–2866. 14 indexed citations
10.
Stone, Alan J., et al.. (2019). Model-based Bayesian inference of brain oxygenation using quantitative BOLD. NeuroImage. 202. 116106–116106. 12 indexed citations
11.
Murphy, Kevin, Alan J. Stone, Michael Germuska, et al.. (2016). Measurement of oxygen extraction fraction (OEF): An optimized BOLD signal model for use with hypercapnic and hyperoxic calibration. NeuroImage. 129. 159–174. 26 indexed citations
12.
Blockley, Nicholas P. & Alan J. Stone. (2016). Improving the specificity of R2′ to the deoxyhaemoglobin content of brain tissue: Prospective correction of macroscopic magnetic field gradients. NeuroImage. 135. 253–260. 19 indexed citations
13.
Stone, Alan J. & Nicholas P. Blockley. (2016). Data acquired to demonstrate a streamlined approach to mapping and quantifying brain oxygenation using quantitative BOLD. Oxford University Research Archive (ORA) (University of Oxford). 1 indexed citations
14.
Blockley, Nicholas P., et al.. (2015). Sources of systematic error in calibrated BOLD based mapping of baseline oxygen extraction fraction. NeuroImage. 122. 105–113. 22 indexed citations
15.
Wise, Richard G., Ashley D. Harris, Alan J. Stone, & Kevin Murphy. (2013). Measurement of OEF and absolute CMRO2: MRI-based methods using interleaved and combined hypercapnia and hyperoxia. NeuroImage. 83. 135–147. 119 indexed citations
16.
Stone, Alan J.. (2013). How to ...give written feedback. Education for Primary Care. 24(6). 473–475. 2 indexed citations
17.
Stone, Alan J., Jacinta E. Browne, Brian Lennon, James F. Meaney, & Andrew Fagan. (2012). Effect of motion on the ADC quantification accuracy of whole-body DWIBS. Magnetic Resonance Materials in Physics Biology and Medicine. 25(4). 263–266. 7 indexed citations
18.
Stone, Alan J., et al.. (2004). Not Another Back Pain in Pregnancy!. Obstetrical & Gynecological Survey. 60(1). 1–2. 3 indexed citations
19.
Stone, Alan J.. (1990). Tap the Potential of Advisory Boards.. AGB reports. 32(4). 31–33. 1 indexed citations
20.
Stone, Alan J.. (1957). The premarital consultation. American Journal of Obstetrics and Gynecology. 73(6). 1363–1363. 1 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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