D. Checkley

875 total citations
22 papers, 711 citations indexed

About

D. Checkley is a scholar working on Radiology, Nuclear Medicine and Imaging, Biomedical Engineering and Cardiology and Cardiovascular Medicine. According to data from OpenAlex, D. Checkley has authored 22 papers receiving a total of 711 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Radiology, Nuclear Medicine and Imaging, 4 papers in Biomedical Engineering and 3 papers in Cardiology and Cardiovascular Medicine. Recurrent topics in D. Checkley's work include Advanced MRI Techniques and Applications (18 papers), MRI in cancer diagnosis (12 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). D. Checkley is often cited by papers focused on Advanced MRI Techniques and Applications (18 papers), MRI in cancer diagnosis (12 papers) and Radiomics and Machine Learning in Medical Imaging (4 papers). D. Checkley collaborates with scholars based in United Kingdom, Sweden and Singapore. D. Checkley's co-authors include John C. Waterton, Jean Tessier, Xiaoping Zhu, Alan Jackson, Stephen R. Wedge, Jane Kendrew, I. Isherwood, Ian Kamaly-Asl, Gordon C. Jayson and D.S. Hickey and has published in prestigious journals such as British Journal of Cancer, Magnetic Resonance in Medicine and Journal of Magnetic Resonance Imaging.

In The Last Decade

D. Checkley

21 papers receiving 694 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D. Checkley United Kingdom 12 550 110 89 65 56 22 711
Ulf Hoffmann Germany 12 705 1.3× 80 0.7× 31 0.3× 90 1.4× 50 0.9× 17 838
Melanie Heilmann Germany 14 385 0.7× 77 0.7× 23 0.3× 106 1.6× 88 1.6× 17 546
Susan Cheung United Kingdom 14 496 0.9× 41 0.4× 59 0.7× 83 1.3× 66 1.2× 22 617
Kayako Isohashi Japan 15 504 0.9× 71 0.6× 111 1.2× 168 2.6× 40 0.7× 58 773
Chris J. Rose United Kingdom 10 675 1.2× 53 0.5× 63 0.7× 146 2.2× 126 2.3× 14 802
Josef Doll Germany 11 502 0.9× 70 0.6× 60 0.7× 114 1.8× 66 1.2× 13 752
Katharina Strach Germany 18 561 1.0× 68 0.6× 48 0.5× 69 1.1× 61 1.1× 38 907
Samantha J. Mills United Kingdom 21 692 1.3× 133 1.2× 440 4.9× 138 2.1× 62 1.1× 56 1.4k
Ka‐Loh Li United Kingdom 13 527 1.0× 31 0.3× 92 1.0× 51 0.8× 37 0.7× 26 650
Vibeke A. Larsen Denmark 13 258 0.5× 73 0.7× 174 2.0× 69 1.1× 26 0.5× 24 535

Countries citing papers authored by D. Checkley

Since Specialization
Citations

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

Fields of papers citing papers by D. Checkley

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by D. Checkley. 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 D. Checkley. The network helps show where D. Checkley may publish in the future.

Co-authorship network of co-authors of D. Checkley

This figure shows the co-authorship network connecting the top 25 collaborators of D. Checkley. A scholar is included among the top collaborators of D. Checkley 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 D. Checkley. D. Checkley 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.
Worthington, Philip, et al.. (2007). Misregistration artifacts in image‐derived arterial input function in non‐echo‐planar imaging‐based dynamic contrast‐enhanced MRI. Journal of Magnetic Resonance Imaging. 25(6). 1248–1255. 2 indexed citations
2.
3.
Bradley, Daniel P., et al.. (2004). Averaging Keyhole Pulse Sequence with Presaturation Pulses and EXORCYCLE Phase Cycling for Dynamic Contrast-Enhanced MRI. Magnetic Resonance in Medical Sciences. 3(4). 207–210. 4 indexed citations
4.
5.
Bradley, Daniel P., et al.. (2004). The VEGF signaling inhibitors ZD6474 and AZD2171 compromise hemodynamic parameters in an SW620 human colon tumor model: An analysis using perfusion-permeability dynamic contrast-enhanced magnetic resonance imaging (pp-DCE-MRI). 64. 1051–1051. 4 indexed citations
6.
Jackson, Alan, Gordon C. Jayson, Xiaoping Zhu, et al.. (2003). Reproducibility of quantitative dynamic contrast-enhanced MRI in newly presenting glioma. British Journal of Radiology. 76(903). 153–162. 104 indexed citations
7.
8.
Checkley, D., Jean Tessier, Jane Kendrew, John C. Waterton, & Stephen R. Wedge. (2003). Use of dynamic contrast-enhanced MRI to evaluate acute treatment with ZD6474, a VEGF signalling inhibitor, in PC-3 prostate tumours. British Journal of Cancer. 89(10). 1889–1895. 102 indexed citations
9.
Robinson, Simon P., Dominick J. O. McIntyre, D. Checkley, et al.. (2003). Tumour dose response to the antivascular agent ZD6126 assessed by magnetic resonance imaging. British Journal of Cancer. 88(10). 1592–1597. 94 indexed citations
10.
Checkley, D., Jean Tessier, Stephen R. Wedge, et al.. (2003). Dynamic contrast-enhanced MRI of vascular changes induced by the VEGF-signalling inhibitor ZD4190 in human tumour xenografts. Magnetic Resonance Imaging. 21(5). 475–482. 48 indexed citations
11.
Williams, Rebecca E., M. J. W. Prior, H. S. Bachelard, et al.. (2001). MRI studies of the neurotoxic effects of l -2-chloropropionic acid on rat brain. Magnetic Resonance Imaging. 19(2). 133–142. 3 indexed citations
12.
Zhu, Xiaoping, et al.. (2000). Quantification of endothelial permeability, leakage space, and blood volume in brain tumors using combined T1 and T2* contrast-enhanced dynamic MR imaging. Journal of Magnetic Resonance Imaging. 11(6). 575–585. 121 indexed citations
13.
Zhu, Xiaoping, et al.. (2000). Improving estimates of endothelial permeability surface area product using constrained fitting parameters for the estimation of the plasma tracer concentration function (PTCF). Research Explorer (The University of Manchester). 1968–1968. 8 indexed citations
14.
Zhu, Xiaoping, Gordon C. Jayson, Bernadette M. Carrington, et al.. (2000). Quantitative dynamic contrast-enhanced MRI in tumors. A reproducible technique in the head? A reproducible technique in the breast?. Research Explorer (The University of Manchester). 724–724. 2 indexed citations
15.
Checkley, D., et al.. (1996). Effect of ovariectomy on magnetic resonance T2* in rat femur. Magnetic Resonance in Medicine. 36(4). 567–570. 3 indexed citations
16.
Checkley, D., et al.. (1995). Active coil isolation in NMR imaging and spectroscopy using PIN diodes and tuned transmission line: a practical approach. Magnetic Resonance Materials in Physics Biology and Medicine. 3(1). 35–40. 7 indexed citations
17.
Checkley, D., et al.. (1989). High‐Resolution NMR imaging of an antigen‐induced arthritis in the Rabbit Knee. Magnetic Resonance in Medicine. 11(2). 221–235. 28 indexed citations
18.
Checkley, D., et al.. (1987). Detection of myocardial infarction in the mini‐pig using NMR imaging. Magnetic Resonance in Medicine. 5(3). 201–216. 20 indexed citations
19.
Checkley, D., et al.. (1986). A method for increasing the resolution of scanned projection radiography and other digital X-ray systems. British Journal of Radiology. 59(700). 365–371.
20.
Hickey, D.S., et al.. (1986). A method for the clinical measurement of relaxation times in magnetic resonance imaging. British Journal of Radiology. 59(702). 565–576. 22 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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