Edward Ashton

1.2k total citations
39 papers, 963 citations indexed

About

Edward Ashton is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Pathology and Forensic Medicine. According to data from OpenAlex, Edward Ashton has authored 39 papers receiving a total of 963 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Radiology, Nuclear Medicine and Imaging, 10 papers in Computer Vision and Pattern Recognition and 5 papers in Pathology and Forensic Medicine. Recurrent topics in Edward Ashton's work include Radiomics and Machine Learning in Medical Imaging (13 papers), MRI in cancer diagnosis (11 papers) and Medical Image Segmentation Techniques (10 papers). Edward Ashton is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (13 papers), MRI in cancer diagnosis (11 papers) and Medical Image Segmentation Techniques (10 papers). Edward Ashton collaborates with scholars based in United States, United Kingdom and Germany. Edward Ashton's co-authors include Kevin J. Parker, Teresa M. McShane, Michel J. Berg, Chaan S. Ng, Jeffrey L. Evelhoch, Frederick Kelcz, Edward F. Jackson, Steven D. Reich, David Raunig and Saara Tötterman and has published in prestigious journals such as Journal of Clinical Oncology, PLoS ONE and Cancer Research.

In The Last Decade

Edward Ashton

37 papers receiving 923 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Edward Ashton United States 14 404 173 154 117 110 39 963
Chengyan Wang China 18 406 1.0× 222 1.3× 209 1.4× 84 0.7× 62 0.6× 74 1.0k
Melcior Sentís Spain 19 757 1.9× 102 0.6× 306 2.0× 129 1.1× 190 1.7× 61 1.6k
André Homeyer Germany 13 294 0.7× 70 0.4× 229 1.5× 115 1.0× 48 0.4× 37 835
Mark D. Zarella United States 12 444 1.1× 137 0.8× 199 1.3× 68 0.6× 68 0.6× 30 1.1k
Gang Huang China 16 370 0.9× 210 1.2× 46 0.3× 99 0.8× 188 1.7× 44 918
Jiawei Tian China 18 382 0.9× 212 1.2× 138 0.9× 29 0.2× 75 0.7× 54 914
Shichong Zhou China 18 813 2.0× 153 0.9× 229 1.5× 88 0.8× 130 1.2× 63 1.4k
Peter McLaren Black United States 18 419 1.0× 283 1.6× 400 2.6× 308 2.6× 114 1.0× 38 1.6k
Yongchang Zheng China 21 147 0.4× 470 2.7× 109 0.7× 104 0.9× 279 2.5× 78 1.4k
Marios A. Gavrielides United States 21 737 1.8× 174 1.0× 187 1.2× 32 0.3× 400 3.6× 68 1.2k

Countries citing papers authored by Edward Ashton

Since Specialization
Citations

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

Fields of papers citing papers by Edward Ashton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Edward Ashton

This figure shows the co-authorship network connecting the top 25 collaborators of Edward Ashton. A scholar is included among the top collaborators of Edward Ashton 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 Edward Ashton. Edward Ashton 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.
Howard, Heidi, Edward Ashton, Manuel Costa, et al.. (2023). Confidential Consortium Framework: Secure Multiparty Applications with Confidentiality, Integrity, and High Availability. Proceedings of the VLDB Endowment. 17(2). 225–240. 4 indexed citations
2.
3.
Serai, Suraj D., Nancy A. Obuchowski, Sudhakar K. Venkatesh, et al.. (2017). Repeatability of MR Elastography of Liver: A Meta-Analysis. Radiology. 285(1). 92–100. 99 indexed citations
4.
Ashton, Edward, et al.. (2013). Advanced MR techniques in multicenter clinical trials. Journal of Magnetic Resonance Imaging. 37(4). 761–769. 11 indexed citations
5.
Ricart, Alejandro D., Edward Ashton, Matthew M. Cooney, et al.. (2011). A phase I study of MN-029 (denibulin), a novel vascular-disrupting agent, in patients with advanced solid tumors. Cancer Chemotherapy and Pharmacology. 68(4). 959–970. 27 indexed citations
6.
Ashton, Edward. (2010). Quantitative MR in multi‐center clinical trials. Journal of Magnetic Resonance Imaging. 31(2). 279–288. 11 indexed citations
7.
Spencer, Andrew, Oliver G. Ottmann, Thomas Kindler, et al.. (2009). PANOBINOSTAT HAS ACTIVITY IN TREATMENT-REFRACTORY HODGKIN LYMPHOMA. 94. 3 indexed citations
8.
Ashton, Edward, David Raunig, Chaan S. Ng, et al.. (2008). Scan‐rescan variability in perfusion assessment of tumors in MRI using both model and data‐derived arterial input functions. Journal of Magnetic Resonance Imaging. 28(3). 791–796. 58 indexed citations
9.
Ashton, Edward, et al.. (2008). A novel method for illumination suppression in hyperspectral images. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6966. 69660C–69660C. 30 indexed citations
10.
Ashton, Edward. (2007). Quantitative Medical Imaging. Journal of Imaging Science and Technology. 51(2). 117–121. 7 indexed citations
11.
Ashton, Edward. (2007). Widespread functional and molecular imaging in drug development. Expert Opinion on Drug Discovery. 2(11). 1477–1485. 5 indexed citations
12.
Ashton, Edward, Teresa M. McShane, & Jeffrey L. Evelhoch. (2005). Inter-Operator Variability in Perfusion Assessment of Tumors in MRI Using Automated AIF Detection. Lecture notes in computer science. 8(Pt 1). 451–458. 14 indexed citations
13.
Ashton, Edward, Kathryn Ellis, & Stuart W. McDonald. (2004). Course of the short gastric veins and their suitability for pancreatic islet transplantation. Clinical Anatomy. 17(8). 651–657. 1 indexed citations
14.
Ashton, Edward, et al.. (2003). Evaluation of reproducibility for manual and semi-automated feature extraction in CT and MR images. Proceedings - International Conference on Image Processing. 1. III–161. 3 indexed citations
15.
Ashton, Edward, Chihiro Takahashi, Michel J. Berg, et al.. (2003). Accuracy and reproducibility of manual and semiautomated quantification of MS lesions by MRI. Journal of Magnetic Resonance Imaging. 17(3). 300–308. 84 indexed citations
16.
17.
Ashton, Edward, Saara Tötterman, Chihiro Takahashi, José G. Tamez‐Peña, & Kevin J. Parker. (2002). Automated measurement of structures in CT and MR imagery: a validation study. 300–305. 3 indexed citations
18.
Ashton, Edward, et al.. (1997). A novel volumetric feature extraction technique with applications to MR images. IEEE Transactions on Medical Imaging. 16(4). 365–371. 33 indexed citations
19.
Ashton, Edward, et al.. (1995). Segmentation and Feature Extraction Techniques, with Applications to MRI Head Studies. Magnetic Resonance in Medicine. 33(5). 670–677. 32 indexed citations
20.
Ashton, Edward. (1995). Multiple Resolution Bayesian Segmentation of Ultrasound Images. Ultrasonic Imaging. 17(4). 291–304. 13 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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