Erika Denton

3.4k total citations
63 papers, 2.0k citations indexed

About

Erika Denton is a scholar working on Artificial Intelligence, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, Erika Denton has authored 63 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Artificial Intelligence, 31 papers in Radiology, Nuclear Medicine and Imaging and 20 papers in Pulmonary and Respiratory Medicine. Recurrent topics in Erika Denton's work include AI in cancer detection (34 papers), Digital Radiography and Breast Imaging (19 papers) and Image Retrieval and Classification Techniques (12 papers). Erika Denton is often cited by papers focused on AI in cancer detection (34 papers), Digital Radiography and Breast Imaging (19 papers) and Image Retrieval and Classification Techniques (12 papers). Erika Denton collaborates with scholars based in United Kingdom, Spain and China. Erika Denton's co-authors include Reyer Zwiggelaar, Arnau Oliver, Jordi Freixenet, Elsa Pérez, Josep Pont, Robert Martí, Joan Martı́, Azam Hamidinekoo, Andrik Rampun and Arne Juette and has published in prestigious journals such as Gut, IEEE Transactions on Biomedical Engineering and IEEE Transactions on Medical Imaging.

In The Last Decade

Erika Denton

63 papers receiving 1.9k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Erika Denton United Kingdom 21 1.1k 1.1k 603 518 239 63 2.0k
Shandong Wu United States 28 1.3k 1.2× 1.2k 1.1× 653 1.1× 416 0.8× 240 1.0× 105 2.5k
Adrien Depeursinge Switzerland 26 856 0.8× 1.3k 1.2× 611 1.0× 531 1.0× 159 0.7× 117 2.3k
John Heine United States 24 899 0.8× 750 0.7× 474 0.8× 994 1.9× 518 2.2× 76 2.0k
Meyke Hermsen Netherlands 13 1.1k 1.0× 734 0.7× 428 0.7× 227 0.4× 225 0.9× 22 1.6k
Ashirbani Saha Canada 24 890 0.8× 1.3k 1.2× 506 0.8× 230 0.4× 136 0.6× 69 2.3k
Albert Gubern‐Mérida Netherlands 23 1.8k 1.6× 2.0k 1.9× 309 0.5× 667 1.3× 278 1.2× 50 2.7k
Weijie Chen United States 18 805 0.7× 935 0.9× 495 0.8× 178 0.3× 123 0.5× 75 1.9k
Shijun Wang United States 19 499 0.5× 790 0.7× 412 0.7× 451 0.9× 149 0.6× 65 1.8k
Matthew T. Freedman United States 26 930 0.8× 1.1k 1.0× 561 0.9× 687 1.3× 240 1.0× 178 2.6k
Ravi K. Samala United States 23 1.4k 1.2× 1.6k 1.5× 382 0.6× 600 1.2× 271 1.1× 80 2.6k

Countries citing papers authored by Erika Denton

Since Specialization
Citations

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

Fields of papers citing papers by Erika Denton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Erika Denton

This figure shows the co-authorship network connecting the top 25 collaborators of Erika Denton. A scholar is included among the top collaborators of Erika Denton 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 Erika Denton. Erika Denton 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.
Li, Guobin, et al.. (2025). An interpretable CNN-based model for mass classification in mammography. Knowledge-Based Systems. 316. 113372–113372. 1 indexed citations
2.
Sosna, Jacob, Nadya Pyatigorskaya, Gabriël P. Krestin, et al.. (2021). International survey on residency programs in radiology: similarities and differences among 17 countries. Clinical Imaging. 79. 230–234. 6 indexed citations
3.
Denton, Erika, et al.. (2019). Classification of Microcalcification Clusters in Digital Mammograms Using a Stack Generalization Based Classifier. Journal of Imaging. 5(9). 76–76. 9 indexed citations
4.
Denton, Erika, et al.. (2018). Classification of micro-calcification in mammograms using scalable linear Fisher discriminant analysis. Medical & Biological Engineering & Computing. 56(8). 1475–1485. 26 indexed citations
5.
Hamidinekoo, Azam, et al.. (2018). Deep learning in mammography and breast histology, an overview and future trends. Medical Image Analysis. 47. 45–67. 200 indexed citations
6.
Petridou, Eleni, Paul Malcolm, Andoni P. Toms, et al.. (2017). Breast fat volume measurement using wide-bore 3 T MRI: comparison of traditional mammographic density evaluation with MRI density measurements using automatic segmentation. Clinical Radiology. 72(7). 565–572. 7 indexed citations
7.
Hogg, Peter, et al.. (2015). Breast image pre-processing for mammographic tissue segmentation. Computers in Biology and Medicine. 67. 61–73. 14 indexed citations
8.
Denton, Erika, et al.. (2015). Breast cancer screening and diagnosis in the 21st century within the UK. Post Reproductive Health. 21(3). 105–111. 7 indexed citations
9.
Lexa, Frank J., Geraldine McGinty, Erika Denton, et al.. (2014). International Perspectives on Radiology Practice Metrics: Australia, France, Germany, Japan, New Zealand, Spain, the UK and USA. Journal of the American College of Radiology. 11(11). 1081–1086. 2 indexed citations
10.
Juette, Arne, et al.. (2014). A Novel Breast Image Preprocessing For Full Field Digital Mammographic Segmentation and Risk Classification.. 79–84. 2 indexed citations
11.
Mercer, Claire, et al.. (2013). Practitioner compression force variability in mammography: a preliminary study. British Journal of Radiology. 86(1022). 20110596–20110596. 51 indexed citations
12.
Chen, Zhili, Erika Denton, & Reyer Zwiggelaar. (2013). Local Feature Based Breast Tissue Appearance Modelling for Mammographic Risk Assessment. 1 indexed citations
13.
Hogg, Peter, Melanie Taylor, Katy Szczepura, Claire Mercer, & Erika Denton. (2012). Pressure and breast thickness in mammography—an exploratory calibration study. British Journal of Radiology. 86(1021). 20120222–20120222. 14 indexed citations
14.
Oliver, Arnau, Jordi Freixenet, Joan Martı́, et al.. (2009). A review of automatic mass detection and segmentation in mammographic images. Medical Image Analysis. 14(2). 87–110. 278 indexed citations
15.
Denton, Erika, et al.. (2009). Mammographic segmentation based on mammographic parenchymal patterns and spatial moments. 5116. 1–4. 4 indexed citations
16.
Oliver, Arnau, Jordi Freixenet, Robert Martí, et al.. (2008). A Novel Breast Tissue Density Classification Methodology. IEEE Transactions on Information Technology in Biomedicine. 12(1). 55–65. 160 indexed citations
17.
Freixenet, Jordi, Arnau Oliver, Robert Martí, et al.. (2008). Eigendetection of masses considering false positive reduction and breast density information. Medical Physics. 35(5). 1840–1853. 20 indexed citations
18.
Jamieson, C P, Erika Denton, & W R Burnham. (1999). Do gastroenterologists want to be trained in ultrasound? A national survey of trainees in gastroenterology. Gut. 44(1). 123–126. 5 indexed citations
19.
Denton, Erika, Luke Sonoda, Daniel Rueckert, et al.. (1999). Comparison and Evaluation of Rigid, Affine, and Nonrigid Registration of Breast MR Images. Journal of Computer Assisted Tomography. 23(5). 800–805. 83 indexed citations
20.
Denton, Erika, et al.. (1998). The value of the chest radiograph in reporting aerosol ventilation-perfusion scans. Nuclear Medicine Communications. 19(1). 71–76. 2 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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