Erika Denton

3.4k citations
63 papers · 2.0k indexed · h-index 21
Topics
AI in cancer detection (34 papers)Digital Radiography and Breast Imaging (19 papers)Image Retrieval and Classification Techniques (12 papers)
Partner nations
United KingdomSpainChina

In The Last Decade

Erika Denton

63 papers receiving 1.9k citations

Peers

Erika Denton
Comparison fields: 5 of 117
  • Artificial Intelligence 1.1k
  • Radiology, Nuclear Medicine and Imaging 1.1k
  • Computer Vision and Pattern Recognition 603
  • Pulmonary and Respiratory Medicine 518
  • Oncology 239
Replace Matthew T. Freedman with:
Matthew T. Freedman United States
Shandong Wu United States
Adrien Depeursinge Switzerland
Caroline Boggis United Kingdom
Jue Jiang United States
Hiroyuki Yoshida United States
Chuan Zhou United States
Chung‐Ming Lo Taiwan
Dorit D. Adler United States
Kazunari Misawa Japan
Erika Denton relative to Matthew T. Freedman United States Matthew T. Freedman's profile →
Citations per field
00.5×1.7×
Matthew T. Freedman · 1×
Citations per year

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
#WorkIndexed citations
1 1
2 6
3 9
4 26
5 200
6 7
7 14
8 7
9 2
10
A Novel Breast Image Preprocessing For Full Field Digital Mammographic Segmentation and Risk Classification.
2
11 51
12
Local Feature Based Breast Tissue Appearance Modelling for Mammographic Risk Assessment
1
13 14
14 278
15 4
16 160
17 20
18 5
19 83
20 2

About Erika Denton

Erika Denton is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 63 papers that have together received 2.0k indexed citations. Recurring topics across this work include AI in cancer detection (34 papers), Digital Radiography and Breast Imaging (19 papers) and Image Retrieval and Classification Techniques (12 papers). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (1.1k citations), Artificial Intelligence (1.1k citations) and Computer Vision and Pattern Recognition (603 citations). Erika Denton has collaborated with scholars based in United Kingdom, Spain and China. Frequent co-authors include Reyer Zwiggelaar, Arnau Oliver, Jordi Freixenet, Elsa Pérez, Josep Pont, Robert Martí, Joan Martı́, Azam Hamidinekoo, Andrik Rampun and Arne Juette. Their work appears in journals such as Gut, IEEE Transactions on Biomedical Engineering and IEEE Transactions on Medical Imaging.

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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