Mitko Veta

69 papers receiving 2.4k citations

Mitko Veta's Hit Papers

Breast Cancer Histopathology Image Analysis: A Review 2014 · 556 citations
5560+4+8Years since publication100200300400500

Peers

Mitko Veta
Comparison fields: 5 of 126
  • Biophysics 339
  • Health Informatics 71
  • Radiology, Nuclear Medicine and Imaging 1.1k
  • Artificial Intelligence 1.5k
  • Computer Vision and Pattern Recognition 909
Replace Yi Gao with:
Yi Gao China
Ajay Basavanhally United States
Xiao Han China
Shan E Ahmed Raza United Kingdom
Ángel Cruz-Roa Colombia
Fuyong Xing United States
Laura E. Boucheron United States
Frank G. Zöllner Germany
Yuanpu Xie United States
Maximilian Baust Germany
Mitko Veta relative to Yi Gao China Yi Gao's profile →
Citations per field
00.5×1.5×1.9×
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Citations per year

Countries citing papers authored by Mitko Veta

Since Specialization
Citations

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

Fields of papers citing papers by Mitko Veta

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Mitko Veta, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mitko Veta Line = papers co-authored together Mitko Veta links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 71 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Breast Cancer Histopathology Image Analysis: A Review
Hit paper breakdown →
2014556
2 2013309
3 2020134
4 2013132
5 201784
6 201681
7 201169
8 202168
9 201268
10 202263
11 201961
12 201855
13 201955
14 202251
15 201947
16 201343
17 201937
18 202036
19 201931
20 202128

About Mitko Veta

Mitko Veta is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence, Computer Vision and Pattern Recognition, Oncology and Biophysics, having authored 71 papers that have together received 2.5k indexed citations. Recurring topics across this work include AI in cancer detection (34 papers), Radiomics and Machine Learning in Medical Imaging (25 papers), Cell Image Analysis Techniques (10 papers), Digital Imaging for Blood Diseases (6 papers), Medical Image Segmentation Techniques (6 papers), Advanced MRI Techniques and Applications (6 papers), Cutaneous Melanoma Detection and Management (5 papers) and Glaucoma and retinal disorders (5 papers). The work is most often cited by research in Biophysics (339 citations), Health Informatics (71 citations), Radiology, Nuclear Medicine and Imaging (1.1k citations), Artificial Intelligence (1.5k citations) and Computer Vision and Pattern Recognition (909 citations). Mitko Veta has collaborated with scholars based in Netherlands, United States and United Kingdom. Frequent co-authors include Josien P. W. Pluim, P. J. van Diest, Max A. Viergever, André Huisman, Robert Kornegoor, Nikolas Stathonikos, Maxime W. Lafarge, Koen A. J. Eppenhof, Pim Moeskops and Coen de Vente. Their work appears in journals such as PLoS ONE, IEEE Transactions on Biomedical Engineering, Journal of Pathology Informatics, Cochrane Database of Systematic Reviews and Scientific Reports.

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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