Mitko Veta

8.3k total citations · 1 hit paper
59 papers, 2.0k citations indexed

About

Mitko Veta is a scholar working on Radiology, Nuclear Medicine and Imaging, Artificial Intelligence and Oncology. According to data from OpenAlex, Mitko Veta has authored 59 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Radiology, Nuclear Medicine and Imaging, 30 papers in Artificial Intelligence and 16 papers in Oncology. Recurrent topics in Mitko Veta's work include AI in cancer detection (29 papers), Radiomics and Machine Learning in Medical Imaging (22 papers) and Cell Image Analysis Techniques (10 papers). Mitko Veta is often cited by papers focused on AI in cancer detection (29 papers), Radiomics and Machine Learning in Medical Imaging (22 papers) and Cell Image Analysis Techniques (10 papers). Mitko Veta collaborates with scholars based in Netherlands, United States and United Kingdom. Mitko Veta's 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, Pieter Vos and Coen de Vente and has published in prestigious journals such as PLoS ONE, Scientific Reports and Cochrane Database of Systematic Reviews.

In The Last Decade

Mitko Veta

57 papers receiving 2.0k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Breast Cancer Histopathology Image Analysis: A Review

2014 482 citations Mitko Veta, Josien P. W. Pluim et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Mitko Veta Netherlands	20	1.3k	992	767	309	223	59	2.0k
Shan E Ahmed Raza United Kingdom	19	1.3k 1.0×	884 0.9×	727 0.9×	355 1.1×	168 0.8×	55	2.1k
Korsuk Sirinukunwattana United Kingdom	16	1.6k 1.2×	1.1k 1.1×	969 1.3×	341 1.1×	163 0.7×	38	2.2k
Ángel Cruz-Roa Colombia	13	1.4k 1.1×	852 0.9×	776 1.0×	206 0.7×	110 0.5×	40	1.8k
Laura E. Boucheron United States	12	1.2k 1.0×	552 0.6×	844 1.1×	386 1.2×	141 0.6×	40	1.8k
Fuyong Xing United States	28	1.7k 1.3×	944 1.0×	1.4k 1.8×	681 2.2×	237 1.1×	79	2.9k
Meyke Hermsen Netherlands	13	1.1k 0.8×	734 0.7×	428 0.6×	198 0.6×	102 0.5×	22	1.6k
Xiao Han China	25	738 0.6×	660 0.7×	350 0.5×	125 0.4×	200 0.9×	145	1.9k
Shadi Albarqouni Germany	17	1.0k 0.8×	706 0.7×	577 0.8×	166 0.5×	161 0.7×	49	1.6k
Shannon C. Agner United States	13	758 0.6×	608 0.6×	447 0.6×	176 0.6×	97 0.4×	25	1.3k
Yuanpu Xie United States	13	901 0.7×	488 0.5×	598 0.8×	309 1.0×	128 0.6×	21	1.4k

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-authorship network of co-authors of Mitko Veta

This figure shows the co-authorship network connecting the top 25 collaborators of Mitko Veta. A scholar is included among the top collaborators of Mitko Veta 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 Mitko Veta. Mitko Veta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Weerd, Jaap van der, F. Van den Berkmortel, Jan Willem de Groot, et al.. (2025). 36P Interpretable histomorphological subtypes linked to ICI response in advanced melanoma using AI-assisted histopathology analysis. TU/e Research Portal. 10. 100235–100235.

Crawley, Richard, Robert J. Holtackers, Sven Plein, et al.. (2024). Automated cardiovascular MR myocardial scar quantification with unsupervised domain adaptation. European Radiology Experimental. 8(1). 93–93. 3 indexed citations

Blokx, Willeke A.M., et al.. (2024). Tissue cross-section and pen marking segmentation in whole slide images. TU/e Research Portal. 10–10. 1 indexed citations

Berkmortel, Franchette van den, Marye J. Boers‐Sonderen, Jan Willem B. de Groot, et al.. (2024). Baseline tumor-infiltrating lymphocyte patterns and response to immune checkpoint inhibition in metastatic cutaneous melanoma. European Journal of Cancer. 208. 114190–114190. 3 indexed citations

Daniels, Johannes M. A., Teodora Radonic, Jan H. von der Thüsen, et al.. (2024). Rapid On-Site Histology of Lung and Pleural Biopsies Using Higher Harmonic Generation Microscopy and Artificial Intelligence Analysis. Modern Pathology. 38(1). 100633–100633. 4 indexed citations

Aubreville, Marc, Frauke Wilm, Nikolas Stathonikos, et al.. (2023). A comprehensive multi-domain dataset for mitotic figure detection. Scientific Data. 10(1). 484–484. 18 indexed citations

Veta, Mitko, et al.. (2022). Optimized automated cardiac MR scar quantification with GAN‐based data augmentation. Computer Methods and Programs in Biomedicine. 226. 107116–107116. 18 indexed citations

Chiribiri, Amedeo, et al.. (2022). Physics-informed neural networks for myocardial perfusion MRI quantification. Medical Image Analysis. 78. 102399–102399. 40 indexed citations

Stathonikos, Nikolas, et al.. (2022). Deep learning-based breast cancer grading and survival analysis on whole-slide histopathology images. Scientific Reports. 12(1). 15102–15102. 55 indexed citations

10.

Baker, Gabrielle M., Tengteng Wang, Mitko Veta, et al.. (2022). Immunohistochemistry scoring of breast tumor tissue microarrays: A comparison study across three software applications. Journal of Pathology Informatics. 13. 100118–100118. 17 indexed citations

11.

Veta, Mitko, et al.. (2021). Whole‐slide margin control through deep learning in Mohs micrographic surgery for basal cell carcinoma. Experimental Dermatology. 30(5). 733–738. 28 indexed citations

12.

Bortsova, Gerda, Cristina González-Gonzalo, Florian Dubost, et al.. (2021). Adversarial attack vulnerability of medical image analysis systems: Unexplored factors. Medical Image Analysis. 73. 102141–102141. 54 indexed citations

13.

Kensler, Kevin H., Gabrielle M. Baker, Andreea Lucia Stancu, et al.. (2020). Deep Learning Image Analysis of Benign Breast Disease to Identify Subsequent Risk of Breast Cancer. JNCI Cancer Spectrum. 5(1). 17 indexed citations

14.

Baker, Gabrielle M., Michael E. Pyle, Kevin H. Kensler, et al.. (2020). Deep learning assessment of breast terminal duct lobular unit involution: Towards automated prediction of breast cancer risk. PLoS ONE. 15(4). e0231653–e0231653. 33 indexed citations

15.

Kensler, Kevin H., Gabrielle M. Baker, Laura C. Collins, et al.. (2020). Automated Quantitative Measures of Terminal Duct Lobular Unit Involution and Breast Cancer Risk. Cancer Epidemiology Biomarkers & Prevention. 29(11). 2358–2368. 9 indexed citations

16.

Tian, Katherine, Douglas I. Lin, Mitko Veta, et al.. (2019). Automated clear cell renal carcinoma grade classification with prognostic significance. PLoS ONE. 14(10). e0222641–e0222641. 41 indexed citations

17.

Lafarge, Maxime W., Josien P. W. Pluim, Koen A. J. Eppenhof, & Mitko Veta. (2019). Learning Domain-Invariant Representations of Histological Images. Frontiers in Medicine. 6. 162–162. 26 indexed citations

18.

Stathonikos, Nikolas, Mitko Veta, André Huisman, & P. J. van Diest. (2013). Going fully digital: Perspective of a Dutch academic pathology lab. Journal of Pathology Informatics. 4(1). 15–15. 125 indexed citations

19.

Veta, Mitko, P. J. van Diest, Robert Kornegoor, et al.. (2013). Automatic Nuclei Segmentation in H&E Stained Breast Cancer Histopathology Images. PLoS ONE. 8(7). e70221–e70221. 278 indexed citations

20.

Veta, Mitko, Robert Kornegoor, André Huisman, et al.. (2012). Prognostic value of automatically extracted nuclear morphometric features in whole slide images of male breast cancer. Modern Pathology. 25(12). 1559–1565. 62 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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