Projects per year
Personal profile
Research profile
Mitko Veta is an associate professor in the Medical Image Analysis group at the TU/e Department of Biomedical Engineering. He specializes in AI methods for computational pathology. His research aims to develop automated, quantitative algorithms that improve the reproducibility and accuracy of pathology reporting. These tools reduce clinical workload and support better treatment planning.
Academic background
Mitko Veta studied Electrical Engineering at the Ss. Cyril and Methodius University in Skopje (Macedonia) where he in 2009 received his Master's degree on Digital Signal Processing with a thesis on digital video classification. In 2010, he moved to the University Medical Center Utrecht (The Netherlands) to perform PhD research on the topic of automatic analysis of histopathology images. In 2014, he obtained his doctorate and started as a postdoctoral researcher at Eindhoven University of Technology (TU/e, the Netherlands). In 2016, he was appointed assistant professor with the TU/e research group Medical Image Analysis of the department of Biomedical Engineering. In 2024 he was appointed as an associate professor in the same group.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 3 Good Health and Well-being
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Collaborations and top research areas from the last five years
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Projects
- 1 Finished
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Spectralligence AI211009
Breeuwer, M. (Project Manager), Veta, M. (Project member), Amirrajab, S. (Project member) & van de Sande, D. M. J. (Project member)
1/11/21 → 31/10/24
Project: Third tier
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Data-driven Synthesis of Magnetic Resonance Spectroscopy Data using a Variational Autoencoder
van de Sande, D. M. J., Merkofer, J. P., Amirrajab, S., Veta, M., Drenthen, G. S., Jansen, J. F. A. & Breeuwer, M., 28 Feb 2026, arXiv.org, 20 p.Research output: Working paper › Preprint › Academic
Open AccessFile19 Downloads (Pure) -
AI-detected tumor-infiltrating lymphocytes and response to PD-1 based treatment in advanced melanoma
Schuiveling, M., van Duin, I. A. J., Ter Maat, L., van der Weerd, J. C., van den Berkmortel, F., Burgers, F., Boers-Sonderen, M. J., van den Eertwegh, A. J. M., de Groot, J. W., Haanen, J., Hospers, G., Kapiteijn, E., Piersma, D., Vreugdenhil, G., Westgeest, H. M., Schrader, A. M. R., Veta, M., Blokx, W., van Diest, P. J. & Suijkerbuijk, K., 1 Jun 2025, In: Journal of Clinical Oncology. 43, 16_suppl, p. 9541-9541 1 p.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile6 Downloads (Pure) -
A novel dataset for nuclei and tissue segmentation in melanoma with baseline nuclei segmentation and tissue segmentation benchmarks
Schuiveling, M. (Corresponding author-nrf), Liu, H., Eek, D., Breimer, G. E., Suijkerbuijk, K. P. M., Blokx, W. A. M. & Veta, M., 19 Feb 2025, In: GigaScience. 14, 12 p., giaf011.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile24 Link opens in a new tab Citations (Scopus)68 Downloads (Pure) -
Artificial intelligence-based triaging of cutaneous melanocytic lesions
Lucassen, R. T. (Corresponding author-nrf), Stathonikos, N., Breimer, G. E., Veta, M. & Blokx, W. A. M., 2025, In: npj Biomedical Innovations. 2, 1, 9 p., 10.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile10 Downloads (Pure) -
Artificial Intelligence-Detected Tumor-Infiltrating Lymphocytes and Outcomes in Anti-PD-1-Based Treated Melanoma
Schuiveling, M., Van Duin, I. A. J., Ter Maat, L. S., van der Weerd, J. C., Verheijden, R. J., Van Den Berkmortel, F., Blank, C. U., Breimer, G. E., Burgers, F. H., Boers-Sonderen, M., Van Den Eertwegh, A. J. M., De Groot, J. W. B., Haanen, J. B. A. G., Hospers, G. A. P., Kapiteijn, E., Piersma, D., Vreugdenhil, G., Westgeest, H., Schrader, A. M. R. & Pluim, J. P. W. & 4 others, , Dec 2025, In: JAMA Oncology. 11, 12, p. 1470-1478Research output: Contribution to journal › Article › Academic › peer-review
1 Link opens in a new tab Citation (Scopus)
Datasets
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MIDOG++: A Comprehensive Multi-Domain Dataset for Mitotic Figure Detection
Aubreville, M. (Creator), Wilm, F. (Creator), Stathonikos, N. (Creator), Breininger, K. (Creator), Donovan, T. (Creator), Jabari, S. (Creator), Veta, M. (Creator), Ammeling, J. (Creator), van Diest, P. J. (Creator), Klopfleisch, R. (Creator) & Bertram, C. (Creator), Figshare, 30 Jun 2023
DOI: 10.6084/m9.figshare.c.6615571, https://springernature.figshare.com/collections/MIDOG_A_Comprehensive_Multi-Domain_Dataset_for_Mitotic_Figure_Detection/6615571 and one more link, https://springernature.figshare.com/collections/MIDOG_A_Comprehensive_Multi-Domain_Dataset_for_Mitotic_Figure_Detection/6615571/1 (show fewer)
Dataset
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MIDOG++ database as JSON format
Aubreville, M. (Creator), Wilm, F. (Creator), Stathonikos, N. (Creator), Breininger, K. (Creator), Donovan, T. (Creator), Jabari, S. (Creator), Veta, M. (Creator), Ammeling, J. (Creator), van Diest, P. J. (Creator), Klopfleisch, R. (Creator) & Bertram, C. (Creator), Figshare, 30 Jun 2023
DOI: 10.6084/m9.figshare.23531121, https://springernature.figshare.com/articles/dataset/MIDOG_database_as_JSON_format/23531121 and one more link, https://springernature.figshare.com/articles/dataset/MIDOG_database_as_JSON_format/23531121/1 (show fewer)
Dataset
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MIDOG++ database in SlideRunner sqlite format
Aubreville, M. (Creator), Wilm, F. (Creator), Stathonikos, N. (Creator), Breininger, K. (Creator), Donovan, T. (Creator), Jabari, S. (Creator), Veta, M. (Creator), Ammeling, J. (Creator), van Diest, P. J. (Creator), Klopfleisch, R. (Creator) & Bertram, C. A. (Creator), Figshare, 30 Jun 2023
DOI: 10.6084/m9.figshare.23531118, https://springernature.figshare.com/articles/dataset/MIDOG_database_in_SlideRunner_sqlite_format/23531118 and one more link, https://springernature.figshare.com/articles/dataset/MIDOG_database_in_SlideRunner_sqlite_format/23531118/1 (show fewer)
Dataset
Courses
Press/Media
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Eindhoven University of Technology Reports Findings in Machine Learning (A review of machine learning applications for the proton MR spectroscopy workflow)
Jansen, J. F. A., van Sloun, R. J. G., Breeuwer, M., Veta, M., Amirrajab, S., Merkofer, J. P. & van de Sande, D. M. J.
17/07/23
1 item of Media coverage
Press/Media: Expert Comment
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Nine AI projects funded to improve the quality of life and healthcare
Veta, M., Chaudron, M. R. V. & de Campos, C. P.
13/09/22
1 item of Media coverage
Press/Media: Expert Comment
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-Eindhoven University of Technology : AI analysis for a healthy eye
Pluim, J. P. W., Veta, M., Heslinga, F. G. & Fitzgerald, B.
22/06/22
5 items of Media coverage
Press/Media: Expert Comment
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AI analysis for a healthy eye
Pluim, J. P. W., Veta, M. & Heslinga, F. G.
21/06/22
2 items of Media coverage
Press/Media: Expert Comment