Dr. ir. Martijn Starmans is Assistant Professor at the Erasmus MC (Rotterdam, the Netherlands) leading the AI for Integrated Diagnostics (AIID) research line, with a dual appointment at the Dept. of Radiology & Nuclear Medicine (BIGR group) and Dept. of Pathology (PHANTOM group). His vision is that we can and should learn more from previous studies, which he pursues by working on meta-level methods across clinical applications. His main research interest is the use of AI to improve the diagnostic work-up in oncology through integrated diagnostics, focussed on radiology (“radiomics”) and pathology (“pathomics”). Specifically, his group develops multi-modal machine learning methods to simultanously co-learn from both modalities (“radiopathomics”), and automated machine learning and meta-learning methods to generalize these methods across clinial applications. To establish his research line, Martijn received a prestigious 2M Euro NGF AINed Personal Fellowship in 2024. Martijn actively collaborates with of the BCN-AIM lab of prof. Lekadir at the University of Barcelona, with whom he created the FUTURE-AI guideline for trustworthy AI. He works on a variety of clinical applications (e.g. sarcoma, liver cancer, colorectal cancer, bladder cancer, melanoma, neuroendocrine tumors).

Collaborations & Consortia Martijn was part of the MICCAI 2024 organization committee one of the two first ever Open Data chairs. To promote sharing of medical imaging data, he organized the first ever Open Data Event at MICCAI 2024, with a focus on underrepresented diseases and populations, with for this year special attention for African datasets. To facilitate sharing of data, he established the AFRICAI repository, which other resources can use to make data FAIR.

Martijn is one of the initiators and PIs of the Sarcoma Artificial Intelligence (SAI) consortium (grant awarded), the Liver AI (LAI) consortium (grant awarded), and project lead of the Colorectal Liver Metastes AI (COLIMA) consortium (grant submitted). In these consortia, in total 51 clinical centers, companies, professional- and patient associations from 18 countries are united. He is also part of the Trustworthy AI for MRI ICAI LAB.

Martijn has a strong affinity with research infrastructure, which besides the MICCAI Open Data initiatives he pursues in various large European Horizon projects. He is a co-applicant of AFRICAI-RI: A Pan-African Research Infrastructure for Collaborative Biomedical Imaging and Artificial Intelligence in Respiratory Care, is work package leader of EuCanImage: Towards a European cancer imaging platform for enhanced Artificial Intelligence in oncology, and EOSC4Cancer: A European-wide foundation to accelerate Data-driven Cancer Research. Additionally, he is external advisor of RadioVal, and member of EUCAIM.

For a better overview on his projects, see his BIGR home page: https://bigr.nl/member/martijn/.

PhD Degree

Martijn obtained his PhD degree ‘‘cum laude’’ on February 1 2022 with his thesis titled Streamlined Quantitative Imaging Biomarker Development: Generalization of radiomics through automated machine learning. Following his passion to efficiently and automatically optimize routines, he developed an adaptive radiomics framework using automated machine learning, described in this paper. He collaborated with a large number of clinicians to develop radiomics biomarkers in a wide variety of clinical applications. His thesis was nominated for the Fredrik Philipsprijs 2023 for Best Dutch Radiology Thesis and made the top five.

Download my PhD Thesis.

Educational activities

Martijn has co-founded two courses and was teaching three courses in total in the BSc and MSc Technical Medicine. He is currently teaching one course in the MSc Applied Physics of the TU Delft. Martijn also was part of the program committee and mentor in the first AFRICAI Summer School, and part of the first Rotterdam Radiology AI course organized by the Dutch Radiology Society. He enjoys working together with students and has so-far (co-)supervised 53 students in interships and thesis projects.

Download my (slightly outdated) resumé .