Martijn P. A. Starmans
Assistant Professor & PI Artificial Intelligence for Integrated Diagnostics (AIID) focused on Medical Imaging in Oncology
Erasmus Medical Center, Department of Radiology & Nuclear Medicine
Erasmus Medical Center, Department of Pathology
Biography
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 .
- Radiomics
- Pathomics
- RadioPathomics
- Multimodal machine learning
- AutoML
- Meta-Learning
- Oncology
- Soft-tissue tumors / sarcoma
- Liver cancer
- Colorectal liver metastases
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PhD ''Streamlined Quantitative Imaging Biomarker Development'' ("cum laude"), 2022
Erasmus Medical Center, Rotterdam, the Netherlands
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MSc Applied Physics, 2016
Delft University of Technology, Delft, the Netherlands
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BSc Applied Physics, 2013
Delft University of Technology, Delft, the Netherlands
Awards & Grants
- Role: Co-PI
- Topic: AFRICAI-RI: A Pan-African Research Infrastructure for Collaborative Biomedical Imaging and Artificial Intelligence
- Total funding: 5M Euro.
- Role: Co-PI
- Topic: Detecting Complex Regional Pain Syndrome and quantifying treatment success using a trustworthy artificial intelligence model based on video thermography
- Total funding: 16k Euro.
- Role: Co-PI
- Topic: Trustworthy and explainable AI models for differentiating benign and malignant bone tumors on radiological imaging
- Total funding: 14k Euro.
- Role: Main applicant
- Topic: RadPath-RI: Research infrastructure to join forces of radiology and pathology through Artificial Intelligence for Integrated Diagnostics (AIID)
- Total funding: 120k Euro.
- Role: Main applicant
- Topic: Radiology and pathology join forces through Artificial Intelligence for Integrated Diagnostics (AIID)
- Total funding: 2M Euro.
- Role: Participant
- Topic: PATH2XNAT: COVID 19 meets Pathomics meets XNAT
- Total funding: 280k Euro.
- Role: Co-PI*
- Topic: The Liver Artificial Intelligence (LAI) consortium: a benchmark dataset and optimized machine learning methods for MRI-based diagnosis of solid appearing liver lesions
- Total funding: 1M Euro.
*Not officially mentioned as Co-PI due to formalities. Reference of formal applicant available upon request.
- Role: Co-PI
- Topic: An artificial intelligence (AI)-based model for detection of incidental pulmonary embolism in chest CTs
- Total funding: 1M Euro.
- Role: Co-applicant
- Topic: EUCAIM: European Federation for Cancer Images
- Total funding: 33M Euro.
- Role: Co-PI*
- Topic: Automatic grading and phenotyping of soft-tissue tumors through machine learning to guide personalized cancer treatment
- Total funding: 400k Euro.
*Not officially mentioned as Co-PI due to formalities. Reference of formal applicant available upon request.
Featured Publications
Recent Publications
Student Projects
We work on various clinical applications with different clinicians, and various technical solutions within medical image analysis & AI. The projects range from very technical hybrid, to more clinical. There are usually too many projects to describe here. Currently, we do not have any predefined projects available, we expect these to soon be put online, but we always have more than enough ideas, so feel free to contact me for more information if you are interested in an internship / thesis! For an overview of some past projects, please see https://bigr.nl/open-projects/.
*Experience and Education
With a joint appointment at the Radiology & Nuclear and Pathology departments, Martijn is heading the AI for Integrated Diagnostics (AIID) research line. The AIID group develops novel multimodal machine learning methods to develop quantitative biomarkers, focused on medical imaging and application in concology.
- Collaboration and awards: Martijn is involved in various working groups and is work package leader in the Horizon 2020 EuCanImage and Horizon 2021 EOSC4Cancer projects. He is initiator and receiptient of various (consortium) grants, including an NWO NGF AINed Perfonal Fellowship (2M), the Liver AI (LAI) consortium (NWO OTP 1M grant), the Sarcoma Artificial Intelligence (SAI) consortium (Hanarth Fonds 400k grant), a Health-Holland 1M TKI grant on incidental pulmonary embolism, 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. Additionally, and he is external advisor of RadioVal.
- MICCAI 2024 organization: first ever Open Data Chair, initiator of the AFRICAI repository for medical imaging.
- Trustworthy AI: co-lead of the FUTURE-AI guideline on trustworthy and deployable AI.
- Supervision: 1 PostDoc, 9 PhD students, and 6 MSc students.
Extending the work of his PhD, Martijn’s research focused on generalization of radiomics biomarkers (conventional and deep learning based) using automated machine learning and meta-learning. He worked on a variety of clinical applications (e.g. sarcoma, liver cancer, colorectal cancer, bladder cancer, melanoma, cardiomyopathy, neuroendocrine tumors, CRPS).
- Management: Co-developer of Imaging Office of department of Radiology and Nuclear Medicine.
- Supervision: 17 MSc students.
- Education: Teaching and continuous development of three courses in the BSc and MSc Technical Medicine
Martijn will visit the group of Prof. Dr. Karim Lekadir to collaborate on AI for oncology and cardiac imaging within the context of the EuCanImage and euCanSHare consortia. While the main focus is on developing novel algorithms for (deep) radiomics, they will also work on federated learning, applying Martijn’s adaptive radiomics framework from his PhD to ``new’’ clinical applications, a second version of the FUTURE-AI guiding principles, and improving the clinical utility of (radiomics) AI tools.
Supervisors: Karim Lekadir
See extended description in the “about” section on this website.
Supervisors: Stefan Klein, Jan-Jaap Visser, Wiro Niessen
- Track: Imaging Physics
- Specialisation: Research & Development
- Thesis: Registration of 3D Breast Ultrasound Scans together with Erasmus Medical Center
- Honours track: Quantum Nanoscience
- Thesis: Activation cycles of stochastically blinking molecules in super-resolution microscopy
Contact
- m.starmans@erasmusmc.nl
- Doctor Molewaterplein 40, Rotterdam, 3015GD
- Department of Radiology & Nuclear Medicine, Room Na-2616
- DM Me