Personal profile
Biography
Dr. Kenneth Gilhuijs is associate professor at the University Medical Center Utrecht (UMC). He obtained his Ph.D. cum laude in Medical Physics from the University of Amsterdam.
He heads a research group on translational imaging in oncology with emphasis on MRI and artificial intelligence (AI). His team includes Ph.D. students and post-docs on the interface between diagnostic imaging, pathology, medical oncology, and surgery. In 2010 he transferred from the Netherlands Cancer Institute to the University Medical Center Utrecht.
His research interests include machine learning, radiomics, deep learning, and computerized decision support systems for patient-tailored cancer treatment on the basis of automated prognostication and response monitoring.
Kenneth Gilhuijs is coordinator of the master’s course medical image processing at UMC, is academic editor for Diagnostics, and serves on several scientific advisory boards.
Education/Academic qualification
BKO, University Medical Center (UMC) Utrecht
Award Date: 1 Oct 2016
BROK, University Medical Center (UMC) Utrecht
Award Date: 1 Mar 2012
PhD, University of Amsterdam
Award Date: 21 Dec 1995
Keywords
- RC0254 Neoplasms. Tumors. Oncology (including Cancer)
Collaborations and top research areas from the last five years
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Deep learning-based radiomics does not improve residual cancer burden prediction post-chemotherapy in LIMA breast MRI trial
Janse, M. H. A., Janssen, L. M., Wolters-van der Ben, E. J. M., Moman, M. R., Viergever, M. A., van Diest, P. J. & Gilhuijs, K. G. A., 2026, In: European Radiology. 36, 2, p. 850–862 13 p.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile1 Downloads (Pure) -
Automated vertebrae identification and segmentation with structural uncertainty analysis in longitudinal CT scans of patients with multiple myeloma
Madzia-Madzou, D. K., Jak, M., de Keizer, B., Verlaan, J.-J., Minnema, M. C. & Gilhuijs, K., Jul 2025, In: European Journal of Radiology. 188, 9 p., 112160.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile25 Downloads (Pure) -
Tumor infiltrating lymphocytes and change in tumor load on MRI to assess response and prognosis after neoadjuvant chemotherapy in breast cancer
Janssen, L. M., de Vries, B. B. L. P., Janse, M. H. A., van der Wall, E., Elias, S. G., Salgado, R., van Diest, P. J. & Gilhuijs, K. G. A., Jan 2025, In: Breast Cancer Research and Treatment. 209, 1, p. 167-175 9 p., 110220.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile4 Downloads (Pure) -
Automated rating of background parenchymal enhancement in MRI of extremely dense breasts without compromising the association with breast cancer in the DENSE trial
Wang, H., H.M.van der Velden, B., Verburg, E., Bakker, M. F., Pijnappel, R. M., Veldhuis, W. B., van Gils, C. H. & Gilhuijs, K. G. A., Jun 2024, In: European Journal of Radiology. 175, 111442.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile5 Downloads (Pure) -
Predicting response to neoadjuvant chemotherapy with liquid biopsies and multiparametric MRI in patients with breast cancer
Janssen, L. M., Janse, M. H. A., Penning de Vries, B. B. L., van der Velden, B. H. M., Wolters-van der Ben, E. J. M., van den Bosch, S. M., Sartori, A., Jovelet, C., Agterof, M. J., Ten Bokkel Huinink, D., Bouman-Wammes, E. W., van Diest, P. J., van der Wall, E., Elias, S. G. & Gilhuijs, K. G. A., Jan 2024, In: NPJ breast cancer. 10, 1, 10.Research output: Contribution to journal › Article › Academic › peer-review
Open AccessFile9 Downloads (Pure)