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dr. K.G.A. (Kenneth) Gilhuijs

Associate Professor
dr. K.G.A. (Kenneth) Gilhuijs
  • Image Sciences Institute

Research Programs

Strategic Program Cancer

Biography

Biography

Dr. Kenneth Gilhuijs is associate professor at the University Medical Center Utrecht (UMC). He received his Ph.D cum laude in Medical Physics at the University of Amsterdam.

He heads a research group on prognostic imaging in breast oncology with emphasis on MRI. His team includes Ph.D. students and post-docs on the interface between diagnostic imaging, pathology, medical oncology, surgery, and radiotherapy. In 2010 he transferred from the Netherlands Cancer Institute to the University Medical Center Utrecht.

His research interests include translational imaging in breast oncology, machine learning, computerized decision support systems for personalized treatment of breast cancer, prognosis, and response monitoring.

Kenneth Gilhuijs is coordinator of the master’s course medical image processing at UMC and serves on scientific advisory boards such as that of the Dutch Cancer foundation (KWF).

Research Output (158)

Volumetric breast density estimation on MRI using explainable deep learning regression

van der Velden Bas H M, Janse Markus H A, Ragusi Max A A, Loo Claudette E, Gilhuijs Kenneth G A 22 okt 2020, In: Scientific Reports. 10

Correcting time-intensity curves in dynamic contrast-enhanced breast MRI for inhomogeneous excitation fields at 7T

van Rijssel Michael J., Pluim Josien P.W., Chan Hui Shan M., van den Wildenberg Lieke, Schmitz Alexander M.Th, Luijten Peter R., Gilhuijs Kenneth G.A., Klomp Dennis W.J. 1 aug 2020, In: Magnetic Resonance in Medicine. 84 , p. 1000-1010 11 p.

Contralateral parenchymal enhancement on breast MRI before and during neoadjuvant endocrine therapy in relation to the preoperative endocrine prognostic index

Ragusi Max A A, Loo Claudette E, van der Velden Bas H M, Wesseling Jelle, Linn Sabine C, Beets-Tan Regina G, Elias Sjoerd G, Gilhuijs Kenneth G A 20 jul 2020, In: European Radiology. 30 , p. 6740-6748 9 p.

Radiogenomic Analysis of Breast Cancer by Linking MRI Phenotypes with Tumor Gene Expression

Bismeijer Tycho, van der Velden Bas H M, Canisius Sander, Lips Esther H, Loo Claudette E, Viergever Max A, Wesseling Jelle, Gilhuijs Kenneth G A, Wessels Lodewyk F A 26 mei 2020, In: Radiology. 296 , p. 277-287 11 p.

Computer-Aided Diagnosis in Multiparametric Magnetic Resonance Imaging Screening of Women With Extremely Dense Breasts to Reduce False-Positive Diagnoses

Verburg Erik, van Gils Carla H, Bakker Marije F, Viergever Max A, Pijnappel Ruud M, Veldhuis Wouter B, Gilhuijs Kenneth G A 6 mrt 2020, In: Investigative Radiology. 55 , p. 438-444 7 p.

Interpretable deep learning regression for breast density estimation on MRI

Van Der Velden Bas H.M., Ragusi Max A.A., Janse Markus H.A., Loo Claudette E., Gilhuijs Kenneth G.A. 1 jan 2020,

Harmonization of Quantitative Parenchymal Enhancement in T1 -Weighted Breast MRI

van der Velden Bas H M, van Rijssel Michael J, Lena Beatrice, Philippens Marielle E P, Loo Claudette E, Ragusi Max A A, Elias Sjoerd G, Sutton Elizabeth J, Morris Elizabeth A, Bartels Lambertus W, Gilhuijs Kenneth G A 1 jan 2020, In: Journal of Magnetic Resonance Imaging. 52 , p. 1374-1382 9 p.

Mutual information for unsupervised deep learning image registration

de Vos Bob D., van der Velden Bas H.M., Sander Jörg, Gilhuijs Kenneth G.A., Staring Marius, Išgum Ivana 2020,

Synchronous Breast Cancer:Phenotypic Similarities on MRI

Wang Hui, van der Velden Bas H M, Chan Hui Shan M, Loo Claudette E, Viergever Max A, Gilhuijs Kenneth G A 19 dec 2019, In: Journal of Magnetic Resonance Imaging. 51 , p. 1858-1867 10 p.

Are contralateral parenchymal enhancement on dynamic contrast-enhanced MRI and genomic ER-pathway activity in ER-positive/HER2-negative breast cancer related?

van der Velden Bas H M, Bismeijer Tycho, Canisius Sander, Loo Claudette E, Lips Esther H, Wesseling Jelle, Viergever Max A, Wessels Lodewyk F A, Gilhuijs Kenneth G A 16 okt 2019, In: European Journal of Radiology. 121

All research output

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