Mark is PhD candidate in the group of dr. Kenneth Gilhuijs, working on the LIMA project: Liquid Imaging and biopsies for improved (breast) cancer care. The aim of the project is to personalize cancer care by making better predictions on the effectivity of neoadjuvant chemotherapy.
His academic background is at Eindhoven University of Technology (TU/e). In 2015 he obtained his BSc degree with an award-winning thesis on the detection of early esophageal cancer, supervised by prof. Peter de With and dr. Fons van der Sommen. In 2018 he obtained an MSc degree in Biomedical Engineering and in Electrical Engineering (both cum laude), with a thesis on radiomic analysis of pancreatic cancer, for which he performed research at Radboudumc Nijmegen. For this research he was supervised prof. Josien Pluim, dr. Sveta Zinger and dr. ir. John Hermans.
Image Sciences Institute
University Medical Center Utrecht
Heidelberglaan 100
Q.02.4.45
3584 CX Utrecht
The Netherlands
email:
M.H.A.Janse-2@umcutrecht.nl
office: E.02.554
phone: +31 88 75 67761
secretary: +31 88 75 57772
Publications
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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
Clinical breast cancer
10
(1),
-
Deep Learning-Based Segmentation of Locally Advanced Breast Cancer on MRI in Relation to Residual Cancer Burden: A Multiinstitutional Cohort Study
Janse, Markus H.A., Janssen, Liselore M., van der Velden, Bas H.M., Moman, Maaike R., Wolters-van der Ben, Elian J.M., Kock, Marc C.J.M., Viergever, Max A., van Diest, Paul J., Gilhuijs, Kenneth G.A.
Dec
2023
in
Journal of Magnetic Resonance Imaging
58
(6),
p. 1739-1749
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Computed Tomography-Based Radiomics Using Tumor and Vessel Features to Assess Resectability in Cancer of the Pancreatic Head
Litjens, Geke, Broekmans, Joris P.E.A., Boers, Tim, Caballo, Marco, van den Hurk, Maud H.F., Ozdemir, Dilek, van Schaik, Caroline J., Janse, Markus H.A., van Geenen, Erwin J.M., van Laarhoven, Cees J.H.M., Prokop, Mathias, de With, Peter H.N., van der Sommen, Fons, Hermans, John J.
Oct
2023
in
Diagnostics (Basel, Switzerland)
13
(20),
-
Improving prediction of response to neoadjuvant treatment in patients with breast cancer by combining liquid biopsies with multiparametric MRI: Protocol of the LIMA study-a multicentre prospective observational cohort study
Janssen, Liselore M., Suelmann, Britt B.M., Elias, Sjoerd G., Janse, Markus H.A., Van Diest, Paul J., Van Der Wall, Elsken, Gilhuijs, Kenneth G.A.
Sep
2022
in
BMJ open [E]
12
(9),
p. 1-8
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Deep Learning Analysis of Cardiac MRI in Legacy Datasets: Multi-Ethnic Study of Atherosclerosis
Suinesiaputra, Avan, Mauger, Charlène A., Ambale-Venkatesh, Bharath, Bluemke, David A., Dam Gade, Josefine, Gilbert, Kathleen, Janse, Markus, Hald, Line Sofie, Werkhoven, Conrad, Wu, Colin O., Lima, Joao A. C., Young, Alistair A.
Jan
2022
in
Frontiers in cardiovascular medicine
8
p. 807728
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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
Oct
2020
in
Scientific Reports
10
(1),
-
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Quantitative CT-based radiomics of pancreatic ductal adenocarcinoma: a valuable tool for radiological staging?
Janse, Mark, Litjens, Geke, Zinger, Svitlana, De With, Peter H.N., Prokop, Mathias, Hermans, J.
jun
2019 in Quantitative CT-based radiomics of pancreatic ductal adenocarcinoma: a valuable tool for radiological staging?: Insights into Imaging p. (Insights into imaging; vol. )
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