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D. Alblas MSc (Dieuwertje)

PhD Candidate

About Me

I am a PhD candidate in the Mathematics of Imaging & AI group in the EEMCS faculty. My PhD project focuses on developing deep-learning methods for finding personalized biomarkers in patients with cardiovascular diseases, specifically abdominal aortic aneurysms (AAAs).

My main research interests are image processing, shape analysis and geometric deep learning.

Besides my job as a researcher, I am chairman of Kwadrant, the alumni association for Applied Mathematics at the University of Twente.

Expertise

Engineering & Materials Science
# Blood
# Convolutional Neural Networks
# Deep Learning
# Magnetic Resonance Imaging
# Semantics
# Thickness Measurement
Medicine & Life Sciences
# Deep Learning
Physics & Astronomy
# Arteries

Organisations

Publications

Recent
Alblas, D., Hofman, M. , Brune, C., Yeung, K. K. , & Wolterink, J. M. (2023). Implicit Neural Representations for Modeling of Abdominal Aortic Aneurysm Progression. In O. Bernard, P. Clarysse, N. Duchateau, J. Ohayon, & M. Viallon (Eds.), Functional Imaging and Modeling of the Heart - 12th International Conference, FIMH 2023, Proceedings (pp. 356-365). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 13958 LNCS). Springer. https://doi.org/10.1007/978-3-031-35302-4_37
Thibeau-Sutre, E. , Alblas, D., Buurman, S. , Brune, C. , & Wolterink, J. M. (Accepted/In press). Uncertainty-based quality assurance of carotid artery segmentation. In Uncertainty for Safe Utilization of Machine Learning in Medical Imaging (UNSURE)
Alblas, D. , Brune, C., Yeung, K. K. , & Wolterink, J. M. (2022). Going Off-Grid: Continuous Implicit Neural Representations for 3D Vascular Modeling. In O. Camara, E. Puyol-Antón, A. Suinesiaputra, A. Young, C. Qin, M. Sermesant, & S. Wang (Eds.), Statistical Atlases and Computational Models of the Heart. Regular and CMRxMotion Challenge Papers: 13th International Workshop, STACOM 2022, Held in Conjunction with MICCAI 2022, Singapore, September 18, 2022, Revised Selected Papers (pp. 79-90) https://doi.org/10.1007/978-3-031-23443-9_8
Alblas, D. , Brune, C. , & Wolterink, J. M. (2022). Deep Learning-Based Carotid Artery Vessel Wall Segmentation in Black-Blood MRI Using Anatomical Priors. In O. Colliot, I. Isgum, B. A. Landman, & M. H. Loew (Eds.), Medical Imaging 2022: Image Processing (Vol. 12032). Article 120320Y (Progress in Biomedical Optics and Imaging - Proceedings of SPIE; Vol. 12032). SPIE. https://doi.org/10.1117/12.2611112

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Visiting Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling (building no. 11), room 2110
Hallenweg 19
7522NH  Enschede
The Netherlands

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Mailing Address

University of Twente
Faculty of Electrical Engineering, Mathematics and Computer Science
Zilverling  2110
P.O. Box 217
7500 AE Enschede
The Netherlands

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University of Twente Drienerlolaan 5
7522 NB Enschede
+31 (0)53 489 9111
info@utwente.nl
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