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ORCIDAdriënne Mendrik
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2020 – today
- 2024
[j7]Elizaveta Sivak
, Paulina Pankowska, Adriënne Mendrik, Tom Emery, Javier Garcia-Bernardo, Seyit Hocuk, Kasia Karpinska, Angelica Maineri, Joris Mulder, Malvina Nissim, Gert Stulp:
Combining the strengths of Dutch survey and register data in a data challenge to predict fertility (PreFer). J. Comput. Soc. Sci. 7(2): 1403-1431 (2024)- [i8]Elizaveta Sivak, Paulina Pankowska, Adriënne Mendrik, Tom Emery, Javier Garcia-Bernardo, Seyit Hocuk, Kasia Karpinska, Angelica Maineri, Joris Mulder, Malvina Nissim, Gert Stulp:
Combining the Strengths of Dutch Survey and Register Data in a Data Challenge to Predict Fertility (PreFer). CoRR abs/2402.00705 (2024) - 2023
- [j6]Laura Boeschoten, Niek C. de Schipper, Adriënne M. Mendrik, Emiel van der Veen, Bella Struminskaya, Heleen Janssen, Theo B. Araujo:
Port: A software tool for digital data donation. J. Open Source Softw. 8(90): 5596 (2023) - 2022
- [j5]Laura Boeschoten, Adriënne Mendrik, Emiel van der Veen, Jeroen Vloothuis, Haili Hu, Roos Voorvaart, Daniel L. Oberski:
Privacy-preserving local analysis of digital trace data: A proof-of-concept. Patterns 3(3): 100444 (2022) - 2021
- [i7]Laura Boeschoten, Adriënne Mendrik, Emiel van der Veen, Jeroen Vloothuis, Haili Hu, Roos Voorvaart, Daniel L. Oberski:
Privacy preserving local analysis of digital trace data: A proof-of-concept. CoRR abs/2110.05154 (2021) - 2020
- [c11]Arkadiy Dushatskiy, Adriënne M. Mendrik, Peter A. N. Bosman, Tanja Alderliesten:
Observer variation-aware medical image segmentation by combining deep learning and surrogate-assisted genetic algorithms. Image Processing 2020: 113131B - [i6]Arkadiy Dushatskiy, Adriënne M. Mendrik, Peter A. N. Bosman, Tanja Alderliesten:
Observer variation-aware medical image segmentation by combining deep learning and surrogate-assisted genetic algorithms. CoRR abs/2001.08552 (2020) - [i5]Evelien Schat, Rens van de Schoot, Wouter M. Kouw, Duco Veen, Adriënne M. Mendrik:
The Data Representativeness Criterion: Predicting the Performance of Supervised Classification Based on Data Set Similarity. CoRR abs/2002.12105 (2020)
2010 – 2019
- 2019
- [c10]Arkadiy Dushatskiy, Adriënne M. Mendrik, Tanja Alderliesten, Peter A. N. Bosman:
Convolutional neural network surrogate-assisted GOMEA. GECCO 2019: 753-761 - [c9]Wouter M. Kouw, Marco Loog, Lambertus W. Bartels, Adriënne M. Mendrik:
Learning An Mr Acquisition-Invariant Representation Using Siamese Neural Networks. ISBI 2019: 364-367 - 2018
- [j4]Jordi Minnema, Maureen van Eijnatten, Wouter M. Kouw, Faruk Diblen, Adriënne Mendrik, Jan Wolff:
CT image segmentation of bone for medical additive manufacturing using a convolutional neural network. Comput. Biol. Medicine 103: 130-139 (2018) - [c8]Ben van Werkhoven, Adriënne Mendrik, Rob van Nieuwpoort:
Poster Abstracts eScience 2018 Conference. eScience 2018: 349 - [c7]Martine de Vos, Berend Weel, Adriënne M. Mendrik, Andre Dekker, Johan van Soest:
Fast and Easy Mapping of Relational Data to RDF for Rapid Learning Health Care. eScience 2018: 382-383 - [i4]Wouter M. Kouw, Marco Loog, Wilbert Bartels, Adriënne M. Mendrik:
Learning an MR acquisition-invariant representation using Siamese neural networks. CoRR abs/1810.07430 (2018) - [i3]Adriënne M. Mendrik, Stephen R. Aylward:
Beyond the Leaderboard: Insight and Deployment Challenges to Address Research Problems. CoRR abs/1811.03014 (2018) - 2017
- [i2]Pim Moeskops, Max A. Viergever, Adriënne M. Mendrik, Linda S. de Vries, Manon J. N. L. Benders, Ivana Isgum:
Automatic segmentation of MR brain images with a convolutional neural network. CoRR abs/1704.03295 (2017) - [i1]Wouter M. Kouw, Marco Loog, Lambertus W. Bartels, Adriënne M. Mendrik:
MR Acquisition-Invariant Representation Learning. CoRR abs/1709.07944 (2017) - 2016
- [j3]Pim Moeskops, Max A. Viergever, Adriënne M. Mendrik, Linda S. de Vries, Manon J. N. L. Benders, Ivana Isgum:
Automatic Segmentation of MR Brain Images With a Convolutional Neural Network. IEEE Trans. Medical Imaging 35(5): 1252-1261 (2016) - 2015
- [j2]Adriënne M. Mendrik, Koen L. Vincken, Hugo J. Kuijf, Marcel Breeuwer, Willem H. Bouvy, Jeroen de Bresser, Amir Alansary, Marleen de Bruijne, Aaron Carass, Ayman El-Baz, Amod Jog, Ranveer Katyal, Ali R. Khan, Fedde van der Lijn, Qaiser Mahmood, Ryan Mukherjee, Annegreet van Opbroek, Sahil Paneri, Sérgio Pereira, Mikael Persson, Martin Rajchl, Duygu Sarikaya, Örjan Smedby, Carlos A. Silva, Henri A. Vrooman, Saurabh Vyas, Chunliang Wang, Liang Zhao, Geert Jan Biessels, Max A. Viergever:
MRBrainS Challenge: Online Evaluation Framework for Brain Image Segmentation in 3T MRI Scans. Comput. Intell. Neurosci. 2015: 813696:1-813696:16 (2015) - 2014
- [c6]Adriënne M. Mendrik, Evert-Jan Vonken, Theo Witkamp, Mathias Prokop, Bram van Ginneken, Max A. Viergever:
Using the Fourth Dimension to Distinguish Between Structures for Anisotropic Diffusion Filtering in 4D CT Perfusion Scans. STIA 2014: 79-87 - 2012
- [c5]Ha Manh Luu, Adriaan Moelker, Camiel Klink, Adriënne Mendrik, Wiro J. Niessen, Theo van Walsum:
Evaluation of Diffusion Filters for 3D CTA Liver Vessel Enhancement. Abdominal Imaging 2012: 168-177 - 2010
- [c4]Adriënne Mendrik, Evert-Jan Vonken, Jan-Willem Dankbaar, Mathias Prokop, Bram van Ginneken:
Noise filtering in thin-slice 4D cerebral CT perfusion scans. Image Processing 2010: 76230N
2000 – 2009
- 2009
- [j1]Adriënne Mendrik, Evert-Jan Vonken, Annemarieke Rutten, Max A. Viergever, Bram van Ginneken:
Noise Reduction in Computed Tomography Scans Using 3-D Anisotropic Hybrid Diffusion With Continuous Switch. IEEE Trans. Medical Imaging 28(10): 1585-1594 (2009) - [c3]Adriënne Mendrik, Evert-Jan Vonken, Annet Waaijer, Ewoud J. Smit, Mathias Prokop, Bram van Ginneken:
Segmentation of arteries and veins on 4D CT perfusion scans for constructing arteriograms and venograms. Image Processing 2009: 72590Z - 2006
- [c2]Bram van Ginneken, Adriënne Mendrik:
Image Denoising with k-nearest Neighbor and Support Vector Regression. ICPR (3) 2006: 603-606 - [c1]Adriënne Mendrik, Evert-Jan Vonken, Arnold M. R. Schilham, Max A. Viergever, Bram van Ginneken:
Hybrid diffusion compared with existing diffusion schemes on simulated low dose CT scans. ISBI 2006: 1008-1011
Coauthor Index
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