Koen A. J. Eppenhof

According to our database, Koen A. J. Eppenhof authored at least 12 papers between 2014 and 2020.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2020

Progressively Trained Convolutional Neural Networks for Deformable Image Registration.

Koen A. J. Eppenhof, Maxime W. Lafarge, Mitko Veta, Josien P. W. Pluim

IEEE Trans. Medical Imaging, 2020

2019

Pulmonary CT Registration Through Supervised Learning With Convolutional Neural Networks.

Koen A. J. Eppenhof, Josien P. W. Pluim

IEEE Trans. Medical Imaging, 2019

Progressively growing convolutional networks for end-to-end deformable image registration.

Koen A. J. Eppenhof, Maxime W. Lafarge, Josien P. W. Pluim

Proceedings of the Medical Imaging 2019: Image Processing, 2019

2018

Deformable image registration using convolutional neural networks.

Koen A. J. Eppenhof, Maxime W. Lafarge, Pim Moeskops, Mitko Veta, Josien P. W. Pluim

Proceedings of the Medical Imaging 2018: Image Processing, 2018

Roto-Translation Covariant Convolutional Networks for Medical Image Analysis.

Erik J. Bekkers, Maxime W. Lafarge, Mitko Veta, Koen A. J. Eppenhof, Josien P. W. Pluim, Remco Duits

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Inferring a third spatial dimension from 2D histological images.

Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof, Pim Moeskops, Mitko Veta

Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018

2017

Supervised local error estimation for nonlinear image registration using convolutional neural networks.

Koen A. J. Eppenhof, Josien P. W. Pluim

Proceedings of the Medical Imaging 2017: Image Processing, 2017

Adversarial Training and Dilated Convolutions for Brain MRI Segmentation.

Pim Moeskops, Mitko Veta, Maxime W. Lafarge, Koen A. J. Eppenhof, Josien P. W. Pluim

Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017

Domain-Adversarial Neural Networks to Address the Appearance Variability of Histopathology Images.

Maxime W. Lafarge, Josien P. W. Pluim, Koen A. J. Eppenhof, Pim Moeskops, Mitko Veta

Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017

2016

Brain-inspired algorithms for retinal image analysis.

Bart M. ter Haar Romeny, Erik J. Bekkers, Jiong Zhang, Samaneh Abbasi-Sureshjani, Fan Huang, Remco Duits, Behdad Dashtbozorg, Tos Berendschot, Iris Smit-Ockeloen, Koen A. J. Eppenhof, Jinghan Feng, Julius Hannink, Jan Schouten, Mengmeng Tong, Hanhui Wu, Han J. W. van Triest, Shanshan Zhu, Dali Chen, Wei He, Ling Xu, Ping Han, Yan Kang

Mach. Vis. Appl., 2016

The truth is hard to make: Validation of medical image registration.

Josien P. W. Pluim, Sascha E. A. Muenzing, Koen A. J. Eppenhof, Keelin Murphy

Proceedings of the 23rd International Conference on Pattern Recognition, 2016

2014

Decision fusion for temporal prediction of respiratory liver motion.

Christine Tanner, Koen A. J. Eppenhof, Jaap Gelderblom, Gábor Székely

Proceedings of the IEEE 11th International Symposium on Biomedical Imaging, 2014