Gijs van Tulder

发表

Automated Segmentation and Volume Measurement of Intracranial Carotid Artery Calcification on Non-Contrast CT

Meike W. Vernooij, Florian Dubost, Gerda Bortsova, 2021, Radiology. Artificial intelligence.

Multi-view analysis of unregistered medical images using cross-view transformers pdf

Elena Marchiori, Yao Tong, Gijs van Tulder, 2021, MICCAI.

Theano: A Python framework for fast computation of mathematical expressions pdf

John Salvatier, Razvan Pascanu, Sina Honari, 2016, ArXiv.

Learning Cross-Modality Representations From Multi-Modal Images

Gijs van Tulder, Marleen de Bruijne, 2019, IEEE Transactions on Medical Imaging.

Question Classification by Weighted Combination of Lexical, Syntactic and Semantic Features

Pascal Wiggers, David M. J. Tax, Babak Loni, 2011, TSD.

Combining Generative and Discriminative Representation Learning for Lung CT Analysis With Convolutional Restricted Boltzmann Machines.

Gijs van Tulder, Marleen de Bruijne, 2016, IEEE transactions on medical imaging.

Learning Features for Tissue Classification with the Classification Restricted Boltzmann Machine

Marleen de Bruijne, Gijs van Tulder, Gijs van Tulder, 2014, MCV.

On the reusability of samples in active learning

Gijs van Tulder, M. Loog, 2022, ArXiv.

Cross-Modality Representations from Multi-Modal Images

Gijs van Tulder, Marleen de Bruijne, 2018 .

On the reusability of samples in active learning

Gijs van Tulder, M. Loog, 2022, ArXiv.

Label Refinement Network from Synthetic Error Augmentation for Medical Image Segmentation

Gijs van Tulder, Marleen de Bruijne, L. Wolff, 2022, 2209.06353.

Automated Segmentation and Volume Measurement of Intracranial Internal Carotid Artery Calcification at Noncontrast CT Bortsova,

Gijs van Tulder, Marleen de Bruijne, M. Vernooij, 2021 .

MRI changes in diaphragmatic motion and curvature in Pompe disease over time

Gijs van Tulder, Marleen de Bruijne, H. Tiddens, 2022, European Radiology.

Label Refinement Network from Synthetic Error Augmentation for Medical Image Segmentation

Gijs van Tulder, Marleen de Bruijne, L. Wolff, 2022, ArXiv.

Diaphragmatic dysfunction in neuromuscular disease, an MRI study

Wim G. M. Janssen, Gijs van Tulder, Marleen de Bruijne, 2021, Neuromuscular Disorders.

Sample reusability in importance-weighted active learning

G. Van Tulder, Gijs van Tulder, 2012 .

Chest MRI to diagnose early diaphragmatic weakness in Pompe disease

Gijs van Tulder, Marleen de Bruijne, P. Wielopolski, 2021, Orphanet Journal of Rare Diseases.

Multi-Task Attention-Based Semi-Supervised Learning for Medical Image Segmentation pdf

Shuai Chen, Marleen de Bruijne, Gijs van Tulder, 2019, MICCAI.

Unpaired, unsupervised domain adaptation assumes your domains are already similar

Gijs van Tulder, Marleen de Bruijne, 2023, Medical Image Analysis.

Weakly Supervised Object Detection with 2D and 3D Regression Neural Networks

Marleen de Bruijne, Wiro Niessen, M. Arfan Ikram, 2019, Medical Image Anal..

Representation Learning for Cross-Modality Classification

Marleen de Bruijne, Gijs van Tulder, Gijs van Tulder, 2016, MCV/BAMBI@MICCAI.

Combining Generative and Discriminative Representation Learning for Lung CT Analysis With Convolutional Restricted Boltzmann Machines

Marleen de Bruijne, Gijs van Tulder, Gijs van Tulder, 2016, IEEE Transactions on Medical Imaging.

An end-to-end approach to segmentation in medical images with CNN and posterior-CRF

Gijs van Tulder, Marleen de Bruijne, Florian Dubost, 2021, Medical Image Anal..

Representation Learning for Cross-Modality Classification

Gijs van Tulder, Marleen de Bruijne, 2016, MCV/BAMBI@MICCAI.

Combining Generative and Discriminative Representation Learning for Lung CT Analysis With Convolutional Restricted Boltzmann Machines

Gijs van Tulder, Marleen de Bruijne, 2016, IEEE Transactions on Medical Imaging.

Why Does Synthesized Data Improve Multi-sequence Classification?

Gijs van Tulder, Marleen de Bruijne, 2015, MICCAI.