David Robben

发表

Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging pdf

Tom Vercauteren, Paul Suetens, Dirk Vandermeulen, 2020, ArXiv.

Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients pdf

Tom Vercauteren, Paul Suetens, Dirk Vandermeulen, 2020, ArXiv.

Whole liver segmentation based on deep learning and manual adjustment for clinical use in SIRT

Jeroen Bertels, David Robben, Georg Schramm, 2020, European Journal of Nuclear Medicine and Molecular Imaging.

Regression and classification using random forest-based techniques

Paul Suetens, Frederik Maes, Daan Christiaens, 2014 .

Differentiable Deconvolution for Improved Stroke Perfusion Analysis

Jan S. Kirschke, Bjoern H. Menze, Bjoern H Menze, 2020, MICCAI.

Detection of vertebral fractures in CT using 3D Convolutional Neural Networks pdf

Dirk Vandermeulen, David Robben, Joeri Nicolaes, 2019, CSI@MICCAI.

Perfusion parameter estimation using neural networks and data augmentation

Paul Suetens, David Robben, 2018, BrainLes@MICCAI.

Contra-Lateral Information CNN for Core Lesion Segmentation Based on Native CTP in Acute Stroke

Paul Suetens, Dirk Vandermeulen, Jeroen Bertels, 2018, BrainLes@MICCAI.

Simultaneous Segmentation and Anatomical Labeling of the Cerebral Vasculature

Pascal Fua, Paul Suetens, Frederik Maes, 2014, MICCAI.

A Voxel-Wise, Cascaded Classification Approach to Ischemic Stroke Lesion Segmentation

Paul Suetens, Frederik Maes, Daan Christiaens, 2015, Brainles@MICCAI.

AIFNet: Automatic Vascular Function Estimation for Perfusion Analysis Using Deep Learning pdf

Bjoern H Menze, David Robben, Bjoern Menze, 2020, Medical Image Anal..

Clinical Implementation of DeepVoxNet for Auto-Delineation of Organs at Risk in Head and Neck Cancer Patients in Radiotherapy

Frederik Maes, Siri Willems, David Robben, 2018, OR 2.0/CARE/CLIP/ISIC@MICCAI.

Simultaneous segmentation and anatomical labeling of the cerebral vasculature

Pascal Fua, Paul Suetens, Frederik Maes, 2016, Medical Image Anal..

Optimization with soft Dice can lead to a volumetric bias pdf

Paul Suetens, Dirk Vandermeulen, Jeroen Bertels, 2019, BrainLes@MICCAI.

Prediction of final infarct volume from native CT perfusion and treatment parameters using deep learning

Paul Suetens, Aad van der Lugt, David Robben, 2018, Medical Image Anal..

Anatomical Labeling of the Circle of Willis Using Maximum A Posteriori Graph Matching

Paul Suetens, Frederik Maes, David Robben, 2013, MICCAI.

Image-based Quantification of Cerebral Vascular Connectivity

David Robben, 2016 .

Improved inter-scanner MS lesion segmentation by adversarial training on longitudinal data

David Robben, Diana M. Sima, Maria Ines Meyer, 2019, BrainLes@MICCAI.

The Role of Medical Image Computing and Machine Learning in Healthcare

Paul Suetens, Dirk Vandermeulen, Frederik Maes, 2019, Artificial Intelligence in Medical Imaging.

Inferring brain deformation during open neurosurgery using CBCT angiography

Paul Suetens, Frederik Maes, Olivier Brina, 2016, 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI).

A reliable and time‐saving semiautomatic spike‐template–based analysis of interictal EEG–fMRI

Patrick Dupont, Simon Tousseyn, David Robben, 2014, Epilepsia.

Segmentation of head-and-neck organs-at-risk in longitudinal CT scans combining deformable registrations and convolutional neural networks

Frederik Maes, Siri Willems, David Robben, 2019, Comput. methods Biomech. Biomed. Eng. Imaging Vis..

Theoretical analysis and experimental validation of volume bias of soft Dice optimized segmentation maps in the context of inherent uncertainty

Paul Suetens, Dirk Vandermeulen, Jeroen Bertels, 2020, Medical Image Anal..

Perfusion Paths: Inference of Voxelwise Blood Flow Trajectories in CT Perfusion

Paul Suetens, Frederik Maes, David Robben, 2015, MICCAI.

Unsupervised 3D Brain Anomaly Detection pdf

David Robben, Ezequiel de la Rosa, Diana M. Sima, 2020, ArXiv.

Intra-patient Non-rigid Registration of 3D Vascular Cerebral Images

Paul Suetens, Frederik Maes, Laura Antanas, 2012, CLIP.

Segmentation of Head and Neck Organs-At-Risk in Longitudinal CT Scans Combining Deformable Registrations and Convolutional Neural Networks

Frederik Maes, David Robben, Wouter Crijns, 2018, DLMIA/ML-CDS@MICCAI.

ISLES Challenge 2015: A voxel-wise, cascaded classification approach to stroke lesion segmentation

Paul Suetens, Frederik Maes, Daan Christiaens, 2015 .