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Jef Vandemeulebroucke
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2020 – today
- 2024
- [j12]Sebastián Amador Sánchez
, Philippe van Overschelde, Jef Vandemeulebroucke
Segmentation-Guided Coordinate Regression for Robust Landmark Detection on X-Rays: Application to Automated Assessment of Lower Limb Alignment. IEEE Access 12: 61484-61497 (2024) - [j11]Selene De Sutter
Modality redundancy for MRI-based glioblastoma segmentation. Int. J. Comput. Assist. Radiol. Surg. 19(10): 2101-2109 (2024) - [j10]Luuk H. Boulogne
The STOIC2021 COVID-19 AI challenge: Applying reusable training methodologies to private data. Medical Image Anal. 97: 103230 (2024) - [c17]Hamza Mekhzoum, Benyameen Keelson, Thierry Scheerlinck, Jef Vandemeulebroucke:
Towards Point Cloud-Based Medical Image Registration for Dynamic 4D-CT Imaging. ShapeMI@MICCAI 2024: 205-223 - 2023
- [j9]Panagiotis Gonidakis
Handcrafted Features Can Boost Performance and Data-Efficiency for Deep Detection of Lung Nodules From CT Imaging. IEEE Access 11: 126221-126231 (2023) - [j8]Dario Farotto, Patricia Lopes, Maryna Kvasnytsia, Mathias Polfliet, Jef Vandemeulebroucke, Roel Wirix-Speetjens, Jos Vander Sloten:
Automated mitral annulus annotation over 4D-CT for transcatheter mitral valve replacement. Comput. methods Biomech. Biomed. Eng. Imaging Vis. 11(3): 711-717 (2023) - [j7]Jakub Ceranka, Joris Wuts
Computer-aided diagnosis of skeletal metastases in multi-parametric whole-body MRI. Comput. Methods Programs Biomed. 242: 107811 (2023) - [c16]Maryna Kvasnytsia
COVID-19 Lesion Segmentation Framework for the Contrast-Enhanced CT in the Absence of Contrast-Enhanced CT Annotations. MILLanD@MICCAI 2023: 71-81 - [i4]Luuk H. Boulogne, Julian Lorenz, Daniel Kienzle, Robin Schön, Katja Ludwig, Rainer Lienhart, Simon Jégou, Guang Li, Cong Chen, Qi Wang, Derik Shi, Mayug Maniparambil, Dominik Müller, Silvan Mertes, Niklas Schröter, Fabio Hellmann, Miriam Elia, Ine Dirks
The STOIC2021 COVID-19 AI challenge: applying reusable training methodologies to private data. CoRR abs/2306.10484 (2023) - 2022
- [j6]Ine Dirks
Computer-aided detection and segmentation of malignant melanoma lesions on whole-body 18F-FDG PET/CT using an interpretable deep learning approach. Comput. Methods Programs Biomed. 221: 106902 (2022) - [c15]Selene De Sutter
Probabilistic Tissue Mapping for Tumor Segmentation and Infiltration Detection of Glioma. BrainLes@MICCAI 2022: 80-89 - [c14]Abel Díaz Berenguer
Representation Learning with Information Theory to Detect COVID-19 and Its Severity. ECCV Workshops (7) 2022: 605-620 - 2020
- [c13]Jakub Ceranka, Frédéric Lecouvet, Johan de Mey
Computer-aided detection of focal bone metastases from whole-body multi-modal MRI. Medical Imaging: Computer-Aided Diagnosis 2020 - [c12]Panagiotis Gonidakis
Artificially augmenting data or adding more samples? A study on a 3D CNN for lung nodule classification. Medical Imaging: Computer-Aided Diagnosis 2020 - [c11]Alexander Sóñora-Mengan
Evaluating several ways to combine handcrafted features-based system with a deep learning system using the LUNA16 Challenge framework. Medical Imaging: Computer-Aided Diagnosis 2020 - [c10]Ine Dirks
Automated threshold selection on whole-body 18F-FDG PET/CT for assessing tumor metabolic response. Medical Imaging: Image Processing 2020: 113131R - [i3]Sofie Tilborghs, Ine Dirks
Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients. CoRR abs/2007.15546 (2020) - [i2]Abel Díaz Berenguer
Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging. CoRR abs/2011.11719 (2020)
2010 – 2019
- 2018
- [j5]Frederik Vandenbroucke
Can tumor coverage evaluated 24 h post-radiofrequency ablation predict local tumor progression of liver metastases? Int. J. Comput. Assist. Radiol. Surg. 13(12): 1981-1989 (2018) - [j4]Mathias Polfliet
Intrasubject multimodal groupwise registration with the conditional template entropy. Medical Image Anal. 46: 15-25 (2018) - [c9]Pieter Thomas Boonen, Nico Buls
Automated Quantification of Blood Flow Velocity from Time-Resolved CT Angiography. CVII-STENT/LABELS@MICCAI 2018: 11-18 - [c8]Jakub Ceranka, Sabrina Verga, Frédéric Lecouvet, Thierry Metens, Johan de Mey, Jef Vandemeulebroucke:
Intensity Standardization of Skeleton in Follow-Up Whole-Body MRI. CSI@MICCAI 2018: 77-89 - 2017
- [c7]Mathias Polfliet, Stefan Klein, Wiro J. Niessen
Laplacian eigenmaps for multimodal groupwise image registration. Medical Imaging: Image Processing 2017: 101331N - [c6]Elhassan Abdou, Johan de Mey
Accurate bolus arrival time estimation using piecewise linear model fitting. Medical Imaging: Image Processing 2017: 101332F - [c5]Jakub Ceranka, Mathias Polfliet, Frédéric Lecouvet, Nicolas Michoux, Jef Vandemeulebroucke
Whole-body diffusion-weighted MR image stitching and alignment to anatomical MRI. Medical Imaging: Image Processing 2017: 1013311 - 2016
- [j3]Wyke Huizinga, Dirk H. J. Poot, Jean-Marie Guyader, R. Klaassen, Bram F. Coolen
PCA-based groupwise image registration for quantitative MRI. Medical Image Anal. 29: 65-78 (2016) - [c4]Mathias Polfliet, Stefan Klein, Wyke Huizinga, Johan de Mey
The pythagorean averages as group images in efficient groupwise registration. ISBI 2016: 1261-1264 - [i1]Arnaud Arindra Adiyoso Setio, Alberto Traverso, Thomas de Bel, Moira S. N. Berens, Cas van den Bogaard, Piergiorgio Cerello, Hao Chen, Qi Dou, Maria Evelina Fantacci, Bram Geurts, Robbert van der Gugten, Pheng-Ann Heng, Bart Jansen, Michael M. J. de Kaste, Valentin Kotov, Jack Yu-Hung Lin, Jeroen T. M. C. Manders, Alexander Sóñora-Mengana, Juan Carlos García-Naranjo, Mathias Prokop, Marco Saletta, Cornelia Schaefer-Prokop, Ernst Th. Scholten, Luuk Scholten, Miranda M. Snoeren, Ernesto Lopez Torres, Jef Vandemeulebroucke, Nicole Walasek, Guido C. A. Zuidhof, Bram van Ginneken, Colin Jacobs:
Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge. CoRR abs/1612.08012 (2016) - 2011
- [j2]Keelin Murphy
Evaluation of Registration Methods on Thoracic CT: The EMPIRE10 Challenge. IEEE Trans. Medical Imaging 30(11): 1901-1920 (2011) - 2010
- [j1]David Sarrut
B-LUT: Fast and low memory B-spline image interpolation. Comput. Methods Programs Biomed. 99(2): 172-178 (2010)
2000 – 2009
- 2009
- [c3]Jef Vandemeulebroucke
Respiratory Motion Estimation from Cone-Beam Projections Using a Prior Model. MICCAI (1) 2009: 365-372 - 2006
- [c2]Jef Vandemeulebroucke
A multi-modal 2D/3D registration scheme for preterm brain images. EMBC 2006: 3341-3344 - [c1]Ewout Vansteenkiste, Jef Vandemeulebroucke
2D/3D Registration of Neonatal Brain Images. WBIR 2006: 272-279
Coauthor Index
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