Jef Vandemeulebroucke
Orcid: 0000-0001-5714-3254
According to our database1,
Jef Vandemeulebroucke
authored at least 32 papers
between 2006 and 2024.
Collaborative distances:
Collaborative distances:
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Bibliography
2024
Int. J. Comput. Assist. Radiol. Surg., October, 2024
The STOIC2021 COVID-19 AI challenge: Applying reusable training methodologies to private data.
Medical Image Anal., 2024
Segmentation-Guided Coordinate Regression for Robust Landmark Detection on X-Rays: Application to Automated Assessment of Lower Limb Alignment.
IEEE Access, 2024
Proceedings of the Shape in Medical Imaging - International Workshop, 2024
2023
Comput. Methods Programs Biomed., December, 2023
Automated mitral annulus annotation over 4D-CT for transcatheter mitral valve replacement.
Comput. methods Biomech. Biomed. Eng. Imaging Vis., May, 2023
Handcrafted Features Can Boost Performance and Data-Efficiency for Deep Detection of Lung Nodules From CT Imaging.
IEEE Access, 2023
COVID-19 Lesion Segmentation Framework for the Contrast-Enhanced CT in the Absence of Contrast-Enhanced CT Annotations.
Proceedings of the Medical Image Learning with Limited and Noisy Data, 2023
2022
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., 2022
Proceedings of the Computer Vision - ECCV 2022 Workshops, 2022
Probabilistic Tissue Mapping for Tumor Segmentation and Infiltration Detection of Glioma.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2022
2020
Explainable-by-design Semi-Supervised Representation Learning for COVID-19 Diagnosis from CT Imaging.
CoRR, 2020
Comparative study of deep learning methods for the automatic segmentation of lung, lesion and lesion type in CT scans of COVID-19 patients.
CoRR, 2020
Automated threshold selection on whole-body 18F-FDG PET/CT for assessing tumor metabolic response.
Proceedings of the Medical Imaging 2020: Image Processing, 2020
Evaluating several ways to combine handcrafted features-based system with a deep learning system using the LUNA16 Challenge framework.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
Artificially augmenting data or adding more samples? A study on a 3D CNN for lung nodule classification.
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
Proceedings of the Medical Imaging 2020: Computer-Aided Diagnosis, 2020
2018
Intrasubject multimodal groupwise registration with the conditional template entropy.
Medical Image Anal., 2018
Can tumor coverage evaluated 24 h post-radiofrequency ablation predict local tumor progression of liver metastases?
Int. J. Comput. Assist. Radiol. Surg., 2018
Proceedings of the Computational Methods and Clinical Applications for Spine Imaging, 2018
Proceedings of the Intravascular Imaging and Computer Assisted Stenting - and - Large-Scale Annotation of Biomedical Data and Expert Label Synthesis, 2018
2017
Proceedings of the Medical Imaging 2017: Image Processing, 2017
Proceedings of the Medical Imaging 2017: Image Processing, 2017
Proceedings of the Medical Imaging 2017: Image Processing, 2017
2016
Medical Image Anal., 2016
Validation, comparison, and combination of algorithms for automatic detection of pulmonary nodules in computed tomography images: the LUNA16 challenge.
CoRR, 2016
Proceedings of the 13th IEEE International Symposium on Biomedical Imaging, 2016
2011
IEEE Trans. Medical Imaging, 2011
2010
Comput. Methods Programs Biomed., 2010
2009
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2009
2006
Proceedings of the Biomedical Image Registration, Third International Workshop, 2006
Proceedings of the 28th International Conference of the IEEE Engineering in Medicine and Biology Society, 2006