Bob D. de Vos
Orcid: 0000-0002-8358-6849Affiliations:
- Amsterdam University Medical Center, The Netherlands
According to our database1,
Bob D. de Vos
authored at least 38 papers
between 2015 and 2023.
Collaborative distances:
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Bibliography
2023
Reconstruction and completion of high-resolution 3D cardiac shapes using anisotropic CMRI segmentations and continuous implicit neural representations.
Comput. Biol. Medicine, September, 2023
2022
Autoencoding low-resolution MRI for semantically smooth interpolation of anisotropic MRI.
Medical Image Anal., 2022
Generative adversarial network for coronary artery plaque synthesis in coronary CT angiography.
Proceedings of the Medical Imaging 2022: Image Processing, 2022
Deep Learning for Ventricular Arrhythmia Prediction Using Fibrosis Segmentations on Cardiac MRI Data.
Proceedings of the Computing in Cardiology, 2022
Weakly-Supervised Deep Learning for Left Ventricle Fibrosis Segmentation in Cardiac MRI Using Image-Level Labels.
Proceedings of the Computing in Cardiology, 2022
2021
Proceedings of the Medical Imaging 2021: Image Processing, Online, February 15-19, 2021, 2021
Unsupervised super-resolution: creating high-resolution medical images from low-resolution anisotropic examples.
Proceedings of the Medical Imaging 2021: Image Processing, Online, February 15-19, 2021, 2021
Deep Learning-Based Data-Point Precise R-Peak Detection in Single-Lead Electrocardiograms.
Proceedings of the 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2021
2020
Deep Learning-Based Regression and Classification for Automatic Landmark Localization in Medical Images.
IEEE Trans. Medical Imaging, 2020
CoRR, 2020
Proceedings of the Medical Imaging 2020: Image Processing, 2020
Proceedings of the Medical Imaging 2020: Image Processing, 2020
Proceedings of the Thoracic Image Analysis - Second International Workshop, 2020
2019
IEEE Trans. Medical Imaging, 2019
Medical Image Anal., 2019
3D Convolutional Neural Networks Image Registration Based on Efficient Supervised Learning from Artificial Deformations.
CoRR, 2019
Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI.
Proceedings of the Medical Imaging 2019: Image Processing, 2019
Response monitoring of breast cancer on DCE-MRI using convolutional neural network-generated seed points and constrained volume growing.
Proceedings of the Medical Imaging 2019: Computer-Aided Diagnosis, 2019
2018
Automatic Calcium Scoring in Low-Dose Chest CT Using Deep Neural Networks With Dilated Convolutions.
IEEE Trans. Medical Imaging, 2018
Proceedings of the Medical Imaging 2018: Image Processing, 2018
2017
IEEE Trans. Medical Imaging, 2017
Automatic Segmentation of the Left Ventricle in Cardiac CT Angiography Using Convolutional Neural Network.
CoRR, 2017
Classification of coronary artery calcifications according to motion artifacts in chest CT using a convolutional neural network.
Proceedings of the Medical Imaging 2017: Image Processing, 2017
End-to-End Unsupervised Deformable Image Registration with a Convolutional Neural Network.
Proceedings of the Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support, 2017
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2017, 2017
2016
Automatic coronary artery calcium scoring in cardiac CT angiography using paired convolutional neural networks.
Medical Image Anal., 2016
2D image classification for 3D anatomy localization: employing deep convolutional neural networks.
Proceedings of the Medical Imaging 2016: Image Processing, 2016
Genome-wide association study of coronary and aortic calcification in lung cancer screening CT.
Proceedings of the Medical Imaging 2016: Image Processing, 2016
Supervised novelty detection in brain tissue classification with an application to white matter hyperintensities.
Proceedings of the Medical Imaging 2016: Image Processing, 2016
Automatic detection of cardiovascular risk in CT attenuation correction maps in Rb-82 PET/CTs.
Proceedings of the Medical Imaging 2016: Image Processing, 2016
Proceedings of the Deep Learning and Data Labeling for Medical Applications, 2016
Deep convolutional neural networks for automatic coronary calcium scoring in a screening study with low-dose chest CT.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, California, United States, 27 February, 2016
Automatic segmentation of the left ventricle in cardiac CT angiography using convolutional neural networks.
Proceedings of the 13th IEEE International Symposium on Biomedical Imaging, 2016
2015
Automatic machine learning based prediction of cardiovascular events in lung cancer screening data.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015