15 citations · 16 across the 4 of their papers we have counts for
5 papers · 2 filters
Response monitoring of breast cancer on DCE-MRI using convolutional neural network-generated seed points and constrained volume growing
Bas H. M. van der Velden, Bob D. de Vos, Claudette E. Loo +3
Response of breast cancer to neoadjuvant chemotherapy (NAC) can be monitored using the change in visible tumor on magnetic resonance imaging (MRI). In our current workflow, seed po…
Automatic Segmentation of Thoracic Aorta Segments in Low-Dose Chest CT
Julia M. H. Noothout, Bob D. de Vos, Jelmer M. Wolterink +1
Morphological analysis and identification of pathologies in the aorta are important for cardiovascular diagnosis and risk assessment in patients. Manual annotation is time-consumin…
Towards increased trustworthiness of deep learning segmentation methods on cardiac MRI
Jörg Sander, Bob D. de Vos, Jelmer M. Wolterink +1
Current state-of-the-art deep learning segmentation methods have not yet made a broad entrance into the clinical setting in spite of high demand for such automatic methods. One imp…
A Deep Learning Framework for Unsupervised Affine and Deformable Image Registration
Bob D. de Vos, Floris F. Berendsen, Max A. Viergever +3
Image registration, the process of aligning two or more images, is the core technique of many (semi-)automatic medical image analysis tasks. Recent studies have shown that deep lea…
CNN-based Landmark Detection in Cardiac CTA Scans
Julia M. H. Noothout, Bob D. de Vos, Jelmer M. Wolterink +2
Fast and accurate anatomical landmark detection can benefit many medical image analysis methods. Here, we propose a method to automatically detect anatomical landmarks in medical i…