309 citations · 616 across the 13 of their papers we have counts for
5 papers · 1 filter
Segmentation of glioblastomas in early post-operative multi-modal MRI with deep neural networks
Ragnhild Holden Helland, Alexandros Ferles, André Pedersen +30
Extent of resection after surgery is one of the main prognostic factors for patients diagnosed with glioblastoma. To achieve this, accurate segmentation and classification of resid…
DeepBrainPrint: A Novel Contrastive Framework for Brain MRI Re-Identification
Lemuel Puglisi, Frederik Barkhof, Daniel C. Alexander +3
Recent advances in MRI have led to the creation of large datasets. With the increase in data volume, it has become difficult to locate previous scans of the same patient within the…
An efficient semi-supervised quality control system trained using physics-based MRI-artefact generators and adversarial training
Daniele Ravi, Frederik Barkhof, Daniel C. Alexander +3
Large medical imaging data sets are becoming increasingly available, but ensuring sample quality without significant artefacts is challenging. Existing methods for identifying impe…
Preoperative brain tumor imaging: models and software for segmentation and standardized reporting
D. Bouget, A. Pedersen, A. S. Jakola +27
For patients suffering from brain tumor, prognosis estimation and treatment decisions are made by a multidisciplinary team based on a set of preoperative MR scans. Currently, the l…
Degenerative Adversarial NeuroImage Nets for Brain Scan Simulations: Application in Ageing and Dementia
Daniele Ravi, Stefano B. Blumberg, Silvia Ingala +3
Accurate and realistic simulation of high-dimensional medical images has become an important research area relevant to many AI-enabled healthcare applications. However, current sta…