43 citations · 81 across the 6 of their papers we have counts for
4 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…
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…
Meningioma segmentation in T1-weighted MRI leveraging global context and attention mechanisms
David Bouget, André Pedersen, Sayied Abdol Mohieb Hosainey +2
Meningiomas are the most common type of primary brain tumor, accounting for approximately 30% of all brain tumors. A substantial number of these tumors are never surgically removed…
Fast meningioma segmentation in T1-weighted MRI volumes using a lightweight 3D deep learning architecture
David Bouget, André Pedersen, Sayied Abdol Mohieb Hosainey +3
Automatic and consistent meningioma segmentation in T1-weighted MRI volumes and corresponding volumetric assessment is of use for diagnosis, treatment planning, and tumor growth ev…