12 citations · 13 across the 5 of their papers we have counts for
5 papers
Deep Learning Segmentation of Diffusion-Weighted MRI Acute Ischaemic Stroke: A Pragmatic Evaluation Across Three Datasets
Atle Bjørnerud, Till Schellhorn, Thor H. Skattør +4
Objective: Diffusion-weighted MRI (DWI-MRI) is the gold standard for visualizing and quantifying acute ischaemic stroke (AIS). Although deep learning methods can accurately segment…
MUSTER: Longitudinal Deformable Registration by Composition of Consecutive Deformations
Edvard O. S. Grødem, Donatas Sederevičius, Esten H. Leonardsen +7
Longitudinal imaging allows for the study of structural changes over time. One approach to detecting such changes is by non-linear image registration. This study introduces Multi-S…
Deep Learning-based Intraoperative MRI Reconstruction
Jon André Ottesen, Tryggve Storas, Svein Are Sirirud Vatnehol +8
Purpose: To evaluate the quality of deep learning reconstruction for prospectively accelerated intraoperative magnetic resonance imaging (iMRI) during resective brain tumor surgery…
Treatment-aware Diffusion Probabilistic Model for Longitudinal MRI Generation and Diffuse Glioma Growth Prediction
Qinghui Liu, Elies Fuster-Garcia, Ivar Thokle Hovden +9
Diffuse gliomas are malignant brain tumors that grow widespread through the brain. The complex interactions between neoplastic cells and normal tissue, as well as the treatment-ind…
Voxels Intersecting along Orthogonal Levels Attention U-Net for Intracerebral Haemorrhage Segmentation in Head CT
Qinghui Liu, Bradley J MacIntosh, Till Schellhorn +3
We propose a novel and flexible attention based U-Net architecture referred to as "Voxels-Intersecting Along Orthogonal Levels Attention U-Net" (viola-Unet), for intracranial hemor…