4 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…
Adaptive Post-Processing Drives Instance-Level Detection in Stroke Lesion Segmentation
Qinghui Liu, Jon André Ottesen, Atle Bjørnerud +1
Instance-level lesion detection has been an increasingly larger focal point in medical image segmentation besides the more standard voxel-level overlap. Still, most pipelines are t…
Beyond Random Partitioning: Unsupervised Spatio-Temporal Stratification for Cohort Balancing in Longitudinal Medical Imaging
Qinghui Liu, Jon André Ottesen, Atle Bjørnerud +1
Rigorous dataset partitioning is a foundational, yet frequently overlooked, prerequisite for reliable deep learning in longitudinal medical imaging. Naively shuffling small clinica…
Deep Learning-Based Prediction of PET Amyloid Status Using Multi-Contrast MRI
Donghoon Kim, Jon Andre Ottesen, Ashwin Kumar +5
Identifying amyloid-beta positive patients is crucial for determining eligibility for Alzheimer's disease (AD) clinical trials and new disease-modifying treatments, but currently r…