21 citations · 27 across the 8 of their papers we have counts for
4 papers · 1 filter
Domain-Agnostic Stroke Lesion Segmentation Using Physics-Constrained Synthetic Data
Liam Chalcroft, Jenny Crinion, Cathy J. Price +1
Segmenting stroke lesions in MRI is challenging due to diverse acquisition protocols that limit model generalisability. In this work, we introduce two physics-constrained approache…
A Robust Ensemble Algorithm for Ischemic Stroke Lesion Segmentation: Generalizability and Clinical Utility Beyond the ISLES Challenge
Ezequiel de la Rosa, Mauricio Reyes, Sook-Lei Liew +55
Diffusion-weighted MRI (DWI) is essential for stroke diagnosis, treatment decisions, and prognosis. However, image and disease variability hinder the development of generalizable A…
Synthetic Data for Robust Stroke Segmentation
Liam Chalcroft, Ioannis Pappas, Cathy J. Price +1
Current deep learning-based approaches to lesion segmentation in neuroimaging often depend on high-resolution images and extensive annotated data, limiting clinical applicability.…
Large-kernel Attention for Efficient and Robust Brain Lesion Segmentation
Liam Chalcroft, Ruben Lourenço Pereira, Mikael Brudfors +5
Vision transformers are effective deep learning models for vision tasks, including medical image segmentation. However, they lack efficiency and translational invariance, unlike co…