7 citations · 28 across the 41 of their papers we have counts for
10 papers · 1 filter
Focal Attention Networks: optimising attention for biomedical image segmentation
Michael Yeung, Leonardo Rundo, Evis Sala +2
In recent years, there has been increasing interest to incorporate attention into deep learning architectures for biomedical image segmentation. The modular design of attention mec…
Incorporating Boundary Uncertainty into loss functions for biomedical image segmentation
Michael Yeung, Guang Yang, Evis Sala +2
Manual segmentation is used as the gold-standard for evaluating neural networks on automated image segmentation tasks. Due to considerable heterogeneity in shapes, colours and text…
StyleGAN-induced data-driven regularization for inverse problems
Arthur Conmy, Subhadip Mukherjee, Carola-Bibiane Schönlieb
Recent advances in generative adversarial networks (GANs) have opened up the possibility of generating high-resolution photo-realistic images that were impossible to produce previo…
Predicting isocitrate dehydrogenase mutation status in glioma using structural brain networks and graph neural networks
Yiran Wei, Yonghao Li, Xi Chen +3
Glioma is a common malignant brain tumor with distinct survival among patients. The isocitrate dehydrogenase (IDH) gene mutation provides critical diagnostic and prognostic value f…
Image reconstruction in light-sheet microscopy: spatially varying deconvolution and mixed noise
Bogdan Toader, Jerome Boulanger, Yury Korolev +4
We study the problem of deconvolution for light-sheet microscopy, where the data is corrupted by spatially varying blur and a combination of Poisson and Gaussian noise. The spatial…
Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy
Michael Yeung, Evis Sala, Carola-Bibiane Schönlieb +1
Background: Colonoscopy remains the gold-standard screening for colorectal cancer. However, significant miss rates for polyps have been reported, particularly when there are multip…