We are co-organizing a workshop on Interpretability of Machine Intelligence in Medical Image Computing at MICCAI 2020 on October 4, 2020 For details please follow this link.
Eye Lab’s research on AI explainability has been featured in the website of Radboudumc. In the recent publication by González-Gonzalo et al in IEEE Transactions on Medical […]
Our paper ‘Iterative Augmentation of Visual Evidence for Weakly-Supervised Lesion Localization in Deep Interpretability Frameworks: Application to Color Fundus Images’, by González-Gonzalo et al, has been […]
Coen de Vente has presented his latest work on “Estimating Uncertainty of Deep Neural Networks for Age-related Macular Degeneration Grading using Optical Coherence Tomography” at the […]
Our paper ‘A Deep Learning Model for Segmentation of Geographic Atrophy to Study its Long-Term Natural History’, by Liefers et al, has been published in Ophthalmology. In […]
Freerk Venhuizen has been awarded the title of Doctor by the Radboud University of Nijmegen after defending his PhD thesis, titled “Machine Learning for Quantification of […]
Our educational exhibit on Generative Adversarial Networks (GANs): A Primer for Radiologists has received a Certificate of Merit award at the annual meeting of the Radiological Society of […]